A comment on "Ab initio calculations of pressure-dependence of high-order elastic constants using finite deformations approach" by I. Mosyagin, A.V. Lugovskoy, O.M. Krasilnikov, Yu.Kh. Vekilov, S.I. Simak and I.A. Abrikosov

Recently, I. Mosyagin, A.V. Lugovskoy, O.M. Krasilnikov, Yu.Kh. Vekilov, S.I. Simak and I.A. Abrikosov in the paper: "Ab initio calculations of pressure-dependence of high-order elastic constants using finite deformations approach"[Computer Physics Communications 220 (2017) 2030] presented a description of a technique for ab initio calculations of the pressure dependence of second- and third-order elastic constants. Unfortunately, the work contains serious and fundamental flaws in the field of finite-deformation solid mechanics.Comment: 3 pages, 0 figure

Coefficient of variation method combined with XGboost ensemble model for wheat growth monitoring

IntroductionObtaining wheat growth information accurately and efficiently is the key to estimating yields and guiding agricultural development.MethodsThis paper takes the precision agriculture demonstration area of Jiaozuo Academy of Agriculture and Forestry in Henan Province as the research area to obtain data on wheat biomass, nitrogen content, chlorophyll content, and leaf area index. By using the coefficient of variation method, a Comprehensive Growth Monitoring Indicator (CGMI) was constructed to perform fractional derivative processing on drone spectral data, and correlation analysis was performed on the fractional derivative spectra with a single indicator and CGMI, respectively. Then, grey correlation analysis was carried out on differential spectral bands with high correlation, the grey correlation coefficients between differential spectral bands were calculated, and spectral bands with high correlation were screened and taken as input variables for the model. Next, ridge regression, random forest, and XGboost models were used to establish a wheat CGMI inversion model, and the coefficient of determination (R2) and root mean squared error (RMSE) were adopted for accuracy evaluation to optimize the wheat optimal growth inversion model.Results and discussionThe results of the study show that: using the data of wheat biomass, nitrogen content, chlorophyll content and leaf area index to construct the comprehensive growth monitoring indicators, the correlation between the wheat growth monitoring indicators and the spectra was calculated, and the results showed that the correlation between the comprehensive growth monitoring indicators and the single indicator correlation had different degrees of increase, and the growth rate could reach 82.22%. The correlation coefficient between the comprehensive growth monitoring indexes and the differential spectra reached 0.92 at the flowering stage, and compared with the correlation coefficient with the original spectra at the same period, the correlation coefficients increased to different degrees, which indicated that the differential processing of spectral data could effectively enhance the spectral correlation. The three models of Random Forest, Ridge Regression and XGBoost were used to construct the wheat growth inversion model with the best effect at the flowering stage, and the XGBoost model had the highest inversion accuracy when comparing in the same period, with the training and test sets reaching 0.904 and 0.870, and the RMSEs were 0.050 and 0.079, so that the XGBoost model can be used as an effective method of monitoring the growth of wheat. To sum up, this study demonstrates that the combination of constructing comprehensive growth monitoring indicators and differential processing spectra can effectively improve the accuracy of wheat growth monitoring, bringing new methods for precision agriculture management

Lifestyle interventions to prevent adverse pregnancy outcomes in women at high risk for gestational diabetes mellitus: a randomized controlled trial

ObjectiveTo examine the effects of lifestyle interventions, including dietary guidance, health education and weight management, on pregnancy outcomes in women at high risk of gestational diabetes mellitus (GDM).MethodsOur study included 251 women at high risk of GDM and 128 randomized to lifestyle interventions (dietary guidance, health education, and weight management); One hundred and twenty-three people were randomly assigned to a control group (regular pregnancy check-ups). Counts between groups were compared using either chi-square test or Fisher’s exact test.ResultsCompared with the control group, the risk of GDM was reduced by 46.9% (16.4% vs 30.9%, P = 0.007) and the risk of pregnancy induced hypertension (PIH) was reduced by 74.2% (2.3% vs 8.9%, P = 0.034) in the intervention group. There were no significant differences in macrosomia, cesarean section, or preterm birth (P >0.05).ConclusionThe lifestyle intervention in this study helped pregnant women to better understand knowledge related to pregnancy, reduce stress and anxiety, and increase intake of adequate prenatal nutrition. This intervention prevented metabolic abnormalities that may occur due to inadequate nutrient intake during pregnancy. In addition, it helped women to control weight gain, maintain appropriate weight gain during pregnancy, and reduce the risk of excessive or insufficient weight gain, ultimately lowering the incidence of GDM and PIH. This highlights the importance of early screening and intervention for high-risk pregnant women.Clinical Trial Registrationhttps://www.chictr.org.cn, identifier ChiCTR2300073766

