bluuebunny/crossref_metadata_2025_split huggingface dataset:
Managing Cyber-Security of in-Bank Ecosystem in Conditions of Digitalization
Authors: Bezdelov A. D. , Loginova E. V. 
Published: December 2020

Information technologies (IT) play a key role in corporate infrastructure. They provide unprecedented economic development of enterprises in our era. IT systems help economize resources and give an opportunity to peep in the essence of corporate transactions. Finance service market develops energetically due to digital economy shaping. Digital technologies have penetrated all spheres of life and the level of innovation technology equipment keeps on growing at the expense of mobile technologies. The system of in-company finance control is included n the structure of management functioning as an obligatory element of the current mechanism of management. The development of programs of in-bank control is a necessary component of work of any finance and credit organization according to international and national legislation. The article describes the structure of unique in-bank mechanism of control, oriented to preventing legalization of criminal incomes and raining personnel for services of internal bank control. The article analyzes in-bank programs aimed at its organization and grounds functional responsibilities of employees in divisions of internal control integrated in the system of monitoring and managing bank risks. The role of questionnaires differentiated by clients’ types is assessed, with the help of which the bank can identify its clients. Programs of training employees of internal control divisions are structured.
Ziziphus spina-christi Leaf Extract Mitigates Mercuric Chloride-induced Cortical Damage in Rats
Authors: Almeer Rafa S. , Alkahtani Saad , Alarifi Saud , Moneim Ahmed E. Abdel , Abdi Saba , Albasher Gadah 
Published: December 2020

Background:
Mercuric chloride (HgCl2) severely impairs the central nervous system
when humans are exposed to it.

Aims:
We investigated the neuroprotective efficiency of Ziziphus spina-christi leaf extract
(ZSCLE) on HgCl2-mediated cortical deficits.

Methods:
Twenty-eight rats were distributed equally into four groups: the control, ZSCLE-treated
(300 mg/kg), HgCl2-treated (0.4 mg/kg), and ZSCLE+HgCl2-treated groups. Animals received
their treatments for 28 days.

Results:
Supplementation with ZSCLE after HgCl2 exposure prevented the deposition of mercury
in the cortical slices. It also lowered malondialdehyde levels and nitrite and nitrate formation,
elevated glutathione levels, activated its associated-antioxidant enzymes, glutathione reductase,
and glutathione peroxidase, and upregulated the transcription of catalase and superoxide dismutase
and their activities were accordingly increased. Moreover, ZSCLE activated the expression of
nuclear factor erythroid 2-related factor 2 and heme oxygenase-1 when compared with the HgCl2
group. Notably, post-treatment with ZSCLE increased the activity of acetylcholinesterase and
ameliorated the histopathological changes associated with HgCl2 exposure. Furthermore, ZSCLE
blocked cortical inflammation, as observed by the lowered mRNA expression and protein levels of
interleukin-1 beta and tumor necrosis factor-alpha, as well as decreased mRNA expression of
inducible nitric oxide synthase. In addition, ZSCLE decreased neuron loss by preventing apoptosis
in the cortical tissue upon HgCl2 intoxication.

Conclusion:
Based on the obtained findings, we suggest that ZSCLE supplementation could be
applied as a neuroprotective agent to decrease neuron damage following HgCl2 toxicity.
COVID-19 Impacts, Diagnosis and Possible Therapeutic Techniques: A Comprehensive Review
Authors: Aziz Ayesha , Asif Muhammad , Ashraf Ghazala , Yang Qiaoli , Wang Shenqi 
Published: December 2020

Background:The spread of COVID-19 has become a growing cause of mortalities over the globe since its major outbreak in December 2019. The scientific and medical communities are rallying to study different strains and probable mutations to develop more rapid and reliable molecular diagnostic tests and possible therapeutic approaches for SARS-CoV-2.Introduction:In the first section, following the introductory part, we shed light on structural and pathogenic features of SARS-CoV-2 and risk factors related to age, gender, neonatal and comorbidities. The next section summarizes the current diagnostic tests for COVID-19, such as nucleic acid and computed tomography (CT) techniques, with further emphasis on emerging diagnostic approaches for COVID-19.Methods:Further, we also review the ongoing therapeutic practices which can block virus-host interaction, cease viral proliferation or inhibit hyperbolic host immune response with subsections on drug therapy, cell therapy, immunotherapy and herbal medicines that are being used for the possible treatment of patients.Results and conclusion:Among the different promising drugs, remdesivir, by inhibiting the RNA-dependent RNA-Polymerase activity, gives much better results, including declined viral load and quick lung tissue recovery. The long-lasting repercussions of COVID-19 have also been discussed at the end. In this review, we have also critically discussed the progress in several vaccines that are under development.
Recent developments and opportunities in fighting COVID-19
Authors: Rao Vikram , Bhattamisra Subrat Kumar 
Published: December 2020

