Atmospheric and Oceanic Sciences

Small-scale fisheries in the Western Indian Ocean are vital to food security, livelihoods, and coastal economies, supporting over 65 million people. Yet, SSFs face mounting threats from various factors, including overexploitation, climate change, and weakly integrated governance systems. Despite growing evidence of climate impacts, critical gaps remain in understanding how these changes affect fisheries and in translating this knowledge into effective policy and practice. This policy brief highlights the urgent need to strengthen the science–policy–practice nexus, enhance cross-sector coordination, and embed climate resilience into fisheries governance to secure sustainable and equitable fisheries management outcomes for the region.

Coral sands are critical in the construction of islands and harbors in tropical regions. Studying their dispersal, specifically the movement of ‘sedimentary clouds’ during marine dumping/dredging operations, is essential for optimizing construction efficiency and mitigating impacts on marine ecosystems. This study investigates the evolutionary characteristics of coral sand particles in still water via controlled indoor experiments. By manipulating parameters such as particle size, mass, nozzle diameter, and air release height, this study evaluated the impact of aspect ratio, Stokes number, and initial particle momentum on the movement of coral sand clouds. The results indicate that variations in air release height modulated the cloud’s width and corresponding diffusion angle, but exerted a negligible impact on the cloud front’s velocity and position. Empirical formulas for traditional quartz sand have limitations in reflecting the complex hydrodynamic settling behavior of coral sand. To address this, this paper establishes a modified empirical equation. This equation effectively predicts the width of coral sand plumes across different air release heights and Stokes number ranges. Furthermore, rather than directly quantifying microscopic morphological features, this study interprets these macroscopic transport characteristics from a process-based hydrodynamic perspective. Ultimately, the resulting predictive data and empirical framework provide a practical reference for evaluating sediment dispersion in reef engineering projects.

Human-wildlife conflict is increasing globally, and within national parks, human interactions with wildlife represent a growing barrier to conservation. Encounters with wildlife during recreational activities in national parks can provoke aggressive behaviour, resulting in interactions that inhibit conservation goals by fostering negative public perceptions and imposing energetic costs for the wildlife involved. However, whether specific recreational activities, species, and a combination of both recreational activities and species are associated with higher frequencies of aggressive encounters remains understudied. This study investigated how recreational activities influence the frequency of aggressive human-wildlife interactions of five large mammal species in Canadian national parks. A generalised linear mixed model with negative binomial distribution and log link function was used to analyse the effect of recreational activity type, species, and species-recreational activity interaction on the frequency of aggressive encounters. We found that recreational activity type and species significantly alter the frequency of aggressive encounters. Low impact activities, such as hiking and running, were associated with significantly more aggressive encounters regardless of species involved, despite their presumed minimal ecological footprint. Of the five species, elk exhibited the highest frequency of aggressive encounters regardless of recreational activity. Species-recreational activity interaction effects showed aggressive encounters vary significantly depending on specific combinations. Notably, aggressive grizzly bear encounters were more frequent during low impact activities while aggressive mule deer and coyote encounters were less frequent during almost all recreational activities. These findings show that large mammals exhibit species-specific risk perception, with subsequent aggressive behaviour varying by recreational activity type. Our results suggest that national parks should target high-risk recreational activity-species interactions to effectively mitigate aggressive encounters, thereby promoting wildlife health and visitor safety, and supporting biodiversity conservation.

Abstract Background: Long-term residence in mining regions exposes populations to environmental contaminants such as heavy metals and natural geochemical factors, both of which may trigger genotoxic stress and disturb cellular homeostasis. The molecular mechanisms underlying these effects in human populations remain incompletely understood. This study aimed to investigate genotoxic and oxidative stress responses and their links to gene expression changes and plasma metal concentrations.Methods: Forty-three residents from mining regions (MRR) and 39 from non-mining areas were examined. Genotoxicity was evaluated using micronucleus assays in lymphocytes and buccal cells. Mitochondrial DNA copy number (mtDNAcn) was quantified by qPCR, oxidative stress was analyzed in erythrocytes and DNA (8-OHdG). Transcriptomic data were integrated with plasma metal levels to identify associations.Results: MRR exhibited higher micronuclei frequency in lymphocytes and reduced mtDNAcn. Micronuclei frequency correlated with plasma manganese and altered CDK10 and JUN expression. mtDNAcn was negatively associated with Mn, positively with Ni, and linked to HSPA1A, IL1A, and TNF expression. Gene-level analyses revealed downregulation of DNA repair genes and upregulation of stress-responsive genes, some of which were associated with both genotoxicity biomarkers and specific metals.Conclusions:Mining-region residency is associated with genomic instability and mitochondrial compromise through dysregulated DNA repair and stress-response genes.

