Search results for: binary logistic regression

Authors: Yungtai Lo

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The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

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Authors: Avinash Thakur, Parmjit S. Panesar, Manohar Singh

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The distribution coefficient, KD for the reactive extraction of lactic acid from aqueous solutions of lactic acid using 10-30% (v/v) tri-n-octyl amine (extractant) dissolved in n-hexane (inert diluent) and 20% (v/v) oleyl alcohol (modifier) was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined interactive effect of seven independent variables, viz lactic acid concentration (cl), pH, TOA concentration in organic phase (ψ), treat ratio (φ), temperature (T), agitation speed (ω) and batch agitation time (τ) on distribution coefficient of lactic acid. The regression analysis recommended that the quadratic model is significant (R2 and adjusted R2 are 98.72 % and 98.69 % respectively) for analysis. A numerical optimization had resulted in maximum lactic acid distribution coefficient (KD) of 3.16 at the optimized values for test variables, cl, pH, ψ, φ, T, ω and τ as 0.15 [M], 3.0, 22.75% (v/v), 1.0 (v/v), 26°C, 145 rpm and 23 min respectively. A good agreement between the predicted and experimentally obtained values for distribution coefficient using the optimized conditions was exhibited.

Keywords: Distribution coefficient, tri-n-octylamine, lactic acid, response surface methodology

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Authors: Jonathan Hinton Westover, Maureen S. Andrade, Doug Miller

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Research has been inconclusive in determining if men or women experience more job satisfaction. A global comparison examining extrinsic and intrinsic factors, work relations, and work-life balance determinants found few differences; however, work relations and work-life balance factors were more significant for male than female workers across occupations. The current study uses International Social Survey Program data representing 37 countries to explore gender differences in job satisfaction in the hospitality industry. Findings demonstrate that mean job satisfaction scores for females are lower across hospitality occupations except for hotel receptionists, housekeeping supervisors, and hotel cleaners. Regression results revealed additional differences such as the significance of co-worker relations, the negative impact of being discriminated against and harassed at work, working weekends, marital status, and supervisory status for women with autonomy, work stress, education, and employment relationship being more salient for men. Interesting work, work being useful to society, job security, pay, relations with management, and work interfering with family were significant for both males and females.

Keywords: job satisfaction, gender, hospitality, global comparisons

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Authors: Usman Yakubu, Muktar Haruna

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The paper examines the impact of the audit committee on the earning quality of the listed consumer goods sector in Nigeria. The study used data collected from annual reports and accounts of the 13 sampled companies for the periods 2007 to 2018. Data were analyzed by means of descriptive statistics to provide summary statistics for the variables; also, correlation analysis was carried out using the Pearson correlation technique for the correlation between the dependent and independent variables. Regression was employed using the Generalized Least Square technique since the data has both time series and cross sectional attributes (panel data). It was found out that the audit committee had a positive and significant influence on the earning quality in the listed consumer goods companies in Nigeria. Thus, the study recommends that competency and personal integrity should be the worthwhile attributes to be considered while constituting the committee; this could enhance the quality of accounting information. In addition to that majority of the committee members should be independent directors in order to allow a high level of independency to be exercised.

Keywords: earning quality, corporate governance, audit committee, financial reporting

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Authors: Atya Nur Aisha, Pamoedji Hardjomidjojo, Yassierli

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Motivation is an important aspect which affects employee behavior to achieve performance. Working motivation tend to be unstable, it easily changing. This condition could be affected by individual factors, namely working ability, and organizational factors, such as working condition and incentives system. The purpose of this study was to examine the impact of individual and organizational factors on non-academic staff motivation. A questionnaire was designed and distributed to 150 non-academic staff of a university in Indonesia. Regression analysis was used to identify the relationship. Results revealed that individual working ability and incentives system had a positive impact on non-academic staff motivation (sig 0.001). This study provides information about practical implication for university authorities and theoretical implications for researchers who interested in exploring motivational and employee performance in a higher education context. It was proposed to increase productivity and work motivation of non-academic staff, university authorities should maintain equality and feasibility of incentives system and design a human resource development to improve employee ability.

