Search Results (7,856)

This paper proposes a micro-Doppler flash detection framework for hovering unmanned aerial vehicle (UAV) detection with linear frequency modulated continuous wave (LFMCW) radar under the dual constraints of strong ground clutter and severe thermal noise conditions. In such scenarios, conventional methods fail not only due to the spectral overlap between hovering targets and clutter but also because of the visual disappearance of micro-Doppler features under heavy noise. The framework consists of three sequential modules. A prior-template orthogonal projection (PTOP) module suppresses clutter via a single-step orthogonal projection, preserving the micro-Doppler flash signature without distortion while approximately maintaining the Gaussian noise statistics required for subsequent detection. A flash power spectrum construction module then collapses the periodic blade flash energy onto a sharp spectral peak in a one-dimensional (1D) power spectrum via Gabor transform, power projection, and fast Fourier transform (FFT). A cell-averaging constant false alarm rate (CA-CFAR) detection module with an analytically derived threshold factor finally renders a reliable detection decision. Simulations under a signal-to-clutter ratio (SCR) of $-21$ dB and signal-to-noise ratio (SNR) of $-23$ dB confirm that the proposed framework achieves reliable detection even when the micro-Doppler flash signatures are visually obscured by residual noise in the time–frequency domain. Parametric SNR sweep curves and a two-dimensional (2D) SCR–SNR detection-probability heatmap under a non-stationary clutter model further quantify the practical performance boundaries of the framework. By transforming these concealed periodic features into a sharp spectral peak, the framework provides robust detection performance where conventional range-Doppler and moving target indication (MTI)-based methods both exhibit severe performance degradation. Full article

In recent years, with the significant decline in fine particulate matter (PM_2.5) concentrations, ozone (O₃) has emerged as a major composite air pollutant during the warm season in China, attracting increasing attention due to its associated health burden and economic costs. This study focuses on Tianjin, using ozone monitoring data from 2017 to 2023 combined with health statistics to assess the health impacts and economic losses attributable to ozone pollution. First, ozone exposure indicators and compliance criteria were constructed based on national air quality standards, and the interannual variation and spatial differences of O₃ levels were analyzed at both citywide and district scales. Second, multiple machine learning classification models, including logistic regression, decision tree, k-nearest neighbors, and gradient boosting, were developed using ozone and meteorological variables to predict the occurrence risks of five diseases: cardiovascular diseases, respiratory diseases, hand-foot-and-mouth disease (HFMD), influenza, and dengue fever. Finally, excess cases were estimated using health impact functions, and the associated economic losses were quantified by combining the value of a statistical life (VSL) with cost-of-illness and willingness-to-pay (WTP) approaches. The results showed that the annual evaluation value of ozone in Tianjin, defined as the 90th percentile of the daily maximum 8 h average O₃ concentration, exhibited a pattern of initially increasing, then decreasing, and subsequently rebounding. It peaked at 201 µg/m³ in 2018, declined to a minimum of 164 µg/m³ in 2021, and rebounded to 188 µg/m³ in 2023. Machine-learning results indicated that the logistic regression model showed relatively stable overall performance across predictions of different diseases, while the gradient boosting tree model also achieved high accuracy in predicting certain infectious diseases. Overall, ozone pollution exhibits significant heterogeneous effects across different disease types, and the associated health-related economic losses show stage-wise fluctuations in response to pollution levels. Based on these findings, it is recommended to implement refined control measures during periods of high ozone exceedance and in key regions, while strengthening protection for vulnerable populations such as the elderly, children, and patients with respiratory diseases, in order to achieve synergistic improvements in air quality management and public health outcomes. Full article

