Search results for: regression logistic

Authors: Xiangmei Li

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Domestic violence (DV) victims are at a greater risk of suffering mental health problems; however, not all victims experience the same degree of depression. Women respond differently to gender inequalities based on their gender ideologies. This study explored the moderating role of gender ideology in the relation between exposure to DV and depression. Data were drawn from a sub-sample of women aged 18-60 from the Third WaveSurvey on the Social Status of Women in China (N = 10,701). The survey adopted astratified three-stage sampling design to select a representative sample of respondents from the country. Regression models were used to examine the moderating effects of gender ideology on the relation between DV and depression. Women who reported DV experience had more severe depressive symptoms after controlling for confounding social–demographic factors (β = 0.592, 95% CI: 0.489 – 0.695). Women's gender ideology moderated the association between DV severity and depression (β = -0.049, 95% CI: -0.085 – -0.013), despite being subjected to the same levels of victimization. The experience of domestic violence is a useful indicator for routine screening for depression in clinic and community settings. Interventions that aim to decrease depression caused by DV are more likely to be effective if they promote more egalitarian gender ideology to counter the mindset that a woman's role is confined to the home and a family suffers if the wife participates in the labor force.

Keywords: domestic violence against wives, depression, gender ideology, moderation

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Authors: Andi Syahputra, R. H. Jatmiko, D. R. Hizbaron

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Land surface temperature (LST) in an area is influenced by conditions of vegetation density, building density, and the number of inhabitants who live in the area. Medan City is one of the largest cities in Indonesia, with a high rate of change from vegetation to developed land. This study aims to identify the relationship between the percentage of building density and land surface temperature in Medan City. Pixel image analysis method is carried out to obtain the value of building density in pixel images of Landsat 8 images with the help of WorldView-2 satellite imagery. The results showed the highest land surface temperature in 2018 of 35, 4°C was found in Medan Perjuangan District, and the lowest was 22.5°C in Medan Belawan District. Building density samples with a density level of 889.17 m were also found in Medan Perjuangan District, while the lowest building density sample was found in Medan Timur District. Linear regression analysis of the effect of building density with land surface temperature obtained a correlation (R) was 0.64, and a coefficient of determination (R²) was 0.411 and modeling of building density based on the LST has a correlation (R), and a coefficient of determination (R²) was 0.72 with The RMSE obtained 0.853.

Keywords: land surface temperature, Landsat, imagery, building density, vegetation, density

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Authors: Ayeni Margaret Foluso, K. A. Omotayo

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This study investigated the impact of selected environmental variables as determinants of students’ achievements in biology in secondary schools. The selected environmental variables are class size and laboratory adequacy. The purpose was to find out whether these environmental variables can bring about improvement in the learning of biology by Senior Secondary School Students. The study design used was descriptive research of the survey type. Two instruments were used that is, Biology Achievement Test and School Environment Questionnaire .The population of the study consisted of all Biology students in both public and private Senior Secondary Schools class III (SSIII) in all the three selected states in South West Nigeria. A sample of 900 Biology students and 45 Biology Teachers from both public and private Senior Secondary Schools Class III were used. Two research hypotheses were generated for the study. The data collected were subjected to both descriptive statistics of mean and standard deviation; and the inferential statistics of regression Analyses was employed to test the hypotheses formulated. From the results, it was revealed that the selected environmental variables had influence on the students’ achievement in biology.

Keywords: environmental variables, determinants, students’ achievement, school science

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Authors: Laura Simmer, Maria Kalt, Oliver Schauer

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Freight transport is growing fast, but many vehicles are empty or just partially loaded. The vision and concepts of the Physical Internet (PI) proposes to eliminate these inefficiencies. Aiming for a radical sustainability improvement, the PI – inspired by the Digital Internet – is a hyperconnected global logistic system, enabling seamless asset sharing and flow consolidation. The implementation of a PI in its full expression will be a huge challenge: the industry needs innovation and implementation support including change management approaches, awareness creation and good practices diffusion, legislative actions to remove antitrust and international commerce barriers, standardization and public incentives policies. In order to take a step closer to this future the project ‘Atropine - Fast Track to the Physical Internet’ funded under the Strategic Economic and Research Program ‘Innovative Upper Austria 2020’ was set up. The two-year research project unites several research partners in this field, but also industrial partners and logistics service providers. With Atropine, the consortium wants to actively shape the mobility landscape in Upper Austria and make an innovative contribution to an energy-efficient, environmentally sound and sustainable development in the transport area. This paper should, on the one hand, clarify the questions what the project Atropine is about and, on the other hand, how a proof of concept will be reached. Awareness building plays an important role in the project as the PI requires a reorganization of the supply chain and the design of completely new forms of inter-company co-operation. New business models have to be developed and should be verified by simulation. After the simulation process one of these business models will be chosen and tested in real life with the partner companies. The developed results - simulation model and demonstrator - are used to determine how the concept of the PI can be applied in Upper Austria. Atropine shall pave the way for a full-scale development of the PI vision in the next few decades and provide the basis for pushing the industry toward a new level of co-operation with more shared resources and increased standardization.

