Precipitation-type discrimination and changes in related climate indices in the upper Heihe River Basin during 1960–2021

Introduction: Precipitation in the upstream region of the Heihe River basin (UHRB) in the northeastern of the Tibetan Plateau, which is the main water source of the basin, has undergone drastic changes in extreme climate events in recent decades. In addition to the amount of precipitation, the type of precipitation has a substantial impact on hydrological processes.Methods: In this study, we compared the results from three methods aimed at improving precipitation type estimation based on daily precipitation type records for 24 discontinuous years. Based on the precipitation type distinction, we examined the spatial and temporal changes in the total precipitation, rainfall, snowfall and air temperature at the six stations as well as the spatial average of the UHRB during the past 62 years. We also analyzed changes in the quantity, duration magnitude, and frequency of extreme precipitation using the RClimDex model and statistical analysis.Results: The probability of detection value of the T3.6_4.5 method was 1.9%, indicating the estimation was closest to actual records. The analyses based on precipitation type diving showed that rainfall accounts for an average of 81.9% of the total precipitation received in a year. In the context of large scale climate warming, temperatures at all six stations increased significantly, but precipitation changes were only apparent at about half of the stations which were located in regions of higher elevation and influenced by both ENSO and the East Asian monsoon. Analysis of the spatial averages in the UHRB revealed that the annual drought events (CDD) were significantly alleviated, and that the growing season length (GSL) was significantly extended. The annual total precipitation, rainfall, and extreme precipitation indices (P99P, P95P, R95P, and SDII) increased in magnitude, and the frequency of extreme precipitation events (P10mm) also significantly increased.Discussion: The findings of this study indicate that under the background of climate warming, the changes of precipitation patterns in the UHRB which may have resulted in bringing better vegetation growth, but also the increasingly frequent extreme rainfall events may pose challenges to growing extreme rainfall events to agriculture and other human activities in local and downstream areas

Expression and function analysis of wheat expasin genes expa2 and expb1

Expansins are a group of plant cell wall loosening proteins that play important roles in plant growth and development. In this study, we performed the first study on the molecular characterization, transcriptional expression and functional properties of two wheat expansin genes TaEXPA2 and TaEXPB1. The results indicated that TaEXPA2 and TaEXPB1 genes had typical structural features of plant expansin gene family. As a member of alpha-expansins, TaEXPA2 is closely related to rice OsEXPA17 while the beta-expansin member TaEXPB1 has closely phylogenetic relationships with rice OsEXPAB4. The genetic transformation to Arabidopsis showed that both TaEXPA2 and TaEXPB1 were located in cell wall and highly expressed in roots, leaves and seeds. Overexpression of TaEXPA2 and TaEXPB1 genes showed similar functions, causing rapid root elongation, early bolting, and increases in leaves number, rosette diameter and stems length. These results demonstrated that wheat expansin genes TaEXPA1 and TaEXPB2 can enhance plant growth and development

Hybrid neural network approaches to predict drug–target binding affinity for drug repurposing: screening for potential leads for Alzheimer’s disease

Alzheimer’s disease (AD) is a neurodegenerative disease that primarily affects elderly individuals. Recent studies have found that sigma-1 receptor (S1R) agonists can maintain endoplasmic reticulum stress homeostasis, reduce neuronal apoptosis, and enhance mitochondrial function and autophagy, making S1R a target for AD therapy. Traditional experimental methods are costly and inefficient, and rapid and accurate prediction methods need to be developed, while drug repurposing provides new ways and options for AD treatment. In this paper, we propose HNNDTA, a hybrid neural network for drug–target affinity (DTA) prediction, to facilitate drug repurposing for AD treatment. The study combines protein–protein interaction (PPI) network analysis, the HNNDTA model, and molecular docking to identify potential leads for AD. The HNNDTA model was constructed using 13 drug encoding networks and 9 target encoding networks with 2506 FDA-approved drugs as the candidate drug library for S1R and related proteins. Seven potential drugs were identified using network pharmacology and DTA prediction results of the HNNDTA model. Molecular docking simulations were further performed using the AutoDock Vina tool to screen haloperidol and bromperidol as lead compounds for AD treatment. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) evaluation results indicated that both compounds had good pharmacokinetic properties and were virtually non-toxic. The study proposes a new approach to computer-aided drug design that is faster and more economical, and can improve hit rates for new drug compounds. The results of this study provide new lead compounds for AD treatment, which may be effective due to their multi-target action. HNNDTA is freely available at https://github.com/lizhj39/HNNDTA

Emotion recognition via face tracking with RealSense\u3csup\u3e™\u3c/sup\u3e 3D camera for children with autism

Although there is a growing recognition of the differences, not diminished abilities, of facial affective expressivity between Typically Developing (TD) and Autism Spectrum Disorder (ASD) individuals, which might lead to the varied recognizability of conveyed emotion by both TD and ASD individuals, little is explored on the ecological validity of these findings; that is, whether spontaneous affective facial expressions can better be produced and recognized by both populations. We aimed to address these issues in the present study, using children\u27s cartoon clips to assess two aspects of spontaneous emotion production and recognition in a context closer to real-life children\u27s cartoon movie watching (at home or a classroom). Based on the facial landmark data and a teacher/parent\u27s manual emotion tags (happy), we performed a computational analysis to compare the happy emotion labels generated by the automated algorithm and the human TD rater. Two pilot studies of six ASD children revealed the potential as well as challenges of such an approach

