Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Search Results (2,806)

Search Parameters:
Keywords = just-in-time

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
31 pages, 4621 KiB  
Perspective
Current Flow in Nerves and Mitochondria: An Electro-Osmotic Approach
by Robert S. Eisenberg
Biomolecules 2025, 15(8), 1063; https://doi.org/10.3390/biom15081063 - 22 Jul 2025
Viewed by 88
Abstract
The electrodynamics of current provide much of our technology, from telegraphs to the wired infrastructure powering the circuits of our electronic technology. Current flow is analyzed by its own rules that involve the Maxwell Ampere law and magnetism. Electrostatics does not involve magnetism, [...] Read more.
The electrodynamics of current provide much of our technology, from telegraphs to the wired infrastructure powering the circuits of our electronic technology. Current flow is analyzed by its own rules that involve the Maxwell Ampere law and magnetism. Electrostatics does not involve magnetism, and so current flow and electrodynamics cannot be derived from electrostatics. Practical considerations also prevent current flow from being analyzed one charge at a time. There are too many charges, and far too many interactions to allow computation. Current flow is essential in biology. Currents are carried by electrons in mitochondria in an electron transport chain. Currents are carried by ions in nerve and muscle cells. Currents everywhere follow the rules of current flow: Kirchhoff’s current law and its generalizations. The importance of electron and proton flows in generating ATP was discovered long ago but they were not analyzed as electrical currents. The flow of protons and transport of electrons form circuits that must be analyzed by Kirchhoff’s law. A chemiosmotic theory that ignores the laws of current flow is incorrect physics. Circuit analysis is easily applied to short systems like mitochondria that have just one internal electrical potential in the form of the Hodgkin Huxley Katz (HHK) equation. The HHK equation combined with classical descriptions of chemical reactions forms a computable model of cytochrome c oxidase, part of the electron transport chain. The proton motive force is included as just one of the components of the total electrochemical potential. Circuit analysis includes its role just as it includes the role of any other ionic current. Current laws are now needed to analyze the flow of electrons and protons, as they generate ATP in mitochondria and chloroplasts. Chemiosmotic theory must be replaced by an electro-osmotic theory of ATP production that conforms to the Maxwell Ampere equation of electrodynamics while including proton movement and the proton motive force. Full article
(This article belongs to the Special Issue Advances in Cellular Biophysics: Transport and Mechanics)
Show Figures

Figure 1

11 pages, 1617 KiB  
Article
Parental Knowledge and Preventive Strategies in Pediatric IgE-Mediated Food Allergy—Results from a Cross-Sectional Survey
by Francesca Galletta, Angela Klain, Sara Manti, Francesca Mori, Carolina Grella, Leonardo Tomei, Antonio Andrea Senatore, Amelia Licari, Michele Miraglia del Giudice and Cristiana Indolfi
Nutrients 2025, 17(15), 2387; https://doi.org/10.3390/nu17152387 - 22 Jul 2025
Viewed by 98
Abstract
Background/Objectives: Food allergy (FA) is a growing concern in pediatric care, requiring effective avoidance strategies and timely emergency responses. The role of caregivers is central to the daily management of FA. This study aimed to assess parental knowledge, preparedness, and behaviors regarding [...] Read more.
Background/Objectives: Food allergy (FA) is a growing concern in pediatric care, requiring effective avoidance strategies and timely emergency responses. The role of caregivers is central to the daily management of FA. This study aimed to assess parental knowledge, preparedness, and behaviors regarding pediatric FA management, focusing on both prevention and emergency readiness. Methods: A cross-sectional survey was conducted from December 2024 to April 2025 through the SurveyMonkey® platform, promoted by the Italian Society of Pediatric Allergology and Immunology (SIAIP). The anonymous, structured questionnaire was distributed online and in two Italian university hospitals. A total of 129 fully completed responses from caregivers of children with FA were analyzed. The survey explored self-perceived knowledge, symptom recognition, preventive actions, emergency preparedness, and communication practices. Results: Only 9.3% of parents considered themselves “very informed,” while 54.3% reported limited or no knowledge. Just 16.0% recognized all symptoms of an allergic reaction, and only 24.0% could distinguish mild reactions from anaphylaxis. Notably, 67.4% reported not knowing how to respond to anaphylaxis, and 83.7% did not possess an epinephrine auto-injector. Preventive measures at home were inconsistently applied, and 41.1% took no precautions when eating out. Communication with external caregivers was often informal or absent. Only 33% updated physicians regularly. Conclusions: The findings reveal significant gaps in parental preparedness and highlight critical areas for educational intervention. Enhanced caregiver training, standardized communication protocols, and improved clinical follow-up are essential to strengthen pediatric FA management and safety. Full article
(This article belongs to the Special Issue Nutrition and Quality of Life for Patients with Chronic Disease)
Show Figures

