Search Results (1,594)

The predator–prey model is a fundamental mathematical tool in ecology used to understand the dynamic relationship between predator and prey populations. This study develops a fractional-order delayed dynamical model for a four-species food web, which includes an intermediate predator feeding on two prey species and a top predator preying on all three species. The boundedness of the system’s solutions is first rigorously established using the Laplace transform method. Next, a nonlinear dynamical analysis is performed to determine the existence conditions and local stability of both the trivial and positive equilibrium points. In particular, by treating the time delay as a bifurcation control parameter, explicit criteria for the onset of Hopf bifurcation are derived. Theoretically, when the delay magnitude exceeds a critical threshold, the system loses stability and exhibits sustained oscillatory behavior. Finally, systematic numerical simulations are performed under specific parameter settings. The effects of varying fractional orders and delay magnitudes on the system’s dynamics are quantitatively explored, and the results show strong agreement with the theoretical predictions. Full article

On the south–central Iberian Peninsula, big game hunting is traditionally carried out using big-game hunting under the “Montería” modality, with dog packs. Breeders of these dogs value their versatility in both chasing and capturing prey. In this context, the most popular breed is the Large-sized Podenco Andaluz, colloquially known as Podenco Campanero. In this study, we aimed to morphologically characterize the hounds of the Sierra Morena in Córdoba and evaluate their possible relationships with other Spanish hunting dog breeds. For this purpose, 255 dogs were measured to obtain sixteen morphometric measurements and eleven indices. To assess morphostructural differentiation, we applied multivariate methodologies. The Podenco Campanero exhibited pronounced sexual dimorphism, with males being significantly (p < 0.001) longer, taller, wider, and deeper than females. The morphostructural model of this breed demonstrated considerable homogeneity and harmony, and the population exhibited distinct morphostructural characteristics, with body size and regional width varying between individuals. The morphometric characteristics of the breeds used in Monterías on the central and southern Iberian Peninsula highlight that the diversity of these local genetic resources is shaped by genetic relationships and selective breeding models chosen by dog pack breeders, which depend on the hunting modality and the terrain characteristics where it is practiced. Full article

Background: Breast cancer-related lymphedema (BCRL) is a common and debilitating treatment-related adverse event that can profoundly impact quality of life and financial well-being. Although prospective surveillance and early intervention for BCRL have been shown to reduce the incidence and severity of this chronic condition, diagnostic accuracy of screening, programmatic utilization and efficacy vary widely. We describe the protocol for the BCRL Prospective Surveillance Model (PSM) and Early Intervention Program at the Dana-Farber Brigham Cancer Center that aims to address these issues by augmenting arm measurements (standard of care) with use of patient-reported outcome metrics (PROMs). Methods: Women with newly diagnosed stage I-III breast cancer at high risk for developing BCRL based on tumor and treatment characteristics are eligible for inclusion in our PSM care pathway, which uses both the Breast Cancer and Lymphedema Symptom Experience Index PROMs and arm measurements for screening. Screening begins prior to the initiation of neoadjuvant therapy and continues at regular intervals postoperatively. A positive screen, defined as new patient-reported arm swelling/heaviness and/or relative volume change (RVC) ≥ 5% in the affected limb, triggers consideration for multidisciplinary early intervention. Analysis: The BCRL detection rate will be compared to years previous to protocol development. PSM feasibility will be determined according to the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Efficacy of the PSM will be gauged by comparing change in patient-reported outcomes of interest and arm volume measurement pre and post early intervention. Feasibility will be determined by calculating the percentage of PSM-eligible individuals who complete all PSM activities in a 1-year span. Characteristics of participants versus non-participants in the target population will be compared. Furthermore, 1:1 semi-structured interviews with enrolled patients will be performed to understand facilitators and barriers to implementation. Conclusions: The findings from this study will be used to develop a standardized approach to PSM and early intervention that can be adapted to both resource-modest and resource-abundant healthcare infrastructures. Full article

