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22 pages, 4216 KB  
Article
Development of an Adapted Water Quality Index for the Danube River Using Objective Weighting Methods
by Atila Bezdan and Jovana Bezdan
Hydrology 2025, 12(12), 329; https://doi.org/10.3390/hydrology12120329 (registering DOI) - 11 Dec 2025
Abstract
The Danube River is one of Europe’s largest transboundary rivers, characterized by substantial spatial heterogeneity in environmental conditions, monitoring practices, and water management frameworks. Developing a harmonized approach for basin-wide surface-water quality assessment is therefore essential. This study presents the development and application [...] Read more.
The Danube River is one of Europe’s largest transboundary rivers, characterized by substantial spatial heterogeneity in environmental conditions, monitoring practices, and water management frameworks. Developing a harmonized approach for basin-wide surface-water quality assessment is therefore essential. This study presents the development and application of an adapted Water Quality Index (Danube WQI) for assessing and monitoring water quality along the Danube River, one of Europe’s largest and most complex transboundary systems. The Danube WQI is based on established WQI methodologies and integrates two objective weighting approaches—the Entropy Weight Method (EWM) and the CRITIC (Criteria Importance Through Inter-Criteria Correlation) method—to minimize subjectivity and improve the robustness of parameter weighting. Long-term water quality data from the TransNational Monitoring Network (TNMN) of the International Commission for the Protection of the Danube River (ICPDR) were used, covering 42 stations across nine countries (1996–2022). Nine parameters were selected: dissolved oxygen (DO), biochemical oxygen demand (BOD5), total nitrogen (TN), nitrate (NO3), ammonium (NH4), total phosphorus (TP), orthophosphate (PO4), electrical conductivity (EC), and pH. During the formation of sub-indices and rating curves, national water quality standards from the Danube countries were harmonized to ensure consistent parameter classification. Results indicate that the Danube River generally exhibits very good water quality, with most sections belonging to the first and second quality classes. Comparison with the Canadian Water Quality Index (CWQI) confirmed similar results but demonstrated higher seasonal sensitivity of the Danube WQI. Additionally, rankings obtained using the PROMETHEE II multicriteria method showed strong agreement with the Danube WQI classifications, further confirming the robustness of the proposed index. The proposed index provides a harmonized and transferable framework that can support integrated water management and policy evaluation across the Danube River Basin and within the EU Water Framework Directive context. Full article
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18 pages, 4921 KB  
Article
Multi-State Photoluminescence of Donor–π–Acceptor Tetrafluorinated Tolane Mesogenic Dimers in Solution, Crystal, and Liquid-Crystalline Phases
by Sorato Inui, Yuto Eguchi, Masato Morita, Motohiro Yasui, Tsutomu Konno and Shigeyuki Yamada
Crystals 2025, 15(12), 1050; https://doi.org/10.3390/cryst15121050 (registering DOI) - 11 Dec 2025
Abstract
Photoluminescent liquid crystals with photoluminescence (PL) and liquid-crystalline (LC) properties have attracted attention as PL-switching materials owing to their thermally induced phase transitions, such as crystal → smectic A/nematic → isotropic phase transitions. Our group previously developed tetrafluorinated tolane mesogenic dimers linked by [...] Read more.
Photoluminescent liquid crystals with photoluminescence (PL) and liquid-crystalline (LC) properties have attracted attention as PL-switching materials owing to their thermally induced phase transitions, such as crystal → smectic A/nematic → isotropic phase transitions. Our group previously developed tetrafluorinated tolane mesogenic dimers linked by flexible alkylene-1,n-dioxy spacers, demonstrating that the position of the tetrafluorinated aromatic ring critically influences the LC behavior. However, these compounds exhibited very weak fluorescence owing to an insufficient D–π–A character of the π-conjugated mesogens, which facilitated internal conversion from emissive ππ* to non-emissive πσ* states. We designed and synthesized derivatives in which the mesogen–spacer linkage was modified from ether to ester, thereby enhancing the D–π–A character. Thermal and structural analyses revealed spacer-length parity effects: even-numbered spacers induced nematic phases, whereas odd-numbered spacers stabilized smectic A phases. Photophysical studies revealed multi-state PL across solution, crystal, and LC phases. Strong blue PL (ΦPL = 0.39–0.48) was observed in solution, while crystals exhibited aggregation-induced emission enhancement (ΦPL = 0.48–0.77) with spectral diversity. In LC states, ΦPL values up to 0.36 were maintained, showing reversible intensity and spectral shifts with phase transitions. These findings establish design principles that correlate spacer parity, phase behavior, and PL properties, enabling potential applications in PL thermosensors and responsive optoelectronic devices. Full article
(This article belongs to the Section Liquid Crystals)
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16 pages, 1662 KB  
Article
Tracing the Onset of Agriculture Through Phytolith Analysis at the Abora I Neolithic Settlement, Eastern Latvia
by Normunds Stivrins, Gunita Zariņa, Vanda Haferberga and Elina Reire
Heritage 2025, 8(12), 524; https://doi.org/10.3390/heritage8120524 (registering DOI) - 11 Dec 2025
Abstract
Phytolith analysis was applied for the first time in Latvian archaeology to investigate plant use at the Abora I settlement, one of the key Late Neolithic sites in the Lubāns Wetland, eastern Latvia. Phytoliths were extracted from sediments, pottery sherds, grinding stones, and [...] Read more.
Phytolith analysis was applied for the first time in Latvian archaeology to investigate plant use at the Abora I settlement, one of the key Late Neolithic sites in the Lubāns Wetland, eastern Latvia. Phytoliths were extracted from sediments, pottery sherds, grinding stones, and human teeth in order to assess evidence for cereal-type grasses and plant processing. A diverse range of phytolith morphotypes was identified, including rondel and bilobate forms commonly associated with grasses of the Triticeae. These morphotypes were most frequently recorded in association with grinding stones and food-related pottery. While previous isotopic and archaeological studies at Abora I indicate a subsistence strategy largely based on fishing, hunting, and gathering, the phytolith evidence points to localised small-scale processing of cereal-type grasses. Taken together, these results indicate that plant exploitation formed part of a mixed, multi-resource economy during the Late Neolithic at Abora I, although differentiation between wild and domesticated grasses remains limited due to taxonomic constraints of phytolith analysis. Full article
(This article belongs to the Section Archaeological Heritage)
27 pages, 1466 KB  
Article
A Lightweight Privacy-Enhanced Federated Clustering Algorithm for Edge Computing
by Jun Wang, Xianghua Chen, Xing Cheng, Jiantong Zhang, Tao Yu and Kewei Qian
Sensors 2025, 25(24), 7544; https://doi.org/10.3390/s25247544 (registering DOI) - 11 Dec 2025
Abstract
In edge computing scenarios, the data generated by distributed devices is characterized by its dispersion, heterogeneity, and privacy sensitivity, posing significant challenges to federated clustering, including high communication overhead, difficulty in adapting to non-IID data, and significant privacy leakage risks. To address these [...] Read more.
