bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Impacts of “Infodemic” on Social Well-Being and Health Preparedness of Indian Communities during COVID-19 Pandemic through WhatsApp groups study
Authors: Azim Syeda Saadia , Dey Dipayan , roy arindam
Published: July 2020

The present study is an attempt to understand the propagation of health-related fake news in India during COVID-19 pandemic in diversely distributed WhatsApp groups comprising uneven groups of members. Ten different WhatsApp groups were selected covering demographic and socio-economic profile and ten most important health-related fake news were studied. Different fake news circulation paths like forward, react, multi-forward, reference etc. were analyzed for different groups. It was observed that older generations (boomers) were more susceptible towards fake news and they tended to distribute the fake news in different groups. Male boomers actively circulate pseudo-science information whereas female boomers distribute faith-based information in the WhatsApp group. It was found that the Gen X as well as Millennials played a role as the first recipients or first responders but primarily most of the forwards were attributed to the Boomers of both genders. Levels of education, social media influence or ignorance, technology access, age, gender and understanding played a major role in the distribution and propagation of fake information during times of COVID. It can be also inferred that easy availability of data and devices, lack of understanding of the game of social media and unscientific baggage of age old beliefs were some factors for over -dependence and reliance on fake news.
Regeneration Technique of Bamboo Species through Nodal Segments: A Review
Authors: Suwal Meena Maiya , Lamichhane Janardan , Gauchan Dhurva Prasad
Published: July 2020

Micropropagation is an alternative technique to propagate at large scale plants to meet global plant demand. Various researchers have worked on the micropropagation technique to regenerate bamboo species by using nodal segments from years. Contamination, browning, necrosis, and acclimatization with physiological stress are the extreme problems of the micropropagation technique. But, many numbers of papers have been published on micropropagation of the bamboo species through nodal segments as explants. The proliferation of the bamboo shoots is dependent on the season of collection, size of explants, the position of explants, diversity of plants, concentration and combination of plant growth regulators, most adequate culture medium, environmental condition of the equipment, handling, and individual species. Bamboo is a monocarpic fast-growing, tall perennial grass and having the high potential to generate economic and social benefits. It helps to maintain land patterns and control soil erosion.  The long life cycle of the bamboo produces a huge amount of seeds but unfortunately, mostly, they are non-viable. So, bamboos are propagated from vegetative by cutting and air layering. However, these methods are only for a small scale and they also tend to destroy large mother plant stocks and difficult to be transported. So, the in vitro propagation technique is useful to obtain large progenies from desired genotypes. Mostly, BAP and TDZ growth hormones are widely used for shoot multiplication and IBA, NAA and IAA are used for root initiation as per developed protocols in tissue culture for large scale production. This review intends to explore an overview of the recent literature reports to summarize the importance of micropropagation by using nodal segments of bamboo species and factors influencing it.
Fundamentals of Electrochemical Corrosion
Authors: Stansbury E.E. , Buchanan R.A.
Published: July 2020

Fundamentals of Electrochemical Corrosion covers the underlying chemistry and materials science associated with the corrosion behavior of metals in aqueous environments. It begins with a review of corrosion processes and the reactions that occur in the interface area between the metal and corrosive media. It describes the basic elements of a corrosion circuit, the criteria for metal-solution reactions, and the effect of corrosion products. It discusses the thermodynamic principles governing the stability of metals in aqueous environments, the kinetics of metal-ion transfer, the role of diffusion, and the influence of solution velocity. It explains how to calculate corrosion rates and estimate corrosion potential and current density. It addresses practical issues such as galvanic coupling, cathodic protection, and the effect of anodic polarization on various metals and alloys. It also covers corrosion-rate measurements, localized and metallurgically influenced corrosion, environment-sensitive fracture, and corrosion fatigue. The book includes charts, graphs, tables, equations, and chapter review questions, and is appropriate for use in upper-level undergraduate and graduate instruction, professional education, individual study, and as a reference and data resource. For information on the print version, ISBN 978-0-87170-676-8, follow this link.
A Base Nacional Curricular Comum e a formação continuada de professores sobre a floresta amazônica
Authors: Gomes Orleylson Cunha , Maria Inês Gasparetto Higuchi
Published: July 2020