Keywords: Atropine, inter-company co-operation, Physical Internet, shared resources, sustainable logistics

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Authors: Beruk Berhanu Desalegn, Gelana Mulu

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Adolescence, especially for females, is a period of an ongoing risk behavior that triggers development of adverse health outcomes during adulthood. This study aimed to investigate the weight control practice and its associated factors among high school female-adolescents in Hawassa town, Ethiopia. A school-based cross-sectional study was conducted on 552 female-adolescents in Hawassa town. The study was conducted between December, 2020 to January, 2021. SPSS version 26 was used to analyse the data from the pre-tested questionnaire of socio-demographic, economic, socio-cultural, and related information. Among the total female-adolescents, 38.6% [95% CI= 34.5-42.8%] took on weight control practices. The study further revealed the condition of the weight control practice to be healthy (20.5%), unhealthy(25.9%, and the rest to be both healthyand unhealthy(7.8%). The multivariate regression model, cutoff p < 0.05, disclosed that predicters like late adolescent age [AOR=1.98; 95% CI=1.33-2.95], middle wealth status [AOR=2.72; 95% CI=1.60-4.63], high wealth status [AOR=5.69; 95% CI=3.43-9.46], normal BMI [AOR=2.36; 95% CI=1.18-4.71], overweight [AOR=2.45; 95% CI=1.13-5.28], mild depression [AOR=1.72; 95% CI=1.12-2.66] and dissatisfied own mid-torso body image [AOR=2.68; 95% CI=1.52-4.73] were found to have significant association with weight control practice. Therefore, it may be benefiting to consider the findings of this study for interventions associated with female adolescents weight control practices.

Keywords: female-adolescents, highschool, weight control practice, Ethiopia

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Authors: Moyosola Jude Akomolafe

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Career commitment among employees is crucial to the success of any organization. However, career commitment has been reported to be very low among teachers in the public secondary schools in Nigeria. This study, therefore, examined the contributions of emotional intelligence and general self-efficacy to career commitment of among secondary school teachers in Nigeria. Descriptive research design of correlational type was adopted for the study. It made use of stratified random sampling technique was used in selecting two hundred and fifty (250) secondary schools teachers for the study. Three standardized instruments namely: The Big Five Inventory (BFI), Emotional Intelligence Scale (EIS), General Self-Efficacy Scale (GSES) and Career Commitment Scale (CCS) were adopted for the study. Three hypotheses were tested at 0.05 level of significance. Data collected were analyzed through Multiple Regression Analysis to investigate the predicting capacity of emotional intelligence and general self-efficacy on career commitment of secondary school teachers. The results showed that the variables when taken as a whole significantly predicted career commitment among secondary school teachers. The relative contribution of each variable revealed that emotional intelligence and general self-efficacy significantly predicted career commitment among secondary school teachers in Nigeria. The researcher recommended that secondary school teachers should be exposed to emotional intelligence and self-efficacy training to enhance their career commitment.

Keywords: career commitment, emotional intelligence, general self-efficacy, secondary school teachers

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Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

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The study used secondary data from foreign and local organizations to explore major challenges and opportunities abound in Information Communication. The study aimed at exploring the tie between tele density (network coverage area) and the number of network subscriptions, probing if the degree of consumer complaints varies significantly among network providers, and assessing if network subscriptions do significantly influence the sector’s GDP contribution. Methods used for data analysis include Pearson product-moment correlation and regression analysis, and the Analysis of Variance (ANOVA) as well. At a two-tailed test of 0.05 confidence level, the results of findings established about 85.6% of network subscriptions were explained by tele density (network coverage area), and the number of network subscriptions; Consumer Complaints’ degree varied significantly among network providers as 80.158291 (F calculated) > 3.490295 (F critical) with very high confidence associated p-value = 0.000000 which is < 0.05; and finally, 65% of the nation’s GDP was explained by network subscription to show a high association.

