Algal blooms can threaten human health if cyanotoxins such as microcystin are produced by cyanobacteria. Regularly monitoring microcystin concentrations in recreational waters to inform management action is a tool for protecting public health; however, monitoring cyanotoxins is resource- and time-intensive. Statistical models that identify waterbodies likely to produce microcystin can help guide monitoring efforts, but variability in bloom severity and cyanotoxin production among lakes and years makes prediction challenging. We evaluated the skill of a statistical classification model developed from water quality surveys in one season with low temporal replication but broad spatial coverage to predict if microcystin is likely to be detected in a lake in subsequent years. We used summertime monitoring data from 128 lakes in Iowa (USA) sampled between 2017 and 2021 to build and evaluate a predictive model of microcystin detection as a function of lake physical and chemical attributes, watershed characteristics, zooplankton abundance, and weather. The model built from 2017 data identified pH, total nutrient concentrations, and ecogeographic variables as the best predictors of microcystin detection in this population of lakes. We then applied the 2017 classification model to data collected in subsequent years and found that model skill declined but remained effective at predicting microcystin detection (area under the curve, AUC ≥ 0.7). We assessed if classification skill could be improved by assimilating the previous years\' monitoring data into the model, but model skill was only minimally enhanced. Overall, the classification model remained reliable under varying climatic conditions. Finally, we tested if early season observations could be combined with a trained model to provide early warning for late summer microcystin detection, but model skill was low in all years and below the AUC threshold for two years. The results of these modeling exercises support the application of correlative analyses built on single-season sampling data to monitoring decision-making, but similar investigations are needed in other regions to build further evidence for this approach in management application.

Cr(VI) is a carcinogen with proven mutagenic and genotoxic effects. The effects of the depositional environment (e.g., paleoweathering, paleoclimate, and paleoredox condition) on Cr enrichment in non-ultramafic aquifer solids are unclear. In this study, we presented the sedimentary characteristics of a borehole from a typical non-ultramafic aquifer with high Cr groundwater in Jingbian, central Ordos Basin, China. Chromium was enriched in the K1h sandstone aquifer, especially at depths of 400-500 m, with the highest value of mass transport coefficient (τAl,Cr) up to 92.13% and τAl,Fe up to 33.5%. The provenance of aquifer Cr was predominantly intermediate and felsic igneous rocks with a mafic rock mixture. This mafic source was inferred from Cr-rich granodiorite and mafic/ultramafic rocks in the Yinshan (Daqingshan-Wulashan) Block, northern Ordos Basin. The Cr-rich aquifer in K1h was developed due to a moderate chemical index of alteration (CIA) (mean, 56.7) under relatively warm and humid paleoclimate, as evidenced by high CIA-temperature (CIA-Temp) (mean, 6.79 °C) and paleoclimatic index values (mean, 0.40). Fe-Mn redox cycling in the oxic to suboxic environments contributed to aquifer Cr accumulation. Using path analysis, we identified that paleoclimate created favorable weathering conditions and enrichment of Fe contributed to the formation of high-Cr aquifers. The study reveals the formation of positive Cr anomalies in non-ultramafic aquifers, which is the potential source of groundwater Cr, and highlights the effects of depositional factors on Cr accumulation during aquifer deposition or early diagenesis. It can provide new insights into the natural processes of high-Cr sediments occurring in non-ultramafic aquifers.

Floating solar photovoltaic has emerged as a highly sustainable and environmentally friendly solution worldwide from the various clean energy generation technologies. However, the installation of floating solar differs from rooftop or ground-mounted solar due to the significant consideration of the availability of water bodies and suitable climatic conditions. Therefore, conducting a feasibility analysis of the suitable climate is essential for installing a floating solar plant on water bodies. These data are evaluated for the viability of installing a 6.7 MW floating solar power plant on Hatirjheel Lake in Dhaka, Bangladesh. The feasibility analysis incorporated various climatic data, such as temperature, humidity, rainfall, sunshine hours, solar radiation, and windspeed, obtained from Meteonorm 8.1 software and the archive of the Bangladesh Meteorological Department. Besides, this study gathered and analyzed the energy demands of the local grid substation operated by Dhaka Power Distribution Company, to determine the appropriate capacity and architecture of the power plant. The power plant design was conducted using the PVsyst 7.3 software, which determined the necessary equipment quantities, DC energy generation capacity, and the energy injected into the grid in MWh. The study also calculated the Levelized Cost of Energy per kilowatt-hour and the payback period for the system, which indicates the economic viability of installing the system. Furthermore, the acquired dataset possesses significant potential and can be utilized for the establishment of all sorts of solar power plants, including floating solar plants, in any location or body of water within the Dhaka Metropolitan area.

