Eutrophication is a serious threat to water quality and human health, and chlorophyll-a (Chla) is a key indicator to represent eutrophication in rivers or lakes. Understanding the spatial-temporal distribution of Chla and its accurate prediction are significant for water system management. In this study, spatial-temporal analysis and correlation analysis were applied to reveal Chla concentration pattern in the Fuchun River, China. Then four exogenous variables (wind speed, water temperature, dissolved oxygen and turbidity) were used for predicting Chla concentrations by six models (3 traditional machine learning models and 3 deep learning models) and compare the performance in a river with different hydrology characteristics. Statistical analysis shown that the Chla concentration in the reservoir river segment was higher than in the natural river segment during August and September, while the dominant algae gradually changed from Cyanophyta to Cryptophyta. Moreover, air temperature, water temperature and dissolved oxygen had high correlations with Chla concentrations among environment factors. The results of the prediction models demonstrate that extreme gradient boosting (XGBoost) and long short-term memory neural network (LSTM) were the best performance model in the reservoir river segment (NSE = 0.93; RMSE = 4.67) and natural river segment (NSE = 0.94; RMSE = 1.84), respectively. This study provides a reference for further understanding eutrophication and early warning of algal blooms in different type of rivers.

The study aimed to investigate the correlation between meteorological parameters and the spread of the COVID-19 pandemic in Islamabad, Pakistan. The meteorological parameters include temperature minimum (°C), temperature maximum (°C), temperature average (°C), humidity minimum (%), humidity maximum (%), humidity average (%), and rainfall (mm). The data of COVID-19, such as the number of new confirmed cases and deaths was obtained from the Ministry of Health, Pakistan. The correlations of various types, i.e., Pearson, Spearman, and Kendall correlations between meteorological parameters and COVID-19, were employed for data analyses. The results exhibited a highly significant relationship between COVID-19 and temperature minimum and temperature average among all meteorological parameters. The study findings may help competitive authorities to combat this disease in Pakistan.

Driving behaviour analysis has drawn much attention in recent years due to the dramatic increase in the number of traffic accidents and casualties, and based on many studies, there is a relationship between the driving environment or behaviour and the driver\'s state. To the best of our knowledge, these studies mostly investigate relationships between one vital sign and the driving circumstances either inside or outside the cabin. Hence, our paper provides an analysis of the correlation between the driver state (vital signs, eye state, and head pose) and both the vehicle maneuver actions (caused by the driver) and external events (carried out by other vehicles or pedestrians), including the proximity to other vehicles. Our methodology employs several models developed in our previous work to estimate respiratory rate, heart rate, blood pressure, oxygen saturation, head pose, eye state from in-cabin videos, and the distance to the nearest vehicle from out-cabin videos. Additionally, new models have been developed using Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) to classify the external events from out-cabin videos, as well as a Decision Tree classifier to detect the driver\'s maneuver using accelerometer and gyroscope sensor data. The dataset used includes synchronized in-cabin/out-cabin videos and sensor data, allowing for the estimation of the driver state, proximity to other vehicles and detection of external events, and driver maneuvers. Therefore, the correlation matrix was calculated between all variables to be analysed. The results indicate that there is a weak correlation connecting both the maneuver action and the overtaking external event on one side and the heart rate and the blood pressure (systolic and diastolic) on the other side. In addition, the findings suggest a correlation between the yaw angle of the head and the overtaking event and a negative correlation between the systolic blood pressure and the distance to the nearest vehicle. Our findings align with our initial hypotheses, particularly concerning the impact of performing a maneuver or experiencing a cautious event, such as overtaking, on heart rate and blood pressure due to the agitation and tension resulting from such events. These results can be the key to implementing a sophisticated safety system aimed at maintaining the driver\'s stable state when aggressive external events or maneuvers occur.

