Search Results (3,703)

Objective: This study investigates how artificial intelligence (AI) research relates to firm value, focusing on dominant thematic trends, theoretical foundations, and global collaboration patterns. Methods: A PRISMA-guided systematic review was conducted on 219 peer-reviewed articles published between 2013 and May 2025 in the Web of Science Social Sciences Citation Index. Bibliometric techniques, including co-word, co-citation, and collaboration network analyses, were performed using the bibliometrix (version 4.2.3) in R (version 4.4.2) package to map key concepts, intellectual structures, and international research partnerships. Results: The literature is primarily grounded in strategic management theories such as the resource-based view (RBV) and dynamic capabilities. Emerging research streams emphasize digital transformation, big data analytics, and decision support systems. Frequently co-occurring terms include “firm performance,” “artificial intelligence,” “dynamic capabilities,” “information technology,” and “decision-making.” Collaboration mapping highlights the United States, United Kingdom, and China as leading hubs, with increasing contributions from emerging economies such as India, Malaysia, and Saudi Arabia. The alignment between co-word and co-citation structures reflects a shift from foundational theory to applied AI capabilities in firm-value creation. Implications: By integrating a systematic review with advanced bibliometric and science-mapping methods, this work establishes a structured foundation for theory development, empirical testing, and policy formulation in AI-driven business landscapes. Full article

University campuses in rapidly urbanizing regions face increasing pressure to balance infrastructure development with environmental sustainability, yet their carbon storage potential remains largely unexplored in sub-Saharan Africa. This study assessed land use changes, carbon storage dynamics, and economic valuation across three Ghanaian universities, University of Ghana (UG), Kwame Nkrumah University of Science and Technology (KNUST), and University of Cape Coast (UCC), from 2017 to 2023, and evaluated five future scenarios using the InVEST carbon model. Land use analysis employed ESRI 10 m annual land cover data, while carbon storage was estimated using regionally appropriate carbon pool values, and economic valuation applied Ghana’s social cost of carbon ($0.970/tCO₂). Historical analysis revealed substantial carbon losses: UG declined by 17.1% (19,695 Mg C), KNUST by 29.5% (20,063 Mg C), and UCC by 7.9% (3292 Mg C), due to tree cover conversion to built areas. Scenario modeling demonstrated that infrastructure-focused development would cause additional losses of 4211–6891 Mg C, while extensive tree expansion could increase storage by 1686–5227 Mg C. Economic analysis showed tree expansion generating positive net present values ($1612–$5070), while infrastructure development imposed costs (−$4028 to −$6684). These findings provide quantitative evidence for sustainable campus planning prioritizing carbon conservation in tropical institutional landscapes. Full article

High-rise building facades offer an alternative site for installing photovoltaic panels, which are traditionally placed on rooftops. The unique spatial configuration of high-rise buildings, characterized by a small footprint area relative to their height, supports the application of vertical facades for this purpose. Photovoltaic panels installed in these areas not only generate electricity but also enhance the aesthetic dimension of the urban landscape. The proposed methodology uses the EnergyPlus software to simulate the electricity generation of photovoltaic panels mounted on the walls of high-rise buildings in the city of Kragujevac, Serbia. A technical, economic, and environmental analysis was conducted for two scenarios: (1) photovoltaic panels installed on two facade areas with the highest solar potential, and (2) photovoltaic panels installed on all four available facade areas. In Scenario 1, the annual reduction in electricity consumption, annual cost savings in electricity consumption, and investment payback period range from 13 to 38%, 11 to 31%, and 8.4 to 10.6 years, respectively. In Scenario 2, these values range from 23 to 58%, 18 to 47%, and 10.9 to 12.9 years, respectively. The results indicate that southeast and southwest facades consistently achieve higher levels of electricity generation, underscoring the importance of prioritizing high-performing orientations rather than maximizing overall surface coverage. The methodology is particularly efficient for analyzing the solar potential of numerous buildings with comparable shapes, which is a characteristic commonly found in Eastern European architecture from the late 20th century. The study demonstrates the applicability of the proposed methodology as a practical and adaptable tool for assessing early-stage solar potential and providing decision support in urban energy planning. The approach addresses the identified methodological gap by offering a low-cost, flexible framework for assessing solar potential across diverse urban contexts and building typologies, while significantly simplifying the modeling process. Full article

