Estimation of monthly pan evaporation using support vector machine in Three Gorges Reservoir Area, China

Pan evaporation plays a critical role in estimating water budget and modeling crop water requirements. However, it has been measured at a very limited number of meteorological stations. Estimation of pan evaporation from measured meteorological variables offers an important alternative and drawn increasing attention in the recent years. This paper investigated the performance of support vector machine (SVM) in the estimation of monthly pan evaporation using commonly measured meteorological variables in Three Gorges Reservoir Area in China. Evaluation suggested that SVM models showed remarkable performances and significantly outperformed the empirical model. The SVM model with polynomial as kernel function outperformed that with radial basis function. In the case of unavailable measurements of pan evaporation and meteorological variables to construct the SVM model, pan evaporation can be well-estimated by SVM model developed using data at other sites. The results indicated that the SVM method would be a promising alternative over the traditional approaches for estimating pan evaporation from measured meteorological variables

Convolutional Neural Networks for Searching Superflares from Pixel-level Data of TESS

In this work, six convolutional neural networks (CNNs) have been trained based on %different feature images and arrays from the database including 15,638 superflare candidates on solar-type stars, which are collected from the three-years observations of Transiting Exoplanet Survey Satellite ({\em TESS}). These networks are used to replace the artificially visual inspection, which was a direct way to search for superflares, and exclude false positive events in recent years. Unlike other methods, which only used stellar light curves to search superflare signals, we try to identify superflares through {\em TESS} pixel-level data with lower risks of mixing false positive events, and give more reliable identification results for statistical analysis. The evaluated accuracy of each network is around 95.57\%. After applying ensemble learning to these networks, stacking method promotes accuracy to 97.62\% with 100\% classification rate, and voting method promotes accuracy to 99.42\% with relatively lower classification rate at 92.19\%. We find that superflare candidates with short duration and low peak amplitude have lower identification precision, as their superflare-features are hard to be identified. The database including 71,732 solar-type stars and 15,638 superflare candidates from {\em TESS} with corresponding feature images and arrays, and trained CNNs in this work are public available.Comment: 25 pages, 11 figures, 3 tables, submitte

Study on multi-period palaeotectonic stress fields simulation and fractures distribution prediction in Lannigou gold mine, Guizhou

A significant controlling factor for gold mineralisation is the tectonic stress field, and the fractures formed under its action are the migration channels and ore-holding spaces of ore-forming fluids, which often directly control the migration and accumulation of ore-forming fluids. Therefore, performing quantitative prediction research on the distribution of fractures in the Guizhou, Lannigou gold deposit in order to identify potential fluid flow pathways is of utmost importance for ore prospecting in practical. In this study, a 3D geological entity model was generated based on the GOCAD platform by analysing and processing the geological data of the studied area, as well achieved is the accurate characterisation of the study area’s geometric model. By integrating regional tectonic evolution history analysis, geological interpretation, rock mechanics experiments and acoustic emission testing, the finite element method was utilised to create a 3D geomechanical model of the research area, the paleotectonic stress field after the Indosinian and Yanshanian movements were superimposed was simulated, in associated with the rock failure criterion, the comprehensive fracture rate parameter (Iz) is introduced to predict the fracture distribution. The results show that the research area’s maximum principal stress is primarily distributed between 153.85 and 189.53 MPa, and the maximum shear stress is between 83.53 and 98.42 MPa. The spatial distribution of faults influences the stress distribution characteristics significantly, and the stress level is relatively high at the intersection of the fault, the end of the fault and the vicinity of the fault zone, and the stress value between the faults is relatively low. The tectonic stress field primarily controls the distribution and development of fractures, which is usually consistent with the areas with high values of maximum principal stress and maximum shear stress. Using the combined modeling technique of GOCAD and midas GTS to realize the conversion from 3D geological model to geomechanical model, a set of comprehensive fracture distribution prediction technique for the superposition of multi-stage tectonic stress fields of mineral deposits in complex tectonic areas has been formed, and provide a reference for the prediction of fracture distribution in similar complex structural areas.This study was supported by the program of China Scholarships Council (No. 202006670005); the National Natural Science Foundation of China (Project Nos. 51964007, 52264004, 52104080, 41962008); the Guizhou Province Science and Technology Support Program Project (Number: QIANKEHE Support [2021] General 516); Scientific and Technological Innovation Talents Team in Guizhou Province (Project No. [2019]5619); the Guizhou Province Highlevel Innovative Talents Training Project (Grant No. JZ2016-4011). Major Collaborative Innovation Project for Strategic Action of Mineral Search Breakthrough in Guizhou Province ([2022] ZD005); Natural Science Special (Special Post) Scientific Research Fund Project of Guizhou University (Project No. Guizhou University Special Post (2021) 51).Peer ReviewedPostprint (published version

