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Search Results (103,584)

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31 pages, 3874 KB  
Review
Designing the Next Generation: A Physical Chemistry Approach to Surface Coating Materials
by Maria Pastrafidou, Vassilios Binas and Ioannis A. Kartsonakis
Appl. Sci. 2025, 15(19), 10817; https://doi.org/10.3390/app151910817 (registering DOI) - 8 Oct 2025
Abstract
Surface coating materials have many applications in various sectors, such as aerospace, medical technology, packaging, and construction, due to their unique properties, including self-healing, corrosion resistance, and protection from external factors. Their use not only enhances the durability and lifespan of surfaces but [...] Read more.
Surface coating materials have many applications in various sectors, such as aerospace, medical technology, packaging, and construction, due to their unique properties, including self-healing, corrosion resistance, and protection from external factors. Their use not only enhances the durability and lifespan of surfaces but also their functionality and esthetic value. These coatings can be effective barriers against moisture, oxygen, chemicals, and the growth of microorganisms, which makes them indispensable in industries where reliability and safety are paramount. In the aerospace sector, they provide protection at extreme temperatures and limit component wear. Special coatings in biomedicine improve implant compatibility and prevent bacterial adhesion. In packaging, they extend the shelf life of products, while in construction they prevent the degradation of structural elements. This review article examines the major categories of these materials, as well as their advantages and limitations, and demonstrates a comparative evaluation of their use in certain applications. Full article
(This article belongs to the Collection Organic Corrosion Inhibitors and Protective Coatings)
21 pages, 3933 KB  
Article
Mechanical Design and Experimental Study of a Small-Scale Wind Turbine Model
by Eduardo Muñoz-Palomeque, Segundo Esteban and Matilde Santos
Machines 2025, 13(10), 929; https://doi.org/10.3390/machines13100929 (registering DOI) - 8 Oct 2025
Abstract
The advancement of onshore and offshore wind turbines depends on the experimental validation of new technologies, novel component designs, and innovative concepts. However, full-scale models are typically very expensive, have limited functionality, and are difficult to adapt to diverse research needs. To address [...] Read more.
The advancement of onshore and offshore wind turbines depends on the experimental validation of new technologies, novel component designs, and innovative concepts. However, full-scale models are typically very expensive, have limited functionality, and are difficult to adapt to diverse research needs. To address this shortcoming, this article presents the design of a low-cost, modular 3D-printed small prototype of a wind turbine. It includes a multi-hollow platform for marine environments configuration and stabilization, the turbine tower, and three blades with active pitch control, not always included in wind turbine prototypes. The modular tower design allows for easy height extensions, while the rotor incorporates custom blades optimized for the prototype geometry and experimental setup. Tests were conducted to evaluate the system’s operational response and verify the proper functioning of the assembled components at various wind speeds and blade pitch angles. The results confirm that the rotor speed with the prototype’s onshore configuration is highly pitch-dependent, reaching a maximum efficiency of approximately 5°. The tower displacement, measured with an IMU, remained within a narrow range, oscillating around 2° and reaching up to 4° at higher wind speeds due to elastic deflections of the PLA structure. These results, consistent with the prototype scale, validate its usefulness in capturing essential aerodynamic and structural behaviors of the wind turbine. They also demonstrate its relevance as a new tool for experimental studies of wind turbines and open up new research, validation, and control possibilities not considered in previous developments by incorporating blade pitch control. Full article
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15 pages, 1670 KB  
Article
Effects of Separate Cognitive Training on Endurance Exercise Performance
by Neil Dallaway, Steven R. Bray, Kira L. Innes, Kathryn E. Andrusko and Christopher Ring
J. Funct. Morphol. Kinesiol. 2025, 10(4), 391; https://doi.org/10.3390/jfmk10040391 (registering DOI) - 8 Oct 2025
Abstract
Background: Combined cognitive and physical training develops resilience to mental fatigue, reduces perceived effort, and improves endurance exercise performance when compared to physical training and no training. The isolated contribution of cognitive training toward endurance performance has yet to be determined. Accordingly, we [...] Read more.