Muito se fala sobre a importância da floresta amazônica, porém suas relações no ecossistema ainda são pouco compreendidas pela população. Essa falta de conhecimento pode afetar iniciativas para sua preservação. Várias ações têm sido realizadas no âmbito das políticas públicas, como o novo código florestal de 2012, o bolsa floresta familiar. No entanto, acorda-se que é por meio da educação que efetivas mudanças de proteção ao sistema ambiental podem ocorrer. Inserir no currículo escolar a complexidade da floresta amazônica pode estimular nos estudantes a formação de responsabilidades para a preservação desse ecossistema. Nesse sentido, esse trabalho teve como objetivo verificar como a temática “floresta amazônica” pode ser inserida na formação continuada de professores de ciências naturais e biologia, visando à sua interação na Base Nacional Curricular Comum – BNCC a partir de um diálogo profundo com pesquisadores deste bioma. O percurso metodológico adotado foi uma análise documental da BNCC e a correspondente matriz pedagógica adotada num curso de formação continuada desenvolvido em parceria com pesquisadores da área florestal do Instituto Nacional de Pesquisas da Amazônia - INPA. Os resultados mostram que a floresta amazônica está absorta com um tema amplo e pouco contextualizado, mesmo com os avanços propostos pela BNCC. Esse estado pode e deve ser compensado com uma formação continuada mais especifica e com parcerias de profissionais que se dedicam na produção científica desse ecossistema, dando aos professores o respaldo de conhecimento e reflexões necessárias para sua atividade de ensino.
RESEARCH OF WATER RESERVES IN SNOW COVER OF ALLUVIAL SOILS
Authors: Evsenkin Konstantin , Ilinskiy Andrey
Published: July 2020

The article presents the results of studying the water reserves in the snow cover on a stationary site of reclaimed alluvial soil of JSC "Moskovskoe" (Ryazan region). The analysis of the height and density of snow cover is also presented. A comparative assessment of water reserves in the snow cover of reclaimed lands of JSC «Moskovskoe» with water reserves in the snow of the reclamation object «Tinki-2» is given.
Densitometric analysis of brain computed tomography as a new prognostic factor in patients with acute subdural hematoma
Authors: García-Pérez Daniel , Panero-Pérez Irene , Eiriz Fernández Carla , Moreno-Gomez Luis Miguel , Esteban-Sinovas Olga , Navarro-Main Blanca , Gómez López Pedro A. , Castaño-León Ana M. , Lagares Alfonso
Published: July 2020

OBJECTIVE

Acute subdural hematoma (ASDH) is a major cause of mortality and morbidity after traumatic brain injury (TBI). Surgical evacuation is the mainstay of treatment in patients with altered neurological status or significant mass effect. Nevertheless, concerns regarding surgical indication still persist. Given that clinicians often make therapeutic decisions on the basis of their prognosis assessment, to accurately evaluate the prognosis is of great significance. Unfortunately, there is a lack of specific and reliable prognostic models. In addition, the interdependence of certain well-known predictive variables usually employed to guide surgical decision-making in ASDH has been proven. Because gray matter and white matter are highly susceptible to secondary insults during the early phase after TBI, the authors aimed to assess the extent of these secondary insults with a brain parenchyma densitometric quantitative CT analysis and to evaluate its prognostic capacity.

METHODS

The authors performed a retrospective analysis among their prospectively collected cohort of patients with moderate to severe TBI. Patients with surgically evacuated, isolated, unilateral ASDH admitted between 2010 and 2017 were selected. Thirty-nine patients were included. For each patient, brain parenchyma density in Hounsfield units (HUs) was measured in 10 selected slices from the supratentorial region. In each slice, different regions of interest (ROIs), including and excluding the cortical parenchyma, were defined. The injured hemisphere, the contralateral hemisphere, and the absolute differences between them were analyzed. The outcome was evaluated using the Glasgow Outcome Scale–Extended at 1 year after TBI.

RESULTS

Fifteen patients (38.5%) had a favorable outcome. Collected demographic, clinical, and radiographic data did not show significant differences between favorable and unfavorable outcomes. In contrast, the densitometric analysis demonstrated that greater absolute differences between both hemispheres were associated with poor outcome. These differences were detected along the supratentorial region, but were greater at the high convexity level. Moreover, these HU differences were far more marked at the cortical parenchyma. It was also detected that these differences were more prone to ischemic and/or edematous insults than to hyperemic changes. Age was significantly correlated with the side-to-side HU differences in patients with unfavorable outcome.

CONCLUSIONS

The densitometric analysis is a promising prognostic tool in patients diagnosed with ASDH. The supplementary prognostic information provided by the densitometric analysis should be evaluated in future studies.
Fine configuration of the dural fibrous network and the extradural neural axis compartment in the jugular foramen: an epoxy sheet plastination and confocal microscopy study
Authors: Bond Jacob D. , Xu Zhaoyang , Zhang Ming
Published: July 2020

OBJECTIVE

The extradural neural axis compartment (EDNAC) is an adipovenous zone that is located between the meningeal (ML) and endosteal (EL) layers of the dura mater and has been minimally investigated in the jugular foramen (JF) region. In this study, the authors aimed to explore the fine architecture of the EDNAC within the JF and evaluate whether the EDNAC can be used as a component for JF compartmentalization.

METHODS

A total of 46 cadaveric heads (31 male, 15 female; age range 54–96 years) and 30 dry skulls were examined in this study. Twelve of 46 cadaveric heads were plastinated as a series of transverse (7 sets), coronal (3 sets), and sagittal (2 sets) slices and examined using stereomicroscopy and confocal microscopy. The dural entry points of the JF cranial nerves were recorded in 34 cadaveric skulls. The volumes of the JF, intraforaminal EDNAC, and internal jugular vein (IJV) were quantified.

