Search Results (185,207)

Digital twin (DT) technology has expanded far beyond its industrial origins, increasingly finding application across environmental and territorial domains. This review provides a structured mapping of DT deployments at environmental and territorial scales over the period 2020–2025, examining 117 peer-reviewed publications (109 applied studies and 8 review articles) through a structured 16-parameter classification framework. The review traces three major conceptual shifts in the DT paradigm: from industrial assets to living entities, from discrete systems to Earth-scale representations, and from closed deterministic models to ecological and systemic frameworks, as reflected in the emergence of ecological digital twins (EcoDTs), environmental digital twins (EDTs), and territorial digital twin (TDT) definitions. The results reveal a clear growth trajectory in DT applications across themes, with urban systems as the most consolidated application domain, and progressive diversification into marine, coastal, forestry, river/lake, and Earth system applications from 2022 onward. Institutional actors dominate production in this space, aligned with European flagship initiatives such as Destination Earth (DestinE) and the European Digital Twin of the Ocean (EDITO). The findings position and expand the notion of territorial digital twins as an evolving paradigm, underscoring both the momentum generated by EU digital and environmental policy and the need for integrated tools to answer and respond to key environmental challenges. Full article

This study examines motivational and capability barriers to internet non-adoption in Thailand’s near-saturated digital economy. Using the 2025 Q4 ICT Household Survey conducted by Thailand’s National Statistical Office, the analysis focuses on 20,633 adult non-adopters who report either motivational or capability-related barriers. The dependent variable distinguishes capability non-adoption, defined as lack of skill or awareness, from motivational non-adoption, defined as lack of perceived need or privacy/security concerns. Weighted logistic regression with normalised population weights, PSU-clustered robust standard errors, and average marginal effects is used to estimate associations between household ICT access, age, education, employment, smartphone access, and barrier type. Motivational barriers account for 56.2% of the two-category non-adopter population and capability barriers for 43.8%. Although motivational reasons are the more common, household ICT access is positively—if modestly—associated with capability rather than motivational barriers (average marginal effect +1.7 percentage points): capability-constrained non-adopters are concentrated in connected households, the compositional signature predicted by the second-level digital divide. Age does not significantly moderate this association. Among older non-adopters, education, employment, and smartphone access are negatively associated with capability barriers, while household ICT access is not. The findings suggest that in post-access digital economies, household connectivity is insufficient for digital market inclusion; individual-level skills and device access become central to expanding effective digital market reach. Full article

Thorium (Th) is increasingly considered a promising fertile material for sustainable nuclear energy—which is not fissile itself, but convertible to fissile ²³³U—particularly as a by-product of rare earth element (REE) processing. This study develops a parametric techno-economic assessment (TEA) framework synthesizing published data from China, Russia, the USA, India, and Europe to establish the methodological foundation for evaluating thorium recovery economics from monazite ores and REE tailings under Central Asian conditions. Monazite typically contains 4–12% ThO₂, while tailings contain 0.1–3%, making secondary resources attractive for future recovery strategies. Particular attention is given to integration with uranium tailings and the application of advanced materials such as nanocomposite sorbents and carbon-based electrodes. Reported production costs of ThO₂ range from 50 to 500 USD/kg depending on process scale, feedstock quality, and co-production of REEs. The reviewed studies consistently show that coupling thorium recovery with REE processing improves economic feasibility. Modern approaches, including hybrid technologies and electrosorption systems, may reduce operational costs and improve process efficiency. Despite challenges related to capital investment, market uncertainty, and radioactive waste management, thorium continues to attract growing interest as a potential component of future nuclear fuel cycles and advanced reactor systems, including small modular reactors. To the best of the authors’ knowledge, this is the first parametric TEA framework structured around Central Asian conditions, combining literature-derived regional data, scenario-based process economics, and Monte Carlo sensitivity analysis within a single discounted cash flow structure. Full article

