Search Results (2,172)

In Ecuador, the transmission of dengue has steadily increased in recent decades, particularly in coastal cities like Manta, where the conditions are favorable for the proliferation of the Aedes aegypti mosquito. The objective of this study was to model the spatial distribution of dengue transmission risk in Manta, a coastal city in Ecuador with consistently high incidence rates. A total of 148 georeferenced dengue cases from 2018 to 2021 were collected, and environmental and socioeconomic variables were incorporated into a maximum entropy model (MaxEnt). Additionally, climate and social zoning were performed using a multi-criteria model in TerrSet. The MaxEnt model demonstrated excellent predictive ability (training AUC = 0.916; test AUC = 0.876) and identified population density, sewer system access, and distance to rivers as the primary predictors. Three high-risk clusters were identified in the southern, northwestern, and northeastern parts of the city, while the coastal strip showed lower suitability due to low rainfall and vegetation. These findings reveal the strong spatial heterogeneity of dengue risk at the neighborhood level and provide operational information for targeted interventions. This approach can support more efficient surveillance, resource allocation, and community action in coastal urban areas affected by vector-borne diseases. Full article

This study addresses the growing importance of integrating innovation into corporate sustainability strategies by examining the financial and environmental performance of ten firms listed on the Borsa Istanbul Sustainability Index over a five-year period. The main objective is to develop and test a novel, data-driven analytical framework that reduces reliance on subjective expert judgments while providing actionable insights for sustainability-oriented decision-making. Within this framework, the entropy method from the Multi-Criteria Decision Making (MCDM) approach is first applied to calculate the objective weights of sustainability criteria, ensuring that the analysis is grounded in real performance data. Building on these weights, an innovative reverse Decision-Making Trial and Evaluation Laboratory (DEMATEL) model, implemented through a custom artificial neural network-based software, is introduced to estimate direct influence matrices and reveal the causal relationships among criteria. This methodological advance makes it possible to explore how environmental and financial factors interact with R&D expenditures and to simulate their systemic interdependencies. The findings demonstrate that R&D serves as a central driver of both environmental and financial sustainability, highlighting its dual role in fostering corporate innovation and long-term resilience. By positioning R&D as both an enabler and outcome of sustainability dynamics, the proposed framework contributes a novel tool for aligning innovation with strategic sustainability goals, offering broader implications for corporate managers, policymakers, and researchers. Full article

Undetected cracks in railroad wheels pose significant safety and economic risks, while current inspection methods are limited by cost, coverage, or contact requirements. This study explores the use of passive, air-coupled ultrasonic acoustic (UA) sensors for detecting wheel damage on stationary or moving wheels. Two controlled datasets of wheelsets, one with clear damage and another with early, service-induced defects, were tested using hammer impacts. An automated system identified high-energy bursts and extracted features in both time and frequency domains, such as decay rate, spectral centroid, and entropy. The results demonstrate the effectiveness of UAE (ultrasonic acoustic emission) techniques through Kernel Density Estimation (KDE) visualization, hypothesis testing with effect sizes, and Receiver Operating Characteristic (ROC) analysis. The decay rate consistently proved to be the most effective discriminator, achieving near-perfect classification of severely damaged wheels and maintaining meaningful separation for early defects. Spectral features provided additional information but were less decisive. The frequency spectrum characteristics were effective across both axial and radial sensor orientations, with ultrasonic frequencies (20–80 kHz) offering higher spectral fidelity than sonic frequencies (1–20 kHz). This work establishes a validated “ground-truth” signature essential for developing a practical wayside detection system. The findings guide a targeted engineering approach to physically isolate this known signature from ambient noise and develop advanced models for reliable in-motion detection. Full article

