Search results for: microsoft

Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

Procedia PDF Downloads 156

Authors: Addisu Tadesse Sahile, Mussie Wubshet Teka, Solomon Muluken Ayehu

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Background: Diabetes is one of the common public health problems of the century that was estimated to affect one in a tenth of the world population by the year 2030, where diabetes ketoacidosis is one of its common acute complications. Objectives: The aim of this review was to assess the magnitude of diabetes ketoacidosis among patients with type 1 diabetes in Ethiopia. Methods: A systematic data search was done across Google Scholar, PubMed, Web of Science, and African Online Journals. Two reviewers carried out the selection, reviewing, screening, and extraction of the data independently by using a Microsoft Excel Spreadsheet. The Joanna Briggs Institute's prevalence critical appraisal tool was used to assess the quality of evidence. All studies conducted in Ethiopia that reported diabetes ketoacidosis rates among type 1 diabetes were included. The extracted data was imported into the comprehensive meta-analysis version 3.0 for further analysis. Heterogeneity was checked by Higgins’s method, whereas the publication bias was checked by using Beggs and Eggers’s tests. A random-effects meta-analysis model with a 95% confidence interval was computed to estimate the pooled prevalence. Furthermore, subgroup analysis based on the study area (Region) and the sample size was carried out. Result and Conclusion: After review made across a total of 51 articles, of which 12 articles fulfilled the inclusion criteria and were included in the meta-analysis. The pooled prevalence of diabetes ketoacidosis among type 1 diabetes in Ethiopia was 53.2% (95%CI: 43.1%-63.1%). The highest prevalence of DKA was reported in the Tigray region of Ethiopia, whereas the lowest was reported in the Southern region of Ethiopia. Concerned bodies were suggested to work on the escalated burden of diabetes ketoacidosis in Ethiopia.

Keywords: DKA, Type 1 diabetes, Ethiopia, systematic review, meta-analysis

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Authors: Zerihun Yohannes Amare, Belayneh Birku Geremew, Nigatu Melise Kebede, Sisaynew Getahun Amera

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In Ethiopia, agricultural production is predominantly rainfed. The El Niño Southern Oscillation (ENSO) is the driver of climate variability, which affects the agricultural production system in the country. This paper aims to study trends, variability of rainfall, and impacts of El Niño Southern Oscillation (ENSO) on rainfall amount. The study was carried out in Ethiopia's Western Amhara National Regional State, which features a variety of seasons that characterize the nation. Monthly rainfall data were collected from fifteen meteorological stations of Western Amhara. Selected El Niño and La Niña years were also extracted from National Oceanic and Atmospheric Administration (NOAA) from 1986 to 2015. Once the data quality was checked and inspected, the monthly rainfall data of the selected stations were arranged in Microsoft Excel Spreadsheet and analyzed using XLSTAT software. The coefficient of variation and the Mann-Kendall non-parametric statistical test was employed to analyze trends and variability of rainfall and temperature. The long-term recorded annual rainfall data indicated that there was an increasing trend from 1986 to 2015 insignificantly. The rainfall variability was less (Coefficient of Variation, CV = 8.6%); also, the mean monthly rainfall of Western Amhara decreased during El Niño years and increased during La Niña years, especially in the rainy season (JJAS) over 30 years. This finding will be useful to suggest possible adaptation strategies and efficient use of resources during planning and implementation.

Keywords: rainfall, Mann-Kendall test, El Niño, La Niña, Western Amhara, Ethiopia

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Authors: Wei Wen Yang, Emily Chia Yu Su

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Dengue fever is a mosquito-borne tropical infectious disease caused by the dengue virus. After infection, symptoms usually start from three to fourteen days. Dengue virus may cause a high fever and at least two of the following symptoms, severe headache, severe eye pain, joint pains, muscle or bone pain, vomiting, feature skin rash, and mild bleeding manifestation. In addition, recovery will take at least two to seven days. Dengue fever has rapidly spread in tropical and subtropical areas in recent years. Several phenomena around the world such as global warming, urbanization, and international travel are the main reasons in boosting the spread of dengue. In Taiwan, epidemics occur annually, especially during summer and fall seasons. On the other side, Singapore government also has announced the amounts number of dengue cases spreading in Singapore. As the serious epidemic of dengue fever outbreaks in Taiwan and Singapore, countries around the Asia-Pacific region are becoming high risks of susceptible to the outbreaks and local hub of spreading the virus. To improve public safety and public health issues, firstly, we are going to use Microsoft Excel and SAS EG to do data preprocessing. Secondly, using support vector machines and decision trees builds predict model, and analyzes the infectious cases between Taiwan and Singapore. By comparing different factors causing vector mosquito from model classification and regression, we can find similar spreading patterns where the disease occurred most frequently. The result can provide sufficient information to predict the future dengue infection outbreaks and control the diffusion of dengue fever among countries.

