Search Results (9,179)

Background: Previous research has found that mindfulness-based techniques are beneficial for reducing stress in heavy-drinking individuals. However, the underlying neurobiology of these stress-reducing effects are unclear. Moreover, much of the research examining neurobiological correlates of mindfulness has used static functional connectivity, suggesting that brain activity goes unchanged for the entire length of an MRI scan. Methods: In the current study, we used a state-based dynamic functional connectivity model to examine brain states during either a 10 min mindfulness session or resting control that followed an individually tailored stress imagery task. Using a hidden semi-Markov model (HSMM), six brain states and the associated dynamics of state traversal were estimated for a population of moderate-to-heavy drinkers (N = 32). We modeled the 36 Schaefer atlas regions spanning the salience and default mode networks, and the HSMM characterized each state by its distinct multivariate pattern of activity and covariance structure. Group differences in dwell times, transition behavior, and overall state dynamics were evaluated using permutation tests and mixed-effects models. Results: Participants that experienced the mindfulness session had more transitions and longer time spent in states in which the salience network was more active. Participants assigned to the control group had more transitions and increased time spent in states in which nodes of the default mode network were more active. Moreover, for control participants, increased occupancy time to SN-dominant states was associated with lower perceived stress. Conclusions: Using HSMM provided a unique insight into network connectivity during mindful states; we believe it offers a novel approach to testing and optimizing mindful-based therapies. Full article

Environmental pressure in Nigeria persistently escalates despite several development efforts, prompting questions about the structural factors contributing to the nation’s ecological vulnerability. Considering this, the study employs a time-series research design that synthesizes collective theoretical perspectives to elucidate the interplay between income inequality (GINI), institutional quality (INST), trade in services (TO), and population density (POPd) in shaping Nigeria’s ecological footprint (ECF), utilizing data for the aforementioned variables from 1960 to 2024. The analysis shows time-varying dynamics across pollution regimes using Quantile-on-Quantile Regression (QQR) and Wavelet Quantile Correlation (WQC). The result reveals notable asymmetries across the ECF distribution. GINI and POPd intensify ecological pressure mainly at higher ECF quantiles. While INST serves as a key mitigating factor of ECF, particularly in a long-term pollution scenario. TO exhibits a regime-dependent effect, aligning with the Pollution Haven expectation in poor environments. These findings suggest that environmental outcomes in emerging economies are shaped by structural inequality and institutional strength. Highlighting the necessity of building institutional capacity to decouple inequality that drives ecological degradation. Thus, connecting national strategies with the Sustainable Development Goals (SDGs) 1, 8, 10, 11, 12, 13, 15, 16, and 17. These provide actionable insights into an inclusive and resilient environment. Full article

In this study, we propose a compartmental mathematical model that considers two interacting populations (citrus plants and insect vectors) and investigate the transmission dynamics of Huanglongbing in citrus crops. This disease is caused by the bacterium Candidatus Liberibacter asiaticus and is vectored by the psyllid Diaphorina citri. The disease is modeled under the following three main assumptions: there is vital dynamics with constant recruitment rates of citrus plants, the force of infection in both populations is a spatially dependent function varying with geographic location, and there is a spatial displacement of the vectors. In the main results of the paper, we formulate a coupled ordinary and partial differential equation system with initial and zero flux boundary conditions, establish the existence and uniqueness of solutions to the proposed model by applying semigroup theory, and introduce a numerical approximation of the system. Moreover, we develop a stability and persistence analysis. From the analytical point of view, we calculate the basic reproduction number $R_0$ and prove three facts: the disease-free equilibrium is globally asymptotically stable when $R_0<1$; the disease-free equilibrium is globally asymptotically stable when $R_0>1$; and the hybrid system exhibits uniform persistence of infection when $R_0>1$. In addition, we present some numerical examples. Full article

