Search Results (129)

Extreme maximum temperatures in summer present a significant risk to agroindustry as crops and their ecological interactions have critical thermal limits that can affect their performance and microorganisms-related. Gray mold disease caused by Botrytis cinerea is the most critical disease affecting crops worldwide. In this sense, the impact of temperature on agricultural productivity is well documented in the Northern Hemisphere; the risk of extreme temperatures on the infection rate of B. cinerea in Central Chile is limited. This study analyzes historical climate data from January and February between 1951 and 2023 for the cities of Santiago, Talca, Chillán, and Los Ángeles. The aim was to examine trends in extreme maximum temperatures (EMTs) and develop a simple model to estimate the infection rate of B. cinerea. Linear trend analyses were conducted, as was analysis of the probability of occurrence. Additionally, five-year averages were calculated, and a generic model was presented to assess the effects of warming on the infection rate. The analysis shows positive growth in extreme maximum temperatures in January and February, with projections for 2024, 2025, and 2026 at 70%, 80%, and 80%, respectively. February showed the most significant thermal increase among all stations, with Chillán and Los Ángeles recording higher increases than Santiago and Talca. Projections suggest temperatures near 40–41 °C. The five-year averages for Chillán and Los Ángeles exceeded 37 °C in the 2016–2020 period, the highest values during the analyzed time frame. Trends for 2021–2026 indicate upper limits above 38 °C. These trends, combined with dry summers, could increase the severity of infections and modify the optimal thermal conditions for the pathogen. The results suggest that thermal changes could reduce the infection risk by B. cinerea on fruit crops in Central Chile, and a theoretical approach is proposed to develop predictive tools to facilitate risk assessment in a warming environment. Full article

This paper presents an efficient and compact MATLAB code for 3D topology optimization of multi-materials. The multi-material problem using a mapping-based material interpolation function is adopted from previous work, in which each material is modeled in the same way, presenting a clear (clean) result of 0 and 1 for each material of the optimized structures, without gray elements, thus facilitating the manufacturing process. A new projection function, the sigmoid function, is adopted for the filtered design variables for each material in the domain. The proposed method improves computational efficiency, reducing computational costs by up to 36.7%, while achieving a 19.1% improvement in the objective function compared to the hyperbolic tangent function. A multi-material topology optimization solution with minimal compliance under volume constraints, including details of the optimization model, filtering, projection, and sensitivity analysis procedures, is presented. Numerical examples are also used to demonstrate the effectiveness of the code, and the influence of the position of the support on the optimized results is also proven. The complete MATLAB code for 3D elastic structures is presented as an example. Full article

Ambient air pollution is the most important environmental factor impacting human health. Urban landscapes present unique air quality challenges, which are compounded by climate change adaptation challenges, as air pollutants can also be affected by the urban heat island effect, amplifying the deleterious effects on health. Nature-based solutions have shown potential for alleviating environmental stressors, including air pollution and heat wave abatement. However, such solutions must be designed in order to maximize mitigation and not inadvertently increase pollutant exposure. This study aims to demonstrate potential applications of nature-based solutions in urban environments for climate stressors and air pollution mitigation by analyzing two distinct scenarios with and without green infrastructure. Utilizing low-cost sensors, we examine the relationship between green infrastructure and a series of environmental parameters. While previous studies have investigated green infrastructure and air quality mitigation, our study employs low-cost sensors in tropical urban environments. Through this novel approach, we are able to obtain highly localized data that demonstrates this mitigating relationship. In this study, as a part of the NERC-FAPESP-funded GreenCities project, four low-cost sensors were validated through laboratory testing and then deployed in two locations in São Paulo, Brazil: one large, heavily forested park (CIENTEC) and one small park surrounded by densely built areas (FSP). At each site, one sensor was located in a vegetated area (Park sensor) and one near the roadside (Road sensor). The locations selected allow for a comparison of built versus green and blue areas. Lidar data were used to characterize the profile of each site based on surrounding vegetation and building area. Distance and class of the closest roadways were also measured for each sensor location. These profiles are analyzed against the data obtained through the low-cost sensors, considering both meteorological (temperature, humidity and pressure) and particulate matter (PM₁, PM_2.5 and PM₁₀) parameters. Particulate matter concentrations were lower for the sensors located within the forest site. At both sites, the road sensors showed higher concentrations during the daytime period. These results further reinforce the capabilities of green–blue–gray infrastructure (GBGI) tools to reduce exposure to air pollution and climate stressors, while also showing the importance of their design to ensure maximum benefits. The findings can inform decision-makers in designing more resilient cities, especially in low-and middle-income settings. Full article

