Investigating the Effects of Am rap and Classic Cross-fit Training in Freestyle Wrestlers on Physical Fitness Parameters

This study aims to investigate anaerobic strength alterations of wrestlers who perform AMRAP (As many reps as possible) and Classic CrossFit pieces of training. The research was implemented on 32 male wrestlers who were challenged in the Turkish Wrestling 1st League in the season of 2018-2019. The volunteer participants taken part in test groups performed CrossFit models in the preseason for 8-weeks; Group I (Classic CrossFit) and Group II (CrossFit AMRAP). Bodyweight, height, and age values were recorded respectively by creating measuring parkour and arranged on MS Excel spreadsheet program. Two-factor variance analysis was used in repetitive measurements for identifying the differences between pre and final measuring anaerobic strength values of the participants. As findings, it was observed there was a significant difference in terms of group x time interaction dimension in back squat movement, 1 min on behalf of AMRAP. According to the simple effect test results, there were significant values in both groups. The numerical increase in some performance values of the AMRAP CrossFit training group after 8-weeks of training was more prominent than the classic CrossFit training group. In addition, AMRAP CrossFit training was effective in reducing body weight. Both models were found to have a positive effect on their physical capacities effectively. Although there are studies on CrossFit in the literature, there is no significant study on AMRAP and thus this study might be the pioneer in terms of contributions to the literature and lead to further comments on sports science as well. Thus, this study is significant to reveal the effectiveness of Amrap and CrossFit training on physical fitness parameters.

Null Distribution of the Test Statistic for Model Selection via Marginal Screening: Implications for Multivariate Regression Analysis

Marginal screening (MS) is the computationally simple and commonly used for the dimension reduction procedures. In it, a linear model is constructed for several top predictors, chosen according to the absolute value of marginal correlations with the dependent variable. Importantly, when kpredictors out of mprimary covariates are selected, the standard regression analysis may yield false-positive results if m>> k(Freedman's paradox). In this work, we provide analytical expressions describing null distribution of the test statistics for model selection via MS. Using the theory of order statistics, we show that under MS, the common F-statistic is distributed as a mean of ktop variables out of mindependent random variables having a 21χdistribution. Based on this finding, we estimated critical p-values for multiple regression models after MS, comparisons with which of those obtained in real studies will help researchers to avoid false-positive result. Analytical solutions obtained in the work are implemented in a free Excel spreadsheet program.

XLSIM: Developing a Software Tool to Assist Training and Learning in Microsimulation Modelling

This chapter describes the development of a training model, XLSIM, a static tax-benefit model built upon on the Microsoft Excel© platform and used in microsimulation modelling. The chapter first describes, in general terms, the theoretical requirements of developing a microsimulation model. It then catalogues an evaluation of the choice of software to be used for training purposes, justifying the use of a spreadsheet program. The chapter later describes in more detail the components of microsimulation models and some of the advantages and constraints of these models in the context of this framework. Finally, the structure of the model, the databases used by the model, and the structure of the individual worksheets of the model are described.

Necrotizing Fasciitis: Risk Factors and Outcomes in the COVID-19 Era

Background: Necrotizing Fasciitis is a severe, rapidly spreading soft tissue infection with high morbidity and mortality. Diabetes mellitus, hypertension, and immune suppression are the some of the predisposing factors for the disease. The objective of this study was to study the risk factors and outcomes of necrotizing fasciitis in the COVID-19 era. Methods and Materials: a retrospective analysis of the data of forty-four patients admitted with the diagnosis of NF from April 2020 to April 2021was done at Dr Ram Manohar Lohia Hospital, New Delhi. Data was recorded in MS Excel spreadsheet program. SPSS v23 (IBM Corp.) was used for data analysis. Descriptive statistics were elaborated in the form of means/standard deviations and medians/IQRs for continuous variables, and frequencies and percentages for categorical variables. Chi-square test (X2) was used for group comparisons of categorical data. Results: Out of forty-four patients, 26 (59.10%) were male and 18 (40.9%) were female. The mean age was 54.2 years (+ 14.4 years). Extremities (68.2%) were the most commonly involved site followed by perineum (29.5%) and abdominal wall (2.2%). Diabetes mellitus (DM) was the most prevalent comorbidity. 10 patients had both DM and hypertension (HTN). Fourteen patients (32%) had a polymicrobial infection on tissue culture. Rest thirty patients had involvement of gram positive (44%) and gram negative (24%) organisms. Twenty-two patients (50%) had healthy granulation tissue as the final outcome. However, the rest 50% patients had a poor outcome in form of amputation (13.63%) and mortality (36.36%). Average duration from onset of symptoms to presentation at the hospital was 7.11 (+ 3.47) days. Patients who presented early to the hospital within 7 days of symptom onset had a good outcome in the form of healthy granulation tissue (X2= 7.62 and p <0.05). Conclusions: Early diagnosis and prompt surgical intervention in necrotizing fasciitis is the key to its management. Delayed presentation was because of restricted movement, government-imposed lockdowns, patients ignoring their symptoms, and resorting to self-medications. The delay in diagnosis leading to a delay in treatment is one of the major factors contributing to poor outcomes in the COVID-19 era. Keywords: necrotizing fasciitis, risk factors, COVID 19.

