With the explosion of the generation, transmission and sharing of image data over the Internet and other unsecured networks, the need and significance for the development of novel image encryption algorithms is unprecedented. In this research work, we propose a novel framework for image encryption that is based on two hyperchaotic maps, utilized in conjunction with the single neuron model (SNM). The framework entails three successive stages, where in every stage, a substitution box (S-box) is applied, then XORing with an encryption key is carried out. The S-boxes and the encryption keys are generated from the numerical solutions of the hyperchaotic maps and the SNM. The performance of the proposed framework is gauged through a number of metrics, reflecting superior performance and complete asymmetry between the plain images and their encrypted versions. However, the main advantages of this work are: (1) The attained width of the key space; and (2) The achieved efficiency in software implementation. The superior key space of 2^{2551} is the result of employing the two hyperchaotic maps, while the improved efficiency, resulting in an average encryption rate of 8.54 Mbps, is the result of the utilization of the single neuron model, as well as the employment of optimized parallel processing techniques. In addition, the proposed encryption framework is shown to output encrypted images that pass the NIST SP 800 suite.

Single-confinement housing can pose welfare risks to domestic horses. This study investigated horses’ stress responses when confined to single stalls in different stable designs in a tropical savanna region to address a literature gap. In total, 23 horses were assigned to a stable with a central corridor and solid external walls (A) (N = 8), a stable with one side corridor and solid external walls (B) (N = 6) or a stable with a central corridor and no solid external walls (C) (N = 9). Air velocity, relative humidity, air temperature and noxious gases were measured inside the stables, and the heart rate and HRV of the horses were also determined. The relative humidity was lower in stable C than in stable A (p < 0.05), while the air temperature was higher in stable C than in stable B (p < 0.05) during the day. The airflow and ammonia levels were higher in stable C than in stables B and A (p < 0.01–0.0001). Overall, horses’ HRV in stable A was lower than in those in stables B and C (p < 0.05-0.01). Horses in stable A tended to experience more stress than those in other stables.

The Fractal Analysis of Medical Images is an investigation field in those that numerous results of important value have been obtained. This work describes the basic foundations of the Fractal Analysis and its application has more than enough medical images, leaning on in five scientific investigations.

Secure Secret Sharing Single-Source Shortest Distance (SSSD) protocols, built on the Secure Multi-Party Computation (SMC) foundation, have emerged as a promising solution to address the secure distribution and management of sensitive secrets among multiple parties. This paper focuses on the crucial aspect of security proof within SSSD protocols based on SMC, aiming to provide a scientifically rigorous understanding of the formal verification process and the robust guarantees they offer. Through a comprehensive examination of the fundamental principles underpinning SMC and the specific design considerations unique to SSSD protocols, this paper meticulously explores the key components and intricate steps involved in constructing a rigorous security proof. Furthermore, it discusses the adversarial model, precise security definitions, cryptographic assumptions utilized within the proof, and sophisticated techniques and reductions to establish its validity. By means of a meticulous analysis of the security proof for SSSD protocols, this paper critically evaluates both the strengths and limitations of the proposed approach, offering valuable insights to inform future research and development within this significant domain of study.

The detection performance of small objects in remote sensing images has not been satisfactory compared to large objects, especially in low-resolution and noisy images. A generative adversarial network (GAN)-based model called enhanced super-resolution GAN (ESRGAN) showed remarkable image enhancement performance, but reconstructed images usually miss high-frequency edge information. Therefore, object detection performance showed degradation for small objects on recovered noisy and low-resolution remote sensing images. Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we applied a new edge-enhanced super-resolution GAN (EESRGAN) to improve the quality of remote sensing images and used different detector networks in an end-to-end manner where detector loss was backpropagated into the EESRGAN to improve the detection performance. We proposed an architecture with three components: ESRGAN, EEN, and Detection network. We used residual-in-residual dense blocks (RRDB) for both the ESRGAN and EEN, and for the detector network, we used a faster region-based convolutional network (FRCNN) (two-stage detector) and a single-shot multibox detector (SSD) (one stage detector). Extensive experiments on a public (car overhead with context) dataset and another self-assembled (oil and gas storage tank) satellite dataset showed superior performance of our method compared to the standalone state-of-the-art object detectors.

Distributed deformation based on Fiber Bragg Grating sensors or other kinds of strain sensors can be used to evaluate safety in operating periods of bridges. However, most of the published researches about distributed deformation monitoring are focused on solid rectangular beam rather than box girder—a kind of typical hollow beam widely employed in actual bridges. Considering that the entire deformation of a single-cell box girder contains not only bending deflection but also two additional deformations respectively caused by shear lag and shearing action, this paper again revises the improved conjugated beam method (ICBM) based on the LFBG sensors to satisfy the requirements for monitoring two mentioned additional deformations. The best choice for the LFBG sensor placement in box gilder is also proposed in this paper due to strain fluctuation on flange caused by shear lag effect. Results from numerical simulations show that most of the theoretical monitoring errors of the revised ICBM are 0.3%~1.5%, and the maximum error is 2.4%. A loading experiment for a single-cell box gilder monitored by LFBG sensors show that most of the practical monitoring errors are 6%~8%, and the maximum error is 11%.

Majority of the studied MADS box members are linked with flowering and fruit traits. However, higher volumes of studies on the type II of their two types so far suggest that florigenic effect of the gene members could just be tip of the iceberg. In current study we used a systematic approach to have general overview on the MADS box members their cross-trait and multifactor associations as well as their pleiotropic potentials based on local reference database curated for MADS box members. While doing so, we screened for the co-occurrence of the terms of interest within the title or abstract of each reference with threshold of 3 hits. Analysis results showed that our approach can retrieve multi-faceted information on the subject of study (MADS box gene members in current case) which could otherwise have been skewed depending on the authors’ expertise and/or volume of literature reference base. Overall, our study discusses on the roles of MADS box members in association with plant organs and traits-linked factors among plant species. Our assessment showed that plants with majority of the MADS box member studies include tomato, apple, rice etc., after Arabidopsis. Furthermore, based on the degree of their multi-trait associations, FLC, SVP, SOC1, etc. are suggested to have relatively higher pleiotropic potential among others in plant growth, development and flowering process. The approach devised in this study is expected applicable for having basic understanding on any study subject of interest regardless of depth prior knowledge.

Organic Coatings have potential applications in the prevention of metal corrosion in an aqueous solution. The protective effect of SEBS coated copper corrosion in NaCl 3% solution was investigated by using electrochemical methods. The main objective of this work is to find the optimal conditions of the protocol immersion to evaluate the effects of SEBS ratio and two-immersion time on the anticorrosive behaviour of copper in 3 wt % NaCl solution in order to determine the best conditions to produce a protective SEBS film on the copper surface. Response Surface Methodology (RSM) is used as an optimization method. The study’s findings show the combination of three environmental factors that minimize corrosion rate. The Box-Behnken Design (BBD) is working perfectly for the statistical significance of the model (ANOVA test). This analysis calculates the contribution value of each parameter in changing the value of the corrosion rate (CR) in not only individual but also synergistic cases. The optimized parameters were found to be a 2.17% of SEBS ratio, 20 min of immersion 1, and 21 min of immersion 2. The electrochemical impedance spectroscopy tests confirmed the results.

Single particle tracking (SPT) is a powerful class of methods for studying the dynamics of biomolecules inside living cells. The techniques reveal the trajectories of individual particles, with a resolution well below the diffraction limit of light, and from them the parameters defining the motion model, such as diffusion coefficients and confinement lengths. Most existing algorithms assume these parameters are constant throughout an experiment. However, it has been demonstrated that they often vary with time as the tracked particles move through different regions in the cell or as conditions inside the cell change in response to stimuli. In this work, we propose an estimation algorithm to determine time-varying parameters of systems that discretely switch between different linear models of motion with Gaussian noise statistics, covering dynamics such as diffusion, directed motion, and Ornstein-Uhlenbeck dynamics. Our algorithm consists of three stages. In the first stage, we use a sliding window approach, combined with Expectation Maximization (EM) to determine maximum likelihood estimates of the parameters as a function of time. These results are only used to roughly estimate the number of model switches that occur in the data to guide the selection of algorithm parameters in the second stage. In the second stage, we use change detection (CD) techniques to identify where the models switch, taking advantage of the off-line nature of the analysis of SPT data to create non-causal algorithms with better precision than a purely causal approach. Finally, we apply EM to each set of data between the change points to determine final parameter estimates. We demonstrate our approach using experimental data generated in the lab under controlled conditions.

Biological parameters extracted from electrical signals from various body parts have been used for many years to analyze the human body and its behavior. In addition, electrical signals from cancer cell lines, normal cells, and viruses, among others, have been widely used for the detection of various diseases. Single-cell parameters such as cell and cytoplasmic conductivity, relaxation frequency, and membrane capacitance are important. There are many techniques available to characterize biomaterials, such as scanning tunneling microscopy (STM), nanotechnology, microstrip cavity resonance measurement, dielectric impedance measurement (DEPIM), etc. This article reviews the single cell isolation and sorting techniques, summarizes the common single cell operations such as impedance flow cytometry, cell electrical impedance, electrical impedance sensing, and summarizes the current single cell analysis techniques and their applications.

The purpose of this article is to study a proposal for image processing and machine learning techniques to detect the pest Aleurothrixus floccosus in citrus in the area of Pedregal de Arequipa, Peru. Thus, in the collection of images a type of simple random sampling is adopted for the decrease of the bias in different citrus trees alternating and extracting leaves from the plantation also applying image processing techniques for noise reduction and edge smoothing, segmentation for the detection of the target and using machine learning algorithms that aims to perform the classification of the images, a methodology for the detection of the white fly or Aleurothrixus floccosus is achieved. It is necessary to understand that in the development of the article, it was possible to identify three stages of the pest in the plant, these being the presence of yellow areas, leaf rolling, and secretion of melase, likewise in the process it was possible to obtain a sample of 1200 images.

: F-box proteins are a large gene family in plants, and play crucial roles in plant growth, development, and stress response. However, a comprehensive investigation of F-box family genes in cultivated peanut (Arachis hypogaea L.), has not been undertaken. In this study, we used a bioinformatics approach to identify and analyze F-box protein family genes in the cultivated peanut genome, and examined their expression profiles. Herein, a total of 95 F-box protein family members on 18 chromosomes were identified in cultivated peanut, which were sequentially designed as AhFBX1-AhFBX95. Phylogenetic analysis classified these AhFBXs into four different groups (Group I - IV), and eight subfamilies based on the structural domains of the C-terminal. Structural analysis revealed the presence of ten unique motifs within these genes. Additionally, the investigation of non-synonymous and synonymous substitution rates (Ka/Ks), and synteny in the F-box proteins, provided valuable insights into the evolutionary and domestication processes of AhFBX genes in peanut. Furthermore, in silico expression profiling of 22 different tissues demonstrated that most genes were predominantly expressed in leaves, pistils, and the aerial gynophore tip, while some members showed tissue-specific expression at the apex of both vegetative and reproductive shoots. Subsequently, we validated the expression of 9 differentially expressed genes (DEGs) using transcriptomeic data of lateral branch development and qRT-PCR analysis. These DEGs may be involved in regulating the development of lateral branches and subsequently affect the architecture of peanut plants.

UAVs are becoming a crucial tool in modern warfare, primarily due to their cost-effectiveness, risk reduction, and ability to perform a wider range of activities. The use of autonomous UAVs to conduct strike missions against highly valuable targets is the focus of this research. Due to developments in ledger technology, smart contracts, and machine learning, such activities formerly carried out by professionals or remotely flown UAVs are now feasible. Our study provides the first in-depth analysis of challenges and potential solutions for successful implementation of an autonomous UAV mission.

Artificial Intelligence (AI) is required since multiple resources are in need to complete depending on a daily basis. As a result, automating routine tasks is an excellent idea. This reduces the foundation's work schedules while also improving efficiency. Furthermore, the business can obtain talented personnel for the business strategy through Artificial Intelligence. Explainability in XAI derives from a combination of strategies that improve machine learning models' environmental flexibility and interpretability. When Artificial Intelligence is trained with a large number of variables to which we apply alterations, the entire processing is turned into a black box model which is in turn difficult to understand. The data for this research's quantitative analysis is gathered from the IEEE, Web of Science, and Scopus databases. This study looked at a variety of fields engaged in the (Explainable Artificial Intelligence) XAI trend, as well as the most commonly employed techniques in domain of XAI, the location from which these studies were conducted, the year-by-year publishing trend, and the most frequently occurring keywords in the abstract. Ultimately, the quantitative review reveals that employing Explainable Artificial Intelligence or XAI methodologies, there is plenty of opportunity for more research in this field.