Background: Combined cognitive and physical training develops resilience to mental fatigue, reduces perceived effort, and improves endurance exercise performance when compared to physical training and no training. The isolated contribution of cognitive training toward endurance performance has yet to be determined. Accordingly, we examined the effects of separate cognitive training on endurance exercise performance. Method: Two studies employed a pre-test/training/post-test design, with participants randomly assigned to cognitive training or control groups. At pre-test and post-test, participants completed a rhythmic handgrip task (Study 1) or a graded exercise test on a cycle ergometer (Study 2). In Study 1, the cognitive training group completed 20 sessions (four 20 min sessions per week for five weeks) of cognitive training (incongruent Stroop and 2-back tasks), whereas the control group completed no training. In Study 2, the cognitive training group completed nine sessions (three 10 min sessions per week for three weeks) of cognitive training (incongruent Stroop, stop-signal and typing inhibition tasks), whereas the control group completed nine sessions of sham training (congruent Stroop, sham stop-signal and sham typing inhibition tasks). Endurance exercise performance was measured as force production (Study 1) and time to exhaustion (Study 2). Heart rate, exertion and fatigue were also measured. Results: Endurance performance, indexed by force production (Study 1) and time to exhaustion (Study 2), did not change from pre-test to post-test and did not differ between cognitive training and control groups. Similarly, ratings of perceived exertion and heart rate during the exercise tasks did not differ between cognitive training and control groups (Studies 1 and 2). Conclusions: Since separate cognitive training did not improve exercise endurance performance, combined training should be used to create a synergistic training stimulus for brain adaptation and performance enhancement. Full article
(This article belongs to the Section Kinesiology and Biomechanics)
10 pages, 437 KB  
Article
Caregivers’ Emotional Responses Triggered by a False-Positive VLCADD in Newborn Screening in Oita Prefecture
by Sakura Morishima, Yumi Shimada and Kenji Ihara
Int. J. Neonatal Screen. 2025, 11(4), 90; https://doi.org/10.3390/ijns11040090 (registering DOI) - 8 Oct 2025
Abstract
Neonatal screening programs for inborn errors of metabolism are essential for early diagnosis and intervention. However, false-positive results can cause unnecessary psychological stress for caregivers. This study investigated the emotional impact on a small number of caregivers in Oita Prefecture in Japan, whose [...] Read more.
Neonatal screening programs for inborn errors of metabolism are essential for early diagnosis and intervention. However, false-positive results can cause unnecessary psychological stress for caregivers. This study investigated the emotional impact on a small number of caregivers in Oita Prefecture in Japan, whose infants received false-positive screening results for very long-chain acyl-CoA dehydrogenase deficiency (VLCADD). Particular attention was given to caregivers’ concerns regarding episodes of transient fasting suggestive of nutritional deficiency, as well as their perspectives on appropriate feeding practices for newborns. Nineteen infants in Oita Prefecture were identified as having elevated acylcarnitines, which were later confirmed as false positives. Of these cases, 11 mothers consented to participate in a survey and long-term growth evaluation using health check records. Thirty children with normal screening results were included as controls. While no differences in physical growth were found between groups by 3.5 years of age, some mothers of false-positive infants reported persistent anxiety. Their concerns included regret for inadequate breastfeeding and latent adverse effects on long-term growth or development. Conversely, caregivers’ anxiety diminished over time as they directly observed their infants’ normal growth and development. No regret was expressed regarding breastfeeding, and concerns about VLDCAD were not observed. Caregivers’ responses may help reduce their psychological burden. Full article
24 pages, 745 KB  
Article
A One-Phase Fractional Spatial Stefan Problem with Convective Specification at the Fixed Boundary
by Diego E. Guevara, Sabrina D. Roscani, Domingo A. Tarzia and Lucas D. Venturato
Axioms 2025, 14(10), 757; https://doi.org/10.3390/axioms14100757 - 8 Oct 2025
Abstract
We address a fractional spatial Stefan problem derived from a non-Fourier heat flux model with a convective boundary condition at the fixed boundary. An explicit solution is obtained in terms of a three-parameter Mittag–Leffler function. A dimensionless formulation is used to derive a [...] Read more.
