Database Technology Research Articles

Advances in digital twins technology of human skeletal muscle

The human skeletal muscle drives skeletal movement through contraction. Embedding its functional information into the human morphological framework and constructing a digital twin of skeletal muscle for simulating physical and physiological functions of skeletal muscle are of great significance for the study of "virtual physiological humans". Based on relevant literature both domestically and internationally, this paper firstly summarizes the technical framework for constructing skeletal muscle digital twins, and then provides a review from five aspects including skeletal muscle digital twins modeling technology, skeletal muscle data collection technology, simulation analysis technology, simulation platform and human medical image database. On this basis, it is pointed out that further research is needed in areas such as skeletal muscle model generalization, accuracy improvement, and model coupling. The methods and means of constructing skeletal muscle digital twins summarized in the paper are expected to provide reference for researchers in this field, and the development direction pointed out can serve as the next focus of research.

Technology diffusion and uneven development

We propose a conceptualisation of the process of technology adoption that takes into account the uneven relative costs of technology implementation, especially country differences in wage levels. The novelties and contributions of our approach are the following. First, we introduce a dynamic macroeconomic model of technology diffusion, which is the first to directly account for the difference in factor cost proportions in an endogenous cross-country setting. Second, we utilise the Cross-country Historical Adoption of Technology (CHAT) and Penn World Table databases to calibrate the model using non-linear approximation across countries and technologies, which explains about 50% of the variability in technology density. Third, the results of the calibrated model offer a new insight into the dynamics and patterns of technology diffusion of differently developed countries, offering both an approximation of the average technology adoption across differently developed countries over time and an approximation of the relative technology density adoption curves, which are country specific generalisations of the logistic curves and depend highly on the general level of development and wage levels.

Diagnosis and Treatment Knowledge Graph Modeling Application Based on Chinese Medical Records

In this study, a knowledge graph of Chinese medical record data was constructed based on graph database technology. An entity extraction method based on natural language processing, disambiguation, and reorganization for Chinese medical records is proposed, and dictionaries of drugs and treatment plans are constructed. Examples of applications of the knowledge graph in diagnosis and treatment prediction are given. Experimentally, it is found that the knowledge graph based on the graph database is 116.7% faster than the traditional database in complex relational queries.

Contemporary Technologies for Promoting Safe Cities: The Case of Al-Salheya Compound in Iraq

After the events of 9/11, the world's perception of security in the cities has changed. Management and security have become an important issue of contemporary cities. In fact, almost all cities of the world seek to have their cities safe from terrorism, and threats of vice. To reach this goal, the contemporary cities use modern techniques and technologiesin various fields, installed by individuals, societies, as well as institutions. Installing security and civil technologies in public places and vital sites is one of the most important ways to improve safety, security, and civil control. The hardware, software, and qualified human element, with the presence of the latest auxiliary and supportive mechanisms, contribute significantly to achieving safety of the cities. The research examinessecurity technologies implemented in the Al-Salheya residential compound in Iraq to enhance safety of the city. It therefore carries out a comprehensive review of modern security technologies in contemporary cities. It employs a qualitative approach as a research methodology. Data is collected from surveys, observation, questionnaires and interviews. It concludes a variety of security and civil technologies at the levels of monitoring, verification, reaction, central database, and support technologies compatible with the needs of Al-Salheya compound in Iraq.

A Perspective on Materials, Technology and Property Data Base Development for Aero Gas Turbine Discs

Modern aero engine concepts set very high technology standards for the component design, as they operate in an increasingly hostile thermo-mechanical environment. With rapid advancement in material and manufacturing processes there is a constant demand to upgrade mechanical technologies and design analysis methods. The design complexity of aero engines can be best appreciated by its demands to confirm to stringent design and operational specifications with minimum weight. The complexity of loads and constraints on weight and space has led to search of new materials and mechanical technologies which will play a key role in design of discs in future. The paper presents a perspective on integrated approach to material selection, current material & structural technologies and challenges of material property data base for application to gas turbine engines, with specific focus on rotating discs

Frozen embryo transfer outcomes decline with increasing female body mass index in female but not male factor infertility: analysis of 56,564 euploid blastocyst transfers

