Search Results (478)

Carbon flow tracking and spatial pattern optimization at the scale of urban functional zones are key scientific challenges in achieving carbon neutrality. However, due to the complexity of carbon metabolism processes within urban functional zones, related studies remain limited. To address these scientific challenges, this study, based on the “source–sink–flow” ecosystem services framework, develops an integrated analytical approach at the scale of urban functional zones. The carbon balance is quantified using the CASA model in combination with multi-source data. A network model is employed to trace carbon flow pathways, identify critical nodes and interruption points, and optimize the urban spatial pattern through a low-carbon land use structure model. The research results indicate that the overall carbon balance in Hangzhou exhibits a spatial pattern of “deficit in the center and surplus in the periphery.” The main urban area shows a significant carbon deficit and relatively poor connectivity in the carbon flow network. Carbon sequestration services primarily flow from peripheral areas (such as Fuyang and Yuhang) with green spaces and agricultural functional zones toward high-emission residential–commercial and commercial–public functional zones in the central area. However, due to the interruption of multiple carbon flow paths, the overall carbon flow transmission capacity is significantly constrained. Through spatial optimization, some carbon deficit nodes were successfully converted into carbon surplus nodes, and disrupted carbon flow edges were repaired, particularly in the main urban area, where 369 carbon flow edges were restored, resulting in a significant improvement in the overall transmission efficiency of the carbon flow network. The carbon flow visualization and spatial optimization methods proposed in this paper provide a new perspective for urban carbon metabolism analysis and offer theoretical support for low-carbon city planning practices. Full article

Localization has emerged as a critical problem over the past decades, with diverse techniques developed to address robot and mobile localization challenges across varied domains. However, existing localization methods still fall short of achieving the precision needed for certain high-demand applications. The proposed algorithm is designed to enhance localization accuracy by integrating mathematical modeling with the Crow Search Algorithm (CSA). The objective is to identify the most probable position within a designated search space. Anchored by a network of fixed points, the search area is initially defined. A mathematical approach is then applied to reduce this area by calculating the intersections between circles centered at each anchor point. Within this reduced area, an array of candidate points are selected, and their centroid is computed to serve as an initial estimate. The modified CSA iteratively improves upon this estimate by emulating the natural behavior of crows, updating its variables to converge on the optimal position. Experimental evaluations, conducted on both real and simulated datasets, demonstrate that the proposed algorithm leads to a better localization accuracy than existing methods. The proposed methodology achieves a significant accuracy improvement with an accuracy of 98%. These results confirm the effectiveness of our approach for applications that require high precision with minimal infrastructure and low computational complexity. Full article

A broadband, efficient monolithic microwave integrated circuit power amplifier (MMIC PA) in OMMIC’s 0.1 μm GaN-on-Si technology for 5G millimeter-wave communication is presented. This study concentrates on the output matching design, which has an important influence on the PA’s performance. A compact one-order synthesized transformer network (STN) is adopted to match the 50 Ω load to the extracted large-signal output model of the transistor. A dual-objective strategy is developed for parameter optimization, incorporating the impedance transformation trajectory inside the predefined optimal impedance domain (OID) that satisfies the required specifications, with approximation to selected optimal load impedances. By introducing a custom adjustment factor β into the error function, coupled with an automated iterative tuning process based on S-parameter simulations, desired broadband matching results can be rapidly achieved. The proposed two-stage PA occupies a small chip area of only 1.23 mm² and demonstrates good frequency consistency over the 24–31 GHz band. Continuous-wave characterization shows a flat small-signal gain of 19.7 ± 0.5 dB; both the output power (P_out) and the power-added efficiency (PAE) at the 4 dB compression point remain smooth, ranging from 32.3 to 32.7 dBm and 35.5% to 37.8%, respectively. The peak PAE reaches up to nearly 40% at the center frequency. Full article

