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17 pages, 554 KB

Open AccessArticle

Enhancing the Reliability of AD936x-Based SDRs for Aerospace Applications via Active Register Scrubbing and Autonomous Fault Recovery

by Jinyang Wang, Zhugang Wang and Li Zhou

Sensors 2025, 25(21), 6801; https://doi.org/10.3390/s25216801 (registering DOI) - 6 Nov 2025

Abstract

Single Event Upsets (SEUs) in Commercial Off-The-Shelf (COTS) Software-Defined Radios (SDRs) are frequent in a erospace applications, especially in GEO (Geostationary Orbit) orbit during severe solar activity, and can lead to unexpected register corruption and communication failures. This work presents a purely software-based [...] Read more.

Single Event Upsets (SEUs) in Commercial Off-The-Shelf (COTS) Software-Defined Radios (SDRs) are frequent in a erospace applications, especially in GEO (Geostationary Orbit) orbit during severe solar activity, and can lead to unexpected register corruption and communication failures. This work presents a purely software-based Fault Detection, Isolation, and Recovery (FDIR) framework tailored for the AD936x RF agile transceiver, requiring no hardware modifications. The proposed method classifies all device registers into four impact categories and applies dedicated scrubbing strategies—standard refresh, masked refresh, procedural refresh, and forced refresh—combined with real-time register health monitoring and adaptive recovery actions. Fault injection experiments comprising 10,000 diverse test cases achieved 100% fault coverage for the tested scenarios, with an average recovery time of 0.75 s for typical SEUs and a guaranteed worst-case recovery under 4.4 s for critical failures, while maintaining a CPU load below 1.3%. The approach ensures continuous SDR operation under SEU events and offers a scalable, lightweight, and cost-effective reliability enhancement for CubeSats and other resource-constrained aerospace platforms. Full article

(This article belongs to the Section Communications)

23 pages, 1712 KB

Open AccessArticle

Balancing Forecast Accuracy and Emissions for Hourly Wind Power at Dumat Al-Jandal: Sustainable AI for Zero-Carbon Transitions

by Haytham Elmousalami, Felix Kin Peng Hui and Aljawharah A. Alnaser

Sustainability 2025, 17(21), 9908; https://doi.org/10.3390/su17219908 (registering DOI) - 6 Nov 2025

Abstract

This paper develops a Sustainable Artificial Intelligence-Driven Wind Power Forecasting System (SAI-WPFS) to enhance the integration of renewable energy while minimizing the environmental footprint of deep learning computations. Although deep learning models such as CNN, LSTM, and GRU have achieved high accuracy in [...] Read more.

This paper develops a Sustainable Artificial Intelligence-Driven Wind Power Forecasting System (SAI-WPFS) to enhance the integration of renewable energy while minimizing the environmental footprint of deep learning computations. Although deep learning models such as CNN, LSTM, and GRU have achieved high accuracy in wind power forecasting, existing research rarely considers the computational energy cost and associated carbon emissions, creating a gap between predictive performance and sustainability objectives. Moreover, limited studies have addressed the need for a balanced framework that jointly evaluates forecast precision and eco-efficiency in the context of large-scale renewable deployment. Using real-time data from the Dumat Al-Jandal Wind Farm, Saudi Arabia’s first utility-scale wind project, this study evaluates multiple deep learning architectures, including CNN-LSTM-AM and GRU, under a dual assessment framework combining accuracy metrics (MAE, RMSE, R²) and carbon efficiency indicators (CO₂ emissions per computational hour). Results show that the CNN-LSTM-AM model achieves the highest forecasting accuracy (MAE = 29.37, RMSE = 144.99, R² = 0.74), while the GRU model offers the best trade-off between performance and emissions (320 g CO₂/h). These findings demonstrate the feasibility of integrating sustainable AI into wind energy forecasting, aligning technical innovation with Saudi Vision 2030 goals for zero-carbon cities and carbon-efficient energy systems. Full article

(This article belongs to the Special Issue Sustainable Energy Systems and Applications)

19 pages, 2049 KB

Open AccessFeature PaperArticle

Eco-Friendly Biotechnological Approaches to Enhance Germination Efficiency in Lavandula angustifolia Mill.

by Ioan-Adrian Georgiu, Elena Adriana Ciulca, Giancarla Velicevici, Radu E. Sestras, Monica Boscaiu, Oscar Vicente and Adriana F. Sestras

Horticulturae 2025, 11(11), 1339; https://doi.org/10.3390/horticulturae11111339 (registering DOI) - 6 Nov 2025

Abstract

The improvement of Lavandula angustifolia Mill. seed germination represents a crucial step towards the development of eco-biotechnological solutions for the sustainable propagation of aromatic plants. This study evaluated the effects of four biostimulant formulations, namely Amino 16 (amino acid-based), Razormin (humic–fulvic complex), Germinoseed [...] Read more.

The improvement of Lavandula angustifolia Mill. seed germination represents a crucial step towards the development of eco-biotechnological solutions for the sustainable propagation of aromatic plants. This study evaluated the effects of four biostimulant formulations, namely Amino 16 (amino acid-based), Razormin (humic–fulvic complex), Germinoseed (phytoextract-based), and Atonik (nitrophenolate), together with a non-treated control, on the germination efficiency and early growth of nine Lavandula genotypes under controlled laboratory conditions. A factorial design (9 × 5) with four replications was applied, and multiple germination indices were calculated. Data were analysed using a two-way ANOVA with genotype and treatment as main factors. Results indicated significant genotype-dependent responses. Amino 16 and Razormin markedly increased germination percentage, speed of emergence, and seedling vigour, achieving up to 100% germination in responsive genotypes such as ‘Ellagance Snow’ and ‘Blue Spear’. Correlation and clustering analyses revealed strong links between seed size, germination rate, and seedling development, suggesting a possible synergistic role of amino and humic substances in stimulating metabolic activation during germination. These findings demonstrate that eco-friendly biostimulants function as effective biotechnological activators of seed physiology, supporting low-input propagation systems and the transition toward a circular green bioeconomy. Full article

(This article belongs to the Section Propagation and Seeds)

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30 pages, 870 KB

Open AccessArticle

Fractional Optimal Control of Anthroponotic Cutaneous Leishmaniasis with Behavioral and Epidemiological Extensions

by Asiyeh Ebrahimzadeh, Amin Jajarmi and Mehmet Yavuz

Math. Comput. Appl. 2025, 30(6), 122; https://doi.org/10.3390/mca30060122 (registering DOI) - 6 Nov 2025

Abstract

Sandflies spread the neglected vector-borne disease anthroponotic cutaneous leishmaniasis (ACL), which only affects humans. Despite decades of control, asymptomatic carriers, vector pesticide resistance, and low public awareness prevent eradication. This study proposes a fractional-order optimal control model that integrates biological and behavioral aspects [...] Read more.

