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Recent Articles  

23 pages, 3601 KB  
Article
Identification of Stress Location During Low-Speed Mobility Travel Using Environmental Data
by Narumon Jadram, Yuri Nishikawa and Midori Sugaya
Sensors 2026, 26(6), 1859; https://doi.org/10.3390/s26061859 (registering DOI) - 15 Mar 2026
Abstract
This study proposes an exploratory framework for identifying stress locations during travel with low-speed mobility devices (LMDs), such as electric wheelchairs. In this framework, stress factors perceived during LMD travel were identified through a post-ride questionnaire, and the travel route was divided into [...] Read more.
This study proposes an exploratory framework for identifying stress locations during travel with low-speed mobility devices (LMDs), such as electric wheelchairs. In this framework, stress factors perceived during LMD travel were identified through a post-ride questionnaire, and the travel route was divided into 100 m segments to enable location-specific stress evaluation. The identified factors were quantified using environmental data to construct an environment-based stress estimation index. Based on these quantified factors, a Composite Stress Score (CSS) was calculated to estimate stress levels along the route. Experiments with healthy adult participants were conducted to examine the feasibility of the proposed method. The results identified poor road surface conditions and vibrations, encounters with other road users, and narrow sidewalks as key stress factors during LMD travel. To examine whether the proposed method captures stress-related responses, correlations between CSS-based stress estimates and heart rate variability (HRV) indices were analyzed. The results showed that CSS calculated from poor road surface/vibrations, encounters with other road users, and narrow sidewalks exhibited moderate negative correlations with SDNN, suggesting that higher CSS values may correspond to increased physiological stress responses. These findings provide preliminary support for the exploratory feasibility of estimating potential stress locations during LMD travel using environmental data. However, the generalizability of the results is limited due to the specific experimental route and the use of healthy adult participants. Full article
(This article belongs to the Section Wearables)
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18 pages, 7585 KB  
Article
Design and Characterization of a Bench-Top Ludwieg Tube for Aerodynamic Measurements via Simultaneous Quantification of Mach Number and Velocity
by Boris S. Leonov, Richard Q. Binzley, Nathan G. Phillips, Roman Rosser, Farhan Siddiqui, Arthur Dogariu and Richard B. Miles
Fluids 2026, 11(3), 80; https://doi.org/10.3390/fluids11030080 (registering DOI) - 15 Mar 2026
Abstract
This article presents the design and detailed characterization of a new supersonic wind tunnel at the Aerospace Laboratory for Lasers, ElectroMagnetics, and Optics of Texas A&M University, tailored for optical diagnostic development and sub-scale fundamental compressible fluid dynamics research. A Ludwieg tube tunnel [...] Read more.
This article presents the design and detailed characterization of a new supersonic wind tunnel at the Aerospace Laboratory for Lasers, ElectroMagnetics, and Optics of Texas A&M University, tailored for optical diagnostic development and sub-scale fundamental compressible fluid dynamics research. A Ludwieg tube tunnel architecture was selected due to its robustness, versatility, and low operational costs. The tunnel consists of a 50-foot-long driver tube constructed from modular Tri-Clamp spools, a Mach 4 nozzle with 3 in. exit diameter configured as a free jet, and a fast-acting valve with 14 ms opening time for high-duty-cycle operation. Such construction proved to be a robust, compact, and affordable solution for academic applications. Characterization methods consisted of simultaneous high-speed dot-schlieren, total and static pressure measurements, and femtosecond laser electronic excitation tagging. Average flow velocity for the first steady-state test time was measured via FLEET at (668.0 ± 5.7) m/s. The Mach number was calculated based on the angles of the attached oblique shocks formed near the 30° cone model. Calculated Mach number was repeatable from run to run and had small oscillations near the average value of 3.96 ± 0.03. Based on the simultaneously measured velocity and Mach number, the static temperature was calculated to be between (68.6 ± 0.3) K and (66.3 ± 0.3) K throughout the 400 ms test time, completely defining the thermodynamic state of the generated freestream flow. Full article
(This article belongs to the Special Issue High-Speed Processes in Continuous Media)
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20 pages, 2758 KB  
Article
A Dynamic Risk Assessment System for Expressway Lane-Changing: Integrating Bayesian Networks and Markov Chains Under High-Density Traffic
by Quantao Yang and Peikun Li
Systems 2026, 14(3), 306; https://doi.org/10.3390/systems14030306 (registering DOI) - 15 Mar 2026
Abstract
In high-density expressway environments, lane-changing (LC) maneuvers act as stochastic perturbations that compromise the hydrodynamic stability of traffic flow, leading to safety hazards and operational delays. While existing literature has extensively modeled crash severity in static complex environments (e.g., tunnels and mountainous terrains), [...] Read more.
In high-density expressway environments, lane-changing (LC) maneuvers act as stochastic perturbations that compromise the hydrodynamic stability of traffic flow, leading to safety hazards and operational delays. While existing literature has extensively modeled crash severity in static complex environments (e.g., tunnels and mountainous terrains), there remains a critical deficiency in quantifying the dynamic, systemic risks induced by LC maneuvers under saturation conditions. To address this gap, this study proposes a novel Systemic Risk Assessment Framework. First, a Hidden Markov Model (HMM) is employed to decode the latent state transitions of following vehicles, quantifying the systemic consequence of LC maneuvers as “operational delay” based on traffic wave theory. Second, a Bayesian Network (BN) is constructed to infer the causal probability of risk, integrating geometric proxies such as insertion angle with kinematic variables. Validated with real-world trajectory data, the model achieves high accuracy in identifying risk accumulation precursors. This research contributes to the field of transportation systems by shifting the risk paradigm from static collision prediction to dynamic system reliability analysis, offering theoretical support for Connected and Autonomous Vehicle (CAV) decision logic. Full article
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26 pages, 5614 KB  
Article
Experimental and Simulation Study on Liquid Entrainment in the Gas Cyclone–Liquid Jet Absorption Separator
by Liang Ma, Yang Su, Anlin Liu, Zhisheng Zhao, Junhong Wu, Xiaoxu Duan and Yuting Zhang
Processes 2026, 14(6), 929; https://doi.org/10.3390/pr14060929 (registering DOI) - 15 Mar 2026
Abstract
Liquid entrainment presents a significant challenge in wet flue gas desulfurization systems, leading to downstream corrosion and secondary pollution. This study systematically investigates the characteristics of liquid entrainment and pressure drop in a gas cyclone–liquid jet absorption separator (GLAS) through both experimental and [...] Read more.
