Search Results (3,441)

The Sanjiang Plain hosts the largest freshwater wetland in Northeastern China and plays a critical role in regional climate stability. However, climate change and human activities have degraded the wetland, forming a successional gradient from the original flooded wetland to dry shrub and forest vegetation with a lower ground water level. This degradation has altered soil microbial structure and functions, reducing ecological and socio-economic benefits. Along this successional gradient, we used Biolog-ECO plates combined with soil enzyme assays (catalase, urease, sucrase, and acid phosphatase) to assess the dynamics of microbial carbon metabolic activity, measured by average well color development (AWCD). The results showed a systematic decline in AWCD values with advancing succession, revealing a pronounced reduction in overall microbial metabolic activity during wetland degradation. This trend correlated with loss of soil moisture, organic carbon, and nitrogen nutrients. Microbial communities in early successional wetland stages (i.e., original natural wetland and wetland edge) preferred labile carbon sources (e.g., carbohydrates, amino acids), while forested stages favored relatively more structural (e.g., polymers, phenolic compounds). These findings indicate that vegetation succession regulates microbial carbon metabolism by modifying soil physicochemical properties, providing insights for wetland restoration. Full article

The incorporation of Artificial Intelligence (AI) into medical services in Saudi Arabia offers a substantial opportunity. Despite the increasing integration of AI techniques such as machine learning, natural language processing, and predictive analytics, there persists an issue in the thorough comprehension of their applications, advantages, and issues within the Saudi healthcare framework. This study aims to perform a thorough systematic literature review (SLR) to assess the current status of AI in Saudi healthcare, determine its alignment with Vision 2030, and suggest practical recommendations for future research and policy. In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, 699 studies were initially obtained from electronic databases, with 24 studies selected after the application of established inclusion and exclusion criteria. The results indicated that AI has been effectively utilised in disease prediction, diagnosis, therapy optimisation, patient monitoring, and resource allocation, resulting in notable advancements in diagnostic accuracy, operational efficiency, and patient outcomes. Nonetheless, limitations to adoption, such as ethical issues, legislative complexities, data protection issues, and shortages in worker skills, were also recognised. This review emphasises the necessity for strong ethical frameworks, regulatory control, and capacity-building efforts to guarantee the responsible and fair implementation of AI in healthcare. Recommendations encompass the creation of national AI ethics and governance frameworks, investment in AI education and training initiatives, and the formulation of modular AI solutions to guarantee scalability and cost-effectiveness. This breakthrough enables Saudi Arabia to realise its Vision 2030 objectives, establishing the Kingdom as a global leader in AI-driven healthcare innovation. Full article

This study investigates flooding and erosion impacts and human responses in Aoraki Mount Cook and Westland Tai Poutini national parks in Aotearoa New Zealand. These fast-eroding landscapes provide important test cases and insights for considering the public access dimensions of climate change. Our objectives were to explore and characterise the often-overlooked role of public access as a ubiquitous concern for protected areas and other area-based conservation approaches that facilitate connections between people and nature alongside their protective functions. We employed a mixed-methods approach including volunteered geographic information (VGI) from a park user survey (n = 273) and detailed case studies of change on two iconic mountaineering routes based on geospatial analyses of digital elevation models spanning 1986–2022. VGI data identified 36 adversely affected locations while 21% of respondents also identified beneficial aspects of recent landscape changes. Geophysical changes could be perceived differently by different stakeholders, illustrating the potential for competing demands on management responses. Impacts of rainfall-triggered erosion events were explored in case studies of damaged access infrastructure (e.g., roads, tracks, bridges). Adaptive responses resulted from formal or informal (park user-led) actions including re-routing, rebuilding, or abandonment of pre-existing infrastructure. Three widely transferable dimensions of public access management are identified: providing access that supports the core functions of protected areas; evaluating the impacts of both physical changes and human responses to them; and managing tensions between stakeholder preferences. Improved attention to the role of access is essential for effective climate change adaptation in parks and reserves. Full article