Microalgal-bacterial systems provide a promising strategy to enhance the nitrate removal performance of denitrifiers via the traditionally assumed provision of electron donors or enrichment of functional microorganisms, while the single-species regulatory mechanism remains unclear. Chlorella vulgaris ( C. vulgaris ) could markedly improve the nitrate removal by Paracoccus denitrificans ( P. denitrificans ) even under nutrient-replete conditions, contributing to a 2.48-fold increase in the nitrate removal rate constant compared to the sum of monocultures, indicating non-nutritional regulatory effects. Transcriptomics showed glycolytic genes in P. denitrificans were upregulated by 1.65 to 10.1-fold, accompanied by a 51.0% increase in NADH production. Lactate, as a key intermediate, activated the bacterial electron transport chain (ETC), with ETC-related gene expression upregulated by 2.83 to 2.95-fold. Furthermore, bacterial ammonium induced microalgal glutamate synthesis and release, which likely acted as a signaling molecule to upregulate bacterial nitrate reductase expression. These interactions redirected electrons toward nitrate reduction, increasing carbon utilization efficiency for nitrate removal by 82.75%. Microalgae coordinately optimized bacterial carbon and nitrogen metabolism, reprogramming electron generation, transfer, and allocation to achieve efficient nitrate conversion. This work provides molecular-level mechanistic insights and supports the design of controllable strategies for environmental remediation.