Sandflies spread the neglected vector-borne disease anthroponotic cutaneous leishmaniasis (ACL), which only affects humans. Despite decades of control, asymptomatic carriers, vector pesticide resistance, and low public awareness prevent eradication. This study proposes a fractional-order optimal control model that integrates biological and behavioral aspects of ACL transmission to better understand its complex dynamics and intervention responses. We model asymptomatic human illnesses, insecticide-resistant sandflies, and a dynamic awareness function under public health campaigns and collective behavioral memory. Four time-dependent control variables—symptomatic treatment, pesticide spraying, bed net use, and awareness promotion—are introduced under a shared budget constraint to reflect public health resource constraints. In addition, Caputo fractional derivatives incorporate memory-dependent processes and hereditary effects, allowing for epidemic and behavioral states to depend on prior infections and interventions; on the other hand, standard integer-order frameworks miss temporal smoothness, delayed responses, and persistence effects from this memory feature, which affect optimal control trajectories. Next, we determine the optimality conditions for fractional-order systems using a generalized Pontryagin’s maximum principle, then solve the state–adjoint equations numerically with an efficient forward–backward sweep approach. Simulations show that fractional (memory-based) dynamics capture behavioral inertia and cumulative public response, improving awareness and treatment efforts. Furthermore, sensitivity tests indicate that integer-order models do not predict the optimal allocation of limited resources, highlighting memory effects in epidemiological decision-making. Consequently, the proposed method provides a realistic and flexible mathematical basis for cost-effective and sustainable ACL control plans in endemic settings, revealing how memory-dependent dynamics may affect disease development and intervention efficiency. Full article

(This article belongs to the Special Issue Mathematics and Applied Data Science)

19 pages, 4023 KB

Open AccessArticle

Hacking Extracellular Vesicles: Using Vesicle-Related Tags to Engineer Mesenchymal Stromal Cell-Derived Extracellular Vesicles

by Gabriele Scattini, Giulia Pianigiani, Stefano Capomaccio, Maria Rachele Ceccarini, Samanta Mecocci, Laura Musa, Luca Avellini, Olimpia Barbato, Antonello Bufalari, Patrizia Casagrande Proietti, Rodolfo Gialletti, Alessia Sulla, Tommaso Beccari and Luisa Pascucci

Pharmaceutics 2025, 17(11), 1435; https://doi.org/10.3390/pharmaceutics17111435 (registering DOI) - 6 Nov 2025

Abstract

Background/Objectives: Extracellular Vesicles (EVs) have shown great promise as diagnostic and therapeutic tools, as well as pharmacological nanocarriers. Various strategies are being explored to develop EVs for monitoring, imaging, loading with pharmacological agents, and surface decoration with tissue-specific ligands. EVs derived from [...] Read more.

Background/Objectives: Extracellular Vesicles (EVs) have shown great promise as diagnostic and therapeutic tools, as well as pharmacological nanocarriers. Various strategies are being explored to develop EVs for monitoring, imaging, loading with pharmacological agents, and surface decoration with tissue-specific ligands. EVs derived from Mesenchymal Stromal Cells (MSC-EVs) are of particular interest both as therapeutics per se and as natural nanocarriers for the targeted delivery of biotherapeutics. Methods: In this study, we investigated the ability of different tags to deliver a reporter protein into canine MSC-EVs with the aim of identifying the most effective endogenous loading mechanism. To this aim, canine MSCs were engineered to express the Green Fluorescent Protein (GFP) fused to CD63, Syntenin-1, TSG101, and the palmitoylation signal of Lck, which were expected to promote GFP incorporation into EVs. Overexpression of tagged GFP in canine MSCs was confirmed by Western blotting and examined by confocal microscopy and transmission electron microscopy to map intracellular localization. Results: All tags were able to deliver GFP into EVs. Syntenin-1 showed relatively high loading efficiency and secretion index but exhibited a diffuse localization pattern in the transfected cells. The palmitoylation signal showed low loading efficiency and localization specificity. TSG101 displayed a morphological pattern consistent with specific localization in endosomal structures, but its low expression level prevented further evaluations. Finally, CD63 showed the highest expression efficiency, as GFP-CD63 levels were approximately 5-fold higher than untagged GFP. Conclusions: In conclusion, CD63 emerged as the most suitable tag for canine MSC-EV engineering. Indeed, even if the secretion index favours Syntenin-1, CD63’s higher abundance in the lysate suggests its substantial post-secretion uptake. Further studies aimed at elucidating CD63’s specific contribution and identifying the domains involved in vesicle trafficking could provide valuable insights into EV bioengineering. Full article

(This article belongs to the Special Issue Extracellular Vesicles for Targeted Delivery)

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25 pages, 3674 KB

Open AccessArticle

ESG, Innovation and the Competitive Advantage of Construction Enterprises in China—An Analysis Based on the System Dynamics

by Dan Han and Shengyue Hao

Systems 2025, 13(11), 997; https://doi.org/10.3390/systems13110997 (registering DOI) - 6 Nov 2025

Abstract

The unique characteristics of Environmental, Social, and Governance (ESG) in the construction industry and its impact mechanisms within a complex environment still need to be further explored. This study employs grounded theory and a system dynamics model to construct a system of ESG, [...] Read more.

The unique characteristics of Environmental, Social, and Governance (ESG) in the construction industry and its impact mechanisms within a complex environment still need to be further explored. This study employs grounded theory and a system dynamics model to construct a system of ESG, innovation, and the competitive advantage in construction enterprises. Through simulation analysis, this study elucidates the dynamic relationships, causal links, and evolutionary patterns among system elements. The results indicate that (1) ESG, innovation, and the competitive advantage exhibit oscillatory convergence patterns, with innovation and competitive advantage exhibiting time-lagged responses; (2) improvements in environmental (E), social (S), and governance (G) awareness generate diminishing marginal effects on corresponding performance metrics, while reductions in S awareness lead to more pronounced performance deterioration; and (3) simultaneous strengthening of E, S, and G awareness substantially elevates peak levels of innovation and competitive advantage while accelerating their attainment. This study systematically analyzes the dynamic and complex mechanisms through which ESG influences construction enterprises’ competitive advantage and provides valuable suggestions for the sustainable development of construction enterprises. Full article

(This article belongs to the Section Systems Practice in Social Science)

25 pages, 6570 KB

Open AccessArticle

Analytical Analysis of Recirculating Flow in Single-Screw Extruders

by Chris Rauwendaal

Polymers 2025, 17(21), 2959; https://doi.org/10.3390/polym17212959 (registering DOI) - 6 Nov 2025

Abstract

Current analytical theories of recirculating flow in single-screw extruders consider only cross-channel flow in channels of infinite width with only one exception. Proper analysis of recirculating flow requires inclusion of normal velocities and the effect of finite channel width. More broadly, this paper [...] Read more.

