基于ER Rule的多分类器汽车评论情感分类研究

该文针对汽车评论语料的情感二分类问题,提出一种基于证据推理规则的多分类器融合的情感分类方法。在情感特征构建方面,通过实验对比不同特征模型对分类结果的影响,并改进传统的TFIDF权重计算方法。同时,在此基础上使用ER Rule融合不同分类器进行文本情感极性分析,并考虑各分类器的权重和可靠度。最后,爬取汽车网站上的评论数据对上述方法进行测试,并用公开的中文酒店评论语料数据进行了验证,结果表明该方法能够有效集成不同分类器的优点,与传统机器学习分类算法相比,其结果在Recall,F1值和Accuracy三个指标上得到了提高,与目前流行的深度学习算法和集成学习算法相比,其结果总体占优。

Digital Development Rights in Developing Countries:Where the Governance Rules for Cross-Border Data Flows

The digital development rights in developing countries are based on establishing a new international economic order and ensuring equal participation in the digital globalization process to achieve people's well-rounded development in the digital society.The relationship between cross-border data flows and the realization of digital development rights in developing countries is quite complex.Currently,developing countries seek to safeguard their existing digital interests through unilateral regulation to protect data sovereignty and multilateral regulation for cross-border data cooperation.However,developing countries still have to face internal conflicts between national digital development rights and individual and corporate digital development rights during the process of realizing digital development rights.They also encounter external contradictions such as developed countries interfering with developing countries'data sovereignty,developed countries squeezing the policy space of developing countries through dominant rules,and developing countries having conflicts between domestic and international rules.This article argues that balancing openness and security on digital trade platforms is the optimal solution for developing countries to realize their digital development rights.The establishment of WTO digital trade rules should inherently reflect the fundamental demands of developing countries in cross-border data flows.At the same time,given China's dual role as a digital powerhouse and a developing country,it should actively promote the realization of digital development rights in developing countries.

GAMYB transcription factor LoMYB65 from lily plays a vital role in pollen development

Lily(Lilium spp.)is an important horticultural crop,but its use is limited due to serious pollen contamination problems.There are many studies on pollen development in model plants,but few on flower crops such as lilies.Gibberellin(GA)is a large class of hormones and plays an important role in plant vegetative growth and reproductive development.GAMYB is a group of the R2R3-MYB family upregulated by gibberellin,and plays an important role in anther development.Here,we isolated a novel GAMYB,named LoMYB65,from lily,which was closely related to the AtMYB65 and AtMYB33 in Arabidopsis.Fluorescence quantitative PCR results showed that LoMYB65 was mainly expressed in lily anthers.LoMYB65 could be activated by 288μmol·L^(-1)GA3treatment and the LoMYB65 protein was located in the nucleus and cytoplasm,and had transactivation in yeast and tobacco leaf cells.The conserved motif within 226 amino acids of the C-terminal of LoMYB65 contributed to its transactivation.Overexpression of LoMYB65 caused dwarf phenotype,unnormal tapetum development,less seeds of siliques in transgenic Arabidopsis plants,the transgenic plants showed partly male sterile.Simultaneously,silencing of LoMYB65 with VIGS(Virus Induced Gene Silencing)in lily anthers caused unnormal pollen development and reduced the pollen amount.Overexpression of LoMYB65 in Arabidopsis and silencing of LoMYB65 in lily resulted in decreased pollen counts,so we speculate that LoMYB65 may be dose-dependent.Overall,these findings suggest that LoMYB65 may play an important role in anther development and pollen formation in lily.LoMYB65 may provide a useful candidate gene for pollenless breeding of lily.

