bluuebunny/crossref_metadata_2025 huggingface dataset:
Promoting Evidence-based Veterinary Medicine through the online resource ‘EBVM Learning’: User feedback
Authors: Sellers Ellie , Baillie Sarah , Dean Rachel , Warman Sheena , Janicke Heidi , Arlt Sebastian P , Boulton Clare , Brennan Marnie , Brodbelt David , Brown Fiona , Buckley Louise , Du Myai , Gallop Emma , Goran George , Grindlay Douglas JC , Haddock Laura , Ireland Joanne , McGowan Catherine , Moberly Heather K , Place Emma , Rahman Md Mizanur , Rees Gwen , Reyher Kristen , Sanchez Javier , Schoeman Johan P , Urdes Laura , VanLeeuwen John , Verheyen Kristien
Published: February 2021

Abstract

‘EBVM Learning’ is a freely available resource created in 2015 by an international team with the support of RCVS Knowledge. The resource comprises a series of online modules teaching the fundamental concepts of evidence-based veterinary medicine (EBVM) (Ask, Acquire, Appraise, Apply & Assess) supported by case studies, exercises, worked examples and quizzes. The aim of the current study (undertaken in 2019) was to review ‘EBVM Learning’ to ensure its ongoing relevance and usefulness to the range of learners engaged in EBVM. Feedback was gathered from stakeholder groups using website statistics and feedback forms, a survey and semi-structured interviews to provide a combination of quantitative and qualitative data.

Website statistics revealed an international audience and a steady increase in visitors exceeding 1,000 per month in August 2020. Feedback via the online form (n=35) and survey (n=71) indicated that the resource was well structured, with an appropriate level and amount of content, useful examples and quizzes and the majority of respondents would use it again. Semi-structured interviews of educators (n=5) and veterinarians (n=8) identified three themes: features of the ‘EBVM Learning’ resource (strengths, suggestions for improvement), embedding the resource in education (undergraduate, postgraduate) and promoting EBVM (challenges, motivation for engagement). At a project team workshop the results were used to plan updates to the existing content and to identify new ways to promote learning and engagement. An updated version of ‘EBVM Learning’ was developed.

‘EBVM Learning’ is helping to produce the next generation of evidence-based practitioners and enabling to engage in the concepts of EBVM as part of their clinical practice.
Methods to Optimize Recruitment, Participation, and Retention Among Vulnerable Individuals Participating in a Longitudinal Clinical Trial
Authors: Doran Kelly , Collado Anahi , Taylor Hailey , Felton Julia W. , Tormohlen Kayla N. , Yi Richard
Published: February 2021

Low-income and ethnic/racial minority adults do not often participate in research or may face unique barriers when participating in research, which delays and impedes medical advances for this vulnerable population. This article describes in detail the evidenced-based methods used to enhance recruitment, participation, and retention in a clinical trial at a center serving ethnic/racial minorities and low-income individuals. The article details the partnership with a community outreach center and describes the duties and impact of a community liaison to enhance recruitment, participation, and retention in a randomized controlled trial with a 6-month follow-up. Of the 246 individuals initially recruited for screening, 80 did not meet inclusion criteria with the most common reason for disqualification being meeting criteria for substance use disorder (n = 44). One hundred sixty-six participants qualified for participation. The majority of participants identified as African American (n = 127, 77.1%) and reported an annual individual income under $10,000 (n = 121 (74.2%). Forty-five percent of the sample completed the requested number of sessions (i.e., 12). Sixty-three percent of participants completed post intervention assessments and 42% completed 6-month follow-up data collection. The participation and retention numbers in this study appear higher than typical participation and retention rates in longitudinal studies with similar populations. The methods and lessons learned may be useful for other clinical trials that recruit vulnerable populations and wish to enhance participation, engagement, and retention.
Different Types of Theories by Level of Abstraction in Nursing: A Discussion Paper
Authors: Im Eun-Ok
Published: February 2021

Background and Purpose

Despite different labels used to refer to different types of nursing theories by different authors, agreements were made on three major types of theories by level of abstraction. The purpose of this analysis was to discuss the characteristics of the three major types of nursing theories by level of abstraction that were published in refereed journals and to propose directions for future theoretical development in nursing.

Methods

An integrated literature review was conducted using PUBMED, CINAHL, and PsycINFO. A total of 116 articles were included in this analysis. The retrieved articles were sorted by the type of theories (by level of abstraction), and analyzed in terms of scope, theorizing process, specificity and abstraction, contextual understanding, links to research and practice, and diversity and generalizability. Finally, themes reflecting the characteristics of the three major types of nursing theories were extracted and discussed.

Results

A total of 17 themes were found. Although most of the themes reflected what were known about these theories, there were three new findings. First, all the grand theories that were reviewed tended to have more specific foci rather than explaining general nature, mission, or goals of nursing. Second, middle-range theories were developed based on various types/levels of theories using various sources for theorizing. Third, situation-specific theories began to be used to generate propositions and tested through statistical and qualitative analyses.

