bluuebunny/crossref_metadata_2025 huggingface dataset:
Special aspects of the participation of persons suffering from mental disorders in criminal proceedings: theoretical and practical aspects
Authors: Lazareva Dariya
Published: July 2021

The paper contains the results of the system analysis of conceptual framework for defining mental disorders in domestic legislation (in criminal law and health care) and the findings show that there is no unified approach to defining this term. The paper studies the matters of special procedural and tactical aspects of the interrogation of persons with mental disorders, as well as instances of testimony recognition of this category of persons as admissible evidence in criminal proceedings. The author has concluded that the participation of persons with mental disorders in criminal proce-?dings has its own features, which are: first, in the absence of a uniform approach to the definition of "mental disorder"; secondly, in the absence of legislative regulation of the procedure for conducting investigative actions with the participation of persons with mental disorders; thirdly, in difficulties in assessing the testimony of this category of persons and recognizing them as admissible evidence in criminal proceedings In order to resolve the existing legislative gaps and consolidate additional procedural guarantees for the participation of persons with mental disorders in criminal proceedings, it is considered necessary to make a number of changes to the provisions of the CPC of Ukraine, in particular in particular to enshrine in the Criminal Procedural Code of Ukraine the definition of the term “mental disorder”, to recognize the testimony of persons with mental disorders as admissible evidence only taking into account forensic psychiatric or complex psychological and psychiatric examination and in combination with other evidence in criminal proceedings; add to the list of persons who cannot be questioned as witnesses.
Nternational standard of proof of «reasonable suspicion» in the prosecutor's implementation of the prosecution function
Authors: Sukhachova Iryna
Published: July 2021

The article provides a comprehensive study of the international standard of proof reasonable suspicion" in the implementation of the prosecutor's function of prosecution. The author found that the standard of proof «reasonable suspicion» is the standard of proof in criminal proceedings, which is used by the prosecutor to make current (intermediate) decisions related to the restriction of individual rights during criminal proceedings (request for application and direct use of means ensuring criminal proceedings, conducting investigative (investigative) and covert investigative (investigative) actions; notification of suspicion) and consists in the established probabilities (assumptions) of a person committing a certain act, which is determined by common sense and objective data that can be verified during criminal proceedings and which would encourage an impartial and reasonable person to take practical action to determine whether such suspicion is justified. Вased on the results of the analysis of the case law of the European Court of Human Rights, the author concludes that the standard of proof «reasonable suspicion» used by the prosecutor in the prosecution in the pre-trial investigation of crimes is characterized by the following criteria: 1) reasonable suspicion to convince an objective observer that the person concerned could have committed an act that falls under the signs of a criminal offense, the responsibility for which at the time of its commission was established by the norms of the Criminal Code; 2) a reasonable suspicion must be based on evidence obtained by the prosecutor, sufficient in its entirety to make a decision, and may not be based on assumptions; 3) the existence of a reasonable suspicion is established by national courts and is reflected in court decisions by stating the content of the suspicion, the circumstances of the case and the evidence that allows a person to be reasonably suspected of committing a criminal offense; 4) the burden of proving the existence of a reasonable suspicion rests with the prosecutor and cannot be transferred to the defense.
Algorithms of actions of law enforcement officers during the investigation of the involvement of minors in illegal activities
Authors: Prylovskyy Volodymyr
Published: July 2021

The scientific article is devoted to covering some aspects of the investigation of the involvement of minors in illegal activities. Algorithms of actions of law enforcement officers in the studied category of criminal proceedings are considered. It is stated that the relevant authorized persons must perform their duties according to the specific circumstances and circumstances. In general, we can say that one of the fundamental scientific categories for planning and organizing a pre-trial investigation is the investigative situation. At the same time, the involvement of minors in illegal activities is characterized by specific circumstances that affect the algo-rithms of actions of the National Police during the detection and investigation of these criminal offenses. It is determined that at the initial stage of the investigation of involvement of minors in illegal ac-tivities, the following typical investigative situations arise: a) the person who involved a minor in illegal activities is known and detained, there is sufficient material and personal evidence reports of suspicion; b) the person who involved the minor in the illegal activity is known, but the material and personal evidence is not sufficient to inform him of the suspicion; c) the person who involved the juvenile in illegal activities is known to have a sufficient amount of material and personal evidence, but the offender is hiding from law enforcement agencies; d) the fact of involvement of the juvenile in illegal activity is revealed, but the identity of the criminal isn't established. The order of actions of the authorized persons according to each of them is defined. In particular, with regard to the first situation, it is stated that it is the simplest. At the moment of violation of entering information into the URPI, the event of involvement of a minor in illegal activities and the manner of committing a criminal offense are obvious. In addition, the identity of the offender and the juvenile involved in illegal activities, as well as the nature of the relationship between them. The circumstances of the juvenile's illegal actions are known, and the offender admits his guilt and gives truthful testimony.
The influence of geopolitics on the national security of the state
Authors: Lazarev Vladyslav , Sydorova Elvira , Paleshko Yana
Published: July 2021

