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This study aimed to assess the effects of three flat running surfaces (i.e. athletic track, road, and gravel) on the critical power (CP) parameters and running patterns of highly trained trail runners. Within a two-week timeframe, thirteen male and seven female trail runners underwent three testing sessions to evaluate CP and the work over CP (W'). Each session comprised two time trials of 9 and 3 minutes, separated by a 30-min rest, in which a Stryd running power meter was used to collect the data. The CP and W' were subsequently determined using the inverse of time linear CP model. There were no significant differences in CP across the different surfaces (F= 1.4; p = 0.253). However, significant differences were found in W' (F= 3.8; p = 0.032). Specifically, athletes displayed a higher W' on the track compared to gravel (1.8 [0.2 to 3.4] kJ, p = 0.026), and higher, though non-significant, W' on the road compared to gravel (0.9 [-0.7 to 2.5] kJ, p = 0.478). Regarding the running patterns, the athletes displayed lower duty factor on the track compared to gravel (-1.1 [-2.2 to -0.1] %; p = 0.030) as well as on the road compared to gravel (-1.1 [-2.0 to -0.1] %; p = 0.019). In conclusion, the CP remained stable across surfaces, whereas W' was reduced on gravel compared to track and road. The differences in W' were accompanied by significant changes in the athletes' running patterns. Specifically, athletes exhibited a lower duty factor on the track and road compared to gravel, resulting in a more aerial running form.
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http://dx.doi.org/10.1007/s00421-025-05840-z | DOI Listing |
Bioresour Technol
September 2025
Key Laboratory of the Three Gorges Reservoir Region's Eco-Environment, Ministry of Education, Chongqing University, Chongqing 400045, China; College of Environment and Ecology, Chongqing University, Chongqing 400045, China. Electronic address:
Bioclogging from organic accumulation significantly limits efficiency and longevity of constructed wetlands (CWs). In this study, hematite was introduced to enhance the oxidation of organics by dissimilatory iron reduction (DIR). Compared to gravel CWs (G-CWs), hematite CWs (H-CWs) enhanced the removal of COD, ammonium, and phosphate by 12 %, 46 %, and 72 %, while reducing CH and NO emissions by 69 % and 36 %.
View Article and Find Full Text PDFGround Water
September 2025
Department of Earth and Environmental Sciences, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
Borehole nuclear magnetic resonance (NMR) can be used to estimate the hydraulic conductivity (K) of unconsolidated materials. Various petrophysical models have been developed to predict K based on NMR response, with considerable efforts on optimizing site-specific constants. In this study, we assessed the utility of NMR logs to estimate K within highly heterogeneous glaciofluvial deposits by comparing them with K measurements from three types of co-located hydraulic testing methods, including permeameter, multi-level slug, and direct-push hydraulic profiling tool (HPT) logging tests.
View Article and Find Full Text PDFJ Hazard Mater
September 2025
Department of Mining Engineering, College of Engineering, University of Kentucky, Lexington, KY 40506, USA. Electronic address:
Occupational exposure to respirable crystalline silica (RCS) remains a significant health concern in metal and nonmetal (MNM) mining operations, contributing to the development of silicosis, lung cancer, and other chronic respiratory conditions. This review examines the prevalence and effects of RCS exposure in MNM mining environments, the toxicity of silica dust, and the effectiveness of regulatory interventions aimed at controlling exposure and mitigating health hazards. Key factors influencing RCS concentrations, including mine type, size, and geographic location, are analyzed, with particular focus on the impact of recent regulatory updates from the Mine Safety and Health Administration (MSHA).
View Article and Find Full Text PDFFront Big Data
August 2025
School of Computer Science and Engineering, Vellore Institute of Technology - Chennai Campus, Chennai, Tamil Nadu, India.
Introduction: OpenStreetMap (OSM) road surface data is critical for navigation, infrastructure monitoring, and urban planning but is often incomplete or inconsistent. This study addresses the need for automated validation and classification of road surfaces by leveraging high-resolution aerial imagery and deep learning techniques.
Methods: We propose a MaskCNN-based deep learning model enhanced with attention mechanisms and a hierarchical loss function to classify road surfaces into four types: asphalt, concrete, gravel, and dirt.
Sci Rep
August 2025
Xi 'an Chuangmiao Technology Co., Ltd., Xi'an, 710065, China.
To address the environmental concerns of oil shale waste (OSW) accumulation and improve road engineering sustainability, this paper proposes a novel cold resistance structure (CRS) incorporating extruded polystyrene (XPS) insulation plates and OSW-modified soil. OSW primarily consists of two components: residual semi-coke from retorting processes and combustion-derived ash residues. The improper disposal of accumulated OSW poses significant environmental risks.
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