Search Results (2,125)

Background: Nutrition and sleep are critical determinants of athletic performance and recovery. Direct comparative research between endurance and strength–power athletes remains limited. This study aimed to evaluate and compare nutritional knowledge, dietary habits, sleep quality, and Body Mass Index between ultramarathon runners and American football players, as well as to explore independent predictors of sleep quality. Methods: A cross-sectional study was conducted among 231 male athletes. To address group size disparity and mitigate statistical bias, a random undersampling technique was applied to create a balanced cohort of 86 athletes comprising 43 ultramarathon runners and 43 American football players. Nutritional parameters were assessed using the Kom-PAN questionnaire. Sleep quality was evaluated using the Pittsburgh Sleep Quality Index. Between-group comparisons were performed using the Mann–Whitney U test with False Discovery Rate correction. An integrated multiple regression model was constructed to identify predictors of global sleep quality. Results: Ultramarathon runners demonstrated significantly better overall sleep quality (p = 0.026) and higher nutritional knowledge (p < 0.001) compared to American football players. Differences in adherence to pro-healthy and non-healthy dietary patterns were not statistically significant after False Discovery Rate correction. The integrated multiple regression model revealed that the athletic discipline was the primary independent predictor of global sleep quality (p = 0.001), while dietary variables did not exhibit a significant independent effect. Furthermore, higher Body Mass Index was independently associated with better sleep scores within the multivariate model (p = 0.008). Conclusions: Significant sport-specific differences exist in BMI, nutritional knowledge, and sleep quality. Global sleep quality appears to be primarily associated with the specific physiological and environmental demands of the athletic discipline rather than individual dietary factors, which were not independently significant in the multivariable model. These findings suggest that recovery strategies in strength–power athletes may require a broader, multifactorial approach beyond nutritional education alone. Full article

Light hydrocarbons in shale oil readily volatilize during conventional coring, surface handling, storage, and laboratory preparation. The resulting evaporative loss causes systematic underestimation of Rock-Eval S₁ peak (free hydrocarbons measured by programmed pyrolysis), which can bias oil-bearing evaluation, sweet-spot delineation, and resource assessment. Here we investigate Chang 7₃ lacustrine shale oil in the Ordos Basin (China) using frozen cores recovered by pressure-retained coring from four wells. Time-series Rock-Eval pyrolysis and thermal desorption–gas chromatography (TD–GC) were used to quantify the magnitude, temporal evolution, and practical equilibrium time of light-hydrocarbon loss and to establish a practical restoration model. S₁ decreases with storage time and exhibits a clear two-stage behavior. Shale shows a rapid-loss stage during 0–90 days, followed by a practical equilibrium stage after 90 days (S₁ change less than 5%). Sandstone interbeds lose light hydrocarbons faster and more completely, reaching practical equilibrium after 60 days. TD–GC indicates that the lost fraction is dominated by n-alkane components lighter than C₁₃, with gaseous hydrocarbons showing the greatest depletion; medium and heavy fractions decrease modestly. Loss is coupled with progressive desorption from kerogen and clays, leading to enrichment of heavier components in the residual free hydrocarbons and a shift of the modal carbon number toward higher values. At the shale equilibrium time, total organic carbon (TOC) and vitrinite reflectance (R_o) jointly control the restoration factor K. We propose a two-parameter restoration model: K = (0.4024·ln (TOC) + 0.821)·(0.652·R_o + 0.4292). Applying the model to more than 50 conventionally cored wells reveals that the Qingyang–Zhengning area in the southwestern basin is the principal enrichment zone of original free hydrocarbons, followed by the Jiyuan area in the north and the Huachi area in the central basin, whereas the eastern basin is relatively depleted. The workflow provides a robust and transferable approach for correcting S₁ and improving shale-oil evaluation in lacustrine systems. Full article