Keywords: Tele density, Subscription, Network coverage, Information communication, Consumer

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Authors: Slim Amami

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A model is developed to prevent the risks related to climate conditions in the agricultural sector. It will determine the yearly optimum premium to be paid by a farmer in order to reach his required turnover. The model is mainly based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, main ones of which are daily average sunlight, rainfall and temperature. By a simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is deduced from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. Optimal premium is then deduced, and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect their harvest. The application to wheat production in the French Oise department illustrates the reliability of the present model with as low as 6% difference between predicted and real data. The model can be adapted to almost every agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, database, meteorological factors, production model, optimal price

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Authors: Abbas Nesayan

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Background: In recent years, autism has been under consideration in public and research area. Autistic children have dysfunction in communication, socialization, repetitive and stereotyped behaviors. In addition, they clinically suffer from difficulty in attention, challenge with familiar behaviors and sensory processing problems. Several variables are linked to sensory processing problems in autism, one of these variables is working memory. Working memory is part of the executive function which provides the necessary ability to completing multiple stages tasks. Method: This study has categorized in correlational research methods. After determining of entry criteria, according to purposive sampling method, 50 children were selected. Dunn’s sensory profile school companion was used for assessment of sensory processing patterns; behavioral rating inventory of executive functions was used (BRIEF) for assessment of working memory. Pearson correlation coefficient and linear regression were used for data analyzing. Results: The results showed the significant relationship between sensory processing patterns (low registration, sensory seeking, sensory sensitivity and sensory avoiding) with working memory in autistic children. Conclusion: According to the findings, there is the significant relationship between the patterns of sensory processing and working memory. So, in order to improve the working memory could be used some interventions based on the sensory processing.

Keywords: sensory processing patterns, working memory, autism, autistic children

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Authors: Ranala Nirmala, Rajanala Krishna Gopal

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Business schools train management graduates to join the industry in managerial positions. Most of the managerial positions require leadership competency and while some of the business schools have leadership development as a course, many assume leadership development among students through their curriculum. While literature supports the need for leadership development among students, there are few studies which explored the role of department and leadership skills in business management students. This paper is based on an empirical study of students of a university based business school and explored the relationship between the perceived role of department, including the faculty, infrastructure, etc on the leadership skills and potential of the students. Students have been administered an instrument that captured different leadership aspects of the students and the data was reduced into fourteen dimensions including leadership skills perceived by student, role of department in developing leadership skills, leadership potential of students, etc. Anova and regression analysis are the primary statistical tools were used (using SPSS 17.0) and the results revealed that there is a significant relationship between the student perceptions of their leadership potential and the role of department, the faculty, the curriculum, etc. This study supports introducing focused courses in management curriculum to promote leadership among students.

Keywords: students, management education, leadership, role of institution

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Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

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Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.

Keywords: COVID-19, modeling, time series, copula function

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Authors: Montoya C.A., Erina J., Erina I.

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The purpose of this research is to assess the performance and impact of CSR on business in the banking sector in Australia by applying the financial indicators of 20 ASX banks for the period from 2016-2017. The authors carried out CSR assessment in several stages of research: 1) gathering the nonfinancial and financial indicators of 20 ASX listed banks (available were only 16) from the annual reports of Australian banks for 2016 and 2017; 2) calculation of bank performance indicators using such financial indicators as return on assets (ROA), return on equity (ROE), efficiency ratio and net interest margin; 3) analysis of financial data using cross-sectional regression and answers to the research questions. Based on the obtained research results, the authors obtained answers to the initially raised research questions and came to a conclusion that Q1 - Insignificant positive coefficient result - slight positive relationship between CSR disclosure and business performance 2016; Q2 - Insignificant negative coefficient result - slight negative relationship between CSR disclosure and business performance 2017; Q3 - Insignificant positive coefficient result - slight positive relationship between CSR disclosure and business performance.

