Search results for: squared prediction risk

Authors: David Dolbow, Daniel Credeur, Mujtaba Rahimi, Dobrivoje Stokic, Jennifer Lemacks, Andrew Courtner

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Introduction: Obesity is at epidemic proportions in the spinal cord injury (SCI) population (66-75%), as individuals who suffer from paralysis undergo a dramatic decrease in muscle mass and a dramatic increase in adipose deposition. Obesity is a major public health concern which includes a doubling of the risk of heart disease, stroke and type II diabetes mellitus. It has been demonstrated that physical activity, and especially HIIT, can promote a healthy body composition and decrease the risk cardiometabolic disease in the able-bodied population. However, SCI typically limits voluntary exercise to the arms, but a high prevalence of shoulder pain in persons with chronic SCI (60-90%) can cause increased arm exercise to be problematic. Functional electrical stimulation (FES) cycling has proven to be a safe and effective way to exercise paralyzed leg muscles in clinical and home settings, saving the often overworked arms. Yet, HIIT-FES cycling had not been investigated prior to the current study. The purpose of this study was to investigate the body composition changes with combined HIIT-FES cycling and nutritional counseling on individuals with SCI. Design: A matched (level of injury, time since injury, body mass index) and controlled trail. Setting: University exercise performance laboratory. Subjects: Ten individuals with chronic SCI (C5-T9) ASIA impairment classification (A & B) were divided into the treatment group (n=5) for 30 minutes of HIIT-FES cycling 3 times per week for 8 weeks and nutritional counseling over the phone for 30 minutes once per week for 8 weeks and the control group (n=5) who received nutritional counseling only. Results: There was a statistically significant difference between the HIIT-FES group and the control group in mean body fat percentage change (-1.14 to +0.24) respectively, p = .030). There was also a statistically significant difference between the HIIT-FES and control groups in mean change in legs lean mass (+0.78 kg to -1.5 kg) respectively, p = 0.004. There was a nominal decrease in weight, BMI, total fat mass and a nominal increase in total lean mass for the HIIT-FES group over the control group. However, these changes were not found to be statistically significant. Additionally, there was a nominal decrease in the mean blood glucose levels for both groups 101.8 to 97.8 mg/dl for the HIIT-FES group and 94.6 to 93 mg/dl for the Nutrition only group, however, neither were found to be statistically significant. Conclusion: HIIT-FES cycling combined with nutritional counseling can provide healthful body composition changes including decreased body fat percentage in just 8 weeks. Future study recommendations include a greater number of participants, a primer electrical stimulation exercise program to better ready participants for HIIT-FES cycling and a greater volume of training above 30 minutes, 3 times per week for 8 weeks.

Keywords: body composition, functional electrical stimulation cycling, high-intensity interval training, spinal cord injury

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Authors: Doua AlSaad, Ahmed Awaisu, Samah Elsalem, Palli Valapila Abdulrouf, Binny Thomas, Moza AlHail

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Background: It has been suggested that pyridoxine has an anti-lactogenic effect. Studies of the efficacy of pyridoxine in suppressing lactation have reported conflicting results. The aim of this review is to evaluate the effectiveness and safety of high-dose pyridoxine in postpartum lactation inhibition. Methods: This systematic review included published trials that compared the efficacy and/or safety of pyridoxine to placebo or to other pharmacological agents for the inhibition of postpartum lactation. We searched PubMed, Embase, ScienceDirect, CINAHL, AMED, the Cochrane library, and the clinical trials registry to identify relevant literature. No limit was imposed on the year of publication of the studies, and the review included studies published until 15 January 2016. Two reviewers independently extracted data and assessed the risk of bias. Results: Seven studies were included, with a total of 1155 women, of which 471 women received pyridoxine. Three studies were randomized controlled trials, while the remaining four studies were non-randomized controlled trials. All of the included studies were relatively small (n = 18 – 482). The studies compared pyridoxine with placebo, bromocriptine, and/or stilboestrol. Pyridoxine was given orally, with a total daily dose of 450 – 600 mg for 5 to 7 days. Two trials (n = 349 participants) indicated that pyridoxine was effective in inhibiting lactation in approximately 95% of the enrolled patients. All other studies failed to demonstrate pyridoxine efficacy through either clinical assessment or prolactin level measurements. Pyridoxine safety was assessed by two trials in which no serious untoward side-effects were reported. Overall, the risk of bias for most of the studies was low to moderate. Conclusion: Current evidence supporting the effectiveness of high dose pyridoxine in the inhibition of postpartum lactation is inconsistent and insufficient. Larger randomized trials are needed to confirm the efficacy of pyridoxine in postpartum lactation inhibition. Acknowledgment: This review received a grant from the Medical Research Center of Hamad Medical Corporation in Qatar (grant number: 15100/15).