Keywords: dengue fever, Taiwan, Singapore, Aedes aegypti

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Authors: Authors: A. Lakhal, M. Bahalou, A. Khattabi

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Introduction: Tuberculosis is one of the world's deadliest infectious diseases. In Morocco, a total of 30,636 cases of Tuberculosis, all forms combined, were reported in 2015, representing an incidence of 89 cases per 100,000 population. The number of deaths from tuberculosis (TB) was 656 cases. In the prefecture of Meknes, its incidence remains high compared to the national level. The objective of this work is to describe the epidemiological profile of tuberculosis in the prefecture of Meknes. Methods: It is a descriptive analysis of TB cases reported between 2016 and 2020 at the regional diagnostic center of tuberculosis and respiratory diseases. We performed analysis by using Microsoft Excel and EpiInfo 7. Results: Epidemiological data from 2016 to 2020 report a total of 4100 new cases of all forms of tuberculosis, with an average of 820 new cases per year. The median age is 32 years. There is a clear male predominance, on average 58% of cases are male and 42% female. The incidence rate of bacteriologically confirmed tuberculosis per 100,000 inhabitants has increased from 35 cases per 100,000 inhabitants in 2016 to 39.4 cases per 100,000 inhabitants in 2020. The confirmation rate for pulmonary tuberculosis decreased from 84% in 2016 to 75% in 2020. Pulmonary involvement predominates by an average of 46%, followed by lymph node involvement 29%and pleural involvement by an average of 10%. Digestive, osteoarticular, genitourinary, and meningeal involvement occurs in 8% of cases. Primary tuberculosis infection occurs in an average of 0.5% of cases. The proportion of HIV-TB co-infections was 2.8 in 2020. Conclusion: The incidence of tuberculosis in Meknes remains high compared to the national level. Thus, it is imperative to reinforce the earlier detection; improve the contact tracing, detection methods of cases for their confirmation and treatment, and to reduce the proportion of the lost to follow up as well.

Keywords: tuberculosis, epidemiological profile, meknes, morocco

Procedia PDF Downloads 157

Authors: Merkineh Markos Lorato, Gedefaw Diress Alene

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Introduction: Visual impairment is any condition of the eye or visual system that results in loss/reduction of visual functioning. It significantly influences the academic routine and social activities of children, and the effect is severe for low-income countries like Ethiopia. So, this study aimed to determine the pooled prevalence of visual impairment among school children in Ethiopia. Methods: Databases such as Medical Literature Analysis and Retrieval System Online, Excerpta Medica dataBASE, World Wide Web of Science, and Cochrane Library searched to retrieve eligible articles. In addition, Google Scholar and a reference list of the retrieved eligible articles were addressed. Studies that reported the prevalence of visual impairment were included to estimate the pooled prevalence. Data were extracted using a standardized data extraction format prepared in Microsoft Excel and analysis was held using STATA 11 statistical software. I² was used to assess the heterogeneity. Because of considerable heterogeneity, a random effect meta-analysis model was used to estimate the pooled prevalence of visual impairment among school children in Ethiopia. Results: The result of 9 eligible studies showed that the pooled prevalence of visual impairment among school children in Ethiopia was 7.01% (95% CI: 5.46, 8.56%). In the subgroup analysis, the highest prevalence was reported in South Nations Nationalities and Tigray region together (7.99%; 3.63, 12.35), while the lowest prevalence was reported in Addis Ababa (5.73%; 3.93, 7.53). Conclusion: The prevalence of visual impairment among school children is significantly high in Ethiopia. If it is not detected and intervened early, it will cause a lifetime threat to visually impaired school children, so that school vision screening program plan and its implementation may cure the life quality of future generations in Ethiopia.

Keywords: visual impairment, school children, Ethiopia, prevalence

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Authors: Réka Kovács, György Téglásy, Szilvia Boros

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Introduction: Aim of the Study: Low body fat percentage frequently occurs in aesthetic sports. Because of the unrealistic expectations, their quantity and quality of nutrition intake are inadequate. This can be linked to several health issues which appear in blood samples (iron, ferritin, creatine kinase, etc.). Our retrospective study aimed to investigate the connection between body composition (InBody 770 monitor) and blood samples test results among elite adolescent (14-18 years) and adult (19-28 years) aesthetic athletes. Methods: Data collection happened between 01.08.2022. and 15.08.2022 in National Institute for Sports Medicine, Budapest. The final group consisted of 111 athletes (n=111; adolescents: n=68, adults: n=43). We used descriptive statistics, a two-sample t-test, and correlation analysis with Microsoft Office Excel 2007 software. Our results were considered significant if p<0,05. Results: In 33,3% (37/111) we found low body fat percentage (girls and women: <12%, boys and men: <8%) and in 64% (71/111) high creatine kinase levels. Differences were found mainly in the adolescent group. We found a correlation between body weight and total cholesterol, visceral fat and triglyceride, hematocrit and iron-linking capacity, moreover body fat percentage and ferritin levels. Discussion: It is important to start education about sports nutrition at an early age. The connection between low body fat percentage, serum iron, triglyceride, and ferritin levels refers to the fact that the nutrition intake of the athletes is inadequate. High blood concentrations of creatine kinase may show a lack of proper recovery, which is essential to improve health and performance.