South Africa is a leader in the scholarship on green urbanism in the Global South, but academic progress has not translated to broad implementation. Notably, government-subsidized housing projects have produced peripheral developments featuring low build quality, conventional gray infrastructure, and deficient socio-economic and environmental amenities. Declining delivery and increasing informal settlement spawned a 2014 shift to housing megaprojects to increase output and improve living conditions, socio-economic integration, and sustainability. The shift offered opportunities for a normative focus on greener development mirrored in the discourse surrounding project descriptions. Yet, the level of enactment has remained unclear. In reflecting on these points, this paper employs environmental justice as a theoretical framework and completes a comprehensive review of the academic literature on housing megaprojects and the depth of their greener development commitments. A three-phase, seven-stage review protocol retrieves the relevant literature, and bibliometric and qualitative content analyses identify publication trends and themes. Results indicate limited scholarship on new megaprojects with sporadic and superficial references to greener development, mostly reserved for higher-income segments and private developments. In response, this paper calls for more determined action to launch context-aware and just greener megaprojects and offers corresponding guidance for research and practice of value to South Africa and beyond. Full article

The accurate prediction of rock mass quality ahead of the tunnel face is crucial for optimizing tunnel construction strategies, enhancing safety, and reducing geological risks. This study developed three hybrid models using random forest (RF) optimized by moth-flame optimization (MFO), gray wolf optimizer (GWO), and Bayesian optimization (BO) algorithms to classify the surrounding rock in real time during tunnel boring machine (TBM) operations. A dataset with 544 TBM tunneling samples included key parameters such as thrust force per cutter (TFC), revolutions per minute (RPM), penetration rate (PR), advance rate (AR), penetration per revolution (PRev), and field penetration index (FPI), with rock classification based on the Rock Mass Rating (RMR) method. To address the class imbalance, the Borderline Synthetic Minority Over-Sampling Technique was applied. Performance assessments revealed the MFO-RF model’s superior performance, with training and testing accuracies of 0.992 and 0.927, respectively, and key predictors identified as PR, AR, and RPM. Additional validation using 91 data sets confirmed the reliability of the MFO-RF model on unseen data, achieving an accuracy of 0.879. A graphical user interface was also developed, enabling field engineers and technicians to make instant and reliable rock classification predictions, greatly supporting safe tunnel construction and operational efficiency. These models contribute valuable tools for real-time, data-driven decision-making in tunneling projects. Full article

Exploring and predicting the spatiotemporal evolution characteristics and driving forces of carbon storage in typical mountain forest ecosystems under land-use changes is crucial for curbing the effects of climate change and fostering sustainable, eco-friendly growth. The existing literature provides important references for our related studies but further expansion and improvements are needed in some aspects. This study first proposed an integrated framework comprising gray multi-objective optimization (GMOP), Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), the Patch-level Land Use Simulation Model (PLUS), and optimal parameter-based geographical detector (OPGD) models to further expand and improve on existing research. Then, the integrated model was used to analyze the spatial–temporal variation in land-use pattern and carbon storage at the county scale in China’s Daiyun Mountain’s Rim under four scenarios in 2032, and analyze the driving force of spatial differentiation of carbon storage. The results indicated that (1) land-use change primarily involves the mutual transfer among forest, cultivated, and construction land, with approximately 7.2% of the land-use type area undergoing a transition; (2) in 2032, the natural development scenario projects a significant reduction in forest land and an expansion of cultivated, shrub, and construction lands. Conversely, the economic priority, ecological priority, and economic–ecological coordinated scenarios all anticipate a decline in cultivated land area; (3) in 2032, the natural development scenario will see a 2.8 Tg drop in carbon stock compared to 2022. In contrast, the economic priority, ecological priority, and economic–ecological coordinated scenarios are expected to increase carbon storage by 0.29 Tg, 2.62 Tg, and 1.65 Tg, respectively; (4) the spatial differentiation of carbon storage is jointly influenced by various factors, with the annual mean temperature, night light index, elevation, slope, and population density being the key influencing factors. In addition, the influence of natural factors on carbon storage is diminishing, whereas the impact of socioeconomic factors is on the rise. This study deepened, to a certain extent, the research on spatiotemporal dynamics simulation of carbon storage and its driving mechanisms under land-use changes in mountainous forest ecosystems. The results can serve to provide scientific support for carbon balance management and climate adaptation strategies at the county scale while also offering case studies that can inform similar regions around the world. However, several limitations remain, as follows: the singularity of carbon density data, and the research scope being confined to small-scale mountainous forest ecosystems. Future studies could consider collecting continuous annual soil carbon density data and employing land-use simulation models (such as PLUS or CLUMondo) appropriate to the study area’s dimensions. Full article

