Expert Database Research Articles

PECULIARITIES OF SOOT DEPOSITION, TEARING OF CLOTHING AND HUMAN BODY SIMULATOR DURING SHOOTINGS FROM «FORT 12R» AND «AE 790G1» PISTOLS

The study of macroscopic features of the clothing damage or the damage to the human body, the presence of additional factors of a shot on it – is one of the basic methods of analysis used in medical forensics. The appearance of new types of firearms requires the appropriate conduct of experimental research in order to update the theoretical database of experts.
 The purpose of the work to investigate the features of soot deposition, tearing of clothing and a human body simulator when using «FORT 12R» and «AE 790G1» pistols.
 Material and methods. For the study, 120 gelatin blocks were used, which later remained bare or were covered with one of the fabrics: cotton, denim or leatherette. After that, shots were fired from close range, 25 and 50 cm using «FORT 12R» and «AE 790G1» pistols, with subsequent analysis of macroscopic soot deposition around the entrance firing hole and the number of ruptures in clothing or a human body simulator, if the shot was fired at a bare block.
 Results. When analyzing soot deposition, it was reliably established (p<0.0070) or a tendency (p=0.0763, only for leatherette) towards its macroscopic detection when shots were fired at close range in all studied groups of bare blocks and blocks covered with clothing when shots were fired from a distance of 25 cm and the absence of the soot when fired from a distance of 50 cm when fired from both pistols. When comparing the data on the number of ruptures between the «Fort 12R» and «AE 790G1» pistols, reliably (p<0.01-0.05) higher values were found when firing with the «AE 790G1» from a close distance into blocks covered with cotton and denim fabric, when shot from 25 cm into the blocks covered with cotton fabric and a slight tendency (p=0.095) to higher values when shot with the «AE 790G1» from a close distance into the blocks covered with leatherette.
 Conclusions. When using the «FORT 12R» and «AE 790G1» pistols, practically no differences in soot deposition was found, however, when analyzing the number of ruptures in clothing and the human body simulator, higher values were found when using the «AE 790G1» pistol.

Fault logic circuit design of switching power supply based on soft reference circuit module

The basic idea of the circuit fault diagnosis method based on fault logic is to establish a computer expert database system first, connect the computer to the GPIB interface card, and then connect each intelligent instrument through the GPIB standard bus. Through the connection of the tested object adapter and the tested object, a circuit fault expert diagnosis and test platform are formed. Based on the traditional fault simulation model, this paper improves the fault logic circuit of switching power supply, designs the system model of fault simulation, deals with the logic structure and circuit hierarchy respectively, and produces the final output through the logic gate circuit by comparing the results of the fault logic circuit and the fault-free logic circuit. The designed switching power supply fault logic circuit works in the switching state, which has the characteristics of low loss and high energy conversion efficiency. Through the simulation analysis, the output is connected to the comparator, which plays the role of the whole wave. The simulation results are in line with the parameter indicators. The functional test results of the chip show that the function of the module is basically normal, which has practical application value and good portability and can be used as a reference for similar electrical designs.

On Approaches to the Formation of a Regional System of Scientific and Technical Expertise

The general approaches to expertise in the evaluation of scientific and technical projects at the regional level are considered. The regulatory framework for the organization of expertise at the federal, sectoral and regional levels is considered. The normative and methodological documents on the organization of expertise in large organizations that perform large amounts of work on the examination of scientific and technical projects, the experience of organizing expert activities in such organizations are considered. The experience of organizing expert activities in a number of regions has been reviewed. The approaches to the organization of expertise of scientific and technical projects at the regional level are formulated – the specifics of such expertise associated with a limited number of experts in the region, the breadth of the subject matter to be examined, and a relatively small total number of examinations, increasing the unit costs of organizing expert activities in the region, are considered. Approaches are proposed to ensure the high quality of expertise with limited resources for its organization: the appointment of one of the scientific organizations as the organizer of the examination, the creation and maintenance of a database of experts involved in the examination of regional projects, the development of methodological recommendations for the organization of expertise, taking into account regional specifics.