Musa haekkinenii is a compact wild banana species with emerging value in ornamental horticulture, yet its adaptive responses to environmental factors remain underexplored. This study investigated the morpho-physiological and anatomical responses of M. haekkinenii to contrasting light regimes and irrigation water qualities to identify optimal cultivation conditions. A 210-day factorial experiment was conducted under subtropical greenhouse conditions using a split-plot design, with light intensity (full sun vs. shade) and irrigation water quality (reverse osmosis vs. well water) as treatment factors. Plants grown under shaded conditions and irrigated with reverse osmosis water exhibited significant increases in plant height, pseudostem diameter, leaf number, and sucker production, alongside enhanced pigment accumulation and photosynthetic performance. In contrast, full-sun plants irrigated with well water showed reduced growth, lower photosynthetic efficiency, and increased substrate salinity, indicating additive effects of light and osmotic stress. Leaf anatomical analysis revealed greater stomatal size and density under shade, particularly when combined with high-quality irrigation. Multivariate analysis further supported the association of favorable trait expression with shaded conditions and reverse osmosis water. These findings highlight the importance of microenvironmental management in enhancing the physiological stability and ornamental quality of M. haekkinenii, supporting its potential application in sustainable urban landscaping. Full article

Food waste (FW) presents a critical issue, representing an environmental liability and a largely untapped resource. Its heterogeneity and low valorization rate among main-stream alternative treatments challenge its integration into economically and environmentally sustainable bioprocesses. We explore biorefineries as a solution that can address the complexity of urban food waste through biological strategies capable of converting food waste into valuable products. Exploring the current landscape of FW biorefineries, this study focused on the interplay between feedstock heterogeneity, pretreatment strategies, microbial dynamics, and integration potential. We propose a framework distinguishing between robust fermentations that can use minimally treated FW and tailored fermentations, which require refined media pretreatment and/or supplementation to yield higher-value compounds. Drawing on recent techno-economic and life cycle assessments, this article evaluates process viability and environmental impacts across multiple scales, reinforcing the need for robust analysis to support decision-making. Real-world initiatives and policy frameworks are analyzed to contextualize technological advances within regulatory and infrastructural realities. By linking practical constraints to biochemical and operational strategies, this work outlines how food waste biorefineries can contribute meaningfully to circular economy goals. Instead of treating FW as an intractable problem, it is seen as a versatile feedstock that demands integration, investment, and adaptive process design. Full article

Mobile commerce has transformed the retail landscape, yet the determinants of impulse buying behavior in this environment remain understudied, particularly in emerging markets. This research investigates the factors influencing impulse buying in mobile commerce in Chile using the Stimulus–Organism–Response framework. A quantitative cross-sectional study collected data from 451 mobile shoppers via an online survey. Structural equation modeling with PLS-SEM revealed that eight of the thirteen hypothesized relationships were significant. Mobile application factors (visual appeal and portability) positively influenced hedonic and utilitarian values. Among personal factors, economic well-being, family influence, and credit card use directly impacted impulse buying, while time availability did not. Hedonic value strongly influenced impulse buying behavior, but utilitarian value showed no significant effect. Contrary to expectations, the COVID-19 pandemic negatively impacted impulse buying. These findings extend theoretical understanding of mobile impulse buying determinants and provide practical insights for mobile commerce developers and marketers to enhance their platforms and strategies. Full article

