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Recent Articles  

19 pages, 368 KB  
Article
‘Turing Animism’ and the Disenchantment of Social Cognition: Why Humans Ensoul Large Language Models
by Andrew Skinner
Religions 2026, 17(5), 577; https://doi.org/10.3390/rel17050577 (registering DOI) - 11 May 2026
Abstract
A growing body of empirical study recognises a tendency for users to form (para)social bonds with Large Language Models, even when users know explicitly that these systems lack interiority or personhood. This contribution argues that such attachments arise from evolved human capacities to [...] Read more.
A growing body of empirical study recognises a tendency for users to form (para)social bonds with Large Language Models, even when users know explicitly that these systems lack interiority or personhood. This contribution argues that such attachments arise from evolved human capacities to attribute being, moral status and, in some ways, ‘soul’ to nonhuman others—and that this capacity now operates without the belief-systems that have historically mediated it. When users encounter helpful, patient, emotionally available behaviour in conversational agents, they project the interior states that would produce those behaviours in themselves: authentic interiority and phenomenal consciousness. Humans have been making such assessments throughout our cultural history, developing ontologies and theologies for managing our relations with nonhuman, mythic and spiritual others. By contrast, modernity has disenchanted its landscapes, dismantling these cultural models even as the ‘ensouling architecture’ of our social and semiotic cognition remained unchanged. Contemporary users thus encounter machine others through the same neurocognitive lens as their ancestors did with spirits and animals on enchanted, animate landscapes, but without the mediation of culture, norm and taboos which place a premium on appropriate conduct, reciprocity and moderation. The resulting condition—a ‘Turing Animism’—leads users to ‘feel soul’ where there is only simulacrum. Full article
(This article belongs to the Special Issue Between Soul and Algorithm: Religion and the Humanities in the Age of Artificial Intelligence)
18 pages, 4653 KB  
Article
Thermal Buckling Behaviors of a Fixed-Roof Steel Tank Subjected to Two Adjacent Pool Fires
by Yunhao Li and Song Lin
Fire 2026, 9(5), 198; https://doi.org/10.3390/fire9050198 (registering DOI) - 11 May 2026
Abstract
In a tank farm, even if the separation distance meets the codes and standards, a pool fire in one tank may spread quickly to another tank. Most destructive and uncontrollable fire accidents are induced with multiple pool fires. In current work, the thermal [...] Read more.
In a tank farm, even if the separation distance meets the codes and standards, a pool fire in one tank may spread quickly to another tank. Most destructive and uncontrollable fire accidents are induced with multiple pool fires. In current work, the thermal buckling behaviors of a fixed-roof tank subjected to one (two) neighboring pool fire(s) (burning tanks) are numerically studied. The effects of the number of the pool fires, the separation distance between two pool fires, and the distance between the adjacent tank and pool fires are analyzed. The results indicate that the thermal buckling zone of the target tank subjected to two pool fires is larger than that subjected to one pool fire, and the maximum displacement for two pool fires is almost equal to that for one pool fire. The target tank subjected to one pool fire loses stability and reaches a new stable state faster than that subjected to two pool fires. The thermal buckling zone expands as the distance between the two pool fires increases but decreases with increasing separation distance between the pool fire and the target tank. The findings provide useful guidance for the structural optimization of steel storage tanks against pool fire exposure and offer theoretical support for emergency response and fire rescue in tank farms. Full article
(This article belongs to the Section Fire Risk Assessment and Safety Management in Buildings and Urban Spaces)
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28 pages, 896 KB  
Article
A Conceptual Framework for Mobile Augmented-Reality Storytelling to Support Collaborative Language Learning in Vocational Education and Training
by Eirini Maria Paraskevioti, Athanasios Christopoulos, Stylianos Mystakidis, Mikko-Jussi Laakso and Tapio Salakoski
Multimodal Technol. Interact. 2026, 10(5), 53; https://doi.org/10.3390/mti10050053 (registering DOI) - 11 May 2026
Abstract
Augmented Reality (AR) has been found to produce significant effects on individual learning outcomes but its impact on collaborative applications remains moderate. Existing AR frameworks emphasize individual instructional design, whereas frameworks for collaborative learning rarely engage with the spatial and device-mediated affordances of [...] Read more.
Augmented Reality (AR) has been found to produce significant effects on individual learning outcomes but its impact on collaborative applications remains moderate. Existing AR frameworks emphasize individual instructional design, whereas frameworks for collaborative learning rarely engage with the spatial and device-mediated affordances of mobile AR. In response to this inadequacy in the literature, we introduce the Mobile Augmented-Reality Storytelling for Vocational Education and Training (MARS-VET) framework, a four-dimensional conceptual architecture that integrates Computer-Supported Collaborative Learning (CSCL) scripting principles with mobile AR affordances for collaborative English as a Foreign Language (EFL) writing in Vocational Education and Training (VET) settings. MARS-VET synthesizes theoretical perspectives across four dimensions: contextual anchoring, which embeds activities within authentic workplace scenarios; collaborative orchestration, which structures group interaction through macro- and micro-level scripts; competency cultivation, which sequences writing progression from model-based reproduction toward autonomous professional text production; and capacity building, which addresses the professional-development requirements of implementing educators. Content validity was established through expert panel evaluation involving international specialists (N = 11) who rated the framework against 36 items using a four-point relevance scale and provided additional qualitative feedback. The Scale-level Content Validity Index (S-CVI/Ave = 0.91) exceeded established thresholds, with all four dimensions achieving satisfactory item-level indices. Experts reached unanimous agreement on items addressing workplace scenario identification and co-located access to linguistic resources. Qualitative feedback led to terminology refinements and clarification of orchestration mechanisms. The framework offers VET institutions and educators a reference for the design and evaluation of collaborative AR experiences in an area where integrative frameworks have so far been lacking. Full article
(This article belongs to the Special Issue Online Learning to Multimodal Era: Interfaces, Analytics and User Experiences)
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21 pages, 523 KB  
Article
Alterations in Erythrocyte and Platelet Characteristics Are Poor Indicators of Metastasis in Dogs with Carcinoma or Sarcoma: A Preliminary Study
by Adriana A. Mulder, Amelia Goddard and Paolo Pazzi
Vet. Sci. 2026, 13(5), 465; https://doi.org/10.3390/vetsci13050465 (registering DOI) - 11 May 2026
Abstract
Cancer is a leading cause of death in humans and dogs. Several erythrocyte and platelet characteristics (indices and morphology) have shown promise as indicators of metastasis in humans. Similar studies have not been performed in dogs. This study evaluated erythrocyte and platelet characteristics [...] Read more.