Current analytical theories of recirculating flow in single-screw extruders consider only cross-channel flow in channels of infinite width with only one exception. Proper analysis of recirculating flow requires inclusion of normal velocities and the effect of finite channel width. More broadly, this paper presents an analytical description of lid-driven cavity flow—one of the most frequently studied flows in fluid dynamics. Expressions for velocities and flow rates for Newtonian fluids are obtained that satisfy the balance equations. These expressions have been compared to results of numerical analyses with good agreement. Flow rates and velocities are displayed with 3D surface plots and contour plots. These plots provide better insight into the flow behavior than 2D graphs. We have analyzed flow in slit channels with width much greater than the height (

W > > H

) and flow in a square channel (

W = H

). The vortex center (stagnation point) in a slit channel is located at normal coordinate

ψ = 2 / 3

. The vortex center in a square channel is located at

ψ = 0.76

. These analytical results allow for the development of better analytical models for melt temperature distribution, mixing, and devolatilization in single-screw extruders. Full article

(This article belongs to the Special Issue Advances in Screw Processing of Polymeric Materials - In Memory of Professor James Lindsay White)

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55 pages, 6574 KB

Open AccessArticle

Low-Carbon Water Ecological POI Logistics Route Planning Based on Improved Water Network Space AGNES Clustering Model and Symmetrical Simulated Huffman Spatial Searching Tree Algorithm

by Xiao Zhou, Fan Jiang, Wenbing Liu and Jun Wang

Symmetry 2025, 17(11), 1894; https://doi.org/10.3390/sym17111894 (registering DOI) - 6 Nov 2025

Abstract

To reduce the pollutant emissions of water ecological POI logistics, the water ecological POI logistics route-planning method based on the improved water network space AGNES clustering model and the symmetrical simulated Huffman spatial searching tree (SHSST) algorithm is innovatively established. The improved AGNES [...] Read more.

To reduce the pollutant emissions of water ecological POI logistics, the water ecological POI logistics route-planning method based on the improved water network space AGNES clustering model and the symmetrical simulated Huffman spatial searching tree (SHSST) algorithm is innovatively established. The improved AGNES algorithm is established for water ecological POI clustering, and then the logistics distribution center location model based on water ecological POI clustering is constructed. On the basis of an optimal distribution center, combining the symmetrical feature of vehicle moving paths and distances in logistics sub-intervals and logistics intervals, the sub-interval optimal route-searching algorithm based on the symmetrical SHSST is constructed to determine the optimal path for each logistics sub-interval, and then the global logistics route-planning algorithm based on undirected complete graph spatial search is constructed to search for the global optimal logistics route. Experiments prove that the proposed algorithm can accurately cluster water ecological POIs and output the logistics route with the lowest costs and pollutant emissions. Compared to the traditional AGNES and other clustering algorithms, the improved AGNES algorithm has lower time complexity. Compared to the traditional logistics route algorithms, SHSST has lower algorithm complexity, route costs, and pollutant emissions, and strong stability. The minimum and maximum optimization rates for the same route are 10.06% and 17.58%, while the minimum and maximum optimization rates for the optimal route are 11.41% and 14.29%; it could effectively reduce the negative impact of pollutants on the water ecological environment and POIs. Full article

(This article belongs to the Section Engineering and Materials)

19 pages, 13708 KB

Open AccessArticle

A-BiYOLOv9: An Attention-Guided YOLOv9 Model for Infrared-Based Wind Turbine Inspection

by Sami Ekici, Murat Uyar and Tugce Nur Karadeniz

Appl. Sci. 2025, 15(21), 11840; https://doi.org/10.3390/app152111840 (registering DOI) - 6 Nov 2025

Abstract

This work examines how thermal turbulence patterns can be identified on the blades of operating wind turbines—an issue that plays a key role in preventive maintenance and overall safety assurance. Using the publicly available KI-VISIR dataset, containing annotated infrared images collected under real-world [...] Read more.

This work examines how thermal turbulence patterns can be identified on the blades of operating wind turbines—an issue that plays a key role in preventive maintenance and overall safety assurance. Using the publicly available KI-VISIR dataset, containing annotated infrared images collected under real-world operating conditions, four object detection architectures were evaluated: YOLOv8, the baseline YOLOv9, the transformer-based RT-DETR, and an enhanced variant introduced as A-BiYOLOv9. The proposed approach extends the YOLOv9 backbone with convolutional block attention modules (CBAM) and integrates a bidirectional feature pyramid network (BiFPN) in the neck to improve feature fusion. All models were trained for thirty epochs on single-class turbulence annotations. The experiments confirm that YOLOv8 provides fast and efficient detection, YOLOv9 delivers higher accuracy and more stable convergence, and RT-DETR exhibits strong precision and consistent localization performance. A-BiYOLOv9 maintains stable and reliable accuracy even when the thermal patterns vary significantly between scenes. These results confirm that attention-augmented and feature-fusion-centric architectures improve detection sensitivity and reliability in the thermal domain. Consequently, the proposed A-BiYOLOv9 represents a promising candidate for real-time, contactless thermographic monitoring of wind turbines, with the potential to extend turbine lifespan through predictive maintenance strategies. Full article

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14 pages, 39102 KB

Open AccessArticle

Schrödinger Cat States in Giant Negative Magnetoresistance of 2D Electron Systems

by Jesús Iñarrea

Appl. Sci. 2025, 15(21), 11841; https://doi.org/10.3390/app152111841 (registering DOI) - 6 Nov 2025

Abstract

We investigate the effect of giant negative magnetoresistance in ultrahigh-mobility (

μ ≫ 10^{7} {cm}^{2} V^{- 1} s^{- 1}

) two-dimensional electron systems. These systems present a dramatic drop in the mangetoresistance at low magnetic fields ( [...] Read more.

We investigate the effect of giant negative magnetoresistance in ultrahigh-mobility (

μ ≫ 10^{7} {cm}^{2} V^{- 1} s^{- 1}

) two-dimensional electron systems. These systems present a dramatic drop in the mangetoresistance at low magnetic fields (

B \sim 0.1

T) and temperatures (

T \sim 0.1

K). This effect is reversed by increasing the temperature or the presence of an in-plane magnetic field. The motivation for the present work is to develop a microscopical model to explain the experimental evidence, based on coherent states and Schródinger cat states of the quantum harmonic oscillator. Thus, we approach the giant negative magnetoresistance effect based on the description of ultrahigh-mobility two-dimensional electron systems in terms of Schrödinger cat states (superposition of coherent states of the quantum harmonic oscillator). We explain the experimental results in terms of the increasing disorder in the sample due to the rising temperature or the in-plane magnetic field, breaking up the Schrödinger cat states and giving rise to mere coherent states, which hold magnetoresistance in lower-mobility samples. The latter, jointly with the description of ultrahigh-mobility samples with Schrödinger cat states, accounts for the main contribution. The most interesting application of this novel description of such systems would be in the implementation of qubits for quantum computing based on bosonic models. Full article

(This article belongs to the Section Applied Physics General)

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30 pages, 2028 KB

Open AccessArticle

Forage Carbohydrate Profiles and Endocrine Morphometric Interactions in Traditionally Managed Horses from Romania

by Zsofia Daradics, Maria Popescu, Cornel Cătoi, Mircea Valerian Mircean, Adrian Macri, Oana Mîrza, Andrei Szakacs, Sorana Daina, Florinela Fetea, Mirela Alexandra Tripon, Alexandru Florin Lupșan, Denisa Bungărdean, Anamaria Călugăr, Florin Dumitru Bora and Cristian Mihăiță Crecan

Life 2025, 15(11), 1721; https://doi.org/10.3390/life15111721 (registering DOI) - 6 Nov 2025

Abstract

Horses maintained under traditional management systems and dependent on natural forages are often exposed to seasonal and compositional variations that can affect metabolic homeostasis. This study examined associations between forage nutrient composition and metabolic–morphometric indicators in horses from four agroecologically distinct regions of [...] Read more.