This study delivers a rigorous and in-depth bibliometric examination of 693 scholarly publications addressing the intersection of metaverse technologies and banking, retrieved from the Web of Science Core Collection. Through advanced scientometric tools, including VOSviewer and Bibliometrix, the research systematically unpacks the evolving intellectual and thematic contours of this interdisciplinary frontier. The co-occurrence analysis of keywords reveals a landscape shaped by seven core thematic clusters, encompassing immersive user environments, digital infrastructure, experiential design, and ethical considerations. Factorial analysis uncovers a marked bifurcation between experience-driven narratives and technology-centric frameworks, with integrative concepts such as technology, information, and consumption serving as conceptual bridges. Network visualizations of authorship patterns point to the emergence of high-density collaboration clusters, particularly centered around influential contributors such as Dwivedi and Ooi, while regional distribution patterns indicate a tri-continental dominance led by Asia, North America, and Western Europe. Temporal analysis identifies a significant surge in academic interest beginning in 2022, aligning with increased institutional and commercial experimentation in virtual financial platforms. Our findings argue that the incorporation of metaverse paradigms into banking is not merely a technological shift but a systemic transformation in progress—one that blurs the boundaries between speculative innovation and tangible implementation. This work contributes foundational insights for future inquiry into digital finance systems, algorithmic governance, trust architecture, and the wider socio-economic consequences of banking in virtualized environments. Whether a genuine leap toward financial evolution or a sophisticated illusion, the metaverse in banking must now be treated as a systemic phenomenon worthy of serious scrutiny. Full article

As the cradle of Jiangnan culture, Suzhou is home to a dense concentration of historical architectural heritage that is currently facing existential threats from rapid urbanization. This study aims to develop a spatial heritage corridor network for conservation and sustainable utilization. Using kernel density estimation, this study identifies 15 kernel density groups, along with the Analytic Hierarchy Process (AHP), to pinpoint clusters of historical architectural heritage and assess the involved resistance factors. Current Effective Conductance (CEC) theory is further applied to model spatial flow relationships among heritage nodes, leading to the delineation of 27 heritage corridors and revealing a spatial structure characterized by one primary core, one secondary core, and multiple peripheral zones. Based on 15 source points, six cultural relics-themed routes are proposed—three land-based and three waterfront routes—connecting historical sites, towns, and ecological areas. The study further recommends a resource management strategy centered on departmental collaboration, digital integration, and community co-governance. By integrating historical architectural types, settlement forms, and ecological patterns, the research builds a multi-scale narrative and experience system that addresses fragmentation while improving coordination and sustainability. This framework delivers practical advice on heritage conservation and cultural tourism development in Suzhou and the broader Jiangnan region. Full article

Through the energy conversion of building skins, building-integrated photovoltaic (BIPV) technology, the core carrier of the smart city energy system, encourages the conversion of buildings into energy-generating units. However, the decommissioning of the module faces the challenge of physical dismantling and financial environmental damage because of the close coupling with the building itself. As the first tranche of BIPV projects will enter the end of their life cycle, it is urgent to establish a multi-dimensional collaborative recycling mechanism that meets the characteristics of building pv systems. Based on the theory of reverse logistics network, the research focuses on optimizing the reverse logistics network during the decommissioning stage of BIPV modules, and proposes a dual-objective optimization model that considers both cost and carbon emissions for BIPV. Meanwhile, the multi-level recycling network which covers “building points-regional transfer stations-specialized distribution centers” is designed in the research, the Pareto solution set is solved by the improved NSGA-II algorithm, a “1 + 1” du-al-core construction model of distribution center and transfer station is developed, so as to minimize the total cost and life cycle carbon footprint of the logistics network. At the same time, the research also reveals the driving effect of government reward and punishment policies on the collaborative behavior of enterprise recycling, and provides methodological support for the construction of a closed-loop supply chain of “PV-building-environment” symbiosis. The study concludes that in the process of constructing smart city energy system, the systematic control of resource circulation and environmental risks through the optimization of reverse logistics network can provide technical support for the sustainable development of smart city. Full article

