DDM regression analysis of the in-situ stress field in a non-linear fault zone

A multivariable regression analysis of the in-situ stress field, which considers the non-linear deformation behavior of faults in practical projects, is presented based on a newly developed three-dimensional displacement discontinuity method （DDM） program. The Bar- ton-Bandis model and the Kulhaway model are adopted as the normal and the tangential deformation model of faults, respectively, where the Mohr-Coulomb failure criterion is satisfied. In practical projects, the values of the mechanical parameters of rock and faults are restricted in a bounded range for in-situ test, and the optimal mechanical parameters are obtained from this range by a loop. Comparing with the traditional finite element method （FEM）, the DDM regression results are more accurate.

In-situ structural evolution analysis of Zr-doped Na_(3)V_(2)(PO_(4))_(2)F_(3) coated by N-doped carbon layer as high-performance cathode for sodium-ion batteries

With great superiorities in energy density,rate capability and structural stability,Na_(3)V_(2)(PO_(4))_(2) F_(3)(NVPF)has attracted much attentions as cathode of sodium ion battery(SIB),but it also faces challenges on its poor intrinsic electronic conductivity and the controversial de/sodiation mechanism.Herein,a series of Zr-doped NVPF coated by N-doped carbon layer(~5 nm in thickness,homogenously)materials are fabricated by a sol-gel method,and the optimized heteroatom-doping amounts of Zr and N doping improve intrinsic properties on enlarging lattice distance and enhancing electronic conductivity,respectively.Specifically,among all samples of Na_(3) V_(2-x)Zr_(x)(PO_(4))_(2) F_(3)/NC(NVPF-Zr-x/NC,x=0,0.01,0.02,0.05,and 0.1),the optimized electrode of NVPF-Zr-0.02/NC delivers high reversible capacities(119.2 mAh g^(-1) at0.5 C),superior rate capability(98.1 mA h g^(-1) at 20 C)and excellent cycling performance.The structural evolution of NVPF-Zr-0.02/NC electrode,in-situ monitored by X-ray diffractometer,follows a step-wise Na-extraction/intercalation mechanism with reversible multi-phase changes,not just a solid-solutionreaction one.Full cells of NVPF-Zr-0.02/NC//hard carbon demonstrate high capacity(99.8 mA h g^(-1) at 0.5 C),high out-put voltage(3.5 V)and good cycling stability.This work is favorable to accelerate the development of high-performance cathode materials and explore possible redox reaction mechanisms of SIBs.

An Analysis of Land Use and Land Cover Changes, and Implications for Conservation in Mukumbura (Ward 2), Mt Darwin, Zimbabwe, 2002-2022

Understanding trends of land use land cover (LULC) changes is important for biodiversity monitoring and conservation planning, and identifying the areas affected by change and designing sustainable solutions to reduce the changes. The study aims to evaluate and quantify the historical changes in land use and land cover in Mukumbura (Ward 2), Mt Darwin, Zimbabwe, from 2002 to 2022. The objective of the study was to analyse the LULC changes in Ward 2 (Mukumbura), Mt Darwin, Northern Zimbabwe, for a period of 20 years using geospatial techniques. Landsat satellite images were processed using Google Earth Engine (GEE) and the supervised classification with maximum likelihood algorithm was employed to generate LULC maps between 2002 and 2022 with a five (5) year interval, investigating the following variables, forest cover, barren land, water cover and the fields. Findings revealed a substantial reduction in forest cover by 38.8%, water bodies (wetlands, ponds, and rivers) declined by 55.6%, whilst fields (crop/agricultural fields) increased by 93.3% and the barren land cover increased by 26.3% from 2002 to 2022. These findings point to substantial changes in LULC over the observed years. LULC changes have resulted in habitat fragmentation, reduced biodiversity, and the disruption of ecosystem functions. The study concludes that if these deforestation trends, cultivation, and settlement land expansion continue, the ward will have limited indigenous fruit trees. Therefore, the causes for LULC changes must be controlled, sustainable forest resources use practiced, hence the need to domesticate the indigenous fruit trees in arborloo toilets.