The main task nowadays is to find strategies to ensure a high level of national security. Assurance of the state security must be based on a democratically developed society, guaranteeing of a high level of rights and freedoms of the population, as well as inheritance of European values. National security is intertwined with geopolitics in such terms as state sovereignty, geopolitical role of the country, its geopolitics and geostrategy, the correlation of universal human and national interests, etc. From the scientific point of view, national security of Ukraine can be defined as a system of state and legal as well as social guarantees of living stability and stability of development of the Ukrainian people in general and each citizen in particular, protection of their basic values and legitimate interests, sources of spiritual and material development from possible real and potential, internal and external threats. It is the national security of the state that enables effective management of a transforming society, and this is the most relevant aspect in the current conditions in Ukraine. Political and legal methods and tools, which are based on the basic principles of complexity and systematics, are fundamental factors of national state security. Ukraine's geopolitical location turns it into a kind of geopolitical center - a state that performs communicative functions between two regional systems. Thus, the geopolitical center is a kind of territory of intermediate location, which in its own way is passive, and can be activated at any time in its own interests. The geopolitical component of national security involves preserving sovereignty, territorial integrity and defining its role in the geopolitical space, while ensuring a balance of power through international political, military-political, legal, economic and humanitarian institutions.
Use of special knowledge in the investigation of economic crimes
Authors: Musiyenko Oleh , Pylypenko Mariya , Makitrenko Viktoriya
Published: July 2021

The article considers the issue of using special knowledge in criminal proceedings related to economic crimes. The doctrine on the definition of "special knowledge" is given, the main theoretical aspects of the application of special economic knowledge in the investigation of crimes related to economic activity are established. The requirements of the legislation of Ukraine on the practical use of special knowledge, the procedure for their appointment and the powers of the subjects during the pre-trial investigation and trial are considered. The authors provide statistics on crimes in the field of economic activity for the last calendar year. In addition, a distinction is made between the competence of the investigator, judge and expert in the use of specialized knowledge. The authors also conducted a study of the practice of applying special knowledge by studying court cases and provided some grounds for the appointment of forensic economic expertise and provided examples of issues that are usually posed to experts. Thus, the article states that the use of special knowledge is an integral part of the investigation of almost every crime in the field of economic activity. This provides an opportunity to obtain information, the lack of which may adversely affect the criminal investigation process. In addition, conducting a forensic examination and providing an expert opinion is the most effective and appropriate way to use special knowledge in the investigation of economic crimes.
Efek Green Perceived Value dan Risk terhadap Green Repurchase Intention: Green Trust sebagai Pemediasi pada Pengguna Pertalite di Kota Ternate
Authors: Mada Ardhy La , Hidayanti Ida , Yusuf Ibnu Sina Hi
Published: July 2021

Penelitian ini bertujuan untuk mengetahui pengaruh Green Perceived Value dan Green Perceived Risk terhadap Green Repurchase Intention, dengan Green Trut sebagai variabel mediasi. Penelitian ini merupakan penelitian kuantitatif. Populasi dalam penelitian ini meliputi masyarakat Kota Ternate yang menggunakan BBM jenis Pertalite pada kendaraan bermotor dengan metode pengambilan sampel yaitu Non Probability Sampling dan teknik pengambilan sampel adalah Purposive Sampling. Teknik analisis yang digunakan dalam penelitian ini adalah menggunakan analisis jalur, uji F, uji t dan uji sobel dengan bantuan aplikasi IBM SPSS versi 26. Hasil penelitian ini menunjukkan bahwa: green perceived value berpengaruh positif dan signifikan terhadap green trust dan green repurchase intention, green perceived risk berpengaruh positif dan tidak signifikan terhadap green trust dan green perceived risk berpengaruh negatif dan tidak signifikan green repurchase intention, green trust berpengaruh positif dan signifikan terhadap green repurchase intention, green trust dapat memediasi pengaruh green perceived value ke green repurchase intention, green trust dapat memediasi pengaruh green perceived risk ke green repurchase intention.
Institutional transparency and gender: Analysing the municipalities of the Barcelona Metropolitan Area
Authors: Pano Esther , Magre Jaume , Pons Llorenç , Casajuana Sara
Published: July 2021