Liquid entrainment presents a significant challenge in wet flue gas desulfurization systems, leading to downstream corrosion and secondary pollution. This study systematically investigates the characteristics of liquid entrainment and pressure drop in a gas cyclone–liquid jet absorption separator (GLAS) through both experimental and simulation methods. The effects of inlet gas flow rate (QG), absorbent flow rate (QL), overflow pipe insertion depth, and the presence of a liquid-guiding cover (LGC) were evaluated. The results revealed that liquid entrainment initially increased and then decreased with rising QG, QL, and insertion depth of overflow pipe, given the competing effects of turbulent jet breakup and centrifugal separation. To mitigate liquid entrainment, a novel LGC was introduced at the overflow pipe outlet. This intervention resulted in a reduction in liquid entrainment by up to 23.9%, achieved through physical interception and inertial impaction, while maintaining the difference value of pressure drop of less than 302 Pa. The numerical simulations further analyzed the gas–liquid two-phase distributions in GLAS under various operating conditions, with results that align well with experimental observations. These findings offer valuable insights for mitigating liquid entrainment in GLAS and optimizing its industrial applications. Full article
(This article belongs to the Section Separation Processes)
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15 pages, 4182 KB  
Article
Kernza in Wyoming: Perennial Grains for Vulnerable Lands
by Hannah R. Rodgers, Urszula Norton, Jay B. Norton and Linda T. A. van Diepen
Agronomy 2026, 16(6), 624; https://doi.org/10.3390/agronomy16060624 (registering DOI) - 15 Mar 2026
Abstract
Kernza®, a perennial grain crop created from intermediate wheatgrass (Thinopyrum intermedium), has the potential to mitigate soil degradation in semiarid croplands of the Northern High Plains. From 2021 to 2023, Kernza was grown for the first time in Wyoming [...] Read more.
Kernza®, a perennial grain crop created from intermediate wheatgrass (Thinopyrum intermedium), has the potential to mitigate soil degradation in semiarid croplands of the Northern High Plains. From 2021 to 2023, Kernza was grown for the first time in Wyoming and compared at the field scale to winter wheat–fallow and Conservation Reserve Program (CRP) systems on a working farm. We measured grain and forage yields, root biomass, and soil health and microbiology in bulk and rhizosphere soils. The first growing season was dry, and Kernza produced substantial forage (2995 kg ha−1) but insufficient grain for harvest. In the second year, Kernza produced 286 kg ha−1 of grain, compared to 2172 kg ha−1 for wheat. After two years, Kernza and wheat differed in rhizosphere—but not bulk—soil properties; Kernza rhizosphere organic matter, enzyme activities, and microbial communities were more similar to the rhizosphere of intermediate wheatgrass from CRP than to that of winter wheat. Kernza also produced nearly three times more root biomass and rhizosphere organic matter than winter wheat. Although Kernza remains a low-yielding crop in development, potential soil health benefits, a high market value, and the flexibility to harvest grain or forage may make it a viable option for this region. Full article
(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)
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11 pages, 1034 KB  
Article
Surface Plasmon Resonance Analysis for Evaluating ASO Targeting Structured RNA
by Tomohiro Shinozaki, Takuya Hasegawa, MST Tahmina Akter, Kazuyuki Kumagai, Youichi Suzuki and Taiichi Sakamoto
Methods Protoc. 2026, 9(2), 48; https://doi.org/10.3390/mps9020048 (registering DOI) - 15 Mar 2026
Abstract
Antisense oligonucleotides (ASOs) are nucleic acid therapeutics that regulate gene expression through sequence-specific hybridization with target RNA. Under physiological conditions, many target RNAs adopt higher-order structures, which can strongly influence ASO accessibility and binding behavior. Although UV melting analysis is widely used to [...] Read more.
Antisense oligonucleotides (ASOs) are nucleic acid therapeutics that regulate gene expression through sequence-specific hybridization with target RNA. Under physiological conditions, many target RNAs adopt higher-order structures, which can strongly influence ASO accessibility and binding behavior. Although UV melting analysis is widely used to evaluate the thermal stability of ASO/RNA duplexes, this approach does not adequately account for the structural features of target RNAs. In this study, we investigated the utility of surface plasmon resonance (SPR) analysis as an in vitro method to evaluate ASO binding while considering RNA structural constraints. Multiple ASOs were designed to target PRF84, an 84-nucleotide RNA motif that induces −1 programmed ribosomal frameshifting in HIV-1 Gag-pol expression. SPR analyses were performed to compare ASO interactions with complementary RNA fragments and with structurally folded PRF84. The results demonstrated that identical ASOs exhibited distinct binding behaviors depending on whether the target was a complementary RNA or PRF84, indicating that RNA structure significantly affects ASO binding. These findings suggest that SPR analysis enables the evaluation of ASO–RNA interactions taking structure into account, and may be a useful alternative approach to conventional UV melting analysis-based ASO screening. Full article
(This article belongs to the Special Issue Advanced Methods and Technologies in Drug Discovery)
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23 pages, 153696 KB  
Article
Fine Mapping of Sparse Populus euphratica Forests Based on GF-2 Satellite Imagery and Deep Learning Models
by Hao Li, Jiawei Zou, Qinyu Zhao, Suhong Liu and Qingdong Shi
Remote Sens. 2026, 18(6), 902; https://doi.org/10.3390/rs18060902 (registering DOI) - 15 Mar 2026
Abstract
Populus euphratica is a critical constructive species in arid desert regions, serving as a “natural barrier” for oasis protection. The sustainable management of Populus euphratica forests is directly related to regional ecological security, and the fine identification of sparse Populus euphratica forests is [...] Read more.