Pelatihan Pemanfaatan Spreadsheet untuk Meningkatkan Kompetensi Guru SMK Bisnis dan Manajemen dalam Menyusun Laporan Keuangan

Based on interviews conducted with the Head of the Vocational High School Management and Business Vocational High School Subject Teacher Conference in West Sumatra Province, it was found that teachers need to improve their competence about the use of Computer Accounting Applications. It is known that teachers still lack competence, and teachers are still unfamiliar with how to operate various menus and functions that can be used in a spreadsheet program to complete company financial reports. Based on this condition, the teaching and learning process for subjects has been done more with the lecture method and a little practice. So that this affects the competence of SMK graduates. In fact, the guidance for the world of work requires SMK graduates to operate this application program properly. The community's activity was carried out for two days on 18 and 19 September 2020 at SMKN 2 Kota Padang. The implementation is carried out in three stages, namely material presentation, integrated training, and evaluation. At the end of the activity, it was known that there was an increase in the understanding of the participants regarding the preparation of financial statements of trading companies using Microsoft Excel with a case settlement value that could be achieved was 85.71%. Furthermore, this increase in teacher competence is expected to be transferred to students and is reflected in the value of UKK and the acceptance of graduates in the world of work.

APPLICATION FOR CALCULATING THE PARAMETERS OF A GAS SENSOR FROM THE EXPERIMENTAL KINETIC DEPENDENCE OF RESPONSE

The elements of the structure and user interface of a specialized application for processing experimental data and calculating the parameters of gas sensors, based on the concept of using various software, packages and media are presented that are most effective at each stage. The application provides such service functions as data entry using Excel spreadsheet program; calculations in the mathematical package "Mathcad"; test item examples of using computational algorithms and providing the necessary textual information from internal sources and the Internet.

Epidemiologic Modeling of COVID-19 in Amhara Region, Ethiopia: Using The Best and Worst Scenarios Experienced in The World

Background: The ongoing pandemic of the novel coronavirus (SARS-CoV-2) is currently the first public health agenda. Citizens of resource-poor countries like Ethiopia could be most affected by the pandemic unless aggressive plans are implemented. Despite the prevention and control efforts being made at the national and regional levels, there is no evidence about the worst and best scenarios in the number of COVID-19 cases expected in the Amhara Regional. Besides, there were no efforts to develop predicting models of future values in COVID-19 anticipated cases expected based on the current global trend.Objective: Forecast the latest epidemic situations by estimating and predicting cases and deaths of COVID-19 in the Amhara region.Methods: This study employed models by using the expected number of COVID-19 cases and deaths in Amhara National Regional State using the worst scenarios faced in the world. Data were extracted using a checklist. Existing data on morbidity and mortality by age and sex were collected through a literature search strategy including PubMed/Medline and the Google scholar database. Besides, the Worldometer of the novel COVID-19 was used as a source of data. This study used MS-Excel spreadsheet program for data extraction. COVID-19modeling was made using Susceptible- Infected-Recovered (SIR), Susceptible-Exposed Infected-Recovered (SEIR), and WHO DisMod II software. Result: Without any pharmacological intervention, based on the SEIR model, the expected number of peak COVID-19 cases could reach about 3 million cases occurring on July 29th, 2020.However, with an intervention that could reduce the transmission by 30%, would push the peak period to 22 days (20thAugust). Using the Susceptible–Infected—Recovered model without non-pharmacologic interventions, the expected number of peak COVID-19 cases is 5,947,685, occurring on July 2, 2020.The peak number of Hospitalization is 820, 781, in need of ICU 279,541and deaths 53,529. With the DisModII modeling, outputs showed that males are more affected than females. Accordingly, the total incident cases in the region were estimated to be 837,348 (474, 809 male and 362,540 female). The expected number of total deaths was also estimated at 44,247 (30, 176 male and 14, 071 female). Also, the middle age group is more infected but less at risk of death. The recovery rate decreases drastically as age increase.Conclusion: The discrepancies in findings from the three models used in this study could be driven mainly by data limitation in the Ethiopia context. However, our results from the different models highlight the need for more intervention on non-pharmacological interventions. Besides, highly influential parameters urge further study for better effective evidence-based decision making.