Keywords: body fat percentage, creatine kinase, recovery, sports nutrition

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Authors: Venuste Kayinamura, V. Iyamuremye, A. Ngirabakunzi

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Anti-retroviral therapy (ART) for HIV patient can cause a deficiency in glucose metabolism by promoting insulin resistance, glucose intolerance, and diabetes, diabetes mellitus keep increasing among HIV-infected patients worldwide but there is limited data on levels of blood glucose and its relationship with antiretroviral drugs (ARVs) and HIV-infection worldwide, particularly in Rwanda. A convenient sampling strategy was used in this study and it involved 323 HIV patients (n=323). Patients who are HIV positive under ARVs were involved in this study. The patient’s blood glucose was analyzed using an automated machine or glucometer (COBAS C 311). Data were analyzed using Microsoft Excel and SPSS V. 20.0 and presented in percentages. The highest diabetes mellitus prevalence was 93.33 % in people aged >40 years while the lowest diabetes mellitus prevalence was 6.67% in people aged between 21-and 40 years. The P-value was (0.021). Thus, there is a significant association between age and diabetes occurrence. The highest diabetes mellitus prevalence was 28.2% in patients under ART treatment for more than 10 years, 16.7% were <5years while 20% of patients were on ART treatment between 5-10 years. The P-value here is (0.03), thus the incidence of diabetes is associated with long-term ART use in HIV-infected patients. This study assessed the prevalence of diabetes among HIV-infected patients under ARVs attending the University Teaching Hospital of Butare (CHUB), it shows that the prevalence of diabetes is high in HIV-infected patients under ARTs. This study found no significant relationship between gender and diabetes mellitus growth. Therefore, regular assessment of diabetes mellitus especially among HIV-infected patients under ARVs is highly recommended to control other health issues caused by diabetes mellitus.

Keywords: anti-retroviral, diabetes mellitus, antiretroviral therapy, human immune deficiency virus

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Authors: Simon Mensah Ofosu

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Illicit surface mining activities pollutes agricultural lands and water bodies and results in accumulation of heavy metals in vegetables cultivated in such areas. Heavy metal (HM) accumulation in vegetables is a serious food safety issues due to the adverse effects of metal toxicities, hence the need to investigate the levels of these metals in cultivated vegetables in the eastern region. Cocoyam leaves, cabbage and cucumber were sampled from selected farms in mining areas (Atiwa District) and non -mining areas (Yilo Krobo and East Akim District) of the region for the study. Levels of Cadmium, Lead, Mercury and Arsenic were investigated in the vegetables with Atomic Absorption Spectrometer, and the results statistically analyzed with Microsoft Office Excel (2013) Spread Sheet and ANOVA. Cadmium (Cd) and arsenic (As) were the highest and least concentrated HM in the vegetables sampled, respectively. The mean concentrations of Cd and Pb in cabbage (0.564 mg/kg, 0.470 mg/kg), cucumber (0.389 mg/kg, 0.190 mg/kg), cocoyam leaves (0.410 mg/kg, 0.256 mg/kg) respectively from the mining areas exceeded the permissible limits set by Joint FAO/WHO. The mean concentrations of the metals in vegetables from the mining and non-mining areas varied significantly (P<0.05). The Target Hazard Quotient (THQ) was used to assess the health risk posed to the human population via vegetable consumption. The THQ values of cadmium, mercury, and lead in adults and children through vegetable consumption in the mining areas were greater than 1 (THQ >1). This indicates the potential health risk that the children and adults may be facing. The THQ values of adults and children in the non-mining areas were less than the safe limit of 1 (THQ<1), hence no significant health risk posed to the population from such areas.

Keywords: food safety, risk assessment, illicit mining, public health, contaminated vegetables

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Authors: Nsimbe Allan

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The study examines the impact of Building Information Modeling (BIM) on the cost management of engineering projects, focusing specifically on the Mombasa Port Area Development Project. The objective of this research venture is to determine the mechanisms through which Building Information Modeling (BIM) facilitates stakeholder collaboration, reduces construction-related expenses, and enhances the precision of cost estimation. Furthermore, the study investigates barriers to execution, assesses the impact on the project's transparency, and suggests approaches to maximize resource utilization. The study, selected for its practical significance and intricate nature, conducted a Systematic Literature Review (SLR) using credible databases, including ScienceDirect and IEEE Xplore. To constitute the diverse sample, 69 individuals, including project managers, cost estimators, and BIM administrators, were selected via stratified random sampling. The data were obtained using a mixed-methods approach, which prioritized ethical considerations. SPSS and Microsoft Excel were applied to the analysis. The research emphasizes the crucial role that project managers, architects, and engineers play in the decision-making process (47% of respondents). Furthermore, a significant improvement in cost estimation accuracy was reported by 70% of the participants. It was found that the implementation of BIM resulted in enhanced project visibility, which in turn optimized resource allocation and facilitated the process of budgeting. In brief, the study highlights the positive impacts of Building Information Modeling (BIM) on collaborative decision-making and cost estimation, addresses challenges related to implementation, and provides solutions for the efficient assimilation and understanding of BIM principles.

Keywords: cost management, resource utilization, stakeholder collaboration, project transparency

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Authors: Minhui Chiu

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According to relevant studies, clinical nurses have high work pressure and relatively high job adaptation needs. The nurses who work in oncology wards have more adaptation needs when they face repeating hospitalization patients. The aims of this study were to investigate the job stress adaptation and related factors of nurses in oncology wards and to understand the predictors of job stress adaptation needs. Convenience sampling was used in this study. The nurses in the oncology specialist ward of a regional teaching hospital in southern Taiwan were selected as the research objects. A cross-sectional survey was conducted using a structured questionnaire, random sampling, and the questionnaires were filled out by the participating nurses. A total of 68 people were tested, and 65 valid questionnaires (95.6%). One basic data questionnaire and nurses’ job stress adaptation needs questionnaire were used. The data was archived with Microsoft Excel, and statistical analysis was performed with JMP12.0. The results showed that the average age was 28.8 (±6.7) years old, most of them were women, 62 (95.38%), and the average clinical experience in the hospital was 5.7 years (±5.9), and 62 (95.38%) were university graduates. 39 people (60.0%) had no work experience. 39 people (60.0%) liked nursing work very much, and 23 people (35.3%) just “liked”. 47 (72.3%) people were supported to be oncology nurses by their families. The nurses' job stress adaptation needs were 119.75 points (±17.24). The t-test and variance analysis of the impact of nurses' job pressure adaptation needs were carried out. The results showed that the score of college graduates was 121.10 (±16.39), which was significantly higher than that of master graduates 96.67 (±22.81), and the degree of liking for nursing work also reached a Significant difference. These two variables are important predictors of job adaptation needs, and the R Square is 24.15%. Conclusion: Increasing the love of clinical nurses in nursing and encouraging university graduation to have positive effects on job pressure adaptation needs and can be used as a reference for the management of human resources hospitals for oncology nurses.