Seasonally dry tropical forests (SDTFs) are shaped by strong climatic and edaphic constraints, including pronounced rainfall seasonality, extended dry periods, and shallow karst soils with limited water retention. Understanding how tree species respond to these pressures is crucial for predicting ecosystem resilience under climate change. In the Yucatán Peninsula, we characterized sixteen tree species along a spatial and seasonal precipitation gradient, quantifying wood density, predawn and midday water potential, saturated and relative water content, and specific leaf area. Across sites, diameter classes, and seasons, we measured ≈4 individuals per species (n = 319), ensuring replication despite natural heterogeneity. Using a principal component analysis (PCA) based on individual-level data collected during the dry season, we identified five functional groups spanning a continuum from conservative hard-wood species, with high hydraulic safety and access to deep water sources, to acquisitive light-wood species that rely on stem water storage and drought avoidance. Intermediate-density species diverged into subgroups that employed contrasting strategies such as anisohydric tolerance, high leaf area efficiency, or strict stomatal regulation to maintain performance during the dry season. Functional traits were strongly associated with precipitation regimes, with wood density emerging as a key predictor of water storage capacity and specific leaf area responding plastically to spatial and seasonal variability. These findings refine functional group classifications in heterogeneous karst landscapes and highlight the value of trait-based approaches for predicting drought resilience and informing restoration strategies under climate change. Full article

The aim of this study is to determine the spatial distribution of geochemical anomalies of selected potential toxic elements in the soils of the river basins in the Northeastern Caucasus—specifically the Ulluchay, Sulak, and Sunzha Rivers. A concentration of 25 chemical elements was measured using inductively coupled plasma mass spectrometry (ICP-MS). Petrogenic elements commonly found in the Earth’s crust (Al, Na, Ca, Fe, Mg) showed high concentrations (Na up to 306,600.70 mg/kg). Conversely, concentrations of Ag, Cd, Sn, Sb, and Te at many sampling sites were extremely low, falling below the detection limits of analytical instruments. The geochemical indicators Cf (contamination factor) and Igeo (geoaccumulation index) indicate that the regional characteristics of the territory, such as lithological conditions, hydrochemical schedules, and the history of geological development of the territory, affect the concentration of elements. Anomalous concentrations were found for seven elements (Ba, Na, Zn, Ag, Li, Sc, As), whereas no anomalies were identified for Be, Mg, Al, Mn, Fe, Co, Ni, Cu, Pb, Te, and Cs. For the most part (8 of 10), the sampling sites with anomalous chemical element content are located in the basin of the Sunzha River. Two sites with anomalous chemical element content have been identified in the Sulak River Basin. Anomalous values in the Sulak River Basin are noted for two chemical elements—Ba and Na. Natural features such as geological structure, parent rock composition, vertical climatic zonation, and landscape diversity play a major role in forming geochemical anomalies. The role of anthropogenic factors increases in localized areas near settlements, industrial facilities, and roads. The spatial distribution of geochemical anomalies must be considered in agricultural management, the use of water sources for drinking supply, the development of tourist routes, and comprehensive spatial planning. Full article

In Hong Kong, the interaction between traditional values and modern influences creates a unique cultural landscape that influences family dynamics, intergenerational communication, and adolescent mental health. This study aimed to fill critical research gaps by exploring the relationship between authoritative and authoritarian parenting styles within this hybrid cultural context. Parenting style scores were based on the PSDQ-26 questionnaires completed by both parents of 2325 students. These students also provided demographic data used in the analysis (1013 girls, M_age = 13.35, SD = 1.22). The data analysis examined the correlations between parenting styles and variations across gender and age groups. Contrary to patterns observed in Western contexts, the results indicated no significant correlation between authoritative and authoritarian parenting styles (r = 0.02, p > 0.05), suggesting a complex coexistence influenced by Hong Kong’s hybrid sociocultural context. Notably, the study revealed gender-based differences: boys’ parents reported higher levels of democratic participation and reasoning, reflecting authoritative parenting, while also showing greater use of physical coercion and punitive discipline, indicative of authoritarian parenting. Authoritative parenting, but not authoritarian parenting, showed a decline as children matured. By investigating these dynamics, the study not only addresses a significant gap in the literature but also enhances the understanding of how cultural and developmental factors shape parenting practices. These insights are crucial for developing culturally adapted parenting education materials and informing interventions that support child development in diverse cultural settings. Full article

