Multi-dimensional database design and implementation of dam safety monitoring system

To improve the effectiveness of dam safety monitoring database systems, the development process of a multi-dimensional conceptual data model was analyzed and a logic design wasachieved in multi-dimensional database mode. The optimal data model was confirmed by identifying data objects, defining relations and reviewing entities. The conversion of relations among entities to external keys and entities and physical attributes to tables and fields was interpreted completely. On this basis, a multi-dimensional database that reflects the management and analysis of a dam safety monitoring system on monitoring data information has been established, for which factual tables and dimensional tables have been designed. Finally, based on service design and user interface design, the dam safety monitoring system has been developed with Delphi as the development tool. This development project shows that the multi-dimensional database can simplify the development process and minimize hidden dangers in the database structure design. It is superior to other dam safety monitoring system development models and can provide a new research direction for system developers.

Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

Comprehensive analysis of advanced glycation end-products in commonly consumed foods:presenting a database for dietary AGEs and associated exposure assessment

Advanced glycation end-products(AGEs)are a group of heterogeneous compounds formed in heatprocessed foods and are proven to be detrimental to human health.Currently,there is no comprehensive database for AGEs in foods that covers the entire range of food categories,which limits the accurate risk assessment of dietary AGEs in human diseases.In this study,we first established an isotope dilution UHPLCQq Q-MS/MS-based method for simultaneous quantification of 10 major AGEs in foods.The contents of these AGEs were detected in 334 foods covering all main groups consumed in Western and Chinese populations.Nε-Carboxymethyllysine,methylglyoxal-derived hydroimidazolone isomers,and glyoxal-derived hydroimidazolone-1 are predominant AGEs found in most foodstuffs.Total amounts of AGEs were high in processed nuts,bakery products,and certain types of cereals and meats(>150 mg/kg),while low in dairy products,vegetables,fruits,and beverages(<40 mg/kg).Assessment of estimated daily intake implied that the contribution of food groups to daily AGE intake varied a lot under different eating patterns,and selection of high-AGE foods leads to up to a 2.7-fold higher intake of AGEs through daily meals.The presented AGE database allows accurate assessment of dietary exposure to these glycotoxins to explore their physiological impacts on human health.

A dynamic database of solid-state electrolyte(DDSE)picturing all-solid-state batteries

All-solid-state batteries(ASSBs)are a class of safer and higher-energy-density materials compared to conventional devices,from which solid-state electrolytes(SSEs)are their essential components.To date,investigations to search for high ion-conducting solid-state electrolytes have attracted broad concern.However,obtaining SSEs with high ionic conductivity is challenging due to the complex structural information and the less-explored structure-performance relationship.To provide a solution to these challenges,developing a database containing typical SSEs from available experimental reports would be a new avenue to understand the structureperformance relationships and find out new design guidelines for reasonable SSEs.Herein,a dynamic experimental database containing>600 materials was developed in a wide range of temperatures(132.40–1261.60 K),including mono-and divalent cations(e.g.,Li^(+),Na^(+),K^(+),Ag^(+),Ca^(2+),Mg^(2+),and Zn^(2+))and various types of anions(e.g.,halide,hydride,sulfide,and oxide).Data-mining was conducted to explore the relationships among different variates(e.g.,transport ion,composition,activation energy,and conductivity).Overall,we expect that this database can provide essential guidelines for the design and development of high-performance SSEs in ASSB applications.This database is dynamically updated,which can be accessed via our open-source online system.

Databases of 2D material-substrate interfaces and 2D charged building blocks

Discovery of materials using“bottom-up”or“top-down”approach is of great interest in materials science.Layered materials consisting of two-dimensional(2D)building blocks provide a good platform to explore new materials in this respect.In van der Waals(vdW)layered materials,these building blocks are charge neutral and can be isolated from their bulk phase(top-down),but usually grow on substrate.In ionic layered materials,they are charged and usually cannot exist independently but can serve as motifs to construct new materials(bottom-up).In this paper,we introduce our recently constructed databases for 2D material-substrate interface(2DMSI),and 2D charged building blocks.For 2DMSI database,we systematically build a workflow to predict appropriate substrates and their geometries at substrates,and construct the 2DMSI database.For the 2D charged building block database,1208 entries from bulk material database are identified.Information of crystal structure,valence state,source,dimension and so on is provided for each entry with a json format.We also show its application in designing and searching for new functional layered materials.The 2DMSI database,building block database,and designed layered materials are available in Science Data Bank at https://doi.org/10.57760/sciencedb.j00113.00188.

