Search Results (18,049)

The forest within the Ben En National Park has a diverse flora, which, although protected, remains subject to degradation. The analysis and management strategies for forest degradation within this park were conducted using a phytogeographical approach supplemented by satellite imagery and a SWOT analysis. As a result, the area is characterized by nine distinct vegetation types comprising 1417 vascular plant species (from 902 genera and 196 families). These species belong to endemics from Northern, Central, and all of Vietnam, as well as 16 other phytogeographical elements. Tropical Asian and South China elements dominate the community structure in evergreen broad-leaved closed forests on both limestone and non-limestone mountains. Forest degradation is evident in changes to both floristic composition and vegetation structure. Floristic composition shows a trend of decreasing native elements while simultaneously increasing non-native or introduced elements. This “anthropogenic tropicalization” leads to a declining chain of ecological function from palaeotropical to introduced elements, resulting in biological invasion. For instance, the invasive species, Mimosa pigra, currently occupies about 442 ha in the semi-submerged zone of the Song Muc reservoir, indicating a loss of ecological function and a likely hydrological pathway for further spread. As a consequence of “anthropogenic tropicalization”, the vegetation is fragmented and gradually altered from a natural system to an anthropogenic one through a regressive succession from primary forest to bare land/invaded area. Based on the SWOT analysis, four management actions were proposed: 1—Establish a “sustainable native forest” program and “invasive species control” in the Song Muc reservoir; 2—Launch a “green livelihoods for the buffer zone” initiative; 3—Implement a “Smart forest monitoring” system; and 4—Forge an “ecotourism-conservation-community” alliance. Full article

Edible insects are recognised as a sustainable, high-protein food source, yet consumption in Western diets remains limited due to cultural barriers and concerns about taste, appearance, and safety. This study explored the factors affecting the acceptance of familiar products where insects have been added as ingredients, and how purchase intent is influenced by label information. During sensory evaluation, 59 participants tested pasta-only and pasta-with-sauce samples that were presented with and without insects (controls). Results showed no significant differences in preference between insect and control samples (pasta only: p = 0.150; pasta with sauce: p = 0.193). Open-ended feedback highlighted flavour, texture, and familiarity as key drivers. Label design strongly shaped purchase intent, with participants preferring labels that combined clear allergen and ingredient information with credible nutrition and eco-certification logos. Benefit-focused price framing (protein and sustainability) significantly increased willingness to pay (p < 0.001), while prior insect consumption, age and gender had no effect. Overall, the findings show that adding insects into a well-known ready-meal format, supported by transparent labelling and benefit-based communication, has the potential to improve acceptance. This approach highlights a practical way to bring insect proteins into mainstream food systems while contributing to nutrition and sustainability goals. Full article

The Maceió Metropolitan Region (MMR) has undergone significant changes due to public policies that promote urban growth. This has intensified environmental impacts, adversely affecting local communities. The Remote Sensing Ecological Index (RSEI), a remote sensing-based metric, was used to evaluate ecosystem quality. The study assessed annual ecosystem quality in the MMR, Alagoas, using RSEI values from MODIS data spanning 2000 to March 2024/2025. To ensure data quality and reliable results, all MODIS data underwent rigorous quality control, including the exclusion of pixels affected by cloud cover, shadows, and missing values. Only data points meeting established MODIS quality assurance standards were used. Annual RSEI values varied considerably, from 0.449 in 2005 to 0.636 in 2014. Most areas in the MMR are classified as moderate quality (0.4 < RSEI < 0.6), particularly in central and eastern sectors. The lowest-quality regions (0 < RSEI < 0.4) are concentrated in the east—including Maceió, the hub city—and the west, largely due to high population density. The Sen-Slope Estimator and trend analysis revealed significant trends in the hub city, with positive trends in the northeast. Urban expansion has led to the loss of native vegetation, including sugarcane fields and remnants of the Atlantic Forest. The Pettitt test identified a structural change in 2018, likely linked to environmental violations related to the Braskem petrochemical industry and salt extraction in Maceió. Full article