In edge computing scenarios, the data generated by distributed devices is characterized by its dispersion, heterogeneity, and privacy sensitivity, posing significant challenges to federated clustering, including high communication overhead, difficulty in adapting to non-IID data, and significant privacy leakage risks. To address these issues, this paper proposes a privacy-enhanced federated k-means clustering algorithm based on locality-sensitive hashing, aiming to mine latent knowledge from multi-source distributed data while ensuring data privacy protection. The core innovation of this algorithm lies in leveraging the distance sensitivity of clustering pairs, which effectively mitigates the non-IID problem while preserving data privacy and achieves global clustering in just a single communication round, significantly enhancing its practicality in communication-constrained environments. Specifically, the algorithm first evaluates local data dispersion at the client side, dynamically generates cluster cardinality based on dispersion, and obtains initial clustering centers through the k-means algorithm. Subsequently, it employs locality-sensitive hashing to encrypt the center points, uploading only the encrypted clustering information and weight data to the server, thereby achieving privacy protection without relying on a trusted server. On the server side, a secondary weighted k-means clustering is performed in the encrypted space to generate hashed global centers. Experimental results on the MNIST and CIFAR-10 datasets demonstrate that this method maintains robust clustering performance under non-IID data distributions. Most crucially, through a strict single-round client-to-server communication protocol, this approach significantly reduces communication overhead, providing a distributed data mining solution that is efficient, adaptable, and privacy-preserving for resource-constrained edge computing environments. Full article
(This article belongs to the Section Sensor Networks)
22 pages, 1479 KB  
Article
VMPANet: Vision Mamba Skin Lesion Image Segmentation Model Based on Prompt and Attention Mechanism Fusion
by Zinuo Peng, Shuxian Liu and Chenhao Li
J. Imaging 2025, 11(12), 443; https://doi.org/10.3390/jimaging11120443 (registering DOI) - 11 Dec 2025
Abstract
In the realm of medical image processing, the segmentation of dermatological lesions is a pivotal technique for the early detection of skin cancer. However, existing methods for segmenting images of skin lesions often encounter limitations when dealing with intricate boundaries and diverse lesion [...] Read more.
In the realm of medical image processing, the segmentation of dermatological lesions is a pivotal technique for the early detection of skin cancer. However, existing methods for segmenting images of skin lesions often encounter limitations when dealing with intricate boundaries and diverse lesion shapes. To address these challenges, we propose VMPANet, designed to accurately localize critical targets and capture edge structures. VMPANet employs an inverted pyramid convolution to extract multi-scale features while utilizing the visual Mamba module to capture long-range dependencies among image features. Additionally, we leverage previously extracted masks as cues to facilitate efficient feature propagation. Furthermore, VMPANet integrates parallel depthwise separable convolutions to enhance feature extraction and introduces innovative mechanisms for edge enhancement, spatial attention, and channel attention to adaptively extract edge information and complex spatial relationships. Notably, VMPANet refines a novel cross-attention mechanism, which effectively facilitates the interaction between deep semantic cues and shallow texture details, thereby generating comprehensive feature representations while reducing computational load and redundancy. We conducted comparative and ablation experiments on two public skin lesion datasets (ISIC2017 and ISIC2018). The results demonstrate that VMPANet outperforms existing mainstream methods. On the ISIC2017 dataset, its mIoU and DSC metrics are 1.38% and 0.83% higher than those of VM-Unet respectively; on the ISIC2018 dataset, these metrics are 1.10% and 0.67% higher than those of EMCAD, respectively. Moreover, VMPANet boasts a parameter count of only 0.383 M and a computational load of 1.159 GFLOPs. Full article
(This article belongs to the Section Medical Imaging)
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20 pages, 5905 KB  
Article
Phytoplankton Assemblage in the Campeche Canyon (Southern Gulf of Mexico) and Its Relationship with Hydrography During a “Nortes” Storm Season
by Elizabeth Durán-Campos, David Alberto Salas-de-León, María Adela Monreal-Gómez and Erik Coria-Monter
Phycology 2025, 5(4), 86; https://doi.org/10.3390/phycology5040086 (registering DOI) - 11 Dec 2025
Abstract
The Gulf of Mexico is a marginal sea recognized as one of the world’s Large Marine Ecosystems. It is characterized by significant climate variability that influences phytoplankton communities. In this paper we investigated the phytoplankton assemblages in the Campeche Canyon, located in the [...] Read more.
The Gulf of Mexico is a marginal sea recognized as one of the world’s Large Marine Ecosystems. It is characterized by significant climate variability that influences phytoplankton communities. In this paper we investigated the phytoplankton assemblages in the Campeche Canyon, located in the Southern Gulf of Mexico, during a “Nortes” storm season. Additionally, we assessed the role of hydrographic conditions and circulation patterns in species distribution. The assessment was based on in situ observations collected during a multidisciplinary research cruise conducted in February 2011. High-resolution hydrographic data were gathered using a CTD sonde, and water samples were collected at various depths for phytoplankton cell analysis. The findings revealed a deep thermocline at a depth of 90 m, with a deep chlorophyll-a maximum (DCM) occurring below 75 m. The circulation pattern in the area was dominated by a dipole eddy, consisting of both cyclonic and anticyclonic movements, which created strong currents at the edges. The species composition varied by depth; a total of 77 species were identified in the surface waters, while the DCM exhibited a richness of 81 species. In the surface waters, dinoflagellates were the most abundant group, comprising 41 species, whereas diatoms were more prevalent in the DCM, with 44 species identified. In terms of abundance, dinoflagellates were more prevalent at both depths, with concentrations reaching up to 12,000 cells L‒1. The most abundant species identified included the ciliate Mesodinium rubrum, the cyanobacteria Trichodesmium hildebrandtii, the diatoms Asteromphalus cleveanus and Pseudo-nitzschia multistriata, the dinoflagellates Lingulaulax polyedra and Blepharocysta denticulata, and the silicoflagellate Dictyocha fibula. Analysis of the horizontal distribution patterns of phytoplankton species revealed that species tend to aggregate in areas with strong currents. These findings enhance our understanding of phytoplankton dynamics in the Campeche Canyon, particularly during climatic seasons when in situ observations are limited due to challenging navigation conditions caused by “Nortes” storms. Full article
35 pages, 3089 KB  
Article
Enhancing Shaft Voltage Mitigation with Diffusion Models: A Comprehensive Review for Industrial Electric Motors
by Zuhair Abbas, Arifa Zahir and Jin Hur
Energies 2025, 18(24), 6504; https://doi.org/10.3390/en18246504 (registering DOI) - 11 Dec 2025
Abstract
Industrial electric motors powered by variable frequency drives (VFDs) offer better controllability as compared to the conventional sinusoid-fed motors. However, the switching transients of VFDs induce shaft voltage in electric motors, which can lead to bearing failure. This may cause the machine to [...] Read more.