The Algiers Stock Exchange (ASE) is the only stock exchange in Algeria. It’s one of the newest and smallest emerging stock exchanges in the world. The focus of this paper is to model and forecast monthly returns of the ASE index (DZAIRINDEX) using The Box- Jenkins methodology. The period of this study is from Jun 2010 to July 2019. According to Akaike’s Information Criterion (AIC) estimator, the Seasonal Autoregressive Integrated Moving Average SARIMA(2,0,0)(0,0,1) is chosen as the best model for forecasting the monthly DZAIRINDEX returns. Diagnostic tests confirm that the fitted model is adequate, where the residuals of this model are normally distributed with no autocorrelation and no heteroskedasticity. The forecast of the monthly DZAIRINDEX returns for one year ahead using this model shows a decreasing fluctuations trend. Based on different measures of forecast accuracy such as ME, MAE, RMSE, MASE, we show that the forecast accuracy of SARIMA(2,0,0)(0,0,1) is acceptable and this model performs much better than a naïve model. These results could be used by the financial communities in Algeria to deal with stock exchange risks and to improve their decisions.

In order to reduce the vibration of the transporter and improve the stability of the transporter, the vibration characteristics and key structure optimization research of the mountain orchard transporter are carried out. In this paper, the vibration of electric monorail transporters under different working conditions is tested, and the causes of vibration generated by monorail transporter during operation are explored. The three-dimensional model of the trailer and transmission box is established using Solidworks, and the modal vibration modes of the structure are analyzed theoretically. The modal test system is used for modal test analysis of trailers and transmission boxes. By comparing the results of finite element and experimental modal analysis, the second-order frequency of the trailer is close to the motor's rotating excitation frequency of 50 Hz at rated speed, which is easy to generate resonance. By optimizing the structure of the trailer, the second and third natural frequencies are increased to 54.79 Hz and 58.35 Hz respectively, which avoid the resonance of the trailer during operation and effectively reduce the vibration generated during the transportation of the trailer. Through vibration testing of the optimized electric monorail transporter, the results of vibration testing before and after structural optimization are compared and analyzed, and it is found that the vibration amplitudes of the transporter in X, Y and Z directions are reduced by 0.308m/s², 0.351m/s² and 0.334m/s² respectively, the running stability of the conveyer is improved.

A Invasive emerging pollutants from wastewater effluent discharge, such as dyes, pesticides, etc., pose a serious threat to the ecosystem. Advanced oxidation processes (AOPs) under visible light irradiation have emerged as a promising technology to overcome toxic and recalcitrant organic compounds. In this work, the impact of operational factors, including the concentration of Fe3+ or Fe2+, [H2O2], the molar ratio (Oxalate/ Fe3+ or Fe2+), and the initial pH, was studied to obtain high efficiency in the degradation and mineralization of such a food dye to reduce their pollution. The study deals with the comparison of the efficiency of UV, LED, and sunlight irradiation on the photocatalytic degradation of the dye using Fe3+/Lig and Fe2+/Lig complexes. The results showed that sunlight irradiation gave a very rapid kinetic and higher degradation efficiency of over 70%. The optimized conditions for the maximum elimination of the dye with a photocatalytic degradation efficiency (98%) and a mineralization rate of 96% were obtained with the Fe3+/Lig complex, based on the Box Benhken surface design analysis. In the presence of H2O2, the degradation reached an equilibrium stage after 15 min (97.57%) for the Fe(III)/Lig system. Moreover, the inhibition effect of inorganic ions on the photo-Fenton performance of Fe3+/Lig and Fe2+/Lig was studied. The study suggests that the use of nanocrystals of hematite as a Fenton reagent for treating textile effluents needs further investigation. The results showed that the proposed models were well-suited to batch treatment under sunlight. This study not only proposes a Fe3+/Lig and Fe2+/Lig system for the elimination of a food dye without adjusting the pH of the medium, but it also provides insight into the best source of light irradiation for the photocatalytic degradation process.

Activated sludge process is a well known method to treat municipal and industrial waste water. In this complex process, the oxygen concentration in the reactors plays a critical role in the plant efficiency. This paper proposes the use of a Long Short-Term Memory (LSTM) network to identify an input-output model suitable for the design of an oxygen concentration controller. The model is identified from easy-accessible measures collected from a real plant. This dataset covers almost a month. The performances achieved with the proposed LSTM model are compared with the ones obtained with a standard AutoRegressive model with eXogenous input (ARX). Both models catch the oscillation and the overall behaviour (ARX ρ=0.833 , LSTM ρ=0.921), but, while the ARX model fails in reaching the correct amplitude (FIT=41.20%), the LSTM presents satisfactory performance (FIT=60.56%).

The main property of tripodal ligands is the predictable type of coordination. Homo- and heteroleptic lanthanide complexes with tripodal ligands are a representative class of compounds. However, despite the fact that many of them are paramagnetic their magnetic behavior is poorly understood. This is because their photophysical and catalytic properties have been more attractive. In the present review, we are trying to summarize the available structural information and extremely few data on magnetic properties in order to draw some conclusions about the prospective of tripods using in the design of quantum molecular magnets based on Ln ions. We would like to draw the reader's attention to the fact that despite the consideration of a large part of the currently known lanthanide compounds with tripodal ligands, this review is not exhaustive. However, our goal was to draw the attention of researchers to the fact that a whole niche of air-stable Ln complexes remained outside the attention of magnetochemists and theoreticians.

We consider the problem of scheduling tasks on a single machine subject to an uncertain breakdown to minimize the flowtime. Assume the machine is unavailable during the breakdown; the starting time of the breakdown is a random variable s with distribution function D(s) and the terminating time of the breakdown has no any other information; jobs are non-resumable. Under the assumptions, starting from the perspective of statistical optimization, we first define the expected competitive ratio of an algorithm to find the optimized solution with the considered problem. Further, we propose and prove a certain result on the expected competitive ratio of the SPT rule. In particular, we show that under a quite loose condition the expected competitive ratio of the SPT rule is no more than 5/4. Meanwhile, we also make some discussions about our studies. What we have done will rich and improve the studying results on the area of scheduling to minimize flowtime and advance the development of online optimization and statistical optimization.

Background: Biological processes are based on complex networks of cells and molecules. Single cell multi-OMICs is a new tool aiming to provide new incites in the complex network of events controlling the functionality of the cell.; Methods: Since single cell technologies provide many sample measurements, they are the ideal environment for the application of deep learning and machine learning approaches. An autoencoder (AE) is composed of an encoder and a decoder sub-model. AE are very powerful in data compression and noise removal. However, the decoder model remains a black box from which is impossible to depict the contribution of the single input elements. We have recently developed a new class of autoencoders, called Sparsely Connected Autoencoders (SCA), which have the advantage of providing a controlled association among the input layer and the decoder module. This new architecture has the benefit that the decoder model is no anymore a black box and it can be used to depict new biologically interesting features from single cell data; Results: In this paper, we show that SCA hidden layer can grab new information usually hidden in single cell data, like as providing clustering on meta-features difficult, i.e. transcription factors expression, or impossible, miRNA expression, to depict in single cell RNAseq data. Furthermore, a SCA representation of cell clusters has the advantage of simulating a conventional bulk RNAseq, which is a data transformation allowing the identification of similarity among independent experiments; Conclusions: In our opinion, SCA represent the bioinformatics version of a “Swiss Army knife” for the extraction of hidden knowledgeable features from single cell OMICs data.

Electromagnetic coil is the key component of rotating equipment, and its reliability is very important for the normal operation of the equipment. In order to accurately evaluate the health status of electromagnetic coil, a health evaluation and anomaly detection method based on Mahalanobis distance (MD) and Box-Cox transformations is proposed. With the help of accelerated fatigue experiment, the whole life electrical data of high, medium and low frequency spectrum of electromagnetic coil is collected, and the low and medium frequency spectrum data are constructed as the initial feature set. And then, the initial feature set is mahalanized, and Mahalanobis distance is taken as the feature to evaluate the health state of the electromagnetic coil. With the help of Box-Cox transformations, MD is transformed into normal distribution form, and the electromagnetic coil fault early warning is realized according to 3 σ criterion. The results show that MD can accurately evaluate the degradation state of the electromagnetic coil and realize early warning.

In typical whiskey, the content of higher alcohols is about 1500-2000 mg/L, lead to high intoxicating degree (ID). To produce the low-ID whiskey, the Saccharomyces cerevisiae XF0-h, XF0-H and XF0-LH were successfully constructed by CRISPR-Cas9 gene editing technology to knock out HOM2 (encoding aspartate β-semialdehyde dehydrogenase) in the original strain XF0 and the LEU1 knockout strain XF0-L. The content of higher alcohols in whiskey fermented by the XF0-h, XF0-H, and XF0-LH were 704±8 mg/L, 685±6 mg/L, and 685±19 mg/L, respectively, showing reductions of 23.93%, 25.98%, and 15.81% compared to the XF0, XF0, and XF0-L. The fermentation conditions of the XF0-LH were optimized through single-factor experiments and Box-Behnken design. The optimal conditions were the wort concentration of 9.8 °P, the hydrolyzed broken rice syrup addition of 78 g/L, and the inoculum size of 2.7 × 106 cells/mL. The low-ID whiskey was brewed with higher alcohols content at 556 mg/L by 50L fermenter at the optimal conditions.

Background: Aging impacts semantic abilities, therefore semantic exercises might be a valuable tool for cognitive stimulation in healthy older adults. However, programs in this area are limited. Methods: In the current paper, we adapted the BOX linguistic semantic program for online use via the CerUp platform. Our goal was to prepare the optimization future experience of CerUp users, including potential changes in task structure, level of difficulty and instructions, and participants’ adherence, engagement, performance accuracy, perceived difficulty, and adequacy ratings assigned to the instructions we provided that might guide future changes. Additionally, we created a map of hypothesized task-specific features that may guide tailor-made uses of the program. Results: To that end, we present preliminary results on the usability of CerUp. By analyzing task-specific usability data alongside the hypothesized map of task-specific features, we also tested the validity of the latter. Conclusions: These preliminary results on the usability of the CerUp platform highlight the potential of programs for semantic stimulation. Such findings can inform future optimizations of the program, tailored to users’ needs and effectively supporting overall language skills and general cognition.

The purpose of this study is to investigate the failure mechanism and preventive strengthening methods of prefabricated full length small box girder (PSBG) under car explosion. After damage analysis during blast loads using the commercial software Autodyn, three strengthening methods are presented to improve the blast mitigation performance. The results show that the failure modes and bearing capacity are significantly different with various strengthening measures. Adhering U-shaped steel plate can effectively enhance the shear performance of PSBG under blast loads. Strengthening the bottom of the upper flange of box girder with steel plate can effectively mitigate the local bending failure, and enhance the overall flexural capacity during car explosion.

Abstract: More than 40 hypotheses predict associations between features of nest architecture and at least one measure of reproductive success. However, quantitative studies of reproductive consequences of nest characteristics remain scarce. In addition, most studies were conducted on model species of which nests can be easily monitored with artificial nest-boxes. Here we review the replicability of research protocols and findings in model species with many repeat studies focusing mainly on nest-size components, animal-derived nest material, or fresh greenery in blue tits (Cyanistes caeruleus), great tits (Parus major), tree swallows (Tachycineta bicolor), and starlings (Sturnus spp.). The studies looked for correlations between nest traits and aspects of breeding performance that can be easily quantified in the field, such clutch size, brood size at hatching or fledging, the % of eggs that hatch or fledge, or nestling characteristics assumed to reflect qualities associated with survival probabilities (e.g., morphometry, body condition, blood profiles). We discuss the consequences of poor replicability of research methodologies and provide explanations for why many of these studies reported poor associations between nest design and breeding success at different spatiotemporal scales. We also make suggestions for future research. Keywords: Nest design, Breeding success, Nest-box, Cavity-nesting birds, Replicability

Vectorial Boolean functions and codes are closely related, and each corresponding domain gives been to each other. On the one hand, various requirements of binary linear codes are needed for their theatrical interests but, more importantly, for their practical applicants (such as few-weight codes or minimal codes for secret sharing, locally recoverable codes for storage, etc.). On the other hand, various criteria and tables have been introduced to analyse the security of S-boxes that are related to vectorial Boolean functions, such as the Differential Distribution Table (DDT), the Boomerang Connectivity Table (BCT), and the Differential-Linear Connectivity Table (DLCT). In previous years, two new tables have been proposed for which the literature was pretty abundant: the $c$-DDT to extend the DDT and the $c$-BCT to extend the BCT. In the same vein, we propose extended concepts to study further the security of vectorial Boolean functions, especially the $c$-Walsh transform, the $c$-autocorrelation, and the $c$-differential-linear uniformity, and its accompanying table, the $c$-Differential-Linear Connectivity Table ($c$-DLCT). We study these properties of the novel functions at their optimal level concerning these concepts and describe the $c$-DLCT of the crucial inverse vectorial (Boolean) function case. Finally, the derived functions could lead to new families of binary minimal codes, as the recent achievements on minimal codes from low differential uniformity. We draw new avenues for future research toward linear code designs.