The authentication of Ziziphi Spinosae Semen (ZSS), Ziziphi Mauritianae Semen (ZMS), and Hovenia Acerba Semen (HAS) has become challenging. The chromatic and textural properties of ZSS, ZMS, and HAS are analyzed in this study. Color features were extracted via RGB, CIELAB, and HSI spaces, whereas texture information was analyzed via the gray-level co-occurrence matrix (GLCM) and Law’s texture feature analysis. The results revealed significant differences in color and texture among the samples. The fire–ice ion dimensionality reduction algorithm effectively fuses these features, enhancing their differentiation ability. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) confirmed the algorithm’s effectiveness, with variable importance in projection analysis (VIP analysis) (VIP > 1, p < 0.05) highlighting significant differences, particularly for the fire value, which is a key factor. To further validate the reliability of the algorithm, Back Propagation Neural Network (BP), Support Vector Machine (SVM), Deep Belief Network (DBN), and Random Forest (RF) were used for reverse validation, and the accuracy of the training set and test set reached 98.83–100% and 95.89–99.32%, respectively. The method provides a simple, low-cost, and high-precision tool for the fast and nondestructive detection of food authenticity. Full article

Urban biodiversity is crucial for ecological security, balance, and important for fostering awareness on human-nature interconnectedness among the public. The diversity of birds, as an urban ecosystem indicator, reflects ecosystem services and is impacted by urban development. To explore the impacts of urbanization on bird diversity, stratified to songbirds, terrestrial birds, climbers, swimming birds, wading birds, and raptors, we specifically investigated the existing and potential distributions of selected bird species, analyzed different contributions of environmental factors, and compared these with urban biodiversity conservation policies. We used bird records from the China Birdwatching Record Center (over 1400 species of birds for querying) and remotely-sensed landcover data, based on the MaxEnt model, to analyze bird spatial distribution characteristics and potential habitat corridors throughout Beijing. The results showed that: (1) Songbirds and terrestrial birds were predominantly concentrated in water areas in urban areas. Wading birds, climbers, swimming birds, and raptors were gathered in forest-covered areas, near wetlands and farmland in suburban areas. Projections indicated that the raptor species Common Kestrel (Falco tinnunculus) showed a notable shift toward urban cores. (2) Among climbers, Gray-headed Pygmy Woodpecker (Dendrocopos canicapillus) occupied the highest proportion of high-quality habitats (10.34%), contrasting with the representative songbird species Blackbird (Turdus merula) at 1.38%, which demonstrated adaptability to urban environments. Critical habitats were concentrated in shrub forests, supporting habitat connectivity. Proximity to water bodies was critical for raptors, wading, swimming, and climbers, whereas terrestrial birds and songbirds were more affected by artificial lighting. (3) The “urban and suburban park rings” policy has effectively enhanced habitat quality and connectivity, promoting urban biodiversity resilience. This study improves our understanding of how different bird communities adapt to urbanization in terms of habitats and movement corridors, and provides useful information for formulating urban bird biodiversity conservation strategies. Full article