Dense underwater aquaculture poses significant challenges for intelligent image processing because asymmetric occlusion, turbidity, aeration-like bubbles, and motion blur frequently degrade fish contours and quasi-periodic scale textures. These disturbances often cause conventional detectors to miss detections, merge bounding boxes, experience feature collapse, and exhibit unstable counting. To address this problem, we propose DenseFish-v13, a symmetry-aware NMS-free YOLOv13-Mamba framework for dense underwater fish detection and bio-kinematic behavior recognition. The framework integrates a Bio-Harmonic Frequency Gate to preserve biological texture patterns while suppressing bubble-like frequency noise, a Bi-directional Multi-scale Wavelet Mamba backbone for global occlusion-aware structure recovery, and an asymmetry-aware density repulsion strategy to separate highly overlapping fish instances during bipartite matching. In addition, a lightweight Bio-Kinematic Behavior Head converts continuous detections into interpretable trajectory descriptors for behavior-state recognition. Experiments on the Dense-Aqua benchmark, constructed from public aquaculture datasets, show that DenseFish-v13 achieves 64.8% mAP@50:95 and a Counting MAE of 3.7 on the overall test set, while reaching 64.2% mAP@50:95 and a Counting MAE of 4.1 on the extreme-density split. Under a strong synthetic bubble perturbation, the model shows only a 1.3 percentage-point drop in mAP and maintains 125 FPS on Jetson Orin NX. These results demonstrate its effectiveness in robust, real-time underwater aquaculture monitoring. Full article

The present study aims to address critical research gaps in duckweed–microbe symbiotic systems specifically applied to high-load livestock and poultry breeding wastewater. These gaps include the insufficient development of well-characterized, multi-functional, complex microbial consortia adapted to complex livestock wastewater matrices, and the technical challenge of achieving simultaneous efficient wastewater purification and duckweed feed quality enhancement. This study is motivated by the pressing issue of agricultural non-point source pollution, which is caused by large-scale livestock and poultry breeding wastewater discharge, and the high external dependence of the feed industry on protein raw materials. The present study utilised Spirodela as the fundamental material, and a functionally complementary complex symbiotic bacterial consortium consisting of Bacillus subtilis, Bacillus tequilensis and Pseudomonas fluorescens was screened and constructed. An experiment was conducted over a 14-day period in which a range of inoculation ratios were systematically explored. The aim of this experiment was to ascertain the purification efficiency of the duckweed–bacteria symbiotic system on high-load livestock and poultry breeding wastewater. Furthermore, the experiment sought to determine the effect of this purification process on the feed value of duckweed. The results demonstrated that complex bacterial inoculation significantly enhanced wastewater purification efficiency. The final removal rate of ammonia nitrogen in all treatment groups exceeded 90% after 14 days, and the maximum removal rates of total nitrogen and total phosphorus reached 67.0% and 58.9%, respectively, thereby demonstrating superior purification performance in comparison to the control group. The inoculation ratio of 10:1 was identified as the optimal parameter for wastewater purification, while the 5:1 ratio was found to be the maximum for crude protein accumulation in duckweed. The maximum dry-based crude protein content recorded was 38.9% on day 14, representing an increase of 26.3% in comparison with the control group. The established duckweed–bacteria symbiotic system has the capacity to simultaneously achieve the efficient purification of livestock and poultry breeding wastewater and the high-value utilisation of duckweed. The optimal process parameters for a range of application scenarios have been determined. This study contributes to the theoretical framework of aquatic plant–microbe symbiotic remediation and provides technical support for the recycling of wastewater resources and the sustainable development of the livestock and poultry breeding industry. Full article

Linpan in Chengdu Plain, a distinctive form of dispersed rural settlement on the Chengdu Plain, is composed primarily of traditional rural dwellings embedded within woodlands environments. These settlements play multifunctional roles related to agricultural production, daily life, ecological sustainability, and the preservation of folk culture, thereby holding significant ecological and cultural value. In recent decades, rapid urbanization has profoundly impacted the spatial patterns, ecological environments, and livelihood systems of Linpan in western Sichuan, posing severe challenges to their preservation and development. To investigate the extent and nature of these changes, this study examines the spatiotemporal evolution of Linpan in Chengdu over five time periods from 1980 to 2020, employing both macro- and micro-scale analyses. Settlement types were classified based on their transformation trajectories, and representative cases were selected to identify and interpret the key driving forces behind these changes. The results indicate that: (1) at the macro level, Linpans have undergone a clear transition from small-scale, widely distributed, and irregularly shaped patterns to more centralized, aggregated, and standardized spatial configurations, particularly in the peri-urban areas of Chengdu; (2) at the micro level, the internal composition of Linpan has changed substantially, with a marked decline in woodlands coverage. The original integration of buildings and trees has shifted towards a spatial arrangement characterized by peripheral and fragmented vegetation; (3) Changes in production methods have prompted the spatial restructuring of Linpan settlements, transitioning from uniformly dispersed arrangements to clustered formations along road-adjacent resource points. Concurrent population and housing migration has reduced the total number of Linpan, while individual settlements have increased in size and density. Additionally, planning and construction policies have guided the morphological transformation of Linpan from organically evolved forms to geometrically regular configurations. Full article

