Search Results (398)

This study addresses the construction of high-quality rural landscapes, crucial for China’s rural revitalization strategy, encompassing economic, social, cultural, and ecological dimensions. Focusing on 66 cold-region villages in Heilongjiang Province, it develops a dual-dimensional quality evaluation system that integrates both objective data and subjective perception indicators. It employs the entropy weight TOPSIS model to evaluate and grade the quality of rural landscapes and uses fuzzy-set Qualitative Comparative Analysis (fsQCA) to analyze the complex causal relationships influencing high-quality rural landscapes. The results show that (1) The TOPSIS model identifies four grades of rural landscape quality: “Excellent-Good-Average-Poor”, with “Excellent and Good” grades defined as high-quality rural landscape. (2) The fsQCA reveals eight configuration paths that influence high-quality rural landscapes, which are categorized into four models: natural ecology, efficient industry, cultural heritage, and comprehensive development. The main contribution of this study lies in its systematic analysis of the complex causal relationships affecting rural landscape quality, providing a theoretical and technological foundation for guiding the sustainable development of cold-region rural landscapes within the framework of rural revitalization strategy in China. Full article

Employees are the most valuable resources in any company, and their well-being directly influences work productivity. This research investigates integrating health parameters and sentiment analysis expressed in sent messages to enhance employee well-being within organizations in the context of Industry 5.0. Our primary aim is to develop a Well-Being Index (WBI) that quantifies employee health through various physiological and psychological parameters. A new methodology combining data collection from wearable devices from 1 January 2023 to 18 October 2024 and advanced text analytics was employed to achieve the WBI. This study uses the LbfgsMaximumEntropy ML classification algorithm to construct the Well-Being Model (WBM) and Azure Text Analytics for sentiment evaluation to assess negative messages among employees. The findings reveal a correlation between physiological metrics and self-reported well-being, highlighting the utility of the WBI in identifying areas of concern within employee behavior. We propose that the employee global indicator (EGI) is calculated based on the WBI and the dissatisfaction score component (DSC) to measure the overall state of mind of employees. The WBM exhibited a MacroAccuracy of 91.81% and a MicroAccuracy of 95.95% after 384 configurations were analyzed. Azure Text Analytics evaluated 2000 text messages, resulting in a Precision of 99.59% and an Accuracy of 99.7%. In this case, the Recall was 99.89% and F₁-score was 99.73%. In the Industry 5.0 environment, which focuses on the employee, a new protocol, the Employee KPI Algorithm (EKA), is integrated to prevent and identify employee stress. This study underscores the synergy between quantitative health metrics and qualitative sentiment analysis, offering organizations a framework to address employee needs proactively. Full article

Despite the huge number of studies of the three-body problem in physics and mathematics, the study of this problem remains relevant due to both its wide practical application and taking into account its fundamental importance for the theory of dynamical systems. In addition, one often has to answer the cognitive question: is irreversibility fundamental for the description of the classical world? To answer this question, we considered a reference classical dynamical system, the general three-body problem, formulating it in conformal Euclidean space and rigorously proving its equivalence to the Newtonian three-body problem. It has been proven that a curved configuration space with a local coordinate system reveals new hidden symmetries of the internal motion of a dynamical system, which makes it possible to reduce the problem to a sixth-order system instead of the eighth order. An important consequence of the developed representation is that the chronologizing parameter of the motion of a system of bodies, which we call internal time, differs significantly from ordinary time in its properties. In particular, it more accurately describes the irreversible nature of multichannel scattering in a three-body system and other chaotic properties of a dynamical system. The paper derives an equation describing the evolution of the flow of geodesic trajectories, with the help of which the entropy of the system is constructed. New criteria for assessing the complexity of a low-dimensional dynamical system and the dimension of stochastic fractal structures arising in three-dimensional space are obtained. An effective mathematical algorithm is developed for the numerical simulation of the general three-body problem, which is traditionally a difficult-to-solve system of stiff ordinary differential equations. Full article