Keywords: Australia, banks, business performance, CSR

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Authors: Ngozi N. Sydney-Agbor, Chioma N. Ihegboro

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Stress and personality as factors influencing nurses’ aggressive behaviour were investigated. The participants comprised of one hundred and fifty nurses selected through convenience sampling technique from four (4) private hospitals in Imo State, Nigeria; namely: Eastern Summit Specialist Clinics and Maternity, St. David Hospital, New Cross Hospital, and Christian Teaching Hospital. The nurses were all females with ages between 20–35 and a mean age of 25.10 years and a standard deviation of 4.15. The participants were administered with Job Related Tension Scale, Type A Behaviour Scale and Buss- Perry Aggressive Behaviour Scale. Two hypotheses were postulated and tested. Cross- sectional survey and Regression Analysis were adopted as design and statistics respectively. Results showed that as stress increased, nurses aggression also increased. Personality also predicted nurses aggressive behaviour with Type As’ exhibiting higher aggression than Type Bs’.The study recommended that hospital management board should improve the welfare of the nurses and their morale should be boosted by involving them in policy-making concerning their welfare and care of their patients, this will help minimise situations capable of increasing aggressive behaviour. There should also be sensitization on the negative impact of aggressive behaviour to patients especially amongst the personality Type A’s who are more susceptible to aggression.

Keywords: aggressive behaviour, nurses, personality, stress

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Authors: Yusuf Kaygısız, Necmetti̇n Maraşlı

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Aluminum alloys are produced and used at various areas of industry and especially in the aerospace industry. The advantages of these alloys over traditional iron-based alloys are lightweight, corrosion resistance, and very good thermal and electrical conductivity. The aim of this work is to experimentally investigate the effect of growth rates on the eutectic spacings (λ), microhardness, tensile strength and electrical resistivity in Al–30wt.%Cu–6wt.%Mg eutectic alloy. Al–Cu–Mg eutectic alloy was directionally solidified at a constant temperature gradient (G=8.55 K/mm) with different growth rates, 9.43 to 173.3 µm/s by using a Bridgman-type furnace. The dependency of microstructure, microhardness, tensile strength and electrical resistivity for directionally solidified the Al-Cu-Mg eutectic alloy were investigated. Eutectic microstructure is consisting of regular Al2CuMg lamellar and Al2Cu rod phases with in the α (Al) solid solution matrix. The lamellar eutectic spacings were measured from transverse sections of the samples. It was found that the value of microstructures decrease with the increase the value the growth rates. The microhardness, tensile strength and electrical resistivity of the alloy also were measured from sample and relationships between them were experimentally analyzed by using regression analysis. According to present results, values tensile strength and electrical resistivity increase with increasing growth rates.

Keywords: directional solidification, aluminum alloys, microstructure, electrical properties, hardness test

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Authors: G. Dottavio, M. F. Andrade, F. Renard, V. Cheutet, A.-L. Ladier, S. Vercraene, P. Hoang, S. Briet, R. Dachicourt, Y. Baizet

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An important number of technological equipment and high-skilled workers over long periods of time have to be mobilized during nuclear decommissioning processes. The related operations generate complex flows of waste and high inventory levels, associated to information flows of heterogeneous types. Taking into account that more than 10 decommissioning operations are on-going in France and about 50 are expected toward 2025: A big challenge is addressed today. The management of decommissioning and dismantling of nuclear installations represents an important part of the nuclear-based energy lifecycle, since it has an environmental impact as well as an important influence on the electricity cost and therefore the price for end-users. Bringing new technologies and new solutions into decommissioning methodologies is thus mandatory to improve the quality, cost and delay efficiency of these operations. The purpose of our project is to improve decommissioning management efficiency by developing a decision-support framework dedicated to plan nuclear facility decommissioning operations and to optimize waste evacuation by means of a logistic approach. The target is to create an easy-to-handle tool capable of i) predicting waste flows and proposing the best decommissioning logistics scenario and ii) managing information during all the steps of the process and following the progress: planning, resources, delays, authorizations, saturation zones, waste volume, etc. In this article we present our results from waste nuclear flows simulation during decommissioning process, including discrete-event simulation supported by FLEXSIM 3-D software. This approach was successfully tested and our works confirms its ability to improve this type of industrial process by identifying the critical points of the chain and optimizing it by identifying improvement actions. This type of simulation, executed before the start of the process operations on the basis of a first conception, allow ‘what-if’ process evaluation and help to ensure quality of the process in an uncertain context. The simulation of nuclear waste flows before evacuation from the site will help reducing the cost and duration of the decommissioning process by optimizing the planning and the use of resources, transitional storage and expensive radioactive waste containers. Additional benefits are expected for the governance system of the waste evacuation since it will enable a shared responsibility of the waste flows.