The increasing threat of terrorism involving Radiological Dispersal Devices (RDDs) necessitates comprehensive evaluation and preparedness strategies, especially in densely populated public areas. This study aims to assess the potential consequences of RDD detonation, focusing on the effective doses received by individuals and the ground deposition of radioactive materials in a hypothetical urban environment. Utilizing the HotSpot code, simulations were performed to model the dispersion patterns of ¹³⁷Cs and ²⁴¹Am under varying meteorological conditions, mirroring the complexities of real-world scenarios as outlined in recent literature. The results demonstrate that ¹³⁷Cs dispersal produces a wider contamination footprint, with effective doses exceeding the public exposure limit of 1 mSv at distances up to 1 km, necessitating broad protective actions. In contrast, ²⁴¹Am generates higher localized contamination, with deposition levels surpassing cleanup thresholds near the release point, creating long-term remediation challenges. Dose estimates for first responders highlight the importance of adhering to operational dose limits, with scenarios approaching 100 mSv under urgent rescue conditions. Overall, the findings underscore the need for rapid dose assessment, early shelter-in-place orders, and targeted decontamination to reduce population exposure. These insights provide actionable guidance for emergency planners and first responders, enhancing preparedness protocols for RDD incidents in major urban centers. Full article

Background: Skin diseases of inflammatory origin, such as atopic dermatitis, psoriasis and acne, have a substantial prevalence in the world population. Natural products are particularly important at a topical level. Essential oils are examples of natural products and thyme in particular has been used for medicinal purposes due to its biological properties. Objectives: The aim of present work was to study the anti-inflammatory potential of Thymus mastichina essential oil, focusing on purified terpene-rich fractions. whose major compounds were thymol and linalool, eucalyptol and α-terpineol, and γ-terpinene and terpinolene, respectively. Additionally, a phytocannabinoid formulation containing cannabidiol (CBD) and cannabigerol (CBG) was evaluated to explore potential synergistic effects. Methods: Thymus mastichina essential oil was extracted and purified to obtain terpene-enriched fractions, which were used to develop three distinct formulations. These were screened for antioxidant activity using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay and assessed for cytotoxicity in HaCaT human keratinocytes. Anti-inflammatory potential was evaluated via gene expression. Selected thyme formulations—alone or in combination with CBD/CBG—were also tested in vivo using a mouse model of acute skin inflammation. Results: The antioxidant activity of the three formulations showed a reduction in DPPH radicals. In addition, the formulations demonstrated to be safe in vitro in the human keratinocyte cell model HaCaT. Under PMA-induced inflammatory stress, the fractions modulated-inflammatory gene expression to varying degrees While terpene fractions alone showed moderate activity, their combination with CBD/CBG enhanced the anti-inflammatory response. In vivo, the gel formulations reduced oedema in a mouse model of acute inflammation. Conclusions: The data support the safe and effective use of Thymus mastichina-derived terpene fractions for topical anti-inflammatory applications. The synergistic effect observed with CBD and CBG suggests that combining essential oil terpenes with phytocannabinoids may offer a novel therapeutic strategy for managing inflammatory skin disorders. Full article

Background. Melioidosis is a severe infection caused by Burkholderia pseudomallei and is endemic in regions with a high prevalence of thalassemia. Patients with thalassemia are thought to be at increased risk due to iron overload, splenectomy, and immune dysfunction. However, the pooled prevalence and mortality outcomes of melioidosis in this population remain unclear. Methods. We conducted a systematic review and meta-analysis in accordance with PRISMA 2020 guidelines (PROSPERO: CRD420251108294). PubMed, Embase, and Scopus were searched from inception to July 2025. Observational studies reporting prevalence or mortality of melioidosis in patients with thalassemia were eligible. Pooled odds ratios (ORs) for mortality were calculated using random-effects models, with subgroup and sensitivity analyses based on age, thalassemia subtype, and study quality. Results. Six retrospective studies including 7529 melioidosis patients, of whom 173 had thalassemia, were analyzed. The prevalence of thalassemia among melioidosis cases ranged from 0.5% to 40.7%. Mortality among thalassemia patients varied from 0% to 100%. Pooled analysis demonstrated no significant excess mortality compared with non-thalassemia controls (OR 0.55, 95% CI 0.16–1.89; I² = 44.9%). Sensitivity analysis restricted to moderate- and high-quality studies showed a significantly lower risk of death (OR 0.23, 95% CI 0.15–0.36; I² = 0%). Subgroup analyses by thalassemia subtype and age revealed no clear effect modification, although power was limited. Conclusions. Despite biological plausibility, thalassemia was not associated with increased melioidosis mortality. These findings suggest that closer clinical monitoring, iron chelation, and comorbidity profiles may influence outcomes. Prospective, well-characterized cohort studies are needed to refine risk stratification and guide management in endemic regions. Full article

