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.

流程化工具包在肺癌根治术患者中的应用

目的:探讨流程化工具包在肺癌根治术患者中的应用效果。方法:选取2022年6月1日~12月31日接受肺癌根治术的92例患者作为研究对象,采用随机数字表法分为观察组和对照组各46例,对照组予以常规治疗护理,观察组予以流程化工具包。比较两组术后康复情况、核心体温、术后寒战发生情况、负性情绪[采用焦虑自评量表(SAS)和抑郁自评量表(SDS)]。结果:观察组排气时间、胸管留置时间、住院时间均短于对照组(P<0.01);观察组术中及术后核心体温均高于对照组(P<0.01);观察组术后寒战发生率低于对照组(P<0.01);术后,观察组SAS、SDS评分均低于对照组(P<0.01)。结论:流程化工具包能有效提升肺癌根治术患者术后康复效果,改善术中低体温情况,缓解术后不良情绪。

Discrimination of polysorbate 20 by high-performance liquid chromatography-charged aerosol detection and characterization for components by expanding compound database and library

Analyzing polysorbate 20(PS20)composition and the impact of each component on stability and safety is crucial due to formulation variations and individual tolerance.The similar structures and polarities of PS20 components make accurate separation,identification,and quantification challenging.In this work,a high-resolution quantitative method was developed using single-dimensional high-performance liquid chromatography(HPLC)with charged aerosol detection(CAD)to separate 18 key components with multiple esters.The separated components were characterized by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry(UHPLC-Q-TOF-MS)with an identical gradient as the HPLC-CAD analysis.The polysorbate compound database and library were expanded over 7-time compared to the commercial database.The method investigated differences in PS20 samples from various origins and grades for different dosage forms to evaluate the composition-process relationship.UHPLC-Q-TOF-MS identified 1329 to 1511 compounds in 4 batches of PS20 from different sources.The method observed the impact of 4 degradation conditions on peak components,identifying stable components and their tendencies to change.HPLC-CAD and UHPLC-Q-TOF-MS results provided insights into fingerprint differences,distinguishing quasi products.

Enhancing AI System Privacy:An Automatic Tool for Achieving GDPR Compliance in NoSQL Databases

The EU’s Artificial Intelligence Act(AI Act)imposes requirements for the privacy compliance of AI systems.AI systems must comply with privacy laws such as the GDPR when providing services.These laws provide users with the right to issue a Data Subject Access Request(DSAR).Responding to such requests requires database administrators to identify information related to an individual accurately.However,manual compliance poses significant challenges and is error-prone.Database administrators need to write queries through time-consuming labor.The demand for large amounts of data by AI systems has driven the development of NoSQL databases.Due to the flexible schema of NoSQL databases,identifying personal information becomes even more challenging.This paper develops an automated tool to identify personal information that can help organizations respond to DSAR.Our tool employs a combination of various technologies,including schema extraction of NoSQL databases and relationship identification from query logs.We describe the algorithm used by our tool,detailing how it discovers and extracts implicit relationships from NoSQL databases and generates relationship graphs to help developers accurately identify personal data.We evaluate our tool on three datasets,covering different database designs,achieving an F1 score of 0.77 to 1.Experimental results demonstrate that our tool successfully identifies information relevant to the data subject.Our tool reduces manual effort and simplifies GDPR compliance,showing practical application value in enhancing the privacy performance of NOSQL databases and AI systems.

Classification of Cybersecurity Threats, Vulnerabilities and Countermeasures in Database Systems

Database systems have consistently been prime targets for cyber-attacks and threats due to the critical nature of the data they store.Despite the increasing reliance on database management systems,this field continues to face numerous cyber-attacks.Database management systems serve as the foundation of any information system or application.Any cyber-attack can result in significant damage to the database system and loss of sensitive data.Consequently,cyber risk classifications and assessments play a crucial role in risk management and establish an essential framework for identifying and responding to cyber threats.Risk assessment aids in understanding the impact of cyber threats and developing appropriate security controls to mitigate risks.The primary objective of this study is to conduct a comprehensive analysis of cyber risks in database management systems,including classifying threats,vulnerabilities,impacts,and countermeasures.This classification helps to identify suitable security controls to mitigate cyber risks for each type of threat.Additionally,this research aims to explore technical countermeasures to protect database systems from cyber threats.This study employs the content analysis method to collect,analyze,and classify data in terms of types of threats,vulnerabilities,and countermeasures.The results indicate that SQL injection attacks and Denial of Service(DoS)attacks were the most prevalent technical threats in database systems,each accounting for 9%of incidents.Vulnerable audit trails,intrusion attempts,and ransomware attacks were classified as the second level of technical threats in database systems,comprising 7%and 5%of incidents,respectively.Furthermore,the findings reveal that insider threats were the most common non-technical threats in database systems,accounting for 5%of incidents.Moreover,the results indicate that weak authentication,unpatched databases,weak audit trails,and multiple usage of an account were the most common technical vulnerabilities in database systems,each accounting for 9%of vulnerabilities.Additionally,software bugs,insecure coding practices,weak security controls,insecure networks,password misuse,weak encryption practices,and weak data masking were classified as the second level of security vulnerabilities in database systems,each accounting for 4%of vulnerabilities.The findings from this work can assist organizations in understanding the types of cyber threats and developing robust strategies against cyber-attacks.