Limited by the computational performance limits of the CPU(Central Processing Unit), the traditional Spark architecture struggles to achieve high throughput and low latency under the dual pressure of a large data scale and real-time requirements in centralized control systems. This work uses a publicly available CNC(Computer Numerical Control) milling dataset as a functional validation proxy for time-series data processing, then extends validation to a large-scale synthetic power transmission grid dataset. Furthermore, Spark-GPU(Graphics Processing Unit) collaboration suffers from load balancing failure due to heterogeneous resource scheduling and communication overhead, thus failing to unleash its performance potential. This paper proposes a Spark-GPU fusion acceleration technology path. The path consists of three key components: first, it integrates the RAPIDS accelerator; second, it designs a GPU-aware partitioning and task co-scheduling strategy; and third, it optimizes the zero-copy data path. Together, these components realize an integrated collaboration of heterogeneous resources. Validation on real-world datasets yields the following results. In real-time aggregation scenarios, the proposed solution improves throughput by a factor of 3.7 over the pure CPU baseline and reduces end-to-end latency by 62%. Compared with the basic GPU solution, GPU utilization rises from 51.7% to 72.3%, representing a relative improvement of 39.8%. Furthermore, the solution meets industrial-grade high availability requirements. This research significantly improves the processing throughput and reduces end-to-end latency in typical centralized control scenarios, thus providing a feasible technical route for demanding concurrent centralized control scenarios such as electric power industry manufacturing with high real-time demands. Full article

This study investigates the complex and nonlinear interaction between the dual circulation paradigm and high-quality full employment. Moving beyond the limitations of conventional static partial equilibrium frameworks, the analysis conceptualizes this relationship as a system of three interrelated feedback loops. Drawing on system dynamics (SD) theory, a set of nonlinear differential equations is developed, with model parameters calibrated using macroeconomic data from 2010 to 2025. The simulation results yield three main findings. First, international trade, cross-border investment, and technological exchange jointly form a core reinforcing feedback loop that underpins the mutually beneficial interaction between domestic and international circulations. Second, the integrated development of education, technology, and human capital emerges as a critical state variable for overcoming the persistent trade-off between employment quantity and quality. Third, the interplay between horizontal market expansion and vertical technological advancement constitutes a dual driving mechanism that facilitates the system’s transition toward a higher-level equilibrium, with multi-factor interactions generating pronounced nonlinear multiplier effects. Overall, the study provides a quantitative basis for designing adaptive and targeted employment policies within the dual circulation framework. Full article

Offshore wind farms are increasingly and rapidly expanding due to their ability to harness strong and consistent wind energy resources. Large offshore wind farms are connected to mainland grids through High-Voltage Direct Current (HVDC) technology. However, offshore wind farms can often experience disturbances related to sudden wind changes, voltage drops/dips, faults related to converter switching, and unbalanced grid conditions which affect both the HVDC operation and wind turbine output. As a result, there is a growing need for more advanced and reliable modeling and monitoring tools. Moreover, traditional proportional-integral (PI) controllers are widely applied in wind turbines and HVDC systems due to their simple structure, easy implementation, and reliability. However, PI controllers perform poorly under non-linear and abnormal/fast-changing conditions, especially during sudden drops in wind power and grid faults. With this background, this paper first develops a digital twin model of an offshore wind farm that enables remote operation and monitoring of individual wind turbines. Also, an artificial intelligence (AI)-based controller, namely a fuzzy logic controller (FLC), is proposed to maintain transient stability of a full digital twin-based offshore wind farm connected to the HVDC grid under fault conditions. The effectiveness of the proposed FLC is demonstrated by considering a digital twin-enabled 700 MW offshore wind farm. The performance of the proposed FLC has been compared with that of the PI controller. Simulations performed by the MATLAB/Simulink software show that during the moderate voltage dip at 15 s, the PI controller experienced a 29.8% power reduction with a recovery time of approximately 9 s, whereas the FLC reduced the power drop to 23.1% and recovered within 6 s. During the severe converter disturbance at 15 s, the PI controller recorded a 36.9% power reduction compared to 23.4% for the FLC. Similarly, during the short-duration turbulence at 15 s, the PI controller exhibited a 36.73% power drop and recovered in approximately 7 s, while the FLC limited the power reduction to 19.17% and recovered within 5s. Overall, the FLC provided improved voltage stability, faster recovery, reduced oscillations, and superior fault ride-through capability compared with the conventional PI controller, demonstrating its effectiveness for digital twin-enabled offshore wind farm application. Full article