Horses maintained under traditional management systems and dependent on natural forages are often exposed to seasonal and compositional variations that can affect metabolic homeostasis. This study examined associations between forage nutrient composition and metabolic–morphometric indicators in horses from four agroecologically distinct regions of northwestern Romania. Eighty-eight horses managed under semi-extensive rural conditions underwent clinical examination, body condition scoring (BCS), cresty neck scoring (CNS), and fasting blood sampling. Forage samples (n = 34) from daily rations were analyzed for fermentable carbohydrate content, while serum insulin, leptin, and adiponectin were quantified using validated equine-specific ELISA assays. Forage composition varied substantially among regions, influencing both endocrine and morphometric outcomes. Horses consuming carbohydrate-rich forages exhibited higher insulin (0.95–219 μIU/mL) and leptin concentrations (925–28,190 pg/mL), accompanied by elevated BCS and CNS scores, whereas adiponectin levels tended to decrease with increasing carbohydrate content. These findings demonstrate that naturally occurring variation in forage quality can significantly influence metabolic regulation in horses managed under low-input, traditional systems. Integrating forage nutrient evaluation with clinical and endocrine assessments provides a practical framework for identifying animals at risk of metabolic dysfunction and guiding nutritional strategies to mitigate the incidence of laminitis and related disorders. Full article

(This article belongs to the Special Issue Perspectives on Nutrition and Livestock Health)

28 pages, 1826 KB

Open AccessArticle

Hierarchical Beamforming Optimization for ISAC-Enabled RSU Systems in Complex Urban Environments

by Zhiyuan You, Na Lv, Guimei Zheng and Xiang Wang

Sensors 2025, 25(21), 6803; https://doi.org/10.3390/s25216803 (registering DOI) - 6 Nov 2025

Abstract

Integrated Sensing and Communication (ISAC)-enabled Roadside Units (RSUs) encounter significant performance trade-offs between target sensing and multi-user communication in complex urban environments, where conventional optimization methods are prone to converging to local optima and joint optimization methods often yield sub-optimal results due to [...] Read more.

Integrated Sensing and Communication (ISAC)-enabled Roadside Units (RSUs) encounter significant performance trade-offs between target sensing and multi-user communication in complex urban environments, where conventional optimization methods are prone to converging to local optima and joint optimization methods often yield sub-optimal results due to conflicting objectives. To address the challenge of trade-off between sensing and communication performance, this paper proposes a hierarchical beamforming optimization solution designed to tackle joint sensing–communication problems in such scenarios. The overall optimization problem is decomposed into a two-level “leader-follower” structure. In the leader layer, we introduce a max–min strategy based on the bisection method to transform the non-convex Signal-to-Interference-plus-Noise Ratio (SINR) optimization problem into a second-order cone constraint problem and solve the communication beamforming vector. In the follower layer, the Signal-to-Clutter-plus-Noise Ratio (SCNR) maximization problem is converted into a Semi-Definite Programming (SDP) problem solved via the CVX toolbox. Additionally, we introduce a “spatiotemporal resource isolation” mechanism to project the sensing beam onto the null space of the communication channel. The hierarchical optimization solution jointly optimizes communication SINR and sensing SCNR, enabling an effective balance between sensing accuracy and communication reliability. Simulation results demonstrate the proposed method’s effectiveness in simultaneously improving sensing accuracy and communication reliability. Full article

(This article belongs to the Special Issue Integrated Sensing and Communication in IoT Applications)

22 pages, 1590 KB

Open AccessArticle

A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks

by Ge Zhang, Weimin Shi, Qilong Miao and Xiaofeng Shen

Sensors 2025, 25(21), 6802; https://doi.org/10.3390/s25216802 (registering DOI) - 6 Nov 2025

Abstract

The precise reconstruction of target scattering centers (TSCs) using sensors plays a crucial role in feature extraction and identification of non-cooperative targets. Radar sensor networks (RSNs) are well suited for this task, as they are capable of illuminating targets from multiple aspect angles [...] Read more.

The precise reconstruction of target scattering centers (TSCs) using sensors plays a crucial role in feature extraction and identification of non-cooperative targets. Radar sensor networks (RSNs) are well suited for this task, as they are capable of illuminating targets from multiple aspect angles and rapidly capturing reflected signals. However, the complex geometry and diverse material composition of real-world targets result in significant variations in the radar cross-section (RCS) observed at different angles. Although these RCS responses are interrelated, they exhibit considerable angular diversity. Furthermore, achieving precise spatiotemporal registration and fully coherent processing is infeasible for RSNs composed of small mobile sensor platforms, such as drone swarms. Therefore, an intelligent algorithm is required to extract and accumulate correlated and meaningful information from the target echoes received by the RSN. In this work, a novel collaborative TSC reconstruction framework for RSNs is proposed. The framework performs similarity evaluation on wide-angle high-resolution range profiles (HRRPs) to achieve adaptive angular segmentation of TSC models. It combines the expectation–maximization (EM) algorithm with an enhanced Arctic puffin optimization (EAPO) algorithm to effectively integrate echo information from the RSN in a non-coherent manner, thereby enabling accurate TSC estimation. The proposed method outperforms existing mainstream approaches in terms of spatiotemporal registration requirements, estimation accuracy, and stability. Comparative experiments on measured datasets demonstrate the robustness of the framework and its adaptability to complex target scattering characteristics, confirming its practical value. Full article

(This article belongs to the Special Issue Computer Vision Recognition and Communication Sensing System)

27 pages, 1112 KB

Open AccessArticle

Joint Coherent/Non-Coherent Detection for Distributed Massive MIMO: Enabling Cooperation Under Mixed Channel State Information

by Supuni Gunasekara, Peter Smith, Margreta Kuijper and Rajitha Senanayake

Sensors 2025, 25(21), 6800; https://doi.org/10.3390/s25216800 (registering DOI) - 6 Nov 2025

Abstract

Beyond-5G wireless systems increasingly rely on distributed massive multiple-input multiple-output (MIMO) architectures to achieve high spectral efficiency, low latency, and wide coverage. A key challenge in such networks is that cooperating base stations (BSs) often possess different levels of channel state information (CSI) [...] Read more.