We address a fractional spatial Stefan problem derived from a non-Fourier heat flux model with a convective boundary condition at the fixed boundary. An explicit solution is obtained in terms of a three-parameter Mittag–Leffler function. A dimensionless formulation is used to derive a family of fractional spatial Stefan problems that depend on the Biot and Stefan numbers. Finally, a straightforward numerical method for approximating the solutions is presented, along with numerical experiments analyzing the influence of the physical parameters and the order of fractional differentiation. Full article
53 pages, 2758 KB  
Systematic Review
Applications of Computational Mechanics Methods Combined with Machine Learning and Neural Networks: A Systematic Review (2015–2025)
by Lukasz Pawlik, Jacek Lukasz Wilk-Jakubowski, Damian Frej and Grzegorz Wilk-Jakubowski
Appl. Sci. 2025, 15(19), 10816; https://doi.org/10.3390/app151910816 - 8 Oct 2025
Abstract
This review paper analyzes the recent applications of computational mechanics methods in combination with machine learning (ML) and neural network (NN) techniques, as found in the literature published between 2015 and 2024. We present how ML and NNs are enhancing traditional computational methods, [...] Read more.
This review paper analyzes the recent applications of computational mechanics methods in combination with machine learning (ML) and neural network (NN) techniques, as found in the literature published between 2015 and 2024. We present how ML and NNs are enhancing traditional computational methods, such as the finite element method, enabling the solution of complex problems in material modeling, surrogate modeling, inverse analysis, and uncertainty quantification. We categorize current research by considering the specific computational mechanics tasks and the employed ML/NN architectures. Furthermore, we discuss the current challenges, development opportunities, and future directions of this dynamically evolving interdisciplinary field, highlighting the potential of data-driven approaches to transform the modeling and simulation of mechanical systems. The review has been updated to include pivotal publications from 2025, reflecting the rapid evolution of the field in multiscale modeling, data-driven mechanics, and physics-informed/operator learning. Accordingly, the timespan is now 2015–2025, with a focused inclusion of high-impact contributions from 2024 to 2025. Full article
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27 pages, 5625 KB  
Article
Spawning Habitat Partitioning of Sympatric Salmonid Populations in the Upper Bois Brule River, Wisconsin
by Benjamin T. Schleppenbach, Thomas R. Hrabik, Daniel D. McCann, Karen B. Gran and Greg G. Sass
Fishes 2025, 10(10), 506; https://doi.org/10.3390/fishes10100506 - 8 Oct 2025
Abstract
Spawning habitat partitioning can be important for maintaining sympatric fish species. Likewise, critical spawning habitat loss may challenge the long-term persistence of sympatric fish species. The Bois Brule River, Wisconsin, USA, is a spring-fed, western Lake Superior tributary that supports five naturally reproducing [...] Read more.
Spawning habitat partitioning can be important for maintaining sympatric fish species. Likewise, critical spawning habitat loss may challenge the long-term persistence of sympatric fish species. The Bois Brule River, Wisconsin, USA, is a spring-fed, western Lake Superior tributary that supports five naturally reproducing populations of salmonids (native brook trout Salvelinus fontinalis; introduced brown trout Salmo trutta, rainbow trout Oncorhynchus mykiss, coho salmon O. kisutch, and chinook salmon O. tshawytscha). Given increases in recreational angler use and predicted climate-associated changes to trout stream habitat, a better understanding of species interactions during spawning is important to guide future management and conservation of these anthropogenically derived sympatric native and introduced salmonids. Our aim was to establish whether there was partitioning or overlapping in the redd site location preferences among native and introduced salmonids inhabiting the Bois Brule River. We mapped species-specific redd locations by canoe over a 15.3 river km section known to be important for salmonid spawning and evaluated physical, flow, and thermal conditions of these habitats of the Bois Brule River during 2021–2022. We found that spring spawning rainbow trout and fall spawning pacific salmonids and brown trout used the same spawning locations on mid-channel, larger gravel reefs downstream of riffle sections. Native brook trout spawned on smaller substrates with lower streamflow on the edges of the channel, with the highest spawning activity occurring in littoral areas of lentic portions of the river. Our findings provide valuable knowledge of critical spawning habitats for sympatric salmonids that may inform habitat conservation and enhancement efforts in the Bois Brule River and other Great Lakes tributaries with similar sympatric, naturally reproducing salmonids populations. Full article
23 pages, 7551 KB  
Article
Development of Automatic Labels for Cold Front Detection in South America: A 2009 Case Study for Deep Learning Applications
by Dejanira Ferreira Braz, Luana Albertani Pampuch, Michelle Simões Reboita, Tercio Ambrizzi and Tristan Pryer
Climate 2025, 13(10), 211; https://doi.org/10.3390/cli13100211 - 8 Oct 2025
Abstract
Deep learning models for atmospheric pattern recognition require spatially consistent training labels that align precisely with input meteorological fields. This study introduces an automatic cold front detection method using the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) at [...] Read more.