ObjectiveTo evaluate the association of body mass index (BMI) with cycle outcomes after euploid frozen blastocyst transfer. DesignRetrospective cohort study. SettingNot applicable. Patient(s)A total of 56,564 first single autologous euploid frozen embryo transfers (FET) from the 2016-2019 Society for Assisted Reproductive Technology database were analyzed by BMI and by World Health Organization BMI cohorts. Sub-analyses were performed on cycles among patients with a sole diagnosis of polycystic ovary syndrome (PCOS) (n = 4,626) and among patients with only male factor (n = 10,854). Intervention(s)None. Main outcome measure(s)Clinical pregnancy, pregnancy loss, and live birth. Results(s): Success rates and adjusted odds ratios (aORs) with 95% confidence intervals (CIs) for all outcomes were most favorable among those with normal BMI and progressively worsened with increasing BMI. These trends persisted among patients with PCOS for clinical pregnancy (aOR 0.99, 95% CI 0.98-0.997, p 0.003), pregnancy loss (aOR 1.02, 95% CI 1.01-1.04, p 0.01), and live birth (aOR 0.98, 95% CI 0.97-0.99, p <0.001), but not among patients with male factor only for clinical pregnancy (aOR 1.00, 95% CI 0.99-1.01, p 0.425), pregnancy loss (aOR 1.01, 95% CI 0.99-1.03, p 0.07), or live birth (aOR 0.99, 95% CI 0.98-1.00, p 0.08). Conclusion(s): In the largest cohort to date, increasing BMI was associated with decreased pregnancy and live birth and increased pregnancy loss following euploid FET among the entire cohort and among patients with a sole diagnosis of PCOS; however, these results were attenuated among patients with a sole diagnosis of male factor infertility, suggesting that associated female infertility diagnoses and not BMI alone may underly this trend.

Employing Data Mining Techniques and Machine Learning Models in Classification of Students’ Academic Performance

The study deals with the use of data mining techniques to build a classification model to predict students' academic performance. The research indicates that the use of machine learning models and data mining methods can reveal hidden patterns and relationships in big data, making them indispensable tools in the field of education analysis. Special emphasis was placed on the use of algorithms such as decision trees. The study includes an analysis of factors that affect students' academic performance such as previous academic achievement in educational activities, as well as social and psychological factors. Classification models were applied using the KNIME platform and the WEKA tool to analyse students' performance in three courses: database technology, artificial intelligence, and image processing in the ICT degree program. The results showed that the use of decision trees can effectively classify students' performance and determine the success and failure rate. The cruel outright mistakes, RMS error and relative supreme mistake all showed 0% whereas the kappa esteem got from the analysis extended between 0.991 and 1.00 which significantly concurs with most statistical values.

Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation.

In the unsupervised open set domain adaptation (UOSDA), the target domain contains unknown classes that are not observed in the source domain. Researchers in this area aim to train a classifier to accurately: 1) recognize unknown target data (data with unknown classes) and 2) classify other target data. To achieve this aim, a previous study has proven an upper bound of the target-domain risk, and the open set difference, as an important term in the upper bound, is used to measure the risk on unknown target data. By minimizing the upper bound, a shallow classifier can be trained to achieve the aim. However, if the classifier is very flexible [e.g., deep neural networks (DNNs)], the open set difference will converge to a negative value when minimizing the upper bound, which causes an issue where most target data are recognized as unknown data. To address this issue, we propose a new upper bound of target-domain risk for UOSDA, which includes four terms: source-domain risk, ϵ -open set difference ( ∆ϵ ), distributional discrepancy between domains, and a constant. Compared with the open set difference, ∆ϵ is more robust against the issue when it is being minimized, and thus we are able to use very flexible classifiers (i.e., DNNs). Then, we propose a new principle-guided deep UOSDA method that trains DNNs via minimizing the new upper bound. Specifically, source-domain risk and ∆ϵ are minimized by gradient descent, and the distributional discrepancy is minimized via a novel open set conditional adversarial training strategy. Finally, compared with the existing shallow and deep UOSDA methods, our method shows the state-of-the-art performance on several benchmark datasets, including digit recognition [modified National Institute of Standards and Technology database (MNIST), the Street View House Number (SVHN), U.S. Postal Service (USPS)], object recognition (Office-31, Office-Home), and face recognition [pose, illumination, and expression (PIE)].

