The Relationship between Self-Esteem and Social Phobia among College Students:The Mediating Effect of Fear of Negative Evaluation and the Moderating Effect of Perfectionism

Objectives:To explore the relationship between college students’self-esteem(SE)and their social phobia(SP),as well as the mediating role of fear of negative evaluation(FNE)and the moderating effect of perfectionism.Methods:A convenience sampling survey was carried out for 1020 college students from Shandong Province of China,utilizing measures of college students’self-esteem,fear of negative evaluation,perfectionism,and social phobia.Data analysis was performed using the SPSS PROCESS macro.Results:(1)college students’self-esteem significantly and negatively predicts their social phobia(β=−0.31,t=−10.10,p<0.001);(2)fear of negative evaluation partially mediates the relation between self-esteem and social phobia among college students,with the mediating effect accounting for 48.97%of the total effect(TE);(3)the mediating role of fear of negative evaluation is moderated by perfectionism(β=0.18,t=7.75,p<0.001),where higher levels of perfectionism strengthen the mediating effect of fear of negative evaluation.Conclusions:Perfectionism moderates the mediating effect that fear of negative evaluation plays,establishing a moderated mediating model.

Based on non-targeted metabolomics for differential components screening of Rosae Chinensis Flos and Rosae Rugosae Flos and their quality evaluation

Background:Rosa chinensis Jacq.and Rosa rugosa Thunb.are not only of ornamental value,but also edible flowers and the flower buds have been listed in the Chinese Pharmacopoeia as traditional medicines.The two plants have some differences in efficacy,but the flower buds are easily confused for similar traits.In addition,large-scale cultivation of ornamental rose flowers may lead to a decrease in the effective components of medicinal roses.Therefore,it is necessary to study the chemical composition and make quality evaluation of Rosae Chinensis Flos(Yueji)and Rosae Rugosae Flos(Meigui).Methods:In this study,40 batches of samples including Meigui and Yueji from different regions in China were collected to establish high-performance liquid chromatography fingerprints.Then,the fingerprints data was analyzed using principal component analysis,hierarchical cluster analysis,and partial least squares discriminant analysis analysis chemometrics to obtain information on intergroup differences,and non-targeted metabolomic techniques were applied to identify and compare chemical compositions of samples which were chosen from groups with large differences.Differential compounds were screened by orthogonal partial least-squares discriminant analysis and S-plot,and finally multi-component quantification was performed to comprehensively evaluate the quality of Yueji and Meigui.Results:The similarity between the fingerprints of 40 batches roses and the reference print R was 0.73 to 0.93,indicating that there were similarities and differences between the samples.Through principal component analysis and hierarchical cluster analysis of fingerprints data,the samples from different origins and varieties were intuitively divided into four groups.Partial least-squares discriminant analysis analysis showed that Meigui and Yueji cluster into two categories and the model was reliable.A total of 89 compounds were identified by high resolution mass spectrometry,mainly were flavonoids and flavonoid glycosides,as well as phenolic acids.Eight differential components were screened out by orthogonal partial least-squares discriminant analysis and S-plot analysis.Quantitative analyses of the eight compounds,including gallic acid,ellagic acid,hyperoside,isoquercitrin,etc.,showed that Yueji was generally richer in phenolic acids and flavonoids than Meigui,and the quality of Yueji from Shandong and Hebei was better.It is worth noting that Xinjiang rose is rich in various components,which is worth focusing on more in-depth research.Conclusion:In this study,the fingerprints of Meigui and Yueji were established.The chemical components information of roses was further improved based on non-targeted metabolomics and mass spectrometry technology.At the same time,eight differential components of Meigui and Yueji were screened out and quantitatively analyzed.The research results provided a scientific basis for the quality control and rational development and utilization of Rosae Chinensis Flos and Rosae Rugosae Flos,and also laid a foundation for the study of their pharmacodynamic material basis.