Road construction contributes to embodied carbon in infrastructure, with asphalt-bound layers often dominating construction-stage greenhouse gas emissions in flexible pavements. Reclaimed asphalt pavement (RAP) and high-modulus asphalt concrete can reduce virgin material demand and improve structural efficiency, but their sustainability benefit depends on maintaining equivalent pavement performance. This study develops a climate-informed, mechanistic, environmental, and economic Pareto optimization framework for RAP-modified high-performance asphalt concrete (RAP-HPAC) pavement sections in Alberta. The framework couples fitted dynamic modulus master curves, monthly pavement temperature inputs, ALVA layered elastic analysis, Asphalt Institute fatigue and rutting criteria, A1–A5 global warming potential (GWP), and Alberta 2026 installed unit-price cost data. The RAP-HPAC mixture contains 50% RAP and was designed through a balanced mix design to target approximately 80% effective RAP binder activation. Three traffic classes were evaluated: 731, 1300, and 5426 ESAL/day/direction, each with 2% annual compound growth over a 20-year design period. Relative to independently optimized conventional HMA controls, Pareto-selected RAP-HPAC sections reduced P50 construction-stage GWP by approximately 19–30% and first cost by approximately 6–11% at a conservative 0.90× RAP-HPAC cost multiplier. The results show that RAP-HPAC is most beneficial when used as a structural-bound base that replaces conventional asphalt-bound capacity while preserving sufficient granular support. The framework provides a reproducible design-stage approach for comparing recycled high-modulus asphalt mixtures using performance, carbon, and cost criteria simultaneously. Full article

Train-induced vibrations pose a significant threat to foundation pit slopes adjacent to railways during parallel construction or line renovation projects. To address this issue, this paper proposes a periodic steel-sheet pile barrier for vibration mitigation in narrow construction sites. Firstly, field tests were conducted along the Qinbei Railway in China. The acceleration time history and dominant frequency (27.6 Hz) of ground vibrations were obtained. Secondly, based on periodic structure theory, the dispersion relations and band-gap characteristics of periodic steel-sheet piles were analyzed using the finite element method. Parametric studies were then performed to investigate the effects of key factors, including periodic constants, pile spacing and pile count per unit cell, and construction deviations, on the band-gap boundaries and width. Subsequently, frequency-domain, time-domain, and slope stability analyses were carried out to evaluate the isolation performance. The results show that the optimized barrier, with parameters of a = 1.6 m, D = 0.1 m, n₁ = n₂ = 4, and L = 2S, reduced the peak acceleration by 70% and achieved a vibration reduction of up to 88% at the dominant frequency. Furthermore, slope stability analysis revealed that the barrier increased the factor of safety from 1.16 to 1.46, exceeding the code-required minimum of 1.2–1.3. This study provides a potentially cost-effective and construction-friendly solution for protecting temporary foundation pit slopes from train-induced vibrations in railway-adjacent areas. Full article