Endometrial lesions are common in gynecology, exhibiting considerable clinical heterogeneity across different subtypes. Although ultrasound imaging is the preferred diagnostic modality due to its noninvasive, accessible, and cost-effective nature, its diagnostic performance remains highly operator-dependent, leading to subjectivity and inconsistent results. To address these limitations, this study proposes a hierarchical feature selection and optimization framework for endometrial lesions, aiming to enhance the objectivity and robustness of ultrasound-based diagnosis. Firstly, Kernel Principal Component Analysis (KPCA) is employed for nonlinear dimensionality reduction, retaining the top 1000 principal components. Secondly, an ensemble of three filter-based methods—information gain, chi-square test, and symmetrical uncertainty—is integrated to rank and fuse features, followed by thresholding with Maximum Scatter Difference Linear Discriminant Analysis (MSDLDA) for preliminary feature selection. Finally, the Whale Migration Algorithm (WMA) is applied to population-based feature optimization and classifier training under the constraints of a Support Vector Machine (SVM) and a macro-averaged F1 score. Experimental results demonstrate that the proposed closed-loop pipeline of “kernel reduction—filter fusion—threshold pruning—intelligent optimization—robust classification” effectively balances nonlinear structure preservation, feature redundancy control, and model generalization, providing an interpretable, reproducible, and efficient solution for intelligent diagnosis in small- to medium-scale medical imaging datasets. Full article

The purpose of this research was to investigate whether music empirically associated with therapeutic effects contains intrinsic informational structures that differentiate it from other sound sequences. Drawing on ontology, phenomenology, nonlinear dynamics, and complex systems theory, we hypothesize that therapeutic relevance may be linked to persistent structural patterns embedded in musical signals rather than to stylistic or genre-related attributes. This paper introduces the Discriminating Music Sequences (DiMuSes) method, an unsupervised, structure-oriented analytical framework designed to detect such patterns. The method applies 24 scalar evaluators derived from statistics, fractal geometry, nonlinear physics, and complex systems, transforming sound sequences into multidimensional vectors that characterize their global temporal organization. Principal Component Analysis (PCA) reduces this feature space to three dominant components (PC1–PC3), enabling visualization and comparison in a reduced informational space. Unsupervised k-Means clustering is subsequently applied in the PCA space to identify groups of structurally similar sound sequences, with cluster quality evaluated using Silhouette and Davies–Bouldin indices. Beyond clustering, DiMuSe implements ranking procedures based on relative positions in the PCA space, including distance to cluster centroids, inter-item proximity, and stability across clustering configurations, allowing melodies to be ordered according to their structural proximity to the therapeutic cluster. The method was first validated using synthetically generated nonlinear signals with known properties, confirming its capacity to discriminate structured time series. It was then applied to a dataset of 39 music and sound sequences spanning therapeutic, classical, folk, religious, vocal, natural, and noise categories. The results show that therapeutic music consistently forms a compact and well-separated cluster and ranks highly in structural proximity measures, suggesting shared informational characteristics. Notably, pink noise and ocean sounds also cluster near therapeutic music, aligning with independent evidence of their regulatory and relaxation effects. DiMuSe-derived rankings were consistent with two independent studies that identified the same musical pieces as highly therapeutic.The present research remains at a theoretical stage. Our method has not yet been tested in clinical or experimental therapeutic settings and does not account for individual preference, cultural background, or personal music history, all of which strongly influence therapeutic outcomes. Consequently, DiMuSe does not claim to predict individual efficacy but rather to identify structural potential at the signal level. Future work will focus on clinical validation, integration of biometric feedback, and the development of personalized extensions that combine intrinsic informational structure with listener-specific response data. Full article

