A New Part-of-Speech Tagging System Based on Closed-words,Word Form and Rules

A method of part-of-speech tagging of English text based on closed-words, wold-form and rules, its abstract model and formal description of its realizing procedure are presented. Finally, an experimental example is givento illustrate the application of this method.

Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System

In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.

A U-Shaped Network-Based Grid Tagging Model for Chinese Named Entity Recognition

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

A Novel Anti-Collision Algorithm for Large Scale of UHF RFID Tags Access Systems

When the radio frequency identification(RFID)system inventories multiple tags,the recognition rate will be seriously affected due to collisions.Based on the existing dynamic frame slotted Aloha(DFSA)algorithm,a sub-frame observation and cyclic redundancy check(CRC)grouping combined dynamic framed slotted Aloha(SUBF-CGDFSA)algorithm is proposed.The algorithm combines the precise estimation method of the quantity of large-scale tags,the large-scale tags grouping mechanism based on CRC pseudo-randomcharacteristics,and the Aloha anti-collision optimization mechanism based on sub-frame observation.By grouping tags and sequentially identifying themwithin subframes,it accurately estimates the number of remaining tags and optimizes frame length accordingly to improve efficiency in large-scale RFID systems.Simulation outcomes demonstrate that this proposed algorithmcan effectively break through the system throughput bottleneck of 36.8%,which is up to 30%higher than the existing DFSA standard scheme,and has more significant advantages,which is suitable for application in largescale RFID tags scenarios.

BPR-UserRec:a personalized user recommendation method in social tagging systems

Social tagging is one of the most important characteristics of Web 2.0 services, and social tagging systems （STS） are becoming more and more popular for users to annotate, organize and share items on the Web. Moreover, online social network has been incorporated into social tagging systems. As more and more users tend to interact with real friends on the Web, personalized user recommendation service provided in social tagging systems is very appealing. In this paper, we propose a personalized user recommendation method, and our method handles not only the users＇ interest networks, but also the social network information. We empirically show that our method outperforms a state-of-the-art method on real dataset from Last.fro dataset and Douban.

Molecular analysis of rice plants harboring a multi-functional T-DNA tagging system

About 25,000 rice T-DNA insertional mutant lines were generated using the vector pCAS04 which has both promoter-trapping and activation-tagging function. Southern blot analysis revealed that about 40% of these mutants were single copy integration and the average T-DNA insertion number was 2.28. By extensive phenotyping in the field, quite a number of agronomically important mutants were obtained. Histochemical GUS assay with 4,310 primary mutants revealed that the GUS-staining frequency was higher than that of the previous reports in various tissues and especially high in flowers. The T-DNA flanking sequences of some mutants were isolated and the T-DNA insertion sites were mapped to the rice genome. The flanking sequence analysis demonstrated the different integration pattern of the right border and left border into rice genome. Compared with Arabidopsis and poplar, it is much varied in the T-DNA border junctions in rice.

Tax-folks hybrid navigation:A new model for resource aggregation in social tagging system

With emergence of Web 2.0,taxonomy and folksonomy have shown a trend of complementarity and integration,and a hybrid tax-folks navigation structure has become a new way to facilitate resource aggregation in social tagging system.In this paper,the generation mechanism of tax-folks hybrid navigation model is analyzed,and the tax-folks hybrid navigation model,which consist of six modules:data preparation,concept lattice construction,concept lattice analysis,tax-folks mapping,tax-folks hybrid navigation tree and outputs& evaluation,is constructed with the theory of formal concept analysis.The study finds that tax-folks hybrid navigation model takes into account the advantages of taxonomy and folksonomy,achieves a tree-like resource aggregation,and effectively improves the resources-finding ability in social tagging system.

A Novel RFID Localization Approach to Smart Self-Service Borrowing and Returning System

The misreading problem of a passive ultra-high-frequency(UHF)radio frequency identification(RFID)tag is a frequent problem arising in the field of librarianship.Unfortunately,existing solutions are something inefficient,e.g.,extra resource requirement,inaccuracy,and empiricism.To this end,under comprehensive analysis on the passive UHF RFID application in the librarianship scenario,a novel and judicious approach based on RFID localization is proposed to address such a misreading problem.Extensive simulation results show that the proposed approach can outperform the existing ones and can be an attractive candidate in practice.

Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.