Implications for Practice

The efforts to try to link nursing theories to nursing practice need to be continued through further development and evaluation of the theories regardless of the types of theories.
Determination of the Sample Size on Different Independent K Group Comparisons by Power Analysis
Authors: ASLAN Emre , KOŞKAN Özgür , ALTAY Yasin
Published: February 2021

The purpose of this study was to determine the number of samples that should be used in independent treatment comparisons with different effect sizes (0.25-3.0), the number of treatments (2-5), and the power of the test (70% -95%) in single and multi-factor treatments. The material of the study was the random numbers drawn from the population that shows a normal distribution with N (0, 1) parameter. The power of the test was calculated by sampling with replacement from the population and after the differences between the treatments in terms of standard deviation were established, 10000 simulations were performed. This setup was carried out for experiments with one, two, and three factors. In the comparison of single factor independent treatment means, when the effect size was larger than Δ = 2 and the test power was between 70% and 95%, the sample sizes varied between 3 and 7. In the comparison of two-factor independent treatment means, when the effect size was larger than Δ = 2 and the test power was between 70% and 95%, the sample sizes varied between 2 and 3. In the comparison of three-factor independent treatment means, when the effect size was larger than Δ= 1.5 and the test power was between 70% and 95%, the sample size was 2. If all treatment comparisons were generalized; it was observed that when the effect size increased, and the power of the test decreased, the sample size decreased In the t-test and F tests used in independent treatment comparisons, a power analysis was performed under different situations, and the number of experimental units for each 5% power increment between 70% and 95% were presented in tables. These tables, may help researchers to determine the number of samples without power analysis in independent group comparisons.
Vis-NIR ve pXRF Spektrometrelerinin Toprak Biliminde Kullanımı
Authors: GÖZÜKARA Gafur
Published: February 2021

Toprakların geleneksel yöntemler ile yapılan fiziksel ve kimyasal analizleri genellikle zaman, maliyet ve kimyasal atık çıktıları nedeniyle çevreye ve ekonomiye bazı dezavantajlar getirmektedir. Bu araştırmanın amacı, i-) toprak biliminde görünür yakın kızılötesi yansıma spektroskopisi (Vis-NIR) ve portatif X ışını floresansı (pXRF) spektralarının giderek yaygınlaşan kullanım alanlarını belirlemek, ii-) Vis-NIR ve pXRF spektralarının toprak biliminde kullanılabilecek alanların ve Vis-NIR ve pXRF spektralarından elde edilen etkinliğin artırılmasına katkı sağlamaktır. Vis-NIR ve pXRF spektrasının toprakların geleneksel fiziksel ve kimyasal analiz metotlarına göre üstünlükleri; çevre dostu, düşük maliyetli, herhangi bir kimyasal maddeye ihtiyaç olmaması, toprak örneklerine zarar vermeden hızlı sonuç alınmasıdır. Bu nedenle toprak özelliklerinin belirlenmesinde ve tahmin edilmesinde giderek artan oranda kullanılmaktadır. Vis-NIR ve pXRF spektrası; toprakların kum, silt ve kil içeriğinin, organik karbon, organik madde, kireç, nem içeriği, katyon değişim kapasitesi ve pH’nın tahmin edilmesinde yaygın bir şekilde kullanılmaktadır. Araştırmacılar toprak özelliklerinin belirlenmesi ve tahmin edilmesinde Vis-NIR ve pXRF spektrasının bireysel ve birlikte kullanımlarında oldukça başarılı olduklarını rapor etmişlerdir. Vis-NIR ve pXRF spektrasının toprak biliminde kullanım alanlarının genişletilmesi için farklı ana materyal, arazi kullanımı, iklim ve bitki örtüsü altında gelişen topraklarda daha fazla araştırmalar yapılarak yöntemin ve cihazların kalibrasyonlarının geliştirilmesi gerekmektedir. Böylelikle Vis-NIR ve pXRF spektraları ile toprak özelliklerinin tahmin ve karakterize edilmesinde başarı performansının artacağı öngörülmektedir.
Türkiye’de Yetişen Campanula lyrata Lam. subsp. lyrata’nın Enzim İnhibe Edici Etkilerinin ve Antioksidan Aktivitelerinin Belirlenmesi
Authors: AYAZ Fatma
Published: February 2021

Bu çalışmanın amacı, Türkiye’de yetişen Campanula lyrata Lam. subsp. lyrata’nın toprak üstü kısımlarından elde edilen metanol ve su ekstrelerinin antioksidan ve enzim inhibe edici aktivitelerini araştırmaktır. Ekstrelerin in vitro antioksidan aktiviteleri toplam fenol ve flavonoit miktar tayini, 2-2´-difenil-1-pikirhidrazil (DPPH), 2,2'-azino-bis (3-etilbenzotiyazolin-6-sulfonik asit) (ABTS), demir şelasyon ve β-Karoten/linoleik asit emülsiyon yöntemleri kullanılarak test edilmiştir. Ekstrelerin enzim inhibe edici aktivitelerinde ise, Alzheimer hastalığıyla ilişkili olan asetilkolinesteraz ve butirilkolinesteraz enzimleri; diyabet hastalığıyla ilişkili α-amilaz ve α-glukozidaz enzimleri; cilt beyazlatıcı olarak kozmetikte önemli bir yere sahip olan tirozinaz enzimi test edilmiş ve 96-kuyucuklu plaka yöntemi kullanılmıştır. Araştırma sonuçlarına göre, C. lyrata subsp. lyrata’nın metanol ve su ekstrelerinin DPPH ve demir şelasyon aktivitesi dışında referans maddeyle karşılaştırılabilir düzeyde antioksidan aktivitelere sahip oldukları tespit edilmiştir. Ayrıca, ekstrelerin α-amilaz ve tirozinaz enzimleri üzerinde daha belirgin aktivite gösterdikleri ve diğer enzimlere kıyasla daha fazla inhibe edici etkilere sahip oldukları gözlenmiştir. Sonuç olarak çalışmamız, C. lyrata subsp. lyrata üzerinde aktiviteden sorumlu bileşiklerin araştırılmasına yönelik ilerideki çalışmalara katkı sağlayacak nitelik taşımaktadır.
Amniotic fluid microbiome in asymptomatic pregnants at second trimester
Authors: KÖMÜRCÜ KARUSERCİ Özge , ZER Yasemin , SUCU Seyhun , İŞBİLEN Elif , BADEMKIRAN Hanifi , TAŞDEMİR Hilmi
Published: February 2021