Future of non-invasive graft evaluation:A systematic review of proteomics in kidney transplantation

BACKGROUND Despite the developments in the field of kidney transplantation,the already existing diagnostic techniques for patient monitoring are considered insufficient.Protein biomarkers that can be derived from modern approaches of proteomic analysis of liquid biopsies(serum,urine)represent a promising innovation in the monitoring of kidney transplant recipients.AIM To investigate the diagnostic utility of protein biomarkers derived from proteomics approaches in renal allograft assessment.METHODS A systematic review was conducted in accordance with PRISMA guidelines,based on research results from the PubMed and Scopus databases.The primary focus was on evaluating the role of biomarkers in the non-invasive diagnosis of transplant-related com-plications.Eligibility criteria included protein biomarkers and urine and blood samples,while exclusion criteria were language other than English and the use of low resolution and sensitivity methods.The selected research articles,were categorized based on the biological sample,condition and methodology and the significantly and reproducibly differentiated proteins were manually selected and extracted.Functional and network analysis of the selected proteins was performed.RESULTS In 17 included studies,58 proteins were studied,with the cytokine CXCL10 being the most investigated.Biological pathways related to immune response and fibrosis have shown to be enriched.Applications of biomarkers for the assessment of renal damage as well as the prediction of short-term and long-term function of the graft were reported.Overall,all studies have shown satisfactory diagnostic accuracy of proteins alone or in combination with conventional methods,as far as renal graft assessment is concerned.CONCLUSION Our review suggests that protein biomarkers,evaluated in specific biological fluids,can make a significant contribution to the timely,valid and non-invasive assessment of kidney graft.

Study on the evaluation index system and evaluation method for self-elevating drilling unit design

In the process of designing self-elevating drilling unit, it is important, yet complicated, to use comparison and filtering to select the optimum scheme from the feasible ones. In this research, an index system and methodology for the evaluation of self-elevating drilling unit was proposed. Based on this, a multi-objective combinatorial optimization model was developed, using the improved grey relation Analysis （GRA）, in which the analytic hierarchy process （AHP） was used to determine the weights of the evaluating indices. It considered the connections within the indices, reflecting the objective nature of things, and also considered the subjective interests of ship owners and the needs of designers. The evaluation index system and evaluation method can be used in the selection of an optimal scheme and advanced assessment. A case study shows the index system and evaluation method are scientific, reasonable, and easy to put into practice. At the same time, such an evaluation index system and evaluation method will be helpful for making decisions for other mobile platforms.

Self and Peer Evaluation in English Pronunciation Instruction

A case study was carried out to test the effects of self and peer evaluation in the process of English majors' English pro-nunciation teaching and learning. First-year English majors were directed to do self and peer evaluation, whose views on the evalu-ation experience were collected through individual talks and a questionnaire. The significant majority of subjects have found the re-flection helpful in promoting their English pronunciation learning and facilitating autonomy. However, problems rise with changesof teachers' roles in the class and their assessment on students' performance and learning progress.

On Students' Self-Evaluation and Class Performance——An Empirical Study in College English Class

This paper aims to demonstrate whether students'self-evaluations influence their class performance.A questionnaire is designed and data is collected from 30 sophomore students in English class.The data analysis shows that students who have positive self-evaluation perform better and get higher class performance scores than students who have negative self-evaluation.

The Importance of Self-Evaluation and Goal-Setting in EAT

English Audio Typing(EAT)is a quite complex process which requires the learners input the main information of listening material into a computer at almost the same time when they hear it.There are many facton influence the outcomes of EAT process,among which,self-evaluation and goal-setting are relatively crucial.

Self-determinate evaluation method based on condition of weights non-dictatorial rate

The condition of weightes non-dictatorship is extended and a comprehensive evaluae method emboding self-determinate which is combined with competitive view optimization principles is built. The basic process includes simulating the model of economic man＇s self-benefit bahaviors, taking the place of experts to evaluate, bringing in the model of minimizing the sum of included angles to integrate the information of multiple objects and put the objects in order finally. The method has the advangtages of less dependendence on the subjective information, plenty of information, fair process and simple caculating. Finally, an application example is given to illustrate the effectiveness of the proposed method.

