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22 pages, 1546 KB  
Article
Tissue-Specific Multi-Omics Integration Demonstrates Molecular Signatures Connecting Obesity to Immune Vulnerability
by Ozge Onluturk Aydogan, Aytac Dursun Oksuzoglu and Beste Turanli
Metabolites 2026, 16(2), 95; https://doi.org/10.3390/metabo16020095 (registering DOI) - 27 Jan 2026
Abstract
Background: Adipose tissue surrounds organs and tissues in the body and can alter their function. It could secrete diverse biological molecules, including lipids, cytokines, hormones, and metabolites. In light of all this information, obesity can influence many tissues and organs in the body, [...] Read more.
Background: Adipose tissue surrounds organs and tissues in the body and can alter their function. It could secrete diverse biological molecules, including lipids, cytokines, hormones, and metabolites. In light of all this information, obesity can influence many tissues and organs in the body, and this situation makes obesity a central contributor to multiple disorders. It is very important to investigate the crosstalk between tissues and organs in the body to clarify the key mechanisms of obesity. Methods: In this study, we analyzed the gene expression profiles of the liver, skeletal muscle, blood, visceral, and subcutaneous adipose tissue. Differentially expressed genes (DEGs) were identified for each tissue, and functional enrichment and protein–protein interaction network analyses were performed on genes commonly identified across tissues. Priority candidate genes were identified using network-based centrality measures, and potential molecular intersection points were explored through host-pathogen interaction network analysis. This study provides an integrative framework for characterizing inter-tissue molecular patterns associated with obesity at the network level. Results: The muscle, subcutaneous adipose tissue, and blood have the highest number of DEGs. The subcutaneous adipose tissue and blood stand out due to the number of DEGs they possess, although liver and visceral adipose tissue have lower amounts. Cancer ranks first in terms of diseases associated with obesity, and this association is accompanied by leukemia, lymphoma, and gastric cancer. RPL15 and RBM39 are the top genes in both degree and betweenness metrics. The host–pathogen interaction network consists of 13 unique-host proteins, 54 unique-pathogen proteins, and 27 unique-pathogen organisms, and the Influenza A virus had the highest interaction. There were a small number of common metabolites in all tissues: 2-Oxoglutarate, Adenosine, Succinate, and D-mannose. Conclusions: In this study, we aimed to identify candidate molecules for obesity using an integrative approach, examining the gene profiles of different organs and tissues. The findings of this study suggest a possible link between obesity and immune-related biological processes. The network obtained from the host-pathogen interaction analysis, and especially the pathways associated with viral infections that stand out in the functional enrichment analysis, may overlap with molecular signatures linked to obesity. Furthermore, the co-occurrence of cytokine signaling, insulin, and glucose metabolism pathways in the enrichment results indicates that the response of cells to insulin may be affected in obese individuals, suggesting a potential interaction between immune and metabolic processes; however, further experimental validation is needed to reveal the direct functional effects of these relationships. Full article
(This article belongs to the Special Issue Exploring Pathological Mechanisms in Obesity, Diabetes, and Metabolic Syndrome: 2nd Edition)
26 pages, 1058 KB  
Review
A Review on Farnesoid X Receptor (FXR) Modulators Focusing on Benzimidazole Scaffold
by Naoki Teno, Keigo Gohda and Ko Fujimori
Molecules 2026, 31(3), 450; https://doi.org/10.3390/molecules31030450 (registering DOI) - 27 Jan 2026
Abstract
The discovery of a mechanism by which bile acids (BAs) regulate fat synthesis by modulating the activation of the farnesoid X receptor (FXR) in the liver and intestines has highlighted the central role of BAs in triglyceride synthesis in the liver. FXR has [...] Read more.
The discovery of a mechanism by which bile acids (BAs) regulate fat synthesis by modulating the activation of the farnesoid X receptor (FXR) in the liver and intestines has highlighted the central role of BAs in triglyceride synthesis in the liver. FXR has been reported as a promising drug target for primary biliary cholangitis, metabolic-dysfunction-associated steatohepatitis, and metabolic-dysfunction-associated steatotic liver disease. A large number of FXR modulators with various chemotypes have been developed by many research groups. Although several FXR modulators are advancing into clinical trials, ongoing efforts aim to develop new FXR modulators that minimize the adverse effects associated with long-term administration. To develop drug candidates targeting FXR, various heterocyclic and/or fused heteroaromatic rings have been employed as the core and/or parts of the structures, out of which benzimidazole has been recognized as a valuable structural motif due to its synthetic accessibility and its versatility in constructing structurally diverse target molecules. Herein, we report on the development of FXR modulators incorporating benzimidazole as a fused heteroaromatic ring. Full article
(This article belongs to the Section Medicinal Chemistry)
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29 pages, 1928 KB  
Article
Denoising Stock Price Time Series with Singular Spectrum Analysis for Enhanced Deep Learning Forecasting
by Carol Anne Hargreaves and Zixian Fan
Analytics 2026, 5(1), 9; https://doi.org/10.3390/analytics5010009 (registering DOI) - 27 Jan 2026
Abstract
Aim: Stock price prediction remains a highly challenging task due to the complex and nonlinear nature of financial time series data. While deep learning (DL) has shown promise in capturing these nonlinear patterns, its effectiveness is often hindered by the low signal-to-noise ratio [...] Read more.
Aim: Stock price prediction remains a highly challenging task due to the complex and nonlinear nature of financial time series data. While deep learning (DL) has shown promise in capturing these nonlinear patterns, its effectiveness is often hindered by the low signal-to-noise ratio inherent in market data. This study aims to enhance the stock predictive performance and trading outcomes by integrating Singular Spectrum Analysis (SSA) with deep learning models for stock price forecasting and strategy development on the Australian Securities Exchange (ASX)50 index. Method: The proposed framework begins by applying SSA to decompose raw stock price time series into interpretable components, effectively isolating meaningful trends and eliminating noise. The denoised sequences are then used to train a suite of deep learning architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and hybrid CNN-LSTM models. These models are evaluated based on their forecasting accuracy and the profitability of the trading strategies derived from their predictions. Results: Experimental results demonstrated that the SSA-DL framework significantly improved the prediction accuracy and trading performance compared to baseline DL models trained on raw data. The best-performing model, SSA-CNN-LSTM, achieved a Sharpe Ratio of 1.88 and a return on investment (ROI) of 67%, indicating robust risk-adjusted returns and effective exploitation of the underlying market conditions. Conclusions: The integration of Singular Spectrum Analysis with deep learning offers a powerful approach to stock price prediction in noisy financial environments. By denoising input data prior to model training, the SSA-DL framework enhanced signal clarity, improved forecast reliability, and enabled the construction of profitable trading strategies. These findings suggested a strong potential for SSA-based preprocessing in financial time series modeling. Full article
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18 pages, 2334 KB  
Article
Biofunctionalized Vascular Access Graft Improves Patency and Endothelialization in a Porcine Arteriovenous Model
by Aurora Battistella, Morgan Linger, Meredith Overton, Unimunkh Uriyanghai, Christine Wai, Gang Xi, Prabir Roy-Chaudhury and Wei Tan
J. Funct. Biomater. 2026, 17(2), 65; https://doi.org/10.3390/jfb17020065 (registering DOI) - 27 Jan 2026
Abstract
Reliable vascular access remains a major clinical challenge for hemodialysis patients, as expanded polytetrafluoroethylene (PTFE) grafts exhibit poor patency and frequent complications driven by thrombosis and neointimal hyperplasia. Tissue-engineered vascular grafts offer a regenerative alternative but often lack the mechanical resilience required for [...] Read more.
