Search results for: multivariate logistic regression

Authors: Chinyama Lukama, Million Phiri, Namuunda Mutombo

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Background: Improving access and utilization to high-quality sexual and reproductive health (SRH) information and services, including family planning (FP) commodities, is central to the global developmental agenda of sub-Saharan Africa (SSA). Despite the importance of family planning use in enhancing maternal health outcomes and fertility reduction, the prevalence of adolescents and young women using modern contraception is generally low in SSA. Zambia is one of the countries in Southern Africa with a high prevalence of teenage pregnancies and fertility rates. Despite many initiatives that have been implemented to improve access and demand for family planning commodities, utilization of FP, especially among adolescents and young women, has generally been low. The objective of this research agenda was to better understand the determinants of modern contraceptive use in adolescents and young women in Zambia. This analysis produced findings that will be critical for informing the strengthening of sexual and reproductive health policy strategies aimed at bolstering the provision and use of maternal health services in order to further improve maternal health outcomes in the country. Method: The study used the recent data from the Demographic and Health Survey of 2018. A sample of 3,513 adolescents and young women (ADYW) were included in the analysis. Multilevel logistic regression models were employed to examine the association of individual and contextual factors with modern contraceptive use among adolescents and young women. Results: The prevalence of modern contraception among sexually active ADYW in Zambia was 38.1% [95% CI, 35.9, 40.4]. ADYW who had secondary or higher level education [aOR = 2.16, 95% CI=1.35–3.47], those with exposure to listening to the radio or watching television [aOR = 1.26, 95% CI=1.01–1.57], and those who had decision-making power at household level [aOR = 2.18, 95% CI=1.71–2.77] were more likely to use modern contraceptives. Conversely, strong neighborhood desire for large family size among ADYW [aOR = 0.65 95% CI = 0.47–0.88] was associated with less likelihood to use modern contraceptives. Community access to family planning information through community health worker visits increased the likelihood [aOR = 1.48, 95% CI=1.16–1.91] of using modern contraception among ADYW. Conclusion: The study found that both individual and community factors were key in influencing modern contraceptive use among adolescents and young women in Zambia. Therefore, when designing family planning interventions, the Government of Zambia, through its policymakers and sexual reproductive health program implementers at the Ministry of Health, in collaboration with stakeholders, should consider the community context. There should also be deliberate actions to encourage family planning education through the media.

Keywords: adolescents, young women, modern contraception use, fertility, family planning

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Authors: Yari Vecchio, Margherita Masi, Jorgelina Di Pasquale

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Adoption of Precision Agriculture (PA) is involved in a multidimensional and complex scenario. The process of adopting innovations is complex and social inherently, influenced by other producers, change agents, social norms and organizational pressure. Complexity depends on factors that interact and influence the decision to adopt. Farm and operator characteristics, as well as organizational, informational and agro-ecological context directly affect adoption. This influence has been studied to measure drivers and to clarify 'bottlenecks' of the adoption of agricultural innovation. Making decision process involves a multistage procedure, in which individual passes from first hearing about the technology to final adoption. Awareness is the initial stage and represents the moment in which an individual learns about the existence of the technology. 'Static' concept of adoption has been overcome. Awareness is a precondition to adoption. This condition leads to not encountering some erroneous evaluations, arose from having carried out analysis on a population that is only in part aware of technologies. In support of this, the present study puts forward an empirical analysis among Italian farmers, considering awareness as a prerequisite for adoption. The purpose of the present work is to analyze both factors that affect the probability to adopt and determinants that drive an aware individual to not adopt. Data were collected through a questionnaire submitted in November 2017. A preliminary descriptive analysis has shown that high levels of adoption have been found among younger farmers, better educated, with high intensity of information, with large farm size and high labor-intensive, and whose perception of the complexity of adoption process is lower. The use of a logit model permits to appreciate the weight played by the intensity of labor and complexity perceived by the potential adopter in PA adoption process. All these findings suggest important policy implications: measures dedicated to promoting innovation will need to be more specific for each phase of this adoption process. Specifically, they should increase awareness of PA tools and foster dissemination of information to reduce the degree of perceived complexity of the adoption process. These implications are particularly important in Europe where is pre-announced the reform of Common Agricultural Policy, oriented to innovation. In this context, these implications suggest to the measures supporting innovation to consider the relationship between various organizational and structural dimensions of European agriculture and innovation approaches.

Keywords: adoption, awareness, complexity, precision agriculture

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Authors: Md Rezaul Karim, Farha Taznin

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The purpose of this study was to assess and describe the individual and household characteristics of farmers, to measure the attitude of farmers towards climate adaptation farming practices and to explore the individual and household factors contributing in predicting their attitude towards climate adaptation farming practices. Data were collected through personal interviews using a pre-tested interview schedule. The data collection was done at Biral Upazila under Dinajpur district in Bangladesh from 1st November to 15 December 2018. Besides descriptive statistical parameters, Pearson’s Product Moment Correlation Coefficient (r), multiple regression and step-wise multiple regression analysis were used for the statistical analysis. Findings indicated that the highest proportion (77.6 percent) of the farmers had moderately favorable attitudes, followed by only 11.2 percent with highly favorable attitudes and 11.2 percent with slightly favorable attitudes towards climate adaptation farming practices. According to the computed correlation coefficients (r), among the 10 selected factors, five of them, such as education of household head, farm size, annual household income, organizational participation, and information access by extension services, had a significant relationship with the attitude of farmers towards climate-smart practices. The step-wise multiple regression results showed that two characteristics as education of household head and information access by extension services, contributed 26.2% and 5.1%, respectively, in predicting farmers' attitudes towards climate adaptation farming practices. In addition, more than two-thirds of farmers cited their opinion to the problems in response to ‘price of vermi species is high and it is not easily available’ as 1st ranked problem, followed by ‘lack of information for innovative climate-smart technologies’. This study suggests that policy implications are necessary to promote extension education and information services and overcome the obstacles to climate adaptation farming practices. It further recommends that research study should be conducted in diverse contexts of nationally or globally.