Complex psychosis is a clinically relevant rehabilitation construct rather than a formal diagnostic category and refers to psychotic illness associated with treatment-resistant symptoms, functional impairment, and additional cognitive, psychiatric, neurodevelopmental, or physical health complexity. In this clinician-oriented narrative review, we synthesised current evidence on rehabilitation interventions for adults with complex psychosis, integrating direct evidence from specialist rehabilitation settings with indirect evidence from schizophrenia-spectrum studies when clinically informative. We searched major clinical databases, prioritised guidelines, systematic reviews, meta-analyses, and controlled studies, and organised the synthesis by functional domain and pathway relevance. Evidence was strongest for cognitive remediation, particularly when combined with broader psychiatric rehabilitation or vocational support, for family interventions in relapse prevention, and for individual placement and support in competitive employment. Social–cognitive and metacognitive interventions appear clinically valuable, although transfer to real-world functioning is more variable. Community-based rehabilitation, supported accommodation, illness self-management, and ecological adaptation strategies remain central to functional recovery when embedded within multidisciplinary pathways. Digital and virtual interventions are promising adjuncts, but their efficacy remains heterogeneous and implementation challenges include engagement, privacy, and service integration. Overall, rehabilitation in complex psychosis is most convincing when it is personalised, measurement-based, and delivered through integrated service models linking assessment, intervention selection, supported living, and recovery-oriented care. Full article

As a common brain-computer interface (BCI) paradigm, electroencephalogram (EEG)-based motor imagery provides a critical pathway for both assistive technology to (restoring communication and control) and active rehabilitation (promoting neural plasticity and functional recovery). Domain adaptation has been shown to effectively enhance the decoding performance of motor intentions for target subjects by leveraging labeled data from source subjects. However, EEG data from source subjects often contains extensive personal privacy, and the direct access to source EEG data easily leads to privacy leakage issues. An important research topic is to achieve domain adaptation without directly accessing the source subjects’ raw data. To address this challenge, a privacy-preserving source-free domain adaptation framework, termed Transformer-based SFDA with Class-balanced Multicentric Dynamic Pseudo-labeling (T-CMDP), is proposed for cross-subject motor-imagery EEG classification. This framework consists of three coupled stages. In the source model training stage, a Transformer-based encoder combined with Riemannian manifold-aware feature extraction is employed to learn transferable and discriminative EEG feature representations. In the source-free target adaptation stage, only the pretrained source model is transferred to the target domain and adapted through knowledge distillation and information maximization, without accessing raw source EEG data. In the self-supervised learning stage, class-balanced multicentric prototypes and high-confidence pseudo-label updates are introduced to progressively refine the target-domain decision boundaries. Extensive experiments on three motor-imagery EEG datasets demonstrate that the proposed T-CMDP framework consistently outperforms eleven representative baselines from traditional machine learning, deep learning, and source-free transfer approaches, achieving average accuracies of 56.85%, 76.34%, and 74.49%, respectively. These results indicate that T-CMDP effectively alleviates inter-subject EEG distribution discrepancies and ensures the privacy preserving of source subjects, thereby facilitating more reliable and practical deployment of EEG-based BCI systems. Full article

Introduction: Asthma is a chronic inflammatory disease that impairs daily functioning and quality of life. Despite effective therapies, asthma control remains suboptimal and may improve through greater engagement of community pharmacists. This study assessed the knowledge, practices, and perceived barriers of community pharmacists regarding asthma management in the Aseer region, Saudi Arabia. Methods: A cross-sectional study was conducted using a self-administered online questionnaire covering demographics, asthma-related knowledge, practice, and perceived barriers. Results: A total of 290 community pharmacists participated. Overall, 64.8% showed high asthma-related knowledge, while 51.7% reported high asthma counseling practice. Pharmacists showed strong knowledge of asthma symptoms, triggers, determinants of poor control, and counseling on medication-related adverse effects, but moderate knowledge of asthma control assessment, guideline-based management, and treatment-related side effects. Commonly reported services included patient education on asthma and medications, identification of modifiable risk factors, and discussion of treatment side effects, whereas written asthma action plans, symptom control assessment, and follow-up visits were less common. In multivariable logistic regression, high knowledge (p = 0.002), interest in asthma training (p < 0.001), and greater work experience (p = 0.01) were associated with higher counseling practice, while patient volume showed a borderline association (p = 0.051). Conversely, higher practice (p = 0.002), working in independent community pharmacies (p < 0.001), and pharmacy location (p = 0.034) were associated with higher asthma knowledge. Conclusions: Community pharmacists demonstrated moderate-to-high knowledge of asthma management, but gaps remain in guideline-based practice and follow-up. Strengthening guideline-oriented training and pharmacist integration into asthma care may improve outcomes. Full article