Despite the growing interest in transparency policies and, concomitantly, the need to include a gender perspective in analysing the actions of public authorities, the intersection of both fields has attracted limited attention from the research community. The scarce contributions to this topic do not provide a framework that supports an empirical examination of institutional transparency and gender, and therefore, the implementation of these policies remains unexplored. This paper contributes to the debate on institutional transparency and gender perspective by developing an index of gender inclusion in transparency policies based on the information available on official local government websites, and by identifying and analysing factors that drive variations in the municipal councils. The research focuses on the municipalities of the Metropolitan Area of Barcelona (MAB) and includes other cities for comparative purposes. The findings indicate that the number of inhabitants of the municipality, the presence of women in its political bodies and institutional factors, and particularly the volume of the budget, are positively associated with the incorporation of a gender perspective on institutional websites.
Identification of Blood-Based Glycolysis Gene Associated with Alzheimer’s Disease by Integrated Bioinformatics Analysis
Authors: Wang Fang , Xu Chun-Shuang , Chen Wei-Hua , Duan Shi-Wei , Xu Shu-Jun , Dai Jun-Jie , Wang Qin-Wen
Published: July 2021

Background: Alzheimer’s disease (AD) is one of many common neurodegenerative diseases without ideal treatment, but early detection and intervention can prevent the disease progression. Objective: This study aimed to identify AD-related glycolysis gene for AD diagnosis and further investigation by integrated bioinformatics analysis. Methods: 122 subjects were recruited from the affiliated hospitals of Ningbo University between 1 October 2015 and 31 December 2016. Their clinical information and methylation levels of 8 glycolysis genes were assessed. Machine learning algorithms were used to establish an AD prediction model. Receiver operating characteristic curve (AUC) and decision curve analysis (DCA) were used to assess the model. An AD risk factor model was developed by SHapley Additive exPlanations (SHAP) to extract features that had important impacts on AD. Finally, gene expression of AD-related glycolysis genes were validated by AlzData. Results: An AD prediction model was developed using random forest algorithm with the best average ROC_AUC (0.969544). The threshold probability of the model was positive in the range of 0∼0.9875 by DCA. Eight glycolysis genes (GAPDHS, PKLR, PFKFB3, LDHC, DLD, ALDOC, LDHB, HK3) were identified by SHAP. Five of these genes (PFKFB3, DLD, ALDOC, LDHB, LDHC) have significant differences in gene expression between AD and control groups by Alzdata, while three of the genes (HK3, ALDOC, PKLR) are related to the pathogenesis of AD. GAPDHS is involved in the regulatory network of AD risk genes. Conclusion: We identified 8 AD-related glycolysis genes (GAPDHS, PFKFB3, LDHC, HK3, ALDOC, LDHB, PKLR, DLD) as promising candidate biomarkers for early diagnosis of AD by integrated bioinformatics analysis. Machine learning has the advantage in identifying genes.
The Effect of Prolonged Lockdown Due to COVID-19 on Greek Demented Patients of Different Stages and on Their Caregivers
Authors: Tsapanou Angeliki , Zoi Panagiota , Kalligerou Faidra , Blekou Patra , Sakka Paraskevi
Published: July 2021

Background: The impact of the new coronavirus disease (COVID-19) is deteriorating as time passes and the virus keeps spreading, with people with dementia and their caregivers being affected significantly. Objective: The aim of this study was to examine the effect of prolonged isolation because of the COVID-19 pandemic on people with dementia and their caregivers. Methods: Caregivers answered online questions regarding their own physical and psychological burden, and of the person they take care of. Participants were mostly members of online seminars of the Athens Alzheimer’s Association. Questions referred to their own burden, the overall decline of the persons they take care of, and changes in specific domains as well. Further, participants were asked about any changes between the two major lockdown periods. Analysis was performed including the total sample and then, by three different stages of dementia. Results: A total of 339 caregivers took part in the study. Results indicated significant decline, both in an overall aspect of the people with dementia, and in specific domains (mostly communication and mood). Regarding the caregivers, they reported having significantly increased physical and psychological burden, and also, noticing an overall change between the two lockdown periods in their own burden. Analysis by dementia-stage group indicated that significant decline occurred both in the middle-stage and the late-stage group. Conclusion: An urgency for further support of both the people with neurodegenerative disorders and their caregivers is needed. Collaboration among care workers, online programs, governmental support, and day-care centers should be planned to ensure continuity of care for those in need during the pandemic.
A fuzzy-weighted approach for malicious web domain identification
Authors: Wang Zuli , Chiong Raymond , Fan Zongwen
Published: July 2021

Malicious web domains represent a serious threat to online users’ privacy and security, causing monetary loss, theft of private information, and malware attacks, among others. In recent years, machine learning methods have been widely used as prediction models to identify malicious web domains. In this study, we propose a Fuzzy-Weighted Least Squares Support Vector Machine (FW-LS-SVM) model for malicious web domain identification. In our proposed model, a fuzzy-weighted operation is applied to each data sample considering the fact that different samples may have different importance. This fuzzy-weighted operation is also able to alleviate the influence of noise data and improve the model’s robustness by assigning weights to error constraints. For comparison purposes, three commonly used single machine learning classifiers and three widely used ensemble models are included in our experiments, in order to assess the performance of our proposed FW-LS-SVM and its ensemble version. Hyperlink indicators and uniform resource locator-based features are used to train the prediction models. Experimental results show that our proposed approach is highly effective in identifying malicious web domains, outperforming the well-established single and ensemble models being compared.
The study on the anxiety level of college students in emergencies based on fuzzy rough set over two universes
Authors: Zhang Qiang , Zhang Luyu , Sun Bingzhen
Published: July 2021