Keywords: nuclear decommissioning, logistical optimization, decision-support framework, waste management

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: Minzi Mao, Jianjun Ren, Yu Zhao

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Objectives: The absence of a uniform staging scheme for temporal bone carcinoma (TBC) seriously impedes the improvement of its management strategies. Therefore, this research was aimed to investigate the prognostic values of two currently applying staging schemes, namely, the modified Pittsburgh staging system (MPB) and Stell’s T classification (Stell-T) in patients with TBC. Methods: Areal-world single-institution retrospectivereview of patientsdiagnosed with TBC between2008 and 2019 was performed. Baseline characteristics were extracted, and patients were retrospectively staged by both the MPB and Stell-T classifications. Cox regression analyseswereconductedtocomparetheoverall survival (OS). Results: A total of 69 consecutive TBC patients were included in thisstudy. Univariate analysis showed that both Stell-T and T- classifications of the modified Pittsburgh staging system (MPB-T) were significant prognostic factors for all TBC patients as well as temporal bone squamous cell carcinoma (TBSCC, n=50) patients (P < 0.05). However, only Stell-T was confirmed to be an independent prognostic factor in TBSCC patients (P = 0.004). Conclusions: Tumor extensions, quantified by both Stell-T and MPB-T classifications, are significant prognostic factors for TBC patients, especially for TBSCC patients. However, only the Stell-T classification is an independent prognostic factor for TBSCC patients.

Keywords: modified pittsburgh staging system, overall survival, prognostic factor, stell’s T- classification, temporal bone carcinoma

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Authors: Beatrice Adeoye

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Studies have associated social and demographic characteristics as strong determinants of utilization of health care services; however, not much has been done to explore the dynamics of these variables in Nigeria. This empirical study explores the link between demographic factors and the future use of health care services in Nsukka, southeast Nigeria. A total of 543 respondents were selected using multi-stage sampling technique. The findings of the study showed that majority (56.9%) of the respondents were female while 43.1% were male. More of the respondents were married (50.3%) while 41.80/0 of the respondents were between ages 26-35. Testing the demographic characteristics regarding where people will prefer to go first for treatment with multiple regression, It is only Sex as a demographic variable that indicates positive association for future occurrence to where people will prefer to go first for treatment with 0.08 significance. Age and education indicates no association considering their level of significance. This result shows that sex is one of the determinant factors of where and when people will go for treatment. This is pointing out the realities regarding African society where in the family setting, it is the father that dictates the cause of action. Also to buttress these findings, cross tabulating age with who determines where and when to go for treatment, findings show that majority (58.9%) within age 26-35 said their spouses decide on where and when to go for treatment. Findings showed that patriarchy still plays an important role in the utilization of health care delivery among the people studied.

Keywords: Demographic characters, Determinant, Health Care, treatment, self-medication, symptom,

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Authors: Reza Salehi, Peter L. Dold, Yves Comeau

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The aim of the present study was to investigate the effect of a total of 6 operating parameters including pH (X1), temperature (X2), stirring speed (X3), chemical oxygen demand (COD) (X4), volatile suspended solids (VSS) (X5) and time (X6) on anaerobic orthophosphate release from enhanced biological phosphorus removal (EBPR) sludge. An 8-run Plackett Burman design was applied and the statistical analysis of the experimental data was performed using Minitab16.2.4 software package. The Analysis of variance (ANOVA) results revealed that temperature, COD, VSS and time had a significant effect with p-values of less than 0.05 whereas pH and stirring speed were identified as non-significant parameters, but influenced orthophosphate release from the EBPR sludge. The mathematic expression obtained by the first-order multiple linear regression model between orthophosphate release from the EBPR sludge (Y) and the operating parameters (X1-X6) was Y=18.59+1.16X1-3.11X2-0.81X3+3.79X4+9.89X5+4.01X6. The model p-value and coefficient of determination (R2) value were 0.026 and of 99.87%, respectively, which indicates the model is significant and the predicted values of orthophosphate release from the EBPR sludge have been excellently correlated with the observed values.

Keywords: anaerobic, operating parameters, orthophosphate release, Plackett-Burman design

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Authors: Krutika K. Sawant, Anil Solanki

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The present study deals with the preparation and optimization of ethyl cellulose-containing disopyramide phosphate loaded microspheres using solvent evaporation technique. A central composite design consisting of a two-level full factorial design superimposed on a star design was employed for optimizing the preparation microspheres. The drug:polymer ratio (X1) and speed of the stirrer (X2) were chosen as the independent variables. The cumulative release of the drug at a different time (2, 6, 10, 14, and 18 hr) was selected as the dependent variable. An optimum polynomial equation was generated for the prediction of the response variable at time 10 hr. Based on the results of multiple linear regression analysis and F statistics, it was concluded that sustained action can be obtained when X1 and X2 are kept at high levels. The X1X2 interaction was found to be statistically significant. The drug release pattern fitted the Higuchi model well. The data of a selected batch were subjected to an optimization study using Box-Behnken design, and an optimal formulation was fabricated. Good agreement was observed between the predicted and the observed dissolution profiles of the optimal formulation.