Keywords: factors, attitude, climate adaptation, farming practices, Bangladesh

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Authors: Baqir Khawari

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This study critically examines the influence of remittances on household poverty and income inequality in Mazar-i-Sharif, Balkh Province, Afghanistan, utilizing robust OLS and Logit models with a rigorous multi-random sampling method. The empirical findings reveal that a 1% increase in per capita international remittances is associated with a substantial 0.071% and 0.059% rise in per capita income during the fiscal years 2019/20 and 2020/21, respectively. Furthermore, this increase significantly mitigates the per capita depth of poverty by 0.0272% and 0.025% and the severity of poverty by 0.0149% and 0.0145% over the same periods. Notably, the impact of international remittances on poverty alleviation surpasses that of internal remittances. In addressing income inequality, the analysis demonstrates that remittances contribute to a reduction in the Gini coefficient by 2% in 2019/20 and 7% in 2020/21, underscoring their pivotal role in promoting equitable economic distribution. However, the COVID-19 pandemic has posed significant challenges, diminishing remittance flows and, consequently, their positive effects on household welfare. The logistic regression results further corroborate these findings, indicating that increased per capita remittances, both international and internal, markedly decrease the likelihood of households falling below the poverty line. Specifically, a 1% rise in per capita external remittances reduces this likelihood by 4.5% in 2019/20 and by 3.7% in 2020/21, while internal remittances decrease it by 3% and 2.4%, respectively. The study also explores the demographic determinants of poverty. Larger household sizes and older household heads correlate positively with poverty, whereas higher education levels among household heads and members, and a greater proportion of male members, correlate negatively with poverty incidence and severity. Female-headed households are disproportionately affected by poverty, exacerbated by socio-cultural restrictions. Despite these adversities, the data suggest that remittances are a crucial instrument for poverty alleviation and income inequality reduction in Afghanistan. The findings advocate for policy interventions aimed at enhancing formal remittance channels, promoting education, and empowering women. Effective governance and sustained international assistance are essential to harness the full potential of remittances in combating poverty and inequality. This study highlights the need for strategic, multifaceted approaches to foster sustainable economic development in Afghanistan’s challenging socio-political context.

Keywords: migration, remittances, poverty, inequality, COVID-19, Afghanistan

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Authors: David X. Dong, Qingming Zhang, Meng Lu

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Nitrites enter waterways as runoff from croplands and are discharged from many industrial sites. Excessive nitrite inputs to water bodies lead to eutrophication. On-site rapid detection of nitrite is of increasing interest for managing fertilizer application and monitoring water source quality. Existing methods for detecting nitrites use spectrophotometry, ion chromatography, electrochemical sensors, ion-selective electrodes, chemiluminescence, and colorimetric methods. However, these methods either suffer from high cost or provide low measurement accuracy due to their poor selectivity to nitrites. Therefore, it is desired to develop an accurate and economical method to monitor nitrites in environments. We report a low-cost optical sensor, in conjunction with a machine learning (ML) approach to enable high-accuracy detection of nitrites in water sources. The sensor works under the principle of measuring molecular absorptions of nitrites at three narrowband wavelengths (295 nm, 310 nm, and 357 nm) in the ultraviolet (UV) region. These wavelengths are chosen because they have relatively high sensitivity to nitrites; low-cost light-emitting devices (LEDs) and photodetectors are also available at these wavelengths. A regression model is built, trained, and utilized to minimize cross-sensitivities of these wavelengths to the same analyte, thus achieving precise and reliable measurements with various interference ions. The measured absorbance data is input to the trained model that can provide nitrite concentration prediction for the sample. The sensor is built with i) a miniature quartz cuvette as the test cell that contains a liquid sample under test, ii) three low-cost UV LEDs placed on one side of the cell as light sources, with each LED providing a narrowband light, and iii) a photodetector with a built-in amplifier and an analog-to-digital converter placed on the other side of the test cell to measure the power of transmitted light. This simple optical design allows measuring the absorbance data of the sample at the three wavelengths. To train the regression model, absorbances of nitrite ions and their combination with various interference ions are first obtained at the three UV wavelengths using a conventional spectrophotometer. Then, the spectrophotometric data are inputs to different regression algorithm models for training and evaluating high-accuracy nitrite concentration prediction. Our experimental results show that the proposed approach enables instantaneous nitrite detection within several seconds. The sensor hardware costs about one hundred dollars, which is much cheaper than a commercial spectrophotometer. The ML algorithm helps to reduce the average relative errors to below 3.5% over a concentration range from 0.1 ppm to 100 ppm of nitrites. The sensor has been validated to measure nitrites at three sites in Ames, Iowa, USA. This work demonstrates an economical and effective approach to the rapid, reagent-free determination of nitrites with high accuracy. The integration of the low-cost optical sensor and ML data processing can find a wide range of applications in environmental monitoring and management.