Artificial intelligence is increasingly used in various branches of engineering. In this article, artificial neural networks are used to predict the crush resistance of corrugated packaging. Among the analysed packages were boxes with ventilation openings, packages with perforations, and typical flap boxes, which makes the proposed estimation method very universal. Typical shallow feedforward networks were used, which are perfect for regression problems, mainly when the set of input and output parameters is small, so no complicated architecture or advanced learning techniques are required. The input parameters of the neural networks are selected so as to take into account not only the material used for the production of the packaging, but also the dimensions of the box and the impact of ventilation holes and perforations on the load capacity of individual walls of the packaging. In order to maximize the effectiveness of neural network training process, the group of input parameters was changed so as to eliminate those to which the sensitivity of the model was the lowest. This allowed the selection of the optimal configuration of training pairs for which the estimation error was on the acceptable level. Finally, models of neural networks were selected, for which the training and testing error did not exceed 10%. The demonstrated effectiveness allows to conclude that the proposed set of universal input parameters is suitable for efficient training of a single neural network model capable of predicting the compressive strength of various types of corrugated packaging.

Clinicians are often very sceptical about applying automatic image processing approaches, especially deep learning based methods, in practice. One main reason for this is the black-box nature of these approaches and the inherent problem of missing insights of the automatically derived decisions. In order to increase trust in these methods, this paper presents approaches that help to interpret and explain the results of deep learning algorithms by depicting the anatomical areas which influence the decision of the algorithm most. Moreover, this research presents a unified framework, TorchEsegeta, for applying various interpretability and explainability techniques for deep learning models and generate visual interpretations and explanations for clinicians to corroborate their clinical findings. In addition, this will aid in gaining confidence in such methods. The framework builds on existing interpretability and explainability techniques that are currently focusing on classification models, extending them to segmentation tasks. In addition, these methods have been adapted to 3D models for volumetric analysis. The proposed framework provides methods to quantitatively compare visual explanations using infidelity and sensitivity metrics. This framework can be used by data scientists to perform post-hoc interpretations and explanations of their models, develop more explainable tools and present the findings to clinicians to increase their faith in such models. The proposed framework was evaluated based on a use case scenario of vessel segmentation models trained on Time-of-fight (TOF) Magnetic Resonance Angiogram (MRA) images of the human brain. Quantitative and qualitative results of a comparative study of different models and interpretability methods are presented. Furthermore, this paper provides an extensive overview of several existing interpretability and explainability methods.

In the modern world, all manufacturers strive for the optimal design of their products. This general trend is recently also observed in the corrugated board packaging industry. Colorful prints on displays, perforations in shelf-ready-packaging and various types of ventilation holes in trays, although extremely important for ergonomic or functional reasons, weaken the strength of the box. To meet the requirements of customers and recipients, packaging manufacturers outdo each other in new ideas for the construction of their products. Often the aesthetic qualities of the product become more important than the attention to maintaining the standards of the load capacity of the packaging (which, apart from their attention-grabbing functions, are also intended to protect transported products). The particular flaps design (both top and bottom) and their influence on the strength of the box is investigated in this study. The updated analytical-numerical approach is used here to predict the strength of the packaging with various flap’s offsets. Experimental results indicated a significant decrease in the static load-bearing capacity of packaging in the case of shifted flap creases. The simulation model proposed in our previous work has been modified and updated to take into account also this effect. The results obtained by the model presented in the paper are in satisfactory agreement with the experimental data.

A pixel-based segmentation method was demonstrated to be confounded by developmental stage in estimation of flowering of mango. Categorization of panicles into three developmental stages was undertaken with a single and a two-stage deep learning framework (YOLO and R2CNN), using either upright or rotated bounding boxes. For a validation image set and for total panicle count, the models MangoYOLO(-upright), MangoYOLO-rotated, YOLOv3-rotated, R2CNN(-rotated) and R2CNN-upright achieved: (i) RMSEs of 25.6, 16.0, 15.4, 25.8 and 32.3 panicles per tree image, (ii) Mean average precision (mAP) scores of 72.2, 69.1, 65.0, 62.5 and 70.9% and (iii) weighted F1-scores of 76.5, 76.1, 74.9, 74.0 and 82.0, respectively. For a test set of images involving a different orchard and cultivar and use of a different camera, the R2 for machine vision to human count of panicles per tree was 0.86, 0.80, 0.83, 0.81 and 0.76 for the same models, respectively. Thus, models generalised well, but with no consistent benefit from use of rotated over upright bounding boxes. While the YOLOv3-rotated model was superior in terms of total panicle count, the R2CNN-upright model was more accurate for panicle stage classification. To demonstrate practical application, panicle counts were made weekly for an orchard of 994 trees, with a peak detection routine applied to document multiple flowering events.

In theory and applications, it is often inevitable to work with projectors onto convex sets, where a linear transform is involved. In this article, a novel projector is presented, which generalizes previous results in that it admits a broader family of linear transforms, but on the other hand it is limited to box-type convex sets in the transformed domain. The new projector has an explicit formula and it can be interpreted within the framework of proximal optimization. The benefit of the new projector is demonstrated on an example from signal processing, where it was possible to speed up the convergence of a signal declipping algorithm by a factor of more than two.

Although early work on parental burnout in the 1980s did not link parental burnout to specific parenting situations, the idea that parents affected by specific vulnerability factors were particularly at risk of burnout quickly emerged. Based on the etiological model of parental burnout (i.e., the balance between risks and resources), the objective of this study was to determine if there were specific vulnerability factors that significantly increase the risk of parental burnout. 2,563 parents participated in the study. We compared parents with a child with special needs (n = 25), parents who had adopted a child (n = 130), and single parents (n = 109), to strictly matched control groups of parents. Parents with a child with special needs displayed higher burnout and lower balance between risk and resources than the control group; parents with an adopted child had similar levels of both parental burnout and balance; and single parents had higher parental burnout but similar balance. Parents who combined specific several vulnerability factors were at greater risk of burnout. Single parenthood and adoption do not in themselves trigger a process leading de facto to other risk factors, but having a child with special needs does.

When traditional joint structures are used to widen multi-span continuous concrete box girder bridges, excessive lateral deformation often occurs at the girder ends, typically leading to the squeezing and cracking of seismic blocks by the girder webs. To address these technical challenges, this paper investigates a new type of slide-rail lateral joint structure that can create a longitudinal sliding effect between two bridge decks of the old and new bridge box girders, thereby effectively reducing the lateral deformation at the girder ends. First, this paper employs the finite element method to conduct a numerical analysis of a real-world bridge widen-ing project, exploring the working mechanism and application feasibility of this novel connection method. The results show that, in the case study, if the traditional joint method is used, the lateral displacement at the girder ends can reach up to 40mm after three years of widening. However, when the slide-rail joint structure is employed, the lateral displacement at the girder ends is limited to no more than 6mm. This demonstrates that the new joint method can indeed effectively address the issue of excessive lateral deformation at the ends of the widened struc-ture. Second, given that the slide-rail lateral joint structure is a relatively precise engineering structure, this paper exam-ines the lateral load transfer mechanism under loads such as wheel loads and foundation settlement differences. It discusses the load-bearing characteristics of various components, including square steel pipes, lateral connection rebars, concrete flange plates, and embedded rebars. Finally, through a parameter sensitivity analysis, it is found that the torsional stiffness of the square steel pipes is a critical parameter for ensuring the load-bearing capacity of the structure. Therefore, it is recommended to set the wall thickness of the square steel pipes to 5mm. Based on these research findings, this paper theoretically demon-strates that the new slide-rail lateral joint structure can effectively solve the technical challenges encountered dur-ing the lateral joint widening of multi-span long-span concrete continuous box girder bridges, providing a new solution for this field.

Currently, there is an increasing interest to develop eco-friendly and efficient pigment extraction processes for diverse applications. In this study, we report the comparison between the assisted extraction performed by ultrasonication and microwave with a conventional method to obtain cochineal pigments from Dactylopius coccus Costa. Our independent variables were solvent amount, temperature and irradiation time, and the corresponding optimization was performed by three factors and three levels with a Box-Behnken design. The pigment contents were quanti-fied through UV-vis spectroscopy, and the pigment mixture of extracts was assessed by infrared spectroscopy. It is highlighted that after optimization, the extraction assisted by ultrasound gave a yield of 47% with an efficiency of 31.3 mg/min, whereas the yield obtained from the extraction assisted by microwave was 41% with 27.3 mg/min efficiency, both higher that the efficiency ob-tained with a conventional method (3.5 mg/ml).

In this digital era, laundry applications come as an innovative solution to meet the laundry needs of modern people who often have busy schedules and limited time. This research aims to make a significant contribution to our broader understanding of how digital innovations can revolutionize mundane tasks. This research uses the Waterfall model, which is one of the methods in the Software Development Life Cycle (SDLC). The development process begins with the Requirement Analysis stage, where application requirements and specifications are collected and thoroughly analyzed to ensure that the developed application will meet user expectations. After that, the System Design stage is conducted, where the application architecture, user interface design, and database structure are designed in detail to ensure conformity with the previously identified needs.The next stage is Implementation, where program code is written and application features are developed according to the design that has been made. The final stage is Integration and Testing, where all application components are combined and tested thoroughly to detect and fix any errors or bugs that may exist. The results of this study produced a web-based shuttle laundry service application using the Laravel framework called "All Fresh Laundry". This application can order clothes washing services according to its membership, where there are 3 types of membership based on price and of course have different benefits. In addition, the testing phase of this application using black box testing shows that all menu features function properly according to their functions. Each component of the "All Fresh Laundry" app was thoroughly tested to ensure that no errors or malfunctions occurred. The results of this testing make it clear that every feature, from online ordering to laundry status tracking, works well and meets the specifications that have been set, so that this application can provide an optimal and reliable user experience.

This research proposes an algorithm to sign messages using the ElGamal asymmetric cryptosystem, called: Digital signature algorithm based on ElGamal, Diffie-Hellman protocol and the number π (DSAπ). This proposal has a high level of security like the DSA standard, in addition, execution times are reduced in relation to it. The Diffie-Hellman protocol and the number π were used in the construction of the digital signature algorithm in conjunction with the Hash-Sha-512 function. Some experiments are presented to provide evidence that the bits on the right side of the decimal point of π appear randomly, such as: a color image was constructed of a string of consecutive bits chosen at random, of the number π. Subsequently, parameters such as: entropy, correlation, discrete Fourier transform, goodness-of-fit test χ2 were evaluated. It is mentioned that an S-box 8×8 is involved in the signature. The sensitivity of the signature was measured, that is, when small changes are made to the sender’s private key, or small changes to the message. Finally, an image was constructed using the signatures of random texts, and subsequently the randomness of its pixels was obtained, to verify that there is no relationship between the different signatures.

Ensemble fuzzing in parallel with heterogeneous fuzzers has been proposed to leverage the advantages of diverse fuzzers and improve testing efficiency. However, in current ensemble fuzzing methods, the collaboration among different fuzzers is achieved solely by synchronizing the seeds discovered by each fuzzer. This results in a high likelihood of different fuzzers choosing the same seeds and creating a large number of equivalent testcases, thus reducing overall fuzzing efficiency. Meanwhile, the existing task division method proposed by AFLTeam is highly coupled with the fuzzer specially designed for it, making it challenging to apply to ensemble fuzzing directly. So, in this paper, we proposed a callgraph-based task division method suitable for ensemble fuzzing. Firstly, we divided the target program’s callgraph into subgraphs (subtasks) balancing expected workloads. Then, we divided the global seed corpus into sub-corpora, each corresponding to a subtask, making fuzzers easily accept the subtasks. Finally, we designed synchronization mechanisms for coverage bitmaps and seeds to realize the collaborative fuzzing among different fuzzers, and a cyclic subtask scheduling strategy to fully leverage the benefits of ensemble fuzzing. We have implemented a prototype called TAEF. The evaluation results show that in the best-case scenario, our method has up to 24% more branch coverage than previous work.