Keywords: oncology nurse, job stress, job stress adaptation needs, manpower

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Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

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Authors: Londeka Ntuli, Frasia Oosthuizen

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Background: Tenefovir disiproxil fumarate (TDF) is a nephrotoxic drug and has been proven to contribute to renal insufficiency necessitating intensive monitoring and management of adverse effects arising from prolonged exposure to the drug. TDF is one of the preferred first-line drugs used in combination therapy in most regions. There are estimated 300 000 patients being initiated on the Efavirenz/TDF/Emtricitabine first-line regimen annually in South Africa. It is against this background that this study aims to investigate the effects of TDF on renal sufficiency of HIV positive patients. Methodology: A retrospective quantitative study was conducted, analysing clinical charts of HIV positive patient’s older than 18 years of age and on a TDF-containing regimen for more than 1 year. Data were obtained from the analysis of patient files and was transcribed into Microsoft® Excel® spreadsheet. Extracted data were coded, categorised and analysed using STATA®. Results: A total of 275 patient files were included in this study. Renal function started decreasing after 3 months of treatment (with 93.5% patients having a normal EGFR), and kept on decreasing as time progressed with only 39.6% normal renal function at year 4. Additional risk factors for renal insufficiency included age below 25, female gender, and additional medication. Conclusion: It is clear from this study that the use of TDF necessitates intensive monitoring and management of adverse effects arising from prolonged exposure to the drug. The findings from this study generated pertinent information on the safety profile of the drug TDF in a resource-limited setting of a public health institution. The appropriate management is of tremendous importance in the South African context where the majority of HIV positive individuals are on the TDF containing regimen; thus it is beneficial to ascertain the possible level of toxicities these patients may be experiencing.

Keywords: renal insufficiency, tenefovir, HIV, risk factors

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Authors: Jerome E. Abiemo, Takeshi Mizunoya

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The Aveyime community in the Volta region of Ghana is one of the major hubs for rice production. In the past, rice farmers applied organic pesticides to control pests, and compost as a soil amendment to improve fertility and productivity. However, the introduction of chemical pesticides and fertilizers have led many farmers to convert to inorganic system of rice production, without considering the social costs (e.g. groundwater contamination and health costs) related to the use of pesticides. The study estimates and compares the private and social BCRs of organic and inorganic systems of rice production. Both stratified and simple random sampling techniques were employed to select 300 organic and inorganic rice farmers and 50 pesticide applicators. The respondents were interviewed with pre-tested questionnaires. The Contingent Valuation Method (CVM) which elucidates organic farmers` Willingness-to-Pay (WTP) was employed to estimate the cost of groundwater contamination. The Cost of Illness (COI) analysis was used to estimate the health cost of pesticide-induced poisoning of applicators. The data collated, was analyzed with the aid of Microsoft excel. The study found that high private benefit (e.g. increase in farm yield and income) was the most influential factor for the rapid adoption of pesticides among rice farmers. The study also shows that the social costs of inorganic rice production were high. As such the social BCR of inorganic farming (0.2) was low as compared to organic farming (0.7). Based on the results, it was recommended that government should impose pesticide environmental tax, review current agricultural policies to favour organic farming and promote extension education to farmers on pesticide risk, to ensure agricultural and environmental sustainability.

Keywords: benefit-cost-ratio (BCR), inorganic farming, pesticides, social cost

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Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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Authors: Widari

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This study aims to determine the relationship of fast food consumption preferences with macro and micro nutrient adequacy students of SMP Negeri 5 Padang. This study used a cross sectional study conducted on 100 students of SMP Negeri 5 Padang. The variables studied were fast food preferences, nutrition adequacy macronutrients (carbohydrate, protein, fat, fiber) and micro nutrients (sodium, calcium, iron). Confounding factor in this study was the physical activity level because it was considered quite affecting food consumption of students. Data collected by using a questionnaire food recall as many as 2 x 24 hours to see the history of the respondents eat at school day and on holidays. Then, data processed using software Nutrisurvey and Microsoft Excel 2010. The analysis was performed on samples that have low and medium category on physical activity. The physical activity was not analyzed with another variable to see the strength of the relationship between independent and dependent variables. So that, do restrictions on physical activity variables in an attempt to get rid of confounding in design. Univariate and bivariate analyzes performed using SPSS 16.0 for Windows with Kolmogrov-Smirnov statistical tests, confidence level = 95% (α = 0,05). Results of univariate analysis showed that more than 70% of respondents liked fast food. On average, respondents were malnourished macro; malnourished fiber (100%), carbohydrates (72%), and protein (56%), whereas for fat, excess intake of the respondents (41%). Furthermor, many respondents who have micronutrient deficiencies; 98% for sodium, 96% for iron, and 91% for calcium. The results of the bivariate analysis showed no significant association between fast food consumption preferences with macro and micro nutrient adequacy (p > 0,05). This happens because in the fact not all students who have a preference for fast food actually eat them. To study better in the future, it is expected sampling really like and eat fast food in order to obtain better analysis results.