The benefits of urban green space are socially widely recognized as a direct link between plant-microbe interactions and the maintenance of biodiversity, community stability, and ecosystem functioning. Nevertheless, there is a lack of knowledge about the factors influencing microbial communities in urban green spaces, especially those related to phyllosphere epiphytes and stem epiphytes. In this study, we analyzed the microbial community assembly in leaf and stem bark samples collected from Square, Road, Campus, and Park. Illumina sequecing of 16S amplicons was performed to characterize microbial diversity and composition. The α-diversity was significantly higher in the bark epiphytic community, compared to the phyllosphere. Moreover, urban greenspaces\'type altered the way communities gathered. The main soil and air properties factors of the urban greenhouse (e.g. soil temperature, atmospheric moisture, air temperature) were shaping the characteristics of bacterial communities on the leaf surface and bark epiphytic. In addition, in the co-occurrence network analysis, keystone taxa were not mostly observed in abundant species, which may be necessary to maintain ecosystem functions. Finally, our findings provide a deeper understanding of the ecological dynamics and microbial interactions within plant phyllosphere and stem epiphytes microbiomes.

The apparent optimum air temperature for vegetation photosynthesis (Topt) is a key temperature parameter in terrestrial ecosystem models estimating daily photosynthesis or gross primary production (GPP, g C/m2/day). To date, most models use biome-specific Topt (Topt-biome) parameter values. Given vegetation acclimation and adaptation to local climate, site-specific Topt (Topt-site) is needed to reduce uncertainties in estimating daily GPP across the scales from site to region and the globe. Previous studies have demonstrated using the Enhanced Vegetation Index (EVI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images and daytime air temperature data to estimate the Topt-site at the eddy covariance tower sites. This study used MODIS-derived EVI and ERA5 climate data to estimate and generate global Topt-site data products from 2000 to 2019. The Topt-site of individual pixels within a biome has large variation, which clearly cannot be represented accurately by the widely used Topt-biome. Therefore, using this global dataset of Topt-site estimates might significantly affect GPP simulation in current ecosystem models.

Temperature and humidity are studied in the context of seasonal infections in temperate and tropical zones, but the relationship between viral trends and climate variables in temperate subtropical zones remains underexplored. Our retrospective study analyzes respiratory pathogen incidence and its correlation with climate data in a subtropical zone. Retrospective observational study at Moinhos de Vento Hospital, South Brazil, aiming to assess seasonal trends in respiratory pathogens, correlating them with climate data. The study included patients of all ages from various healthcare settings, with data collected between April 2022 and July 2023. Biological samples were analyzed for 24 pathogens using polymerase chain reaction and hybridization techniques; demographic variables were also collected. The data was analyzed descriptively and graphically. Spearman tests and Poisson regression were used as correlation tests. Tests were clustered according to all pathogens, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza viruses, rhinovirus, and respiratory syncytial virus (RSV). Between April 2022 and July 2023, 3329 tests showed a 71.6% positivity rate. Rhinovirus and RSV predominated, exhibiting seasonal patterns. Temperature was inversely correlated with the viruses, notably rhinovirus, but SARS-CoV-2 was positively correlated. Air humidity was positively correlated with all pathogens, RSV, rhinovirus, and atmospheric pressure with all pathogens and rhinovirus. Our results showed statistically significant correlations, with modest effect sizes. Our study did not evaluate causation effects. Despite the correlation between climate and respiratory pathogens, our work suggests additional factors influencing transmission dynamics. Our findings underscore the complex interplay between climate and respiratory infections in subtropical climates.

The article presents the results of scientific research on the production of lamb in the conditions of the Akmola region. The experiment was conducted on purebred Kazakh short-tailed rough-haired and cross-bred sheep obtained from industrial crossing of Kazakh short-tailed rough-haired queens with sheep- producers of the hampshire breed. Further, the article presents the results of feeding and fattening, as well as the morphological composition of the carcass of sheep of the Kazakh coarse-haired sheep breed of different ages. The object of the study for feeding and fattening were three groups of experimental sheep of the above-mentioned breed, where compound feed was included in the diet of the I experimental group in the form of top dressing, in the II experimental group, grain waste was also used for top dressing, and the control group was kept in the feed without top dressing. Based on the study of the feeding of experimental sheep, it was found that the absolute increase during the feeding period in experimental sheep who received fertilization in the form of compound feed is higher than in their peers, respectively, by 0.2 and 1.49 kg. In terms of morphological and varietal composition, in particular, the number of cuts of grade 1, there was also an advantage of experimental sheep that received fertilization in the form of compound feed compared to their peers, respectively, by 2.3-8.3%. In general, the results of a study on the growth, development and slaughter qualities of experimental sheep, i.e. purebred Kazakh short-tailed rough-haired and crossbred, obtained from crossing with sheep producers of the precocious breed \"hampshire\" showed that from the moment of birth to 2 and 4 months. For example, crossbred sheep were slightly superior to purebred peers in terms of the studied indicators. In particular, the results of feeding sheep of the Kazakh coarse-haired broad-tailed breed from 4 to 6 months, depending on the top dressing.