Keywords: optical sensor, regression model, nitrites, water quality

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Authors: Ahmet Oguz Akturk, Kemal Izci, Gurbuz Caliskan, Ismail Sahin

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Rapid developments in technology are to necessitate societies to closely follow technological developments and change themselves to adopt those developments. It is obvious that one of the areas that are impacted from technological developments is education. Analyzing preservice teachers’ attitudes toward technology is crucial for both educational and professional purposes since teacher candidates are essential for educating future individual living in technological age. In this study, it is aimed to analyze preservice teachers’ attitudes toward technology and some variables (e.g., gender, daily internet usage and possessed technological devices) that predicting those attitudes. In this study, relational survey model used as research method and 329 preservice teachers who are studying in a large university located at the middle part of Turkey are voluntarily participated. Results of the study showed that mostly preservice teachers displayed positive attitudes toward technology while male preservice teachers’ attitudes toward technology was more positive than female preservice teachers. In order to analyze predicting factors for preservice teachers’ attitudes toward technology, stepwise multiple regressions were utilized. The results of stepwise multiple regression showed that daily internet use was the most strong predicting factor for predicting preservice teachers’ attitudes toward technology.

Keywords: attitudes toward technology, preservice teachers, gender, stepwise multiple regression analysis

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Authors: Saheb Yousefi, Kim T. Zebehazy, Parviz Sharifi Daramadi, Tahereh Najafi Fard, Kevin Murfitt

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Context: Children with visual impairments often face challenges in their cognitive, motor, and social development. Sensory-motor and spatial perception therapies can be beneficial for these children, but many existing programs only focus on a limited set of therapies. This study aims to investigate the effectiveness of a rehabilitation program for sensory- motor and spatial perception in reducing the fear of mobility in visually impaired children. Research Aim: The aim of this study is to determine if a rehabilitation program based on parent-child interaction can reduce the fear of mobility in visually impaired children. Methodology: This study uses a semi-experimental approach with an uneven control group design. Visually impaired children aged 10 to 14 and their parents from the Board of the Blind and Visually Impaired in Tehran Province were included in the study. The sample was divided into experimental and control groups, with a total of 30 participants. The experimental group participated in a rehabilitation program for sensory-motor and spatial perception based on parent-child interaction, while the control group did not receive this intervention. Data was collected using questionnaires on transportation issues and analyzed using multivariate and univariate mixed analysis of variance tests. Findings: The analysis of the data showed that the fear of movement was significantly improved in the experimental group compared to the control group after the intervention. Theoretical Importance: This study highlights the effectiveness of a rehabilitation program for sensory- motor and spatial perception based on parent-child interaction in reducing the fear of mobility in visually impaired children. It contributes to the existing knowledge by demonstrating the positive impact of this type of intervention on the cognitive, motor, and social development of these children. Data Collection and Analysis Procedures: Data was collected through the use of questionnaires administered to the children before and after the intervention. The data was analyzed using multivariate and univariate mixed analysis of variance tests to examine the effects of the rehabilitation program. Questions Addressed: This study addresses the question of whether a rehabilitation program based on parent-child interaction can reduce the fear of mobility in visually impaired children. Conclusion: The findings of this study support the effectiveness of the sensory-motor and spatial perception rehabilitation program based on parent-child interaction in reducing the fear of movement in visually impaired children. This intervention can be considered as a suitable method to enhance the fear of mobility in these children.

Keywords: vision impairment, sensory-motor rehabilitation, space perception, parent-child interaction, fear of movement.

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Authors: Adewoyin O. Olusegun, Akinwumi I. Isaac

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In some part of the world where legislations related to site investigations before constructions are not strictly enforced, the expenses and time required for carrying out a comprehensive geotechnical investigation to characterize a site can discourage prospective private residential building developers. Another factor that can discourage a developer is the fact that most of the geotechnical tests procedures utilized during site investigations, to a certain extent, alter the existing environment of the site. This study suggests a quick, non-destructive and non-intrusive method of obtaining key subsoil geotechnical properties necessary for foundation design for proposed engineering facilities. Seismic wave velocities generated from near surface refraction method was used to determine the bulk density of soil, Young’s modulus, bulk modulus, shear modulus and allowable bearing capacity of a competent layer that can bear structural load at the particular study site. Also, regression equations were developed in order to directly obtain the bulk density of soil, Young’s modulus, bulk modulus, shear modulus and allowable bearing capacity from the compressional wave velocities. The results obtained correlated with the results of standard geotechnical investigations carried out.