In 2020, the spread of the COVID-19 epidemic has attracted global attention. As a large-scale group that is receiving higher education, college students also show greater mood swings. How to reduce the psychological harm of anxiety to college students is a problem that needs to be solved urgently. Based on this, this paper proposes an evaluation model for the anxiety level of college students in different regions under the influence of COVID-19. First of all, the general influence index of college student’s anxiety level is obtained by correlation analysis. Secondly, the logical OR of the double quantization variable precision fuzzy set model and the degree fuzzy rough set model is used to establish the evaluation model of the anxiety level of college students under the influence of COVID-19. Finally, used big data, the idea of fuzzy upper and lower approximation, combined with the principle of maximum membership in fuzzy set theory, achieved the quantitative ranking of the anxiety levels of college students in different areas. The research shows that when the accuracy of decision-making is 45%, the anxiety level of the township college students group and the provincial capital or municipality college students group is higher. When the accuracy of decision-making is 65%, the anxiety level of the provincial capital or municipality college students group is higher than others.
End-point prediction of 260 tons basic oxygen furnace (BOF) steelmaking based on WNPSVR and WOA
Authors: Liu Liming , Li Ping , Chu Maoxiang , Gao Chuang
Published: July 2021

Basic oxygen furnace (BOF) steelmaking plays an important role in steelmaking process. Hence, it is necessary to study BOF steelmaking modeling. In this paper, a novel regression algorithm is proposed by using nonparallel support vector regression with weight information (WNPSVR) for the end-point prediction of BOF steelmaking. The weight information is excavated by K-nearest neighbors (KNNs) algorithm. Since the whale optimization algorithm (WOA) has the characteristics of fast convergence speed and a few adjustment parameters, WOA is applied to optimize the parameters in the objective function of WNPSVR. Compared with traditional prediction models, WNPSVR-WOA is not easy to fall into local minimum values and is insensitive to noise. Thus, the prediction and control of molten steel end-point information are more accurate. Experimental results verify the effectiveness and feasibility of the proposed model. Within different error bounds (0.005 wt.% for carbon content model and 10°C for temperature model), the hit rates of carbon content and temperature are 89% and 95%, respectively. Meanwhile, a double hit rate of 85% is achieved. The above results conclude that our WNPSVR-WOA has important reference value for actual BOF application and can improve the steel product quality. Moreover, WNPSVR-WOA can also be used to other fields.
Research on aesthetic models based on neural architecture search
Authors: Zhang Lingyun , Zhang Pingjian
Published: July 2021

Computational aesthetics, which uses computers to learn human aesthetic habits and ultimately replace humans in scoring images, has become a hot topic in recent years due to its wide application. Most of the initial research is to manually extract features and use classifiers such as support vector machines to score images. With the development of deep learning, traditional manual feature extraction methods are gradually replaced by convolutional neural networks to extract more comprehensive features. However, it is a huge challenge to artificially design an aesthetic neural network. Recently, Neural Architecture Search has upsurged to find suitable neural networks for many tasks in deep learning. In this paper, we first attempt to combine Neural Architecture Search with computational aesthetics. We design and apply a customized progressive differentiable architecture search strategy to obtain a light-weighted and efficient aesthetic baseline model. In addition, we simulate the multi-person rating mechanism by outputting the distribution of the aesthetic value of the image, replacing the previous classification scheme of judging the beauty and unbeauty of the image by the threshold value, and propose a self-weighted Earth Mover’s Distance loss to better fit human subjective scoring. Based on the baseline model, we further introduce several strategies including an attention mechanism, the dilated convolution, and adaptive pooling, to enhance the performance. Finally, we design several groups of comparative experiments to demonstrate the effectiveness of our baseline aesthetic model and the introduced improvement strategies.
An extended evidential reasoning approach with confidence interval belief structure
Authors: Wang Jing , Yu Liying
Published: July 2021

