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22 pages, 16937 KB

Open AccessArticle

Spatiotemporal Distribution of Highland Barley Yield Potential and Its Response to Climate Change in the Yarlung Zangbo River and Its Two Tributaries, Tibet

by Tingting Lang, Yuanqing Wang, Ying Liu, Xinzhe Song and Yanzhao Yang

Agriculture 2026, 16(10), 1125; https://doi.org/10.3390/agriculture16101125 (registering DOI) - 21 May 2026

Abstract

The yield of highland barley is not only related to the food security of Tibet but also to the social stability and development in the frontier region. This study revealed the spatiotemporal distribution of highland barley yield potential using the DSSAT model and [...] Read more.

The yield of highland barley is not only related to the food security of Tibet but also to the social stability and development in the frontier region. This study revealed the spatiotemporal distribution of highland barley yield potential using the DSSAT model and GIS technology in the Yarlung Zangbo River and its two tributaries (YZTT) of Tibet from 1981 to 2020, and analyzed its response relationship to climate factors. The results show that the highland barley yield potential ranged from 4284.75 to 7341.15 kg/ha in the YZTT region during 1981 to 2020, with an average of 6719.87 kg/ha. Under the climate change, the highland barley yield potential was on a downward trend of −14.49 kg/ha·a over the past 40 years. In terms of the response of highland barley yield potential to climate change, the highland barley yield potential decreased by 2.90 kg/ha for every 1 MJ/m² decrease in solar radiation. For every 1 °C increase in the maximum temperature, the highland barley yield potential increased by 219.68 kg/ha. Meanwhile, for every 1 °C increase in the minimum temperature, the highland barley yield potential increased by 91.40 kg/ha. These findings aim to provide reference for decision-making in agricultural policy and spatial allocation of agricultural resources. Full article

(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)

23 pages, 1636 KB

Open AccessArticle

Polyhydroxyalkanoate Production by Gordonia lacunae BS2^T in Hydrolysates of Canola FinesS

by Pamela J. Welz, Amrita Ranjan, Thandekile Mthethwa and Marilize le Roes-Hill

Fermentation 2026, 12(5), 250; https://doi.org/10.3390/fermentation12050250 (registering DOI) - 21 May 2026

Abstract

Microbial polyhydroxyalkanoates (PHAs) are biodegradable biopolymers that are gaining traction as replacements for conventional petroleum-based plastics. In this study, sugar utilization, growth and polyhydroxybutyrate (PHB) and polyhdroxyvalerate (PHV) production in synthetic and real hydrolysates of Canola fines (SHCF, RHCF) by Gordonia lacunae BS2 [...] Read more.

Microbial polyhydroxyalkanoates (PHAs) are biodegradable biopolymers that are gaining traction as replacements for conventional petroleum-based plastics. In this study, sugar utilization, growth and polyhydroxybutyrate (PHB) and polyhdroxyvalerate (PHV) production in synthetic and real hydrolysates of Canola fines (SHCF, RHCF) by Gordonia lacunae BS2^T were evaluated: (i) in SHCF under different C:N ratios and O₂ availability, and (ii) in SHCF and RHCF (50% and 100%) under shaking v/s static conditions with limited or non-limited O₂. The bacterium was able to utilize glucose, cellobiose, arabinose, and xylose. Athough O₂ limitation reduced growth, higher measured concentrations of 3-hydroxyvalerate (3HV) were achieved under O₂ limitation, translating into slightly higher 3-hydroxybutyrate (3HB)+3HV yields (15.4 ± 2.36 %wt.wt.) than under non-O₂ limited conditions (12.4 ± 2.26 %wt.wt.). Notably, 50% RHCF was the most suitable medium for growth and PHB+PHV production, while 100% RHCF was the least suitable. The 3HV+3PV concentration (0.35 g/L), 3HV fraction (24%), and yield (15.4 %wt.wt.) in 50% RHCF were highest under static, O₂-limited conditions, corresponding with negligible sugar utilization (1.6 mg/day.100 mL⁻¹ glucose) and suggesting alternative metabolic pathways using other substrates in the RHCF for growth. Nuclear magnetic resonance results indicated that Gordonia lacunae BS2^T produces a desirable co-polymer (PHBV), paving the way for ongoing research using this bacterium. Full article

(This article belongs to the Special Issue Novel and Old Insights for Biotechnological Exploitation of Actinomycetota Strain Fermentations)

23 pages, 3652 KB

Open AccessArticle

Deconstructing Multi-Scale Hybrid Fiber-Reinforced Coarse Aggregate UHPC: From Pore Structure Tailoring to Cross-Scale Toughening

by Jiyang Wang, Yalong Wang, Lingbo Wang, Yu Peng, Qi Zhang, Jingwen Shi, Xianmo Xu and Shuyu Lin

Materials 2026, 19(10), 2171; https://doi.org/10.3390/ma19102171 (registering DOI) - 21 May 2026

Abstract

Ultra-high-performance concrete incorporating coarse aggregates (UHPC-CA) exhibits pronounced multi-scale heterogeneity and staged damage evolution. However, existing single-scale reinforcement strategies often fail to address the complete micro-to-macro fracture process, leaving a critical research gap in achieving full-stage crack control. To address this, this study [...] Read more.

Ultra-high-performance concrete incorporating coarse aggregates (UHPC-CA) exhibits pronounced multi-scale heterogeneity and staged damage evolution. However, existing single-scale reinforcement strategies often fail to address the complete micro-to-macro fracture process, leaving a critical research gap in achieving full-stage crack control. To address this, this study introduces a novel cross-scale toughening strategy using hybrid steel fibers (SF) and calcium carbonate whiskers (CCW), and decouples the coupled influences of water-to-binder (W/B) ratio, coarse aggregate (CA), and multi-scale fibers via an orthogonal design. Mechanical properties, fiber dispersion, and pore structure are jointly characterized to establish structure–property relationships. An optimal composition (W/B = 0.32, CA = 18%, SF = 2%, CCW = 1%) is identified, achieving a balanced enhancement of strength and ductility. Results indicate that matrix densification is primarily controlled by W/B via pore refinement, while mechanical performance is governed by the interplay between fiber spatial uniformity and interfacial integrity; the roles of CA and CCW are clearly stress-state dependent. Furthermore, a novel cross-scale synergistic mechanism is revealed, in which micro-scale CCW regulates microcrack initiation and stabilizes the pre-peak response, whereas macro-scale SF dominates post-peak behavior through crack bridging and pull-out energy dissipation. This sequential activation enables a full-stage enhancement of tensile performance, shifting failure from brittle localization to pseudo-ductile multiple cracking. The findings provide a correlative framework for tailoring UHPC-CA through multi-scale hybrid reinforcement. Full article

(This article belongs to the Special Issue Advances in Ultra-High Performance Concretes and Cementitious Composites (2nd Edition))

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35 pages, 2286 KB

Open AccessArticle

A Bi-Level MIQP + SAC Framework for Short-Term Optimal Scheduling of a Hydro–PV–Battery Energy Storage System

by Haoyan Zhang, Jing Qian, Haocheng He and Danning Tian

Energies 2026, 19(10), 2479; https://doi.org/10.3390/en19102479 (registering DOI) - 21 May 2026

Abstract

With the increasing integration of photovoltaic (PV) generation, short-term scheduling of hydro–PV–battery energy storage systems (HPBS) faces growing challenges due to the stochastic variability of PV output, the temporal coupling of hydropower operation, and the accumulation of deviations during the real-time execution of [...] Read more.