Cancer is a leading cause of death in humans and dogs. Several erythrocyte and platelet characteristics (indices and morphology) have shown promise as indicators of metastasis in humans. Similar studies have not been performed in dogs. This study evaluated erythrocyte and platelet characteristics measured on the Advia 2120i in 59 tumor-bearing dogs with carcinoma or sarcoma. Tumor-bearing dogs with and without intracavitary hemorrhage that underwent complete post-mortem and histopathology examinations were compared to healthy age-controlled dogs. Carcinoma- and sarcoma-bearing dogs without hemorrhage were compared. All tumor-bearing dogs without hemorrhage or metastasis were compared to those with metastasis, and characteristics were evaluated as indicators of metastasis. Tumor-bearing dogs without intracavitary hemorrhage (n = 49) had decreased hematocrit (p = 0.002) and reticulocyte hemoglobin content (p = 0.022), and increase in anisocytosis (p = 0.002), polychromasia (p = 0.002), macrocytosis (p = 0.032), codocytes (p = 0.022), absolute reticulocyte count (p = 0.035), platelet concentration (p = 0.002), plateletcrit (p = 0.022), and platelet volume distribution width (p = 0.022) compared to healthy dogs (n = 20). In tumor-bearing dogs with intracavitary hemorrhage (n = 10), additional significant differences were reflective of acute hemorrhage. No difference in characteristics between carcinoma- and sarcoma-bearing dogs without hemorrhage was identified. After correction for multiple comparisons, no differences in erythrocyte or platelet characteristics were identified between tumor-bearing dogs without intracavitary hemorrhage and metastasis and those without metastasis. Significant differences in characteristics exist between tumor-bearing dogs and healthy dogs. Based on the limited number of dogs in this preliminary study, no red blood cell or platelet characteristics were associated with metastatic disease in tumor-bearing dogs without hemorrhage. Full article
(This article belongs to the Special Issue Advances in Diagnostic Strategies in Veterinary Internal Medicine: From Molecular Biomarkers to Imaging Innovations)
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15 pages, 3067 KB  
Article
Variations in DNA Methylation Are Landmarks of Freshwater Adaptation in Three-Spined Sticklebacks
by Alexey Starshin, Alexandr Mazur, Nikolai Mugue, Daria Kaplun, Artemiy Golden, Ekaterina Khrameeva and Egor Prokhortchouk
Int. J. Mol. Sci. 2026, 27(10), 4265; https://doi.org/10.3390/ijms27104265 (registering DOI) - 11 May 2026
Abstract
Understanding the phenotypic consequences of epigenetic variation and its role in adaptation remains a central challenge in evolutionary biology. Marine and freshwater sticklebacks provide a powerful system to study the interplay between genetic and epigenetic components of phenotypic plasticity that enables colonization of [...] Read more.
Understanding the phenotypic consequences of epigenetic variation and its role in adaptation remains a central challenge in evolutionary biology. Marine and freshwater sticklebacks provide a powerful system to study the interplay between genetic and epigenetic components of phenotypic plasticity that enables colonization of contrasting salinity habitats. Here, we used whole-genome bisulfite sequencing (WGBS) to characterize DNA methylation entropy—a measure of epigenetic stochasticity—in gill tissue from marine and freshwater ecotypes. We found that freshwater sticklebacks exhibit elevated methylation entropy in divergence islands (DIs), genomic regions known as hotspots of genetic divergence between marine and freshwater populations. Within DIs, we identified a subset of genes exhibiting concurrent increases in methylation entropy and transcriptional variance, including osmoregulatory candidates involved in growth modulation, cytoskeletal reorganization, metabolism, and extracellular matrix remodeling. Their linked variability suggests that they may act as “adaptation capacitors” facilitating phenotypic plasticity during salinity transitions. Exploratory enrichment analysis further revealed overrepresented epigenetic regulators within DIs, such as DNA demethylase TET1 and chromatin remodelers ARID5B and BPTF, indicating a potential regulatory basis by which these factors may convert genetic variation into epigenetic diversity. Collectively, our findings demonstrate that DIs are focal points of both genetic divergence and epigenetic heterogeneity, consistent with a model in which DIs may act as multi-layered genomic regions associated with adaptive responses to salinity change. Full article
(This article belongs to the Special Issue Explore Marine Biodiversity: Discover Insights from Genomics and Transcriptomics)
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19 pages, 1838 KB  
Article
Inhibitory Effects of 3-Octanone and 1-Octen-3-ol on Juvenile Survival, Egg Development, and Egg-Mass Hatching in Meloidogyne Species
by Alexandra M. Kortsinoglou, Dionysios Ntinokas, Nikolaos S. Lotsios, Daniel C. Eastwood, E. Joel Loveridge, Vassili N. Kouvelis, Ioannis O. Giannakou and Tariq M. Butt
Horticulturae 2026, 12(5), 591; https://doi.org/10.3390/horticulturae12050591 (registering DOI) - 11 May 2026
Abstract
Root-knot nematodes (RKNs) of the genus Meloidogyne are major plant pests causing severe crop losses. Microbial volatile organic compounds (VOCs) have emerged as promising biopesticides. In this study, we evaluated the effects of two fungal VOCs, 1-octen-3-ol and 3-octanone, on nematode survival in [...] Read more.
Root-knot nematodes (RKNs) of the genus Meloidogyne are major plant pests causing severe crop losses. Microbial volatile organic compounds (VOCs) have emerged as promising biopesticides. In this study, we evaluated the effects of two fungal VOCs, 1-octen-3-ol and 3-octanone, on nematode survival in five Meloidogyne species (M. incognita, M. javanica, M. hapla, M. arenaria, and M. luci) in plate assays. Results showed near-complete (95–100%) J2 mortality at 500–1000 ppm within 24 h. At lower concentrations, mobility declined, and species-dependent differences were observed: 1-octen-3-ol was more effective against M. arenaria. Meanwhile, 3-octanone showed stronger effects only on M. hapla and moderate effects on M. incognita and M. javanica. Further experiments using solely M. javanica showed that egg differentiation was significantly inhibited at 7, 14, and 21 days, with up to an 80% reduction at 1000 ppm, and the effects persisted at 125 ppm. Egg hatching from egg masses was reduced by up to 95% in a concentration-dependent manner, irrespective of compound type. Soil-like microcosm assays resulted in substantial reductions in recovered juveniles, with over 90% reduction at 125 ppm after 24 h, suggesting sustained effects under the tested conditions. In more complex plant–soil greenhouse conditions, effects were reduced, although decreasing trends in nematode infection were observed. Overall, these results indicate that fungal VOCs exhibit strong effects on different nematode life stages under controlled conditions, highlighting 1-octen-3-ol and 3-octanone as promising candidates for further evaluation in nematode management strategies. Full article
(This article belongs to the Special Issue Advanced Integrated Pest Management for Sustainable Horticulture)
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22 pages, 2228 KB  
Article
An Attention-Enhanced Deep Learning Framework for Multi-Label Dental Findings Classification from Panoramic Radiographs
by Mona Almutairi and Samia Dardouri
Information 2026, 17(5), 465; https://doi.org/10.3390/info17050465 (registering DOI) - 11 May 2026
Abstract
Panoramic radiographs are widely used in dental practice due to their ability to provide a comprehensive view of the teeth, jaws, and surrounding anatomical structures in a single examination. However, automated interpretation remains challenging because multiple conditions may co-exist within a single image, [...] Read more.