Industrial electric motors powered by variable frequency drives (VFDs) offer better controllability as compared to the conventional sinusoid-fed motors. However, the switching transients of VFDs induce shaft voltage in electric motors, which can lead to bearing failure. This may cause the machine to shut down and pose a serious threat to the system’s reliability. Several shaft voltage mitigation strategies are suggested in the literature, including insulated bearings, grounding brushes, copper shields, and filters. Although mitigation strategies have been extensively studied, shaft voltage signal processing remains relatively underexplored. This review introduces diffusion models (DMs), a new generative learning technique, as an effective solution for processing shaft voltage signals. These models are good at reducing noise, handling uncertainty, and capturing complex patterns over time. DMs offer robust performance under dynamic conditions as compared to traditional machine learning (ML) and deep learning (DL) techniques. In summary, the review outlines the sources and causes of shaft voltage, its existing mitigation strategies, and the theory behind DMs for shaft voltage analysis. Thus, by combining insights from electrical engineering and artificial intelligence (AI), this work addresses an important gap in the existing literature and provides a strong path forward for improving the reliability of industrial motor systems. Full article
(This article belongs to the Special Issue Advanced Structures, Fault Diagnosis and Tolerant Control of Permanent Magnet Synchronous Motors: 2nd Edition)
12 pages, 651 KB  
Article
Viscosity-Dependent Shrinkage Behavior of Flowable Resin Composites
by Nadja Jeconias, Peter Fischer and Tobias T. Tauböck
Polymers 2025, 17(24), 3292; https://doi.org/10.3390/polym17243292 (registering DOI) - 11 Dec 2025
Abstract
Flowable resin composites are extensively used in restorative dentistry, where linear polymerization shrinkage and the resulting shrinkage stress are critical for clinical success. This study investigated the relationship between viscosity, linear polymerization shrinkage, and shrinkage stress in flowable resin composite materials. Two low-flow [...] Read more.
Flowable resin composites are extensively used in restorative dentistry, where linear polymerization shrinkage and the resulting shrinkage stress are critical for clinical success. This study investigated the relationship between viscosity, linear polymerization shrinkage, and shrinkage stress in flowable resin composite materials. Two low-flow resin composites (Beautifil Flow Plus F00, Estelite Universal Flow SuperLow), two medium-flow resin composites (Tetric EvoFlow, Estelite Universal Flow Medium), and two high-flow resin composites (Beautifil Flow F10, Estelite Universal Flow High) were examined. Viscosity (n = 3) of the unset materials was determined using a cone–plate rheometer. The composites were photoactivated for 20 s at 1226 mW/cm2, and linear polymerization shrinkage (n = 8) and shrinkage stress (n = 8) of 1.5 mm-thick specimens were recorded in real time for 5 min using a custom-made linometer and stress analyzer, respectively. Data were analyzed with Kruskal–Wallis rank tests followed by Conover post hoc tests, and Spearman correlation analyses were conducted to assess relationships between parameters (α = 0.05). A significant negative correlation was observed between viscosity and shrinkage stress (r = −0.943, p = 0.017). Beautifil Flow F10 exhibited the significantly lowest viscosity (14.60 ± 0.17 Pa·s) and the highest shrinkage stress (0.83 ± 0.14 MPa) among the materials, whereas low-flow composite Estelite Universal Flow SuperLow showed the lowest shrinkage stress (0.65 ± 0.10 MPa). Linear shrinkage ranged from 1.89 ± 0.13% to 3.18 ± 0.21%, but was not correlated with viscosity or stress (p > 0.05). In conclusion, viscosity critically influences polymerization-induced shrinkage stress development in flowable resin composites. Higher-viscosity flowable composites might be beneficial regarding stress build-up during polymerization compared with high-flow composites. Full article
(This article belongs to the Special Issue Advanced Polymeric Materials for Dental Applications III)
18 pages, 958 KB  
Article
Metacognition and Social Presence in Connectivist Learning: An Analysis of Bilibili Interactions
by Huijin Lu, Maria Limniou and Xiaojun Zhang
Educ. Sci. 2025, 15(12), 1673; https://doi.org/10.3390/educsci15121673 (registering DOI) - 11 Dec 2025
Abstract
Connectivist learning has emerged as a contemporary theory in technology-enhanced education, emphasising the importance of learners’ metacognitive skills to manage their learning within connected communities. Despite its growing relevance, limited empirical evidence discussing how learners’ metacognitive patterns interact with the development of learning [...] Read more.
Connectivist learning has emerged as a contemporary theory in technology-enhanced education, emphasising the importance of learners’ metacognitive skills to manage their learning within connected communities. Despite its growing relevance, limited empirical evidence discussing how learners’ metacognitive patterns interact with the development of learning communities. This study took the first step by empirically investigating the interplay between metacognition and social presence through reciprocal interactions on Bilibili, a learning social media platform in China. From a dataset of 4084 comments, 485 interactions were extracted and analysed using k-means clustering, followed by a chi-square test to explore associations with social presence interactions. The findings reveal that learners actively engage in metacognition processes, particularly planning, monitoring, and evaluating their learning, within connectivist environments. Furthermore, the dynamic exchange of ideas fosters continuous knowledge construction, supporting both lifelong and informal learning. Crucially, the interdependence between metacognition engagement and social presence not only underscores their role in achieving deep and sustainable learning but also highlights the evolving identity of online learners as network facilitators on social media platforms. Full article
(This article belongs to the Special Issue Learning in Digital Ecologies: Everyday Informal Education and the Fabrication of Social Worlds)
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16 pages, 898 KB  
Article
MoE-World: A Mixture-of-Experts Architecture for Multi-Task World Models
by Cong Tang, Yuang Liu, Yueling Wu, Wence Han, Qian Yin, Xin Zheng, Wenyi Zeng and Qiuli Zhang
Electronics 2025, 14(24), 4884; https://doi.org/10.3390/electronics14244884 (registering DOI) - 11 Dec 2025
Abstract
World models are currently a mainstream approach in model-based deep reinforcement learning. Given the widespread use of Transformers in sequence modeling, they have provided substantial support for world models. However, world models often face the challenge of the seesaw phenomenon during training, as [...] Read more.
World models are currently a mainstream approach in model-based deep reinforcement learning. Given the widespread use of Transformers in sequence modeling, they have provided substantial support for world models. However, world models often face the challenge of the seesaw phenomenon during training, as predicting transitions, rewards, and terminations is fundamentally a form of multi-task learning. To address this issue, we propose a Mixture-of-Experts-based world model (MoE-World), a novel architecture designed for multi-task learning in world models. The framework integrates Transformer blocks organized as mixture-of-experts (MoE) layers, with gating mechanisms implemented using multilayer perceptrons. Experiments on standard benchmarks demonstrate that it can significantly mitigate the seesaw phenomenon and achieve competitive performance on the world model’s reward metrics. Further analysis confirms that the proposed architecture enhances both the accuracy and efficiency of multi-task learning. Full article
(This article belongs to the Special Issue Reinforcement Learning: Sample Efficiency, Generalisation, and AI Applications)
19 pages, 1025 KB  
Article
Study on Low-Temperature Adaptability of High Fly Ash Content-Based Backfill Material
by Wei Wang, Gaofeng Ren, Shishan Ruan, Runing Han and Chao Yang
Minerals 2025, 15(12), 1300; https://doi.org/10.3390/min15121300 (registering DOI) - 11 Dec 2025
Abstract
To address the issues of high cost and poor low-temperature adaptability in cement-based backfill materials, this study developed a high-volume fly ash-based solid waste cementitious backfill material (FAPB) along with a specialized low-temperature admixture. Investigated the fundamental properties and microscopic curing mechanisms of [...] Read more.