Keywords: fast food, nutritional adequacy, preferences, students

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Authors: Atsebaha Gebrekidan Kahsay, Tsehaye Asmelash, Enquebaher Kassaye

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Background: Salmonella remains a global public health problem with a significant burden in sub-Saharan African countries. Human restricted cause of typhoid and paratyphoid fever are S. Typhi and S. Paratyphi, whereas S. Enteritidis and S. Typhimurium is the causative agent of invasive nontyphoidal diseases among humans and animals are their reservoir. The antibiotic resistance of Salmonella is another public health threat around the globe. To come up with full information about human and animal salmonellosis, we made a systematic review of the prevalence, serotypes, and antibiotic resistance of Salmonella in Ethiopia. Methods: This systematic review used Google Scholar and PubMed search engines to search articles from Ethiopia that were published in English in peer-reviewed international journals from 2010 to 2022. We used keywords to identify the intended research articles and used a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist to ensure the inclusion and exclusion criteria. Frequencies and percentages were analyzed using Microsoft Excel. Results: Two hundred seven published articles were searched, and 43 were selected for a systematic review, human (28) and animals (15). The prevalence of Salmonella in humans and animals was 434 (5.2%) and 641(10.1%), respectively. Fourteen serotypes were identified from animals, and S. Typhimurium was among the top five. Among the ciprofloxacin-resistant isolates in human studies, 16.7% was the highest, whereas, for ceftriaxone, 100% resistance was reported. Conclusions: The prevalence of Salmonella among diarrheic patients and food handlers (5.2%) was lower than the prevalence in food animals (10.1%). We did not find serotypes of Salmonella in human studies, although fourteen serotypes were included in food-animal studies, and S. Typhimurium was among the top five. Salmonella species from some human studies revealed a non-susceptibility to ceftriaxone. We recommend further study about invasive nontyphoidal Salmonella and predisposing factors among humans and animals in Ethiopia.

Keywords: antibiotic resistance, prevalence, systematic review, serotypes, Salmonella, Ethiopia

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Authors: Masomeh Jamshid Nejad

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Nowadays, statistical literacy is no longer a necessary skill but an essential skill with broad applications across diverse fields, especially in operational decision areas such as business management, finance, and economics. As such, learning and deep understanding of statistical concepts are essential in the context of business studies. One of the crucial topics in statistical theory and its application is the normal distribution, often called a bell-shaped curve. To interpret data and conduct hypothesis tests, comprehending the properties of normal distribution (the mean and standard deviation) is essential for business students. This requires undergraduate students in the field of economics and business management to visualize and work with data following a normal distribution. Since technology is interconnected with education these days, it is important to teach statistics topics in the context of Python, R-studio, and Microsoft Excel to undergraduate students. This research endeavours to shed light on the effect of Excel-based instruction on learners’ knowledge of statistics, specifically the central concept of normal distribution. As such, two groups of undergraduate students (from the Business Management program) were compared in this research study. One group underwent Excel-based instruction and another group relied only on traditional teaching methods. We analyzed experiential data and BBA participants’ responses to statistic-related questions focusing on the normal distribution, including its key attributes, such as the mean and standard deviation. The results of our study indicate that exposing students to Excel-based learning supports learners in comprehending statistical concepts more effectively compared with the other group of learners (teaching with the traditional method). In addition, students in the context of Excel-based instruction showed ability in picturing and interpreting data concentrated on normal distribution.

Keywords: statistics, excel-based instruction, data visualization, pedagogy

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Authors: Siyabonga Kunene, Calvin Shipley

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Introduction: Despite health benefits that come with running, injuries are common with prevalence ranging between 18.2% and 92.4% worldwide. Differences in gait patterns between barefoot and shod running, can determine traits that could lead to running injuries. The aim was to assess and compare lower limb gait cycle patterns between barefoot and shod running among runners. Methods: An experimental same-subject study design was used. The study population consisted of male and female adult recreational runners who were injury free from a running club in Durban. A convenience sampling method was used and 14 participants were recruited. The study was conducted in the physiotherapy performance laboratory at the University of KwaZulu-Natal. A Woodway Desmo Treadmill and KinePro gait analysis system were used. Descriptive & inferential statistics were analysed using Microsoft Excel and Intercooled Stata. Results: Participants included a greater percentage of females (57.1%, n = 8) than males (42.9%, n = 6). The mean population age was 38.57. A significant difference (p < 0.0009) between barefoot cadence (177.9236steps/min) and shod cadence (171.9445steps/min) was observed. Right (0.261s) and left (0.257s) barefoot stand phase was shorter than right (0.273s) and left (0.270s) shod stand phase. Right barefoot swing phase exhibited less significant (0.420s) results when compared to right shod swing phase (0.427s), whereas left barefoot swing phase was quicker (0.416s) than left shod swing phase (0.432s). Significant differences between barefoot and shod stand (p < 0.009) and swing (p < 0.040) phase symmetry occurred. Conclusion: A considerable difference was found between barefoot and shod running gait cycle patterns among participants. This difference may play a role in prevention of running related injuries.