Keywords: pyridoxine, safety, effectiveness, lactation inhibition

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Authors: A. Md. Bayejid Hosen, B. M Zakir Hossain Howlader, C. Yearul Kabir

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Contamination of soil and agricultural products by heavy metals resulting from rapid industrial development has caused major concern. Dietary exposure to heavy metals has been associated with toxic and adverse health effects. The main threats to human health from heavy metals are associated with exposure to Pb, Cd and Hg. The aim of this study was to monitor the presence of heavy metals in cereals collected from different wholesale markets of Dhaka City. One hundred and sixty cereal samples were collected and analyzed for determination of heavy metals. Heavy metals were analyzed by inductively coupled plasma mass spectrometry (ICP-MS). A total of six heavy metals– lead, chromium, cadmium, mercury, arsenic and antimony were estimated. The average concentrations of heavy metals in cereals fall within the safe limit established by regulatory organizations except for Pb (152.4 μg/100g) and Hg (15.13 μg/100g) which exceeded the safe limits. BARI gom-26 was the highest source of Pb (304.1 μg/100g) whereas Haski-29 rice variety contained the highest amount of Hg (60.85 μg/100g). Though all the cereal varieties contained approximately same amount of Cr the naizer sail varieties contained huge amount of Cr (171.8 μg/100g). Among all the cereal samples miniket rice varieties contained the least amount of heavy metals. The concentration of Cr (63.24 μg/100g), Cd (5.54 μg/100g) and As (3.26 μg/100g) in all cereals were below the safe limits. The daily intake of heavy metals was determined using the total weight of cereals consumed each day multiplied by the concentrations of heavy metals in cereals. The daily intake was compared with provisional maximum tolerable daily intake set by different regulatory organizations. The daily intake of Cd (23.0 μg), Hg (63.0 μg) and as (13.6 μg) through cereals were below the risk level except for Pb (634.0 μg) and Cr (263.1 μg). As the main meal of average Bangladeshi people is boiled rice served with some sorts of vegetables, our findings indicate that the residents of Dhaka City are at risk from Pb and Cr contamination. Potential health risks from exposure to heavy metals in self-planted cereals need more attention.

Keywords: contamination, dietary exposure, heavy metals, human health, ICP-MS

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Authors: Matthew P. Mancini, Vincent Ribiere

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Today’s workers face more numerous and complex challenges and are required to be increasingly interdependent and faster learners. Knowledge sharing activities between people have been understood as a significant element affecting organizational innovation performance. While they do have the potential to spark cognitive conflict, disagreement is important from an organizational perspective because it can stimulate the development of new ideas and perhaps pave the way for creativity, innovation, and competitive advantage. How teams cope with the cognitive conflict dimension of knowledge sharing and the associated interpersonal risk is what captures our attention. Specifically, assertive conflict management strategies have a positive influence on knowledge sharing behaviors, and team psychological safety has a positive influence on knowledge sharing intention. This paper focuses on explaining the impact that these factors have on the shaping of an individual’s decision to engage or not in knowledge sharing activities. To accomplish this, we performed an empirical analysis on the results of our questionnaire about knowledge-sharing related conflict management and team psychological safety in pharmaceutical enterprises located in North America, Europe, and Asia. First, univariate analysis is used to characterize behavior regarding conflict management strategy into two groups. Group 1 presents assertive conflict management strategies and group 2 shows unassertive ones. Then, by using SEM methodology, we evaluated the relationships between them and the team psychological safety construct with the knowledge sharing process. The results of the SEM analysis show that assertive conflict management strategies affect the knowledge sharing process the most with a small, but significant effect from team psychological safety. The findings suggest that assertive conflict management strategies are just as important as knowledge sharing intentions for encouraging knowledge sharing behavior. This paper provides clear insights into how employees manage the sharing of their knowledge in the face of conflict and interpersonal risk and the relative importance of these factors in sustaining productive knowledge sharing activities.

Keywords: cognitive dissonance, conflict management, knowledge sharing, organizational behavior, psychological safety

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Authors: Radu Soflau, Lia-Ecaterina Oltean

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Background: Increasing evidence supports the efficacy of psychological interventions for psychosis. However, it is unclear which one of these interventions is most likely to address negative psychotic symptoms and related outcomes. We aimed to determine the relative efficacy of psychological and psychosocial interventions for negative symptoms, overall psychotic symptoms, and related outcomes. Methods: To attain this goal, we conducted a systematic review and network meta-analysis. We searched for potentially eligible trials in PubMed, EMBASE, PsycInfo, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov databases up until February 08, 2022. We included randomized controlled trials that investigated the efficacy of psychological for adults with psychosis. We excluded interventions for prodromal or “at risk” individuals, as well as patients with serious co-morbid medical or psychiatric conditions (others than depressive and/or anxiety disorders). Two researchers conducted study selection and performed data extraction independently. Analyses were run using STATA network and mvmeta packages, applying a random effect model under a frequentist framework in order to compute standardized mean differences or risk ratio. Findings: We identified 47844 records and screened 29466 records for eligibility. The majority of eligible interventions were delivered in addition to pharmacological treatment. Treatment as usual (TAU) was the most frequent common comparator. Theoretically driven psychological interventions generally outperformed TAU at post-test and follow-up, displaying small and small-to-medium effect sizes. A similar pattern of results emerged in sensitivity analyses focused on studies that employed an inclusion criterion for relevant negative symptom severity. Conclusion: While the efficacy of some psychological interventions is promising, there is a need for more high-quality studies, as well as more trials directly comparing psychological treatments for negative psychotic symptoms.