Background: The fundamental question of normal brain myelination in human is still poorly understood. Methods: Age-dependent global, regional, and interhemispheric sex-related differences in brain myelination of 42 (19 men, 23 women) healthy adults (19–67 years) were explored using the MRI method of fast macromolecular fraction (MPF) mapping. Results: Higher brain myelination in males compared to females was found in global white matter (WM), most WM tracts, juxtacortical WM regions, and putamen. The largest differences between men and women, exceeding 4%, were observed bilaterally in the frontal juxtacortical WM; angular, inferior occipital, and cuneus WM; external capsule; and inferior and superior fronto-orbital fasciculi. The majority of hemispheric differences in MPF were common to men and women. Sex-specific interhemispheric differences were found in juxtacortical WM; men more often had left-sided asymmetry, while women had right-sided asymmetry. Most regions of deep gray matter (GM), juxtacortical WM, and WM tracts (except for projection pathways) showed a later peak age of myelination in women compared to men, with a difference of 3.5 years on average. Body mass index (BMI) was associated with higher MPF and later peak age of myelination independent of age and sex. Conclusions: MPF mapping showed high sensitivity to assess sex-related differences in normal brain myelination, providing the basis for using this method in clinics. Full article

In the actual estimation of construction and demolition waste (C&DW), it is significantly relevant to effective management, design, and planning at project stages, but the lack of reliable estimation methods and historical data prevents the estimation of C&DW quantities for both short- and long-term planning. To address this gap, this study aims to predict C&DW quantities in construction projects more accurately by integrating the gray wolf optimization algorithm (GWO) and the Archimedes optimization algorithm (AOA) into an artificial neural network (ANN). This study uses data concerning the actual quantities of work in 200 real-life construction and demolition projects performed in the Gaza Strip. Different performance parameters, such as mean absolute error (MAE), mean square error (MSE), root mean squared error (RMSE), and the coefficient of determination (R²), are used to evaluate the effectiveness of the models developed. The results of this study have shown that the AOA-ANN model outperforms the other models in terms of accuracy (R² = 0.023728, MSE = 0.00056304, RMSE = 0.023728, MAE = 0.0086648). Moreover, this new hybrid model yields more accurate estimations of C&DW quantities with minimal input parameters, making the process of estimation more feasible. Full article

This paper develops a multi-objective optimization model to address the absence of systematic and practical evaluation methods for selecting construction schemes for steel pipe pile cofferdams. The model aims to minimize duration and cost while maximizing quality. Additionally, it proposes an improved sparrow search algorithm (ISSA) to solve this problem. First, a tent chaotic map is introduced to initialize the sparrow population, enhancing the diversity of the initial population. Second, the principle of non-dominated ordering is introduced to sort the parent and offspring populations during the iteration process, and the appropriate individuals are selected to form the offspring population. Finally, gray correlation analysis is applied to optimize the Pareto solution set and determine the final construction scheme. The effectiveness and superiority of the ISSA is verified by using the Changsha Jinan Avenue project as a case study. The results indicate that the quality of the optimized construction scheme remains at a high level of 0.90 or more; the duration is shortened by 18 days, a reduction of 21%; and the total cost is reduced by CNY 220,000, saving 3% of the cost. Full article

Kidney disease has emerged as a significant global health issue, projected to become the fifth-leading cause of years of life lost by 2040. The kidneys, being highly radiosensitive, are vulnerable to damage from various forms of radiation, including gamma (γ) and X-rays. However, the effects of electron radiation on renal tissues remain poorly understood. Given the localized energy deposition of electron beams, this study seeks to investigate the dose-dependent morphological and molecular changes in the kidneys following electron irradiation, aiming to address the gap in knowledge regarding its impact on renal structures. The primary aim of this study is to conduct a detailed morphological and molecular analysis of the kidneys following localized electron irradiation at different doses, to better understand the dose-dependent effects on renal tissue structure and function in an experimental model. Male Wistar rats (n = 75) were divided into five groups, including a control group and four experimental groups receiving 2, 4, 6, or 8 Gray (Gy) of localized electron irradiation to the kidneys. Biochemical markers of inflammation (interleukin-1 beta [IL-1β], interleukin-6 [IL-6], interleukin-10 [IL-10], tumor necrosis factor-alpha [TNF-α]) and oxidative stress (malondialdehyde [MDA], superoxide dismutase [SOD], glutathione [GSH]) were measured, and morphological changes were assessed using histological and immunohistochemical techniques (TUNEL assay, caspase-3). The study revealed a significant dose-dependent increase in oxidative stress, inflammation, and renal tissue damage. Higher doses of irradiation resulted in increased apoptosis, early stages of fibrosis (at high doses), and morphological changes in renal tissue. This study highlights the dose-dependent effects of electrons on renal structures, emphasizing the need for careful consideration of the dosage in clinical use to minimize adverse effects on renal function. Full article

