Search Results (137)

Improving construction site safety remains a critical challenge in Saudi Arabia’s rapidly growing construction sector, where high accident rates and diverse labor forces demand evidence-based managerial interventions. This study investigated the influence of Managers’ Safety Perceptions and Practices (MSP) on Workers’ Safety Behaviors (WSB) in the Saudi construction industry, emphasizing the mediating roles of Workers’ Safety Awareness (WSA), Safety Competency (WSC), and Safety Actions (SA). The conceptual framework integrates these three mediators to explain how managerial attitudes and practices translate into frontline safety outcomes. A quantitative, cross-sectional design was adopted using a structured questionnaire distributed among construction workers, supervisors, and project managers. A total of 352 from 384 valid responses were collected, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. The findings revealed that MSP does not directly influence WSB but has significant indirect effects through WSA, WSC, and SA. Among these, WSC emerged as the most powerful mediator, followed by WSA and SA, indicating that competency is the most critical driver of safe worker behavior. These results provide robust empirical support for a multidimensional mediation model, highlighting the need for managers to enhance safety behaviors not merely through supervision but through fostering awareness and competency, providing technical training, and implementing proactive safety measures. Theoretically, this study contributes a novel and integrative framework to the occupational safety literature, particularly within underexplored Middle Eastern construction contexts. Practically, it offers actionable insights for safety managers, industry practitioners, and policymakers seeking to improve construction safety performance in alignment with Saudi Vision 2030. Full article

The superhydrophobic coatings for outdoor use need to be exposed to sunlight for a long time; therefore, their UV-aging resistances are crucial in practical applications. In this study, the primary product of titanium dioxide (P-TiO₂) was used as the raw material. Nano-silica (SiO₂) was coated onto the surface of P-TiO₂ by the acid precipitation method to prepare P-TiO₂-SiO₂ composite particles. Then, they were modified and sprayed simply to obtain a superhydrophobic P-TiO₂-SiO₂/HDTMS coating. The results indicated that amorphous nano-SiO₂ was coated on the P-TiO₂ surface, forming a micro–nano binary structure, which was the essential structure to form superhydrophobic coatings. Additionally, the UV-aging property of P-TiO₂ was significantly enhanced after being coated with SiO₂. After continuous UV irradiation for 30 days, the color difference (ΔE*) and yellowing index (Δb*) values of the coating prepared with P-TiO₂-SiO₂ increased from 0 to 0.75 and 0.23, respectively. In contrast, the ΔE* and Δb* of the coating prepared with P-TiO₂ increased from 0 to 1.68 and 0.74, respectively. It was clear that the yellowing degree of the P-TiO₂-SiO₂ coating was lower than that of P-TiO₂, and its UV-aging resistance was significantly improved. After modification with HDTMS, the P-TiO₂-SiO₂ coating formed a superhydrophobic P-TiO₂-SiO₂/HDTMS coating. The water contact angle (WCA) and water slide angle (WSA) on the surface of the coating were 154.9° and 1.3°, respectively. Furthermore, the coating demonstrated excellent UV-aging resistance. After continuous UV irradiation for 45 days, the WCA on the coating surface remained above 150°. Under the same conditions, the WCAs of the P-TiO₂/HDTMS coating decreased from more than 150° to 15.3°. This indicated that the retention of surface hydrophobicity of the P-TiO₂-SiO₂/HDTMS coating was longer than that of P-TiO₂/HDTMS, and the P-TiO₂-SiO₂/HDTMS coating’s UV-aging resistance was greater. The superhydrophobic P-TiO₂-SiO₂/HDTMS self-cleaning coating reported in this study exhibited outstanding UV-aging resistance, and it had the potential for long-term outdoor use. Full article