For most animals, foraging is a crucial activity but one that requires considerable time and energy. As such, we expect animals have evolved behaviours to make fast yet effective foraging decisions to maximise benefits while reducing costs (Pyke 1984;Stephens and Krebs 1986). If such decisions depended exclusively on the absolute value of foods -including the costs (e.g. energetic) and risks (e.g. predation) of acquiring them, alongside the costs (e.g. toxins) and benefits (nutrition) of the food -animals would always choose the food with the highest net value. Inferior or inaccessible options, called decoys, would have no impact on choices among higher value options (Luce 1959;Luce 1977;McNamara et al. 2006). Yet they do. This phenomenon is termed the decoy effect (Huber et al. 1982;Wedell and Pettibone 1996) and has been extensively demonstrated with humans and captive animals in highly controlled, simplified lab-based contexts (Hemingway et al. 2017;Padamwar and Dawra 2024). But does the decoy effect translate from simple choice tasks to decision-making by wild animals? How much do we really know about decoys in the natural world?Here, we explore the ecological significance of the decoy effect in the real world by drawing on available theory and evidence applying it to foraging ecology, using mammalian herbivores as a representative example of these ideas. We begin with an overview of the decoy effect, drawing on lab-based evidence across species. We then move from the lab to the field and address three key questions; do decoys naturally occur in the environment? Do decoys affect foraging decisions in the wild? And, if so, what is the likely adaptive function of the decoy effect? We argue that decoy effects are likely ecologically rational, specifically for foragers. We conclude that it is time to acknowledge and incorporate decoys into foraging ecology, and finish by suggesting key avenues for future decoy research.The Decoy Effect Decisions are never made in a vacuum. Instead, they are influenced by the context of the choice environment, such as the quality and quantity of options and the time available to choose among them. The decoy effect is a key example of context-dependent choice. A seminal marketing study by Huber et al. (1982) provided the first evidence that decoys can change people's choices. In this case, a "dominated decoy" (option of lower value) increased choice for a higher value "target" product over a similarly higher value "competitor" product. Since then, many studies have shown dominated decoys can alter people's choice, across domains of consumer, political, legal, and medical decisions (Padamwar and Dawra 2024). Dominated decoys are not the only type of decoy affecting choice. "Phantom decoys" -superior but inaccessible options -can also cause decoy effects (Pratkanis and Farquhar 1992). A typical example is when an advertised but sold out product (phantom decoy) alters choice between advertised available products (Doyle et al. 1999;Ge et al. 2009;Park and Jang 2018). The outcome of phantom decoy effects is often described in terms of similarity-substitution versus the reactance effect. Similarity-substitution predicts an individual who cannot choose their preferred option (phantom decoy) will 'substitute' it for the most similar option (Tversky 1972;Pettibone and Wedell 2000). In contrast, the reactance effect predicts the individual will become frustrated and choose the most different option (Pettibone and Wedell 2007). Such context-dependent choices violate one principle of economic rational choice theory (Luce 1959) -choice is independent of irrelevant alternatives. Yet this principle underpins much fundamental economic and consumer research.Decoys do not just affect people, but have been found to affect choice in non-human taxa, across domains from food choice, to mate choice, and nest selection (summarised in Hemingway et al. (2017)). Dominated and phantom decoys, for example, can alter instant and short-term food choice (< 30 seconds) in birds (Bateson et al. 2003), bees (Shafir et al. 2002;Tan et al. 2015), and mammals (Scarpi 2011;Jackson and Roberts 2021;Marini et al. 2023;Marini et al. 2024). Dominated decoys can also affect choice across full feeding bouts (e.g. in rufous hummingbirds (Selasphorus rufus) (Bateson et al. 2002;Morgan et al. 2014), bumblebees (Bombus impatiens) (Hemingway et al. 2024), and slime moulds (Physarum polycephalum) (Latty and Beekman 2011)).With the exception of hummingbirds, most evidence for decoy effects on non-human taxa comes from animals in captivity completing highly stylised choice tasks in artificial settings. Such environments bear little resemblance to the real-world. Until we study decoy effects in the wild, their function and ecological relevance remain unclear. Yet, if decoy effects occur in the wild, they matter. Just as decoy effects violate a key principle of economic rationality, they also violate assumptions of traditional foraging models, such as optimal foraging theory (Pyke 1984), marginal value theorem (Charnov 1976), and Bayesian updating (McNamara et al. 2006).In contrast to artificial lab settings, choice in nature is rarely simple. Whether choosing food, mates, or nest sites, animals must make fitness-optimising decisions amongst many multidimensional options in complex environments (Fawcett et al. 2014). Irrespective of how complicated their choices are in this landscape, inferior options (dominated) or inaccessible but superior options (phantom) have the potential to act as decoys.For foraging mammalian herbivores, such as deer, a low quality plant (e.g. highly toxic shrub) in a food patch could act as a dominated decoy when a deer is choosing between a high quality shrub and equally high quality grass (Fig. 1A). Similarly, highly nutritious leaves that a deer can detect (smell/see) but are out of reach in a tall tree (Fig. 1B) or a fenced tree seedling (Fig 1 .C) could act as a phantom decoy for a deer choosing between accessible plants in the understorey. Even a favourite seedling being eaten by a neighbouring conspecific could act as a phantom decoy. We suggest, therefore, that natural decoys do exist in a variety of forms in the real-world; we just need to recognise them. But do wild animals respond to such decoys when foraging?Few studies have investigated decoy effects on foraging behaviour in wild animals, but the evidence indicates their responses to decoys are generally consistent with those in captivity. In free-ranging gray jays (Perisoreus canadensis) and hummingbirds foraging decisions between different types of artificial nectar shifted in the presence of a dominated decoy (Shafir et al. 2002;Bateson et al. 2003;Morgan et al. 2014). Free-ranging swamp wallabies (Wallabia bicolor) also exhibited decoy effects when offered complex artificial foods. A phantom decoy influenced wallabies both at an early stage of the decision-making process -information-gathering (Orlando et al. 2023) and at the later stage of food choice (Jarvis et al. 2026). Collectively, this evidence supports the idea that decoys are relevant in foraging decisions of wild animals. But are their effects ecologically rational? 4 Decoy Effect -Artefact or Adaptation?In the real-world where information is limitless, organisms need to make countless, often timesensitive decisions. In turn, decoy effects could be ecologically rational if decoys increase choice efficiency (Hutchinson and Gigerenzer 2005 We believe there are several reasons that together suggest decoy effects are ecologically, and hence evolutionarily, rational. First, decoys do occur in nature (as above). This means animals can encounter and respond to them in every-day decision making allowing the decoy effect to be frequently reinforced. Further, if the decoy effect is beneficial, there should be strong selective pressure for organisms to exploit it.Second, decoys influence choice across a range of taxa suggesting an evolutionary underpinning for decoy effects (Parrish et al. 2015;Marini et al. 2023;Parrish et al. 2024). In itself, cross-species evidence is not sufficient to argue the decoy effect is ecologically rational. It may still be a lab artefact -tricking multiple species. Nevertheless, the case becomes more compelling the more we accumulate cross-species evidence of decoy effects in realistic settings.Third, decoys could be adaptive because they can enable, and be used in, heuristic decision-making. Heuristics, i.e., "rules-of-thumb", are cognitive strategies that harness subsets of information or stimuli in a given environment, allowing individuals to more easily evaluate options without overloading their cognitive resources (Gigerenzer and Goldstein 1996;Hutchinson and Gigerenzer 2005). Heuristic strategies result in fast, frugal, yet "good-enough" decisions (Gigerenzer and Gaissmaier 2011). Decoy effects may therefore be particularly advantageous, hence ecologically rational, in spatiotemporally variable environments where animals have imperfect knowledge about options in the landscape -such as in foraging. In these environments, fast, frugal, yet "goodenough" may make for efficient, sufficient, foraging choices. Given our limited understanding of the mechanistic value of decoys, exploring their relationships with heuristics may clarify the selected function and benefit of the decoy effect.Decoys in Foraging -Ecologically Significant?Foraging decisions have direct impacts on an individual's nutritional and energetic state. The act of foraging takes time, involves risks (e.g. risk of predation) and imposes missed opportunity costs for other behaviours (e.g. vigilance, mating, or caregiving) (Brown and Kotler 2004). As such, foraging efficiency -gain versus time spent -is critical to an individual's survival and fitness. Harnessing decoys to make the right choice most of the time may be adaptive, especially when time matters and when the absolute quality of food options cannot be known for certain.When foraging, herbivores are faced with unlimited sources of potentially relevant information. Filtering all this information to consider and evaluate food options can create cognitive overload (Tanner and Hemingway 2025) -reaching or exceeding mental processing limits (Chernev et al. 2015). This can lead to poor judgement, e.g. eating a toxic plant, and increase decision latency imposing energy and opportunity costs. However, if a forager uses a decoy as a point-of-reference, it can employ a cognitive shortcut (heuristic-based decision) and evade cognitive overload.Consider a deer foraging at a patch comprising high-quality grasses and shrubs, and a low-quality toxic shrub. The deer could either investigate and compare (by smelling, looking and/or nibbling) all options or could harness the toxic shrub as a dominated decoy to make a quick, heuristic-based decision. The outcome of this decision will depend on the heuristic employed. The deer could eat the most similar option -the non-toxic shrub (similarity-substitution) or eat the most different optionthe grass (reactance effect). In both cases, the outcome is not a function of the plant's absolute-value, but rather, of the decoy effect.In such foraging situations, the chosen food may not always be the most "optimal" but is likely sufficient and nutritionally adequate. Moreover, this choice may be ecologically advantageous for several reasons. First, the nutritional value may be uncertain (until consumption), second, a quick, cognitively manageable decision simultaneously reduces the animal's predation risk and energy costs while increasing available time and mental resources to engage in other essential behaviours.Classic foraging theories -all of which assume animals make decisions based on the absolute-value of foods -have been quite successful in explaining and predicting foraging behaviour and food choices. But if decoys affect foraging decisions of wild animals in the real-world, and affect them often enough, then these theories and their derived predictive models could be improved by including decoy effects. Little empirical research has investigated decoys in the natural world, so the scope and influence of decoy effects is not yet clear. We need more field evidence, across species, investigating how animals navigate decision-making in