To address the issues of high cost and poor low-temperature adaptability in cement-based backfill materials, this study developed a high-volume fly ash-based solid waste cementitious backfill material (FAPB) along with a specialized low-temperature admixture. Investigated the fundamental properties and microscopic curing mechanisms of the FAPB at different temperatures. The results indicate that the yield stress and plastic viscosity of FAPB slurry increase with higher contents of the curing agent and admixture, and rise as the temperature decreases. The variation in slump flow aligns with the rheological parameters, with the minimum slump flow being 14.5 cm (>10 cm). Bleeding rate increases with decreasing amounts of curing agent and admixture content, as well as lower temperatures, reaching a maximum bleeding rate of 9.26% (T5C10). Setting time decreases with increased amounts of curing agent and admixtures, and significantly increases with decreasing temperature. Strength increases with curing time and curing agent content, but decreases significantly as temperature drops. Adding admixtures can compensate for strength deterioration caused by low temperatures, with an optimal dosage of 3%. Microstructural analysis showed that the main hydration products of hardened backfill include AFt, C-S(A)-H, and Ca(OH)2. Low temperature (5 °C) restricts hydration product formation, and the admixture facilitates continuous polycondensation of C-S(A)-H gel, resulting in sustained strength gain. This study provides a theoretical basis for the preparation and application of low-temperature-resistant Fly ash-based backfill materials, holding significant importance for advancing green mining practices in cold regions. Full article
(This article belongs to the Special Issue Rheological, Mechanical and Hydration Properties of Cemented Paste Backfill)
25 pages, 2669 KB  
Review
The Trigger in IVF Cycles: Molecular Pathways and Clinical Implications
by Giorgio Maria Baldini, Domenico Baldini, Dario Lot, Daniele Ferri, Antonio Malvasi, Bernard Fioretti, Maria Matteo and Raoul Orvieto
Int. J. Mol. Sci. 2025, 26(24), 11962; https://doi.org/10.3390/ijms262411962 (registering DOI) - 11 Dec 2025
Abstract
The final trigger of oocyte maturation is a pivotal step in assisted reproductive technology (ART). Different molecules and protocols—including human chorionic gonadotropin (hCG), gonadotropin-releasing hormone agonists (GnRHa), the dual trigger, the double trigger, and emerging agents such as kisspeptin—have been investigated to optimize [...] Read more.
The final trigger of oocyte maturation is a pivotal step in assisted reproductive technology (ART). Different molecules and protocols—including human chorionic gonadotropin (hCG), gonadotropin-releasing hormone agonists (GnRHa), the dual trigger, the double trigger, and emerging agents such as kisspeptin—have been investigated to optimize oocyte competence, embryo development, and pregnancy outcomes while minimizing the risk of ovarian hyperstimulation syndrome (OHSS). HCG remains the most widely used trigger, but its pharmacological profile is associated with a significant risk of OHSS. GnRHa has emerged as an alternative in antagonist cycles, abolishing the risk of severe OHSS but often requiring tailored luteal phase support. Several strategies, including hCG, GnRHa, and combined approaches, have shown improvements in specific outcomes such as the oocyte maturity (MII) rate, fertilization rate, embryo development parameters, and, in selected contexts, a reduction in OHSS risk. Kisspeptin represents a promising option; however, its use remains predominantly within the research setting, with clinical application still limited to early-phase or highly selected studies. Beyond the choice of molecule, the timing of trigger administration—adjusted to follicle size, estradiol concentrations, and progesterone levels—also influences oocyte competence and subsequent clinical outcomes. Triggering final oocyte maturation remains a multifaceted decision that should be individualized according to patient characteristics, ovarian response, and risk of OHSS. Although hCG remains the historical reference standard, accumulating but heterogeneous evidence suggests that GnRHa-based strategies, including dual-trigger protocols, may improve specific outcomes in selected patient subgroups. However, results across trials are inconsistent, particularly in poor responders, and any exposure to hCG maintains a residual risk of OHSS. Kisspeptin represents a promising but still experimental option, with current data largely limited to early-phase clinical studies in highly selected high-risk populations. Well-designed randomized trials are required to clarify the true impact of these strategies on live birth, to refine timing and dosing, and to better define which patients are most likely to benefit. Full article
(This article belongs to the Section Molecular Biology)
35 pages, 4133 KB  
Article
Impact of Coal Mining on Growth and Distribution of Sabina vulgaris Shrublands in Mu Us Sandy Land: Evidence from Multi-Temporal Gaofen-1 Remote Sensing Data
by Jia Li, Huanwei Sha, Xiaofan Gu, Gang Qiao, Shuhan Wang, Boyuan Li and Min Yang
Forests 2025, 16(12), 1849; https://doi.org/10.3390/f16121849 (registering DOI) - 11 Dec 2025
Abstract
Sabina vulgaris is a keystone shrub species endemic to arid northwestern China, renowned for its exceptional drought tolerance, sand fixation capabilities, and critical role in desert ecosystem stability. This study investigates the impact of coal mining activities on the spatiotemporal dynamics of S. [...] Read more.
Sabina vulgaris is a keystone shrub species endemic to arid northwestern China, renowned for its exceptional drought tolerance, sand fixation capabilities, and critical role in desert ecosystem stability. This study investigates the impact of coal mining activities on the spatiotemporal dynamics of S. vulgaris shrublands in the ecologically fragile Mu Us Sandy Land, focusing on the Longde Coal Mine adjacent to the Shenmu S. vulgaris Nature Reserve. Utilizing seven periods (2013–2025) of 2 m resolution Gaofen-1 (GF-1) satellite imagery spanning 12 years of mining operations, we implemented a deep learning approach combining UAV-derived hyperspectral ground truth data and the SegU-Net semantic segmentation model to map shrub distribution via GF-1 data with high precision. Classification accuracy was rigorously validated through confusion matrix analysis (incorporating the Kappa coefficient and overall accuracy metrics). Results reveal contrasting trends: while the S. vulgaris Protection Area exhibited substantial expansion (e.g., Southern Section coverage grew from 2.6 km2 in 2013 to 7.88 km2 in 2025), mining panels experienced significant degradation. Within Panel 202, coverage declined by 15.4% (58.4 km2 to 49.5 km2), and Panel 203 showed a 18.5% decrease (3.16 km2 to 2.57 km2) over the study period. These losses correlate spatially and temporally with mining-induced groundwater depletion and land subsidence, disrupting the shrub’s shallow-root water access strategy. The study demonstrates that coal mining drives fragmentation and coverage reduction in S. vulgaris communities through mechanisms including (1) direct vegetation destruction, (2) aquifer disruption impairing drought adaptation, and (3) habitat fragmentation. These findings underscore the necessity for targeted ecological restoration strategies integrating groundwater management and progressive reclamation in mining-affected arid regions. Full article
(This article belongs to the Special Issue Guidelines for Sustainable Forest Management: Vegetation and Soil and Water Conservation in Arid Areas)
19 pages, 5949 KB  
Article
BCAA (Branched-Chain Amino Acids) Inhibiting the Autophagy System via the Activation of mTORC1, Thereby Upregulating the Tumor Suppressor PDCD4 in Huh7 Hepatoma Cells
by Rasheda Perveen, Iwata Ozaki, Hirokazu Takahashi, Md Manirujjaman, Takuya Kuwashiro and Sachiko Matsuhashi
Cells 2025, 14(24), 1975; https://doi.org/10.3390/cells14241975 (registering DOI) - 11 Dec 2025
Abstract
Branched-chain amino acids (BCAAs) are essential amino acids in humans, with reported anti-proliferative effects on HepG2 hepatoma cells and the potential to reduce hepatocellular carcinoma (HCC) development in cirrhotic patients. PDCD4, a tumor suppressor that is downregulated in many cancers, is also suppressed [...] Read more.