BMPRⅡ^(+)neural precursor cells isolated and characterized from organotypic neurospheres:an in vitro model of human fetal spinal cord development

Roof plate secretion of bone morphogenetic proteins(BMPs)directs the cellular fate of sensory neurons during spinal cord development,including the formation of the ascending sensory columns,though their biology is not well understood.Type-ⅡBMP receptor(BMPRⅡ),the cognate receptor,is expressed by neural precursor cells during embryogenesis;however,an in vitro method of enriching BMPRⅡ^(+)human neural precursor cells(hNPCs)from the fetal spinal cord is absent.Immunofluorescence was undertaken on intact second-trimester human fetal spinal cord using antibodies to BMPRⅡand leukemia inhibitory factor(LIF).Regions of highest BMPRⅡ^(+)immunofluorescence localized to sensory columns.Parenchymal and meningeal-associated BMPRⅡ^(+)vascular cells were identified in both intact fetal spinal cord and cortex by co-positivity with vascular lineage markers,CD34/CD39.LIF immunostaining identified a population of somas concentrated in dorsal and ventral horn interneurons,mirroring the expression of LIF receptor/CD118.A combination of LIF supplementation and high-density culture maintained culture growth beyond 10 passages,while synergistically increasing the proportion of neurospheres with a stratified,cytoarchitecture.These neurospheres were characterized by BMPRⅡ^(+)/MAP2ab^(+/–)/βⅢ-tubulin^(+)/nestin^(–)/vimentin^(–)/GFAP^(–)/NeuN^(–)surface hNPCs surrounding a heterogeneous core ofβⅢ-tubulin^(+)/nestin^(+)/vimentin^(+)/GFAP^(+)/MAP2ab^(–)/NeuN^(–)multipotent precursors.Dissociated cultures from tripotential neurospheres contained neuronal(βⅢ-tubulin^(+)),astrocytic(GFAP+),and oligodendrocytic(O4+)lineage cells.Fluorescence-activated cell sorting-sorted BMPRⅡ^(+)hNPCs were MAP2ab^(+/–)/βⅢ-tubulin^(+)/GFAP^(–)/O4^(–)in culture.This is the first isolation of BMPRⅡ^(+)hNPCs identified and characterized in human fetal spinal cords.Our data show that LIF combines synergistically with high-density reaggregate cultures to support the organotypic reorganization of neurospheres,characterized by surface BMPRⅡ^(+)hNPCs.Our study has provided a new methodology for an in vitro model capable of amplifying human fetal spinal cord cell numbers for>10 passages.Investigations of the role BMPRⅡplays in spinal cord development have primarily relied upon mouse and rat models,with interpolations to human development being derived through inference.Because of significant species differences between murine biology and human,including anatomical dissimilarities in central nervous system(CNS)structure,the findings made in murine models cannot be presumed to apply to human spinal cord development.For these reasons,our human in vitro model offers a novel tool to better understand neurodevelopmental pathways,including BMP signaling,as well as spinal cord injury research and testing drug therapies.

THAPE: A Tunable Hybrid Associative Predictive Engine Approach for Enhancing Rule Interpretability in Association Rule Learning for the Retail Sector

Association rule learning(ARL)is a widely used technique for discovering relationships within datasets.However,it often generates excessive irrelevant or ambiguous rules.Therefore,post-processing is crucial not only for removing irrelevant or redundant rules but also for uncovering hidden associations that impact other factors.Recently,several post-processing methods have been proposed,each with its own strengths and weaknesses.In this paper,we propose THAPE(Tunable Hybrid Associative Predictive Engine),which combines descriptive and predictive techniques.By leveraging both techniques,our aim is to enhance the quality of analyzing generated rules.This includes removing irrelevant or redundant rules,uncovering interesting and useful rules,exploring hidden association rules that may affect other factors,and providing backtracking ability for a given product.The proposed approach offers a tailored method that suits specific goals for retailers,enabling them to gain a better understanding of customer behavior based on factual transactions in the target market.We applied THAPE to a real dataset as a case study in this paper to demonstrate its effectiveness.Through this application,we successfully mined a concise set of highly interesting and useful association rules.Out of the 11,265 rules generated,we identified 125 rules that are particularly relevant to the business context.These identified rules significantly improve the interpretability and usefulness of association rules for decision-making purposes.

