Search Results (108)

Water distribution systems (WDSs) are designed to deliver potable water across urban areas. Unpredicted changes in water demands and hydraulics can increase the residence time in pipes, leading to the growth of microbes and decreased water quality at some locations in a network. During the COVID-19 pandemic, large-scale reductions in demands, especially in industrial and commercial areas as individuals worked from home, led to hot-spots of increased water age. In response to reduced water quality, consumers may avoid using tap water for end uses including drinking, cooking, and cleaning. The lack of access to clean water can create high costs for some households due to the cost of buying bottled water. Inequitable access to safe, affordable water is explored in this research in the context of the COVID-19 pandemic through a coupled framework. This research extends an existing agent-based modeling (ABM) framework that simulated COVID-19 transmission, social distancing decision-making, reductions in water demands, and flows in a water distribution system. The ABM is extended in this work to simulate households that perceive water quality problems with tap water and choose to buy bottled water for cooking, cleaning, and hygienic purposes. Agents choose tap water avoidance behaviors based on water age, a surrogate for water quality. Equity is evaluated using the cost of water, both tap and bottled, as a percentage of income. An optimization approach is coupled with the ABM framework and applied to design operational strategies that improve equitable access to safe affordable water. A graph theory approach identifies valves that should be opened and closed to improve water quality at nodes and maximize equity. The results demonstrate an increase in water age due to social distancing behaviors, and water of high age is observed to be disproportionately located near industrial areas. Adjusted income demonstrates inequities in access to safe and affordable water. Operational strategies are developed to improve equity for a community through valve operations that improve the equitable delivery of safe water. This research develops an approach to assess equity of the quality of delivered water and can be used to facilitate WDS management that provides equitable access to safe water. Full article

Brain–computer interfaces (BCIs) are pivotal in translating neural activities into control commands for external assistive devices. Non-invasive techniques like electroencephalography (EEG) offer a balance of sensitivity and spatial-temporal resolution for capturing brain signals associated with motor activities. This work introduces MOVING, a Multi-Modal dataset of EEG signals and Virtual Glove Hand Tracking. This dataset comprises neural EEG signals and kinematic data associated with three hand movements—open/close, finger tapping, and wrist rotation—along with a rest period. The dataset, obtained from 11 subjects using a 32-channel dry wireless EEG system, also includes synchronized kinematic data captured by a Virtual Glove (VG) system equipped with two orthogonal Leap Motion Controllers. The use of these two devices allows for fast assembly (∼1 min), although introducing more noise than the gold standard devices for data acquisition. The study investigates which frequency bands in EEG signals are the most informative for motor task classification and the impact of baseline reduction on gesture recognition. Deep learning techniques, particularly EEGnetV4, are applied to analyze and classify movements based on the EEG data. This dataset aims to facilitate advances in BCI research and in the development of assistive devices for people with impaired hand mobility. This study contributes to the repository of EEG datasets, which is continuously increasing with data from other subjects, which is hoped to serve as benchmarks for new BCI approaches and applications. Full article

From an agricultural perspective, carrots are a significant tap root vegetable crop in the Apiaceae family because of their nutritional value, health advantages, and economic importance. The edible part of a carrot, known as the storage root, contains various beneficial compounds, such as carotenoids, anthocyanins, dietary fiber, vitamins, and other nutrients. It has a crucial role in human nutrition as a significant vegetable and raw material in the nutraceutical, food, and pharmaceutical industries. The cultivation of carrot fields is susceptible to a wide range of biotic and abiotic hazards, which can significantly damage the plants’ health and decrease yield and quality. Scientific research mostly focuses on important biotic stressors, including pests, such as nematodes and carrot flies, as well as diseases, such as cavity spots, crown or cottony rot, black rot, and leaf blight, caused by bacteria, fungi, and oomycetes. The emerging challenges in the field include gaining a comprehensive understanding of the interaction between hosts and pathogens in the carrot–pathogen system, identifying the elements that contribute to disease development, expanding knowledge of systemic treatments, exploring host resistance mechanisms, developing integrated control programs, and enhancing resistance through breeding approaches. In fact, the primary carrot-growing regions in tropical and subtropical climates are experiencing abiotic pressures, such as drought, salinity, and heat stress, which limit carrot production. This review provides an extensive, up-to-date overview of the literature on biotic and abiotic factors for enhanced and sustainable carrot production, considering the use of different technologies for the shelf-life extension of carrots. Therefore, it addresses the current issues in the carrot production chain, opening new perspectives for the exploration of carrots both as a food commodity and as a source of natural compounds. Full article