Figure 1

12 pages, 722 KiB  
Review
Bacteriophages: Potential Candidates for the Dissemination of Antibiotic Resistance Genes in the Environment
by Shahid Sher, Husnain Ahmad Khan, Zaman Khan, Muhammad Sohail Siddique, Dilara Abbas Bukhari and Abdul Rehman
Targets 2025, 3(3), 25; https://doi.org/10.3390/targets3030025 - 22 Jul 2025
Viewed by 221
Abstract
The invention of antibacterial agents (antibiotics) was a significant event in the history of the human race, and this invention changed the way in which infectious diseases were cured; as a result, many lives have been saved. Recently, antibiotic resistance has developed as [...] Read more.
The invention of antibacterial agents (antibiotics) was a significant event in the history of the human race, and this invention changed the way in which infectious diseases were cured; as a result, many lives have been saved. Recently, antibiotic resistance has developed as a result of excessive use of antibiotics, and it has become a major threat to world health. ARGs are spread across biomes and taxa of bacteria via lateral or horizontal gene transfer (HGT), especially via conjugation, transformation, and transduction. This review concerns transduction, whereby bacteriophages or phages facilitate gene transfer in bacteria. Bacteriophages are just as common and many times more numerous than their bacterial prey, and these phages are much more influential in controlling the population of bacteria. It is estimated that 25% of overall genes of Escherichia coli have been copied by other species of bacteria due to the HGT process. Transduction may take place via a generalized or specialized mechanism, with phages being ubiquitous in nature. Phage and virus-like particle (VLP) metagenomics have uncovered the emergence of ARGs and mobile genetic elements (MGEs) of bacterial origins. These genes, when transferred to bacteria through transduction, confer resistance to antibiotics. ARGs are spread through phage-based transduction between the environment and bacteria related to people or animals, and it is vital that we further understand and tackle this mechanism in order to combat antimicrobial resistance. Full article
(This article belongs to the Special Issue Small-Molecule Antibiotic Drug Development)
Show Figures

Figure 1

20 pages, 2652 KiB  
Article
Moderate Impact of Increasing Temperatures on Food Intake in Human Populations
by Per M. Jensen and Marten Sørensen
Challenges 2025, 16(3), 34; https://doi.org/10.3390/challe16030034 - 21 Jul 2025
Viewed by 201
Abstract
Increasing temperatures associated with climate change will lead to (periodic) temperature-induced reductions in food intake in human and other mammal populations. Human adults, however, are both tolerant and resilient to periodic nutritional deficits, and the associated health effects should be limited. Intermittent nutritional [...] Read more.
Increasing temperatures associated with climate change will lead to (periodic) temperature-induced reductions in food intake in human and other mammal populations. Human adults, however, are both tolerant and resilient to periodic nutritional deficits, and the associated health effects should be limited. Intermittent nutritional deficits may also cause growth restriction in developing foetuses and young children, which potentially affects their food intake in later life. Therefore, temperature-induced hypophagia can be hypothesised to manifest as later compensatory responses with multiple concomitant (or extended) lags of varying temporal dimensions. We examined the relationship between calorie intake and ambient outdoor temperatures for a time series covering past decades (FAO data for 1961–2013) in 80 countries to determine if humans alter their food intake in response to elevated temperatures. We included eleven different temporal “windows of exposure” of varying lag. These windows considered current and recent exposure, just as lagged effects allowed for a consideration of past effects on mothers, their children, and childhood exposure. It was hypothesised that one of these could provide a basis for predicting future changes in human calorie intake in response to climate change. Our analyses showed no apparent association with temperatures in ten of the eleven hypotheses/models. The remaining hypothesis suggests that current calorie intake is linked to decadal mean temperatures with a lag of approximately three decades, pointing to an impact on mothers and their (developing) children. The impact of an increase in mean temperature varies with temperature amplitudes, and negative impacts are only found in countries with low temperature amplitudes (warmer countries), albeit the impact on calorie intake caused by a 2–3 °C change in temperatures or temperature amplitudes is generally modest. However, in considering calorie intake, we only address quantities of food (with unspecified quality), which insufficiently reflect the full range of nutritional challenges associated with increasing temperatures. Understanding climate-driven changes in human food intake requires global interdisciplinary collaboration across public health, environmental science, and policy. Full article
(This article belongs to the Section Human Health and Well-Being)
Show Figures

