Search Results (10,099)

Accurately predicting the muscle strength of key muscle–tendon units during human motion is vital for understanding movement mechanisms, optimizing exercise training, evaluating rehabilitation progress, and advancing prosthetic control technologies. Traditional prediction methods often suffer from low accuracy and high computational complexity. To address these challenges, this study employs independent component analysis (ICA) to predict the muscle strength of tendon units in primary moving parts of the human body. The proposed method had the highest accuracy in localization, at 98% when the sample size was 20. When the sample size was 100, the proposed method had the shortest localization time, with a localization time of 0.025 s. The accuracy of muscle strength prediction based on backpropagation neural network for key muscle–tendon units in human motion was the highest, with an accuracy of 99% when the sample size was 100. The method can effectively optimize the accuracy and efficiency of muscle strength prediction for key muscle–tendon units in human motion and reduce computational complexity. Full article

The electrostatic potential in certain types of boundary value problems can be found by solving Laplace’s Equation (LE). It is important for students to develop the ability to recognize the utility of LE and apply the method to solve physics problems. To develop students’ problem-solving skills for solving problems that can be solved effectively using Laplace’s equation in an upper-level electricity and magnetism course, we developed and validated a tutorial focused on finding electrostatic potential in a Cartesian coordinate system. The tutorial was implemented across three instructors’ classes, accompanied by scaffolded pretest (after traditional lecture) and posttest (after the tutorial). We also conducted think-aloud interviews with advanced students using both unscaffolded and scaffolded versions of the pretest and posttest. Findings reveal common student difficulties that were included in the tutorial as a guide to help address them. The difference in the performance of students from the pretest after lecture to the posttest after the tutorial was similar on the scaffolded version of the tests (in which the problems posed were broken into sub-problems) for all three instructors’ classes and interviewed students. Equally importantly, interviewed students demonstrated greater differences in scores from the pretest and posttest on the unscaffolded versions in which the problems were not broken into sub-problems, suggesting that the scaffolded version of the tests may have obscured evidence of actual learning from the tutorial. While a scaffolded test is typically intended to guide students through complex reasoning by breaking a problem into sub-problems and offering structured support, it can limit opportunities to demonstrate independent problem-solving and evidence of learning from the tutorial. Additionally, one instructor’s class underperformed relative to others even on the pretest. This instructor had mentioned that the tests and tutorial were not relevant to their current course syllabus and offered a small amount of extra credit for attempting to help education researchers, highlighting how this type of instructor framing of instructional tasks can negatively impact student engagement and performance. Overall, in addition to identifying student difficulties and demonstrating how the tutorial addresses them, this study reveals two unanticipated but critical insights: first, breaking problems into sub-parts can obscure evidence of students’ ability to independently solve problems, and second, instructor framing can significantly influence student engagement and performance. Full article

This review examines the vast opportunities and key challenges in renewable waste management across the Gulf region, with a particular emphasis on Saudi Arabia. As global demand for sustainable energy intensifies, driven by technological advancements and environmental concerns, the Gulf Cooperation Council nations, notably Saudi Arabia, are beginning to acknowledge the urgency of transitioning from fossil fuel reliance to renewable waste management. This review identifies the abundant renewable resources in the region and highlights progress in policy development while emphasizing the need for comprehensive frameworks and financial incentives to drive further investment and innovation. Waste-to-energy (WTE) technologies offer a promising avenue for reducing environmental degradation and bolstering energy security. With Saudi Arabia targeting the development of 3 Gigawatts of WTE capacity by 2030 as part of national sustainability initiatives, barriers such as regulatory complexities, financial constraints, and public misconceptions persist. Ultimately, this review concludes that advancing renewable waste management in the Gulf, particularly through stronger policies, stakeholders’ collaboration, investment in WTE and an enhancement in public awareness and education, is critical for achieving sustainability goals. By harnessing these opportunities, the region can take decisive steps toward achieving sustainability, positioning Saudi Arabia as a leader in the global fight against climate change and resource depletion. Full article

As part of non-terrestrial networks (NTN), the Low Earth Orbit (LEO) plays a critical role in supporting high-throughput wireless communication. However, the high-speed mobility of LEO satellites, coupled with the high density of user terminals, makes efficient user assignment crucial in maintaining overall wireless performance. The suboptimal assignment from LEO satellites to user terminals can result in frequent unnecessary handovers, rendering the user terminal unable to receive the entire downlink signal. Consequently, it reduces user rate and user satisfaction metrics. However, finding the optimum user assignment to reduce handover issues is categorized as a non-linear programming problem with a combinatorial number of possible solutions, resulting in excessive computational complexity. Therefore, this study proposes a distributed user assignment for the LEO networks. By utilizing message-passing frameworks that map the optimization problem into a graphical representation, the proposed algorithm splits the optimization problem into a local mapping issue, thereby significantly reducing computational complexity. By exchanging small messages iteratively, the proposed algorithm autonomously determines the near-optimal solution. The extensive simulation results demonstrate that the proposed algorithm significantly outperforms the conventional algorithm in terms of user rate and user satisfaction metric under various wireless parameters. Full article