The development of digital learning technologies has introduced innovative tools to enhance science and chemistry education, including PhET simulations. This study aims to evaluate the effectiveness of PhET simulations on students’ learning outcomes through a systematic literature review following the PRISMA 2020 guidelines. A systematic search of Scopus and Crossref databases was conducted (last search: January 2026) using predefined keywords. Eligible studies were empirical research published between 2020 and 2026 that investigated PhET simulations in science-related education and reported learning outcomes, while non-empirical studies and non-Scopus-indexed articles were excluded. Risk of bias was assessed using an adapted Joanna Briggs Institute critical appraisal tool. Due to heterogeneity in study designs and outcome measures, the results were synthesized using a narrative approach. A total of 14 studies across elementary to higher education levels were included. The findings indicate that PhET simulations consistently improve learning outcomes, particularly academic achievement and conceptual understanding, with effects generally favoring simulation-based instruction over traditional methods. However, higher-order skills and affective outcomes such as motivation and attitude remain less frequently investigated. The evidence is limited by variability in study designs, incomplete reporting of non-cognitive outcomes, and the absence of quantitative synthesis. Overall, PhET simulations demonstrate strong potential as an effective interactive learning medium, although their impact depends on instructional design, teacher facilitation, and technological accessibility. Full article

Acid mine drainage (AMD) pollution from closed coal mines in karst regions represents a major environmental challenge in the global mining industry. The complexity of hydrogeological conditions in such regions leads to significant challenges in both predictability and controllability of pollution. Taking the Yudong River Basin in Guizhou Province, Southwest China, as the study area, and based on six years (2017–2023) of systematic remediation practices and monitoring data, this study systematically evaluates the effectiveness and applicable conditions of three types of treatment technologies: centralized treatment stations, source control combined with end-of-pipe treatment, and water-sealing ecological plugging. On this basis, governance models applicable to karst regions are distilled. The results show that after six years of remediation, the number of pollution points in the Yudong River Basin decreased from 27 to 12. At the outflow section, the total Fe reduction rate reached 88.3%, the total Mn reduction rate reached 62.3%, and the proportion of contaminated river length was reduced by 78.5%. Each of the three technologies has its own applicable conditions. Centralized treatment stations, characterized by mature technology but high operational costs, are suitable for emergency transition periods. Source control combined with end-of-pipe treatment addresses both symptoms and root causes, making it applicable to complex pollution points. Water-sealing ecological plugging, although cost-controllable, carries a risk of secondary pollution in karst-developed areas. The failure of water-sealing ecological plugging technology is mainly attributed to two mechanisms: bypass flow through karst conduits and overflow induced by water level rise. Based on the six-year remediation practice, this study proposes a source control model for karst conduits centered on the core concepts of “filling, isolating, plugging, intercepting, draining, and controlling”. The implementation process consists of four stages: detailed investigation, graded optimization, stepwise implementation, and long-term monitoring. The core innovation lies in the cross-disciplinary application of coal mine water control techniques to environmental remediation, achieving a shift from passive end-of-pipe treatment to active source control. This model can provide theoretical reference and practical guidance for karst mining areas in Southwest China and other regions with similar geological conditions. Full article

In the context of SDG 7 and SDG 13 of the 2030 Sustainable Development Agenda, a new performance indicator has started to gain momentum in scientific research: renewable energy productivity. Understanding the drivers and the challenges of green energy productivity could help add on to the classical focus of renewable energy research on infrastructure, technical and economic feasibility, and environmental and social impacts, by considering the performance indicators in this field more. Only very few studies have explored the influencing factors of renewable energy productivity. Thus, this research aims to reveal the impact of social, economic, energy, and environmental variables on green energy productivity. The methodological approach involves bibliometric analyses of the literature on green energy productivity (GEP) and panel data regression models involving 16 independent variables. The main findings indicate positive effects of green taxes, female participation in the workforce, and highly educated people on GEP, pointing out the importance of green taxation, education, and gender equality in sustainable development. On the other hand, negative relationships of green energy productivity with economic growth, traditional energy variables, and air pollution were found for the European Union’s member states over 2007 and 2023. The results suggest that the analyzed European countries based their economic growth on traditional resources, with less importance given to renewable resources and green technologies, as the share of renewable resources of GDP was also negatively correlated. While private financial resources increase green energy productivity, questions about research and development investments, urbanization, and diversity index are still debatable. Full article