This paper puts forward a selection principle and an optimization configuration method for short-circuit current-limiting measures to address the increasingly severe short-circuit current-exceeding problem brought about by the high-speed development of large power grids. Firstly, we introduce the function principle and the advantages and disadvantages of various short-circuit current-limiting measures in the power system and give the selection conditions of generalized short-circuit current-limiting measures. Then, we adopt the hierarchical analysis method (AHP) and entropy weighting method (EWM) to evaluate the weights of the indicators of the short-circuit current level, the line-loading level, the active loss, and the economic cost; perform the selection of multiple short-circuit current-limiting schemes after the combination of the assigned weights; and describe the generalized process of engineering used to solve the problem of short-circuit currents exceeding limits. We then provide a generalized process with which to solve the short-circuit current-exceeding problem in engineering. Finally, we take the actual large-scale power grid as an example, propose multiple short-circuit current-limiting schemes for a 220 kV power grid, and carry out the selection of optimal schemes to verify the validity and reliability of the study. The results show that this process plays an important role in controlling the short-circuit current of the power system, maintaining the safe and stable operation of the power system and improving the power system’s grid structure. Full article

Soft matter electrolytes could solve the safety problem of widely used liquid electrolytes in Li-ion batteries which are burnable upon heating. Simultaneously, they could solve the problem of poor contact between electrodes and solid electrolytes. However, the ionic conductivity of soft matter electrolytes is relatively low when mechanical properties are relatively good. In the present review, mechanisms of ionic conduction in soft matter electrolytes are discussed in order to achieve higher ionic conductivity with sufficient mechanical properties where soft matter electrolytes are defined as polymer electrolytes and polymeric or inorganic gel electrolytes. They could also be defined by Young’s modulus from about ${10}^5$ Pa to ${10}^9$ Pa. Many soft matter electrolytes exhibit VFT (Vogel–Fulcher–Tammann) type temperature dependence of ionic conductivity. VFT behavior is explained by the free volume model or the configurational entropy model, which is discussed in detail. Mostly, the amorphous phase of polymer is a better ionic conductor compared to the crystalline phase. There are, however, some experimental and theoretical reports that the crystalline phase is a better ionic conductor. Some methods to increase the ionic conductivity of polymer electrolytes are discussed, such as cavitation under tensile deformation and the microporous structure of polymer electrolytes, which could be explained by the conduction mechanism of soft matter electrolytes. Full article

Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River Economic Belt (YREB). Ecological, social, and economic subsystems are defined as condition subsystems, while the water resource subsystem is defined as the outcome subsystem. The entropy weight method is used to calculate and calibrate the comprehensive score of each subsystem. By analyzing the necessity of a single condition subsystem and the sufficiency of condition subsystem configuration via a dynamic QCA, we qualitatively analyze the impact extent and pathways of the ecological, social, and economic subsystems on the water resource subsystem within the WRCC framework. The results reveal generally stable water resource levels despite regional variances, thereby pinpointing the influence pathways, including ecological–social and ecological–economic configurations. The 2011–2015 period saw poor stability, which subsequently improved until 2019 before declining in 2020 in the YREB. The middle-reach urban cluster showed the highest stability, which was less impacted by condition subsystems. These findings could enable provinces and municipalities to tailor policies and enhance subsystem levels for better water resource management. Full article

This paper presents an innovative approach to high-temperature health monitoring of aircraft structures utilizing an ultrasonic guided wave transmission and reception system integrated with a zirconia heat buffer layer. Aiming to address the challenges posed by environmental thermal noise and the installation of heat buffers, which can introduce structural nonlinearities into guided wave signals, a composite guided wave consisting of longitudinal and Lamb waves was proposed for online damage detection within thermal protection systems. To effectively analyze these complex signals, a hybrid damage monitoring technique combining variational mode decomposition (VMD) and fuzzy entropy (FEN) was introduced. The VMD was employed to isolate the principal components of the guided wave signals, while the fuzzy entropy of these components served as a quantitative damage factor, characterizing the extent of the structural damage. Furthermore, this study validated the feasibility of piezoelectric probes equipped with heat buffer layers for both exciting and receiving ultrasonic guided wave signals in a dual heat buffer layer, a one-transmit-one-receive configuration. The experimental results demonstrated the efficacy of the proposed VMD-FEN damage factor for real-time monitoring of damage in aircraft thermal protection systems, both at ambient and elevated temperatures (up to 150 °C), showcasing its potential for enhancing the safety and reliability of aerospace structures operating under extreme thermal conditions. Full article