In Dempster-Shafer theory, belief structure plays a key role, which provides a useful framework for information representation of uncertain variables. Basic Probability Assignment (BPA) is the most important component, which is difficult to be determined due to the uncertainty of information. Generally, there are two ways to get BPA of evidential theory: One is a subjective judgment of the expert’s experience, Interval Belief Structure (IBS) can solve the fuzziness and uncertainty of expert’s judgment. The other is an objective calculation by sampling existing data, in which BPA is viewed as the point estimate. Therefore, one of the contributions of this paper is that the definitions and theories of Confidential Interval Belief Structure (CIBS) is developed to describe BPA in Dempster-Shafer theory, which can give a range of population parameter values and contain more information to deal with the uncertainty and fuzziness of existing data. And then, based on evidential reasoning rule for counter-intuitive behavior, another contribution of this paper is that the extended evidential reasoning approach with CIBS is proposed to obtain the combined belief degree. The proposed method can be flexibly adjusted by appropriate errors and confidence levels, which is the main advantage. Finally, a case of sustainable operation of Shanghai rail transit system to verify the feasibility of proposed method and great performance of the extended method is shown.
LTHS: A heuristic algorithm based on local two-hop search strategy for influence maximization in social networks
Authors: Qiu Liqing , Yang Zhongqi , Zhu Shiwei , Gu Chunmei , Tian Xiangbo
Published: July 2021

Influence maximization is a classic network optimization problem, which has been widely used in the field of viral marketing. The influence maximization problem aims to find a fixed number of active nodes. After a specific propagation model, the number of active nodes reaches the maximum. However, the existing influence maximization algorithms are overly pursuing certain indicators of efficiency or accuracy, which cannot be well accepted by some researchers. This paper proposes an effective algorithm to balance the accuracy and efficiency of the influence maximization problem called local two-hop search algorithm (LTHS). The core of the proposed algorithm is a node not only be affected by one-hop neighbor nodes, but also by two-hop neighbor nodes. Firstly, this paper selects initial seed nodes according to the characteristics of the node degree. Generally, the high degree of nodes regards as influential nodes. Secondly, this paper proposes a node two-hop influence evaluate function called two-hop diffusion value (THDV), which can evaluate node influence more accurately. Furthermore, in order to seek higher efficiency, this paper proposes a method to reduce the network scale. This paper conducted full experiments on five real-world social network datasets, and compared with other four well-known algorithms. The experimental results show that the LTHS algorithm is better than the comparison algorithms in terms of efficiency and accuracy.
ASU-Net: U-shape adaptive scale network for mass segmentation in mammograms
Authors: Sun Kexin , Xin Yuelan , Ma Yide , Lou Meng , Qi Yunliang , Zhu Jie
Published: July 2021

U-Net is a commonly used deep learning model for mammogram segmentation. Despite outstanding overall performance in segmenting, U-Net still faces from two aspects of challenges: (1) the skip-connections in U-Net have limitations, which may not be able to effectively extract multi-scale features for breast masses with diverse shapes and sizes. (2) U-Net only merges low-level spatial information and high-level semantic information through concatenating, which neglects interdependencies between channels. To address these two problems, we propose the U-shape adaptive scale network (ASU-Net), which contains two modules: adaptive scale module (ASM) and feature refinement module (FRM). In each level of skip-connections, ASM is used to adaptively adjust the receptive fields according to the different scales of the mass, which makes the network adaptively capture multi-scale features. Besides, FRM is employed to allows the decoder to capture channel-wise dependencies, which make the network can selectively emphasize the feature representation of useful channels. Two commonly used mammogram databases including the DDSM-BCRP database and the INbreast database are used to evaluate the segmentation performance of ASU-Net. Finally, ASU-Net obtains the Dice Index (DI) of 91.41% and 93.55% in the DDSM-BCRP database and the INbreast database, respectively.
Circular intuitionistic fuzzy TOPSIS method: pandemic hospital location selection
Authors: Alkan Nurşah , Kahraman Cengiz
Published: July 2021

A circular intuitionistic fuzzy set (CIFS) recently introduced by Atanassov as a new extension of intuitionistic fuzzy sets is represented by a circle whose radius is r and whose center is composed of membership and non-membership degrees. The idea is similar to type-2 fuzzy sets, which are based on the fuzziness of membership functions with a third dimension. CIFSs help us define membership functions more flexibly, taking into account the vagueness in membership and non-membership degrees. In this study, TOPSIS, which is a multi-criteria decision-making (MCDM) method, is developed under circular intuitionistic fuzzy environment. The proposed CIF-TOPSIS method is applied to determine the most appropriate pandemic hospital location selection problem. Then, a sensitivity analysis based on criteria weights and the weight of the decision maker’s optimistic and pessimistic attitudes are conducted to check the robustness of the decisions given by the proposed approach. A comparative analysis with the single-valued intuitionistic fuzzy TOPSIS, Pythagorean fuzzy TOPSIS, picture fuzzy TOPSIS methods is also performed to verify the developed approach and to demonstrate its effectiveness.
A novel integrated AHP and MULTIMOORA method with interval-valued spherical fuzzy sets and single-valued spherical fuzzy sets to prioritize financial ratios for financial accounting fraud detection
Authors: Hamal Serhan , Senvar Ozlem
Published: July 2021