Beyond-5G wireless systems increasingly rely on distributed massive multiple-input multiple-output (MIMO) architectures to achieve high spectral efficiency, low latency, and wide coverage. A key challenge in such networks is that cooperating base stations (BSs) often possess different levels of channel state information (CSI) due to fronthaul constraints, user mobility, or hardware limitation. In this paper, we propose two novel detectors that enable cooperation between BSs with differing CSI availability. In this setup, some BSs have access to instantaneous CSI, while others only have long-term channel information. The proposed detectors—termed the coherent/non-coherent (CNC) detector and the differential CNC detector—integrate coherent and non-coherent approaches to signal detection. This framework allows BSs with only long-term information to actively contribute to the detection process, while leveraging instantaneous CSI where available. This approach enables the system to integrate the advantages of non-coherent detection with the precision of coherent processing, improving overall performance without requiring full CSI at all cooperating BSs. We formulate the detectors based on the maximum likelihood (ML) criterion and derive analytical expressions for their pairwise block error probabilities under Rayleigh fading channels. Leveraging the pairwise block error probability expression for the CNC detector, we derive a tight upper bound on the average block error probability. Numerical results show that the CNC and differential CNC detectors outperform their respective single-BS baseline-coherent ML and non-coherent differential detection. Moreover, both detectors demonstrate strong resilience to mid-to-high range correlation at the BS antennas. Full article

(This article belongs to the Special Issue Future Wireless Communication Networks: 3rd Edition)

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36 pages, 4481 KB

Open AccessArticle

Multi-Weather DomainShifter: A Comprehensive Multi-Weather Transfer LLM Agent for Handling Domain Shift in Aerial Image Processing

by Yubo Wang, Ruijia Wen, Hiroyuki Ishii and Jun Ohya

J. Imaging 2025, 11(11), 395; https://doi.org/10.3390/jimaging11110395 (registering DOI) - 6 Nov 2025

Abstract

Recent deep learning-based remote sensing analysis models often struggle with performance degradation due to domain shifts caused by illumination variations (clear to overcast), changing atmospheric conditions (clear to foggy, dusty), and physical scene changes (clear to snowy). Addressing domain shift in aerial image [...] Read more.

Recent deep learning-based remote sensing analysis models often struggle with performance degradation due to domain shifts caused by illumination variations (clear to overcast), changing atmospheric conditions (clear to foggy, dusty), and physical scene changes (clear to snowy). Addressing domain shift in aerial image segmentation is challenging due to limited training data availability, including costly data collection and annotation. We propose Multi-Weather DomainShifter, a comprehensive multi-weather domain transfer system that augments single-domain images into various weather conditions without additional laborious annotation, coordinated by a large language model (LLM) agent. Specifically, we utilize Unreal Engine to construct a synthetic dataset featuring images captured under diverse conditions such as overcast, foggy, and dusty settings. We then propose a latent space style transfer model that generates alternate domain versions based on real aerial datasets. Additionally, we present a multi-modal snowy scene diffusion model with LLM-assisted scene descriptors to add snowy elements into scenes. Multi-weather DomainShifter integrates these two approaches into a tool library and leverages the agent for tool selection and execution. Extensive experiments on the ISPRS Vaihingen and Potsdam dataset demonstrate that domain shift caused by weather change in aerial image-leads to significant performance drops, then verify our proposal’s capacity to adapt models to perform well in shifted domains while maintaining their effectiveness in the original domain. Full article

(This article belongs to the Special Issue Celebrating the 10th Anniversary of the Journal of Imaging)

40 pages, 10740 KB

Open AccessArticle

Structural Design of an Unmanned Aerial Underwater Vehicle with Coaxial Twin Propellers and the Numerical Simulation of the Cross-Domain Characteristics

by Jiancheng Wang, Yikun Feng, Guoqing Zhang, Qiqian Ge, Haobin Jin and Zhewei Zhang

Drones 2025, 9(11), 766; https://doi.org/10.3390/drones9110766 (registering DOI) - 6 Nov 2025

Abstract

This paper addresses the structural adaptability and dynamic stability challenges faced by unmanned aerial underwater vehicle (UAUV) during the transition between air and water. To overcome these issues, this paper innovatively proposes a UAUV that uses coaxial twin propellers for propulsion and conducts [...] Read more.

This paper addresses the structural adaptability and dynamic stability challenges faced by unmanned aerial underwater vehicle (UAUV) during the transition between air and water. To overcome these issues, this paper innovatively proposes a UAUV that uses coaxial twin propellers for propulsion and conducts a detailed overall structural design and subsystem design for it. Accurate prediction of the kinematic characteristics of UAUV during cross-domain motion is of great significance for the design of high-performance UAUVs. Therefore, a numerical simulation method for UAUV cross-domain motion based on the STAR CCM+ (version 202402) software, the volume of fluid (VOF) method, and the dynamic fluid body interaction (DFBI) module was established. The results showed that when the water-entry speed is small, as the water-entry angle increases, the UAUV’s movement trajectory will exhibit continuous undulating motion. Moreover, during the water-exit process, the smaller the water-exit speed and angle, the greater the change in attitude. The analysis of the dynamic characteristics of cavitation during the UAUV’s water-entry process reveals that the premature rupture of the cavities is detrimental to the UAUV’s movement along the initial entry direction. During the process of the UAUV’s exit from the water, the detachment of water adhering to the UAUV surface will cause certain disturbances to its attitude. The findings of this study provide key theoretical insights and technical references for optimizing the structural design of UAUVs. Full article

(This article belongs to the Topic International Conference on Autonomous Unmanned Systems (5th ICAUS 2025))

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18 pages, 324 KB

Open AccessReview

Drug Repurposing in Veterinary Oncology: Myth or Reality?

by Stefano Ciccarelli, Chiara Perrone, Maria Alfonsa Cavalera and Antonio Giuliano

Vet. Sci. 2025, 12(11), 1067; https://doi.org/10.3390/vetsci12111067 (registering DOI) - 6 Nov 2025

Abstract

Drug repurposing, that is, the identification of new therapeutic indications for existing medications, has been shown to be a cost-effective and time-efficient alternative to de novo drug development. This review provides a comprehensive overview of repurposed drugs in veterinary oncology, describing their mechanisms [...] Read more.

Drug repurposing, that is, the identification of new therapeutic indications for existing medications, has been shown to be a cost-effective and time-efficient alternative to de novo drug development. This review provides a comprehensive overview of repurposed drugs in veterinary oncology, describing their mechanisms of action, current evidence of clinical benefit, and translational relevance. The therapeutic agents discussed include non-steroidal anti-inflammatory drugs (e.g., piroxicam), metabolic modulators (e.g., metformin), anti-parasitic drugs (e.g., fenbendazole), immunomodulators (e.g., thalidomide, oclacitinib), cardiovascular agents (e.g., propranolol, statins, losartan), and other compounds such as auranofin and disulfiram. A critical evaluation of the extant evidence-based data from preclinical research, naturally occurring tumor models, and clinical studies is provided, with particular emphasis on both the therapeutic potential and the current limitations. The present review also focused on combination strategies and multimodal protocols, where repurposed drugs may enhance the efficacy of chemotherapy, targeted therapies, or immunotherapy. Challenges to clinical implementation, including limited funding, regulatory and ethical considerations, and the need for well-designed, multi-institutional clinical trials, are discussed. Ultimately, drug repurposing represents a practical and translationally valuable approach to broaden therapeutic options, improve quality of life in companion animals, and advance comparative oncology by promoting progress that benefits both veterinary and human patients. Full article

(This article belongs to the Special Issue Focus on Tumours in Pet Animals: 2nd Edition)

19 pages, 558 KB

Open AccessReview

From Burnout to Resilience: Addressing Moral Injury in Nursing Through Organizational Innovation in the Post-Pandemic Era

by Enășoni Sorina, Dorin Novacescu, Alina Cristina Barb, Alexandru Ciolofan, Cristina Stefania Dumitru, Flavia Zara, Raul Patrascu and Alexandra Enache

Healthcare 2025, 13(21), 2822; https://doi.org/10.3390/healthcare13212822 (registering DOI) - 6 Nov 2025

Abstract

The COVID-19 pandemic has profoundly amplified burnout and moral injury among nurses, exposing structural vulnerabilities in healthcare systems and accelerating workforce attrition. Beyond the acute crisis, nurses continue to face chronic staff shortages, overwhelming workloads, and unresolved ethical tensions that compromise both well-being [...] Read more.