Deposit-feeding sea cucumbers ingest sediment-like particles, making substrate-associated exposure pathways ecologically relevant in coastal aquaculture. In this study, a sea mud feed matrix was used to evaluate short-term dietborne/substrate-linked glyphosate exposure in Apostichopus japonicus over 72 h, with the aim of characterizing early residue formation, short-term sublethal biomarker responses, and gut microbiota shifts under a benthic feeding scenario. Analytical verification confirmed a clear glyphosate gradient in the prepared feed matrices, with no glyphosate detected in the control matrix and measured concentrations of 8.66 ± 1.59 mg/kg, 1330 ± 390 mg/kg, and 6960 ± 1710 mg/kg in the low-, medium-, and high-dose groups, respectively. No mortality or obvious external lesions were observed during the exposure period. Tissue analysis confirmed measurable internal glyphosate residues and compartment-specific distribution, indicating successful internal exposure under the matrix-linked route. Most digestive and immune/antioxidant biomarkers remained relatively stable within the 72 h window; however, amylase showed a marked response in the low-dose group, and superoxide dismutase showed dose-associated changes in the medium- and high-dose groups, indicating selective sensitivity among enzyme endpoints. Gut microbiota analysis revealed a dominance-structured community with limited alpha-diversity variation among groups, whereas community composition showed subtle treatment-related shifts that were more evident at finer taxonomic resolution. Predicted functional profiles remained broadly similar across treatments. Overall, the 72 h exposure design was effective for identifying early internal exposure and short-term biological responses under a sea mud-associated feeding route, while host physiological responses remained largely buffered over this time scale and the gut microbiota provided a more sensitive interface-level signal of exposure-associated change. These findings support the value of a route-specific, gut-centered framework for evaluating early herbicide exposure responses in benthic mariculture species and suggest that matrix-associated feeding conditions may modify the apparent magnitude of short-term responses. Full article

Returning spent mushroom substrate (SMS) to the field is an effective way to dispose of it. However, given the substantial nutrient consumption associated with Volvariella volvacea SMS, their effects on soil properties and crop performance warrant further investigation. By analyzing the effects of three different application rates of SMS on soil nutrients and lettuce (Lactuca sativa L.) quality, the results showed that the group with 1.5 kg m⁻² SMS addition improved the total nitrogen (+21.2%), and organic content (+27.9%) in soil, and it demonstrated particularly outstanding performance in enhancing the survival rate (+21.9%), average weight (+71.7%), chlorophyll content (+45.6%), and total phenolic content (+25.2%) of lettuce. By comparing the soil microbial communities in the control group, the SMS (1.5 kg m⁻²) treatment group, and the organic fertilizer treatment group, it was found that they were mainly composed of Group S1, S2, and S3 microorganisms, respectively. The microbial community evenness in the treatment groups was greater than that in the control group. Furthermore, the results also revealed that the microbial conversion efficiency of nitrogen and phosphorus in the SMS treatment group was higher than the control group, which promoted nutrient cycling and improved the quality of lettuce. Our analysis provides an environmentally friendly way for Volvariella volvacea SMS disposal. Full article

Hypertension is a major health issue, both globally and in Japan. Potassium-rich foods help prevent hypertension by promoting sodium excretion. We evaluated whether Dadacha-mame (a local potassium-rich edamame variety) improves sodium excretion and influences dietary behavior. This 2-week stratified randomized exploratory trial included 54 (mean age: 20.5 ± 1.4 years; 53.7% females) adults assigned to an intervention group [15 g/day of dried Dadacha-mame; n = 27] or a control group [usual diet; n = 27]. Urinary sodium-to-potassium (Na/K) ratios were compared. Shifts in the dietary behavior-change stages (pre-contemplation and contemplation) were assessed at baseline and post-intervention. No significant between-group baseline differences were observed. While no overall effect on the Na/K ratio was observed, subgroup analysis showed a significant reduction in the Na/K ratio in the intervention group (4.39 vs. 5.91 in Control, p = 0.027). The intervention prompted positive dietary behavior changes, with the proportion of participants in the pre-contemplation stage decreasing from 50.0% at baseline to 33.3% post-intervention. Dietary intervention with Dadacha-mame can significantly improve sodium excretion in individuals at a higher risk of hypertension and encourage healthy dietary behaviors. Utilizing local potassium-rich foods may be a valuable public health strategy, creating added value for agricultural products and benefiting community health. Full article