Data processing and preliminary results of the Chang'e-3 VIS/NIR Imaging Spectrometer in-situ analysis

The Chang＇e-3 Visible and Near-infrared Imaging Spectrometer （VNIS） is one of the four payloads on the Yutu rover. After traversing the landing site during the first two lunar days, four different areas are detected, and Level 2A and 2B ra- diance data have been released to the scientific community. The released data have been processed by dark current subtraction, correction for the effect of temperature, radiometric calibration and geometric calibration. We emphasize approaches for re- flectance analysis and mineral identification for in-situ analysis with VNIS. Then the preliminary spectral and mineralogical results from the landing site are derived. After comparing spectral data from VNIS with data collected by the Ma instrument and samples of mare that were returned from the Apollo program, all the reflectance data have been found to have similar absorption features near 1000 nm except lunar sample 71061. In addition, there is also a weak absorption feature between 1750-2400nm on VNIS, but the slopes of VNIS and Ma reflectance at longer wavelengths are lower than data taken from samples of lunar mare. Spectral parameters such as Band Centers and Integrated Band Depth Ratios are used to analyze mineralogical features. The results show that detection points E and N205 are mixtures of high-Ca pyroxene and olivine, and the composition of olivineat point N205 is higher than that at point E, but the compositions of detection points S3 and N203 are mainly olivine-rich. Since there are no obvious absorption features near 1250 nm, plagioclase is not directly identified at the landing site.

Fabrication and analysis of TIG welding-brazing butt joints of in-situ TiB2/7050 composite and TA2

Lightweight hybrid structures of Al MMCs and titanium alloy dissimilar materials have great prospect in the defence industry application. So, it is necessary to join Al MMCs with Ti metal to achieve this structural design. In this work, in-situ Ti B_(2)/7050 composite and TA2 were firstly attempted to join by TIG welding-brazing technique. The result was that the intact welding-brazing butt joint was successfully fabricated. The joint presents dual characteristics, being a brazing on TA2 side and a welding on Ti B_(2)/7050 side. At brazing joint side, ER4043 filler metal effectively wets on TA2 under TIG heating condition,and a continuous interfacial reaction layer with 1 e3 mm is formed at welded metal/TA2 interface. The whole interfacial reaction layers are composed of Ti(Al Si)3 intermetallic compounds(IMCs), but their morphologies at the different regions present obvious distinguishes. The microhardness of the reaction layers is as much as 141 e190 HV. At welding joints side, the fusion zone appears the equixaed crystal structure, and the grain sizes are much smaller than those of welded metal, which is attributed to the effect of Ti B2 particulates from the melted Ti B_(2)/7050 on acceleration formation and inhibiting growth for the new crystal nucleus. The tensile test results show that average tensile strength of the optimal welding-brazing joint is able to achieve 138 MPa. The failure of the tensile joint occurs by quasi-cleavage pattern, and the cracks initiate from the IMCs layer at the groove surface of TA2 and propagate into the welded metal.

Analysis on Protection of GI Product Xiangshan Spirit and Suggestions of Its Industrial Supervision

From name, historic stories, reputation, traffic and location factors, and natural factors as production and processing, water, raw material and yeast, this paper firstly analyzes key factors for protection of GI product Xiangshan Spirit. Then, it discusses differences in quality characteristics between Xiangshan Spirit and other rice flavor type spirits. Besides, industrial development of Xiangshan Spirit is analyzed from residues of pesticides, quality of water for making wine, and exclusive use of geographical indication Xiangshan Spirit. Finally, it puts forward following suggestions, including formulating and implementing local standard GI Product Xiangshan Spirit, strengthening quality control over rice raw material, implementing "enterprise + base" industrial model, and support group enterprises with government as leader.