Keywords: disopyramide phosphate, ethyl cellulose, microspheres, controlled release, Box-Behnken design, factorial design

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Authors: Osamede Asowata

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Optimized gain in respect to output power of stand-alone photovoltaic (PV) systems is one of the major focus of PV in recent times. This is evident in its low carbon emission and efficiency. Power failure or outage from commercial providers, in general, does not promote development to public and private sector; these basically limit the development of industries. The need for a well-structured PV system is of importance for an efficient and cost effective monitoring system. The purpose of this paper is to validate the maximum power point of an off-grid PV system taking into consideration the most effective tilt and orientation angles for PV's in the southern hemisphere. This paper is based on analyzing the system using a solar charger with maximum power point tracking (MPPT) from a pulse width modulation (PWM) perspective. The power conditioning device chosen is a solar charger with MPPT. The practical setup consists of a PV panel that is set to an orientation angle of 0°N, with a corresponding tilt angle of 36°, 26°, and 16°. Preliminary results include regression analysis (normal probability plot) showing the maximum power point in the system as well the best tilt angle for maximum power point tracking.

Keywords: poly-crystalline PV panels, solar chargers, tilt and orientation angles, maximum power point tracking, MPPT, Pulse Width Modulation (PWM).

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Authors: B. Hamidu, A. Abdulhamid, S. Mohammed, S. Idi

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This study examined the household expenditure pattern on animal products in Bauchi metropolis. A cross-sectional data were collected from 157 households using systematic sampling technique. The data were analyzed using descriptive statistics, correlation and regression models. The results reveal that the mean age, mean household size, mean monthly income and mean total expenditure on animal products were found to be 39 years, 7 persons, N28,749 and N1,740 respectively. It was also found that household monthly income, number of children and educational level of the household heads (P<0.01) significantly influence the level of household expenditure on animal products. Similarly, income was found to be the most important factor determining the proportion of total expenditure on animal products (20.91%). Income elasticity was found to be 0.66 indicating that for every 1% increase in income, expenditure on animal products would increase by 0.66%. Furthermore, beef was found to be the most preferred (54.83%) and most regularly consumed (61.84%) animal products. However, it was discovered that the major constraints affecting the consumption of animal products were low-income level of the households (29.85%), high cost of animal products (15.82%) and increase in prices of necessities (15.82%). Therefore to improve household expenditure on animal products per capita real income of the households should be improved through creation of employment opportunities. Also stabilization of market prices of animal products and other foods items of necessities through increased production are recommended.

Keywords: animal products, economics, expenditure, households

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Authors: Festus M. Epetimehin

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Resources are essential materials required for production of goods and services. Effective allocation of these resources can engender the success of current business activities and its sustainability for future generation. The study examined effect of resource allocation of small agribusinesses on entrepreneurship development in Southwest Nigeria. Sample size of 385 was determined using Cochran’s formula. 350 valid copies of questionnaire were used in the analysis. In order to achieve the objective, research design (descriptive and cross sectional designs) was used to gather data for the study through the administration of questionnaire to respondents. Both descriptive and inferential statistics were used to investigate the objective of the study. The result obtained indicated that resource allocation by small agribusinesses had a substantial positive effect on entrepreneurship development with the p-value of (0.0000) which was less than the 5.0% critical value with a positive regression coefficient of 0.53. The implication of this is that the ability of the entrepreneurs to deploy their resources efficiently through adequate realization of better gross margin could enhance business activities and development. The study recommends that business owners still need some level of serious training and exposure on how to manage modern small agribusiness resources to enhance business performance. The intervention of Agricultural Development Programme (ADP) and other Agricultural institutions are needed in this regard.