Populus euphratica is a critical constructive species in arid desert regions, serving as a “natural barrier” for oasis protection. The sustainable management of Populus euphratica forests is directly related to regional ecological security, and the fine identification of sparse Populus euphratica forests is essential for the conservation of natural Populus euphratica forests. Currently, most mapping studies on Populus euphratica distribution focus on the extraction of dense, contiguous Populus euphratica forests, with insufficient attention paid to the identification of sparse Populus euphratica forests. This study utilizes Gaofen-2 (GF-2) satellite imagery as the data source and takes a typical sparse Populus euphratica forests distribution area in the Tarim River Basin as the study site. It systematically evaluates the performance of nine mainstream deep learning models, including U-Net, DeepLabV3+, and SegFormer, in the task of sparse Populus euphratica forests identification. The results indicate that: (1) The false-color sample set, synthesized from near-infrared, red, and green bands, contributes to improved model accuracy. Compared to the true-color (red, green, blue bands) dataset, the average Intersection over Union (IoU) of the nine models shows a relative improvement of approximately 20%. (2) For the sparse Populus euphratica forests identification task based on the false-color dataset, four models—U-Net, U-Net++, MA-Net, and DeepLabV3+—exhibited excellent performance, with IoU exceeding 75%. (3) Using U-Net as the baseline model, this study integrated the max-pooling indices mechanism, atrous spatial pyramid pooling, and residual connection modules to construct a semantic segmentation network tailored for sparse Populus euphratica forests, named Sparse Populus euphratica Segmentation Network (SPS-Net). This model achieved an IoU of 80%, a relative improvement of approximately 6.3% over the baseline model, and demonstrated good stability in large-scale classification tests. The identification scheme for sparse Populus euphratica forests constructed using GF-2 imagery and deep learning models proposed in this study can provide effective technical support for the refined monitoring and protection of natural Populus euphratica forests. Full article
(This article belongs to the Special Issue Machine Learning for Applications in Agriculture and Vegetation Using Remote Sensing)
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16 pages, 2394 KB  
Article
A TSS-Compliant Ship Automatic Route-Planning Algorithm
by Ning Zhang, Fang He, Lubin Chang and Jingwen Zong
Algorithms 2026, 19(3), 220; https://doi.org/10.3390/a19030220 (registering DOI) - 15 Mar 2026
Abstract
Aiming at solving the problem that existing automatic route-planning algorithms fail to consider the navigation rules in traffic separation scheme (TSS) zones, this paper proposes a ship automatic route-planning algorithm that fully considers TSS-zone navigation constraints. First, a formalized TSS-zone automatic planning module [...] Read more.
Aiming at solving the problem that existing automatic route-planning algorithms fail to consider the navigation rules in traffic separation scheme (TSS) zones, this paper proposes a ship automatic route-planning algorithm that fully considers TSS-zone navigation constraints. First, a formalized TSS-zone automatic planning module with a quadrilateral decomposition mechanism is designed, which realizes standardized processing of regular TSS zones and completes TSS-compliant route replanning through three core steps: invalid waypoint deletion, TSS-zone-traversal-order determination, and constrained route replanning. Second, a particle swarm optimization (PSO) algorithm is selected as the base global route-planning algorithm via a multi-algorithm comparative framework, considering the requirements of optimality, stability and real-time performance for ship-navigation. The TSS module is deeply integrated with the PSO algorithm, forming a unified global route-planning algorithm that balances TSS compliance and route optimality. Comparative experiments with four mainstream swarm intelligence algorithms (PSO/SSA/IVY/GOA) show that the PSO algorithm outperforms the others in terms of route length, stability and comprehensive efficiency, with an optimal route length of 57.71 and a low standard deviation of 3.42. Furthermore, the proposed algorithm is validated by real nautical chart data of Bohai Bay under single- and double-TSS-zone scenarios. The results indicate that the algorithm can stably generate TSS-compliant routes, with only a small increase in route length (0.6% and 4.4% for a single TSS zone, 1.1% and 1.8% for two TSS zones) and computational time and can automatically adjust the traversal strategy according to the start–end point settings. The designed TSS module has good scalability and can be integrated with other optimization algorithms, providing a feasible technical solution for an intelligent ship navigation system to realize automatic and compliant route planning in TSS zones with dense traffic. Full article
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33 pages, 4501 KB  
Review
Water–Energy–Carbon Nexus: Biochar-Based Catalysts via Waste Valorization for Sustainable Catalysis
by Hossam A. Nabwey and Maha A. Tony
Catalysts 2026, 16(3), 267; https://doi.org/10.3390/catal16030267 (registering DOI) - 15 Mar 2026
Abstract
The water–energy–carbon (WEC) nexus provides a systems framework for minimizing trade-offs among water security, energy reliability, and carbon mitigation. Within this framework, waste-derived biochar catalysts offer a circular pathway that simultaneously valorizes residues, reduces process energy demand, and supports carbon management through stable [...] Read more.
The water–energy–carbon (WEC) nexus provides a systems framework for minimizing trade-offs among water security, energy reliability, and carbon mitigation. Within this framework, waste-derived biochar catalysts offer a circular pathway that simultaneously valorizes residues, reduces process energy demand, and supports carbon management through stable carbon storage and catalytic co-benefits. This review consolidates recent advances in biochar-based catalysts engineered from agricultural, industrial, municipal, and sludge-derived wastes, highlighting how feedstock selection and thermochemical processing, namely pyrolysis, hydrothermal carbonization (HTC), and torrefaction, as well as activation and post-modification (heteroatom doping and metal/metal-oxide incorporation) govern structure–property–performance relationships. The synthesized catalysts have been widely applied in water and wastewater treatment, including adsorption–advanced oxidation process (AOP) hybrids, Fenton-like systems, peroxydisulfate/persulfate (PS) and peroxymonosulfate (PMS) activation, photocatalysis, and the removal of emerging contaminants. They have also demonstrated strong potential in energy conversion processes such as the hydrogen evolution reaction (HER), oxygen reduction and evolution reactions (ORR/OER), biomass reforming, and carbon dioxide (CO2) conversion. In addition, these materials contribute to carbon management through sequestration pathways, avoided emissions, and life cycle assessment (LCA)-based sustainability evaluations. Finally, we propose a WEC-aligned design roadmap integrating techno-economic analysis (TEA), LCA, and scale-up considerations to guide next-generation biochar catalysts toward robust performance in real matrices and deployment-ready systems. Full article
(This article belongs to the Special Issue Catalysis and Sustainable Green Chemistry)
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18 pages, 11105 KB  
Article
The Effects of Compound Chinese Herbal Medicine on the Growth and Digestive and Immune Systems of Megalobrama amblycephala
by Xijing Ye, Yunsheng Zhang, Hu Xia, Huangjie Fan, Jiahui Hu, Yanan Gong, Rurou Fu, Fuyan Chen and Liangguo Liu
Animals 2026, 16(6), 925; https://doi.org/10.3390/ani16060925 (registering DOI) - 15 Mar 2026
Abstract
Chinese herbal medicine is rich in active ingredients that can promote growth and enhance immune function. In this study, Lycium barbarum, Panax ginseng, Astragalus membranaceus and Phragmitis rhizoma were crushed and mixed to prepare a compound Chinese herbal medicine. The basic [...] Read more.