Figure 1

17 pages, 560 KiB  
Review
Navigating a New Normal: A Mixed-Methods Study of the Pediatric Tracheostomy Parent-Caregiver Experience
by Laine DiNoto, Adrianne Frankel, Taylor Wheaton, Desirae Smith, Kimberly Buholtz, Rita Dadiz and Kathryn Palumbo
Children 2025, 12(7), 956; https://doi.org/10.3390/children12070956 - 21 Jul 2025
Viewed by 198
Abstract
Objective: To explore the experiences and self-efficacy of parent-caregivers providing care for a child with a tracheostomy tube. Study Design: Parent-caregivers completed surveys and participated in semi-structured interviews about their experiences learning to care for their child with a tracheostomy tube. Survey data [...] Read more.
Objective: To explore the experiences and self-efficacy of parent-caregivers providing care for a child with a tracheostomy tube. Study Design: Parent-caregivers completed surveys and participated in semi-structured interviews about their experiences learning to care for their child with a tracheostomy tube. Survey data were analyzed using descriptive statistics. Interviews were transcribed verbatim and analyzed thematically through coding. Results: Fifteen parent-caregivers participated in the survey, 13 of whom completed an interview. After receiving a tracheostomy, children were hospitalized a median of 6 months prior to discharge home. At the time of our study, children had been home for a median of 3.5 years. Parent-caregivers felt more prepared to perform routine daily care compared to triaging a change in medical status. Parent-caregiver self-efficacy in performing tracheostomy care skills improved with experience at home. Four themes were identified from interviews: new identity formation, enduring education, child and family biopsychosocial support, and establishing normalcy. Parent-caregivers shared that education was more than just acquiring skills; it also involved discovering diverse ways of learning and building confidence in one’s own abilities to fulfill the many types of roles they serve to successfully care for and keep their child safe while supporting their social and emotional needs as parent-caregivers. Conclusions: Parent-caregivers’ reflections on their experiences provide critical insight into their psychosocial needs and challenges in providing care to children with tracheostomies. Further investigation of lived experiences is vital to shaping a community that can support families of medically complex children. Full article
Show Figures

Figure 1

19 pages, 1942 KiB  
Article
Adaptive Multi-Agent Reinforcement Learning with Graph Neural Networks for Dynamic Optimization in Sports Buildings
by Sen Chen, Xiaolong Chen, Qian Bao, Hongfeng Zhang and Cora Un In Wong
Buildings 2025, 15(14), 2554; https://doi.org/10.3390/buildings15142554 - 20 Jul 2025
Viewed by 128
Abstract
The dynamic scheduling optimization of sports facilities faces challenges posed by real-time demand fluctuations and complex interdependencies between facilities. To address the adaptability limitations of traditional centralized approaches, this study proposes a decentralized multi-agent reinforcement learning framework based on graph neural networks (GNNs). [...] Read more.
The dynamic scheduling optimization of sports facilities faces challenges posed by real-time demand fluctuations and complex interdependencies between facilities. To address the adaptability limitations of traditional centralized approaches, this study proposes a decentralized multi-agent reinforcement learning framework based on graph neural networks (GNNs). Experimental results demonstrate that in a simulated environment comprising 12 heterogeneous sports facilities, the proposed method achieves an operational efficiency of 0.89 ± 0.02, representing a 13% improvement over Centralized PPO, while user satisfaction reaches 0.85 ± 0.03, a 9% enhancement. When confronted with a sudden 30% surge in demand, the system recovers in just 90 steps, 33% faster than centralized methods. The GNN attention mechanism successfully captures critical dependencies between facilities, such as the connection weight of 0.32 ± 0.04 between swimming pools and locker rooms. Computational efficiency tests show that the system maintains real-time decision-making capability within 800 ms even when scaled to 50 facilities. These results verify that the method effectively balances decentralized decision-making with global coordination while maintaining low communication overhead (0.09 ± 0.01), offering a scalable and practical solution for resource management in complex built environments. Full article
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
Show Figures