Kang Youwei (1858–1927) reimagined Confucius as the founding religious leader of Confucianism, a conceptual framework underpinning his entire ideological system of Confucian thought. Yet existing scholarship has largely overlooked systematic analysis of this theoretical reconstruction. Influenced by the impact–response paradigm, many studies have also neglected Kang’s core intention to pursue cross-civilizational dialogue and establish a universalist Confucianism through such interpretive innovation. Faced with the late-Qing predicament of the imbalance between a dominant Western world and a weakened China, Kang thoroughly redefined Confucius by shifting his image from a sage who transmitted rather than created ancient wisdom to a religious authority who reformed institutions through classical precedents. This paper argues that Kang’s reinterpretation was neither a simplistic religious adaptation nor a conservative defence of traditional culture. His fundamental aim was to correct Western-centric bias, facilitate equal Sino-Western civilizational dialogue, critique inherent structural dilemmas of modern Western civilization, and propose the Confucian Way as a viable solution to these deep-rooted crises. Full article

In sandstorm environments, a large number of suspended particles in the air absorb and scatter light, causing strong color bias, low contrast, and blurred details in images. These degradations reduce the reliability of computer vision applications in surveillance systems, intelligent transportation systems, unmanned aerial vehicle monitoring, and outdoor autonomous driving systems. A complete sandstorm image enhancement method was developed in this study by combining sky detection, color correction, contrast enhancement, and adaptive dark channel prior (ADCP) dehazing. The Lab color space was used to correct the color bias. The L channel was enhanced using normalized gamma correction and contrast-limited adaptive histogram equalization to improve brightness and contrast. Then, the sky region is detected to avoid over-processing, preserving the natural appearance of the sky region. Finally, ADCP is applied to non-sky regions for further dehazing. Experiments show that the proposed method provides better subjective and objective performance compared to other algorithms. Full article

Impacted mandibular third-molar surgery commonly causes early postoperative pain, swelling, and trismus. This randomized, controlled, three-arm parallel trial evaluated whether intra-alveolar corticosteroid delivery via an absorbable gelatin sponge improves postoperative recovery compared with a saline control. Fifty-five patients were assessed for eligibility; 37 healthy adults (18–35 years) undergoing standardized mandibular third-molar extraction were randomized to dexamethasone 8 mg (Decort^®), methylprednisolone 40 mg (Prednol^®), or control (saline), all applied intra-alveolarly using a gelatin sponge carrier. Doses were selected using standard systemic glucocorticoid equivalence tables as a pragmatic potency reference, acknowledging unknown intra-alveolar pharmacokinetics/bioavailability. The prespecified primary endpoint (used for sample size planning) was postoperative Day 1 VAS pain; key secondary endpoints were Day 1 analgesic consumption and Day 3 facial swelling. Pain (VAS), analgesic use, trismus, and facial swelling (tragus–pogonion, tragus–labial commissure, and angulus–canthus distances) were assessed on postoperative Days 1, 2, 3, and 7 by a blinded evaluator. Two participants in the methylprednisolone group did not attend postoperative visits. To address potential attrition bias, an Intention-to-Treat (ITT) sensitivity analysis using conservative control-median imputation was performed alongside the available-case analyses. A global False Discovery Rate (FDR) correction was also applied to control for multiplicity. In both analyses, the steroid groups showed lower Day 1 pain scores than the control group. Methylprednisolone was associated with lower Day 3 swelling values than control for the tragus–pogonion and angulus–canthus measurements. These findings should be interpreted as preliminary, given the small sample size, linear swelling measurements, and lack of blinding verification. Full article

East Africa is highly vulnerable to climate change due to limited adaptive capacity and strong reliance on rain-fed agriculture. Ethiopia, in particular, experiences recurrent socio-economic losses from droughts and floods. This study presents a national-scale assessment of observed (1981–2010) and projected (2041–2100) changes in extreme seasonal precipitation across Ethiopia using ten ETCCDIs. High-resolution Enhancing National Climate Services (ENACTS) observations and bias-corrected outputs from a selected ensemble of CMIP6 models under SSP2-4.5 and SSP5-8.5 scenarios are used to assess historically trends and future extreme precipitation, respectively. Historical trends show increases in extreme precipitation during the Kiremt (JJAS) season, particularly over the northwestern, western, and southwestern highlands; however, most of these increases are not statistically significant. In contrast, the Belg (FMAM) season exhibits widespread declines, which are also largely not statistically significant. Future projections suggest increases in total precipitation (PRCPTOT), heavy (R10) and very heavy rainfall days (R20), very wet days (R95p) and extremely wet days (R95p), and rainfall intensity (SDII) over northwestern, western, southwestern, and parts of northeastern Ethiopia during JJAS. During FMAM, PRCPTOT is projected to increase in the northern and northwestern regions, while decreases are expected in the northeastern and southeastern regions. The Awash and Tekeze basins emerge as key hotspots of change, indicating potential seasonal shifts and an increased likelihood of extreme weather in these regions. Despite inter-model uncertainty, the results highlight the need for flexible, uncertainty-informed adaptation strategies to enhance climate resilience in Ethiopia. Full article