Creative insight is a core phenomenon of human cognition, often characterized by the sudden emergence of novel and contextually appropriate ideas. Classical models based on symbolic search or associative networks struggle to capture the non-linear, context-sensitive, and interference-driven aspects of insight. In this work, we propose a computational model of insight generation grounded in continuous-time quantum walks over weighted semantic graphs, where nodes represent conceptual units and edges encode associative relationships. By exploiting the principles of quantum superposition and interference, the model enables the probabilistic amplification of semantically distant but contextually relevant concepts, providing a plausible account of non-local transitions in thought. The model is implemented using standard Python 3.10 libraries and is available both as an interactive fully reproducible Google Colab notebook and a public repository with code and derived datasets. Comparative experiments on ConceptNet-derived subgraphs, including the Candle Problem, 20 Remote Associates Test triads, and Alternative Uses, show that, relative to classical diffusion, quantum walks concentrate more probability on correct targets (higher AUC and peaks reached earlier) and, in open-ended settings, explore more broadly and deeply (higher entropy and coverage, larger expected radius, and faster access to distant regions). These findings are robust under normalized generators and a common time normalization, align with our formal conditions for transient interference-driven amplification, and support quantum-like dynamics as a principled process model for key features of insight. Full article

Background/Objectives: Germ Cell Neoplasia In Situ (GCNIS) is considered the precursor lesion for the majority of testicular germ cell tumors (TGCTs). The aim of this study was to evaluate whether first-order radiomics features derived from volumetric diffusion tensor imaging (DTI) metrics—specifically apparent diffusion coefficient (ADC) and fractional anisotropy (FA) histogram parameters—can detect GCNIS. Methods: This study included 15 men with TGCTs and 10 controls. All participants underwent scrotal MRI, including DTI. Volumetric ADC and FA histogram metrics were calculated for the following tissues: group 1, TGCT; group 2: testicular parenchyma adjacent to tumor, histologically positive for GCNIS; and group 3, normal testis. Non-parametric statistics were used to assess differences in ADC and FA histogram parameters among the three groups. Pearson’s correlation analysis was followed by ordinal regression analysis to identify key predictive histogram parameters. Results: Widespread distributional differences (p < 0.05) were observed for many ADC and FA variables, with both TGCTs and GCNIS showing significant divergence from normal testes. Among the ADC statistics, the 10th percentile and skewness (p = 0.042), range (p = 0.023), interquartile range (p = 0.021), total energy (p = 0.033), entropy and kurtosis (p = 0.027) proved the most significant predictors for tissue classification. FA_energy (p = 0.039) was the most significant fingerprint of the carcinogenesis among the FA metrics. These parameters correctly characterized 88.8% of TGCTs, 87.5% of GCNIS tissues and 100% of normal testes. Conclusion: Radiomics features derived from volumetric ADC and FA histograms have promising potential to differentiate TGCTs, GCNIS, and normal testicular tissue, aiding early detection and characterization of pre-cancerous lesions. Full article

Using 31 provinces (cities and districts) on the Chinese mainland (2013–2023) as the research object, this study analyzes the development level of e-commerce through the entropy weight method and uses panel data to empirically test the driving effect of e-commerce development level on low-carbon development. According to this study, the overall development of e-commerce has a positive driving effect on low-carbon development. E-commerce development lowers the intensity of carbon emissions by optimizing regional industrial structures, innovating green technologies, and establishing resource sharing. Moreover, the analysis of the effects of regional heterogeneity reveals that, although low-level areas still have great development potential, high-level economic development areas have the greatest effect on low-carbon development. In conclusion, we clarify how e-commerce contributes to low-carbon development and provide resources for enhancing the quality and efficiency of e-commerce to conserve energy and reduce emissions. Full article