To achieve the rapid grade classification of camellia seed oil, hyperspectral imaging technology was used to acquire hyperspectral images of three distinct grades of camellia seed oil. The spectral and image information collected by the hyperspectral imaging technology was preprocessed by different methods. The characteristic wavelength selection in this study included the continuous projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS), and the gray-level co-occurrence matrix (GLCM) algorithm was used to extract the texture features of camellia seed oil at the characteristic wavelength. Combined with genetic algorithm (GA) and support vector machine algorithm (SVM), different grade classification models for camellia seed oil were developed using full wavelengths (GA-SVM), characteristic wavelengths (CARS-GA-SVM), and fusing spectral and image features (CARS-GLCM-GA-SVM). The results show that the CARS-GLCM-GA-SVM model, which combined spectral and image information, had the best classification effect, and the accuracy of the calibration set and prediction set of the CARS-GLCM-GA-SVM model were 98.30% and 96.61%, respectively. Compared with the CARS-GA-SVM model, the accuracy of the calibration set and prediction set were improved by 10.75% and 12.04%, respectively. Compared with the GA-SVM model, the accuracy of the calibration set and prediction set were improved by 18.28% and 18.15%, respectively. The research showed that hyperspectral imaging technology can rapidly classify camellia seed oil grades. Full article

This study aims to investigate the coupling and harmonization between land ecological security (LES) and high-quality agricultural development (HAD) in the Han River Basin (HRB), China, with the objective of promoting harmonious coexistence between agriculture and ecosystems. Using 17 cities in the HRB as the research objects, an evaluation index system of two systems, LES and HAD, was constructed, analyzed, and evaluated via projective tracer modeling for multiple intelligent genetic algorithms (MIGA-PTM). The degree of coupling coordination (DCC) was used to quantitatively evaluate the coupling coordination development status of the two systems, the obstacle model (OM) was used to identify the main influencing factors, and the gray predictive model first-order univariate model (GM (1, 1)) was used to predict the DCC of the LES and HAD from 2025 to 2040. The results show the following: (1) the LES and HAD levels of the 17 cities in the HRB tended to increase during the study period, and there was a large gap between cities; (2) the spatial distributions of the DCCs of the LES and HAD in the HRB were uneven, with high values in the southern and low values in the central and northern parts, and the overall degree of coupling tended to fluctuate. The overall DCC showed a fluctuating upward trend; (3) the degree of obstacles, per capita water resources, greening coverage, and rate of return on financial expenditure are the main influencing factors; and (4) the prediction results of GM (1, 1) indicate that the LES and HAD of the HRB will be close to reaching the intermediate stage of coupling in 2035. This research offers critical insights into sustainable development practices that facilitate the alignment of agricultural growth with ecological preservation. Full article

Mu opioid receptors (MORs) represent a vital mechanism related to the modulation of stress-induced analgesia (SIA). Previous studies have reported on the gamma-aminobutyric acid (GABA)ergic “disinhibition” mechanisms of MORs on the descending pain modulatory pathway of SIA induced in the midbrain. However, the role of the MORs expressed in the medial prefrontal cortex (mPFC), one of the main cortical areas participating in pain modulation, in SIA remains completely unknown. In this study, we investigated the contributions of MORs expressed on glutamatergic (MORGlut) and GABAergic (MORGABA) neurons of the medial prefrontal cortex (mPFC), as well as the functional role and activity of neurons projecting from the mPFC to the periaqueductal gray (PAG) region, in male mice. We achieved this through a combination of hot-plate tests, c-fos staining, and 1 h acute restraint stress exposure tests. The results showed that our acute restraint stress protocol produced mPFC MOR-dependent SIA effects. In particular, MORGABA was found to play a major role in modulating the effects of SIA, whereas MORGlut seemed to be unconnected to the process. We also found that mPFC–PAG projections were efficiently activated and played key roles in the effects of SIA, and their activation was mediated by MORGABA to a large extent. These results indicated that the activation of mPFC MORGABA due to restraint stress was able to activate mPFC–PAG projections in a potential “disinhibition” pathway that produced analgesic effects. These findings provide a potential theoretical basis for pain treatment or drug screening targeting the mPFC. Full article