Figure 1

19 pages, 2565 KiB  
Article
Use of Machine Learning Algorithms to Predict Almen (Shot Peening) Intensity Values of Various Steel Materials
by Murat İnce and Hatice Varol Özkavak
Appl. Sci. 2025, 15(14), 7997; https://doi.org/10.3390/app15147997 - 18 Jul 2025
Viewed by 221
Abstract
Wear, fatigue, and corrosion are just a few of the issues that mechanical components in engineering experience, leading to surface deterioration. Enhancing the surface characteristics of engineering components is therefore essential. The surface properties of engineering objects can be improved by applying different [...] Read more.
Wear, fatigue, and corrosion are just a few of the issues that mechanical components in engineering experience, leading to surface deterioration. Enhancing the surface characteristics of engineering components is therefore essential. The surface properties of engineering objects can be improved by applying different surface treatments. One of these processes is shot peening (SP). Process parameters are crucial for SP. This necessitates the optimization of SP process parameters. In this study, we applied SP and vibratory shot peening (VSP) processes to different steel materials (AISI 8620, AISI 5140, AISI 4140, and AISI 1020) using different process parameters, aiming to determine the effects of these parameters on hardness, residual stress, and surface roughness. The highest compressive residual stress (CRS) and hardness values for shot-peened samples were obtained at the 24–26 A intensity for all steels. For all steel-group VSP samples, the highest CRS and hardness values were obtained at the 60 s −4 mm parameter. This paper aims to predict Almen intensity values using CRS, surface roughness, and hardness values from various steels. The supplied experimental data was utilized to estimate the SP Almen intensity value using a number of machine learning (ML) methods, eliminating the need for costly and time-consuming experimentation. With an RMSE of 0.0731, R2 of 0.9665, and MAE of 0.0613, the deep neural network (DNN) surpassed the other models in terms of prediction accuracy. The results indicate that artificial intelligence technology could be utilized to accurately evaluate Almen intensity. Full article
(This article belongs to the Special Issue Advanced Processing and Characterization of Metals and Their Alloys)
Show Figures

Figure 1

24 pages, 816 KiB  
Review
Implementation of Behavior Change Theories and Techniques for Physical Activity Just-in-Time Adaptive Interventions: A Scoping Review
by Parker Cotie, Amanda Willms and Sam Liu
Int. J. Environ. Res. Public Health 2025, 22(7), 1133; https://doi.org/10.3390/ijerph22071133 - 17 Jul 2025
Viewed by 249
Abstract
(1) Background: Physical activity (PA) is a key modifiable risk factor for chronic diseases, yet many adults do not meet PA guidelines. Just-in-time adaptive interventions (JITAIs), a type of mobile health (mHealth) intervention, offer tailored support based on an individual’s context to promote [...] Read more.
(1) Background: Physical activity (PA) is a key modifiable risk factor for chronic diseases, yet many adults do not meet PA guidelines. Just-in-time adaptive interventions (JITAIs), a type of mobile health (mHealth) intervention, offer tailored support based on an individual’s context to promote PA. Integrating behavior change techniques (BCTs) and theories is critical to the design of effective mHealth interventions. Understanding which BCTs and theories work best can inform future JITAI development. (2) Objective: The objective of this study is to examine how behavior change theories and BCTs are implemented in mHealth PA JITAIs and assess their relationship with PA-related outcomes. (3) Methods: This scoping review followed the PRISMA-ScR guidelines. A total of 29 studies were included. (4) Results: The most commonly used BCTs include prompts/cues (n = 29), goal-setting (behavior) (n = 15), and feedback on behavior (n = 14), while self-determination theory (n = 4) and social cognitive theory (n = 4) are the most commonly used theories. However, there is insufficient evidence as to which theories and BCTs are most effective in eliciting effective PA behavior change. (5) Conclusions: Clearer reporting and integration of BCTs and behavior change theories, along with optimized user interfaces, are needed to improve the intervention quality, replicability, and long-term effectiveness of PA JITAIs. Full article
Show Figures