Infrared focal plane arrays (IRFPAs) often suffer from spatiotemporal nonuniformity that persists after conventional two-point nonuniformity correction (NUC), especially under temperature drift and time-varying readout conditions. These residuals are typically structured, including column-group striping caused by shared column-end circuits and row-wise baseline/common-mode drift induced by row-scanning paths. We propose a structured, digital-twin-inspired detector-side refinement of two-point NUC that augments the bias term with interpretable low-dimensional components: a static column bias vector capturing group-correlated residuals and a row-related structured term consisting of a static row baseline and a frame-synchronous common-mode component with row-dependent sensitivity, while keeping the two-point gain/offset backbone unchanged. Rather than representing a full system-level digital twin of the infrared payload, the proposed framework serves as a detector-side virtual representation of dominant readout-induced structured residual states that can be estimated and updated from calibration data. Experiments on blackbody calibration data across multiple temperature points demonstrate that the column-related structured component significantly reduces group-wise column residuals, the row-related structured component suppresses time-varying row striping, and the combined method improves both column- and row-direction metrics consistently across temperatures. Full article

Multi-campus AI data centers procure identical hardware and service SKUs across geographically heterogeneous locations, yet finance and operations require a single system-level benchmark (“world price”) per SKU for budgeting, chargeback, and capacity planning. Naive deployment-weighted aggregation preserves total cost but can induce Simpson-type aggregation bias, where heterogeneous location mixes reverse global SKU rankings and weaken managerial decision signals. This study formalizes the problem of location-robust, cost-preserving aggregation and develops two mathematically structured operators for production cost pipelines. The first operator applies a two-way fixed-effects decomposition to separate global SKU effects from campus-specific premia, followed by normalization to guarantee exact cost preservation. This yields an interpretable benchmark that performs well when campus coverage is sufficiently broad and location effects remain approximately additive. The second operator solves a constrained convex common-weight optimization, producing a unified set of non-negative campus weights that preserves total cost while providing the strongest protection against dominance reversals in the ordered setting. Simulation experiments and a semi-real calibrated AI datacenter OPEX illustration show that both operators substantially improve ranking stability relative to naive blending, while the convex operator serves as the more conservative safeguard under adverse heterogeneity. The resulting detect–correct–validate workflow provides a scalable decision-support framework for robust cost aggregation in distributed AI infrastructure and illustrates how symmetry-preserving aggregation operators can stabilize benchmarking in large heterogeneous systems. Full article

Satellite-derived bathymetry (SDB) offers a practical alternative for mapping shallow reefs in remote oceanic settings where acoustic surveys are costly and logistically constrained. Here we benchmark PlanetScope 8-band (3 m) surface reflectance—an underused commercial constellation for reef SDB—using ICESat-2 Advanced Topographic Laser Altimeter System (ATLAS) ATL03 photon data (Release 006) as independent vertical control. Seventeen ATL03 ground tracks (2019–2025) were processed using geometric filtering, photon classification, and explicit air–water refraction correction. This yielded 5171 candidate seafloor observations, of which 5021 were co-located with valid PlanetScope water pixels after Usable Data Mask screening (UDM2/UDM2.1), sun-glint correction, and reflectance quality screening. Four SDB formulations (Lyzenga, Bierwirth, and Stumpf) were calibrated and independently validated using depth-stratified train/validation partitions (70/30, 80/20, and 90/10). Across partitions, the multiband polynomial model of Lyzenga 2006 generalized best (R² = 0.843–0.859; RMSE = 1.734–1.813 m; bias = −0.070 to −0.081 m), followed by Bierwirth (R² = 0.826–0.845; RMSE = 1.818–1.904 m). Lyzenga 1985 reported lower skill (RMSE ≈ 3.1 m), while the Stumpf log-ratio failed in independent validation. ICESat-2 photon bathymetry provides repeatable point-based control in clear waters but remains less precise than echo sounding due to photon classification and spatial-support effects; therefore, uncertainties and applicability limits must be reported. Overall, PlanetScope 3 m, 8-band surface reflectance supports reproducible reef-scale SDB in Seaflower under the evaluated conditions, with Lyzenga 2006 as a robust baseline. Full article