Keywords: psychosis, network meta-analysis, psychological interventions, efficacy, negative symptoms

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Authors: Sumohon Matilal, Neveen Abdelrehim

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The purpose of this study is to examine the way households manage the risks of civil war, using the calculative practices of accounting as a lens. As is the case with other social phenomena, accounting serves as a conduit for attributing values and rationales to crisis and in the process makes it visible and calculable. Our focus, in particular, is on the dialogue facilitated by the numerical logic of accounting between the householder and a crisis scenario, such as civil war. In other words, we seek to study how the risk of war is rationalized through household budgets, income and expenditure statements etc. and how such accounting constructs in turn shape attitudes toward earnings and spending in a wartime economy. The existing literature on war and accounting demonstrates how an accounting logic can have potentially destabilising consequences and how it is used to legitimise war. However, very few scholars have looked at the way accounting constructs are used to internalise the effects of war in an average household and the behavioural consequences that arise from such accounting. Relatedly, scholars studying household accounting have mostly focussed on the links between gender and hierarchy in relation to managing the financial affairs. Few have focused on the role of household accounts in a crisis scenario. This study intends to fill this gap. We draw upon Egypt, a country in the middle of civil war since 2011 for our purpose. We intend to carry out 15-20 semi-structured interviews with middle income households in Cairo that maintain some form of accounts to study the following issues: 1. How do people internalise the risks of civil war? What kind of accounting constructs do they use (this may take the form of simple budgets, income-expenditure notes/statements on a periodic basis, spreadsheets etc.) 2. How has civil war affected household expenditure? Are people spending more/less than before? 3. How has civil war affected household income? Are people finding it difficult/easy to survive on the pre-war income? 4. How is such accounting affecting household behaviour towards earnings and expenditure? Are families prioritising expenditure on necessities alone? Are they refraining from indulging in luxuries? Are family members doing two or three jobs to cope with difficult times? Are families increasingly turning toward borrowing? Is credit available? From whom?

Keywords: risk, accounting, war, crisis

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

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Authors: Benjamin Bobbia, Matthias Picard

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In recent years active learning methodologies based on the representativity of the data seems more promising to limit overfitting. The presented query methodology for regression using the Wasserstein distance measuring the representativity of our labelled dataset compared to the global distribution. In this work a crucial use of GroupSort Neural Networks is made therewith to draw a double advantage. The Wasserstein distance can be exactly expressed in terms of such neural networks. Moreover, one can provide explicit bounds for their size and depth together with rates of convergence. However, heterogeneity of the dataset is also considered by weighting the Wasserstein distance with the error of approximation at the previous step of active learning. Such an approach leads to a reduction of overfitting and high prediction performance after few steps of query. After having detailed the methodology and algorithm, an empirical study is presented in order to investigate the range of our hyperparameters. The performances of this method are compared, in terms of numbers of query needed, with other classical and recent query methods on several UCI datasets.

Keywords: active learning, Lipschitz regularization, neural networks, optimal transport, regression

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Authors: Maryam Ghareh Chaei, Masuzyo Chilwesa, Ali Akbarnezhad, Arnaud Castel, Redmond Lloyd, Stephen Foster

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Cement hydration is an exothermic chemical reaction generally leading to a rise in concrete’s temperature. This internal heating of concrete may, in turn, lead to a temperature difference between the hotter interior and the cooler exterior of concrete and thus differential thermal stresses in early ages which could be particularly significant in mass concrete. Such differential thermal stresses result in early age thermal cracking of concrete when exceeding the concrete’s tensile strength. The extent of temperature rise and thus early age differential thermal stresses is generally a function of hydration heat intensity, thermal properties of concrete and size of the concrete element. Both hydration heat intensity and thermal properties of concrete may vary considerably with variations in the type cementitious materials and other constituents. With this in mind, partial replacement of cement with supplementary cementitious materials including fly ash and ground granulated blast furnace slag has been investigated widely as an effective strategy to moderate the heat generation rate and thus reduce the risk of early age thermal cracking of concrete. However, there is currently a lack of adequate literature on effect of partial replacement of cement with fly ash and/or ground granulated blast furnace slag on the thermal properties of concrete. This paper presents the results of an experimental conducted to evaluate the effect of addition of varying percentages of fly ash (up to 60%) and ground granulated blast furnace slag (up to 50%) on the heat capacity and thermal conductivity of early age cement paste. The water to cementitious materials ratio is kept 0.45 for all the paste samples. The results of the experimental studies were used in a numerical analysis performed using Comsol Multiphysics to highlight the effects of variations in the thermal properties of concrete, due to variations in the type of aggregate and content of supplemenraty cementitious materials, on the risk of early age cracking of a concrete raft.