Reliable vascular access remains a major clinical challenge for hemodialysis patients, as expanded polytetrafluoroethylene (PTFE) grafts exhibit poor patency and frequent complications driven by thrombosis and neointimal hyperplasia. Tissue-engineered vascular grafts offer a regenerative alternative but often lack the mechanical resilience required for high-flow arteriovenous (AV) environments. Here, we developed a reinforced, biofunctionalized coaxial electrospun graft comprising a poly(ε-caprolactone) mechanical core and a norbornene-functionalized poly(ethylene glycol) sheath incorporating pro-endothelialization cues. Circumferential PTFE rings were added to improve kink resistance. Grafts were implanted in a porcine AV configuration that recapitulates clinical hemodynamic conditions. Mechanical characterization included compliance, burst pressure, and kink resistance; host remodeling was assessed using histology, immunofluorescence, and multiphoton imaging at 4 weeks. Ring-reinforced electrospun grafts demonstrated a kink radius of 0.187 cm, compliance of 1.04 ± 0.29%/100 mmHg, and burst pressure of 1505 ± 565 mmHg, values all comparable to Gore-Tex PTFE and within industrial performance standards. In vivo, the electrospun grafts showed extensive host cell infiltration, collagen deposition, and formation of smooth muscle-like tissue, whereas PTFE controls remained largely acellular. Immunofluorescence confirmed intramural α-SMA+ and CD31+ cell populations, and multiphoton microscopy revealed significantly greater collagen and elastin content compared with PTFE (p < 0.05). Collectively, these findings demonstrate that the reinforced electrospun graft maintains mechanical integrity under physiological AV loading while supporting in situ endothelialization and extracellular matrix remodeling in a clinically relevant, large animal model. This work provides one of the first demonstrations of functional tissue regeneration within a fully synthetic, acellular scaffold in a porcine hemodialysis model and advances the translational development of durable, regenerative vascular access grafts that couple mechanical resilience with bioactive healing capacity. Full article
(This article belongs to the Special Issue Biomaterials in Cardiovascular Regeneration and Pathogenesis Investigation (2nd Edition))
27 pages, 1700 KB  
Article
A Unified Online Assessment Framework for Pre-Fault and Post-Fault Dynamic Security
by Xin Li, Rongkun Shang, Qiao Zhao, Yaowei Zhang, Jingru Liu, Changjie Wu and Panfeng Guo
Energies 2026, 19(3), 673; https://doi.org/10.3390/en19030673 - 27 Jan 2026
Abstract
With the expansion of interconnection in power systems and the extensive adoption of phasor measurement units (PMUs), the secure operation of power systems has been increasingly covered in research. In this article, a unified online framework for pre-fault and post-fault dynamic security assessment [...] Read more.
With the expansion of interconnection in power systems and the extensive adoption of phasor measurement units (PMUs), the secure operation of power systems has been increasingly covered in research. In this article, a unified online framework for pre-fault and post-fault dynamic security assessment (DSA) is proposed. First, maximum mutual information (MIC) and the random subspace method (RSM) are employed to select the key variables and enhance the diversity of input data, serving as feature engineering. Then, a deep forest (DF) regressor and classifier are utilized respectively to predict security margin (SM) and security state (SS) during online pre-fault and post-fault DSA based on the selected variables. In pre-fault DSA, scenarios with high SM are identified as stable, while those with low SM are forwarded to post-fault DSA. In addition, a time self-adaptive scheme is employed to balance low response time and high prediction accuracy. This approach prevents the misclassification of unstable scenarios as stable by either outputting high-credibility predictions of unstable SS or deferring decisions on SS until the end of the decision-making period. The unified framework, tested on an IEEE 39-bus system and a practical 1648-bus system provided by the PSS/E version 35 software, demonstrates significantly improved assessment accuracy and response times. Specifically, it achieves an average response time (ART) of 2.66 cycles for the IEEE 39-bus system and 3.13 cycles for the 1648-bus system while maintaining an accuracy exceeding 98%, surpassing the performance of currently widely used deep learning models. Full article
7 pages, 547 KB  
Article
Integrating Point-of-Care Ultrasound into Orthopedic Residency: A Longitudinal Evaluation
by Sami Chergui, Mostafa Alhabboubi, Paul Brisebois and Anthony Albers
Surgeries 2026, 7(1), 19; https://doi.org/10.3390/surgeries7010019 - 27 Jan 2026
Abstract
Background/Objectives: Point-of-care ultrasound (POCUS) is an accessible and low-cost diagnostic tool that is seldom used by orthopedic residents. This study aims to assess the efficacy of a POCUS training program within an orthopedic surgery residency curriculum in terms of knowledge retention and clinical [...] Read more.
Background/Objectives: Point-of-care ultrasound (POCUS) is an accessible and low-cost diagnostic tool that is seldom used by orthopedic residents. This study aims to assess the efficacy of a POCUS training program within an orthopedic surgery residency curriculum in terms of knowledge retention and clinical usage among the group of residents. Methods: This study included didactic and hands-on teaching sessions. The impact of the teaching sessions was evaluated through surveys (pre-course, immediate post-course, and 6 months post-course). The surveys were divided into three sections: participant’s interest in and usage of POCUS, ultrasound-related knowledge, and perceived limitations related to the usage of ultrasound. All orthopedic residents who attended the teaching sessions and completed all the surveys were included. Results: There were 14 participants. There was a significant increase in interest in POCUS (scale 1 to 5) from 3.36 ± 0.50 in the pre-course survey to 3.93 ± 0.83 in the final post-course survey (p = 0.04). However, there was no significant change in the amount of POCUS usage in clinical settings. Levels of comfort with ultrasound-related procedures significantly increased immediately following the teaching session but did not stay significantly higher after 6 months. When tested on knowledge, the residents’ scores were still significantly greater than they were at the time of the pre-course test at 6 months (p = 0.01). Lack of ultrasound-related knowledge, lack of time, and site culture were the two most prevalent perceived barriers. Conclusions: This study demonstrates that POCUS teaching for orthopedic residents yields long-term benefits in terms of interest and knowledge. However, recurrent teaching sessions and further efforts are required to address perceived obstacles to PoCUS usage and increase clinical implementation. Full article
(This article belongs to the Section Hand Surgery and Research)
23 pages, 1275 KB  
Review
Separation Strategies for Indium Recovery: Exploring Solvent Extraction, Ion-Exchange, and Membrane Methods
by Ewa Rudnik
Metals 2026, 16(2), 156; https://doi.org/10.3390/met16020156 - 27 Jan 2026
Abstract
Indium is a strategically important metal, essential for the production of transparent conductive oxides, flat panel displays, thin-film photovoltaics, and advanced optoelectronic devices. Due to its limited natural abundance and its occurrence in trace amounts alongside other metals in both primary and secondary [...] Read more.
