Search Results (2,039)

This paper presents an analysis of the effectiveness of the existing reinforcement of steel lattice tower legs made of L-sections by expanding to closely spaced built-up members. Due to the significant differences between the standard assumptions and the existing reinforcement, numerical analyses based on the component-based finite element method (CBFEM) were used to estimate the capacity of the existing structure’s tower legs. Geometrically and materially nonlinear stress analysis and linear buckling analysis were performed. The obtained results (stress distribution maps, buckling forms, and corresponding critical forces) were used to modify the geometric parameters of the section of the analyzed tower legs in order to adapt the standard formulas in the calculation procedure. In the analyzed case, distance of the connections between the branches exceeded that indicated in EN 1993-1-1:2005 for the condition concerning the possibility of ignoring the deformation susceptibility in the calculation process. However, it did not result in the separate operation of each branch of the section. Thus, in the case of the analyzed reinforcement, it is possible to neglect the form susceptibility when calculating the buckling resistance of the element. The buckling capacity of the reinforced legs of the tower and the compression capacity of the section of the analyzed structure were calculated according to the method that took into account the results of the numerical analyses. These values are about 35–48% and 30–39% higher, respectively, than the capacity of the unreinforced angle calculated according to EN 1993-1-1:2005 and EN 1993-1-8:2006 standards. Thus, it may be possible to avoid costly and labor-intensive retrofitting of the existing reinforcement to meet the standard requirements. A key issue, and one that is particularly important in light of the lack of standard guidelines aimed at designing reinforcements for telecommunications structures, seems to be the performance of full-scale experimental tests. Full article

This study investigates the effectiveness of the large eddy simulation version of the Weather Research and Forecasting model (WRF-LES) in reproducing the atmospheric conditions observed during a Perdigão field experiment. When comparing the results of the WRF-LES with observations, using LES settings can accurately represent both large-scale events and the specific characteristics of atmospheric circulation at a small scale. Six sensitivity experiments are performed to evaluate the impact of different planetary boundary layer (PBL) schemes, including the MYNN, YSU, and Shin and Hong (SH) PBL models, as well as large eddy simulation (LES) with Smagorinsky (SMAG), a 1.5-order turbulence kinetic energy closure (TKE) model, and nonlinear backscatter and anisotropy (NBA) subgrid-scale (SGS) stress models. Two case studies are selected to be representative of flow conditions. In the northeastern flow, the MYNN NBA simulation yields the best result at a height of 100 m with an underestimation of 3.4%, despite SH generally producing better results than PBL schemes. In the southwestern flow, the MYNN TKE simulation at station Mast 29 is the best result, with an underestimation of 1.2%. The choice of SGS models over complex terrain affects wind field features in the boundary layer more than above the boundary layer. The NBA model generally produces better results in complex terrain when compared to other SGS models. In general, the WRF-LES can model the observed flow with high-resolution topographic maps in complex terrain with different SGS models for both flow regimes. Full article

Plants face an array of environmental stresses, including both abiotic and biotic stresses. These stresses significantly impact plant lifespan and reduce agricultural crop productivity. Abiotic stresses, such as ultraviolet (UV) radiation, high and low temperatures, salinity, drought, floods, heavy metal toxicity, etc., contribute to widespread crop losses globally. On the other hand, biotic stresses, such as those caused by insects, fungi, and weeds, further exacerbate these challenges. These stressors can hinder plant systems at various levels, including molecular, cellular, and development processes. To overcome these challenges, multi-omics computational approaches offer a significant tool for characterizing the plant’s biomolecular pool, which is crucial for maintaining homeostasis and signaling response to environmental changes. Integrating multiple layers of omics data, such as proteomics, metabolomics, ionomics, interactomics, and phenomics, simplifies the study of plant resistance mechanisms. This comprehensive approach enables the development of regulatory networks and pathway maps, identifying potential targets for improving resistance through genetic engineering or breeding strategies. This review highlights the valuable insights from integrating multi-omics approaches to unravel plant stress responses to both biotic and abiotic factors. By decoding gene regulation and transcriptional networks, these techniques reveal critical mechanisms underlying stress tolerance. Furthermore, the role of secondary metabolites in bio-based products in enhancing plant stress mitigation is discussed. Genome editing tools offer promising strategies for improving plant resilience, as evidenced by successful case studies combating various stressors. On the whole, this review extensively discusses an advanced multi-omics approach that aids in understanding the molecular basis of resistance and developing novel strategies to improve crops’ or organisms’ resilience to abiotic and biotic stresses. Full article