This study examines how mothers raising children with disabilities in American Samoa experience the processes of seeking diagnosis, navigating special education, and advocating for services within an insular rural context. American Samoa, an unincorporated U.S. territory located 2600 miles from Hawaiʻi with a population under 50,000, represents a case of what we term insular rurality—a condition in which the structural disadvantages of rurality are intensified by oceanic isolation, territorial governance, and colonial history. Data were collected through three focus groups with fifteen mothers whose children hold a range of disability diagnoses, with a card sort activity at the outset of each session serving as an idiographic anchor to protect individual voice within the group format. Analysis followed Interpretative Phenomenological Analysis adapted for focus groups (IPA-FG), proceeding from line-by-line exploratory noting through Personal Experiential Themes and Group Experiential Themes within each focus group case to cross-case convergence and divergence analysis, interpreted through the Fonofale model of Pacific wellness. Findings reveal two overarching themes: systemic invalidation, in which mothers encountered deficit-based assumptions, stagnant educational goals, and institutional disengagement; and parent peer support as the primary infrastructure, in which mothers became de facto experts, built community-driven solutions, and envisioned more inclusive futures. Technology emerged as a contradictory force—valuable for parent learning but largely ineffective for children’s remote therapy. These findings suggest how workforce shortages and geographic isolation create conditions in which maternal advocacy becomes a systems-level necessity rather than a personal choice. Implications for rural education policy, IDEA implementation in U.S. territories, and culturally grounded family support are discussed. Full article

Lithium has become one of the key raw materials for the energy transition due to the central role of lithium-ion batteries in electromobility, energy storage, and the integration of renewable energy sources. However, the rapid increase in demand reveals growing environmental, social, geopolitical, and market tensions. The aim of the paper is a critical synthesis of global lithium utilization from the perspective of challenges, technological innovations, and integrative strategies supporting a more sustainable material–energy system. A broad, systematic literature review covering the entire value chain was applied: resources, extraction, processing, end-use applications, second life of batteries, recycling, and governance. The analysis shows that the strategic importance of lithium arises from the increasing demand pressure from electric vehicles and stationary storage, while the sustainability of the current model is constrained by supply concentration, uneven control over downstream stages, the water–carbon footprint of extraction and processing, social conflicts, and incomplete integration of secondary loops. At the same time, innovations such as direct lithium extraction (DLE), recovery from geothermal brines, design for recycling, second life, and battery passports can partially alleviate these tensions, but they do not eliminate the need for primary supply in the short term. The conclusion of the work is that sustainable global lithium utilization requires simultaneous diversification of sources, development of circular value chains, and multi-level governance integrating resource security, environmental efficiency, and social legitimacy. Full article

We review the recent developments on the decoupling limit zooming in on a BPS string state in heterotic string theory. In this limit, the target-space geometry lacks any ten-dimensional metric description and acquires various non-Lorentzian features. We present the supersymmetric worldsheet sigma model in the decoupling limit. This sigma model describes the heterotic version of non-relativistic string theory, whose second quantization is related to heterotic matrix string theory. We introduce bookkeeping to separate the Yang–Mills gauge and gravitational anomaly analyses. We review the Yang–Mills gauge anomaly analysis in the sigma models before and after the decoupling limit is performed and provide further details on how the quantum calculation commutes with the decoupling limit. We comment on how the analogous calculation can be performed for the gravitational anomaly. This contribution is based on a talk at the University of Science and Technology of China. Full article