Validity and Reliability of the Dyslexia Checklist for Chinese Children

The study on developmental dyslexia (DD) has fairly matured in the past decades, even when there is a lack of a standardized and convenient instrument for dyslexia in the Chinese population. The purpose of this study was to assess the reliability and validity of the Dyslexia Checklist for Chinese Children (DCCC), which was administered to Chinese students in primary school. A total of 545 students from grades 2 through 6 were recruited in Wuhan to participate in this study. We used confirmatory factor analysis (CFA) to evaluate the structure validity of the DCCC. Concurrent validity was determined via correlations between the DCCC and the verbal comprehension index (VCI), and Chinese achievement. The reliability of the DCCC was assessed via test-retest reliability and internal consistency. The CFA suggested that the first order model with eight factors and 55 items fit the data well (RMSEA = 0.057, CFI = 0.930, and TLI = 0.925). The DCCC was negatively associated with VCI (r = −0.218) and Chinese achievement (r = −0.372). The test-retest reliability of the DCCC was 0.734, and the internal consistency of all subscales was above 0.752. The DCCC thus proved to have adequate validity and reliability to screen Chinese dyslexia among students in grades 2 through 6

Emergence of Fatal PRRSV Variants: Unparalleled Outbreaks of Atypical PRRS in China and Molecular Dissection of the Unique Hallmark

Porcine reproductive and respiratory syndrome (PRRS) is a severe viral disease in pigs, causing great economic losses worldwide each year. The causative agent of the disease, PRRS virus (PRRSV), is a member of the family Arteriviridae. Here we report our investigation of the unparalleled large-scale outbreaks of an originally unknown, but so-called “high fever” disease in China in 2006 with the essence of PRRS, which spread to more than 10 provinces (autonomous cities or regions) and affected over 2,000,000 pigs with about 400,000 fatal cases. Different from the typical PRRS, numerous adult sows were also infected by the “high fever” disease. This atypical PRRS pandemic was initially identified as a hog cholera-like disease manifesting neurological symptoms (e.g., shivering), high fever (40–42°C), erythematous blanching rash, etc. Autopsies combined with immunological analyses clearly showed that multiple organs were infected by highly pathogenic PRRSVs with severe pathological changes observed. Whole-genome analysis of the isolated viruses revealed that these PRRSV isolates are grouped into Type II and are highly homologous to HB-1, a Chinese strain of PRRSV (96.5% nucleotide identity). More importantly, we observed a unique molecular hallmark in these viral isolates, namely a discontinuous deletion of 30 amino acids in nonstructural protein 2 (NSP2). Taken together, this is the first comprehensive report documenting the 2006 epidemic of atypical PRRS outbreak in China and identifying the 30 amino-acid deletion in NSP2, a novel determining factor for virulence which may be implicated in the high pathogenicity of PRRSV, and will stimulate further study by using the infectious cDNA clone technique

An Adaptive Control Combination Forecasting Method for Time Series Data

According to the individual forecasting methods, an adaptive control combination forecasting (ACCF) method with adaptive weighting coefficients was proposed for short-term prediction of the time series data. The US population dataset, the American electric power dataset, and the vibration signal dataset in a hydraulic test rig were separately tested by using ACCF method, and then, the accuracy analysis of ACCF method was carried out in the study. The results showed that, in contrast to individual methods or combination methods, the proposed ACCF method was adaptive to adopt one or some of prediction methods and showed satisfactory forecasting results due to flexible adaptability and a high accuracy. It was also concluded that the higher the noise ratio of the tested datasets, the lower the prediction accuracy of the ACCF method; the ACCF method demonstrated a better prediction trend with good volatility and following quality under noisy data, as compared with other methods

Distribution and significance of steroids in recent sediments in China

Abstract In order to study the distribution and geological significance of steroids compounds in the surface sediments, 13 recent sedimentary samples were collected from the rivers in Guangzhou, Jieyang and Yichang, and Fuxian Lake in Kunming. We investigated the distributions of steroids and the mineral compositions in those samples were analysed. Meanwhile, the relationship of mineral composition to the steroid distributions were analysed. The results showed that the mineral composition of the investigated recent sediments varied with different regions. Regular steranes were existed in all of Soxhlet extracts of the investigated sediments, while aromatic steroids were absent in some samples. Meanwhile, aromatic steroids can be generated by both biogeochemical reaction and thermal maturation catalysed by clay minerals. The sediments from the Yichang and Fuxian Lake areas revealed that the clay minerals showed little catalytic effects during the early diagenesis. And the samples from the Guangzhou and Jieyang areas suggested that the microbial reactions had dominant effect during the steroids aromatization. Therefore, the distributions of steroids in those recent sediments mainly influenced by microbial reaction

Extracting urban road area based on combination of trajectory continuity and image feature similarity

Urban road area detecting is the imperious demand in the area of management of city land use, transportation planning and so on. Trajectory extraction, remote sensing image classification and artificial collection are the traditional methods for road network detection with some limits on automation degree or extraction quality. This paper proposes a method for detecting road area in high-resolution remote sensing image based on trajectory continuity and image feature similarity, and this method utilizes the advantages of GNSS trajectory and remote sensing image. The proposed methods could be divided into three steps: firstly, using GNSS trajectory points to construct images of trajectory feature and selecting the high-confidence grids with high density value. Secondly, generating road objects based on trajectory continuity in average direction feature image. Thirdly, dividing high-resolution remote sensing image into several small areas by using road segments and extending road areas based on image feature similarity automatically to detect roads which not covered by trajectory. The experiment evidences that this method could detect road areas efficiency and accuracy in high-resolution remote sensing image and decreasing the bad effect on the different roads with different spectrums. Compared with the traditional remote sensing image classification methods, the proposed method has a higher precision and automatic degree