RESULTS

Based on constant osseous landmarks, the JF was subdivided into preforaminal, intraforaminal, and subforaminal segments. The ML-derived fascial sheath along the anteromedial wall of the IJV demarcated the “venous portion” and the “EDNAC portion” of the bipartite JF. The EDNAC did not surround the intraforaminal IJV and comprised an ML-derived dural fibrous network and an adipose matrix. A fibrovenous curtain subdivided the intraforaminal EDNAC into a small anterior column containing cranial nerve (CN) IX and the anterior condylar venous plexus and a large posterior adipose column containing CNs X and XI. In the intraforaminal segment, the IJV occupied a slightly larger space in the foramen (57%; p < 0.01), whereas in the subforaminal segment it occupied a space of similar size to that of the EDNAC.

CONCLUSIONS

Excluding the IJV, the neurovascular structures in the JF traverse the dural fibrous network that is dominant in the foraminal EDNAC. The results of this study will contribute to anatomical knowledge of the obscure yet crucially important JF region, increase understanding of foraminal tumor growth and spread patterns, and facilitate the planning and execution of surgical interventions.
Safety and efficacy of brainstem biopsy in children and young adults
Authors: Hersh David S. , Kumar Rahul , Moore Kenneth A. , Smith Luke G. F. , Tinkle Christopher L. , Chiang Jason , Patay Zoltan , Gajjar Amar , Choudhri Asim F. , Lee-Diaz Jorge A. , Vaughn Brandy , Klimo Paul
Published: July 2020

OBJECTIVE

Biopsies of brainstem lesions are performed to establish a diagnosis in the setting of an atypical clinical or radiological presentation, or to facilitate molecular studies. A better understanding of the safety and diagnostic yield of brainstem biopsies would help guide appropriate patient selection.

METHODS

All patients who underwent biopsy of a brainstem lesion during the period from January 2011 to June 2019 were reviewed. Demographic, radiological, surgical, and outcome data were collected.

RESULTS

A total of 58 patients underwent 65 brainstem biopsies during the study period. Overall, the median age was 7.6 years (IQR 3.9–14.2 years). Twenty-two of the 65 biopsies (34%) were open, 42 (65%) were stereotactic, and 1 was endoscopic. In 3 cases (5%), a ventriculoperitoneal shunt was placed, and in 9 cases (14%), a posterior fossa decompression was performed during the same operative session as the biopsy. An intraoperative MRI (iMRI) was performed in 28 cases (43%). In 3 of these cases (11%), the biopsy was off target and additional samples were obtained during the same procedure. New neurological deficits were noted in 5 cases (8%), including sensory deficits, ophthalmoparesis/nystagmus, facial weakness, and hearing loss; these deficits persisted in 2 cases and were transient in 3 cases. A pseudomeningocele occurred in 1 patient; no patients developed a CSF leak or infection. In 8 cases (13%) an additional procedure was needed to obtain a diagnosis.

CONCLUSIONS

Brainstem biopsies are safe and effective. Target selection and approach should be a collaborative effort. iMRI can be used to assess biopsy accuracy in real time, thereby allowing any adjustment if necessary.
The limited influence of neurosurgeons’ behavior on inpatient satisfaction: a retrospective multihospital analysis
Authors: Park Christine , Zakare-Fagbamila Rasheedat T. , Dickson Wes , Garcia Alessandra N. , Gottfried Oren N.
Published: July 2020

OBJECTIVE

The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) is a survey that assesses patient satisfaction, which is an important measure of the quality of hospital care and ultimately the overall hospital rating (OHR). However, the survey covers several elements of patient satisfaction beyond the patient-surgeon interaction. In this study, authors investigated which admission and experience factors had the highest impact on the OHR.

METHODS

This was a retrospective cohort analysis of HCAHPS surveys from patients who, in the period between August 1, 2016, and January 31, 2018, had been discharged from the neurosurgical or orthopedic service at three hospitals serving a single metropolitan area. The top-box score was defined as the highest rating obtainable for each survey question. Baseline admission attributes were obtained, and multivariate logistic regression was used to determine predictors of the top-box OHR.

RESULTS

After application of the inclusion and exclusion criteria, 1470 patients remained in the analysis. Categories on the HCAHPS included OHR, communication, education, environment, pain management, and responsiveness. After excluding identifying questions from the survey and adjusting for subspecialty and hospital, 7 of 17 HCAHPS survey items were significant predictors of OHR. Only 2 of these were related to the surgeon: 1) discharge, “Did you get information in writing about what symptoms or health problems to look out for after you left the hospital?” (OR 5.93, 95% CI 2.52–13.94); and 2) doctor, “Did doctors explain things in a way you could understand?” (OR 2.78, 95% CI 1.73–4.46). The top three strongest correlating items were 1) discharge; 2) nursing, “Did nurses treat you with courtesy and respect?” (OR 3.86, 95% CI 2.28–6.52); and 3) hospital environment, “Were your room and bathroom kept clean?” (OR 2.86, 95% CI 1.96–4.17).