Aim: The purpose of this prospective cohort study is to evaluate the possible microbiome of the amniotic cavity in the second trimester in asymptomatic pregnant women by the culture-based technique. Materials and Methods: This prospective cohort study was conducted in Gaziantep University Gynecology and Obstetrics Clinic between October 2017 and November 2019. 100 pregnant women who had amniocentesis for genetic screening in the fetus, and who had no complaints or clinical symptoms of vaginal or chorioamnionitis infection, were included in the study. While culture tests were performed by using the amniotic fluids of these pregnant women, glucose and leukocyte levels of their amniotic fluids were also measured. At the same time, culture and gram staining analyses were performed by collecting vaginal swab specimens from the patients. Results: 12 patients (12%, 95% confidence interval, 0 to 41%) had positive amniotic fluid culture results. The most observed bacteria were E. coli (5%). No findings of clinical infection were observed in the patients with positive amniotic fluid culture results. These patients delivered healthy babies with no complications. Conclusion: The amniotic fluid has its own microbiome, and the vaginal flora plays a role in the formation of this microbiome. This is a preliminary study; therefore, larger studies and targeted broad range molecular methods are needed to find the variety of the possible flora of the amniotic fluid.
Kewenangan Kurator Dalam Pemberhentian Direksi Perseroan Terbatas
Authors: Kartika Clara Renny
Published: February 2021

Direksi Perseroan Terbatas sebagai organ Perseroan memiliki tanggung jawab terhadap kepengurusan Perseroan Terbatas yang mengartikan bahwa Perseroan tidak akan ada apabila tanpa peranan Direksi dan begitu pula sebaliknya. Apabila terjadi kepailitan, Direksi Perseroan Terbatas dapat diberhentikan oleh Rapat Umum Pemegang Saham (RUPS) dengan persetujuan dari Kurator yang diatur dalam Undang-Undang Perseroan Terbatas. Kurator tidak berwenang mengadakan RUPS sendiri dan mengubah anggaran dasar tanpa adanya peranan RUPS. Akibat hukum dari adanya pemberhentian Direksi Perseroan Terbatas memberikan berbagai dampak yang mempengaruhi kelangsungan usaha-usaha perusahaan itu sendiri atau terhadap pemegang saham lainnya bila mekanisme pemberhentiannya tidak sesuai dengan ketentuan yang berlaku walaupun tidak dirasakan secara langsung akibat yang ditimbulkannya. Jika Direksi dilepaskan tanggung jawabnya melalui pemberhentian oleh Kurator maka hal ini dapat dinilai terjadi ketidakefektifan dalam pengurusan dan pemberesan harta pailit karena sebenarnya organ Perseroan Terbatas yang mana itu Direksi masih dibutuhkan oleh Kurator dalam penanganan hal tersebut. Pemberhentian Direksi oleh Kurator ini juga dinilai dapat menghalangi keberlakuan proses rehabilitasi yang mana Direksi berhak mengajukan rehabilitasi kepada Pengadilan yang telah mengucapkan putusan pernyataan pailit. Direksi Perseroan Terbatas yang diberhentikan oleh Kurator dapat melakukan upaya hukum yang berupa gugatan lain-lain tindakan Kurator serta melakukan pelaporan ke Dewan Kehormatan Organisasi asal Kurator terkait pelanggaran kode etik yang dilakukan oleh Kurator.
Role of Education in the Concept of Innovative Economic Development
Authors: Vedeneeva V.
Published: February 2021

Innovations are the main form of transformation of knowledge into welfare. They represent a key feature of a post-industrial economy and of the relevant knowledge-based economy in which the knowledge becomes a critical factor and a primary source of socio-economic development. The shaping of the educational services market is one of requirements for transition to a post-industrial society, which presupposes a comprehensive modernization of the country. The statement of modernization itself primarily applies to education, – both basic and further. In Russia, a new structure of higher education was created, in which the leading role belongs to federal and national universities designed to prepare professionals for the new economy and science. In the transition period, one of the main tasks of higher education is to train engineers of innovative type. However, the level of engineering education in universities as a whole does not meet the requirements of an innovative economy, and the most demanded professions do not belong to the sphere of innovations. Young people are still motivated to obtain a profession that allows to ensure high wages, primarily in the financial sector and management. This problem is solved by developing a real cooperation between universities and business, by the expansion of academic mobility, as well as the introduction of additional professional development programs and training of engineering personnel.
Evolution of French Social State Model
Authors: Trofimova O.
Published: February 2021