Impact of index admission cholecystectomy vs interval cholecystectomy on readmission rate in acute cholangitis: National Readmission Database survey

BACKGROUND Elective cholecystectomy(CCY)is recommended for patients with gallstone-related acute cholangitis(AC)following endoscopic decompression to prevent recurrent biliary events.However,the optimal timing and implications of CCY remain unclear.AIM To examine the impact of same-admission CCY compared to interval CCY on patients with gallstone-related AC using the National Readmission Database(NRD).METHODS We queried the NRD to identify all gallstone-related AC hospitalizations in adult patients with and without the same admission CCY between 2016 and 2020.Our primary outcome was all-cause 30-d readmission rates,and secondary outcomes included in-hospital mortality,length of stay(LOS),and hospitalization cost.RESULTS Among the 124964 gallstone-related AC hospitalizations,only 14.67%underwent the same admission CCY.The all-cause 30-d readmissions in the same admission CCY group were almost half that of the non-CCY group(5.56%vs 11.50%).Patients in the same admission CCY group had a longer mean LOS and higher hospitalization costs attrib-utable to surgery.Although the most common reason for readmission was sepsis in both groups,the second most common reason was AC in the interval CCY group.CONCLUSION Our study suggests that patients with gallstone-related AC who do not undergo the same admission CCY have twice the risk of readmission compared to those who undergo CCY during the same admission.These readmis-sions can potentially be prevented by performing same-admission CCY in appropriate patients,which may reduce subsequent hospitalization costs secondary to readmissions.

MC-Tree: Dynamic Index Structure for Partially Clustered Multi-Dimensional Database

Index structure that enables efficient similarity queries in high-dimensional space is crucial for many applications. This paper discusses the indexing problem in dataset composed of partially clustered data, which exists in many applications. Current index methods are inefficient with partially clustered datasets. The dynamic and adaptive index structure presented here, called a multi-cluster tree (MC-tree), consists of a set of height-balanced trees for indexing. This index structure improves the querying efficiency in three ways: 1) Most bounding regions achieve uniform distributions, which results in fewer splits and less overlap compared with a single indexing tree. 2) The clusters in the dataset are dynamically detected when the index is updated. 3) The query process does not involve a sequential scan. The MC-tree was shown to be better than hierarchical and cluster-based indexes for the partially clustered datasets.

A MySQL-Based Software System of Urban Land Planning Database of Shanghai in China

With the development of the digital city,data and data analysis have become more and more important.The database is the foundation of data analysis.In this paper,the software system of the urban land planning database of Shanghai in China is developed based on MySQL.The conceptual model of the urban land planning database is proposed,and the entities,attributes and connections of this model are discussed.Then the E-R conceptual model is transformed into a logical structure,which is supported by the relational databasemanagement system(DBMS).Based on the conceptual and logical structures,by using Spring Boot as the back-end framework and using MySQL and Java API as the development tools,a platformwith datamanagement,information sharing,map assistance and other functions is established.The functionalmodules in this platformare designed.The results of J Meter test show that the DBMS can add,store and retrieve information data stably,and it has the advantages of fast response and low error rate.The software system of the urban land planning database developed in this paper can improve the efficiency of storing and managing land data,eliminating redundant data and sharing data.

Prognostic Factors of Liver Transplantation for Hepatocellular Carcinoma: A Surveillance, Epidemiology, and End Results (SEER) Database Analysis

Objective We aimed to identify new,more accurate risk factors of liver transplantation for liver cancer through using the Surveillance,Epidemiology,and End Results(SEER)database.Methods Using the SEER database,we identified patients that had undergone surgical resection for non-metastatic hepatocellular carcinoma(HCC)and subsequent liver transplantation between 2010 and 2017.Overall survival(OS)was estimated using Kaplan-Meier plotter.Cox proportional hazards regression modelling was used to identify factors independently associated with recurrent disease[presented as adjusted hazard ratios(HR)with 95%CIs].Results Totally,1530 eligible patients were included in the analysis.There were significant differences in ethnicity(P=0.04),cancer stage(P<0.001),vascular invasion(P<0.001)and gall bladder involvement(P<0.001)between the groups that survived,died due to cancer,or died due to other causes.In the Cox regression model,there were no significant differences in OS at 5 years with different operative strategies(autotransplantation versus allotransplantation),nor at survival at 1 year with neoadjuvant radiotherapy.However,neoadjuvant radiotherapy did appear to improve survival at both 3 years(HR:0.540,95%CI:0.326–0.896,P=0.017)and 5 years(HR:0.338,95%CI:0.153–0.747,P=0.007)from diagnosis.Conclusion This study demonstrated differences in patient characteristics between prognostic groups after liver resection and transplantation for HCC.These criteria can be used to inform patient selection and consent in this setting.Preoperative radiotherapy may improve long-term survival post-transplantation.