CONCLUSIONS

The study findings demonstrated that there are several nonmodifiable factors (i.e., specialty, experience) and items that are not under the direct purview of the neurosurgeon (e.g., nursing communication, hospital environment) that are significant influences on overall inpatient satisfaction on the HCAHPS survey. Furthermore, components of the survey that ultimately influence the OHR vary across different hospitals. Hence, HCAHPS survey results should be broadly interpreted as a way to make health systems more aware of the overall hospital factors that can improve quality of care and patient experience.
Mediators of racial disparities in mortality rates after traumatic brain injury in childhood: data from the Trauma Quality Improvement Program
Authors: Piatt Joseph
Published: July 2020

OBJECTIVE

Social disparities in healthcare outcomes are almost ubiquitous, and trauma care is no exception. Because social factors cannot cause a trauma outcome directly, there must exist mediating causal factors related to the nature and severity of the injury, the robustness of the victim, access to care, or processes of care. Identification of these causal factors is the first step in the movement toward health equity.

METHODS

A noninferiority analysis was undertaken to compare mortality rates between Black children and White children after traumatic brain injury (TBI). Data were derived from the Trauma Quality Improvement Program (TQIP) registries for the years 2014 through 2017. Inclusion criteria were age younger than 19 years and head Abbreviated Injury Scale scores of 4, 5, or 6. A noninferiority margin of 10% was preselected. A logistic regression propensity score model was developed to distinguish Black and White children based on all available covariates associated with race at p < 0.10. Stabilized inverse probability weighting and a one-tailed 95% CI were used to test the noninferiority hypothesis.

RESULTS

There were 7273 observations of White children and 2320 observations of Black children. The raw mortality rates were 15.6% and 22.8% for White and Black children, respectively. The final propensity score model included 31 covariates. It had good fit (Hosmer-Lemeshow χ2 = 7.1604, df = 8; p = 0.5194) and good discrimination (c-statistic = 0.752). The adjusted mortality rates were 17.82% and 17.79% for White and Black children, respectively. The relative risk was 0.9986, with a confidence interval upper limit of 1.0865. The relative risk corresponding to the noninferiority margin was 1.1. The hypothesis of noninferiority was supported.

CONCLUSIONS

Data captured in the TQIP registries are sufficient to explain the observed racial disparities in mortality after TBI in childhood. Speculations about genetic or epigenetic factors are not supported by this analysis. Discriminatory care may still be a factor in TBI mortality disparities, but it is not occult. If it exists, evidence for it can be sought among the data included in the TQIP registries.
Professional Activity of a University Teacher: Personal Values and Temporal Perception
Authors: Moskvina N. B. , Fishman B. E.
Published: July 2020

The purpose of the article is to actualize the problems of personality values and senses in university teachers’ professional activities. The authors present and substantiate the methodology for identifying the relation between personal significance for teachers of various aspects of their professional activities and time costs for the implementation of these aspects (components). The methodology is based on their pairwise comparison. This comparison is carried out first by the criterion of the significance of these aspects, and after 1-2 weeks – by the criterion of their time cost. Based on their own work as well as other studies, the authors identify three of the most timeconsuming aspects of teachers’ activity: the preparation and conducting of lessons and lectures; scientific products creation; work with documents. It is confirmed that the preparation and conducting of lessons and lectures as well as the preparation of various plans, programs, reports, etc. are the dominant components of university teachers’ activity. The disparity between the personal significance and time costs is the smallest if it concerns preparation of lessons. In this case, the time cost is compensated by understanding of its importance. As for work with documents, such compensation does not exist here. So, it turns into a potential source of internal tensions and conflicts. The component “creation of scientific products” is quite contradictory: time costs for it subjectively seem quite large while this component is perceived as not high significant. This is consistent with other studies that show that this aspect of activity often turns out to be formally motivated, not related to serious scientific research. In the article, the situation, empirically recognized by many authors, gets a fundamentally new interpretation, as the temporal parameter acquires the status of value. The authors propose to consider time costs in relation to various aspects of university teachers’ activities in this particular context.
Local Face Antimagic Evaluations and Coloring of Plane Graphs
Authors: Bong Novi , Bača Martin , Semaničová-Feňovčíková Andrea , Sugeng Kiki A. , Wang Tao-Ming
Published: July 2020

We investigate a local face antimagic labeling of plane graphs, and we introduce a new graph characteristic, namely local face antimagic chromatic number of type ( a; b; c). Then we determine the precise value of this parameter for wheels and ladders.
Role of artificial intelligence and enterprise risk management to promote corporate entrepreneurship and business performance: evidence from korean banking sector
Authors: Lee Hoyoung
Published: July 2020