Self-compacting concrete is essential for vertical structures due to high reinforcement and usage of pumps for transporting the concrete at the working site. SCC is mainly influenced by self-curing for arid areas. To explore the SCC (Self-Compacting Concrete) mixture and condition influencing the self-curing condition were determined using the experimental procedure. Determination of various parameters was done using T50 slump flow, V-funnel, L-box-box, J ring test, compressive strength, splitting tensile strength, and flexural strength test. After the experimental investigation, it shows that if the dose if the dosage of superplasticizer (SNF%) increases, it will improve the concrete mixture's different properties, such as flowability and ability to pass. Higher water-to-cement ratios (w/c) generally result in enhanced flowability and stability. Mixture 9 (SNF 0.35, w/c 0.5) demonstrates favourable results across all parameters, indicating excellent flowability and stability. Mixture 9 (SNF 0.35, w/c 0.5) also shows favourable flowability and stability characteristics. Lower concentrations, such as 0.5%, may have a positive effect up to a certain point but might not provide sustained improvement over the curing period. On the other hand, concentrations of 1% and 2% demonstrated consistent and significant enhancement in strength throughout the 28 days. It is found that the higher concentrations of PEG 4000 may be more effective in improving the material strength.

In current study, the production of microparticles from fifteen commercial sugarcane pulp (SCP) lunch-boxes into different types of food under different conditions was investigated, where we used DI water, 4% HAc, and 95% EtOH to simulate aqueous, acidic, and fatty foods. Results showed that compared with DI water and 95% EtOH, 4% HAc caused the degradation of sugarcane fibers, resulting in the highest number of microparticles released, which was significantly greater than the specified limit value. It was estimated that consumers might intake a total number of 36,400 ~ 231,700 items per meal per lunch-box, of which the proportion of microparticles with particle size between 100 ~ 500 μm was the largest, with a number of 12,376 ~ 130,795 items. Moreover, of all SCP lunch-box except S-11, Al and Fe are the main metals, ranging between 35.16 ~ 1244.04 and 44.71 ~ 398.52 mg/kg, respectively, followed by Pb, Ti, and Sr. Interestingly, unlike other lunch-boxes, the content of Pb in S-11 was the highest, with a number of 136 mg/kg. This study provides important information that the safeness including both the production of microparticles and the metallic elements should be considered for SCP lunch-boxes when in contact with food.

The current research work illustrates an economic and rapid approach towards biogenic synthesis of silver nanoparticles using aqueous Punica granatum leaves extract (PGL-AgNPs). The optimization of major parameters involved in the biosynthesis process was done using Box-Behnken Design (BBD). The effects of different independent variables (parameters) namely concentration of AgNO3, temperature and ratio of extract to AgNO3on response viz. particle size and polydispersity index were analyzed. As a result of experiment designing, 17 reactions were generated which were further validated experimentally. The statistical and mathematical approaches were employed on these reactions in order to interpret the relationship between the factors and responses. The biosynthesized nanoparticles were initially characterized by UV-vis spectrophotometry followed by physicochemical analysis for determination of particle size, polydispersity index and zeta potential via dynamic light scattering (DLS), SEM and EDX studies. Moreover, the determination of functional group present in the leaves extract and PGL-AgNPs was done by FTIR. Antibacterial and antibiofilm efficacies of PGL-AgNPs against Gram-positive and Gram-negative bacteria were further determined. The physicochemical studies suggested that PGL-AgNPs were round in shape and of ~ 37.5 nm in size with uniform distribution. Our studies suggested that PGL-AgNPs exhibit potent antibacterial, and antibiofilm properties.

RAD51 is a recombinase that plays a pivotal role in homologous recombination. Although the role of RAD51 in homologous recombination has been extensively studied, it is unclear whether RAD51 can be involved in gene regulation as a co-factor. In this study, we found in silico evidence that RAD51 may contribute to the regulation of genes involved in the autophagy pathway through interaction with E-box proteins such as USF1, USF2, and/or MITF in GM12878, HepG2, K562, and MCF-7 cell lines. The canonical USF binding motif (CACGTG) was significantly identified at RAD51 binding sites in all four cell lines. In addition, genome-wide USF1, USF2, and/or MITF-binding regions significantly coincided with the RAD51-binding sites in the same cell line. Interestingly, the promoters of genes associated with the autophagy pathway were significantly occupied by RAD51 in all four cell lines. Taken together, these results predicted a novel role of RAD51 that had not been addressed previously, and provided evidence that RAD51 could possibly be involved in regulating genes associated with the autophagy pathway, through interaction with E-box binding proteins.

Because of lower solubility and considerable metabolism, vardenafil (VRD) bioavailability is 15 %. To get over this obstacle, this study aimed to increase the solubility, hasten the onset of action, and mask the unpleasant taste of VRD utilizing β-cyclodextrin (β-CD) and formulation of the inclusion complex as oral disintegrating tablets (ODTs). The solubility of the obtained complexes in various ratios has been studied. A Box-Behnken design (BBD) was utilized to investigate the influence of excipients on the quality of ODTs. The solubility of VRD was improved at 1:2 drug: β-CD ratio. The formulated VRD-ODTs exhibited satisfying results regarding the hardness and disintegration time. In addition, in vivo taste masking and disintegration time showed improved results, after placing the tablets in the oral cavity of the healthy volunteers. The pharmacokinetic parameters for the optimized VRD–ODTs exhibited a significant improvement with P < 0.05 in the maximum plasma concentration and reduction in the time needed to reach this concentration when compared with the marketed tablets. Finally, the optimized VRD-ODTs exhibited increased oral absorption of VRD and subsequent decreasing the time of onset of clinical effect and masking the unpleasant taste, which is favored for patients with erectile dysfunction.

Single-molecule magnets (SMMs) have garnered significant interest in the field of molecular magnetism due to their unique magnetic properties at the nanoscale. These molecular systems exhibit magnetisation behaviour reminiscent of conventional bulk magnets but with distinct advantages such as size-dependent properties and potential applications in quantum computing and high-density data storage. However, challenges remain in harnessing their properties for practical applications, including their susceptibility to degradation and limited control over their assembly and organisation.

The folding of certain proteins (e.g., enzymes) into perfectly defined 3D conformations via multi-orthogonal interactions is critical to their function. Concerning synthetic polymers chains, the “folding” of individual polymer chains at high dilution via intra-chain interactions leads to so-called single-chain nanoparticles (SCNPs). This review article describes the advances carried out in recent years in the folding of single polymer chains into discrete SCNPs via multi-orthogonal interactions using different reactive chemical species where intra-chain bonding only occurs between groups of the same species. First, we summarize results from computer simulations of multi-orthogonally folded SCNPs. Next, we comprehensively review multi-orthogonally folded SCNPs synthesized via either non-covalent bonds or covalent interactions. Finally, we conclude by summarizing recent research about multi-orthogonally folded SCNPs prepared through both reversible (dynamic) and permanent bonds.

ACE2, the putative receptor for the novel coronavirus (2019-nCoV), played an important role in cell entry of 2019-nCoV. However, it is not yet clear what cell types within the human body express ACE2. Here, a systematic analysis was undertaken using published single cell datasets. In total, our study analyzed 229652 cells, from five different organs, derived from 88 donors. The top ACE2 expressing cells include proximal tubule cells in the kidney and enterocytes in the intestine. Other major ACE2 expressing cells in the kidney include podocytes, intercalated cells and endothelial cells. Our results offer a comprehensive atlas of ACE2 expression at the single cell level and unravel the enormous potential targets of 2019-nCoVinfection beyond the lung.

Clean use of photons from light to activate chemical reactions offer many possibilities in different fields, from chemistry and biology to materials science and medicine. This review article describes the advances carried out in last decades toward the phototriggered synthesis of single-chain polymer nanoparticles (SCNPs) as soft nanomaterials with promising applications in enzyme-mimicking catalysis and nanomedicine, among other different uses. First, we summarize different strategies developed to synthesize SCNPs based on photoactivated intrachain homocoupling, phototriggered intrachain heterocoupling and photogenerated collapse induced by external cross-linker. Next, we comprehensively review the emergent topic of photoactivated multifolding applied to SCNP construction. Finally, we conclude by summarizing recent strategies towards phototriggered disassembly of SCNPs.

Curved continuous steel box girders are extensively utilized in bridge construction due to its efficiency and environmental benefits. However, in regions with significant temperature fluctuations, temperature effects can result in cumulative deformation and stress concentration, which may severely impact structural safety and durability. This study examines the structural response of curved continuous steel box girders under diverse temperature conditions and also develops a comprehensive parameterized thermodynamic numerical model. The model assesses the influence of cross-sectional shape parameters including; the number of cross-sectional box chambers, diaphragm thickness, and height-to-width ratio, as well as longitudinal structural parameters such as planar configurations, width-to-span ratio, and support arrangements, along with the arrangement of stiffening ribs on the temperature-induced effects in the girders. Results indicate that optimizing the width and eccentricity of support stiffeners to 30% and 25% in the support plate size, respectively, can significantly alleviate local temperature-induced stresses. Additionally, variations in longitudinal and transverse stiffeners manifest minimal impact on thermal performance. These findings provide a theoretical foundation for improved design and construction practices, offering practical design recommendations to mitigate temperature effects and enhance the longevity and safety of such structures.

High purity hydrogen is a necessary need for fuel cell. Pressure swing adsorption (PSA) technology is one of the effective methods for hydrogen purification and separation. A layered adsorption bed packed with activated carbon and zeolite 5A for five-component gas mixture (H2/CH4/CO/N2/CO2=56.4/26.6/8.4/5.5/3.1 mol%) PSA model was built. The model was validated by breakthrough curves and comparing the results with the experimental data. The purification performance of six-step layered bed PSA cycle was studied using the model. In order to optimize the cycle, the Box-Behnken design (BBD) method was used, as implemented in Design Expert™. In addition to adsorption time, the pressure equalization time and the feed flow rate were considered as independent optimization parameters. Quadratic regression equations were then obtained for three responses of the system, namely purity, recovery, and productivity. To explore a better optimization solution, a novel optimization method of machine learning with back propagation neural network (BPNN) was proposed in this work, a kind of heuristic algorithm of genetic algorithm (GA) is introduced to optimize the structure of BPNN. The predicted outputs of hydrogen production using two kinds of models based on back propagation neural network-genetic algorithm (BPNN-GA) and BBD method integrated with BPNN-GA (BBD-BPNN-GA) models. The results showed that the BBD-BPNN-GA model have a better performance with the mean square error (MSE) of 0.0005, while the MSE of BPNN-GA model was 0.0035. And the correlation coefficient of R-values were much closer to 1 of the BBD-BPNN-GA model, which was illustrated that the BBD-BPNN-GA model can be effectively applied to the prediction and optimization of PSA process.

The Opuntia ficus-indica (OFI) prickly pear peel, is a residue product and was used as a substrate in solid-state fermentation (SSF) to obtain bioactive compounds of interest due to its antimicrobial and antioxidant activity. A Box Hunter &amp; Hunter design to evaluate the independent factors was used. These factors were temperature (°C), inoculum (spores/g), humidity (%), pH, NaNO3 (g/L), MgSO4 (g/L), KCl (g/L) and KH2PO4 (g/L). The response factors were hydrolyzable and condensed tannins amount. In addition, the fermentation extracts the antioxidant and antimicrobial activity were evaluated. The results showed that the humidity (%), inoculum (spores/g) and temperature (°C) affect the release of hydrolyzable and condensed tannins. The treatments 13 and 16 were the best to accumulate condensed (43 mg/g) and hydrolyzable tannins (3.8 mg/g) respectively. Besides, the fermented extracts showed a higher antioxidant activity compared than the unfermented peel extracts, as well as a high inhibition versus E. coli, Alternaria sp. and Botrytis spp. The use of the fermentation process is a good alternative for the recovery of waste and the accumulation of bioactive molecules with potential industrial application.

The cutter structure and layout scheme of PDC (Polycrystalline Diamond Compact) bits are important factors in improving efficiency. To further improve the drilling efficiency of PDC bits, axe, triangular prism, and cylindrical PDC cutters were used as research objects. Based on the measured granite data, a finite element model of non-homogeneous granite was established and verified by uniaxial compression simulation. The rock-breaking process of different cutter combination schemes was compared using the finite element method, and the parameters in the best scheme were optimized using the Box-Behnken response surface method. The results show that the constructed model of non-homogeneous granite is consistent with the stress-strain relationship of real granite and is reliable. The axe PDC cutter is more aggressive than the other two cutters and is more suitable for the front row of the bit blade tooth arrangement, while the triangular prism cutter is the second most aggressive and is suitable for the rear row of tooth arrangement, and the best combination scheme is the front row of axe cutter and the rear row of triangular prism cutter arranged alternately with the axe cutter. The optimal transverse and longitudinal distances of the optimized triangular prism cutter from the front axe cutter are 10mm and 7mm, and the optimal transverse and longitudinal distances of the rear axe cutter from the front cutter are 10.06mm and 7mm. The drilling speed is more stable during drilling and the PDC bit with mixed tooth arrangement has 16.8% and 16.6% higher rate of penetration(ROP) compared with the bit with single axe cutter and triangular prism cutter, and the drilling speed is more stable during working, which can effectively improve the rock breaking efficiency of the PDC bit. The field application proves that the bit with mixed cutter arrangement is easier to break the complex formations, with more stable ROP and better efficiency. The study can provide theoretical support for the cutter layout of the PDC bit.