Prior studies have failed to adequately address intangible characteristics and lacked a comprehensive quantification of cultural dimensions. Additionally, such works have not merged supervised and unsupervised classification methodologies. To address these gaps, this study employed multidimensional numerical techniques for precise spatial pattern recognition and urban morphology classification at the block scale. By examining building density, mean floor numbers, functional compositions, and street block mixed-use intensities, alongside historical and contemporary cultural assets within blocks—with assigned weights and entropy calculations from road networks, building vectors, and POI data—a hierarchical categorization of high, medium, and low groups was established. As a consequence, cluster analysis revealed seven distinctive morphology classifications within the studied area, each with unique spatial configurations and evolutionary tendencies. Key findings include the dominance of high-density, mixed-use blocks in the urban core, the persistence of historical morphologies in certain areas, and the emergence of new, high-rise clusters in recently developed zones. The investigation further elucidated the spatial configurations and evolutionary tendencies of each morphology category. These insights lay the groundwork for forthcoming studies to devise morphology-specific management strategies, thereby advancing towards a more scientifically grounded, rational, and precision-focused approach to urban morphology governance. Full article

This study proposes a charging efficiency calculation model based on an equivalent internal resistance framework. A data-driven neural network model is developed to predict the charging efficiency of lithium titanate (LTO) batteries for 5% state of charge (SOC) segments under various charging conditions. By considering the impact of entropy change on the open-circuit voltage (OCV) during the charging process, the accuracy of energy efficiency calculations is improved. Incorporating battery data under various charging conditions, and comparing the predictive accuracy and computational complexity of different hyperparameter configurations, we establish a backpropagation neural network model designed for implementation in embedded systems. The model predicts the energy efficiency of subsequent 5% SOC segments based on the current SOC and operating conditions. The results indicate that the model achieves a prediction error of only 0.29% under unknown charging conditions while also facilitating the deployment of the neural network model in embedded systems. In future applications, the relevant predictive data can be transmitted in real time to the cooling system for thermal generation forecasting and predictive control of battery systems, thereby enhancing temperature control precision and improving cooling system efficiency. Full article

In order to improve the magnetocaloric properties of MnNiSi-based alloys, a new type of high-entropy magnetocaloric alloy was constructed. In this work, Mn_0.6Ni_1−xSi_0.62Fe_0.4Co_xGe_0.38 (x = 0.4, 0.45, and 0.5) are found to exhibit magnetostructural first-order phase transitions from high-temperature Ni₂In-type phases to low-temperature TiNiSi-type phases so that the alloys can achieve giant magnetocaloric effects. We investigate why c_hexagonal/a_hexagonal (c_hexa/a_hexa) gradually increases upon Co substitution, while phase transition temperature (T_tr) and isothermal magnetic entropy change (ΔS_M) tend to gradually decrease. In particular, the x = 0.4 alloy with remarkable magnetocaloric properties is obtained by tuning Co/Ni, which shows a giant entropy change of 48.5 J∙kg⁻¹K⁻¹ at 309 K for 5 T and an adiabatic temperature change (ΔT_ad) of 8.6 K at 306.5 K. Moreover, the x = 0.55 HEA shows great hardness and compressive strength with values of 552 HV2 and 267 MPa, respectively, indicating that the mechanical properties undergo an effective enhancement. The large ΔS_M and ΔT_ad may enable the MnNiSi-based HEAs to become a potential commercialized magnetocaloric material. Full article

In response to the rapid growth of air passenger and cargo transportation services and the sharp increase in congestion at various airports, it is necessary to optimize the allocation of flight schedules. On the basis of reducing the total airport delay time and ensuring the total deviation of flight schedules applied by airlines, it is necessary to consider finely configuring flight schedules with slot coordination parameters, introducing a 5 min slot coordination parameter, and optimizing airport flight schedules in different time periods. This article considers factors such as flight schedule uniqueness, corridor flow restrictions, and time adjustment range limitations to establish a three-objective flight-schedule refinement configuration model, which is solved using the NSGA-II algorithm based on the entropy weight method. Taking Beijing Capital International Airport as an example, the optimized results show that the total flight delay was reduced from 4130 min to 1142 min, and the original delay of 389 flights was reduced to 283 flights. Therefore, flight schedule optimization considering the fine-grained configuration of slot coordination parameters can effectively reduce airport delays, fully utilize time resources, and reduce waste of time slot resources. Full article