High-dimensional global optimization and microgrid economic scheduling problems are often dominated by nonlinear search landscapes, strong coupling among decision variables, and stringent operational constraints, which severely limit the effectiveness of conventional metaheuristic approaches. In response to these challenges, this study presents a multi-strategy cooperative optimization framework derived from stock exchange trading principles, referred to as MESETO. The proposed method departs from the single-path evolutionary process of the standard SETO algorithm by introducing a diversified strategy collaboration mechanism that enables the dynamic adjustment of search behaviors throughout the optimization process. Multiple complementary update strategies are jointly employed to balance global exploration and local exploitation, while an adaptive probability regulation scheme continuously reallocates computational effort toward strategies that demonstrate superior performance. In addition, a solution validation mechanism is incorporated to prevent population degradation by rejecting ineffective evolutionary moves, thereby enhancing convergence stability. Extensive numerical experiments conducted on the CEC2017 and CEC2022 benchmark suites across different dimensional configurations demonstrate that MESETO consistently achieves improved solution accuracy, faster convergence, and stronger robustness compared with several representative state-of-the-art metaheuristic algorithms. Furthermore, the applicability of the proposed optimizer is verified through a 24 h microgrid economic scheduling case that integrates renewable energy sources, energy storage systems, dispatchable generators, and grid interaction. Simulation results confirm that MESETO effectively reduces operational costs while maintaining stable and efficient scheduling performance. Overall, the results indicate that MESETO constitutes a reliable and efficient optimization framework for solving complex global optimization problems and practical energy management applications. Full article

Since 2025, 45% of the world’s population of 8.2 billion people has lived in cities, and by 2050, that number is expected to increase to 66%. As the number of people living in cities increases, natural landscapes will be transformed into impervious surfaces, leading to serious challenges and resulting in a phenomenon named the urban heat island (UHI) effect. Although urban thermal variation has been studied globally, few studies have examined the impact of land use transitions on local surface temperatures. This study aims to address this gap by investigating the impact of LULC transitions on the land surface temperature (LST) and the urban thermal field variation index (UTFVI) in the five most populated cities in Saudi Arabia between 2000 and 2024: Riyadh, Jeddah, Makkah, Madinah, and Dammam. This study provides not only a comprehensive overview of the cities in Saudi Arabia but also a detailed analysis of each city using a novel approach that integrates thermal land use analysis. In this study, Landsat TM-5, OLI-TIRS-8, and OLI2-TIRS2-9 were used to process the LULC using random forest machine learning and thermal indices. Fifteen LULC maps were generated and assessed based on four classifications across the cities and time periods: urban area, barren land, vegetation, and water. The difference-in-difference (DiD) analytical approach was used to compute the thermal effect size and compare the specified changed pixels (barren-to-urban, vegetation-to-urban) with stable urban. Then, the relationship between the LST and the NDVI–NDBI were investigated. The results show that the overall accuracy of the 15 LULC classifications ranged from 89.00% to 97.00%. The urban area increased across all the cities, with the greatest changes being 448.84, 179.67, 177.96, 126.33, and 95.69 km² in Riyadh, Jeddah, Dammam, Madinah, and Makkah, respectively. Furthermore, the vegetation cover increased in most of the cities over time. The LST of the urban areas increased by 8.31 °C in Riyadh, 5.24 °C in Jeddah, and 1.41 °C in Makkah in 2024 compared to 2000, while those in Dammam and Madinah decreased by 2.67 °C and 0.60 °C, respectively. This study delivers robust insights into two decades of urban surface temperature dynamics across major Saudi Arabian cities, offering critical evidence to inform UHI mitigation strategies and support the long-term sustainability of urban environments. Full article

The milpa (a traditional Mesoamerican agricultural system) constitutes a dynamic space with a great diversity of agro-food and sociocultural resources. The objective of this study was to evaluate the milpa’s contribution to food self-sufficiency and to document perceptions of its attributes and cultural significance in San Felipe Tejalápam, Oaxaca. Using a mixed-methods design that included food frequency questionnaires, 24 h dietary recalls (n = 50), and semi-structured interviews (n = 12), the percentage of adequacy (PA) and the symbolic perception of the milpa were analyzed. The results indicate that milpa foods are important for local nutrition, providing significantly higher percentages of adequacy (p ≤ 0.05) for carbohydrates (63.72%), fiber (69.72%), and iron (77.22%). However, the system proved insufficient in energy (42.35%), protein (32.38%), vitamin C (2.69%), vitamin E (0.17%), and potassium (11.14%) compared to external food sources. From a cultural perspective, the milpa was identified as a pillar of community identity. Participants highlighted its culinary properties, health benefits, and its role as a driver of economic and food self-sufficiency. It is concluded that the milpa not only satisfies key nutritional needs but also preserves ancestral knowledge and strengthens the social fabric of the population. Full article