Hardaliye, a traditional non-alcoholic beverage, made from red grape pomace from wine production and produced by lactic acid fermentation with addition of different concentrations of whole/ground or heat-treated mustard seeds and of sour cherry leaves. Short shelf life of hardaliye limits its consumption and search in trend to process hardaliye to extend its shelf life. Thus, high hydrostatic pressure treatment of hardaliye drink with determination of changes in physicochemical and sensory properties in addition to microbial inactivation were studied according to Box-Behnken design. Maximum 5.10±0.00, 4.21±0.00, 5.38±0.59 and 5.05±0.22 log reductions were obtained in total mesophilic aerobic bacteria, total mold and yeast, Brettanomyces bruxellensis and Lactobacillus brevis by HHP. Shelf-life studies of the hardaliye samples were conducted with optimum processing parameters of 490 MPa, 29 oC for 15 min with the response variables of OD520 and inactivation of L. brevis. Both control and HHP treated samples were stored at 4 and 22 C for shelf-life studies. While control samples at 4 and 22 °C were spoiled at the 15th and 3rd days, HHP treated samples were spoiled after 108th and 228th days, respectively.

In response to the need to address the safety challenges in the use of artificial intelligence (AI), this research aimed to develop a framework for a safety controlling system (SCS) to address the AI black-box mystery in the healthcare industry. The main objective was to propose safety guidelines for implementing AI black-box models to reduce the risk of potential healthcare-related incidents and accidents. The system was developed by adopting the multi-attribute value model approach (MAVT), which comprises four symmetrical parts: extracting attributes, generating weights for the attributes, developing a rating scale, and finalizing the system. On the basis of the MAVT approach, three layers of attributes were created. The first level contained 6 key dimensions, the second level included 14 attributes, and the third level comprised 78 attributes. The key first level dimensions of the SCS included safety policies, incentives for clinicians, clinician and patient training, communication and interaction, planning of actions, and control of such actions. The proposed system may provide a basis for detecting AI utilization risks, preventing incidents from occurring, and developing emergency plans for AI-related risks. This approach could also guide and control the implementation of AI systems in the healthcare industry.

Culverts are often required under earth embankment to allow for the crossing of a watercourse, like streams, to prevent the road embankment from obstructing the natural waterway. The opening of the culvert is determined based on the waterway required to accommodate the design flood, whereas the thickness of the culvert section is designed based on the loads applied to the culvert. This paper studies some design parameters of box culverts, such as the thickness of the haunch, the coefficient of earth pressure, the thickness of box culvert, and depth of fill on the top slab, to show the effect of haunch on the stresses of the box culvert. The study investigated the variation in stresses and the cost comparison made for different width of the box culvert. The percentage reduction in the cost of culvert based on the presence of haunch is presented.

The research paper investigates the synthesis of metal matrix composites (MMCs) through the amalgamation of aluminum and silicon carbide particles, employing a two-step mixing methodology called the stir casting method. Metal matrix composites are materials that enhance the capabilities of a metallic matrix by incorporating another material. This leads to better characteristics such as tensile and shear moduli, fatigue and fracture properties, thermal expansion coefficient, and more. Aluminum-matrix composites are a class of materials that possess distinct characteristics that may be modified by altering factors such as the type of reinforcing material, the amount of reinforcement, and the fabrication technique employed to produce the composite. The concept aims to combine the desirable properties of metals and ceramics by incorporating durable refractory particles into a malleable metal structure. The fabrication process employs the stir casting technique, where reinforcing phases are mechanically stirred into a molten matrix to create cast composites with reinforcement volume percentages of up to 30%. The study utilizes Response Surface Methodology to enhance the mechanical properties of the composites through the optimization of manufacturing parameters, including stirring temperature, time, and speed. The study entails analyzing the correlation between different casting conditions and the resulting changes in hardness and tensile strength.

In this paper, we make research on fractal characteristics of the superposition of fractal surfaces in the view of fractal dimension. We give the upper bound of the lower and upper Box dimension of the graph of the sum of two bivariate continuous functions and calculate the exact values of them under some particular conditions. Further, it has been proved that the superposition of two continuous surfaces cannot keep the fractal dimensions invariable unless both of them are two-dimensional. A concrete example of numerical experiment has been provided to verify our theoretical results. This study can be applied to the fractal analysis of metal fracture surfaces or computer image surfaces.

This study aimed to compare the differences in durability and prestress loss between normal-weight concrete (NC) and lightweight aggregate concrete (LWC) prestressed box girders, which were constructed at the same time in the same area, so as to verify the superiority of using synthetic lightweight aggregate (LWA) made from reservoir sediments in prestressed bridges. For the NCs and LWCs used in prestressed box girders, the basic mechanical properties were tested on the one hand, and the durability properties were tested on the other hand. Then, through the prestress monitoring system, the prestress loss of the two groups of the prestressed box girders was tracked. The results of the durability test confirmed that LWC can inhibit the penetration of air, water, and chloride ions by strengthening the interfacial transition zone between the aggregate and the cement paste, thereby improving its durability. Moreover, the magnetic flux prestress loss of the NC prestressed box girder reached 8.1%. In contrast, the magnetic flux prestress losses on both sides of the LWC prestressed box girder were 4.6% and 4.9%, respectively. This verified that, under the same environmental conditions, the use of LWC produced less of a prestress loss than the use of NC.

Supercritical fluid extraction (SFE) is an innovative green technology for the extraction of phytochemicals from plants. Therefore, this study aimed to evaluate the application of SFE and to optimize the extraction condition of the Thai herbal formula, Kleeb Bua Daeng (KBD). A Box-Behnken design (BBD) with response surface methodology was used to determine the effect of extraction time, temperature, and pressure on response variables including extraction yield, total phenolic content (TPC), total flavonoid content (TFC), total carotenoid content (TCC) and total anthocyanin content (TAC) of KBD formula. The highest percentage extraction yield, TPC, TFC, and TCC of the extracts were 3.81%, 464.56 mg gallic acid equivalents/g extract, 217.19 mg quercetin equivalents/g extract, and 22.26 mg β-carotene equivalents/g extract, respectively. The results indicated that SFE is a suitable method of extraction for green recovery of some phytochemicals from the KBD formula.

Machining titanium alloy (Ti6Al4V) used in orthopedic implants by conventional metal cutting processes is challenging due to excessive cutting forces, low surface integrity and tool wear. To overcome these difficulties and for ensuring high-quality products, various industries employ wire electrical discharge machining (WEDM) for precise machining of intricate shapes in titanium alloy. The objective is to make WEDM machining parameters as efficient as possible for machining the bio-compatible alloy Ti6Al4V using box-behnken design (BBD) and Non-dominated Sorting Genetic Algorithm II (NSGA II). A quadratic mathematical model is created to represent the productivity and the quality factor (MRR and surface roughness) in terms of varying input parameters, such as pulse active (Ton) time, pulse inactive (Toff) time, peak amplitude (A) current and applied servo (V) voltage. The established regression models and related prediction plots provide a reliable approach for predicting how the process variables affect the two responses viz MRR and SR. The effects of four process variables on both the responses were examined, and the findings revealed that the pulse duration and voltage has a major influence on the rate at which material is removed (MRR) whereas pulse duration influence quality (SR).  The trade-off between MRR and SR, when significant process factors are included emphasizes the need for a reliable multi-objective optimization method. The intelligent metaheuristic optimization method named non-dominated sorting genetic algorithm II (NSGA II) is utilized to provide pareto optimum solutions in order to achieve high material removal rate (MRR) and low surface roughness (SR).

F-box protein is a key protein of the SCF E3 ubiquitin ligase complex, responsible for substrate recognition and degradation through specific interactions. Previous studies have shown that F-box proteins play crucial roles in Cryptococcus sexual reproduction. However, the molecular mechanism by which F-box proteins regulate sexual reproduction in C. neoformans is unclear. In the study, we discovered the AICAR transformylase/IMP cyclohydrolase Ade16 as a substrate of Fbp1. Through protein interaction, protein stability, and in vivo ubiquitination experiments, we demonstrated that Ade16 is a substrate for Fbp1. To examine the role of ADE16 in C. neoformans, we constructed the iADE16 strains and ADE16OE strains to analyze the function of Ade16. Our results revealed that the iADE16 strains had a smaller capsule and showed growth defects under NaCl, while the ADE16OE strains were sensitive to SDS but not to Congo red, which is consistent with the stress phenotype of the fbp1Δ strains, indicating that the intracellular protein expression level after ADE16 overexpression was similar to that after FBP1 deletion. Interestingly, although iADE16 strains can produce basidiospores normally, ADE16OE strains can produce mating mycelia but not basidiospores after mating, which is consistent with the fbp1Δmutant strains, suggesting that Fbp1 is likely to regulate the sexual reproduction of C. neoformans through the modulation of Ade16. Fungal nuclei development assay showed that the nuclei of the ADE16OE strains failed to fuse in the bilateral mating, indicating that Ade16 plays a crucial role in the regulation of meiosis during mating. In summary, our findings have revealed a new determinant factor involved in fungal development related to the post-translational regulation of AICAR transformylase/IMP cyclohydrolase.

The building sector is the largest consumer of energy and there are still major scientific challenges in this field. The façade, being the interface between the exterior and interior space, plays a key role in the energy efficiency of a building. In this context, this paper focuses on a ventilated bioclimatic wall for NZEB zero energy buildings. The objective of this study is to investigate an experimental set-up based on a Hot Box allowing characterizing the thermal performances of the ventilated wall. A specific ventilated prototype and an original thermal metrology has been developed. This paper presents the ventilated prototype, the experimental set-up and experimental results on the thermal performances of the ventilated wall. The influence of the air space thickness and the air flow rate on the thermal performances of the ventilated wall is studied.

District heating networks have become widespread due to their ability to distribute thermal energy efficiently, which leads to reduced carbon emissions and improved air quality. The characteristics of these networks vary remarkably depending on the urban layout and system amplitude. Moreover, extensive data about the energy distribution and thermal capacity of different areas are seldom available. Design, optimization and control of these systems are enabled by the availability of fast and scalable models of district heating networks. This work addresses this issue by proposing a novel method to develop a scale-free model of large-scale district heating networks. Starting from coarse data available at the main substations, a physics-based model of the system aggregated regions is developed by identifying the heat capacity and heat loss coefficients. The model validation on the network of Västerås, Sweden, shows compatibility with literature data and can therefore be exploited for system design, optimization and control-oriented applications. In particular, the possibility to estimate the heat storage potential of network regions allows new smart management strategies to be investigated.

Ucuùba fat is fat obtained from a plant found in South America, mainly in Amazonian Brazil. Due to its biocompatibility and bioactivity, the Ucuùba fat was used for production of ketoconazole-loaded nanostructured lipid carriers (NLC) in view of an application for the treatment of onychomycosis and other persistent fungal infections. The development and optimization of the Ucuùba fat based NLC were performed using a Box-Behnken design of experiment. The independent variables were surfactant concentration (% w/v), liquid lipids concentration (% w/v), solid lipids concentration (% w/v), while the outputs of interest were particle size, polydispersity index (PDI) and drug encapsulation efficiency (EE). The Ucuùba fat based NLC were produced and the process optimized determining a predictive mathematical model. Applying the model, two formulations with the pre-required particle size, i.e., 30 and 85 nm, were produced for further evaluation. The optimized formulations were characterized and showed a particle size in agreement to the predicted value, i.e. 33.6 nm and 74.6 nm, respectively. The optimized formulations were also characterized using multiple techniques in order to investigate the solid state of drug and excipients (DSC and XRD), particle morphology (TEM) and interactions between the formulation components (FTIR). Furthermore, particle size and surface charge of the formulations was studied during a one-month stability study and did not evidence any significative modification during storage.

Carukia barnesi (Cb), Malo kingi (Mk) and Chironex fleckeri (Cf) are dangerous Australian box jellyfish species that provoke distinct and not well understood envenomation syndromes. Specifically, Cb and Mk are small, rare and able to induce a systemic syndrome of generalised muscle pain and catecholamine excess termed “Irukandji syndrome”; Cf has been widely regarded as one of the most venomous organisms in the animal kingdom causing severe sting site pain combined with potentially lethal cardiotoxicity. Building on past studies of major chirodropid and carybdeid species venoms, this study compared the utility of various cubozoan specific antibody reagents to better define the relationships between venom proteins from both exemplar Irukandji species (Cb and Mk) and the archetype C. fleckeri box jellyfish. With the aid of commercial ovine derived Cf-specific antivenom, mouse antibodies reactive to Cb and Mk and rabbit antibodies specific to two Cf toxins (CfTX-1 and 2), as well as human sera, the cross-reactivity of jellyfish species-specific polyclonal antibodies against these three cubozoan venoms was investigated. Immunoblot assays revealed distinc levels of immune recognition across the three species, indicating that Mk specific reagents may bind both Irukandji and Cf venoms. Irukandji venom appears to be antigenic with the exception of a few proteins in the range of 43/46 kDa maybe homologous to CfTX-1 and 2. The implications of such antibody binding for future antivenom development require further investigation.