The oxygen evolution reaction (OER) stands out as a key electrochemical process for the conversion of clean energy. However, the practical implementation of OER is frequently impeded by its slow kinetics and the necessity for scarce and expensive noble metal catalysts. High-entropy transition metal sulfides (HETMS) stand at the forefront of OER catalysts, renowned for their exceptional catalytic performance and diversity. Herein, we have synthesized a HETMS catalyst, (FeCoNiCuMn₅₀)S₂, encapsulated within carbon nanofibers through a one-step process involving the synergistic application of electrospinning and chemical vapor deposition. By precisely controlling the doping levels of sulfur, we have demonstrated that sulfur incorporation significantly increases the exposed surface area of alloy particles on carbon nanofibers and optimizes the electronic configuration of the alloy elements. These findings reveal that sulfur doping is instrumental in the substantial improvement of the catalyst’s OER performance. Notably, the catalyst showed optimal activity at a sulfur-to-metal atom ratio of 2:1, delivering an overpotential of 254 mV at a current density of 10 mA cm⁻² in 1.0 M KOH solution. Furthermore, the (FeCoNiCuMn₅₀)S₂ catalyst exhibited remarkable electrochemical stability, underscoring its potential as an efficient and robust OER electrocatalyst for sustainable energy applications. Full article

This study explores the role of information entropy in understanding nuclear density distributions, including both stable configurations and non-traditional structures such as neutron halos and $\alpha$-clustering. By quantifying the uncertainty and disorder inherent in nucleon distributions in nuclear many-body systems, information entropy provides a macroscopic measure of the physical properties of the system. A more dispersed and disordered density distribution results in a higher value of information entropy. This intrinsic relationship between information entropy and system complexity allows us to quantify uncertainty and disorder in nuclear structures by analyzing various geometric parameters such as nuclear radius, diffuseness, neutron skin, and cluster structural features. Full article

The use of physical unclonable functions (PUFs) linked to the manufacturing process of the electronic devices supporting applications that exchange critical data over the Internet has made these elements essential to guarantee the authenticity of said devices, as well as the confidentiality and integrity of the information they process or transmit. This paper describes the development of a configurable PUF/TRNG module based on ring oscillators (ROs) that takes full advantage of the structure of modern programmable devices offered by Xilinx 7 Series families. The proposed architecture improves the hardware efficiency with two main objectives. On the one hand, we perform an exhaustive statistical characterization of the results derived from the exploitation of RO configurability. On the other hand, we undertake the development of a new version of the module that requires a smaller amount of resources while considerably increasing the number of output bits compared to other proposals previously reported in the literature. The design as a highly parameterized intellectual property (IP) module connectable through a standard interface to a soft- or hard-core general-purpose processor greatly facilitates its integration into embedded solutions while accelerating the validation and characterization of this element on the same electronic device that implements it. The studies carried out reveal adequate values of reliability, uniqueness, and unpredictability when the module acts as a PUF, as well as acceptable levels of randomness and entropy when it acts as a true random number generator (TRNG). They also illustrate the ability to obfuscate and recover identifiers or cryptographic keys of up to 4096 bits using an implementation of the PUF/TRNG module that requires only an array of $4\times 4$ configurable logic blocks (CLBs) to accommodate the RO bank. Full article

Shopping malls have become vibrant public spaces, serving as commercial centers and sociocultural hubs. However, the arrangement of stationary elements such as elevators and escalators significantly impacts the visual quality of the atrium and the overall navigation experience within the complex. This research focuses on analyzing the configuration of elevators and escalators in shopping mall atriums and their influence on visual richness and accessibility. Descriptive-analytical and survey methods are employed, utilizing data from 10 successful malls worldwide. The UCL-Depth map software and space syntax variables are used for analysis. Connectivity, clustering-coefficient, and controllability analyses assess visual richness, while integration, mean-depth, entropy, depth, step-depth, and gate-count analyses evaluate accessibility. The research includes a questionnaire to obtain optimal indices for each space syntax variable, enhancing the accuracy of the findings. The results highlight the significant impact of the positioning of vertical access elements within the atrium on its visual richness and the accessibility of shops. The research identifies an optimal configuration: placing the escalator in the middle of the atrium, deviating 30° from the entrance axis, and separately locating the elevators. This configuration provides the highest level of access to shops and the central atrium from any point, minimizing the number of turns required to reach different locations within the mall. Furthermore, the separate placement of elevators improves the flow of individuals between shops and the atrium, resulting in increased integration. In conclusion, selecting an appropriate configuration of elevators and escalators in shopping mall atriums can greatly enhance wayfinding and improve the visual richness and accessibility of the complex. Architects and designers can utilize these findings to optimize the design of public spaces within shopping centers, promoting social interactions and enhancing the overall visitor experience. Full article