Triboelectric nanogenerators (TENGs) are devices that efficiently transform mechanical energy into electrical energy by utilizing the triboelectric effect and electrostatic induction. Embroidery triboelectric nanogenerators (ETENGs) offer a distinct prospect to incorporate energy harvesting capabilities into textile-based products. This research work introduces an embroidered triboelectric nanogenerator that is made using polyester and nylon 66 yarn. The ETENG is developed by using different embroidery parameters and its characteristics are obtained using a specialized tapping and friction device. Nine ETENGs were made, each with different stitch lengths and line spacings for the polyester yarn. Friction and tapping tests were performed to assess the electrical outputs, which included measurements of short circuit current, open circuit voltage, and capacitor charging. One sample wearable embroidered energy harvester collected 307.5 μJ (24.8 V) of energy under a 1.5 Hz sliding motion over 300 s and 72 μJ (12 V) of energy through human walking over 120 s. Another ETENG sample generated 4.5 μJ (3 V) into a 1 μF capacitor using a tapping device with a 2 Hz frequency and a 50 mm separation distance over a duration of 520 s. Measurement of the current was also performed at different pressures to check the effect of pressure and validate the different options of the triboelectric/electrostatic characterization device. In summary, this research explains the influence of embroidery parameters on the performance of ETENG (Embroidery Triboelectric Nanogenerator) and provides valuable information for energy harvesting applications. Full article

Salivary pH is one of the crucial biomarkers used for non-invasive diagnosis of intraoral diseases, as well as general health conditions. However, standard pH sensors are usually too bulky, expensive, and impractical for routine use outside laboratory settings. Herein, a miniature hydrogel sensor, which enables quick and simple colorimetric detection of pH level, is shown. The sensor structure was manufactured from non-toxic hydrogel ink and patterned in the form of a matrix with 5 mm × 5 mm × 1 mm individual sensing pads using a 3D printing technique (bioplotting). The authors’ ink composition, which contains sodium alginate, polyvinylpyrrolidone, and bromothymol blue indicator, enables repeatable and stable color response to different pH levels. The developed analysis software with an easy-to-use graphical user interface extracts the R(ed), G(reen), and B(lue) components of the color image of the hydrogel pads, and evaluates the pH value in a second. A calibration curve used for the analysis was obtained in a pH range of 3.5 to 9.0 using a laboratory pH meter as a reference. Validation of the sensor was performed on samples of artificial saliva for medical use and its mixtures with beverages of different pH values (lemon juice, coffee, black and green tea, bottled and tap water), and correct responses to acidic and alkaline solutions were observed. The matrix of square sensing pads used in this study provided multiple parallel responses for parametric tests, but the applied 3D printing method and ink composition enable easy adjustment of the shape of the sensing layer to other desired patterns and sizes. Additional mechanical tests of the hydrogel layers confirmed the relatively high quality and durability of the sensor structure. The solution presented here, comprising 3D printed hydrogel sensor pads, simple colorimetric detection, and graphical software for signal processing, opens the way to development of miniature and biocompatible diagnostic devices in the form of flexible, wearable, or intraoral sensors for prospective application in personalized medicine and point-of-care diagnosis. Full article

