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.

Domain semantic mapping of database metasearch engine

In order to implement semantic mapping of database metasearch engines, a system is proposed, which uses ontology as the organization form of information and records the new words not appearing in the ontology. When the new word＇ s frequency of use exceeds the threshold, it is added into the ontology. Ontology expansion is implemented in this way. The search process supports ＂and＂ and ＂or＂ Boolean operations accordingly. In order to improve the mapping speed of the system, a memory module is added which can memorize the recent query information of users and automatically learn the user＇ s query interest during the mapping which can dynamically decide the search order of instances tables. Experiments prove that these measures can obviously reduce the average mapping time.

Development of a panel of unigene-derived polymorphic EST–SSR markers in lentil using public database information

Lentil(Lens culinaris Medik.), a diploid(2n = 14) with a genome size greater than 4000 Mbp, is an important cool season food legume grown worldwide. The availability of genomic resources is limited in this crop species. The objective of this study was to develop polymorphic markers in lentil using publicly available curated expressed sequence tag information(ESTs). In this study, 9513 ESTs were downloaded from the National Center for Biotechnology Information(NCBI) database to develop unigene-based simple sequence repeat(SSR) markers. The ESTs were assembled into 4053 unigenes and then analyzed to identify 374 SSRs using the MISA microsatellite identification tool. Among the 374 SSRs, 26 compound SSRs were observed.Primer pairs for these SSRs were designed using Primer3 version 1.14. To classify the functional annotation of ESTs and EST–SSRs, BLASTx searches(using E-value 1 × 10-5) against the public UniP rot(http://www.uniprot.org/) and NCBI(http://www.ncbi.nlh.nih.gov/) databases were performed. Further functional annotation was performed using PLAZA(version3.0) comparative genomics and GO annotation was summarized using the Plant GO slim category. Among the synthesized 312 primers, 219 successfully amplified Lens DNA. A diverse panel of 24 Lens genotypes was used to identify polymorphic markers. A polymorphic set of 57 markers successfully discriminated the test genotypes. This set of polymorphic markers with functional annotation data could be used as molecular tools in lentil breeding.

iORbase:A database for the prediction of the structures andfunctions of insect olfactory receptors

Insect olfactory receptors(iORs)with atypical 7-transmembrane domains,unlike Chordata olfactory receptors,are not in the GPCR protein family.iORs selectively bind to volatile ligands in the environment and affect essential insect behaviors.In this study,we constructed a new platform(iORbase,https://www.iorbase.com)for the structural and functional analysis of iORs based on a combined algorithm for gene annotation and protein structure prediction.Moreover,it provides the option to calculate the binding affinities and binding residues between iORs and pheromone molecules by virtual screening of docking.Furthermore,iORbase supports the automatic structural and functional prediction of user-submitted iORs or pheromones.iORbase contains the well-analyzed results of approximately 6000 iORs and their 3D protein structures identified from 59 insect species and 2077 insect pheromones from the literature,as well as approximately 12 million pairs of simulated interactions between functional iORs and pheromones.We also built 4 online modules,iORPDB,iInteraction,iModelTM,and iOdorTool to easily retrieve and visualize the 3D structures and interactions.iORbase can help greatly improve the experimental efficiency and success rate,identify new insecticide targets,or develop electronic nose technology.This study will shed light on the olfactory recognition mechanism and evolutionary characteristics from the perspectives of omics and macroevolution.

A product module mining method for PLM database

Modular technology can effectively support the rapid design of products, and it is one of the key technologies to realize mass customization design. With the application of product lifecycle management(PLM) system in enterprises, the product lifecycle data have been effectively managed. However, these data have not been fully utilized in module division, especially for complex machinery products. To solve this problem, a product module mining method for the PLM database is proposed to improve the effect of module division. Firstly, product data are extracted from the PLM database by data extraction algorithm. Then, data normalization and structure logical inspection are used to preprocess the extracted defective data. The preprocessed product data are analyzed and expressed in a matrix for module mining. Finally, the fuzzy c-means clustering(FCM) algorithm is used to generate product modules, which are stored in product module library after module marking and post-processing. The feasibility and effectiveness of the proposed method are verified by a case study of high pressure valve.