Participation in sports and the presence of sports injuries have a lasting impact on youth athletes’ physical, cognitive, and emotional development and sense of self-identity. There is an ongoing growth in participation in sports for youth, as well as growing literature on the epidemiology and outcomes of sports-related injuries. However, there is a paucity of published research regarding the psychological aspects of sports injury, including psychosocial factors, stressors, and responses, from the perspective of young athletes. Key risk factors include the youth’s sex, the types of sports activity, and any previous injuries. Psychosocial models, such as the stress-injury model, help explore such risk factors and their relationship to outcomes of stress. Implications for sports injury outcomes vary within the pediatric population, and the recovery and rehabilitation process requires integrated healthcare to optimize health and mental health outcomes. This review aims to describe the psychosocial factors related to sports injuries in children and adolescents, provide an understanding of sports injury models for youth athletes, and point to recovery and prevention through integrated behavioral health interventions. Based on a literature search, we identified 40 articles most relevant to our aims to explore psychosocial factors and stressors, predisposing and risk factors, and developmental aspects of sports injuries in children and adolescents. Full article

Global Navigation Satellite Systems (GNSSs) are widely used in many applications but can be out of use in some critical conditions. Hybrid pseudolite systems utilize ground and aero stations as pseudolites to provide positioning signals for users within the covered area. The positioning accuracy is an important performance parameter for the pseudolite system and is decided by the layout of the pseudolites. This paper proposes a layout optimization method based on an Incremental Geometric Dilution of Precision (IGDOP) model. The IGDOP considers the GDOP value into two parts. One is the fixed part corresponding to the ground stations, and the other is the varying part related to the movable aero pseudolite stations. Thus, when the aero pseudolites’ position changes, the new GDOP value could be obtained only by calculating the varying part. Then, a Monte-Carlo Genetic Algorithm (MC-GA) is proposed for the IGDOP calculation for a minimum value. This algorithm comprises two main components: first, it leverages the random sampling capability of the Monte-Carlo Algorithm to provide sample points that satisfy the sample space for the subsequent Genetic Algorithm, which serve as individuals of the initial population; subsequently, it searches for the minimum value of IGDOP via the Genetic Algorithm and determines the optimized layout of the hybrid pseudolite system. Simulations are carried out using a hybrid pseudolite system with four fixed stations and n movable stations. The results validate the developed IGDOP model and show that the approach enables scalable optimization of n − 1 movable stations via four fixed stations, providing an efficient, low-complexity solution to the system layout optimization. Full article

Optimizing pavement maintenance and rehabilitation (M&R) strategies is essential, especially in developing countries with limited budgets. This study presents an integrated framework combining a deterioration prediction model and a genetic algorithm (GA)-based optimization model to plan cost-effective M&R strategies for flexible pavements, including asphalt concrete (AC) and double bituminous surface treatment (DBST). The GA schedules multi-year interventions by accounting for varied deterioration rates and budget constraints to maximize pavement performance. The optimization process involves generating a population of candidate solutions representing a set of selected road sections for maintenance, followed by fitness evaluation and solution evolution. A mixed Markov hazard (MMH) model is used to model uncertainty in pavement deterioration, simulating condition transitions influenced by pavement bearing capacity, traffic load, and environmental factors. The MMH model employs an exponential hazard function and Bayesian inference via Markov Chain Monte Carlo (MCMC) to estimate deterioration rates and life expectancies. A case study on Cambodia’s road network evaluates six budget scenarios (USD 12–27 million) over a 10-year period, identifying the USD 18 million budget as the most effective. The framework enables road agencies to access maintenance strategies under various financial and performance conditions, supporting data-driven, sustainable infrastructure management and optimal fund allocation. Full article