Background:
COVID-19, a Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCov-
2), was first diagnosed in the patients from Wuhan, China, in December 2019. Within a couple
of months of infection, it was declared as pandemic by the World health organization.
COVID-19 has become the most contagious infection with a serious threat to global health. In this
review, we aimed to discuss the pathogenesis, diagnostics, current treatments and potential
vaccines for COVID-19.

Methods:
An extensive literature search was conducted using keywords “COVID-19”; “Coronavirus”;
“SARS-Cov-2”; “SARS” in public domains of Google, Google scholar, PubMed, and ScienceDirect.
Selected articles were used to construct this review.

Results:
SARS-Cov-2 uses the Spike (S) protein on its surface to recognize the receptor on angiotensin-
converting enzyme 2 (ACE2) and bind with 10-folds greater affinity than SARS-Cov-1.
Molecular assays and immunoassays are the most frequently used tests, whereas computed tomography
(CT) scans and artificial intelligence enabled diagnostic tools were also used in patients. In
therapeutic treatment, few drugs were repurposed and about 23 therapeutic molecules, including
the repurposed drugs are at different stages of the clinical trial. Similarly, the development of
vaccines is also in the pipeline. Few countries have managed well to contain the spread by rapid
testing and identifying the clusters.

Conclusion:
Till now, the acute complications and mortality of COVID-19 have been linked to
pre-existing comorbid conditions or age. Besides the development of therapeutic strategies that include
drugs and vaccine, the long term implication of COVID-19 infection in terms of the disorder/
disability in the cured/discharged patients is a new area to investigate.
Major Drugs Used in COVID-19 Treatment: Molecular Mechanisms, Validation
and Current Progress in Trials
Authors: Khan Md. Asaduzzaman , Bin Islam Shad , Rakib Mejbah Uddin , Alam Didarul , Hossen Md. Munnaf , Tania Mousumi , Asad Asaduzzaman 
Published: December 2020

Background:
Currently, the present world is facing a new deadly challenge against a pandemic disease called
COVID-19, which is caused by a coronavirus, named SARS-CoV-2. To date, there is no drug or vaccine that can treat
COVID-19 completely, but some drugs have been used primarily, and they are in different stages of clinical trials. This
review article discussed and compared those drugs which are running ahead in COVID-19 treatments.

Methods:
We have explored PUBMED, SCOPUS, WEB OF SCIENCE, as well as press release of WHO, NIH and FDA for
articles about COVID-19, and reviewed them.

Results:
Drugs like favipiravir, remdesivir, lopinavir/ritonavir, hydroxychloroquine, azithromycin, ivermectin,
corticosteroids and interferons have been found effective in some extents, and partially approved by FDA and WHO to treat
COVID-19 at different phases of pandemic. However, some of these drugs have been disapproved later, although clinical
trials are going on. In parallel, plasma therapy has been found fruitful in some extents too, and a number of vaccine trails are
going on.

Conclusions:
This review article discussed the epidemiologic and mechanistic characteristics of SARS-CoV-2, and how
drugs could act on this virus with the comparative discussion on progress and backwards of major drugs used till date,
which might be beneficial for choosing therapies against COVID-19 in different countries.
Keefektifan model pembelajaran CORE dengan strategi konflik kognitif ditinjau dari prestasi belajar, berpikir kritis, dan self-efficacy
Authors: Ningsih Sri Wahyuni , Sugiman Sugiman , Merliza Pika , Ralmugiz Uke 
Published: December 2020