Indium is a strategically important metal, essential for the production of transparent conductive oxides, flat panel displays, thin-film photovoltaics, and advanced optoelectronic devices. Due to its limited natural abundance and its occurrence in trace amounts alongside other metals in both primary and secondary sources, the recovery of indium through efficient separation techniques has gained increasing attention. This review discusses three major separation strategies for indium recovery: solvent extraction, ion-exchange, and membrane processes, applied to both synthetic solutions and real leachates. D2EHPA has demonstrated its applicability as an effective agent for indium separation, not only in solvent extraction but also as an impregnating agent in polymer resins and membranes. While solvent extraction achieves high recovery rates, ion-exchange resins and membrane-based methods offer significant advantages in terms of reusability, reduced chemical consumption, and minimal environmental impact. The selective separation of indium from impurities such as Fe3+ and Sn2+ remains a key consideration, which can be addressed by optimizing feed solution conditions or adjusting the selective stripping stages. A comparative overview of these methods is provided, focusing on separation efficiency, operational conditions, and potential integration into close-loop systems. The article highlights recent innovations and outlines the challenges involved in achieving sustainable indium recovery, in line with circular economy principles. Full article
(This article belongs to the Special Issue Cutting-Edge Innovations in Metal Recovery from Electronic Waste: Challenges, Techniques and Future Horizons)
21 pages, 1910 KB  
Article
A Prototypical Silencer–Resonator Concept Applied to a Heat Pump Mock-Up—Experimental and Numerical Studies
by Sebastian Wagner and Yohko Aoki
Acoustics 2026, 8(1), 6; https://doi.org/10.3390/acoustics8010006 - 27 Jan 2026
Abstract
Modern, electrically operated heat pumps are characterized by a high degree of efficiency and represent an attractive alternative to conventional heating systems. However, the noise emissions from heat pumps installed outside can lead to increasing noise pollution in densely populated residential areas, which [...] Read more.
Modern, electrically operated heat pumps are characterized by a high degree of efficiency and represent an attractive alternative to conventional heating systems. However, the noise emissions from heat pumps installed outside can lead to increasing noise pollution in densely populated residential areas, which represents an obstacle to widespread use. As part of a research project, a heat pump mock-up was built based on an outdoor unit in the Fraunhofer IBP. With this mock-up, investigations have now been carried out with a prototypical silencer–resonator concept. The aim was to reduce the sound power on the outlet side of the heat pump mock-up. To estimate the effect of this silencer–resonator concept for heat pumps, FEM simulations were first carried out using COMSOL Multiphysics® with a simplified model. The simulation results validated the silencer–resonator concept for heat pumps and indicated the considerable potential for sound reduction. A measurement was then set up, with which different silencer lengths and absorber thicknesses in the silencer were tested. The measured sound attenuation was higher than the simulated values. The results showed that porous absorbers with sufficient thickness can achieve effective performance in the mid-frequency range. A maximum sound power reduction of 5.7 dB was achieved with the 0.15 m absorber. Additionally, Helmholtz resonators were implemented to attenuate the low-frequency range and tonal peaks. With these resonators sound attenuation was increased to 7.7 dB. Full article
19 pages, 4564 KB  
Article
Molecular Insights into the Wettability and Hydration Mechanism of Magnesite (104) Surface
by Yuan Tang, Lifeng Ye, Dongsheng He, Wanzhong Yin, Zhili Li and Yanhong Fu
Processes 2026, 14(3), 451; https://doi.org/10.3390/pr14030451 - 27 Jan 2026
Abstract
The flotation efficiency of magnesite in the slurry system is critically influenced by its surface wettability. In this work, molecular dynamics (MD) and density functional theory (DFT) calculations were employed to investigate the interactions between water molecules and the magnesite (104) surface. To [...] Read more.
The flotation efficiency of magnesite in the slurry system is critically influenced by its surface wettability. In this work, molecular dynamics (MD) and density functional theory (DFT) calculations were employed to investigate the interactions between water molecules and the magnesite (104) surface. To elucidate the underlying mechanisms, systematic evaluations were conducted, encompassing frontier orbital energies, water molecule adsorption behavior, and the water wetting process. Results indicate that electrons readily transfer from the highest occupied molecular orbital (HOMO) of water to the lowest unoccupied molecular orbital (LUMO) of magnesite. Specifically, the chemisorption of a single water molecule onto the magnesite surface was observed, with a calculated adsorption energy of −91.6 kJ/mol. This process involves an interaction between the oxygen atom of water and a surface magnesium atom, leading to the formation of an Mg–OW bond. This bond primarily arises from hybridization between the Mg 2p, Mg 2s, and OW 2p orbitals. Furthermore, water molecules within the first adsorbed monolayer exhibited an average adsorption energy of −66.3 kJ/mol, which further confirms the occurrence of chemisorption. Notably, minimal changes were observed in the orbital interactions between water molecules and surface Mg atoms, a trend consistent with the single-molecule adsorption case. The average adsorption energies for the second and third water layers were calculated to be −63.2 kJ/mol and −45.6 kJ/mol, respectively. The stabilization of the hydration layer structure is attributed to the hydrogen-bonding network formed among water molecules in the outer layers. As the number of water layers increases, the structural disorder of water molecules on the magnesite surface progressively intensifies. This decrease in adsorption energy with increasing layer number is attributed to the progressively enhanced contribution of hydrogen-bonding interactions between water molecules across different layers. Consequently, the magnesite surface exhibits a low contact angle, indicating high intrinsic hydrophilicity. Collectively, these findings provide molecular-level insights into the wettability of the magnesite surface, thereby contributing to a more fundamental understanding of magnesite flotation mechanisms. Full article
(This article belongs to the Section Chemical Processes and Systems)
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31 pages, 1755 KB  
Review
Exercise Protects Skeletal Muscle Fibers from Age-Related Dysfunctional Remodeling of Mitochondrial Network and Sarcotubular System
by Feliciano Protasi, Matteo Serano, Alice Brasile and Laura Pietrangelo
Cells 2026, 15(3), 248; https://doi.org/10.3390/cells15030248 - 27 Jan 2026
Abstract
In skeletal muscles fibers, cellular respiration, excitation–contraction (EC) coupling (the mechanism that translates action potentials in Ca2+ release), and store-operated Ca2+ entry (SOCE, a mechanism that allows recovery of external Ca2+ during fatigue) take place in organelles specifically dedicated to [...] Read more.