Keywords: resource, resource allocation, small businesses, agriculture, entrepreneurship development

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Use of speed prediction models sometimes appears as a feasible alternative to laborious field measurement particularly, in case when field data cannot fulfill designer’s requirements. However, developing speed models is a challenging task specifically in the context of developing countries like India where vehicles with diverse static and dynamic characteristics use the same right of way without any segregation. Here the traffic composition plays a significant role in determining the vehicular speed. The present research was carried out to examine the effects of traffic volume and its composition on vehicular speed under mixed traffic conditions. Classified traffic volume and speed data were collected from different geometrically identical six lane divided arterials in New Delhi. Based on these field data, speed prediction models were developed for individual vehicle category adopting Kriging approximation technique, an alternative for commonly used regression. These models are validated with the data set kept aside earlier for validation purpose. The predicted speeds showed a great deal of agreement with the observed values and also the model outperforms all other existing speed models. Finally, the proposed models were utilized to evaluate the effect of traffic volume and its composition on speed.

Keywords: speed, Kriging, arterial, traffic volume

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Authors: Ibrahim Bashir, Yahaya Y. Yusuf

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The ongoing shift towards Industry 4.0 represents a critical growth factor in the industrial enterprise, where the digital transformation of industries is increasingly seen as a crucial element for competitiveness. This transformation holds substantial potential, yet its full benefits have yet to be realized due to the fragmented approach to introducing Industry 4.0 technologies. Therefore, this pilot study aims to explore the individual and collective impact of Industry 4.0 technologies and digital transformation on organizational performance. Data were collected through a questionnaire-based survey across 51 companies in the manufacturing industry in the United Kingdom. The correlations and multiple linear regression analyses were conducted to assess the relationship and impact between the variables in the study. The results show that Industry 4.0 and digital transformation positively influence organizational performance and that Industry 4.0 technologies positively influence digital transformation. The results of this pilot study indicate that the implementation of Industry 4.0 technology is vital for increasing organizational performance; however, their roles differ largely. The differences are manifest in how the types of Industry 4.0 technologies correlate with how organizations integrate digital technologies into their operations. Hence, there is a clear indication of a strong correlation between Industry 4.0 technology, digital transformation, and organizational performance. Consequently, our study presents numerous pertinent implications that propel the theory of I4.0, digital business transformation (DBT), and organizational performance forward, as well as guide managers in the manufacturing sector.

Keywords: industry 4.0 technologies, digital transformation, digital integration, organizational performance

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Authors: Gholam Reza Mirzaei, Mehran Roost

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This research was conducted with the aim of predicting the relationship between coronavirus anxiety and psychological hardiness in employees working at Shahid Beheshti Hospital in Shiraz. The current research design was descriptive and correlational. The statistical population of the research consisted of all the employees of Shahid Beheshti Hospital in Shiraz in 2021. From among the statistical population, 220 individuals were selected and studied based on available sampling. To collect data, Kobasa's psychological hardiness questionnaire and coronavirus anxiety questionnaire were used. After collecting the data, the scores of the participants were analyzed using Pearson's correlation coefficient multiple regression analysis and SPSS-24 statistical software. The results of Pearson's correlation coefficient showed that there is a significant negative correlation between psychological hardiness and its components (challenge, commitment, and control) with coronavirus anxiety; also, psychological hardiness with a beta coefficient of 0.20 could predict coronavirus anxiety in hospital employees. Based on the results, plans can be made to enhance psychological hardiness through educational workshops to relieve the anxiety of the healthcare staff.

Keywords: the corona virus, commitment, hospital employees, psychological hardiness

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Authors: F. Marchini, A. Caputo, J. Balonan, F. Fedele, A. Napoli, V. Langher

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Aim: The present study aims to explore the specific role of defense mechanisms in persons with type 2 diabetes mellitus in treatment adherence. Materials and methods: A correlational study design was employed. Thirty-two persons with type 2 diabetes mellitus were enrolled and assessed with Defense Mechanism Inventory, Beck Depression Inventory-II, Toronto Alexithymia Scale and Self-Care Inventory-Revised. Bivariate correlation and two-step regression analyses were performed. Results: Treatment adherence negatively correlates with hetero-directed hostility (r= -.537; p < .01), whereas it is positively associated with principalization (r= .407; p < .05). These two defense mechanisms overall explain an incremental variance of 26.9% in treatment adherence (ΔF=4.189, df1=2, df2 =21, p < .05), over and above the control variables for depression and alexithymia. However, only higher hetero-directed hostility is found to be a solid predictor of a decreased treatment adherence (β=-.497, p < .05). Conclusions: Despite providing preliminary results, this pilot study highlights the original contribution of defense mechanisms in adherence to type 2 diabetes regimens. Specifically, hetero-directed hostility may relate to an unconscious process, according to which disease-related painful feelings are displaced onto care relationships with negative impacts on adherence.

