Principal Directions of Digital Transformation of Higher Education System in Sustainable Education

© The Authors, published by EDP Sciences, 2020. From the perspective of a systematic integrated approach, the article formulates the main directions of digital transformation of higher education system in sustainable education in all its components, taking into account the requirements of the modern digital economy as the leading trend in the country's innovative development model. The authors consider essential content of the digital economy as a vector of innovative trends focused on the training of specialists of a qualitatively different level, and present the results of the formation of the digital economy in the Personnel and Education direction in 2025. One of the essential components of the modern educational process is the electronic information and educational environment, which is considered as a system that includes innovative technology platforms as an indispensable element for the generation and processing of knowledge. The article explores the prospects for improving the Russian scientific and educational system based on innovative methods of education using neural network technologies, the need for a transition to online education with integrated systems of natural and artificial intelligence. The paper identifies obstacles that significantly hamper the sustainable development of online education, one of which is the lack of teachers of the new formation who can work in the digital environment. It also presents an analysis of the results of a comprehensive study to assess the readiness of higher education to the parameters of the digital economy, showing that most universities are at the initial stage of the informatization and automation processes, which proves the relevance of the materials presented

Female life expectancy, maternal mortality, fertility and birth rates of female genital mutilation high prevalence countries

© 2020 The Author(s) Female genital mutilation/cutting FGM/C is the process of removing part or all of the female external genitalia. Twenty-nine countries are known to be FGM/C prevalent. The prevalent countries are mostly in Sub Saharan Africa, Middle East, and Asia. FGM/C prevalence countries have total high fertility rate (TFR), high maternal mortality ratio (MMR), low female life expectancy (LEF) and high birth rate (BR). This paper extracted the TFR, MMR, LEF, and BR of FGM/C prevalent countries from each metric's comprehensive databases. Correlation analysis was used to find links between FGM/C and the four health metrics. There is a significant negative correlation between TFR and the duo of LEF and BR, which implies that having more children reduces women's life expectancy and FGM/C prevalent countries. The average TFR, MMR, LEF and BR for the 29 countries are 4.44 children, 517.24 deaths per 10,000, 63.03 years, and 33.83 per 1000 population. Behavioral change and maternal education are recommended to change the religious and cultural view of female sexuality and reduce FGM/C prevalence

Coronavirus disease 2019 (COVID‐19) and individuals with intellectual and developmental disabilities in Nigeria

This article chronicles the present situation of coronavirus disease 2019 (COVID‐19) on individuals with intellectual and developmental disabilities (IDD) in Nigeria. A systematic search was conducted on three bibliographic databases: MEDLINE Complete, Web of Science and Scopus, and supplemented with grey literature searches to assess studies on the effect of COVID‐19 on these individuals in Nigeria with data on this group from December 2019 to July 2020. There were no studies found concerning individuals with IDD in Nigeria. This article argues for an urgent call to action by Nigerian policymakers to make data available to help understand the impact of COVID‐19 and to develop and implement appropriate interventions. This article provides steps to support and care for these individuals in Nigeria. Forecasting models are recommended which offer better approaches in yielding accurate predictions and provide valuable decisions in the event of future threats and infectious disease outbreak in Nigeria

Statistical analysis of frequencies of opponents’ eliminations in Royal Rumble wrestling matches, 1988–2018

The datasets and their analyses presented in this paper revealed some frequencies of opponents׳ eliminations by entrance or order of elimination in Royal Rumble wrestling matches from 1988 to 2018. The frequency of eliminations by the order of entrant is quite different from the order of eliminations. Statistical methods, algorithms and machine learning methods can be applied to the raw data to obtain more hidden trend not included in this article

Quality of life in adults with Down syndrome: A mixed methods systematic review.

