Dynamic Update Scheme of Spectrum Information Based on Spectrum Opportunity Incentive in the Database-Assisted Dynamic Spectrum Management

To solve the problem of delayed update of spectrum information(SI) in the database assisted dynamic spectrum management(DB-DSM), this paper studies a novel dynamic update scheme of SI in DB-DSM. Firstly, a dynamic update mechanism of SI based on spectrum opportunity incentive is established, in which spectrum users are encouraged to actively assist the database to update SI in real time. Secondly, the information update contribution(IUC) of spectrum opportunity is defined to describe the cost of accessing spectrum opportunity for heterogeneous spectrum users, and the profit of SI update obtained by the database from spectrum allocation. The process that the database determines the IUC of spectrum opportunity and spectrum user selects spectrum opportunity is mapped to a Hotelling model. Thirdly, the process of determining the IUC of spectrum opportunities is further modelled as a Stackelberg game by establishing multiple virtual spectrum resource providers(VSRPs) in the database. It is proved that there is a Nash Equilibrium in the game of determining the IUC of spectrum opportunities by VSRPs. Finally, an algorithm of determining the IUC based on a genetic algorithm is designed to achieve the optimal IUC. The-oretical analysis and simulation results show that the proposed method can quickly find the optimal solution of the IUC, and ensure that the spectrum resource provider can obtain the optimal profit of SI update.

Power Information System Database Cache Model Based on Deep Machine Learning

At present,the database cache model of power information system has problems such as slow running speed and low database hit rate.To this end,this paper proposes a database cache model for power information systems based on deep machine learning.The caching model includes program caching,Structured Query Language(SQL)preprocessing,and core caching modules.Among them,the method to improve the efficiency of the statement is to adjust operations such as multi-table joins and replacement keywords in the SQL optimizer.Build predictive models using boosted regression trees in the core caching module.Generate a series of regression tree models using machine learning algorithms.Analyze the resource occupancy rate in the power information system to dynamically adjust the voting selection of the regression tree.At the same time,the voting threshold of the prediction model is dynamically adjusted.By analogy,the cache model is re-initialized.The experimental results show that the model has a good cache hit rate and cache efficiency,and can improve the data cache performance of the power information system.It has a high hit rate and short delay time,and always maintains a good hit rate even under different computer memory;at the same time,it only occupies less space and less CPU during actual operation,which is beneficial to power The information system operates efficiently and quickly.

Application and research of global grid database design based on geographic information

Energy crisis and climate change have become two seriously concerned issues universally. As a feasible solution, Global Energy Interconnection(GEI) has been highly praised and positively responded by the international community once proposed by China. From strategic conception to implementation, GEI development has entered a new phase of joint action now. Gathering and building a global grid database is a prerequisite for conducting research on GEI. Based on the requirement of global grid data management and application, combining with big data and geographic information technology, this paper studies the global grid data acquisition and analysis process, sorts out and designs the global grid database structure supporting GEI research, and builds a global grid database system.

Journal of Arid Land was included in Abstract Journal,All-Russian Institute of Scientific and Technical Information(VINITI) Database

On December 22, 2010, an E-mail by Dr. Elena Raevskaya, the manager of Asia and Africa Section, All-Russian Institute of Scientific and Technical Information （V1NITI）, was sent to Journal Publishing Center, Xinjiang Insti- tute of Ecology and Geography, CAS and said “Here is some new information about the Chinese journals evaluated by our experts. Ten journals have been found informative and useful in our work and have been included in VINITI database for regular abstraction （some of these journals were reexamined by expertise）.”

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.