With the increasing integration of photovoltaic (PV) generation, short-term scheduling of hydro–PV–battery energy storage systems (HPBS) faces growing challenges due to the stochastic variability of PV output, the temporal coupling of hydropower operation, and the accumulation of deviations during the real-time execution of day-ahead schedules. This paper proposes a bi-level coordinated scheduling framework that integrates day-ahead mixed-integer quadratic programming (MIQP) with intraday Soft Actor–Critic (SAC)-based correction. In the upper layer, MIQP generates a 24 h baseline schedule subject to unit output limits, mutually exclusive charging/discharging logic, and operational constraints. In the lower layer, SAC performs bounded real-time residual correction for hydropower and battery storage around the MIQP baseline, while a deviation-triggered replanning mechanism forms a closed-loop process of planning, execution, correction, and replanning. Comparative experiments under the tested setting show that SAC achieves better overall performance than Deep Deterministic Policy Gradient (DDPG), Twin Delayed Deep Deterministic Policy Gradient (TD3), and Proximal Policy Optimization (PPO). Typical-day evaluations under dry-, normal-, and wet-season conditions show that, in the selected case studies, the proposed MIQP + SAC framework achieves better performance than standalone MIQP and MIQP-Replan, which refers to a deviation-triggered MIQP re-optimization strategy, in load tracking, PV curtailment reduction, and hydro-storage coordination. These results indicate the effectiveness of the proposed framework for short-term HPBS scheduling under representative operating conditions. Full article

24 pages, 1304 KB

Open AccessArticle

A Causally Constrained Framework Coupling Causal Discovery and SEIR Mechanisms for Interpretable Epidemic Modeling

by Rui Zhu, Yijiang Zhao, Zhixiong Fang and Yizhi Liu

Mathematics 2026, 14(10), 1776; https://doi.org/10.3390/math14101776 (registering DOI) - 21 May 2026

Abstract

Infectious disease transmission is a complex dynamic process governed by intrinsic causal mechanisms rather than simple statistical correlations. Although deep learning paradigms have demonstrated powerful nonlinear representation capabilities, their “black-box” and purely data-driven nature often lead to a severe lack of causal consistency [...] Read more.

Infectious disease transmission is a complex dynamic process governed by intrinsic causal mechanisms rather than simple statistical correlations. Although deep learning paradigms have demonstrated powerful nonlinear representation capabilities, their “black-box” and purely data-driven nature often lead to a severe lack of causal consistency and logical transparency. To bridge this gap, this paper proposes CCSANet (Causally Constrained SEIR-Aware Network), an interpretable forecasting framework that seamlessly embeds epidemiological priors directly into the neural architecture. The model integrates SEIR dynamics into a temporal causal discovery framework, utilizing a mechanism-aware prior loss to guide a CausalFormer in learning a global temporal causal graph from multi-source heterogeneous data. This ensures that the identified relationships strictly adhere to the fundamental evolutionary logic of contagion. Subsequently, the extracted causal subgraphs are encoded as structural priors within a Causal-SCI-Block via a specialized masking mechanism, effectively forcing information to propagate exclusively along epidemiologically legitimate pathways. To ensure deep alignment between neural representations and physical reality, a causal strength alignment loss is introduced to synchronize the network’s attention weights with actual transmission intensities. Experimental evaluations on real-world multi-city datasets demonstrate that this integrated approach significantly outperforms baselines such as LSTM, Informer, and its predecessor, ESASNet. Under a 7-day sliding window configuration, the model maintains a Coefficient of Determination

R^{2}

stably above 0.97, achieving an accuracy improvement of 5.5% to 6.2% and an 8% to 10% reduction in SMAPE, thereby demonstrating that coupling causal discovery with SEIR constraints substantially enhances both predictive precision and physical interpretability. Full article

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26 pages, 3867 KB

Open AccessArticle

Attitude Stabilization Control Methods for a Tracked Agricultural Transport Platform in Hilly and Mountainous Terrain Based on Adaptive Kalman Filtering

by Yongjun Sun, Yaqin Tong, Jiachen Ding, Yejun Zhu, Weihua Wei, Maohua Xiao and Guosheng Geng

Agriculture 2026, 16(10), 1123; https://doi.org/10.3390/agriculture16101123 (registering DOI) - 21 May 2026

Abstract

This study proposes an attitude stabilization method based on an improved adaptive Kalman filter (AKF). The aim is to address attitude fluctuations and rollover risks in rail-based agricultural transport platforms on hilly terrain caused by slope changes, load shifts and vibrations. A dynamic [...] Read more.

This study proposes an attitude stabilization method based on an improved adaptive Kalman filter (AKF). The aim is to address attitude fluctuations and rollover risks in rail-based agricultural transport platforms on hilly terrain caused by slope changes, load shifts and vibrations. A dynamic model integrating the load distribution and center-of-mass migration was established, and an adaptive noise covariance mechanism was used to precisely estimate the roll and pitch angles in real time. A dual-channel proportional–integral–derivative controller was designed for automatic leveling, and a rollover risk index (RRI) was adopted for safety evaluation. Simulations revealed the ability of the improved AKF to decrease the roll estimation (RMSE) from 1.2684° to 0.8670° and the stabilization time from 0.6250 to 0.3830 s for the roll and from 0.6930 to 0.4110 s for the pitch. Under 10–30° slope disturbances, the average RRI decreased from 0.1861 to 0.1506. Field tests further demonstrated decreases in the peak roll and pitch angles from 4.8° and 4.1° to 3.1° and 2.7°, respectively, and a decrease in the average RRI from 0.203 to 0.169. The improvements in estimation accuracy, leveling performance, and operational safety under complex disturbances indicate the strong engineering potential of the proposed method. Full article

(This article belongs to the Section Agricultural Technology)

30 pages, 17171 KB

Open AccessArticle

Optical Gas Imaging with Cooled and Uncooled Thermal Infrared Cameras

by Gabriel Jobert, Nicolas Vannier, Charlène Lefèvre, Eléa Bourliaud, Adrien Bertrand, Emmanuelle Chazelle and Eric Mallet

Sensors 2026, 26(10), 3270; https://doi.org/10.3390/s26103270 (registering DOI) - 21 May 2026

Abstract

In a context of greenhouse-gas-reduction for climate-change mitigation, Optical Gas Imaging (OGI) is cited by US and EU regulations as a key technology for detecting methane leaks in the oil and gas industry. The paper outlines the principles of OGI, covering specificity of [...] Read more.