Figure 1

34 pages, 14529 KiB  
Review
Research and Applications of Additive Manufacturing in Oil and Gas Extraction and Gathering Engineering
by Xiang Jin, Jubao Liu, Wei Fan, Mingyuan Sun, Zhongmin Xiao, Zongheng Fan, Ming Yang and Liming Yao
Materials 2025, 18(14), 3353; https://doi.org/10.3390/ma18143353 - 17 Jul 2025
Viewed by 447
Abstract
The growing consumption of oil and gas resources and the increasing difficulty of extraction have created major challenges for traditional manufacturing and maintenance, particularly in the timely supply of critical components, customized production, and complex structure fabrication. Additive manufacturing (AM) technology, with its [...] Read more.
The growing consumption of oil and gas resources and the increasing difficulty of extraction have created major challenges for traditional manufacturing and maintenance, particularly in the timely supply of critical components, customized production, and complex structure fabrication. Additive manufacturing (AM) technology, with its high design freedom, precision, and rapid prototyping, provides new approaches to address these issues. However, systematic reviews of related efforts are scarce. This paper reviews the applications and progress of metal and non-metal AM technologies in oil and gas extraction and gathering engineering, focusing on the just-in-time (JIT) manufacturing of failed components, the manufacturing and repair of specialized equipment and tools for oil and gas extraction and gathering, and artificial core and reservoir geological modeling fabrication. AM applications in this field remain exploratory and face challenges with regard to their standards, supply chains, materials, and processes. Future research should emphasize developing materials and processes for extreme conditions, optimizing process parameters, establishing standards and traceability systems, and integrating AM with digital design and reverse engineering to support efficient, safe, and sustainable industry development. This work aims to provide a reference for advancing AM research and engineering applications in the oil and gas sector. Full article
Show Figures

Figure 1

22 pages, 1441 KiB  
Article
Utility of Domain Adaptation for Biomass Yield Forecasting
by Jonathan M. Vance, Bryan Smith, Abhishek Cherukuru, Khaled Rasheed, Ali Missaoui, John A. Miller, Frederick Maier and Hamid Arabnia
AgriEngineering 2025, 7(7), 237; https://doi.org/10.3390/agriengineering7070237 - 14 Jul 2025
Viewed by 270
Abstract
Previous work used machine learning (ML) to estimate past and current alfalfa yields and showed that domain adaptation (DA) with data synthesis shows promise in classifying yields as high, medium, or low. The current work uses similar techniques to forecast future alfalfa yields. [...] Read more.
Previous work used machine learning (ML) to estimate past and current alfalfa yields and showed that domain adaptation (DA) with data synthesis shows promise in classifying yields as high, medium, or low. The current work uses similar techniques to forecast future alfalfa yields. A novel technique is proposed for forecasting alfalfa time series data that exploits stationarity and predicts differences in yields rather than the yields themselves. This forecasting technique generally provides more accurate forecasts than the established ARIMA family of forecasters for both univariate and multivariate time series. Furthermore, this ML-based technique is potentially easier to use than the ARIMA family of models. Also, previous work is extended by showing that DA with data synthesis also works well for predicting continuous values, not just for classification. The novel scale-invariant tabular synthesizer (SITS) is proposed, and it is competitive with or superior to other established synthesizers in producing data that trains strong models. This synthesis algorithm leads to R scores over 100% higher than an established synthesizer in this domain, while ML-based forecasters beat the ARIMA family with symmetric mean absolute percent error (sMAPE) scores as low as 12.81%. Finally, ML-based forecasting is combined with DA (ForDA) to create a novel pipeline that improves forecast accuracy with sMAPE scores as low as 9.81%. As alfalfa is crucial to the global food supply, and as climate change creates challenges with managing alfalfa, this work hopes to help address those challenges and contribute to the field of ML. Full article
Show Figures