Introduction Maintenance inefficiency in groundwater systems is often treated as a reliability problem, while post-failure restoration performance remains less systematically measured. Methods This study introduces a context-conditioned frontier framework for evaluating individual restoration events using stratified Slack-Based Measure (SBM) benchmarking with undesirable outputs, namely Failure Downtime (FD) and Failure Cost (FC). Clustered bootstrap bias correction is applied, and post-frontier operational modeling is used to examine whether bias-adjusted inefficiency is associated with maintenance-regime structure and asset replacement status. Results The results show that inefficiency is structurally concentrated rather than randomly distributed. Mechanical events record lower mean bias-corrected efficiency than electrical events, 0.783 versus 0.923. At the component level, system-level faults form the dominant restoration-burden reservoir, accounting for 2,400 avoidable hours and 1,074,963 SAR in avoidable FC. Maintenance intervention category does not significantly explain efficiency variation after technical severity is controlled. As a secondary post-frontier finding, the active-asset subset suggests that shifting from monthly scheduling to a structured three-month preventive regime is associated with lower predicted inefficiency, with an average marginal effect of −0.225 ( p = 0.046), while asset replacement status shows no significant association. Discussion Overall, the evidence supports a focused prioritization strategy targeting escalation-prone mechanical and system-level faults, with maintenance-regime information retained only as a supporting operational planning signal.