In a context of greenhouse-gas-reduction for climate-change mitigation, Optical Gas Imaging (OGI) is cited by US and EU regulations as a key technology for detecting methane leaks in the oil and gas industry. The paper outlines the principles of OGI, covering specificity of both high-performance cooled cameras and cost-effective thermal infrared uncooled cameras. It explains camera design, the optical-radiometric theory of contrast and sensitivity, and provides a comprehensive description of the key performance indicators (KPIs) such as NETD, NECL, and MDLR; together with parameters that influence them. These theoretical concepts are supported by measurements taken under laboratory conditions and outdoors, with wind and complex scenes. Finally, video-processing methods for visualizing gas leaks are presented, showing how they increase visual sensitivity and reduce the user’s cognitive load. Full article

(This article belongs to the Section Optical Sensors)

23 pages, 2491 KB

Open AccessArticle

Firm Entry, Environmental Regulation, and Air Pollution: Evidence from China’s Air Pollution Prevention and Control Action Plan

by Kaiyi Guo, Rundong Luo and Tianyue Pei

Sustainability 2026, 18(10), 5202; https://doi.org/10.3390/su18105202 (registering DOI) - 21 May 2026

Abstract

This paper examines how local firm entry affects air pollution and whether the Air Pollution Prevention and Control Action Plan (APPCAP) changes this relationship. Using a county–month panel for 2010–2020, we match the Chinese Industrial and Commercial Enterprise Registration Database with county-level monthly [...] Read more.

This paper examines how local firm entry affects air pollution and whether the Air Pollution Prevention and Control Action Plan (APPCAP) changes this relationship. Using a county–month panel for 2010–2020, we match the Chinese Industrial and Commercial Enterprise Registration Database with county-level monthly PM2.5 data to measure new firm entry and its sectoral composition. To address the potential endogeneity of firm entry, we use the opening of high-speed rail as an instrumental variable. The results show that firm entry significantly increases county-level PM2.5 concentrations. This effect is highly heterogeneous across industries, with stronger pollution effects in sectors such as wholesale and retail, manufacturing, and accommodation and catering. We further find that the APPCAP significantly weakens the positive effect of firm entry on air pollution. Additional evidence suggests that the policy improves air quality not only by tightening environmental constraints, but also by shifting firm entry toward relatively cleaner industries. This paper explains the environmental consequences of local economic expansion from the perspective of incremental firm entry and provides new evidence on the joint role of environmental regulation and industrial restructuring in air pollution control. Full article

(This article belongs to the Section Air, Climate Change and Sustainability)

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42 pages, 3786 KB

Open AccessArticle

Hybrid Validation of a Quality-Controlled, Waveform-Centered AI Framework with Optional Multi-Sensor Support for Seismic Monitoring

by Askar Abdykadyrov, Yerik Alipuly, Maxat Mamadiyarov, Bekbolat Tashev, Akerke Yerkinova and Kalmukhamed Tazhen

Sensors 2026, 26(10), 3269; https://doi.org/10.3390/s26103269 (registering DOI) - 21 May 2026

Abstract

Rapid and reliable seismic monitoring requires accurate waveform inference, together with robustness to noise, incomplete sensing, and unstable predictions. This study investigates a quality-controlled, waveform-centered, AI-assisted framework for seismic event detection, P- and S-phase picking, graph-aware inter-station refinement, and rapid hazard-related characterization. The [...] Read more.

Rapid and reliable seismic monitoring requires accurate waveform inference, together with robustness to noise, incomplete sensing, and unstable predictions. This study investigates a quality-controlled, waveform-centered, AI-assisted framework for seismic event detection, P- and S-phase picking, graph-aware inter-station refinement, and rapid hazard-related characterization. The framework includes optional DAS, MEMS, and high-rate GNSS branches; however, the primary empirical validation is based on real waveform-centered IRIS records from the Almaty seismic region, not on a fully synchronized multimodal field deployment. The dataset includes seven seismic stations, HHZ waveforms sampled at 100 Hz, 219 seismic events, 1260 event traces, and 240 s P-centered windows from 1 January 2023 to 31 December 2024. Optional auxiliary branches are evaluated through controlled branch-availability, reduced-input, fallback, and stress-test scenarios. Under the standard-condition benchmark, the proposed framework achieved a precision of 0.941, recall of 0.932, F1 score of 0.936, false-alarm rate of 0.051, detection latency of 173 ms, and P- and S-pick mean absolute errors of 31 ms and 54 ms. Under controlled low-SNR testing, it retained an F1 score of 0.846. The findings support waveform-centered, quality-controlled monitoring, while broader cross-domain and fully synchronized multimodal validation remain necessary. Full article

(This article belongs to the Section Intelligent Sensors)

15 pages, 13547 KB

Open AccessArticle

Protective Effects of Vitis coignetiae Vine Stem Extract Against Carbon Tetrachloride-Induced Acute Liver Injury in Mice

by Nam-Kyu Yoon, Jeongjun Lee, Hunsuk Chung, Jae-Kwang Kim and Sae-Kwang Ku

Antioxidants 2026, 15(5), 651; https://doi.org/10.3390/antiox15050651 (registering DOI) - 21 May 2026

Abstract

Vitis coignetiae Pulliat ex Planch, commonly referred to as “meoru” in Korea (crimson glory vine), is a grape species belonging to the Vitaceae family, native to East Asia. This study investigated the protective effects of a hot water extract prepared from the vine [...] Read more.

Vitis coignetiae Pulliat ex Planch, commonly referred to as “meoru” in Korea (crimson glory vine), is a grape species belonging to the Vitaceae family, native to East Asia. This study investigated the protective effects of a hot water extract prepared from the vine stems of V. coignetiae (CG) in a model of CCl₄-induced acute liver injury. Mice received oral administration of CG (100, 200, and 400 mg/kg) or silymarin (200 mg/kg) once daily for 7 consecutive days, followed by intraperitoneal injection of CCl₄ (0.5 mL/kg). CG attenuated CCl₄-induced oxidative stress, as indicated by reduced hepatic malondialdehyde production and decreased 4-hydroxynonenal-positive cells. These effects were accompanied by restoration of antioxidant defense systems, including increased glutathione levels and superoxide dismutase and catalase activities, along with increased nuclear factor erythroid 2-related factor 2 (Nrf2) mRNA expression. Hepatic inflammatory responses were also attenuated by CG treatment, with reductions in TNF-α, interleukin (IL)-1β, and IL-6 levels, inflammatory cell infiltration, and nuclear factor-κB (NF-κB) mRNA expression. Furthermore, CG attenuated apoptotic cell death, as evidenced by decreased cleaved caspase-3-positive and cleaved poly(ADP-ribose) polymerase (PARP)-positive cells. CG also lowered serum aspartate aminotransferase, alanine aminotransferase, and γ-glutamyl transferase levels, and alleviated hepatocellular degeneration in histopathological analysis. Collectively, these findings suggest that CG may exert protective effects against CCl₄-induced liver injury by regulating oxidative stress, inflammation, and apoptosis. Full article

(This article belongs to the Special Issue Oxidative Stress in Hepatic Diseases)

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24 pages, 616 KB

Open AccessReview

Regulatory T Cells in Hepatocellular Carcinoma: Spatial Niches, Biomarkers, and Clinical Implications

by Dimitris Liapopoulos, Panagiotis Sarantis, Georgios Zogas, Eleni-Myrto Trifylli, Thaleia-Eleftheria Bousou, Konstantina Kamitaki, Ioanna A. Anastasiou, Stefania Kokkali, Sotiris Mavromatis, Evangelos Koustas, Ioannis Elefsiniotis, Theodora Biniari and Michalis V. Karamouzis

Int. J. Mol. Sci. 2026, 27(10), 4630; https://doi.org/10.3390/ijms27104630 (registering DOI) - 21 May 2026

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality worldwide, increasingly driven by metabolic dysfunction-associated steatotic liver disease alongside viral and alcohol-related cirrhosis. The tolerogenic immune environment of the liver enables tumor immune escape, with regulatory T cells (Tregs) playing a central [...] Read more.