Keywords: thermal diffusivity, early age thermal cracking, concrete, supplementary cementitious materials

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Authors: Tesfaldet Mekonnen Estifanos, Chen Hui, Afewerki Weldezgi

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Background: Youth in general and young females in particular, remain at the center of the HIV/AIDS epidemic. Sexual risk-taking among young unmarried women is relatively high and are the most vulnerable and highly exposed to HIV/AIDS. Improvements in the status of HIV/AIDS knowledge and acceptance attitude towards people living with HIV (PLWHIV) plays a great role in averting the incidence of HIV/AIDS. Thus, the aim of the study was to explore the level and correlates of HIV/AIDS knowledge and accepting attitude toward PLWHIV. Methods: A cross-sectional study was conducted using data from the Uganda Demographic Health Survey 2016 (UDHS-2016). National level representative household surveys using a multistage cluster probability sampling method, face to face interviews with standard questionnaires were performed. Unmarried women aged 15-24 years with a sample size of 2019 were selected from the total sample of 8674 women aged 15-49 years and were analyzed using SPSS version 23. Independent variables such as age, religion, educational level, residence, and wealth index were included. Two binary outcome variables (comprehensive HIV/AIDS knowledge and acceptance attitude toward PLWHIV) were utilized. We used the chi-square test as well as multivariate regression analysis to explore correlations of explanatory variables with the outcome variables. The results were reported by odds ratios (OR) with 95% confidence interval (95% CI), taking a p-value less than 0.05 as significant. Results: Almost all (99.3%) of the unmarried women aged 15-24 years were aware of HIV/AIDS, but only 51.2% had adequate comprehensive knowledge on HIV/AIDS. Only 69.4% knew both methods: using a condom every time had sex, and having only one faithful uninfected partner can prevent HIV/AIDS transmission. About 66.6% of the unmarried women reject at least two common local misconceptions about HIV/AIDS. Moreover, an alarmingly few (20.3%) of the respondents had a positive acceptance attitude to PLWHIV. On multivariate analysis, age (20-24 years), living in urban, being educated and wealthier, were predictors of having adequate comprehensive HIV/AIDS knowledge. On the other hand, research participants with adequate comprehensive knowledge about HIV/AIDS were highly likely (OR, 1.94 95% CI, 1.52-2.46) to have a positive acceptance attitude to PLWHIV than those with inadequate knowledge. Respondents with no education, Muslim, and Pentecostal religion were emerged less likely to have a positive acceptance attitude to PLWHIV. Conclusion: This study found out the highly accepted level of awareness, but the knowledge and positive acceptance attitude are not encouraging. Thus, expanding access to comprehensive sexuality and strengthening educational campaigns on HIV/AIDS in communities, health facilities, and schools is needed with a greater focus on disadvantaged women having low educational level, poor socioeconomic status, and those residing in rural areas. Sexual risk behaviors among the most affected people - young women have also a role in the spread of HIV/AIDS. Hence, further research assessing the significant contributing factors for sexual risk-taking might have a positive impact on the fight against HIV/AIDS.

Keywords: acceptance attitude, HIV/AIDS, knowledge, unmarried women

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Authors: Mahdi Fakoor, Hannaneh Manafi Farid

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In order to predict the fracture behavior of cracked orthotropic materials under mixed-mode loading, well-known minimum strain energy density (SED) criterion is extended. The crack is subjected along the fibers at plane strain conditions. Despite the complicities to solve the nonlinear equations which are requirements of SED criterion, SED criterion for anisotropic materials is derived. In the present research, fracture limit curve of SED criterion is depicted by a numerical solution, hence the direction of crack growth is figured out by derived criterion, MSED. The validated MSED demonstrates the improvement in prediction of fracture behavior of the materials. Also, damaged factor that plays a crucial role in the fracture behavior of quasi-brittle materials is derived from this criterion and proved its dependency on mechanical properties and direction of crack growth.

Keywords: mixed-mode fracture, minimum strain energy density criterion, orthotropic materials, fracture limit curve, mode II critical stress intensity factor

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Authors: Junjie Peng, Jinbao Chen, Shuai Kong, Danxu Liu

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On the basis of traditional resource allocation strategies, the usage of resources on physical servers in cloud data center is great uncertain. It will cause waste of resources if the assignment of tasks is not enough. On the contrary, it will cause overload if the assignment of tasks is too much. This is especially obvious when the applications are the same type because of its resource preferences. Considering CPU intensive application is one of the most common types of application in the cloud, we studied the optimization strategy for CPU intensive applications on the same server. We used resource preferences to analyze the case that multiple CPU intensive applications run simultaneously, and put forward a model which can predict the execution time for CPU intensive applications which run simultaneously. Based on the prediction model, we proposed the method to select the appropriate number of applications for a machine. Experiments show that the model can predict the execution time accurately for CPU intensive applications. To improve the execution efficiency of applications, we propose a scheduling model based on priority for CPU intensive applications. Extensive experiments verify the validity of the scheduling model.