Background DaVinci Single-Port (SP) robotic surgery offers several benefits compared to traditional multiport laparoscopic or robotic surgeries. One of the main advantages is that it allows for a minimally invasive approach, resulting in a single, smaller incision and reduced trauma to the patient’s body leading to less postoperative pain, faster recovery, and reduced risk of complications. The cosmesis of a single port with minimal visible scarring is also an attractive aspect to the patients; however, many surgeons use an additional port for energy device, stapler use, and drain insertion. Pure single port surgery with one incision is still rare. Here we share our experience of first 10 cases using SP robotic platform in colorectal surgery. Methods From May 2023 to December 2023, colorectal patients who underwent SP-robotic surgery were analyzed. Placement of the incision was umbilicus for 8 patients, and right lower quadrant for 2 patients through which ileostomy maturation was performed. Data including perioperative parameters and postoperative outcomes were analyzed with a median follow-up of 4.6months (range 0.6-7.4months). Results A total number of 10 colorectal patients underwent DaVinci Single-Port robotic colorectal surgery at our institution during this period. Demographics of the patients showed 4 males (40%) and 6 females (60%) with a median age of 63.5years (range 50-75years). Median body mass index (BMI) was 22.89kg/m2 (range 19.92-26.84kg/m2), and 9 patients were diagnosed with colorectal cancer and 1 patient was diagnosed with rectal gastrointestinal tumor. One patient underwent anterior resection and cholecystectomy simultaneously. Mean operation time was 222min (range 142-316min), and mean wound size was 3.25cm (range 2.5-4.5cm). Nine patients underwent surgery with single incision through which single port trocar was inserted, and one patient had one additional port for drain insertion. Mean hospital stay was 6 days (range 4-8 days) with 1 postoperative complication of bleeding requiring transfusion, but there was no re-admission within 30 days. Conclusion Overall, our experience with single-port robotic colorectal surgery has been promising. With only one patient with additional port for drain insertion, all nine patients underwent SP-robotic surgery with single incision for colon as well as rectal surgeries. Compared to an average postoperative length of stay of 6.5-8 days in laparoscopic colorectal surgeries reported in literature, SP-robotic surgery showed faster recovery of 6 days highlighting its benefits in patient recovery and satisfaction.

This study investigated the influence of nutrient inputs and their timing on saffron yield and quality. The study was conducted from 2016 to 2020 and involved the application of eight different fertilization treatments at various stages of saffron growth. These treatments included single doses in Autumn (A), Winter (W), and Spring (S); double doses in Winter-Spring (AW), Autumn-Spring (AS), and Winter-Spring (WS); and a triple dose in Autumn-Winter-Spring (AWS). A control group (C) received no fertilizer. A compound fertilizer with a 15-15-15 composition was applied across all treatments, with nitrogen (N) rates of 67.5 kg/ha for single doses (A, W, S), 135 kg/ha for double doses (AWF, ASF, WSF), and 202.5 kg/ha for the triple dose (AWSF). Similar rates were applied for phosphorus (P) and potassium (K). The findings demonstrated that fertilization generally enhanced saffron attributes. The triple dose treatment yielded the most effective results. The timing of fertilization also played a crucial role, as split applications during different growth stages led to higher production especially winter fertilization. However, spring fertilization had limited impact due to decreased plant activity and reduced nutrient absorption during that period. Although the yield increased, the qualitative aspects of saffron, including color (crocin), taste (picrocrocin), and aroma (safranal), were not significantly influenced by the fertilization treatments. Nevertheless, these attributes remained within the natural limits defined by ISO-3632, indicating that fertilization practices did not compromise saffron quality. Our study highlights the significance of nutrient inputs and their timing in optimizing saffron yield. It provides valuable insights for developing efficient fertilization programs to enhance saffron production while preserving its quality characteristics.

Background. In the central-eastern region of the Mediterranean island of Sardinia more than two decades ago, a mountain area was identified where the population displays exceptional longevity, especially among men (the longevity Blue Zone, LBZ). This community was thoroughly investigated seeking to understand the underlying factors of this phenomenon. In the present study, 11 genetic markers previously associated with longevity in several long-lived populations were analyzed. Methods. APOE (rs429358 and rs7412), APOE promoter (rs449647, rs769446, and rs405509), ACE1 (rs1799752), IL6 ‒174G/C (rs1800795), TNFα ‒308G/A (rs1800629), FOXO3A (rs2802292), KLOTHO (rs9536314) and G6PD (c.563C→T) were investigated. PCR-based genotyping was performed following genomic DNA extraction from 150 nonagenarians living in the LBZ and 150 controls from a nearby area. Results. No significant deviation of the frequency of the analyzed markers was detected between the two groups except a weak association with the –174G&gt;C gene variant of the IL-6 gene (p=0.040), a major modulator of the inflammatory response. Conclusions. The findings of this study do not support a significant association of known genetic variants on survival in the population of the Sardinian LBZ. Other genetic or epigenetic traits might play a role not yet identified.

Sperm gain fertilization ability and forward movement characteristics during epididymal transport. Sperm maturation is inseparable from the processing of the epididymis. Compared with other reproductive organs, relatively little is known about the epididymis. However, with the development of molecular biology and the improvement of single-cell sequence technology, we gradually realized that we should re-examine the importance of the epididymis for sperm mat-uration and for the entire male reproductive system. Recently, epididymis related reports have tended to be more regionalized and more refined. We can understand cell distribution and gene expression from the perspective of a single cell. It has been reported that different regions of the epididymis have different functions and different cell compositions, which may be determined by gene expression. Here, we comprehensively reviewed the epididymal studies. From the ana-tomical structure of the epididymis to the division of its regions, we focused on the cell compo-sition and region-specific genes differentially expressed in the epididymis. The gene expression of the epididymis extends to a series of biological processes of sperm in the epididymal cavity, and the serious effects of epididymal diseases on reproduction are discussed. Therefore, the importance of the epididymis in male reproduction is emphasized. With the maturity of single-cell spatial transcriptomics, it is hoped that the technology can be applied to epididymal research and bring about the spatiotemporal landscape of the epididymis at the single-cell level.

The strong coupling between individual quantum emitters and resonant optical micro/nanocavities is beneficial to understand light and matter interactions. Here we propose a plasmonic nanoantenna placed on a metal film to achieve an ultra-high electric field enhancement in the nanogap and ultra-small optical mode volume. The strong coupling between a single quantum dot and the designed structure is investigated in detail by both numerical simulations and theoretical calculations. When a single QD is inserted into the nanogap of the silver nanoantenna, scattering spectra show remarkably large spectral splitting and typical anti-crossing behavior of the vacuum Rabi splitting, which can be realized in the scattering spectra by varying the nanoantenna thickness. Our work shows a possible way to enhance light-matter interaction at a single quantum emitter limit, which can be useful for future quantum and nanophotonic applications.

Long-read single-molecule sequencing has revolutionized de novo genome assembly and enabled the automated reconstruction of reference-quality genomes. It also has been widely used to study structural variants, phase haplotypes and more. Here, we introduce the assembler— SMARTdenovo, which is an SMS assembler that follows the overlap-layout-consensus (OLC) paradigm. SMARTdenovo (RRID: SCR_017622) was designed to be a fast assembler that did not require highly accurate raw reads for error correction, unlike other, contemporaneous SMS assemblers. It has performed well for evaluating congeneric assemblers and has been successful for a variety of assembly projects. It is compatible with Canu for assembling high-quality genomes, and several of the assembly strategies in this program have been incorporated into subsequent popular assemblers. The assembler has been in use since 2015, and here we provide information on the development of SMARTdenovo and how to implement its algorithms into current projects.

An experiment was conducted to investigate the role of single nucleotide polymorphisms of the gene RNF34 3′UTR-588 G>A and RNF128 I1-2380C>T with carcass and meat quality traits of Chinese Simmental-cross steers. METHOD: We performed sequencing and restriction enzyme digestion to detect genotypes of RNF34 3′UTR-588 G>A and RNF128 I1-2380C>T. Then, we analyzed the association of novel single nucleotide polymorphisms in intron regions of the RNF128 gene and in the 3′UTR region of RNF34 and meat quality traits of Chinese Simmental-cross steers. RESULTS: Statistical analyses revealed that SNP of RNF128 (I1-2380C>T) was significantly associated with dressed weight, forepaw weight, carcass depth, carcass brisket depth, hind legs length (P<0.05), etc. And RNF34 (3′UTR-588 G>A) were significantly associated with testis weight, kidney weight, tare weight (P<0.05), etc. CONCLUSION: Our findings suggest that polymorphisms in RNF34 and RNF128 might be important genetic factors that influence carcass and meat quality in beef cattle. Thus, they might be useful markers for meat quality traits in future marker-assisted selection programs in beef cattle breeding and production.

In the last decade, we have witnessed an upsurge in nuclei-based studies, particularly coupled with next-generation sequencing. Such studies aim at understanding the molecular states that exist in heterogeneous cell populations by applying increasingly more affordable sequencing approaches, in addition to optimized methodologies developed to isolate and select nuclei. Although these powerful new methods promise unprecedented insights, it is important to understand and critically consider the associated challenges. Here, we provide a comprehensive overview of the rise of nuclei-based studies and elaborate on their advantages and disadvantages. Improved designs and appropriate use of the various experimental strategies will result in acquiring biologically accurate and meaningful information.

The CACCC-box motif emerges as a pivotal cis-regulatory element implicated in diverse developmental processes and diseases, particularly cardiovascular diseases (CVDs). This study centers on the intricate interplay between the CACCC-box and its binding proteins such as: the Krüppel-like family (KLF) of transcription factors as primary effectors in the context of CVDs. Our analysis was through a bioinformatics approach, which reveal significant transcriptional activity among KLF subgroup 2, exhibiting the highest number of interactions focusing on the established roles: pluripotency, cancer, and cardiovascular development and diseases. Our analysis reveals KLF's interactions with GATA4, MEF2C, NKX2.5 and other ~ 90 potential genes that participate in the regulation of the hypertrophic environment (or CVD's Environment). Also, the GO analysis showed genes containing the motif CACCC were enriched for multiple CVD’s, in combination with STRING analysis these results pointed to a link between KLFs and these diseases. The analysis further identifies other potential CACCC-box binding factors, such as SP family members, WT1, VEZF1, and -SALL4, which are implicated in cardiac contraction, remodeling, and inflammation processes.

Digital twins are an emerging technology that could be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components, as proportional valves. An input-output model for a novel water proportional cartridge valve is derived from physical modelling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two 2/2-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. The orifice equation, which is based on Bernoulli principles, is approximated by a polynomial which makes parameter estimation easier and makes modelling possible without measuring pressure of the varying control volume situated in the pilot stage part of the valve. Data were collected when the valve was operating as a component in a closed-loop system as part of a press-mill machine in a steel manufacturing plant. Parameter estimation was made by convex optimization with physical constraints to overcome problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method used for parameter estimation. A thorough estimation of the parameters relative errors is presented. The model contains 5 parameters related to the design parameters of the valve. The modelled position output is in good agreement with experimental data for training and test data. The model can be used for real time monitoring of the valve’s status by the model parameters. One of the model parameters varies linearly with production cycles. Thus, aging of the valve can be monitored.

Single-fluid electrospinning creates nanofibers from molten polymer solutions with active ingredients. The study utilized a combination of a fractional factorial design and a Box-Behnken design to examine crucial factors among a multitude of parameters and to optimize the electrospinning conditions that impact the fiber mats' morphology and entrapment efficiency of the Senna alata leaf extract. The findings indicated that the shellac content had the greatest impact on both fiber diameter and bead formation. The optimum electrospinning conditions were identified as a voltage of 24 kV, a solution feed rate of 0.8 mL/h, and a shellac-extract ratio of 38.5:3.8. These conditions produced nanosized fibers with a diameter of 306 nm, a low bead-to-fiber ratio of 0.29, and an extract entrapment efficiency of 96% within the fibers. The biphasic profile of optimized nanofibers was confirmed through an in vitro release study. This profile consisted of an initial burst release of 88% within the first hour, which was succeeded by a sustained release pattern surpassing 90% for the next 12 h, as predicted by zero-order release kinetics. The optimized nanofibers demonstrated antimicrobial efficacy against diverse pathogens, suggesting promising applications in wound dressings and protective textiles.