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality worldwide, increasingly driven by metabolic dysfunction-associated steatotic liver disease alongside viral and alcohol-related cirrhosis. The tolerogenic immune environment of the liver enables tumor immune escape, with regulatory T cells (Tregs) playing a central role. This review synthesizes human-focused evidence (tissues, blood, clinical cohorts, and single-cell/spatial studies) through September 2025 to define how Tregs are recruited, maintained, and functionally deployed in HCC. Across datasets, intratumoral effector-like Tregs (eTregs) expressing ICOS, CTLA-4, CCR8, and CD39/CD73 accumulate within tumors and co-localize with exhausted cytotoxic PD-1^hi CD8⁺ T cells and suppressive myeloid cells. Recruitment is driven mainly by CCL20–CCR6 and CCL22/CCL17–CCR4 signaling, while CCR8 marks highly suppressive tumor-resident Tregs. Their persistence is supported by TGF-β, IL-10, IL-35, adenosine signaling, IL-2 sequestration, and metabolic adaptation. Spatial biomarkers, including ICOS⁺/CCR8⁺ eTreg density and CD8:Treg ratios, associate with prognosis and emerging immunotherapy responses. Etiology further shapes immune architecture: HBV-related HCC often forms Treg-exhausted T-cell niches around viral antigens, whereas MASLD/MASH promotes stromal and metabolic barriers that may reduce PD-(L)1 efficacy. Current treatments (PD-(L)1 blockade with anti-VEGF or CTLA-4, and some TKIs) intersect with Treg biology, while emerging strategies targeting CCR8, CCR4, ICOS, or the adenosine pathway aim to selectively disrupt intratumoral eTreg networks. This review underscores that an etiology-aware, spatial-biomarker framework may guide the integration of selective Treg targeting with PD-(L)1-based therapies in HCC. Full article

(This article belongs to the Special Issue Next-Gen Biomarkers for Cancer Immunotherapy)

13 pages, 322 KB

Open AccessArticle

Existence and Blow-Up of Compressible Spherically Symmetric Euler Equations with Vacuum Free Boundary

by Lijun Zhang, Junmei Shi and Chaudry Masood Khalique

Mathematics 2026, 14(10), 1775; https://doi.org/10.3390/math14101775 (registering DOI) - 21 May 2026

Abstract

This paper studies the compressible spherically symmetric Euler equations with a vacuum free boundary, a fundamental model for astrophysical gas dynamics. We rigorously resolve an open problem by proving that nontrivial homogeneous linear velocity solutions exist if, and only if, the adiabatic exponent [...] Read more.

This paper studies the compressible spherically symmetric Euler equations with a vacuum free boundary, a fundamental model for astrophysical gas dynamics. We rigorously resolve an open problem by proving that nontrivial homogeneous linear velocity solutions exist if, and only if, the adiabatic exponent

γ = 4 / 3

, the critical value for monatomic gases and radiative stellar atmospheres. Using qualitative analysis of the reduced planar dynamical system, we characterize the flow’s global existence and finite-time blow-up behavior, establish a sharp existence threshold, and derive an explicit upper bound for the blow-up time. Quantitative energy estimates via Bernoulli’s head verify the physical consistency of solutions in both regimes. Our results complete the classification of self-similar solutions in this class, laying a rigorous theoretical foundation for planetary atmospheric gas flows and providing a practical criterion for predicting blow-up. Full article

(This article belongs to the Special Issue Computational Mechanics and Applied Mathematics, 2nd Edition)

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29 pages, 1788 KB

Open AccessArticle

Pomegranate Peel Powder as a Functional Ingredient in Yogurt: Effects on Bioactive Profile, Physicochemical Properties, Microstructure, Texture, and Sensory Quality

by Andra Dorina Șuler, Roxana Nicoleta Rațu, Florina Stoica, Petru Marian Cârlescu, Andreea Bianca Balint, Ioana Cristina Crivei, Ionuț Dumitru Velescu, Iuliana Motrescu, Florin Daniel Lipsa and Gabriela Râpeanu

Appl. Sci. 2026, 16(10), 5157; https://doi.org/10.3390/app16105157 (registering DOI) - 21 May 2026

Abstract

Pomegranate peel, an agro-industrial by-product, is a promising source of functional compounds. This study evaluated pomegranate peel powder (PP) as a multifunctional yogurt ingredient and assessed its effects on the phytochemical profile, antioxidant activity, physicochemical properties, color, texture, microstructure, mineral composition, storage stability, [...] Read more.

Pomegranate peel, an agro-industrial by-product, is a promising source of functional compounds. This study evaluated pomegranate peel powder (PP) as a multifunctional yogurt ingredient and assessed its effects on the phytochemical profile, antioxidant activity, physicochemical properties, color, texture, microstructure, mineral composition, storage stability, and sensory acceptability. Yogurts supplemented with 3% and 6% PP were compared with a control. PP contained 12.49 mg GAE/g dw total polyphenols, 9.16 mg CE/g dw flavonoids, 63.66 mg C3G/100 g dw anthocyanins, 17.48% dietary fiber, 341.88 mg/100 g calcium, and 140.99 mg/100 g magnesium. PP addition improved yogurt functionality in a concentration-dependent manner. The 6% formulation showed the highest total polyphenol content (9.71 mg GAE/g dw), antioxidant activity (63.67 µmol TE/g dw), dry matter (19.20 g/100 g), and dietary fiber (1.19 g/100 g). Syneresis decreased from 18.22% in the control to 12.17% and 9.22% in the 3% and 6% PP yogurts, respectively, while firmness increased from 3.85 N to 4.80 N. After 21 days of refrigerated storage, fortified yogurts retained high phytochemical and antioxidant levels. Although the 6% formulation provided greater enrichment, the 3% yogurt offered the best balance between functionality, technological performance, and sensory quality, supporting PP valorization in cleaner-label dairy products. Full article

(This article belongs to the Special Issue Functional Foods and Active Natural Products)

22 pages, 5508 KB

Open AccessArticle

Tracking of Neuroinflammation Dynamics During Combined Anti-β-Amyloid Therapy (AAT) and Immunomodulation in a Preclinical Alzheimer’s Disease Model

by Karin Wind-Mark, Lea H. Kunze, Michael Willem, Giovanna Palumbo, Camilla Giudici, Brigitte Nuscher, Guido Boening, Franz J. Gildehaus, Simon Lindner, Rudolf A. Werner, Nicolai Franzmeier, Johannes S. Gnörich, Matthias Brendel and Artem Zatcepin

Int. J. Mol. Sci. 2026, 27(10), 4632; https://doi.org/10.3390/ijms27104632 (registering DOI) - 21 May 2026

Abstract

Neuroinflammation is increasingly recognized as a key modulator of therapeutic response and adverse events in Alzheimer’s disease (AD), especially during anti-amyloid-β (Aβ) monoclonal antibody (Aβ-mAb) treatment. We applied longitudinal translocator protein (TSPO) positron emission tomography (PET) to evaluate TSPO-associated neuroinflammatory responses to chronic [...] Read more.