Unified Platform About Information Issuing,Integration and Management of Meta-Database and Spatial-Database Based on Geology Metadata Standard

With the deepening informationization of Resources & Environment Remote Sensing geological survey conducted,some potential problems and deficiency are:(1) shortage of unified-planed running environment;(2) inconsistent methods of data integration;and(3) disadvantages of different performing ways of data integration.This paper solves the above problems through overall planning and design,constructs unified running environment, consistent methods of data integration and system structure in order to advance the informationization

Developing a Geological Management Information System: National Important Mining Zone Database

Geo-data is a foundation for the prediction and assessment of ore resources, so managing and making full use of those data, including geography database, geology database, mineral deposits database, aeromagnetics database, gravity database, geochemistry database and remote sensing database, is very significant. We developed national important mining zone database （NIMZDB） to manage 14 national important mining zone databases to support a new round prediction of ore deposit. We found that attention should be paid to the following issues： ① data accuracy： integrity, logic consistency, attribute, spatial and time accuracy; ② management of both attribute and spatial data in the same system;③ transforming data between MapGIS and ArcGIS; ④ data sharing and security; ⑤ data searches that can query both attribute and spatial data. Accuracy of input data is guaranteed and the search, analysis and translation of data between MapGIS and ArcGIS has been made convenient via the development of a checking data module and a managing data module based on MapGIS and ArcGIS. Using AreSDE, we based data sharing on a client/server system, and attribute and spatial data are also managed in the same system.

Fashion Information Database

In the field of fashion industry, it is a bottleneck of how to control and apply the information in the procedure of fashion merchandising. By the aid of digital technology, a perfect and practical fashion information database could be established so that high-quality and efficient, low-cost and characteristic fashion merchandising system could be realized. The basic structure of fashion information database is discussed.

Database Development Based on MFC Application in Management of Curriculum Information

There are hundreds of records in the curriculum of our Language Learning Lab every semester and every record has several important properties. It takes too much time to manage the information in the traditional way and it always makes mistakes. Managing the information with database technology, designing program to access the database with Visual c tool, setting a combobox in the application UI and inquiring curriculum information by selecting the room name in the combobox. It is easy to operate the program for the staff members. The result is accurate, this way promotes the efficiency of managing information.

Soil Database Management Software Development for Optimizing Land Resource Information Utilization to Support National Food Security

Since land resource database development in 1987/1988, a large amount of digital data in spatial, tabular and metadata format has been collected and generated. There are some application softwares of soil database to manage such a large amount of data, i.e.: Side & Horizon (SHDE4), Soil Sample Analysis (SSA), and Land Unit in dbf file, while Site and Horizon is in DataEase formats. The database contains soil physics and chemical property data of each soil horizon from surface to effective soil depth, climate, land surface condi- tions, and other parameters required for soil classification. Currently, database management software for land resources is still based on DOS and is stand alone. The system is not efficient and effectively used as Agri- cultural Land Resource Information System. At present, as a key component of this system requires review and development of new database software is compatible with the development of information technology. This paper explains about development of interactive agricultural land resources information system for op- timizing land resources data utilization. Hopefully, the software can give contributions in national Agricul- tural Land Resources System Information development for supporting food security.

Analysis on the Construction Path of Database of Zhuang and Yao Medicine Information Resources

In order to realize the sharing,exchange,protection and rational utilization of Zhuang and Yao medicine resources,the problems encountered in the development of Zhuang and Yao medicine industry can be solved by using modern information technology in accordance with the present situation of Zhuang and Yao medicine resources in Guangxi Zhuang Autonomous Region and the actual needs of the development of ethnic medicine.This paper expounds the significance of constructing the database of Zhuang and Yao medicine information resources from three aspects:the inheritance and development of Zhuang and Yao medicine,the sustainable development of Zhuang and Yao medicine industry and the information service system.On this basis,the principle and framework of constructing Zhuang and Yao medicine information resource database are put forward.