Keywords: characterize, environment, geophysical, geotechnical, regression

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Authors: Kasim Görenekli, Ali Gülbağ

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This study presents a comprehensive analysis of water consumption patterns in Kocaeli province, Turkey, utilizing various machine learning approaches. We analyzed data from 5,000 water subscribers across residential, commercial, and official categories over an 80-month period from January 2016 to August 2022, resulting in a total of 400,000 records. The dataset encompasses water consumption records, weather information, weekends and holidays, previous months' consumption, and the influence of the COVID-19 pandemic.We implemented and compared several machine learning models, including Linear Regression, Random Forest, Support Vector Regression (SVR), XGBoost, Artificial Neural Networks (ANN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU). Particle Swarm Optimization (PSO) was applied to optimize hyperparameters for all models.Our results demonstrate varying performance across subscriber types and models. For official subscribers, Random Forest achieved the highest R² of 0.699 with PSO optimization. For commercial subscribers, Linear Regression performed best with an R² of 0.730 with PSO. Residential water usage proved more challenging to predict, with XGBoost achieving the highest R² of 0.572 with PSO.The study identified key factors influencing water consumption, with previous months' consumption, meter diameter, and weather conditions being among the most significant predictors. The impact of the COVID-19 pandemic on consumption patterns was also observed, particularly in residential usage.This research provides valuable insights for effective water resource management in Kocaeli and similar regions, considering Turkey's high water loss rate and below-average per capita water supply. The comparative analysis of different machine learning approaches offers a comprehensive framework for selecting appropriate models for water consumption prediction in urban settings.

Keywords: mMachine learning, water consumption prediction, particle swarm optimization, COVID-19, water resource management

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Authors: Byeongju Choi, Sanggil Lee, Kyung-Eun Lee

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Introduction: In the republic of Korea, the number of workers in the beauty industry has been increasing. Because the prevalence of hepatitis B carriers in Korea is higher than in other countries, the risk of blood-borne infection including viral hepatitis B and C, among the workers by using the sharp and contaminated instruments during procedure can be expected among beauty salon workers. However, the health care policies for the workers to prevent the blood-borne infection are not established due to the lack of evidences. Moreover, the workers in hair and nail salon were mostly employed at small businesses, where national mandatory systems or policies for workers’ health management are not applied. In this study, the risk of the viral hepatitis B and C from the job experiencing the hair and nail procedures in the mortality was assessed. Method: We conducted a retrospective review of the job histories and causes of death in the female deaths from 2006-2016. 132,744 of female deaths who had one more job experiences during their lifetime were included in this study. Job histories were assessed using the employment insurance database in Korea Employment Information Service (KEIS) and the causes of death were in death statistics produced by Statistics Korea. Case group (n= 666) who died from viral hepatitis was classified the death having record involved in ‘B15-B19’ as a cause of deaths based on Korean Standard Classification of Diseases(KCD) with the deaths from other causes, control group (n=132,078). The group of the workers in the beauty service industry were defined as the employees who had ever worked in the industry coded as ‘9611’ based on Korea Standard Industry Classification (KSIC) and others were others. Other than job histories, birth year, marital status, education level were investigated from the death statistics. Multiple logistic regression analysis were used to assess the risk of deaths from viral hepatitis in the case and control group. Result: The number of the deaths having ever job experiences at the hair and nail salon was 255. After adjusting confounders of age, marital status and education, the odds ratio(OR) for deaths from viral hepatitis was quite high in the group having experiences with working in the beauty service industry with 3.14(95% confidence interval(CI) 1.00-9.87). Other associated factors with increasing the risk of deaths from viral hepatitis were low education level(OR=1.34, 95% CI 1.04-1.73), married women (OR=1.42, 95% CI 1.02-1.97). Conclusion: The risk of deaths from viral hepatitis were high in the workers in the beauty service industry but not statistically significant, which might attributed from the small number of workers in beauty service industry. It was likely that the number of workers in beauty service industry could be underestimated due to their temporary job position. Further studies evaluating the status and the incidence of viral infection among the workers with consideration of the vertical transmission would be required.

Keywords: beauty service, viral hepatitis, blood-borne infection, viral infection

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Authors: Prince Vivek, Vijay Kumar Bharti, Deepak Kumar, Rohit Kumar, Kapil Nehra, Dhananjay Singh, Om Prakash Chaurasia, Bhuvnesh Kumar

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High altitude native people still rely heavily on animal transport for logistic support at eastern and northern Himalayas regions. The prevalent mountainous terrains and rugged region are not suitable for the motorized vehicle to use in logistic transport. Therefore, people required high endurance pack animals for load carrying and riding. So far to the best of our knowledge, no studies have been taken to evaluate the effect of loads on the physiology of ponies in high altitude region. So, in this view, we evaluated variation in physiological, hematological, biochemical, and cytokines indices of Zanskar ponies during load carrying at high altitude. Total twelve (12) of Zanskar ponies, mare, age 4-6 years selected for this study, Feed was offered at 2% of body weight, and water ad libitum. Ponies were divided into three groups; group-A (without load), group-B (60 kg), and group-C (80 kg) of backpack loads. The track was very narrow and slippery with gravel, uneven with a rocky surface and has a steep gradient of 4 km uphill at altitude 3291 to 3500m. When we evaluate these parameters, it is understood that the heart rate, pulse rate, and respiration rate was significantly increased in 80 kg group among the three groups. The hematology parameters viz. hemoglobin significantly increased in 80 kg group on 1st day after load carrying among the three groups which was followed by control and 60 kg whereas, PCV, lymphocytes, monocytes percentage significantly increased however, ESR and eosinophil % significantly decreased in 80 kg group after load carrying on 7th day after load carrying among the three groups which were followed by control and 60 kg group. In biochemical parameters viz. LA, LDH, TP, hexokinase (HK), cortisol (CORT), T3, GPx, FRAP and IL-6 significantly increased in 80 kg group on the 7th day after load carrying among the three groups which were followed by control and 60 kg group. The ALT, ALB, GLB, UR, and UA significantly increased in 80 kg group on the 7th day before and after load carrying among the three groups which were followed by control and 60 kg group. The CRT, AST, and CK-MB were significantly increased in 80 kg group on the 1st and 7th day after load carrying among the three groups which were followed by control and 60 kg group. It has been concluded that, heart rate, respiration rate, hematological indices like PCV, lymphocytes, monocytes, Hb and ESR, biochemical indices like lactic acid, LDH, TP, HK, CORT, T3, ALT, AST and CRT, ALB, GLB, UR, UA, GPx, FRAP and IL-6 are important biomarkers to assess effect of load on animal physiology and endurance. Further, this result has revealed the strong correlation of change in biomarkers level with performance in ponies during load carry. Hence, these parameters might be used for the performance of endurance of Zanskar ponies in the high mountain region.