Korean banking industry has achieved significant growth in financial market, however, these banks are lacking with entrepreneurship activities due to low information system risk management. Objective of this study is to examine the effect of artificial intelligence, information system risk management and corporate entrepreneurship on business performance of Korean banks. The current study introduced artificial intelligence as one of the elements to boost risk management activities, corporate entrepreneurship and business performance. This objective was achieved through a research survey among Korean banks. Questionnaires were distributed among the employees of banks by using simple random sampling. Partial Least Square (PLS)-Structural Equation Modeling (SEM) was used for data analysis. Results of the study revealed that artificial intelligence has key role to influence information system risk management. It has positive role to enhance information system risk management practices. Information system risk management practices has vital importance to promote corporate entrepreneurship which increases the business performance of banks. This study is important for Korean banks to make various strategies for risk management, corporate entrepreneurship and business performance.
Spatial feature analysis of rural basic public service supply based on TOPSIS model and Data aggregation algorithm
Authors: Cui Li , Zhou Huiqiu
Published: July 2020

The provision of basic public services in rural areas is a necessary condition for promoting farmers, agriculture, and rural development, and has important economic effects. The supply of basic public services in rural areas has an impact on agricultural growth, rural poverty reduction, and farmers’ production and investment, and ultimately directly or indirectly affect farmers’ income and consumption. In order to effectively improve the effectiveness of providing basic public services in rural areas, this study takes rural basic public services as the research object, and analyzes the economic and geographic perspectives, models, and algorithms of supply effectiveness through a literature review. It was found that the research area level needs to be deepened, and the shortcomings of traditional models and algorithms were also found. This article will make full use of the TOPSIS model’s methodological advantages in comprehensive ranking, combine the entropy method with the TOPSIS model, and sort the evaluation objects by approaching the optimal solution, so as to more objectively evaluate the rural basic public service supply in the sample counties. Based on the data aggregation algorithm, with the help of spatial analysis methods, Gini coefficient, and Theil index to further study the spatial distribution characteristics of supply. The research shows that the method has good performance and can be used as a reference for the subsequent related research rural basic services theory.
Risk evaluation of urban rainwater system waterlogging based on neural network and dynamic hydraulic model
Authors: Zhiming Cai , Daming Li , Lianbing Deng
Published: July 2020

With the rapid development of urban construction and the further improvement of the degree of urbanization, despite the intensification of the drainage system construction, the problem of urban waterlogging is still showing an increasingly significant trend. In this paper, the authors analyze the risk evaluation of urban rainwater system waterlogging based on neural network and dynamic hydraulic model. This article introduces the concept of risk into the study of urban waterlogging problems, combines advanced computer simulation methods to simulate different conditions of rainwater systems, and conducts urban waterlogging risk assessment. Because the phenomenon of urban waterlogging is vague, it is affected by a variety of factors and requires comprehensive evaluation. Therefore, the fuzzy comprehensive evaluation method is very suitable for solving the risk evaluation problem of urban waterlogging. In order to improve the scientificity of drainage and waterlogging prevention planning, sponge cities should gradually establish rainwater impact assessment and waterlogging risk evaluation systems, comprehensively evaluate the current capacity of urban drainage and waterlogging prevention facilities and waterlogging risks, draw a map of urban rainwater and waterlogging risks, and determine the risk level. At the same time, delineate drainage and waterlogging prevention zones and risk management zones to provide effective technical support for the formulation of drainage and storm waterlogging prevention plans and emergency management.
Research on English score analysis system based on improved decision tree algorithm and fuzzy set
Authors: Zhang Weiying
Published: July 2020

At present, the data mining technology is introduced into the analysis of English scores, the data is deeply explored and analyzed reasonably, and the analysis results are used to guide the smooth development of teaching, which is conducive to improving the quality of English teaching. The main work of this thesis is based on the background of this study: taking the academic performance of college students as the application background, this paper first introduces the basic theoretical knowledge of data mining and the application status of data mining technology in education field. Secondly, this paper establishes a student performance database and uses data mining technology to carry out in-depth mining of the established performance database. Finally, the mining results are analyzed, and the factors affecting students’ academic performance are obtained. These analysis results have important reference value for the future improvement of teaching work in colleges and universities.
Analysis of financial market trend based on autoregressive conditional heteroscedastic model and BP neural network prediction
Authors: Zhang Xin
Published: July 2020

High-frequency data such as stock prices are aggregated into low-frequency monthly data for modeling. However, the summation method only applies to high frequency data in the form of flow, and the summation method reduces the sample size. Based on this, this paper uses the mixing model to construct the financial status index, which can model the data of different frequencies and compensate for the defects of the same frequency data modeling to some extent. Moreover, based on principal component analysis and text mining technology, this paper constructs two kinds of sentiment indexes, and studies the influence and prediction of two sentiment indexes on the closing price of stock market. In addition, in the empirical analysis, this paper establishes the GARCH model and BP neural network prediction model and predicts the closing price. Finally, this paper compares the pros and cons of predictive models and sentiment indices. The research shows that the BP neural network model established by using the lag variable of the Web text sentiment index as the input layer variable is more reliable and can be widely used in the stock market.
Using machine learning techniques to develop prediction models for detecting unpaid credit card customers
Authors: Yontar Meltem , Namli Özge Hüsniye , Yanik Seda
Published: July 2020