This study presents a quantitative, scenario-based framework for analyzing humanity’s potential progression along the Kardashev scale, with emphasis on the transition to Type I (planetary-scale) and Type II (stellar-scale) civilization status. Using humanity as an empirical reference case, we integrate four coupled dimensions of civilizational development: energy utilization, information processing capacity, large-scale construction mass, and population dynamics, modeled through historical data, empirical trends, and physically motivated growth constraints. Energy availability is characterized using global energy production records and insolation statistics for potentially habitable exoplanets, explicitly acknowledging observational biases toward cooler host stars. Information processing growth is constrained by thermodynamic limits and observed trends in global data generation, while construction mass and population evolution are described using exponential and logistic growth models, respectively. These components are combined into a composite Civilization Development Index (CDI), a weighted logarithmic metric designed to track multi-scale civilizational advancement and tested through sensitivity analyses. Under optimistic assumptions of uninterrupted technological growth and absence of civilization-scale catastrophes, the framework suggests that humanity could reach Type I civilization status on the order of the 23rd century, while Type II status represents a substantially longer-term outcome extending into the third millennium or beyond. These timescales should be interpreted as lower bounds, as catastrophic events, sociopolitical constraints, or resource bottlenecks could significantly delay or prevent such transitions. By explicitly delineating assumptions, uncertainties, and physical constraints, this work provides a structured baseline for studies of long-term civilizational trajectories and the factors governing the emergence or absence of advanced technological civilizations. Full article

Background: Routine immunization programs in Pakistan rely heavily on estimated population denominators, limiting accurate identification and follow-up of zero-dose and under-immunized children, particularly in high-risk urban settings such as Quetta, Balochistan. Methods: A quasi-experimental, pre–post implementation study was conducted from June 2024 to June 2025 across three low-performing union councils. A CHW-based household tracking tool was integrated within existing PEI–EPI systems. Data were derived from CHW Books, Rapid Convenience Assessments (RCA), and routine MIS reports. Descriptive statistical analysis was employed to assess trends in immunization coverage and program performance; no inferential statistical tests were applied due to the use of complete programmatic (census-based) data rather than sampled observations. Results: Antigen-specific coverage improved substantially, with Penta-3 coverage increasing from 22% to 95%, zero-dose conversion from 45% to 65%, and defaulter follow-up from 14% to 79%. All three union councils transitioned to Category 1 operational status. Administrative coverage exceeding 100%, reflecting population-level coverage and denominator correction rather than true population-level coverage. Conclusions: Integrating CHW-based tracking with dynamic denominator verification enhances routine immunization, microplanning, equity, and operational performance in high-risk LMIC urban settings. Full article

Reservation prices determine which goods consumers are willing to buy and, therefore, shape demand curves in markets. Neoclassical economics postulates that reservation prices optimally reflect the marginal utility provided by a good given all other possible uses of the consumer’s budget, as well as a rational response to the information environment. In contrast, behavioral economics suggests that reservation prices are influenced by extraneous factors and are, thus, less stable and more difficult to predict. In this article, I propose a behavioral model of how the reservation price changes during sequential price searches. The model assumes bounded rationality, is rooted in the psychological theory of aspiration levels, and posits that the reservation price adjusts towards the lowest price known. A corollary is that when higher prices are charged in a market, consumers become willing to pay more in the short term. Results from an online laboratory experiment with more than 400 participants from the general population suggest that the model performs well in explaining the dynamics of the reservation price during a search spell. While the results imply that reservation prices are malleable, competition can protect consumers from sellers exploiting their adaptiveness. Full article