LOCAL CORRELATION DISCRIMINANT ANALYSIS AND ITS SEMI-SUPERVISED EXTENSION

Considering limitations of Linear Discriminant Analysis (LDA) and Marginal Fisher Analysis (MFA), a novel discriminant analysis called Local Correlation Discriminant Analysis (LCDA) is proposed in this paper. The main idea behind LCDA is to use more robust similarity measure, correlation metric, to measure the local similarity between image data. This results in better classifi-cation performance. In addition, to further improve the discriminant power of LCDA, we extend LCDA to semi-supervised case, which can make use of both labeled and unlabeled data to perform dis-criminant analysis. Extensive experimental results on ORL and AR face databases demonstrate that the proposed LCDA and its semi-supervised version are superior to Principal Component Analysis (PCA), LDA, CEA, and MFA.

A Data Analysis Framework for Earth System Simulation within an <i>In-Situ</i>Infrastructure

This paper presents a generic procedure to implement a scalable and high performance data analysis framework for large-scale scientific simulation within an in-situ infrastructure. It demonstrates a unique capability for global Earth system simulations using advanced computing technologies (i.e., automated code analysis and instrumentation), in-situ infrastructure (i.e., ADIOS) and big data analysis engines (i.e., SciKit-learn). This paper also includes a useful case that analyzes a globe Earth System simulations with the integration of scalable in-situ infrastructure and advanced data processing package. The in-situ data analysis framework can provides new insights on scientific discoveries in multiscale modeling paradigms.

Analysis of Identification and Supervision of Financial Risk Based on One Belt and One Road

With the continuous development andprogress of social economy, people pay more and moreattention to financial risks. Thus modern economy hasclose link with finance, and the One Belt and One Roadis a new exploration of social economy. If the moderneconomy wants better development, One Belt and OneRoad construction should be brought into economicdevelopment. And it has an impact on trade financingand outward investment of enterprises. Therefore,if it wants to be carried out smoothly, the financialmanagement mechanism should be improved. In thispaper, a concrete analysis of the identification andsupervision of financial risks will be made under OneBelt and One Road construction.

Key Points of Supervision of Third-Party Payment Business:A Comparative Analysis of China's Mainland and Macao

China's Mainland has witnessed remarkable achievements in payment innovations based on internet and financial technologies in recent years,whereas Macao has made little progress in financial technologies,especially in payment technologies.Based on the concept and types of third-party payment business in China's Mainland and Macao,as well as to investigate the causes for Macao’s lack of innovation in third-party payment,this study compares their differences from two aspects:business licensing authorities and key points of supervision.By comparison,although the classification and methods of third-party payment businesses are different between China's Mainland and Macao,they are all managed and licensed by a unified supervision department.Moreover,the key points of supervision in both places are similar,but unlike China's Mainland,which takes financial risk prevention as the principle and financial technology as the means to encourage innovation,Macao showed obvious deficiencies.In order to further deepen the connection between the financial markets of China's Mainland and Macao as well as boost financial technologies in Macao,this study aims to provide some suggestions and references for the development of cross-border payment systems.

Semi-supervised learning based probabilistic latent semantic analysis for automatic image annotation

In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficient and effective searching environment for users to query their images more easily. In this paper,a semi-supervised learning based probabilistic latent semantic analysis( PLSA) model for automatic image annotation is presenred. Since it's often hard to obtain or create labeled images in large quantities while unlabeled ones are easier to collect,a transductive support vector machine( TSVM) is exploited to enhance the quality of the training image data. Then,different image features with different magnitudes will result in different performance for automatic image annotation. To this end,a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible. Finally,a PLSA model with asymmetric modalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores. Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PLSA for the task of automatic image annotation.

Analysis on Protection of GI Product Liupao Tea and Suggestions of its Industrial Supervision

From humanistic characteristics,historical origin,fame,quality,and the correlation between quality and production region,we analyze key factors of protection for Geographic Indication product Liupao Tea.We also analyze industrial development of Liupao Tea from processing threshold,scale of processing enterprises,standard and index,planting base,research and development and technology popularization,and pesticide control.In line with these situations,we put forward following suggestions.First,it is proposed to raise standard index and formulate national standard for Liupao Tea.Second,we should popularize the industrial mode of "market + association(enterprise) + base" and establish demonstration area for protection of Geographic Indication product Liupao Tea.Third,it is recommended to raise the production and processing threshold.Fourth,we should establish special production inspection and research and development institution.Fifth,it is suggested to set up independent supervision organization.