A Model of an Automated System for Evaluating the Quality of Startups in the Field of Software Engineering

This article introduces an automated system for evaluating startups in the field of Software Engineering. It outlines the system's components, including database management, expert assessments, and project viability estimation. The article also presents a conceptual database model and discusses the user interface for assessment calculations. The system is designed to enhance the evaluation of Software Engineering startups and holds potential applications in various scenarios.

Technical research of the Intelligent substation’s secondary maintenance safety measure system

Major changes have taken place during the secondary equipment maintenance and isolation of the intelligent substation and conventional substation in that the physical connection of the conventional cable has become invisible and not to be touched. This change, no undoubtedly, has added the difficulty for the relay protection staff to operate. The secondary maintenance safety measure system of the intelligent substation described in this thesis can automatically complete the writing and implementation of the secondary safety measure sheet by adopting Groovy rules and self-learning fuzzy inference mechanism. The safety measure system expert data base has been continuously improved through manual correction and self-learning technology, which has greatly improved the work efficiency of the site operators, and reduced the impact of the wrong implementation of the secondary safety measures on the normal operation of the power system.

The Occupational Panel for Germany

Abstract The occupational panel for Germany provides a comprehensive database for studying the development of occupations over time. It is based on the IAB Employment History (BeH), which contains all social security notifications that employers have to submit for their employees subject to social security and minor employees. The current version of the panel covers the years 2012–2018. Information on employees is aggregated at the occupational level such as shares by age, qualification or gender. In addition, occupational information from the expert database BERUFENET of the Federal Employment Agency, e.g. the substitution potential or the Digital-Tools Index, is prepared and merged to the occupational panel.

A One Health information database based on standard bibliometric analysis

BackgroundOne Health is an integrated concept of health that aims to optimize the health of humans, animals, plants, and the environment. Identifying research gaps and specific expertise areas is important for understanding the role of One Health in practice. This information on One Health could be used to promote collaboration and research, inspire innovative ideas, and accelerate the translation of evidence-based practices into policies. MethodsWe searched the Scopus database for publications related to One Health between 2012 and 2021 to extract bibliometric information and investigate the possibility of establishing a dedicated expertise database. We matched scholarly information using SciVal to exclude duplicate information and identify scholars’ affiliations, countries, and academic profiles. Individual academic contributions to One Health were evaluated according to their citations, publication impact, publication type, and author contributions. ResultsA total of 8,313 publications on One Health over a ten-year period were identified, with the number of publications increasing over time. The largest number of publications came from the United States and the United Kingdom. These countries also had the highest number of experts and a high level of international collaboration. We identified 500 scholars from 53 countries and 313 affiliations with a median Hirsch Index of 20 who could be included in a One Health expert database. These scientists had a median of six publications on One Health, with topics mostly focusing on dengue and antimicrobial resistance. ConclusionA One Health information database could be used as a third-party reference for scholars, a source to track the ongoing academic progress, and support for active scholars in this field of research.

A COST Action on microbial responses to low pH: Developing links and sharing resources across the academic-industrial divide

We present work of our COST Action on “Understanding and exploiting the impacts of low pH on micro-organisms”. First, we summarise a workshop held at the European Federation of Biotechnology meeting on Microbial Stress Responses (online in 2020) on “Industrial applications of low pH stress on microbial bio-based production”, as an example of an initiative fostering links between pure and applied research. We report the outcomes of a small survey on the challenging topic of developing links between researchers working in academia and industry that show that, while people in different sectors strongly support such links, barriers remain that obstruct this process. We present the thoughts of an expert panel held as part of the workshop above, where people with experience of collaboration between academia and industry shared ideas on how to develop and maintain links. Access to relevant information is essential for research in all sectors, and because of this we have developed, as part of our COST Action goals, two resources for the free use of all researchers with interests in any aspects of microbial responses to low pH. These are (1) a comprehensive database of references in the literature on different aspects of acid stress responses in different bacterial and fungal species, and (2) a database of research expertise across our network. We invite the community of researchers working in this field to take advantage of these resources to identify relevant literature and opportunities for establishing collaborations.