Soil structure has an important role in storing and transporting substances, providing natural habitats for soil microorganisms, and allowing chemical reactions in the soil. A complex investigation on factors affecting soil structure characteristics under herbaceous (H), deciduous (D), mixed (M), and coniferous (SP—Scots Pine and NS—Norway Spruce) vegetation was conducted at three experimental stations—Gabra, Govedartsi, and Igralishte, located correspondingly in the Lozenska, Rila, and Maleshevska Mountains in South-West Bulgaria. The data set obtained includes soil structure indicators and physical, physicochemical, chemical, mineralogical, and microbiological parameters of the A and AC horizons of 11 soil profiles. Under different vegetation conditions, soil structure indicators respond differently depending on climatic conditions and basic soil properties. Regarding the plant available water capacity (PAWC), air capacity (AC), and water-stable aggregates (WSAs), the surface soil layers have an optimal structure in Gabra (H, D), Govedartsi (H, SP, NS), and Igralishte (H). The values for the relative field capacity (RFC < 0.6) showed that the studied soils were water-limited. The WSAs correlated with SOC in Gabra, while in Govedartsi and Igralishte, the WSAs correlated with the β-glucosidase known to hydrolyze organic carbon compounds in soil. The information obtained is important for soil quality monitoring under climatic and anthropogenic changes. Full article

The reconstruction of high-resolution (HR) remote sensing images (RSIs) from low-resolution (LR) counterparts is a critical task in remote sensing image super-resolution (RSISR). Recent advancements in convolutional neural networks (CNNs) and Transformers have significantly improved RSISR performance due to their capabilities in local feature extraction and global modeling. However, several limitations remain, including the underutilization of multi-scale features in RSIs, the limited receptive field of Swin Transformer’s window self-attention (WSA), and the computational complexity of existing methods. To address these issues, this paper introduces the NGSTGAN model, which employs an N-Gram Swin Transformer as the generator and a multi-attention U-Net as the discriminator. The discriminator enhances attention to multi-scale key features through the addition of channel, spatial, and pixel attention (CSPA) modules, while the generator utilizes an improved shallow feature extraction (ISFE) module to extract multi-scale and multi-directional features, enhancing the capture of complex textures and details. The N-Gram concept is introduced to expand the receptive field of Swin Transformer, and sliding window self-attention (S-WSA) is employed to facilitate interaction between neighboring windows. Additionally, channel-reducing group convolution (CRGC) is used to reduce the number of parameters and computational complexity. A cross-sensor multispectral dataset combining Landsat-8 (L8) and Sentinel-2 (S2) is constructed for the resolution enhancement of L8’s blue (B), green (G), red (R), and near-infrared (NIR) bands from 30 m to 10 m. Experiments show that NGSTGAN outperforms the state-of-the-art (SOTA) method, achieving improvements of 0.5180 dB in the peak signal-to-noise ratio (PSNR) and 0.0153 in the structural similarity index measure (SSIM) over the second best method, offering a more effective solution to the task. Full article