Hydrogeochemical Characteristics and Groundwater Quality in a Coastal Urbanized Area, South China: Impact of Land Use

Land use transformation accompanied with various human activities affects groundwater chemistry and quality globally, especially in coastal urbanized areas because of complex human activities. This study investigated the impact of land use on groundwater chemistry and quality in a coastal alluvial aquifer (CAA) of the Pearl River Delta where urbanization continues. A fuzzy synthetic evaluation method was used to evaluate the groundwater quality. Besides, factors controlling groundwater chemistry and quality in the CAA were discussed by using a principal components analysis (PCA). Nearly 150 groundwater samples were collected. All samples were filtered on-site and stored at 4 °C until the laboratory procedures could be performed. Nineteen chemical parameters including pH, dissolved oxygen, redox potential, total dissolved solids, K+, Na+, Ca2+, Mg2+, NH4+, HCO3−, NO3−, SO42−, Cl−, I−, NO2−, Pb, Mn, Fe, and As were analyzed. Results show that groundwater chemistry in the CAA was dominated by Ca-HCO3 and Ca·Na-HCO3 facies. In addition, groundwater with NO3 facies was also present because of more intensive human activities. In the CAA, 61.8% of groundwaters were fit for drinking, and 10.7% of groundwaters were undrinkable but fit for irrigation, whereas 27.5% of groundwaters were unfit for any purpose. Poor-quality groundwaters in urban and agricultural areas were 1.1–1.2 times those in peri-urban areas, but absent in the remaining area. Groundwater chemistry and quality in the CAA was mainly controlled by five factors according to the PCA. Factor 1 is the release of salt and NH4+ from marine sediments, and the infiltration of domestic and septic sewage. Factor 2 is agricultural activities related to the irrigation of river water, and the use of chemical fertilizers. Factor 3 is the industrial pollution related to heavy metals and acid deposition. Factor 4 is the input of anthropogenic reducing sewage inducing the reductive dissolution of As-loaded Fe minerals and denitrification. Factor 5 is the I− contamination from both of geogenic and anthropogenic sources. Therefore, in order to protect groundwater quality in coastal urbanized areas, repairing old sewer systems in urban areas, building sewer systems in peri-urban areas, limiting sewage irrigation and the amount of chemical fertilizers application in agricultural areas, as well as strengthening the supervision of the industrial exhaust gas discharge in urban and peri-urban areas are recommended

The development of a Kinect-based online socio-meter for users with social and communication skill impairments: A computational sensing approach

Some people have impairments in social skills due to autism, phobia, or physical disabilities such as blindness. The proposed web-based system is intended to measure social interaction and communication among people situated around the target user based on their gestures and behaviors. Such multimodal portraits of behavioral data will be captured using the Kinect sensor (version 2) and provide rich sources to predict their social relationship, which will then be delivered to the target user in both qualitative and quantitative units, either in mobile or desktop applications. Currently, our system is capable of capturing and analyzing the raw data, sending the processed one to Microsoft Azure for data visualization and further behavioral analysis. The visualized data can then be ported to the therapists, doctors, parents, or caregivers for further actions. Unlike previous works which aim to accurately classify the dyadic social interactions between an adult-child pair, and thus characterizing the physiological synchrony between the pair, our study thereby adds richness to the understanding of computational sensing for the diagnosis, assessment and intervention of children with autism

Traffic-Related Trace Element Accumulation in Roadside Soils and Wild Grasses in the Qinghai-Tibet Plateau, China

This research examines traffic-source trace elements accumulations and distributions in roadside soils and wild grasses in the Qinghai-Tibet Plateau. A total of 100 soil samples and 100 grass samples including Achnatherum splendens, Anaphalis nepalensis, Artemisia sphaerocephala, Carex moorcroftii, Iris lacteal, Kobresia myosuroides, Oreosolen wattii, Oxytropis ochrocephala and Stellera chamaejasme were collected at 100 sites from different road segments. The contents of metals and metalloids, including Cu, Zn, Cd, Pb, Cr, Co, Ni and As, in the soil and grass samples were analyzed using ICP-MS. The total mean concentrations of the eight trace elements in soils are Cu (22.84 mg/kg), Zn (100.56 mg/kg), Cd (0.28 mg/kg), Pb (28.75 mg/kg), Cr (36.82 mg/kg), Co (10.24 mg/kg), Ni (32.44 mg/kg) and As (21.43 mg/kg), while in grasses are Cu (9.85 mg/kg), Zn (31.47 mg/kg), Cd (0.05 mg/kg), Pb (2.06 mg/kg), Cr (14.16 mg/kg), Co (0.55 mg/kg), Ni (4.03 mg/kg) and As (1.33 mg/kg). The metal and metalloid concentrations in the nine grass species were all below the critical values of hyperaccumulators. The mean values and Multivariate Analysis of Variance (MANOVA) results indicate that: (1) the concentrations of the trace elements in the soils are higher than those in the grasses, (2) the concentrations of Cu, Zn, Cd, Pb in the soils decrease as the roadside distance increases, (3) the concentrations of trace elements in the grasses are the highest at 10 m from the road edge, (4) the higher the traffic volume, the higher the concentrations of the trace elements in the roadside soils and grasses, and (5) when the land cover is meadow, the lower the sand content in the soil, the lower the trace element concentrations. With a trace element's bioavailability represented by its transfer factor (TF) from the soil to the grass, the TFs of the eight trace elements are not in the same orders for different grass species