In skeletal muscles fibers, cellular respiration, excitation–contraction (EC) coupling (the mechanism that translates action potentials in Ca2+ release), and store-operated Ca2+ entry (SOCE, a mechanism that allows recovery of external Ca2+ during fatigue) take place in organelles specifically dedicated to each function: (a) aerobic ATP production in mitochondria; (b) EC coupling in intracellular junctions formed by association between transverse tubules (TTs) and sarcoplasmic reticulum (SR) named triads; (c) SOCE in Ca2+ entry units (CEUs), SR-TT junctions that are in continuity with membranes of triads, but that contain a different molecular machinery (see Graphical Abstract). In the past 20 years, we have studied skeletal muscle fibers by collecting biopsies from humans and isolating muscles from animal models (mouse, rat, rabbit) under different conditions of muscle inactivity (sedentary aging, denervation, immobilization by casting) and after exercise, either after voluntary training in humans (running, biking, etc.) or in mice kept in wheel cages or after running protocols on a treadmill. In all these studies, we have assessed the ultrastructure of the mitochondrial network and of the sarcotubular system (i.e., SR plus TTs) by electron microscopy (EM) and then collected functional data correlating (i) the changes occurring with aging and inactivity with a loss-of-function, and (ii) the structural improvement/rescue after exercise with a gain-of-function. The picture that emerged from this long journey points to the importance of the internal architecture of muscle fibers for their capability to function properly. Indeed, we discovered how the intracellular organization of the mitochondrial network and of the membrane systems involved in controlling intracellular calcium concentration (i[Ca2+]) is finely controlled and remodeled by inactivity and exercise. In this manuscript, we give an integrated picture of changes caused by inactivity and exercise and how they may affect muscle function. Full article
(This article belongs to the Special Issue Skeletal Muscle: Structure, Physiology and Diseases)
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13 pages, 263 KB  
Article
Feeling Rested Improves Cognitive Performance Among University Students: Testing of a Novel Psychophysiological Measurement System
by Márk Komóczi, Levente Lévai, Péter Barna and Karolina Kósa
Brain Sci. 2026, 16(2), 136; https://doi.org/10.3390/brainsci16020136 - 27 Jan 2026
Abstract
Background: Academic performance is related to cognitive functions and satisfied physiological needs such as proper sleep, a factor frequently overlooked by university students. Our aim was to investigate sleep-related variables, cognitive performance and stress level measured by heart rate variability among university students. [...] Read more.
Background: Academic performance is related to cognitive functions and satisfied physiological needs such as proper sleep, a factor frequently overlooked by university students. Our aim was to investigate sleep-related variables, cognitive performance and stress level measured by heart rate variability among university students. Methods: A novel psychophysiological measurement system was used for data collection in which a screen-adapted questionnaire was used to collect data on sleep; gamified versions of standard psychological tests were used to assess cognitive performance, and ECG data were recorded by a wearable ECG sensor, all synchronized by a software. University students volunteered for anonymous testing that lasted approximately one hour. Results: Of the 107 students (mean age: 22.2 years, SD ± 2.22; 52% female), those who reported being well-rested achieved significantly higher overall cognitive performance (p = 0.024). Sleep duration did not correlate with cognitive performance but longer sleep duration was associated with feeling rested (rho = 0.326; p < 0.001). Cognitive performance showed significant association with two HRV parameters such as the Baevsky Stress Index (r = 0.195), higher values of which reflect higher autonomic stress load. Significant negative relation was found between cognitive performance and RMSSD (r = −0.195), another HRV parameter, higher values of which allude to higher parasympathetic activity (p = 0.050 for both). These findings suggest a link between mild arousal and performance. Conclusions: Being rested and lower autonomic stress load are positively correlated with cognitive performance. The novel psychophysiological measurement system integrating subjective and objective measurements of cognitive and physiological functions is feasible for assessing cognitive functions and stress levels in students. Full article
(This article belongs to the Special Issue Relationships Between Disordered Sleep and Mental Health)
17 pages, 5506 KB  
Article
Thermal Performance of Segmented Stator Teeth Topologies for Electric Motors
by Luke Saunders, Yusuf Ugurluoglu, Mehmet C. Kulan and Glynn Atkinson
Energies 2026, 19(3), 672; https://doi.org/10.3390/en19030672 - 27 Jan 2026
Abstract
Different topologies for individual stator teeth as modular electric motor components are investigated via several different metrics such as finite element analysis (FEA), winding methodologies, and thermal performance during electrical power loading. These are easily quantifiable metrics which allow for the direct comparison [...] Read more.
Different topologies for individual stator teeth as modular electric motor components are investigated via several different metrics such as finite element analysis (FEA), winding methodologies, and thermal performance during electrical power loading. These are easily quantifiable metrics which allow for the direct comparison of the different topologies, particularly with respect to the concentrated windings of the copper wire around the stator teeth. The paper assesses temperature rise, heat dissipation, and the role of air gaps within the copper wire windings. The results show that the winding via robot resulted in 30 (±5)% lower temperature rises on average compared to commercial (hairpin) winding systems, due to more ordered winding which results in larger air gaps between the wires. The air gaps appear to play a critical role in the thermal performance of the stator windings. It is also shown that the different topologies affect thermal performance during electrical loading, suggesting that the different topologies could be useful in different applications. Full article
(This article belongs to the Section J: Thermal Management)
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18 pages, 403 KB  
Review
Rotator Cuff Disorders: Practical Recommendations for Conservative Management Based on the Literature
by Adrien J.-P. Schwitzguébel
Medicina 2026, 62(2), 272; https://doi.org/10.3390/medicina62020272 - 27 Jan 2026
Abstract
Conservative management of rotator cuff disorders remains challenging, with no comprehensive, evidence-based framework integrating diagnosis, prognosis, rehabilitation, and biological therapies. Existing recommendations usually address isolated components of care, leading to inconsistent treatment strategies. This article proposes a global, pragmatic protocol for the non-surgical [...] Read more.