Customer behavior prediction is gaining more importance in the banking sector like in any other sector recently. This study aims to propose a model to predict whether credit card users will pay their debts or not. Using the proposed model, potential unpaid risks can be predicted and necessary actions can be taken in time. For the prediction of customers’ payment status of next months, we use Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification and Regression Tree (CART) and C4.5, which are widely used artificial intelligence and decision tree algorithms. Our dataset includes 10713 customer’s records obtained from a well-known bank in Taiwan. These records consist of customer information such as the amount of credit, gender, education level, marital status, age, past payment records, invoice amount and amount of credit card payments. We apply cross validation and hold-out methods to divide our dataset into two parts as training and test sets. Then we evaluate the algorithms with the proposed performance metrics. We also optimize the parameters of the algorithms to improve the performance of prediction. The results show that the model built with the CART algorithm, one of the decision tree algorithm, provides high accuracy (about 86%) to predict the customers’ payment status for next month. When the algorithm parameters are optimized, classification accuracy and performance are increased.
Bipolar neutrosophic DEMATEL for urban sustainable development
Authors: Abdullah Lazim , Rahim Siti Nuraini
Published: July 2020

Recently, researchers have shown an increased interest in integrating the neutrosophic sets with multi-criteria decision making (MCDM) methods. Previous literature have suggested the integration of neutrosophic set with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, in which the three memberships of neutrosophic set are utilized to solve problems that are characterized by non-deterministic information. Differently from the neutrosophic DEMATEL, which directly used three independent memberships, this paper proposes bipolar neutrosophic DEMATEL (Bipolar NS-DEMATEL) of which the positive and negative of truth, indeterminate and false memberships of bipolar neutrosophic set are introduced to enhance decision in urban sustainable development. Three criteria and fifteen sub-criteria of urban sustainable development are the main MCDM structures that need to be solved using the proposed method. A group of experts were invited to provide rating of performance values of sub-criteria of urban sustainable development problem using a bipolar neutrosophic linguistic scale. The proposed Bipolar NS-DEMATEL is applied to segregate the sub-criteria of urban sustainable development into cause and effect groups. In addition, the network relation map is drawn to observe the interaction among the sub-criteria. The Bipolar NS-DEMATEL suggests that air quality (SC12) is the most important sub-criteria in managing urban sustainable development. The result also unveils that the sub-criterion safety (SC21) is impacted and influenced by other sub-criteria. The identification of sub-criteria in accordance with their net causer and net receiver would help the authority in prioritizing sub-criteria that may directly be affected by urban development.
Cantor set based neighbor generation method for permutation solution representation
Authors: Öztürk Melike , Alabaş-Uslu Çiğdem
Published: July 2020

Metaheuristics gained world-wide popularity and researchers have been studying them vigorously in the last two decades. A relatively less explored approach in the improvement of metaheuristics is to design new neighbor generation mechanisms. Neighbor generation mechanisms are very important in the success of any single solution-based heuristic since they directly guide the search. In this study, a neighbor generation mechanism called cantor-set based (CB) method for single solution-based heuristics which use permutation solution representation is described. The inspiration for CB method stems from the recursive algorithm that constructs a cantor set which is a fractal set. Three variations of CB method are discussed (CB-1, CB-2, CB-3) considering the presented design possibilities. The computational experiments are conducted by embedding the mechanisms into the classical local search and simulated annealing algorithms, separately, to test their efficiency and effectiveness by comparing them to classical swap and insertion mechanisms. The traveling salesman problem (TSP) and quadratic assignment problem (QAP) which are very different problems that have incompatible characteristics have been chosen to test the mechanisms and sets of benchmark instances with varying sizes are chosen for the comparisons. The computational tests show that CB-2 gives very favorable results for TSP and CB-1 gives favorable results for QAP which means that CB-2 is suitable for problems that have steep landscapes and CB-1 is suitable for the problems that have flat landscapes. It is observed that CB-3 is a more generalized mechanism because it gives consistently good results for both TSP and QAP instances. The best mechanism for a given instance of the both problem types outperforms the classical neighbor generation of swap and insertion in terms of effectiveness.
Evaluating social sustainable development factors using multi-experts Z-fuzzy AHP
Authors: Tüysüz Nurdan , Kahraman Cengiz
Published: July 2020

This study presents a multi-experts multiple criteria decision making approach for quantitatively evaluating social sustainable development factors. The proposed model which integrates Z-fuzzy numbers and fuzzy AHP enables to weight and rank social sustainable development factors, which may give guidance to many sustainable development researches. In addition to the first usage of the Z-fuzzy numbers for the weighting decision of social sustainable development factors, another contribution of the study is presenting the Z-fuzzy numbers integrated AHP method with multi-experts which can be useful in many problems and applications containing uncertainty. The most important advantage of the Z-fuzzy numbers integrated AHP method is that it allows the degree of confidence of decision makers to be included to the calculations. An application of the proposed approach is also presented for prioritizing the social sustainable development factors based on the experts’ evaluations together with a sensitivity analysis.
Cross-view pedestrian clustering via graph convolution network for unsupervised person re-identification
Authors: Wang Yuanyuan , Li Xiang , Jiang Mingxin , Zhang Haiyan , Tang E
Published: July 2020