Penelitian ini bertujuan untuk menguji keefektifan model pembelajaran Connecting, Organizing, Reflecting, Extending (CORE) dengan strategi konflik kognitif ditinjau dari prestasi belajar, berpikir kritis, dan self-efficacy siswa. Jenis penelitian ini adalah quasi experiment dengan pretest-posttest nonequivalent group design. Populasi dalam penelitian ini adalah siswa kelas VIII SMP Negeri 3 Yogyakarta dan dipilih secara acak kelas VIII-C dan Kelas VIII-F sebagai sampel penelitian. One sample t-test digunakan untuk menguji keefektifan model CORE dengan strategi konflik kognitif dan model konvensional, sedangkan untuk menguji perbedaan keefektifan model pembelajaran digunakan uji Manova (Hotteling’s Trace). Hasil penelitian menunjukkan bahwa: (1) model pembelajaran CORE dengan strategi konflik kognitif efektif ditinjau dari prestasi belajar, kemampuan berpikir kritis, dan self-efficacy siswa; (2) model pembelajaran CORE dengan strategi konflik kognitif lebih efektif dibandingkan model konvensional ditinjau dari prestasi belajar, kemampuan berpikir kritis, dan self-efficacy siswa.The effectiveness of the CORE learning model with cognitive conflict strategies in terms of learning achievement, critical thinking, and self-efficacyAbstractThe study aimed to examine the effectiveness of Connecting, Organizing, Reflecting, Extending (CORE) learning model with cognitive conflict strategies in terms of students’ achievement, critical thinking, and self-efficacy. The study was a quasi-experiment with a pretest-posttest nonequivalent group design. The population of the study was all students of 8th-grade of SMP Negeri 3 Yogyakarta (Junior High School) and randomly selected class VIII-C and class VIII-F as the sample. One sample t-test was used to examine the effectiveness of the CORE learning model with cognitive conflict strategies and the conventional model. Whereas, to examine the difference between the effectiveness of the learning model, the Manova test (Hotteling’s Trace) was used. The result of the study showed that: (1) the CORE learning model with cognitive conflict strategies was effective in terms of students’ learning achievement, critical thinking skill, and self-efficacy; (2) The CORE learning model with cognitive conflict strategies was more effective than the conventional model in terms of students’ learning achievement, critical thinking skills, and self-efficacy.
Mortality Prediction of Patients With Cardiovascular Disease Using Medical Claims Data Under Artificial Intelligence Architectures: Validation Study
Authors: Tran Linh , Chi Lianhua , Bonti Alessio , Abdelrazek Mohamed , Chen Yi-Ping Phoebe 
Published: December 2020

Background
Cardiovascular disease (CVD) is the greatest health problem in Australia, which kills more people than any other disease and incurs enormous costs for the health care system. In this study, we present a benchmark comparison of various artificial intelligence (AI) architectures for predicting the mortality rate of patients with CVD using structured medical claims data. Compared with other research in the clinical literature, our models are more efficient because we use a smaller number of features, and this study could help health professionals accurately choose AI models to predict mortality among patients with CVD using only claims data before a clinic visit.

Objective
This study aims to support health clinicians in accurately predicting mortality among patients with CVD using only claims data before a clinic visit.

Methods
The data set was obtained from the Medicare Benefits Scheme and Pharmaceutical Benefits Scheme service information in the period between 2004 and 2014, released by the Department of Health Australia in 2016. It included 346,201 records, corresponding to 346,201 patients. A total of five AI algorithms, including four classical machine learning algorithms (logistic regression [LR], random forest [RF], extra trees [ET], and gradient boosting trees [GBT]) and a deep learning algorithm, which is a densely connected neural network (DNN), were developed and compared in this study. In addition, because of the minority of deceased patients in the data set, a separate experiment using the Synthetic Minority Oversampling Technique (SMOTE) was conducted to enrich the data.

Results
Regarding model performance, in terms of discrimination, GBT and RF were the models with the highest area under the receiver operating characteristic curve (97.8% and 97.7%, respectively), followed by ET (96.8%) and LR (96.4%), whereas DNN was the least discriminative (95.3%). In terms of reliability, LR predictions were the least calibrated compared with the other four algorithms. In this study, despite increasing the training time, SMOTE was proven to further improve the model performance of LR, whereas other algorithms, especially GBT and DNN, worked well with class imbalanced data.