This study aimed to predict the potential habitats of Luciola unmunsana using a species distribution model (SDM). Luciola unmunsana is an endemic species that lives only in South Korea, and because its females do not have genus wings and are less fluid, it is difficult to collect, so research related to its distribution and restoration is relatively understudied. Therefore, this study predicted the potential habitats of Luciola unmunsana across South Korea using the single model Maximum Entropy (MaxEnt) and a multi-model ensemble model to prepare basic data necessary for a conservation and habitat restoration plan for the species. A total of 39 points of occurrence were built based on public data and prior research from the Jeonbuk Green Environment Support Center (JGESC), the Global Biodiversity Information Facility (GBIF), and the National Institute of Biological Resources (NIBR). Among the input variables, climate variables were based on the shared socioeconomic pathway (SSP) scenario-based ecological climate index, while nonclimate variables were based on topography, land cover maps, and the Enhanced Vegetation Index (EVI). The main findings of this study are summarized below. First, in predicting Luciola unmunsana potential habitats, the EVI, water network analysis, land cover, and annual precipitation (Bio12) were identified as good predictors in both models. Accordingly, areas with high vegetation activity in their forests, adjacent to water resources, and stable humidity were predicted as potential habitats. Second, by overlaying the predicted potential habitats and highly significant variables, we found that areas with high vegetation vigor within their forests, proximity to water systems, and relatively high annual precipitation, which can maintain stable humidity, are potential habitats for Luciola unmunsana. Third, literature surveys used to predict potential habitat sites, including Geumsan-gun, Chungcheongnam-do, Yeongam-gun, Jeollabuk-do, Mudeungsan Mountain, Gwangju-si, Korea, and Gijang-gun, Busan-si, Korea, confirmed the occurrence of Luciola unmunsana. This study is significant in that it is the first to develop a regional SDM for Luciola unmunsana, whose population is declining due to urbanization. In addition, by applying various environmental variables that reflect ecological characteristics, it contributes to more accurate predictions of the potential habitats of this species. The predicted results can be used as basic data for the future conservation of Luciola unmunsana and the establishment of habitat restoration strategies. Full article

Urban tourism has experienced significant growth driven by platforms such as Airbnb, yet the relationship between short-term rental (STR) location and guest mobility remains underexplored. In this study, a structured survey of STR guests in Madrid during 2024 was administered face-to-face through property managers and luggage-storage services to examine factors influencing public transport (PT) use. Responses on bus and metro usage were combined into a three-level ordinal variable and modeled using ordered logistic regression against tourist demographics, trip characteristics, and accommodation attributes, including geocoded location zones. The results indicate that first-time and international visitors are less likely to use PT at high levels, while tourists visiting more points of interest and those who rated PT importance highly when choosing accommodation are significantly more frequent users. Accommodation in the central almond or periphery correlates positively with higher PT use compared to the city center. Distances to transit stops were not significant predictors, reflecting overall network accessibility. These findings suggest that enhancing PT connectivity in peripheral areas could support the spatial dispersion of tourism benefits and improve sustainable mobility for STR guests. Full article

Ultrafine fibers from poly(3-hydroxybutyrate) (PHB) and polyvinylpyrrolidone (PVP) and their blends with different component ratios in the range of 0/100 to 100/0 wt.% were obtained, and their structure and dynamic properties were studied. The polymers were obtained via electrospinning in solution mode. The structure, morphology, and segmental dynamic behavior of the fibers were determined using optical microscopy, SEM, EPR, DSC, and IR spectroscopy. The low-temperature maximum on the DSC endotherms provided information on the state of the PVP hydrogen bond network, which made it possible to determine the enthalpies of thermal destruction of these bonds. The PHB/PVP fiber blend ratio significantly affected the structural and dynamic parameters of the system. Thus, at low concentrations of PVP (up to 9%) in the structure of ultra-fine fibers, the distribution of this polymer occurs in the form of tiny particles, which are crystallization centers, which causes a significant increase in the degree of crystallinity (χ) activation energy (E_act) and slowing down of molecular dynamics (τ). At higher concentrations of PVP, loose interphase layers were formed in the system, which caused a decrease in these parameters. The strongest changes in the concentration of hydrogen bonds occurred when PVP was added to the composition from 17 to 50%, which was due to the formation of intermolecular hydrogen bonds both in PVP and during the interaction of PVP and PHB. The diffusion coefficient of water vapor in the studied systems (D) decreased as the concentration of glassy PVP in the composition increased. The concentration of the radical decreased with an increase in the proportion of PVP, which can be explained by the glassy state of this polymer at room temperature. A characteristic point of the 50/50% mixture component ratio was found in the region where an inversion transition of PHB from a dispersion material to a dispersed medium was assumed. The conducted studies made it possible for the first time to conduct a comprehensive analysis of the effect of the component ratio on the structural and dynamic characteristics of the PHB/PVP fibrous material at the molecular scale. Full article