The configuration of French welfare state is determined by a mix of factors. Historically, the nation’s social insurance system is based on the principles of solidarity, social protection, collective efforts and government’s responsibility. To a large extent this explains its paternalistic features. The French social model has a complex institutional structure and consists of different insurance schemes which are highly segmented according to the professions and industries, to belonging to the private or public sectors. The article deals with the theoretical framework, specifics of the development and modernization of French social model, its adaptation to the most recent economic changes triggered by the processes of globalization and European integration. The French welfare state’s transformations are necessitated by domestic and external economic, social and political challenges. The financing of the system is largely based on Bismarkian principle, namely, the bulk of social contributions are traditionally assumed by the firms along with the workers themselves. But it is mixed with a dose of Beveridgian society with its wide solidarity via general taxation. The author focuses on the welfare policy and legislation framework according to its model and type of regime. The analysis of the reform’s process reveals the specifics of the weaknesses of French model which still faces contradictions between dirigist and market approaches in resolving social problems, between the aims of economic effectiveness and social protection. Successive reforms of the social protection system towards reductions of state social expenditures and privatization of pensions will help France to recalibrate its welfare model in accordance with a new logic at the European level and its mainstream in social policy. Acknowledgements. The article has been supported by a grant of the Russian Humanitarian Scientific Foundation. Project no. 14-07-00048 “Transformation of Concept and Practices of Social State in EU Countries”.
Digital Technologies in TV and Transformation of Media Market
Authors: Rozanova N. , Yushin A.
Published: February 2021

The article analyzes new phenomena in the field of television associated with the digital era, in particular, the transformation of media market under the influence of technological, economic, financial and institutional factors of digitalization. Contemporary international and Russian television industry is in the process of digital revolution. The era of traditional television as a typical broadcasting technology, a traditional social, economic and cultural phenomenon, has come to an end. We are on the verge of a global and irrevocable shift to mass utilization of various digital devices that certainly affect the positions of television as a separate industry. Modern television is outlined as a part of a wide digital media market, just a segment of a highly competitive entertainment structure with complex network interactions. In terms of Russia, the new phenomena accompanying the evolution of media and television markets in the process of digitalization urgently need an economic analysis. In what direction is it necessary to develop the local broadcasting? Is there a sound commercial future of national and regional television companies? What lessons can extract Russia from world experience? What else does Russian television need to improve efficiency and global competitiveness? These issues are detail considered in the article. Trends and obstacles for the implementation of a prospective business model for Russian TV are shown. It is concluded that successful development of the Russian television industry is possible only under the conditions of efficient formation of a fundamentally new configuration of a multi-market structure type.
Androgen Receptor Binding Category Prediction with Deep Neural Networks and Structure-, Ligand-, and Statistically-Based Features
Authors: García-Sosa Alfonso T.
Published: February 2021

Substances that can modify the androgen receptor pathway in humans and animals are entering the environment and food chain with the proven ability to disrupt hormonal systems and leading to toxicity and adverse effects on reproduction, brain development, and prostate cancer, among others. State-of-the-art databases with experimental data of human, chimp, and rat effects by chemicals have been used to build machine learning classifiers and regressors and evaluate these on independent sets. Different featurizations, algorithms, and protein structures lead to dif- ferent results, with deep neural networks (DNNs) on user-defined physicochemically-relevant features developed for this work outperforming graph convolutional, random forest, and large featurizations. The results show that these user-provided structure-, ligand-, and statistically-based features and specific DNNs provided the best results as determined by AUC (0.87), MCC (0.47), and other metrics and by their interpretability and chemical meaning of the descriptors/features. In addition, the same features in the DNN method performed better than in a multivariate logistic model: validation MCC = 0.468 and training MCC = 0.868 for the present work compared to evalu- ation set MCC = 0.2036 and training set MCC = 0.5364 for the multivariate logistic regression on the full, unbalanced set. Techniques of this type may improve AR and toxicity description and predic- tion, improving assessment and design of compounds. Source code and data are available at https://github.com/AlfonsoTGarcia-Sosa/ML
Neurophobia: A Study of Australian Medical Students and Junior Doctors
Authors: Yeung Alex Lai Ming , Karimi Leila , Wijeratne Tissa
Published: February 2021