Branched-chain amino acids (BCAAs) are essential amino acids in humans, with reported anti-proliferative effects on HepG2 hepatoma cells and the potential to reduce hepatocellular carcinoma (HCC) development in cirrhotic patients. PDCD4, a tumor suppressor that is downregulated in many cancers, is also suppressed by serum, EGF, or TPA treatment. This study examined the effect BCAA has on PDCD4 expression and related cellular pathways in Huh7 hepatoma cells. Cells were treated with different concentrations of BCAA, and analyzed by Western blotting, qRT-PCR, and immunofluorescence staining. Treatment with BCAA upregulated the protein levels of PDCD4, while downregulating its mRNA levels. BCAA enhanced the phosphorylation of mTORC1 substrate 4E-BP1, p70S6K1, and p70S6K1 substrate S6 ribosomal protein. BCAA also elevated the protein levels of autophagy factors p62 and ATG5 while reducing LC3-II particle formation, thus indicating impaired autophagy. ULK1 knockdown also upregulated the protein levels of PDCD4 and p62. Additionally, BCAA upregulated the phosphorylation of ULK1 at serine 757, which was inhibited by rapamycin. These findings suggest that BCAA inhibits autophagy through the mTORC1-mediated phosphorylation of ULK1 at serine 757, thereby impairing autophagosome formation and upregulating the PDCD4 protein levels by inhibiting its degradation via autophagy. Furthermore, FACS analysis showed that BCAA inhibited the proliferation of Huh7 cells. BCAA may have a preventive effect against tumor development through the modulation of autophagy and the tumor suppressor pathways. Full article
(This article belongs to the Section Cell Signaling)
19 pages, 7066 KB  
Article
Improvement and Validation of Transient Analysis Code FRTAC for Liquid Metal-Cooled Fast Reactors
by Jian Hong, Bo Kuang, Lixia Ren, Yuping Zhou, Xintong Zhao, Xiaochen Xu, Shirui Li and Wenjun Hu
Energies 2025, 18(24), 6503; https://doi.org/10.3390/en18246503 (registering DOI) - 11 Dec 2025
Abstract
Transient safety analysis is a critical aspect of ensuring the safe design of Liquid Metal-cooled Fast Reactors (LMRs), relying heavily on advanced system analysis programs. To this end, the China Institute of Atomic Energy (CIAE) independently developed the Fast Reactor Transient Analysis Code [...] Read more.
Transient safety analysis is a critical aspect of ensuring the safe design of Liquid Metal-cooled Fast Reactors (LMRs), relying heavily on advanced system analysis programs. To this end, the China Institute of Atomic Energy (CIAE) independently developed the Fast Reactor Transient Analysis Code (FRTAC) system analysis code for LMRs, which has been applied to the safety analysis of several reactor types. However, long-term use has revealed certain limitations, such as complex control system modeling and numerical dissipation from the first-order numerical scheme. This study analyzes the current limitations of the code and carries out systematic improvements and validation. The main improvements include enhancing the system compilation architecture and refactoring functional modules to improve computational efficiency, scalability, and usability; introducing a second-order accurate numerical scheme based on a limiter to reduce numerical dissipation in the convection term while ensuring computational stability; and optimizing the solution procedure to accommodate the new architecture and algorithms. The improved code’s computational stability and accuracy were validated using the Edwards blowdown experiment and the Energy Technology Engineering Center (ETEC) once-through steam generator steady-state test, respectively. The validation results show that the improved code maintains excellent numerical stability in problems with rapid transient pressure changes. In steady-state convective heat transfer problems, the computational accuracy and grid convergence are significantly improved, with the relative deviation of the water-side outlet temperature reduced from −3.56% to −0.59%. Under the same computational conditions, the computational efficiency was increased by up to 36.1%. The results of this study will provide a more accurate and efficient system analysis code for the transient safety analysis of LMRs. Full article
(This article belongs to the Special Issue Thermal Hydraulics and Safety Research for Nuclear Reactors)
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8 pages, 366 KB  
Protocol
Supporting Self-Direction in Social and Daily Life Contexts Among Vulnerable Older Adults: A Protocol for an Integrative Review and Concept Analysis
by Golnaz Atefi, Lieve Roets-Merken and Maud J. L. Graff
Behav. Sci. 2025, 15(12), 1718; https://doi.org/10.3390/bs15121718 (registering DOI) - 11 Dec 2025
Abstract
Objectives: This study aims to provide conceptual clarity on self-direction support in the care of vulnerable older adults, particularly those with dementia. It focuses on how self-direction is supported in meaningful daily activities and social participation. The goal is to define and operationalize [...] Read more.
Objectives: This study aims to provide conceptual clarity on self-direction support in the care of vulnerable older adults, particularly those with dementia. It focuses on how self-direction is supported in meaningful daily activities and social participation. The goal is to define and operationalize the concept by identifying its key attributes, antecedents, and consequences across care contexts. Methods: A two-phase approach will be used. First, an integrative review will synthesize empirical evidence from gerontology, occupational therapy, psychology, nursing, and health ethics to examine current conceptualizations and practices. Second, a concept analysis will explore the theoretical structure of self-direction support. Findings will be synthesized into a conceptual framework. Expected outcomes: This study is expected to provide a clearer conceptual framework outlining the core components of self-direction as described in existing literature. This framework will define key attributes, identify influencing factors, and propose measurable indicators. The framework aims to guide professionals in balancing autonomy, safety, and care needs. Conclusions: As this is a study protocol, no results are presented; findings will be reported in the forthcoming review. The anticipated outcomes are expected to contribute to theory and practice by framing self-direction within social health. The framework may inform future research, policy, and intervention development to strengthen self-direction in meaningful activities and participation among vulnerable older adults. Further validation across settings and cultural contexts will be required. Full article
(This article belongs to the Special Issue Psychosocial Care and Support in Dementia)
23 pages, 4511 KB  
Article
Modeling Habitat Suitability for Endemic Anthemis pedunculata subsp. pedunculata and Anthemis pedunculata subsp. atlantica in Mediterranean Region Using MaxEnt and GIS-Based Analysis
by Kaouther Mechergui, Wahbi Jaouadi, Carlos Henrique Souto Azevedo, Khadeijah Yahya Faqeih, Somayah Moshrif Alamri, Eman Rafi Alamery, Maha Abdullah Aldubehi and Philipe Guilherme Corcino Souza
Diversity 2025, 17(12), 851; https://doi.org/10.3390/d17120851 - 11 Dec 2025
Abstract
Climate change accelerates biodiversity loss, threatening ecosystems worldwide. Using predictive models, such as the maximum entropy model (Maxent), allows us to identify changes in species distribution and guide conservation strategies. This study aims to model the current and future distribution of Anthemis pedunculata [...] Read more.