Panoramic radiographs are widely used in dental practice due to their ability to provide a comprehensive view of the teeth, jaws, and surrounding anatomical structures in a single examination. However, automated interpretation remains challenging because multiple conditions may co-exist within a single image, class distributions are highly imbalanced, and several findings exhibit subtle radiographic characteristics. This study presents a deep learning framework for multi-label dental findings classification using panoramic radiographs from the publicly available VZRAD2 dataset. Following a label curation process, eleven clinically relevant classes were retained, including diseases, treatments, and anatomical structures. The proposed EfficientNet-B4-CBAM model integrates an EfficientNet-B4 backbone with a Convolutional Block Attention Module (CBAM) to enhance feature representation through channel and spatial attention. EfficientNet-B4 and ResNet50 were used as baseline models for comparison under a unified training protocol. The training pipeline incorporates data augmentation, weighted sampling to address class imbalance, AdamW optimization, and Binary Cross-Entropy with Logits loss for multi-label learning. On the validation set, the proposed model achieved the highest micro-F1 score of 0.8567, compared to 0.8424 for EfficientNet-B4 and 0.8469 for ResNet50. ROC analysis showed comparable separability across models, with micro-AUC values of 0.946 (EfficientNet-B4-CBAM), 0.947 (EfficientNet-B4), and 0.960 (ResNet50). Class-wise evaluation indicated strong performance for visually distinct findings such as impacted tooth, implant, filling, and root canal treatment, while anatomically diffuse or underrepresented classes remained more challenging. Grad-CAM visualizations suggest that the model focuses on clinically relevant regions, supporting interpretability. Overall, the results indicate that attention-enhanced convolutional models can provide effective and interpretable support for multi-label dental findings classification. However, the observed performance improvements are modest, and further validation on independent datasets, along with clinical evaluation, is required to confirm generalizability and real-world applicability. Full article
(This article belongs to the Special Issue Deep Learning in Medical Image Analysis: Foundations, Techniques, and Applications)
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9 pages, 1767 KB  
Article
Retrospective Evaluation of the Impact of the COVID-19 Pandemic on the Incidence of Alopecia Areata in a Single Dermatological Department
by Łukasz Chętko, Julia Hofmann, Karolina Brzychcy, Marta Matych, Dorota Sobolewska-Sztychny, Marcin Noweta, Bartosz Zakrzewski, Małgorzata Dominiak, Joanna Narbutt and Aleksandra Lesiak
J. Clin. Med. 2026, 15(10), 3682; https://doi.org/10.3390/jcm15103682 (registering DOI) - 11 May 2026
Abstract
Background: Alopecia areata (AA) is an autoimmune disease characterized by diverse patterns of non-scarring hair loss. Due to its susceptibility to immune dysregulation and psychological stress, there is growing speculation regarding the potential role of SARS-CoV-2 infection and the COVID-19 pandemic in its [...] Read more.
Background: Alopecia areata (AA) is an autoimmune disease characterized by diverse patterns of non-scarring hair loss. Due to its susceptibility to immune dysregulation and psychological stress, there is growing speculation regarding the potential role of SARS-CoV-2 infection and the COVID-19 pandemic in its development, recurrence, or exacerbation. This retrospective study aimed to evaluate patients affected by AA from a single dermatological center, specifically focusing on the impact of the COVID-19 pandemic on hospitalization rates. Methods: Data comprising demographic characteristics, disease subtype, number, and duration of hospitalizations were digitized and statistically analyzed. The five-year period prior to the pandemic (2015–2019) was compared with the subsequent four years (2020–2023) to assess any changes. Results: The study involved 428 individuals (256 children and 172 adults), with a slight predominance of women (68.2%). The median ages in adults and children were 39.13 years and 8.66 years, respectively. Following the pandemic, there was a 13.81% decrease in the mean age among adult males. Hospitalizations surged by 207.62% after the pandemic, increasing from 223 to 686 admissions. Additionally, the diagnosis of alopecia areata totalis increased significantly by 55.6%. The residential distribution of pediatric patients also shifted notably, with 72.16% residing in urban areas and 27.84% in rural areas between 2020 and 2023. Conclusions: The significant increase in hospitalization rates and the diversity of disease subtypes observed in this study may suggest a potential correlation between COVID-19 and the development or altered course of alopecia areata. A deeper understanding of this association could enhance treatment outcomes in dermatology, ultimately improving patient care. Full article
(This article belongs to the Special Issue Alopecia, Atopic Dermatitis and Other Chronic Inflammatory Skin Diseases: Pathogenesis, Comorbidities, and Precision Management)
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22 pages, 613 KB  
Article
Exact Pattern-Aware Extraction for Equality Saturation via Bounded-Depth Tree Covering
by Zi Cheng, Mengting Yuan and Lefei Zhang
Algorithms 2026, 19(5), 377; https://doi.org/10.3390/a19050377 (registering DOI) - 11 May 2026
Abstract
Equality saturation explores equivalent program expressions via e-graphs, and its extraction step selects one representative per equivalence class to form an output tree. Standard extraction minimizes a decomposable per-node cost function that cannot capture multi-node structural patterns arising in SMT preprocessing and compiler [...] Read more.
Equality saturation explores equivalent program expressions via e-graphs, and its extraction step selects one representative per equivalence class to form an output tree. Standard extraction minimizes a decomposable per-node cost function that cannot capture multi-node structural patterns arising in SMT preprocessing and compiler instruction selection. We formalize pattern-aware extraction as a weighted pattern cover problem on AND-OR DAGs and establish its correspondence to tree covering in instruction selection. Three challenges arise when migrating tree covering to e-graphs: annotation ambiguity from multiple candidates per class, context-dependent selection from depth-2 templates, and DAG sharing conflict. We show that the coupled selection–tiling problem reduces to a tree DP with three mutually exclusive tile-role states, generalizing BURS tree covering from fixed trees to AND-OR DAGs. A bottom-up pass computes optimal DP values, and a top-down pass traces back decisions to produce the output tree. For template depth at most two, the algorithm computes an exact optimum in O(N·K·|P|·Cmax) time. The evaluation targets extraction-level coverage, since end-to-end performance additionally depends on rewrite-rule design and saturation completeness. On SMT-COMP benchmarks, the algorithm achieves up to 31× higher weighted pattern coverage than standard extraction. Depth-2 tiling contributes 45–51% additional improvement, with overhead within 1.5× of standard extraction. Full article
(This article belongs to the Section Combinatorial Optimization, Graph, and Network Algorithms)
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15 pages, 2652 KB  
Article
A Hybrid Physics-Based and Data-Driven Framework for Predicting Water Velocities in a Draining Pipeline Using Pressurised Air
by David Patiño-Ruiz, Oscar E. Coronado-Hernández and Manuel Saba
Water 2026, 18(10), 1148; https://doi.org/10.3390/w18101148 (registering DOI) - 11 May 2026
Abstract
Draining operations using pressurised air can produce sub-atmospheric pressures that pose a significant risk to structural integrity, given the pipe stiffness class. This research presents a modelling strategy for predicting water velocities during the occurrence of this phenomenon. The proposed approach combines a [...] Read more.