Multi-angle remote sensing observations play an important role in the remote sensing of solar radiation absorbed by land surfaces. Currently, the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) teams have successively applied the Ross–Li kernel-driven bidirectional reflectance distribution function (BRDF) model to integrate multi-angle observations to produce long time series BRDF model parameter products (MCD43 and VNP43), which can be used for the inversion of various surface parameters and the angle correction of remote sensing data. Even though the MODIS and VIIRS BRDF products originate from sensors and algorithms with similar designs, the consistency between BRDF parameters for different sensors is still unknown, and this likely affects the consistency and accuracy of various downstream parameter inversions. In this study, we applied BRDF model parameter time-series data from the overlapping period of the MODIS and VIIRS services to systematically analyze the temporal and spatial differences between the BRDF parameters and derived indices of the two sensors from the site scale to the region scale in the red band and NIR band, respectively. Then, we analyzed the sensitivity of the BRDF parameters to variations in Normalized Difference Hotspot–Darkspot (NDHD) and examined the spatiotemporal distribution of zero-valued pixels in the BRDF parameter products generated by the constraint method in the Ross–Li model from both sensors, assessing their potential impact on NDHD derivation. The results confirm that among the three BRDF parameters, the isotropic scattering parameters of MODIS and VIIRS are more consistent, whereas the volumetric and geometric-optical scattering parameters are more sensitive and variable; this performance is more pronounced in the red band. The indices derived from the MODIS and VIIRS BRDF parameters were compared, revealing increasing discrepancies between the albedo and typical directional reflectance and the NDHD. The isotropic scattering parameter and the volumetric scattering parameter show responses that are very sensitive to increases in the equal interval of the NDHD, indicating that the differences between the MODIS and VIIRS products may strongly influence the consistency of NDHD estimation. In addition, both MODIS and VIIRS have a large proportion of zero-valued pixels (volumetric and geometric-optical parameter layers), whereas the spatiotemporal distribution of zero-valued pixels in VIIRS is more widespread. While the zero-valued pixels have a minor influence on reflectance and albedo estimation, such pixels should be considered with attention to the estimation accuracy of the vegetation angular index, which relies heavily on anisotropic characteristics, e.g., the NDHD. This study reveals the need in optimizing the Clumping Index (CI)-NDHD algorithm to produce VIIRS CI product and highlights the importance of considering BRDF product quality flags for users in their specific applications. The method used in this study also helps improve the theoretical framework for cross-sensor product consistency assessment and clarify the uncertainty in high-precision ecological monitoring and various remote sensing applications. Full article

Soil quality, characterized by its physical, chemical, and biological properties, is closely linked to soil management. Reducing soil disturbance can limit soil degradation; however, tillage is still considered essential, particularly on poorly drained soils. This study aimed to identify the optimal tillage practices for winter wheat crops following long-term no tillage practice and crop rotation (2020–2023). Additionally, it highlights the considerable advantages of particular tillage practices in emphasizing their role in enhancing soil health and sustainable agriculture. The experiment followed a randomized complete block design with three replications and two tillage practices: no tillage (NT) and conventional tillage (CT). The research was carried out on a cambic chernozem soil type. The results revealed that physical properties such as bulk density (BD) can increase or decrease under NT, while soil water content (SWC) increased under the same system. The status of water-stable aggregates (WSAs) also improved in NT (88.41%) due to the incorporation of cover crop or plant residues in the 0–10 cm depth. Notably, the highest SWC value at harvest was obtained in the 0–10 cm soil depth, under NT, reaching 24.47%. Grain yields over four years of research were also influenced by tillage systems, resulting in mean yields of 6070 kg/ha for CT and 4285.25 kg/ha for the NT system. The Pearson correlation coefficient was calculated for the soil physical properties considered in pairs. Between BD and water-stable aggregates (WSAs), there was a moderate positive correlation (r = 0.458**) and statistical significance, but no linear correlation between BD and SWC (r = 0.089), and between WSAs and SWC (r = 0.026). Generally, using NT, which reduces soil disturbance and maintains residues on the surface, could contribute to land sustainability and climate mitigation in north-east Romania. Full article

No-tillage (NT) is a key practice in conservation agriculture that minimizes soil disturbance, thereby enhancing soil structure, porosity, and overall quality. However, its long-term effects on soil pore networks and hydro-physical functions remain underexplored. This study evaluated the impacts of NT and conventional tillage (CT) on soil hydro-physical properties using undisturbed soil columns, X-ray computed tomography, and standard physical measurements. A field experiment was conducted under an eight-year continuous cropping system, with a four-year rotation [winter wheat (Triticum aestivum L.)—maize (Zea mays L.)—sunflower (Helianthus annuus L.)—peas (Pisum sativum L.)], comparing NT and CT treatments with three replications. Soil parameters including bulk density (BD), moisture content, total porosity (SP), water-stable aggregates (WSA), and saturated hydraulic conductivity (Ksat) were measured. Results showed that NT increased BD (1.45 g/cm³) compared to CT (1.19 g/cm³), likely due to reduced soil disturbance. Moisture content under NT was up to 78% higher than CT. Saturated hydraulic conductivity was also higher in NT, with 17% and 43% increases observed at harvest in 2022 and 2023, respectively, except in the 0–30 cm layer immediately after sowing. Micro-CT analysis revealed a 34–115% increase in macropores (>1025 μm) under NT at 10–40 cm depth. These findings demonstrate that long-term NT improves key soil hydro-physical properties, supporting its integration into sustainable farming systems to balance productivity and environmental stewardship. Full article