The COVID-19 pandemic has profoundly amplified burnout and moral injury among nurses, exposing structural vulnerabilities in healthcare systems and accelerating workforce attrition. Beyond the acute crisis, nurses continue to face chronic staff shortages, overwhelming workloads, and unresolved ethical tensions that compromise both well-being and quality of care. Synthesis of recent meta-analyses in this review indicates that nurse burnout during the pandemic ranged between 30% and 50%, illustrating the magnitude of the problem. Particular attention is given to innovative organizational strategies that foster resilience, including workload redistribution, enhanced professional autonomy, supportive leadership, and the integration of digital technologies such as telecare. Comparative perspectives across healthcare systems illustrate how policy reforms, staffing models, and ethical frameworks can mitigate psychological distress and strengthen organizational resilience. By reframing burnout and moral injury not only as individual challenges but as systemic phenomena requiring structural solutions, this review emphasizes the imperative of multilevel interventions. Building resilient nursing workforces through innovation, leadership, and evidence-based policies is essential for sustaining high-quality patient care in the post-pandemic era. Full article

(This article belongs to the Special Issue Innovating Care in the Post-Pandemic Era: Models, Leadership, and Technologies for the Future of Nursing)

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16 pages, 832 KB

Open AccessArticle

Long-Term Efficacy and Safety of 0.1% Cyclosporine A Cationic Emulsion in Advanced Dry Eye Disease: A 24-Month Retrospective Study

by Monika Sarnat-Kucharczyk, Martyna Nowak and Ewa Mrukwa-Kominek

Pharmaceuticals 2025, 18(11), 1682; https://doi.org/10.3390/ph18111682 (registering DOI) - 6 Nov 2025

Abstract

Background: To evaluate the effectiveness of 0.1% cyclosporine A (CsA) cationic emulsion in managing advanced dry eye disease (DED), based on clinical parameters: Ocular Surface Disease Index (OSDI), best-corrected visual acuity (BCVA), Tear Break-Up Time (TBUT), corneal fluorescein staining (CFS) on the [...] Read more.

Background: To evaluate the effectiveness of 0.1% cyclosporine A (CsA) cationic emulsion in managing advanced dry eye disease (DED), based on clinical parameters: Ocular Surface Disease Index (OSDI), best-corrected visual acuity (BCVA), Tear Break-Up Time (TBUT), corneal fluorescein staining (CFS) on the Oxford scale, Schirmer test, and intraocular pressure (IOP). Methods: This retrospective study included 20 patients (40 eyes) with severe DED unresponsive to previous therapies. All patients continued artificial tears and added 0.1% CsA once daily. Baseline assessments included OSDI, BCVA, TBUT, corneal staining, Schirmer test, and IOP. Follow-ups occurred at 1–3, 6, 12, and 24 months. Data were analyzed for treatment effect and progression over time. Results: The mean age was 53.5 ± 13.5 years; 80% were female. BCVA showed no significant changes. OSDI scores improved from severe (>53) to moderate (approximately 35). Schirmer test increased from ~6.2 mm to >10 mm (p < 0.001). TBUT improved from approximately 6 to 10 s (p < 0.001), with significant differences after 6 months. CFS scores decreased from 3.4 to 2.05 (p < 0.001), indicating reduced corneal damage. IOP remained stable throughout the study period. Conclusions: Long-term use of 0.1% cyclosporine A cationic emulsion led to marked and sustained improvement in both subjective symptoms and objective ocular surface parameters in severe dry eye disease. The therapy was safe, well tolerated, and did not affect visual acuity or intraocular pressure, supporting its value as a long-term treatment option. Full article

(This article belongs to the Section Medicinal Chemistry)

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13 pages, 3079 KB

Open AccessArticle

A Novel Energetic Nitroform Salt Derived from Bis-(Triazolyl)-Furoxan

by Fawei Wang, Jiapeng Wang, Zihu Wang, Jianhua Wang and Yucun Liu

Crystals 2025, 15(11), 960; https://doi.org/10.3390/cryst15110960 (registering DOI) - 6 Nov 2025

Abstract

This study presents the synthesis and comprehensive characterization of a novel nitroform salt, bis(2-methyl-3-amino-1,2,4-triazolyl)furoxan trinitromethanide (compound 2), derived from the molecular scaffold of bis-(2-methyl-3-amino-1,2,4-triazolyl)-furoxan (compound 1). The incorporation of the nitroform anion significantly enhances the energetic performance while maintaining moderate stability. [...] Read more.

This study presents the synthesis and comprehensive characterization of a novel nitroform salt, bis(2-methyl-3-amino-1,2,4-triazolyl)furoxan trinitromethanide (compound 2), derived from the molecular scaffold of bis-(2-methyl-3-amino-1,2,4-triazolyl)-furoxan (compound 1). The incorporation of the nitroform anion significantly enhances the energetic performance while maintaining moderate stability. Single-crystal X-ray diffraction analysis revealed that compound 2 crystallizes in the orthorhombic space group P2₁2₁2₁ with a density of 1.712 g·cm⁻³. Although its crystal packing adopts a less optimal zigzag-type mixed stacking mode and exhibits uneven electrostatic potential distribution, an extensive intramolecular hydrogen-bonding network contributes to its structural stability, as evidenced by a thermal decomposition temperature of 141 °C and impact sensitivity of 17 J. Detonation parameters calculated using EXPLO5 software demonstrate superior performance (detonation velocity = 8271 m·s⁻¹, detonation pressure = 26.9 GPa) compared to TNT and close proximity to RDX, coupled with markedly improved mechanical stability over both RDX and HMX. Hirshfeld surface and electrostatic potential analyses further elucidate the relationship between molecular structure and sensitivity, highlighting the critical role of hydrogen bonding in moderating mechanical sensitivity despite high energy content. These results underscore the potential of nitroform functionalization for designing advanced energetic materials with balanced performance and safety. Full article

(This article belongs to the Section Crystal Engineering)

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17 pages, 2104 KB

Open AccessArticle

Predicting Packaging Material–Food Interactions and the Respective Migration and Permeation Based on Hansen Solubility Parameters—A Case Study of Bio-Based Polyester Cutin

by Costas Tsioptsias, Athanasios Goulas, Maria Tsini, Athanasia Zoglopiti, Anna Marinopoulou and Vassilis Karageorgiou

Polymers 2025, 17(21), 2961; https://doi.org/10.3390/polym17212961 (registering DOI) - 6 Nov 2025

Abstract

One of the current and serious environmental problems is the pollution due to microplastics. There is an urgent need for biodegradable and bio-based materials for numerous applications, including food packaging. In this work we examine the bio-based polyester cutin for its potential to [...] Read more.