Many studies have used different financial ratios for financial accounting fraud detection. This study focuses on multicriteria decision-making (MCDM) for ranking 25 financial ratios with respect to six criteria in detecting financial accounting fraud using interval-valued spherical fuzzy sets (IVSFS) and single-valued spherical fuzzy sets (SVSFS) to overcome uncertainties in decision-making process of financial analysts. This study proposes an integrated Analytic Hierarchy Process (AHP) and Multi-Objective Optimization by a Ratio Analysis plus the Full Multiplicative Form (MULTIMOORA) approach using IVSFS and SVSFS. Comparative results are obtained and discussed in prioritization of financial ratios for both IVSFS and SVSFS.
Extension of capital budgeting techniques using interval-valued Fermatean fuzzy sets
Authors: Sergi Duygu , Sari Irem Ucal , Senapati Tapan
Published: July 2021

Capital budgeting requires dealing with high uncertainty from the unknown characteristics of cash flow, interest rate, and study period forecasts for future periods. Many fuzzy extensions of capital budgeting techniques have been proposed and used in a wide range of applications to deal with uncertainty. In this paper, a new fuzzy extension of the most used capital budgeting techniques is proposed. In this content, first interval-valued Fermatean fuzzy sets (IVFFSs) are defined, and the algebraic and aggregation operations are determined for interval-valued Fermatean fuzzy (IVFF) numbers. The formulations of IVFF net present value, IVFF equivalent uniform annual value, and IVFF benefit-cost ratio (B/C) methods are generated. To validate the proposed methods, proposed formulations are illustrated with a hypothetical example, and the results are compared with classical fuzzy capital budgeting techniques.
Analysis of traffic accidents with fuzzy and crisp data mining techniques to identify factors affecting injury severity
Authors: Tuncalı Yaman Tutku , Bilgiç Emrah , Fevzi Esen M.
Published: July 2021

Injury severity in motor vehicle traffic accidents is determined by a number of factors including driver, vehicle, and environment. Airbag deployment, vehicle speed, manner of collusion, atmospheric and light conditions, degree of ejection of occupant’s body from the crash, the use of equipment or other forces to re-move occupants from the vehicle, model and type of vehicle have been considered as important risk factors affecting accident severity as well as driver-related conditions such as age, gender, seatbelt use, alcohol and drug involvement. In this study, we aim to identify important variables that contribute to injury severity in the traffic crashes. A contemporary dataset is obtained from National Highway Traffic Safety Administration’s (NHTSA) Fatality Analysis Reporting System (FARS). To identify accident severity groups, we performed different clustering algorithms including fuzzy clustering. We then assessed the important factors affecting injury severity by using classification and regression trees (CRT). The results which would guide car manufacturers, policy makers and insurance companies indicate that the most important factor in defining injury severity is deployment of air-bag, followed by extrication, ejection occurrences, and travel speed and alcohol involvement.
Targeted Therapies for Leigh Syndrome: Systematic Review and Steps Towards a ‘Treatabolome’
Authors: Tiet May Yung , Lin Zhiyuan , Gao Fei , Jennings Matthew James , Horvath Rita
Published: July 2021

Background: Leigh syndrome (LS) is the most frequent paediatric clinical presentation of mitochondrial disease. The clinical phenotype of LS is highly heterogeneous. Though historically the treatment for LS is largely supportive, new treatments are on the horizon. Due to the rarity of LS, large-scale interventional studies are scarce, limiting dissemination of information of therapeutic options to the wider scientific and clinical community. Objective: We conducted a systematic review of pharmacological therapies of LS following the guidelines for FAIR-compliant datasets. Methods: We searched for interventional studies within Clincialtrials.gov and European Clinical trials databases. Randomised controlled trials, observational studies, case reports and case series formed part of a wider MEDLINE search. Results: Of the 1,193 studies initially identified, 157 met our inclusion criteria, of which 104 were carried over into our final analysis. Treatments for LS included very few interventional trials using EPI-743 and cysteamine bitartrate. Wider literature searches identified case series and reports of treatments repleting glutathione stores, reduction of oxidative stress and restoration of oxidative phosphorylation. Conclusions: Though interventional randomised controlled trials have begun for LS, the majority of evidence remains in case reports and case series for a number of treatable genes, encoding cofactors or transporter proteins of the mitochondria. Our findings will form part of the international expert-led Solve-RD efforts to assist clinicians initiating treatments in patients with treatable variants of LS.
Enhancement of sub-thermal neutron flux through cold polyethylene
Authors: Fritz D. , Danon Y. , Liu E.
Published: July 2021