The rapid growth of electric vehicles (EVs) poses significant challenges to the safe operation of charging stations and distribution networks. Variations in charging power across different EV manufacturers lead to substantial load fluctuations at charging stations. In some tourist cities in China, charging loads can surge at specific times, yet existing research mainly focuses on optimizing station location and basic capacity configuration, neglecting sudden peak load management. To address this, we propose a method that enhances charging station carrying capacity (CSCC) by coordinating multi-flexibility resources. This method optimizes the configuration of soft open points (SOPs) to enable flexible interconnections between feeders and incorporates elastic load scheduling for data centers. An optimization model is developed to coordinate these flexible resources, thereby improving the CSCC. Case studies demonstrate that this approach effectively increases CSCC at lower costs, facilitates the utilization of renewable energy, and enhances the overall system economy. The results validate the feasibility and effectiveness of the proposed approach, offering new insights for urban grid planning and EV charging stations optimization. Full article

This paper presents a co-design approach for a microwave amplifier–phase shifter that integrates an arbitrary termination impedance reflection-type phase shifter as the input matching network of a microwave transistor. Since the proposed reflection-type phase shifter input matching network is capable of transforming both real and/or complex impedances to a system impedance of 50 Ω, the co-design approach can directly match the optimum source impedance of the microwave transistor to 50 Ω through a reflection-type phase shifter input matching network. To validate the proposed method, prototypes of microwave amplifier–phase shifters with different input matching networks configurations are designed, fabricated, and measured with a center frequency of 2.45 GHz. The experimental results demonstrate that the proposed co-design microwave amplifier–phase shifter achieves improved electrical performances compared to the conventional approach, where a 50-to-50 Ω termination impedance phase shifter is cascaded with a 50-to-50 Ω termination impedance conventional microwave amplifier. Measurement results demonstrate that the gains of a standalone conventional microwave amplifier, a cascaded phase shifter with a conventional microwave amplifier, and the proposed co-design microwave amplifier–phase shifter are 14.13 dB, 13.28 dB, and 13.74 dB, while the 1 dB compression points are 25.72 dBm, 24.77 dBm, and 25.26 dBm, respectively. Within the 200 MHz bandwidth, the proposed co-design microwave amplifier–phase shifter exhibits a maximum phase shift range of 185.62° and a phase deviation error of ±4.3°. The circuit size of the co-designed microwave amplifier–phase shifter is 38.5% smaller than the conventional cascaded phase shifter with a conventional microwave amplifier. Full article

To address the issues of insufficient feature extraction, single-fall judgment method, and poor real-time performance of traditional fall detection algorithms in occluded scenes, a top-down fall detection algorithm based on improved YOLOv8 combined with BAM-HRNet is proposed. First, the Shufflenetv2 network is used to make the backbone of YOLOv8 light weight, and a mixed attention mechanism network is connected stage-wise at the neck to enable the network to better obtain human body position information. Second, the HRNet network integrated with the channel attention mechanism can effectively extract the position information of key points. Then, by analyzing the position information of skeletal key points, the decline speed of the center of mass, the angular velocity between the trunk and the ground, and the human body height-to-width ratio are jointly used as the discriminant basis for identifying fall behaviors. In addition, when a suspected fall is detected, the system automatically activates a voice inquiry mechanism to improve the accuracy of fall judgment. The results show that the accuracy of the object detection module on the COCO and Pascal VOC datasets is 64.1% and 61.7%, respectively. The accuracy of the key point detection module on the COCO and OCHuman datasets reaches 73.49% and 70.11%, respectively. On the fall detection datasets, the accuracy of the proposed algorithm exceeds 95% and the frame rate reaches 18.1 fps. Compared with traditional algorithms, it demonstrates superior ability to distinguish between normal and fall behaviors. Full article