Chinese herbal medicine is rich in active ingredients that can promote growth and enhance immune function. In this study, Lycium barbarum, Panax ginseng, Astragalus membranaceus and Phragmitis rhizoma were crushed and mixed to prepare a compound Chinese herbal medicine. The basic feed of Megalobrama amblycephala was supplemented with 0 (control group), 1% (T1), 2% (T2) and 4% (T3) of this compound medicine. After raising for 90 days, in the T1 and T2 experimental groups, the length and width of intestinal villi and the activities of amylase, trypsin and lipase in the intestine were significantly higher than those in the control group. The weight gain rate and specific growth rates were highest and the feed coefficient was lowest in the T2 experimental group. In the control group, a large number of dilated hepatic sinusoids were detected, while this number significantly decreased in the T1 experimental group and they were not detected at all in the T2 and T3 experimental groups. The spleen and liver body indices were highest in the T2 experimental group. In all experimental groups, the Lys content and the activities of T-SOD, CAT, ACP, AKP and GSH-PX in serum were significantly higher than those of the control group. The expression of IgM, C3, TNF-ɑ and IL-1β in the head kidney; C3, TNF-ɑ and IL-1β in the spleen; C3 and IL-1β in the gills; IgM, C3 and IL-1β in liver; and IL-1β in the intestine was highest in the T2 experimental group. After challenge with Aeromonas hydrophila, the cumulative mortality rate of M. amblycephala was lowest in the T2 experimental group. The results of this study indicated that this compound Chinese herbal medicine could significantly enhance immunity, increase the activity of intestinal digestion-related enzymes and promote the growth of M. amblycephala. The appropriate addition amount of this compound Chinese herbal medicine in the basic feed of M. amblycephala was 2%. Full article
(This article belongs to the Special Issue Advances in Fish Immunology: Novel Strategies for Disease Prevention)
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14 pages, 2689 KB  
Article
The Infra-Bullar Groove: Assessing a Novel Surgical Landmark for Identifying the Natural Maxillary Ostium
by Jameel Ghantous, Ayalon Hadar, Itay Chen, Chanan Shaul and Boaz Forer
Life 2026, 16(3), 475; https://doi.org/10.3390/life16030475 (registering DOI) - 15 Mar 2026
Abstract
Functional endoscopic sinus surgery (FESS) is the gold-standard surgical treatment for chronic rhinosinusitis (CRS) not responding to appropriate medical therapy. Identifying the natural maxillary ostium (NMO) during FESS is often challenging due to the lack of definitive landmarks. To aid in the identification [...] Read more.
Functional endoscopic sinus surgery (FESS) is the gold-standard surgical treatment for chronic rhinosinusitis (CRS) not responding to appropriate medical therapy. Identifying the natural maxillary ostium (NMO) during FESS is often challenging due to the lack of definitive landmarks. To aid in the identification of the NMO, we describe and assess the feasibility of using a new surgical landmark, the infra-bullar groove (IBG), and evaluate its visibility and reproducibility during FESS. Methods: Video recordings of 41 maxillary antrostomy procedures in patients with varying severity of CRS were reviewed. Surgeons of different experience levels assessed IBG visibility and its termination at the NMO. Results: In video recordings where the ethmoid bulla was preserved during uncinectomy, the IBG and its connection to the NMO were successfully identified by all reviewers in 100% of analyzable cases. The mean time to IBG identification did not significantly differ among surgeons. The IBG was consistently more pronounced in cases with well-pneumatized bullae. Conclusions: Under controlled surgical conditions where the ethmoid bulla is preserved during uncinectomy, the IBG demonstrates high visibility and reproducibility for locating the NMO. However, further prospective studies are needed to establish its real-world utility and impact on surgical outcomes. Full article
(This article belongs to the Section Medical Research)
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14 pages, 3531 KB  
Article
Full-Field Assessment of Damage Evolution in Compressed Masonry with Bed Joint Reinforcement Using Digital Image Correlation
by Artur Piekarczuk, Przemysław Więch and Jacek Głodkiewicz
Materials 2026, 19(6), 1145; https://doi.org/10.3390/ma19061145 (registering DOI) - 15 Mar 2026
Abstract
This experimental study investigates the influence of selected bed joint reinforcement systems on the evolution of damage and crack development in masonry elements subjected to axial compression. Autoclaved aerated concrete masonry samples reinforced with steel truss reinforcement, unidirectional carbon fibre mesh and steel [...] Read more.
This experimental study investigates the influence of selected bed joint reinforcement systems on the evolution of damage and crack development in masonry elements subjected to axial compression. Autoclaved aerated concrete masonry samples reinforced with steel truss reinforcement, unidirectional carbon fibre mesh and steel cords embedded in a fibreglass matrix were tested and compared to an unreinforced reference specimen. Full-field deformation and strain localisation were monitored using digital image correlation (DIC). The results indicate that bed joint reinforcement does not lead to a measurable increase in compressive load-bearing capacity, as differences in ultimate load remain within experimental uncertainty. However, clear differences in the evolution and spatial distribution of damage were observed. Steel truss reinforcement promoted strain redistribution and delayed localisation of tensile strains, while the remaining reinforcement systems exhibited only limited influence on crack morphology. The findings confirm that bed joint reinforcement in compressed masonry should be classified as a nonstructural solution and demonstrate the diagnostic value of full-field deformation monitoring for assessing damage evolution and crack control in masonry structures. Full article
(This article belongs to the Special Issue Advances in Assessment and Health Monitoring of Construction Materials)
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17 pages, 922 KB  
Article
Candidemia in Southern Poland (2017–2022): Multicenter Analysis of Species Distribution and Antifungal Susceptibility
by Magdalena Namysł, Magdalena Skóra, Monika Pomorska-Wesołowska, Małgorzata Romanik, Wioletta Świątek-Kwapniewska, Piotr Serwacki, Iwona Pawłowska, Aldona Olechowska-Jarząb and Jadwiga Wójkowska-Mach
J. Fungi 2026, 12(3), 212; https://doi.org/10.3390/jof12030212 (registering DOI) - 15 Mar 2026
Abstract
Candida fungi are among the most common human fungal pathogens and invasive candidiasis is one of the predominant invasive mycoses that mainly affects hospitalized patients with suppression of the immunological system and breaches in skin or mucosal barriers. Rapid diagnosis and implementation of [...] Read more.