Semantic Consistency and Correctness Verification of Digital Traffic Rules

The consensus of the automotive industry and traffic management authorities is that autonomous vehicles must follow the same traffic laws as human drivers.Using formal or digital methods,natural language traffic rules can be translated into machine language and used by autonomous vehicles.In this paper,a translation flow is designed.Beyond the translation,a deeper examination is required,because the semantics of natural languages are rich and complex,and frequently contain hidden assumptions.The issue of how to ensure that digital rules are accurate and consistent with the original intent of the traffic rules they represent is both significant and unresolved.In response,we propose a method of formal verification that combines equivalence verification with model checking.Reasonable and reassuring digital traffic rules can be obtained by utilizing the proposed traffic rule digitization flow and verification method.In addition,we offer a number of simulation applications that employ digital traffic rules to assess vehicle violations.The experimental findings indicate that our digital rules utilizing metric temporal logic(MTL)can be easily incorporated into simulation platforms and autonomous driving systems(ADS).

STRONGLY CONVERGENT INERTIAL FORWARD-BACKWARD-FORWARD ALGORITHM WITHOUT ON-LINE RULE FOR VARIATIONAL INEQUALITIES

This paper studies a strongly convergent inertial forward-backward-forward algorithm for the variational inequality problem in Hilbert spaces.In our convergence analysis,we do not assume the on-line rule of the inertial parameters and the iterates,which have been assumed by several authors whenever a strongly convergent algorithm with an inertial extrapolation step is proposed for a variational inequality problem.Consequently,our proof arguments are different from what is obtainable in the relevant literature.Finally,we give numerical tests to confirm the theoretical analysis and show that our proposed algorithm is superior to related ones in the literature.

FE65:a hub for neurodevelopment

FE65,initially identified as a binding partner of amyloid precursor protein(APP),is an adaptor protein enriched in the brain and regulated during development.FE65 belongs to the FE65 protein family.This family is comprised of three members,FE65,FE65 like-1(FE65L1),and FE65 like-2(FE65L2).

Density Clustering Algorithm Based on KD-Tree and Voting Rules

Traditional clustering algorithms often struggle to produce satisfactory results when dealing with datasets withuneven density. Additionally, they incur substantial computational costs when applied to high-dimensional datadue to calculating similarity matrices. To alleviate these issues, we employ the KD-Tree to partition the dataset andcompute the K-nearest neighbors (KNN) density for each point, thereby avoiding the computation of similaritymatrices. Moreover, we apply the rules of voting elections, treating each data point as a voter and casting a votefor the point with the highest density among its KNN. By utilizing the vote counts of each point, we develop thestrategy for classifying noise points and potential cluster centers, allowing the algorithm to identify clusters withuneven density and complex shapes. Additionally, we define the concept of “adhesive points” between two clustersto merge adjacent clusters that have similar densities. This process helps us identify the optimal number of clustersautomatically. Experimental results indicate that our algorithm not only improves the efficiency of clustering butalso increases its accuracy.

Spatial Differentiation and Convergence Trend of High-quality Development Level of China’s Tourism Economy

This paper aims to interpret the connotation of high-quality development of tourism economy(HQTE)from the perspective of the new development concepts of innovation,coordination,green,openness and sharing,and then to evaluate the spatial differenti-ation of China’s HQTE based on provincial panel data from 2009 to 2018.Specifically,we employ the spatial convergence model to ex-plore the absolute and conditionalβconvergence trends of HQTE in the whole country and the eastern,central and western regions of China.Our empirical results reveal that:1)within the decade,from 2009 to 2018,regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region,but the fastest growing one is the western region of China fol-lowed by the central region and then the eastern region.2)Whether or not the spatial effect is included,there are absolute and condition-alβconvergence in HQTE in the whole country and aforementioned three regions.3)The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions.The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions.The above conclusions could deepen the understanding of the regional imbalance and spatial conver-gence characteristics of HQTE,clarify the primary development objects,and accomplish the goal of China’s HQTE.