Bohai X oilfield has reached the extra-high water cut stage of more than 95%, dominated by the bottom water reservoir. The oilfield mainly adopts horizontal-well exploitation, with the characteristics of high difficulty and low success rate for well water plugging. To solve the above problem, the segmented production technology of horizontal wells was developed to guide oilfield applications and tap their potential. In the segmented design stage, the horizontal section is objectively segmented by drilling condition analysis, optimally based on drilling through interlayers or permeability discrepancy formation, simultaneously combined with the numerical simulation method. When implementing measures, annulus chemical packer materials are squeezed between segments to effectively inhibit the fluid flow between the open hole and the sand-packing screen pipe. Moreover, the packers are used to seal between segments to effectively restrain the flow between the screen and the central tube, achieving the establishment of compartments. In the production process, the valve switch on the central tube can be independently controlled by a remotely adjustable method to achieve optimal production. This segmented production technology was successfully tested for the first time in Bohai oilfield. Up to now, a total of six compartment measures have been implemented, remarkably decreasing water cut and increasing oil production for horizontal wells in the bottom water reservoir. This method does not require water testing, and the optimal production section can be chosen through segmented independent production, greatly improving the success rate of water-plugging measures for horizontal wells. This technology opens up a new mode for the efficient development of horizontal wells in bottom water reservoirs and is planned to be widely promoted and applied in similar oilfields. Full article

In this study, we report a multiplexed platform for the simultaneous determination of five marine toxins. The proposed biosensor is based on a disposable electrical printed (DEP) microarray composed of eight individually addressable carbon electrodes. The electrodeposition of gold nanoparticles on the carbon surface offers high conductivity and enlarges the electroactive area. The immobilization of thiolated aptamers on the AuNP-decorated carbon electrodes provides a stable, well-orientated and organized binary self-assembled monolayer for sensitive and accurate detection. A simple electrochemical multiplexed aptasensor based on AuNPs was designed to synchronously detect multiple cyanotoxins, namely, microcystin-LR (MC-LR), Cylindrospermopsin (CYL), anatoxin-α, saxitoxin and okadaic acid (OA). The choice of the five toxins was based on their widespread presence and toxicity to aquatic ecosystems and humans. Taking advantage of the conformational change of the aptamers upon target binding, cyanotoxin detection was achieved by monitoring the resulting electron transfer increase by square-wave voltammetry. Under the optimal conditions, the linear range of the proposed aptasensor was estimated to be from 0.018 nM to 200 nM for all the toxins, except for MC-LR where detection was possible within the range of 0.073 to 150 nM. Excellent sensitivity was achieved with the limits of detection of 0.0033, 0.0045, 0.0034, 0.0053 and 0.0048 nM for MC-LR, CYL, anatoxin-α, saxitoxin and OA, respectively. Selectivity studies were performed to show the absence of cross-reactivity between the five analytes. Finally, the application of the multiplexed aptasensor to tap water samples revealed very good agreement with the calibration curves obtained in buffer. This simple and accurate multiplexed platform could open the window for the simultaneous detection of multiple pollutants in different matrices. Full article

Brain–computer interface (BCI) systems include signal acquisition, preprocessing, feature extraction, classification, and an application phase. In fNIRS-BCI systems, deep learning (DL) algorithms play a crucial role in enhancing accuracy. Unlike traditional machine learning (ML) classifiers, DL algorithms eliminate the need for manual feature extraction. DL neural networks automatically extract hidden patterns/features within a dataset to classify the data. In this study, a hand-gripping (closing and opening) two-class motor activity dataset from twenty healthy participants is acquired, and an integrated contextual gate network (ICGN) algorithm (proposed) is applied to that dataset to enhance the classification accuracy. The proposed algorithm extracts the features from the filtered data and generates the patterns based on the information from the previous cells within the network. Accordingly, classification is performed based on the similar generated patterns within the dataset. The accuracy of the proposed algorithm is compared with the long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM). The proposed ICGN algorithm yielded a classification accuracy of 91.23 ± 1.60%, which is significantly (p < 0.025) higher than the 84.89 ± 3.91 and 88.82 ± 1.96 achieved by LSTM and Bi-LSTM, respectively. An open access, three-class (right- and left-hand finger tapping and dominant foot tapping) dataset of 30 subjects is used to validate the proposed algorithm. The results show that ICGN can be efficiently used for the classification of two- and three-class problems in fNIRS-based BCI applications. Full article

