Air pollution and ischemic stroke (IS) are both vital factors affecting the health of Beijing citizens. This study aims at exploring the associations between air pollution, meteorology, and the hospital admission of IS (IS HA). Information on 476,659 IS inpatients in secondary and higher hospitals in Beijing from 2013 to 2018 were collected. A time-stratified case-crossover design with the generalized additive model and the distributed lag nonlinear model were used. In the single-pollutant models, an inter-quartile range increase in O₃, SO₂, CO, and NO₂ resulted in a significant highest increase in IS HA by 2.23% (95% CI: 1.56%, 2.90%), 1.53% (95% CI: 1.12%, 1.95%), 1.05% (95% CI: 0.70%, 1.40%), and 0.51% (95% CI: 0.24%, 0.79%) on the day of pollution, so did PM₂.₅ and PM₁₀ by 1.13% (95% CI: 0.68%, 1.59%) and 1.19% (95% CI: 0.74%, 1.64%) at a lag of 0–5 days. There was a nonlinear relationship between meteorology and IS HA. In the multivariate model, the cumulative relative risks with a maximum lag time of 21 days of PM₂.₅ and NO₂ were 1.11 (95% CI: 1.04, 1.19) and 0.88 (95% CI: 0.82, 0.94), while the effects of SO₂, O₃, and meteorology were insignificant. The findings suggested that particulate pollutants could increase the risk of IS, and the elderly were more sensitive to it, while the results of gaseous pollutants are still discordant. The control of air pollution and the protection of susceptible populations should receive higher attention from policymakers.

Agricultural water use has long accounted for more than 70% of water consumption in Northeast China. Estimating farmland irrigation water requirements and water balance is essential to ensure safe agricultural water and promote rational development and utilization of regional water resources. In this study, based on the modified Penman–Monteith equation recommended by the Food and Agriculture Organization (FAO) and Geographic Information System (GIS) technology, the net crop irrigation water requirements for four main crops in Northeast China were calculated, and the spatiotemporal distribution characteristics were also analyzed. Additionally, regional farmland irrigation water requirements were estimated, water balance in a typical year was determined, and the dominant factors affecting farmland irrigation water requirements in different regions were analyzed. From 1986 to 2020, the net irrigation water requirements for four main crops all showed the temporal trend of no significant increase and the spatial distribution characteristic of being high in the west and low in the east. The farmland irrigation water requirement decreased, and the monthly average farmland irrigation water requirement peaked in July during 2010–2019. Compared with 2010, in 2019, the irrigation water requirement per cultivated land grid cell in 20 cities increased and that in 16 cities decreased. Most cities were facing varying degrees of water shortage. Precipitation had the greatest direct effect on the farmland irrigation water requirement in different regions. These results quantify the farmland irrigation water requirement and water balance in Northeast China, and provide a reference for water resources and related environmental governance.

During the outbreak of the COVID-19, China implemented an urban lockdown in the first period. These measures not only effectively curbed the spread of the virus but also brought a positive impact on the ecological environment. The water quality of urban inland river has a significant impact on urban ecology and public health. This study uses Sentinel-2 visible and near-infrared band reflectance and the Normalized Difference Turbidity Index (NDTI) to analyze the water quality of the Haihe River Basin during the control period of COVID-19. It is found that during the lockdown period, the river water quality was significantly improved compared to the same period in 2019. The average NDTI of the Haihe River Basin in March decreased by 0.27, a decrease of 219.06%; in April, it increased by 0.07, that is 38.38%. Further exploration using VIIRS lights found that the brightness of the lights in the main urban area was significantly lower in February, the beginning of the lockdown. However, as the city was unblocked, the lights rose sharply in March and then recovered to normal. There is obvious asynchrony in changes between river turbidity and light. The results can help understand the impact of human activities on the natural environment.