Keywords: biochemical, endurance, high altitude, load, ponies

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Authors: Davut Disci

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Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance- Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling(SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: education, mobile behavior, mobile learning, technology, Turkey

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Authors: Nzereogu Stella Kosi, Igwe Ogbonnaya, Emeh Chukwuebuka Odinaka

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A comparative analysis of the expansion rate and soil erodibility of some gullies in Nnewi and Nnobi both of Nanka Formation were studied. The study involved an integration of field observations, geotechnical analysis, slope stability analysis, multivariate statistical analysis, gully expansion rate analysis, and determination of the soil erodibility factor (K) from Revised Universal Soil Loss Equation (RUSLE). Fifteen representative gullies were studied extensively, and results reveal that the geotechnical properties of the soil, topography, vegetation cover, rainfall intensity, and the anthropogenic activities in the study area were major factors propagating and influencing the erodibility of the soils. The specific gravity of the soils ranged from 2.45-2.66 and 2.54-2.78 for Nnewi and Nnobi, respectively. Grain size distribution analysis revealed that the soils are composed of gravel (5.77-17.67%), sand (79.90-91.01%), and fines (2.36-4.05%) for Nnewi and gravel (7.01-13.65%), sand (82.47-88.67%), and fines (3.78-5.02%) for Nnobi. The soils are moderately permeable with values ranging from 2.92 x 10-5 - 6.80 x 10-4 m/sec and 2.35 x 10-6 - 3.84 x 10⁻⁴m/sec for Nnewi and Nnobi respectively. All have low cohesion values ranging from 1–5kPa and 2-5kPa and internal friction angle ranging from 29-38° and 30-34° for Nnewi and Nnobi, respectively, which suggests that the soils have low shear strength and are susceptible to shear failure. Furthermore, the compaction test revealed that the soils were loose and easily erodible with values of maximum dry density (MDD) and optimum moisture content (OMC) ranging from 1.82-2.11g/cm³ and 8.20-17.81% for Nnewi and 1.98-2.13g/cm³ and 6.00-17.80% respectively. The plasticity index (PI) of the fines showed that they are nonplastic to low plastic soils and highly liquefiable with values ranging from 0-10% and 0-9% for Nnewi and Nnobi, respectively. Multivariate statistical analyses were used to establish relationship among the determined parameters. Slope stability analysis gave factor of safety (FoS) values in the range of 0.50-0.76 and 0.82-0.95 for saturated condition and 0.73-0.98 and 0.87-1.04 for unsaturated condition for both Nnewi and Nnobi, respectively indicating that the slopes are generally unstable to critically stable. The erosion expansion rate analysis for a fifteen-year period (2005-2020) revealed an average longitudinal expansion rate of 36.05m/yr, 10.76m/yr, and 183m/yr for Nnewi, Nnobi, and Nanka type gullies, respectively. The soil erodibility factor (K) are 8.57x10⁻² and 1.62x10-4 for Nnewi and Nnobi, respectively, indicating that the soils in Nnewi have higher erodibility potentials than those of Nnobi. From the study, both the Nnewi and Nnobi areas are highly prone to erosion. However, based on the relatively lower fine content of the soil, relatively lower topography, steeper slope angle, and sparsely vegetated terrain in Nnewi, soil erodibility and gully intensity are more profound in Nnewi than Nnobi.

Keywords: soil erodibility, gully expansion, nnewi-nnobi, slope stability, factor of safety

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Authors: A. F. Suleimanov, A. B. Saduakassova, V. S. Pokrovsky, D. V. Vinnikov

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Relevance: Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, with relapse occurring in about 70% of advanced cases with poor prognoses. The aim of the study was to evaluate functional visceral fat activity (VAT) evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in epithelial ovarian cancer (EOC). Materials and methods: We assessed 53 patients with histologically confirmed EOC who underwent ¹⁸F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVₘₐₓ) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also identified the best areas under the curve (AUC) for SUVₘₐₓ with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted-for regression models and ROC analysis, ¹⁸F-FDG accumulation in RE (cut-off SUVₘₐₓ 1.18; Se 64%; Sp 64%; AUC 0.669; p = 0.035) could predict later metastases in EOC patients, as opposed to age, sex, primary tumor location, tumor grade, and histology. Conclusions: VAT SUVₘₐₓ is significantly associated with later metastases in EOC patients and can be used as their predictor.