Background/Objectives: The latest National Comprehensive Cancer Network (NCCN) Central Nervous System (CNS) Guidelines recommend utilizing next-generation sequencing (NGS) to enable comprehensive genomic profiling (CGP) as the preferred approach for molecular characterization of central nervous system (CNS) malignancies. CNS malignancies present distinct challenges due to the infeasibility of tissue-based testing for many patients and the restrictive nature of the blood–brain barrier (BBB) making plasma-based liquid biopsy an ineffective alternative. Recent advances in liquid biopsy have extended molecular testing beyond plasma to include cerebrospinal fluid (CSF), which serves as a valuable source for tumor-derived nucleic acids. Methods: The Belay Summit™ 2.0 is a high-throughput CGP assay capable of detecting multiple variant types, including single nucleotide variants (SNVs) and small insertion and deletions (Indels), copy number variations (CNVs), gene fusions, splice variants, and immunotherapy biomarkers such as microsatellite instability (MSI) and tumor mutational burden (TMB). This study details the analytical and clinical validation of Summit™ 2.0 to assess its technical performance and clinical sensitivity. Analytical validation was conducted using 68 specimens, demonstrating robust and reproducible detection of all variant types with 15 ng of CSF-derived total nucleic acid (tNA). Results: The analytical sensitivity of the Belay Summit™ 2.0 assay for SNVs and Indels was determined to be 96.7% with a 100% limit of detection (LoD) at a variant allele frequency of 0.3%. Clinical validity was evaluated across a cohort of 118 CSF specimens, including both primary and metastatic CNS tumors, demonstrating 96% sensitivity and 98% specificity. Conclusions: These findings support the use of the Belay Summit™ 2.0 assay for accurate and reproducible genomic profiling of CNS tumors using tumor-derived nucleic acids from CSF in patients for whom tissue-based testing is considered infeasible, unsafe, or not deemed by the prescribing physician to be clinically appropriate. Full article

Anthropogenic stressors increasingly threaten freshwater biodiversity, with fish communities particularly sensitive to habitat modification. This study evaluates how river morphological alterations influence fish assemblage structure in 114 mountain rivers of the Southern Carpathians, assessing whether such changes cause species loss or drive shifts toward disturbance-tolerant communities. Using a multi-scale analytical framework integrating non-metric multidimensional scaling, redundancy analysis, and variance partitioning, we quantified the contributions of spatial, catchment, and local habitat variables to community patterns. Spatial- and catchment-scale factors explained the largest variance in fish assemblages (12% in adults and 17% in small-bodied fish). However, morphological pressures proved significant in shaping community structure with clear ecological consequences. Weirs and embankments reduced abundances of rheophilic species (flow-dependent) by 27–38%, potamodromous by 23–42%, invertivorous by 26–49%, benthic by 40–46% and lithophilic taxa by 27–41%, indicating the loss of habitat specialists. In contrast, limnophilic taxa (preferring slow or still water) increased 25 times, phytophilic spawners by 17–41%, and tolerant species by 10%, reflecting biotic homogenization. By integrating a trait-based approach, this study highlights functional shifts that may be overlooked in species-level assessments. It underscores the need to couple local habitat restoration with catchment-scale management to conserve fish biodiversity and maintain natural ecological gradients in mountain river systems. Full article

Advancing the Sustainable Development Goals (SDGs)—framed around social, environmental, and governance dimensions—offers societies across the world the possibility of achieving long-term prosperity and ensuring that future generations enjoy a high quality of life. Governments pursue the 17 SDGs in accordance with their own socioeconomic and cultural contexts, institutional capacities, and available resources. Because countries differ substantially in structure and capability, their progress toward these goals varies, making the systematic measurement and analysis of SDG performance essential for appropriate timing and efficient resource allocation. This study proposes a hybrid assessment system to evaluate the sustainable development performance of upper-middle-income developing countries under both fuzzy and non-fuzzy environments. This integrated evaluation system consists of four main stages. In the first stage, evaluation criteria and alternative countries are specified, relevant data are obtained, and an initial decision matrix is developed. In the second stage, an efficiency analysis is conducted to identify countries that are efficient and those that are not. In the third stage, evaluation criteria are weighted using AHP and Fuzzy AHP methods. In the final stage, the TOPSIS and Fuzzy TOPSIS methods are used to rank efficient countries depending on sustainable development performance criteria. As a result, six countries were identified as inefficient countries based on sustainable development: China, Kazakhstan, Mongolia, Paraguay, Namibia and Turkmenistan. The AHP and Fuzzy AHP methods produced similar criterion weight values compared to each other. The criteria were prioritized from most important to least one as follows: Life expectancy, expected years of schooling, mean years of schooling, gross national income per capita, CO₂ emissions per capita, and material footprint per capita. While some countries achieved similar rankings using the TOPSIS and Fuzzy TOPSIS methods, most countries achieved different rankings because of the multidimensional nature of sustainable development. When the rankings obtained from the fuzzy and non-fuzzy approaches were compared, a noticeable level of overlap was observed, with a Spearman’s rank correlation coefficient of 68.73%. However, the fuzzy TOPSIS method is considered more reliable for assessing sustainable development performance due to its ability to handle data uncertainty, imprecision, and the multidimensional nature of SDG indicators. The results of this study demonstrate that analyses related to sustainable development, which may not contain precise and clear values and have a complex structure encompassing many areas such as social, environmental, and governance, should preferably be conducted within a fuzzy logic framework to ensure more robust and credible evaluations. Full article