Neuroinflammation is increasingly recognized as a key modulator of therapeutic response and adverse events in Alzheimer’s disease (AD), especially during anti-amyloid-β (Aβ) monoclonal antibody (Aβ-mAb) treatment. We applied longitudinal translocator protein (TSPO) positron emission tomography (PET) to evaluate TSPO-associated neuroinflammatory responses to chronic Aβ-mAb therapy and their modulation by the peroxisome proliferator-activated receptor γ (PPARγ) agonist pioglitazone. App^NL-G-F knock-in mice underwent TSPO-PET and Aβ-PET imaging at 5, 7.5, and 10 months of age across four treatment arms: placebo, Aβ-mAb, pioglitazone, and combination therapy. TSPO-PET detected early and progressive neuroinflammatory responses to Aβ-mAb that appeared lower with pioglitazone co-treatment. Both mono- and combination therapy were associated with altered temporal and spatial dynamics of the TSPO-PET signal. In addition, we applied a previously validated microglia desynchronization index based on TSPO-PET connectivity, which captured individual variation in regional TSPO-PET organization and correlated with cognitive performance. Together, TSPO-PET and its regional synchronicity can quantify longitudinal, region-specific treatment effects, which may help differentiate harmful from adaptive neuroinflammatory responses. These findings highlight the potential of TSPO-PET as a stratification biomarker to optimize therapeutic interventions. TSPO-PET therefore enables in vivo tracking of treatment-associated neuroinflammatory responses during anti-Aβ immunotherapy and provides a non-invasive framework for evaluating combination strategies targeting amyloid pathology and immune regulation in AD. Full article

(This article belongs to the Special Issue Molecular Advances in Neuroimaging)

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20 pages, 1873 KB

Open AccessArticle

Geometric Bias and Centrality Dependence of Jet Quenching in High-Energy Nuclear Collisions

by Changle Sun, Yichao Dang and Shanshan Cao

Universe 2026, 12(5), 150; https://doi.org/10.3390/universe12050150 (registering DOI) - 21 May 2026

Abstract

Jet quenching provides a valuable measure of the opacity of the quark–gluon plasma (QGP) produced in high-energy heavy-ion collisions. However, substantial suppression of charged hadron spectra is observed in highly peripheral collisions, despite the expectation of negligible jet–QGP interactions in this regime. To [...] Read more.

Jet quenching provides a valuable measure of the opacity of the quark–gluon plasma (QGP) produced in high-energy heavy-ion collisions. However, substantial suppression of charged hadron spectra is observed in highly peripheral collisions, despite the expectation of negligible jet–QGP interactions in this regime. To address this, we develop a HIJING-based initial condition model that accounts for the impact parameter dependence of both inelastic nucleon–nucleon (NN) collisions and the number of hard partonic scatterings per inelastic NN collision. This dependence introduces a geometric bias effect on the jet yield within a given centrality class of nucleus–nucleus (AA) collisions, suppressing the high-

p_{T}

hadron spectrum in peripheral collisions due to dilute nucleon overlap at large AA impact parameters. By combining this improved initial condition model with a linear Boltzmann transport model for jet–QGP interactions, we obtain a satisfactory description of the centrality dependence of charged hadron suppression in Pb+Pb collisions at

\sqrt{s_{NN}} = 5.02

TeV. Full article

(This article belongs to the Special Issue Relativistic Heavy-Ion Collisions: Theory and Observation)

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43 pages, 10370 KB

Open AccessReview

Carbon Dots in Nanomedicine: Advanced Fabrication, Biomedical Applications, and Future Clinical Perspectives

by Muhammad Sohail Khan, Imran Zafar, Dayeon Ham, Ki Sung Kang and Il-Ho Park

Pharmaceutics 2026, 18(5), 632; https://doi.org/10.3390/pharmaceutics18050632 (registering DOI) - 21 May 2026

Abstract

Carbon dots (CDs), including carbon quantum dots (CQDs), are ultra-small carbon-based nanomaterials, typically below 10 nm, with tunable photoluminescence, high aqueous dispersibility, favorable biocompatibility, low toxicity, and abundant surface functional groups. These properties make CDs promising multifunctional platforms for nanomedicine, particularly in bioimaging, [...] Read more.

Carbon dots (CDs), including carbon quantum dots (CQDs), are ultra-small carbon-based nanomaterials, typically below 10 nm, with tunable photoluminescence, high aqueous dispersibility, favorable biocompatibility, low toxicity, and abundant surface functional groups. These properties make CDs promising multifunctional platforms for nanomedicine, particularly in bioimaging, biosensing, targeted drug/gene delivery, photodynamic therapy (PDT), photothermal therapy (PTT), antimicrobial treatment, and theranostic applications. This review critically examines recent advances in CD fabrication, including top-down, bottom-up, green biomass-derived, microwave-assisted, hydrothermal, and emerging hybrid strategies, with emphasis on how precursor selection, heteroatom doping, surface passivation, and polymer/ligand functionalization regulate optical performance, biological interaction, and therapeutic efficiency. The review discusses structural classification, including CQDs, graphene quantum dots (GQDs), carbon nanodots, and carbonized polymer dots (CPDs), together with major characterization approaches such as ultraviolet–visible (UV–Vis) spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and high-resolution transmission electron microscopy (HRTEM). Particular attention is given to red/near-infrared (NIR) emission, renal clearance, drug-loading behavior, reactive oxygen species (ROS) generation, toxicity mechanisms, biodistribution, and long-term biosafety. This review also highlights key translational barriers, including batch-to-batch variability, limited standardization, scalable manufacturing, regulatory uncertainty, and incomplete pharmacokinetic evaluation. It considers artificial intelligence (AI) and machine learning (ML) as emerging tools for reproducible CD design. CDs represent versatile and clinically promising nanoplatforms, but their translation requires standardized synthesis, rigorous safety assessment, and application-specific regulatory validation. Full article

(This article belongs to the Special Issue Nanomaterials for Cell Biological and Biomedical Applications)

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32 pages, 6072 KB

Open AccessArticle

Assessing Urban Vulnerability Through a Multi-Hazard Framework with Independent Events Modelling

by Glenda Mascheri, Nicola Chieffo, Cláudia Pinto and Paulo B. Lourenço

Appl. Sci. 2026, 16(10), 5154; https://doi.org/10.3390/app16105154 (registering DOI) - 21 May 2026

Abstract

Natural hazards and their negative impacts on assets are increasing because of a variety of causes, including climate change, population expansion, and urbanization. Moreover, several areas are susceptible to multiple hazards that interact spatially and/or temporally, necessitating a multi-hazard assessment to adequately mitigate [...] Read more.