Self-organizing fuzzy clustering neural network and application to electronic countermeasures effectiveness evaluation

A self-organizing fuzzy clustering neural network by combining the self-organizing Kohonen clustering network with the fuzzy theory is proposed. This network model is designed for the effectiveness evaluation of electronic countermeasures, which not only exerts the advantages of the fuzzy theory, but also has a good ability in machine learning and data analysis. The subjective value of sample versus class is computed by the fuzzy computing theory, and the classified results obtained by self-organizing learning of Kohonen neural network are represented on output layer. Meanwhile, the fuzzy competition learning algorithm keeps the similar information between samples and overcomes the disadvantages of neural network which has fewer samples. The simulation result indicates that the proposed algorithm is feasible and effective.

Teaching evaluation on a WebGIS course based on dynamic self-adaptive teaching–learning-based optimization

Teaching evaluation on a WebGIS course is a multi-objective nonlinear high-dimensional NP-hard problem. The index system for the teaching evaluation of a WebGIS course, including teacher- and student-oriented sub-systems, is first established and used for questionnaires from 2013 to 2017. The multi-objective nonlinear high-dimensional evaluation model is constructed and then solved via dynamic self-adaptive teaching–learning-based optimization (DSATLBO). DSATLBO is based on teaching–learning-based optimization with five improvements: dynamic nonlinear self-adaptive teaching factor, extracurricular tutorship factor, dynamic self-adaptive learning factor, multi-way learning factor, and non-dominated sorting factor. WebGIS teaching performance is fully evaluated based on questionnaires and DSATLBO. Optimal weights and weighted scores from DSATLBO are compared with those from the non-dominated sorting genetic algorithm-II using the Pareto front, coverage to two sets, and spacing of the non-dominated solution sets to validate the performance of DSATLBO. The results show that DSATLBO can be uniformly distributed along the Pareto front. Therefore, DSATLBO can efficiently and feasibly solve the multi-objective nonlinear high-dimensional teaching evaluation model of a WebGIS course. The proposed teaching evaluation method can help reflecting the quality of all aspects of classroom teaching and guide the professional development of students.

Self-Expanded Clustering Algorithm Based on Density Units with Evaluation Feedback Section

This paper presents an effective clustering mode and a novel clustering result evaluating mode. Clustering mode has two limited integral parameters. Evaluating mode evaluates clustering results and gives each a mark. The higher mark the clustering result gains, the higher quality it has. By organizing two modes in different ways, we can build two clustering algorithms： SECDU（Self-Expanded Clustering Algorithm based on Density Units） and SECDUF（Self-Expanded Clustering Algorithm Based on Density Units with Evaluation Feedback Section）. SECDU enumerates all value pairs of two parameters of clustering mode to process data set repeatedly and evaluates every clustering result by evaluating mode. Then SECDU output the clustering result that has the highest evaluating mark among all the ones. By applying ＂hill-climbing algorithm＂, SECDUF improves clustering efficiency greatly. Data sets that have different distribution features can be well adapted to both algorithms. SECDU and SECDUF can output high-quality clustering results. SECDUF tunes parameters of clustering mode automatically and no man＇s action involves through the whole process. In addition, SECDUF has a high clustering performance.

Development of self-generated proppant based on modified low-density and low-viscosity epoxy resin and its evaluation

Hydraulic fracturing is a critical technology for the economic development of unconventional oil and gas reservoirs.The main factor influencing fracture propping and reservoir stimulation effect is proppant performance.The increasing depth of fractured oil and gas reservoirs is causing growing difficulty in hydraulic fracturing.Moreover,the migration of conventional proppants within the fracture is always limited due to small fracture width and rigid proppant structure.Thus,proppants with good transportation capacity and fracture propping effects are needed.First,a novel self-generated proppant based on toughened low-viscosity and low-density epoxy resin was developed to satisfy this demand.Then,proppant performances were evaluated.Low-viscosity and low-density epoxy resin was generated when the thiol-ene click chemical reaction product of eugenol and 1-thioglycerol reacts with the epichlorohydrin.Then,the resin was toughened with graphite particles to increase its compressive strength from50.8 to 72.1 MPa based on micro-cracking mechanism and crazing-nail anchor mechanism.The adduct of diethylene triamine and butyl glycidyl ether and the Si O2 nanoparticles were treated as the curing agent and emulsifier respectively to form the emulsion.The emulsion is transformed into solid particles of various sizes within a reservoir to prop the fracture.Evaluation shows good migration capacity of this self-generated proppant due to the low density of epoxy resin.