The European wildcat exhibits considerable plasticity in its habitat requirements across its distribution, with differences increasing along a continental-scale latitudinal gradient. While wildcats often favor deciduous and mixed forests with dense cover and prey, studies show these preferences vary across their expansion. Range-wide conservation efforts will benefit from incorporating knowledge generated by robust regional ecological models. We used data from a large camera trap grid (n = 292 stations), spanning across eight wildcat-associated habitats, within its range in northern Greece, to understand the regional ecological parameters affecting the species’ habitat selection. We analyzed the data using single-season density-induced detection heterogeneity occupancy models (Royle–Nichols), considering 12 environmental and anthropogenic parameters. The global model’s GoF was high (p = 0.9). Elevation and percent forest cover were both significantly negatively related to wildcat occupancy (as derived from the modeled “relative abundance index” N). Likewise, there was a negative, but moderate, relation between distance to freshwater bodies and human settlements with wildcat occupancy. We used the model-average coefficients to generate a predictive map of wildcat relative abundance across northern Greece, which identified 47,930 km² of potential wildcat habitat. Assuming a range of densities between 0.05 and 0.3 ind/km² in areas with predicted low, medium, and high relative abundance, we speculate the putative wildcat population in northern Greece to be between 3535 and 7070 individuals. The findings, which vary from ecological models of the species in northern Europe, show the need for regional models and the importance of Greece, and the Balkan peninsula, for the species. Full article

While loneliness is a known correlate of social withdrawal, the underlying mechanisms, particularly within college student populations, remain inadequately understood. This study addresses this gap by investigating the mediating role of internet addiction and the moderating role of sex in the relationship between loneliness and social withdrawal. A cross-sectional survey was conducted with 1978 Chinese college students. Analyses were performed using SEM (AMOS) and the PROCESS for SPSS to test a moderated mediation model. Results confirmed a significant positive association between loneliness and social withdrawal. Internet addiction was found to significantly mediate this relationship, explaining 50.7% of the total effect. Moreover, sex moderated the indirect pathway, suggesting that the strength of the mediating effect varied by sex. These findings provide empirical support for the Evolutionary Theory of Loneliness by elucidating the psychological processes linking loneliness to social withdrawal within a collectivist cultural context. The study also offers practical implications for developing targeted mental health interventions to reduce social withdrawal and promote social participation among college students. Full article

Keel bone lesions (KBLs) represent a relevant welfare concern in laying hens, arising from complex interactions among genetics, housing systems, and management practices. This study presents the development of an image analysis system for the automated detection and classification of KBLs in slaughterhouse videos, enabling scalable and retrospective welfare assessment. In addition to lesion classification, the system can track and count individual carcasses, providing estimates of the total number of specimens with and without significant lesions. Videos of brown laying hens from a commercial slaughterhouse in northeastern Italy were recorded on the processing line using a smartphone. Six hundred frames were extracted and annotated by three independent observers using a three-scale scoring system. A dataset was constructed by combining the original frames with crops centered on the keel area. To address class imbalance, samples of class 1 (damaged keel bones) were augmented by a factor of nine, compared to a factor of three for class 0 (no or mild lesion). A YOLO-based model was trained for both detection and classification tasks. The model achieved an F1 score of 0.85 and a mAP@0.5 of 0.892. A BoT-SORT tracker was evaluated against human annotations on a 5 min video, achieving an F1 score of 0.882 for the classification task. Potential improvements include increasing the number and variability of annotated images, refining annotation protocols, and enhancing model performance under varying slaughterhouse lighting and positioning conditions. The model could be applied in routine slaughter inspections to support welfare assessment in large populations of animals. Full article

Although Artificial Intelligence (AI) is transforming teachers’ knowledge and professional practice, its full potential has yet to be fully realized. To incorporate AI effectively into pedagogical contexts, it is essential that teachers possess the knowledge necessary to guide its responsible use. However, in Latin America, there remains limited empirical evidence to support this process. To address this gap, this empirical study analyzes teachers’ knowledge of AI using the Intelligent-TPACK framework, which includes an ethical dimension. A validated and adapted questionnaire was administered to 709 primary and secondary school teachers from the Metropolitan Region of Chile, using a non-probability sampling method. The sample is compositional–descriptive in nature for the study variables and is not statistically representative of the broader population. Data were analyzed through descriptive and inferential statistical methods. The results reveal mixed levels of knowledge—slightly higher in technological knowledge yet lower in terms of integration and ethical awareness. Significant differences were found by gender, age, teaching level, and subject area. Regression models identified teaching experience, gender, and educational level as the most consistent predictors. Additionally, cluster analysis revealed four exploratory professional profiles characterized by varying degrees of knowledge. These findings are discussed in light of teacher training needs and aim to inform the development of professional learning programs better aligned with the actual demands of the teaching profession. Full article