Background: Clinical reasoning is a vital competency for safe nursing practice, yet no validated Arabic instrument exists to assess this skill among nursing students in Saudi Arabia. Aim: This study aimed to translate, culturally adapt, and psychometrically evaluate the Arabic version of the Clinical Reasoning Scale (CRS) and to investigate clinical reasoning among Saudi nursing students. Methods: This methodological instrument validation study with a cross-sectional survey component was conducted in Saudi Arabia between January 2024 and May 2025 among nursing students. The Arabic Clinical Reasoning Scale (CRS-A) was translated and culturally adapted in accordance with the WHOQOL Group guidelines for instrument translation. Content validity was assessed by 10 experts, and construct validity was evaluated using exploratory factor analysis (n = 365). The response rate was 98.65%. Internal consistency was evaluated using Cronbach’s alpha (n = 365), and test–retest reliability (n = 30) was measured with the Intraclass Correlation Coefficient (ICC) over a two-week period. Descriptive statistics, one-way analysis of variance (ANOVA), and independent sample t-tests were also performed. Results: The tool’s content validity (S-CVI = 0.98) was confirmed by a panel of experts. The CRS-A demonstrated excellent temporal stability (ICC = 0.95, p < 0.001) and internal consistency (Cronbach’s α = 0.935). The exploratory factor analysis showed that the 16 items’ factor loadings ranged from 0.542 to 0.807, and three factors accounted for 64.33% of the total variance. Students self-reported agreement with clinical reasoning abilities (mean scores: 3.81–4.18). No significant differences in clinical reasoning were found by age (p = 0.102) or gender (p = 0.226), but significant differences were found by Cumulative Grade Point Average (CGPA) (p < 0.001). Conclusions: The Arabic Clinical Reasoning Scale demonstrated preliminary psychometric performance for measuring clinical reasoning among Arabic-speaking student nurses. It provides educators with a valuable tool for identifying learning needs and evaluating educational interventions. Full article

Background/Objectives: Chronic home oxygen therapy—long-term oxygen therapy (LTOT)—improves survival and quality of life in chronic respiratory failure when used ≥15 h/day, but adherence is frequently suboptimal and specific patient-reported outcome measures (PROMs) are scarce. To develop, validate and apply a specific PROM for patients on LTOT. Methods: A prospective observational cohort study was conducted at San Juan de Alicante University Hospital (April 2024–December 2025) following a four-stage process: conceptual framework definition and expert workshop, content validation and item reduction, cognitive interviews with pilot reliability testing (n = 25), and field application to 120 consecutive chronic LTOT users. The LTOT-PROM was designed to capture the patient-perceived impact attributable to LTOT during the previous 4 weeks. Internal consistency was assessed with Cronbach’s α and test–retest reproducibility with the intraclass correlation coefficient (ICC). Results: The final instrument comprises 15 scored items in two dimensions—Daily Activity (9 items) and Adverse Effects (6 items)—plus one ambulatory-only mobility item excluded from the total score. Cronbach’s α was 0.814 (95% CI 0.681–0.906) for Daily Activity, 0.743 (95% CI 0.548–0.872) for Adverse Effects and 0.808 (95% CI 0.677–0.902) for the total scale; total ICC(A,1) was 0.890 (95% CI 0.767–0.950). Among the 120 patients (62 men, 58 women; mean age 78 ± 13 years; mean therapy duration 40 ± 32 months), 68% reported reduced effort for daily activities, 66% reported a reduction in dyspnoea and 67% reported improved self-confidence; 49% reported morning airway dryness and 7% abandoned the equipment due to nasal dryness or rhinitis. Conclusions: The LTOT-PROM is a brief, reliable and reproducible oxygen-specific instrument for assessing the recent patient-perceived impact of LTOT in routine clinical practice. Further studies should evaluate structural validity, external validity and the relationship between LTOT-PROM scores and objective adherence measures. The construct was predefined as the patient-perceived impact attributable to LTOT during a standardised 4-week recall window, and cognitive interviews confirmed that respondents interpreted the items as experienced benefit/burden during that period rather than as week-to-week symptom change. Full article

This study compares the performance of time-series (TS) and cross-sectional (CS) momentum strategies in the Taiwan stock market from January 1993 to December 2025. Using a sample of 1169 listed and delisted firms, we construct five TS and five CS momentum strategies across multiple lookback and holding periods, resulting in 80 TS and 80 CS strategy specifications. Strategy performance is evaluated using annualized average excess returns (AERs), certainty equivalent returns (CERs), CAPM alphas, and Fama–French three-factor (FF3) alphas. The results show that volatility-scaled strategies significantly outperform conventional momentum strategies. On average, TS strategies generate higher returns and superior risk-adjusted performance than CS strategies. Decomposition analysis indicates that momentum profits are primarily driven by long positions, while short positions become more important during market crash periods. Overall, the findings highlight the importance of volatility management in enhancing momentum profitability in the Taiwan stock market. Full article