PURPOSE: We aimed to develop a machine learning model to predict activities of daily living (ADL) at discharge in stroke patients and identify key predictors to guide rehabilitation decisions. MATERIALS AND METHODS: Data of 589 stroke inpatients (2019-2024) were split into good (BI ≥ 60) and poor (BI < 60) ADL groups. Continuous variables were processed using Z-score normalization, followed by preliminary univariate regression screening (P < 0.05) and final feature selection via LASSO regression (lambda.1se = 0.0488). The screened features were used to train and validate ten machine learning algorithms; 30% of the dataset (n = 177) was allocated as an independent test set for model evaluation, and SHAP analysis was performed to interpret the optimal model. RESULTS: Six of 41 features were retained. Random forest achieved the best performance (AUC = 0.958; accuracy = 0.936; sensitivity = 0.934; specificity = 0.950). SHAP identified the top drivers: admission Barthel Index, standing balance, Brunnstrom stages (upper and lower limb), dressing, and grooming abilities. CONCLUSION: The ADL risk prediction model constructed using machine learning, particularly the random forest model, shows excellent predictive performance and clinical interpretability, making it valuable for individualized risk assessment of daily living skills in stroke patients at discharge.

Gas separation is central to industrial processes that drive climate mitigation, clean energy, and sustainable technologies. Metal–organic frameworks (MOFs) offer remarkable tunability for adsorption-based separations, yet identifying optimal materials remains challenging due to their vast structural diversity, costly simulations, and the difficulty of achieving a full range of desired properties. Existing machine learning approaches have accelerated screening but often lack generalizability across diverse gas pairs and operating conditions. Herein, we present BiMix-Bench, a curated database comprising ∼125,900 MOFs and five binary gas mixtures. Leveraging this dataset, LightGBM regressor (LGBMR) models are developed to achieve high predictive accuracy for gas uptakes ( R 2 = 0.93 and 0.92) and selectivity ( R 2 = 0.95) under strict robustness controls, including seed randomness and cross validation. Using CO 2 /H 2 as a case study, we evaluate both zero-shot and few-shot transfer performance. While zero-shot predictions provide limited out-of-distribution accuracy, the pretrained LGBMR models can be efficiently adapted with a small number of new simulations ( N = 204) through transfer learning. This data-efficient adaptation enables the rapid identification of top-performing MOFs, which are subsequently validated through grand canonical Monte Carlo simulations. This generalizable and interpretable framework enables scalable, data-driven discovery of advanced adsorbents for complex and evolving separation tasks.