Candida fungi are among the most common human fungal pathogens and invasive candidiasis is one of the predominant invasive mycoses that mainly affects hospitalized patients with suppression of the immunological system and breaches in skin or mucosal barriers. Rapid diagnosis and implementation of appropriate antifungal treatment are key to achieving recovery. In recent years, attention has been drawn to the increasing significance of Candida species other than C. albicans, in particular C. auris and fluconazole-resistant C. parapsilosis. The aim of this work was to present the species spectrum and drug susceptibility of 570 Candida strains isolated from candidemia cases diagnosed in patients hospitalized in southern Poland in the period 2017–2022. The results of Candida-positive blood cultures obtained from five hospitals were analyzed. C. albicans was the most common species, accounting for 42.6% of all strains, followed by Nakaseomyces glabratus (formerly C. glabrata) and C. parapsilosis complex—22.1% and 18.8%, respectively. No C. auris was found. Fluconazole resistance was found in 4.9% of C. albicans strains, 34.7% of N. glabratus strains, and 8.7% of C. parapsilosis complex strains. Full article
(This article belongs to the Section Fungal Pathogenesis and Disease Control)
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21 pages, 1824 KB  
Article
An Optimized Pedestrian Inertial Navigation Method Based on the Birkhoff Pseudospectral Method
by Zihong Zhang, Dangjun Zhao and Di Tian
Sensors 2026, 26(6), 1850; https://doi.org/10.3390/s26061850 (registering DOI) - 15 Mar 2026
Abstract
Pedestrian inertial navigation is a pivotal technology for achieving seamless indoor and outdoor positioning. Traditional methods based on the Extended Kalman Filter (EKF) suffer from cumulative errors induced by inertial measurement unit (IMU) noise, which severely degrade the accuracy of pedestrian trajectory [...] Read more.
Pedestrian inertial navigation is a pivotal technology for achieving seamless indoor and outdoor positioning. Traditional methods based on the Extended Kalman Filter (EKF) suffer from cumulative errors induced by inertial measurement unit (IMU) noise, which severely degrade the accuracy of pedestrian trajectory estimation over long durations. To address this critical limitation, a post-processing trajectory optimization approach for pedestrian inertial navigation based on the Birkhoff pseudospectral method is proposed in this paper. Leveraging the initial attitude and position estimates derived from the Zero-Velocity Update (ZUPT) technique and the EKF framework, the proposed method first parameterizes continuous-time acceleration measurements by adopting Chebyshev nodes as collocation points, and then formulates and solves the trajectory optimization problem via a Birkhoff pseudospectral framework, which effectively suppresses noise interference from the IMU accelerometer. Simulation experiments validate the superior noise suppression capability of the proposed algorithm. Furthermore, physical experiments conducted with a foot-mounted IMU demonstrate that the final position error is reduced by approximately 90% in comparison with the traditional EKF-based method. Full article
(This article belongs to the Section Navigation and Positioning)
30 pages, 3776 KB  
Article
Divergent Fates of Kidney-Resident Polyomaviruses: Stable Shedding Versus Near-Silent Persistence
by Anik Mojumder, Kimin W. Nguyen and Christopher S. Sullivan
Viruses 2026, 18(3), 359; https://doi.org/10.3390/v18030359 (registering DOI) - 15 Mar 2026
Abstract
Polyomaviruses establish long-term infection in the kidney and are intermittently shed in urine. However, the relationship between kidney-resident viral genomes and urinary shedding during persistent infection remains poorly defined. Using a genetically barcoded murine polyomavirus library, we tracked thousands of viral lineages in [...] Read more.
Polyomaviruses establish long-term infection in the kidney and are intermittently shed in urine. However, the relationship between kidney-resident viral genomes and urinary shedding during persistent infection remains poorly defined. Using a genetically barcoded murine polyomavirus library, we tracked thousands of viral lineages in vivo by pairing longitudinal urine sampling with endpoint barcode sequencing of kidney tissue in four mice. Across all animals, kidney infection consistently resolved into two stable viral populations, with near-silent persistence as the dominant fate. Most kidney-resident barcodes were never detected in late urine at late stages of infection, even though many reached substantial abundance within the kidney, demonstrating that kidney viral genome levels alone do not predict urinary shedding. In contrast, only a small minority of kidney barcodes contributed disproportionately to urine virus output at late timepoints, and these barcodes exhibited stable longitudinal behavior, with repeated detection in urine over time and markedly higher peak urine abundance than late non-shed or random barcode controls. Shedding behavior was not explained by input virus stock abundance, barcode sequence features, predicted miRNA targeting, or ongoing reseeding from blood or other tissues. Instead, barcodes that ultimately dominated late urine already showed elevated urine detection early after infection, indicating that shedding fate is established early and maintained throughout persistent infection. Together, these findings reveal that persistent kidney infection is a structured reservoir composed of a large population of deeply restricted viral genomes and a smaller, stable subset that repeatedly produces urine-detectable viruses, with concurrent smoldering infections and latency-like restriction representing one possible model to explain the sharply different probabilities of shedding among kidney-resident genomes. Full article
(This article belongs to the Special Issue Polyomavirus)
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19 pages, 1660 KB  
Article
Stiffness Control Process for Supports with Flexible Elements of Different Technical Properties Used in Mechanical and Mechatronic Systems
by Audrius Čereška and Andrius Terebas
Processes 2026, 14(6), 933; https://doi.org/10.3390/pr14060933 (registering DOI) - 15 Mar 2026
Abstract
A support is a machine element that transmits loads to the base or other structures. A simple support is designed to withstand forces acting in the longitudinal direction, and a flexible support is designed to withstand forces in both longitudinal and transverse directions. [...] Read more.
A support is a machine element that transmits loads to the base or other structures. A simple support is designed to withstand forces acting in the longitudinal direction, and a flexible support is designed to withstand forces in both longitudinal and transverse directions. The possibilities for the use of flexible supports are very wide. In precision mechanics, flexible supports are used in positioning systems, micropositioning systems, vibration damping systems, as well as in fastening applications requiring adjustment and other structural configurations. The main problem of flexible supports is ensuring stability. This work examines the dependence of the stiffness of supports used in mechanical and mechatronic systems on the material and dimensions of the flexible element. A theoretical analysis of the stiffness of flexible supports, finite element method (FEM) modeling, and experimental stiffness research were performed. A special stand was manufactured for experimental research. A research methodology was developed, according to which experimental research was carried out. After theoretical, FEM and experimental research, the results obtained were compared and conclusions were formulated. The obtained data can be practically used in the research and design of new flexible supports that ensure desired stability, as well as in the improvement of existing support structures. Full article
(This article belongs to the Special Issue Intelligent Control and Diagnostic Processes in Mechanical and Mechatronic Systems)
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36 pages, 5742 KB  
Article
EEDC: Energy-Efficient Distance-Controlled Clustering for Bottleneck Avoidance in Wireless Sensor Networks
by Ahmad Abuashour, Yahia Jazyah and Naser Zaeri
IoT 2026, 7(1), 29; https://doi.org/10.3390/iot7010029 (registering DOI) - 15 Mar 2026
Abstract
Wireless Sensor Networks (WSNs) commonly employ clustering to improve scalability and energy efficiency; however, cluster heads (CHs) located near the base station (BS) often suffer from excessive relay traffic, leading to rapid energy depletion and reduced network lifetime. This article proposes an Energy-Efficient [...] Read more.