Fusion of Hash-Based Hard and Soft Biometrics for Enhancing Face Image Database Search and Retrieval

The utilization of digital picture search and retrieval has grown substantially in numerous fields for different purposes during the last decade,owing to the continuing advances in image processing and computer vision approaches.In multiple real-life applications,for example,social media,content-based face picture retrieval is a well-invested technique for large-scale databases,where there is a significant necessity for reliable retrieval capabilities enabling quick search in a vast number of pictures.Humans widely employ faces for recognizing and identifying people.Thus,face recognition through formal or personal pictures is increasingly used in various real-life applications,such as helping crime investigators retrieve matching images from face image databases to identify victims and criminals.However,such face image retrieval becomes more challenging in large-scale databases,where traditional vision-based face analysis requires ample additional storage space than the raw face images already occupied to store extracted lengthy feature vectors and takes much longer to process and match thousands of face images.This work mainly contributes to enhancing face image retrieval performance in large-scale databases using hash codes inferred by locality-sensitive hashing(LSH)for facial hard and soft biometrics as(Hard BioHash)and(Soft BioHash),respectively,to be used as a search input for retrieving the top-k matching faces.Moreover,we propose the multi-biometric score-level fusion of both face hard and soft BioHashes(Hard-Soft BioHash Fusion)for further augmented face image retrieval.The experimental outcomes applied on the Labeled Faces in the Wild(LFW)dataset and the related attributes dataset(LFW-attributes),demonstrate that the retrieval performance of the suggested fusion approach(Hard-Soft BioHash Fusion)significantly improved the retrieval performance compared to solely using Hard BioHash or Soft BioHash in isolation,where the suggested method provides an augmented accuracy of 87%when executed on 1000 specimens and 77%on 5743 samples.These results remarkably outperform the results of the Hard BioHash method by(50%on the 1000 samples and 30%on the 5743 samples),and the Soft BioHash method by(78%on the 1000 samples and 63%on the 5743 samples).

Phylobone: a comprehensive database of bone extracellular matrix proteins in human and model organisms

The bone extracellular matrix(ECM) contains minerals deposited on highly crosslinked collagen fibrils and hundreds of noncollagenous proteins. Some of these proteins are key to the regulation of bone formation and regeneration via signaling pathways,and play important regulatory and structural roles. However, the complete list of bone extracellular matrix proteins, their roles, and the extent of individual and cross-species variations have not been fully captured in both humans and model organisms. Here, we introduce the most comprehensive resource of bone extracellular matrix(ECM) proteins that can be used in research fields such as bone regeneration, osteoporosis, and mechanobiology. The Phylobone database(available at https://phylobone.com) includes 255proteins potentially expressed in the bone extracellular matrix(ECM) of humans and 30 species of vertebrates. A bioinformatics pipeline was used to identify the evolutionary relationships of bone ECM proteins. The analysis facilitated the identification of potential model organisms to study the molecular mechanisms of bone regeneration. A network analysis showed high connectivity of bone ECM proteins. A total of 214 functional protein domains were identified, including collagen and the domains involved in bone formation and resorption. Information from public drug repositories was used to identify potential repurposing of existing drugs. The Phylobone database provides a platform to study bone regeneration and osteoporosis in light of(biological) evolution,and will substantially contribute to the identification of molecular mechanisms and drug targets.