Deep learning models for atmospheric pattern recognition require spatially consistent training labels that align precisely with input meteorological fields. This study introduces an automatic cold front detection method using the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) at 850 hPa, specifically designed to generate physically consistent labels for machine learning applications. The approach combines the Thermal Front Parameter (TFP) with temperature advection (AdvT), applying optimized thresholds (TFP < 5 × 10−11 K m−2; AdvT < −1 × 10−4 K s−1), morphological filtering, and polynomial smoothing. Comparison against 1426 manual charts from 2009 revealed systematic spatial displacement, with mean offsets of ~502 km. Although pixel-level overlap was low, with Intersection over Union (IoU) = 0.013 and Dice coefficient (Dice) = 0.034, spatial concordance exceeded 99%, confirming both methods identify the same synoptic systems. The automatic method detects 58% more fronts over the South Atlantic and 44% fewer over the Andes compared to manual charts. Seasonal variability shows maximum activity in austral winter (31.3%) and minimum in summer (20.1%). This is the first automatic front detection system calibrated for South America that maintains direct correspondence between training labels and reanalysis input fields, addressing the spatial misalignment problem that limits deep learning applications in atmospheric sciences. Full article
(This article belongs to the Special Issue Meteorological Forecasting and Modeling in Climatology)
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20 pages, 4099 KB  
Article
Research on Aerodynamic Load Simulation Techniques for Floating Vertical-Axis Wind Turbines in Basin Model Test
by Qun Cao, Ying Chen, Kai Zhang, Xinyu Zhang, Zhengshun Cheng, Zhihao Jiang and Xing Chen
J. Mar. Sci. Eng. 2025, 13(10), 1924; https://doi.org/10.3390/jmse13101924 - 8 Oct 2025
Abstract
Floating vertical−axis wind turbines present unique advantages for deep−water offshore deployments, but their basin model testing encounters significant challenges in aerodynamic load simulation due to Reynolds scaling effects. While Froude−scaled experiments accurately replicate hydrodynamic behaviors, the drastic reduction in Reynolds numbers at the [...] Read more.
Floating vertical−axis wind turbines present unique advantages for deep−water offshore deployments, but their basin model testing encounters significant challenges in aerodynamic load simulation due to Reynolds scaling effects. While Froude−scaled experiments accurately replicate hydrodynamic behaviors, the drastic reduction in Reynolds numbers at the model scale leads to substantial discrepancies in aerodynamic forces compared to full−scale conditions. This study proposed two methodologies to address these challenges. Fully physical model tests adopt a “physical wind field + rotor model + floating foundation” approach, realistically simulating aerodynamic loads during rotor rotation. Semi−physical model tests employ a “numerical wind field + rotor model + physical floating foundation” configuration, where theoretical aerodynamic loads are obtained through numerical calculations and then reproduced using controllable actuator structures. For fully physical model tests, a blade reconstruction framework integrated airfoil optimization, chord length adjustments, and twist angle modifications through Taylor expansion−based sensitivity analysis. The method achieved thrust coefficient similarity across the operational tip−speed ratio range. For semi−physical tests, a cruciform−arranged rotor system with eight dynamically controlled rotors and constrained thrust allocation algorithms enabled the simultaneous reproduction of periodic streamwise/crosswind thrusts and vertical−axis torque. Numerical case studies demonstrated that the system effectively simulates six−degree−of−freedom aerodynamic loads under turbulent conditions while maintaining thrust variation rates below 9.3% between adjacent time steps. These solutions addressed VAWTs’ distinct aerodynamic complexities, including azimuth−dependent Reynolds number fluctuations and multidirectional force coupling, which conventional methods fail to accommodate. The developed techniques enhanced the fidelity of floating VAWT basin tests, providing critical experimental validation tools for emerging offshore wind technologies. Full article
(This article belongs to the Section Ocean Engineering)
24 pages, 15793 KB  
Article
AirCalypse: A Case Study of Temporal and User-Behaviour Contrasts in Social Media for Urban Air Pollution Monitoring in New Delhi Before and During COVID-19
by Prithviraj Pramanik, Tamal Mondal, Sirshendu Arosh and Mousumi Saha
Sustainability 2025, 17(19), 8924; https://doi.org/10.3390/su17198924 - 8 Oct 2025
Abstract
Air pollution has become a significant concern for human health, especially in developing countries. Among Primary Pollutants, particulate matter 2.5 (PM2.5), refers to airborne particles which have a diameter of 2.5 micrometres or less, and has become a widely used [...] Read more.