One of the current and serious environmental problems is the pollution due to microplastics. There is an urgent need for biodegradable and bio-based materials for numerous applications, including food packaging. In this work we examine the bio-based polyester cutin for its potential to be used as food packaging material, in terms of migration, based on the Hansen Solubility Parameters (HSP). Cutin is a cross-linked polymer that is swelled by various solvents. We use the degree of swelling of cutin in carefully selected solvents of various polarities in order to estimate the HSP of cutin. Some solvents can induce alteration of the chemical structure of cutin, as proven by Fourier Transform Infrared (FTIR) measurements. This interferes with the process of estimation of the HSP and is discussed in depth. The distance R_a and the Relative Energy Difference (RED) between the HSP of cutin and various food components are calculated and used to predict the existence of favorable interactions between cutin and the food components, which is translated to a high probability for the existence of migration and permeation. Experimental confirmation of one prediction based on HSP is provided by UV-VIS photometry. Similar calculations were performed for other polyesters (poly(lactic acid) and poly(hydroxy butyrate)). Cutin exhibits compatibility with substances of low polarity, such as fats and lipids and non-polar compounds found in essential oils. Thus, migration into fatty foods is expected as well as sorption and permeation of some (volatile) compounds into cutin. Nevertheless, we conclude that the overall migration risk for cutin is lower than the one of other bio-based polyesters. HSP can be used for initial screening of potential migration risks; however, further research is necessary in order to assess the occurrence, extent, and significance of the actual migration. Full article

(This article belongs to the Section Biobased and Biodegradable Polymers)

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17 pages, 8309 KB

Open AccessArticle

Green Synthesis of Chitosan Silver Nanoparticle Composite Materials: A Comparative Study of Microwave and One-Pot Reduction Methods

by Ahmed Hosney, Algimanta Kundrotaitė, Donata Drapanauskaitė, Marius Urbonavičius, Šarūnas Varnagiris, Sana Ullah and Karolina Barčauskaitė

Polymers 2025, 17(21), 2960; https://doi.org/10.3390/polym17212960 (registering DOI) - 6 Nov 2025

Abstract

Green synthesis methods of silver nanoparticles have gained great attention because they offer sustainable, eco-friendly, and less-toxic alternatives to traditional methods. This study sheds light on the green synthesis of chitosan silver nanoparticle composites, providing a comparative evaluation of microwave-assisted (M1) and a [...] Read more.

Green synthesis methods of silver nanoparticles have gained great attention because they offer sustainable, eco-friendly, and less-toxic alternatives to traditional methods. This study sheds light on the green synthesis of chitosan silver nanoparticle composites, providing a comparative evaluation of microwave-assisted (M1) and a one-pot (M2) reduction methods. The morphological, crystallinity, and structural uniformity characteristics were evaluated by UV-Visible, Raman spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM) with employing image processing pipeline based on deep learning model for segmentation and particles size estimation. The UV-visible spectrum exhibited independent SPR peaks ranging from 400 to 450 nm for all samples; however, microwave assisted-synthesis possessed narrower and more intense peaks indicative of better crystallinity and mono-dispersity. SEM depicted smaller, more uniformly dispersed particles for microwave-assisted (M1), while deep learning segmentation showed lower particle size variability (σ ≈ 24–43 nm), compared to polydisperse (σ ≈ 16–59 nm) in M2 samples. XRD showed crystalline face-centered cubic (FCC) silver with dominant peaks in M1 samples, whereas M2 had broader, less intense peaks with amorphous features. Raman vibrations revealed more structural order and homogenous capping in M1 than M2. Therefore, microwave-assisted (M1) showed better control on nucleation, particle size, crystallinity, and homogeneity due to a faster and uniform energy distribution. The future research would focus on the antimicrobial evaluation of such nanoparticles in agronomy. Full article

(This article belongs to the Special Issue Functional Chitosan-Based Nanocomposites: Synthesis, Characterization and Applications)

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20 pages, 2056 KB

Open AccessArticle

A New 5D Chaotic Supply Chain System with Transport Lag: Modeling, Bifurcation Analysis, Offset Boosting Control and Synchronization

by Muhamad Deni Johansyah, Khaled Benkouider, Sundarapandian Vaidyanathan, Aceng Sambas and Chittineni Aruna

Mathematics 2025, 13(21), 3560; https://doi.org/10.3390/math13213560 (registering DOI) - 6 Nov 2025

Abstract

This paper introduces an enhanced five-dimensional Chaotic Supply Chain Model (5DCSCM) by incorporating a transport lag variable into a previously established four-dimensional model. The newly added differential equation in the transit dynamics of the supply chain model captures the inherent lag between customer [...] Read more.

This paper introduces an enhanced five-dimensional Chaotic Supply Chain Model (5DCSCM) by incorporating a transport lag variable into a previously established four-dimensional model. The newly added differential equation in the transit dynamics of the supply chain model captures the inherent lag between customer demand and the physical response in transportation, modeled as a first-order transport lag system. Through comprehensive numerical simulations, the influence of various system parameters—including customer demand rate, delivery efficiency, information distortion, contingency reserve, safety stock, and transportation lag—are examined. The study utilizes bifurcation diagrams and a Lyapunov Exponent (LE) to investigate tran-sitions between periodic and chaotic behavior. Additionally, the model is extended with offset boosting control, allowing for controlled amplitude adjustment without altering the underlying chaotic dynamics. Offset boosting control (OBC) is useful in chaotic supply chain systems because it stabilizes inventory and order fluctuations by counter-acting the amplification of small disturbances, reducing the bullwhip effect, and im-proving overall system reliability and responsiveness. As an application, integral sliding mode control (ISMC) technique has been applied to achieve complete synchronization between a pair of the 5DCSCM. Synchronization based on ISMC is useful in chaotic supply chain systems because it ensures robust coordination between different tiers, suppresses chaos-induced fluctuations, and maintains stable inventory and order patterns even under disturbances and uncertainties. Full article

(This article belongs to the Special Issue Advanced Computational Modeling and Optimization in Operations Research and Supply Chain Management)

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40 pages, 1229 KB

Open AccessReview

Can Dietary Supplements Support Muscle Function and Physical Activity? A Narrative Review

by Louise Brough, Gail Rees, Lylah Drummond-Clarke, Jennifer E. McCallum, Elisabeth Taylor, Oleksii Kozhevnikov and Steven Walker

Nutrients 2025, 17(21), 3495; https://doi.org/10.3390/nu17213495 (registering DOI) - 6 Nov 2025

Abstract

Dietary supplementation is commonly used by athletes to gain muscle mass, enhance performance, and improve recovery. Most adults engage in insufficient physical activity. Yet healthy muscles are also critical for activities of daily living (ADLs), maintaining a good quality of life and positive [...] Read more.