During the past few decades, abundant evidence for physics beyond the two standard models of particle physics and cosmology was found. Yet, we are tapping in the dark regarding our understanding of the dark sector. For more than a century, open problems related to the nature of the vacuum remained unresolved. As well as the traditional high-energy frontier and cosmology, technological advancement provides complementary access to new physics via high-precision experiments. Among the latter, the Casimir And Non-Newtonian force EXperiment (Cannex) has successfully completed its proof-of-principle phase and is going to commence operation soon. Benefiting from its plane parallel plate geometry, both interfacial and gravity-like forces are maximized, leading to increased sensitivity. A wide range of dark sector forces, Casimir forces in and out of thermal equilibrium, and gravity can be tested. This paper describes the final experimental design, its sensitivity, and expected results. Full article

Cryptographic primitives nowadays are not only implemented in high-performance systems but also in small-scale systems, which are increasingly powered by open-source processors, such as RISC-V. In this work, we leverage RISC-V’s modular base instruction set and architecture to propose a generic instruction set extension (ISE) for symmetric cryptography. We adapt the work from Engels et al. in ARITH’13, the non-linear/linear instruction set extension (NLU), which presents a generic hardware/software co-design solution for efficient symmetric crypto implementations through a hardware unit extending the 8-bit AVR instruction set. These new instructions realize non-linear and linear layers, which are widely used to implement the block ciphers in symmetric cryptography. Our proposal modifies and extends the NLU instructions to a 32-bit RISC-V architecture; hence, we call the proposed ISE ‘NLU-V’. The proposed architecture is integrated into the open-source RISC-V implementation ‘Icicle’ and synthesized on a Xilinx Kintex-7 XC7K160T FPGA. The area overhead for the proposed NLU-V ISE is 1088 slice registers and 4520 LUTs. As case studies, the PRESENT and AES block ciphers are implemented using the new ISE on RISC-V in assembly. Our evaluation metric to showcase the performance gain, Z ‘time-area-product (TAP)’ (the execution time in clock cycles times code memory consumption), reflects the impact of the proposed family of instructions on the performance of the cipher implementations. The simulations show that the NLU-V achieves 89% gain for PRESENT and 68% gain for AES. Further, the NLU-V requires 44% less lines of code for the PRESENT and 23% less for the AES implementation. Full article

This work investigates micro-electro discharge machining (EDM) performance involving deionized and tap water. The chosen machining regime was semi-finishing, where open voltage (from 100 to 130 V) and current values (5–10 A) were applied using a 0.5 µs pulse-on time and a frequency of 150 kHz, i.e., a duty cycle of 25%. First, numerical analyses were performed via COMSOL Multiphysics and used to estimate the plasma channel distribution and melted material, varying the current, sparking gap, electrical conductivity, and permittivity of the two fluids. Then, experimentally, the micro-EDM of holes and channels in hardened thin steel plates were replicated three times for each considered fluid. The material removal rate (MRR), tool wear ratio (TWR), radius overcut, and surface roughness were plotted as a function of open voltage and electrical conductivity. The study proves that as voltage and current increase, the MRR and TWR decrease with electrical conductivity. Nonetheless, for higher electrical conductivity (tap water), the process did not proceed for lower open voltages and currents, and the radius overcut was reduced, contrary to what is commonly acknowledged. Finally, the crater morphology and size were evaluated using a confocal microscope and compared to simulated outcomes. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder whose prevalence has steadily been rising over the years. Specialist neurologists across the world assess and diagnose patients with PD, although the diagnostic process is time-consuming and various symptoms take years to appear, which means that the diagnosis is prone to human error. The partial automatization of PD assessment and diagnosis through computational processes has therefore been considered for some time. One well-known tool for PD assessment is finger tapping (FT), which can now be assessed through computer vision (CV). Artificial intelligence and related advances over recent decades, more specifically in the area of CV, have made it possible to develop computer systems that can help specialists assess and diagnose PD. The aim of this study is to review some advances related to CV techniques and FT so as to offer insight into future research lines that technological advances are now opening up. Full article

