Search Results (4,502)

A common challenge when modeling social–ecological systems (SESs) is defining the spatial extent of the system. Boundaries that do not adequately capture both social and ecological processes and their interactions can lead to mischaracterization of the system, while expanding boundaries too widely can impact model complexity and required resources. Socially, boundaries can invoke and influence identity, culture, power, and sense of place. Boundary decisions benefit from flexible, iterative approaches and the expertise of local communities. Here, we use a structured database search supplemented with citation searching to identify and review the literature that addresses choosing or defining spatial boundaries in SESs mapping or modeling and, when applicable, how participatory methods were used in the research process. In a review of the resulting 79 studies, we discovered that pre-existing social or ecological boundaries were used most frequently (36 and 18 publications, respectively). Twenty-one publications combined social and ecological boundaries or data to create custom boundaries, and four studies used an alternative approach to conventional boundaries. Informed by the literature review, we present a general framework for defining boundaries at the outset of SES research. We then connect the framework to a specific case study based on a collaborative project with Tribal, university, and federal scientists to develop a social–ecological climate adaptation plan. We present guiding questions alongside candidate boundaries for our study system and explore the tradeoffs of these boundary options, which can function as a useful template for other social–ecological research collaborations. Full article

Floodplains are key components of inland river systems of Australia with floodplain vegetation playing important roles in habitat provision, nutrient cycling, and supporting strong cultural values. These vegetation communities are highly dynamic, particularly in response to flooding. However, decades of water development and highly managed water resources are linked to wetland habitat decline in this region. We explored patterns of vegetation response to flooding over twenty years at the Narran Lakes Ramsar site, a terminal floodplain wetland system in the northern Murray–Darling Basin, Australia. We collated data from previous monitoring efforts and resampled permanent plots for understorey vegetation structure and composition. Three flood events were surveyed over a 20-year period, with each event surveyed on two occasions first, following initial drawdown (minimal standing water) and a second survey under dry or drier conditions (~6 months after the recession of floodwaters). Overall, we observed a high diversity of native plant species (~110 species) in understorey communities across the wetland and high compositional turnover both between flood events and within years (i.e., paired surveys). Notably, vegetation cover, but not species richness, was greatest in the 2023 survey following the largest of the three flood events investigated. Understorey composition was strongly driven by inundation regimes, particularly the duration of recent inundation, and the number of wet and dry years prior. Large flood events are critical for supporting vegetation resilience in these systems, increasingly so under a drier climate and with stretched water resources. Continued long-term monitoring of vegetation through flood cycles at the Narran Lakes will be critical to understanding ecological responses to longer-term changes in climate and hydrology to inform adaptive water management and maintain the values of this Ramsar site. Full article

Background: Soil-transmitted helminth (STH) infections are a recognized public health challenge, particularly in rural and island settings. Despite the implementation of national control programs, epidemiological data from geographically isolated communities remain limited. In this study, we aimed to determine the prevalence of STH infections and identify associated risk factors among adults in Koh Yao Islands, southern Thailand. Methods: A community-based cross-sectional survey was conducted in three subdistricts of Koh Yao, Phang Nga Province, from January to September 2024. Demographic data and information on potential risk factors were collected using structured questionnaires. Stool specimens were analyzed using the formalin–ethyl acetate concentration technique and the modified Kato–Katz method. Associations were assessed using univariate and multivariate logistic regression analyses. Results: A total of 241 adults participated in the study, with females accounting for 68.9% and males for 31.1%. The overall prevalence of STH infections was 2.49%, with hookworms and Trichuris trichiura identified as the predominant species. All infected individuals had an educational level lower than a bachelor’s degree. Univariate analysis showed that participants who did not use hygienic toilets at home had a significantly higher likelihood of developing STH than those who did (crude odds ratio = 46.80; 95% confidence interval [CI]: 2.55–859.00; p = 0.010). Multivariable logistic regression analysis confirmed that the absence of hygienic toilet use at home was independently associated with STH infection (adjusted odds ratio = 30.69; 95% CI: 1.17–804.65; p = 0.040). Conclusions: This study documents low overall prevalence of STH infections in the study area, with hookworms and T. trichiura as the predominant organisms. These findings support continued targeted public health measures, including periodic deworming and health education initiatives, to strengthen hygiene practices, particularly in high-risk populations. Future investigations should incorporate environmental assessments and longitudinal monitoring to evaluate the durability of current control strategies. Full article