Polycyclic aromatic hydrocarbons (PAHs) and black carbon (BC) often coexist in PM2.5 because both form during the incomplete combustion of organic matter. These compounds are regarded as hazardous air pollutants with potential health effects, including respiratory and cardiovascular effects. In this study, to evaluate the health risks of PAHs and BC at an urban site in northern Taiwan, 16 priority PAHs and BC, identified by the United States Environmental Protection Agency, were analyzed and quantified in PM2.5 to determine their concentrations, their relationship with each other, and their likely sources. The results indicated that the mean concentrations of total PAHs and BC were 0.91 ng m-3 and 0.97 μg m-3, respectively, with a significant positive correlation between them, indicating the same emission sources. The results also indicated that fossil fuel combustion and traffic emissions were primary contributors to PAHs, with wood and biomass combustion playing a less prominent role. Among these 16 priority PAHs, benzo[a]pyrene, dibenz[a,h]anthracene, benzo[b]fluoranthene, and indeno[1,2,3-cd]pyrene served as major carcinogenic compounds, accounting for 89.0% of the total carcinogenic toxicity. Thus, the lifetime excess cancer risk resulting from PAH exposure was estimated as 8.03 × 10-6, indicating a potential carcinogenic risk to human health at the sampling site. Overall, this study highlights the need for future mitigation policies for traffic emissions and fossil fuel combustion for reducing the local emissions of BC and co-produced PAHs in northern Taiwan.

With the continuous expansion of cities, the land cover type of the region is transformed, a large number of natural landscapes are replaced by man-made landscapes, and the environmental temperature rises. The study of the response relationship between urban spatial pattern and thermal environment provides some guidance for improving the ecological environment and optimizing the urban spatial layout. Based on the Landsat 8 series remote sensing image data of Hefei City in 2020 and analysis platforms such as ENVI and ARCGIS, Pearson correlation and profile lines were used to reflect the correlation between the two. Then, the three spatial pattern components with the greatest correlation were selected to construct multiple regression functions to investigate the influence of urban spatial pattern on urban thermal environment and its mechanism of action. The results showed that:① the high temperature area of Hefei City increased significantly with the advance of time during 2013-2020. For different seasons, the urban heat island effect showed that summer>autumn>spring>winter. ② In the central urban area, the building occupancy, building height, imperviousness occupancy, and population density were significantly higher than those in the suburbs, whereas fractional vegetation coverage presented a higher suburban than urban area and mainly showed a point distribution in the urban area and an irregular distribution of water bodies. ③ The urban high-temperature zone was mainly distributed in various development zones in urban areas, whereas other places in urban areas were dominated by medium-high temperature and above-temperature zoning, and suburban areas were dominated by medium-low temperature. ④ The Pearson coefficients between the spatial pattern of each element and the thermal environment were positively correlated with the building occupancy (0.395), impervious surface occupancy (0.333), population density (0.481), and building height (0.188) and negatively correlated with fractional vegetation coverage (-0.577) and water occupancy (-0.384). The coefficients of the constructed multiple regression functions, including building occupancy, population density, and fractional vegetation coverage, were 8.372, 0.295, and -5.639 respectively, with a constant of 38.555. The results of this study can provide a reference basis for optimizing urban spatial layouts and improving urban living quality.

The COVID-19 severely affected the world in 2020. Taking the two outbreaks in China in 2020 and 2022 as examples, the spatiotemporal changes in surface water quality levels and CODMn and NH3-N concentrations were analyzed, and the relationships between the variations in the two pollutants and environmental and social factors were evaluated. The results showed that during the two lockdowns, due to the total water consumption (including industrial, agricultural, and domestic water) decreased, the proportion of good water quality increased by 6.22% and 4.58%, and the proportion of polluted water decreased by 6.00% and 3.98%, the quality of water environment has been improved significantly. However, the proportion of excellent water quality decreased by 6.19% after entering the unlocking period. Before the second lockdown period, the average CODMn concentration exhibited a \"falling, rising, and falling\" trend, while the average NH3-N concentration changed in the opposite direction. The correlation analysis revealed that the increasing trend of pollutant concentrations was positively correlated with longitude and latitude, and weakly correlated with DEM and precipitation. A slight decrease trend in NH3-N concentration was negatively correlated with the population density variation and positively correlated with the temperature variation. The relationship between the change in the number of confirmed cases in provincial regions and the change in pollutant concentrations was uncertain, with positive and negative correlations. This study demonstrates the impact of lockdowns on water quality and the possibility of improving water quality through artificial regulation, which can provide a reference basis for water environmental management.