Rosaceae fruit transcriptome database(ROFT)-a useful genomic resource for comparing fruits of apple,peach,strawberry,and raspberry

Rosaceae is a large plant family consisting of many economically important fruit crops including peach,apple,pear,strawberry,raspberry,plum,and others.Investigations into their growth and development will promote both basic understanding and progress toward increasing fruit yield and quality.With the ever-increasing high-throughput sequencing data of Rosaceae,comparative studies are hindered by inconsistency of sample collection with regard to tissue,stage,growth conditions,and by vastly different handling of the data.Therefore,databases that enable easy access and effective utilization of directly comparable transcript data are highly desirable.Here,we describe a database for comparative analysis,ROsaceae Fruit Transcriptome database(ROFT),based on RNA-seq data generated from the same laboratory using similarly dissected and staged fruit tissues of four important Rosaceae fruit crops:apple,peach,strawberry,and red raspberry.Hence,the database is unique in allowing easy and robust comparisons among fruit gene expression across the four species.ROFT enables researchers to query orthologous genes and their expression patterns during different fruit developmental stages in the four species,identify tissue-specific and tissue-/stage-specific genes,visualize and compare ortholog expression in different fruit types,explore consensus co-expression networks,and download different data types.The database provides users access to vast amounts of RNA-seq data across the four economically important fruits,enables investigations of fruit type specification and evolution,and facilitates the selection of genes with critical roles in fruit development for further studies.

SCSMRD: A database for single-cell skeletal muscle regeneration

Skeletal muscle regeneration is a complex process where various cell types and cytokines are involved.Single-cell RNA-sequencing (scRNA-seq) provides the opportunity to deconvolute heterogeneous tissue into individual cells based on their transcriptomic profiles.Recent scRNA-seq studies on mouse muscle regeneration have provided insights to understand the transcriptional dynamics that underpin muscle regeneration.However,a database to investigate gene expression profiling during skeletal muscle regeneration at the single-cell level is lacking.Here,we collected over 105 000 cells at 7 key regenerative time-points and non-injured muscles and developed a database,the Singlecell Skeletal Muscle Regeneration Database (SCSMRD).SCSMRD allows users to search the dynamic expression profiles of genes of interest across different cell types during the skeletal muscle regeneration process.It also provides a network to show the activity of regulons in different cell types at different time points.Pesudotime analysis showed the state changes trajectory of muscle stem cells (MuSCs) during skeletal muscle regeneration.This database is freely available at https://scsmrd.fengs-lab.com.

Comment on: Bibliometric analysis of glaucoma-related literature based on SCIE database: a 10-year literature analysis from 2009 to 2018

Dear Editor,Sun et al[1]recently published a bibliometric paper in the International Journal of Ophthalmology entitled“Bibliometric analysis of glaucoma-related literature based on SCIE database:a 10-year literature analysis from 2009 to 2018”.The authors mentioned in section MATERIALS AND METHODS that“SCIE database established by Institute for Scientific Information(ISI)was used for the purpose of this study.”and“The search strategy was as follows:theme=(glaucoma OR ocular hypertension),and the‘theme’field contains:title,abstract,author keywords,and keywords plus.Document type=(article),and other types of articles,such as case reports,reviews,letters to the editors,and so on,were excluded.The time period of publications was focused on the latest 10y from 2009 to 2018.And the search date was 2019-3-29.”

ARGs-OAP v3.0:Antibiotic-Resistance Gene Database Curation and Analysis Pipeline Optimization

Antibiotic resistance,which is encoded by antibiotic-resistance genes(ARGs),has proliferated to become a growing threat to public health around the world.With technical advances,especially in the popularization of metagenomic sequencing,scientists have gained the ability to decipher the profiles of ARGs in diverse samples with high accuracy at an accelerated speed.To analyze thousands of ARGs in a highthroughput way,standardized and integrated pipelines are needed.The new version(v3.0)of the widely used ARGs online analysis pipeline(ARGs-OAP)has made significant improvements to both the reference database-the structured ARG(SARG)database-and the integrated analysis pipeline.SARG has been enhanced with sequence curation to improve annotation reliability,incorporate emerging resistance genotypes,and determine rigorous mechanism classification.The database has been further organized and visualized online in the format of a tree-like structure with a dictionary.It has also been divided into sub-databases for different application scenarios.In addition,the ARGs-OAP has been improved with adjusted quantification methods,simplified tool implementation,and multiple functions with userdefined reference databases.Moreover,the online platform now provides a diverse biostatistical analysis workflow with visualization packages for the efficient interpretation of ARG profiles.The ARGs-OAP v3.0 with an improved database and analysis pipeline will benefit academia,governmental management,and consultation regarding risk assessment of the environmental prevalence of ARGs.