This review analyses and logically structures modern intelligent sensor technologies in the context of animal husbandry, feed production, and veterinary medicine. The main research discussed in the article focuses on machine learning based on modern neural network models, computer vision, and sensor systems that are transforming the methods for assessing the health, behavior, and nutrition of farm animals. The first part examines modern approaches to quality control and optimization of mineral and vitamin premixes, including visual inspection using visual sensors and neural networks. Key roles are played by precise dosing, component stability (minerals, vitamins), and the transition to more bioefficient organic forms of micronutrients to reduce environmental impact. Improvements in feed and premix production are analyzed, including automation, energy management, and the use of machine learning for non-destructive quality control, defect detection, mixing homogeneity assessment, and vitamin stability prediction. The second part analyzes methods for animal location and behavior detection. This article presents computer vision-based systems, including modifications of YOLO, for automatically tracking and classifying key behavioral patterns (lying down, standing, feeding, and aggression) in cattle and pigs, even in crowded conditions. It also discusses the use of ultra-wideband (UWB) systems and accelerometers combined with machine learning for high-precision positioning and detection of specific behavioral anomalies, such as lameness and playfulness. The third section focuses on the application of machine learning in veterinary diagnostics, including the automated interpretation of medical images (X-ray, ultrasound, and MRI) as sensor data streams for the diagnosis of cardiovascular, oncological, and orthopedic diseases in farm and small animals. Furthermore, the article examines the use of machine learning models for proactive disease diagnosis in farm animals and poultry based on multimodal data and image analysis. Considerable attention is given to methods and tools for radiometric diagnosis of animal diseases at an early stage using microwave sensors, as well as laser therapy and surgery in veterinary medicine. The review concludes that the integration of intelligent systems enables a transition to data-driven livestock management, significantly improving animal welfare and, consequently, the efficiency and sustainability of agricultural production. Full article

Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative technology for resolving cellular heterogeneity and deciphering gene regulatory networks in complex tissues. Despite challenges such as incomplete genome annotation, technical variability across platforms, and limitations in robust cell-type annotation, scRNA-seq has substantially advanced our understanding of the developmental processes, physiological regulation, and disease responses in pigs, an economically and biomedically important species, thereby providing insights into traits of agricultural and translational relevance. By profiling transcriptomes at the single-cell resolution, scRNA-seq enables the identification of rare cell populations, dynamic cellular states, and lineage trajectories that are critical for reproduction, growth, immunity, and metabolic homeostasis. Recent porcine scRNA-seq studies have generated high-resolution cellular atlases spanning embryos, reproductive organs, immune tissues, skeletal muscle, and the gastrointestinal tract, revealing cell-type-specific regulatory mechanisms associated with reproductive performance, muscle accretion, adipogenesis, immune competence, and intestinal functionality. This review summarizes the fundamental principles and analytical strategies of scRNA-seq, highlights its major applications in porcine biology and production, and discusses current challenges as well as future perspectives for integrating single-cell technologies into livestock science. Full article

Driven by the high-end furniture industry’s demand for skin-tactile decorative boards, UV inkjet printing shows potential for wood-based surface finishing. Using primer-treated inkjet-printed melamine-faced panels, this study compared traditional UV varnish coatings with different thicknesses and UV curing intensities and 254 nm UV excimer-cured coatings with different radiant energies. Varnish thickness significantly affected surface roughness, 20° gloss, 85° gloss, and color difference, indicating a trade-off between matte tactile appearance and color fidelity. Thinner varnish coatings exhibited higher roughness and lower gloss but larger color differences, whereas thicker coatings better preserved color fidelity but resulted in higher gloss. For the UV excimer-cured system, one-way ANOVA showed significant treatment effects on acrylate conversion, water contact angle, 85° gloss, surface roughness, and abrasion mass loss. The coating prepared at an excimer radiant energy of 827.9 mJ/cm² showed the lowest 85° gloss of 5.28 GU and a pencil hardness of 3H, but also exhibited the highest abrasion mass loss in the short-cycle abrasion screening test. For both coating systems, three independently prepared specimens were tested for each processing condition. The UV varnish system was analyzed using two-way ANOVA, whereas the UV excimer-cured system was analyzed using one-way ANOVA. Friedman tests of sensory evaluation data showed significant differences among the eight selected samples for fineness, smoothness, and elasticity, with the excimer-cured coatings generally receiving higher fineness and smoothness scores than the UV varnish coatings. These results indicate that 254 nm UV excimer curing is a promising route for producing low-gloss, micro-wrinkle-induced skin-tactile surfaces on inkjet-printed melamine-faced panels, although optimization should balance tactile quality, gloss reduction, and abrasion resistance. Full article