Keywords: ¹⁸F-FDG, PET/CT, EOC, predictive value

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Authors: Cesar Vazquez-Gonzalez, Sophie Avila-Foucat, Leonardo Ortiz-Lozano, Patricia Moreno-Casasola, Alejandro Granados-Barba

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In the last twenty years, academic and scientific literature has been focused on understanding the processes and factors of coastal social-ecological systems vulnerability and resilience. Some scholars argue that resilience and vulnerability are isolated concepts due to their epistemological origin, while others note the existence of a strong resilience-vulnerability relationship. Here we present an ordinal logistic regression model based on the analytical framework about dynamic resilience-vulnerability interaction along adaptive cycle of complex systems and disasters process phases (during, recovery and learning). In this way, we demonstrate that 1) during the disturbance, absorptive capacity (resilience as a core of attributes) and external response capacity explain the probability of households capitals to diminish the damage, and exposure sets the thresholds about the amount of disturbance that households can absorb, 2) at recovery, absorptive capacity and external response capacity explain the probability of households capitals to recovery faster (resilience as an outcome) from damage, and 3) at learning, adaptive capacity (resilience as a core of attributes) explains the probability of households adaptation measures based on the enhancement of physical capital. As a result, during the disturbance phase, exposure has the greatest weight in the probability of capital’s damage, and households with absorptive and external response capacity elements absorbed the impact of floods in comparison with households without these elements. At the recovery phase, households with absorptive and external response capacity showed a faster recovery on their capital; however, the damage sets the thresholds of recovery time. More importantly, diversity in financial capital increases the probability of recovering other capital, but it becomes a liability so that the probability of recovering the household finances in a longer time increases. At learning-reorganizing phase, adaptation (modifications to the house) increases the probability of having less damage on physical capital; however, it is not very relevant. As conclusion, resilience is an outcome but also core of attributes that interacts with vulnerability along the adaptive cycle and disaster process phases. Absorptive capacity can diminish the damage experienced by floods; however, when exposure overcomes thresholds, both absorptive and external response capacity are not enough. In the same way, absorptive and external response capacity diminish the recovery time of capital, but the damage sets the thresholds in where households are not capable of recovering their capital.

Keywords: absorptive capacity, adaptive capacity, capital, floods, recovery-learning, social-ecological systems

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Authors: Davut Disci

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Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance-Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore, these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling (SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: learning technology, instructional technology, mobile learning, technology

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Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

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Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

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Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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Authors: Gamze Sekeroglu, Mikail Altan

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Working capital is identified as firm’s all current assets. Inventories which are one of the working capital elements are very important among current assets for firms. Because, profitability is an indicator for firms’ financial success is provided with minimum cost and optimum inventory quantity. So in this study, it is investigated as comparatively that the effect of inventory management on the profitability of Turkish firms which operated in weaving industry, eatables industry, wholesale and retail industry in between 2003 – 2012 years. Research data consist of profitability ratios and inventory turnovers ratio calculated by using balance sheets and income statements of firms which operated in Borsa Istanbul (BIST). In this research, the relationship between inventories and profitability is investigated by using SPSS-20 software with regression and correlation analysis. The results achieved from three industry departments which exist in study interpreted as comparatively. Accordingly, it is determined that there is a positive relationship between inventory management and profitability in eatables industry. However, it was founded that there is no relationship between inventory management and profitability in weaving industry and wholesale and retail industry.

Keywords: profitability, regression analysis, inventory management, working capital

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Authors: Archil Undilashvili, Ketevan Stvilia, Dustin Gilbreath, Giorgi Dzneladze, Gordon Charchward

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Introduction: In recent years, diverse types of wheelchairs, both local production and imported, have been made available on the Georgian market for wheelchair users. Some types of wheelchairs are sold together with a service package, while the others, including the State Program, Supported locally-produced ones, don’t provide adjustment and maintenance service packages to users. Within the USAID Physical Rehabilitation Project in Georgia, a study was conducted to assess the impact of the wheelchair service provision in line with the WHO guidelines on the health and overall satisfaction of wheelchair users in Georgia. Methodology: A cross-sectional survey was conducted in May 2021. A structured questionnaire was used for telephone interviews that, along with socio-demographic characteristics, included questions for assessment of accessibility, availability, timeliness, cost and quality of wheelchair services received. Out of 1060 individuals listed in the census of wheelchair users, 752 were available for interview, with an actual response rate of 73.4%. 552 wheelchair users (31%) or their caregivers (69%) agreed to participate in the survey. In addition to using descriptive statistics, the study used multivariate matching of wheelchair users who received wheelchair services and who did not (control group). In addition, to evaluate satisfaction with service provision, respondents were asked to assess services. Findings: The majority (67%) of wheelchair users included in the survey were male. The average age of participants was 43. The three most frequently named reasons for using a wheelchair were cerebral palsy (29%), followed by stroke (18%), and amputation (12%). Users have had their current chair for four years on average. Overall, 60% of respondents reported that they were assessed before providing a wheelchair, but only half of them reported that their preferences and needs were considered. Only 13% of respondents had services in line with WHO guidelines and only 22% of wheelchair users had training when they received their current chair. 16% of participants said they had follow-up services, and 41% received adjustment services after receiving the chair. A slight majority (56%) of participants were satisfied with the quality of service provision and the service provision overall. Similarly, 55% were satisfied with the accessibility of service provision. A slightly larger majority (61%) were satisfied with the timeliness of service provision. The matching analysis suggests that users that received services in line with WHO guidelines were more satisfied with their chairs (the difference 17 point/0-100 scale) and they were four percentage points less likely to have health problems attributed to the chair. The regression analysis provides a similar finding of a 21 point increase in satisfaction attributable to services. Conclusion: The provision of wheelchair services in line with WHO guidelines and with follow-up services is likely to have a positive impact on the daily lives of wheelchair users in Georgia. Wheelchair services should be institutionalized as a standard component of wheelchair provision in Georgia.