Comparative study of differentiating human pluripotent stem cells into vascular smooth muscle cells in hydrogel-based culture methods

Vascular smooth muscle cells (VSMCs), which provides structural integrity and regulates the diameter of vasculature, are of great potential for modeling vascular-associated diseases and tissue engineering. Here, we presented a detailed comparison of differentiating human pluripotent stem cells (hPSCs) into VSMCs (hPSCs-VSMCs) in four different culture methods, including 2-dimensional (2D) culture, 3-dimensional (3D) PNIPAAm-PEG hydrogel culture, 3-dimensional (3D) alginate hydrogel culture, and transferring 3- dimensional alginate hydrogel culture to 2-dimensional (2D) culture. Both hydrogel-based culture methods could mimic in vivo microenvironment to protect cells from shear force, and avoid cells agglomeration, resulting in the extremely high culture efficiency (e.g., high viability, high purity and high yield) compared with 2D culture. We demonstrated hPSC-VSMCs produced from hydrogel-based culture methods had better contractile phenotypes and the potential of vasculature formation. The transcriptome analysis showed the hPSC-VSMCs derived from hydrogel-based culture methods displayed more upregulated genes in vasculature development, angiogenesis and blood vessel development, extracellular matrix compared with 2D culture. Taken together, hPSC-VSMCs produced from hydrogel-based culture system could be applied in various biomedical fields, and further indicated the suitable development of alginate hydrogel for industrial production by taking all aspects into consideration

B→KπB\to K\pi Decays with 1/mb1/m_b Corrections in QCDQCD Factorization

It is commonly believed that a careful investigation of the subleading terms is crucial for a better understanding of the $QCD$ factorization in charmless B decays. In this work the penguin-dominated $B\to K\pi$ decays are discussed systematically, including the subleading corrections in $1/m_b$ due to soft and hard gluons, besides the annihilation contributions. Soft-gluon effects for all the relevant 4-quark effective operators are calculated within the framework of the light-cone QCD sum rules (LCSR). Our observation is that such soft and hard corrections are less important than the annihilation effects, enhancing only the branching ratios by a few percent; the resultant increase in the branching ratios due to the overall ${\cal O}(1/m_b)$ effects is between about $(22-27)$ of the QCD factorization results with the ${\cal O}(\alpha_s)$ corrections, as the weak phase $\gamma (=\textmd{Im}V_{ub}^*)$ ranges from $40^0$ to $80^0$. Impacts of the involved uncertainties are discussed in some details.Comment: 22 pages,6 figure

Isolation, identification and odour-producing abilities of geosmin/2-MIB in actinomycetes from sediments in Lake Lotus, China

This study aimed to determine whether actinomycetes could contribute to the odours occurring in Lake Lotus, China. In total, 55 actinomycete strains were isolated from sediments in Lake Lotus and their odorous metabolites, geosmin and 2-methylisoborneol (2-MIB), were identified using HSPME-GC-MS. Results showed that 24, 23 and 34 strains produced geosmin and/or 2-MIB in Gause, TSB and M liquid media, respectively. Of odour-producing actinomycetes, most could produce geosmin and some produced both metabolites, while few of them produced only 2-MIB. Six isolates with high-level odour were selected for further investigation. Their biomass and odour-producing abilities were monitored in both the slants and liquid media. The results suggest that TSB was the most suitable medium for the growth of mycelium; Gause and M slant supported good production of spores, while M liquid medium was the most favourable for the production of both geosmin and 2-MIB. Those strains that produced geosmin only were less influenced than those that produced both geosmin and 2-MIB under shaking conditions. The results indicate that actinomycetes from sediments should be taken into consideration when off-flavours occur in water columns. According to the 16S rRNA sequences, six actinomycetes were classified in the Streptomyces