The precursor infiltration and pyrolysis (PIP) route is widely adopted to fabricate carbon fiber-reinforced silicon carbide (C_f/SiC) composites; however, the atomic-scale restructuring of the pyrolytic carbon/silicon carbide (PyC/SiC) interface during ceramization—and its impact on mechanical integrity—remains elusive. Here, reactive molecular dynamics (ReaxFF MD) simulations elucidate the coupled thermochemical–mechanical evolution of polycarbosilane (PCS) precursors on PyC substrates with orientation angles (OAs) of 0°, 25°, 55°, and 85°. Dynamic pyrolysis triggers a pivotal transition from sp² to sp³ hybridization at the interface. High-OA substrates (55° and 85°) present a dense population of reactive edge sites, fostering extensive cross-interfacial covalent bonding. Subsequent shear loading reveals that these pyrolysis-induced chemical bridges govern failure modes, shifting from interlayer sliding dominated by weak non-bonded interactions (0°) to ductile fracture featuring uniform plasticity and crack deflection. The OA = 55° interface attains a theoretical peak shear strength of 15 GPa and exhibits the most favorable combination of high strength and ductile failure under tensile loading, owing to an optimal balance between reactive site availability and interlayer steric openness. In contrast, the OA = 85° interface, despite comparable peak stress, fails via brittle crack penetration into the SiC matrix. By correlating atomistic structure with macroscopic performance, this study provides a bottom-up framework for engineering C_f/SiC composites via interfacial texturing and optimized pyrolysis protocols. Full article

Molecular interactions underpin the functioning of the living cell. Molecules exist in distinct quaternary structural forms, associate with molecular partners in signaling cascades, form transient quinary interactions, localize in membrane domains, and cluster in membrane-less condensates. Measuring the concentration, size, and dynamics of these molecular assemblies remains an enduring biophysical challenge, particularly in cells, where heterogeneity is the rule rather than the exception. Orthogonal signals derived from fluorescence lifetime, fluorescence fluctuations, and fluorescence polarization provide valuable metrics for probing interactions and environments, concentration and size, and rotational dynamics, respectively. This paper combines fluorescence lifetime imaging microscopy with image correlation analysis and polarization to determine the concentrations, brightness, lifetime, and rotational correlation time of different fluorescent states. A two-population model is examined as a prototypical example of a heterogeneous system. The analysis is illustrated on a simple fluorescence model system, where cluster densities, relative brightnesses, lifetimes, and rotational correlation times are extracted. Full article

Phascolosoma esculenta is an economic species endemic in China and a highly prized delicacy along the country’s southeastern coast. This study focused on five P. esculenta populations and investigated their genetic diversity, population structure, and historical population dynamics. These populations were sampled from five locations, namely Beihai (BH) and Fangchenggang (FCG), in Guangxi; Putian, in Fujian (FJ); Danzhou, in Hainan (HN); and Zhanjiang (ZJ), in Guangdong Beihai, Guangxi (BH), Fangchenggang, Guangxi (FCG), Putian, Fujian (FJ), Danzhou, Hainan (HN), and Zhanjiang, Guangdong (ZJ). Genomic data were obtained through restriction site-associated DNA sequencing (RAD-seq) of 100 individuals. After quality filtering, a panel of 158,264 high-quality single nucleotide polymorphism (SNP) markers was established for subsequent analysis. The results revealed that the observed heterozygosity (Ho = 0.1872–0.2065) was lower than the expected heterozygosity (He = 0.2304–0.2382), with inbreeding coefficients (Fis) ranging from 0.1114 to 0.1592, indicating heterozygote deficiency and moderate inbreeding. Genetic diversity was moderate across all populations, as reflected in the values I (0.5220–0.5530), π (0.2415–0.2478), and PIC (0.1914–0.1982). Low genetic differentiation was observed among populations (Fst: 0.0339–0.0509) accompanied by high gene flow (Nm = 4.6658–7.1192), suggesting ongoing genetic exchange between populations. Analysis of Molecular Variance (AMOVA) indicated that most genetic variation occurred within populations. Genetic distance and genetic similarity ranged from 0.0345 to 0.0522 and 0.9491 to 0.9661, respectively, with no significant isolation by distance (Mantel test, R = 0.0793, p = 0.4307). Analysis of the species’ historical population dynamics suggests that P. esculenta may have experienced a substantial population contraction beginning approximately 300 years ago. Overall, the five populations exhibit moderate genetic diversity, though signs of inbreeding and recent population decline may indicate early stages of germplasm degradation. These findings provide important insights for the conservation and sustainable aquaculture of this species. Full article

