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.

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 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.

Type-2 Neutrosophic Set and Their Applications in Medical Databases Deadlock Resolution

Electronic patient data gives many advantages,but also new difficulties.Deadlocks may delay procedures like acquiring patient information.Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties.Soft computing-based solutions have been developed to solve this challenge.In a single framework,ambiguous,vague,incomplete,and inconsistent transaction attribute information has received minimal attention.The work presented in this paper employed type-2 neutrosophic logic,an extension of type-1 neutrosophic logic,to handle uncertainty in real-time deadlock-resolving systems.The proposed method is structured to reflect multiple types of knowledge and relations among transactions’features that include validation factor degree,slackness degree,degree of deadline-missed transaction based on the degree of membership of truthiness,degree ofmembership of indeterminacy,and degree ofmembership of falsity.Here,the footprint of uncertainty(FOU)for truth,indeterminacy,and falsity represents the level of uncertainty that exists in the value of a grade of membership.We employed a distributed real-time transaction processing simulator(DRTTPS)to conduct the simulations and conducted experiments using the benchmark Pima Indians diabetes dataset(PIDD).As the results showed,there is an increase in detection rate and a large drop in rollback rate when this new strategy is used.The performance of Type-2 neutrosophicbased resolution is better than the Type-1 neutrosophic-based approach on the execution ratio scale.The improvement rate has reached 10%to 20%,depending on the number of arrived transactions.

Analysis of E2F3 gene variants,expression and clinical significance in melanoma based on multiple databases

Objective:To investigate the variation,expression and clinical significance of E2F3 gene in melanoma.Methods:Firstly,cBioportal database,Oncomine database and GEO database were used to analyze the variation and expression level of E2F3 gene in melanoma.OSskcm database and TISIDB database were used to analyze the relationship between E2F3 and melanoma prognosis and tumor immune infiltrating cells.Then,the LinkedOmics database was used to identify the differential genes related to E2F3 expression in melanoma and analyze their biological functions.Finally,small molecule compounds for the treatment of melanoma were screened through the CMap database.Results:The mutation rate of E2F3 gene in melanoma is about 4%,and there are 21 mutation sites.Compared with normal skin tissues,the expression of E2F3 gene in melanoma was significantly increased(P<0.01).The mutation and increased expression of E2F3 gene were associated with the shortened overall survival(OS)of melanoma patients(P<0.05).The CNA level of E2F3 was negatively correlated with the expression levels of lymphocytes such as pDC,Neutrophil,Act DC and Th17,and negatively correlated with the expression levels of chemokines such as CXCL5,CCL13 and CCR1.The methylation level of E2F3 was positively correlated with the expression levels of Th1,Neutrophil,Act DC and other lymphocytes,and positively correlated with the expression levels of CXCL16,CXCL12,CCR1 and other chemokines.The expression level of E2F3 was negatively correlated with the expression levels of lymphocytes such as Th17,Tcm CD4 and Th1,and negatively correlated with the expression levels of chemokines such as CXCL 16,CCL 22 and CCL 2.The expression of 96 genes such as UHRF1BP1 in melanoma was significantly correlated with the expression of E2F3(|cor|0.5,P<0.05).The above genes were mainly related to RNA transport,eukaryotic ribosome biogenesis,cell cycle and other pathways.Among them,WDR12,WDR43,RBM28,UTP18,DKC1,PAK1IP1,DDX31,TEX10,TRUB1 and TRMT61B were the top 10 hub genes.YC-1,simvastatin,cytochalasin-d,Deforolimus and cytochalasin-b may be five small molecule compounds for the treatment of melanoma.Conclusion:The mutation and increased expression level of E2F3 gene are related to the poor prognosis of melanoma and participate in the occurrence and development of melanoma by affecting the expression of different tumor immune infiltrating cell subtypes,which may be a potential diagnostic marker and therapeutic target for melanoma.

TCM抗阻训练在肥胖型阻塞性睡眠呼吸暂停低通气综合征患者中的应用

目的:探讨过渡期护理(TCM)抗阻训练在肥胖型阻塞性睡眠呼吸暂停低通气综合征(OSAHS)患者中的应用效果。方法:选取2022年1月1日~2023年1月1日接受治疗的102例肥胖型OSAHS患者作为研究对象,根据随机数字表法将其分为对照组和研究组各51例。对照组行常规抗阻训练,研究组行TCM抗阻训练;对比两组入院次日、出院1个月时体质指标[包括体质量指数(BMI)、颈围、腹围]、嗜睡程度[采用中文版Epworth嗜睡量表(ESS)]及生活质量[采用睡眠呼吸暂停低通气综合征生命质量评估表(QOL-OSAHS)]。结果:共有102例患者参与研究,其中对照组有1例在中途失访剔除,最后101例患者完整参与研究。出院1个月时,两组BMI、颈围、腹围及均ESS评分均低于入院次日(P<0.05),且研究组低于对照组(P<0.05);出院1个月时,两组QOL-OSAHS评分高于入院次日(P<0.05),且研究组高于对照组(P<0.05)。结论:TCM抗阻训练可有效改善肥胖型OSAHS患者体质指标,提升睡眠质量和生活质量。