Species reintroductions, an increasingly used measure in conservation, may be imposed, hindered, or conditioned by law. The European bison ( Bison bonasus ), once extinct in the wild, now lives in several free-ranging populations all stemming from reintroductions. Reintroduction of European bison to Sweden has been proposed and advocated. Zooarchaeological findings indicate that wild European bison existed in Sweden 11,200-9,500 years before present. Here we address and apply the relevant legal prerequisites for a reintroduction of European bison to Sweden. Applying international, European Union, and national Swedish law, we first show that there is no strict obligation for Sweden to reintroduce European bison. The responsible authority has considerable discretion in whether to allow a reintroduction of European bison. Rules on species protection, site protection, animal health, and animal welfare set conditions for how a reintroduction process should be implemented. Unclear legal rules on compensation and civil liability for damages caused by European bison create uncertainties about financial risks. Finally, the European bison is a protected species under the EU Habitats Directive, which further limits management options after reintroduction. Our assessment shows how law influences the feasibility of a reintroduction of a protected animal species to an EU Member State.

The Middle Route of the South-to-North Water Diversion Project is a core national strategic water transfer infrastructure of China; intact natural woodland at intake sites is essential to purify inflow water, conserve water resources and sustain long-term ecological security of the whole water diversion system, which necessitates systematic woodland biodiversity investigation. The SNWDP is a major national strategic water project in China, and its intake area plays a key role in water security and ecological protection. To clarify plant diversity and community characteristics in the intake area of the SNWDP Canal in Nanyang City, 12 standard sample plots were set up in Xixia, Neixiang, and Xichuan counties. We systematically investigated the tree, shrub, and herb layers using stratified sampling. A total of 122 higher plant species belonging to 55 families, 108 genera were recorded. Quercus variabilis was the absolute dominant species in both the tree layer and shrub layer, while Carex breviculmis dominated the herb layer. Two national Class II protected plant species ( Emmenopterys henryi and Cymbidium goeringii ) and two invasive alien species ( Erigeron sumatrensis and Bidens pilosa ) were found. Species diversity followed the order: shrub layer &amp;gt; herb layer &amp;gt; tree layer. The tree layer was dominated by young and middle-aged individuals, indicating that the community is in the mid-successional stage. This study provides basic data and a scientific reference for water-source forest conservation, biodiversity protection, and ecological restoration in the SNWDP intake area.

Community participation in conservation education is critical to the success and long-term sustainability of conservation initiatives. However, the global research landscape in this domain remains insufficiently underexplored. This study provides a holistic review of research on community participation in conservation education from 2020 to 2025. A bibliometric analysis was conducted using literature from the Scopus database, and visualisations were generated using Bibliometric (R Studio) and VOSviewer. The study analysed publication trends, journal publishers, key institutions, contributing countries, keywords, trending topics, most-cited articles, and authors. A network of associations was built from keyword co-occurrences, highlighting the research topic’s relevance. Four prominent thematic clusters emerged: environmental education, citizen science, biodiversity conservation, and climate change education. Sustainability was identified as the leading journal, and the United States, India, and Spain contributed the most published studies. Emerging topics include ecotourism, ecosystem services, and nature-based solutions, signaling a shift towards applied and interdisciplinary approaches. The findings underscore the need for increased funding to support conservation education in developing countries, with particular emphasis on integrating indigenous knowledge. Special attention should be given to the application of citizen science and digital technologies to develop inclusive, community-based education.

Abstract Euler deconvolution remains one of the most widely used techniques for gravity interpretation because of its simplicity and computational efficiency. However, its outputs are generally limited to discrete source-point estimations and may become unstable under noisy conditions or inappropriate structural-index assumptions, particularly in complex geological environments.&amp;#xD;To overcome these limitations, we propose a multi-task deep learning framework that directly estimates three key structural depth attributes---the top boundary, structural center, and an effective lower depth---from gravity data. &amp;#xD;Unlike conventional workflows that first invert for physical properties and subsequently infer structural boundaries, the proposed framework adopts a geometry-driven learning paradigm that directly predicts structurally meaningful depth attributes from gravity anomalies.&amp;#xD;The shared encoder and multi-decoder architecture enables joint learning of correlated depth attributes, improving depth stability and structural consistency. &amp;#xD;Synthetic experiments demonstrate that the proposed framework produces spatially continuous and noise-robust structural representations with improved structural coherence and geological interpretability.&amp;#xD;The results suggest that deep learning provides a geometry-oriented alternative for extracting continuous structural representations from gravity data, rather than serving as a strict mathematical deconvolution method.&amp;#xD;This work provides a new pathway for potential-field interpretation by offering a direct and stable framework for subsurface structural characterization from gravity anomalies.&amp;#xD;