A Novel Dinuclear Copper(Ⅱ)Complex:Synthesis,Crystal Structure,Properties and Hirshfeld Surface Analysis

A novel copper complex [Cu2（L）（DMF）2]（1, H4L =（1 Z,N？Z）-3,5-dibromo-N？-（（3,5-dibromo-2-hydroxyphenyl）（hydroxy）methylene）-2-hydroxybenzohydrazonic acid which was synthesized by in-situ oxidation reaction derived from H2hdb（H2hdb = 6,6′-（（1 E,1？E）-hydrazine-1,2-diylidenebis（methanylylidene）） bis（2,4-dibromophenol）） has been synthesized and characterized by IR, elemental analysis（CHN）, TG and single-crystal X-ray diffraction. The single crystal belongs to monoclinic system, space group P21/c with a = 13.538（1）, b = 3.912（1）, c = 23.778（1）A°, β = 105.232（5）o, Mr = 857.08, V = 1214.9（1） A°^3, Z = 2, Dc = 2.343 g/cm^3, F（000） = 824, μ = 8.375 mm^–1, R = 0.0566, and w R = 0.1610. Compound 1 displays weak anti-ferromagnetic interactions through a η^1：η^1：η^1：η^1：η^1：η^1：μ2-L^4- bridging mode. Hirshfeld surface analysis revealed that complex 1 was supported mainly by Br···H and H···H intermolecular interactions.

An Emotion Analysis Method Using Multi-Channel Convolution Neural Network in Social Networks

As an interdisciplinary comprehensive subject involving multidisciplinary knowledge,emotional analysis has become a hot topic in psychology,health medicine and computer science.It has a high comprehensive and practical application value.Emotion research based on the social network is a relatively new topic in the field of psychology and medical health research.The text emotion analysis of college students also has an important research significance for the emotional state of students at a certain time or a certain period,so as to understand their normal state,abnormal state and the reason of state change from the information they wrote.In view of the fact that convolutional neural network cannot make full use of the unique emotional information in sentences,and the need to label a large number of highquality training sets for emotional analysis to improve the accuracy of the model,an emotional analysismodel using the emotional dictionary andmultichannel convolutional neural network is proposed in this paper.Firstly,the input matrix of emotion dictionary is constructed according to the emotion information,and the different feature information of sentences is combined to form different network input channels,so that the model can learn the emotion information of input sentences from various feature representations in the training process.Then,the loss function is reconstructed to realize the semi supervised learning of the network.Finally,experiments are carried on COAE 2014 and self-built data sets.The proposed model can not only extract more semantic information in emotional text,but also learn the hidden emotional information in emotional text.The experimental results show that the proposed emotion analysis model can achieve a better classification performance.Compared with the best benchmark model gram-CNN,the F1 value can be increased by 0.026 in the self-built data set,and it can be increased by 0.032 in the COAE 2014 data set.

Game Analysis of Rational FRS on Market Admittance

The dynamic signaling game-model is employed to study countermeasures of Q, U and C for supply-demand on financial market. As the game result, the mixed equilibrium of Q and U exists naturally without FRS. It is concluded that FRS on market admittance is objective demand of financial market, also the rational management behavior of government FRSI. And in addition to the empirical criteria, the FRS agreements between FRSI and financial-institutions should be considered as one of advanced FRS techniques. These must cover:① the regulation conformed status investigation with sufficient frequency,② corresponding punitive measures with sufficient strength. Thus the information can be delivered FRSI have ensured only qualified and regulation-conformed financial-institutions could be allowed to enter. That could safeguard the steadiness of the financial market.

