Search Results (1,706)

In this paper, we investigate and characterize a family of optimization problems introduced by interval-valued functionals that are determined by curvilinear integrals. To this end, we first state the path independence and (strictly) LU convexity properties of the considered functionals. Thereafter, we formulate the corresponding controlled variational inequalities. The main results of this paper provide some connections for the above-mentioned variational models. Since the objective functionals have a physical importance, an illustrative application is considered and studied by using the theoretical elements obtained in this study. Full article

Purpose: To investigate the impact of physiologically based pharmacokinetic (PBPK) parameters on physical, biological, and statistical measures in lutetium-177-labeled radiopharmaceutical therapies (RPTs) targeting the prostate-specific membrane antigen (PSMA). Methods: Using a clinically validated PBPK model, realistic time–activity curves (TACs) for tumors, salivary glands, and kidneys were generated based on various model parameters. These TACs were used to calculate the area-under-the-TAC (AUC), dose, biologically effective dose (BED), and figure-of-merit BED (fBED). The effects of these parameters on radiobiological, pharmacokinetic, time, and statistical features were assessed. Results: Manipulating PBPK parameters significantly influenced AUC, dose, BED, and fBED outcomes across four different BED models. Higher association rates increased AUC, dose, and BED values for tumors, with minimal impact on non-target organs. Increased internalization rates reduced AUC and dose for tumors and kidneys. Higher serum protein-binding rates decreased AUC and dose for all tissues. Elevated tumor receptor density and ligand amounts enhanced uptake and effectiveness in tumors. Larger tumor volumes required dosimetry adjustments to maintain efficacy. Setting the tumor release rate to zero intensified the impact of association and internalization rates, enhancing tumor targeting while minimizing the effects on salivary glands and kidneys. Conclusions: Optimizing PBPK parameters can enhance the efficacy of lutetium-177-labeled RPTs targeting PSMA, providing insights for personalized and effective treatment regimens to minimize toxicity and improve therapeutic outcomes. Full article

Prostate-specific membrane antigen (PSMA), a transmembrane glycoprotein, was shown to be expressed 100–1000 fold higher in prostate adenocarcinoma as compared to normal prostate epithelium. Given the enzymatic function of PSMA with the presence of an internalization triggering motif, various Glu-urea-Lys-based inhibitors have been developed and, amongst others, radiolabeled with positron emitters for targeted positron emission tomography imaging such as ⁶⁸Ga-PSMA-HBED-CC Glu-urea-Lys(Ahx) as well as with beta and alpha-emitting radioisotopes for targeted therapy, e.g., ¹⁷⁷Lu-PSMA-617. In this paper, we review and discuss the potential implications for targeted imaging and therapy of altered PSMA-glycosylation, of PSMA-driven activation of the P13K/Akt/mTOR, of the evolution over time and the relationship with androgen signaling and changes in DNA methylation of PSMA, and of androgen deprivation therapy (ADT) in prostate carcinoma. Full article

The problem of soil salinization has seriously hindered agricultural development. Cotton is a pioneering salinity-tolerant crop, so harvesting its key salinity-tolerant genes is important for improving crop salt tolerance. In this study, we analyzed changes in the transcriptome expression profiles of the salt-tolerant cultivar Lu Mian 28 (LM) and the salt-sensitive cultivar Zhong Mian Suo 12 (ZMS) after applying salt stress, and we constructed weighted gene co-expression networks (WGCNA). The results indicated that photosynthesis, amino acid biosynthesis, membrane lipid remodeling, autophagy, and ROS scavenging are key pathways in the salt stress response. Plant–pathogen interactions, plant hormone signal transduction, the mitogen-activated protein kinase (MAPK) signaling pathway, and carotenoid biosynthesis are the regulatory networks associated with these metabolic pathways that confer cotton salt tolerance. The gene-weighted co-expression network was used to screen four modules closely related to traits, identifying 114 transcription factors, including WRKYs, ERFs, NACs, bHLHs, bZIPs, and MYBs, and 11 hub genes. This study provides a reference for acquiring salt-tolerant cotton and abundant genetic resources for molecular breeding. Full article