Draining operations using pressurised air can produce sub-atmospheric pressures that pose a significant risk to structural integrity, given the pipe stiffness class. This research presents a modelling strategy for predicting water velocities during the occurrence of this phenomenon. The proposed approach combines a physically based hydraulic formulation with machine learning techniques for making this prediction. A calibrated rigid water column model is first employed to reproduce the transient interaction between the expanding air phase and the draining water column. Input parameters include pipe bridge height varying from 0.5 to 3.0 m, a valve loss dimensionless coefficient ranging from 2.0 to 14.0, and an initial water column length between 163.0 and 286.3 m. Subsequently, a Monte Carlo scheme is used to generate a representative dataset. A total of 28 models were assessed, among which a wide neural network demonstrated superior predictive capability, achieving root-mean-square error values between 0.043 and 0.056 m/s and coefficients of determination ranging from 0.996 to 0.997 for the validation and testing stages, respectively. Sensitivity analyses indicate that the minor loss coefficient governs the water velocity response, whereas geometric features such as the pipe bridge height exert a comparatively minor influence. Full article
(This article belongs to the Section New Sensors, New Technologies and Machine Learning in Water Sciences)
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21 pages, 12291 KB  
Article
ERIME-UPF and CSVSF-VBL Fusion for Accurate State of Charge Inconsistency Tracking in Dynamic Battery Environments
by Renhui Luo, Rong Yang, Hang Yang and Wei Huang
World Electr. Veh. J. 2026, 17(5), 257; https://doi.org/10.3390/wevj17050257 (registering DOI) - 11 May 2026
Abstract
Accurate online tracking of state of charge (SOC) inconsistency in lithium-ion battery packs is essential for safety. It is equally critical for effective battery management in real-world operation. To achieve robust performance in dynamic battery environments characterized by temperature fluctuations and cell aging, [...] Read more.
Accurate online tracking of state of charge (SOC) inconsistency in lithium-ion battery packs is essential for safety. It is equally critical for effective battery management in real-world operation. To achieve robust performance in dynamic battery environments characterized by temperature fluctuations and cell aging, a method combining enhanced Rime optimized-unscented particle filter (ERIME-UPF) with cubature smooth variable structure filter-varying boundary layer (CSVSF-VBL) is proposed. The cell mean-difference model is used to simulate the behavior characteristics of the battery module, including the hysteresis effect dynamic migration model, and the Rint model. First, module SOC is estimated using an ERIME-UPF, which adaptively adjusts the noise covariances of UPF via the enhanced RIME optimizer. Simultaneously, CSVSF-VBL employs the Rint model to estimate cell SOC inconsistencies, incorporating capacity and internal resistance coefficients into the second-order performance chattering to better capture cell inconsistency. Experiments focus on LiFePO4 batteries under various inconsistencies, temperature, and aging states. The results show that ERIME-UPF achieves an average mean absolute error (MAE) of 0.33% for module SOC estimation, while CSVSF-VBL achieves a peak MAE of 3.28% for cell SOC estimation. Demonstrating superior accuracy and robustness in tracking SOC inconsistency under dynamic and degraded operating conditions. Full article
(This article belongs to the Special Issue State Estimation and Efficient Charging Strategies for Lithium-Ion Batteries in Electric Vehicles)
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2 pages, 132 KB  
Editorial
Recent Advances in Computer-Aided Drug Design and Drug Discovery
by John Z. H. Zhang
Molecules 2026, 31(10), 1606; https://doi.org/10.3390/molecules31101606 (registering DOI) - 11 May 2026
Abstract
The field of Computer-Aided Drug Design (CADD) has undergone remarkable transformations, evolving from a niche discipline into a cornerstone of modern pharmaceutical research [...] Full article
(This article belongs to the Special Issue Recent Advances in Computer-Aided Drug Design and Drug Discovery)
17 pages, 1745 KB  
Article
Closing Material and Water Loops in Lithium-Ion Battery Recycling: Integrated Nanofiltration–Membrane Distillation for Sustainable Metal Recovery
by Thiago Vinícius Barros, Franciele Pereira Camacho, Leandro Vitor Pavão, José Augusto de Oliveira, Ana Caroline Raimundini Aranha, Abhijit Data, Biplob Pramanik, Linhua Fan, Veeriah Jegatheesan and Lucio Cardozo-Filho
Sustainability 2026, 18(10), 4759; https://doi.org/10.3390/su18104759 (registering DOI) - 11 May 2026
Abstract
This study investigates the integration of nanofiltration (NF) and membrane distillation (MD) for the selective separation and recovery of critical metals from effluents generated by supercritical water oxidation (SCWO) of lithium-ion batteries. Beyond resource recovery, the proposed hybrid system addresses the urgent environmental [...] Read more.
This study investigates the integration of nanofiltration (NF) and membrane distillation (MD) for the selective separation and recovery of critical metals from effluents generated by supercritical water oxidation (SCWO) of lithium-ion batteries. Beyond resource recovery, the proposed hybrid system addresses the urgent environmental challenge associated with highly contaminated battery recycling effluents, which pose severe risks to aquatic ecosystems if improperly managed. NF90 and NF270 membranes exhibited complementary behavior: NF90 achieved high rejection of Co, Ni, and Mn (>70%) with a minimum lithium rejection of 30%, whereas NF270 showed lower rejection of divalent metals (40%) and lower lithium rejection (<20% at pH = 7), along with a higher permeability. Subsequent MD enabled water recovery while concentrating lithium in the MD concentrate (brine), maintaining near-complete rejection of transition metals (>90%) and reducing the effluent conductivity by more than 85%. Surface characterization (SEM–EDS, AFM, BET, and contact angle) revealed fouling mechanisms and wettability loss, highlighting operational stability limitations. In this hybrid approach, nanofiltration enables the selective separation of lithium from transition metals, while membrane distillation promotes water recovery and concentrates lithium into a recoverable brine, with fouling and wetting defining the operational boundaries of the process. Overall, the results demonstrate that coupling SCWO with NF–MD represents a viable and scalable pathway for simultaneous effluent detoxification and lithium recovery, contributing to circular economy strategies and the sustainable management of battery-recycling wastewater. Full article
(This article belongs to the Section Sustainable Chemical Engineering and Technology)
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12 pages, 5429 KB  
Article
Soil Fungal Communities’ Characteristics of the Lamiophlomis rotata Root-Zone to Altitude and Their Relationship with Environmental Factors
by Ming Fan, Yaming Yang, Hui Chu, Ping Chu and Qiang Li
Microorganisms 2026, 14(5), 1083; https://doi.org/10.3390/microorganisms14051083 (registering DOI) - 11 May 2026
Abstract
This study aimed to investigate differences and patterns in fungal communities within the root-zone soil of Lamiophlomis rotata across varying altitudes. Specifically, it analyzed the characteristics of soil fungal communities at altitudes of 3600, 3800, 4000, and 4200 m and examined their relationships [...] Read more.