Keywords: alexithymia, defense mechanisms, treatment adherence, type 2 diabetes mellitus

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Authors: Olabamiji J. Onifade, Peter O. Ajayi, Paul O. Jegede

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This study aimed at investigating the preparedness of the undergraduate final year students of Computer Science as the next entrants into the workplace. It assessed their self-efficacy in computational tasks and examined the relationship between their self-efficacy and their learning experiences in Southwest Nigerian universities. The study employed a descriptive survey research design. The population of the study comprises all the final year students of Computer Science. A purposive sampling technique was adopted in selecting a representative sample of interest from the final year students of Computer Science. The Students’ Computational Task Self-Efficacy Questionnaire (SCTSEQ) was used to collect data. Mean, standard deviation, frequency, percentages, and linear regression were used for data analysis. The result obtained revealed that the final year students of Computer Science were averagely confident in performing computational tasks, and there is a significant relationship between the learning experiences of the students and their self-efficacy. The study recommends that the curriculum be improved upon to accommodate industry experts as lecturers in some of the courses, make provision for more practical sessions, and the learning experiences of the student be considered an important component in the undergraduate Computer Science curriculum development process.

Keywords: computer science, learning experiences, self-efficacy, students

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Authors: N. Jena, Nitin Seth

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Globalization and free trade has forced the organizations to continuously rethink and rework on the increasing cost of logistics. World wide, it is visualized that on one side the steel sector is witnessing rapid growth and on the other side it is facing huge challenges in terms of availability of raw materials for uninterrupted production. Inbound logistics also gains significant importance for ensuring the timely availability of raw materials. It is seen that in Indian steel sector logistic cost is still very large and challenging. Effectively managing the inbound logistics in steel decides the profitability and serviceability of the organization. Effective management of inbound logistics also has a major role on the inventory of the organization. Since, the logistics for the steel industry in India is evolving rapidly and it is the interplay of infrastructure, technology and new types of service providers that will define whether the industry is able to help its customers to reduce their logistics costs. Integration of Logistics has been treated as one of the most potential area for the companies to provide a base for cost reduction. In spite of the proven area for benefits for the industry, it is very surprising that none of the researchers have explored this area. Although, many researchers explored the subject of logistics in steel industry, but their perspective varied from exploring and understanding the associated cost and finding out the relations between them. Visualizing a potential gap, the present research is under taken to explore the integration opportunities in inbound logistics for steel sector. Typically in Indian steel sector where in most of the manufacturers depend on imported materials for processing the logistics is very challenging and accounts for transactions at supplier – who is situated in different country, shipper- who is transporting the material to the host country, regulators in both countries-that include customs and various clearing agents, local logistics service providers and local transporters/handlers. It is seen that In bound logistics cost in the steel sector is very high and accounts for about 15-16% of the turn over, integration of information across different channels provides and opportunity for improvements and growth of the organization. In the present paper, a case of leading steel manufacturer has been taken and the potentials for integration of information across various partners have been identified. The paper provides the identification of grey area in steel sector for major improvements in cycle time and lowering the inventories by integration of information. Finally, based on integration of information, the paper presents a business information framework for steel sector.

Keywords: integration, steel sectors, suppliers, shippers, customs and cargo agents, transporters

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Authors: Narvada Ramdhany, Reena Bhattu Babajee

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The 2007-2008 Global Financial Crisis which initiated in the US had a global outreach, impacting the financial and banking sectors of several economies; such as European countries, developing and emerging countries in Asia, Latin America and Africa. European countries represent one of the main sources of export earnings for Mauritius and given that Europe has been quite profoundly affected by the crisis, the Mauritian economy also could have been negatively affected. This study is being undertaken to see if the crisis had a spill-over effect on the Mauritian banking system. It will also enable to determine if the measures put in place to counteract the crisis by regulatory authorities have been effective. The study will be carried out on 17 banks and data will be collected over a time frame of seven years; with a pre-crisis period from 2005 to 2007 and a post-crisis period from 2009 to 2011. The impact of the crisis as such will be measured through the financial performance of the banks, using financial ratios and regression analysis. The results show that during the period concerned Mauritian banks have remained solvent and relatively stable. One of the main explanations put forward to explain the resilience of the banking sector to the crisis is that foreign exposure was relatively low. Another explanation put forward is that Mauritian banks normally transact mainly with prime borrowers unlike most the banks which were affected by the financial crisis.  

Keywords: global financial crisis, banking sector, financial performance, Mauritian banks

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