In this article, we study scalar-on-function regression with functional covariates observed through replicated measurements subject to measurement error. Treating replicated curves as surrogates of an underlying latent process, the proposed framework resolves the identifiability issues commonly encountered in functional measurement error models. Through functional principal component analysis, the model is represented as a finite-dimensional hierarchical linear measurement error model. Parameter estimation is carried out using an expectation-maximization algorithm, and alternative correction strategies based on adjusted regression calibration and simulation extrapolation are also considered for comparison. Simulation studies demonstrate the advantages of explicitly accounting for measurement error in terms of bias reduction and estimation stability. An application to soybean yield prediction in Illinois, using meteorological variables contaminated by measurement error, illustrates the practical value of the proposed approach. Full article

Understanding habitat use and connectivity in estuarine fishes is essential for effective conservation and management. In this study, otolith microchemistry was applied to investigate habitat use and connectivity of the estuarine catfish Genidens genidens across three estuaries in southeastern Brazil. A total of 58 individuals were analyzed using laser ablation inductively coupled plasma mass spectrometry, focusing on strontium-to-calcium (Sr:Ca) and barium-to-calcium (Ba:Ca) ratios. Variations in elemental ratios along otolith transects were used to infer individual ontogenetic patterns along the estuarine–marine gradient. Most individuals exhibited combined use of estuarine and marine environments, while trajectories restricted to freshwater were rare. The apparent complexity of chemical profiles tended to increase with age; however, this pattern disappeared after correction for size-related bias, suggesting that age itself did not significantly influence habitat-use transitions. These patterns are consistent with ecological plasticity and partial migration within populations of G. genidens, although they may also reflect exposure to variable environmental conditions. Sr:Ca ratios were useful indicators of salinity-related transitions, whereas Ba:Ca ratios provided complementary information associated with continental influence. Overall, this study highlights the applicability of otolith microchemistry for investigating habitat-use patterns in estuarine fishes and reinforces the ecological importance of estuaries for feeding, growth, and recruitment in G. genidens, while acknowledging inherent limitations related to environmental variability and proxy interpretation. Full article

Large-scale integration of photovoltaics (PV) introduces complex source-load temporal volatility and grid-connection/off-grid transitions. Traditional static reliability assessments fail to capture these dynamics, resulting in “considerable deviations” in system indices. This paper proposes a reliability evaluation framework that couples temporal source-load trajectories with a multi-stage fault recovery process. Unlike traditional methods that rely on a single static snapshot, the proposed model evaluates the system state across a continuous 5-h restoration window. The novelty lies in the unique integration of a Dynamic Time Warping (DTW)–Kmedoids method to preserve temporal phase-shifts and a multi-stage Mixed-Integer Linear Programming (MILP) model to simulate PV grid-connection transitions throughout this window. By capturing the intra-outage evolution of sources and loads, the framework fundamentally corrects the “considerable deviations” of static assessments. Case studies demonstrate high precision with an error of less than 0.71% and a 20-fold speedup. Crucially, the framework corrects the 22.31% risk underestimation bias inherent in static models by tracking real-time source-load evolution. This confirms that temporal coordination performance is the primary determinant of the reliability ceiling in active distribution networks. The findings reveal that the precise alignment of intermittent generation and fluctuating demand defines the actual operational safety margin, providing a superior quantitative foundation for grid resilience enhancement. Full article