Wireless Sensor Networks (WSNs) commonly employ clustering to improve scalability and energy efficiency; however, cluster heads (CHs) located near the base station (BS) often suffer from excessive relay traffic, leading to rapid energy depletion and reduced network lifetime. This article proposes an Energy-Efficient Distance-Controlled Clustering (EEDC) scheme that adjusts CH density and transmission power according to each node’s distance from the BS. In EEDC, a higher number of CHs is deployed near the BS to balance forwarding loads, while fewer CHs are selected in distant regions to conserve energy. Additionally, CHs adapt their transmission power to enable distance-proportional communication. A mathematical model is developed to analyze the relationship between CH distribution, transmission power, and overall energy consumption. Performance evaluation is conducted through simulations and compared with LEACH, HEED, DEEC, SEP, and EECS. The results show that EEDC improves the stability period by up to 42%, extends network lifetime by 23%, increases average residual energy by 13–29%, enhances throughput by 16–44%, and achieves 23–61% higher packet delivery efficiency. Moreover, cumulative CH energy consumption is reduced by 5–21%, leading to more balanced energy distribution. These findings indicate that distance-controlled CH selection and adaptive transmission power effectively alleviate the BS energy bottleneck and enhance the energy efficiency and operational longevity of clustered WSNs. Full article
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16 pages, 3754 KB  
Article
Correlation Between Microstructural Evolution and Magnetocaloric Response in Suction-Cast MnCoGeB0.02 Alloy
by Rafael Suárez, Israel Betancourt, Jesús Arenas, Marco Camacho, Israel Núñez-Tapia and Jonathan Zamora
Materials 2026, 19(6), 1144; https://doi.org/10.3390/ma19061144 (registering DOI) - 15 Mar 2026
Abstract
Magnetic and structural transitions can interact significantly, leading to an enhanced magnetocaloric effect (MCE), also known as the giant or colossal effect. In this study, we investigate how subtle microstructural changes impact the magnetocaloric behavior of a MnCoGeB0.02 alloy fabricated via suction [...] Read more.
Magnetic and structural transitions can interact significantly, leading to an enhanced magnetocaloric effect (MCE), also known as the giant or colossal effect. In this study, we investigate how subtle microstructural changes impact the magnetocaloric behavior of a MnCoGeB0.02 alloy fabricated via suction casting. We obtained conical samples and analyzed them to understand their structure and magnetic properties. X-ray diffraction patterns revealed a coexistence of a metastable high-temperature hexagonal phase and a stable low-temperature orthorhombic phase in different regions of each cone. The presence and proportion of these phases determine the degree of magneto-structural coupling, which in turn influences the MCE. The magnetic entropy change (|ΔSPeak|) varied notably among the samples, ranging from 12.3 to 6 Jkg−1K−1 under a magnetic field change of Δµ0H = 5.0 T. These findings demonstrate that even minor microstructural changes caused by differences in solidification during suction casting can lead to noticeable variations in magnetocaloric performance. Understanding and controlling these microstructural details is vital for optimizing the functional behavior of MnCoGe-based materials. Full article
(This article belongs to the Special Issue Modern Technologies in Metallurgical Manufacturing)
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11 pages, 621 KB  
Article
Synthesis and Structures of Ru(II)-p-Cymene Sandwich Complexes with Electron-Withdrawing Cyclopentadienyl Ligands
by Uttam R. Pokharel, Sean Parkin and John P. Selegue
Crystals 2026, 16(3), 201; https://doi.org/10.3390/cryst16030201 (registering DOI) - 15 Mar 2026
Abstract
A modular synthetic route has been developed to prepare a new series of cationic ruthenium(II) complexes with electron-withdrawing 1,2-diacylcyclopentadienyl ligands. The 2-acyl-6-hydroxyfulvenes were synthesized from cyclopentadienide and acyl chlorides and converted to Tl(I) cyclopentadienyl salts using Tl2SO4/KOH. Transmetalation with [...] Read more.
A modular synthetic route has been developed to prepare a new series of cationic ruthenium(II) complexes with electron-withdrawing 1,2-diacylcyclopentadienyl ligands. The 2-acyl-6-hydroxyfulvenes were synthesized from cyclopentadienide and acyl chlorides and converted to Tl(I) cyclopentadienyl salts using Tl2SO4/KOH. Transmetalation with [Ru(η6-p-cymene)(μ-Cl)Cl]2 followed by PF6− metathesis gives the complexes [Ru{η5-1,2-C5H3(CO–R)2}(η6-p-cymene)][PF6] (R = t-Bu, p-Tol, p-ClC6H4, p-IC6H4) in moderate to high yields. The new compounds were characterized by NMR and IR spectroscopy; mass spectrometry and elemental analysis were performed where applicable. X-ray analysis of one of the complexes confirms that electron-deficient Cp ligands retain η5-coordination and structural planarity within Ru(II)–arene sandwich architectures, highlighting their potential utility in electronically tunable organometallic frameworks. Full article
(This article belongs to the Special Issue Transition Metal Complexes with Heterocyclic Ligands: Structural Insights, Biological Potential, and Computational Perspectives)
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32 pages, 10642 KB  
Article
Dynamic Beam Control-Based Neighbor Discovery Protocol for Underwater Acoustic Networks with Multi-Parallel Transceiver
by Jianjun Zhang, Lin Zhou, Haijun Wang, Zhiyong Zeng and Qing Hu
Sensors 2026, 26(6), 1855; https://doi.org/10.3390/s26061855 (registering DOI) - 15 Mar 2026
Abstract
Neighbor discovery in underwater acoustic networks (UANs) faces challenges such as high propagation delay and limited spectrum resources. This study proposes a dynamic beam control-based multi-parallel transceiver neighbor discovery protocol (DBCB), which improves node discovery efficiency by dynamically matching transmission beams and optimizing [...] Read more.