Research on the User Information Optimized Retrieval Technology in Distributed Database

The traditional method first classifies the user information and combines the query method to retrieve the interest information, but neglects to calculate the weight of the user interest information, which leads to the low retrieval accuracy. A retrieval method based on the fuzzy proximity classification technology is proposed. Approximation between the fuzzy sets is used to represent the consistency between the user interest information features, and the consistency calculation formula and the skewness confidence matrix between the user interest information features are given. The fuzzy classification of the user interest information can obtain the most consistent confidence data and eliminate the redundant approximation interference data. The probabilistic model of the information word frequency and the user interest information length calculates the weight of the user interest information, and adjusts the weight formula constantly.

High-Performance Chemical Information Database towards Accelerating Discovery of Metal-Organic Frameworks for Gas Adsorption with Machine Learning

Chemical structure searching based on databases and machine learning has at-tracted great attention recently for fast screening materials with target func-tionalities.To this end,we estab-lished a high-performance chemical struc-ture database based on MYSQL engines,named MYDB.More than 160000 metal-organic frameworks(MOFs)have been collected and stored by using new retrieval algorithms for effcient searching and recom-mendation.The evaluations results show that MYDB could realize fast and effcient key-word searching against millions of records and provide real-time recommendations for similar structures.Combining machine learning method and materials database,we developed an adsorption model to determine the adsorption capacitor of metal-organic frameworks to-ward argon and hydrogen under certain conditions.We expect that MYDB together with the developed machine learning techniques could support large-scale,low-cost,and highly convenient structural research towards accelerating discovery of materials with target func-tionalities in the eld of computational materials research.

The Development of a Geographic Information System(GIS) Database for Jiuzhaigou National Nature Reserve and Its Application

The objective of this paper is to develop a GIS(Geographic Information System) database for Jiuzhaigou National Nature Reserve(Jiuzhaigou,hereafter) in China and demonstrate its application as a research tool.A cost-effective procedure was developed to compile a variety of geographical and biological data of the study area in terms of popular GIS format such as shape files.These files were further calibrated and validated using field surveys data.The developed GIS database was used to quantify the distributions of the wildlife(amphibians,mammals,and birds) using the distances of the wildlife to the centerline of the bus-tour routes.The Pearson correlation coefficient was used to quantify the correlation in space between pairs of different wildlife using the number of habitats for given space contexts.An ArcObject-based macro was developed to perform the analysis.The results showed the majority of the habitats of wildlife are located in the proximity of the tour-bus routes with an average distance ranging from 564 to 894 m depending on types of wildlife.This indicates a possibility of the disturbance to the wildlife by human activities.The correlation coefficient of the wildlife ranged from 0.36 to 0.64 depending on pairs of wildlife,indicating some correlations in space.However,due to the limited sample size,the statistical significances need to be further investigated.This paper has successfully demonstrated the use of the GIS-based database as a research tool for environmental study.

A Privacy Preservation Method for Attributed Social Network Based on Negative Representation of Information

Due to the presence of a large amount of personal sensitive information in social networks,privacy preservation issues in social networks have attracted the attention of many scholars.Inspired by the self-nonself discrimination paradigmin the biological immune system,the negative representation of information indicates features such as simplicity and efficiency,which is very suitable for preserving social network privacy.Therefore,we suggest a method to preserve the topology privacy and node attribute privacy of attribute social networks,called AttNetNRI.Specifically,a negative survey-based method is developed to disturb the relationship between nodes in the social network so that the topology structure can be kept private.Moreover,a negative database-based method is proposed to hide node attributes,so that the privacy of node attributes can be preserved while supporting the similarity estimation between different node attributes,which is crucial to the analysis of social networks.To evaluate the performance of the AttNetNRI,empirical studies have been conducted on various attribute social networks and compared with several state-of-the-art methods tailored to preserve the privacy of social networks.The experimental results show the superiority of the developed method in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topology disturbing and attribute hiding parts.The experimental results show the superiority of the developed methods in preserving the privacy of attribute social networks and demonstrate the effectiveness of the topological interference and attribute-hiding components.