Background: Co-prescribing opioids and gabapentinoids (GABA, gabapentin and pregabalin) is associated with increased risk of falls, fractures, opioid overdose and deaths. The Centers for Disease Control and Prevention (CDC) in 2016 and the Food and Drug Administration (FDA) in 2019 recommended caution in such co-prescribing. A key step in updating policy and revising prescribing guidelines aimed at reducing opioid and GABA co-use and its associated consequences is a thorough understanding of the prescriber and the patient factors associated with co-use. We thus examined national trends and patterns in opioid and GABA co-prescribing among Medicare beneficiaries from 2017 to 2022. Methods: We conducted a retrospective study of Medicare beneficiaries with ≥90 consecutive days of opioid use from 2017 to 2022. The study outcome was GABA use during the 90-day opioid use episode. A multivariable logistic regression model was constructed to examine the patient, prescriber and prescription factors associated with receiving a GABA prescription. Results: Our sample comprised 8035 opioid-only and 2818 opioid and GABA users. Non-cancer (e.g., back and neuropathic) pain was a more common diagnosis in the opioid and GABA cohorts than in the opioid-only cohorts. The opioid-GABA co-prescribing rate did not substantially change (2017: 24.5%, 2019: 28.2% and 2022: 25%). Co-prescribing rates were higher in non-white patients, those on Medicaid and Medicare, and those whose initial Medicare entitlement was not based on age. Tramadol and hydrocodone were the most prescribed opioids. Approximately 33% of opioid and GABA users started with an initial daily GABA dose of ≥1200 mg. In the 12-month lookback period, patients on opioids and GABA had nearly 17 clinic visits to approximately 8 different providers. Factors associated with co-prescribing were seeing pain physicians (odds ratio = 1.29, 95% confidence interval-[CI] = 1.11–1.50), having more healthcare encounters (6–11 visits, odds ratio-[OR] = 1.19, 95% CI = 1.02–1.39; 12–19, OR = 1.20, 95% CI = 1.00–1.43; 20+, OR = 1.27, 95% CI = 1.03–1.57) and seeing >10 providers (OR = 1.40, 95% CI = 1.12–1.73). Conclusions: One in four Medicare beneficiaries with long-term opioid use received opioid and GABA prescriptions. Our findings of association in co-prescribing with multiple visits to different clinics/prescribers can inform the development of public health policy and practice guidelines (e.g., prescription-drug monitoring program checks within electronic medical records, EMR alerts with opioid and GABA co-prescribing) to potentially reduce opioid and GABA prescriptions and associated adverse outcomes. Full article

Scientific studies of mine closure and ecosystem management have become very important since the rate of coal mine closures in China has increased rapidly over the last decade. This study first analyzed spatiotemporal changes in land use and ecosystem services value (ESV) during the period 2000–2020 around the Kailuan Mining Area in Tangshan City. The area has a history of over 100 years of continuous mining activities in the region. The analyses used the PLUS model, multi-scenario simulation, and ESV equivalent factor method and multi-source data on land use, mining activities, socioeconomic factors, and climatic conditions. The study then projected land-use changes and spatiotemporal ESV characteristics for the year 2030 for two alternatives: (1) the Current Development Scenario (CDS), representing the current pace of development without mine closure; and (2) the Ecological Restoration Scenario (ERS), representing mine closure and ecological restoration. Key results include: (1) during 2000–2020, cultivated land and construction land were the primary land uses, with the overall trends showing decrease in cultivated, forest, pasture, and unused lands, varying water use areas, and continuously increasing construction land; (2) the revised ESV results show that total ESV declined from 31.27 million USD in 2000 to 25.30 million USD in 2020, a net decrease of 6.19 million USD, mainly because of cropland loss and degradation of forest and grassland; and (3) for 2030, the CDS projected a continued decline in total ESV to 24.30 million USD, whereas the ERS increased total ESV to 26.50 million USD, which is 2.19 million USD higher than the CDS and 1.20 million USD higher than the 2020 baseline. Compared with the CDS, the ERS increased cropland by 13.20 km² and reduced construction land by 10.06 km², indicating that reclaiming subsided water bodies and idle construction land into cropland and restored ecological land can enhance ecosystem services while mitigating subsidence-related risks. The framework can support data-driven post-mining land-use planning and ecological management in resource-based regions. Full article