At present, supervised person re-identification method achieves high identification performance. However, there are a lot of cross cameras with unlabeled data in the actual application scenarios. The high cost of marking data will greatly reduce the effect of the supervised learning model transferring to other scene domains. Therefore, unsupervised learning of person re-identification becomes more attractive in the real world. In addition, due to changes in camera angle, illumination and posture, the extracted person image representation is generally different in the non-cross camera view, but the existing algorithm ignores the difference among cross camera images under camera parameters and environments. In order to overcome the above problems, we propose unsupervised person re-identification metric learning method. The model learns a shared space to reduce the discrepancy under different cameras. The graph convolution network is further employed to cluster the cross-view image features extracted from the shared space. Our model improves the scalability of pedestrian re-identification in practical application scenarios. Extensive experiments on four large-scale person re-identification public datasets have been conducted to demonstrate the effectiveness of the proposed model.
New expected impact functions and algorithms for modeling games under soft sets
Authors: Deli Irfan , Long Hoang Viet , Son Le Hoang , Kumar Raghvendra , Dey Arindam
Published: July 2020

Soft set is the power tool to deal with uncertainty in a parametric manner. In applications of soft set, one of the most important steps is to define mappings on soft sets. In this study, we model theory of game under theory of soft set which is an effective tool for handling uncertainties events and problems that may exist in a game. To this end, we first define some expected impact functions of players in soft games. Then, we propose three new decision making algorithms to solve the 2.2 × p, 2 . n × p and m . 2 × p soft matrix games, which cannot be settled by the relevant soft methods such as saddle points, lover and upper values, dominated strategies and Nash equilibrium. The proposed soft game algorithms are illustrated by examples.
Collision-avoidance steering control for autonomous vehicles using neural network-based adaptive integral terminal sliding mode
Authors: Sun Zhe , Zou Jiayang , He Defeng , Man Zhihong , Zheng Jinchuan
Published: July 2020

Due to the complex driving conditions confronted by an autonomous vehicle, it is significant for the vehicle to possess a robust control system to achieve effective collision-avoidance performance. This paper proposes a neural network-based adaptive integral terminal sliding mode (NNAITSM) control scheme for the collision-avoidance steering control of an autonomous vehicle. In order to describe the vehicle’s lateral dynamics and path tracking characteristics, a two-degrees-of-freedom (2DOF) dynamic model and a kinematic model are adopted. Then, an NNAITSM controller is designed, where a radial basis function neural network (RBFNN) scheme is utilized to online approximate the optimal upper bound of lumped system uncertainties such that prior knowledge about the uncertainties is not required. The stability of the control system is proved via Lyapunov, and the selection guideline of control parameters is provided. Last, Matlab-Carsim co-simulations are executed to test the performance of the designed controller under different road conditions and vehicle velocities. Simulation results show that compared with conventional sliding mode (CSM) and nonsingular terminal sliding mode (NTSM) control, the proposed NNAITSM control scheme owns evident superiority in not only higher tracking precision but also stronger robustness against various road surfaces and vehicle velocities.
Dynamic user modeling for expert recommendation in community question answering
Authors: He Tongze , Guo Caili , Chu Yunfei , Yang Yang , Wang Yanjun
Published: July 2020

Community Question Answering (CQA) websites has become an important channel for people to acquire knowledge. In CQA, one key issue is to recommend users with high expertise and willingness to answer the given questions, i.e., expert recommendation. However, a lot of existing methods consider the expert recommendation problem in a static context, ignoring that the real-world CQA websites are dynamic, with users’ interest and expertise changing over time. Although some methods that utilize time information have been proposed, their performance improvement can be limited due to fact that they fail they fail to consider the dynamic change of both user interests and expertise. To solve these problems, we propose a deep learning based framework for expert recommendation to exploit user interest and expertise in a dynamic environment. For user interest, we leverage Long Short-Term Memory (LSTM) to model user’s short-term interest so as to capture the dynamic change of users’ interests. For user expertise, we design user expertise network, which leverages feedback on users’ historical behavior to estimate their expertise on new question. We propose two methods in user expertise network according to whether the dynamic property of expertise is considered. The experimental results on a large-scale dataset from a real-world CQA site demonstrate the superior performance of our method.
Fractional-order modeling and control of pneumatic-hydraulic upper limb rehabilitation training system1
Authors: Wang Hongyan , Huang Zhi , Lu Jinbo
Published: July 2020