In elevator systems, pressure plates secure guide rails and limit displacement, but defects compromise their performance under stress. Current detection algorithms face challenges in achieving high localization accuracy and computational efficiency when detecting small defects in guide rail pressure plates. To overcome these limitations, this paper proposes a lightweight defect detection network (LGR-Net) for guide rail pressure plates based on the YOLOv8n algorithm. To solve the problem of excessive model parameters in the original algorithm, we enhance the baseline model’s backbone network by incorporating the lightweight MobileNetV3 and optimize the neck network using the Ghost convolution module (GhostConv). To improve the localization accuracy for small defects, we add a high-resolution small object detection layer (P2 layer) and integrate the Convolutional Block Attention Module (CBAM) to construct a four-scale feature fusion network. This study employs various data augmentation methods to construct a custom dataset for guide rail pressure plate defect detection. The experimental results show that LGR-Net outperforms other YOLO-series models in terms of overall performance, achieving optimal results in terms of precision (p = 98.7%), recall (R = 98.9%), mAP (99.4%), and parameter count (2,412,118). LGR-Net achieves low computational complexity and high detection accuracy, providing an efficient and effective solution for defect detection in elevator guide rail pressure plates. Full article

Sugars will eventually be exported transporter (SWEET), a class of glucose transport proteins, is crucial in plants for glucose transport by redistribution of sugars and regulates growth, development, and stress tolerance. Although the SWEET family has been studied in many plants, little is known about its function in winter B. rapa (Brassica rapa L.). Bioinformatics approaches were adopted to identify the SWEET gene (BraSWEETs) family in B. rapa to investigate its role during overwintering. From the whole-genome data, 31 BraSWEET genes were identified. Gene expansion was realized by tandem and fragment duplication, and the 31 genes were classified into four branches by phylogenetic analysis. As indicated by exon–intron structure, cis-acting elements, MEME (Multiple EM for Motif Elicitation) motifs, and protein structure, BraSWEETs were evolutionarily conserved. According to the heat map, 23 BraSWEET genes were differentially expressed during overwintering, revealing their potential functions in response to low-temperature stress and involvement in the overwintering memory-formation mechanism. BraSWEET10 is mainly associated with plant reproductive growth and may be crucial in the formation of overwintering memory in B. rapa. The BraSWEET10 gene was cloned into B. rapa (Longyou-7, L7). The BraSWEET10 protein contained seven transmembrane structural domains. Real-time fluorescence quantitative PCR (qRT-PCR) showed that the BraSWEET10 gene responded to low-temperature stress. BraSWEET10 was localized to the cell membrane. The root length of overexpressing transgenic A. thaliana was significantly higher than that of wild-type (WT) A. thaliana under low temperatures. Our findings suggest that this gene may be important for the adaptation of winter B. rapa to low-temperature stress. Overall, the findings are expected to contribute to understanding the evolutionary links of the BraSWEET family and lay the foundation for future studies on the functional characteristics of BraSWEET genes. Full article

Background: Adequate levels of leisure-time exercise (LTE) are associated with mental health benefits. Despite increased research in recent years through randomized controlled trials (RCTs), a systematic literature review summarizing these findings is lacking. Here, we examined publication trends, impact, and research gaps regarding LTE’s effects on mental health in the form of a bibliometric analysis. Methods: Five electronic databases (PubMed, EMBASE, Web of Science, Ovid Medline, and the Cumulative Index for Nursing and Allied Health Literature) were searched from their inception until 20 November 2024. Citations were independently screened by two authors and included based on pre-determined eligibility criteria. Bibliometric analysis was conducted using SciVal and VOSviewer under five themes: (1) descriptive analysis, (2) network analysis, (3) thematic mapping, (4) co-citation and co-occurrence analysis, and (5) bibliometric coupling. Results: The systematic search identified 5792 citations, of which 78 RCTs met the inclusion criteria. Only one study was conducted in a low- or middle-income country. Sixty-four percent of studies were published in quartile-one journals. Most studies were conducted in the United States, followed by Australia, Canada, and the United Kingdom. National collaborations yielded the highest citation rates, reflecting the influence of cultural and social norms on exercise and mental health. Research gaps were identified with regards to the validity of mental health measures, the paucity of data from low- and middle-income countries, and emerging research sources. Conclusions: This bibliometric analysis highlights the existing evidence on LTE’s impact on mental health and identifies areas for future research and policy. Trials exploring valid mental health outcomes, biomarkers such as mood and oxidative stress, and collaborative research are needed, particularly in underrepresented regions of the world. Full article