Natural hazards and their negative impacts on assets are increasing because of a variety of causes, including climate change, population expansion, and urbanization. Moreover, several areas are susceptible to multiple hazards that interact spatially and/or temporally, necessitating a multi-hazard assessment to adequately mitigate their effects. The goal of this study is to investigate the direct monetary losses produced by the simultaneous interaction of two independent hazards in Lisbon’s city centre, i.e., earthquake and pluvial flood. Seismic hazard has been assessed in terms of macro-seismic intensity, while flood scenario allows for the prediction of water depth for different return periods through a hydrologic-hydraulic model in HEC-RAS software. The seismic and flood vulnerability of the urban investigated compound was evaluated through MCDM methodology—specifically, AHP and TOPSIS methods. A framework for multi-hazard analysis was subsequently developed, explicitly accounting for the interaction between the two hazards and their joint occurrence probabilities based on historical data from the case study area. The results demonstrate that multi-hazard losses are 108 M€ for a 2-year return period and 232 M€ for a 475/500-year scenario, emphasizing that floods contribute more across all return periods in the research area; however, for longer return periods, the earthquake contribution increases significantly. Full article

(This article belongs to the Special Issue Digital Multi-Hazard Risk Modelling and Life-Cycle Assessment for Next-Generation Resilient and Sustainable Built Environments)

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24 pages, 2250 KB

Open AccessArticle

From Generic to Adaptive: Similarity-Adaptive Receptive-Field Cross DETR for Remote-Sensing Object Detection

by Chenyu Lin, Yunzhan Fu, Hang Xu, Xuyang Teng and Tingyu Wang

Remote Sens. 2026, 18(10), 1670; https://doi.org/10.3390/rs18101670 (registering DOI) - 21 May 2026

Abstract

Object detection in optical remote sensing imagery faces persistent challenges from severe instance overlap, extreme spatial density, and motion or atmospheric blur. These degradations cause conventional detectors to over-mix neighboring instance features and fail to separate closely packed objects. To address these limitations, [...] Read more.

Object detection in optical remote sensing imagery faces persistent challenges from severe instance overlap, extreme spatial density, and motion or atmospheric blur. These degradations cause conventional detectors to over-mix neighboring instance features and fail to separate closely packed objects. To address these limitations, we propose SARC-DETR, a detection framework that augments the RT-DETR architecture with two complementary plug-in modules: Similarity Adaptive Convolution (SAC) and Receptive Field Cross Convolution (RCC). SAC introduces a reproducing-kernel-Hilbert-space (RKHS) motivated similarity gate that selectively suppresses responses inconsistent with local feature prototypes, thereby reducing cross-instance interference in overlapped and blurred regions. RCC constructs a large directional receptive field through orthogonal strip-based aggregation and content-adaptive fusion, enabling efficient long-range context capture without quadratic complexity overhead. Both modules can be integrated into existing DETR-style detectors without modifying the detection head or training protocol. On VisDrone2019-DET, SARC-DETR improves

{AP}^{val}

from 29.7 to 34.8,

{AP}_{50}^{val}

from 49.5 to 56.2, and

{AP}_{S}^{val}

from 19.2 to 24.8. On DIOR, AP rises from 57.9 to 68.4, and on NWPU VHR-10, from 44.4 to 66.5, demonstrating robust cross-dataset generalization. After structural reparameterization, the additional overhead is less than 0.75 M parameters and 0.36 G FLOPs, confirming deployment suitability for UAV and satellite-based remote sensing applications. Full article

(This article belongs to the Special Issue Deep Learning-Based Interpretation and Processing of Remote Sensing Images)

31 pages, 20058 KB

Open AccessArticle

Hidden Forest in Non-Forest Land: A Remote Sensing-Based Mapping Case in Lithuania

by Monika Papartė, Donatas Jonikavičius and Gintautas Mozgeris

Remote Sens. 2026, 18(10), 1665; https://doi.org/10.3390/rs18101665 (registering DOI) - 21 May 2026

Abstract

Woody vegetation growing outside officially designated forest land represents a significant but poorly quantified resource in many countries, where institutional and methodological limitations hinder its systematic accounting. This study develops and applies a multi-stage remote sensing-based framework to identify and characterize forest-eligible areas [...] Read more.

Woody vegetation growing outside officially designated forest land represents a significant but poorly quantified resource in many countries, where institutional and methodological limitations hinder its systematic accounting. This study develops and applies a multi-stage remote sensing-based framework to identify and characterize forest-eligible areas (FEAs) in Lithuania by integrating airborne LiDAR, Sentinel-2 time series, historical orthophotos, and national geospatial datasets. The workflow combines (i) LiDAR-derived canopy height model generation and object-based segmentation, (ii) rule-based aggregation of vegetation segments according to legal forest criteria, (iii) multi-index Sentinel-2 change detection to exclude recent disturbances, and (iv) deep learning-based classification of historical orthophotos to assess stand age. Three detection approaches were evaluated—LiDAR-based, land parcel identification system (LPIS)-based, and their combination. A total of 111,754.4 ha of FEAs were identified outside official forest land, of which 76,204.6 ha meet the minimum age criterion for classification as forest land under national legislation. The designation of these areas as forest land would increase national forest cover from 33.9% to 35.0%. The LiDAR-based approach achieved the highest overall accuracy after dataset refinement (91.5%), while the combined approach yielded the highest precision (97.1%). Accuracy improved notably when reference points affected by definitional conflicts and temporal inconsistencies were excluded, indicating that apparent detection errors were largely attributable to reference data limitations rather than algorithmic failure. The proposed framework offers a scalable solution for wall-to-wall identification and monitoring of unregistered forest resources, with direct applications for national forest inventories and LULUCF reporting. Full article

(This article belongs to the Special Issue Remote Sensing-Guided Land-Use Optimization for Carbon Neutrality)

16 pages, 5001 KB

Open AccessArticle

The Impact of Delayed Neutron Precursor Migration on the Activation of Structural Material and Coolant in Molten Salt Reactor Heat Exchangers

by Haiyan Yu, Guifeng Zhu, Changqing Yu, Yinan Zhu, Ye Dai, Xuzhong Kang, Rui Yan, Xiaohan Yu and Yang Zou

J. Nucl. Eng. 2026, 7(2), 37; https://doi.org/10.3390/jne7020037 (registering DOI) - 21 May 2026

Abstract

In molten salt reactors (MSRs), molten salt performs dual essential roles as fuel and coolant. The continuous circulation of the fuel salt in the primary loop inevitably leads to significant neutron activation of loop components, particularly the structural alloys of the heat exchanger [...] Read more.