Air pollution has become a significant concern for human health, especially in developing countries. Among Primary Pollutants, particulate matter 2.5 (PM2.5), refers to airborne particles which have a diameter of 2.5 micrometres or less, and has become a widely used measure for monitoring air quality globally. The standard go-to method usually uses Federal Reference Grade sensors to understand air quality. But, they are quite cost-prohibitive, so the popular alternative is low-cost (LC) air quality sensors. Even LC air quality monitors do not cover many areas, especially across the global south. On the other hand, the ubiquitous use of online social media OSM has led to its evolution in participatory sensing. While it does not function as a physical sensor, it can be a proxy indicator of public perception on the topic under study. OSM platforms such as Twitter/X and Reddit have already demonstrated their value in understanding human perception across various domains, including air quality monitoring. This study focuses on understanding air pollution in a resource-constrained setting by examining how the community perception on social media can complement traditional monitoring. We leverage metadata readily available from social media user data to find patterns with air quality fluctuations before and during the pandemic. We use the US Embassy PM2.5 data for baseline measurement. In the study, we empirically analyse the variations in quantitative & intent-based community perception in seasonal & pandemic outbreaks with varying air quality. We compare the baseline against temporal & user-specific attributes of Twitter/X relating to tweets like daily frequency of tweets, tweet lags 1–5, user followers, user verified, and user lists memberships across two timelines: pre-COVID-19 (20 March 2019– 29 February 2020) & COVID-19 (1 March 2020–20 September 2020). Our analysis examines both the quantitative and the intent-based community engagement, highlighting the significance of features like user authenticity, tweet recurrence rates, and intensity of participation. Furthermore, we show how behavioural patterns in the online discussions diverged across the two periods, which reflected the broader shifts in the air pollution levels and the public attention. This study empirically demonstrates the significance of X/Twitter metadata, beyond standard tweet content, and provides additional features for modelling and understanding air quality in developing countries. Full article
(This article belongs to the Special Issue Air Pollution and Sustainability)
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17 pages, 297 KB  
Article
Psychosocial Representations of Gender-Based Violence Among University Students from Northwestern Italy
by Ilaria Coppola, Marta Tironi, Elisa Berlin, Laura Scudieri, Fabiola Bizzi, Chiara Rollero and Nadia Rania
Behav. Sci. 2025, 15(10), 1373; https://doi.org/10.3390/bs15101373 - 8 Oct 2025
Abstract
The aim of the study was to explore the psychosocial perceptions that young adults have regarding gender-based violence, including those based on their personal experiences, and to highlight perceptions related to social media and how its use might be connected to gender-based violence. [...] Read more.
The aim of the study was to explore the psychosocial perceptions that young adults have regarding gender-based violence, including those based on their personal experiences, and to highlight perceptions related to social media and how its use might be connected to gender-based violence. The participants were 40 university students from Northwestern Italy with an average age of 21.8 years (range: 19–25); 50% were women. Sampling was non-probabilistic and followed a purposive convenience strategy. Semi-structured interviews were conducted online and audio-recorded, and data were analyzed using the reflective thematic approach. The results revealed that young adults are very aware, at a theoretical level, of “offline” physical, psychological, and verbal gender-based violence and its effects, while they do not give much consideration to online violence, despite often being victims of it, as revealed by their accounts, for example, through unsolicited explicit images or persistent harassment on social media. Therefore, the results of this research highlight the need to develop primary prevention programs focused on increasing awareness and providing young people with more tools to identify when they have been victims of violence, both online and offline, and to process the emotional experiences associated with such events. Full article
(This article belongs to the Special Issue Psychological Research on Sexual and Social Relationships)
16 pages, 414 KB  
Article
Beliefs and Behaviors: Mind-Body Health Influences on Health Behaviors Amidst COVID-19
by Aarti P. Bellara, Emily L. Winter, Johanna M. deLeyer-Tiarks, Adeline Bray and Melissa A. Bray
COVID 2025, 5(10), 169; https://doi.org/10.3390/covid5100169 - 8 Oct 2025
Abstract
In order to understand how health beliefs map onto health behaviors, a national survey, administered in the wake of the COVID-19 campus closures, was conducted to explore college students’ mind-body health beliefs and their health behaviors (across dimensions of physical exercise, diet/nutrition, and [...] Read more.