Heat shock protein A2 (HSPA2) is a testis-specific molecular chaperone of the 70 kDa heat shock protein (HSP70) family and reported to play a key role in spermatogenesis as well as in the remodelling of the sperm surface during capacitation. It is established that mice lacking HSPA2 gene are infertile and spermatozoa that fail to interact with the zona pellucida of the oocyte consistently lack HSPA2 protein expression. However, its role in post fertilization events is not fully understood. Owing to the importance of HSPA2 in male reproduction, the present study is undertaken to reveal the association between genetic mutation and phenotypic variation in recurrent pregnancy loss (RPL) patients through an in silico prediction analysis. In this study, we used different computational tools and servers such as SIFT, PolyPhen2, PROVEAN, nsSNPAnalyzer, and SNPs & GO to analyse the functional consequences of the nsSNPs in human HSPA2 gene. The most damaging amino acid variants generated were subjected to I-Mutant 2.0 and ConSurf. Post-translational modifications such as phosphorylation mediated by these deleterious nsSNPs were analysed using NetPhos 2.0, and gene-gene interaction study was conducted using GeneMANIA. Finally, in-depth studies of the nsSNPs were studied through Project HOPE. The findings of the study revealed 18 nsSNPs to be deleterious using a combinatorial bioinformatic approach. Further functional analysis suggests that screening of nsSNP variants of HSPA2 that tend to be conserved and has potential to undergo phosphorylation at critical positions (rs764410231, rs200951589, rs756852956) may be useful for predicting outcome in altered reproductive outcome. The physicochemical alterations and its impact on the structural and functional conformity were determined by Project HOPE. Gene-gene interaction depicts its close association with antioxidant enzyme (SOD1) strongly supporting an inefficient oxidative scavenging regulatory mechanism in the spermatozoa of RPL patients as reported earlier. The present study has thus identified high-risk deleterious nsSNPs of HSPA2 gene and would be beneficial in the diagnosis and prognosis of the paternal effects in RPL patients.

In this study, six supervised classification algorithms were compared. The algorithms were based on cluster analysis, distance, deep learning, and object-based image analysis. Our objective was to determine which of these algorithms has the highest overall accuracy in both detection and automated estimation of agave cover in a given area to help growers manage their plantations. An orthomosaic with a spatial resolution of 2.5 cm was derived from 300 images obtained with a DJI Inspire 1 unmanned aerial system. Two training classes were defined: (1) sites where the presence of agaves was identified and (2) “absence” where there were no agaves but other plants were present. The object-oriented algorithm was found to have the highest overall accuracy (0.963), followed by the support-vector machine with 0.928 accuracy and the neural network with 0.914. The algorithms with statistical criteria for classification were the least accurate: Mahalanobis distance = 0.752 accuracy and minimum distance = 0.421. We further recommend that the object-oriented algorithm be used, because in addition to having the highest overall accuracy for the image segmentation process, it yields parameters that are useful for estimating the coverage area, size, and shapes, which can aid in better selection of agave individuals for harvest.

Aldehydes have been shown to be potentially carcinogenic, mutagenic, and cardiotoxic to humans. Dietary fiber reduces exposure to certain environmental pollutants and has been widely used to improve various metabolic disorders. However, the effects of dietary fiber on serum concentrations of aldehydes remain unexplored. Data was collected from the National Health and Nutrition Examination Survey (NHANES) 2013–2014. Generalized linear regression and restricted cubic spline models were performed to elucidate the association of dietary fiber intake with the serum concentration of aldehydes. After fully adjusting for age, sex, education level, race, smoking status, alcohol use, diabetes, hypertension, body mass index, energy intake, poverty-income ratio, and physical activity, dietary fiber intake had a strong negative association with serum levels of isopentanaldehyde and propanaldehyde and a positive association with serum levels of benzaldehyde. The estimated increases in the mean log2-unit (ng/mL) of aldehydes for each fold increase in dietary fiber were −0.140 (95% confidence interval [CI]: −0.195 to −0.085) for isopentanaldehyde, −0.060 (95% CI: −0.099 to −0.015) for propanaldehyde, and 0.084 (95% CI: 0.017 to 0.150) for benzaldehyde, respectively. No significant association was observed between dietary fiber intake and the concentration of any other aldehydes. These results demonstrate that dietary fiber reduces the concentration of certain aldehydes in serum.

Metal pollution is one of the main environmental threats in freshwater ecosystems. Aquatic animals can accumulate these substances and transfer them across the food web, posing risks for both predators and humans. Accumulation patterns strongly vary depending on the location, species, and size (which in fish and crayfish is related to age) of individuals. Moreover, high metal concentrations can negatively affect animals’ health. To assess the intraspecific relationship between metal accumulation and size and health (proxied by the body condition) of individuals, the concentration of 14 metals (Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mg, Mn, Ni, Pb, Se, Zn) was analyzed in six alien species from the highly anthropogenically altered Arno River (Central Italy): five fish (Alburnus alburnus, Pseudorasbora parva, Lepomis gibbosus, Ictalurus punctatus, and Silurus glanis) and one crayfish (Procambarus clarkii). We found that in P. clarkii, Cu was negatively related to size, as well as Al in L. gibbosus and Mg for adult I. punctatus. Positive size-dependent relationships were found for Hg in L. gibbosus, Fe in S. glanis, and Cr in juvenile I. punctatus. Only Co and Mg in S. glanis were found to negatively correlate with individual health. Since metal concentrations in animal tissue depend on trade-offs between uptake and excretion, the few significant results suggest different types of trade-offs across different species and age classes. However, only predatory fish species (L. gibbosus, I. punctatus, and S. glanis) presented significant relationships, suggesting that feeding habits are one of the primary drivers of metal accumulation.