Neighbor discovery in underwater acoustic networks (UANs) faces challenges such as high propagation delay and limited spectrum resources. This study proposes a dynamic beam control-based multi-parallel transceiver neighbor discovery protocol (DBCB), which improves node discovery efficiency by dynamically matching transmission beams and optimizing spatiotemporal frequency resource allocation. During node initialization, the master node broadcasts omnidirectionally to quickly capture coarse-grained neighbor parameters. After obtaining these parameters, the master node dynamically allocates orthogonal frequency bands for directional multi-beam validation and optimizes beam alignment, resource allocation, and topology stability through real-time feedback. The protocol adaptively optimizes transmission power and continues the discovery task, while nodes that remain undiscovered for extended periods automatically adjust their receiving gain. The adaptive power control mechanism adjusts the transmission power based on node distance and azimuth, enabling the protocol to maintain low power consumption and enhance interference resilience. Simulation results show that the DBCB protocol outperforms similar neighbor discovery protocols based on directional transmission-reception (DTR) and random two-way (RTW) mechanisms, with improvements of 7.84% and 28.17% in average discovery rate, and reductions of 28.13% and 59.06% in average discovery delay, respectively. The anechoic tank experiment demonstrates that multi-beam parallel transmission effectively improves underwater node discovery efficiency, with simulation results aligning with experimental data, confirming the stability and high efficiency of the system. Full article
(This article belongs to the Section Sensor Networks)
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28 pages, 851 KB  
Article
AI-Enabled Remote Sensing Assessment of Cultivated Land Quality and Sustainability Under Climate Stress: Evidence from Saudi Arabia
by Amina Hamdouni
Resources 2026, 15(3), 44; https://doi.org/10.3390/resources15030044 (registering DOI) - 15 Mar 2026
Abstract
This study investigates the dynamic and causal effects of climate stress and Artificial Intelligence-enabled agricultural monitoring on cultivated land quality, productivity, and sustainability in Saudi Arabia. Using a balanced panel of region–crop observations covering 13 administrative regions and six major crops over the [...] Read more.
This study investigates the dynamic and causal effects of climate stress and Artificial Intelligence-enabled agricultural monitoring on cultivated land quality, productivity, and sustainability in Saudi Arabia. Using a balanced panel of region–crop observations covering 13 administrative regions and six major crops over the period 2010–2024, the analysis integrates high-resolution climate variables with remote sensing-based indicators, including the Normalized Difference Vegetation Index, Enhanced Vegetation Index, Net Primary Productivity, Water-Use Efficiency, and crop water productivity. A comprehensive econometric framework combining the System Generalized Method of Moments, Difference-in-Differences, and event-study approaches is employed to address persistence, endogeneity, and causal identification. The results show that water availability—captured by soil moisture and precipitation—significantly enhances cultivated land outcomes (coefficients ≈ 0.05–0.11), while heat stress and wind speed exert strong negative effects (coefficients ≈ −0.04 to −0.12), highlighting the vulnerability of arid agricultural systems. Artificial Intelligence-enabled monitoring and smart irrigation adoption consistently improve land quality and productivity, with the largest gains observed in water-use efficiency and crop water productivity. Artificial Intelligence adoption increases water-use efficiency and crop water productivity by approximately 8–10%, while heat stress reduces vegetation indicators by about 9–12%. Event-study evidence confirms that these effects emerge after adoption and persist over time, supporting a causal interpretation. Overall, the findings demonstrate that AI technologies mitigate climate stress primarily through improved water management and adaptive decision-making. The study provides policy-relevant insights aligned with Saudi Vision 2030, emphasizing digital agriculture as a key instrument for sustainable cultivated land governance, climate adaptation, and food security in water-scarce environments. Full article
(This article belongs to the Special Issue Cultivated Land Resources: Protection, Transformation and Sustainable Governance)
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17 pages, 2515 KB  
Article
Temperature Evolution of Crystal Structure, Ferroelectricity and Ionic Conductivity of Ca9La(VO4)7
by Oksana V. Baryshnikova, Bogdan I. Lazoryak, Vladimir A. Morozov, Sergey Yu. Stefanovich, Alexander V. Mosunov, Eldar M. Gallyamov, Sergey M. Aksenov and Dina V. Deyneko
Molecules 2026, 31(6), 984; https://doi.org/10.3390/molecules31060984 (registering DOI) - 15 Mar 2026
Abstract
The properties of a Ca9La(VO4)7 single crystal were studied using dielectric spectroscopy and second-harmonic generation. The crystal structure of Ca9La(VO4)7 grown using the Czochralski technique was refined using single-crystal data. The distribution of [...] Read more.
The properties of a Ca9La(VO4)7 single crystal were studied using dielectric spectroscopy and second-harmonic generation. The crystal structure of Ca9La(VO4)7 grown using the Czochralski technique was refined using single-crystal data. The distribution of Ca2+ and La3+ cations over structural positions was determined. The crystal structure refinement results were compared with those obtained previously from powder X-ray diffraction data. It was shown that the refinement carried out using two different data sets leads to approximately the same results for the distances in the polyhedra, but their distortion is significantly less in the case of using single-crystal data for calculation. Dielectric properties and conductivity measurements were performed on polished single-crystal wafers cut parallel and perpendicular to the c axis. Second-harmonic generation and dielectric temperature measurements revealed the presence of a reversible ferroelectric first-order phase transition at about 1224 K from the ferroelectric β-phase (space group R3c) to the paraelectric β′-phase. The ferroelectric–paraelectric phase transition is accompanied by a complex structural rearrangement, including a 60° rotation of the V1O4 tetrahedron, as well as slight displacements of the Ca2+ and La3+ cations. It has been shown that the conductivity differs only slightly along the polar axis and perpendicular to it. Above the phase transition temperature, the activation energy of the conductivity is the same for all directions, Ea~1.2 eV. The influence of composition on the phase transition temperature and the formation of ferroelectric and nonlinear optical properties is discussed. Full article
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27 pages, 3606 KB  
Article
Inverse Calibration of Confinement and Softening in RC Beam-Column Joints for Improved DSFM Predictions
by Mehmet Ozan Yılmaz
Buildings 2026, 16(6), 1157; https://doi.org/10.3390/buildings16061157 (registering DOI) - 15 Mar 2026
Abstract
Standard compatibility-based truss models, including the Disturbed Stress Field Model (DSFM), often underestimate the shear strength and deformation capacity of reinforced-concrete (RC) beam-column joints. This study investigates the origin of this bias through a systematic inverse identification framework and derives joint-core constitutive relationships [...] Read more.