Keywords: cloud computing, CPU intensive applications, resource optimization, strategy

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Authors: Oktavian Prasetia Wardana, Martono Tri Utomo, Risa Etika, Kartika Darma Handayani, Dina Angelika, Wurry Ayuningtyas

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Background: Critically ill neonates are newborn babies with high-risk factors that potentially cause disability and/or death. Scoring systems for determining the severity of the disease have been widely developed as well as some designs for use in neonates. The SNAPPE-II method, which has been used as a mortality predictor scoring system in several referral centers, was found to be slow in assessing the outcome of critically ill neonates in the Neonatal Intensive Care Unit (NICU). Objective: To analyze the predictive value of MSNS on the outcome of critically ill neonates at the time of arrival up to 24 hours after being admitted to the NICU. Methods: A longitudinal observational analytic study based on medical record data was conducted from January to August 2022. Each sample was recorded from medical record data, including data on gestational age, mode of delivery, APGAR score at birth, resuscitation measures at birth, duration of resuscitation, post-resuscitation ventilation, physical examination at birth (including vital signs and any congenital abnormalities), the results of routine laboratory examinations, as well as the neonatal outcomes. Results: This study involved 105 critically ill neonates who were admitted to the NICU. The outcome of critically ill neonates was 50 (47.6%) neonates died, and 55 (52.4%) neonates lived. There were more males than females (61% vs. 39%). The mean gestational age of the subjects in this study was 33.8 ± 4.28 weeks, with the mean birth weight of the subjects being 1820.31 ± 33.18 g. The mean MSNS score of neonates with a deadly outcome was lower than that of the lived outcome. ROC curve with a cut point MSNS score <10.5 obtained an AUC of 93.5% (95% CI: 88.3-98.6) with a sensitivity value of 84% (95% CI: 80.5-94.9), specificity 80 % (CI 95%: 88.3-98.6), Positive Predictive Value (PPV) 79.2%, Negative Predictive Value (NPV) 84.6%, Risk Ratio (RR) 5.14 with Hosmer & Lemeshow test results p>0.05. Conclusion: The MSNS score has a good predictive value and good calibration of the outcomes of critically ill neonates admitted to the NICU.

Keywords: critically ill neonate, outcome, MSNS, NICU, predictive value

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Authors: Eylem G. Cengiz, Ersin Çilek, Gözde Başkaya, Havva Nur Taş

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It is possible to define the abuse and neglect of the child as a social problem. Such adverse experiences of the child are witnessed by wider social circles as well as his or her immediate environment. The most effective institution among these social circles is the school. The awareness of teachers, administrators, and even auxiliary personnel on this issue can act as a protective and preventive buffer because teachers have the opportunity to be with children every day and constantly observe them; therefore, they can notice the physical and mental changes in students. Furthermore, school administrators have an undeniable role in recognizing and responding to the risk of neglect and abuse. This study aims to evaluate the awareness of school administrators on the risk factors, clues, and ways of intervention towards abuse and neglect through the scenarios given to them. Data were collected from 37 primary, secondary, and high school administrators working in various provinces of Turkey through descriptive and scenario-based questions to determine their general knowledge of the concepts of neglect and abuse and their general tendencies towards practice. Descriptive questions were evaluated with content analysis, and scenario-based questions were evaluated with numerical qualitative data analysis. Concepts and themes were tried to be reached by content analysis from the descriptive data collected. When the results are evaluated in general, it is striking that the concept of child abuse means only sexual abuse for some school administrators. There is an important uncertainty for school administrators in the content of the idea of neglect. When the views on the causes of neglect and abuse are examined, the family factor was seen as the primary source of both neglect and abuse. In addition, among the prevention strategies applied by school administrators, intervention for the family -interviewing and informing- was recommended by only 9 (29%) out of 31 administrators. When the responses to the physical, emotional, and sexual abuse scenarios are examined, it is revealed that the administrators generally realize the abuse but fail to develop an appropriate/whole intervention method. The research results show that school administrators' awareness should be increased. Although administrators have sensitivity towards children, they should be empowered to recognize all types of neglect and abuse and develop appropriate intervention tools.

Keywords: assessment child abuse and neglect, child abuse, child neglect, school administrators

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Authors: Edén Bojórquez, Victor Baca, Alfredo Reyes-Salazar, Jorge González

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In this paper, simplified equations to predict maximum inter-story drift demands of steel framed buildings are proposed in terms of two ground motion intensity measures based on the acceleration spectral shape. For this aim, the maximum inter-story drifts of steel frames with 4, 6, 8 and 10 stories subjected to narrow-band ground motion records are estimated and compared with the spectral acceleration at first mode of vibration Sa(T1) which is commonly used in earthquake engineering and seismology, and with a new parameter related with the structural response known as INp. It is observed that INp is the parameter best related with the structural response of steel frames under narrow-band motions. Finally, equations to compute maximum inter-story drift demands of steel frames as a function of spectral acceleration and INp are proposed.

Keywords: intensity measures, spectral shape, steel frames, peak demands

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Authors: Maomao Cao

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Objective: To test the performance of ctDNA methylation for the detection of liver cancer. Methods: A total of 1233 individuals have been recruited in 2017. 15 male and 15 female samples (including 10 cases of liver cancer) were randomly selected in the present study. CfDNA was extracted by MagPure Circulating DNA Maxi Kit. The concentration of cfDNA was obtained by Qubit™ dsDNA HS Assay Kit. A pre-constructed predictive model was used to analyze methylation data and to give a predictive score for each cfDNA sample. Individuals with a predictive score greater than or equal to 80 were classified as having liver cancer. CT tests were considered the gold standard. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the diagnosis of liver cancer were calculated. Results: 9 patients were diagnosed with liver cancer according to the prediction model (with high sensitivity and threshold of 80 points), with scores of 99.2, 91.9, 96.6, 92.4, 91.3, 92.5, 96.8, 91.1, and 92.2, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of ctDNA methylation for the diagnosis of liver cancer were 0.70, 0.90, 0.78, and 0.86, respectively. Conclusions: ctDNA methylation could be an acceptable diagnostic modality for the detection of liver cancer.