Climate change accelerates biodiversity loss, threatening ecosystems worldwide. Using predictive models, such as the maximum entropy model (Maxent), allows us to identify changes in species distribution and guide conservation strategies. This study aims to model the current and future distribution of Anthemis pedunculata subsp. Atlantica and Anthemis pedunculata subsp. pedunculata in Mediterranean regions through MaxEnt modeling with bioclimatic predictors. Using the MaxEnt algorithm, we combine bioclimatic variables and 49 occurrence locations of Anthemis pedunculata subsp. pedunculata and 13 occurrence locations of Anthemis pedunculata subsp. atlantica. The future distribution of the species is projected using MIROC6 model simulations under emission scenario SSP5-8.5 for 2030 and 2050. The current model predicted approximately 99,330,066 ha as a suitable habitat for Anthemis pedunculata subsp. pedunculata. Projections for the future range exhibited a gradual increase in the suitable area in 2030 by 144,365,562 ha and 2050 by 147,335,265 ha. The current model predicted approximately 201,179,880 ha as a suitable habitat for Anthemis pedunculata subsp. atlantica. Projections for the future range exhibited a gradual enhancement of the suitable area in 2030 by 213,898,608 ha and 2050 by 229,357,062. Our results provide further evidence of the negative impact of climate change on these endemic species and emphasize the importance of their conservation. This study provides information that could strengthen the protection of these species and identify potential protection areas. Full article
(This article belongs to the Section Plant Diversity)
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15 pages, 646 KB  
Article
Plant-Based vs. Pork Sausages: Protein Nutritional Quality and Antioxidant Potential in the Bioaccessible Fraction
by Narigul Khamzaeva, Bettina Hieronimus, Christina Kunz, Larissa E. Pferdmenges and Karlis Briviba
Foods 2025, 14(24), 4271; https://doi.org/10.3390/foods14244271 (registering DOI) - 11 Dec 2025
Abstract
The sales volume and consumption of plant-based meat substitutes is steadily increasing. Since meat and meat products are an important protein source, this study focused on the nutritional protein quality (Digestible Indispensable Amino Acid Score (DIAAS)) of alternative sausages based on soy, wheat, [...] Read more.
The sales volume and consumption of plant-based meat substitutes is steadily increasing. Since meat and meat products are an important protein source, this study focused on the nutritional protein quality (Digestible Indispensable Amino Acid Score (DIAAS)) of alternative sausages based on soy, wheat, and a wheat-soy blend in comparison to a pork-based sausage using the tiny-TIMsg gastrointestinal model. The protein digestibility of all products ranged from 80.8% (soy sausage) and 87.1 to 89.0% (other sausages). The highest DIAAS values were obtained for pork sausage limited by leucine (116%). Soy sausage was limited in sulfur-containing amino acids (86%). Wheat and wheat-soy sausages were limited by lysine (33% and 41%, respectively). The antioxidant activity of the bioaccessible fractions revealed a higher antioxidative potential of the plant-based sausages. While plant-based sausages offer comparable protein digestibility and superior antioxidant capacity, their significantly lower DIAAS values underscore the potential for formulation strategies that consider nutritional aspects. Full article
(This article belongs to the Special Issue Alternative Protein: Sources, Bioactivities, Potential Health Benefits, and Application)
26 pages, 1135 KB  
Review
Impact of Oral and Gut Microbiota Dysbiosis in Patients with Multiple Myeloma and Hematological Malignancies: A Narrative Review
by Antonio Belmonte, Ylenia Leanza, Alessandro Polizzi, Alessandra Romano, Alessandro Allegra, Rosalia Leonardi, Cristina Panuzzo and Gaetano Isola
Oral 2025, 5(4), 101; https://doi.org/10.3390/oral5040101 (registering DOI) - 11 Dec 2025
Abstract
The interplay between the oral and gut microbiota and systemic health has garnered significant attention in recent years, particularly concerning hematological malignancies. Multiple myeloma and other hematological cancers are characterized by immune dysfunction, creating a bidirectional relationship with microbial communities. Dysbiosis, defined as [...] Read more.
The interplay between the oral and gut microbiota and systemic health has garnered significant attention in recent years, particularly concerning hematological malignancies. Multiple myeloma and other hematological cancers are characterized by immune dysfunction, creating a bidirectional relationship with microbial communities. Dysbiosis, defined as an imbalance in microbial composition, may influence disease progression, treatment response, and overall prognosis. This narrative review is based on a non-systematic search of PubMed and Scopus (2010–2024) using terms related to oral microbiota, gut microbiota, dysbiosis, hematological malignancies, multiple myeloma, immune modulation, and treatment-related complications. Studies were selected for relevance to pathogenesis, immune regulation, clinical implications, and therapeutic interactions. As this is a narrative review, no quantitative synthesis or formal grading of evidence strength was performed; findings are therefore interpreted qualitatively based on the available literature. The role of microbial-derived metabolites, their effects on immune modulation, and their potential as biomarkers for disease and treatment outcomes have been explored. Specific attention is given to the implications of dysbiosis in chemotherapy-induced complications, such as mucositis and infections, and emerging therapeutic strategies, including probiotics, prebiotics, and fecal microbiota transplantation. Additionally, the influence of anticancer therapies on microbial ecosystems has been highlighted and the bidirectional impact of host–microbe interactions in shaping disease trajectory has been discussed. Understanding these complex interactions could lead to novel diagnostic and therapeutic approaches, ultimately improving patient outcomes. This review aims to provide clinicians and researchers with a comprehensive overview of current knowledge and future perspectives on the role of oral and gut microbiota in the context of hematological malignancies. Full article
21 pages, 11885 KB  
Article
Solvent-Free Catalytic Synthesis of Ethyl Butyrate Using Immobilized Lipase Based on Hydrophobically Functionalized Dendritic Fibrous Nano-Silica
by Mengqi Wang, Yi Zhang, Yunqi Gao, Huanyu Zheng and Mingming Zheng
Foods 2025, 14(24), 4272; https://doi.org/10.3390/foods14244272 (registering DOI) - 11 Dec 2025
Abstract
Ethyl butyrate is a typical flavor ester with pineapple-banana scents, but the poor yield from natural fruits limits its feasibility in food and fragrance industries. In this study, dendritic fibrous nano-silica (DFNS) was hydrophobically modified with octyl groups (DFNS-C8) to immobilize [...] Read more.