用于激光照明的荧光粉@SiO_(2)气凝胶复合发光材料的制备与发光性能研究

通过溶胶-凝胶法成功制备了Tb_(3)Al_(5)O_(12)(TAG)荧光粉。热分析数据证实,增加H_(3)BO_(3)摩尔比会导致最终相的转变温度降低。同时,通过扫描电镜观察到,H_(3)BO_(3)摩尔比的提高会导致荧光粉颗粒尺寸增大。在激发波长为275 nm的条件下,发射光谱在480~650 nm范围内出现了由Tb^(3+)的5d→4f跃迁产生的多个发射峰。然后通过物理掺杂和超临界干燥工艺成功制备了荧光粉@SiO_(2)气凝胶复合发光材料。与荧光粉相比,荧光粉@SiO_(2)气凝胶复合发光材料的内量子产率显著增加,可达63.64%。采用波长为355 nm的激光源激发荧光粉@SiO_(2)气凝胶复合发光材料,可实现长距离无导线方式发光,并具有良好均匀性。以上结果证明了荧光粉@SiO_(2)气凝胶复合发光材料在激光应急照明领域具有潜在的应用前景。

月桂酸甘油二酯和豆蔻酸甘油二酯的固定化脂肪酶R IM-03催化合成及纯化

为促进固定化脂肪酶R IM-03在合成甘油二酯(DAG)中的应用,采用固定化脂肪酶RIM-03催化月桂酸/豆蔻酸和甘油酯化合成甘油二酯,并采用分子蒸馏对其进行纯化。对酯化反应和分子蒸馏的工艺条件进行了优化,并考察了纯化产物的理化性质。结果表明:固定化脂肪酶R IM-03催化甘油和月桂酸/豆蔻酸合成甘油二酯的最优条件为底物(脂肪酸与甘油)物质的量比2∶1、反应温度60℃、反应时间6h、酶添加量6%(以底物质量计),在此条件下月桂酸甘油二酯和豆蔻酸甘油二酯粗产物中甘油二酯含量分别为43.87%和30.00%,甘油三酯(TAG)含量分别为8.71%和6.87%,催化剂可重复利用至少10次;月桂酸甘油二酯粗产物纯化的最优条件为一级分子蒸馏温度170℃、二级分子蒸馏温度180℃,豆蔻酸甘油二酯粗产物纯化的最优条件为一级分子蒸馏温度170℃、二级分子蒸馏温度190℃,在最优条件下纯化月桂酸甘油二酯和豆蔻酸甘油二酯中甘油二酯含量分别达81.29%和80.08%,1,3-甘油二酯含量分别为53.16%和54.27%,DAG/(DAG+TAG)约为80%;纯化月桂酸甘油二酯和豆蔻酸甘油二酯的滑动熔点分别为48.9℃和57.0℃,在30~40℃区间的固体脂肪含量呈陡然下降趋势,在两者复配的体系中,当豆蔻酸甘油二酯占60%以上时,相容性理想。综上,固定化脂肪酶RIM-03具有在甘油二酯合成中应用的潜力,DAG/(DAG+TAG)可作为关键控制指标,异酸甘油二酯复配可改变产物的熔化性质。

Molecular Tagging of a New Resistance Gene to Maize Dwarf Mosaic Virus Using Microsatellite Markers

With joint analysis based on the parents, F 1, F 2 and backcrosses, the authors found that the resistance of the maize inbred line Huangzaosi to the maize dwarf mosaic virus strain B was conditioned by a major gene and polygene, and identified a new major gene. Bulked segregate and microsatellite analysis of a F 2 progeny from the combination of Huangzaosi×Mo17 were used to identify the resistance gene, mdm1(t), on the long arm of chromosome 6. This new resistance gene is tightly linked to and located between the microsatellite markers loci, phi077 and bnlg391. The linkage distances between phi077-mdm1(t) and mdm1(t)-bnlg391 are 4.74 centiMorgan (cM) and 6.72 cM respectively.

Connotea中Social Tagging机制研究

选取Connotea为研究对象,统计分析标签、被标引资源、标引者两两关联关系,发现标签覆盖资源范围较广,标签共现现象突出,部分用户标引活跃,资源平均标签数较低,用户对内容关注度规律性转移,科研领域的用户比较多地使用规范词。提出增加标引词结构关联和细粒内容定位标引。

Serum proteins differentially expressed in gestational diabetes mellitus assessed using isobaric tag for relative and absolute quantitation proteomics

BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients and their altered expression in the serum,proteomics techniques were deployed to detect the differentially expressed proteins(DEPs)of in the serum of GDM patients to further explore its pathogenesis,and find out possible biomarkers to forecast GDM occurrence.METHODS Subjects were divided into GDM and normal control groups according to the IADPSG diagnostic criteria.Serum samples were randomly selected from four cases in each group at 24-28 wk of gestation,and the blood samples were identified by applying iTRAQ technology combined with liquid chromatography-tandem mass spectrometry.Key proteins and signaling pathways associated with GDM were identified by bioinformatics analysis,and the expression of key proteins in serum from 12 wk to 16 wk of gestation was further verified using enzyme-linked immunosorbent assay (ELISA).RESULTS Forty-seven proteins were significantly differentially expressed by analyzing the serum samples between the GDMgravidas as well as the healthy ones. Among them, 31 proteins were found to be upregulated notably and the rest16 proteins were downregulated remarkably. Bioinformatic data report revealed abnormal expression of proteinsassociated with lipid metabolism, coagulation cascade activation, complement system and inflammatory responsein the GDM group. ELISA results showed that the contents of RBP4, as well as ANGPTL8, increased in the serumof GDM gravidas compared with the healthy ones, and this change was found to initiate from 12 wk to 16 wk ofgestation.CONCLUSION GDM symptoms may involve abnormalities in lipid metabolism, coagulation cascade activation, complementsystem and inflammatory response. RBP4 and ANGPTL8 are expected to be early predictors of GDM.

国外Social Tagging研究群体分析

基于抽取的国外知名数据库的学术文献,分析探讨Social Tagging研究群体的学科特征和研究视角。结果表明当前Social Tagging的研究群体主要局限于信息科学与计算机科学,且未形成居于统治权威地位的研究团体和研究人员。自从Social Tagging产生以来,"Social Tagging的组成功能"的研究一直是Social Tagging的基础性研究维度,不过随着应用深入发展,研究维度逐步转而融合信息检索和人机交互这两个相关领域知识分析"Tagger的行为及Social Tagging的界面设计"和"Social Tagging自身的组织和使用"这两个主要研究维度。

Influence of ear tags on the results of body composition analysis in mice

Background:The aim of this study was to investigate the influence of marking meth-ods on the outcomes of body composition analysis and provide guidance for the se-lection of marking methods in mouse body composition analysis.Methods:Male C57BL/6J mice aged 6 weeks were randomly assigned for pre-and post-ear tagging measurements.The body composition of the mice was measured using a small animal body composition analyzer,which provided measurements of the mass of fat,lean,and free fluid.Then,the mass of fat,lean and free fluid to body weight ratio was gained.Further data analysis was conducted to obtain the range and coeffi-cient of variation in body composition measurements for each mouse.The distribution of fat and lean tissue in the mice was also analyzed by comparing the fat-to-lean ratio.Results:(1)The mass of all body composition components in the ear tagging group was significantly lower than that in the control group.(2)There was a significant in-crease in the range and coefficient of variation of body composition measurements between the ear tagging group and the control group.(3)The fat-to-lean ratio in the ear tagging group was significantly lower than that in the control group.Conclusions:Ear tagging significantly lowered the results of body composition analy-sis in mice and higher the results of measurement error.Therefore,ear tagging should be avoided as much as possible when conducting body composition analysis experi-ments in mice.

Comparison of biliary protein spectrum in gallstone patients with obesity and those with normal body weight

Background: Obesity is a common public health issue and is currently deemed a disease. Research has shown that the risk of gallstones in individuals with obesity is elevated. This study aimed to explore the bile proteomics differences between cholelithiasis patients with obesity and normal body weight. Methods: Bile samples from 20 patients(10 with obesity and 10 with normal body weight) who underwent laparoscopic cholecystectomy at our center were subjected to tandem mass tag labeling(TMT) and liquid chromatography-tandem mass spectrometry(LC-MS/MS), followed by further bioinformatic analysis. Results: Among the differentially expressed proteins, 23 were upregulated and 67 were downregulated. Bioinformatic analysis indicated that these differentially expressed proteins were mainly involved in cell development, inflammatory responses, glycerolipid metabolic processes, and protein activation cascades. In addition, the activity of the peroxisome proliferator-activated receptor(PPAR, a subfamily of nuclear receptors) signaling pathway was decreased in the Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis. Two downregulated proteins in the PPAR signaling pathway, APO A-Ⅰ and APO A-Ⅱ, were confirmed using enzyme-linked immunosorbent assay. Conclusions: The PPAR signaling pathway may play a crucial role in the development of cholelithiasis among patients with obesity. Furthermore, biliary proteomics profiling of gallstones patients with obesity is revealed, providing a reference for future research.