Keywords: motivation, incentives, working ability, non-academic staff

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Authors: Tigist Mekonnen Melesse

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Since rural households are basically entitled to food through own production, improving productivity might lead to enhance the welfare of rural population through higher food availability at the household level and lowering the price of agricultural products. Increasing agricultural productivity through the use of improved technology is one of the desired outcomes from sensible food security and agricultural policy. The ultimate objective of this study was to evaluate the potential impact of improved agricultural technology adoption on smallholders’ crop productivity and welfare. The study is conducted in Ethiopia covering 1500 rural households drawn from four regions and 15 rural villages based on data collected by Ethiopian Rural Household Survey. Endogenous treatment effect model is employed in order to account for the selection bias on adoption decision that is expected from the self-selection of households in technology adoption. The treatment indicator, technology adoption is a binary variable indicating whether the household used improved seeds and chemical fertilizer or not. The outcome variables were cereal crop productivity, measured in real value of production and welfare of households, measured in real per capita consumption expenditure. Results of the analysis indicate that there is positive and significant effect of improved technology use on rural households’ crop productivity and welfare in Ethiopia. Adoption of improved seeds and chemical fertilizer alone will increase the crop productivity by 7.38 and 6.32 percent per year of each. Adoption of such technologies is also found to improve households’ welfare by 1.17 and 0.25 percent per month of each. The combined effect of both technologies when adopted jointly is increasing crop productivity by 5.82 percent and improving welfare by 0.42 percent. Besides, educational level of household head, farm size, labor use, participation in extension program, expenditure for input and number of oxen positively affect crop productivity and household welfare, while large household size negatively affect welfare of households. In our estimation, the average treatment effect of technology adoption (average treatment effect on the treated, ATET) is the same as the average treatment effect (ATE). This implies that the average predicted outcome for the treatment group is similar to the average predicted outcome for the whole population.

Keywords: Endogenous treatment effect, technologies, productivity, welfare, Ethiopia

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Authors: Ala Rakhshandeh, Zahra Ashkar, Solmaz Dehghani Dolatabadi, Hossein Bayat

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The present study has been conducted to investigate the role of family emotional climate and emotional expression style in the academic well-being of students with military parents. Children, including 280 female students of Shahriar police officers, were selected by random sampling method, and they have been investigated through Alfred B. Hillburn's family emotional climate questionnaire (1964), King and Ammon's emotional expression questionnaire (1990), and Pitrinen, Sweeney, and Falto's academic well-being questionnaire (2014). The data were analyzed using statistical methods of correlation coefficient and stepwise multiple regression under the SPSS23 program. The results reveal that the variables of family emotional climate and emotional expression can explain 36.4% of the variance in academic well-being. This finding reveals that with an increase of standard deviation on the scores of family emotional climate and emotional expression, 0.513 and 0.155 standard deviations are added to the scores of academic well-being, respectively. The emotional climate of the family has a superior distinctive role in predicting the educational well-being of female students. Thus, the emotional climate of the family and the style of emotional expression play a meaningful role in the academic well-being of students with the military parent.

Keywords: emotional climate, family, emotional expression style, academic well-being

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Authors: Hend Almaseb

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Gottman proposed a model of marital conflict with three phases: Agenda-Building, Arguing, and Negotiation. Among a sample of 520 married Kuwaiti women, this study examined the relationship between these phases and the following demographic variables: Level of education, Family income, Health, Occupation, and Tribal affiliation. In addition, the study 1) investigated the marital conflict phases the participants reported having experienced or are currently experiencing and 2) identified the variables that predict one of these conflict phases. The results showed a significant relationship between the following: 1) the Agenda-Building phase and Health; 2) the Arguing phase and Family income, Occupation, and Tribal Affiliation; and 3) the Negotiation phase and Level of education. In addition, a linear regression shows a substantial correlation between the two predictor variables (Level of education and Health problems) and the Agenda Building and Negotiation phases and 5) another substantial correlation between Family income and Arguing.

Keywords: clinical social work, Kuwait, marital conflict, women

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Authors: Nattapong Techarattanased

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The objectives of this research were to study the influence of market orientation and supply chain management on competitive capability in case of the automotive parts industry in Thailand. This study employed by survey research and questionnaire was used to collect the data from 400 entrepreneurs in the automotive parts industry in Thailand. The descriptive statistics and multiple regression analysis were used to analyze data. The results revealed that the overall dimensions of marketing orientation, namely, responsiveness, intelligence generation, and intelligence dissemination were rated at the high level. As well, the overall dimensions of supply chain management, namely, collaboration, communication, trust, and commitment were also rated at the high level. Furthermore, the hypothesis testing results showed that supply chain management and market orientation affected competitive capability of the automotive parts industry in Thailand which these two variables could be combined to predict competitive capability of the automotive parts industry in Thailand by 31.5 percent.