The increasing adoption of digital technologies, robotic systems, and IoT applications in sectors such as medicine, agriculture, and industry drives a surge in data generation and necessitates secure and efficient encryption. For resource-constrained systems, lightweight yet robust cryptographic algorithms are critical. This study addresses the security demands of IoRT systems by proposing an enhanced chaos-based encryption method. The approach integrates the lightweight structure of NIST-standardized Ascon-AEAD128 with the randomness of the Zaslavsky map. Ascon-AEAD128 is widely used on many hardware platforms; therefore, it must robustly resist both passive and active attacks. To overcome these challenges and enhance Ascon’s security, we integrate into Ascon the keys and nonces generated by the Zaslavsky chaotic map, which is deterministic, nonperiodic, and highly sensitive to initial conditions and parameter variations.This integration yields a chaos-based Ascon variant with a higher encryption security relative to the standard Ascon. In addition, we introduce exploratory variants that inject non-repeating chaotic values into the initialization vectors (IVs), the round constants (RCs), and the linear diffusion constants (LCs), while preserving the core permutation. Real-time tests are conducted using Raspberry Pi 3B devices and ROS 2–based IoRT robots. The algorithm’s performance is evaluated over 100 encryption runs on 12 grayscale/color images and variable-length text transmitted via MQTT. Statistical and differential analyses—including histogram, entropy, correlation, chi-square, NPCR, UACI, MSE, MAE, PSNR, and NIST SP 800-22 randomness tests—assess the encryption strength. The results indicate that the proposed method delivers consistent improvements in randomness and uniformity over standard Ascon-AEAD128, while remaining comparable to state-of-the-art chaotic encryption schemes across standard security metrics. These findings suggest that the algorithm is a promising option for resource-constrained IoRT applications. Full article

Recent literature reports have shown that individual HEAs, especially those of the AlCoCrFeNi composition system alloyed with appropriately selected elements, exhibit excellent mechanical properties and corrosion resistance, making them promising candidates for replacing conventional materials such as austenitic steels in corrosive environments. Therefore, in the present study, the high-entropy alloy AlCoCrFeNiMo_0.25 was examined and compared with AISI 304L steel and the reference alloy AlCoCrFeNi. The HEA was produced by arc melting in vacuum. The effect of molybdenum addition (5% at.) on the structure, mechanical properties, and corrosion resistance was evaluated. Potentiodynamic polarization and electrochemical impedance spectroscopy tests were carried out in a 3.5% NaCl solution in a three-electrode electrochemical system. The addition of molybdenum to AlCoCrFeNiMo_x alloy additionally caused, along with the BCC phase, the formation of σ phase and FCC phase (less than 1%), as well as changes in the microstructure, leading to the fragmentation of grains and the formation of a mosaic structure. On the basis of nanoindentation tests, it was established that the addition of Mo increases hardness and elastic modulus and improves nanoindentation coefficients H/E and H³/E², as well as an increase in the elastic recovery index while decreasing plasticity index (vs. the reference equiatomic HEA). This indicates the improvement of anti-wear properties with impact loading resistance. In turn, electrochemical tests have shown that the addition of Mo improves corrosion resistance. Corrosion pitting develops in Al- and Ni-rich areas of HEA alloys, as a result of galvanic microcorrosion related to Cr chemical segregation. In general, the addition of 5% Mo results in a fine-grained mosaic structure, which primarily translates into favorable nanoindentation and corrosion properties of the AlCoCrFeNiMo_0.25 alloy. Full article

Against the backdrop of accelerating global urbanization and intensifying ecological pressures, investigating the relationship between urbanization levels and ecological resilience in resource-based cities has become crucial for nations striving to achieve both sustainable development and ecological conservation. Utilizing panel data from 114 resource-based cities in China between 2010 and 2023, this study innovatively employs a composite nighttime light index to measure urbanization levels and constructs a comprehensive ecological resilience index using the entropy method. By applying a double machine learning model, this study thoroughly examines the impact, mechanisms, and heterogeneity of urbanization on ecological resilience in these cities. The findings reveal a gradual increase in ecological resilience among China’s resource-based cities, with the majority reaching high resilience levels by 2023. Spatial aggregation centers are identified in eastern China, the Yangtze River Delta, and the Pearl River Delta. Moreover, urbanization demonstrates a significant positive correlation with ecological resilience, a conclusion reinforced through robustness tests. Mechanism analysis reveals that industrial structure upgrading, green technology innovation, and energy efficiency improvement serve as key transmission channels. Heterogeneity analysis indicates that urbanization exerts a more pronounced effect on enhancing ecological resilience in regenerative resource-based cities as well as those located in eastern and central regions, while its impact is relatively weaker in declining resource-based cities and those in western and northeastern regions. Finally, this study proposes policy recommendations focusing on advancing industrial structure sophistication, constructing a green technology innovation ecosystem, implementing an energy efficiency enhancement initiative, deepening region-specific governance, and adopting targeted policy interventions. These findings provide theoretical support for precise policy formulation in resource-based cities and contribute to advancing academic understanding of the relationship between sustainable development and ecological resilience in such regions. Full article