Metabolic engineering and genome editing strategies for enhanced lipid production in microalgae

Depleting global petroleum reserves and skyrocketing prices coupled with succinct supply have been a grave concern,which needs alternative sources to conventional fuels.Oleaginous microalgae have been explored for enhanced lipid production,leading towards biodiesel production.These microalgae have short life cycles,require less labor,and space,and are easy to scale up.Triacylglycerol,the primary source of lipids needed to produce biodiesel,is accumulated by most microalgae.The article focuses on different types of oleaginous microalgae,which can be used as a feedstock to produce biodiesel.Lipid biosynthesis in microalgae occurs through fatty acid synthesis and TAG synthesis approaches.In-depth discussions are held regarding other efficient methods for enhancing fatty acid and TAG synthesis,regulating TAG biosynthesis bypass methods,blocking competing pathways,multigene approach,and genome editing.The most potential targets for gene transformation are hypothesized to be a malic enzyme and diacylglycerol acyltransferase while lowering phosphoenolpyruvate carboxylase activity is reported to be advantageous for lipid synthesis.

Analysis of quality-related proteins in golden pompano(Trachinotus ovatus)fillets with modified atmosphere packaging under superchilling storage

Here,we aimed to study the changes in proteome of golden pompano fillets during post-mortem storage.Tandem mass tags(TMT)-labeled quantitative proteomic strategy was applied to investigate the relationships between protein changes and quality characteristics of modified atmosphere packaging(MAP)fillets during superchilling(-3°C)storage.Scanning electron microscopy was used to show that the muscle histology microstructure of fillets was damaged to varying degrees,and low-field nuclear magnetic resonance was used to find that the immobilized water and free water in the muscle of fillets changed significantly.Total sulfhydryl content,TCA-soluble peptides and Ca2+-ATPase activity also showed that the fillet protein had a deterioration by oxidation and denaturation.The Fresh(FS),MAP,and air packaging(AP)groups were set.Total of 150 proteins were identified as differential abundant proteins(DAPs)in MAP/FS,while 209 DAPs were in AP/FS group.The KEGG pathway analysis indicated that most DAPs were involved in binding proteins and protein turnover.Correlation analysis found that 52 DAPs were correlated with quality traits.Among them,8 highly correlated DAPs are expected to be used as potential quality markers for protein oxidation and water-holding capacity.These results provide a further understanding of the muscle deterioration mechanism of packaging golden pompano fillets during superchilling.

Puerarin modulation of CENPA affects downstream PLK1 and CCNB1 expression to inhibit bladder cancer cell proliferation

Background:The treatment alternatives for bladder cancer(BLCA),the 10th most prevalent cancer in the world,need to be further investigated,and many active substances like Puerarin in herbal medicine were found to be effective in treating BLCA.The purpose of this study was to investigate the potential treating mechanisms of Puerarin on BLCA.Methods:The cell counting kit 8 assay and flow cytometry were performed to confirm Puerarin’s ability to suppress BLCA.The differentially expressed proteins(DEPs)were obtained by Tandem Mass Tags technology and functional enrichment analysis performed by R studio.The most enriched pathways were selected for study and the DEPs were screened out.Protein-protein interaction network maps were created using String and Cytoscape and key proteins,which will be analyzed for survival,expression,and upstream transcription factor prediction,were screened out using the cytoHubba plugin.CHEA3 was used to obtain upstream transcription factor validated by molecular docking and western blotting experiments.Results:Cell counting kit 8 showed that Puerarin inhibited BLCA cells,with 50%inhibitory concentration of 218μmol/L in T24 and 198μmol/L in 5637.Flow cytometry reveals that Puerarin blocks T24 and 5637 cells in G1 phase.1,385 DEPs were obtained and the enrichment analysis revealed that cell cycle and DNA replication were the two main areas in which DEPs were enriched.Cyclin-B-cyclin dependent kinase 1(CDK1),cyclin B1(CCNB1),and polo-like kinase 1(PLK1)were identified as key proteins,and their upstream transcription factor was predicted to be centromere protein A(CENPA).Puerarin’s binding energy to CENPA was determined by molecular docking to be−6.3 kcal/mol,indicating a strong binding interaction.Western blot showed that Puerarin significantly reduced the expression of CENPA.Conclusion:We hypothesize that Puerarin may inhibit the proliferation of bladder cancer cells by inhibiting CENPA expression to regulate PLK1 and CCNB1 expression,thereby affecting cell cycle.