中医药团体标准评价体系(SCORE-TCM)解读

本文全面解读了中医药团体标准评价体系(System of Consortium Standards Rating and Evaluation of Traditional Chinese Medicine,SCORE-TCM)。SCORE-TCM是结合定性与定量评价,全面评估中医药团体标准在制定主体、文本编写、技术内容、推广应用和实施效益等几方面特征的综合评价工具。文中详述了SCORE-TCM的构建目的、定义和构建过程,解释了评价指标体系中的各项指标,并对每项指标的评价材料进行介绍。本文旨在帮助中医药团体标准的制定者、第三方评价机构和其他相关方更好地理解SCORE-TCM各评价条目的含义,更有效地运用于中医药团体标准的自评价或第三方评价,SCORE-TCM将为《中医药团体标准管理办法》的贯彻实施,以及中医药团体标准的高质量发展提供技术支持。

基于SCORE-TCM的中医药团体标准抽样评价方案设计

目前,各社会团体积极参与中医药标准的制定和发布,特别是“十四五”以来,中医药团体标准化工作更是迎来了提质增效的关键阶段。深入评估社会团体发布的中医药标准质量,是推进中医药团体标准工作的关键环节和重点任务。前期已研制并形成了中医药团体标准评价体系(System of Consortium Standards Rating and Evaluation of Traditional Chinese Medicine, SCORETCM)。在上述背景下,本研究通过专家共识法,设计了一套基于SCORE-TCM的中医药团体标准抽样评价方案,应用场景为对于特定社会团体发布的标准,或各团体发布的特定技术类别的标准进行快速评估。该方案涵盖了标准抽样、材料收集、标准评价、结果解读的完整流程,为中医药团体标准的抽样评价工作提供了参考方案。

Chen Shigong,Founder of“TCM Orthodox School of External Medicine”

Chen Shigong,styled name Yuren,was also known by the literary name Ruoxu.Coming from Donghaichongchuan(present Nantong City,Jiangsu Province)he was a famous traditional Chinese medicine(TCM)specialist of external medicine of the Ming Dynasty(1368-1644).The Orthodox Lineage of External Medicine(Wai Ke Zheng Zong)written by him has been valued as the founder of the TCM Orthodox School of External Medicine.

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.

From Research on TCM Images to Historiography of TCM Images——Comments on History of Chinese Image Culture:Medical Image Volume

1 Introduction.Chinese medicine has a long and rich history,dating back to the classics of the Qin and Han dynasties and extending to the integration of Chinese and Western medicine in the modern era.The vast amount of literature and scholarly works in this field makes it essential to thoroughly study the history of traditional Chinese medicine(TCM)in order to understand its development path throughout the ages and boost innovation based on tradition.This is why the sages emphasized the importance of“classifying the works into different schools and tracing back to their origins”(辨章学术,考镜源流).

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.

A Conversation with Professor Ted Kaptchuk,a Key Architect of Modern TCM in the West

The interview was conducted on November 20th,2022 by Ioannis Solos and Charles Buck.Ted Kaptchuk(泰开阳)is a Professor of Medicine and a Professor of Global Health&Social Medicine at Harvard Medical School.In 1975,he graduated from the Macao Institute of Chinese Medicine,Macao,China.After returning to the West,Ted taught Chinese medicine throughout the States,Europe,Latin America,and Australia.Ted’s book,The Web that Has No Weaver:Understanding Chinese Medicine is a groundbreaking explanation of East Asian medicine that continues to shape the discourse of the Chinese medicine profession in the West and has been translated into 13 languages.In 1990,Ted was recruited in Harvard Medical School to help research Chinese medicine.After encountering high placebo responses in multiple acupuncture clinical trials,Ted decided to switch his career to primarily studying placebo.He has published over 300 peer-reviewed articles.He has been awarded the Lifetime Achievement Award from the Society of Acupuncture Research(2015),the Lifetime Achievement Award from the Society for Interdisciplinary Placebo Studies(2021),and the William Silen Lifetime Achievement Award in Mentoring from Harvard Medical School(2022).

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.

Analysis of standardization development of TCM in Sichuan

Sichuan province is home to rich traditional Chinese medicine(TCM)resources.Recent years have seen unremitting efforts of TCM standardization in the province.By analyzing the measures and existing problems,this paper provides recommendations to boost TCM development through standardization.

My Relationship with TCM

A Spanish businessman becomes a dedicated advocate of traditional Chinese medicine after witnessing its effects in treating his terminally ill young son.MY relationship with traditional Chinese medicine(TCM)-and with China-began in 1988,when I traveled to Beijing with my two-year-old son Joan.He was suffering from an extremely rare disease called leukoencephalopathy,in which the brain is affected,and we wanted to explore treatment possibilities.

Classification research of TCM pulse conditions based on multi-label voice analysis

Objective:To explore the feasibility of remotely obtaining complex information on traditional Chinese medicine(TCM)pulse conditions through voice signals.Methods: We used multi-label pulse conditions as the entry point and modeled and analyzed TCM pulse diagnosis by combining voice analysis and machine learning.Audio features were extracted from voice recordings in the TCM pulse condition dataset.The obtained features were combined with information from tongue and facial diagnoses.A multi-label pulse condition voice classification DNN model was built using 10-fold cross-validation,and the modeling methods were validated using publicly available datasets.Results: The analysis showed that the proposed method achieved an accuracy of 92.59%on the public dataset.The accuracies of the three single-label pulse manifestation models in the test set were 94.27%,96.35%,and 95.39%.The absolute accuracy of the multi-label model was 92.74%.Conclusion: Voice data analysis may serve as a remote adjunct to the TCM diagnostic method for pulse condition assessment.

Research Status of TCM Rehabilitation in Chronic Obstructive Pulmonary Disease (COPD)

This paper mainly analyzes the application status of TCM rehabilitation in chronic obstructive pulmonary disease(COPD),hoping to provide support and help for clinical staff through this study,and promote the further development of COPD rehabilitation program.

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.