Keywords: physical rehabilitation, wheelchair users, persons with disabilities, wheelchair production

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Authors: Heba Abdelmotaal

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This paper explores the impact of the extent of a company's environmental, social, and governance (ESG) disclosure on credit rating and capital structure. The analysis is based on a sample of 202 firms from the 350 FTSE firms over the period of 2008-2013. ESG disclosure score is measured using Proprietary Bloomberg score based on the extent of a company's Environmental, Social, and Governance (ESG) disclosure. The credit rating is measured by The QuiScore, which is a measure of the likelihood that a company will become bankrupt in the twelve months following the date of calculation. The Capital Structure is measured by long term debt ratio. Two hypotheses are test using panel data regression. The results suggested that the higher degree of ESG disclosure leads to better credit rating. There is significant negative relationship between ESG disclosure and the long term debit percentage. The paper includes implications for the transparency which is resulting of the ESG disclosure could support the Monitoring Function. The monitoring role of disclosure is the increasing in the transparency of the credit rating agencies, also it could affect on managers’ actions. This study provides empirical evidence on the material of ESG disclosure on credit ratings changes and the firms’ capital decision making.

Keywords: capital structure, credit rating agencies, ESG disclosure, panel data regression

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Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

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Authors: Marzieh Talebzadeh Shoushtari

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The present study aimed to determine the effectiveness of Metaphor therapy on depression among female students. The sample included 60 female students with depression symptoms selected by simple sampling and randomly divided into two equal groups (experimental and control groups). Beck Depression Inventory was used to measure the variables. This was an experimental study with a pre-test/post-test design with control group. Eight metaphor therapy sessions were held for the experimental group. A post-test was administered to both groups. Data were analyzed using multivariate analysis of covariance (MANCOVA). Results showed that the Metaphor therapy decreased depression in the experimental group compared to the control group.

Keywords: metaphor therapy, depression, female, students

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Authors: Austyn Snowden

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Aim: To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Background: Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Design: Secondary analysis of existing dataset of responses to TEIQue-SF using concurrent application of Rasch analysis and confirmatory factor analysis. Method: First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis.

Keywords: emotional intelligence, rasch analysis, factor analysis, nurse recruiters

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Authors: Aikaterini-Melpomeni Papadopoulou, Kyriaki Apergi, Margarita-Vasiliki Panagopoulou, Olga Malisova

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Introduction: Adequate hydration is a vital factor that enhances concentration, memory, and decision-making abilities throughout the workday. Various factors may affect hydration status in workplace settings, and many variables, such as age, gender and activity level affect hydration needs. Employees frequently overlook their hydration needs amid busy schedules and demanding tasks, leading to dehydration that can negatively affect cognitive function, productivity, and overall well-being In addition, dietary habits, including fluid intake and food choices, can either support or hinder optimal hydration. However, factors that affect hydration balance among workers in Greece have not been adequately studied. Objective: This study aims to evaluate the hydration status of the working population in Greece and investigate the various factors that impact hydration status in workplace settings, considering demographic, dietary, and occupational influences in a Greek sample of employees from diverse working environments Materials & Methods: The study included 212 participants (46.2% women) from the working population in Greece. A validated questionnaire (Water Balance Questionnaire) was used to evaluate hydration status, along with additional questions on drinking habits and work-related factors. In particular, volunteers answered questions of different categories such as a) demographic socio-economic b) work style characteristics c) health, d) physical activity, e) food and fluid intake, f) fluid excretion and g) trends on fluid and water intake. Individual and multivariate regression analyses were performed to assess the relationships between demographic, work-related factors, and hydration balance. Results: Analysis showed that demographic factors like gender, age, and BMI, as well as certain work-related factors, had a weak and statistically non-significant effect on hydration balance. However, the use of a bottle or water container during work hours (b = 944.93, p < 0.001) and engaging in intense physical activity outside of work (b = -226.28, p < 0.001) were found to have a significant impact. Additionally, the consumption of beverages other than water (b = -416.14, p = 0.059) could negatively impact hydration balance. On average, the total consumption of the sample is 3410 ml of water daily, with men consuming approximately 440 ml / day more water (3470 ml / day) compared to women (3030 ml / day) with this difference also being statistically significant. Finally, the water balance, defined as the difference between water intake and water excretion, was found to be negative on average for the entire sample. Conclusions: This study is among the first to explore hydration status within the Greek working population. Findings indicate that awareness of adequate hydration and individual actions, such as using a water bottle during work, may influence hydration balance.