Background: Neurological disorders are the leading cause disability in Australia and the world. Combating the perceived difficulty of neurology or “neurophobia” and improving physician education is a key component in addressing this problem. We aim to conduct the first study to identify whether neurophobia exists in medical students and junior doctors in an Australian population and try to identify factors that may contribute to this in this population. Methods: A 24 question online validated survey was distributed via email broadcast to all medical students and junior doctors at a metropolitan tertiary care centre in Australia. Responses were collected over 6 weeks with weekly reminder emails for 4 weeks after the initial invitation email. Results: 114 medical students and junior doctors participated in the study. Participants perceived neurology as the most difficult medical speciality compared to 10 other medical specialties (p=0.001). The top three factors contributing to this perceived difficulty were: a lack of understanding of neuroanatomy, lack of diagnostic certainty and lack of clinical exposure. 65% of the participants stated that they had too little planned teaching in neurology with only 36% of the participants having performed a neurology rotation during medical school. Conclusion: The prevalence of neurophobia in this Australian cohort of medical students and junior doctors is consistent with previous findings from around the world. This concerning finding requires further examination into the contributing factors in order to created trials of targeted interventions in order to resolve this.
Normality Testing of High-Dimensional Data Based on Principle Component and Jarque-Bera Statistics
Authors: Song Ya-nan , Zhao Xuejing
Published: February 2021

The testing of high-dimensional normality has been an important issue and has been intensively studied in literatures, it depends on the Variance-Covariance matrix of the sample, numerous methods have been proposed to reduce the complex of the Variance-Covariance matrix. The principle component analysis(PCA) was widely used since it can project the high-dimensional data into lower dimensional orthogonal space, and the normality of the reduced data can be evaluated by Jarque-Bera(JB) statistic on each principle direction. We propose two combined statistics, the summation and the maximum of one-way JB statistics, upon the independency of each principle direction, to test the multivariate normality of data in high dimensions. The performance of the proposed methods is illustrated by the empirical power of the simulated data of normal data and non-normal data. Two real examples show the validity of our proposed methods.
Epidemic Evolution: Source, Lock-down and Removal Modifications to the SIR Model
Authors: Lerche Ian
Published: February 2021

The original purpose of this article was to modify the original SIR equations to allow for a direct source of infection (without which the original equations would have no solutions unless one starts with an already infected population) and also to see to what extent one could obtain multiple outbreaks of an infectious disease. In the course of developing the basic ideas several other factors arose to take prominent roles.Perhaps one of the more salient factors is the point that choosing an arbitrary time to change conditions from say a lock-down for the population to a less stringent social behavior, such as allowing partial or complete opening of businesses and schools, etc. should be based on knowledge of the disease and its evolution. Such decisions are usually made by politicians who have less than full information concerning the consequences of their actions. Several examples are given to illustrate these points.
Evaluation of COVID-19 spread effect on the Commercial Instagram Posts (CIPs) using ANN: a case study on Holy Shrine, Mashhad, Iran
Authors: Shooshtari Mohammad Javad , Etemadfard Hossein , Shad Rouzbeh
Published: February 2021

The widespread deployment of social media has helped researchers access an enormous amount of data in various domains, including the pandemic caused by the COVID-19 spread. This study presents a heuristic approach to classify Commercial Instagram Posts (CIPs) and explores how the businesses around the Holy Shrine – a sacred complex in Mashhad, Iran, surrounded by numerous shopping centers – were impacted by the pandemic. Two datasets of Instagram posts (one gathered data from March 14th to April 10th, 2020, when Holy Shrine and nearby shops were closed, and one extracted data from the same period in 2019), two word embedding models – aimed at vectorizing associated caption of each post, and two neural networks – multi-layer perceptron and convolutional neural network – were employed to classify CIPs in 2019. Among the scenarios defined for the 2019 CIPs classification, the results revealed that the combination of MLP and CBoW achieved the best performance, which was then used for the 2020 CIPs classification. It is found out that the fraction of CIPs to total Instagram posts has increased from 5.58% in 2019 to 8.08% in 2020, meaning that business owners were using Instagram to increase their sales and continue their commercial activities to compensate for the closure of their stores during the pandemic. Moreover, the portion of non-commercial Instagram posts (NCIPs) in total posts has decreased from 94.42% in 2019 to 91.92% in 2020, implying the fact that since the Holy Shrine was closed, Mashhad citizens and tourists could not visit it and take photos to post on their Instagram accounts.
Extending Cooling Rate Performance of Fast Scanning Chip Calorimetry by Liquid Droplet Cooling
Authors: Zhuravlev Evgeny , Jiang Jing , Zhou Dongshan , Androsch René , Schick Christoph
Published: February 2021

The liquid droplet cooling technique for fast scanning chip calorimetry (FSC) is introduced, increasing the cooling rate for large samples on a given sensor. Reaching higher cooling rates and using a gas as the cooling medium, the common standard for ultra-fast temperature control in cooling, requires reducing the lateral dimensions of the sample and sensor. The maximum cooling rate is limited by the heat capacity of the sample and the heat exchange between the gas and the sample. The enhanced cooling performance of the new liquid droplet cooling technique is demonstrated for both metals and polymers, on examples of solidification of large samples of indium, high-density polyethylene (HDPE), and poly (butylene 2,6-naphthalate) (PBN). It was found that the maximum cooling rate can be increased up to 5 MK/s in room temperature environment, that is, by 2 orders of magnitude, compared to standard gas cooling. Furthermore, modifying the droplet size and using coolants at different temperatures provide options to adjust the cooling rate in the temperature ranges of interest.
Osteoporosis
Authors: Anderson Paul A. , Freedman Brett A. , Brox W. Timothy , Shaffer William O.
Published: February 2021

➤ Osteoporosis is common in orthopaedic patients, not only in those sustaining fragility fractures but also in patients ≥50 years old who are having elective orthopaedic surgery.