Accurate rainfall information is essential for rainfall–runoff modeling in monsoon-influenced basins, where pronounced spatial variability and limited gauge coverage introduce significant uncertainty. Satellite precipitation products provide spatially continuous estimates but are affected by systematic biases, and improvements in statistical rainfall accuracy do not necessarily translate into hydrologically consistent model forcing. This study interpreted satellite rainfall bias correction through a rainfall–runoff framework in the Phetchaburi River Basin, Thailand, using the DWCM-AgWU hydrological model. Simulations were driven by gauge observations and multiple satellite-based rainfall products (GSMaP, CMORPH, CHIRPS, and PERSIANN-CCS), with bias correction applied using Linear Scaling and Quantile Mapping under rainfall-specific calibration. Results showed that bias correction significantly modified rainfall characteristics in distinct ways. Linear Scaling primarily preserved temporal and spatial structure while adjusting rainfall magnitude, whereas Quantile Mapping improved the distributional representation of rainfall intensities. These differences propagated through hydrological processes, leading to systematic variations in runoff responses across multiple metrics, including water balance consistency, peak magnitude, and timing errors. This suggests that each method performs differently depending on the aspect of system response. Rather than identifying a universally optimal method, the findings highlight trade-offs in how rainfall correction strategies influence hydrological system response. Runoff behavior is interpreted as a process-level indicator of rainfall representation, emphasizing that hydrological consistency depends not only on rainfall accuracy but also on its interaction with model structure. These results suggest a process-oriented perspective for interpreting the role of satellite rainfall products in regulated and monsoon-affected basins. Full article

Recent global events have slowed progress toward achieving the Sustainable Development Goals (SDGs), making robust sustainability reporting (SR) systems critical for monitoring and corrective actions. While research on the link between corporate sustainability performance (CSP) and corporate financial performance (CFP) is extensive, the specific role of sustainability reporting as a communication channel remains insufficiently explored. Therefore, the objective of this paper is to address this gap in the literature by assessing the relevance of sustainability reporting for modeling the relationship between CSP and CFP. In this study, a univariate meta-analysis based on a PRISMA screening framework was performed to assess the unidirectional relationship between SR and CFP, specifically investigating whether SR acts as a moderating or mediating factor in the CSP-CFP nexus. The analysis is limited to 19 high-quality articles published in top-tier accounting journals between 2014 and 2024 to minimize publication bias and ensure reliability. The meta-analysis reveals no statistically significant moderating effect of SR on CFP. Instead, the results confirm a significant mediating effect, particularly when considering the presence of sustainability reports rather than just their specific content. These findings suggest that SR serves as a vital catalyst for corporate communication, providing more positive effects in voluntary compared to mandatory disclosure settings. This paper has both theoretical and practical implications, which are mainly relevant to standard-setters for assessing the efforts of SR disclosure regulation, and is of fundamental importance to managers as it indicates that SR does not relate solely to the practice of conformity, but rather to essential channels of communication and value creation. Full article

Micro-public space (MPS) regeneration is typically evaluated at the point of delivery, yet long-term performance depends on whether everyday stewardship can be sustained thereafter. This study reframes neighbourhood social capital as a governance–environment signal reflecting coordination capacity and examines whether residents’ willingness to participate in post-regeneration co-management is primarily appraisal-driven (perceived value, attitude, and perceived behavioural control) or coordination-driven via a residual direct channel consistent with routine governance. A cross-sectional survey of adults residing within walkable catchments of five regenerated MPS sites in Nan’an District, Chongqing, China ($N=477$), was conducted. An integrated Stimulus–Organism–Response × TPB model was estimated using WLSMV with ordered categorical indicators; indirect effects were assessed via bias-corrected bootstrap confidence intervals. Coordination capacity was strongly associated with perceived value, participation attitude, and perceived behavioural control. In the joint model, only perceived value retained a statistically reliable positive association with stewardship willingness, whereas the incremental contributions of attitude and perceived behavioural control were negligible once the stimulus was included. A residual direct association from coordination capacity to willingness persisted beyond the appraisal block, supporting a direct-dominant interpretation; bootstrap analyses yielded no robust evidence for mediation (BCa 95% CIs crossed zero). These findings suggest that sustaining regenerated micro-spaces requires low-friction governance designs that minimise coordination costs, reinforce soft accountability, and render institutional responsiveness visible to residents. Full article