This study examines the tension between audience interests and editorial lines in the major national and regional digital media outlets in Chile. It analyzes how editors incorporate metrics and user feedback into content selection and prioritization processes. The sample included the five websites with the largest national reach according to the 2024 ComScore ranking (El Mercurio Online, BioBioChile, La Tercera, Megamedia and Chilevisión), along with digital media outlets from the country’s five most populous cities without counting the capital (La Serena, Rancagua, Antofagasta, Valparaíso, and Temuco). Semi-structured interviews were conducted with directors or editors to assess whether the use of metrics influences journalistic judgment and editorial autonomy. Data were analyzed through a thematic analysis, combining categories drawn from the literature with emergent codes. The findings indicate that audience feedback affects editorial decision-making, although to varying degrees depending on the type of outlet. In national newspapers, a fiduciary vision is more firmly sustained due to greater financial capacity, albeit with internal tensions. In contrast, regional media outlets face greater challenges in maintaining their editorial line in the face of metrics, as lower economic stability and dependence on digital traffic tend to favor dynamics closer to a market-driven model. Although the findings are based on professional discourse and do not include direct observation of production routines, the comparison between national and regional media offers a cross-cutting perspective on editorial autonomy within the Chilean digital media ecosystem, an area that remains underexplored in the country. Overall, the study shows that metrics place pressure on both editorial policy and journalistic practices by requiring a continuous balancing of professional judgment and real-time audience behavior. Full article

In large-scale dam construction, the efficiency of concrete transport operations is fundamentally governed by the coordination between horizontal hauling and vertical hoisting capacities. Traditional experience-based scheduling approaches often fail to capture the stochastic, cyclic, and resource-coupled nature of these transport systems. This study developed a closed queuing network-based stochastic simulation framework to model dam concrete transportation as a finite-population cyclic service system. The process was abstracted into sequential service stages with stochastic service times, and a structured state-space representation combined with time-step simulation was constructed to describe dynamic resource occupation and task transitions under varying truck and cable crane configurations. Application to a real large-scale dam project revealed a characteristic multi-stage performance evolution pattern governed by capacity matching mechanisms. As the truck fleet size increased, system performance transitioned from a transport-limited regime to a capacity-coordination regime and ultimately to a hoisting-saturated regime in which further fleet expansion yielded diminishing returns. Sensitivity analysis demonstrated that hoisting capacity imposed an upper bound on system throughput, while adaptive fleet reconfiguration could restore operational equilibrium under constrained equipment availability. The results indicated that dam concrete transport should be treated as a dynamic capacity regulation problem rather than a static allocation task. The proposed framework provides an interpretable and quantitative decision-support tool for equipment configuration, bottleneck identification, and adaptive scheduling in large-scale hydraulic infrastructure projects. Full article

Intelligence metrics based on benchmark performance or population norms are useful for measuring comparative ability within defined test environments, but they do not directly evaluate the structural coherence of an agent’s trajectory across time, domains, and perturbations. This article introduces Reflexive Signature Intelligence (RSI) as a bounded theoretical framework for addressing that different problem. RSI is developed within a causal-symmetric informational perspective in which intelligence is understood as the capacity of a system to maintain and restore alignment with a structurally constrained invariant without collapsing the open gradient of development. On this basis, the paper formulates the Principle of Bounded Subjectivity and the Prohibition of Finality as framework-level principles, arguing that intelligence should be assessed not as arrival at a completed end state but as the quality of an asymptotic trajectory. The framework is then operationalized on two coupled levels: a micro-level proposed as a future measurement program linked heuristically to resilience and prediction-error dynamics, and a macro-level expressed through five dimensions of structural integrity, including reflexive regulation, cross-domain integration, internal consistency, stabilization, and signature-setting. The article concludes by outlining implications for AI evaluation and alignment, with particular relevance for distinguishing full agents, partial systems, and human–AI composite configurations. Full article