Quorum Quenching (QQ) is a mechanism that disrupts Quorum Sensing (QS) signaling systems, which regulate gene expression based on bacterial population density. Many fish pathogens, such as Aeromonas, utilize QS systems to regulate the expression of their virulence factors. Disrupting these systems using QQ is a promising approach for infection control in aquaculture and may provide a safe alternative to antibiotics. Therefore, identifying microorganisms with QQ activity is a relevant task in agricultural microbiology and veterinary medicine. This study examines the identification of isolates with QQ activity in the microbial community of perch and assesses their probiotic potential for the prevention of aeromonosis. In this study, we isolated 32 strains of microorganisms capable of degrading N-acylhomoserine lactone (AHL), six of which exhibited stable QQ activity. Five strains were found to belong to the genus Rhodococcus, and one strain to the genus Exiguobacterium. The selected strains were tested for the enzymatic/non-enzymatic and intra-/extracellular QQ activity, pathogen growth inhibition, biofilm formation, and hemolytic activity, as well as growth ability under various environmental conditions (salinity, pH, bile acids, and temperature). Based on the results of these tests, the R. erythropolis PFS1.20 strain was selected as the most promising probiotic. The genomic analysis revealed that the studied strain contains genes encoding QQ enzymes, siderophore biosynthesis clusters, osmoprotectors, and compounds with antimicrobial properties. These results indicate the high probiotic potential of the R. erythropolis PFS1.20. Full article

This in vitro study evaluated the effect of irrigation on different polishing protocols and their influence on the surface roughness, microhardness, and mass of resin composites. Three resin composites (Admira^® Fusion, Filtek Supreme™ XTE, and Ceram.X Spectra™ STHV) were polished using four systems (Sof-Lex™, DIATECH^® ShapeGuard, Astropol^®, and Enhance™/PoGo™) under wet and dry conditions. Eight test groups were established for each resin composite (n = 10 per group). Vickers microhardness, surface roughness (R_a), and specimen mass were measured before and after polishing with one of the four systems, applied either with or without irrigation. For Admira^® Fusion polished with Sof-Lex^™, R_a values were lower without irrigation (p = 0.048), whereas Filtek Supreme^™ XTE and Ceram.X Spectra^™ STHV polished with the Enhance^™/PoGo^™ system showed lower R_a values when irrigation was used (p = 0.010 and p = 0.004, respectively). Sof-Lex^™ and DIATECH^® ShapeGuard produced the highest microhardness values for both Admira^® Fusion and Filtek Supreme^™ XTE. Moreover, specimens of Admira^® Fusion and Ceram.X Spectra^™ STHV polished with DIATECH^® ShapeGuard exhibited higher microhardness under irrigation (p = 0.048 and p = 0.027, respectively). Overall, polishing resulted in measurable material removal, reflected by a reduction in specimen mass, and in an increase in microhardness. Wet polishing generally increased microhardness, although the effect varied depending on the polishing system and resin composite. Clinicians should therefore consider both the resin composite and the polishing system when deciding whether to use irrigation, as appropriate irrigation control may help optimize the surface smoothness and microhardness of resin composite restorations. Conference Presentation: Preliminary data from this study were previously presented as an oral communication at the 32nd Portuguese Dental Association Annual Meeting. This manuscript represents a substantially expanded and revised version, developed as a full research article. Full article

Post-quantum cryptographic implementations in Internet-of-Things (IoT) devices are significantly threatened by physical side-channel attacks, where practical attack risks are increased by physical accessibility and resource limitations. In particular, recent work has shown that belief propagation-based attacks can recover secret keys from lattice-based digital signatures using only a single side-channel trace of the Number Theoretic Transform (NTT). This work introduces the Quantum-Randomized Number Theoretic Transform (QR-NTT), an implementation-level defense mechanism that integrates quantum-derived entropy directly into the execution flow of lattice-based signature algorithms. Rather than treating randomness as a static input, QR-NTT uses quantum entropy to introduce controlled variability in execution ordering, arithmetic factor usage, and memory access behavior while preserving mathematical correctness and constant-time execution. The proposed framework is designed for embedded platforms and remains compatible with existing post-quantum cryptographic standards and IoT communication protocols. A complete implementation on an ARM Cortex-M4 platform, coupled with commercial quantum random number generator (QRNG) hardware, demonstrates that QR-NTT significantly degrades the effectiveness of template matching and belief propagation attacks. Experimental evaluation shows a reduction in single-trace attack success rates from over 90% to below 3% and an increase of approximately two orders of magnitude in the number of traces required for successful key recovery. These security gains are achieved with moderate overheads of 18.3% in execution time and 1.8 KB of additional memory while remaining well within practical IoT constraints. The results indicate that quantum-derived entropy can be leveraged as a practical implementation-level defense against physical attacks, complementing algorithmic post-quantum security. QR-NTT demonstrates a viable path toward strengthening the real-world resilience of post-quantum IoT systems without sacrificing deployability. Full article