INTRODUCTION: Orphaned children face heightened vulnerability due to the absence of parental care and limited access to preventive services. Evidence linking oral health knowledge, attitudes, and practice (KAP) with clinical outcomes in this population remains limited. This study aimed to assess oral health KAP among orphaned children in Karaj, Iran, and examine their associations with clinical indicators of dental caries, gingival status, and oral hygiene. METHODS: In this cross-sectional study, 72 children aged 6-12 years residing in four government-run quasi-family centers in Karaj were examined between October 2024 and January 2025 through a census sampling approach. Inclusion required age eligibility and informed consent, whereas children with systemic or developmental disorders or those receiving orthodontic treatment were excluded. Data were collected using a structured, validated questionnaire (α = 0.83) to assess KAP and demographic factors. Clinical examinations were performed by a calibrated examiner (ZJ) (Kappa = 87.68%) using the CAST, GI, and OHI-s indices. Logistic and linear regression models were used to examine predictor variables of KAP and oral health outcomes. RESULTS: The mean scores of knowledge, attitude, and practice were 3.16 ± 1.60 (out of 7), 33.52 ± 4.36 (out of 50), and 10.26 ± 2.72 (out of 20), respectively. Overall, 62.5% of children demonstrated fair oral hygiene (OHI-s = 1.75 ± 1.58) with mild gingival inflammation. CAST assessment indicated that fewer than one-third of primary molars were sound, while more than half of permanent first molars showed enamel caries. Regression analyses showed that frequent toothbrushing (p = 0.015, OR=0.52, 95% CI: 0.30-0.88) and more positive attitudes toward oral health (p = 0.013, OR=0.70, 95% CI: 0.53-0.93) were significant predictors of improved oral status, whereas knowledge and self-reported practice were not consistent predictors. CONCLUSIONS: Orphaned children in Karaj demonstrated moderate oral hygiene, a high prevalence of untreated dental caries, and limited awareness of oral health. Addressing these behavioral and systemic gaps through targeted, evidence-based interventions-particularly oral health education, caregiver involvement, and routine dental monitoring-may help improve oral health outcomes in this vulnerable population.

To address the stability challenges of suspended roof goaf and engineering disasters in coal mine goafs under long-term water immersion, coal rock mass was selected as the research object. Triaxial compression tests under seepage-stress coupling were conducted to analyze the strength degradation and permeability evolution of coal rock mass. Based on the bearing characteristics of coal pillars in suspended roof goaf, a critical criterion for instability of room pillar suspended roof goaf was established, then the numerical simulation studies were conducted using UDEC 7.0 to investigate the influence of different mining parameters and occurrence conditions on the stability of goaf. The research results show that: (1) When the seepage pressure is constant, as the confining pressure increases, the peak stress of the coal samples increases gradually, while the permeability coefficient gradually decreases; when the confining pressure is constant, as the seepage pressure increases, the peak stress gradually decreases, while the permeability coefficient increases gradually. (2) When the stability safety factor of the coal pillar is lower than 1.5, the coal pillar will not be able to maintain long-term stability and corresponding reinforcement measures need to be taken. (3) The increase of occurrence depth will lead to the increase of coal pillar deformation, but as long as the ratio of mining and remaining is moderate, the coal pillar can support the overlying strata and maintain stability; (4) The increase in ratio of mining and remaining strengthens the supporting effect of coal pillars, which helps to improve the stability of the roof, reduce the subsidence of the rock strata above the goaf, and lower the risk of roof collapse. The research results can provide technical references for the prevention and control of hanging roof disasters in mines with similar coal mining processes.