Wheat spike count is one of the critical indicators for assessing the growth and yield of wheat. However, illumination variations, mutual occlusion, and background interference have greatly affected wheat spike detection. A lightweight detection method was proposed based on the YOLOv5s. Initially, the original YOLOv5s was improved by combing the additional small-scale detection layer and integrating the ECA (Efficient Channel Attention) attention mechanism into all C3 modules (YOLOv5s + 4 + ECAC3). After comparing GhostNet, ShuffleNetV2, and MobileNetV3, the GhostNet architecture was finally selected as the optimal lightweight model framework based on its superior performance in various evaluations. Subsequently, the incorporation of five different activation functions into the network led to the identification of the RReLU (Randomized Leaky ReLU) activation function as the most effective in augmenting the network’s performance. Ultimately, the network’s loss function of CIoU (Complete Intersection over Union) was optimized using the EIoU (Efficient Intersection over Union) loss function. Despite a minor reduction of 2.17% in accuracy for the refined YOLOv5s + 4 + ECAC3 + G + RR + E network when compared to the YOLOv5s + 4 + ECAC3, there was a marginal improvement of 0.77% over the original YOLOv5s. Furthermore, the parameter count was diminished by 32% and 28.2% relative to the YOLOv5s + 4 + ECAC3 and YOLOv5s, respectively. The model size was reduced by 28.0% and 20%, and the Giga Floating-point Operations Per Second (GFLOPs) were lowered by 33.2% and 9.5%, respectively, signifying a substantial improvement in the network’s efficiency without significantly compromising accuracy. This study offers a methodological reference for the rapid and accurate detection of agricultural objects through the enhancement of a deep learning network. Full article

The main ocean–continent transformation stage of the Qinling and Qilian conjunction zone happened in the Early Paleozoic with the occurrence of a lot of subduction–collision–related magmatic rocks. However, there is still considerable controversy over the duration of the subduction–collision orogeny process of the Proto-Tethys Ocean, here termed as the Wushan–Shangdan Ocean. We provide geochronological, geochemical, and Lu-Hf isotopic data for typical Early Devonian igneous rocks there, named Tailu pluton. The Tailu pluton at 410 Ma comprised K-rich, calc-alkaline, metaluminous A-type granite with low Y/Nb ratios (0.85 to 1.35) and A/CNK values (0.90 to 1.01); with high SiO₂ contents (65.44 to 74.46 wt%), Mg^# values (39.2 to 50.7), and zircon saturation temperatures (745 to 846 °C); and with negative ε_Hf (t) values (−8.0 to −1.9); therefore, they resulted from the partial melting of the ancient felsic lower crust accompanied by the incorporation of mantle-derived material during the intraplate magmatism process. Research on Tailu pluton has provided more sufficient evidence for the evolution process of the Qinling–Qilian conjunction zone in the Early Paleozoic, associated with evolution of the Wushan–Shangdan Ocean, the northern part of the Proto-Tethys Ocean. Full article

This research project aimed to address the growing concern about methane emissions from seaweed by developing a Convolutional Neural Network (CNN) model capable of accurately predicting these emissions. The study used PANDAS to read and analyze the dataset, incorporating statistical measures like mean, median, and standard deviation to understand the dataset. The CNN model was trained using the ReLU activation function and mean absolute error as the loss function. The model performance was evaluated through MAPE graphs, comparing the mean absolute percentage error (MAPE) between training and validation sets and between true and predicted emissions, and analyzing trends in yearly greenhouse gas emissions. The results demonstrated that the CNN model achieved a high level of accuracy in predicting methane emissions, with a low MAPE between the expected and actual values. This approach should enhance our understanding of methane emissions from Sargassum, contributing to more accurate environmental impact assessments and effective mitigation strategies. Full article

Skin cancer diagnosis greatly benefits from advanced machine learning techniques, particularly fine-tuned deep learning models. In our research, we explored the impact of traditional machine learning and fine-tuned deep learning approaches on prediction accuracy. Our findings reveal significant improvements in predictability and accuracy with fine-tuning, particularly evident in deep learning models. The CNN, SVM, and Random Forest Classifier achieved high accuracy. However, fine-tuned deep learning models such as EfficientNetB0, ResNet34, VGG16, Inception _v3, and DenseNet121 demonstrated superior performance. To ensure comparability, we fine-tuned these models by incorporating additional layers, including one flatten layer and three densely interconnected layers. These layers play a crucial role in enhancing model efficiency and performance. The flatten layer preprocesses multidimensional feature maps, facilitating efficient information flow, while subsequent dense layers refine feature representations, capturing intricate patterns and relationships within the data. Leveraging LeakyReLU activation functions in the dense layers mitigates the vanishing gradient problem and promotes stable training. Finally, the output dense layer with a sigmoid activation function simplifies decision making for healthcare professionals by providing binary classification output. Our study underscores the significance of incorporating additional layers in fine-tuned neural network models for skin cancer classification, offering improved accuracy and reliability in diagnosis. Full article