Improved STNModels and Heuristic Rules for Cooperative Scheduling in Automated Container Terminals

Improving the cooperative scheduling efficiency of equipment is the key for automated container terminals to copewith the development trend of large-scale ships. In order to improve the solution efficiency of the existing spacetimenetwork (STN) model for the cooperative scheduling problem of yard cranes (YCs) and automated guidedvehicles (AGVs) and extend its application scenarios, two improved STN models are proposed. The flow balanceconstraints in the original model are decomposed, and the trajectory constraints of YCs and AGVs are added toacquire the model STN_A. The coupling constraint in STN_A is updated, and buffer constraints are added toSTN_A so that themodel STN_B is built.As the size of the problem increases, the solution speed of CPLEX becomesthe bottleneck. So a heuristic method containing three groups of heuristic rules is designed to obtain a near-optimalsolution quickly. Experimental results showthat the computation time of STN_A is shortened by 49.47% on averageand the gap is reduced by 1.69% on average compared with the original model. The gap between the solution ofthe heuristic rules and the solution of CPLEX is less than 3.50%, and the solution time of the heuristic rules is onaverage 99.85% less than the solution time of CPLEX. Compared with STN_A, the computation time for solvingSTN_B increases by 58.93% on average.

Rule acquisition of three-way semi-concept lattices in formal decision context

Three-way concept analysis is an important tool for information processing,and rule acquisition is one of the research hotspots of three-way concept analysis.However,compared with three-way concept lattices,three-way semi-concept lattices have three-way operators with weaker constraints,which can generate more concepts.In this article,the problem of rule acquisition for three-way semi-concept lattices is discussed in general.The authors construct the finer relation of three-way semi-concept lattices,and propose a method of rule acquisition for three-way semi-concept lattices.The authors also discuss the set of decision rules and the relationships of decision rules among object-induced three-way semi-concept lattices,object-induced three-way concept lattices,classical concept lattices and semi-concept lattices.Finally,examples are provided to illustrate the validity of our conclusions.

Advancements in Medication Rule for Pulmonary Nodules: A Review of Current Research Progress

This paper reviewed the literature on medication rule of pulmonary nodules in recent years. It is found that contemporary doctors pay more attention to regulating Qi, clearing heat and detoxifying, eliminating phlegm, dissolving phlegm and dissipating masses. They use mild drugs, cold and warm treatments in parallel, combining the tastes of pungent, bitterness, and sweetness at the same time. The treatment focuses on the five viscera with emphasis on the lung meridian while also considering the spleen and stomach functions as well as soothing liver stagnation. This information aims to provide some reference for clinical treatment of pulmonary nodules.

Learning Vector Quantization-Based Fuzzy Rules Oversampling Method

Imbalanced datasets are common in practical applications,and oversampling methods using fuzzy rules have been shown to enhance the classification performance of imbalanced data by taking into account the relationship between data attributes.However,the creation of fuzzy rules typically depends on expert knowledge,which may not fully leverage the label information in training data and may be subjective.To address this issue,a novel fuzzy rule oversampling approach is developed based on the learning vector quantization(LVQ)algorithm.In this method,the label information of the training data is utilized to determine the antecedent part of If-Then fuzzy rules by dynamically dividing attribute intervals using LVQ.Subsequently,fuzzy rules are generated and adjusted to calculate rule weights.The number of new samples to be synthesized for each rule is then computed,and samples from the minority class are synthesized based on the newly generated fuzzy rules.This results in the establishment of a fuzzy rule oversampling method based on LVQ.To evaluate the effectiveness of this method,comparative experiments are conducted on 12 publicly available imbalance datasets with five other sampling techniques in combination with the support function machine.The experimental results demonstrate that the proposed method can significantly enhance the classification algorithm across seven performance indicators,including a boost of 2.15%to 12.34%in Accuracy,6.11%to 27.06%in G-mean,and 4.69%to 18.78%in AUC.These show that the proposed method is capable of more efficiently improving the classification performance of imbalanced data.