Figure 1

35 pages, 2297 KiB  
Article
Secure Cooperative Dual-RIS-Aided V2V Communication: An Evolutionary Transformer–GRU Framework for Secrecy Rate Maximization in Vehicular Networks
by Elnaz Bashir, Francisco Hernando-Gallego, Diego Martín and Farzaneh Shoushtari
World Electr. Veh. J. 2025, 16(7), 396; https://doi.org/10.3390/wevj16070396 - 14 Jul 2025
Viewed by 152
Abstract
The growing demand for reliable and secure vehicle-to-vehicle (V2V) communication in next-generation intelligent transportation systems has accelerated the adoption of reconfigurable intelligent surfaces (RIS) as a means of enhancing link quality, spectral efficiency, and physical layer security. In this paper, we investigate the [...] Read more.
The growing demand for reliable and secure vehicle-to-vehicle (V2V) communication in next-generation intelligent transportation systems has accelerated the adoption of reconfigurable intelligent surfaces (RIS) as a means of enhancing link quality, spectral efficiency, and physical layer security. In this paper, we investigate the problem of secrecy rate maximization in a cooperative dual-RIS-aided V2V communication network, where two cascaded RISs are deployed to collaboratively assist with secure data transmission between mobile vehicular nodes in the presence of eavesdroppers. To address the inherent complexity of time-varying wireless channels, we propose a novel evolutionary transformer-gated recurrent unit (Evo-Transformer-GRU) framework that jointly learns temporal channel patterns and optimizes the RIS reflection coefficients, beam-forming vectors, and cooperative communication strategies. Our model integrates the sequence modeling strength of GRUs with the global attention mechanism of transformer encoders, enabling the efficient representation of time-series channel behavior and long-range dependencies. To further enhance convergence and secrecy performance, we incorporate an improved gray wolf optimizer (IGWO) to adaptively regulate the model’s hyper-parameters and fine-tune the RIS phase shifts, resulting in a more stable and optimized learning process. Extensive simulations demonstrate the superiority of the proposed framework compared to existing baselines, such as transformer, bidirectional encoder representations from transformers (BERT), deep reinforcement learning (DRL), long short-term memory (LSTM), and GRU models. Specifically, our method achieves an up to 32.6% improvement in average secrecy rate and a 28.4% lower convergence time under varying channel conditions and eavesdropper locations. In addition to secrecy rate improvements, the proposed model achieved a root mean square error (RMSE) of 0.05, coefficient of determination (R2) score of 0.96, and mean absolute percentage error (MAPE) of just 0.73%, outperforming all baseline methods in prediction accuracy and robustness. Furthermore, Evo-Transformer-GRU demonstrated rapid convergence within 100 epochs, the lowest variance across multiple runs. Full article
Show Figures