To address the low-voltage violations that may occur in distribution networks with high penetration of distributed photovoltaic (PV) during sunset and evening peak periods under extreme high-temperature conditions, this paper establishes a source–grid–load electro-thermal coupling model that accounts for load thermal accumulation, transient conductor thermal inertia, temperature-dependent line impedance, and PV thermal derating. Based on a soft safety lower bound and a risk-preference utility function, the probability of voltage violation, violation depth, and expected violation duration are introduced to construct node-level and system-level comprehensive risk factors. The cumulant method combined with the Cornish–Fisher expansion is used to reconstruct the probability distribution of nodal voltages, enabling analytical risk calculation. Simulation results on the IEEE 33-bus system at 45 °C show that the proposed method can quantitatively reflect the temporal variations of nodal voltage distributions, physical violation depth, dimensionless severity utility, and expected violation duration, and identify weak nodes in the later part of the evening peak, providing a reference for risk early warning in distribution networks under extreme heat. Full article

The energy transition constitutes not only a technological and regulatory challenge but also a communicative and cultural one, in which corporate narratives play a decisive role in shaping social understanding, legitimacy, and trust. This study examines how major energy companies operating in Spain construct the narrative of the energy transition through their corporate discourse and evaluates the extent to which these narratives integrate pedagogical and relational dimensions oriented toward society. Using a qualitative content analysis approach supported by lexical frequency analysis as a heuristic tool, the study analyzes the CEO or Chair letters published in sustainability reports by four energy companies—Iberdrola, Endesa, Naturgy, and Holaluz—over a five-year period (2020–2024), comprising a total of 20 reports, from which 18 CEO/Chair letters were extracted and treated as a single analytical unit. Two reports (Iberdrola and Naturgy, 2024) adopted the ESRS/CSRD format directly, eliminating the traditional chairperson’s letter. To triangulate and contextualize the documentary analysis, a two-round Delphi study was conducted with 11 independent experts. The findings reveal a predominantly technical and self-referential discourse focused on corporate strategy, performance, and regulatory compliance, with a limited presence of explanatory or citizen-oriented narratives. Despite increasing terminological convergence driven by regulatory standardization, the analysis reveals persistent divergence in narrative framing, with the challenger company articulating purpose-driven and citizen-empowerment frames largely absent from incumbent discourse. The Delphi results reinforce these findings, emphasizing the need to strengthen pedagogical clarity, accessibility, and relational orientation in energy communication. On this basis, the study proposes a relational model of energy communication that highlights narrative mediation, social intelligibility, and stakeholder-oriented discourse as key factors for enhancing legitimacy and trust in the context of the energy transition. The analysis further identifies a structural tension between regulatory standardization and narrative capacity, exemplified by the elimination of the CEO letter in one company’s 2024 report following ESRS adoption. Full article

Clarifying the sources of disparity and the systemic structure of influencing factors behind China’s economic resilience is crucial for promoting regional coordinated development and ensuring national security. This study constructs an evaluation index system based on the DPSIR model and employs the entropy method to measure China’s economic resilience from 2008 to 2023, examining its temporal evolution and spatial distribution. A bi-dimensional decomposition method of Gini coefficient is applied to examine disparities from both spatial and structural perspectives. Furthermore, the DEMATEL-ISM model is employed to reveal the systemic structure of influencing factors. The findings reveal that: (1) China’s economic resilience steadily improved during the study period, showing a spatial gradient of “Eastern > Central > Northeastern > Western,” with its geographic center shifting southeastward, reflecting strong spatial dependence. (2) Disparities in economic resilience have generally widened. Inter-regional differences are the main source of spatial disparities, while variations in response dominate the structural disparities. Initially, disparities were mainly due to differences in influence between eastern and western regions, but by the end of the period, disparities in driving forces became the key contributor. (3) Influencing factors follow a four-level, three-stage hierarchical structure. Foreign capital withdrawal risks, innovation investment, technological progress, factor supply, and the output of opening-up constitute deep-level factors influencing economic resilience. This study refines the evaluation framework of economic resilience and provides important references for understanding the disparities in China’s economic resilience and developing targeted improvement strategies. Full article