This study aimed to investigate differences and patterns in fungal communities within the root-zone soil of Lamiophlomis rotata across varying altitudes. Specifically, it analyzed the characteristics of soil fungal communities at altitudes of 3600, 3800, 4000, and 4200 m and examined their relationships with key bioactive medicinal constituents and soil nutrients. The results indicated that Ascomycota, Mortierellomycota, and Basidiomycota were the dominant fungal phyla in the L. rotata root-zone soil, with Pseudosperma and Clavaria as the predominant genera. The Shannon and Chao1 diversity indices of soil fungi initially decreased and subsequently increased with increasing altitude. At the same altitude, these indices were higher in the root-zone soil than in the non-root-zone soil. Redundancy analysis revealed that available phosphorus was the primary factor influencing fungal communities in the non-root-zone soil. In conclusion, altitude significantly affected the characteristics of fungal communities in root-zone soil, which differed significantly from those in the non-root-zone soils. These findings provide valuable data to support the conservation of L. rotata resources on the Qinghai–Tibet Plateau. Full article
(This article belongs to the Section Environmental Microbiology)
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19 pages, 4969 KB  
Article
Pharmacokinetics and Exploratory Exposure–Response Analysis of Chikusetsusaponin IVa in Myocardial Ischemia/Reperfusion-Injured Rats
by Xiaomin Shuai, Hui Wang, Jianmin Luo, Yangqiao Zeng, Ying Wang, Lijun Zhu, Zhongqiu Liu and Yuanyuan Cheng
Pharmaceuticals 2026, 19(5), 749; https://doi.org/10.3390/ph19050749 (registering DOI) - 11 May 2026
Abstract
Background: Myocardial ischemia/reperfusion injury (MIRI) remains a major limitation to effective cardioprotection. Chikusetsusaponin IVa (CS-IVa) has shown promising cardioprotective activity; however, its pharmacokinetic behavior and exposure–response relationship under MIRI pathological conditions remain insufficiently characterized. This study aimed to evaluate the disease-state-related pharmacokinetics of [...] Read more.
Background: Myocardial ischemia/reperfusion injury (MIRI) remains a major limitation to effective cardioprotection. Chikusetsusaponin IVa (CS-IVa) has shown promising cardioprotective activity; however, its pharmacokinetic behavior and exposure–response relationship under MIRI pathological conditions remain insufficiently characterized. This study aimed to evaluate the disease-state-related pharmacokinetics of CS-IVa in MIRI rats and to explore its concentration–effect relationship using a revised descriptive PK framework. Methods: A rat MIRI model was established by ligation and reperfusion of the left anterior descending coronary artery. The cardioprotective effects of CS-IVa were evaluated using echocardiography, hemodynamic parameters, myocardial infarct size, histopathological examination, and biochemical markers of myocardial injury and oxidative stress. Plasma CS-IVa concentrations were quantified by UHPLC-MS/MS over 0–24 h after administration. Non-compartmental pharmacokinetic parameters were statistically compared between normal and MIRI rats. To address model reliability and parameter identifiability, candidate PK models with different structural assumptions and weighting schemes were systematically re-evaluated. The selected descriptive PK model was further assessed using the leave-one-rat-out robustness analysis. An exploratory exposure–response analysis was performed using CK-MB as the longitudinal PD endpoint, and a Ke0 sensitivity analysis was conducted to evaluate the robustness of the downstream effect-compartment interpretation. Data-driven models were retained only as supplementary exploratory predictive analyses. Results: CS-IVa improved cardiac function; reduced myocardial infarct size; attenuated histopathological injury; decreased serum CK-MB, cTnI, LDH and plasma MDA levels; and restored SOD activity in MIRI rats. In normal rats, systemic exposure to CS-IVa increased with dose escalation. Compared with normal rats at 15 mg/kg, MIRI rats showed markedly altered pharmacokinetic behavior, including reduced Cmax and AUC, delayed Tmax, shortened apparent half-life, and increased apparent volume of distribution. After systematic model re-evaluation, a one-compartment model with first-order absorption, no lag time, and unweighted fitting was selected as the revised working descriptive PK model, providing a better balance between model fit, parameter stability, and parsimony. The leave-one-rat-out analysis supported the robustness of this revised model. The exploratory concentration–effect analysis revealed a temporal dissociation between plasma CS-IVa exposure and CK-MB response, suggesting a delayed pharmacodynamic response. Ke0 sensitivity analysis indicated that effect-compartment-based PD fitting was sensitive to Ke0 selection; accordingly, the exposure–response analysis is interpreted as exploratory rather than as a definitive mechanistic PK/PD model. Conclusions: CS-IVa exerted cardioprotective effects in MIRI rats, while MIRI markedly altered its overall pharmacokinetic behavior. The revised analysis supports disease-state-related PK changes and an exploratory exposure–response delay between plasma CS-IVa exposure and CK-MB response. These findings provide a pharmacokinetic basis for understanding CS-IVa under MIRI pathological conditions; however, further studies incorporating individual-level PD endpoints, tissue distribution data, and clinically relevant formulations are needed before translational dosing recommendations can be made. Full article
(This article belongs to the Section Pharmacology)
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23 pages, 9319 KB  
Article
Eye Movement Patterns as Robust Biomarkers for Schizophrenia Identification Using a Novel Data Transformation Approach
by Lijin Huang, Senhao Li, Zhi Liu, Dan Zhang, Lihua Xu, Tianhong Zhang and Jijun Wang
J. Eye Mov. Res. 2026, 19(3), 51; https://doi.org/10.3390/jemr19030051 (registering DOI) - 11 May 2026
Abstract
Although eye movement abnormalities are documented in schizophrenia (SZ), their translation into objective diagnostic biomarkers remains limited. In this study, we propose a novel identification framework that integrates a Sparsity-Scoring Kernel Entropy Component Analysis (SSKECA) algorithm with a multidimensional eye movement feature set. [...] Read more.