Amidst the swift progression of urban expansion, transformations in land utilization have become increasingly pronounced, posing significant threats to ecosystem coherence and continuity. Establishing a well-designed ecological security pattern (ESP) framework proves essential for preserving environmental equilibrium and enhancing species diversity. This investigation centers on the Fuzhou urban agglomeration as its primary study zone, employing the patch-oriented land utilization simulation (PLUS) approach to forecast 2030 land cover modifications under environmentally conscious conditions. By integrating morphological spatial configuration assessment (MSPA) with habitat linkage evaluation, critical ecological hubs were pinpointed. Subsequent application of electrical circuit principles alongside the minimal cumulative resistance (MCR) methodology enabled the identification of vital ecological pathways and junctions, culminating in the development of a comprehensive territorial ESP framework. Key findings reveal the subsequent outcomes: (1) the main land use type in the Fuzhou metropolitan area is woodland, which accounts for over 80% of its area, and under the ecological priority scenario for 2030, woodland fragmentation was significantly improved; (2) ecological sources are mainly distributed in the northwest, northeast, and central regions, with their total area proportion increasing to 40.49% by 2030; (3) we constructed 35 ecological corridors and 42 ecological nodes, including 14 key ecological pinch points, 9 potential ecological pinch points, and 4 ecological barrier points; and (4) the final ESP formed the pattern of “three cores, three areas, multiple corridors, and multiple sources,” providing strong support for ecological protection and regional sustainable development in the Fuzhou metropolitan area. In this research, we explore the coupled methods of land use simulation and ecological network construction, offering insights for optimizing ESPs in other rapidly urbanizing areas. Full article

Background: The agri-food sector is a major contributor to environmental degradation and emissions, highlighting the need for sustainable practices to mitigate its impact. Within this sector, perishable food crops require targeted efforts to reduce their environmental footprint. Vertical integration is crucial for ensuring alignment between strategic and tactical decision making in supply chain management. This article presents a multi-objective mathematical model that integrates both economic and environmental considerations within the perishable food supply chain, aiming to determine optimal solutions for conflicting objectives. Methods: In this research, we employed combining goal programming with the epsilon constraint approach; this comprehensive methodology reveals optimal solutions by discretizing the values derived from the payoff table. Results: The model is applied to a real case study of the tomato paste supply chain in Ethiopia. To identify Pareto-efficient points, the results are presented in two scenarios: Case I and Case II. Conclusions: The findings emphasize the significant influence of the geographical location of manufacturing centers in supplier selection, which helps optimize the trade-off between environmental impact and total cost. The proposed solution provides decision makers with an effective strategy to optimize both total cost and eco-costs in the design of perishable food supply chain networks. Full article

This paper investigates the distributed state estimation problem for the linear system against non-Gaussian noise, where every sensor commutates information only within its adjacent sensors without the need for a fusion center. Correntropy is a similarity metric based on a kernel function that has symmetry. Symmetry means that for any two data points, the output value of the kernel function does not depend on the order of the data points. By adopting a correntropy cost function based on the rational quadratic kernel function approximation to restrain non-Gaussian heavy-tailed noise, a centralized maximum correntropy Kalman filter is first derived for the linear sens+or network system at first. Then the corresponding centralized maximum correntropy information filter is attained by employing the information matrices, which is a foundation for further designing distributed information algorithms under multi-sensor networks. Thirdly, the distributed rational quadratic maximum correntropy information filter and distributed adaptive rational quadratic maximum correntropy information filter are designed by exploiting the weighted census average to solve the non-Gaussian heavy-tailed noise interference in sensor networks. Finally, the performance of the proposed algorithms is illustrated through numerical simulations on the sensor network system. Full article