Anthropogenic ponds have the potential to shape the post-industrial landscape and mitigate the effects of climate change, particularly in urban heat island-threatened areas. However, decisions regarding their inclusion in blue–green infrastructure networks require balancing costs and benefits while considering potential pollution risks. The objectives of this study are: (i) to develop an efficient decision-making framework based on standard aquatic science tools; (ii) to apply this framework to a specific artificial pond in the Upper Silesian Industrial Region, Poland, in order to optimize actions based on resources, advantages, limitations, and informativeness of the data. Eighteen methods, grouped into five categories, including historical document analyses, hydroacoustic and modeling methods, multiparametric water quality measurements, and ecotoxicological tests, were used. Optimization-focused analysis indicated that investigating historical documents should precede further testing, as it enables decision-makers to select the most effective methods to assess the pond’s value for blue–green infrastructure. In this case, the tests based on metal pollution, bathymetry, and biodiversity appeared sufficient. The presented approach offers a straightforward screening method for assessing reservoirs in post-industrial areas. Full article

Tree rings, tree needles, and moss can be used as biomonitors to evaluate atmospheric pollutant concentrations and deposition patterns spanning different timescales. This study compares output from air quality modeling and measurements to patterns observed using a combination of sulfur concentration and isotope composition in moss (using moss bags and controls) as biomonitors in a region of southern Alberta, Canada influenced by industrial emissions. Tree rings allow comparisons of historical to current sulfur deposition patterns. Moss, which integrates atmospheric nutrients during growth, allows for concurrent comparisons. The contrast of inorganic and organic sulfur within conifer tree needles provides a measure of pollutant uptake over their short lifespans. Sulfur uptake within biomonitors in a southern Alberta ecosystem allow assessment of the presence (in moss, needles) and effects (on conifer growth) of atmospheric sulfur deposition from industrial emissions. These data were examined relative to California Puff (CALPuff) model projections and traditional active and passive air quality sampling. Patterns in sulfur isotope abundance (δ³⁴S) from moss bags placed throughout the eastern slopes of the southern Alberta foothills of the Rocky Mountains implicate local industry as the dominant atmospheric sulfur source over winter, with the tissues of conifers (needles and cores) and moss decreasing with distance from industrial emissions. This was consistent with apportionment calculations based on active and passive sampling, which also showed a surprising trend of sulfur deposition upwind of the industrial stack in the mountains to the west. δ³⁴S values for pine needles and tree rings were consistent with greater sulfur stress and reductions in tree growth associated with increased industrial sulfur concentrations and deposition. We conclude that plant biomonitors are effective short-term (tree needles and moss) and long-term (tree cores) indicators of sulfur pollution in a complex, mountainous landscape. Full article

Modern cybersecurity threats continue to evolve in both complexity and prevalence, demanding advanced solutions for intrusion detection. Traditional AI-based detection systems face significant challenges in model selection, as performance varies considerably across different network environments and attack scenarios. To overcome these limitations, we propose a comprehensive ensemble learning approach that systematically integrates feature selection, model optimization, and rigorous evaluation components. Our framework evaluates fourteen distinct machine learning approaches, ranging from individual classifiers to sophisticated ensemble methods including bagging, boosting, and hybrid stacking/blending architectures. These techniques are applied to multiple base algorithms such as neural networks and tree-based models. Extensive testing was conducted on two complementary benchmark datasets (RoEduNet-SIMARGL2021 and CICIDS-2017) to assess detection capabilities across varied threat landscapes. Our experimental results revealed several key findings. Ensemble techniques universally surpass standalone models in detection accuracy, with random forest achieving the best performance on RoEduNet-SIMARGL2021, while the blending and bagging methods approach yielded perfect scores (F1 > 0.996) on CICIDS-2017. Feature selection via information gain demonstrated particular value, reducing model training times by 94% while maintaining detection accuracy. Among ensemble methods, XGBoost showed exceptional computational efficiency, whereas stacking and blending architectures delivered maximum accuracy at the expense of greater resource requirements. This research provides practical guidance for security professionals in model selection based on specific operational constraints and threat profiles. To support community advancement, we have made our complete framework publicly available, facilitating reproducibility and future innovation in intrusion detection systems. Full article