Effect of Traditional Chinese Medicine combined with Western Medicine on blood lipid levels and inflammatory factors in patients with angina pectoris in coronary heart disease identified as intermingled phlegm and blood stasis syndrome: a network Meta-analysis.

To evaluate the clinical efficacy of Traditional Chinese Medicine prescriptions for resolving phlegm in the treatment of angina pectoris of phlegm-stasis coronary heart disease by a network Meta-analysis. Randomized controlled trials (RCTs) on clinical efficacy of CHD angina pectoris with interaction of phlegm and blood stasis were searched in PubMed, Springer, the Cochrane Library and Chinese-language databases China National Knowledge Infrastructure, China Science and Technology Journal Database, and Wanfang Data from their inception to December 2021. Literature was screened and literature bias risk was assessed by RevMan5.4 software. The overall response rate, the duration of angina attack, the levels of serum lipids such as total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), and high density lipoprotein cholesterol (HDL-C), and expression of hypersensitive C-reactive protein (hs-CRP) were selected as outcome indicators for network Meta-analysis and mapped using Stata15.1 software. Totally, 26 RCTs were included, involving 2098 participants. There were 6 TCM formulas with the effects of dispelling phlegm and removing blood stasis. Taking conventional Western Medicine as the common intervention measures, the results showed that the overall response improvement rate from high to low was displayed as modified Xiaoxianxiong decoction (, MXD), Danlou tablet (, DT), modified Gualou Xiebai Banxia decoction (, MGXBD), modified Wendan decoction (, MWD), modified Zhishi Xiebai Guizhi decoction (, MZXGD), and modified Erchen decoction (, MED). The sequence of angina attack duration improvement from high to low was MZXGD, MGXBD, DT, MWD, MXD. The sequence of TC improvement from high to low was MZXGD, MED, DT, and MGXBD. Sequence of improving TG from high to low was MED, MZXGD, MGXBD, and DT. For LDL-C improvement, the effect from good to poor was MZXGD, MGXBD, DT, and MED. With regard to HDL-C improvement, the effect was ranked as MED, MZXGD, MGXBD, and DT from good to poor. hs-CRP expression from high to low was MZXGD, MXD, MED, MWD, and MGXBD. TCM formula with the effects of dispelling phlegm and removing blood stasis combined with conventional Western Medicine has obvious advantages in treating CHD angina pectoris with interaction of phlegm and blood stasis. MZXGD has great potential in increasing the overall response rate, reducing Duration of angina attack improving blood lipids, and reducing inflammatory factors. However, due to the limitations of extant studies, the conclusions of this study need to be confirmed by numerous reasonably-designed RCTs.

Technology Enabled Intelligent Solution in Human Resource Management for Smart Cities

The foundation of smart cities is based on an autonomous and decentralized architecture, which consists of sophisticated information and communication technologies (ICT) in convergence with technology enabled solution to improve the business management process in industry 4.0. This study tends to examine the adoption of blockchain technologies (DLT) in the human resource management (HRM) of organizations in building solutions for IOT (Internet of things) smart cities. The current study explores a unique set of factors selected from the extensive literature and acquired information from fifteen experts having significant experience of blockchain technology in their respective organizations. An integrated fuzzy analytic hierarchy process (F-AHP) is applied to prioritize the identified success factors. Further, the modified decision-making trial and evaluation laboratory (M-DEMATEL) method is utilized to represent the complicated causal relationships among different sub-factors on blockchain-HRM integration. The findings show the application of blockchain will foster a paradigm change in IOT based smart communities, where recruiters verify the candidate credentials including education, skills, and work experience. The payroll managers would determine the more effective way to make work less complex and moderate, enabling timelier payments to global employees. Furthermore, DLT would enhance the employee learning records and update the real-time information in HRM database technologies. Thus, providing a detailed guide for future Industry 4.0 developers about how blockchain can improve the next generation of industrial applications. The developed method can help the decision-makers and provide a foundational view to examine the benefits of implementing blockchain technology in the HRM setting of an organization before they choose to integrate in order to enhance Industry 4.0 technologies. This research will be a novel attempt to synthesize the key factors and subfactors about technology enabled solution within the intelligent HRM process, shedding light to rethink HRM strategies to incorporate blockchain technology in organizations.