With the in-depth advancement of the “Digital China” initiative, policies and research discourses related to the digital economy have continued evolved, making it necessary to systematically examine their stage-specific characteristics and underlying logic from a long-term perspective. Accordingly, this study adopts information society theory as the analytical framework and selects the annual series of reports on China’s digital economy development published by the China Academy of Information and Communications Technology (CAICT) from 2015 to 2024 as the research corpus. Using text mining techniques and Latent Dirichlet Allocation (LDA) topic modeling, this paper conducts a longitudinal examination of the stage-wise systemic evolution of key topics in China’s digital economy development. The findings indicate that over the past decade, the topic structure of China’s digital economy has followed a clear evolutionary trajectory, progressing from “informatization-driven development” to “platform expansion,” and subsequently to “data factors and institutional governance.” In the early stage, the focus was on information infrastructure development and industrial integration; the middle stage shifted toward the platform economy and enterprise growth; more recently, the emphasis has increasingly been placed on the construction of data factor markets and the improvement of governance frameworks. This process of topic evolution not only reflects changes in the practical forms of the digital economy but also reveals the ongoing adjustment of the state’s cognitive framework and governance logic regarding digital economy development. These findings provide empirical evidence for understanding the systemic evolution of China’s digital economy over time. By identifying the stage-specific pathways of China’s digital economy, this study extends the application of information society theory within this context and provides new empirical evidence for understanding the evolutionary logic underlying high-quality digital economy development. Full article

Climate change is increasingly recognized as a source of psychological distress, yet the prevalence, predictors, and behavioral implications of climate anxiety remain unevenly understood. This study examines climate anxiety, its key drivers, and associated behavioral responses in a multi-country sample of adults. A cross-sectional online survey was conducted across 21 countries using the Climate Change Anxiety Scale (CCAS), alongside measures of awareness, coping strategies, social support, and food-related behaviors, including food waste reduction, increased plant-based food consumption, and home or community gardening. Analyses included descriptive statistics, exploratory factor analysis (EFA), and multivariable regression. Given the uneven country-level representation, results are reported as pooled patterns with a few exploratory cross-country comparisons. Climate anxiety was widely reported, with over 60% of participants indicating that climate challenges were emotionally overwhelming. Regression analyses showed that climate awareness and frequency of climate-related thinking were positively associated with higher anxiety, although the effect sizes were small and explanatory power was limited (R² = 0.055). EFA identified two related dimensions: cognitive concern about future impacts and affective distress. Climate anxiety across countries showed modest variation (2.44–3.23) and no statistically significant differences, despite variation in awareness. A gap between concern and climate action was evident: only 39.1% reported environmentally motivated dietary changes. Cost, limited availability, and lack of information were the main barriers to climate action, and only 24.4% reported frequent social support. These findings indicate that climate anxiety is shaped by both psychological and structural factors, and that reducing it requires not only increasing awareness but also enabling conditions that support meaningful climate action. Full article

The assessment of managerial competencies in information technology (IT) organizations requires robust and validated instruments capable of predicting performance in volatile, uncertain, complex, and ambiguous environments. This study presents a preliminary validation of the MLPD (Machine Learning Predictive Development) model, which integrates 360° multidimensional evaluation, situational awareness, and exploratory analytics. Conceived as a pilot application and proof-of-concept, the research was conducted within the IT organization of a Chilean Defense Institution responsible for the management and administration of information and communication technologies. This study aims to determine how the three most commonly cited managerial competency domains (Transformational Leadership, Situational Awareness, and Collaborative Management) are weighted in additive models of 360° performance evaluation in a defense IT context, and also seeks to determine whether these weightings differ between civilian and military evaluators. Although the study focuses on a specialized case study with a limited sample of 9 IT leaders, the robustness of the preliminary findings is supported by the analysis of 165 rating records from 360° evaluations clustered within 9 leaders. Through this granular data set, multiple linear regression models were developed to examine the predictive relationships among three core competency domains—Transformational Leadership, Situational Awareness, and Collaborative Management—and their impact on overall managerial performance. The results identify Collaborative Management as the strongest predictor of performance, and highlight significant differences between civilian and military evaluators. This finding challenges conventional assumptions about leadership effectiveness in IT contexts and suggests that horizontal coordination capabilities are more critical than vertical authority. These preliminary results validate the model’s internal structure within a highly hierarchical environment, establishing a foundational benchmark for future large-scale applications of the MLPD model in diverse organizational contexts. Full article