Primary lung carcinoma in children and adolescents: An analysis of the European Cooperative Study Group on Paediatric Rare Tumours (EXPeRT)

BackgroundPrimary lung carcinoma is an exceptionally rare childhood tumour, as per definition of the European Cooperative Study Group on Paediatric Rare Tumours (EXPeRT), with an incidence of 0.1–0.2/1,000,000 per year. Little is known about the clinical characteristics of children with primary lung carcinoma, a gap which this joint analysis of the EXPeRT group aimed to fill. Patients and methodsWe performed a retrospective case series of children (aged 0–18 years) with primary lung carcinoma, as collected through the EXPeRT databases between 2000 and 2021. We recorded relevant clinical characteristics including treatment and outcome. ResultsThirty-eight patients were identified with a median age of 12.8 years at diagnosis (range: 0–17). Mucoepidermoid carcinoma (MEC) was the most frequent entity (n = 20), followed by adenocarcinoma (n = 12), squamous cell carcinoma (n = 4), adenosquamous carcinoma (n = 1) and small-cell lung cancer (n = 1). Patients with MEC presented rarely with lymph node metastases (2/20 cases). Overall, 19/20 patients achieved long-lasting remission by surgical resection only. Patients with other histologies often presented in advanced stages (14/18 TNM stage IV). With multimodal treatment, 3-year overall survival was 52% ± 13%. While all patients with squamous cell carcinoma died, the 12 patients with adenocarcinoma had a 3-year overall survival of 64% ± 15%. ConclusionsPrimary lung carcinomas rarely occur in children. While the outcome of children with MEC is favourable with surgery alone, patients with other histotypes have a poor prognosis, despite aggressive treatment, highlighting the need to develop new strategies for these children, such as mutation-guided treatment.

Constructing marine expert management knowledge graph based on Trellisnet-CRF.

Creating and maintaining a domain-specific database of research institutions, academic experts and scholarly literature is essential to expanding national marine science and technology. Knowledge graphs (KGs) have now been widely used in both industry and academia to address real-world problems. Despite the abundance of generic KGs, there is a vital need to build domain-specific knowledge graphs in the marine sciences domain. In addition, there is still not an effective method for named entity recognition when constructing a knowledge graph, especially when including data from both scientific and social media sources. This article presents a novel marine science domain-based knowledge graph framework. This framework involves capturing marine domain data into KG representations. The proposed approach utilizes various entity information based on marine domain experts to enrich the semantic content of the knowledge graph. To enhance named entity recognition accuracy, we propose a novel TrellisNet-CRF model. Our experiment results demonstrate that the TrellisNet-CRF model reached a 96.99% accuracy rate for marine domain named entity recognition, which outperforms the current state-of-the-art baseline. The effectiveness of the TrellisNet-CRF module was then further demonstrated and confirmed on entity recognition and visualization tasks.

An Enhanced Identification and Classification Algorithm for Plant Leaf Diseases Based on Deep Learning

Identification of plant disease sis a difficult task for farmers. If the diseases are misidentified, there will be a huge crop failure, which threatens the living of farmers. This paper proposes a new tool for farmers to identify plant leaf diseases automatically, and provide solutions to this problem on expert database. Firstly, the infected spots of the leaf are recognized through fuzzy c-means clustering (FCM). Then, the features are extracted by gray-level co-occurrence matrix (COLCM), and classified by progressive neural architecture search (PNAS). The proposed tool was tested on Mendeley Dataset, which covers 2,278 images of healthy leaves, and 2,225 leaves with leaf blights, rust, mealy bugs, and powderily mildew, angular leaf spot, and downy mildew. The experimental results show that our approach outperformed the other methods in accuracy (up to 95%).