Integrated Management Technology of Geophysics and Geology Data

This paper describes the three main development stages of geophysics and geology data management, analyzes the business and data characteristics faced at each stage, discusses the development trend of integrated geophysical and geological data management with the development of information technology and database technology; analyzes the challenges faced by geophysical and geological data in terms of data collection, data storage and data application, explains the sources and causes of the problems. The concept of integrated management of geophysical and geological data is proposed, based on the data governance framework system, the integrated data management platform is built, covering the construction of data source collection, efficient data services and comprehensive data management, so as to realize unified, efficient and secure data collection, management and application services, the content and characteristics of the main data management strategy of geophysical and geological data are analyzed, and on the basis of the above discussion. Finally, it explores and practices the application of this technology system outside the oil and gas field, proposes the application support scheme of integrated geophysical and geological data management for business, and further demonstrates the value and significance of the wide business application of integrated data management.

A Comparative Study of Relasional and NoSQL database for Big Data Analytics

The Database technology suite is rapidly evolving and consistently answering solutions user needs, one of which is the ability of the database to accommodate one piece of information quite a lot, the ability of the Database to accommodate data must be balanced together speed in loading the information needed by the user. In these fast-paced times today’s sophisticated information technology forces us to be able to serve data requests as well as process data quickly and efficiently, but if a system has accommodated too much a lot of data will certainly experience a time constraint in processing the data. The research method used is the type of library research (Library Research). The data obtained is sourced from the literature. NoSQL database discussion literature searched using keywords: SQL, NoSQL, databases from various publication databases. The results of the study are comparisons between relational databases and NoSQL involving factors&#x0D; Such as data models, scalability, data flexibility, and query and analytics capabilities. Databases Relational is more suitable for structured data and strict consistency, whereas database NoSQL is better suited for unstructured data and prioritizes scalability and flexibility.

IFLA Agenda of Green and Sustainable Library: a Literature Study

Green library sustainability initiatives include all the wise decisions that must be made to maintain the balance between the library system and the underlying environmental system. The green library philosophy advocates a careful understanding of the environment and the creation of methods for managing library facilities and programs while keeping environmental concerns in mind. This study aims to build the understanding and perception of librarians about the concept of green libraries for environmental sustainability; and analyze the practices adopted by libraries according to the IFLA checklists in libraries in several locations. This research method uses literature search in the Library, Information Science &amp; Technology Abstracts database. A search was conducted on the google scholar, focusing on documents published between 2010 and 2020 using the search terms “green libraries” “sustainable/sustainable/eco-friendly” “IFLA checklist” revealing 22 results. The title of each reference returned is checked for relevance and appropriateness. The results show that the concept of green and sustainable logistics has received increasing attention and consideration from the government sector, academia, practitioners, and international organizations. The result of a systematic investigation that combines conference proceedings, reports, and valuable books in the field of green libraries and is expected to illustrate a more comprehensive knowledge map for future research on Green and Sustainable Libraries.

The Effect of Preoperative Imaging on the Negative Appendicectomy Rate.

Background Appendicitis is one of the most common causes of acute abdominal pain and appendicectomy is one of the most frequently performed surgical procedures. The proliferation of radiological imaging has reduced the number of patients who have a normal appendix removed, i.e., a negative appendicectomy. We aimed to assess the effect of preoperative imaging on the negative appendicectomy rate (NAR). Methodology All emergency appendicectomies performed at a district general hospital in the United Kingdom over two separate one-year periods were retrospectively analysed using emergency theatre log books. The timeframes were chosen based on the introduction of a diagnostic pathway to reduce the number of appendicectomies performed on patients later found not to have appendicitis or alternative abnormality, i.e., a negative appendicectomy. This pathway involved a greater emphasis placed on preoperative imaging (CT or ultrasound) for patients with suspected appendicitis. The study excluded any patients who were found to have an alternative pathology during surgery. Information technology databases were used to collect data on patient demographics, date of surgery, histology, and any preoperative imaging that was performed. All histological findings showing acutely inflamed appendices and those positive for malignancy were categorised as positive, whereas all other findings were categorised as negative. Results During our initial data collection period (April 2018 to April 2019), we collected data on 207 patients who underwent an appendicectomy. The NAR was 17%. During our subsequent data collection period (August 2020 to August 2021), we collected data on 184 patients. The NAR was 16%. In our adult population, the NAR decreased from 13% to 9%. Discussion At first glance, the NAR does not seem to have improved. On closer look, all patients over the age of 21 years in our re-audit underwent pr-operative CT, and there was a reduction in the NAR in these patients. The issue arises with younger patients, in whom justifying the radiation associated with a CT scan may be difficult. Although ultrasound does not carry the same radiation risk, previous audits at our trust have that shown its sensitivity and specificity for appendicitis is approximately 60%. We may have to explore alternative imaging modalities such as MRI in the paediatric population or accept the higher NAR.