Soil contamination by complex pesticide mixtures poses a systemic threat to ecosystem health, yet the mechanisms of microbial community assembly under the coexistence of legacy and modern pollutants remain insufficiently understood. This study evaluated the influence of legacy organochlorine pesticides (OCPs) versus current-use agrochemicals on the structure and inferred functional potential of soil bacterial communities in the Almaty Region, Kazakhstan, using high-throughput 16S rRNA gene sequencing and GC–MS/MS analysis of 217 compounds. Results revealed a clear contrast between contamination regimes: modern organophosphate insecticides and herbicides, such as simazine (up to 32.3 mg kg⁻¹ at the Amangeldy site), were associated with lower alpha diversity (Shannon ≈ 3.03) and enrichment of copiotrophic taxa such as Pseudomonas and Sphingobium. In contrast, persistent OCP residues, such as p,p′-DDE (up to 1.43 mg kg⁻¹ at the Kyzylkairat site), were associated with higher diversity (Shannon ≈ 5.46) and enrichment of more stress-tolerant oligotrophic lineages, including Acidobacteria and Vicinamibacteraceae. Procrustes analysis supported significant concordance between pesticide profiles and taxonomic structure (M² = 0.286, p < 0.001), indicating that pesticide residue composition was strongly associated with bacterial community structure across the studied soils. The observed shift in community balance, particularly the relative increase in Pseudomonas versus Acidobacteria, is proposed as a candidate compositional indicator of ecosystem instability in semi-arid agricultural soils and may inform future remediation-oriented studies. Full article

Wild edible fruits play an important role in supporting food security, nutrition, and traditional knowledge systems in rural communities, yet their diversity and uses remain insufficiently documented in many parts of Thailand. This study aimed to investigate the diversity, utilization, and ethnobotanical significance of wild edible fruit species in Kut Chum District, Yasothon Province. Ethnobotanical data were collected through semi-structured interviews and field surveys with local informants, and quantitative indices, including the Cultural Importance Index (CI), Fidelity Level (%FL), and Informant Consensus Factor (ICF), were applied to evaluate species significance and medicinal agreement. A total of 71 species belonging to 33 families were recorded, with most species consumed as fresh fruits and a subset used for medicinal purposes. Several species, such as Irvingia malayana Oliv. ex A.W.Benn., Phyllanthus emblica L., and Syzygium cumini (L.) Skeels exhibited high cultural importance, reflecting their key roles in local diets. High ICF values across therapeutic categories indicated strong consensus in ethnomedicinal knowledge. Additionally, 44 species not used medicinally in the study area were reported as medicinal in other regions, highlighting spatial variation in knowledge systems. These findings emphasize the importance of wild edible fruits as multifunctional resources contributing to food and nutritional security. Integrating culturally important species into conservation and sustainable use strategies may support biodiversity preservation and the continuity of traditional ecological knowledge. Full article

Background/Objectives: Effective information seeking is essential for new graduate nurses’ adaptation to the workplace. The objective of this study was to identify how nurse managers and senior nurses support new graduate nurses’ information seeking and the expectations underlying such support. Methods: Nurse managers and senior nurses from Japanese hospitals participated in semi-structured interviews. Data were analyzed using qualitative content analysis by coding meaningful units, grouping similar codes into subcategories, and organizing them into broader categories. Ethical approval was obtained from the research ethics committee of the first author’s institution, and written informed consent was obtained from all participants. Results: Participants included twelve nurse managers from five hospitals and fourteen senior nurses from three hospitals. The nurse managers had an average of 7.4 years of supervisory experience, and the senior nurses had an average of 14.2 years of clinical experience. Participants expected new graduate nurses to demonstrate appropriate attitudes toward seeking information, engage in proactive communication to express their needs or uncertainties, take initiative in seeking and obtaining information, and build relationships with senior nurses that would facilitate information seeking. To support these expectations, participants adopted approaches that encouraged information seeking, proactively provided necessary information, and promoted information sharing among peers. Nurse managers also sought to create a work environment in which all staff members collectively nurtured new graduate nurses. Conclusions: To facilitate information seeking among new graduate nurses, nurse managers and senior nurses need to foster a supportive work environment. They also need to recognize the information content, sources, tactics, and timing appropriate for new graduate nurses. Full article