基于Self-Attention-BiLSTM网络的西瓜种苗叶片氮磷钾含量高光谱检测方法

元素含量无损检测技术可以为植物生长发育的环境精准调控提供关键实时数据。以西瓜苗为例,提出了一种基于图谱特征融合的氮磷钾含量深度学习检测方法。首先,使用高光谱仪拍摄西瓜苗叶片的高光谱图像,使用连续流动化学分析仪测定叶片的3种元素含量。然后,采用基线偏移校正(BOC)叠加高斯平滑滤波(GF)的光谱预处理方法和随机森林算法(RF)建立预测模型,基于竞争性自适应重加权采样(CARS)和连续投影算法(SPA)2种算法初步筛选出特征波长,再综合考虑波长数和建模精度设计了一种最优波长评价方法,将波长数进一步减少到3~4个。最后,提取使用U-Net网络分割的彩色图像颜色和纹理特征,和光谱反射率特征一起作为输入,基于自注意力机制-双向长短时记忆(Self-Attention-BiLSTM)网络构建了3种元素含量的预测模型。实验结果表明,氮磷钾含量预测的R2分别为0.961、0.954、0.958,RMSE分别为0.294%、0.262%、0.196%,实现了很好的建模效果。使用该模型对另2个品种西瓜进行测试,R2超过0.899、RMSE小于0.498%,表明该模型具有很好的泛化性。该高光谱建模方法使用少量波长光谱即实现了高精度检测,在精度和效率上达成了很好的平衡,为后续便携式高光谱检测装备开发奠定了理论基础。

Self Evaluation in Department of Communicable Diseases, Faculty of Medicine, Tehran University of Medical Sciences

Introduction: Self evaluation is a process that defines and collects required data to judge about decision making issues at educational system on whether the educational department is fit to educate students? The objective of this study was determining the quality of the structural elements of the department of Communicable Diseases & determining the strengths, weaknesses, opportunities and threats to improve the quality of activities in the department under research. Materials and Methods: The employed method was Mixed methods (qualitative & quantitative research), on the basis of 10 procedural steps and within 8 sections dealing with evaluated factors;such as 1) organizational and management structure 2) scientific board members 3) students 4) Manpower 5) Space of educational research and health care 6) Equipment 7) curriculum 8) satisfaction of graduates, which were studied using 61 criteria and 172 indicators. Five-point Likert Scale was used for the responses in the questionnaire (1 - 1.75 = undesirable, to 4.2 - 5 completely desirable). Finally the data were analyzed using descriptive statistics indices and the assessment software of the Educational Development Center of TUMS. The instruments used in this method included assessment software, interview, observation and self-prepared questionnaire which consisted of 7 questionnaires and 2 check lists. Finding: The results of the research showed that general average of 8 investigating sections was 56.9% as a rather desirable research work. Conclusions: Therefore, it was concluded that function of the educational management in that group was directly in line with evaluation process, but continuing the process of evaluation seems necessary.