Risk factors and prevalence of cognitive impairment in maintenance haemodialysis patients: A systematic review and meta-analysis of observational studies.

To systematically identify the risk factors for cognitive impairment in maintenance haemodialysis patients and to assess its prevalence in included studies. Systematic review and meta-analysis about observational studies. Systematic search of seven databases, including PubMed, Web of Science, Scope, Wanfang Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database and Weipu Chinese Science and Technology Journal Database, from inception until October 2021. Observational studies reporting the risk factors for cognitive impairment in maintenance haemodialysis patients in English and Chinese language were included. Meta-analysis was performed to identify risk factors and prevalence of cognitive impairment in maintenance haemodialysis patients with STATA 15.0 software. Overall, 37 eligible studies encompassing 129,849 cases were included. The risk factors with statistical significance after meta-analysis were older age, female sex, fewer years of education, hypertension, diabetes, cerebrovascular accident, multiple comorbid conditions, systolic blood pressure variability, arterial stiffness and low haemoglobin and albumin level. The overall prevalence of cognitive impairment in maintenance haemodialysis patients was 49.1%. The current analysis indicated a high prevalence of cognitive impairment in maintenance haemodialysis patients. Eleven risk factors for cognitive impairment in maintenance haemodialysis patients were identified, among which more attention should be paid to modifiable factors such as cardiovascular disease risk factors and specific kidney and dialysis-related factors. This paper provides an updated estimate of the pooled prevalence of cognitive impairment in maintenance haemodialysis patients. Identification of risk factors associated with cognitive impairment may assist in developing targeted prevention strategies for maintenance haemodialysis patients at high risk. This study was a systematic review completed by the authors in accordance with relevant guidelines and processes and did not include the participation of patients, service users, caregivers or the general public.

Accurate prediction of isothermal gas chromatographic Kováts retention indices

We describe a freely available web server called Retention Index Predictor (RIpred) (https://ripred.ca) that rapidly and accurately predicts Gas Chromatographic Kováts Retention Indices (RI) using SMILES strings as chemical structure input. RIpred performs RI prediction for three different stationary phases (semi-standard non-polar (SSNP), standard non-polar (SNP), and standard polar (SP)) for both derivatized (trimethylsilyl (TMS) and tert‑butyldimethylsilyl (TBDMS) derivatized) and underivatized (base compound) forms of GC-amenable structures. RIpred was developed to address the need for freely available, fast, highly accurate RI predictions for a wide range of derivatized and underivatized chemicals for all common GC stationary phases. RIpred was trained using a Graph Neural Network (GNN) that used compound structures, their extracted features (mostly atom-level features) and the GC-RI data from the National Institute of Standards and Technology databases (NIST 17 and NIST 20). We curated this NIST 17 and NIST 20 GC-RI data, which is available for all three stationary phases, to create appropriate inputs (molecular graphs in this case) needed to enhance our model performance. The performance of different RIpred predictive models was evaluated using 10-fold cross validation (CV). The best performing RIpred models were identified and when tested on hold-out test sets from all stationary phases, achieved a Mean Absolute Error (MAE) of <73 RI units (SSNP: 16.5–29.5, SNP: 38.5–45.9, SP: 46.52–72.53). The Mean Absolute Percentage Error (MAPE) of these models were typically within 3% (SSNP: 0.78–1.62%, SNP: 1.87–2.88%, SP: 2.34–4.05%). When compared to the best performing model by Qu et al., 2021, RIpred performed similarly (MAE of 16.57 RI units [RIpred] vs. 16.84 RI units [Qu et al., 2021 predictor] for derivatized compounds). RIpred also includes ∼5 million predicted RI values for all GC-amenable compounds (∼57,000) in the Human Metabolome Database HMDB 5.0 (Wishart et al., 2022).