Ethyl butyrate is a typical flavor ester with pineapple-banana scents, but the poor yield from natural fruits limits its feasibility in food and fragrance industries. In this study, dendritic fibrous nano-silica (DFNS) was hydrophobically modified with octyl groups (DFNS-C8) to immobilize Candida antarctica lipase B (CALB) for solvent-free esterification of ethyl butyrate. The immobilized lipase CALB@DFNS-C8, with the enzyme loading of 354.6 mg/g and the enzyme activity of 0.064 U/mg protein, achieved 96.0% ethyl butyrate conversion under the optimum reaction conditions where the molar ratio of butyric acid to ethanol was 1:3, with a reaction temperature and time of 40 °C and 4 h. Under the solvent-free catalytic reactions, CALB@DFNS-C8 presented the maximum catalytic efficiency of 35.1 mmol/g/h and retained 89% initial activity after ten reuse cycles. In addition, the immobilized lipase can efficiently catalyze the synthesis of various flavor esters (such as butyl acetate, hexyl acetate, butyl butyrate, etc.) and exhibits excellent thermostability and solvent tolerance. A molecular docking simulation reveals that the hydrophobic cavity around the catalytic triad stabilizes the acyl intermediate and ensures the precise orientation of both acid and alcohol substrates. This work provides new insights into the sustainable production of flavor esters using highly active and recyclable immobilized lipases through rational carrier hydrophobization and structural confinement design. Full article
(This article belongs to the Special Issue Functional Lipids and Proteins—Chemistry, Nutrition and Health Promotion)
23 pages, 938 KB  
Article
MintSR: Multi-Intent Perception with Time-Based Segmentation for Session-Based Recommendation
by Yuan Huang, Ruizhi Yin, Xiaozheng Zhou and Pengwei Shi
Appl. Sci. 2025, 15(24), 13078; https://doi.org/10.3390/app152413078 (registering DOI) - 11 Dec 2025
Abstract
In an anonymous session recommendation scenario, the key to predicting the user’s next interaction item is accurately recognizing the user’s intent. Traditional methods focusing on the item Identity Document (ID) modeling have limitations. They often only consider the current preference based on the [...] Read more.
In an anonymous session recommendation scenario, the key to predicting the user’s next interaction item is accurately recognizing the user’s intent. Traditional methods focusing on the item Identity Document (ID) modeling have limitations. They often only consider the current preference based on the target session and the last clicked item, neglecting the user’s long-term intention tendencies and dynamic changes in intent over time. Moreover, solely relying on ID modeling can result in biased recommendations towards popular items, overlooking subtle shifts in user preferences. To address these issues, this paper introduces the MintSR session recommendation algorithm. MintSR utilizes a hierarchical decoupling model based on time dimensions, categorizing user intent into long-term, short-term, and instantaneous levels. The global context information is mapped to long-term intent, and in the long-term intent, we use the Transformer encoder to eliminate the problem of long-distance dependency and design a unique intent capture module that captures the intent through the category similarity, which can be used to capture the user’s intent through category similarity. The same capture module is also used to capture the user’s short-term and transient intent through category similarity. Through this hierarchical division, the algorithm can fully explore the user’s potential intent and deeply integrate the item category information for modeling. Based on the integration of the three levels of intent, the category comparison learning mechanism is introduced to improve the recommendation performance. Finally, the MintSR algorithm is tested on three real datasets, and the results show that its accuracy is better than other mainstream algorithms. Full article
(This article belongs to the Section Computing and Artificial Intelligence)
27 pages, 959 KB  
Article
Optimizing Intermittent Pumping Duration with a Physics–Data Dual-Driven CatBoost Model Enhanced by Bayesian and Attention Mechanisms
by Chengming Zhang, Fuping Feng, Cong Zhang, Shiyuan Li and Junzhuzi Xie
Processes 2025, 13(12), 4012; https://doi.org/10.3390/pr13124012 (registering DOI) - 11 Dec 2025
Abstract
Traditional oilfields face challenges such as high energy consumption, imprecise control, and lax management in mid-to-late development stages, leading to increased costs and reduced efficiency. To address these issues, this work aims to develop an intelligent optimization framework for intermittent pumping by explicitly [...] Read more.
Traditional oilfields face challenges such as high energy consumption, imprecise control, and lax management in mid-to-late development stages, leading to increased costs and reduced efficiency. To address these issues, this work aims to develop an intelligent optimization framework for intermittent pumping by explicitly integrating physical mechanisms with data-driven modeling. Specifically, we propose a data–physics dual-driven method that combines physics-based parameters derived from seepage mechanics with data-driven feature selection using Pearson correlation analysis to identify nine key production factors. An improved CatBoost regression framework is developed through systematic preprocessing, including data cleaning, cubic polynomial feature expansion, F-value screening, and Z-score normalization. The model is further enhanced using Bayesian hyperparameter optimization, a weight adaptation mechanism, and an attention-based multi-level architecture. The novelty of this work lies in the unified dual-driven optimization strategy and the enhanced CatBoost framework that jointly improve prediction accuracy and model generalization. Experimental results demonstrate that the proposed method can accurately predict pumping operation times. Compared with the original CatBoost model, the MAE of the large-interval model decreases by 56.94%, while that of the small-interval model decreases by 16.23%. In addition, the accuracy of the large-interval model increases by 4.1%, and that of the small-interval model increases by 1.22%. These improvements show that the enhanced CatBoost model significantly strengthens predictive performance. This approach provides a reliable basis for optimizing pumping schedules, reducing energy consumption, and promoting intelligent and refined oilfield management. Full article
(This article belongs to the Section Petroleum and Low-Carbon Energy Process Engineering)
22 pages, 1913 KB  
Article
Comprehensive Phytohormone Analysis Reveals the Roles of Auxin, Cytokinin, and Gibberellin in Enhancing Seed Germination and Growth of Chimonobambusa utilis
by Wanqi Zhao, Simei Ai, Haixiang Yuan, Mingzhen Lv and Shuyan Lin
Plants 2025, 14(24), 3780; https://doi.org/10.3390/plants14243780 (registering DOI) - 11 Dec 2025
Abstract
Bamboo seeds (often called bamboo rice) are nutritionally rich, offering protein, fiber, and essential minerals like potassium and manganese. Chimonobambusa utilis seeds, especially, represent an underexplored nutritional resource with exceptional edible and agricultural potential. Here, we report that Ch. utilis seeds contain remarkably [...] Read more.