Twitter Arabic Sentiment Analysis to Detect Depression Using Machine Learning

Depression has been a major global concern for a long time,with the disease affecting aspects of many people’s daily lives,such as their moods,eating habits,and social interactions.In Arabic culture,there is a lack of awareness regarding the importance of facing and curing mental health diseases.However,people all over the world,including Arab citizens,tend to express their feelings openly on social media,especially Twitter,as it is a platform designed to enable the expression of emotions through short texts,pictures,or videos.Users are inclined to treat their Twitter accounts as diaries because the platform affords them anonymity.Many published studies have detected the occurrence of depression among Twitter users on the basis of data on tweets posted in English,but research on Arabic tweets is lacking.The aim of the present work was to develop a model for analyzing Arabic users’tweets and detecting depression among Arabic Twitter users.And expand the diversity of user tweets,by adding a new label(“neutral”)so the dataset include three classes(“depressed”,“non-depressed”,“neutral”).The model was created using machine learning classifiers and natural language processing techniques,such as Support Vector Machine(SVM),Random Forest(RF),Logistic Regression(LR),K-nearest Neighbors(KNN),AdaBoost,and Naïve Bayes(NB).The results showed that the RF classifier outperformed the others,registering an accuracy of 82.39%.

SpectraTr:A novel deep learning model for qualitative analysis of drug spectroscopy based on transformer structure

The drug supervision methods based on near-infrared spectroscopy analysis are heavily dependent on the chemometrics model which characterizes the relationship between spectral data and drug categories.The preliminary application of convolution neural network in spectral analysis demonstrates excellent end-to-end prediction ability,but it is sensitive to the hyper-parameters of the network.The transformer is a deep-learning model based on self-attention mechanism that compares convolutional neural networks(CNNs)in predictive performance and has an easy-todesign model structure.Hence,a novel calibration model named SpectraTr,based on the transformer structure,is proposed and used for the qualitative analysis of drug spectrum.The experimental results of seven classes of drug and 18 classes of drug show that the proposed SpectraTr model can automatically extract features from a huge number of spectra,is not dependent on pre-processing algorithms,and is insensitive to model hyperparameters.When the ratio of the training set to test set is 8:2,the prediction accuracy of the SpectraTr model reaches 100%and 99.52%,respectively,which outperforms PLS DA,SVM,SAE,and CNN.The model is also tested on a public drug data set,and achieved classification accuracy of 96.97%without preprocessing algorithm,which is 34.85%,28.28%,5.05%,and 2.73%higher than PLS DA,SVM,SAE,and CNN,respectively.The research shows that the SpectraTr model performs exceptionally well in spectral analysis and is expected to be a novel deep calibration model after Autoencoder networks(AEs)and CNN.

Enhancement of Sentiment Analysis Using Clause and Discourse Connectives

The sentiment of a text depends on the clausal structure of the sentence and the connectives’discourse arguments.In this work,the clause boundary,discourse argument,and syntactic and semantic information of the sentence are used to assign the text’s sentiment.The clause boundaries identify the span of the text,and the discourse connectives identify the arguments.Since the lexicon-based analysis of traditional sentiment analysis gives the wrong sentiment of the sentence,a deeper-level semantic analysis is required for the correct analysis of sentiments.Hence,in this study,explicit connectives in Malayalam are considered to identify the discourse arguments.A supervised method,conditional random fields,is used to identify the clause boundary and discourse arguments.For the study,1,000 sentiment sentences from Malayalam documents were analyzed.Experimental results show that the discourse structure integration considerably improves sentiment analysis performance from the baseline system.

Applied research of correspondence analysis method in waste tailings reservoir heavy metal pollution monitoring points optimization

In order to optimize monitoring points and monitoring factor, the relationshipbetween pollutants and soil sample were established by correspondence analysis.Thestudy results show that the reflecting monitoring points and monitoring factors in thegraphic on the same factor axis can clearly express the intrinsic link between pollutantsand monitoring points and distribution characteristics.To determine the main monitoringpoint and the main monitoring indicators can reduce and optimize the number of monitoringpoints under the premise of ensuring the typical and representative of monitoring data.Using the correlation of pollutants can reduce the number of monitoring indicators and improvethe effectiveness of data collection.