Although eye movement abnormalities are documented in schizophrenia (SZ), their translation into objective diagnostic biomarkers remains limited. In this study, we propose a novel identification framework that integrates a Sparsity-Scoring Kernel Entropy Component Analysis (SSKECA) algorithm with a multidimensional eye movement feature set. A total of 40 patients with SZ and 50 healthy controls (HC) completed a free-viewing task involving 100 distinct semantic images. The proposed SSKECA algorithm optimizes multidimensional feature representations to capture latent eye movement patterns characteristic of SZ. The SSKECA–AdaBoost model achieved competitive performance, with an accuracy of 0.933 and an area under the receiver operating characteristic curve (AUC) of 0.960. Notably, when restricted to only 25 highly discriminative images, the SSKECA–XGBoost model achieved an accuracy of 0.922. Feature ablation analyses not only reproduced previously reported eye movement findings but also highlighted additional atypical patterns. Misclassification analyses revealed more pronounced eye movement deficits in incorrectly classified SZ patients. Overall, the proposed framework translates complex eye movement patterns into robust indicators for subject-level identification, offering a practical and efficient tool to support objective assessment in SZ. Full article
(This article belongs to the Special Issue Digital Advances in Binocular Vision and Eye Movement Assessment)
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28 pages, 441 KB  
Review
Comprehensive Insight into the Male Dog Reproductive System in Health and Diseases: Developmental, Genetic, and Environmental Factors—Review on Research and Clinical Trials
by Aybike Turkmen, Grzegorz Lonc, Begum Yurdakok-Dikmen, Koray Tekin, Dorota Gil, Marta Zarzycka, Katarzyna Kania and Malgorzata Kotula-Balak
Vet. Sci. 2026, 13(5), 464; https://doi.org/10.3390/vetsci13050464 (registering DOI) - 11 May 2026
Abstract
As in other mammalian species, the complex and specific interactions between internal biological processes and external factors regulate and impact the male dog reproductive system functions. This comprehensive review integrates physiological and molecular mechanisms underlying the reproductive system maintenance throughout the anatomical and [...] Read more.
As in other mammalian species, the complex and specific interactions between internal biological processes and external factors regulate and impact the male dog reproductive system functions. This comprehensive review integrates physiological and molecular mechanisms underlying the reproductive system maintenance throughout the anatomical and histological structure of reproductive organs and their functions from development to aging. Simultaneously, the presentation of fundamental hormonal regulations and functions of the reproductive system is comprised. Special attention is put on e.g., genetic, developmental, age- and environmental-related disorders. The structural and hormonal status of the reproductive organs in response to single or mixed influences: genetic predispositions (e.g., cryptorchidism, sex chromosome aneuploidy syndrome), developmental courses (e.g., cryptorchidism, uterus masculinus, hypospadias), age-related diseases (e.g., tumors), and environmental stressors: e.g., endocrine-disrupting chemicals, toxins, heat stress (possibly leading to e.g., hypogonadism, cryptorchidism, infertility, tumors, precocious aging) is provided. Such multidirectional and comprehensive associations of grouped, selected, clinically significant pathological processes and diseases are broadly considered and linked here for the first time. Based on both epidemiological and experimental findings, the etiologies, current diagnostic approaches, treatment options, and prognostic assessments of these common male dog disorders are presented. This compendium seems useful for young veterinarians, researchers, breeders, and dog owners, enabling them to integrate knowledge on biological principles and processes with clinical practices and research in recent and future canine andrology. Full article
18 pages, 1836 KB  
Article
Why Do Consumers Who Prefer Physical Entertainment Behave Digitally? Understanding the Preference–Behavior Gap
by Ștefan Bulboacă, Eliza Ciobanu, Ioana Bianca Chițu, Gabriel Brătucu, Cristinel Petrisor Constantin and Radu Constantin Lixăndroiu
Behav. Sci. 2026, 16(5), 744; https://doi.org/10.3390/bs16050744 (registering DOI) - 11 May 2026
Abstract
This study examines the discrepancy between stated preferences and actual behavior in entertainment consumption, with a particular focus on the role of perceived accessibility constraints. While literature suggests that factors such as time and cost may hinder the translation of preferences into behavior, [...] Read more.
This study examines the discrepancy between stated preferences and actual behavior in entertainment consumption, with a particular focus on the role of perceived accessibility constraints. While literature suggests that factors such as time and cost may hinder the translation of preferences into behavior, the direction of this relationship remains unclear. Using survey data from 608 respondents, the analysis investigates why individuals who express a preference for physical entertainment often exhibit higher levels of digital consumption. To address this question, the study constructs composite indices capturing physical consumption (PCI), digital consumption (DCI), and perceived accessibility constraints (PACI), and estimates a series of logistic regression models to identify the determinants of the preference–behavior gap. The results reveal that perceived accessibility constraints have a statistically significant effect on behavioral inconsistency. However, contrary to initial expectations, the relationship is negative, indicating that higher perceived constraints are associated with a lower probability of exhibiting a preference–behavior gap. In contrast, gender differences remain significant, while consumption intensity measures do not explain the observed discrepancy. These findings suggest that the preference–behavior gap is shaped less by actual consumption patterns and more by how individuals perceive the feasibility of engaging in their preferred activities. Full article
(This article belongs to the Special Issue The Emotional Antecedents and Consequences of Buying and Consuming: A Multidisciplinary Perspective on Consumers’ Emotions—Second Edition)
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13 pages, 1857 KB  
Article
Photo-Oxidative Stability of Recycled Polypropylene: Effect of a Repair Additive on Degradation and Mechanical Retention
by Giulia Bernagozzi, Rossella Arrigo and Alberto Frache
Appl. Sci. 2026, 16(10), 4744; https://doi.org/10.3390/app16104744 (registering DOI) - 11 May 2026
Abstract
The increasing use of recycled polypropylene (rPP) in technical and outdoor applications requires strategies to limit photo-oxidative degradation while maintaining adequate performance after reprocessing. In this work, the photo-oxidative stability of rPP films was investigated under accelerated weathering conditions, focusing on the effect [...] Read more.