Keywords: barefoot running, shod running, gait cycle pattern, same-subject study design

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Authors: Bouhouf Atef, Beloulou Mohamed Lamine

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Introduction: Outpatient surgery is continually developing compared to conventional inpatient surgery; its rate is constantly increasing every year due to global socio-economic pressure. Most hospitals continue to perform proctologic surgery in conventional hospitalization. Purpose: As part of a monocentric prospective descriptive study, we examined the feasibility of proctologic surgery under saddle block on an outpatient basis with the same safety conditions as in traditional hospitalization. Material and methods: This is a monocentric prospective descriptive study spread over a period of 24 months, from December 2018 to December 2020 including 150 patients meeting the medico-surgical and socio-environmental criteria of eligibility for outpatient surgery, operated for proctological pathologies under saddle block in outpatient mode, in the surgery department of the regional military hospital of Constantine Algeria. The data were collected and analyzed by the biomedical statistics software Epi-info and Microsoft Excel, then compared with other related studies. Results: This study involved over a period of two years, 150 male patients with an average age of 32 years (20-64). Most patients (95,33%) were ASA I class, and 4,67% ASA II class. All patients received saddle blocks. The average length of stay of patients was six hours. The quality indicators in outpatient surgery in our study were: zero (0)% of deprogrammings, three (3)% of conversions to full hospitalization, 0,7% of readmissions, an average waiting time before access to the operating room of 83 minutes without delay of discharge, a satisfaction rate of 90,8% and a reduction in the cost compared to conventional inpatient surgery in proportions ranging from – 32,6% and – 48,75%. Conclusions: The outpatient management of proctological surgery under saddle block is very beneficial in terms of safety, efficiency, simplicity, and economy. Our results are in line with those of the literature and our work deserves to be continued to include many patients.

Keywords: outpatient surgery, proctological surgery, saddle block, satisfaction, cost

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Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar

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Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.

Keywords: NLP, multilingual, sentiment analysis, texts

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Authors: Shobhit Mittal

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Headcount budgeting stands as a pivotal element in organizational financial management, extending beyond traditional budgeting to encompass strategic resource allocation for workforce-related expenses. This process is integral to maintaining financial stability and fostering a productive workforce, requiring a comprehensive analysis of factors such as market trends, business growth projections, and evolving workforce skill requirements. It demands a collaborative approach, primarily involving Human Resources (HR) and finance departments, to align workforce planning with an organization's financial capabilities and strategic objectives. The dynamic nature of headcount budgeting necessitates continuous monitoring and adjustment in response to economic fluctuations, business strategy shifts, technological advancements, and market dynamics. Its significance in talent management is also highlighted, aligning financial planning with talent acquisition and retention strategies to ensure a competitive edge in the market. The consequences of incorrect headcount budgeting are explored, showing how it can lead to financial strain, operational inefficiencies, and hindered strategic objectives. Examining case studies like IBM's strategic workforce rebalancing and Microsoft's shift for long-term success, the importance of aligning headcount budgeting with organizational goals is underscored. These examples illustrate that effective headcount budgeting transcends its role as a financial tool, emerging as a strategic element crucial for an organization's success. This necessitates continuous refinement and adaptation to align with evolving business goals and market conditions, highlighting its role as a key driver in organizational success and sustainability.

Keywords: strategic planning, fiscal budget, headcount planning, resource allocation, financial management, decision-making, operational efficiency, risk management, headcount budget

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Authors: Lori W. Gordon, Karen A. Jones

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Today’s high-speed data connectivity depends on a vast global network of infrastructure across space, air, land, and sea, with undersea cable infrastructure (UCI) serving as the primary means for intercontinental and ‘long-haul’ communications. The UCI landscape is changing and includes an increasing variety of state actors, such as the growing economies of Brazil, Russia, India, China, and South Africa. Non-state commercial actors, such as hyper-scale content providers including Google, Facebook, Microsoft, and Amazon, are also seeking to control their data and networks through significant investments in submarine cables. Active investments by both state and non-state actors will invariably influence the growth, geopolitics, and security of this sector. Beyond these hyper-scale content providers, there are new commercial satellite communication providers. These new players include traditional geosynchronous (GEO) satellites that offer broad coverage, high throughput GEO satellites offering high capacity with spot beam technology, low earth orbit (LEO) ‘mega constellations’ – global broadband services. And potential new entrants such as High Altitude Platforms (HAPS) offer low latency connectivity, LEO constellations offer high-speed optical mesh networks, i.e., ‘fiber in the sky.’ This paper focuses on understanding the role of submarine cables within the larger context of the global data commons, spanning space, terrestrial, air, and sea networks, including an analysis of national security policy and geopolitical implications. As network operators and commercial and government stakeholders plan for emerging technologies and architectures, hedging risks for future connectivity will ensure that our data backbone will be secure for years to come.