Total thermal neutron cross section measurements serve as the primary means of validation for thermal neutron scattering kernels, an important quantity for neutron transport calculations. In an effort to improve the quality of thermal neutron scattering kernels, researchers at Rensselaer Polytechnic Institute (RPI) designed and constructed a polyethylene based cold moderation system to enhance neutron flux below 10 meV when coupled with the Enhanced Thermal Target (ETT) at the RPI Gaerttner LINAC. The final design yielded an increase in sub-thermal neutron flux (below 10 meV) by a factor of 4.5 for a moderator temperature of 37.5 K relative to the ETT alone. A further increase to a factor of 6 is expected after a minor geometry modification and decrease in polyethylene temperature to 25 K. This novel capability will be used to conduct total thermal neutron cross section measurements from 0.0005–10 eV for different materials including moderator materials.
Postural stability and handicap of dizziness after preoperative vestibular ablation and vestibular prehabilitation in patients undergoing vestibular schwannoma resection
Authors: Fellmann Jonas , Bächinger David , Dalbert Adrian , Röösli Christof , Huber Alexander , Wettstein Vincent G.
Published: July 2021

BACKGROUND: Surgical treatment of vestibular schwannoma (VS) leads to acute ipsilateral vestibular loss if there is residual vestibular function before surgery. To overcome the sequelae of acute ipsilateral vestibular loss and to decrease postoperative recovery time, the concept of preemptive vestibular ablation with gentamicin and vestibular prehabilitation before surgery has been developed (“vestibular prehab”). OBJECTIVE: Studying postural stability during walking and handicap of dizziness over a 1-year follow-up period in VS patients undergoing vestibular prehab before surgical treatment of VS. METHODS: A retrospective review of consecutive patients with a diagnosis of a VS undergoing surgical therapy from June 2012 to March 2018 was performed. All patients were included with documentation of the length of hospital duration and the Dizziness Handicap Inventory (DHI) and the Functional Gait Assessment (FGA) assessed preoperatively as well as 6 weeks and 1 year postoperatively. RESULTS: A total 68 VS patients were included, of which 29 patients received preoperative vestibular ablation by intratympanic injection of gentamicin. Mean VS diameter was 20.2 mm (SD 9.4 mm) and mean age at surgery was 49.6 years (SD 11.5 years). Vestibular prehab had no effect on DHI and FGA at any time point studied. CONCLUSIONS: We found no effect of vestibular prehab on postural stability during walking and on the handicap of dizziness. These findings add to the body of knowledge consisting of conflicting results of vestibular prehab. Therefore, vestibular prehab should be applied only in selected cases in an experimental setting.
Assessing the risks of teenagers’ socialization and exploring the healthy personality development under the backgrounds of internet society and time-space transformation
Authors: Zhang Yushi , Sun Jun , Qiao Shuang , Wang Yijiang
Published: July 2021

BACKGROUND: Under rapid information technology development, teenagers learn knowledge and skills and master social laws through the internet, growing from the initial innocent stage to the socialized stage. The internet will become a social force that has a profound impact on the development of teenagers. OBJECTIVES: The purposes are to assess teenagers’ socialization risks under the time-space transformation of internet society and investigate teenagers’ healthy personality development. METHODS: A questionnaire is designed to survey personality development situations and assess teenagers’ socialization risks. Data collected via the questionnaire survey are counted and analyzed. RESULTS: The background information analysis reveals a balanced gender ratio of survey participants, most of whom are members of the Chinese Communist Youth League. Risks of teenagers’ socialization are assessed from multiple perspectives, including online posts, wording, online identity, pornographic and violent content, and plagiarism. Teenagers’ overall understanding of the internet tends positive. The six dimensions of healthy personality development all score above 3 points, indicating a comprehensive development system of teenagers’ personality. Students under such a development system are newcomers with a healthy personality, who are needed urgently in the development of the times. CONCLUSION: Overall, teenage students tend to be active in their understanding of the internet. Further scientific management of teenagers’ online behaviors can give play to the positive socialization functions of the internet and provide new ideas for the healthy growth and personality development of teenagers.
The role of sustainable urban employee basic medical insurance in health risk appraisal of urban residents
Authors: Zhang Yansheng , Zhao Chunying
Published: July 2021

BACKGROUND: The basic medical insurance for urban workers has always been a hot issue concerned by all walks of life. However, at this stage, there are still some problems in the the basic medical insurance system implement for urban employees in China, such as poor implementation and lack of insurance funds. OBJECTIVE: This study aims at exploring the role of basic medical insurance for urban workers in the health risk assessment of urban residents. METHODS: The data of China Health and Retirement Longitudinal Study (CHARLS) from 2016 to 2018 are used as sample analysis data, and SPSS statistical analysis software is used for statistical data analysis. RESULTS: In the self-assessment of residents’ health status, only the basic medical insurance of urban employees has a significant impact on the health status of residents, while others such as new rural cooperative medical system, free medical care, basic medical insurance for urban residents, and commercial insurance have no significant impact on residents’ health status. The activity of daily living (ADL) score of the experimental group who participate in the basic medical insurance of urban workers is significantly reduced by 181.38%compared with the experimental group without the basic medical insurance. The sample of basic medical insurance for urban employees is significantly correlated with outpatient and inpatient services at 1%level. CONCLUSIONS: The basic medical insurance of urban workers positively functions in the health risk assessment of urban residents. The positive impact of basic medical insurance of urban workers is mainly reflected in the self-evaluation of urban residents’ health status and the utilization of medical and health services.
The influence of employee pressure on the management cost of enterprise technological innovation using mental health education
Authors: Yang Jie , Qin Yuanjian , Moulaert Frank
Published: July 2021