Conclusions
Compared with other research in the clinical literature involving AI models using claims data to predict patient health outcomes, our models are more efficient because we use a smaller number of features but still achieve high performance. This study could help health professionals accurately choose AI models to predict mortality among patients with CVD using only claims data before a clinic visit.
Intervención grupal online para la elaboración del duelo y recuperación del bienestar psicológico tras una ruptura amorosa
Authors: Navarro Vásquez Perla 
Published: December 2020

Este estudio buscó verificar si aumentaban los niveles de bienestar psicológico en personas que han vivido una ruptura amorosa, luego de participar de una intervención grupal de modalidad online basada en el modelo de tareas del duelo de Worden, y el uso de técnicas recomendadas por este autor para el trabajo de duelo. La muestra final del estudio estuvo compuesta por 12 participantes adultos, residentes en la República Dominicana. La recolección de datos cuantitativos se hizo con el uso de las Escalas de Bienestar Psicológico de Ryff en su adaptación española realizada por Rodríguez-Carvajal et al. (2010). Además, se recolectaron datos cualitativos a través de un cuestionario de preguntas abiertas. Los resultados muestran un aumento significativo en los niveles de bienestar psicológico tras la intervención (m=28.58; t=5.86, p<0.001). Los hallazgos cualitativos, clasificados en cinco categorías principales, evidencian la percepción de cambios positivos en los participantes luego de haber participado de la intervención, como el desarrollo de la empatía con los miembros del grupo, el cambio de ideas erróneas que pudieran interferir en el proceso de duelo y la motivación para continuar procesos terapéuticos. Se recomienda realizar otras investigaciones con una muestra mayor y con grupo control, de modo que puedan hacerse generalizaciones y conclusiones definitivas sobre la efectividad del programa diseñado y aplicado.
Patient Health Utility Equations for a Type 2 Diabetes Model
Authors: Neuwahl Simon J. , Zhang Ping , Chen Haiying , Shao Hui , Laxy Michael , Anderson Andrea M. , Craven Timothy E. , Hoerger Thomas J. ,   the Look AHEAD Research Group
Published: December 2020

OBJECTIVETo estimate the health utility impact of diabetes-related complications in a large, longitudinal U.S. sample of people with type 2 diabetes.RESEARCH DESIGN AND METHODSWe combined Health Utilities Index Mark 3 data on patients with type 2 diabetes from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Look AHEAD (Action for Health in Diabetes) trials and their follow-on studies. Complications were classified as events if they occurred in the year preceding the utility measurement; otherwise, they were classified as a history of the complication. We estimated utility decrements associated with complications using a fixed-effects regression model.RESULTSOur sample included 15,252 persons with an average follow-up of 8.2 years and a total of 128,873 person-visit observations. The largest, statistically significant (P &lt; 0.05) health utility decrements were for stroke (event, −0.109; history, −0.051), amputation (event, −0.092; history, −0.150), congestive heart failure (event, −0.051; history, −0.041), dialysis (event, −0.039), estimated glomerular filtration rate (eGFR) &lt;30 mL/min/1.73 m2 (event, −0.043; history, −0.025), angina (history, −0.028), and myocardial infarction (MI) (event, −0.028). There were smaller effects for laser photocoagulation and eGFR &lt;60 mL/min/1.73 m2. Decrements for dialysis history, angina event, MI history, revascularization event, revascularization history, laser photocoagulation event, and hypoglycemia were not significant (P ≥ 0.05).CONCLUSIONSWith use of a large study sample and a longitudinal design, our estimated health utility scores are expected to be largely unbiased. Estimates can be used to describe the health utility impact of diabetes complications, improve cost-effectiveness models, and inform diabetes policies.
PENGEMBANGAN MEDIA PEMBELAJARAN MEMBACA MENGEJA BERBASIS APLIKASI UNTUK KELAS 1 SEKOLAH DASAR
Authors: Widyowati Ferty Tri , Rahmawati Intan , Priyanto Wawan 
Published: December 2020