Keywords: liver cancer, ctDNA methylation, detection, diagnostic performance

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Daniel Mokatsanyane, Johnny Jansen Van Rensburg

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The integral role oil-crushing companies play in sunflower oil production is often overlooked to offer high-quality oil to refineries and end consumers. Sunflower oil crushing companies in South Africa are exposed to price fluctuations resulting from the local and international markets. Hedging instruments enable these companies to hedge themselves against unexpected prices spikes and to ensure sustained profitability. A crushing company is a necessary middleman, and as such, these companies have exposure to the purchasing and selling sides of sunflower. Sunflower oil crushing companies purchase sunflower seeds from farmers or agricultural companies that provide storage facilities. The purchasing price is determined by the supply and demand of sunflower seed, both national and international. When the price of sunflower seeds in South Africa is high but still below import parity, then the crush margins realised by these companies are reduced or even negative at times. There are three main products made by sunflower oil crushing companies, oil, meal, and shells. Profits are realised from selling three products, namely, sunflower oil, meal and shells. However, when selling sunflower oil to refineries, sunflower oil crushing companies needs to hedge themselves against a reduction in vegetable oil prices. Hedging oil prices is often done via futures and is subject to specific volume commitments before a hedge position can be taken in. Furthermore, South African oil-crushing companies hedge sunflower oil with international, Over-the-counter contracts as South Africa is a price taker of sunflower oil and not a price maker. As such, South Africa provides a fraction of the world’s sunflower oil supply and, therefore, has minimal influence on price changes. The advantage of hedging using futures ensures that the sunflower crushing company will know the profits they will realise, but the downside is that they can no longer benefit from a price increase. Alternative hedging instruments like options might pose a solution to the opportunity cost does not go missing and that profit margins are locked in at the best possible prices for the oil crushing company. This paper aims to investigate the possibility of employing options alongside futures to simulate different scenarios to determine if options can bridge the opportunity cost gap.

Keywords: derivatives, hedging, price risk, sunflower, sunflower oil, South Africa

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: M. A. Ansari, A. Hussain, A. Uddin

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A side weir is a flow diversion structure provided in the side wall of a channel to divert water from the main channel to a branch channel. The trapezoidal labyrinth weir is a special type of weir in which crest length of the weir is increased to pass higher discharge. Experimental and numerical studies related to the coefficient of discharge of trapezoidal labyrinth weir in an open channel have been presented in the present study. Group Method of Data Handling (GMDH) with the transfer function of quadratic polynomial has been used to predict the coefficient of discharge for the side trapezoidal labyrinth weir. A new model is developed for coefficient of discharge of labyrinth weir by regression method. Generalized models for predicting the coefficient of discharge for labyrinth weir using Group Method of Data Handling (GMDH) network have also been developed. The prediction based on GMDH model is more satisfactory than those given by traditional regression equations.

Keywords: discharge coefficient, group method of data handling, open channel, side labyrinth weir

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Authors: Nima Pirhadi, Yong Bo Shao, Xusheng Wa, Jianguo Lu

Abstract:

Several models based on the simplified method introduced by Seed and Idriss (1971) have been developed to assess the liquefaction potential of saturated sandy soils. The procedure includes determining the cyclic resistance of the soil as the cyclic resistance ratio (CRR) and comparing it with earthquake loads as cyclic stress ratio (CSR). Of all methods to determine CRR, the methods using shear-wave velocity (Vs) are common because of their low sensitivity to the penetration resistance reduction caused by fine content (FC). To evaluate the capability of the models, based on the Vs., the new data from Bachu-Jianshi earthquake case history collected, then the prediction results of the models are compared to the measured results; consequently, the accuracy of the models are discussed via three criteria and graphs. The evaluation demonstrates reasonable accuracy of the models in the Banchu region.

Keywords: seismic liquefaction, banchu-jiashi earthquake, shear-wave velocity, liquefaction potential evaluation

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

Abstract:

This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Y. H. Wu, Ji-Yuan Lin, Yu-Ming Liou

Abstract:

This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future.

Keywords: instability index method, logistic regression, landslide susceptibility, SRC curve

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Authors: Jia Xin Low, Keng Wah Choo

Abstract:

This paper presents an automatic normal and abnormal heart sound classification model developed based on deep learning algorithm. MITHSDB heart sounds datasets obtained from the 2016 PhysioNet/Computing in Cardiology Challenge database were used in this research with the assumption that the electrocardiograms (ECG) were recorded simultaneously with the heart sounds (phonocardiogram, PCG). The PCG time series are segmented per heart beat, and each sub-segment is converted to form a square intensity matrix, and classified using convolutional neural network (CNN) models. This approach removes the need to provide classification features for the supervised machine learning algorithm. Instead, the features are determined automatically through training, from the time series provided. The result proves that the prediction model is able to provide reasonable and comparable classification accuracy despite simple implementation. This approach can be used for real-time classification of heart sounds in Internet of Medical Things (IoMT), e.g. remote monitoring applications of PCG signal.