Determining the responses of non-photosynthetic vegetation (NPV) and photosynthetic vegetation (PV) communities to climate change is crucial in illustrating the sensitivity and sustainability of these ecosystems. In this study, we evaluated the accuracy of inverting NPV and PV using Landsat imagery with random forest (RF), backpropagation neural network (BPNN), and fully connected neural network (FCNN) models. Additionally, we inverted MODIS NPV and PV time-series data using spectral unmixing. Based on this, we analyzed the responses of NPV and PV to precipitation and drought across different ecological regions. The main conclusions are as follows: (1) In NPV remote sensing inversion, the softmax activation function demonstrates greater advantages over the ReLU activation function. Specifically, the use of the softmax function results in an approximate increase of 0.35 in the R² value. (2) Compared with a five-layer FCNN with 128 neurons and a three-layer BPNN with 12 neurons, a random forest model with over 50 trees and 5 leaf nodes provides better inversion results for NPV and PV (R²__RF-NPV = 0.843, R²__RF-PV = 0.861). (3) Long-term drought or heavy rainfall events can affect the utilization of precipitation by NPV and PV. There is a high correlation between extreme precipitation events following prolonged drought and an increase in PV coverage. (4) Under long-term drought conditions, the vegetation in the study area responded to precipitation during the last winter and growing season. This study provides an illustration of the response of semi-arid ecosystems to drought and wetting events, thereby offering a data basis for the effect evaluation of afforestation projects. Full article

Prostate cancer, a leading cause of cancer-related mortality among men, is characterized by complex genetic and epigenetic alterations, dysregulation of oncogenic pathways, and a dynamic tumor microenvironment. Advances in molecular diagnostics and targeted therapies have significantly transformed the management of this disease. Prostate-specific membrane antigen (PSMA) has emerged as a critical biomarker, enhancing the precision of prostate cancer diagnosis and treatment. Theranostics, which integrates PSMA-targeted imaging with radioligand therapies, has shown remarkable efficacy in detecting and treating advanced prostate cancer. By leveraging the dual capabilities of PSMA-based diagnostics and therapeutic agents, theranostics offers a personalized approach that improves patient outcomes. This comprehensive review explores the latest developments in PSMA-targeted theranostics and their impact on the future of prostate cancer management, highlighting key clinical trials and emerging therapeutic strategies. Full article

This paper presents an innovative approach that utilizes infused images from vibration signals and visual inspections to enhance the efficiency and accuracy of structure health monitoring through GoogLeNet. Scrutiny of the structure of GoogLeNet identified four key parameters, and thus, the optimization of GoogLeNet was completed through manipulation of the four key parameters. First, the impact of the number of inception modules on the performance of GoogLeNet revealed that employing eight inception layers achieves remarkable 100% accuracy while requiring less computational time compared to nine layers. Second, the choice of activation function was studied, with the Rectified Linear Unit (ReLU) emerging as the most effective option. Types of optimizers were then researched, which identified Stochastic Gradient Descent with Momentum (SGDM) as the most efficient optimizer. Finally, the influence of learning rate was compared, which found that a rate of 0.001 produces the best outcomes. By amalgamating these findings, a comprehensive optimized GoogLeNet model was found to identify damage cases effectively and accurately through infused images from vibrations and visual inspections. Full article

The Shisong lü 十誦律, translated in the early 5th century, remains the only complete version of this Buddhist Vinaya text preserved to date and represents the first Vinaya text translated into Chinese. This Vinaya text introduced standardized terminology that significantly influenced subsequent translations of Vinaya texts and profoundly impacted Chinese Buddhism during the Six Dynasties period. Due to its complex translation history, the text is bifurcated into two lineages: the Northern lineage, featuring an initial 58-scroll version (without a preface), and the Southern lineage, with an expanded 61-scroll version (including a preface). This study examines the two oldest extant manuscripts of the Lüxu 律序 (Preface to the Shisong lü) from the Southern lineage—one from the Dunhuang collection currently preserved in Japan and the other from the Nara Japan. Through intensive comparisons with woodblock editions, these manuscripts from Dunhuang, and ancient Japanese manuscript Buddhist canons, this study not only traces the textual evolution of the Southern lineage of the Shisong lü from the 6th to the 13th centuries but also offers new insights into both the historical development and the relationship between these two lineages of the text. Methodologically, this paper provides inspiration for textual criticism of the Vinaya in particular and Buddhist studies in general. Full article