Serial correlations within temperature time series serve as indicators of the temporal consistency of climate events. This study delves into the serial correlations embedded in global surface air temperature (SAT) data. Initially, we preprocess the SAT time series to eradicate seasonal patterns and linear trends, resulting in the SAT anomaly time series, which encapsulates the inherent variability of Earth\'s climate system. Employing diverse statistical techniques, we identify three distinct types of serial correlations: short-term, long-term, and nonlinear. To identify short-term correlations, we utilize the first-order autoregressive model, AR(1), revealing a global pattern that can be partially attributed to atmospheric Rossby waves in extratropical regions and the Eastern Pacific warm pool. For long-term correlations, we adopt the standard detrended fluctuation analysis, finding that the global pattern aligns with long-term climate variability, such as the El Niño-Southern Oscillation (ENSO) over the Eastern Pacific. Furthermore, we apply the horizontal visibility graph (HVG) algorithm to transform the SAT anomaly time series into complex networks. The topological parameters of these networks aptly capture the long-term correlations present in the data. Additionally, we introduce a novel topological parameter, Δσ, to detect nonlinear correlations. The statistical significance of this parameter is rigorously tested using the Monte Carlo method, simulating fractional Brownian motion and fractional Gaussian noise processes with a predefined DFA exponent to estimate confidence intervals. In conclusion, serial correlations are universal in global SAT time series and the presence of these serial correlations should be considered carefully in climate sciences.

BACKGROUND: Fatigue in surgical technologists is of paramount importance and is known as a priority because it can be regarded as a threat to the nurse\'s health and patient\'s safety. The fatigue level of healthcare workers can be affected by some factors, while the role of part of these factors is less known. This study aimed to determine the predictive role of resilience and the hospital ethical climate in the fatigue of surgical technologists working in operating rooms (ORs).
METHODS: This is a cross-sectional study conducted on 217 surgical technologists working in ORs of hospitals affiliated with Shiraz University of Medical Sciences. Data were collected using Connor-Davidson\'s Resilience scale, Olson\'s Hospital Ethical Climate Survey, and the Multidimensional Fatigue Inventory, and then analyzed using Pearson\'s correlation coefficient and multiple regression analysis.
RESULTS: 87.1% and 12.9% of surgical technologists reported low and high fatigue, respectively. All fatigue subscales had significant and negative relationships with resilience (p < 0.05). Moreover, the relationship between fatigue and ethical climate was significant (p = 0.02). The multiple linear regression model showed the predictive role of resilience in fatigue (β=-0.29, P < 0.001). According to the model, 10% of the change of fatigue was related to resilience and ethical climate.
CONCLUSIONS: The present study demonstrated the relationship between resilience and ethical climate with fatigue. Moreover, resilience was a predictor of the surgical technologists\' fatigue, so that their fatigue decreased with increasing resilience. However, future studies are recommended to determine other factors influencing fatigue in surgical technologists.

BACKGROUND: There were controversial findings in terms of the association between the incidence of Benign Paroxysmal Positional Vertigo (BPPV) and climate changes, so the current systematic review plus meta-analysis is designed to discover this possible relationship.
METHODS: Web of science, PubMed, Scopus, Google Scholar, Embase, and Cochrane library were systematically searched up to August 2023. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and Problem/Population, Intervention, Comparison, and Outcome (PICO) guidelines were used. Two authors independently reviewed the eligible articles and assessed the quality of them.
RESULTS: In total, 15 studies including 16144 patients met the inclusion criteria. Ten studies reported the relation of BPPV to monthly mean temperature, 7 to monthly average humidity, 4 to monthly average rainfall, 6 to monthly sunlight time, and 2 to average solar radiation. The incidence of BPPV was associated significantly with atmospheric pressure (P: 0.003) and rainfall (P: 0.017). However, there was not any statistically significant correlation between incidence of BPPV and humidity, sunlight time, temperature, and solar radiation level (P > 0.05).
CONCLUSIONS: The incidence of BPPV was higher in cold months of a year in both northern hemisphere and southern hemisphere countries. Although it can be because of negative correlation with temperature, the current meta-analysis did not find any statistically significant negative correlation with temperature. In addition, the incidence of BPPV was associated significantly with atmospheric pressure (positive correlation) and rainfall (negative correlation).