Keywords: automotive parts industry, competitive capability, market orientation, supply chain management

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Authors: Muhammad Safder Shafi, Uzma Javed, Tooba Qasim

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The purpose of this paper is to find out the relationship between training and turnover intention in the presence of mediating variables promotion opportunities and job satisfaction among IT professionals in project based industry. It investigates the relationship directly between 1 independent variable training and dependent variable turnover intention. It also investigates the relationship between independent variable to the mediating variables and mediating variables to the turnover intention. Promotion opportunities and job satisfaction act as a mediator. The study sample comprised of 186 IT professionals from Pakistan, who work on different IT projects. Linear regression and Baron and Kenny approach were used to test the direct and mediated relationship between variables. The survey results demonstrated that job satisfaction fully mediate the relationship between promotion opportunities and turnover intention. Promotion opportunities fully mediate the relationship between employee training and job satisfaction. Promotion opportunities and job satisfaction mediates the relationship between training and turnover intention. The findings from the collected data may help top management to improve organizational strategies to cope up with improving different HR practices like training, pay structure and promotions in order to retain their workforce.

Keywords: HCT, SET, career growth opportunities, job satisfaction, training, turnover intention

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Authors: Shakirat Abimbola Adesola, Shuaib Akintunde Asifat, Jelili Olalekan Amoo

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This paper presented the impact of students’ emotions on learning when receiving lectures and when taking tests. It was observed that students experience different types of emotions during the study, and this was found to have a significant effect on their academic performance. A total of one thousand six hundred and seventy-five (1675) students from the department of Computer Science in two Colleges of Education in South-West Nigeria took part in this study. The students were randomly selected for the research. Sample comprises of 968 males representing 58%, and 707 females representing 42%. A structured questionnaire, of Motivated Strategies for Learning Questionnaire (MSLQ) was distributed to the participants to obtain their opinions. Data gathered were analyzed using the IBM SPSS 20 to obtain ANOVA, descriptive analysis, stepwise regression, and reliability tests. The results revealed that emotion moderately shape students’ motivation and engagement in learning; and that self-regulation and self-determination do have significant impact on academic performance. It was further revealed that test anxiety has a significant correlation with academic performance.

Keywords: motivation, self-determination, test anxiety, academic performance, and academic engagement

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Authors: Itiola Kehinde Adeniran

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This paper investigated the influence of harnessing entrepreneurial opportunities on the national security in Nigeria with a specific focus on the security situation of the post-amnesty programmes of the Federal Government in Ondo State. The self-administered structured questionnaire was employed to collect data from one hundred and twenty participants through purposive sampling method. Inferential statistics was used to analyze the data, specifically; ordinary least squares linear regression method was employed with the aid of statistical package for social science (SPSS) version 20 in order to determine the influence of independent variable (entrepreneurial opportunities) on dependent variable (national security). The result showed that business opportunities have a significant influence on the rate of criminal activities. The study also revealed that entrepreneurial opportunity creation and discovery as well as providing a model on how these entrepreneurial opportunities could be effectively and efficiently utilized jointly predict better national security, which counted for 69% variance of crime rate reduction. The paper, therefore, recommended that citizens should be encouraged to develop an interest in the skill-based activities in order to change their mindset towards self-employment which can motivate them in identify entrepreneurial opportunities.

Keywords: entrepreneurship, entrepreneurial opportunities, national security, unemployment

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Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

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Authors: Wajid Ali Khan

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Extensive experimentation and numerical investigation are performed to predict the machining-induced residual stresses in the end milling of AISI 1045 steel, and an optimization code has been developed using the particle swarm optimization technique. Experiments were conducted using a single factor at a time and design of experiments approach. Regression analysis was done, and a mathematical model of the cutting process was developed, thus predicting the machining-induced residual stress with reasonable accuracy. The mathematical model served as the objective function to be optimized using particle swarm optimization. The relationship between the different cutting parameters and the output variables, force, and residual stresses has been studied. The combined effect of the process parameters, speed, feed, and depth of cut was examined, and it is understood that 85% of the variation of these variables can be attributed to these machining parameters under research. A 3D finite element model is developed to predict the cutting forces and the machining-induced residual stresses in end milling operation. The results were validated experimentally and against the Johnson-cook model available in the literature.