Background and Objectives: Acute exercise lowers vagal HRV, yet it is unclear who will show the largest drop and whether simple questionnaires can identify them. To test whether resting HRV complexity (Sample Entropy) predicts the magnitude of acute vagal withdrawal and whether this physiology-based marker has greater practical utility than self-report activity/sleep measures for screening and recovery decisions. Materials and Methods: In a single-arm pre–post experimental study, twenty-nine students (20.4 ± 0.5 y; 13 males, 16 females) completed one morning visit (08:00–12:00 h). After a 2 min resting ECG and a Sustained Attention to Response Task (SART), participants cycled 15 min at 0.85 × (220 − age) bpm following a 5 min 25 W warm-up. HRV was re-recorded within ~2 min and SART ~5 min post exercise. The IPAQ defined low/medium/high activity tertiles. Correlations related baseline measures to change scores. Results: RMSSD decreased by −12.93 ms [−25.71, −2.03] (p = 0.003, r = 0.60) and SDNN by −14.91 ms [−22.30, 7.66] (p = 0.011, r = 0.51). Reaction time shortened slightly (−8.77 ms [−59.33, 30.40], p = 0.35). Activity tertiles did not differ in ΔRMSSD, ΔSDNN, or ΔRT (all p > 0.10). Sample Entropy predicted autonomic change (ΔRMSSD r = 0.43, p = 0.034; ΔSDNN r = 0.59, p = 0.002), whereas the PSQI and IPAQ did not. Equivalence tests showed non-significant tertile differences were not within our predefined equivalence bounds. Conclusions: Individuals with more complex resting HRV were more likely to show a larger immediate vagal withdrawal after moderate cycling. Questionnaires did not identify these responders. Non-linear HRV may aid practical screening/monitoring, whereas self-reports alone appear insufficient. Generalizability is limited by the homogeneous young adult sample. Full article

Understanding the shear behavior of loess–concrete interfaces is essential for foundation design in collapsible loess regions, yet the pore-scale mechanisms remain unclear. This study investigates the relationship between interface shear strength and loess microstructure at different burial depths. Direct shear tests were conducted on undisturbed loess samples under stress conditions simulating in situ confinement. High-resolution SEM images were analyzed via Avizo to quantify pore area ratios at multiple scales, fractal dimensions, and directional probability entropy. Pearson correlation, principal component analysis (PCA), and hierarchical cluster analysis (HCA) were employed to statistically interpret the microstructure–mechanics relationship. Results show that interface shear strength increases significantly with depth (35.2–258.4 kPa), primarily due to reduced total porosity and macropore content, increased small and micropore fractions, and enhanced isotropy of pore orientation. Fractal dimension negatively correlates with strength, indicating that compaction-induced boundary regularization enhances particle contact and shear resistance, while entropy positively correlates with strength, reflecting structural homogenization and isotropic pore orientation. PCA and HCA further confirm that small and micropores are the dominant contributors to interface resistance. This study provides a quantitative framework linking microstructural evolution to mechanical performance, offering new insights for optimizing pile–soil interface design in loess areas. Full article