The increasing use of recycled polypropylene (rPP) in technical and outdoor applications requires strategies to limit photo-oxidative degradation while maintaining adequate performance after reprocessing. In this work, the photo-oxidative stability of rPP films was investigated under accelerated weathering conditions, focusing on the effect of a commercially available additive, Nexamite® R201 (NEX), previously shown to partially restore PP molecular weight after reprocessing. Films of rPP and rPP containing 5 wt.% NEX were produced by cast extrusion and exposed to cyclic UVA irradiation and water condensation in a QUV chamber, and the evolution of the functional and structural degradation of the materials was monitored as a function of aging time. Spectroscopical analyses showed progressive oxidation in both systems, with carbonyl growth starting after an induction period of about 200 h. A faster increase in the carbonyl index was observed for rPP containing NEX, indicating that the additive does not improve chemical oxidative resistance under the adopted conditions. However, NEX significantly enhanced the retention of mechanical properties during aging, with higher elongation and stress at break compared with unmodified rPP, thus delaying embrittlement. Overall, the results show that the investigated additive effectively mitigates the loss of mechanical integrity during photo-aging, likely as a consequence of the macromolecular restructuring induced during reprocessing. Full article
(This article belongs to the Special Issue Polymer Materials Chemistry: Design, Synthesis and Emerging Applications, Second Edition)
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18 pages, 5846 KB  
Article
Discovery of Natural α-Glucosidase Inhibitors from Hericium erinaceus Through Integrated Isolation, Structural Characterization, In Vitro Evaluation, and Molecular Dynamics Simulations
by Xianxian Miao, Xiangming Kong, Xiaodong Shang, Yan Yang, Wei Han, Jingsong Zhang and Na Feng
Molecules 2026, 31(10), 1605; https://doi.org/10.3390/molecules31101605 (registering DOI) - 11 May 2026
Abstract
Recognized for its dual nutritional and therapeutic value, the fungus Hericium erinaceus is increasingly acknowledged as a rich resource of naturally derived α-glucosidase inhibitors. In this study, eight compounds were isolated from H. erinaceus, including three novel compounds designated as erinacerins [...] Read more.
Recognized for its dual nutritional and therapeutic value, the fungus Hericium erinaceus is increasingly acknowledged as a rich resource of naturally derived α-glucosidase inhibitors. In this study, eight compounds were isolated from H. erinaceus, including three novel compounds designated as erinacerins X−Z (1, 2, and 6). Their absolute configurations were definitively elucidated using a combination of NMR, HR-MS, and ECD calculations. Furthermore, an integrated screening strategy combining molecular docking, molecular dynamics (MD) simulations, and surface plasmon resonance (SPR) analysis identified two isoindolin-1-ones (2 and 3) as potent naturally derived α-glucosidase inhibitors. Notably, in vitro testing established compounds 2 and 3 as robust α-glucosidase inhibitors, affording IC50 values of 17.80 ± 1.03 μM and 19.50 ± 1.33 μM, respectively. MD simulations revealed that electrostatic interactions and van der Waals forces are the primary drivers of this intermolecular association. These findings were further corroborated by SPR analysis, which quantified their high-affinity binding kinetics to the enzyme. Overall, this combined approach establishes a solid foundation for the discovery and development of natural α-glucosidase inhibitors from H. erinaceus. Full article
(This article belongs to the Section Organic Chemistry)
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15 pages, 1295 KB  
Article
Determinants and Dynamics of COVID-19 Vaccine Hesitancy in University Students: A Machine Learning Analysis
by Daliana Lobo Torres and Zahid Ahmad Butt
Vaccines 2026, 14(5), 429; https://doi.org/10.3390/vaccines14050429 (registering DOI) - 11 May 2026
Abstract
Background: Booster vaccine hesitancy poses a challenge to sustained COVID-19 immunization even among individuals who accepted primary vaccination. This study examined associated factors and patterns of change in vaccine attitudes among university students in Ontario, Canada. Methods: A cross-sectional survey dataset was analyzed [...] Read more.
Background: Booster vaccine hesitancy poses a challenge to sustained COVID-19 immunization even among individuals who accepted primary vaccination. This study examined associated factors and patterns of change in vaccine attitudes among university students in Ontario, Canada. Methods: A cross-sectional survey dataset was analyzed using validated psychometric scales to measure hesitancy toward primary and booster COVID-19 vaccination. Changes in hesitancy were operationalized as the continuous difference between booster and primary scores (ΔVH). Gradient Boosting and XGBoost regression models were fitted to estimate ΔVH from demographic characteristics (age, gender, socioeconomic status), vaccination history, and attitudinal constructs including complacency, confidence in vaccine safety, and perceived necessity of vaccination. Predictor contributions were assessed using SHapley Additive exPlanations, and Gaussian Mixture Modeling was employed to identify latent profiles among students with increased hesitancy. Results: A substantial proportion of students demonstrated higher hesitancy toward booster doses. Attitudinal factors, particularly complacency and safety perceptions, were the most influential predictors of increased hesitancy, whereas sociodemographic characteristics showed limited influence. Three distinct profiles of booster hesitancy were identified, reflecting heterogeneous patterns of vaccine attitudes and behaviors. Conclusions: These findings suggest that booster hesitancy in the study population is primarily associated with modifiable perceptions and can be effectively characterized using machine learning approaches that may inform targeted public health communication strategies. Full article
(This article belongs to the Special Issue Acceptance and Hesitancy in Vaccine Uptake: 3rd Edition)
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18 pages, 3548 KB  
Article
Optimal Control of Opinion Dynamics on Complex Networks via Discounted LQR: Theory and Computation
by Yajin Chen, Hongwei Gao, Yanshan Liu and Zhonghao Jiang
Mathematics 2026, 14(10), 1623; https://doi.org/10.3390/math14101623 (registering DOI) - 11 May 2026
Abstract
This paper investigates the optimal control problem of opinion dynamics within complex networks. By introducing a state transformation, the original problem is reformulated within a discounted Linear Quadratic Regulator (LQR) framework, establishing a connection between opinion control and classical control theory. Within this [...] Read more.
This paper investigates the optimal control problem of opinion dynamics within complex networks. By introducing a state transformation, the original problem is reformulated within a discounted Linear Quadratic Regulator (LQR) framework, establishing a connection between opinion control and classical control theory. Within this unified framework, the optimal control law can be obtained by solving the discrete-time algebraic Riccati equation, thereby circumventing the complexity of dealing with linear terms inherent in traditional dynamic programming approaches. Numerical experiments validate the effectiveness of the algorithm in a benchmark case, a 20-node complete network, and complex topologies. They also reveal the influence mechanisms of network heterogeneity on convergence speed and control energy consumption, providing a theoretical basis for public opinion guidance strategies under different network structures. Full article
(This article belongs to the Special Issue Trends and Prospects in Control and Dynamic Games)
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19 pages, 2154 KB  
Article
Improving Land Information Through Integrating Remote Sensing and Field Surveys: Evidence from the Bangladesh National Forest Inventory
by Rashed Jalal, Akhter Hossain, Zaheer Iqbal, Mariam Akhter, Tariq Aziz, Rajib Mahamud, Mondal Falgoonee Kumar, Shahidul Islam, Mohammad Abdul Hadi, Amit Ghosh, Fatima Mushtaq, Gael Sola, Liam Costello and Kristofer Johnson
Land 2026, 15(5), 812; https://doi.org/10.3390/land15050812 (registering DOI) - 11 May 2026
Abstract
Reliable land cover information is essential for scaling plot-based measurements in national forest inventories (NFIs). This study compared the precision of key forest indicators in the Bangladesh NFI using remote sensing (RS)-derived and field-assigned land cover data. Field data from 1781 plots, collected [...] Read more.