UNASSIGNED: Screening and identification of hematologic molecular indicators of pulmonary tuberculosis (PTB) is crucial for its diagnose and therapy. Therefore, our work aims to detect the diagnostic value of blood marker B and T lymphocyte attenuator (BTLA) in PTB, and provide a certain theoretical basis for the auxiliary diagnosis of PTB.
UNASSIGNED: Based on the inclusion criteria, 56 Patients with clinically confirmed pulmonary TB by clinical between January 2020 and December 2021 at our hospital were selected as the research objects of this study. Fifty-two matched healthy population at our hospital was used as the control group. Clinical characteristics were got from clinical laboratory. Real-time polymerase chain reaction (RT-PCR) was used to analyze changes in BTLA along with its ligand in peripheral blood. Changes in BTLA on the surface of different cells were analyzed by flow cytometry. The correlation test was used to determine the associations between BTLA and clinical indicators. Receiver operating characteristic (ROC) curve analysis was used to evaluate the auxiliary diagnostic value in PTB of BTLA expression from different sources.
UNASSIGNED: Compared with the control, changes in peripheral blood BTLA in the PTB group were significantly increased (P=0.0187) rather than its ligand. Changes in BTLA on the surface of CD68 and antigen-presenting cell (APC) CD11c were significantly increased in the PTB group (P=0.0004, P<0.0001), while changes in BTLA on the surface of CD4+ T and CD8+ T cells were not significantly different (P=0.0792, P=0.8706). The expression of BTLA+CD11c+ was negatively correlated with the expression of immunoglobulin A (IgA) (r=-0.2934, P=0.0282) and positively related to C-reactive protein (r=0.3277, P=0.0137). ROC curve analysis suggested that the area under the curve (AUC), sensitivity and specificity of BTLA RT-PCR detection were 0.6315, 53.57%, 57.69% while for BTLA+CD11c+ detection were 0.8039, 88.46% and 73.21% and for BTLA+CD68+ detection were 0.6973, 60.71% and 61.54%.
UNASSIGNED: BTLA is highly expressed in peripheral blood and specific cell types of patients with PTB and is correlated with specific clinical indicators, which may be an important molecular marker for the auxiliary diagnosis of PTB.

The problem of urban ozone (O3) pollution has become prominent in recent years. However, the meteorological factors associated with O3 pollution remain unclear. Analyzing the characteristics of O3 pollution in Suzhou, as a typical urban city, and exploring the high-impact meteorological factors with O3 pollution are crucial to the prevention and control of air pollution in this region. This study used correlation analysis and machine learning methods to analyze the variation in O3 concentration and the relationship between meteorological driving factors in Suzhou based on the O3 concentration data provided by Suzhou Environmental Monitoring Center and the contemporaneous meteorological observation data in Suzhou from April to September in 2015 to 2020. The results showed that: ① O3 pollution exceeding the standard rate was more than 20% in ozone seasons during the past six years; further, pollution days of O3 and the number of pollution days of O3 as the primary pollutant increased yearly. Evidently, the problem of O3 pollution has become increasingly prominent. ② The diurnal variations in O3 were unimodal with the valley point at 07:00 and the highest peak between 15:00 and 16:00. Similar trends were found in diurnal variations of both air temperature and solar radiation, but the daily highest peak came earlier than that of O3. The results also showed an apparent weekend effect of O3 concentration in 2017 and 2019 and a significant correlation between O3 concentration and solar irradiance during the week. In addition, the monthly variation in O3 concentration and pollution exceeding the standard rate was bimodal. ③The occurrence of ozone pollution was affected by various meteorological conditions. The maximum number of days appeared when daily sunshine hours lasted longer than 7 hours, with a daily maximum air temperature around 30℃, solar irradiance ranging from 350 to 440 kW·m-2, and relative humidity ranging from 50% to 75%, at which time the intensity of pollution was the strongest. When the wind speed of easterly wind was less than 1.5 m·s-1, or the wind speed of southwest wind was less than 3.5 m·s-1, moderate ozone pollution occurred. ④ An optimal prediction model of O3 concentration was established based on machine learning, which had good predictive ability for O3 concentration in April, May, July, and September but did not perform well when O3 concentration exceeded 200 μg·m-3. Meanwhile, it was found that solar radiation had the most obvious effect on O3 concentration, followed by relative humidity, whereas the temperature and wind were less important than the former two factors.