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.

Database Search Behaviors: Insight from a Survey of Information Retrieval Practices

This study examines the database search behaviors of individuals, focusing on gender differences and the impact of planning habits on information retrieval. Data were collected from a survey of 198 respondents, categorized by their discipline, schooling background, internet usage, and information retrieval preferences. Key findings indicate that females are more likely to plan their searches in advance and prefer structured methods of information retrieval, such as using library portals and leading university websites. Males, however, tend to use web search engines and self-archiving methods more frequently. This analysis provides valuable insights for educational institutions and libraries to optimize their resources and services based on user behavior patterns.

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.

A Systematic Review of Automated Classification for Simple and Complex Query SQL on NoSQL Database

A data lake(DL),abbreviated as DL,denotes a vast reservoir or repository of data.It accumulates substantial volumes of data and employs advanced analytics to correlate data from diverse origins containing various forms of semi-structured,structured,and unstructured information.These systems use a flat architecture and run different types of data analytics.NoSQL databases are nontabular and store data in a different manner than the relational table.NoSQL databases come in various forms,including key-value pairs,documents,wide columns,and graphs,each based on its data model.They offer simpler scalability and generally outperform traditional relational databases.While NoSQL databases can store diverse data types,they lack full support for atomicity,consistency,isolation,and durability features found in relational databases.Consequently,employing machine learning approaches becomes necessary to categorize complex structured query language(SQL)queries.Results indicate that the most frequently used automatic classification technique in processing SQL queries on NoSQL databases is machine learning-based classification.Overall,this study provides an overview of the automatic classification techniques used in processing SQL queries on NoSQL databases.Understanding these techniques can aid in the development of effective and efficient NoSQL database applications.

Application of Thermodynamic Database to Corrosion of ZrO_(2) Containing Submerged Entry Nozzle in Steel Continuous Casting Process

The CALPHAD thermodynamic databases are very useful to analyze the complex chemical reactions happening in high temperature material process.The FactSage thermodynamic database can be used to calculate complex phase diagrams and equilibrium phases involving refractories in industrial process.In this study,the FactSage thermodynamic database relevant to ZrO_(2)-based refractories was reviewed and the application of the database to understanding the corrosion of continuous casting nozzle refractories in steelmaking was presented.

软件开发工具包个人信息保护问题及检测手段

数字经济时代,我国移动互联网蓬勃发展,手机应用程序(Application Program,APP)、应用分发平台、小程序、软件开发工具包(Software Development Kit,SDK)等持续快速发展,也成为个人信息保护的关键领域。其中,SDK作为APP开发必不可少的功能模块,在为APP研发提供便利、促进产业繁荣发展的同时,也造成了一系列侵害用户权益的问题。为进一步加强SDK个人信息保护治理,我国SDK个人信息保护方面的政策法规、检测手段和管理模式不断完善。

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.

Large Language Model Based Semantic Parsing for Intelligent Database Query Engine

With the rapid development of artificial intelligence, large language models (LLMs) have demonstrated remarkable capabilities in natural language understanding and generation. These models have great potential to enhance database query systems, enabling more intuitive and semantic query mechanisms. Our model leverages LLM’s deep learning architecture to interpret and process natural language queries and translate them into accurate database queries. The system integrates an LLM-powered semantic parser that translates user input into structured queries that can be understood by the database management system. First, the user query is pre-processed, the text is normalized, and the ambiguity is removed. This is followed by semantic parsing, where the LLM interprets the pre-processed text and identifies key entities and relationships. This is followed by query generation, which converts the parsed information into a structured query format and tailors it to the target database schema. Finally, there is query execution and feedback, where the resulting query is executed on the database and the results are returned to the user. The system also provides feedback mechanisms to improve and optimize future query interpretations. By using advanced LLMs for model implementation and fine-tuning on diverse datasets, the experimental results show that the proposed method significantly improves the accuracy and usability of database queries, making data retrieval easy for users without specialized knowledge.