This paper examines an optimal investment–consumption problem in a setting where the financial environment is influenced by both stochastic factors and delayed effects. The investor, endowed with Constant Relative Risk Aversion (CRRA) preferences, allocates wealth between a risk-free asset and a single risky asset. The short rate follows a Vas$\check{\mathrm{i}}$ček-type term structure model, while the risky asset price dynamics are driven by a delayed Heston specification whose variance process evolves according to a Cox–Ingersoll–Ross (CIR) diffusion. Delayed dependence in the wealth dynamics is incorporated through two auxiliary variables that summarize past wealth trajectories, enabling us to recast the naturally infinite-dimensional delay problem into a finite-dimensional Markovian framework. Using Bellman’s dynamic programming principle, we derive the associated Hamilton–Jacobi–Bellman (HJB) partial differential equation and demonstrate that it generalizes the classical Merton formulation to simultaneously accommodate delay, stochastic interest rates, stochastic volatility, and consumption. Under CRRA utility, we obtain closed-form expressions for the value function and the optimal feedback controls. Numerical illustrations highlight how delay and market parameters impact optimal portfolio allocation and consumption policies. Full article

Background and Objectives: Vaginal natural orifice transluminal endoscopic surgery, vNOTES, has become an increasingly preferred minimally invasive option for benign hysterectomy. General anesthesia is still the routine choice, yet regional methods such as combined spinal epidural anesthesia may support a smoother postoperative course. Although the use of vNOTES is expanding, comparative information on anesthetic approaches remains limited, and its unique physiologic setting requires dedicated evaluation. To compare combined spinal epidural anesthesia with general anesthesia for benign vNOTES hysterectomy, focusing on postoperative nausea and vomiting, recovery quality, and intraoperative physiologic safety. Materials and Methods: This retrospective cohort study was conducted in a single center and identified women who underwent benign vNOTES hysterectomy between March 2024 and August 2025 from electronic medical records. Participants received either combined spinal epidural anesthesia or general anesthesia according to routine clinical practice. All patients were managed within an enhanced recovery pathway that incorporated standardized analgesia and prophylaxis for postoperative nausea and vomiting. The primary outcome was the incidence of postoperative nausea and vomiting during the first day after surgery. Secondary outcomes included time to discharge from the recovery unit, pain scores at set postoperative intervals, early functional recovery, patient satisfaction and physiologic parameters extracted from intraoperative monitoring records. Analyses were performed according to the anesthesia group documented in the medical files. Results: One hundred forty patients met inclusion criteria and were included in the analysis. Combined spinal epidural anesthesia was linked to a lower incidence of postoperative nausea and vomiting, a shorter stay in the post-anesthesia care unit, and reduced pain scores in the first 24 h (adjusted odds ratio 0.32, ninety five percent confidence interval 0.15 to 0.68). Early ambulation and oral intake were reached sooner in the combined spinal epidural group, with higher overall satisfaction also noted. Adherence to ERAS elements was similar between groups, with no meaningful differences in early feeding, mobilization, analgesia protocols or PONV prophylaxis. During the procedure, combined spinal epidural anesthesia produced more episodes of hypotension and bradycardia, while general anesthesia was linked to higher airway pressures and lower oxygen saturation. Complication rates within the first month were low in both groups. Conclusions: In this observational cohort study, combined spinal epidural anesthesia was associated with lower postoperative nausea, earlier recovery milestones and greater patient comfort compared with general anesthesia. Hemodynamic instability occurred more often with neuraxial anesthesia but was transient and manageable. While these findings point to potential recovery benefits for some patients, the observational nature of the study and the modest scale of the differences necessitate a cautious interpretation. They should be considered exploratory rather than definitive. The choice of anesthesia should therefore be individualized, weighing potential recovery benefits against the risk of transient hemodynamic effects. Larger and more diverse studies are needed to better define patient selection and clarify the overall risk benefit balance. These findings should be interpreted cautiously and viewed as hypothesis-generating rather than definitive evidence supporting one anesthetic strategy over another. Full article