The rapid integration of electric vehicles (EVs) and decentralized renewable energy sources is transforming urban power systems, while simultaneously increasing the complexity of real-time coordination across charging infrastructure, distributed energy resources, and grid-support devices. This systematic review synthesizes recent research on multi-agent reinforcement learning (MARL) for EV–grid coordination, with emphasis on four emerging dimensions: forecasting-informed control, safety-constrained learning, explainability and interpretability, and trustworthy decentralized coordination. A systematic literature search was conducted in IEEE Xplore, Scopus, Web of Science, ScienceDirect, MDPI, and arXiv, covering primarily the period 2016–2025, with selected early-2026 studies retained where relevant, with selected earlier foundational studies retained for context. The review was conducted and reported in accordance with the PRISMA 2020 framework. A total of 412 records were identified through database searching; after duplicate removal and screening, 58 studies were included in the final qualitative synthesis. The reviewed literature shows that MARL is increasingly being applied to EV charging coordination, demand-side management, community energy systems, transactive energy, and ancillary grid services. The evidence further indicates that forecasting integration improves anticipatory control, safety-aware formulations enhance operational reliability, and explainability-oriented designs help address transparency and trust barriers in safety-critical grid environments. However, the literature remains limited by heterogeneous benchmarks, inconsistent evaluation metrics, and a lack of real-world deployment evidence. This review provides a structured synthesis of current methodologies, identifies critical research gaps, and outlines future directions for the development of safe, interpretable, and deployment-ready MARL frameworks for urban energy systems. Full article

This study proposes an innovative instructional approach to promote scientific literacy by integrating the Nature of Science and the Nature of Scientific Inquiry with experimental practice and the history of physics. The aim is to foster a deep understanding of how scientific knowledge is constructed and to promote informed trust in science. Using an explicit and reflective methodology, the intervention combines experimental activities with historical reflection. The core of the learning sequence is the experimental reconstruction of Galileo’s studies on falling bodies, based on the historical manuscript folio 116v, an original document that provides the empirical evidence for the law of falling bodies, illustrating the transition from raw experimental data to mathematical formalization. Through this activity, students engage with key epistemic aspects of scientific practice, including the management of uncertainty—distinguished into statistical/aleatory and structural/epistemic forms—the probabilistic nature of scientific knowledge, the predictive power of models and theories, and the underdetermination of scientific theories. Additional themes addressed include the role of thought experiments, the importance of communicating results for scrutiny and validation, the function of models as mediators between theory and phenomena, and the process of de-idealization. The study also challenges the persistent myth of a single, linear “scientific method,” highlighting instead the theory-laden character of scientific inquiry and the central role of the scientific community. This dimension is explored through the historical comparison between Galileo and Mersenne, which illustrates elements of the scientific ethos and the role of peer review as a mechanism for the correction and refinement of knowledge. The results obtained with pre-service teachers, with whom this instructional sequence was implemented, indicate that this contextualized approach facilitates the overcoming of a view of science as a set of absolute truths. Instead, it promotes a more mature understanding of science as a dynamic, provisional, and self-correcting human enterprise, while equipping future citizens with the critical tools necessary to navigate the challenges of the twenty-first century. Full article

Background/Objectives: Diet is implicated in the high burden of mental health on society, and research examining associations between these two fields is growing. However, qualitative explorations are lacking, especially within culturally diverse settings. This study aims to explore the beliefs on the mechanisms of the relationship between diet, food systems, and mental health, and the lived experience of such, through a case study of one Caribbean Small Island Developing State, to inform culturally grounded public health strategies that integrate nutritional and psychological well-being. Methods: Fifteen interviews with food system stakeholders and five focus groups with the general public were conducted. Transcripts were analyzed using a grounded theory approach with a critical realist epistemological stance. Results: Four major categories centered on beliefs of mechanistic effects of diet on mental health, as well as broader perspectives of the relationship between food systems, food experiences, and mental health. Participants believed that (1) unhealthy diets of processed and chemically treated foods contribute to poor mental health and that (2) food insecurity is a key threat to mental health, but they also believed that (3) consumption of locally produced foods and (4) residing in agricultural communities can be beneficial to mental health. Conclusions: Participants recognize that diet influences mental health through physiological, social, and structural pathways, but this connection is threatened by rising dependence on imported, processed foods. Along with complementary quantitative research, the findings highlight the potential of expanding nutritional health literacy and clinical guidance and strengthening local food systems and traditional diets for mental well-being among Caribbean Small Island Developing States. Full article