Figure 1

13 pages, 2828 KiB  
Article
Efficient Single-Exposure Holographic Imaging via a Lightweight Distilled Strategy
by Jiaosheng Li, Haoran Liu, Zeyu Lai, Yifei Chen, Chun Shan, Shuting Zhang, Youyou Liu, Tude Huang, Qilin Ma and Qinnan Zhang
Photonics 2025, 12(7), 708; https://doi.org/10.3390/photonics12070708 - 14 Jul 2025
Viewed by 123
Abstract
Digital holography can capture and reconstruct 3D object information, making it valuable for biomedical imaging and materials science. However, traditional holographic reconstruction methods require the use of phase shift operation in the time or space domain combined with complex computational processes, which, to [...] Read more.
Digital holography can capture and reconstruct 3D object information, making it valuable for biomedical imaging and materials science. However, traditional holographic reconstruction methods require the use of phase shift operation in the time or space domain combined with complex computational processes, which, to some extent, limits the range of application areas. The integration of deep learning (DL) advancements with physics-informed methodologies has opened new avenues for tackling this challenge. However, most of the existing DL-based holographic reconstruction methods have high model complexity. In this study, we first design a lightweight model with fewer parameters through the synergy of deep separable convolution and Swish activation function and then employ it as a teacher to distill a smaller student model. By reducing the number of network layers and utilizing knowledge distillation to improve the performance of a simple model, high-quality holographic reconstruction is achieved with only one hologram, greatly reducing the number of parameters in the network model. This distilled lightweight method cuts computational expenses dramatically, with its parameter count representing just 5.4% of the conventional Unet-based method, thereby facilitating efficient holographic reconstruction in settings with limited resources. Full article
(This article belongs to the Special Issue Advancements in Optical Metrology and Imaging)
Show Figures

Figure 1

14 pages, 767 KiB  
Article
Evaluation of Awareness, Use, and Perceptions of Injury Prevention Programs Among Youth Sport Coaches in Poland
by Bartosz Wilczyński, Patryk Szczurowski, Jakub Hinca, Łukasz Radzimiński and Katarzyna Zorena
J. Clin. Med. 2025, 14(14), 4951; https://doi.org/10.3390/jcm14144951 - 12 Jul 2025
Viewed by 359
Abstract
Background/Objectives: Injury prevention programs (IPPs) are evidence-based interventions that reduce musculoskeletal injuries in youth sports. Despite their proven benefits, the adoption of IPPs by coaches remains limited. This study aimed to evaluate the awareness, usage, and perceptions of IPPs among youth sports [...] Read more.
Background/Objectives: Injury prevention programs (IPPs) are evidence-based interventions that reduce musculoskeletal injuries in youth sports. Despite their proven benefits, the adoption of IPPs by coaches remains limited. This study aimed to evaluate the awareness, usage, and perceptions of IPPs among youth sports coaches in Poland and to identify factors associated with their implementation. Methods: A cross-sectional study was conducted using a web-based survey tailored to youth sports coaches in Poland. Coaches of athletes aged 9–17 were recruited through targeted outreach to clubs and professional networks. The survey assessed IPP awareness, implementation, perceptions, and sources of information. Statistical analyses included chi-square tests, non-parametric comparisons, Firth’s logistic regression, and cluster profiling. Results: Only 54.6% of coaches (59 out of 108) were aware of IPPs, and among them, just 47.5% reported using them. No significant associations were found between IPP use and demographic variables such as gender, sport, or place of residence. Coaches who were aware of IPPs were significantly younger than those who were unaware (p = 0.029). The information source was the strongest predictor of IPP implementation: coaches trained via formal courses were over 20 times more likely to use IPPs compared to those learning from peers (OR = 20.4, p < 0.001). While coaches generally perceived IPPs as beneficial for fitness and recovery, 28.6% expressed doubts about their effectiveness in reducing injury risk. Conclusions: Despite broadly positive beliefs, only 47.5% of coaches who were aware of IPPs reported using them. Formal training significantly enhances the likelihood of adoption. These findings emphasize the need for structured educational efforts and improved dissemination strategies to promote evidence-based injury prevention in youth sports settings. Full article
Show Figures