Building a Database for the Future:Humans and Lakes within Ecosystems

1 Introduction Fresh or saline,lakes constantly exchange with other water bodies on the Earth.Together,they form a crucial part of the water cycle–one of the most important ecosystem functions supporting humans and other biological communities.Lakes have provided invaluable and irreplaceable ecosystem services(benefits)for the

A Simplified Database-Oriented Web Framework

The paper firstly analyses disadvantages in the traditional Web database systems. And then it puts forward a simplified framework called database-oriented Web framework (DOWF). In this framework, the pages and the data are all managed by database system. In order to get keywords or search a special page, which the users accessed before, users access the static pages by common script procedure (CSP), and access the dynamic pages by functional script procedure (FSP) and CSP. The article expounds the method how to implement DOWF in details. The paper also analyses the mechanism of a DOWF site by implementing a prototype system. At last, the article gives the features of DOWS in search, in security, in reuse of pages and in offline waiting, etc. Key words database-oriented - Web framework - common script procedure (CSP) - functional script procedure (FSP) CLC number TP 391 Foundation item: Supported by Natural Science Foundation of Jiangsu Province (BK2003030).Biography: ZHU Qiao-ming (1963-), male, professor, research direction: Web information processing chinses information processing.

Modulating J-V hysteresis of planar perovskite solar cells and mini-modules via work function engineering

Commercialization of perovskite solar cells(PSCs) requires the development of high-efficiency devices with none current density-voltage(J-V) hysteresis. Here, electron transport layers(ETLs) with gradual change in work function(WF) are successfully fabricated and employed as an ideal model to investigate the energy barriers, charge transfer and recombination kinetics at ETL/perovskite interface. The energy barrier for electron injection existing at ETL/perovskite is directly assessed by surface photovoltage microscopy, and the results demonstrate the tunable barriers have significant impact on the J-V hysteresis and performance of PSCs. By work function engineering of ETL, PSCs exhibit PCEs over 21% with negligible hysteresis. These results provide a critical understanding of the origin reason for hysteresis effect in planar PSCs, and clear reveal that the J-V hysteresis can be effectively suppressed by carefully tuning the interface features in PSCs. By extending this strategy to a modified formamidinium-cesium-rubidium(FA-Cs-Rb) perovskite system, the PCEs are further boosted to 24.18%. Moreover, 5 cm × 5 cm perovskite mini-modules are also fabricated with an impressive efficiency of 20.07%, demonstrating compatibility and effectiveness of our strategy on upscaled devices.

Neuropeptide cholecystokinin:a key neuromodulator for hippocampal functions

Spatial memory is crucial for survival within external surroundings and wild environments.The hippocampus,a critical hub for spatial learning and memory formation,has received extensive investigations on how neuromodulators shape its functions(Teixeira et al.,2018;Zhang et al.,2024).However,the landscape of neuromodulations in the hippocampal system remains poorly understood because most studies focus on classical monoamine neuromodulators,such as acetylcholine,serotonin,dopamine,and noradrenaline.The neuropeptides,comprising the most abundant neuromodulators in the central nervous system,play a pivotal role in neural information processing in the hippocampal system.Cholecystokinin(CCK),one of the most abundant neuropeptides,has been implicated in regulating various physiological and neurobiological statuses(Chen et al.,2019).CCK-A receptor(CCK-AR)and CCK-B receptors(CCK-BR)are two key receptors mediating the biological functions of CCK,both of which belong to class-A sevenfold transmembrane G protein-coupled receptors(Nishimura et al.,2015).CCK-AR preferentially reacts to sulfated CCK,whereas CCK-BR binds both CCK and gastrin with similar affinities(Ding et al.,2022).The expression patterns of CCK-AR and CCK-BR are distinct,implying that CCK has various functions in target regions.For instance,CCK-AR is widely expressed in the GI and brain subregions and is hence implicated in the control of digestive function and satiety regulation.Conversely,CCK-BR is abundantly and widely distributed in the central nervous system,which majorly regulates anxiety,learning,and memory(Ding et al.,2022).However,the roles of endogenous CCK and CCK receptors in regulating hippocampal function at electrophysiological and behavioral levels have received less attention.