Climate change and sea-level change (SLC) are intensifying flooding in U.S. coastal communities, with disproportionate impacts on Black and minority neighborhoods that face displacement, economic hardship, and heightened health risks. In Norfolk, Virginia, sea levels are projected to rise by at least 0.91 m (3 ft) by 2100, placing underserved neighborhoods such as Oakleaf Forest at particular risk. This study investigates the compounded impacts of flooding at both the building and urban scales, situating the work within the framework of the UN Sustainable Development Goals (UN SDGs). A mixed-method, community-based approach was employed, integrating literature review, field observations, and community engagement to identify flooding hotspots, document lived experiences, and determine preferences for adaptation strategies. Community participants contributed actively through mapping sessions and meetings, providing feedback on adaptation strategies to ensure that the process was collaborative, place-based, and context-specific. Preliminary findings highlight recurring flood-related vulnerabilities and the need for interventions that address both environmental and social dimensions of resilience. The study proposes multi-scale, nature-based solutions (NbS) to mitigate flooding, restore ecological functions, and enhance community capacity for adaptation. Ultimately, this work underscores the importance of coupling technical strategies with participatory processes to strengthen resilience and advance climate justice in vulnerable coastal neighborhoods. Full article

Consumer choice, liking, and preference can be assessed in different ways. We tested the application of a novel method called Hedonext^® for the measurement of consumer liking and preference for extra virgin olive oil (EVOO). Consumers were instructed that they would be presented with up to eight olive oils and invited to taste each of them in sequence until they found the oil that they liked or preferred, thus ending the test, and that they would receive that oil as their reward. We compared the outcomes of the Hedonext Method to hedonic ratings on the nine-point hedonic scale of all eight oils, which were then analyzed by preference mapping. A total of 139 and 141 consumers, who consumed EVOO at least once a week and were evenly distributed by age (18–65 years old) and gender (60% women, 40% men), evaluated the set of olive oils from Italy, Spain, or California with Hedonext or the nine-point hedonic scale, respectively. The oils that were chosen most often by consumers in the Hedonext procedure were also the oils that received the highest mean hedonic ratings on the nine-point hedonic scale, and those picked the least often with Hedonext also received the lowest hedonic ratings. Traditional preference mapping from hedonic ratings and an alternative preference mapping approach through Hedonext also produced similar outcomes. The Hedonext Method was shorter to administer and was enjoyed by the consumers who experienced it because of its game-like nature. It does require, though, that the product under testing be perceived as valuable by consumers, as it serves as the reward for their participation. We conclude that the Hedonext Method represents a novel and valuable alternative to the 9-point hedonic scale, particularly for the evaluation of premium or luxury consumer products. Full article