Many regions worldwide are exposed to multiple omnipresent hazards occurring in complex interactions. However, multi-hazard assessments are not yet fully integrated into current planning tools, particularly when referring to transboundary areas. This work aims to enable spatial planners to include multi-hazard assessments in their climate change adaptation measures using available data. We focus on a set of hazards (e.g., extreme heat, drought, landslide) and propose a four-step methodology to (i) harmonise existing data from different databases and scales for multi-hazard assessment and mapping and (ii) to read identified multi-hazard bundles in homogeneous territorial areas. The methodology, whose outputs are replicable in other EU contexts, is applied to the illustrative case of Northeast Italy. The results show a significant difference between hazards with a ‘dichotomous’ spatial behaviour (shocks) and those with a more complex and nuanced one (stresses). The harmonised maps for the single hazards represent a new piece of knowledge for our territory since, to date, there are no comparable maps with this level of definition to understand hazards’ spatial distribution and interactions between transboundary areas. This study does present some limitations, including putting together data with a remarkable difference in definition for some hazards. Full article

Predicting damage to materials under multiaxial fatigue is a complex challenge, especially when normal and shear stresses interact in dynamic and non-linear ways. Traditional methods often oversimplify these interactions, leading to less reliable fatigue predictions and limiting their usefulness in real-world applications. To address this, we present a novel algorithm based on the principles of the Stress Scale Factor (SSF), designed to dynamically evaluate the relative contributions of normal and shear stresses to fatigue damage. By providing a more accurate mapping of multiaxial fatigue damage, this approach enables improved predictions of fatigue life. The methodology combines experimental insights with mathematical modeling to create a flexible and adaptive framework. By making it possible to map multiaxial fatigue damage with greater precision, this SSF-based approach not only enhances the understanding of fatigue behavior but also enables better design decisions. The result is safer, more reliable, and efficient structures across a range of applications. This study bridges the gap between theoretical methods and practical needs, offering engineers and researchers a powerful tool to improve fatigue analysis and optimize structural performance. Full article

The stay-green (SG) trait enhances photosynthetic activity during the late grain-filling period, benefiting grain yield under drought and heat stresses. CH7034 is a wheat breeding line with SG. To clarify the SG loci carried by CH7034 and obtain linked molecular markers, in this study, a recombinant inbred line (RIL) population derived from the cross between CH7034 and non-SG SY95-71 was genotyped using the Wheat17K single-nucleotide polymorphism (SNP) array, and a high-density genetic map covering 21 chromosomes and consisting of 2159 SNP markers was constructed. Then, the chlorophyll content of flag leaf from each RIL was estimated for mapping, and one QTL for SG on chromosome 7D was identified, temporarily named QSg.sxau-7D, with the maximum phenotypic variance explained of 8.81~11.46%. A PCR-based diagnostic marker 7D-16 for QSg.sxau-7D was developed, and the CH7034 allele of 7D-16 corresponded to the higher flag leaf chlorophyll content, while the 7D-16 SY95-71 allele corresponded to the lower value, which confirmed the genetic effect on SG of QSg.sxau-7D. QSg.sxau-7D located in the 526.4~556.2 Mbp interval is different from all the known SG loci on chromosome 7D, and 69 high-confidence annotated genes within the interval expressed throughout the entire period of flag leaf senescence. Moreover, results of an association analysis based on the diagnostic marker showed that there is a positive correlation between QSg.sxau-7D and thousand-grain weight. Our results revealed a novel QTL QSg.sxau-7D whose CH7034 allele had a strong effect on SG, which can be applied in further wheat molecular breeding. Full article