Microbiota treatment of functional constipation:Current status and future prospects

Functional constipation(FC)is a common disorder that is characterized by diffi-cult stool passage,infrequent bowel movement,or both.FC is highly prevalent,recurs often,accompanies severe diseases,and affects quality of life;therefore,safe and effective therapy with long-term benefits is urgently needed.Microbiota treatment has potential value for FC treatment.Microbiota treatments include modulators such as probiotics,prebiotics,synbiotics,postbiotics,and fecal micro-biota transplantation(FMT).Some probiotics and prebiotics have been adopted,and the efficacy of other microbiota modulators is being explored.FMT is con-sidered an emerging field because of its curative effects;nevertheless,substantial work must be performed before clinical implementation.

Research Progress on Neuroprotective Effects of Salvianolic Acid B in an Animal Model of Parkinson's Disease

As an active ingredient extracted from Salvia miltiorrhiza,the neuroprotective effects of salvianolic acid B in Parkinson's disease include antioxidation,improvement of mitochondrial function,modulation of neuroinflammation,inhibition of apoptosis,promotion of neuronal differentiation and proliferation,and influence on intestinal flora.As an adjuvant drug,salbutamol B can be used in combination with conventional therapeutic drugs to enhance the efficacy and minimize the side effects,which provides a method and basis for the early diagnosis and treatment of Parkinson's disease in clinical practice.

Protein sequence databases generated from metagenomics and public databases produced similar soil metaproteomic results of microbial taxonomic and functional changes

Soil metaproteomics has excellent potential as a tool to elucidate the structural and functional changes in soil microbial communities in response to environmental alterations. However, soil metaproteomics is hindered by several challenges and gaps. Soil microbial communities possess extremely complex microbial composition, including many uncultured microorganisms without whole genome sequencing. Thus, how to select a suitable protein sequence database remains challenging in soil metaproteomics. In this study, the Public database and Meta-database were constructed using protein sequences from public databases and metagenomics, respectively. We comprehensively analyzed and compared the soil metaproteomic results using these two kinds of protein sequence databases for protein identification based on published soil metaproteomic raw data. The results demonstrated that many more proteins, higher sequence coverage, and even more microbial species and functional annotations could be identified using the Meta-database compared with those identified using the Public database. These findings indicated that the Meta-database was more specific as a protein sequence database. However, the follow-up in-depth metaproteomic analyses exhibited similar main results regardless of the database used. The microbial community composition at the genus level was similar between the two databases, especially the species annotations with high peptide-spectrum match and high abundance. The functional analyses in response to stress, such as the gene ontology enrichment of biological progress and molecular function and the key functional microorganisms, were also similar regardless of the database. Our analysis revealed that the Public database could also meet the demand to explore the functional responses of microbial proteins to some extent. This study provides valuable insights into the choice of protein sequence databases and their impacts on subsequent bioinformatic analysis in soil metaproteomic research and will facilitate the optimization of experimental design for different purposes.

An overview of human protein databases and their application to functional proteomics in health and disease

Functional proteomics can be defined as a strategy to couple proteomic information with biochemical and physiological analyses with the aim of understanding better the functions of proteins in normal and diseased organs.In recent years,a variety of publicly available bioinformatics databases have been developed to support protein-related information management and biological knowledge discovery.In addition to being used to annotate the proteome,these resources also offer the opportunity to develop global approaches to the study of the functional role of proteins both in health and disease.Here,we present a comprehensive review of the major human protein bioinformatics databases.We conclude this review by discussing a few examples that illustrate the importance of these databases in functional proteomics research.