天气雷达基数据通用工具包设计与实现

气雷达基数据格式多样,造成数据解析、可视化困难,经常发生兼容性问题。通用工具包由格式转换工具和可视化工具组成。前者在基数据格式分类、解析和封装的基础上,以“基数据标准格式V1.1(FMT)”为中间类型,凝练出其它格式向FMT转换、FMT向其它格式转换的10类转换算法,实现基数据格式的自由转换;后者以FMT为基础,凝练出9类观测要素的回波图形化算法,实现基数据的可视化。利用此工具包,甘肃省气象数据中心将该省8部雷达历史基数据转换为标准格式保存,统一了数据格式;利用可视化工具将基数据转换为png图形文件,供前台网站使用。应用证明,工具包能不依赖任何开发环境和支撑系统独立运行,使用方便,既能面向普通用户,又能为二次开发做支撑。

手术室团队策略和工具包管理模式对宫颈癌手术护理质量的影响

目的探讨针对宫颈癌手术患者采用手术室团队策略与工具包管理模式干预的效果。方法选取2021年1月—2023年6月于苏州大学附属张家港医院拟行宫颈癌手术的80例患者,采用抽签法分为研究组和对照组,每组40例。对照组采用常规管理措施,研究组采用手术室团队策略和工具包管理措施。同时,选择手术室护理人员44名,分为对照组和观察组,每组22名。比较两组护理人员操作能力评分,安全态度评分,并且采用健康简易量表(SF-36)评估患者生活质量。结果研究组护理人员隔离技术、无菌技术、体位摆放、预防术中低体温、预防术中压疮等指标评分均高于对照组,差异有统计学意义(P<0.05);研究组护理人员团队协作、安全氛围、管理感知、工作满意度、工作条件、压力感知等指标评分均高于对照组,差异有统计学意义(P<0.05);干预前,两组患者生活质量各维度评分比较,差异无统计学意义(P>0.05);干预后,两组患者生活质量各维度评分均干预护理前,且研究组高于对照组,差异有统计学意义(P<0.05)。结论手术室团队策略和工具包管理干预可提高护理护理人员的操作能力和安全态度,改善患者的生活质量,显著提高宫颈癌手术的质量。

儿童服务设计工具包,一起拯救地球

“拯救地球儿童服务设计工具包”是一款帮助儿童了解周围的设计和环境问题,以及减少碳足迹的产品。该工具包鼓励儿童运用创造性和想象力,想出解决环境问题的新方法。它还教会人们如何开发新的解决方案,培养年轻的服务设计师的环境意识和责任感,并鼓励他们采取行动。

针对政策类别模糊 应用方向不清等问题 山西更新升级产业用地政策“工具包”

为进一步优化营商环境,激发市场主体活力,近日,山西省自然资源厅印发《山西省产业用地政策实施工作指引(2023年版)》(以下简称《指引(2023年版)》),针对当前产业用地政策分布趋散、政策类别模糊、应用方向不清等问题,系统梳理介绍产业用地政策的法律依据、概念内涵、实施原则以及适用情形等,为全省产业用地提供最新的政策“工具包”和使用说明书。

新型电力高空作业安全工具包

1创新背景电力高空作业时需要使用钳子、扳手、螺丝刀等众多工具,一般将这些工具装入工具包,再将工具包通过皮带或者其他束缚带固定在腰部。由于是高空作业,工具一旦脱手很容易形成高工坠物,造成安全隐患。2技术方案为解决上述问题,我们创新设计了新型电力高空作业安全工具包。图1所示为新型电力高空作业安全工具包结构示意图。

跨理论模型联合意外、死亡、伤害工具包在出院老年人跌倒防范中的应用研究

目的:探讨跨理论模型联合意外、死亡、伤害工具包防范出院老年人跌倒的效果。方法:选取2020年10月—12月重庆医科大学附属第一医院老年科,经汉化版Morse量表证实有跌倒风险的住院老年人为研究对象,随机分为试验组和对照组,试验组(122例)采用跨理论模型联合意外、死亡、伤害工具包防范措施进行干预,对照组(117例)采用常规跌倒防范干预,比较两组老年人出院24周内跌倒防范措施执行率、跌倒和跌伤发生率。结果:试验组的老年人对各类居家防跌倒措施的执行率在出院后的4周(除了视力和足部管理)、12周(除了视力和足部管理)和24周(除了足部管理)均高于对照组(P<0.05);试验组跌倒发生率为8.20%(10/122),低于对照组17.95%(21/117)(P<0.05);试验组跌伤发生率为10.00%(1/10),低于对照组52.4%(11/21)(P<0.05)。结论:跨理论模型联合意外、死亡、伤害工具包能有效提高老年人出院后的跌倒防范措施执行率,降低跌倒和跌伤发生率,可作为一种新的防跌倒策略应用于出院老年人跌倒防范。

基于Geodatabase数据模型和Case工具设计实现配电GIS数据库

传统的地理信息系统数据模型难以表达非结构化数据和GIS中具有复杂结构的数据,也不能表达继承、聚合等在GIS中广泛使用的关系。文章概述了Geodatabase模型的结构和特点,并针对配电网数据结构的特点,在Geodatabase模型的基础上,利用UML建模语言和ArcGIS提供的Case工具,设计并实现了配电GIS数据库。这种数据模型和设计方法比传统方法直观、简单且易于修改,对配电网的描述更贴切,利于数据库设计的优化,是设计空间数据库的一种较好的方法。