Research has shown that a whole-school approach (WSA) is needed to increase student physical activity. There is a lack of empirical data on teachers’ opinions and needs regarding the implementation of a WSA approach to encourage physical activity. Our study aims to address this gap by identifying teachers’ and academics’ beliefs about the usefulness, content, and delivery mode of a WSA in fostering physical activity. To address the research aim, an exploratory mixed methods design was employed. Initially, a qualitative study with academics and stakeholders was conducted, followed by a quantitative investigation with teachers and school employees. In the first study, seven participants working in education took part in one-to-one interviews concerning their views on the usefulness, content, and delivery of whole-school education. The participants stressed the importance of the WSA and urged that educational authorities should consider the needs of children and the school community, promote teacher collaboration, pursue longevity, and engage with stakeholders and institutions throughout the process. In the second study, 160 school teachers and staff answered a survey about the content and delivery mode of an educational material for the promotion of WSA to fostering physical activity. The analyses indicated that participants preferred a three to six hours course, a hybrid mode of delivery, inclusion of best practices, and knowledge on how to implement a WSA. The study’s findings reveal several implications and recommendations for educators creating comprehensive school-based physical activity programs. Full article

Background/Objectives: This study examined factors influencing health behaviours among 13–17-year-olds in Surrey, focusing on rising obesity rates and socioeconomic disparities using a whole systems approach to capture both the stakeholders’ voice and the young people’s voices. Methods: The research involved two components: a survey of youth service providers (e.g., teachers, youth workers; n = 35) and focus groups with adolescents (n = 27). Results: The survey revealed challenges faced by stakeholders, including insufficient training, environmental factors (e.g., schools, social media, food systems), and limited support from parents and healthcare professionals. The focus groups identified two key themes: (1) domains of care, for example diet and how availability and cost of food affects food choices, and (2) barriers and solutions, addressing financial, structural, and emotional obstacles to and facilitators of a healthy lifestyle. Transcending these themes was the key role of health inequalities linked to income, geography, and gender. Conclusions: This study underscores the complexity of adolescent health behaviours and calls for a multi-level, coordinated approach to address inequalities and foster supportive environments for healthier choices. Full article

The influence of different mineral and organic fertiliser applications on the soil organic matter (SOM) content and quality was monitored in long-term field trials. We used long-term field experiments (27 years) with a crop rotation of potatoes, winter wheat, and spring barley on cambisol soil. The treatments were as follows: an unfertilised control (Cont), sewage sludge in normal and triple doses (SS1 and SS3, respectively), farmyard manure (F1) in a conventional dose, a half dose of farmyard manure with a half dose of mineral nitrogen (F1/2 + N1/2), straw with mineral nitrogen fertiliser (N + St), and mineral nitrogen without any organic fertiliser (N). This study focused on the ability of the total and easily extractable glomalin-related soil protein (T-GRSP and EE-GRSP, respectively) and the water stability of aggregates (WSA) as indicators of long-term SOM quality changes. The results were compared with the content of humic substance fractions and the carbon in humic substances (C_HS), humic acids (C_HA), and fulvic acids (C_FA). The lowest SOM content and quality were observed in the control treatment. The highest overall SOM quality, including the degree of polymerisation (HA) and the GRSP content, was found in the F1 treatment. The organic matter in sewage sludge contributed less to the formation of stable SOM than straw. A significant correlation was found between both the EE-GRSP and the T-GRSP and the content of the C_SOM, C_HS, C_HA, and HA, but not with the C_FA. The influence of fertiliser on the GRSP content was demonstrated. However, no relationship was observed between the WSA and SOM quality, the EE-GRSP, or the T-GRSP content. Full article