The growing complexity of distribution-level virtual power plants (VPPs) demands a rethinking of how flexible demand is modeled, aggregated, and dispatched under uncertainty. Traditional optimization frameworks often rely on deterministic or homogeneous assumptions about end-user behavior, thereby overestimating controllability and underestimating risk. In this paper, we propose a behavior-aware, two-stage stochastic dispatch framework for VPPs that explicitly models heterogeneous user participation via integrated behavioral economics and social interaction structures. At the behavioral layer, user responses to demand response (DR) incentives are captured using a Prospect Theory-based utility function, parameterized by loss aversion, nonlinear gain perception, and subjective probability weighting. In parallel, social influence dynamics are modeled using a peer interaction network that modulates individual participation probabilities through local contagion effects. These two mechanisms are combined to produce a high-dimensional, time-varying participation map across user classes, including residential, commercial, and industrial actors. This probabilistic behavioral landscape is embedded within a scenario-based two-stage stochastic optimization model. The first stage determines pre-committed dispatch quantities across flexible loads, electric vehicles, and distributed storage systems, while the second stage executes real-time recourse based on realized participation trajectories. The dispatch model includes physical constraints (e.g., energy balance, network limits), behavioral fatigue, and the intertemporal coupling of flexible resources. A scenario reduction technique and the Conditional Value-at-Risk (CVaR) metric are used to ensure computational tractability and robustness against extreme behavior deviations. Full article

Intangible heritage comprises a wealth of knowledge, crafts, and skills that are passed down through the generations, embodied in our cultural practices. Many of these intertwine with landscape and environment; so, they are sensitive to climate change. While there have been studies of the impact of climate change on intangible heritage, these typically use heritage as a lens to examine climate impacts. There are few assessments of specific climate processes that threaten heritage. A climate-based approach allows researchers to identify mechanisms of change and quantify past impacts and project these into the future to give a sense of management options. We explore the threats to UNESCO domains of intangible heritage using weather and climate data from a range of sources to assess threats demonstrating the importance of data-informed approaches and show that timing of season and frequency of extreme events are important in climate-based assessments. These play out over different spatial and temporal scales that reveal elements of sensitivity to environmental change. The management response to the climate threat seems in need of a rights-based approach to empower those who own, safeguard, or practice the heritage. Research to enhance conservation should be translated into a form that speaks to local values and social structures. Full article

Cellular organisms store heritable information in two forms, genetic and epigenetic, the latter being largely dependent on cytosine methylation (5mC). Chargaff’s Second Parity Rule (CSPR) describes the nucleotide composition of cellular genomes in terms of intra-strand DNA symmetry. However, it remains unknown whether DNA methylation patterns display intra-strand DNA symmetry. Computational analysis was conducted of the DNA methylation patterns observed in human cell lines and in tissue samples from healthy donors. Analysis of 5mC marks in mutually reverse-complementary pairs of short oligomers, containing CpG dinucleotide in the middle, revealed deviations from CSPR and methylation asymmetry that can be observed for two non-overlapping mirror groups defined by CpG methylation values. Deviations from CSPR, together with combinatorial probabilities of pattern distributions and computer simulations, highlight the non-random nature of methylation processes and enabled us to identify specific cell types as outliers. Further analysis revealed a compensatory methylation asymmetry that reduces deviations from intra-strand symmetry and implies the existence of strand-specific methylation during cell differentiation. Among six pairs of reverse-complementary tetranucleotides, four pairs with specific sequence motifs display pronounced methylation asymmetry. This mirror asymmetry may be associated with chromosome folding and the formation of a complex three-dimensional landscape. Full article