➤ The American Society for Bone and Mineral Research (ASBMR) has developed consensus-based recommendations for secondary fracture prevention for all patients who are ≥65 years old with a hip or spine fracture.

➤ The ASBMR encourages orthopaedic surgeons to “Own the Bone,” by beginning prevention of a secondary fracture during hospitalization for a fragility fracture, if practicable, and arranging follow-up for continued bone health care after discharge.

➤ The International Society for Clinical Densitometry (ISCD) recognized that many poor outcomes and complications of elective orthopaedic surgery are related to osteoporosis.

➤ The ISCD used an evidence-based approach to create official positions to identify which patients ≥50 years old who are having elective orthopaedic surgery should undergo assessment of bone health and how this should be performed.
Osteogenesis Imperfecta
Authors: Kopplin Echo , Watkins Elyse
Published: February 2021

This article reviews the emerging literature on the efficacy of denosumab as a treatment for patients with osteogenesis imperfecta (OI). Denosumab improves bone density in adults with osteoporosis. However, a lack of evidence-based research exists to promote the use of denosumab as a current treatment in patients with OI. Denosumab research on bone density in patients with OI is ongoing. The evidence suggests that denosumab use in patients with OI does improve bone density but gives inconsistent results regarding fracture prevention. Further research must establish the dosing and measurable gains of denosumab treatment in OI.
PSYCHOLOGICAL EFFECTS OF PAKISTANI FILMS ON SPECTATORS WITH SPECIAL REFERENCE TO THE 21ST CENTURY FILMS
Authors: Sultana Noreen , Aqdas Kunza , Khan Sadaf , Mehmood Sohail , Mehmood Shahid
Published: February 2021

The aim of present paper is to investigate the psychological outcomes of 21st century Pakistani movies on viewers. The most important four outcomes are as following: (a) Violent behavior (b) Sensuality and Depression (c) Stereotypes (d) Misconception about Islam and Pakistani culture. By psychologically examining the theme of the film, we can take a look at the producer’s psychological methods and analyze the performance of the theme in the film. This paper is psychological analysis of five film themes and their carriage in productions. The films under analysis are Khuda Kay Liay (2007), Bol (2011), Bin Roye(2015), Malik (2016) Waar (2013). It is inferred from this study that these films have strong psychological impact on audience’s conscious and unconscious.
Climate and Hydrologic Ensembling Lead to Differing Streamflow and and Sediment Yield Predictions
Authors: Dahl Travis A. , Kendall Anthony D. , Hyndman David W.
Published: February 2021

This record contains datasets related to the journal article "Climate and Hydrologic Ensembling Lead to Differing Streamflow and Sediment Yield Predictions", which is currently undergoing submission to the journal Climatic Change.
Stable Semisimple Modules, Stable t- Semisimple Modules and Strongly Stable t-Semisimple Modules
Authors: Hadi Inaam Mohammed Ali
Published: February 2021

Throughout this paper, three concepts are introduced namely stable semisimple modules, stable t-semisimple modules and strongly stable t-semisimple. Many features co-related with these concepts are presented. Also many connections between these concepts are given. Moreover several relationships between these classes of modules and other co-related classes and other related concepts are introduced.
Determination of Sulfacetamide Sodium in Pure and Their Pharmaceutical Formulations by Using Cloud Point Extraction Method
Authors: Alaallah Nisreen jassam , Dhahir Saadiyah Ahmad , Ali Hameed Hussein
Published: February 2021

In this study, simple, low cost, precise and speed spectrophotometric methods development for evaluation of sulfacetamide sodium are described. The primary approach contains conversion of sulfacetamide sodium to diazonium salt followed by a reaction with p-cresol as a reagent in the alkaline media.  The colored product has an orange colour with absorbance at λmax 450 nm. At the concentration range of (5.0-100 µg.mL-1), the Beer̆ s Low is obeyed with correlation coefficient (R2= 0.9996), limit of detection as 0.2142 µg.mL-1, limit of quantification as 0.707 µg.mL-1 and molar absorptivity as 1488.249 L.mol-1.cm-1. The other approach, cloud point extraction was utilized to an estimation of a trace amount of the colored product in the previous procedure followed by a measuring process with a UV-Vis spectrophotometer. The linearity of the calibration graph was above the range of (1.0-60 µg.mL-1), the correlation coefficient (R2= 0.9991) and molar absorptivity was 7417.622 L.mol-1.cm-1. The detection limit(LOD) and quantification limit(LOQ) were based to be  0.070 and 0.231 µg.mL-1 , respectively. This approach was successfully employed for sulfacetamide sodium detection within the pure and pharmaceutical formulation.
Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System
Authors: Salah Hussein Ali , Ahmed Ahmed Shihab
Published: February 2021

Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breathing difficulty) used to diagnose the person being infected by COVID-19 virus or not. Secondly, this approach divides the infected peoples into four classes, based on their immune system risk level (very high degree, high degree, mild degree, and normal), and using two indices of age and current health status like diabetes, heart disorders, or hypertension. Where, these people are graded and expected to comply with their class regulations. There are six important COVID-19 virus infections of different classes that should receive immediate health care to save their lives. When the test is positive, the patient age is considered to choose one of the six classifications depending on the patient symptoms to provide him the suitable care as one of the four types of suggested treatment protocol of COVID-19 virus infection in COVID-19 DSS application. Finally, a report of all information about any classification case of COVID-19 infection is printed where this report includes the status of patient (infection level) and the prevention protocol. Later, the program sends the report to the control centre (medical expert) containing the information. In this paper, it was suggested the use of C4.5 Algorithm for decision tree.
An Efficient Image Encryption Using a Dynamic, Nonlinear and Secret Diffusion Scheme
Authors: RIMANI Rachid , SAID Naima HADJ , PACHA Adda ALI , RAMOS Juan Antonio López
Published: February 2021

The growing use of tele
This paper presents a new secret diffusion scheme called Round Key Permutation (RKP) based on the nonlinear, dynamic and pseudorandom permutation for encrypting images by block, since images are considered particular data because of their size and their information, which are two-dimensional nature and characterized by high redundancy and strong correlation. Firstly, the permutation table is calculated according to the master key and sub-keys. Secondly, scrambling pixels for each block to be encrypted will be done according the permutation table. Thereafter the AES encryption algorithm is used in the proposed cryptosystem by replacing the linear permutation of ShiftRows step with the nonlinear and secret permutation of RKP scheme; this change makes the encryption system depend on the secret key and allows both to respect the second Shannon’s theory and the Kerckhoff principle. Security analysis of cryptosystem demonstrates that the proposed diffusion scheme of RKP enhances the fortress of encryption algorithm, as can be observed in the entropy and other obtained values.
communications implementing electronic transfers of personal data, require reliable techniques and secure. In fact, the use of a communication network exposes exchanges to certain risks, which require the existence of adequate security measures. The data encryption is often the only effective way to meet these requirements. This paper present a cryptosystem by block for encrypting images, as images are considered particular data because of their size and their information, which are two dimensional nature and characterized by high redundancy and strong correlation. In this cryptosystem, we used a new dynamic diffusion technique called round key permutation, which consists to permute pixels of each bloc in a manner nonlinear, dynamic and random using permutation table calculated according to the master key and sub-keys. We use thereafter the AES encryption algorithm in our cryptosystem by replacing the linear permutation of ShiftRows with round key permutation technique; this changing makes the encryption scheme depend on encryption key. Security analysis of cryptosystem demonstrate that the modification made on using the proposed technique of Round Key Permutation enhances the fortress of encryption  algorithm,  as can be observed in the entropy and other obtained values.
Near-Infrared Heterojunction Field Modulated Phototransistors with Distinct Photodetection/Photostorage Switching Feature for Artificial Visuals
Authors: Wang Jun , Du Xiaoyang , Han Jiayue , Zhang Zhenghan , He Zeyu , Xie RunZhang , Shan Chong-Xin , Tao Silu , Hu Weida , Ming Yang , Gou Jun , Wu Zhiming , Jiang Yadong
Published: February 2021

With the rising demand of recording, computing and image capture, advanced optoelectronic detection, storage and logic devices are highly pursued. Nevertheless, multi-functional vision chip based on infrared detection and memory switching has never been demonstrated. Here, by utilizing the electronic extraction layer ZnO and face-on orientation of D-A, we exhibit the broadband visible to near-infrared photo-response and photo-storage characters on graphene phototransistor. Functions as photodetection and photo-storage can be switched with the variation of gate voltage. The device demonstrates high photo-responsivity up to 1.88 × 106 A/W at 895 nm corresponding detectivity of 4.8 × 1012 Jones. Importantly, the rewritable and switching infrared optoelectronic memory function can be achieved with good retention over 104 s. The both retinomorphic vision and memorial preprocessing in artificial visual are simultaneously realized by photodetection/photostorage switching property. Such nearly all-solution processes in our phototransistors may open up the path for the large-scale and easy manufacturing infrared multifunctional bio-optoelectronic device.
Burnout syndrome among medical students in Kazakhstan
Authors: Bolatov Aidos K. , Seisembekov Telman Z. , Askarova Altynay Zh. , Igenbayeva Bahyt B. , Smailova Dariga S. , Hosseini Hengameh
Published: February 2021

This study aims at investigating burnout and associated factors in a sample of medical students from Astana Medical University (AMU), using the Russian version of the Copenhagen Burnout Inventory - Student Survey (R-CBI-S), which was validated in the current study. 771 medical students responded. The study included socio-demographic and personal questions, and a tool to measure burnout. Statistical analyses included test-retest reliability, internal consistency, item analysis, confirmatory factor analysis for validation and measures of descriptive statistics, and logistic regression analysis for evaluating burnout. The R-CBI-S demonstrated good reliability and validity. The test-retest reliability showed an ICC of 0.81. Cronbach’s alpha coefficient was 0.94. R-CBI-S achieved good levels of goodness-of-fit indices (RMSEA = 0.0611; CFI = 0.940; TLI = 0.933). Overall, 28% of medical students reported burnout; R-CBI-S mean score was 40. There is no significant gender difference in burnout. On regression analysis, to be a 2nd year student, compare to dormitory students live at home or rented a house, having suicidal ideation, having thoughts of dropping out, having interpersonal relationship problems with family or friends, smoking, using alcohol were independently associated with increased risk for burnout. Enrolling in a medical university by its own decision and having satisfaction with academic performance associated with a decreasing of developing burnout syndrome. In conclusion, the test results indicated the R-CBI-S scale appears to be a reliable and valid instrument. Factors associated with burnout were identified.
Prevalence and correlates of psychological distress, unmet supportive care needs, and fear of cancer recurrence among haematological cancer patients during the COVID-19 pandemic
Authors: Zomerdijk Nienke , Jongenelis Michelle , Short Camille E , Smith Andrew , Turner Jane , Huntley Kathryn
Published: February 2021