Design of Underground Space Intelligent Disaster Prevention System Based on Multisource Data Deep Learning

With the rapid development of national economy, the population to big cities gathered themselves together, and especially the first-line cities, lead to city continuously extend outward, city scale is more and more big, the surface space is completely unable to meet the needs of urban development and transportation, the demand such as life, development, and use of underground space has become the important way of solving the urban development diameter. With the vigorous development of underground space, many disaster problems, such as fire and flood, have also appeared in many places, which have brought huge human and financial losses to the society. In order to solve the problem of disaster in underground space, this paper summarizes the main disasters, and urban underground space analysis of the different degrees of the risk of disasters; the emergency toughness of disaster prevention concept, combined with intelligent technology application in urban underground space disaster warning and decision-making, according to the requirement of the underground space of disaster prevention wisdom, put forward to underground space disaster, disaster prevention expert database, such as multisource data fusion. Deep learning is used to realize the linkage of disaster rescue and recovery, and an intelligent disaster prevention system based on deep learning of multisource data is established. The results show that the urban underground space disasters mainly include fire, explosion, earthquake, flood, toxic, and combustible gas. Combining with the overlapping characteristics of different disasters and the inability to define the boundaries, the theory of emergency resilience disaster prevention provides effective suggestions and measures for the decision-making and treatment of underground space fires. The intelligent comprehensive disaster prevention system of urban underground space is established from the three aspects of predisaster prevention, rescue in disaster, and reconstruction after disaster, so as to realize the full coverage of intelligent disaster prevention in the whole life cycle of underground space and provide data support for integrated decision-making of disaster prevention and reduction. The research results have important guiding significance for digitization, informationization, and intelligent construction of sudden disaster decision-making in underground space.

Multi-Feature Intelligent Oral English Error Correction Based on Few-Shot Learning Technology.

The computer-aided language teaching system is maturing thanks to the advancement of few-shot learning technologies. In order to support teachers and increase students' learning efficiency, more computer-aided language teaching systems are being used in teaching and examinations. This study focuses on a multifeature fusion-based evaluation method for oral English learning, completely evaluating specific grammar, and assisting oral learners in improving their oral pronunciation skills. This study proposes an improved method based on HMM a posteriori probability scoring, in which the only standard reference model is no longer used as the basis for scoring and error determination, and instead, the average level of standard pronunciation in the entire corpus is introduced as another judgment basis, based on a preliminary study of speech recognition technology, scoring methods, and relevant theoretical knowledge of information feedback. This strategy can reduce the score limitation caused by standard pronunciation personal differences, lower the system's misjudgment rate in detecting pronunciation errors, and improve the usefulness of error correction information. An expert opinion database has been created based on the most prevalent forms of spoken pronunciation problems, which can successfully assist learners improve their spoken English level by combining the database's corrected information. Finally, this study proposes an artificial scoring system for spoken English that performs activities such as identification, scoring, error judgment, and correction opinion feedback, among others. Finally, it has been demonstrated through trials and tests that adding the average pronunciation level to the system improves the system's scoring performance and has a certain effect on increasing users' oral pronunciation level.

Research on integrated test technology of relay protection device based on cloud-edge collaboration

The relay protection debugging of smart substation is limited to single unit test. For the intelligent equipment across bays, it can only be tested in batches and one by one, and there is no means to test the integrated system of bus and main transformer with multiple bays. This paper proposes an integrated test technology of intelligent substation based on cloud-edge collaboration. Build an integrated test system based on cloud edge collaboration, which is cross bays, multi intelligent devices and remote vertical connection. Open up the test island of single equipment. Establish equipment signal acquisition and output, multi-protocol access of edge equipment, unified cloud management and process monitoring system. It can realize the value integration of high-quality resources such as substation managers, testers and test expert database. This method improves the testing comprehensiveness, pertinence and timeliness.

A systematic review suggests marked differences in the prevalence of infant-directed vocalization across groups of populations.