Association of smoking, alcohol drinking and dietary factors with esophageal cancer in high- and low-risk areas of Jiangsu Province, China

To study the main environmental and lifestyle factors that account for the regional differences in esophageal cancer (EC) risk in low- and high-risk areas of Jiangsu Province, China. Since 2003, a population-based casecontrol study has been conducted simultaneously in lowrisk (Ganyu County) and high-risk (Dafeng County) areas of Jiangsu Province, China. Using identical protocols and pre-tested standardized questionnaire, following written informed consent, eligible subjects were inquired about their detail information on potential determinants of EC, including demographic information, socio-economic status, living conditions, disease history, family cancer history, smoking, alcohol drinking, dietary habits, frequency, amount of food intake, etc. Conditional logistic regression with maximum likelihood estimation was used to obtain Odds ratio (OR) and 95 % confi dence interval (95% CI), after adjustment for potential confounders In the preliminary analysis of the ongoing study, we recruited 291 pairs of cases and controls in Dafeng and 240 pairs of cases and controls in Ganyu, respectively. In both low-risk and high-risk areas, EC was inversely associated with socio-economic status, such as level of education, past economic status and body mass index. However, this disease was more frequent among those who had a family history of cancer or encountered misfortune in the past 10 years. EC was also more frequent among smokers, alcohol drinkers and fast eaters. Furthermore, there was a geographic variation of the associations between smoking, alcohol drinking and EC risk despite the similar prevalence of these risk factors in both low-risk and high-risk areas. The dose-response relationship of smoking and smoking related variables, such as age of the fi rst smoking, duration and amount were apparent only in high-risk areas. On the contrary, a dose-response relationship on the effect of alcohol drinking on EC was observed only in low-risk area

Preparation and characterization of novel chitosan-based mixed matrix membranes resistant in alkaline media

In this work, mixed matrix membranes (MMMs) based on chitosan (CS) and different fillers (room temperature ionic liquid [emim][OAc] (IL), metallic Sn powder, layered titanosilicate AM-4 and layered stannosilicate UZAR-S3) were prepared by solution casting. The room temperature electrical conductivity and electrochemical response in strong alkaline medium were measured by electrochemical impedance spectroscopy and cyclic voltammetry (CV). The ionic conductivity of pure CS membranes was enhanced, from 0.070 to 0.126 mS cm21, for the pristine CS and Sn/CS membranes, respectively, as a function of the hydrophilic nature of the membrane and the coordination state of Sn. This hydrophilic and charge nature was corroborated by water uptake measurements, where only the introduction of IL in the CS membrane led to a water uptake of 3.96 wt %, 20 or 30 times lower than the other membranes. Good thermal and chemical stability in alkaline media were observed by thermogravimetric analyses and X-ray photoelectron spectroscopy analyses, respectively, and good interaction between CS and the fillers observed by X-ray diffraction, scanning electron microscopy and CV. Thus, thin CS-based MMMs (40–139 mm), resistant in high alkaline media, show higher conductivity than pure CS membranes, especially those fillers containing tin, and although the electrochemical performance is lower than commercially available anion-exchange membranes they have potential in pervaporation.This work has been funded by the Spanish MINECO through grants CTQ2010-20347, at the University of Alicante, and CTQ2012-31229 and RYC2011-08550, at the University of Cantabria. The authors gratefully thank Prof. Frank Marken, from the University of Bath (UK), for his advice on the electrochemical impedance characterization, and Dr. César Rubio, Dr. Carlos Téllez, and Prof. Joaquín Coronas, from the University of Zaragoza and the Instituto de Nanociencia de Aragón, Spain, for the UZAR-S3 sample and fruitful discussions