Multi-modal knowledge graph inference via media convergence and logic rule

Media convergence works by processing information from different modalities and applying them to different domains.It is difficult for the conventional knowledge graph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledge graph inference less effective.To address the issue,an inference method based on Media Convergence and Rule-guided Joint Inference model(MCRJI)has been pro-posed.The authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link prediction.First,a multi-headed self-attention approach is used to obtain the attention of different media features of entities during semantic synthesis.Second,logic rules of different lengths are mined from knowledge graph to learn new entity representations.Finally,knowledge graph inference is performed based on representing entities that converge multi-media features.Numerous experimental results show that MCRJI outperforms other advanced baselines in using multi-media features and knowledge graph inference,demonstrating that MCRJI provides an excellent approach for knowledge graph inference with converged multi-media features.

Development and formation of wing cuticle based on transcriptomic analysis in Locusta migratoria during metamorphosis

Wings are an important flight organ of insects.Wing development is a complex process controlled by a series of genes.The flightless wing pad transforms into a mature wing with the function of migratory flight during the nymphto-adult metamorphosis.However,the mechanism of wing morphogenesis in locusts is still unclear.This study analyzed the microstructures of the locust wing pads at pre-eclosion and the wings after eclosion and performed the comparative transcriptome analysis.RNA-seq identified 25,334 unigenesand 3,430 differentially expressed genes(DEGs)(1,907 up-regulated and 1,523 down-regulated).The DEGs mainly included cuticle development(LmACPs),chitin metabolism(Lm Idgf4),lipid metabolism-related genes,cell adhesion(Integrin),zinc finger transcription factors(LmSalm,LmZF593 andLmZF521),and others.Functional analysis based on RNA interference and hematoxylin and eosin(H&E)staining showed that the three genes encoded zinc finger transcription factors are essential for forming wing cuticle and maintaining morphology in Locusta migratoria.Finally,the study found that the LmSalm regulates the expression of LmACPs in the wing pads at pre-eclosion,and LmZF593 and LmZF521 regulate the expression of LmIntegrin/LmIdgf4/LmHMT420 in the wings after eclosion.This study revealed that the molecular regulatory axis controls wing morphology in nymphal and adult stages of locusts,offering a theoretical basis for the study of wing development mechanisms in hemimetabolous insects.

Role of self-help groups on socioeconomic development and the achievement of Sustainable Development Goals(SDGs)among rural women in Cooch Behar District,India

This study examines the transformative role of self-help groups(SHGs)in the socioeconomic development of rural women in Cooch Behar District,India,and their contribution toward achieving Sustainable Development Goals(SDGs)of the United Nations.In this study,we explored the effect of SHGs on rural women by specifically addressing SDGs,such as no poverty(SDG 1),zero hunger(SDG 2),good health and well-being(SDG 3),quality education(SDG 4),and gender equality(SDG 5).Given this issue,a cross-sectional survey and comparison analyses are needed to assess the socioeconomic development of rural women and their awareness level before and after the participation of rural women in SHGs.The survey conducted as part of this study was divided into three sections,namely,demographic characteristics,socioeconomic development,and awareness level,with each focusing on different aspects.A group of 400 individuals who were part of SHGs completed the questionnaire survey form.The results showed that the participation of rural women in SHGs significantly improved their socioeconomic development and awareness level,as supported by both mean values and t test results.Memberships in SHGs and microcredit programs were the major elements that boosted the socioeconomic development of rural women,which also achieves SDGs 1,2,3,4,and 5.This study revealed that participation in SHGs and related financial services significantly aided rural women in economically disadvantaged communities in accumulating savings and initiating entrepreneurial ventures.Moreover,participation in SHGs was instrumental in enhancing the self-confidence,self-efficacy,and overall self-esteem of rural women.Finally,doing so enabled them to move more freely for work and other activities and to make family and common decisions.