Anthropological reports have long suggested that speaking to young children is very infrequent in certain populations (notably farming ones), which is in line with scattered quantitative studies. A systematic review was undertaken to use available literature in order to estimate the extent of population variation. Database searches, expert lists, and citation searches led to the discovery of 29 reports on the frequency of vocalizations directed to infants aged 24 months or younger, based on systematic observations of spontaneous activity in the infant's natural environment lasting at least 30 min in length. Together, these studies provide evidence on 1314 infants growing up in a range of communities (urban, foraging, farming). For populations located outside of North America, the frequency with which vocalization was directed to urban infants was much higher than that for rural infants (including both foraging and farming, medians=12.6 vs. 3.6% of observations contained infant-directed vocalization behaviors). We benchmarked this effect against socio-economic status (SES) variation in the United States, which was much smaller. Infants in high SES American homes were spoken to only slightly more frequently than those in low SES homes (medians=16.4 vs. 15.1% of observations contained infant-directed vocalization behaviors). Although published research represents a biased sample of the world's populations, these results invite further cross-population research to understand the causes and effects of such considerable population group differences.

TeachMe: a web-based teaching system for annotating abdominal lymph nodes

The detection and characterization of lymph nodes through interpreting abdominal medical images are significant for diagnosing and treating colorectal cancer recurrence. However, interpreting abdominal medical images manually is labor-intensive and time-consuming. The related radiology education has many limitations as well. In this context, we seek to build an extensive collection of abdominal medical images with ground truth labels for lymph nodes recognition research and help junior doctors to train their interpretation skills. Therefore, we develop TeachMe, which is a web-based teaching system for annotating abdominal lymph nodes. The system has a three-level annotation-review workflow to construct an expert database of abdominal lymph nodes and a feedback mechanism helping junior doctors to learn the tricks of interpreting abdominal medical images. TeachMe’s functionalities make itself stand out against other platforms. To validate these functionalities, we invite a medical team from Gastrointestinal Surgery Center, West China Hospital, to participate in the data collection workflow and experience the feedback mechanism. With the help of TeachMe, an expert dataset of abdominal lymph nodes has been created and an automated detection model for abdominal lymph nodes with incredible performances has been proposed. Moreover, through three rounds of practicing via TeachMe, our junior doctors’ interpretation skills have been improved.

The values and barriers of Building Information Modeling (BIM) implementation combination evaluation in smart building energy and efficiency

With the continuous increase in the number of buildings, the phenomenon of excessively high energy consumption becomes more and more serious. It is particularly important to reduce the energy consumption during the operation of the whole life cycle of the building. Building Information Modeling (BIM) technology is based on the relevant parameters of construction projects, and uses digital information simulation to establish building information models. It is one of the technical means of building energy consumption analysis and energy saving management, that can be explained as the main reason for stakeholders to guide energy and efficiency changes of the driving factor in buildings. We start co-occurrence statistics and type analysis based on the co-occurrence context analysis, construct the co-occurrence information that affects the values and barriers combination of BIM implementation for smart building energy and efficiency, and chose the expert database of the Green Construction and Intelligent Building Branch (GCIBB) of China Construction Association, that obtained 104 samples through modified snowball sampling, using exploratory factor analysis with factor load linear functions, and combined factor variance contribution rate weights. We created index function of the values and barriers combination of BIM implementation in smart building energy and efficiency, and classified and calculated the comprehensive score of each factor according to the ranking evaluation index, and mapped its practical significance. The results show that the 18 combined evaluation indicators proposed in this paper are suitable for evaluating the three elements of benefit, efficiency and quality of smart buildings, and can achieve continuous optimization of building energy consumption. The constructed multi-factor combination evaluation model, the extracted common factor variance cumulative contribution rate is greater than 80%.