The detection of internal solitary waves (ISWs) in the ocean using Synthetic Aperture Radar (SAR) images is important for the safety of marine engineering structures. Based on 4120 Sentinel SAR images obtained from 2014 to 2024, an ISW dataset covering the Andaman Sea (AS), the South China Sea (SCS), the Sulu Sea (SS), and the Celebes Sea (CS) is constructed, and a deep learning dataset containing 3495 detection samples and 2476 segmentation samples is also established. Based on the YOLOv8 lightweight model, combined with an anti-interference strategy, a multi-size block detection strategy, and a post-processing repair module, an ISW detection method is proposed. This method reduces the false detection rate by 44.20 percentage points in terms of anti-interference performance. In terms of repair performance, the repair rate reaches 85.2%, and the error connection rate is less than 3.1%. The detection results of applying this method to Sentinel images in multiple sea areas show that there are significant regional differences in ISW activities in different sea areas: in the AS, ISW activities peak in the dry season of March and are mainly concentrated in the eastern and southern regions; the western part of the SS and the southern part of the CS are also the core areas of ISW activities. From the perspective of temporal characteristics, the SS maintains a relatively high ISW activity level throughout the dry season, while the CS exhibits more complex seasonal dynamic features. The lightweight detection method proposed in this study has good applicability and can provide support for marine disaster prevention work. Full article

Nontuberculous mycobacteria are opportunistic pathogens increasingly associated with human disease. Within this group, the Mycobacterium avium complex (MAC), which includes M. avium, M. intracellulare and M. intracellulare subsp. chimaera, is the most frequent cause of infection. The increase in MAC cases worldwide has made it crucial to understand their population structure, clinical relevance and resistance mechanisms. Recent advances in whole-genome sequencing (WGS) and molecular approaches have improved the knowledge of taxonomy, population structure and genetic diversity, while also enabling the investigation of transmission and epidemiology. Clinically, MAC most often causes chronic pulmonary disease, but extrapulmonary forms, including disseminated disease, also occur. Presentation can vary by infecting species, while host factors such as pre-existing lung disease or immunosuppression further increase the risk. Treatment outcomes remain less favourable than desired, in part due to antimicrobial resistance involving de novo-acquired mutations. Pathogenesis is also influenced by interactions between MAC and host cells, including mechanisms of immune evasion and inflammatory modulation. In addition, emerging evidence suggests that gut–lung axis dysbiosis may influence susceptibility to MAC infection. This review outlines current knowledge on the population structure, clinical significance, resistance and host–pathogen interactions of MAC. Full article

Immune checkpoint inhibitors (ICIs), including PD-L1 inhibitors, have been approved by the FDA for the treatment of cancers; however, only a small number of cancer patients benefit from these ICIs. Furthermore, the development of drug resistance to this type of treatment is often inevitable. The mechanisms of resistance to PD-L1 inhibitors can be attributed, in part, to an incomplete understanding of the regulation of PD-L1 protein expression. In this study, we identified the role of the E3 ligase GP78, also known as the Autocrine Motility Factor Receptor (AMFR), in the regulation of PD-L1 protein levels. We show that GP78 physically interacts with PD-L1, which is confirmed by IP and Western blotting and is supported by molecular modelling using AlphaFold2. Our modeling studies predict that the interface amino acids of the Ig1 domain of PD-L1 interact with the RING domain and a β-hairpin preceding the CUE domain of GP78. The crystal structure of the PD-1/PD-L1 complex reveals that the interaction with PD-1 is mediated by the Ig1 domain of PD-L1. Furthermore, proteasomal degradation of PD-L1 has been observed via GP78-mediated K48-linked ubiquitination, indicating a key regulatory role for GP78 in the downregulation of PD-L1. Because GP78 expression is inversely correlated with PD-L1 levels in cancer, these findings may have clinical implications for predicting tumor immune evasion and patient response to PD-1/PD-L1 blockade therapies. Taken together, these findings identify a previously unknown mechanism by which GP78 targets PD-L1 for ubiquitination and subsequent degradation in cancer cells, and suggest that blocking the interaction between PD-L1 and PD-1 by an E3 ligase is a novel strategy to improve immunotherapies for cancer patients. Full article