Figure 1

19 pages, 3806 KiB  
Article
Electroactive Poly(amic acid) Films Grafted with Pendant Aniline Tetramer for Hydrogen Sulfide Gas Sensing Applications
by Kun-Hao Luo, Yun-Ting Chen, Hsuan-Yu Wu, Zong-Kai Ni and Jui-Ming Yeh
Polymers 2025, 17(14), 1915; https://doi.org/10.3390/polym17141915 - 11 Jul 2025
Viewed by 317
Abstract
Hydrogen sulfide (H2S) is a highly toxic and corrosive gas generated in numerous industrial and environmental processes; rapid, sensitive detection at low ppm levels is therefore crucial for ensuring occupational safety and protecting public health. This work explores the effect of [...] Read more.
Hydrogen sulfide (H2S) is a highly toxic and corrosive gas generated in numerous industrial and environmental processes; rapid, sensitive detection at low ppm levels is therefore crucial for ensuring occupational safety and protecting public health. This work explores the effect of grafting various loadings of pendant aniline tetramer pendants (PEDA) onto electroactive poly(amic acid) (EPAA) films and evaluates their performance as H2S gas sensors. Comprehensive characterization including ion trap mass spectrometry (Ion trap MS), Fourier-transform infrared spectroscopy (FTIR), cyclic voltammetry (CV), and four-probe conductivity measurements, confirmed successful PEDA incorporation and revealed enhanced electrical conductivity with increasing PEDA content. Gas sensing tests revealed that EPAA3 (3 wt% PEDA) achieved the best overall performance toward 10 ppm H2S, producing a 591% response with a rapid 108 s response time. Selectivity studies showed that the response of EPAA3 to H2S exceeded those for SO2, NO2, NH3, and CO by factors of five to twelve, underscoring its excellent discrimination against common interferents. Repeatability tests over five successive cycles gave a relative standard deviation of just 7.4% for EPAA3, and long-term stability measurements over 16 days in ambient air demonstrated that EPAA3 retained over 80%. These findings establish that PEDA-grafted PAA films combine the processability of poly(amic acid) with the sharp, reversible redox behavior of pendant aniline tetramers, delivering reproducible, selective, and stable H2S sensing. EPAA3, in particular, represents a balanced composition that maximizes sensitivity and durability, offering a promising platform for practical environmental monitoring and industrial safety applications. Full article
(This article belongs to the Special Issue Development of Applications of Polymer-Based Sensors and Actuators)
Show Figures

Figure 1

21 pages, 2552 KiB  
Article
Technical, Economic, and Environmental Optimization of the Renewable Hydrogen Production Chain for Use in Ammonia Production: A Case Study
by Halima Khalid, Victor Fernandes Garcia, Jorge Eduardo Infante Cuan, Elias Horácio Zavala, Tainara Mendes Ribeiro, Dimas José Rua Orozco and Adriano Viana Ensinas
Processes 2025, 13(7), 2211; https://doi.org/10.3390/pr13072211 - 10 Jul 2025
Viewed by 260
Abstract
Conventional ammonia production uses fossil-based hydrogen, resulting in high greenhouse gas emissions. Given the growing demand for sustainable solutions, it is essential to replace fossil hydrogen with renewable alternatives. This study assessed the technical, economic, and environmental viability of renewable ammonia production in [...] Read more.
Conventional ammonia production uses fossil-based hydrogen, resulting in high greenhouse gas emissions. Given the growing demand for sustainable solutions, it is essential to replace fossil hydrogen with renewable alternatives. This study assessed the technical, economic, and environmental viability of renewable ammonia production in Minas Gerais. To this end, an optimization model based on mixed integer linear programming (MILP) was developed and implemented in LINGO 20® software. The model incorporated investment costs; raw materials; transportation; emissions; and indicators such as NPV, payback, and minimum sale price. Hydrogen production routes integrated into the Haber–Bosch process were analyzed: biomass gasification (GS_WGS), anaerobic digestion of vinasse (Vinasse_BD_SMR), ethanol reforming (Ethanol_ESR), and electrolysis (PEM_electrolysis). Vinasse_BD_SMR showed the lowest costs and the greatest economic viability, with a payback of just 2 years, due to the use of vinasse waste as a raw material. In contrast, the electrolysis-based route had the longest payback time (8 years), mainly due to the high cost of the electrolyzers. The substitution of conventional hydrogen made it possible to avoid 580,000 t CO2 eq/year for a plant capacity of 200,000 t NH3/year, which represents 13% of the Brazilian emissions from the nitrogenated fertilizer sector. It can be concluded that the viability of renewable ammonia depends on the choice of hydrogen source and logistical optimization and is essential for reducing emissions at large scale. Full article
(This article belongs to the Section Chemical Processes and Systems)
Show Figures

Figure 1

Back to TopTop