Keywords: communications, global, infrastructure, technology

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Authors: Mimoza Canga, Vito Malagnino, Giulia Malagnino, Irene Malagnino

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Objective: The objective of this study was to compare the effectiveness of Mtwo and RaCe rotary instruments, in cleaning and shaping root canals curvature. Material and Method: The present study was conducted on 160 simulated canals in resin blocks, with an angle curvature 15°-30°. These 160 simulated canals were divided into two groups, where each group consisted of 80 blocks. Each group was divided into two subgroups (n=40 canals each). The simulated canals subgroups were prepared with Mtwo and RaCe rotary nickel-titanium instruments. The root canals were measured at four different points of reference, starting at 13 mm from the orifice. In the first group, the canals were prepared using Mtwo rotary system (VDW, Munich, Germany). The Mtwo files used were: 10/0.04, 15/0.05, 20/0.06, and 25/0.06. These instruments entered in the full length of the canal. Each file was rotated in the canal until it reached the apical point. In the second group, the canals were prepared using RaCe instruments (La Chaux-De-Fonds, Switzerland), performing the crown down technique, using the torque electric control motor (VDWCO, Munich, Germany), with 600 RPM and 2n/cm as follow: ≠40/0.10, ≠35/0.08, ≠30/0.06, ≠25/0.04, ≠25/0.02. The data were recorded using SPSS version 23 software (Microsoft, IL, USA). Data analysis was done using ANOVA test. Results: The results obtained by using the Mtwo rotary instruments, showed that these instruments were able to clean and shape in the right-to-left motion curved canals, at different levels, without any deviation, and in perfect symmetry, with a P-value=0.000. The data showed that the greater the depth of the root canal, the greater the deviations of the RaCe rotary instruments. These deviations occurred in three levels, which are: S2(P=0.004), S3( P=0.007), S4(P=0.009). The Mtwo files can go deeper and create a greater angle in S4 level (21°-28°), compared to RaCe instruments with an angle equal to 19°-24°. Conclusion: The present study noted a clinically significant difference between Mtwo rotary instruments and RaCe rotary files used for the canal preparation and indicated that Mtwo instruments are a better choice for the curved canals.

Keywords: canal curvature, canal preparation, Mtwo, RaCe, resin blocks

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Authors: A. Barratt, M. H. Granat, S. Buttress, B. Roy

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Introduction: Physiotherapy is an essential part of the treatment of patients with shoulder problems. The focus of treatment is usually centred on addressing specific physiotherapy goals, ultimately resulting in the improvement in pain and function. This study investigates if computerised physiotherapy using gamification principles are as effective as standard physiotherapy. Methods: Physiotherapy exergames were created using a combination of commercially available hardware, the Microsoft Kinect, and bespoke software. The exergames used were validated by mapping physiotherapy goals of physiotherapy which included; strength, range of movement, control, speed, and activation of the kinetic chain. A multicenter, randomised prospective controlled trial investigated the use of exergames on patients with Shoulder Impingement Syndrome who had undergone Arthroscopic Subacromial Decompression surgery. The intervention group was provided with the automated sensor-based technology, allowing them to perform exergames and track their rehabilitation progress. The control group was treated with standard physiotherapy protocols. Outcomes from different domains were used to compare the groups. An important metric was the assessment of shoulder range of movement pre- and post-operatively. The range of movement data included abduction, forward flexion and external rotation which were measured by the software, pre-operatively, 6 weeks and 12 weeks post-operatively. Results: Both groups show significant improvement from pre-operative to 12 weeks in elevation in forward flexion and abduction planes. Results for abduction showed an improvement for the interventional group (p < 0.015) as well as the test group (p < 0.003). Forward flexion improvement was interventional group (p < 0.0201) with the control group (p < 0.004). There was however no significant difference between the groups at 12 weeks for abduction (p < 0.118067) , forward flexion (p < 0.189755) or external rotation (p < 0.346967). Conclusion: Exergames may be used as an alternative to standard physiotherapy regimes; however, further analysis is required focusing on patient engagement.

Keywords: shoulder, physiotherapy, exergames, gamification

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Authors: Abdoullah Nyassi, Golam Sarwar, Sarra Baldeh, Mamadou S. K. Jallow, Bai Lamin Dondeh, Isaac Osei, Grant A. Mackenzie

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A randomized controlled trial is the "gold standard" for evaluating the efficacy of an intervention. Large-scale, cluster-randomized trials are expensive and difficult to conduct, though. To guarantee the validity and generalizability of findings, high-quality, dependable, and accurate data management systems are necessary. Robust data management systems are crucial for optimizing and validating the quality, accuracy, and dependability of trial data. Regarding the difficulties of data gathering in clinical trials in low-resource areas, there is a scarcity of literature on this subject, which may raise concerns. Effective data management systems and implementation goals should be part of trial procedures. Publicizing the creative clinical data management techniques used in clinical trials should boost public confidence in the study's conclusions and encourage further replication. In the ongoing pneumococcal vaccine schedule study in rural Gambia, this report details the development and deployment of multi-data management systems and methodologies. We implemented six different data management, synchronization, and reporting systems using Microsoft Access, RedCap, SQL, Visual Basic, Ruby, and ASP.NET. Additionally, data synchronization tools were developed to integrate data from these systems into the central server for reporting systems. Clinician, lab, and field data validation systems and methodologies are the main topics of this report. Our process development efforts across all domains were driven by the complexity of research project data collected in real-time data, online reporting, data synchronization, and ways for cleaning and verifying data. Consequently, we effectively used multi-data management systems, demonstrating the value of creative approaches in enhancing the consistency, accuracy, and reporting of trial data in a poor resource setting.