Experimental measurement of porous polypropylene (PP) using the DTC-25 TA laboratory equipment and hot box test has been compared. The thermal conductivity of materials indicates the insulation capability of building materials. Excellent building materials will have a lower thermal conductivities value as well as other building insulator performance metrics. While results show that increasing the volume fraction of fluid in the porous PP has an inverse association with the thermal conductivity of the material as predicted by porous media theories, there is a marked difference in the measured values of the thermal conductivity using the two methods. The thermal conductivity values of porous from DTC-25 and hot box test were 0.21 and 0.0033 W/mK, respectively. The difference in the thermal conductivity values was due to the misapplication of the Fourier’s guarded heat flow model in the DTC-25 device to a convective fluid porous medium material.

Background High Mobility Group Box-1 (HMGB-1) is implicated in the pathogenesis of thrombosis and cancer. In the present study, we aimed to evaluate its potential role as a diagnostic biomarker of portal vein thrombosis (PVT) among patients with hepatocellular carcinoma (HCC). Methods The study population included N=100 prospectively recruited patients with a novel diagnosis of HCC. We compared circulating HMGB-1 levels between 34 healthy controls, HCC patients with PVT (N=22), and HCC patients without PVT (N=78). Results HCC patients without PVT showed significantly higher median HMGB-1 serum levels (8.2 [5.5-13.1] ng/ml) than those observed in the case of HCC with PVT (5.5 [4.4-8.5] ng/ml; p=0.012) and in healthy controls (4.1 [3.1-8.2] ng/ml; p&lt;0.001). Among HCC patients, at univariate analysis, the presence of PVT was associated with higher median age (p=0.036), larger major cancer node diameter (p&lt;0.001), and lower HMGB-1 serum level (p=0.012). At multivariate analysis, the presence of PVT maintained a positive association with major node diameter p=0.001) and an inverse association with serum HMGB-1 levels (p=0.003). Conclusions These findings indicate that serum HMGB-1 bears an inverse association with PVT complicating HCC at the time of diagnosis and suggest that serum HMGB-1 depletion may mark PVT development in cirrhotic patients with HCC.

This work exclusively focuses on the assessment of the thermal performance of a multifunctional facade panel incorporating PCM in foam layers, recurring to a hot box heat flux meter method to determine the thermal transmittance (U-value). The experimental setup is based on the steady-state approach using climatic chambers, assuring a stable thermal environment. Even small fractions of PCM achieved a small reduction in thermal amplitude. Numerical simulations using Ansys Fluent were developed to evaluate the performance of PCM use over a wide range of temperature boundary conditions and operating modes. These numerical models were calibrated and validated using the results of experimental tests, achieving a correlation factor of 0.9674, thus accurately representing a real-world scenario. The decrement factor (f) was used to analyse the data. It was identified that the efficiency of the panel and size of the optimum region increased with the PCM fraction growth. The simulated behaviour was optimum when the input mean temperature is of 20 °C for a room temperature of between 18-20 °C. The results show the significant potential of the multi-layered panel and the thermal regulator effect of the PCM incorporated on indoor space temperature to reach good thermal comfort levels.

Image encryption is increasingly becoming an important area of research in information security and network communications, as digital images are widely used in various applications and are vulnerable to various types of attacks. In this research work, a color image cryptosystem that is based on a 3-layer permutation-substitution network (PSN) is proposed. For every layer, an encryption key and an S-box are generated and utilized. Those are based on a four-dimensional (4D) dynamical Chen system of a fractional-order, the Mersenne Twister, OpenSLL, Rule 30 Cellular Automata and Intel’s MKL. The sequential application of Shannon’s ideas of diffusion and confusion for 3 times guarantees a total distortion of any input plain image, resulting in a totally encrypted one. Apart from the excellent and comparable performance to counterpart algorithms from the literature, showcasing resistance to visual, statistical, entropy, differential, known plaintext and brute-force attacks, the proposed image cryptosystem provides an exceptionally superior performance in 2 aspects: a vast key space of 2^1658 and an average encryption rate of 3.34 Mbps. Furthermore, the proposed image cryptosystem is shown to successfully pass all the tests of the NIST SP 800 suite.

This work aims to investigate systematically the tecno-economic feasibility of ther-mos-catalytic cracking process for two solid waste materials, a lipid-base material (re-sidual fat/scum from retention box of the University Restaurant of UFPA) and a lig-nin-cellulosic material Açaí seed (Euterpe oleracea. Mart). The thermo-catalytic process-es were carried out in pilot scale (THERMTEK/LEQ/UFPA/IME/RJ), and their economic feasibility analyzed. The yields of biofuels produced by fractional distillation were al-so studied. The physicochemical characteristics of the raw materials, the organic liquid product (bio-oil) and the chemical composition of kerosene, light-diesel and heavy-diesel from the lipid-base material, as well as those of kerosene and light-diesel from the Açaí seed were also determined. The economic indicators for the evaluation of the most viable cracking (pyrolysis) and distillation process of bio-oils were: a) the sim-ple payback criterion, b) discounted payback, c) net present value (NPV), d) internal rate of return (IRR), and e) index of profitability (IP). The analysis of the indicators showed the economic viability of crude palm oil (Elaeis guineensis, Jacq) and unfeasibil-ity for the palm oil neutralization. The minimum fuel selling price (MFSP) obtained is this work for the biofuels was of 1.34 US$/L) and the breakeven point obtained was of 1.28 US$/L. The sensibility analysis demonstrated that the pyrolysis and distillation yields are the most important variables to affect the minimum fuel selling price (MFSP).

The molten salt reactor (MSR) specific 3D spatial dynamics code leveraging the neutronics and thermal-hydraulics (TH) coupling method, TMSR3D, has been extended for static and transient analysis of large advanced light water reactors (LWRs), particularly focusing on control rod ejection accidents. The code is built upon the neutron diffusion model leveraging the widely used "two-step" strategy in three-dimensional Cartesian coordinates. A polynomial nodal expansion method (NEM) is utilized to handle spatial variables, while the neutron kinetics solver employs the exponential transformation technique. The code also integrates a single-channel TH module and a steam table set at 15.5 Mpa. The accuracy of the code has been validated through three transient benchmarks, including the 3D-LRA benchmark for boiling water reactors (BWRs), the NEACRP 3D benchmark, and the MOX/UO2 core benchmark for pressurized water reactors (PWRs). These benchmarks cover both static and transient behaviors, and the results have been thoroughly analyzed. The close alignment of extended version of TMSR3D outcomes with reference data and other codes supports its reliability, making it a promising tool for future dynamic analyses of large-scale advanced PWRs.

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous and the most common form of head and neck cancer, posing significant challenges for disease management. Single-cell RNA sequencing (sc-RNAseq) has emerged as a valuable tool for addressing these challenges by enabling detailed characterization of the tumor microenvironment (TME) at the cellular level. This review assesses the utility of sc-RNAseq in HNSCC research, compiling current strategies employing single-cell technologies. For HNSCC etiology, sc-RNAseq allows for the construction of cellular atlases, characterization of different cell types, and investigation of key genes and processes involved in cancer initiation, development, and progression within the TME. In terms of HNSCC diagnosis and prognosis, the high resolution offered by sc-RNAseq enables the identification of cell type-specific signatures, enhancing prognostic models and disease stratifiers for more accurate patient outcome assessments. Regarding HNSCC treatment, sc-RNAseq provides insights into cellular responses to various treatments, including radiotherapy, chemotherapy, and immunotherapy, contributing to improved patient stratification and personalized treatment strategies. This review highlights the unique contributions of sc-RNAseq to HNSCC research, addressing its cellular and biological complexity, and emphasizes its potential for advancing research and clinical practice in other cancer types.

We fabricated high-quality MAPbBr3 single crystals (SC) by introducing moderate amount electron-rich poly(propylene glycol bis(2-aminopropyl ether) (PEA) additives with an inverse temperature crystallization (ITC) method. The intramolecular vibrations and defective states of prepared MAPbBr3 single crystals were systemically studied by the in situ variable-temperature Fourier Transform Infrared (FTIR) Spectroscopy, X-ray photoelectron spectroscopy (XPS), and the synchrotron-based X-ray absorption near edge structure (XANES), et al. We infer that the proper amount of PEA additives would prevent the formation of intermediate states and crystal boundaries, passivating the density of defective states. The X-ray detection properties of single-crystal MAPbBr3 crystals were investigated, using both high dose and low dose X-ray photons at 40keV in synchrotron beamlines. The photocurrent of optimized PEA-treated MAPbBr3 single crystals demonstrate better performance compared with the as-prepared single crystals. Meanwhile, the decay time of MAPbBr3 single crystal is decreased from 460 ns to 210 ns by Time-resolved photoluminescence (TRPL) decay measurement, owing to the defect passivation by 0.5wt% PEA additives. The PEA-treated single crystals possess much faster decay time than the commercialized Ce:YAG scintillator (>500ns). These results help elucidate the passivation of defective states and contribute paths to manufacture high-quality single crystal perovskites for next-generation optoelectronic devices.

The first single crystal structure of the homoleptic copper (II) ML2 complex (M=Cu (II), L=curcumin) was obtained and its structure was elucidated by X-ray diffraction showing a square planar geometry. The supramolecular arrangement is supported by C-H···O interactions and the solvent (MeOH) plays an important role in stabilizing the crystal packing. The cytotoxic activity of the complex against six cancer cell lines substantially surpasses that of curcumin itself, and it is particularly selective against leukemia (K562) and human glioblastoma (U251) cell lines with similar antioxidant activity to BHT. This constitutes the first crystal structure of pristine curcumin complexed with a metal ion.

Cancer is a multifactorial disease that continues to increase. Lignans are known to be important anticancer agents. However, due to the structural diversity of lignans, it is difficult to associate anticancer activity with a particular subclass. Therefore, the present study sought to evaluate the association of lignan subclasses with antitumor activity, considering the genetic profile of the variants of the selected targets. For this, predictive models were built against the targets tyrosine-protein kinase ABL (ABL), epider-mal growth factor receptor erbB1 (EGFR), histone deacetylase (HDAC), Serine/threonine-protein kinase mTOR (mTOR) and Poly [ADP-ribose] polymerase-1 (PARP1). Then, mapped single nucleotide polymorphisms and designed target mutations, and performed molecular docking with the lignans with the best predicted biological activity. The results showed more anticancer activity in the dibenzocyclooctadiene, furofuran and aryltetralin subclasses. The lignans with the best predictive values of biological activity showed varying binding energy results in the presence of certain genetic variants.

Atypical hemolytic uremic syndrome (aHUS) is a rare and life-threatening disease characterized by microangiopathic hemolytic anemia, thrombocytopenia, and acute kidney injury, necessitating differentiation from other thrombotic microangiopathy disorders. Definitive biomarkers for disease diagnosis and activity are currently lacking, and identifying molecular markers is essential. We conducted single-cell sequencing on peripheral blood mononuclear cells from 13 aHUS patients, 3 aHUS family members, and 4 healthy controls. Analysis included clustering, cell type annotation, pseudotime estimation, and cell-cell communication. Immune cell populations differ among aHUS, aHUS families, and healthy controls. Disease activity and treatment influence T, NK, B, and monocyte subpopulations, with increased intermediate monocyte levels distinguishing aHUS from controls and aHUS groups with varying disease activity. Subclustering revealed differential gene expression in patients compared to controls; higher expression of mitochondria-related genes suggests cell metabolism may influence clinical course. Pseudotime trajectory analysis demonstrated unique immune cell differentiation, and cell-cell interaction analysis identified distinct signaling pathways among patients, family members, and controls. This single-cell sequencing study is the first to confirm immune cell dysregulation in aHUS pathogenesis, offering valuable insights into molecular mechanisms and potential new diagnostic and disease activity markers.

A quantum Otto engine with a single ion harmonic oscillator as its working substance is studied for an adiabatic operation at high and low temperature limits. Using the universal optimization method, the heat engine is effectively optimized and found to yield better working conditions in some ranges of temperature ratios. Accordingly, the figure of merit, ψ, is found to be greater than unity in the range: 0&lt;β2β1≤0.12; showing that the heat engine performs better in the optimized condition than in the maximum power working condition. ψ is determined to be less than one in the range 0.12≤β2β1≤0.35 under the same temperature limit ; depicting that the maximum power working condition is preferred to the optimized working condition. On the other hand, in the low temperature limit, the figure of merit, ψ, is found to be greater than unity in the range 3.7&lt;ω1ω2≤18; revealing that optimized working condition is better than the maximum power working condition for the heat engine. In the same temperature limit, ψ is found to be less than one in the range 0≤ω1ω2≤3.7; showing that maximum power working condition is preferred to the optimized one. For the model of heat engine studied, in some ranges of temperature ratio, it is found to work better in the optimized condition, whereas in the other ranges it performs better under the maximum power working condition. So, it is possible to switch the engine between the two conditions depending on one’s need.