Background The COVID-19 pandemic has had a disruptive effect on people with haematological cancers, who represent a high-risk population due to the nature of their disease and immunosuppressive treatments. We aimed to identify the psychological impacts of the COVID-19 pandemic on haematology patients and identify correlated factors to inform the development of appropriate supportive interventions.Methods 394 respondents volunteered their participation in response to a study advertisement distributed online through established haematology groups. Participants completed a self-report online survey exploring well-being, psychological distress, unmet supportive care needs, and fear of cancer recurrence.Results At least 1 in 3 respondents (35%) reported clinical levels of distress and nearly 1 in 3 (32%) identified at least one unmet need. Among respondents in remission (n = 134), clinical fear of cancer recurrence was reported by nearly all (95%). Unmet needs, pre-existing health conditions, younger age, financial concerns, and perceived risk of contracting COVID-19 were the dominant factors contributing to psychological distress during the pandemic. Psychological distress, lost income, perceived inadequate support from care team, perceived risk of contracting COVID-19, and being a woman were significantly associated with unmet needs. Psychological distress and concern about the impact of COVID-19 on cancer management were significantly associated with fear of cancer recurrence among respondents in remission.Conclusion Results highlight the high psychological burden and unmet needs experienced by people with haematological cancers during the COVID-19 pandemic and indicate a need for innovative solutions to rapidly identify distress and unmet needs during, and beyond, pandemic times.
The role of B cells in regulation of Th cell differentiation in Coxsackievirus B3-Induced Acute Myocarditis
Authors: Cen Zhihong , Li Yong , Wei Bin , Wu Weifeng , Huang Yanlan , Lu Jing
Published: February 2021

Background:Viral myocarditis (VMC) is the major cause of sudden death in adolescents. To date, no effective treatment has been identified for VMC. Studies have shown that T helper (Th) cells such as Th1, Th2, Th17, and Th22 cells are involved in the pathogenesis of VMC. However, the role of B cells and their impact on Th cells in VMC is unclear. In this study, we investigated the role of B cells in Th cell differentiation in myocardial damage in an animal model of VMC.Methods and Results:C57BL/6 mice were infected with Coxsackievirus B3 (CVB3) intraperitoneally or injected with phosphate-buffered saline as a control condition. At day 7, samples from these mice were analyzed by histology, ELISA, flow cytometry, and gene expression assays. We found that TNF-α-, IL-6-, and IL-17-producing B cell numbers were significantly increased, while IL-4-producing B cell population was significantly reduced in acute VMC. Furthermore, we performed B cell knockout (BKO), SCID, and SCID+B cells reconstitution experiments. We found that BKO alleviated the cardiac damage following CVB3 infection, may hamper the differentiation of Th1 and Th17 cells, may promote the differentiation of Th2 cells, and proved ineffective for the differentiation of Th22 cells. In contrast, SCID+B cells reconstitution experiment exacerbated the cardiac damage. Ex vivo studies further revealed that B cells promote the differentiation of Th1 and Th17 cells and inhibit the differentiation of Th2 cells.Conclusions:Our study shows that B cells are activated and have strong abilities of antigen presentation and producing cytokines in VMC; B cells not only play a pathogenic role in VMC independent of T cells, but also promote Th1 and Th17 cell differentiation, and hamper Th2 cell differentiation in VMC.
Modeling and Prediction of the Transmission Dynamics of COVID-19 Based on the SINDy-LM Method
Authors: Jiang Yu-Xin , Du Lin , Xiong Xiong , Zhang Shuo , Wang Jia-Xiang , Li Jia-Chun
Published: February 2021

The transmission dynamics of COVID-19 is investigated in this study. A SINDy-LM modeling method that can effectively balance model complexity and prediction accuracy is proposed based on data-driven technique. First, the Sparse Identification of Nonlinear Dynamical systems (SINDy) method is used to discover and describe the nonlinear functional relationship between the dynamic terms in the model in accordance with the observation data of the COVID-19 epidemic. Moreover, the Levenberg–Marquardt (LM) algorithm is utilized to optimize the obtained model for improving the accuracy of the SINDy algorithm. Second, the obtained model, which is consistent with the logistic model in mathematical form with small errors and high robustness, is leveraged to review the epidemic situation in China. Otherwise, the evolution of the epidemic in Australia and Egypt is predicted, which demonstrates that this method has universality for constructing the global COVID-19 model. The proposed model is also compared with the extreme learning machine (ELM), which shows that the prediction accuracy of the SINDy-LM method outperforms that of the ELM method and the generated model has higher sparsity.