Keywords: residual stresses, end milling, 1045 steel, optimization

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Authors: Karen L. Lindsay, Sonja Entringer, Claudia Buss, Pathik D. Wadhwa

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Maternal nutrition and stress are independently recognized as among the most important factors that influence prenatal biology, with implications for fetal development and poor pregnancy outcomes. While there is substantial evidence from non-pregnancy human and animal studies that a complex, bi-directional relationship exists between nutrition and stress, to the author’s best knowledge, their interaction in the context of pregnancy has been significantly understudied. The aim of this study is to assess the interaction between maternal psychological stress and diet quality across pregnancy and its effects on biomarkers of prenatal insulin resistance and inflammation. This is a prospective longitudinal study of N=235 women carrying a healthy, singleton pregnancy, recruited from prenatal clinics of the University of California, Irvine Medical Center. Participants completed a 4-day ambulatory assessment in early, middle and late pregnancy, which included multiple daily electronic diary entries using Ecological Momentary Assessment (EMA) technology on a dedicated study smartphone. The EMA diaries gathered moment-level data on maternal perceived stress, negative mood, positive mood and quality of social interactions. The numerical scores for these variables were averaged across each study time-point and converted to Z-scores. A single composite variable for 'STRESS' was computed as follows: (Negative mood+Perceived stress)–(Positive mood+Social interaction quality). Dietary intakes were assessed by three 24-hour dietary recalls conducted within two weeks of each 4-day assessment. Daily nutrient and food group intakes were averaged across each study time-point. The Alternative Healthy Eating Index adapted for pregnancy (AHEI-P) was computed for early, middle and late pregnancy as a validated summary measure of diet quality. At the end of each 4-day ambulatory assessment, women provided a fasting blood sample, which was assayed for levels of glucose, insulin, Interleukin (IL)-6 and Tumor Necrosis Factor (TNF)-α. Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was computed. Pearson’s correlation was used to explore the relationship between maternal STRESS and AHEI-P within and between each study time-point. Linear regression was employed to test the association of the stress-diet interaction (STRESS*AHEI-P) with the biological markers HOMA-IR, IL-6 and TNF-α at each study time-point, adjusting for key covariates (pre-pregnancy body mass index, maternal education level, race/ethnicity). Maternal STRESS and AHEI-P were significantly inversely correlated in early (r=-0.164, p=0.018) and mid-pregnancy (-0.160, p=0.019), and AHEI-P from earlier gestational time-points correlated with later STRESS (early AHEI-P x mid STRESS: r=-0.168, p=0.017; mid AHEI-P x late STRESS: r=-0.142, p=0.041). In regression models, the interaction term was not associated with HOMA-IR or IL-6 at any gestational time-point. The stress-diet interaction term was significantly associated with TNF-α according to the following patterns: early AHEI-P*early STRESS vs early TNF-α (p=0.005); early AHEI-P*early STRESS vs mid TNF-α (p=0.002); early AHEI-P*mid STRESS vs mid TNF-α (p=0.005); mid AHEI-P*mid STRESS vs mid TNF-α (p=0.070); mid AHEI-P*late STRESS vs late TNF-α (p=0.011). Poor diet quality is significantly related to higher psychosocial stress levels in pregnant women across gestation, which may promote inflammation via TNF-α. Future prenatal studies should consider the combined effects of maternal stress and diet when evaluating either one of these factors on pregnancy or infant outcomes.

Keywords: diet quality, inflammation, insulin resistance, nutrition, pregnancy, stress, tumor necrosis factor-alpha

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Authors: Satabdi Das

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Background:The abortion debate has polarized women, pitting them against each other in the binary of pro-choice and pro-life. While the followers of pro-choice views the right to an abortion as inherent to a women's right to sovereignty, the latter believes that it is unethical to kill a unborn baby as it is in a way denying the foetus' right to life. So there are innumerable arguments and counter arguments without hyphenation and the dilemma remains that which one is more significant – the mother's right to terminate pregnancy or the foetus' right to life. This pro-life and pro-choice debate has an western root which is more about reproductive freedom. But the Western standard of looking at abortion debate is not fully relevant in the Indian context. The situation is entirely different here. Sex selective foeticide is a social ill in India which cannot be explained through the prism of abortion debate only. It must take into account the problems of forced female foeticide. Objectives: Against this backdrop the study sheds light on the following issues: -How the Reproductive debate has been evolved? -How it is relevant in the Indian Context where female foeticide is a harsh reality? -How one should address the dilemma between life and death in the context of pro life-pro choice debate? Methodology: The study employs historical analytical and descriptive analytical methods and uses primary documents like governmental documents and secondary sources like analytical articles in books, journals, and relevant websites. Findings: -Fertility control is not a modern day phenomenon. It has its roots throughout ancient, medieval and present epochs. However, there existed debates over the rights of the foetus and the question of ethics pertaining to the act of abortion. -Pre-natal sex determination for sex selective abortion is a common phenomenon in India because of the wish for male heirs. The cultural preferences for male child over female ones have resulted in the disappearance of girl children. -When does the life begin has not been recognized by any law. Considering Indian case, it can be said that the Pro life/ pro choice is not that relevant as it is in the US. Here the women are often denied the basic human rights. They are murdered at the womb in many places. Their right to lives are jeopardised in that way. In the liberal abortion regime of India, women's choice to end a pregnancy is limited among very few enlightened families. In many cases, it is the decision of the family to end a pregnancy for boy preference. For that pre natal sex determination plays a crucial role. Conclusion: In India, we can be pro life only when the right to life of the unborn can be secured irrespective of its sex. Similarly we belong to pro-choice group only when the choice to terminate a baby is entirely decided by the mother for her own reasons.