Phytochemical Screening of Rhizome Extract of Curcuma longa Linn. Grown in Bangladesh through GC-MS and its Bioactivities

The methanolic extract of Curcuma longa L. rhizome was subjected to Gas Chromatography-Mass Spectrometric (GC-MS) analysis. The chromatographic investigation of the extract showed 27 constituents of which 19 compounds were newly found from C. longa. Here, the peaks obtained in the total ion chromatogram were compared with the National Institute of Standards and Technology (NIST) database for identification of the constituents. The most plentiful component was 9-octadecenamide (Z) (5.93%). The component present in the lowest amount was 4-hydroxy-3-methoxy benzoic acid methyl ester (0.08%). The rhizome extract of C. longa and its six fractions (F1-F6) obtained through vacuum liquid chromatography (VLC) were also investigated for antioxidant, cytotoxic and antimicrobial activities.The crude extract and its fractions (F4-F6) exhibited strong antioxidant activity having IC50 values of 19.85, 18.41, 26.72 and 16.79 μg/ml, respectively compared to the standards butylated hydroxyl anisole (IC50 = 11.42 μg/ml) and ascorbic acid (IC50 = 9.01 μg/ml). Strong cytotoxicity was found in crude extract (LC50 = 1.81 μg/ml) and fractions F4 (LC50 = 2.4 μg/ml), F5 (LC50 = 2.5 μg/ml) and F6 (LC50 = 2.3 μg/ml) when compared to the standard, tamoxifen (LC50 = 0.13 μg/ml). Fractions F1-F3 displayed mild to moderate antibacterial activity against Bacillus megaterium, Staphylococcus aureus and Pseudomonas aeruginosa in comparison with the standard, Kanamycin. The compounds obtained through GC-MS may explain the above activities. The present results showed the prospect of this medicinal plant to explore further to determine the bioactive components. Dhaka Univ. J. Pharm. Sci. 22(1): 11-20, 2023 (June)

Digital Sustainability of Intangible Cultural Heritage: The Example of the “Wu Leno” Weaving Technique in Suzhou, China

Digital technology can be used to enable the living preservation and heritage innovation of the intangible cultural heritage of Chinese traditional textile skills for sustainable development. Taking the “Wu Leno” weaving technique in Suzhou as the research object, we first elaborated on the origin, development, and evolution of “Wu Leno” through documentary research and case study methods. Second, considering the inheritance of the Leno weaving technique, we used digital technology to establish the pattern. The study showed that a digital database and virtual reality technology can be used to build a loom model and create a simulation library to realize innovative applications and interactive experiences in apparel design. The study also showed that the digital database and the interactive technology of virtual reality can provide practical pathways and explore experiences for the preservation, inheritance, cross-border communication, and sustainable innovation development of Suzhou “Wu Leno” weaving techniques in modern times.

Information Technologies in Databases: Role and Application Features

This article explores the use of information technology in databases. It describes the role of information technology in ensuring the efficient management and storage of data, ensuring the integrity and security of information, supporting analytics and decision making, automating processes and integrating with other information systems. The article discusses the unique features of the use of information technology in databases and their importance for modern business.

Research on optimal path planning technology for vehicle positioning and navigation system

Abstract Intelligent Transportation System (ITS) is created in the context of the full development and progress of contemporary science and technology, aiming to help people make the best choice, drive the best vehicle, and control the best road network traffic. Intelligent vehicle positioning and navigation system is a high-tech integrated system that applies automatic vehicle positioning technology, geographic information system and database technology, computer technology, multimedia technology, and modern communication technology. In this paper, based on the research of GPS and GIS technology, by analyzing and comparing the advantages and disadvantages of different optimal path planning algorithms, we propose to optimize the A* algorithm by using the minimum heap sorting method for nodes and combining the twoway search and hierarchical search strategies to complete the improvement of the A* algorithm. The experimental results show that the path search speed of the improved algorithm has been significantly improved and the path design optimization is obvious. The improvement algorithm proposed in this paper is feasible and reasonable, which is good for upgrading the in-vehicle navigation system and relieving urban traffic congestion.