Conservative management of rotator cuff disorders remains challenging, with no comprehensive, evidence-based framework integrating diagnosis, prognosis, rehabilitation, and biological therapies. Existing recommendations usually address isolated components of care, leading to inconsistent treatment strategies. This article proposes a global, pragmatic protocol for the non-surgical management of rotator cuff lesions, from initial assessment to long-term follow-up. Drawing on clinical expertise supported by recent literature, we outline a stepwise approach that begins with a comprehensive diagnostic process that combines history, clinical examination, and targeted imaging. Based on lesion type, associated shoulder or neurogenic conditions, and patient profile, rotator cuff disorders are stratified into three prognostic categories under conservative care: good, borderline, and poor prognosis, highlighting factors that require treatment adaptation or early surgical consideration. Rehabilitation objectives are structured around four domains: (1) inflammation and pain control, (2) mobility and scapular kinematics, (3) strengthening and motor control with tendon-sparing strategies, and (4) preservation or restoration of anatomy. For each prognostic category, we define a monitoring plan integrating clinical reassessment, ultrasound follow-up, and functional milestones, including return-to-play criteria for athletes. This comprehensive narrative review demonstrates that precise diagnosis and individualized rehabilitation can optimize medical follow-up, active strengthening, and complementary or regenerative therapies. Aligning therapeutic decisions with prognostic and functional goals allows clinicians to optimize patient satisfaction and recovery, providing a clear, evidence-informed roadmap for conservative management of rotator cuff disorders. Full article
(This article belongs to the Special Issue Development and Application of Objective Measures in Physiotherapy for Musculoskeletal Disorders, Orthopedics, and Sports Medicine—2nd Edition)
29 pages, 5001 KB  
Article
Integrated Assessment of Soil Loss and Sediment Delivery Using USLE, Sediment Yield, and Principal Component Analysis in the Mun River Basin, Thailand
by Pee Poatprommanee, Supanut Suntikoon, Morrakot Khebchareon and Schradh Saenton
Land 2026, 15(2), 220; https://doi.org/10.3390/land15020220 - 27 Jan 2026
Abstract
The Mun River Basin, the largest Mekong tributary in Northeast Thailand, has experienced extensive agricultural expansion and forest decline, raising concerns over increasing soil erosion and sediment transfer. This study provides an integrated assessment of soil loss, sediment yield (SY), and [...] Read more.
The Mun River Basin, the largest Mekong tributary in Northeast Thailand, has experienced extensive agricultural expansion and forest decline, raising concerns over increasing soil erosion and sediment transfer. This study provides an integrated assessment of soil loss, sediment yield (SY), and sediment delivery ratio (SDR) across 19 sub-watersheds using the Universal Soil Loss Equation (USLE), field-based SY data, and multivariate statistical analyses in 2024. Basinwide soil loss was estimated at ~35 million t y−1 (mean 4.96 t ha−1 y−1), with more than 80% of the basin classified in the no erosion to very low erosion classes. Despite substantial hillslope erosion, only 402,405 t y−1 of sediment reaches the river network, corresponding to a low SDR of 1.15%, which falls within the range reported for large tropical watersheds with significant reservoir infrastructure. Soil loss is most strongly influenced by slope and forested terrain, while SY responds primarily to rainfall and tree plantations; urban land, croplands, and reservoirs act as sediment sinks. Principal Component Analysis (PCA) resolved multicollinearity and produced six components explaining over 90% of predictor variance. A PCA-based regression model predicted SY per unit area with high accuracy (r = 0.81). The results highlight the dominant roles of hydroclimate and land-use structure in shaping sediment connectivity, supporting targeted soil and watershed-management strategies. Full article
(This article belongs to the Section Land Use, Impact Assessment and Sustainability)
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23 pages, 1828 KB  
Article
Performance Evaluation of Hot Mix Asphalt Modified with Biomass-Based Waste Chestnut Shells as Filler Replacement
by Ceren Beyza İnce
Materials 2026, 19(3), 512; https://doi.org/10.3390/ma19030512 - 27 Jan 2026
Abstract
This study aims to investigate the feasibility and performance effects of using waste chestnut shells (CNS), derived from agricultural biomass, as a filler replacement material in hot mix asphalt mixtures. The influence of CNS on the mechanical behavior of hot mix asphalt mixtures [...] Read more.
This study aims to investigate the feasibility and performance effects of using waste chestnut shells (CNS), derived from agricultural biomass, as a filler replacement material in hot mix asphalt mixtures. The influence of CNS on the mechanical behavior of hot mix asphalt mixtures was evaluated through a comprehensive experimental program. Initially, the physical and conventional properties of the B50/70 asphalt binder, aggregates, and CNS material were characterized to establish a reference framework for mixture design. The optimum asphalt content (OAC) for the control mixture was established using the Marshall mix design procedure. Mixture specimens incorporating CNS were produced by introducing the material at four different proportions, corresponding to filler substitution levels ranging from 5% to 20% by weight. The prepared specimens were evaluated through a series of mechanical and durability-related tests, including Marshall stability and flow, Retained Marshall, moisture damage, dynamic creep stiffness, indirect tensile strength (ITS), fatigue performance, and indirect tensile stiffness modulus (ITSM). The results indicated that mixtures with 10% CNS replacement exhibited notable improvements in stability, water sensitivity, ITS, ITSM, dynamic creep, and fatigue resistance, suggesting that CNS has the potential to enhance the performance characteristics of hot mix asphalt pavements. Full article
(This article belongs to the Section Construction and Building Materials)
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18 pages, 1167 KB  
Article
AI Agent- and QR Codes-Based Connected and Autonomous Vehicles: A New Paradigm for Cooperative, Safe, and Resilient Mobility
by Jianhua He, Fangkai Xi, Dashuai Pei, Jiawei Zheng and Han Yang
Mathematics 2026, 14(3), 451; https://doi.org/10.3390/math14030451 (registering DOI) - 27 Jan 2026
Abstract
The rapid advancement of connected and autonomous vehicles (CAVs) has the potential to revolutionize road transportation, promising significant improvements in safety, efficiency, and sustainability. However, traditional CAV architectures are predominantly modular and rule-based. They struggle with interaction, cooperation, and adaptability in complex mixed-traffic [...] Read more.