In molten salt reactors (MSRs), molten salt performs dual essential roles as fuel and coolant. The continuous circulation of the fuel salt in the primary loop inevitably leads to significant neutron activation of loop components, particularly the structural alloys of the heat exchanger (HX) and the coolant salt within the HX. This activation is strongly influenced by delayed neutron fluxes generated by the migration of delayed neutron precursors (DNPs) within the flowing fuel salt. Accurate quantification of the radioactivity of primary HX components is essential for establishing reliable modular replacement strategies, optimizing shutdown maintenance schedules, and ensuring operational safety. To address this requirement, a comprehensive simulation methodology has been developed to model the DNP transport through the primary HX in a small modular molten salt reactor (SM-MSR). It aims to quantitatively evaluate activation levels of HX structural alloys and circulating coolant salt within the HX. Comparative simulations were conducted to contrast scenarios with dynamic DNP migration and static-fuel scenarios excluding it. The results indicate that consideration of DNP migration increases the neutron flux at the top region of the HX by approximately three orders of magnitude compared with the static-fuel scenario. This elevates coolant salt radioactivity by over 50%. Significant increases in irradiation damage parameters (displacements per atom and helium production) are observed in the upper sections of HX structural alloys. These findings highlight the necessity of incorporating DNP migration effects for accurate prediction of primary loop component neutron activation. This provides a reference for future shielding design optimization, irradiation damage assessments, and shutdown dose rate calculations in the SM-MSR. Full article

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18 pages, 10911 KB

Open AccessSystematic Review

The Effectiveness of Psychological Interventions for Patients Undergoing Anterior Cruciate Ligament Reconstruction: A Meta-Analysis and Systematic Review

by Manxue Zhang, Bohua Li, Jialiang Tian, Yi Huang and Xiaobing Pu

J. Clin. Med. 2026, 15(10), 3980; https://doi.org/10.3390/jcm15103980 (registering DOI) - 21 May 2026

Abstract

Background: No systematic review has yet been conducted simultaneously on the effectiveness of psychological interventions across multiple outcome measures during rehabilitation following anterior cruciate ligament reconstruction (ACLR). This study aims to assess the effects of such interventions on pain, psychological outcomes, patient-reported [...] Read more.

Background: No systematic review has yet been conducted simultaneously on the effectiveness of psychological interventions across multiple outcome measures during rehabilitation following anterior cruciate ligament reconstruction (ACLR). This study aims to assess the effects of such interventions on pain, psychological outcomes, patient-reported knee function, objective knee measures, and quality of life following ACLR. Methods: We searched PubMed, Medline, Embase, PsycINFO, and the Cochrane Library from inception to 20 April 2026 (PROSPERO CRD42023483889). Eligible randomized controlled trials compared psychological interventions with usual care in ACLR patients. Two reviewers assessed eligibility, risk of bias, and extracted data. Random-effects models were used; effect sizes were interpreted using Cohen’s guidelines. Results: Of 401 records screened, 11 RCTs (440 participants) were included. Psychological interventions significantly improved pain (six trials, SMD = −0.96, 95% CI −1.40 to −0.52, p < 0.001, I² = 47%; large effect), kinesiophobia (TSK-11: five trials, SMD = −0.48, −0.74 to −0.22, I² = 0%; small effect), knee self-efficacy (K-SES: three trials, SMD = 0.53, 0.19–0.86, I² = 0%, moderate effect), patient-reported knee function (IKDC: two trials, SMD = 0.58, 0.26–0.90, I² = 0%, moderate effect), and physical role function (SF-36: two trials, SMD = 0.41, 0.04–0.78, I² = 0%, small effect). No significant effects were found for KT1000, knee strength, SF-36 mental well-being, or ACL-RSI (all p > 0.05, with substantial heterogeneity for ACL-RSI). Particularly, imagery therapy reduced pain (three trials, SMD = −1.54, I² = 15%). Conclusions: This meta-analysis provides preliminary evidence that psychological interventions, especially imagery therapy, may improve pain, psychological outcomes, patient-reported knee function, and quality of life after ACLR. Adequately powered trials with standardized protocols are needed to confirm these findings. Full article

(This article belongs to the Special Issue Advances in Anterior Cruciate Ligament Injury Treatment)

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16 pages, 11013 KB

Open AccessArticle

Atmospheric-Pressure Plasma Polymerization of Fluorosilane Coatings for Suppressing DC Surface Flashover on Polystyrene

by Tianran Zhang, Zexi Gao, Penghao Zhang, Chengguo Yao and Shoulong Dong

Coatings 2026, 16(5), 627; https://doi.org/10.3390/coatings16050627 (registering DOI) - 21 May 2026

Abstract

Direct current (DC) surface flashover on polystyrene (PS) remains a critical bottleneck that impedes its reliable application in high-voltage insulation apparatus. To circumvent the protracted processing durations and stringent film-forming conditions inherent in conventional surface modification techniques, this study proposes a novel “liquid-film-assisted [...] Read more.

Direct current (DC) surface flashover on polystyrene (PS) remains a critical bottleneck that impedes its reliable application in high-voltage insulation apparatus. To circumvent the protracted processing durations and stringent film-forming conditions inherent in conventional surface modification techniques, this study proposes a novel “liquid-film-assisted in situ rapid plasma curing” strategy. By harnessing atmospheric-pressure dielectric barrier discharge (DBD) technology within an argon ambient, the rapid (<6 min) and efficient deposition of a fluorosilane (FAS-13) functional coating onto the substrate was achieved. Microscopic characterizations coupled with isothermal surface potential decay (SPD) measurements reveal that this coating substantially mitigates the detrapping and surface migration of charge carriers. Macroscopic DC flashover testing corroborates that, under the optimal modification ratio, the surface breakdown voltage of PS is elevated to 14.04 kV, yielding an insulation gain of 26.94%. To elucidate the underlying physical mechanisms, density functional theory (DFT) calculations were conducted, revealing that the energy band misalignment between the wide-bandgap fluorinated layer and the substrate facilitates the construction of a high-density deep trap network (with a depth of ~0.8 eV) at the coating–substrate interface. By robustly anchoring primary electrons and inducing the formation of a homopolar space charge shielding layer, these deep traps physically arrest the evolution of the secondary electron emission avalanche (SEEA). Consequently, this work not only establishes a viable engineering framework for the rapid, large-scale surface reinforcement of DC insulation equipment but also provides profound quantum chemical insights into interfacial trap regulation within all-organic dielectrics. Full article

(This article belongs to the Section Functional Polymer Coatings and Films)

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31 pages, 756 KB

Open AccessTutorial

A Dual-Stage Ransomware Defense Framework Combining an Artificial Immune System and Honeyfile Traps

by Xiang Fang, Huseyn Huseynov and Tarek Saadawi

Electronics 2026, 15(10), 2223; https://doi.org/10.3390/electronics15102223 (registering DOI) - 21 May 2026

Abstract

The escalating sophistication of ransomware requires defensive strategies that are both proactive against zero-day attacks and operationally efficient. Existing solutions often force a trade-off—sacrificing low false-positive rates for broad detection, or vice versa. This work introduces an integrated framework designed to transcend this [...] Read more.