Dietary supplementation is commonly used by athletes to gain muscle mass, enhance performance, and improve recovery. Most adults engage in insufficient physical activity. Yet healthy muscles are also critical for activities of daily living (ADLs), maintaining a good quality of life and positive ageing. There is growing interest in whether dietary supplementation is of value, particularly among subgroups such as the occasionally active, the ill and elderly, and peri- and menopausal women. By focusing on function, performance, mass and strength, ADLs, exercise-induced muscle damage and delayed onset muscle soreness, this review sought to examine muscle health through a nutritional lens. Further, to look at the potential benefits and harms of some commonly proposed dietary supplements in non-athlete adults, while exploring the emerging role of the gut–muscle axis. Inflammation appears central to cellular events. Several supplements were identified that, alone or in combination, may help optimise muscle health, particularly when combined with exercise or where a deficit may exist. Although supportive evidence is emerging, real-world clinical benefits remain to be substantiated. Though dietary supplements are generally safe, their regulation is less stringent than for medicines. Adherence to recommended dosage, seeking medical advice regarding possible side effects/interactions, and obtaining supplies from reliable sources are recommended. Full article

(This article belongs to the Special Issue Research Progress on Immune and Anti-Inflammatory Effects of Food Active Substances)

20 pages, 713 KB

Open AccessArticle

Social Responses and Change Management Strategies in Smart City Transitions: A Socio-Demographic Perspective

by Shadi Shayan and Ki Pyung Kim

Smart Cities 2025, 8(6), 188; https://doi.org/10.3390/smartcities8060188 (registering DOI) - 6 Nov 2025

Abstract

Technological advancements alone, without addressing public responses to social changes cannot ensure inclusive and sustainable smart city transitions as cities and societies comprise diverse individuals and communities with varied socio-demographic backgrounds. Thus, this research investigates social responses to smart city transitions aiming to [...] Read more.

Technological advancements alone, without addressing public responses to social changes cannot ensure inclusive and sustainable smart city transitions as cities and societies comprise diverse individuals and communities with varied socio-demographic backgrounds. Thus, this research investigates social responses to smart city transitions aiming to understand individuals’ social reactions to the changes across diverse socio-demographic profiles, and identify socio-demographic group-specific change management strategies to enhance public engagement and minimise resistance during the transition. Through a questionnaire survey using multivariate analysis, correlations between socio-demographic profiles and social reactions are identified. Age and frustration showed a positive correlation indicating that elderly individuals express greater concerns about unfamiliar smart technologies. Weak negative correlations emerged between income levels and transition-related stress including shock, frustration and depression. Significant differences were revealed between income groups (AUD 126,000+ and below AUD 90,000) associated with job security due to smart technologies and digital automation. Improving digital proficiency through free local government-led training, and reinforcing the benefits of digitally transformed urban environments through timely technical support were identified as the most essential change management strategies. Thus, this research will contribute to enabling local governments and policymakers to have practical insights in developing socially inclusive and community-centric transition plans with minimised social resistance. Full article

28 pages, 2366 KB

Open AccessArticle

High-Order Vibroacoustic Modal Analysis Framework for Fluid-Structure Coupling

by Dario Magliacano

Aerospace 2025, 12(11), 994; https://doi.org/10.3390/aerospace12110994 (registering DOI) - 6 Nov 2025

Abstract

This work develops and validates a high-order, three-dimensional Carrera Unified Formulation (CUF) framework for coupled structural–acoustic eigenanalysis, aiming at accurate low-frequency modal characterization of interior cavity-structure systems with significantly reduced degrees of freedom. The proposed approach employs high-order polynomial expansions to discretize both [...] Read more.

This work develops and validates a high-order, three-dimensional Carrera Unified Formulation (CUF) framework for coupled structural–acoustic eigenanalysis, aiming at accurate low-frequency modal characterization of interior cavity-structure systems with significantly reduced degrees of freedom. The proposed approach employs high-order polynomial expansions to discretize both the structural and fluid domains. The methodology integrates fully coupled fluid-structure analyses into a unified variational formulation, enabling the systematic assembly of global stiffness and mass matrices via sophisticated numerical integration techniques. Validation against a Comsol Multiphysics benchmark model confirms that the CUF-based high-order frameworks converge with significantly fewer degrees of freedom and reliably capture the intricate interactions at the fluid–structure interface. In addition, the approach is versatile, accommodating a range of boundary conditions and material models, underscoring its broad applicability in modern engineering design. Overall, this work advances the state of the art in vibroacoustic analysis by offering a robust tool for predicting natural frequencies and mode shapes, and it lays the groundwork for future extensions to nonlinear, transient, and data-driven applications. Full article

(This article belongs to the Section Aeronautics)

53 pages, 4351 KB

Open AccessReview

Epigallocatechin Gallate as a Molecular Therapeutic in Heart Failure and Cardio-Oncology: Mechanistic Pathways and Translational Perspectives

by Faika Ajaz, Jewel Haddad, Bintul Huda, Maryam Yousuf, Rajashree Patnaik, Farida Bhurka and Yajnavalka Banerjee

Int. J. Mol. Sci. 2025, 26(21), 10798; https://doi.org/10.3390/ijms262110798 (registering DOI) - 6 Nov 2025

Abstract

The global burden of heart failure (HF) continues to escalate, with a lifetime risk approaching one in four adults in the United States. Concurrently, advances in cancer therapeutics have created a burgeoning population of long-term survivors, who now face the significant morbidity and [...] Read more.

The global burden of heart failure (HF) continues to escalate, with a lifetime risk approaching one in four adults in the United States. Concurrently, advances in cancer therapeutics have created a burgeoning population of long-term survivors, who now face the significant morbidity and mortality of chemotherapy-induced cardiovascular disease (CVD). This review addresses the critical overlap of these two pathologies, which share fundamental drivers such as oxidative stress, inflammation, and metabolic dysregulation. Epigallocatechin gallate (EGCG), the most abundant and biologically active polyphenol in green tea, has demonstrated pleiotropic bioactivity in preclinical models, encompassing potent antioxidant, anti-inflammatory, and anti-apoptotic properties. The central aim of this review is to provide a critical and comprehensive synthesis of the evidence supporting EGCG’s dual protective role. This review dissects its molecular mechanisms in modulating key pathways in HF and cardio-oncology, evaluates its translational potential, and importantly, delineates the significant gaps that must be addressed for its clinical application. This analysis uniquely positions EGCG not merely as a nutraceutical, but as a multi-target molecular therapeutic capable of simultaneously addressing the convergent pathological cascades of heart failure and cancer-related cardiotoxicity. The synthesis of preclinical evidence with a critical analysis of its translational barriers offers a novel perspective and a strategic roadmap for future research. Full article

(This article belongs to the Section Molecular Biology)

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