In order to understand how health beliefs map onto health behaviors, a national survey, administered in the wake of the COVID-19 campus closures, was conducted to explore college students’ mind-body health beliefs and their health behaviors (across dimensions of physical exercise, diet/nutrition, and socialization). To this end, the Mind-Body Health Screener (MBHS), a five-item, Likert scale, brief measure, was developed. The present study applied an online survey design administered nationally to U.S. undergraduate students during the initial lockdowns with the pandemic (n = 557). To examine the psychometric properties of the MBHS, exploratory and confirmatory factor analyses were run as well as measures of reliability. Furthermore, linear regressions and effect sizes were computed to understand the connection between mind-body health beliefs and behaviors. While initial data supported the psychometric properties of the Mind-Body Health Screener (MBHS) developed for this purpose, substantive results suggested that mind-body health beliefs did not relate to mind-body health behaviors (either before or after the campus closures), aligning with the Cognitive Dissonance Theory. Post hoc analysis did, however, suggest a significant change in health behaviors from pre-campus closures to during the closures, suggesting students engaged in more physical exercise, eating behaviors, and socializing before campus closed, observed with small to large effects. Taken together, the findings of the present study illustrate how the Cognitive Dissonance Theory is a relevant perspective to consider the relation between health beliefs and behaviors during a period of immense stress, such as the COVID-19 initial campus closures. Full article
(This article belongs to the Section COVID Public Health and Epidemiology)
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28 pages, 7904 KB  
Article
Optimising Rice Straw Bale Quality Through Vibration-Assisted Compression
by Fudong Xu, Wenlong Xu, Changsu Xu, Jinwu Wang and Han Tang
Agriculture 2025, 15(19), 2094; https://doi.org/10.3390/agriculture15192094 - 8 Oct 2025
Abstract
This study focuses on enhancing the comprehensive utilisation of rice straw by proposing a vibration-assisted compression technology, with the aim of resolving inherent issues in traditional baling, such as uneven compression and low density. This study designed a multi-point vibration-assisted compression test rig [...] Read more.
This study focuses on enhancing the comprehensive utilisation of rice straw by proposing a vibration-assisted compression technology, with the aim of resolving inherent issues in traditional baling, such as uneven compression and low density. This study designed a multi-point vibration-assisted compression test rig and established a vibration-enhanced compression mechanical model based on the physical properties of rice straw. By integrating discrete element method (DEM) simulations with bench testing, the optimal length-to-width ratio of 1:1 was identified for achieving superior compaction quality. A systematic analysis was conducted to evaluate the effects of vibration point configuration, frequency, and amplitude control on straw bale integrity. The results of the DEM simulations demonstrated that vibration-assisted compression significantly enhanced the compaction uniformity and stability of rice straw. The dimensional stability coefficient and pressure transmission rates of the straw bales reached 88.25% and 58.04%, respectively, validating the efficacy of the vibration-assisted compression technique. This study provides innovative concepts and theoretical foundations for optimising the design of straw baling and in-field collection equipment. It holds critical significance for advancing the resource-efficient utilisation of agricultural residues and promoting sustainable agricultural practices. Full article
(This article belongs to the Section Agricultural Technology)
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32 pages, 1492 KB  
Review
Quantitative MRI in Neuroimaging: A Review of Techniques, Biomarkers, and Emerging Clinical Applications
by Gaspare Saltarelli, Giovanni Di Cerbo, Antonio Innocenzi, Claudia De Felici, Alessandra Splendiani and Ernesto Di Cesare
Brain Sci. 2025, 15(10), 1088; https://doi.org/10.3390/brainsci15101088 - 8 Oct 2025
Abstract
Quantitative magnetic resonance imaging (qMRI) denotes MRI methods that estimate physical tissue parameters in units, rather than relative signal. Typical readouts include T1/T2 relaxation (ms; or R1/R2 in s−1), proton density (%), diffusion metrics (e.g., ADC in mm2/s, FA), [...] Read more.