Intensive agricultural management affects the physical, chemical, and biological properties of soil, potentially contributing to a decrease in soil carbon storage. In this study, the effects of soil management intensity on soil organic carbon (SOC) content and its labile fractions, i.e., water-soluble organic carbon (OC-sol) and permanganate oxidizable carbon (POXC), were evaluated in a volcanic-ash-derived soil (Andisol) with a very high soil organic matter (SOM) content (>20%). These indicators were associated with water-stable aggregates (WSAs) and biological indicators, namely, earthworm density, cellulase activity, and autoclaved-citrate-extractable (ACE) proteins, related to the decomposition of SOM and its physical protection. The conditions evaluated were secondary native forest (SF), naturalized grassland (NG), no-till (NT), and conventional tillage (CT), considering the last item to be representative of a higher agriculture management intensity. Soil samples were collected by horizon. The SF and NG soil showed higher contents of SOC, OC-sol, and POXC. When comparing the evaluated annual cropping systems, NT showed higher values than CT (p < 0.05) in the first horizon (Hz1), while similar values were found at deeper horizons. The highest cellulase activity, ACE protein levels, and earthworm densities were found in NG and SF. NT also showed significantly higher levels of the aforementioned factors than CT (p < 0.05). A positive and significant relationship was found between the SOC content and WSA (R² = 0.76; p < 0.05) in the whole profile and between POXC and WSA for Hz1 (R² = 0.67; p < 0.05). Soil C storage was affected by the intensity of agricultural management, mainly because of the effect of tillage on structural stability, considering that biological activity synthesizes compounds such as enzymes and proteins that react and adhere to the mineral fraction affecting aggregate stability. The C content stored in the soil is consequently a key indicator with which to regulate SOM and protect SOC. Full article

Surface defect detection is essential for ensuring the quality and safety of steel products. While Transformer-based methods have achieved state-of-the-art performance, they face several limitations, including high computational costs due to the quadratic complexity of the attention mechanism, inadequate detection accuracy for small-scale defects due to substantial downsampling, inconsistencies between classification scores and localization confidence, and feature resolution loss caused by simple upsampling and downsampling strategies. To address these challenges, we propose the HCT-Det model, which incorporates a window-based self-attention residual (WSA-R) block structure. This structure combines window-based self-attention (WSA) blocks to reduce computational overhead and parallel residual convolutional (Res) blocks to enhance local feature continuity. The model’s backbone generates three cross-scale features as encoder inputs, which undergo Intra-Scale Feature Interaction (ISFI) and Cross-Scale Feature Interaction (CSFI) to improve detection accuracy for targets of various sizes. A Soft IoU-Aware mechanism ensures alignment between classification scores and intersection-over-union (IoU) metrics during training. Additionally, Hybrid Downsampling (HDownsample) and Hybrid Upsampling (HUpsample) modules minimize feature degradation. Our experiments demonstrate that HCT-Det achieved a mean average precision (mAP@0.5) of 0.795 on the NEU-DET dataset and 0.733 on the GC10-DET dataset, outperforming other state-of-the-art approaches. These results highlight the model’s effectiveness in improving computational efficiency and detection accuracy for steel surface defect detection. Full article