Fast Algorithms of Mining Probability Functional Dependency Rules in Relational Database

This paper defines a new kind of rule, probability functional dependency rule. The functional dependency degree can be depicted by this kind of rule. Five algorithms, from the simple to the complex, are presefited to mine this kind of rule in different condition. The related theorems are proved to ensure the high efficiency and the correctness of the above algorithms.

BnlR:A multi-omics database with various tools for Brassica napus research and breeding

In the post-genome-wide association study era,multi-omics techniques have shown great power and poten-tial for candidate gene mining and functional genomics research.However,due to the lack of effective data integration and multi-omics analysis platforms,such techniques have not still been applied widely in rape-seed,an important oil crop worldwide.Here,we report a rapeseed multi-omics database(BnlR;http:/l yanglab.hzau.edu.cn/BnlR),which provides datasets of six omics including genomics,transcriptomics,variomics,epigenetics,phenomics,and metabolomics,as well as numerous"variation-gene expression-phenotype"associations by using multiple statistical methods.In addition,a series of multi-omics search and analysis tools are integrated to facilitate the browsing and application of these datasets.BnlR is the most comprehensive multi-omics database for rapeseed so far,and two case studies demonstrated its power to mine candidate genes associated with specific traits and analyze their potential regulatory mechanisms.

A Method of Clustering Components into Modules Based on Products' Functional and Structural Analysis

Modularity is the key to improving the cost-variety trade-off in product development. To achieve the functional independency and structural independency of modules, a method of clustering components to identify modules based on functional and structural analysis was presented. Two stages were included in the method. In the first stage the products’ function was analyzed to determine the primary level of modules. Then the objective function for modules identifying was formulated to achieve functional independency of modules. Finally the genetic algorithm was used to solve the combinatorial optimization problem in modules identifying to form the primary modules of products. In the second stage the cohesion degree of modules and the coupling degree between modules were analyzed. Based on this structural analysis the modular scheme was refined according to the thinking of structural independency. A case study on the gear reducer was conducted to illustrate the validity of the presented method.

A FIXED POINT APPROACH TO THE STABILITY OF A GENERAL MIXED ADDITIVE-CUBIC EQUATION ON BANACH MODULES

Using a fixed-point method, we establish the generalized Hyers-Ulam stability of a general mixed additive-cubic equation： f（kx ＋ y） ＋ f（kx - y） = kf（x ＋ y） ＋ kf（x - y） ＋ 2f（kx） - 2kf（x） in Banach modules over a unital Banach algebra.

Unbiased parameter estimation of continuous-time system based on modulating functions with input and output white noises

An efficient unbiased estimation method is proposed for the direct identification of linear continuous-time system with noisy input and output measurements.Using the Gaussian modulating filters,by numerical integration,an equivalent discrete identification model which is parameterized with continuous-time model parameters is developed,and the parameters can be estimated by the least-squares (LS) algorithm.Even with white noises in input and output measurement data,the LS estimate is biased,and the bias is determined by the variances of noises.According to the asymptotic analysis,the relationship between bias and noise variances is derived.One equation relating to the measurement noise variances is derived through the analysis of the LS errors.Increasing the degree of denominator of the system transfer function by one,an extended model is constructed.By comparing the true value and LS estimates of the parameters between original and extended model,another equation with input and output noise variances is formulated.So,the noise variances are resolved by the set of equations,the LS bias is eliminated and the unbiased estimates of system parameters are obtained.A simulation example by comparing the standard LS with bias eliminating LS algorithm indicates that the proposed algorithm is an efficient method with noisy input and output measurements.

Evolution Properties of Modules in Complex Networks

In complex networks, network modules play a center role, which carry out a key function. In this paper, we introduce the spatial correIation function to describe the relationships among the network modules. Our focus is to investigate how the network modules evolve, and what the evolution properties of the modules are. In order to test the proposed method, as the examples, we use our method to analyze and discuss the ER random network and scale-free network. Rigorous analysis of the existing data shows that the introduced correlation function is suitable for describing the evolution properties of network modules. Remarkably, the numerical simulations indicate that the ER random network and scale-free network have different evolution properties.