Odontogenic sinusitis (ODS) is a common cause of unilateral maxillary sinusitis arising from periapical lesions (PALs) or other dental sources. The infection is typically polymicrobial and dominated by anaerobic bacteria, which are often under detected by routine culture. Molecular approaches such as quantitative polymerase chain reaction (QPCR) and next-generation sequencing (NGS) may provide improved characterization of the microbial burden and community structure. This study aimed to compare culture-based methods, targeted quantitative PCR, and 16S rRNA sequencing in paired samples to characterize microbial composition of ODS and evaluate diagnostic performance. Paired sinus mucosal biopsy (SIN) and periapical lesion (PAL) samples were collected from 28 patients with clinically confirmed ODS. Bacterial detection was performed using conventional culture and targeted QPCR assays for ten clinically relevant taxa. In three randomly selected patients, paired samples were additionally analyzed by 16S rRNA gene amplicon sequencing. Microbial load, taxa richness, and similarity between the two anatomically connected sites were assessed using Wilcoxon signed-rank, McNemar, Jaccard distance, and Bray–Curtis dissimilarity analyses. Results: Culture showed low sensitivity, identifying a limited number of pathogens, primarily Staphylococcus aureus, Streptococcus anginosus, and Fusobacterium nucleatum, in a minority of samples. In contrast, QPCR demonstrated substantially higher detection rates, particularly in PAL samples. Porphyromonas gingivalis (96.8%), Fusobacterium spp. (100.0%), and the S. anginosus group (90.3%) were highly prevalent in PAL specimens, with overlapping but lower detection in SIN samples. PAL samples exhibited significantly higher bacterial loads and taxa richness than paired SIN samples (Wilcoxon p = 0.0004). 16S rRNA sequencing confirmed polymicrobial communities at both sites and identified additional taxa not included in the QPCR panel. Similarity analyses revealed pronounced interindividual variability, ranging from near-identical to highly divergent paired microbiota. Periapical lesions act as reservoirs of predominantly anaerobic bacteria that may seed the maxillary sinus in ODS. Although microbial overlap exists, sinus communities display lower burden and site-specific compositional shifts. Culture-based diagnostics underestimate ODS microbial complexity, whereas combined molecular approaches provide a more comprehensive and clinically informative assessment. Full article

In single-carrier underwater acoustic (UWA) communication systems, sparse multipath channels and long delay spreads pose significant challenges to adaptive equalization, often leading to limited steady-state accuracy and degraded detection performance. To address this issue, this paper proposes a data reuse-based ${\ell }_1$-regularized proportionate recursive least-squares algorithm (DR-${\ell }_1$-PRLS) for sparse adaptive equalization. The proposed method incorporates a data reuse (DR) mechanism into the ${\ell }_1$-PRLS framework, enabling multiple equivalent uses of each received–reference sample pair without increasing pilot overhead. Meanwhile, by combining the proportionate update strategy with the ${\ell }_1$ sparsity constraint, the structural information of sparse channels can be more fully exploited, thereby improving parameter estimation accuracy. Numerical simulations are conducted to evaluate the proposed method in terms of convergence behavior, tracking capability, computational complexity, and bit error rate (BER), and comparisons are made with LMS, RLS, PRLS, ${\ell }_1$-PRLS, and DR-PRLS algorithms. Simulation results show that, under sparse underwater acoustic channel conditions, DR-${\ell }_1$-PRLS achieves lower steady-state error and better BER performance while maintaining good tracking capability, thereby demonstrating its effectiveness and robustness for sparse adaptive equalization in single-carrier underwater acoustic communications. Full article

Multi-UAV cooperative search is important for applications such as target reconnaissance, environmental monitoring, and emergency response. In practice, communication is often spatially heterogeneous due to terrain occlusion and environmental interference, which may delay information sharing and weaken coordination efficiency when UAVs traverse communication-blocked areas. To address this issue, we propose an Age of Information (AoI)- and Dempster–Shafer (DS)-enhanced cooperative search framework for multi-UAV systems under spatially structured communication constraints. Specifically, a DS belief map is introduced to fuse uncertain observations, while AoI is used to characterize the freshness of delayed information. An AoI-aware update mechanism further integrates buffered observations into the global belief map after communication recovery. The search process is then formulated as a communication-aware multi-agent sequential decision-making problem and solved using reinforcement learning. To demonstrate the generality of the proposed framework, we instantiate it with Proximal Policy Optimization (PPO), Multi-Agent Proximal Policy Optimization (MAPPO), and Q-value Mixing Network (QMIX). Experimental results show that the proposed framework consistently outperforms the baseline methods under heterogeneous environments and different communication conditions. Among all variants, AoI-DS-MAPPO achieves the best overall performance, improving average reward, success rate, and the number of detected targets by 26.13%, 24.32%, and 3.65%, respectively, while reducing episode length by 31.96% relative to the strongest baseline. Full article