This paper aimed to investigate the possibility of using alkaline-based binders made from the industrial waste produced by ceramic tiles in the field of conservation and the restoration of monuments and archaeological heritage. Geopolymer mortars, which are environmentally sustainable products obtained by chemical consolidation at room temperature, are studied for their versatility in applications as reintegration or bedding mortars and pre-cast elements, namely bricks, tiles or missing parts for archaeological pottery, as an alternative to traditional not sustainable products. Starting from a well-established formulation, the function of the product, meaning its technical characteristics and its workability, was optimized by changing the aggregates used, by adding a Ca-rich compound or by changing the liquid/solid ratio with the use of tap water. The possibility of tailoring the finishing of the obtained products was also evaluated. X-ray diffraction analysis showed the influence of adding the additive with the presence of newly formed phases, which positively affect the product’s workability. On the contrary, no important variations were observed with the increase in the water content of the same formulation, opening up the possibility of managing it according to the required fluidity of the final product. Good results were observed, jumping above the laboratory scale and overcoming criticalities linked to the variabilities on site and the higher volume of materials used for industrial processes. The present research also demonstrates that ceramic-based geopolymers are suitable for application in a large variety of cultural heritage projects and with different purposes. Therefore, the paper encourages the use of alkali-activated mortars for green restoration, specifically given the wide range of ceramic materials. Full article

The study’s objective was to evaluate the feasibility and dispersion of an open approach to the transversus abdominis plane (TAP) block in eight adult equine cadavers. A ventral midline incision was made, starting 2 cm cranial to the umbilicus and extending 25 cm cranially. In total, 0.5 mL/kg of new methylene blue (NMB) was injected per horse, divided into six injections. Using an 18 g, 8 cm Tuohy needle, three injections were made per side. The needle was guided blindly into the TAP using palpation. A 60 mL syringe was attached directly to the needle, depositing ~0.08 mL/kg at each site. The time to complete the injections was recorded for each cadaver. Following injection, the ventral body wall was dissected to determine if the dye was present within the TAP space as well as to measure the extent of the dispersion of the dye, the cranial to caudal extent, and the width of the dye’s spread. Complete deposition of NMB into the TAP (six of six sites) was achieved in 5/8 horses. The median time needed to perform all the injections was 263 s. Increased adiposity (retroperitoneal fat) was associated with unsuccessful injections. This approach to the TAP was easily and quickly performed, though less successful in horses with increased retroperitoneal fat and increased BCS. Full article

This research aimed to analyze and understand the perceived landscape preferences of lake parks (LPs) and how the public perceives and prefers these elements within the context of lake parks. The objective was to provide insights beneficial for landscape design, urban planning, and the creation of more appealing and sustainable lake parks. To achieve this, two primary methods were employed in this study: the Automated Machine Learning (Auto ML) model and the DeepLab v3+ model. To gather data for the research, 46,444 images were collected from 20 different lake parks from 2019 to 2022. Social media platforms such as Instagram, Flickr, and specific lake park community groups were tapped to source photographs from both professional photographers and the general public. According to the experimental findings, the perceived frequency of natural landscapes was 69.27%, which was higher than that of humanistic landscapes by 30.73%. The perceived intensity was also maintained between 0.09 and 0.25. The perceived frequency of water body landscapes was much greater on a macro-scale, at 73.02%, and the public had various plant preferences throughout the year. Aquatic plant landscapes with low-to-medium green visibility were preferred by the public, according to the landscape share characterization, while amusement rides with medium-to-high openness were preferred. The sky visibility of amusement rides was between 0 and 0.1 and between 0.3 and 0.5, indicating that the public preferred amusement rides with medium-to-high openness. In lake parks, the populace chose settings with less obvious architectural features. When combined, the two models used in this study are useful for identifying and analyzing the intended traits and preferences of lake parks among the general public. They also have theoretical and practical application value for directing the development of lake parks and urban landscapes. Full article