Keywords: convolutional neural network, discrete wavelet transform, deep learning, heart sound classification

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Authors: Fahad Alahmadi, Norhan Abd Rahman, Mohammad Abdulrazzak, Zulikifli Yusop

Abstract:

Runoff prediction of ungauged catchment is still a challenging task especially in arid regions with a unique land cover such as volcanic basalt rocks where geological weathering and fractures are highly significant. In this study, Bathan catchment in Madinah western Saudi Arabia was selected for analysis. The aim of this paper is to evaluate different rainfall loss methods; soil conservation Services curve number (SCS-CN), green-ampt and initial-constant rate. Different direct runoff methods were evaluated: soil conservation services dimensionless unit hydrograph (SCS-UH), Snyder unit hydrograph and Clark unit hydrograph. The study showed the superiority of SCS-CN loss method and Clark unit hydrograph method for ungauged catchment where there is no observed runoff data.

Keywords: urban runoff modelling, arid regions, ungauged catchments, volcanic rocks, Madinah, Saudi Arabia

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Authors: K. S. Vedasingha, K. K. M. T. Perera, K. I. Hathurusinghe, H. W. I. Akalanka, Nelum Chathuranga Amarasena, Nalaka R. Dissanayake

Abstract:

Railways provide the most convenient and economically beneficial mode of transportation, and it has been the most popular transportation method among all. According to the past analyzed data, it reveals a considerable number of accidents which occurred at railways and caused damages to not only precious lives but also to the economy of the countries. There are some major issues which need to be addressed in railways of South Asian countries since they fall under the developing category. The goal of this research is to minimize the influencing aspect of railway level crossing accidents by developing the “railway process automation system”, as there are high-risk areas that are prone to accidents, and safety at these places is of utmost significance. This paper describes the implementation methodology and the success of the study. The main purpose of the system is to ensure human safety by using the Internet of Things (IoT) and image processing techniques. The system can detect the current location of the train and close the railway gate automatically. And it is possible to do the above-mentioned process through a decision-making system by using past data. The specialty is both processes working parallel. As usual, if the system fails to close the railway gate due to technical or a network failure, the proposed system can identify the current location and close the railway gate through a decision-making system, which is a revolutionary feature. The proposed system introduces further two features to reduce the causes of railway accidents. Railway track crack detection and motion detection are those features which play a significant role in reducing the risk of railway accidents. Moreover, the system is capable of detecting rule violations at a level crossing by using sensors. The proposed system is implemented through a prototype, and it is tested with real-world scenarios to gain the above 90% of accuracy.

Keywords: crack detection, decision-making, image processing, Internet of Things, motion detection, prototype, sensors

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Authors: S. O. Oyamakin, A. U. Chukwu,

Abstract:

We proposed a Hyperbolic Gompertz Growth Model (HGGM), which was developed by introducing a stabilizing parameter called θ using hyperbolic sine function into the classical gompertz growth equation. The resulting integral solution obtained deterministically was reprogrammed into a statistical model and used in modeling the height and diameter of Pines (Pinus caribaea). Its ability in model prediction was compared with the classical gompertz growth model, an approach which mimicked the natural variability of height/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using goodness of fit tests and model selection criteria. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the compliance of the error term to normality assumptions while using testing the independence of the error term using the runs test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic gompertz growth models better than the source model (classical gompertz growth model) while the results of R2, Adj. R2, MSE, and AIC confirmed the predictive power of the Hyperbolic Monomolecular growth models over its source model.

Keywords: height, Dbh, forest, Pinus caribaea, hyperbolic, gompertz

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Authors: Hasen Keder Edris, Ryuji Matsunaga, Toshi Yamanaka

Abstract:

The issue of climate change and its impact is a major contemporary global concern. Ethiopia is one of the countries experiencing adverse climate change impact including frequent extreme weather events that are exacerbating drought and water scarcity. Due to this reason, the government of Ethiopia develops a strategic document which focuses on the climate resilience green economy. One of the major components of the strategic framework is designed to improve community adaptation capacity and mitigation of drought. For effective implementation of the strategy, identification of regions relative vulnerability to drought is vital. There is a growing tendency of applying Geographic Information System (GIS) and Remote Sensing technologies for collecting information on duration and severity of drought by direct measure of the topography as well as an indirect measure of land cover. This study aims to show an application of remote sensing technology and GIS for developing drought vulnerability index by taking lowland of Ethiopia as a case study. In addition, it assesses integrated Information Communication Technology (ICT) potential of Ethiopia lowland and proposes integrated solution. Satellite data is used to detect the beginning of the drought. The severity of drought risk prone areas of livestock keeping pastoral is analyzed through normalized difference vegetation index (NDVI) and ten years rainfall data. The change from the existing and average SPOT NDVI and vegetation condition index is used to identify the onset of drought and potential risks. Secondary data is used to analyze geographical coverage of mobile and internet usage in the region. For decades, the government of Ethiopia introduced some technologies and approach to overcoming climate change related problems. However, lack of access to information and inadequate technical support for the pastoral area remains a major challenge. In conventional business as usual approach, the lowland pastorals continue facing a number of challenges. The result indicated that 80% of the region face frequent drought occurrence and out of this 60% of pastoral area faces high drought risk. On the other hand, the target area mobile phone and internet coverage is rapidly growing. One of identified ICT solution enabler technology is telecom center which covers 98% of the region. It was possible to identify the frequently affected area and potential drought risk using the NDVI remote-sensing data analyses. We also found that ICT can play an important role in mitigating climate change challenge. Hence, there is a need to strengthen implementation efforts of climate change adaptation through integrated Remote Sensing and web based information dissemination and mobile alert of extreme events.