Glioblastoma (GBM) is the most common primary brain tumor in adults, with few available therapies and a 5-year survival rate of 7.2%. Hence, strategies for improving GBM prognosis are urgently needed. The translocator protein 18kDa (TSPO) plays crucial roles in essential mito-chondria-based physiological processes and is a validated biomarker of neuroinflammation, which is implicated in GBM progression. The TSPO gene has a germline single nucleotide pol-ymorphism, rs6971, which is the most common SNP in the Caucasian population. High TSPO gene expression is associated with reduced survival in GBM patients; however, the relation between the most frequent TSPO genetic variant and GBM pathogenesis is not known. The present study ret-rospectively analyzed the correlation of the TSPO polymorphic variant rs6971 with overall and progression-free survival in GBM patients using three independent cohorts. TSPO rs6971 poly-morphism was significantly associated with shorter overall survival and progression-free survival in male GBM patients but not in females in one large cohort of 441 patients. We observed similar trends in two other independent cohorts. These observations suggest that the TSPO rs6971 pol-ymorphism could be a significant predictor of poor prognosis in GBM, with a potential for use as a prognosis biomarker in GBM patients. These results reveal for the first time a biological sex-specific relation between rs6971 TSPO polymorphism and GBM.

“Clickase” single-chain nanoparticles (Ck-SCNPs) are folded, enzyme-mimetic unimolecular polymeric nano-objects containing copper (Cu) ions able to catalyze the azide-alkyne Huisgen cycloaddition reaction in water and/or selected organic solvents, often in the presence of a reductant. Herein, we investigate the effect of morphology on catalytic activity of Ck-SCNPs synthesized by means of two different routes. An amphiphilic random copolymer composed of oligo(ethylene glycol) methyl ether methyl methacrylate (OEGMA) and 2-acetoacetoxy ethyl methacrylate (AEMA) units was used as precursor of these Ck-SCNPs. Folding was promoted through metal complexation between Cu(II) ions and beta-ketoester-containing AEMA moieties. The first route resulted in Ck-SCNPs1 containing Cu ions homogeneously distributed within each nanoparticle, whereas the second one promoted intra-chain clustering of Cu ions inside Ck-SCNPs2. A model fluorogenic “click” reaction between 9-(azidomethyl)anthracene and phenylacetylene, which was catalyzed either by Ck-SCNPs1 or Ck-SCNPs2, was used to unravel the effect of morphology on catalytic activity. This work paves the way to improve the catalytic activity of metallo-folded SCNPs through control of the intra-chain distribution of catalytic sites.

Single cell proteins are the dead dried cells of microorganisms or purified protein isolated from microorganism’s cell culture, used as a food supplement to humans’ food and animals feed. World suffer from malnutrition particularly developing countries, due to rapid increase in population, increased the demand for protein and nutrients requirement. Bacteria is potential microorganism for SCP production due to high protein content, fast generation time, bio-active secondary metabolites production and can grow on various substrates. Actinobacteria species and strain have capability to produce biological active compounds, produced about two-thirds of antibiotics available in the market, actively used as antibiotics, antiprotozoal, antifungal, antiviral, anticancer, anticholesterol, antihelminth and immunosuppressant. Actinomycetes can be used as probiotic as well as single cell protein that will deal with antibiotic as well as protein source.

In this work we demonstrate the proof-of-concept of real-time discrimination between patches of serine or isoleucine monomers in the primary structure of custom-engineered, macro-dipole-like peptides, at uni-molecular level. We employed single-molecule recordings to examine the ionic current through the α-hemolysin (α-HL) nanopore, when hydrophilic serine or hydrophobic isoleucine residues, flanked by segments of oppositely charged arginine and glutamic amino acids functioning as a voltage-dependent ‘molecular brake’ on the peptide, were driven at controllable rates across the nanopore. The observed differences in the ionic currents blockades through the nanopore, visible at time resolutions corresponding to peptide threading through the α-HL’s constriction region, was explained by a simple model of the volumes of electrolyte excluded by either amino acid species, as groups of three serine or isoleucine monomers transiently occupy the α-HL. To provide insights into the conditions ensuring optimal throughput of peptide readout through the nanopore, we probed the sidedness-dependence of peptide association to and dissociation from the electrically and geometrically asymmetric α-HL.

The present study investigates the failure mechanisms of industrial fiber materials, using a custom designed fiber cutting performance test bench. The fracture morphologies of single PA6 fibers are examined by scanning electron microscopy. The analysis reveals that fiber cutting can be distinguished according to four distinct stages of fiber failure represented by shearing, cutting, brittle fracture, and tensile failure, which are the result of different mechanisms active during the processes of crack initiation, extension and fracture. The results of fractographic analysis are further verified by an analysis of the blade assembly speed with respect to time over the entire fracture failure process based on high-speed camera data. The results of fractographic analysis and blade assembly speed are fully consistent.

Single umbilical artery (SUA) is considered an ultrasound marker of anomalies. Although it may be present in about 5% of normal gestations, it has been observed to be associated with an increased risk of intrauterine growth retardation, cardiac, genitourinary and gastrointestinal malformations, as well as with the appearance of chromosomal anomalies such as trisomy 21 and 18. Objectives: This study aims to check whether the presence of isolated SUA (ISUA) is related to adverse perinatal outcomes. Methods: This is a descriptive, observational and retrospective study with a total of 1266 gestations were studied (1189 normal gestations and deliveries collected from the registry of the Hospital Univeritario de Salamanca, during the period from January 1st to August 31st, 2023 and 77 cases of ISUA). Results: The presence of ISUA was associated with a lower gestational age (38 vs 39 weeks) and a lower birth weight (3013 vs 3181 g) though not increasing the prematurity rate. No significant differences were found in the increase in malformations, genetic disorders, Apgar test, pH at birth or admissions in the neonatal ICU. Conclusions: The presence of ISUA during gestation is associated with lower gestational age and lower birth weight though this did not result in a higher rate of prematurity or an increase in the number of admissions associated with low birth weight. No significant association was found between the presence of ISUA and genetic disorders or fetal malformations. Neither were worse Apgar test scores or lower pH values found in these newborns.

Friction stir welding (FSW) is a solid state welding process for joining metallic alloys and dissimilar metals. It has emerged as an alternative technology for welding high strength alloys that are difficult to join with conventional techniques. FSW is used to produce products with better mechanical properties. Now a days aluminum alloys have been widely used in several industrial applications such as aerospace, marine, automobile and commercial applications due to their light weight structure, better mechanical properties and high corrosion resistance.In this work, three welding parameters such as spindle speed, welding speed and plunge depth were considered for friction stir welding. FSW was carried out between dissimilar aluminum alloy plates (AA6061 and AA 8011) to produce butt joint.A Box-Behnken design with three factors and three levels was chosen to minimize the number of experimental conditions .The tensile strength and hardness of the welded regions were evaluated. The optimum level settings and the major parameters that influence the joint strength were obtained by Box-Behnken design.

In this work we study the intersection properties of a finite disk system in the euclidean space. We accomplish this by utilizing subsets of spheres with varying dimensions and analyze specific points within them, referred to as poles. Additionally, we introduce two applications: estimating the common scale factor for the radii that makes the re-scaled disks intersects in a single point, this is the \v{C}ech scale, and constructing the minimal Axis-Aligned Bounding Box (AABB) that encloses the intersection of all disks in the system.

Due to the non-degradability of petroleum-based packaging materials, serious environmental pollution and the depletion of non-renewable resources have become pressing issues. In order to actively promote green production and address these concerns, there is an urgent need for new packaging materials to replace traditional plastic products. Starch-based packaging materials, composed of starch, fiber, and plasticizers, offer a degradable and environmentally friendly alternative. Starch alone cannot undergo thermoplastic processing due to its inherent structural characteristics. Therefore, researchers have explored modifications by incorporating plasticizers to create processable thermoplastic starch (TPS). However, there are challenges related to the high crystallinity and poor compatibility between TPS and fibers, resulting in decreased mechanical properties. To address these challenges, a novel approach combining plasticizer optimization and response surface method (RSM) optimization has been proposed to enhance the mechanical properties of starch-based packaging materials. This method leverages the advantages of composite plasticizers and process parameters. The findings demonstrate that the composite plasticizer effectively disrupt the hydrogen bonding and granule morphology of starch, leading to a significant reduction in crystallinity. Based on these findings, the optimal process parameters are determined using the RSM, resulting in a forming temperature of 198 °C, forming time of 5.4 minutes, and AC content of 0.84 grams. Compared with the non-optimized values, the tensile strength increases by 12.2% and the rebound rate increases by 8.1%.

In this work, we have developed a non-ordinary state-based peridynamic model for multiple crack initiation and propagation due to compression-compression fatigue load. In each loading cycle, the fatigue loading is redistributed among the peridynamic solid body, leading to the progressive fatigue damage initiation and propagation in an autonomous fashion. The proposed fatigue model parameters are firstly validated by 3D numerical benchmark tests, and then it is applied to simulate widespread fatigue damage evolution of the aircraft wing corner box. The modified constitutive damage model has been implemented into the peridynamics framework at finite strain. Furthermore, the criterion algorithm from multiple initiation to propagation is discussed. It is shown that the numerical results obtained from peridynamics simulations are in general agreement with those from the experiment data. The comparison of experimental and numerical results indicates that the proposed non-ordinary state-based peridynamics fatigue model has the ability to capture the multiple crack initiation and propagation and other features of the aluminium alloy material.

It is well known that fiber sizing is one of the most important component in the manufacturing of composites, and it does affect the mechanical properties including strength and stiffness. In this work, the influence of fiber sizing levels on the mechanical properties of carbon fibers (CF) is reported at room temperature by using single fiber tensile testing (Favimat+), single fiber pullout testing (SFPO), and interfacial elemental analysis using X-ray photoelectron spectroscopy (XPS). Standard modulus of CF (7±0.2 μm in diameter) were sized using two Michelman commercially available sizing formulations. The average solid content for each sizing formulation is 26.3 ± 0.2% and 34.1 ± 0.2%, respectively. HEXION RIMR 135 with curing agent RIMH 137 was used as a model thermoset epoxy matrix during the SFPO measurements. A predictive engineering fiber sizing methodology is also developed. Sizing amounts of 0.5, 1, and 2 wt. % on the surface of the fiber is achieved for both sizing formulations. For each fiber sizing level, 50 single fiber tensile testing experiments and 20 single fiber pull-out tests were conducted. The ultimate tensile strength (σult) of the carbon fibers and the interfacial shear strength (τ_app) of the single fiber composite were analyzed. it is also investigated the effect of the sizing levels on the interfacial shear stress and the O/C (Oxygen/Carbon) surface composition ratio. As a result, generalized fiber sizing and characterization methods were established. The developed methods can be used to characterize the strength and interfacial shear strength of any man-made fibers with different sizing formulations and solid contents, irrespective of the matrix i.e. thermoset or thermoplastic.

Numerous dynamic and complicated processes characterize development from the oocyte to the embryo. However, given the importance of functional transcriptome profiles, long non-coding RNAs, single-nucleotide polymorphisms, and alternative splicing during embryonic development, the effect that these features have on the blastomeres of 2-, 4-, 8-, 16-cell, and morula stages of development have not been studied. Here, we conducted a scRNA-seq survey of cells from sheep from the oocyte to the blastocyst developmental stages. We then carried out experiments to identify and functionally analyze the transcriptome profiles, long non-coding RNAs, single-nucleotide polymorphisms (SNPs), and alternative splicing (AS). We founded that between the oocyte and zygote groups significantly down-regulated genes and the second-largest change in gene expression occurred between the 8- and 16-cell stages. We used various methods to construct a profile to characterize cellular and molecular features and systematically analyze the related GO and KEGG profile of cells of all stages from the oocyte to the blastocyst. This large-scale, single-cell atlas provides key cellular information and will likely assist clinical studies in improving preimplantation genetic diagnosis.

In recent years, the advent of Single Electron Transistor (SET) technology has opened new avenues for low power and high density circuit design. This paper presents an optimized design of an Arithmetic Logic Unit utilizing Single Electron Transistor MOSFET (SET-MOSFET) technology. The proposed design leverages the unique properties of SETs such as Coulomb blockade and quantum tunneling to achieve significant reductions in power consumption and increased speed. Through comprehensive simulations and analysis the performance metrics of the SET-MOSFET based ALU architecture includes optimized arithmetic and logical units are compared with conventional MOSFET based designs demonstrating the superiority of the proposed approach in terms of energy efficiency and operational speed. Comprehensive simulations demonstrate that the SET-MOSFET based ALU achieves a 99.97 % to 99.99 % reduction in power consumption, a 5 to 50 times increase in speed compared to conventional MOSFET based designs.