Quantitative magnetic resonance imaging (qMRI) denotes MRI methods that estimate physical tissue parameters in units, rather than relative signal. Typical readouts include T1/T2 relaxation (ms; or R1/R2 in s−1), proton density (%), diffusion metrics (e.g., ADC in mm2/s, FA), magnetic susceptibility (χ, ppm), perfusion (e.g., CBF in mL/100 g/min; rCBV; Ktrans), and regional brain volumes (cm3; cortical thickness). This review synthesizes brain qMRI across T1/T2 relaxometry, myelin/MT (MWF, MTR/MTsat/qMT), diffusion (DWI/DTI/DKI/IVIM), susceptibility imaging (SWI/QSM), perfusion (DSC/DCE/ASL), and volumetry using a unified framework: physics and signal model, acquisition and key parameters, outputs and units, validation/repeatability, clinical applications, limitations, and future directions. Our scope is the adult brain in neurodegenerative, neuro-inflammatory, neuro-oncologic, and cerebrovascular disease. Representative utilities include tracking demyelination and repair (T1, MWF/MTsat), grading and therapy monitoring in gliomas (rCBV, Ktrans), penumbra and tissue-at-risk assessment (DWI/DKI/ASL), iron-related pathology (QSM), and early dementia diagnosis with normative volumetry. Persistent barriers to routine adoption are protocol standardization, vendor-neutral post-processing/QA, phantom-based and multicenter repeatability, and clinically validated cut-offs. We highlight consensus efforts and AI-assisted pipelines, and outline opportunities for multiparametric integration of complementary qMRI biomarkers. As methodological convergence and clinical validation mature, qMRI is poised to complement conventional MRI as a cornerstone of precision neuroimaging. Full article
(This article belongs to the Special Issue Application of MRI in Brain Diseases)
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14 pages, 1530 KB  
Article
Assessing Musculoskeletal Injury Risk in Hospital Healthcare Professionals During a Single Daily Patient-Handling Task
by Xiaoxu Ji, Thomaz Ahualli de Sanctis, Mahmoud Alwahkyan, Xin Gao, Jenna Miller and Sarah Thomas
Data 2025, 10(10), 160; https://doi.org/10.3390/data10100160 - 8 Oct 2025
Abstract
Background: Healthcare professionals are at significant risk of musculoskeletal injuries due to the physically demanding nature of patient-handling tasks. While various ergonomic interventions have been introduced to mitigate these risks, comprehensive methods for assessing and addressing musculoskeletal hazards remain limited. Purpose: This study [...] Read more.
Background: Healthcare professionals are at significant risk of musculoskeletal injuries due to the physically demanding nature of patient-handling tasks. While various ergonomic interventions have been introduced to mitigate these risks, comprehensive methods for assessing and addressing musculoskeletal hazards remain limited. Purpose: This study presents a novel approach to evaluating musculoskeletal injury risks among healthcare workers, marking the first instance in which two motion tracking systems are used simultaneously. This dual-system setup enables a more comprehensive and dynamic analysis of worker interactions in real time. Healthcare professionals were divided into three groups to perform patient transfer tasks. Three key poses within the task, associated with peak lumbar forces, were identified and analyzed. Results: The resulting compressive forces on the participants’ lower back ranged from 581.0 N to 3589.1 N, and the Anterior–Posterior (A/P) shear forces ranged from 33.1 N to 912.3 N across the three poses. Relative differences in trunk flexion showed strong correlations with compressive and A/P shear forces at each pose, respectively. Discussion and conclusion: Strong associations were found between lumbar loads and participant’s anthropometrics. Recommendations for optimal postures and partner pairings were developed to help reduce the risk of lower back injuries during patient handling. Full article
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