Understanding the coupled and coordinated development of China’s urban and rural basic education systems is crucial for fostering their interaction and synergistic growth. Using China’s provincial panel data from 2011 to 2023, this study measures the coupled and coordinated development level of urban–rural basic education (CCD-URBE) via the entropy weight method, G1-method and coupling coordination degree model. On this basis, the Dagum Gini coefficient decomposition method, traditional and spatial Markov chain models, as well as convergence test models are employed for empirical research. The results show that: (1) During the study period, the CCD-URBE across the nation and the four major regions improves significantly. Both intra-regional and inter-regional disparities show a consistent downward trend. Inter-regional disparities are the main source of the overall disparities, and the contribution rate of transvariation density to the overall disparities exhibits the most significant increase. (2) The CCD-URBE demonstrates strong stability, as most regions tend to maintain their original CCD-URBE grades. Meanwhile, neighborhood grades moderate the local transition probability significantly. Neighborhoods with high CCD-URBE promote the upward improvement of the local CCD-URBE, while those with low CCD-URBE inhibit it. (3) The CCD-URBE across the nation and the four major regions shows obvious trends of σ-convergence, absolute β-convergence, and conditional β-convergence. The central region, which has lower CCD-URBE, exhibits higher convergence speed. Based on these findings, targeted policy implications are derived. Full article

Quantifying uncertainty in complex systems is a central problem in reliability analysis and engineering applications. In this work, we develop an information-theoretic framework for analyzing linear consecutive k-out-of-n:G systems using the cumulative residual Tsallis entropy (CRTE). A general analytical expression for CRTE is derived, and its behavior is investigated under various stochastic ordering relations, providing insight into the reliability of systems governed by continuous lifetime distributions. To address challenges in large-scale settings or with nonstandard lifetimes, we establish analytical bounds that serve as practical tools for uncertainty quantification and reliability assessment. Beyond theoretical contributions, we propose a nonparametric CRTE-based test for dispersive ordering, establish its asymptotic distribution, and confirm its statistical properties through extensive Monte Carlo simulations. The methodology is further illustrated with real lifetime data, highlighting the interpretability and effectiveness of CRTE as a probabilistic entropy measure for reliability modeling. The results demonstrate that CRTE provides a versatile and computationally feasible approach for bounding analysis, characterization, and inference in systems where uncertainty plays a critical role, aligning with current advances in entropy-based uncertainty quantification. Full article

How to rationally design composition of alloys with desired properties has always been an open and challenging question, especially for high-entropy alloy (HEA) which has huge selections of composition due to the feature of multi-principal elements. Although great efforts have been made in the past decades, such as approaches based on thermo-kinetic analysis and simulations, strategies to quick determine the optimal HEA composition remain lacking. In this study, based on the effective estimations of elastic modulus of alloys from compositions, we proposed a strategy to design intrinsically strong, ductile, and low-weight refractory HEA (RHEA) compositions. First, the Young’s moduli of three RHEAs were experimentally measured using uniaxial tensile test and impulse excitation of vibration (IEV) test. Then, the present results, combining with the data of elastic moduli of ~130 HEAs in literature, were utilized to validate the prediction of elastic moduli from compositions of HEAs. Finally, based on the property maps that containing 38,326 compositions, a novel RHEA was designed and experimentally tested, exhibiting superior strength, ductility, and low density compared to the equimolar NbMoTaVW alloy. This study provides a new strategy for developing HEAs and contributes to the development of new refractory HEAs with desired properties. Full article

This study aims to explore whether and how data elements affect the green total factor productivity (GTFP) of China’s logistics industry, and conducts empirical tests using the super-efficiency SBM model, Malmquist exponential model, and spatial Dubin model. Based on the relevant data of 30 provinces in China from 2013 to 2021, we employ the Super-efficiency SBM model and the Malmquist dynamic index model to calculate the green total factor productivity of the logistics sector. We then establish a three-tier evaluation framework for data elements, employ the entropy method to determine the weighting of each indicator, and utilize linear weighting to calculate the comprehensive evaluation value of data elements. By incorporating appropriate control variables and employing the spatial Durbin model, this study examines the impact of data elements on the GTFP of the logistics industry. It is found that data elements have a contributing effect on improving GTFP of the logistics industry in the local region as well as a positive spillover effect on the neighboring regions, and this is achieved by improving the level of technical progress. In addition, the coefficients are decomposed into direct, indirect, and total effects by partial differentiation, again verifying the above conclusions. This study investigates the impact of data elements on GTFP in the logistics industry from theoretical mechanisms and empirical tests, and analyzes the dual impact of data elements and other factors on the local region and neighboring regions. The findings of this study can provide references for better empowering the development of the logistics industry with data elements. Full article