Bamboo seeds (often called bamboo rice) are nutritionally rich, offering protein, fiber, and essential minerals like potassium and manganese. Chimonobambusa utilis seeds, especially, represent an underexplored nutritional resource with exceptional edible and agricultural potential. Here, we report that Ch. utilis seeds contain remarkably high levels of unsaturated fatty acids (67.39% of total lipids), with linoleic and linolenic acids comprising 36.5% and 26.7%, respectively, exceeding major vegetable oils by 1.5 to 3.3-fold. Comprehensive plant growth regulator (PGR) screening revealed distinct regulatory patterns: gibberellic acid (GA3, 8.66 µM) exhibits biphasic dose–response kinetics, cytokinins (6-BA, 222.0 µM) show nonlinear responses transitioning from low-concentration inhibition to high-concentration promotion with preferential lateral root induction, while auxins (NAA, 134.2 µM) demonstrate unimodal responses with concentration-dependent efficacy, achieving the strongest root-promoting effect (27% increase, p < 0.05). Mechanistically, optimal phytohormone treatments sustained elevated soluble sugar levels and differentially modulated key enzymes. Notably, 6-BA potently suppressed sucrose synthase activity while NAA maximally stimulated starch biosynthetic enzyme activities (AGPase and GBSS), identifying sucrose metabolism as a pivotal regulatory node. Comparative evaluation of germination capacity and seedling vigor revealed that individual treatments with 8.66 µM GA3, 222.0 µM 6-BA, or 134.2 µM NAA achieved the best performance among tested concentrations, reducing germination time by 5 days and increasing germination percentage by 4.2 to 6.3% relative to control. These findings establish Ch. utilis as a premium oil crop candidate and provide mechanistic insights into phytohormone-mediated germination control with broad implications for bamboo seed biology and propagation optimization. Full article
(This article belongs to the Special Issue The Genetic and Epigenetic Regulation of Bamboo Growth and Development)
15 pages, 2321 KB  
Article
Does Coxsackievirus B3 Require Autophagosome Formation for Replication? Evidence for an Autophagosome-Independent Mechanism: Insights into Its Limited Potential as a Therapeutic Target
by Yun Ji Ga and Jung-Yong Yeh
Pharmaceuticals 2025, 18(12), 1880; https://doi.org/10.3390/ph18121880 - 11 Dec 2025
Abstract
Background/Objectives: Coxsackievirus B3 (CVB3), a neurotropic enterovirus, is a major causative agent of viral encephalitis and myocarditis, yet no protective vaccine or effective antiviral therapy is currently available. Autophagy plays a dual role in viral infections, acting as both an antiviral defense and [...] Read more.
Background/Objectives: Coxsackievirus B3 (CVB3), a neurotropic enterovirus, is a major causative agent of viral encephalitis and myocarditis, yet no protective vaccine or effective antiviral therapy is currently available. Autophagy plays a dual role in viral infections, acting as both an antiviral defense and a process that can be exploited by certain viruses. Although CVB3 has been proposed to utilize autophagosomes as replication platforms, the underlying mechanisms remain controversial. Methods: In this study, we investigated the relationship between CVB3 replication and autophagosome formation under starvation-induced conditions and in ATG5 knockout cells. Results: While nutrient deprivation robustly induced autophagy, CVB3 infection did not trigger autophagosome formation. Moreover, viral replication proceeded efficiently in ATG5-deficient cells lacking autophagosomes. Pharmacological modulation of autophagy using rapamycin, a potent autophagy inducer, did not alter intracellular viral titers or protein expression, although extracellular viral release was modestly reduced. These results indicate that CVB3 replication occurs independently of autophagosome formation, suggesting that pharmacological targeting of autophagy provides limited therapeutic benefit. Conclusions: This study refines our understanding of autophagy as an antiviral target and highlights the need to identify alternative host-directed pathways for antiviral drug development. Full article
(This article belongs to the Special Issue The Development and Application of Broad-Spectrum Antiviral Drugs)
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18 pages, 3480 KB  
Article
Development of an Underwater Vehicle-Manipulator System Based on Delta Parallel Mechanism
by Zhihao Xu, Yang Zhang, Zongyu Chang, Boyuan Huang, Yuanqiang Bing, Chengyu Zeng, Pinghu Ni, Yachen Feng and Haibo Wang
J. Mar. Sci. Eng. 2025, 13(12), 2361; https://doi.org/10.3390/jmse13122361 (registering DOI) - 11 Dec 2025
Abstract
Underwater Vehicle-Manipulator Systems (UVMSs) play a critical role in various marine operations, where the choice of manipulator architecture significantly influences system performance. While serial robotic arms have been widely adopted in UVMS applications due to their operational flexibility, their inherent structural characteristics present [...] Read more.
Underwater Vehicle-Manipulator Systems (UVMSs) play a critical role in various marine operations, where the choice of manipulator architecture significantly influences system performance. While serial robotic arms have been widely adopted in UVMS applications due to their operational flexibility, their inherent structural characteristics present certain challenges in underwater environments. These challenges primarily stem from the cumulative effects of joint mechanisms and dynamic interactions with the fluid medium. In this context, we explore an innovative UVMS solution that incorporates the Delta parallel mechanism, which offers distinct advantages through its symmetrical architecture and unilateral motor configuration, particularly in maintaining operational stability. We develop a comprehensive framework that includes mechanical design optimization, implementation of distributed control systems, and formulation of closed-form kinematic models, with comparative analysis against conventional serial robotic arms. Experimental validation demonstrates the system’s effectiveness in underwater navigation, target acquisition, and object manipulation under operator-guided control. The results reveal substantial enhancements in motion consistency and gravitational stability compared to traditional serial-arm configurations, positioning the Delta-based UVMS as a viable solution for complex underwater manipulation tasks. Furthermore, this study provides a comparative analysis of the proposed Delta-based UVMS and conventional serial-arm systems, offering valuable design insights and performance benchmarks to inform future development and optimization of underwater manipulation technologies. Full article
(This article belongs to the Special Issue Design and Application of Underwater Robots for Navigation and Manipulation)
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28 pages, 1373 KB  
Article
Heritage Hospitality and Sustainable Tourism in Mountain Cultural Landscapes: The Case of Zagori Within the UNESCO Framework
by George Tsamos, Aimilia Vlami, Efthymia Sarantakou and Agni Christidou
Heritage 2025, 8(12), 523; https://doi.org/10.3390/heritage8120523 (registering DOI) - 11 Dec 2025
Abstract
Mountain cultural landscapes represent dynamic systems where heritage, policy, and tourism intersect to shape local resilience. This study explores how public incentives and adaptive reuse frameworks can transform traditional settlements into sustainable tourism destinations. Building on an established Conservation–Development model, an additional “Investigation” [...] Read more.
Mountain cultural landscapes represent dynamic systems where heritage, policy, and tourism intersect to shape local resilience. This study explores how public incentives and adaptive reuse frameworks can transform traditional settlements into sustainable tourism destinations. Building on an established Conservation–Development model, an additional “Investigation” axis is introduced to empirically link policy intent, investment implementation, and demographic outcomes. Combining archival research, quantitative indicators and spatial analysis, the study examines the impact of successive development laws (1982–2022) on the evolution of heritage hospitality, focusing on small-scale, high-altitude enterprises that integrate cultural preservation with local entrepreneurship. The UNESCO cultural landscape of Zagori, Greece, serves as the empirical context of this analysis. The results reveal that heritage hospitality, driven by policy incentives rather than spontaneous market growth, has formed a micro-network of small-scale hotels, reinforcing both preservation and local resilience. Municipal-level patterns indicate that population decline was mitigated where heritage hospitality coexisted with diversified tourism infrastructure. Conversely, overconcentration or policy gaps led to stagnation. These findings position Zagori as a model for policy-driven, heritage-based sustainability in mountain cultural landscapes, emphasizing the interplay between legislation, built heritage and population vitality. Full article
(This article belongs to the Special Issue Cultural Landscape and Sustainable Heritage Tourism)
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