The rapid advancement of connected and autonomous vehicles (CAVs) has the potential to revolutionize road transportation, promising significant improvements in safety, efficiency, and sustainability. However, traditional CAV architectures are predominantly modular and rule-based. They struggle with interaction, cooperation, and adaptability in complex mixed-traffic environments. Moreover, the substantial infrastructure investment required and the absence of compelling killer applications have limited large-scale deployment of CAVs and roadside units (RSUs), resulting in insufficient penetration to realize the full safety benefits of CAV applications and creating a deployment stalemate. To address the above challenges, this paper proposes an innovative connected autonomous vehicle system, termed AQ-CAV, which leverages recent advances in AI agents and QR codes. AI agents are employed to enable cooperative, self-adaptive, and intelligent vehicular behavior, while QR codes provide a cost-effective, accessible, robust, and scalable mechanism for supporting CAV deployment. We first analyze existing CAV systems and identify their fundamental limitations. We then present the architectural design of the AQ-CAV system, detailing the components and functionalities of vehicle-side and infrastructure-side agents, inter-agent communication and coordination mechanisms, and QR code-based authentication for AQ-CAV operations. Representative applications of the AQ-CAV system are investigated, including a case study on emergency response. Preliminary results demonstrate the feasibility and effectiveness of the proposed system, which achieves significant safety improvements at low system cost. Finally, we discuss the key challenges faced by AQ-CAV and outline future research directions that require exploration to fully realize its potential. Full article
(This article belongs to the Special Issue Advances in Mobile Network and Intelligent Communication, 2nd Edition)
21 pages, 1211 KB  
Article
Memory Retrieval After an Acute Academic Stressor: An Exploratory Analysis of Anticipatory Cortisol and DHEA Responses
by Sara Garces-Arilla, Vanesa Hidalgo, Camino Fidalgo, Teresa Peiró, Alicia Salvador and Magdalena Mendez-Lopez
Appl. Sci. 2026, 16(3), 1306; https://doi.org/10.3390/app16031306 - 27 Jan 2026
Abstract
The relationship between hormonal reactivity to acute stress and memory is well established, but the role of anticipatory cortisol and dehydroepiandrosterone (DHEA) levels remains underexplored. This study aimed to assess the psychobiological responses (anxiety, affect, cortisol and DHEA) to an academic examination, subsequent [...] Read more.
The relationship between hormonal reactivity to acute stress and memory is well established, but the role of anticipatory cortisol and dehydroepiandrosterone (DHEA) levels remains underexplored. This study aimed to assess the psychobiological responses (anxiety, affect, cortisol and DHEA) to an academic examination, subsequent memory performance and associations between anticipatory hormonal response and memory retrieval. Seventy-nine undergraduates (10 males) completed an acquisition session involving picture encoding and immediate free recall. Forty-eight hours later, during the recall session, they sat a written examination followed by delayed free recall and recognition tasks. Results showed higher anticipatory anxiety, negative affect and cortisol levels in the recall session than in the acquisition session. Participants showed poorer delayed recall performance and reduced recognition of neutral pictures. In addition, after correction for multiple comparisons, exploratory hierarchical regression analyses indicated that anticipatory cortisol levels and the cortisol/DHEA ratio assessed prior to the recall session were negatively associated with total delayed free recall performance, with the cortisol/DHEA ratio also being negatively associated with delayed free recall of negative pictures. In the absence of a control group, these findings cannot be used to make causal inferences. However, they are consistent with theoretical accounts of DHEA’s anti-glucocorticoid role and highlight associations between cortisol/DHEA balance and delayed free recall performance, particularly for negative emotional material. Full article
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19 pages, 1583 KB  
Article
Rapid Identification of Candidate SNPs and QTLs for Capsicum annuum Chili Fruit Size and Capsaicin Content Using ddRAD-Sequencing and Bulk Segregant Analysis
by Misbah Naseem, Adrian Christopher Brennan, Rashid Mehmood Rana, Christophe Patterson and Waqas Iqbal
Curr. Issues Mol. Biol. 2026, 48(2), 141; https://doi.org/10.3390/cimb48020141 (registering DOI) - 27 Jan 2026
Abstract
Fruit size and pungency are key yield and quality traits in chili. This study combines high-throughput genotyping with bulk segregant analysis (BSA) to identify candidate SNPs and quantitative trait loci (QTLs) by analyzing extreme phenotypes from a Ghotki × Chakwal-4 F2 population. The [...] Read more.
Fruit size and pungency are key yield and quality traits in chili. This study combines high-throughput genotyping with bulk segregant analysis (BSA) to identify candidate SNPs and quantitative trait loci (QTLs) by analyzing extreme phenotypes from a Ghotki × Chakwal-4 F2 population. The traits were fruit length, diameter, length-to-diameter ratio, and weight, along with capsaicin content. Significant correlations were observed among length, diameter, and length-to-diameter ratio. A total of 534 single nucleotide polymorphisms (SNP) markers were used to develop genetic maps from 4315 to 6607 cM long. The SNP frequency data was pooled for the 25% of individuals showing extreme values for each measured trait, and bulk segregant analysis (BSA) was performed. BSA identified high-scoring SNPs associated with pungency (SNP 1_41308232; SNP 12_104377148), fruit length (SNP 1_92509300; SNP 6_218780813), and fruit weight (SNP 6_100989762 and SNP 6_138660974). Genetic mapping identified twelve pungency QTLs, three for fruit length, two for fruit diameter, two for the length-to-diameter ratio, and thirteen for fruit weight. Overlapping QTL regions on chromosome 6 influence fruit length, fruit width, and capsaicin content, indicating potential pleiotropy and offering promising targets for multi-trait selection in chili breeding. The study identifies key SNPs and QTLs that simultaneously influence chili fruit size and pungency, providing valuable targets for multi-trait breeding. Full article
(This article belongs to the Special Issue Molecular Breeding and Genetics Research in Plants—3rd Edition)
19 pages, 2391 KB  
Article
The International Trade Competitiveness of China’s Licorice Exports Evidence from a Multi-Indicator Static Assessment and Constant Market Share Decomposition
by Su-Yang Tang, Yi-Cheng Yu, Wen-Chao Han, Chen Fu and Bing-Gan Lou
Agriculture 2026, 16(3), 318; https://doi.org/10.3390/agriculture16030318 - 27 Jan 2026
Abstract
Licorice is an important specialty crop that links agricultural production, processing and trade, and rural livelihoods in the arid and semi-arid regions of China. Using UN Comtrade data for HS 130212 from 1990 to 2024, this study evaluates the international Trade Competitiveness of [...] Read more.
Licorice is an important specialty crop that links agricultural production, processing and trade, and rural livelihoods in the arid and semi-arid regions of China. Using UN Comtrade data for HS 130212 from 1990 to 2024, this study evaluates the international Trade Competitiveness of China’s licorice exports and identifies the sources of export growth. A multi-indicator static framework is constructed, combining International Market Share (IMS), the Trade Competitiveness Index (TC), the Revealed Symmetric Comparative Advantage index (RSCA) and the Revealed Competitive Advantage index (CA). The results show that China maintains a relatively large and stable global market share and a persistent net export position, but its comparative and net Competitive Advantages are weaker than those of high-end suppliers such as France and Israel, revealing a pattern of “large scale but weak competitiveness”. To capture dynamic drivers, an extended Constant Market Share (CMS) model is applied to decompose China’s licorice exports into world demand, structural and competitiveness effects. The decomposition indicates that export growth has gradually shifted from being mainly driven by global demand expansion to relying more on improvements in product competitiveness and market reconfiguration, particularly in emerging markets. These findings suggest that upgrading product quality and processing, strengthening standards and branding, and promoting more inclusive value-chain development are essential for transforming China’s licorice exports from scale expansion to high-quality growth and for enhancing rural incomes in producing regions. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
36 pages, 4679 KB  
Review
Harnessing the Therapeutic Potential of Extracellular Vesicles for Oral Wound Healing
by Helly A. Patel, Bianca Schmiliver, Keerthi Priya Chinniyampalayam Sekar, Mirelle Dogini, Chidubem Onyeagoro, Daniel C. Shah, M. Hope Robinson, Babatunde Giwa-Otusajo, David T. Wu and Steven L. Goudy
Bioengineering 2026, 13(2), 148; https://doi.org/10.3390/bioengineering13020148 - 27 Jan 2026
Abstract
Oral wound healing is a robust process; however, complications from surgery, systemic diseases, and aging can impair healing. While some treatments exist, regenerative therapies to promote mucosal wound healing remain limited. In recent years, there has been a significant rise in FDA-approved cell-based [...] Read more.