BackgroundAs the life expectancy of adults (aged ≥ 18 years) with Down syndrome increases for a plethora of reasons including recognition of rights, access, and technological and medical advances, there is a need to collate evidence about their quality of life.ObjectiveUsing Schalock and Verdugo's multidimensional quality of life assessment model, this systematic review aimed to identify, synthesise and integrate the quantitative and qualitative evidence on quality of life in adults with Down syndrome via self-and proxy-reporting.MethodsFive databases were systematically searched: MEDLINE, CINAHL, PsycINFO, Scopus, and Web of Science to identify relevant articles published between 1980 and 2022 along with grey literature and reference lists from relevant studies. A mixed methods systematic review was performed according to the Joanna Briggs Institute methodology using the convergent integrated approach. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.ResultsThirty-nine studies were included: 20 quantitative, 17 qualitative, and 2 mixed methods studies. The synthesised findings were grouped into the 8 core domains of quality of life: personal development, self-determination, interpersonal relations, social inclusion, rights, emotional, physical and material well-being. Of the 39 studies, 30 (76.92%) reported on emotional well-being and 10 (25.64%) on rights. Only 7 (17.94%) studies reported that adults with Down syndrome have a good quality of life centred around self-determination and interpersonal relations. Most adults with Down syndrome wanted to become more independent, have relationships, participate in the community, and exercise their human rights. Self-reported quality of life from adults with Down syndrome was rated higher than proxy reported quality of life. Discrepancies in quality of life instruments were discovered.ConclusionThis review highlighted the need for a better systematic approach to improving the quality of life in adults with Down syndrome in targeted areas. Future research is required to evaluate self-and proxy-reporting methods and culture-specific quality of life instruments that are more appropriate for adults with Down syndrome. In addition, further studies should consider including digital assistive technologies to obtain self-reported quality of life data in adults with Down syndrome.International prospective register of systematic reviews registration numberCRD42019140056

Single-label machine learning classification revealed some hidden but inter-related causes of five psychotic disorder diseases

Psychotic disorder diseases (PDD) or mental illnesses are group of illnesses that affect the minds and impair the cognitive ability, retard emotional ability and obstruct the process of communication and relationship with others and are characterized by delusions, hallucinations and disoriented or disordered pattern of thinking. Prognosis of PDD is not sufficient because of the nature of the diseases and as such adequate form of diagnosis is required to detect, manage and treat the illness. This paper applied the single-label classification (SLC) machine learning approach in mining of electronic health records of people with PDD in Nigeria using eleven independent (demographic) variables and five PDD as target variables. The five PDDs are Insomnia, Schizophrenia, Minimal Brain dysfunction (MBD), which is also known as Attention-Deficit/Hyperactivity Disorder (ADHD), Vascular Dementia (VD) and Bipolar Disorder (BD). The aim of using SLC is that it would be easier to detect some PDDs that are related to each other without the loss of information, which is a plus over multi-label classification (MLC). ReliefF algorithm was used at each experiment to precipitate the order of importance of the independent variables and redundant variables were excluded from the analysis. The order of the variables in feature selection was matched with feature importance after the classifications and quantified using the Spearman rank correlation coefficient. The data was divided into: 70% for training and 30% for testing. Four new performance metrics adapted from the root mean square (RMSE) were proposed and used to measure the differences between the performance results of the 10 Machine learning models in terms of the training and testing and secondly, feature and without feature selection. The new metrics are close to zero which is an indication that the use of feature selection and cross validation may not greatly affects the accuracy of the SLC. When the PDDs are included as predictors for classifying others, there was a tremendous improvement as revealed by the four new metrics for classification accuracy (CA), precision and recall. Analysis of variance showed the four different metrics differs significantly for classification accuracy (CA) and precision. However, there were no significant difference between the CA and precision when the duo are compared together across the four evaluation metrics at p value less than 0.05

Topographical Distribution of Neuroanatomical Abnormalities Following COVID-19 Invasion: A Systematic Literature Review.

PURPOSE: This systematic review is aimed at synthesising the literature base to date on the frequency and topographical distribution of neuroanatomical changes seen on imaging following COVID-19 invasion with a focus on both the acute and chronic phases of the disease. METHODS: In this study, 8 databases were systematically searched to identify relevant articles published from December 2019 to March 2022 and supplemented with a manual reference search. Data were extracted from the included studies and narrative synthesis was employed to integrate the findings. RESULTS: A total of 110 studies met the inclusion criteria and comprised 119,307 participants (including 31,073 acute and 143 long COVID-19 patients manifesting neurological alterations) and controls. Considerable variability in both the localisation and nature of neuroanatomical abnormalities are noted along the continuum with a wide range of neuropathologies relating to the cerebrovascular/neurovascular system, (sub)cortical structures (including deep grey and white matter structures), brainstem, and predominant regional and/or global alterations in the cerebellum with varying degrees of spinal involvement. CONCLUSION: Structural regional alterations on neuroimaging are frequently demonstrated in both the acute and chronic phases of SARS-CoV‑2 infection, particularly prevalent across subcortical, prefrontal/frontal and cortico-limbic brain areas as well as the cerebrovascular/neurovascular system. These findings contribute to our understanding of the acute and chronic effects of the virus on the nervous system and has the potential to provide information on acute and long-term treatment and neurorehabilitation decisions