Selective laser melting (SLM) builds metal parts layer by layer by locally melting powder with a fine laser beam, generating complex, geometry-dependent temperature gradients that govern density, microstructure, defects, and residual stresses. Resolving these gradients with high-fidelity finite-element (FE) models is prohibitively slow because the temperature field must be evaluated at dense points along every scan track across multiple layers, while the laser spot is orders of magnitude smaller than typical layer dimensions. This study replaces FE analysis with a deep neural network that predicts the end-of-build temperature field orders of magnitude faster. A benchmark part containing characteristic shape features is introduced to supply diverse training cases, and a novel control-volume-based geometry-abstraction scheme encodes arbitrary workpiece shapes into compact, learnable descriptors. Thermal simulation data from the benchmark train the network, which then predicts the residual temperature field of an unseen, geometrically dissimilar part with a mean absolute error of ~10 K and a mean relative error of ~1% across 500–1300 K. The approach thus offers a rapid, accurate surrogate for FE simulations, enabling efficient temperature-driven optimization of SLM process parameters and part designs. Full article

(1) Background: Comprehensive conceptual models can result in complex artifacts, consisting of many concepts that interact through multiple mechanisms. This complexity can be acceptable and even expected when generating rich models, for instance to support ensuing analyses that find central concepts or decompose models into parts that can be managed by different actors. However, complexity can become a barrier when the conceptual model is used directly by individuals. A ‘transparent’ model can support learning among stakeholders (e.g., in group model building) and it can motivate the adoption of specific interventions (i.e., using a model as evidence base). Although advances in graph-to-text generation with Large Language Models (LLMs) have made it possible to transform conceptual models into textual reports consisting of coherent and faithful paragraphs, turning a large conceptual model into a very lengthy report would only displace the challenge. (2) Methods: We experimentally examine the implications of two possible approaches: asking the text generator to simplify the model, either via abstractive (LLMs) or extractive summarization, or simplifying the model through graph algorithms and then generating the complete text. (3) Results: We find that the two approaches have similar scores on text-based evaluation metrics including readability and overlap scores (ROUGE, BLEU, Meteor), but faithfulness can be lower when the text generator decides on what is an interesting fact and is tasked with creating a story. These automated metrics capture textual properties, but they do not assess actual user comprehension, which would require an experimental study with human readers. (4) Conclusions: Our results suggest that graph algorithms may be preferable to support modelers in scientific translations from models to text while minimizing hallucinations. Full article

The direct deposition of highly concentrated polyelectrolyte complexes based on poly(ethyleneimine) (PEI) and poly(sodium methacrylate) (PMANa) onto inorganic sand microparticles (F100 and F200) resulted in the formation of versatile core-shell composites with fast removal properties in dynamic conditions toward anionic charged pollutants. Herein, in situ-generated nonstoichiometric PEI/PMANa polyelectrolyte complexes were directly precipitated as a soft organic shell onto solid sand microparticles at a 5% mass ratio (organic/inorganic part = 5%, w/w%). The sorption of an anionic model pollutant (Indigo Carmine (IC)) onto the composite particles in dynamic conditions depended on the inorganic core size, the flow rate, the bed type (fixed or fluidized) and the initial dye concentration. The maximum sorption capacity, after 10 cycles of sorption/desorption of IC onto F100@P5% and F200@P5%, was between 16 and 18 mg IC/mL composite. The newly synthesized core-shell composites could immobilize IC at a high flow rate (8 mL/min), either from concentrated (C_IC = 60 mg/L) or very diluted (C_IC = 0.2 mg/L) IC aqueous solution, demonstrating that this type of material could be promising in water treatment or efficient in solid-phase extraction (concentration factor of 2000). Full article

Cultural heritage is important for every group and society, as it represents a part of their identity and helps preserve traditions, along with significant tangible and intangible elements. These elements are not only passed on to future generations but also play a role in education today. Many studies have examined digital applications that promote cultural heritage, particularly those that use Augmented Reality (AR) technology. However, few have systematically examined the methodologies used in the design, development and evaluation of AR applications for cultural heritage. This narrative review addresses that gap by analyzing 45 papers published between 2008 and 2024 from the Scopus and Web of Science databases. The review identifies the main motivations for AR applications, such as enhancing the learning experience, promoting tourism and the use of gamification. The majority of these applications concentrate on tangible cultural heritage, such as historical buildings and cultural routes, while intangible heritage remains less explored. In most cases, AR applications were developed with a focus on user experience, using various development tools and showing different levels of technical complexity. Although many applications initiated evaluation processes, few completed them thoroughly. These evaluations vary widely, ranging from usability tests to pre-/post-tests. The results generally report positive impacts in terms of learning and user experience. This review offers a structured framework and useful insights for researchers regarding the design and evaluation of AR applications and helps identify research gaps and limitations for future work. Full article