Natural disasters often strike unexpectedly, leaving thousands of victims and affected individuals each year. Effective disaster preparedness is critical to reducing these consequences and accelerating recovery. This paper presents Eghatha, a blockchain-based decentralized system designed to optimize humanitarian aid delivery during crises. By enabling secure and transparent transfers of donations and relief from donors to beneficiaries, the system enhances trust and operational efficiency. All transactions are immutably recorded and verified on a blockchain network, reducing fraud and misuse while adapting to local contexts. The platform is volunteer-driven, coordinated by civil society organizations with humanitarian expertise, and supported by government agencies involved in disaster response. Eghatha’s design accounts for disaster-related constraints—including limited mobility, varying levels of technological literacy, and resource accessibility—by offering a user-friendly interface, support for local currencies, and integration with locally available technologies. These elements ensure inclusivity for diverse populations. Aligned with Morocco’s “Digital Morocco 2030” strategy, the system contributes to both immediate crisis response and long-term digital transformation. Its scalable architecture and contextual sensitivity position the platform for broader adoption in similarly affected regions worldwide, offering a practical model for ethical, decentralized, and resilient humanitarian logistics. Full article

Background/Objectives: Sleep is integral to cognitive functioning, yet many college students experience poor sleep, often influenced by dysfunctional beliefs about sleep. Dysfunctional beliefs can exacerbate sleep issues and negatively impact executive functioning (EF). Distinct EF facets, including inhibition, working memory, and cognitive flexibility, may differ in their sensitivity to sleep disruptions. While research suggests links between sleep and EF, less is known about how sleep-related beliefs may moderate this relationship and how sleep can affect the various EF facets. Utilizing an undergraduate population, this study examined how sleep quality/quantity affects the different EF facets, how this relationship differs between subjective and objective measurements, and whether dysfunctional beliefs about sleep moderate the relationship. Methods: Undergraduate students (N = 212, ages 18–23) completed self-report measures assessing dysfunctional beliefs about sleep (DBAS-16), sleep quality (ISI), and sleep quantity (self-reported sleep duration). Objective EF was measured using computerized CNS Vital Signs tasks targeting inhibition (Stroop Test), working memory (4-Part Continuous Performance Test), and cognitive flexibility (Shifting Attention). Subjective EF was measured using individual subscales on the Behavioral Rating Inventory of Executive Functioning—Adult Version (BRIEF-A). Results: Moderation analyses were conducted via linear regression. When measured objectively, neither sleep quantity nor insomnia severity (sleep quality) significantly affected any EF facets, and dysfunctional beliefs about sleep did not have any significant moderation effect. When measured subjectively, insomnia severity (sleep quality), but not sleep quantity, significantly predicted inhibition and cognitive flexibility; in contrast, neither predictor significantly predicted working memory. Regarding specific predictors, dysfunctional sleep beliefs were found to exert significant effect over all three facets; this effect was diminished when insomnia severity was included in the model. Regarding moderation, dysfunctional beliefs about sleep moderated the relationship between sleep quantity and all three EF facets. Conclusions: The impact of sleep quality, sleep quantity, and dysfunctional beliefs about sleep varies depending on whether the facets of EF are measured subjectively or objectively. Dysfunctional beliefs about sleep may exacerbate the perceived effect of short sleep duration on daytime cognitive functioning. In addition, insomnia severity may account for the effects of dysfunctional sleep beliefs on perceived inhibitory control and cognitive flexibility; however, working memory may be more resistant to the effects of sleep disturbances and dysfunctional sleep beliefs. Clinical implications of these results and future directions are discussed. Full article