Macrobrachium nipponense is one of the major economic species in freshwater aquaculture in China. As an important component of aquaculture ecosystem, microorganisms participate in key processes such as material cycling and water quality regulation, exerting significant impacts on the cultured organisms. In this study, high-throughput sequencing of the 16S rRNA, 18S rRNA, and ITS regions was employed to comparatively analyze the characteristics of microbial communities before and during the cultivation period, combined with correlation analysis of environmental factors. The results showed that the dominant microbial groups in the prawn pond water were Proteobacteria, Cyanobacteria, Ascomycota, Basidiomycota, Chlorophyta, and Arthropoda. The microbial community structure differed significantly between the pond water during the culture period and the pre-culture external river baseline: manifested as an increase in the relative abundances of Cyanobacteria, Chytridiomycota, and zooplankton, and a decrease in the abundances of Ascomycota, Basidiomycota, and Chlorophyta. Analysis of LEfSe revealed that the low-nitrogen pond was enriched with taxa such as Muribaculaceae; the high-nitrogen pond was enriched with taxa such as Cyanobium_PCC-6307; and the control pond was enriched with taxa such as CL500-29_marine_group. Functional prediction indicated that heterotrophic metabolism-related functions dominated the microbial communities. The abundance of fungal pathogens was significantly higher in the low-nitrogen group, while potential pathogenic bacteria were enriched in the high-nitrogen group. Ammonia nitrogen is a core environmental factor associated with differences in microbial community structure. The findings of this study can provide theoretical references and data support for water quality optimization and the construction of healthy aquaculture models in freshwater shrimp and crab farming waters. Full article

Explainable Artificial Intelligence (XAI) has become a critical requirement in medical image analysis, where transparency and interpretability are essential for clinical trust and decision support. Melanoma is recognized as one of the most deadly types of skin cancer, with its occurrence exhibiting an increasing pattern in recent times. However, detecting this cancer in its initial stages greatly increases patients’ chances of long-term survival. Various computer-based techniques have recently been proposed to diagnose skin lesions at their early stages. Even though the machine learning community has achieved a certain degree of success, there is still an unresolved research challenge regarding high error margins and the limited interpretability of automated systems. This study focuses on addressing both segmentation and classification tasks, with particular emphasis on two key concepts: (1) improving image quality to maximize distinguishability between foreground and background regions, thereby enhancing visual interpretability and segmentation accuracy and (2) eliminating redundant and cluttered feature information to generate the most discriminative and compact feature representations. The input images are initially processed using a novel metaheuristic contrast-stretching method to estimate image-specific key parameters, thereby enhancing lesion boundary clarity in a clinically interpretable manner. Following this, the improved images are fed into selected pre-trained deep models, including DenseNet-201, Inception-ResNet v2, and NASNet-Mobile. The extracted features from all pre-trained models are fused to produce resultant vectors, which are then refined using a bio-inspired feature selection method, termed entropy-controlled whale optimization, to retain only the most informative attributes. The selected discriminative feature set is subsequently classified using multiple classifiers. The results indicate that the proposed framework achieves superior performance compared to existing methods in terms of accuracy, sensitivity, specificity, and F1-score. Additionally, it facilitates a more explainable, transparent, and structured diagnostic pipeline appropriate for medical applications. Full article

Despite the productivity and economic limitations imposed by environmental and climatic conditions, livestock systems play a fundamental role in preserving habitats and high-conservation-value species, while delivering a broad spectrum of ecosystem services to rural populations. Breeders need timely information to produce safe, inexpensive, environmentally, and welfare-friendly food products. Information on feeding and nutrition is of particular importance since it represents a significant percentage of animal breeding costs. Automating the collection, analysis, and use of production-related information on livestock feeding systems represents one of the central challenges facing the sector. Precision feeding systems (PFSs) have deeply changed farm management by providing new information on the health status of animals, their welfare, and nutritional requirements. PFSs encompass modern electronic and ICT-related (information and communication technologies) technologies that facilitate the electronic measurement of critical components, ensuring optimum efficiency of both resource use and animal productivity. This review analyzes the current state and potential applications of precision feeding systems for sustainable livestock production. The implementation and feasibility of PFSs have been investigated across the major animal production species and contexts. Based on the available literature, real-time monitoring and control systems can improve the production efficiency of livestock farms. However, further research is needed, as several components of PFSs are still at different stages of development and commercial readiness. Full article