This study involved the use of a real-time online respiratory metabolism-monitoring system to examine the effects of water temperature on koi carp metabolism, focusing on the oxygen-consumption rate (OCR), carbon dioxide-excretion rate (CER), and respiratory quotient (RQ). Experiments were conducted at four temperatures: 18 °C, 22 °C, 26 °C, and 30 °C. The results showed that as the temperature increased from 18 °C to 26 °C, the OCR and CER rose significantly, indicating higher metabolic rates. At 30 °C, these indicators declined, reflecting physiological stress and reduced efficiency. The RQ showed minimal fluctuations at 22 °C, suggesting optimal metabolic stability, while at 26 °C and 30 °C, RQ fluctuations increased and rhythmicity was lost, indicating disrupted metabolic activity. Autocorrelation and self-organizing map (SOM) analyses revealed stable circadian rhythms at 18 °C and 22 °C, which were significantly disrupted at higher temperatures. These findings indicate that the optimal temperature range for koi carp is 22 °C to 26 °C, at which temperatures metabolic activity is efficient and rhythms are stable. Beyond this range, metabolism becomes disrupted. This study underscores the importance of maintaining suitable water temperatures in aquaculture to promote fish health and productivity, particularly in the context of climate change. Full article

The demand for medicinal and aromatic plants (MAPs) has grown significantly in recent years, due to their therapeutic value. Among these, Sideritis cypria Post is a promising yet under-evaluated species. Existing research assessing the effects of nitrogen (N) fertilization, zinc (Zn) foliar applications, and toxic copper (Cu) concentrations often overlooks MAPs such as S. cypria. Additionally, the interactions among these parameters, as well as their combined roles in MAPs plant physiology and secondary metabolite biosynthesis, have yet to be fully elucidated. In this study, hydroponically grown S. cypria plants were cultivated using nutrient solutions (NSs) with different N (75, 150, and 300 mg L⁻¹) and Cu (5 and 100 μM) levels, combined with foliar spraying (0 and 1.74 mM Zn), to evaluate the growth, mineral uptake, secondary metabolites production and stress response. N levels at 75 and 150 mg L⁻¹ resulted in increased dry matter content, whereas fresh biomass production was preserved. Foliar Zn applications enhanced chlorophylls and antioxidants, contingent upon N and Cu in the NS. Increased N accumulation was observed via the increase in N in the NS, while foliar Zn enhanced its uptake at moderate N levels. Excess Cu stimulated its accumulation, while a reduction was observed with foliar Zn at low and high N levels. Excess Cu increased lipid peroxidation (MDA) at low and moderate N in the NS, while foliar Zn decreased both MDA and hydrogen peroxide, contingent upon Cu and N levels. Low-to-moderate N in the NS can be applied under excess Cu without compromising the yield, quality, and safety of S. cypria plants, while foliar Zn can modulate the stress response of plants under excess Cu and the production of secondary metabolites. These results may be utilized for optimizing nutrient management strategies for the cultivation of MAPs, contributing to conservation efforts by supporting the cultivation of endemic species like S. cypria, considering the potential benefits of Zn foliar applications under Cu-contaminated conditions. Full article

The effect of the presence of guar gum (0–0.75 wt%) in a thermo-responsive triple-network (TN) PVA/TA/PVA-MA-g-PNIPAAm hydrogel (PVA: polyvinyl alcohol; MA: methacrylate, PNIPAAm: poly-N-isopropyl acryl amide; TA: tannic acid) with respect to the structural, mechanical, and viscoelastic properties was mapped. A comprehensive analysis, using large-amplitude oscillatory shear (LAOS), SEM imaging, XRD, and mechanical analysis revealed that guar enhances hydrogel crystallinity (up to 30% at 0.75 wt%), which goes along with a strain hardening. The hydrogel achieved superior mechanical performance at a gum concentration of 0.5 wt% with a 40% increase in shear-thickening, an enhanced strain tolerance in nonlinear regimes, and a good mechanical robustness (maximum elongation to break of 500% and stress of 620 kPa). The hydrogel with 0.5 wt% guar exhibited also a good thermal response (equilibrium swelling ratio changed from 8.4 at 5 °C to 2.5 at 50 °C) and an excellent thermal cycling dimensional stability. Higher guar concentrations reduce structural resilience, leading to brittle hydrogels with lower extensibility and viscoelastic stability. Full article