The presence of filler in asphalt concrete may improve the properties of the mixture. This study investigates the mechanical and volumetric properties of such a mixture using walnut shell ash as a filler in various replacement ratios. The mixtures were mixed with various proportions of limestone (0%, 10%, 20%, 30%, 40%, 50%, 60%, 80%, and 100%) in addition to WSA as a replacement filler. Tests were subsequently carried out, including tests of Marshall’s stability and flow, voids in mineral aggregates, air voids, and theoretical maximum specific gravity. The results revealed that increasing the replacement percentage resulted in a considerable improvement in the performance of the asphalt–concrete mixtures. The results revealed that the mixture with a 60% replacement ratio achieved the best Marshall stability, achieving an improvement of 15.02% compared to the conventional sample, alongside good flow properties. This improvement was accompanied by high conformity with the other physical properties of the asphalt mixture, including a 3.55% air void percentage, which is within the permissible limits for the surface layer, as well as a 21.80% increase in the percentage of voids in the mineral aggregate, which is considered an ideal value. These results paved the way for further study and adjustments to other requirements of the asphalt mixture, as there were no issues with the availability or production costs of the filler material, given the abundance of raw materials. However, it is important to note that, as is evident from the results, a complete 100% replacement led to undesirable outcomes, resulting in a 10.68% decrease in Marshall strength compared to that of the conventional sample. This decrease indicates that the mixture was unable to provide its most important property. Although improving the other properties with complete replacement is not beneficial, a detailed investigation into this ineffective percentage revealed that, according to the results, the ideal replacement ratio is 60% walnut shells and 40% limestone, which results in optimal performance. Full article

Multivariate and statistical tool advancements help to assess potential pollution threats, their geochemical distribution, and the competition between natural and anthropogenic influences, particularly on sediment contamination with potentially toxic metals (PTMs). For this, riverine sediments from 25 locations along urban banksides of the River Ravi, Pakistan, were collected and analyzed to explore the distribution, pollution, ecological, and toxicity risk indices of PTMs like Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Sb, Sn, Sr, V, and Zn using Inductively Coupled Plasma–Optical Emission Spectrometry (ICP-OES) technique. Additionally, techniques such as X-ray Diffraction (XRD) and Scanning Electron Microscopy–Energy Dispersive X-ray Spectroscopy (SEM-EDS) were employed to investigate the mineralogical and morphological aspects. The results indicated that mean concentrations (mg kg⁻¹) of Cd (2.37), Cr (128), Hg (16.6), Pb (26.6), and Sb (2.44) were significantly higher than reference values given for upper continental crust (UCC) and world soil average (WSA), posing potential threats. Furthermore, the geochemical pollution indices showed that sediments were moderately polluted with Cd (I_geo = 2.37, EF = 12.1, and CF = 7.89) and extremely polluted with Hg (I_geo = 4.54, EF = 63.2, and CF = 41.41). Ecological and toxicity risks were calculated to be extremely high, using respective models, predominantly due to Hg (Er_i = 1656 and ITRI = 91.6). SEM-EDS illustrated the small extent of anthropogenic particles having predominant concentrations of Zn, Fe, Pb, and Sr. Multivariate statistical analyses revealed significant associations between the concentrations of PTMs and the sampling locations, highlighting the anthropogenic contributions linked to local land-use characteristics. The present study concludes that River Ravi sediments exhibit moderate levels of Cd and extreme pollution by Hg, both of which contribute highly to extreme ecological and toxicity risks, influenced by both natural and anthropogenic contributions. Full article

Conventional cement production is a major source of carbon dioxide emissions, which creates a significant environmental challenge. This research addresses the problem of how to reduce the carbon footprint of cement paste production using agricultural and industrial waste by-products, namely wheat straw ash (WSA) and silica fume (SF). Currently, accurate models that can predict the mechanical properties of cement pastes incorporating these waste materials are lacking. To fill this gap, our study proposes a model based on response surface methodology and Box-Behnken design, designed to predict the strength of cement pastes with partial substitutions of WSA and SF. Through mechanical and characterization tests, the model demonstrated high accuracy in predicting the strength of the pastes, validated with three mixes, which showed maximum errors of less than 6% at different ages (7, 28, and 56 days). Response surface analysis revealed that replacing cement with 0–20% WSA and more than 5% SF can effectively reduce the carbon footprint by maximizing waste incorporation. This model allows for the calculation of optimal cement substitution levels based on the required strength, thus promoting sustainability in the construction industry through the use of local waste/resources. Full article