dbSCI:A manually curated database of SARS-CoV-2 inhibitors for COVID-19

Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)is the pathogen of the ongoing coronavirus disease 2019(COVID-19)global pandemic.Here,by centralizing published cell-based experiments,clinical trials,and virtual drug screening data from the NCBI PubMed database,we developed a database of SARS-CoV-2 inhibitors for COVID-19,dbSCI,which includes 234 SARS-CoV-2 inhibitors collected from publications based on cell-based experiments,81 drugs of COVID-19 in clinical trials and 1305 potential SARS-CoV-2 inhibitors from bioinformatics analyses.dbSCI provides four major functions:(1)search the drug target or its inhibitor for SARS-CoV-2,(2)browse target/inhibitor information collected from cell experiments,clinical trials,and virtual drug screenings,(3)download,and(4)submit data.Each entry in dbSCI contains 18 types of information,including inhibitor/drug name,targeting protein,mechanism of inhibition,experimental technique,experimental sample type,and reference information.In summary,dbSCI provides a relatively comprehensive,credible repository for inhibitors/drugs against SARS-CoV-2 and their potential targeting mechanisms and it will be valuable for further studies to control COVID-19.

Query Optimization Framework for Graph Database in Cloud Dew Environment

The query optimizer uses cost-based optimization to create an execution plan with the least cost,which also consumes the least amount of resources.The challenge of query optimization for relational database systems is a combinatorial optimization problem,which renders exhaustive search impossible as query sizes rise.Increases in CPU performance have surpassed main memory,and disk access speeds in recent decades,allowing data compression to be used—strategies for improving database performance systems.For performance enhancement,compression and query optimization are the two most factors.Compression reduces the volume of data,whereas query optimization minimizes execution time.Compressing the database reduces memory requirement,data takes less time to load into memory,fewer buffer missing occur,and the size of intermediate results is more diminutive.This paper performed query optimization on the graph database in a cloud dew environment by considering,which requires less time to execute a query.The factors compression and query optimization improve the performance of the databases.This research compares the performance of MySQL and Neo4j databases in terms of memory usage and execution time running on cloud dew servers.

Envelope Method and More General New Global Structures of Solutions for Multi-dimensional Conservation Law

For the two-dimensional(2D)scalar conservation law,when the initial data contain two different constant states and the initial discontinuous curve is a general curve,then complex structures of wave interactions will be generated.In this paper,by proposing and investigating the plus envelope,the minus envelope,and the mixed envelope of 2D non-selfsimilar rarefaction wave surfaces,we obtain and the prove the new structures and classifications of interactions between the 2D non-selfsimilar shock wave and the rarefaction wave.For the cases of the plus envelope and the minus envelope,we get and prove the necessary and sufficient criterion to judge these two envelopes and correspondingly get more general new structures of 2D solutions.

Towards sparse matrix operations:graph database approach for power grid computation

The construction of new power systems presents higher requirements for the Power Internet of Things(PIoT)technology.The“source-grid-load-storage”architecture of a new power system requires PIoT to have a stronger multi-source heterogeneous data fusion ability.Native graph databases have great advantages in dealing with multi-source heterogeneous data,which make them suitable for an increasing number of analytical computing tasks.However,only few existing graph database products have native support for matrix operation-related interfaces or functions,resulting in low efficiency when handling matrix calculations that are commonly encountered in power grids.In this paper,the matrix computation process is expressed by a strategy called graph description,which relies on the natural connection between the matrix and structure of the graph.Based on that,we implement matrix operations on graph database,including matrix multiplication,matrix decomposition,etc.Specifically,only the nodes relevant to the computation and their neighbors are concerned in the process,which prunes the influence of zero elements in the matrix and avoids useless iterations compared to the conventional matrix computation.Based on the graph description,a series of power grid computations can be implemented on graph database,which reduces redundant data import and export operations while leveraging the parallel computing capability of graph database.It promotes the efficiency of PIoT when handling multi-source heterogeneous data.An comprehensive experimental study over two different scale power system datasets compares the proposed method with Python and MATLAB baselines.The results reveal the superior performance of our proposed method in both power flow and N-1 contingency computations.

Research and Practice on the Multi-dimensional Course Goal Achievement Evaluation of Software Engineering

According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.