In this paper, by replacing the integral mass flow equation to fractional-order mass flow equation, the fractional-order mathematical model of 2DOF pneumatic-hydraulic upper limb rehabilitation training system is established. A new 2DOF fractional-order fuzzy PID (FOFPID) controller is designed, to provides a new reference for improving the control accuracy of the pneumatic system. In the design of the controller, the weight parameters of the input terms are transformed into the weight parameters of the error, and the input, which are analyzed to improve the accuracy of the controller design. The parameters of the control system are determined by multi-objective particle swarm optimization. To prove the effectiveness of the proposed control method, the experimental research was carried out by building the experimental platform of pneumatic-hydraulic upper limb rehabilitation training system. The results show that the 2DOF FOFPID controller has better performance than other designed controllers under different working conditions.
Hallucinations and Development of Dementia in Parkinson’s Disease
Authors: Gryc Wojciech , Roberts Kathryn A. , Zabetian Cyrus P. , Weintraub Daniel , Trojanowski John Q. , Quinn Joseph F. , Hiller Amie L. , Chung Kathryn A. , Poston Kathleen L. , Yang Laurice , Hu Shu-Ching , Edwards Karen L. , Montine Thomas J. , Cholerton Brenna A.
Published: July 2020

Neuropsychiatric symptoms are common in Parkinson’s disease (PD). We investigated the relationship between neuropsychiatric symptoms and current and future diagnosis of PD dementia (PDD). Individuals with PD who had a study partner were enrolled (n = 696). Study partners were administered the Neuropsychiatric Inventory or Neuropsychiatric Inventory Questionnaire at baseline. Participants were assigned a cognitive diagnosis at baseline and follow up visits. Hallucinations were significantly associated with a diagnosis of PDD cross-sectionally (p < 0.001) and with shortened time to dementia longitudinally among initially nondemented participants (n = 444; p = 0.005). Screening for hallucinations may be useful for assessing risk of dementia in participants with PD.
Use of hyperbaric oxygen therapy of purpura fulminans in an extremely low birth weight preterm: A case report
Authors: Yılmaz A. , Kaya N. , Meriç R. , Bayramli Z. , Öroğlu B. , Celkan T.T. , Vural M. , Perk Y.
Published: July 2020

Purpura fulminans (PF) is a rare and fatal complication of septic shock or diffuse intravascular coagulation (DIC) resulting in skin and soft tissue necrosis. PF can be caused by congenital or acquired protein C (PC) or protein S (PS) deficiency. The most common cause of PF in a neonate is sepsis. In our extremely low birth weight preterm case, due to PF that started in the right-hand fingers, examination was made and protein S deficiency was detected as well as MTHFR (A1298C) and Factor V Leiden (R506Q) homozygous mutations. While being unresponsive to fresh frozen plasma (FFP) and unfractionated heparin (UFH) therapy, we want to highlight the curative treatment with hyperbaric oxygen (HBOT), which has not previously been used in extremely low birth weight preterm infants for this purpose.
Dynamic CT assessment of disease change and prognosis of patients with moderate COVID-19 pneumonia
Authors: Zhang Hua , Liu Xiaohong , Yu Peng , Cheng Mingyuan , Wang Weiting , Sun Yipeng , Zeng Bingliang , Fan Bing
Published: July 2020

OBJECTIVES:

To assess prognosis or dynamic change from initial diagnosis until recovery of the patients with moderate coronavirus disease (COVID-19) pneumonia using chest CT images.

MATERIALS AND METHODS:

In this retrospective study, 33 patients (18 men, 15 women; median age, 49.0 years) with confirmed with moderate COVID-19 pneumonia in a multicenter hospital were included. The patients underwent at least four chest non-contrast-enhanced computed tomography (CT) scans at approximately 5-day intervals. We analyzed the clinical and CT characteristics of the patients. Moreover, the total CT score and the sum of lung involvement were determined for every CT scan.

RESULTS:

The most widespread presenting symptoms were fever (32/33, 97.0%) and cough (17/33, 51.5%), which were often accompanied by decreased lymphocyte count (15/33, 45.5%) and increased C-reactive protein levels (18/33, 54.6%). Bilateral, multifocal ground glass opacities (32/33, 97.0%), consolidation (25/33, 75.8%), vascular thickening (23/33, 69.7%), and bronchial wall thickening (21/33, 63.6%) with peripheral distribution were the most frequent CT findings during moderate COVID-19 pneumonia. In patients recovering from moderate COVID-19 pneumonia, four stages (stages 1–4) of evolution were identified on chest CT with average CT scores of 3.4±2.3, 6.0±4.4, 5.6±3.8, and 4.9±3.2, respectively, from the onset of symptoms. For most patients, the peak of average total CT score increased for approximately 8 days after the onset of symptoms, after which it decreased gradually. The mean CT score of all patients was 4.7 at the time of discharge.

CONCLUSION:

The moderate COVID-19 pneumonia CT score increased rapidly in a short period of time initially, followed by a slow decline over a relatively long time. The peak of the course occurred in stage 2. Complete recovery of patients with moderate COVID-19 pneumonia with high mean CT score at the time of discharge requires longer time.