Color accuracy is both important and elusive in cultural heritage imaging. An established method for improving color accuracy is dual-RGB imaging, where RGB images of an object are captured sequentially under two different conditions and then combined. As part of an initiative to increase accessibility to color-accurate imaging, the use of lighting filters with the dual-RGB method is investigated. Gel lighting filters are low-cost and can be directly integrated into an imaging workflow by placing them in front of the existing light sources. This research found that color accuracy can be increased by using lighting filters, but it can also be decreased by a poor selection of filter combinations. The identity of the best-performing filters is highly dependent on the light source and can be affected by the pixels selected to represent the color target. Current simulation approaches are insufficient to predict which filters will increase color accuracy. While lighting filters are a promising method for accessible multispectral imaging, their practical implementation is complex and requires further research and adjustments to the method. Full article

This study investigated the effects of high (atmospheric) and low (5% O₂) oxygen tension, as well as a combination of the two, on oocyte metabolism and quality during maturation. Cumulus cell–oocyte complexes collected from gilt ovaries were used for in vitro maturation. In addition, RNA-seq was conducted on the cumulus cells. Low oxygen tension throughout oocyte maturation did not alter the developmental rate to the blastocyst stage; however, it increased oocyte ATP and lipid content while reducing mitochondrial reactive oxygen species and mitochondrial membrane potential. Low-oxygen conditions increased glucose consumption but reduced mitochondrial DNA copy number and mitochondrial protein in cumulus cells. RNA-seq of cumulus cells revealed that low oxygen tension reduced mitochondrial activity and increased glycolysis, with the upregulation of glycolytic genes and downregulation of oxidative phosphorylation and steroidogenesis-related genes. In addition, a two-step oxygen protocol with low (5%) for the first period (0–21 h) and high (20%) for the last half period (21–44 h) increased the ATP and lipid content in oocytes and improved the embryonic developmental ability of the oocytes compared to the high-oxygen group. In conclusion, low oxygen tension during the first part of the maturation period is beneficial for oocyte quality, considering the observed metabolic changes. Full article

Armed conflicts continue to severely impact human populations and essential infrastructure, particularly water supply systems. This study examines the Yechilla area, a high-intensity battle corridor during the Tigray (between 12°15′26″ 14°57′49″ N latitude; and 36°20′57″–39°58′54″ E longitude) war (2020–2022). Using Cochran’s formula, a representative sample of 89 water schemes was selected for onsite assessment. Additional data on damages to water offices, personnel, equipment, and related infrastructure were gathered through face-to-face interviews with local officials and water professionals, onsite visits, and reviews of governmental and non-governmental archives, and previous studies. The findings reveal that 48.3% of water schemes in the study area are non-functional (does not deliver water), which is a significant increase from pre-war non-functionality rates of approximately 7.1% regionally and 21.1% nationally. Despite the Pretoria peace agreement, non-functionality levels remain critically high two years after conflict. Damage includes partial impairments, lack of technical and spare part support, complete destruction, and looting of water scheme components. The widespread destruction of civilian water infrastructure during the Tigray conflict underscores the insufficiency of existing international legal frameworks, such as the International Humanitarian Law and International Water Law, which are inadequately protecting civilians and their property. Understanding the broader consequences of armed conflicts requires examining the indirect effects and the complex interactions within and between social, economic, and environmental systems. These interconnected impacts are essential to fully grasp how conflict affects livelihoods and human security on a wider scale. Full article

Powder Bed Fusion-Laser Beam/Metals (PBF-LB/M) enables the layer-by-layer fabrication of complex parts; however, non-uniform thermal transients during the process induce high stresses. Geometric constraints dominate stress–relaxation behavior, which is the primary mechanism leading to part distortion. Therefore, the printing structure serves as a major factor influencing the distortion of PBF-LB/M-fabricated components, of which the forming angle and support structure parameters are the two key factors affecting the printing structure. This study investigates the effects of forming angles and support parameters on the distortion behavior of oral stents manufactured via PBF-LB/M. The results indicate that the magnitude of distortion varies significantly with the forming angle, with the minimum distortion of 0.667 mm occurring at 75°, while the maximum distortion reaches 1.706 mm at 30°. Combined stiffness theory and thermal stress analysis reveal that the thermal stress peaks at a forming angle of 30°, which is governed mainly by the printed cross-sectional area per layer and the cumulative build height. Meanwhile, structural stiffness gradually decreases as the forming angle increases. The study also confirms that support parameters significantly affect distortion, confirming that larger support mesh size and spacing directly contribute to increased maximum distortion. Based on stiffness theory and thermal stress analysis, it is concluded that support structures reduce distortion primarily through two mechanisms: enhancing the overall structural stiffness and facilitating force transmission. Full article