Multigenerational toxicity tests provide more sensitive measures of population-level effects than conventional single-generation tests. Particularly for stressors which exhibit slow uptake rates (e.g. nanomaterials), multigenerational tests may also provide a more realistic representation of natural exposure scenarios. To date, the inherently high costs and labor intensity have however limited the use of multigenerational toxicity tests and thereby their incorporation in environmental risk assessment. The aim of the present study was therefore to determine to what extent short(er) term endpoints which are conventionally measured in Daphnia magna toxicity tests hold predictive capacity towards reproduction measured over longer timescales, including multiple generations. To assess this, a case-study was performed in which effects of TiO2 nanoparticles (0, 0.02, 0.2, 2 and 5 mg L-1) on D. magna life-history traits were assessed over five generations. Additionally, it was determined whether offspring derived from exposed parents exhibited sustained adverse effects when rearing them in clean (non-exposed) media after each generation of exposure. The present study showed that although various life-history traits correlate with the total reproductive output in the same- and subsequent generation under non-exposed conditions, these correlations were decoupled in presence of exposure to nTiO2. In addition, it was found that nTiO2 can induce adverse effects on population relevant endpoints at concentrations 1-2 orders of magnitude lower than previously found (i.e. 0.02 mg L-1), and close to the range of concentrations occurring in natural freshwater ecosystems.

Long-term retention and accumulation of heavy metals in surface water and sediment pose a great threat to the sustainable development of aquatic ecosystems and human health. In this research, macrozoobenthos, and surface water and sediment heavy metal (Mn, Cr, Cu, Ni, Pb, Zn, Cd, and As) samples were collected from 23 sites in the upper and middle reaches of the Heihe River in the summers of 2019-2020. The interrelationships between heavy metals and macrozoobenthos were analyzed by Pearson correlation analysis and redundancy analysis (RDA), and the contamination level and potential ecological risk of the heavy metals in surface water and sediments were assessed by comprehensive pollution index (WQI), single potential ecological risk index ([Formula: see text]), and sediment quality guideline-quotient (SQG-Q), respectively. The results showed that the level of heavy metal pollution in the surface water of the Heihe River was extremely low, but the contents of Mn and Pb exceeded the third class of surface water environmental quality standards (GB 3838-2002). The spatial distribution of heavy metals in surface sediments were significantly different, and the average concentration of 8 heavy metals exceeded the background values of Gansu Province. Meanwhile, the pollution level of heavy metals in surface sediments was high pollution, and the ecological risk level was moderate risk. Combining [Formula: see text] and SQG-Q evaluations showed that Cd, Ni, and Cr were the main ecological risk factors. In addition, the distribution coefficients of Cr and Cd were low, indicating that Cr and Cd were easily released from the surface sediments, causing secondary pollution. In terms of the source of the heavy metals, Cu, As, Zn, Cr, and Ni mainly came from industrial and agricultural wastewaters, Pb was from the mining industry and natural sources, and Mn and Cd mainly came from tailings and their landfill leachate. Basommatophora and Araneae can be used as potential indicator organisms for heavy metal pollution in surface water, and Basommatophora, Coleoptera, Hemiptera, and Araneae can be used as indicator species for heavy metal pollution in surface sediments. The study showed that macroinvertebrate community characteristics had a sensitive response to heavy metals in the surface waters and sediments of the Heihe River, which can be used to evaluate the pollution status of heavy metals in inland rivers.