Patients with non-tuberculous mycobacteriosis in clinical practice

Incidence and prevalence of non-tuberculous mycobacteriosis (NTM) are recorded in many countries, but the rates vary. There are no official statistics on the prevalence and incidence of NTMs in the Russian Federation at the moment. The regulatory and expert clinical database for NTMs has not yet been developed. The aim of thе article is to share the experience of the Federal State Scientific Institution “Central Research Institute of Tuberculosis” (FSSI “CRIT”) in working with patients with NTMB over the past 7 years. Methods. The study included 190 patients with a confirmed diagnosis of NTMB who were treated at the FSSI “CRIT” in 2011 – 2018. Before the diagnosis of NTMB, all patients were followed for a long time by various specialists (pulmonologists, general practitioners) for various chronic respiratory diseases. NTMs were isolated from the diagnostic material by the culture method. The material was inoculated into a liquid medium in an automated BACTEC MGIT 960 system and into Levenshtein – Jensen dense medium until the culture growth was obtained. The HTM species was determined using DNA strips GenoType® Mycobacterium CM by Hain Lifescience (Germany). Results. More than half of the examined patients were registered with a phthisiatrician for various clinical forms of pulmonary tuberculosis (disseminated, fibro-cavernous, focal). In 85.6% of cases, no MBT DNA was found in the sputum and skin tests with recombinant tuberculosis antigen (Diaskintest®) were negative. Nevertheless, the changes in the lungs detected on the chest CT and even a single detection of acid-fast microorganisms (AFB) without typing led to an erroneous diagnosis of tuberculosis. In some patients (6.8%), a combination of pulmonary tuberculosis and NTMB was diagnosed. Bronchiectasis and COPD were the most common chronic nonspecific lung diseases. 66.7% of the patients had centrilobular foci characterized by the involvement of not only the bronchial wall but also the pulmonary vessels. NTMB resistance to a wide range of antibacterial drugs was determined in 118 patients (out of 190). The prolonged use of chemotherapy drugs revealed a wide range of drug intolerance. Side effects were handled in various ways: drug replacement (with consideration to the sensitivity), temporary withdrawal, and drug discontinuation. Conclusion. This work reflects the long-term experience of the FSSI “CRIT” staff with patients with NTMs, which can be used in creating national recommendations on NTMs.

How Knowledge Graphs are Changing Data Analytics

Abstract Knowledge graphs are a big trend in the advanced data science world, but aren’t as widely known as they could be. Graph Database Expert Maya Natarajan says that needs to change.

The impact of Covid-19 on Belgian mental health care: A Delphi study among psychosocial health professionals, patients, and informal caretakers

The Covid-19 pandemic is primarily viewed as a threat to physical health, and therefore, biomedical sciences have become an integral part of the public discourse guiding policy decisions. Nonetheless, the pandemic and the measures implemented have an impact on the population’s psychosocial health. The impact of Covid-19 on the psychosocial care system should be thoroughly investigated to mitigate this effect. In this context, the present study was conducted to establish a consensus about the impact of Covid-19 on psychosocial health and the care system in Belgium. Using the Belgian Superior Health Council’s expert database, a three-round Delphi consensus development process was organized with psychosocial experts (i.e., professionals, patients, and informal caregiver representatives). Overall, 113 of the 148 experts who participated in round 1 fully completed round 2 (76% response rate). Consensus (defined as >70% agreement and an interquartile interval (IQR) of no more than 2) was reached in round 2 for all but three statements. Fifty experts responded to round 3 by providing some final nuances, but none of them reaffirmed their positions or added new points to the discussion (44.25% response rate). The most robust agreement (>80%) was found for three statements: the pandemic has increased social inequalities in society, which increase the risk of long-term psychosocial problems; the fear of contamination creates a constant mental strain on the population, wearing people out; and there is a lack of strategic vision about psychosocial care and an underestimation of the importance of psychosocial health in society. Our findings show that experts believe the psychosocial impact of Covid-19 is underappreciated, which has a negative impact on psychosocial care in Belgium. Several unmet needs were identified, but so were helpful resources and barriers. The Delphi study’s overarching conclusion is that the pandemic does not affect society as a whole in the same way or with the same intensity. The experts, thereby, warn that the psychosocial inequalities in society are on the rise.