Standard compatibility-based truss models, including the Disturbed Stress Field Model (DSFM), often underestimate the shear strength and deformation capacity of reinforced-concrete (RC) beam-column joints. This study investigates the origin of this bias through a systematic inverse identification framework and derives joint-core constitutive relationships tailored to the highly confined, nonuniform stress states of joints. Inverse analyses show that improving confinement effectiveness alone leads to unrealistic parameter saturation and cannot reproduce the measured energy absorption, indicating that conventional compression-softening formulations remain excessively punitive for joint cores. When confinement activation and softening are identified simultaneously, a clear mechanism shift emerges: unlike panel-based theories that link softening to tensile-cracking measures (principal strain ratio), joint softening is overwhelmingly governed by the principal compressive strain, consistent with crushing-dominated damage accumulation. Based on these trends, unified power-law expressions are proposed for both passive confinement activation and damage-induced softening as functions of principal compressive strain only, adhering to a parsimonious formulation without auxiliary variables such as concrete strength or reinforcement ratio (R2≈0.89). The model is validated on an independent database of 113 specimens, including high-strength concrete and exterior joints, eliminating the systematic conservatism of the standard DSFM and improving the mean experimental-to-predicted strength ratio from 0.85 to 1.01 while reducing the coefficient of variation from 34.5% to 13%. The proposed formulation supports more reliable joint shear backbone predictions for seismic assessment of RC frame buildings. Full article
(This article belongs to the Section Building Structures)
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19 pages, 443 KB  
Article
Long-Term Effects of a Multidisciplinary School-Based Intervention on Children’s Healthy Habits: A 1-Year Follow-Up
by Fioretta Silvestri, Davide Curzi, Giovanna Zimatore, Valerio Bonavolontà, Silvia Migliaccio, Ludovica Cardinali, Carlo Baldari, Laura Guidetti and Maria Chiara Gallotta
Nutrients 2026, 18(6), 926; https://doi.org/10.3390/nu18060926 (registering DOI) - 15 Mar 2026
Abstract
Background: Multidisciplinary school-based interventions are considered a key strategy for promoting healthy lifestyles and preventing childhood obesity. However, evidence on the persistence of their effects beyond the intervention period remains limited. Objectives: This study investigated the long-term effect of different one-year combined physical [...] Read more.
Background: Multidisciplinary school-based interventions are considered a key strategy for promoting healthy lifestyles and preventing childhood obesity. However, evidence on the persistence of their effects beyond the intervention period remains limited. Objectives: This study investigated the long-term effect of different one-year combined physical education and nutritional interventions on children’s lifestyles. Methods: One hundred forty-five primary school children (8–10 years of age) were randomly assigned to a traditional physical education group, a coordinative physical education group, or a control group. Anthropometric variables, physical activity levels, sedentary time, and eating habits were assessed at baseline, after a 1-school-year intervention period, at 6-month follow-up, and at 1-year follow-up. An ANOVA test for repeated measures was performed to detect the among-group difference in all measured variables from baseline to 1-year follow-up over the three time points. Results: Physical activity levels increased significantly in both intervention groups and remained elevated at follow-up, whereas no meaningful changes were observed in the control group. Fat mass percentage increased over time in the traditional and control groups but remained stable in the coordinative group. Overall, consumption of healthy foods increased and intake of unhealthy foods decreased across time, with more pronounced improvements in children participating in physical education programs. Conclusions: A combined school-based nutritional and physical education intervention can produce sustained improvements in children’s lifestyle behaviours. Coordinative physical education may offer additional benefits in preventing unfavourable changes in body composition during late childhood. Full article
(This article belongs to the Section Nutrition and Public Health)
28 pages, 3784 KB  
Article
FPGA-Based Front-End Low-Light Enhancement for Deterministic Vision-Only Driving Perception
by Fuwen Xie, Hanhui Jing, Zhiting Lu, Shaoxin Ju, Bochun Peng, Tianle Xie, Linfang Yang, Wenman Han, Zhizhong Wang and Gaole Sai
Electronics 2026, 15(6), 1224; https://doi.org/10.3390/electronics15061224 (registering DOI) - 15 Mar 2026
Abstract
Vision-only driving perception systems are highly sensitive to illumination variations, particularly under low-light conditions where reduced contrast and structural degradation impair detection and segmentation accuracy. Rather than treating enhancement as a post-processing step, this work investigates the system-level impact of relocating low-light enhancement [...] Read more.
Vision-only driving perception systems are highly sensitive to illumination variations, particularly under low-light conditions where reduced contrast and structural degradation impair detection and segmentation accuracy. Rather than treating enhancement as a post-processing step, this work investigates the system-level impact of relocating low-light enhancement to the FPGA-based front end within a heterogeneous FPGA–ARM architecture. A hardware-accelerated visual pipeline is designed to perform color space conversion, fixed-point convolutional enhancement, and multi-channel fusion prior to high-level perception on the ARM processor. Experimental results demonstrate that the proposed FPGA-based front-end enhancement introduces only 13 ms of additional processing latency, which executes in parallel with the preceding frame’s neural network inference and therefore imposes zero net overhead on the end-to-end pipeline. In contrast, an equivalent software-based back-end enhancement approach would add its full processing time serially to the inference stage, increasing total system latency proportionally. The system achieves a sustained throughput of 58 fps while supporting real-time multi-task perception including lane detection (YOLOPv2, 539 ms per frame), object detection and emergency braking (YOLOv5, 432 ms per frame), and hardware-level multi-camera synchronization. Full article
(This article belongs to the Special Issue Hardware and Software Co-Design in Intelligent Systems)
40 pages, 6965 KB  
Review
Application of Transition Metal Dichalcogenides in Electrocatalytic Hydrogen Evolution Reaction
by Yan Liu, Yanchun Li, Yutong Chu, Baoyi Yang, Lan Ma, Li Du, Lixin Chen, Hongli Wang and Yaru Pei
Catalysts 2026, 16(3), 266; https://doi.org/10.3390/catal16030266 (registering DOI) - 15 Mar 2026
Abstract
As a cornerstone of sustainable hydrogen generation, the hydrogen evolution reaction (HER) demands efficient, earth-abundant electrocatalysts to replace costly platinum benchmarks. Two-dimensional transition metal dichalcogenides (2D-TMDs) represent a highly promising class of non-precious materials for this application. This review provides a comprehensive analysis [...] Read more.
As a cornerstone of sustainable hydrogen generation, the hydrogen evolution reaction (HER) demands efficient, earth-abundant electrocatalysts to replace costly platinum benchmarks. Two-dimensional transition metal dichalcogenides (2D-TMDs) represent a highly promising class of non-precious materials for this application. This review provides a comprehensive analysis of recent progress in TMD-based HER catalysis. It begins by elucidating the intrinsic structural properties that underpin their catalytic potential, followed by a summary of key synthesis routes and characterization techniques. The central focus is on strategic engineering approaches to optimize TMD performance. Finally, we discuss persisting challenges and propose future research directions aimed at scalable production, advanced operando studies, and the design of bifunctional TMD catalysts for integrated water-splitting systems. Full article
(This article belongs to the Special Issue Theoretical and Experimental Research on Catalytic Hydrogen Evolution)
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