Oral wound healing is a robust process; however, complications from surgery, systemic diseases, and aging can impair healing. While some treatments exist, regenerative therapies to promote mucosal wound healing remain limited. In recent years, there has been a significant rise in FDA-approved cell-based therapies; however, extracellular vesicles represent an emerging cell-free alternative that may mitigate risks associated with cellular therapies, including tumorigenesis and immunogenicity. These lipid-encapsulated nanovesicles can deliver therapeutic cargo, such as proteins, lipids, nucleic acids, or drugs, to the wound site. Extracellular vesicles can be derived from mesenchymal stromal cells, immune cells, bodily fluids, or bacteria, and engineered through genetic modification, preconditioning, or direct cargo loading to enhance therapeutic potency. Furthermore, advanced delivery platforms, including hydrogels, microneedles, and aerosols, allow for sustained and localized EV delivery to the oral wound site. This review examines differences between cutaneous and oral wound healing; factors that impair oral repair; extracellular vesicle sources and engineering strategies; and delivery strategies for developing EV-based therapeutics for oral wound healing. Full article
(This article belongs to the Special Issue Oral Wound Healing and Material Engineering)
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24 pages, 11379 KB  
Article
NCSS-Net: A Negatively Constrained Network with Self-Supervised Band Selection for Hyperspectral Image Underwater Target Detection
by Mengxin Liu and Shengwei Zhong
Remote Sens. 2026, 18(3), 418; https://doi.org/10.3390/rs18030418 - 27 Jan 2026
Abstract
Detecting nearshore underwater targets in hyperspectral imagery faces significant challenges due to complex background clutter, weak and distorted underwater target signals. Extracting discriminative features is a critical step. Current methods are often constrained by high spectral redundancy and reliance on manual annotations, leading [...] Read more.
Detecting nearshore underwater targets in hyperspectral imagery faces significant challenges due to complex background clutter, weak and distorted underwater target signals. Extracting discriminative features is a critical step. Current methods are often constrained by high spectral redundancy and reliance on manual annotations, leading to suboptimal detection performance. To address these problems, this paper proposes a novel underwater target detection framework that integrates self-supervised band selection with a physically-constrained detection, called the negatively constrained network with self-supervised band selection (NCSS-Net). Specifically, NCSS-Net first generates a target-prior abundance map via Normalized Difference Water Index and spectral unmixing. This abundance map is then converted into a binary target mask through adaptive thresholding. The binary target mask serves as pseudo labels and guides an Artificial Bee Colony algorithm to identify a maximally discriminative band subset. These bands are then fed into a negatively-constrained autoencoder. This network is trained with a specialized loss function to enforce negative correlation between the target and water endmembers, thereby enhancing their separability. Experimental results demonstrate that NCSS-Net outperforms existing state-of-the-art methods, offering an effective and practical solution for nearshore underwater monitoring applications. Our code will be available online upon acceptance. Full article
(This article belongs to the Special Issue Underwater Remote Sensing: Status, New Challenges and Opportunities)
23 pages, 2976 KB  
Article
Transfer Learning-Based Piezoelectric Actuators Feedforward Control with GRU-CNN
by Yaqian Hu, Herong Jin, Xiangcheng Chu and Yali Yi
Appl. Sci. 2026, 16(3), 1305; https://doi.org/10.3390/app16031305 - 27 Jan 2026
Abstract
To compensate for hysteresis, low damping vibration, and their coupling effects, this paper proposes a gated recurrent unit and convolutional neural network (GRU-CNN) model as a feedforward control model that maps desired displacement trajectories to driving voltages. The GRU-CNN integrates a gated recurrent [...] Read more.
To compensate for hysteresis, low damping vibration, and their coupling effects, this paper proposes a gated recurrent unit and convolutional neural network (GRU-CNN) model as a feedforward control model that maps desired displacement trajectories to driving voltages. The GRU-CNN integrates a gated recurrent unit (GRU) layer to capture long-term temporal dependencies, a multi-layer convolutional neural network (CNN) to extract local data features, and residual connections to mitigate information distortion. The GRU-CNN is then combined with transfer learning (TL) for feedforward control of cross-batch and cross-type piezoelectric actuators (PEAs), so as to reduce reliance on training datasets. The analysis focuses on the impacts of target PEA data volume and source-target similarity on transfer learning strategies. The GRU-CNN trained on PEA #1 achieves high control accuracy, with a mean absolute error (MAE) of 0.077, a root mean square error (RMSE) of 0.129, and a coefficient of determination (R2) of 0.997. When transferred to cross-batch PEA #2 and cross-type PEA #3, the GRU-CNN feedforward controller still delivers favorable performance; R2 values all exceed 0.98, representing at least a 27% improvement compared to training from scratch. These results indicate that the proposed transfer learning-based feedforward control method can effectively reduce retraining effort, suggesting its potential applicability to batch production scenarios. Full article
21 pages, 3514 KB  
Article
Diffusion-Guided Model Predictive Control for Signal Temporal Logic Specifications
by Jonghyuck Choi and Kyunghoon Cho
Electronics 2026, 15(3), 551; https://doi.org/10.3390/electronics15030551 - 27 Jan 2026
Abstract
We study control synthesis under Signal Temporal Logic (STL) specifications for driving scenarios where strict rule satisfaction is not always feasible and human experts exhibit context-dependent flexibility. We represent such behavior using robustness slackness—learned rule-wise lower bounds on STL robustness—and introduce sub-goals that [...] Read more.