A novel total joint replacement (TJR) that treats lumbar spine degeneration was previously assessed under Mode I and Mode IV conditions. In this study, we relied on these previous wear tests to establish a relationship between finite element model (FEM)-based bearing stresses and in vitro wear penetration maps. Our modeling effort addressed the following question of interest: Under reasonably worst-case misaligned conditions, do the lumbar total joint replacement (L-TJR) polyethylene stresses and strains remain below values associated with Mode IV impingement wear tests? The FEM was first formally verified and validated using the risk-informed credibility assessment framework established by ASME V&V 40 and FDA guidance. Then, based on criteria for unreasonable misuse outlined in the surgical technique guide, a parametric analysis of reasonably worst-case misalignment using the validated L-TJR FEM was performed. Reasonable misalignment was created by altering device positioning from the baseline condition in three scenarios: Axial Plane Convergence (20–40°), Axial Plane A-P Offset (0–4 mm), and Coronal Plane Tilt (±20°). We found that, for the scenarios considered, the contact pressures, von Mises stresses, and effective strains of the L-TJR-bearing surfaces remained consistent with Mode I (clean) conditions. Specifically, the mechanical response values fell below those determined under Mode IV (worst-case) boundary conditions, which provided the upper-bound benchmarks for the study (peak contact pressure 83.3 MPa, peak von Mises stress 32.2 MPa, and peak effective strain 42%). The L-TJR was judged to be insensitive to axial and coronal misalignment under the in vitro boundary conditions imposed by the study. Full article

Deep mining in metal mines faces more and more complex geological conditions, such as “three highs and one disturbance” (high ground stress, high permeability, high temperature, and mining-induced disturbance), which can easily trigger water inrush disasters and seriously affect the safety and efficiency of deep mining. This paper focuses on the deep hydrogeological structural characteristics of the Huize lead–zinc mine. Firstly, two main factors affecting the production safety of the mining area, namely the water source and water channel of the mine, were analyzed. Based on this analysis, nine factors were determined as indicators for the risk assessment of water inrush, including the water head difference, water-bearing capacity, permeability coefficient, aquifer thickness, water pressure, fault type, fault scale, fault water conductivity, and karst zoning characteristics. Then, a water inrush risk assessment model for the deep mine was constructed, and the weights of the individual factors were determined using the analytic hierarchy process (AHP) and entropy weight method (EWM). Combined with the multi-factor spatial fitting function of the GIS, a zoning map of the risk assessment of water inrush was developed. The results showed that the aquifer groups of the Permian Liangshan Formation and the Carboniferous Maping Formation (P₁l + C₃m) were relatively safe, whereas the karst fissure aquifer of the Qixia–Maokou Formation (P₁q + m) posed a high risk of water inrush, necessitating advanced exploration and water drainage in the area. These findings provide guidance for water control measures in the Huize lead–zinc mine and offer valuable insights into the prediction and prevention of mine water hazards associated with ore body mining in karst aquifers. Full article

Thermal refuges in streams are essential for the survival of coldwater fish species such as Redband trout (Oncorhynchus mykiss) in landscapes with stressful or lethal stream temperatures. We utilized an uncrewed aerial system (UAS) mounted with thermal and natural color sensors to conduct hourly flights over a 24 h period in the desert stream Little Jacks Creek during late summer when temperatures were near seasonal maximums and streamflow was near seasonal minimums. We used fine-resolution imagery to map stream temperatures and characterize how our thermal sensor exhibits variability across a diel period in an environment where thermal sensor viability had not yet been assessed. Thermal imagery from 3 out of 24 flights showed no significant differences when compared to true water temperatures from in-stream temperature loggers, which appeared to be highly dependent on atmospheric conditions. The thermal imagery (range of $9.17$ to $21.04 °$C) consistently underestimated HOBO logger stream temperatures (range of $13.6$ to $17.1 °$C) during cooler, nighttime flights and overestimated temperatures during hotter, afternoon hours, resulting in a global RMSE of 2.12 $°$C. Between-flight RMSE values ranged from 0.53$°$C to 4.00$°$C, within the error range of the thermal sensor. The thermal data support existing findings of optimal hours for flying UAS thermal surveys and showed specific patterns in TIR sensor accuracy that were dependent on the time of flight. This study yields valuable lessons for future stream temperature data collection in environments with highly variable temperatures, aiding in the calibration of thermal sensors on UAS missions. Furthermore, our results provide insights into environmental stressors such as increased stream temperatures, which is vital for conservation efforts for organisms that rely on coldwater refuges within desert streams. Full article