Keywords: data management, data collection, data cleaning, cluster-randomized trial

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Authors: S. L. Tulasi Devi, Shivam Azad

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The primary objective of this study is to analyze the impact of green bond issuance on the stock prices of respective Indian companies. An event study methodology has been employed to study the effect of green bond issuance. For in-depth study and analysis, this paper used different window frames, including 15-15 days, 10-10 days, 7-7days, 6-6 days, and 5-5 days. Further, for better clarity, this paper also used an uneven window period of 7-5 days. The period of study covered all the companies which issued green bonds during the period of 2017-2022; Adani Green Energy, State Bank of India, Power Finance Corporation, Jain Irrigation, and Rural Electrification Corporation, except Indian Renewable Energy Development Agency and Indian Railway Finance Corporation, because of data unavailability. The paper used all three event study methods as discussed in earlier literature; 1) constant return model, 2) market-adjusted model, and 3) capital asset pricing model. For the fruitful comparison between results, the study considered cumulative average return (CAR) and buy and hold average return (BHAR) methodology. For checking the statistical significance, a two-tailed t-statistic has been used. All the statistical calculations have been performed in Microsoft Excel 2016. The study found that all other companies have shown positive returns on the event day except for the State Bank of India. The results demonstrated that constant return model outperformed compared to the market-adjusted model and CAPM. The p-value derived from all the methods has shown an almost insignificant impact of the issuance of green bonds on the stock prices of respective companies. The overall analysis states that there’s not much improvement in the market efficiency of the Indian Stock Markets.

Keywords: green bonds, event study methodology, constant return model, market-adjusted model, CAPM

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Authors: Daria Zabolotnaya, Svetlana Degtyareva, Veronika Kanestri, Danila Konnov

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An adequate choice of the initial antiretroviral treatment determines the treatment efficacy. In the clinical guidelines in Russia non-nucleoside reverse transcriptase inhibitors (NNRTIs) are still considered to be an option for first-line treatment while pretreatment drug resistance (PDR) testing is not routinely performed. We conducted a cohort retrospective study in HIV-positive treatment naïve patients of the H-clinic (Moscow, Russia) who performed PDR testing from July 2017 to November 2021. All the information was obtained from the medical records anonymously. We analyzed the mutations in reverse transcriptase and protease genes. RT-sequences were obtained by AmpliSens HIV-Resist-Seq kit. Drug resistance was defined using the HIVdb Program v. 8.9-1. PDR was estimated using the Stanford algorithm. Descriptive statistics were performed in Excel (Microsoft Office, 2019). A total of 261 HIV-1 infected patients were enrolled in the study including 197 (75.5%) male and 64 (24.5%) female. The mean age was 34.6±8.3 years. The median CD4 count – 521 cells/µl (IQR 367-687 cells/µl). Data on risk factors of HIV-infection were scarce. The total quantity of strains containing mutations in the reverse transcriptase gene was 75 (28.7%). From these 5 (1.9%) mutations were associated with PDR to nucleoside reverse transcriptase inhibitors (NRTIs) and 30 (11.5%) – with PDR to NNRTIs. The number of strains with mutations in protease gene was 43 (16.5%), from these only 3 (1.1%) mutations were associated with resistance to protease inhibitors. For NNRTIs the most prevalent PDR mutations were E138A, V106I. Most of the HIV variants exhibited a single PDR mutation, 2 were found in 3 samples. Most of HIV variants with PDR mutation displayed a single drug class resistance mutation. 2/37 (5.4%) strains had both NRTIs and NNRTIs mutations. There were no strains identified with PDR mutations to all three drug classes. Though earlier data demonstrated a lower level of PDR in HIV treatment naïve population in Russia and our cohort can be not fully representative as it is taken from the private clinic, it reflects the trend of increasing PDR especially to NNRTIs. Therefore, we consider either pretreatment testing or giving the priority to other drugs as first-line treatment necessary.

Keywords: HIV, resistance, mutations, treatment

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Authors: Yvonne Nanaama Brew, Bismark Jampim Abrokwah

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Children with disabilities in Ghana are not routinely registered, and this can imply that they may be neglected in national policy planning since global estimates may not be near the exact numbers. Although there are some studies with reports on the prevalence of disability among children in Ghana, reliable information on the prevalence, types of disability in children, and children who die with disabilities in the Greater Accra region are lacking. The current study seeks to investigate the incidence of disability among children two to fourteen years at selected districts in the Greater Accra region of Ghana. A cross-sectional design is adapted with a quantitative method for this study. Parents with disabled children who access child welfare clinics at the Greater Accra regional hospital, Maamobi hospital, Ga west, and Ga south district hospitals will be selected through purposive sampling for the study. An adapted UNICEF structured Ten Questions will be used to collect relevant data about participants. The responses to the questions will be either 'Yes' or 'No'. Parents with children who answer 'Yes' to a disability and purposively sampled parents with children who answer 'No' to disability will be invited to Child Health Clinic at the Greater Accra regional hospital for a free clinical assessment. Data will be entered into Microsoft Office Excel 2013 and imported into STATA version 15 for analysis. The study is expected to provide reliable disaggregated data on less than fourteen years of children with disabilities in the Greater Accra region. The findings and recommendations of the study will demonstrate the importance of early detection of disability and facilitate more quality and holistic planning of appropriate programmes that best safeguard the rights of children with disabilities in Ghana. It will help in policy and decision-making on children less than fourteen years with disabilities in Ghana. Also, findings will be useful for health facilities in Ghana to plan services for disabled children. Finally, the study is expected to add to the guides for the National Council of Persons with Disabilities to fulfill its legal mandate for disabled persons in Ghana.

Keywords: prevalence, disability, children, Ghana

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

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