BACKGROUND: Pressure will erode the health and vitality of employees, which undermines the combat effectiveness. OBJECTIVES: It tends to release employees stress and manage the pressure while reducing management costs. METHODS: Relationship between work pressure and innovation cost management is investigated. A model of impact of increased employee stress on human cost is proposed. Job demand control (JDC) model is employed to evaluate mental health status, work pressure, engagement, innovation ability, etc. Sensitivity of technical innovation management cost (TIMC) to various costs is analyzed. RESULTS: All factors of employees’ mental health are negatively correlated with work support, control, and duration. The worse the mental health, the lower the control over work resources. Through analysis of employees’ work stress and engagement variables, significance indicators of each factor are all less than 0.05, indicating a significant correlation between employee pressure and work engagement. TIMC is highly sensitive to the change of labor cost, but not to changes of fixed cost and material cost. CONCLUSIONS: Work demands and engagement were positively correlated, and so were work support and engagement. Enterprises should focus on labor cost, improve organizational and management and innovation efficiency.
Construction of the evaluation system of snowboarders’ motor function and the risk evaluation of health sports
Authors: Nian Qing , Liu Junyi
Published: July 2021

BACKGROUND: The athletes’ physical function level is correlated with the sports risk. OBJECTIVE: The study aims to evaluate the function level and seek the relationship between sports risk and physical function level. METHODS: The Analytic Hierarchy Process (AHP) is introduced, the evaluation index, index weight, and evaluation standards are determined, so as to construct the evaluation system of physical function of disabled snowboarder. The health sports risk evaluation system based on human natural and social attributes is constructed. The different functional indexes and the overall physical function level of the research object are analysed statistically to reveal the relationship between sports risk and physical function level. RESULTS: The physical functions of most subjects are “relatively good” and a few are “excellent”. For the cardiovascular risk, pulse wave velocity (PWV) has the highest correlation with the overall score of physical function for both male and female athletes. Overall, different sensitivity indexes are greatly correlated to the physical function level. CONCLUSIONS: This study provides theoretical and data support for grasping the level of athlete’ physical function and exploring the relationship between sports risk and physical function level.
Health risk appraisal of rural population in poverty
Authors: Kang Le , Marlene Rodrigues
Published: July 2021

BACKGROUND: Health is no longer simply limited to the absence of pain but a state of physical and psychological integrity that adapts to the social environment. People’s understanding of poverty has expanded from simply emphasizing income and consumption to many fields. OBJECTIVE: The research is made to understand the relationship between poverty and health effectively, indeed find out the factors affecting the health of the rural population in poverty, and establish a sound health risk assessment system for the rural population in poverty. METHODS: The influencing factors of the rural population in poverty’s health are analyzed by using the psychology, economics, statistics, and behavior science, the health risk management model of the rural population in poverty is proposed, and the effectiveness of the method proposed is further verified combined with specific case data. RESULTS: The rural population in poverty have higher health needs, but because of the cost, it is difficult to get effective treatment, and the prevalence rate and chronic diseases are also significantly higher than those of non-poor people. When the proportion of health expenditure in the total family income exceeds 20%, there will be excessive health economic risk; 69.3%of the families in poverty use the means of borrowing, and the significant characteristic of the intensity of negative health events in families in poverty is that they have more expenditure and income. CONCLUSION: The health risk management model of the rural population in poverty proposed can comprehensively analyze the risk problems faced by the rural population in poverty, which can create a theoretical basis for the practice mode of health risk management of rural families in poverty.
Usage of deep learning in environmental health risk assessment
Authors: Qin Shengyang , Duan Xinxing , Kimm Paul
Published: July 2021

BACKGROUND: Environmental pollution caused by economic development poses a serious threat to human health. How to prevent and control environmental health risks has received extensive attention. OBJECTIVE: It is to explore the application of deep learning methods in assessment and prediction of environmental health risks. METHODS: A time series prediction model is constructed based on the generalized additive model (GAM) and a long short-term memory neural network (LSTM) prediction model is established based on deep learning, and they are combined into a hybrid model. The three models are used to predict and analyse the number of hospitalizations of the three diseases under environmental pollutants. RESULTS: Compared with the GAM and LSTM models, the mean absolute percentage error (MAPE) value of the hybrid model to predict the number of hospitalized patients with respiratory diseases decreases by 2.3%and 1.9%, respectively. CONCLUSION: The hybrid prediction model proposed can better predict the number of hospitalized patients with systemic diseases under the influence of environmental pollutants, and provide an important reference for the application of deep learning neural networks in risk assessment of environmental health.