Keywords: climate changes, ICT, pastoral, remote sensing

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Authors: Meriem Harmel, Houari Khachai

Abstract:

We have investigated the structural, electronic and optical properties of a compound perovskite CsSrF3 using the full-potential linearized augmented plane wave (FP-LAPW) method within density functional theory (DFT). In this approach, both the local density approximation (LDA) and the generalized gradient approximation (GGA) were used for exchange-correlation potential calculation. The ground state properties such as lattice parameter, bulk modulus and its pressure derivative were calculated and the results are compared whit experimental and theoretical data. Electronic and bonding properties are discussed from the calculations of band structure, density of states and electron charge density, where the fundamental energy gap is direct under ambient conditions. The contribution of the different bands was analyzed from the total and partial density of states curves. The optical properties (namely: the real and the imaginary parts of the dielectric function ε(ω), the refractive index n(ω) and the extinction coefficient k(ω)) were calculated for radiation up to 35.0 eV. This is the first quantitative theoretical prediction of the optical properties for the investigated compound and still awaits experimental confirmations.

Keywords: DFT, fluoroperovskite, electronic structure, optical properties

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Authors: Haftay Abraha Tadesse

Abstract:

Background: Staphylococcus is a genus of worldwide distributed bacteria correlated to several infectious of different sites in human and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. Objective: The objective of this study was to determine the isolates, antimicrobial susceptibility patterns and public health significance for Staphylococcus aureus in raw meat from butchery and abattoir houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from April to October 2019. Sociodemographic data and public health significance were collected using predesigned questionnaire. The raw meat samples were collected aseptically in the butchery and abattoir houses and transported using ice box to Mekelle University, College of Veterinary Sciences for isolating and identification of Staphylococcus aureus. Antimicrobial susceptibility tests were determined by disc diffusion method. Data obtained were cleaned and entered in to STATA 22.0 and logistic regression model with odds ratio were calculated to assess the association of risk factors with bacterial contamination. P-value < 0.05 was considered as statistically significant. Results: In present study, 88 out of 250 (35.2%) were found to be contamination with Staphylococcus aureus. Among the raw meat specimens to be positivity rate of Staphylococcus aureus were 37.6% (n=47) and (32.8% (n=41), butchery and abattoir houses, respectively. Among the associated risk factories not using gloves reduces risk was found to (AOR=0.222; 95% CI: 0.104-0.473), Strict Separation b/n clean & dirty (AOR= 1.37; 95% CI: 0.66-2.86) and poor habit of hand washing (AOR=1.08; 95%CI: 0.35-3.35) were found to be statistically significant and ha ve associated with Staphylococcus aureus contamination. All isolates thirty sevevn of Staphyloco ccus aureus were checked displayed (100%) sensitive to doxycycline, trimethoprim, gentamicin, sulphamethoxazole, amikacin, CN, Co trimoxazole and nitrofurantoi. whereas the showed resistance of cefotaxime (100%), ampicillin (87.5%), Penicillin (75%), B (75%), and nalidixic acid (50%) from butchery houses. On the other hand, all isolates of Staphylococcus aur eu isolate 100% (n= 10) showed sensitive chloramphenicol, gentamicin and nitrofurantoin whereas the showed 100% resistance of Penicillin, B, AMX, ceftriaxone, ampicillin and cefotaxime from abattoirs houses. The overall multi drug resistance pattern for Staphylococcus aureus were 90% and 100% of butchery and abattoirs houses, respectively. Conclusion: 35.3% Staphylococcus aureus isolated were recovered from the raw meat samples collected from the butchery and abattoirs houses. More has to be done in the developed of hand washing behavior, and availability of safe water in the butchery houses to reduce burden of bacterial contamination. The results of the present finding highlight the need to implement protective measures against the levels of food contamination and alternative drug options. The development of antimicrobial resistance is nearly always as a result of repeated therapeutic and/or indiscriminate use of them. Regular antimicrobial sensitivity testing helps to select effective antibiotics and to reduce the problems of drug resistance development towards commonly used antibiotics. Key words: abattoir houses, antimicrobial resistance, butchery houses, Ethiopia,

Keywords: abattoir houses, antimicrobial resistance, butchery houses, Ethiopia, staphylococcus aureuse, MDR

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