Florivory is the consumption or damage of flowers by herbivorous animals. It can directly affect plant fitness by damaging reproductive organs or indirectly by negatively influencing flower attractiveness to pollinators. We investigated florivory in field bindweed Convolvulus arvensis L. (Convolvulaceae) by combining data from natural surveys, experimental damage, and laboratory experiments on flower preferences of florivores. Surveys showed that flowers suffer damage from predators, including Leptophyes albovittata Kollar (Orthoptera: Tettigoniidae), which causes partial corolla damage, and from unknown predators that cause holes in the corolla. Experimentally damaged flowers had significantly lower reproductive success (number of seeds and proportion of total reproductive failure) than intact flowers. However, laboratory experiments with naïve bumblebees Bombus terrestris L. (Hymenoptera: Apidae) failed to detect a preference for undamaged flowers. This may be because B. terrestris is not a frequent pollinator of C. arvensis at our field sites, and naïve foragers, lacking prior experience, had not learned to associate corolla damage with reduced floral rewards. Our research shows that florivory negatively impacts C. arvensis reproductive success by altering pollinator behavior through reduced flower attractiveness. Full article

Background/Objectives: Gambling disorder (GD) is characterized by a high prevalence of co-occurring psychiatric disorders, including personality disorders (PDs), which may negatively influence clinical presentation, treatment outcomes, and relapse rates. The aim of this systematic review was to synthesize recent evidence regarding the association between GD and formally diagnosed PD and/or diagnostically anchored PD symptomatology, and to describe the main personality dimension most frequently reported in affected individuals. Methods: A systematic search was conducted in the PubMed and Dialnet databases for articles published between 30 November 2015 and 30 November 2025, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guidelines. PubMed was selected as the primary database because it is the most comprehensive source for peer-reviewed biomedical and psychiatric research, while Dialnet was included to complement PubMed by ensuring coverage of peer-reviewed psychiatric and psychological research published in other Romance-language journals, which are often underrepresented in international databases. The methodological quality and risk of bias of the included studies were evaluated using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for cross-sectional studies and the Newcastle–Ottawa Scale (NOS) for observational studies. Data extraction and synthesis were performed manually by two independent reviewers. Eight studies, predominantly cross-sectional in nature, assessing exclusively formally diagnosed personality disorders in adult individuals (≥18 years) diagnosed with GD were included. Results: Eight studies met the inclusion criteria, including a total of 4607 patients with GD. Across studies, personality pathology was highly prevalent among individuals with GD, with antisocial and borderline personality disorders most consistently reported. Elevated levels of impulsivity, emotional dysregulation, and narcissistic traits were frequently observed and were additionally associated with greater gambling severity, earlier onset, and poorer clinical outcomes. Antisocial personality symptoms were strongly linked to high-risk gambling subtypes, while obsessive–compulsive personality traits showed a more heterogeneous relationship with gambling severity. Conclusions: These results underscore the importance of personality assessment in individuals with GD and highlight the need for longitudinal studies using standardized diagnostic frameworks to inform tailored prevention and treatment strategies. Full article

The demand for clean-label functional foods has increased interest in natural polysaccharides with health benefits. Acemannan, an O-acetylated glucomannan from Aloe vera, possesses antioxidant, immunomodulatory, and prebiotic activities, but its performance in fat-based systems is not well understood. This study examined the incorporation of acemannan into dark chocolate at 1% and 5% (w/w) and its effects on physicochemical, rheological, antioxidant, and sensory properties. Particle size distribution remained within acceptable limits, though the 5% sample showed a larger mean size and broader span. Rheological tests confirmed shear-thinning behavior, with the higher concentration increasing viscosity at low shear and reducing it at high shear. Antioxidant activity measured by the DPPH assay showed modest improvement in enriched samples. Consumer tests with 30 panelists indicated a strong preference (89%) for the 1% formulation, which maintained a smooth mouthfeel and balanced sensory characteristics, while the 5% sample displayed more fruity and earthy notes with lower acceptance. GC–MS analysis revealed altered volatile profiles, and FTIR spectroscopy confirmed acemannan stability in the chocolate matrix. These findings demonstrate that acemannan can be incorporated into dark chocolate up to 1% as a multifunctional, structurally stable polysaccharide ingredient without compromising product quality. Full article