The escalating sophistication of ransomware requires defensive strategies that are both proactive against zero-day attacks and operationally efficient. Existing solutions often force a trade-off—sacrificing low false-positive rates for broad detection, or vice versa. This work introduces an integrated framework designed to transcend this limitation. Our dual-stage approach synergizes pre-encryption behavioral analysis with definitive post-encryption confirmation. The first stage employs a specialized artificial immune system (AIS) that monitors a curated set of 47 features, including API-call n-grams and file entropy dynamics, to identify malicious activity before file encryption begins. This pre-emptive analysis is complemented by an enhanced, cross-platform R-Locker mechanism, which uses Windows named pipes and symbolic links to deploy honeyfiles that trap ransomware during I/O operations, providing a high-fidelity trigger for automated containment. We subjected this framework to a rigorous evaluation against 3500 real-world ransomware samples and 12,000 benign applications. The results demonstrate a 98.2% detection rate with a 0.8% false-positive rate, achieving a mean response time of 1.3 s. A key finding is the framework’s efficiency on both Windows and Linux (the only platforms tested), with the AIS and R-Locker modules consuming a combined 101 MB of memory. While the system excels in real-time detection, we note that its current memory forensics capability for key recovery is incompatible with certain ransomware families due to architectural obfuscations. Our findings suggest that the integrated approach performs well under laboratory conditions; further real-world validation is required to confirm robustness in diverse environments. Full article

(This article belongs to the Special Issue Cryptography and Computer Security, 2nd Edition)

16 pages, 5797 KB

Open AccessArticle

Ultrasound-Assisted Soaking Facilitates Purine Dissolution from Soybean Powder: Development and Preliminary Application of Low-Purine Soybean Powder

by Hongfeng Yu, Yuting Zheng, Lulu Yang, Yong Zhao, Xinxin Ma, Li Li and Haiquan Liu

Foods 2026, 15(10), 1827; https://doi.org/10.3390/foods15101827 (registering DOI) - 21 May 2026

Abstract

People suffering from gout and hyperuricemia have limited consumption of soy products because of their high purine content, even though soybean is a nutrient-rich crop. This study developed a combined purine reduction process: ultrasonic-assisted soaking to promote purine dissolution and isoelectric point precipitation [...] Read more.

People suffering from gout and hyperuricemia have limited consumption of soy products because of their high purine content, even though soybean is a nutrient-rich crop. This study developed a combined purine reduction process: ultrasonic-assisted soaking to promote purine dissolution and isoelectric point precipitation to separate purines with minimal protein loss. A high-performance liquid chromatography (HPLC) method for rapid purine determination was first established (R² > 0.9999, RSD < 0.23%), thereby providing technical support for process optimization. Using soybean powder as the raw material, optimal ultrasonic conditions (58 °C, 250 W, 58 min) were identified, achieving a purine removal rate of 61.15% with a protein recovery of 94.23%. Scanning electron microscopy (SEM) and Fourier-transform infrared (FTIR) spectroscopy analyses revealed that ultrasonic treatment altered the microstructure of the soybean powder, thereby facilitating purine dissolution. Low-purine soymilk prepared from the resulting soybean powder exhibited a unique flavor, with enhanced electronic nose response signals of its flavor compounds. This process effectively reduces purine content while preserving soy protein and flavor, offering a feasible technical solution for the development and industrial application of low-purine soy products. However, challenges remain in process scale-up and in optimizing the balance between purine removal and nutrient retention. Full article

(This article belongs to the Section Food Engineering and Technology)

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19 pages, 22996 KB

Open AccessFeature PaperArticle

Beyond Helium-3: Instruments for Cosmic-Ray Neutron Sensing Based on Boron-10 Neutron Detectors

by Markus Köhli and Jannis Weimar

Instruments 2026, 10(2), 31; https://doi.org/10.3390/instruments10020031 (registering DOI) - 21 May 2026

Abstract

Cosmic-Ray Neutron Sensing (CRNS) has become a standard method for non-invasive soil moisture monitoring at the field scale. With most CRNS sensors being derivatives from scientific nuclear equipment, the development of instruments based on alternative neutron detection technologies is a major development goal [...] Read more.

Cosmic-Ray Neutron Sensing (CRNS) has become a standard method for non-invasive soil moisture monitoring at the field scale. With most CRNS sensors being derivatives from scientific nuclear equipment, the development of instruments based on alternative neutron detection technologies is a major development goal for CRNS. We present a modular instrument family based on boron-10-lined proportional counters, specifically designed for long-term autonomous field operation. The system is controlled by a data logger supporting various telemetry options and external SDI-12 environmental sensors, while the frontend electronics use pulse-height and pulse-length information to suppress non-neutron background and electronic noise. Our results show high energy efficiency, with the latest generation close to 50 mW, allowing solar-powered operation even in challenging environments. The performance of the instruments is validated within long-term field deployments in different settings, showing that boron-10-based systems provide a scalable, low-power and cost-efficient alternative for the next generation of CRNS monitoring networks. Full article

(This article belongs to the Section Sensing Technologies and Precision Measurement)

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22 pages, 4090 KB

Open AccessArticle

Nitrogen Addition-Induced Variations in Stoichiometric Ratio of Organic Acids from Litter Decomposition in a Temperate Forest

by Qiangqiang Lu, Xinping Cai, Xiaomin Zeng, Ji Chen, Fan Chang, Guanghua Jing, Jiaqi Guo, Sha Zhou, Zhikun Chen, Lili Jia, Jun Liu and Tianjiao Liu

Forests 2026, 17(5), 622; https://doi.org/10.3390/f17050622 (registering DOI) - 21 May 2026

Abstract

Litter decomposition is a key regulator of soil carbon formation and nutrient cycling in the plant–soil continuum. However, the utility of structural chemical indicators for capturing the relationship between litter decomposition and environmental factors under nitrogen (N) enrichment remains unclear. We conducted a [...] Read more.

Litter decomposition is a key regulator of soil carbon formation and nutrient cycling in the plant–soil continuum. However, the utility of structural chemical indicators for capturing the relationship between litter decomposition and environmental factors under nitrogen (N) enrichment remains unclear. We conducted a two-year in situ decomposition experiment with different N addition treatments in a pure Quercus variabilis forest on the Qinling Mountains, China. During the active six-month growing season, we investigated the stoichiometric ratios of typical organic acids in litter and soil layers and their responses to soil environments. The total relative content of the four organic acids showed the most pronounced nonlinear shift along the N addition gradient, peaking at N75 (7.5 g N m⁻²) then declining. The stoichiometric ratios of some typical organic acids varied analogously to soil physicochemical properties, microbial diversity and abundance. This inter-annual response was particularly pronounced in the warmer and wetter year of 2023. Structural chemical analysis revealed that steric hindrance and molecular symmetry are key factors regulating the decomposition efficiency of typical organic acids in litter. Notably, phenolic acid and butyric acid isomer ratios exhibited significant subgroup-specific responses to soil physicochemical factors, enzyme activities, and microbial abundances. Collectively, these ratios may indicate N addition impacts on litter decomposition, hold potential for predicting climatic variability responses, and provide conceptual support for an integrated framework linking N enrichment, litter chemistry, and soil carbon dynamics in temperate forests. Full article

(This article belongs to the Special Issue Soil Nutrition, Soil Hydrology, and Soil Microbial Diversity and Activity in Forest Ecosystem)

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