Tuning the diffusion constant to optimize the readout of positional information of spatial concentration patterns

Positional information encoded in spatial concentration patterns is crucial for the development of multicellular organisms.However,it is still unclear how such information is affected by the physically dissipative diffusion process.Here we study one-dimensional patterning systems with analytical derivation and numerical simulations.We find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration patterns.Specifically,there exists an optimal diffusion constant that maximizes the positional information.Moreover,we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

A recovery method using recently updated record information in shared-nothing spatial database cluster

A shared nothing spatial database cluster is system that provides continuous service even if some system failure happens in any node. So, an efficient recovery of system failure is very important. Generally, the existing method recovers the failed node by using both cluster log and local log. This method, however, cause several problems that increase communication cost and size of cluster log. This paper proposes novel recovery method using recently updated record information in shared nothing spatial database cluster. The proposed technique utilizes update information of records and pointers of actual data. This makes a reduction of log size and communication cost. Consequently, this reduces recovery time of failed node due to less processing of update operations.

Silent information regulator sirtuin 1 ameliorates acute liver failure via the p53/glutathione peroxidase 4/gasdermin D axis

BACKGROUND Acute liver failure(ALF)has a high mortality with widespread hepatocyte death involving ferroptosis and pyroptosis.The silent information regulator sirtuin 1(SIRT1)-mediated deacetylation affects multiple biological processes,including cellular senescence,apoptosis,sugar and lipid metabolism,oxidative stress,and inflammation.AIM To investigate the association between ferroptosis and pyroptosis and the upstream regulatory mechanisms.METHODS This study included 30 patients with ALF and 30 healthy individuals who underwent serum alanine aminotransferase(ALT)and aspartate aminotransferase(AST)testing.C57BL/6 mice were also intraperitoneally pretreated with SIRT1,p53,or glutathione peroxidase 4(GPX4)inducers and inhibitors and injected with lipopolysaccharide(LPS)/D-galactosamine(D-GalN)to induce ALF.Gasdermin D(GSDMD)^(-/-)mice were used as an experimental group.Histological changes in liver tissue were monitored by hematoxylin and eosin staining.ALT,AST,glutathione,reactive oxygen species,and iron levels were measured using commercial kits.Ferroptosis-and pyroptosis-related protein and mRNA expression was detected by western blot and quantitative real-time polymerase chain reaction.SIRT1,p53,and GSDMD were assessed by immunofluorescence analysis.RESULTS Serum AST and ALT levels were elevated in patients with ALF.SIRT1,solute carrier family 7a member 11(SLC7A11),and GPX4 protein expression was decreased and acetylated p5,p53,GSDMD,and acyl-CoA synthetase long-chain family member 4(ACSL4)protein levels were elevated in human ALF liver tissue.In the p53 and ferroptosis inhibitor-treated and GSDMD^(-/-)groups,serum interleukin(IL)-1β,tumour necrosis factor alpha,IL-6,IL-2 and C-C motif ligand 2 levels were decreased and hepatic impairment was mitigated.In mice with GSDMD knockout,p53 was reduced,GPX4 was increased,and ferroptotic events(depletion of SLC7A11,elevation of ACSL4,and iron accumulation)were detected.In vitro,knockdown of p53 and overexpression of GPX4 reduced AST and ALT levels,the cytostatic rate,and GSDMD expression,restoring SLC7A11 depletion.Moreover,SIRT1 agonist and overexpression of SIRT1 alleviated acute liver injury and decreased iron deposition compared with results in the model group,accompanied by reduced p53,GSDMD,and ACSL4,and increased SLC7A11 and GPX4.Inactivation of SIRT1 exacerbated ferroptotic and pyroptotic cell death and aggravated liver injury in LPS/D-GalNinduced in vitro and in vivo models.CONCLUSION SIRT1 activation attenuates LPS/D-GalN-induced ferroptosis and pyroptosis by inhibiting the p53/GPX4/GSDMD signaling pathway in ALF.