The Xifanping deposit is a distinct Cenozoic porphyry Cu (Au) deposit located in the Sanjing porphyry metallogenic belt 100–150 km east of the JinshajFiang fault in the western Yangtze craton. We present new zircon U–Pb–Lu–Hf isotopic studies and geochemical data of the ore-bearing quartz monzonite porphyry from the Xifanping deposit to determine their petrogenesis and geodynamic mechanisms. LA–ICP–MS zircon U–Pb dating yielded precise emplacement ages of 31.87 ± 0.41 Ma (MSWD = 0.86) and 32.24 ± 0.61 Ma (MSWD = 1.8) for quartz monzonite porphyry intrusions, and 254.9 ± 5.1 Ma (MSWD = 1.7) for inherited zircons of the monzonite porphyry. The ore-bearing monzonite porphyry is characterized by high-K calc–alkaline to shoshonite and peraluminous series, relatively enriched in light over heavy REEs, with no distinct Eu anomalies, as well as enrichment in LILEs and depletion of HFSEs, with adakitic affinities. The zircon Lu–Hf isotope data ranged from εHf(t) values of −2.94 to +3.68 (average −0.47) with crustal model (T_DM2) ages ranging from 0.88 to 1.30 Ga, whereas the inherited zircons displayed positive εHf(t) values ranging from +1.83 to +7.98 (average +5.82), with crustal model (T_DM2) ages ranging from 0.77 to 1.17 Ga. Results suggest that the Xifanping porphyry Cu (Au) deposit is related to two periods of magmatic activities. Early magmas were generated from the Paleo-Tethys oceanic subduction during the Late Permian. The subsequent porphyry magma was likely formed by the remelting of previously subduction-modified arc lithosphere, triggered by the continental collision between the Indian and Asian plates in the Cenozoic. The deep magmas and late hydrothermal fluids took advantage of the early magma transport channels along tectonically weak zones during the transition from an extrusive to an extensional–tensional tectonic environment. Early dikes from remelted and assimilated crust contributed to the two age ranges observed in the porphyry intrusions from the Xifanping deposit. The juvenile lower crust materials of the early magmatic arc were potential sources of the Cenozoic porphyry magmas, which has significant implications for mineral exploration and the geological understanding of porphyry Cu deposits in this region. Full article

This paper focuses on improving the tracking accuracy for servo systems and increasing the contouring performance of precision machining. The dynamic friction during precision machining is analyzed using the LuGre model. The dynamic and static parameters in the friction model are efficiently and accurately identified using the improved Drosophila swarm algorithm based on cross-mutation. The friction tracking error can be deduced from the friction state space and an expression is derived. To compensate for the tracking error caused by friction, a feedforward compensation control is designed to avoid signal lag in traditional friction controllers. Furthermore, the factors of multi-axis parameter mismatching that impact the machining profile accuracy are analyzed for multi-axis control. An adaptive cross-coupled control-based pre-compensation strategy of contour error is designed to reduce both the tracking error and the contour error. The effectiveness of the proposed method is validated through several experiments, which demonstrate a remarkable improvement in tracking performance and contour accuracy. Full article

This work presents the results of studying dilute aqueous solutions of commercial Ln(NO₃)₃ · xH₂O salts with Ln = Ce-Lu using X-ray diffraction (XRD), IR spectroscopy, X-ray absorption spectroscopy (XAS: EXAFS/XANES), and pH measurements. As a reference point, XRD and XAS measurements for characterized Ln(NO₃)₃ · xH₂O microcrystalline powder samples were performed. The local structure of Ln-nitrate complexes in 20 mM Ln(NO₃)₃ · xH₂O aqueous solution was studied under total external reflection conditions and EXAFS geometry was applied to obtain high-quality EXAFS data for solutions with low concentrations of Ln³⁺ ions. Results obtained by EXAFS spectroscopy showed significant contraction of the first coordination sphere during the dissolution process for metal ions located in the middle of the lanthanide series. It was established that in Ln(NO₃)₃ · xH₂O solutions with Ln = Ce, Sm, Gd, Yb (c = 134, 100, 50 and 20 mM) there are coordinated and, to a greater extent, non-coordinated nitrate groups with bidentate and predominantly monodentate bonds with Ln ions, the number of which increases upon transition from cerium to ytterbium. For the first time, the antibacterial and antifungal activity of Ln(NO₃)₃ · xH₂O Ln = Ce, Sm, Gd, Tb, Yb solutions with different concentrations and pH was presented. Cross-relationships between the concentration of solutions and antimicrobial activity with the type of Ln = Ce, Sm, Gd, Tb, Yb were established, as well as the absence of biocidal properties of solutions with a concentration of 20 mM, except for Ln = Yb. The important role of experimental conditions in obtaining and interpreting the results was noted. Full article