OsPPG encodes a pseudouridine-5'-phosphate glycosidase and regulates rice spikelet development

Florets are the basic structural units of spikelets,and their morphogenesis determines the yield and quality of rice grains.However,whether and how pseudouridine-5’-phosphate glycosidase participates in rice spikelet development remains an open question.In this study,we identified a novel gene,OsPPG,which encodes a peroxisome-localized pseudouridine-5’-phosphate glycosidase and regulates the development of rice spikelets.osppg mutants exhibited abnormal sterile lemma,lemma,palea,lodicule,stamens,and pistils;male sterility;shorter panicles;and reduced plant height.OsPPG was found to regulate several OsMADS genes,thereby affecting the morphogenesis of rice spikelets.Furthermore,metabolomics revealed that the OsPPG gene was involved in the decomposition of pseudouridine via the pyrimidine metabolism pathway and may affect the jasmonic acid signaling pathway.These results suggest that OsPPG is a key regulator of rice spikelet development.

Identification and Expression Profile of a Neuropeptide LFRFamide-Like Gene During Different Stages of Gonadal Development in the Cephalopod Sepia pharaonis

Neuropeptides are widely distributed in vertebrates and invertebrates,regulating a variety of physiological activities in the organisms,such as metabolism,feeding and reproduction.In this study,to explore the function of neuropeptide LFRFamide in Sepia pharaonis,the full-length cDNA of LFRFamide-like gene(named SpLFRFL,MG869822.1)was identified with rapid amplification of cDNA ends(RACE)method.The sequence of SpLFRFL was 860 bp in length and encoded 188 amino acids containing 4 different mature peptides:1 copy of PHTPFRFamide,NSLFRFamide,TIFRFamide,and 3 copies of GNLFRFamide.Multiple alignment and phylogenetic analysis results showed that SpLFRFL shared high identity with LFRFamides of Sepia officinalis and Sepiella japonica and had the closest relationship with them.Through quantitative Real-time PCR(qRT-PCR),it was found that the SpLFRFL gene was highly expressed in the optic lobe and brain at three different stages during gonad development in both genders.Moreover,the four mature peptides at a concentration of 0.01μmol L^(−1) could inhibit the protein synthesis in the Chinese hamster ovary cell strain-K1(CHOK1)induced by SpGnRH.These data suggest that SpLFRFL might be involved in the development and reproduction of S.pharaonis.The results can contribute to future studies on neuropeptide evolution and function and benefit the cuttlefish farming.

Combining genome-wide association study and transcriptome analysis to identify molecular markers and genetic basis of population-asynchronous ovarian development in Coilia nasus

Coilia nasus,a migratory fish species found in the middle and lower reaches of the Yangtze River and along offshore areas of China,possesses considerable aquacultural and economic potential.However,the species faces challenges due to significant variation in the gonadal development rate among females,resulting in inconsistent ovarian maturation times at the population level,an extended reproductive period,and limitations on fish growth rate due to ovarian prematurity.In the present study,we combined genome-wide association study(GWAS)and comparative transcriptome analysis to investigate the potential single nucleotide polymorphisms(SNPs)and candidate genes associated with population-asynchronous ovarian development in C.nasus.Genotyping of the female population based on whole-genome resequencing yielded 2120695 high-quality SNPs,39 of which were suggestively associated with ovarian development.Of note,a significant SNP peak on LG21 containing 30 suggestively associated SNPs was identified,with cpne5a determined as the causal gene of the peak.Therefore,single-marker and haplotype association analyses were performed on cpne5a,revealing four genetic markers(P<0.05)and seven haplotypes(r2>0.9)significantly associated with the phenotype.Comparative transcriptome analysis of precociously and normally maturing individuals screened out 29 and 426 overlapping differentially expressed genes in the brain and ovary,respectively,between individuals of different body sizes.Integrating the GWAS and transcriptome analysis results,this study identified genes and pathways related to hypothalamic-pituitary-gonadal axis hormone secretion,extracellular matrix,angiogenesis,and gap junctions involved in population-asynchronous ovarian development.The insights gained from this study provide a basis for a deeper understanding of the molecular mechanisms underlying ovarian development in fish and may facilitate the genetic breeding of C.nasus strains exhibiting population-synchronous ovarian development in the future.