To address localization error accumulation in autonomous underwater vehicle (AUV) swarms due to underwater acoustic communication interruptions, this paper proposes a cooperative localization method that integrates Long Short-Term Memory (LSTM) prediction and factor graph optimization. During the real-time stage, each AUV uses a trained LSTM to predict observations, ensuring the Unscented Kalman filter (UKF) maintains continuous state estimation during interruptions and mitigates error accumulation. During the post-processing stage, a factor graph comprising motion model factors, cooperative observation factors, and LSTM prediction factors is constructed on the AUV swarm master node. By adaptively switching factor types based on communication status, global nonlinear optimization is performed on the AUV states. Simulation results show that compared with UKF + LSTM, the proposed method reduces the Average Localization Error (ALE) by 55% and the Root Mean Square Error (RMSE) by 60%; compared with the Rauch–Tung–Striebel (RTS) smoothing algorithm, it reduces the ALE by 36% and the RMSE by 44%. This fully verifies that the strategy combining real-time state maintenance and post-processing global optimization can more effectively correct AUV localization errors in communication-interrupted regions. Experiments under different communication interruption durations further confirm the robustness of the proposed algorithm, with the maximum error-to-range ratio remaining below 0.2% of the range.

Bioelectric toothbrushes deliver a low-level microcurrent intended to disrupt biofilm with reduced mechanical force, yet their effects on denture-tooth wear remain unclear. This in vitro study compared surface roughness and material loss of acrylic denture teeth brushed with a bioelectric toothbrush versus a soft-bristle manual toothbrush. Thirty-six heat-cured polymethylmethacrylate (PMMA) maxillary central incisors were randomly allocated to three groups (n = 12): manual brushing, bioelectric brushing without current ("OFF"), and bioelectric brushing with current ("ON"). Specimens underwent 20,000 brushing strokes (≈2 years of home cleaning) under a 200 g load using a brushing simulator in a 1:1 dentifrice/water slurry. Surface roughness (Ra, µm) and specimen weight (g) were recorded before and after brushing, and surface topography was qualitatively assessed by digital microscopy. Baseline roughness did not differ among groups (p > 0.05). After brushing, Ra increased significantly in the manual group (1.538 ± 0.219 to 2.233 ± 0.370 µm) and the bioelectric-OFF group (1.481 ± 0.199 to 2.157 ± 0.403 µm), whereas the bioelectric-ON group showed a smaller, non-significant change (1.547 ± 0.252 to 1.838 ± 0.197 µm); the bioelectric-ON condition resulted in significantly lower final roughness than the other groups (p < 0.05). No significant weight loss was detected in any group (p = 0.71). Microscopy corroborated profilometry, showing fewer and shallower scratches on specimens brushed with the bioelectric toothbrush in the ON mode. Within the limitations of this in vitro model, bioelectric activation was associated with reduced surface roughening of PMMA denture teeth without measurable material loss; however, clinical studies are needed to confirm its relevance under real-world oral conditions.

Lassa fever is a severe, often fatal febrile illness endemic to West Africa caused by Lassa virus (LASV), with different virus lineages predominating across West African countries. The viral nucleoprotein (NP) is a target antigen for serological assays to identify previous exposure to LASV. To our knowledge, there is no commercially available assay that reliably quantifies anti-LASV-NP IgG antibodies in human serum. We report the development and qualification of an ELISA designed to detect and quantify anti-LASV-NP IgG in human serum samples. Following assay optimization, performance was assessed through assay qualification at clinical trial laboratories within Ghana. Assay positivity criteria, lower limit of detection, upper and lower limits of quantification, inter-assay precision, selectivity and dilutional linearity were determined. A new reference standard prepared from pooled sera from donors in endemic Lassa fever regions was established and calibrated to the first WHO international standard for LASV antibodies. One ELISA assay utilizing lineage IV LASV-NP was applicable for detection of anti-LASV-NP IgG antibodies in serum samples from different West African countries where either LASV lineages I, II, III and IV predominate. The ELISA remained selective in hemolysed serum samples with minimal loss of signal across repeated sample freeze-thaw cycles. Crucially, the developed ELISA was fully concordant with a now discontinued commercially available ELISA kit for quantification of anti-LASV-NP antibodies. Our anti-LASV-NP IgG ELISA was shown to reliably measure anti-LASV-NP IgG levels in human serum. Establishing and conducting this assay within West Africa represents an essential step towards strengthening LASV epidemiology research and supporting urgently needed development of a vaccine to prevent Lassa Fever.