Keywords: hydration, working population, water balance, workplace behavior

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Authors: Hasan Vural

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Turkey is a favorable country to produce a great variety of agricultural products because of her different geographic and climatic conditions which have been used to divide the country into four main and seven sub regions. This classification into seven regions traditionally has been used in order to data collection and publication especially related with agricultural production. Afterwards, nine agricultural regions were considered. Recently, the governmental body which is responsible of data collection and dissemination (Turkish Institute of Statistics-TIS) has used 12 classes which include 11 sub regions and Istanbul province. This study aims to evaluate these classification efforts based on the acreage of ten main crops in a ten years time period (1996-2005). The panel data grouped in 11 subregions has been evaluated by cluster and multivariate statistical methods. It was concluded that from the agricultural production point of view, it will be rather meaningful to consider three main and eight sub-agricultural regions throughout the country.

Keywords: agricultural region, factorial analysis, cluster analysis,

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Authors: H. Bonakdari, I. Ebtehaj

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The prediction of scour depth around bridge piers is frequently considered in river engineering. One of the key aspects in efficient and optimum bridge structure design is considered to be scour depth estimation around bridge piers. In this study, scour depth around bridge piers is estimated using two methods, namely the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). Therefore, the effective parameters in scour depth prediction are determined using the ANN and ANFIS methods via dimensional analysis, and subsequently, the parameters are predicted. In the current study, the methods’ performances are compared with the nonlinear regression (NLR) method. The results show that both methods presented in this study outperform existing methods. Moreover, using the ratio of pier length to flow depth, ratio of median diameter of particles to flow depth, ratio of pier width to flow depth, the Froude number and standard deviation of bed grain size parameters leads to optimal performance in scour depth estimation.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), bridge pier, scour depth, nonlinear regression (NLR)

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Authors: Uwe C. Fischer

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Mental health and well-being for employees working in the human service system are getting more and more important given the increasing rate of absenteeism at work. Besides individual capacities, social and community factors seem to be important in the working setting. Starting from a demand resource framework including the classical demand control aspects, social support systems, specific demands and resources of the client work, and work-family conflict were considered in the present study. We state hypothetically, that these factors have a meaningful association with the mental quality of life of employees working in the field of social, educational and health sectors. 1140 employees, working in human service organizations (education, youth care, nursing etc.) were asked for strains and resources at work (selected scales from Salutogenetic Subjective Work Assessment SALSA and own new scales for client work), work-family conflict, and mental quality of life from the German Short Form Health Survey. Considering the complex influences of the variables, we conducted a multiple hierarchical regression analysis. One third of the whole variance of the mental quality of life can be declared by the different variables of the model. When the variables concerning social influences were included in the hierarchical regression, the influence of work related control resource decreased. Excessive workload, work-family conflict, social support by supervisors, co-workers and other persons outside work, as well as strains and resources associated with client work had significant regression coefficients. Conclusions: Social support systems are crucial in the social, educational and health related service sector, regarding the influence on mental well-being. Especially the work-family conflict focuses on the importance of the work-life balance. Also the specific strains and resources of the client work, measured with new constructed scales, showed great impact on mental health. Therefore occupational health promotion should focus more on the social factors within and outside the working place.

Keywords: client interaction, human service system, mental health, social support, work-family conflict

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Authors: Uyanga Jadamba

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Globalisation of the world economy has necessitated the development and implementation of a comparable and understandable reporting language suitable for use by all reporting entities. The International Accounting Standard Board (IASB) provides an international reporting language that lets all users understand the financial information of their business and potentially allows them to have access to finance at an international level. The study is based on logistic regression analysis to investigate the factors for the adoption of theInternational Financial Reporting Standard for Small and Medium sized Entities (IFRS for SMEs). The study started with a list of 217 countries from World Bank data. Due to the lack of availability of data, the final sample consisted of 136 countries, including 60 countries that have adopted the IFRS for SMEs and 76 countries that have not adopted it yet. As a result, the study included a period from 2010 to 2020 and obtained 1360 observations. The findings confirm that the adoption of the IFRS for SMEs is significantly related to the existence of national reporting standards, law enforcement quality, common law (legal system), and extent of disclosure. It means that the likelihood of adoption of the IFRS for SMEs decreases if the country already has a national reporting standard for SMEs, which suggests that implementation and transitional costs are relatively high in order to change the reporting standards. The result further suggests that the new standard adoption is easier in countries with constructive law enforcement and effective application of laws. The finding also shows that the adoption increases if countries have a common law system which suggests that efficient reportingregulations are more widespread in these countries. Countries with a high extent of disclosing their financial information are more likely to adopt the standard than others. The findings lastly show that the audit qualityand primary education levelhave no significant impact on the adoption.One possible explanation for this could be that accounting professionalsfrom in developing countries lacked complete knowledge of the international reporting standards even though there was a requirement to comply with them. The study contributes to the literature by providing factors that impact the adoption of the IFRS for SMEs. It helps policymakers to better understand and apply the standard to improve the transparency of financial statements. The benefit of adopting the IFRS for SMEs is significant due to the relaxed and tailored reporting requirements for SMEs, reduced burden on professionals to comply with the standard, and provided transparent financial information to gain access to finance.The results of the study are useful toemerging economies where SMEs are dominant in the economy in informing its evaluation of the adoption of the IFRS for SMEs.

Keywords: IFRS for SMEs, international financial reporting standard, adoption, institutional factors

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Authors: M. Bodner, M. Scampicchio

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Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm^–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R² = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R² = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Keywords: adulterated butter, margarine, PCA, PLS-DA, PLS-R, SIMCA

Procedia PDF Downloads 140