Reliable land cover information is essential for scaling plot-based measurements in national forest inventories (NFIs). This study compared the precision of key forest indicators in the Bangladesh NFI using remote sensing (RS)-derived and field-assigned land cover data. Field data from 1781 plots, collected as part of the Bangladesh NFI (2015–2019), were integrated with a 2015 national land cover map produced from SPOT-6/7, Landsat, and Sentinel-2 imagery. The precision of forest indicator estimates was evaluated across land cover domains and ecological zones. Results show that, under an unchanged NFI field measurement and estimation framework, RS-derived land cover reduced the width of confidence intervals (i.e., improved statistical precision) of estimates for most biomass related indicators, including above- and below-ground biomass, tree volume, basal area, and carbon pools, by 15–20% on average, with some reductions exceeding 50%. Improvements were less consistent for regeneration-related indicators (saplings, seedlings). The insights from this study highlight the advantages of remote sensing-derived land cover for improving NFI indicator precision, while underscoring the continued need for advancing ontology-driven approaches with necessary strengthening of field crew capacity to ensure the consistent application of land cover standards. Full article
(This article belongs to the Special Issue Advances on Land Cover/Land Use Ontologies for Innovative Production/Utilization of Land Information)
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6 pages, 166 KB  
Editorial
Innovative Treatment Technologies for Emerging Pollutants in Water
by Wenjie Zhang
Water 2026, 18(10), 1147; https://doi.org/10.3390/w18101147 (registering DOI) - 11 May 2026
Abstract
The rapid advancement of industrialization and urbanization has brought about significant challenges to water quality and environmental health [...] Full article
(This article belongs to the Special Issue Water Treatment Technology for Emerging Contaminants, 2nd Edition)
29 pages, 11784 KB  
Article
Time-Based Energy Conservation Measures in an Academic Building
by Ahmed Abd El-Hafez, Uthman Abdullah Alamri, Amr Sayed Hassan Abdallah, Mohammed A. Nayel, Hossam S. Abbas and Mohamed A. Hendy
Buildings 2026, 16(10), 1893; https://doi.org/10.3390/buildings16101893 (registering DOI) - 11 May 2026
Abstract
This paper proposes a time-based no-cost category of energy conservation measures (ECMs) enabled by audit-driven building energy modeling. The study presents an audit-to-simulation framework applied to an academic building (Electrical Engineering Department, Assiut University, Egypt) following the audit levels and requirements of ASHRAE [...] Read more.
This paper proposes a time-based no-cost category of energy conservation measures (ECMs) enabled by audit-driven building energy modeling. The study presents an audit-to-simulation framework applied to an academic building (Electrical Engineering Department, Assiut University, Egypt) following the audit levels and requirements of ASHRAE Standard 100-2024. The building operation is characterized via audit findings, high-resolution electrical monitoring, and occupancy profiling, then translated into a calibrated building energy model (BEM) developed using SketchUp, OpenStudio, and EnergyPlus. The validated BEM serves as a decision-support testbed to evaluate the proposed ECMs prior to implementation, enabling quantification of their impacts on annual and daily energy use, peak reduction, and load-profile shape. The proposed ECMs are classified into two subcategories: working-day ECMs and time-slot-modification ECMs. The first category involves adjusting the number of working days per week. The second category includes several scheduling-based strategies, namely seasonal time shifts, modification of lecture and tutorial session durations, rearrangement of lectures and tutorial sessions, and shifting peak-demand time slots. The simulation results show that modifying lecture and tutorial durations (ECM3) is the most effective measure, achieving 6.2% annual energy savings, followed by seasonal time shifts (ECM2) with 5.8%. For peak demand, reducing operation during peak periods (ECM5) lowers the daily peak load by 25.9%. The combined implementation of the proposed ECMs reduces annual energy consumption by up to 16% and daily peak demand by 29.4%. The findings highlight the substantial potential of structured audit-informed operational strategies in university buildings, emphasizing their role as low-risk, high-impact interventions for peak management and energy performance enhancement. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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21 pages, 6121 KB  
Article
Juniperus phoenicea L. Essential Oil from Ain El Orak (Algeria): Chemical Analysis by GC/MS, In Vitro Antioxidant and In Vivo/In Silico Gastroprotective and Hepatoprotective Effects
by Meriem Medjekane, Yacine Nait Bachir, Zohra Douaa Benyahlou, Fawzia Nemar, Housseyn Medjahed, Safia Ali Haimoud, Meryem Sadoud, Hiba Naas, Assia Nehari, Messouda Mansouri, Chaima Mimouni, Abdelkader Chouaih and Roberta Foligni
Foods 2026, 15(10), 1667; https://doi.org/10.3390/foods15101667 (registering DOI) - 11 May 2026
Abstract
Juniperus phoenicea L. is a popular plant in alternative medicine, particularly in the steppe and highland regions of western Algeria. The present study focuses on characterizing the essential oil of Juniperus phoenicea growing spontaneously in the Ain El Orak region of El Bayadh [...] Read more.
Juniperus phoenicea L. is a popular plant in alternative medicine, particularly in the steppe and highland regions of western Algeria. The present study focuses on characterizing the essential oil of Juniperus phoenicea growing spontaneously in the Ain El Orak region of El Bayadh province, where it is a valuable resource. The essential oil yield obtained by hydrodistillation was 0.98%, and its characterization by GC-MS revealed 46 compounds, predominantly α-Terpinolene at 21.29%, Limonene at 14.68%, Terpinene 4-ol at 12.04%, β-Myrcene at 9.93%, and β-Pinene at 7.31%. The study of the anti-radical activity against DPPH showed an IC50 value of approximately 0.23 mg/mL. The evaluation of the anti-ulcer property on experimentally induced ulcers in mice through oral administration of ethanol demonstrated excellent protection of the gastric mucosa, with 48.07%, 54.87%, and 81.92% protection for doses of 50, 100, and 200 mg/kg, respectively, comparable to omeprazole at 72.40%. The hepatoprotective activity against toxicity induced by intraperitoneal injection of a 250 mg/kg dose of paracetamol in mice showed a protective effect expressed by the decrease in serum levels of AST (260.33 ± 9.69 IU/L) and ALT (56.22 ± 9.63 IU/L) to values comparable to the those of the physiological group, especially for the 300 mg/kg dose of the essential oil of J. phoenicea. Full article
(This article belongs to the Section Food Quality and Safety)
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