Future climate scenarios are predicting considerable threats to sustainable maize production in arid and semi-arid regions. These adverse impacts can be minimized by adopting modern agricultural tools to assess and develop successful adaptation practices. A multi-model approach (climate and crop) was used to assess the impacts and uncertainties of climate change on maize crop. An extensive field study was conducted to explore the temporal thermal variations on maize hybrids grown at farmer’s fields for ten sowing dates during two consecutive growing years. Data about phenology, morphology, biomass development, and yield were recorded by adopting standard procedures and protocols. The CSM-CERES, APSIM, and CSM-IXIM-Maize models were calibrated and evaluated. Five GCMs among 29 were selected based on classification into different groups and uncertainty to predict climatic changes in the future. The results predicted that there would be a rise in temperature (1.57–3.29 °C) during the maize growing season in five General Circulation Models (GCMs) by using RCP 8.5 scenarios for the mid-century (2040–2069) as compared with the baseline (1980–2015). The CERES-Maize and APSIM-Maize model showed lower root mean square error values (2.78 and 5.41), higher d-index (0.85 and 0.87) along reliable R² (0.89 and 0.89), respectively for days to anthesis and maturity, while the CSM-IXIM-Maize model performed well for growth parameters (leaf area index, total dry matter) and yield with reasonably good statistical indices. The CSM-IXIM-Maize model performed well for all hybrids during both years whereas climate models, NorESM1-M and IPSL-CM5A-MR, showed less uncertain results for climate change impacts. Maize models along GCMs predicted a reduction in yield (8–55%) than baseline. Maize crop may face a high yield decline that could be overcome by modifying the sowing dates and fertilizer (fertigation) and heat and drought-tolerant hybrids.

To know about the reasons leading to variations in dust control efficiency of the surfactant solution spray on coal dust (from the same coal source) with different diameters, the changes of coal dust surface features (specific surface area, pore volume, gas adsorption, and surface potential) with crush degrees and their effects on the wettability were investigated. The experimental results indicated that the surface characteristics of coal dust showed remarkably positive correlations with the crush degree. For example, dust size was reduced from 114.96 to 18.71 μm, the pore volume and gas adsorption of coal dust surface was enhanced by 75%, 104.5%, respectively. It made gas film around dust particles more easily been generated, hindering the contact between dust particles and droplets. The adsorption rate of the surfactant molecules on the coal dust surface was significantly reduced with the dust size decreased, increasing the difficulty of capturing coal dust by surfactant solution. Additionally, based on the linear fitting analysis between surface features and the dust control efficiency, it was indicated that the increased gas adsorption and pore structures on the dust surface was the key factors weakening the dust removal efficiency of the surfactant solution from the perspective of the physical features of coal dust. This study was conducive to optimizing the surfactant-aided dust control technology to better capture coal dust with small size.

The aim of this work has been the identification of the painter’s materials employed in the wall decoration of some destroyed buildings dating approximately between the first century B.C. and the first century A.D. This research originates from a previously started joined archaeological and analytical investigation concerning a varied group of findings that resulted from a rescue excavation performed by Soprintendenza Archeologica in the area of Monte d’Oro in Rome. The focus of this study progression has been directed to a numerous selection of monochrome red, pink and yellow-pigmented fragments. The analyses were performed by means of scanning electron microscopy energy dispersive X-ray spectroscopy (SEM-EDX) combined with Raman and Fourier transform infrared (FTIR) spectroscopies; visible reflectance measurements have also been carried out and the relevance of this technique in such a kind of archaeological studies has been highlighted. Most attention has been given to the assessment of the performances of non-destructive techniques achieved by portable Raman, and visible reflectance instrumentation to test their diagnostic capabilities. In addition to the expected and well-known pigments such as cinnabar, red ochre, hematite for the reds and yellow ochre for the yellows, the study highlighted a diffuse use of mixed colours and in some cases the possible presence of overlapped painted layers and confirmed the presence of gildings. Among the mixtures of pigments, the most singular outcome concerns the pink fragments revealing the possible application of bone white, which seems to be rather uncommon as a pigment in Roman wall decorations.