We study control synthesis under Signal Temporal Logic (STL) specifications for driving scenarios where strict rule satisfaction is not always feasible and human experts exhibit context-dependent flexibility. We represent such behavior using robustness slackness—learned rule-wise lower bounds on STL robustness—and introduce sub-goals that encode intermediate intent in the state/output space (e.g., lane-level waypoints). Prior learning-based MPC–STL methods typically infer slackness with VAE priors and plug it into MPC, but these priors can underrepresent multimodal and rare yet valid expert behaviors and do not explicitly model intermediate intent. We propose a diffusion-guided MPC–STL framework that jointly learns slackness and sub-goals from demonstrations and integrates both into STL-constrained MPC. A conditional diffusion model generates pairs of (rule-wise slackness, sub-goal) conditioned on features from the ego vehicle, surrounding traffic, and road context. At run time, a few denoising steps produce samples for the current situation; slackness values define soft STL margins, while sub-goals shape the MPC objective via a terminal (optionally stage) cost, enabling context-dependent trade-offs between rule relaxation and task completion. In closed-loop simulations on held-out highD track-driving scenarios, our method improves task success and yields more realistic lane-changing behavior compared to imitation-learning baselines and MPC–STL variants using CVAE slackness or strict rule enforcement, while remaining computationally tractable for receding-horizon MPC in our experimental setting. Full article
(This article belongs to the Special Issue Real-Time Path Planning Design for Autonomous Driving Vehicles)
22 pages, 3301 KB  
Article
Design, Synthesis, Biological Evaluation and Molecular Docking Studies of New N-Heterocyclic Compounds as Aromatase Inhibitors
by Fatih Tok, Begüm Nurpelin Sağlık Özkan, Yusuf Özkay and Zafer Asım Kaplancıklı
Pharmaceuticals 2026, 19(2), 224; https://doi.org/10.3390/ph19020224 - 27 Jan 2026
Abstract
Background/Objectives: Breast cancer is the most common cancer and the second leading cause of cancer death in women. The aromatase enzyme plays a role in estrogen biosynthesis and is an important biological target for breast cancer treatment. For this purpose, some new 1,3,4-thiadiazole [...] Read more.
Background/Objectives: Breast cancer is the most common cancer and the second leading cause of cancer death in women. The aromatase enzyme plays a role in estrogen biosynthesis and is an important biological target for breast cancer treatment. For this purpose, some new 1,3,4-thiadiazole (4a–4j) and 1,2,4-triazole (5a–5j) structures were designed and synthesized based on the structures of the existing aromatase inhibitors letrozole and anastrozole. Methods: The antiproliferative activities of the compounds were tested against MCF-7 cancer cells. The NIH3T3 healthy cells were used to evaluate the selectivity of the compounds. The inhibitory activities of all compounds were tested against the aromatase enzyme. Results: The 1,2,4-triazole derivatives 5b, 5c, 5e, 5f and 5g exhibited the highest antiproliferative activity against MCF7 cells with IC50 values ranging from 3.142 to 10.415 μM. Similar to the antiproliferative activity results, triazole derivatives 5b, 5c, 5e, 5f and 5g exhibited comparable anti-aromatase activity to letrozole (IC50 = 0.031 μM) with IC50 values ranging from 0.064 to 2.224 μM and demonstrated the highest anti-aromatase activity within the series. The interactions of compound 5c, the most potent compound based on activity results, with the aromatase enzyme have been elucidated through molecular docking and MD simulation studies. Conclusions: According to experimental studies and molecular docking findings, compound 5c shows promise for further studies with its aromatase enzyme inhibitory potential. Full article
(This article belongs to the Section Medicinal Chemistry)
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17 pages, 2674 KB  
Article
A Cyber Attack Path Prediction Approach Based on aText-Enhanced Graph Attention Mechanism
by Hanjun Gao, Hang Tong, Baoyan Yong and Gang Shen
Electronics 2026, 15(3), 552; https://doi.org/10.3390/electronics15030552 - 27 Jan 2026
Abstract
In order to solve the problem of traditional methods not being able to discover hidden attack trajectories, we propose a cyber attack path prediction approach based on a text-enhanced graph attention mechanism in this paper. Specifically, we design an ontology that captures multi-dimensional [...] Read more.
In order to solve the problem of traditional methods not being able to discover hidden attack trajectories, we propose a cyber attack path prediction approach based on a text-enhanced graph attention mechanism in this paper. Specifically, we design an ontology that captures multi-dimensional links between vulnerabilities, weaknesses, attack patterns, and tactics by integrating CVE, CWE, CAPEC, and ATT&CK into Neo4j. Then, we inject natural language descriptions into the attention mechanism to develop a text-enhanced GAT that can alleviate data sparsity. The experiment shows that compared with existing baselines, our approach improveds MRR and Hits@5 by 12.3% and 13.2%, respectively. Therefore, the proposed approach can accurately predict attack paths and support active cyber defense. Full article
(This article belongs to the Special Issue Cryptography in Internet of Things)
29 pages, 1738 KB  
Article
Investment Efficiency–Risk Mismatch and Its Impact on Supply-Chain Upgrading: Evidence from China’s Grain Industry
by Zihang Liu, Fanlin Meng, Bingjun Li and Yishuai Li
Sustainability 2026, 18(3), 1293; https://doi.org/10.3390/su18031293 - 27 Jan 2026
Abstract
This study examines how investment efficiency and risk jointly shape sustainable grain supply-chain upgrading. Using firm-level panel data for 25 listed grain supply-chain firms in China from 2015 to 2023, this study examines efficiency–risk structures and their heterogeneity across upstream, midstream, and downstream [...] Read more.
This study examines how investment efficiency and risk jointly shape sustainable grain supply-chain upgrading. Using firm-level panel data for 25 listed grain supply-chain firms in China from 2015 to 2023, this study examines efficiency–risk structures and their heterogeneity across upstream, midstream, and downstream segments. A three-stage data envelopment analysis (DEA) is applied to measure investment efficiency while controlling for environmental heterogeneity and statistical noise, and a multidimensional investment risk index is constructed using principal component analysis (PCA), with an emphasis on sustainability metrics. The results reveal a clear supply-chain gradient: downstream firms exhibit the highest mean third-stage investment efficiency (crete = 0.633) and scale efficiency (scale = 0.634), midstream firms are intermediate (crete = 0.308; scale = 0.326), and upstream firms remain lowest (crete = 0.129; scale = 0.138). This ordering is also visible year by year, while risk profiles indicate higher exposure upstream and pronounced volatility midstream. Efficiency decomposition shows that upstream inefficiency is mainly driven by scale inefficiency rather than insufficient pure technical efficiency. Overall, efficiency–risk mismatch—manifested as persistent low scale efficiency and elevated risk exposure in upstream, volatility in midstream, and stability in downstream—constitutes a key micro-level barrier to long-term and resilient upgrading. The study thus offers policy-relevant insights for segment-specific interventions that align with sustainable agricultural development: facilitating land consolidation and integrated risk management for upstream scale inefficiency, promoting supply-chain finance and digital integration for midstream risk volatility, and leveraging downstream stability to drive coordinated upgrading and sustainable value creation through market-based incentives. Full article
(This article belongs to the Section Economic and Business Aspects of Sustainability)
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