Evaluation of Nutrition and Physical Activity Knowledge, Attitudes, Self Efficacy and Behaviors in Teachers and Children after Implementation of the “Healthy Active Kids” Online Program in Australian Elementary Schools

The aims were to examine change in nutrition and physical activity knowledge, self efficacy and attitudes in a cohort of 23 teachers and 304 year 5 and 6 children after the “Healthy Active Kids” online program and to assess any behavioral change in children’s self reported nutrition and physical activity behaviors and investigate the predictors of nutrition knowledge gain in teachers and children. Results found significant (p < 0.0001) increases in teacher and student knowledge of the five food groups;key nutrients provided by each food group, The Australian Guide to Healthy Eating;food labelling laws, identification of common names for fats, sugars and salts on food labels, food proportions on the Healthy Food Plate and the level and percentage of water in the human body and human brain. Teacher attitudes towards the importance of nutrition and diet and self efficacy related to teaching nutrition in class improved (p < 0.01). The final regression model for predictors of the dependent variable, knowledge gain in students was R = 0.53, Adjusted R square = 0.28 (F = 4.76, p < 0.01) indicating that 28% of the variation in knowledge gain was predicted by the negative (low) Time 1 knowledge. Changes to eating habits reported by children were “drinking more water each day” (89.1%) and “eating foods from the five food groups each day” (76.2%);“sharing information about food labels with your family” (52.4%);“reading food labels when you go shopping” (50.0%);“changing what is on your dinner plate each night” (44.2%);“vegetables that you eat now that you didn’t eat before” (42.1%) and “fruits that you eat now” (39%). Results suggest that the development of basic nutrition knowledge is still very important for both teachers and students, but that other factors such as self efficacy, empowerment and skill development also contribute to nutrition behavior change in children.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Frequency Domain Fatigue Evaluation on SCR Girth-Weld Based on Structural Stress

The Steel Catenary Riser(SCR)is a vital component for transporting oil and gas from the seabed to the floating platform.The harsh environmental conditions and complex platform motion make the SCR’s girth-weld prone to fatigue failure.The structural stress fatigue theory and Master S-N curve method provide accurate predictions for the fatigue damage on the welded joints,which demonstrate significant potential and compatibility in multi-axial and random fatigue evaluation.Here,we propose a new frequency fatigue model subjected to welded joints of SCR under multiaxial stress,which fully integrates the mesh-insensitive structural stress and frequency domain random process and transforms the conventional welding fatigue technique of SCR into a spectrum analysis technique utilizing structural stress.Besides,a full-scale FE model of SCR with welds is established to obtain the modal structural stress of the girth weld and the frequency response function(FRF)of modal coordinate,and a biaxial fatigue evaluation about the girth weld of the SCR can be achieved by taking the effects of multi-load correlation and pipe-soil interaction into account.The research results indicate that the frequency-domain fatigue results are aligned with the time-domain results,meeting the fatigue evaluation requirements of the SCR.

Comparative evaluation of commercial Douchi by different molds:biogenic amines,non-volatile and volatile compounds

To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.

Research on a TOPSIS energy efficiency evaluation system for crude oil gathering and transportation systems based on a GA-BP neural network

As the main link of ground engineering,crude oil gathering and transportation systems require huge energy consumption and complex structures.It is necessary to establish an energy efficiency evaluation system for crude oil gathering and transportation systems and identify the energy efficiency gaps.In this paper,the energy efficiency evaluation system of the crude oil gathering and transportation system in an oilfield in western China is established.Combined with the big data analysis method,the GA-BP neural network is used to establish the energy efficiency index prediction model for crude oil gathering and transportation systems.The comprehensive energy consumption,gas consumption,power consumption,energy utilization rate,heat utilization rate,and power utilization rate of crude oil gathering and transportation systems are predicted.Considering the efficiency and unit consumption index of the crude oil gathering and transportation system,the energy efficiency evaluation system of the crude oil gathering and transportation system is established based on a game theory combined weighting method and TOPSIS evaluation method,and the subjective weight is determined by the triangular fuzzy analytic hierarchy process.The entropy weight method determines the objective weight,and the combined weight of game theory combines subjectivity with objectivity to comprehensively evaluate the comprehensive energy efficiency of crude oil gathering and transportation systems and their subsystems.Finally,the weak links in energy utilization are identified,and energy conservation and consumption reduction are improved.The above research provides technical support for the green,efficient and intelligent development of crude oil gathering and transportation systems.

Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.