Latar belakang yang mendorong penelitian ini adalah ditemukan siswa kelas satu yang belum mampu membaca dengan lancar. Rumusan masalah pada penelitian ini adalah Bagaimana karakteristik media pembelajaran membaca mengeja berbasis aplikasi untuk kelas 1 sekolah dasar ?. Penelitian ini bertujuan untuk Mengembangkan karakteristik media pembelajaran Membaca Mengeja berbasis Aplikasi yang validan dan praktis. Jenis penelitian yang digunakan adalah Penelitian dan Pengembangan atau Research and Development (R&D) dengan menggunakan model pengembangan ADDIE. Teknik pengumpulan data menggunakan penilaian validasi ahli materi, ahli media pembelajaran, angket respon guru dan angket respon siswa serta angket kebutuhan guru. Hasil analisis data menunjukkan bahwa angket ahli materi dan ahli media pembelajaran adalah 93,43% dengan kategori “ sangat baik”. Hasil analisis angket respon guru adalah 96,6% dengan kategori “sangat baik”. Hasil analisi angket respon siswa adalah 99,46% dengan ketegori “sangat baik”. Kesimpulannya bahwa pengembangan media pembelajaran membaca mengeja berbasis aplikasi untuk kelas I sekolah dasar layak digunakan pada pembelajaran. Saran yang dapat disampaikan adalah media pembelajaran membaca mengeja berbasis aplikasi dapat digunakan guru dan siswa untuk media pembalajaran membaca.Kata kunci: Pengembangan Media, Membaca Mengeja, Aplikasi
FORECASTING SEASONAL TIME SERIES DATA USING THE HOLT-WINTERS EXPONENTIAL SMOOTHING METHOD OF ADDITIVE MODELS
Authors: Nurhamidah Nurhamidah , Nusyirwan Nusyirwan , Faisol Ahmad 
Published: December 2020

The purpose of this study was to predict seasonal time series data using the Holt-Winters exponential smoothing additive model. The data used in this study is data on the number of passengers departing at Hasanudin Airport in 2009-2019, the source of the data obtained from the official website of the Central Statistics Agency. The results showed that the Holt-Winters exponential smoothing method on the passenger's number at Hasanudin Airport in 2009 to 2019 contained trend patterns and seasonal patterns, by first determining the initial values and smoothing parameters that could minimize forecasting errors.
Monoclonal gammopathies of undetermined significance and smoldering myeloma
Authors: Jurczyszyn Artur , Hutch Ruth , Waszczuk-Gajda Anna , Suska Anna , Krzanowska Katarzyna , Vesole David H. 
Published: December 2020

AbstractMonoclonal gammopathy of undetermined significance (MGUS) is a clonal plasma cell disorder implicated as a precursor of multiple myeloma (MM), while smoldering multiple myeloma (SMM) is a malignant plasma cell disorder without evidence of a myeloma-defining event(s) (MDE). This is a review article of both disorders outlining their current definition and management according to the current standard of care. We focus on the pathogenesis of MM and the role of MGUS and SMM in the development of active MM. MGUS is a benign disorder and, subsequently, is followed by observation. In contrast, for SMM, although the current standard of care is “watch and wait”, this paper will explore the circumstances in which treatment should be considered to prevent MDE.
The Cooling Media Influence on Selected Mechanical Properties of Steel
Authors: Šmak Radim , Votava Jiří , Polcar Adam 
Published: December 2020

Abstract
The aim of experiment was to analyse the structural transformations and changes in mechanical properties of K720 steel during heat treatment (quenching). Three types of cooling medium were selected. The heating parameters and subsequent delays at the recrystallisation temperature were the same for all samples and were observed in a laboratory furnace. Water with the highest cooling capacity was selected as the benchmark cooling medium. Subsequently, the hardening oil TK – 46 was used. Sunflower oil was selected as the last quenching medium, which can be considered an ecological replacement of quenching oil with possibility of biological disposal. The microstructure and microhardness of individual samples were subjected to a metallographic evaluation and evaluated according to ČSN EN ISO 6507, respectively. The impact toughness analysis was performed according to the ČSN EN ISO 148-1 and a three-point bending test was performed according to ČSN EN ISO 7438. This test specifies a method for determining the ability of metallic materials to undergo plastic deformation in bending. The bend test includes subjection of round, square, rectangular or polygonal cross-section to plastic deformation by bending, without changing the direction of loading, until the specified angle of bend is reached.