Keywords: female foeticide, India, prolife/pro choice, right to abortion

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Authors: Cai J. T. Ladd, Mollie F. Duggan-Edwards, Tjeerd J. Bouma, Jordi F. Pages, Martin W. Skov

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Salt marshes are valued for their role in coastal flood protection, carbon storage, and for supporting biodiverse ecosystems. As a biogeomorphic landscape, marshes evolve through the complex interactions between sea level rise, sediment supply and wave/current forcing, as well as and socio-economic factors. Climate change and direct human modification could lead to a global decline marsh extent if left unchecked. Whilst the processes of saltmarsh erosion and expansion are well understood, empirical evidence on the key drivers of long-term lateral marsh dynamics is lacking. In a GIS, saltmarsh areal extent in 25 estuaries across Great Britain was calculated from historical maps and aerial photographs, at intervals of approximately 30 years between 1846 and 2016. Data on the key perceived drivers of lateral marsh change (namely sea level rise rates, suspended sediment concentration, bedload sediment flux rates, and frequency of both river flood and storm events) were collated from national monitoring centres. Continuous datasets did not extend beyond 1970, therefore predictor variables that best explained rate change of marsh extent between 1970 and 2016 was calculated using a Partial Least Squares Regression model. Information about the spread of Spartina anglica (an invasive marsh plant responsible for marsh expansion around the globe) and coastal engineering works that may have impacted on marsh extent, were also recorded from historical documents and their impacts assessed on long-term, large-scale marsh extent change. Results showed that salt marshes in the northern regions of Great Britain expanded an average of 2.0 ha/yr, whilst marshes in the south eroded an average of -5.3 ha/yr. Spartina invasion and coastal engineering works could not explain these trends since a trend of either expansion or erosion preceded these events. Results from the Partial Least Squares Regression model indicated that the rate of relative sea level rise (RSLR) and availability of suspended sediment concentration (SSC) best explained the patterns of marsh change. RSLR increased from 1.6 to 2.8 mm/yr, as SSC decreased from 404.2 to 78.56 mg/l along the north-to-south gradient of Great Britain, resulting in the shift from marsh expansion to erosion. Regional differences in RSLR and SSC are due to isostatic rebound since deglaciation, and tidal amplitudes respectively. Marshes exposed to low RSLR and high SSC likely leads to sediment accumulation at the coast suitable for colonisation by marsh plants and thus lateral expansion. In contrast, high RSLR with are likely not offset deposition under low SSC, thus average water depth at the marsh edge increases, allowing larger wind-waves to trigger marsh erosion. Current global declines in sediment flux to the coast are likely to diminish the resilience of salt marshes to RSLR. Monitoring and managing suspended sediment supply is not common-place, but may be critical to mitigating coastal impacts from climate change.

Keywords: lateral saltmarsh dynamics, sea level rise, sediment supply, wave forcing

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Authors: Ramesh Joshi, Nisha Khatik

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Murraya koenigii (L.) Spreng locally known as “Curry patta” or “Meetha neem” belonging to the family Rutaceae that grows wildly in Southern Asia. Its aromatic leaves are commonly used as the raw material for traditional medicinal formulations in India. The leaves contain essential oil and also used as a condiment. Several monomeric and binary carbazol alkaloids present in the various plant parts. These alkaloids have been reported to possess anti-microbial, mosquitocidal, topo-isomerase inhibition and antioxidant properties. Some of the alkaloids reported in this plant have showed anti carcinogenic and anti-diabetic properties. The conventional method of propagation of this tree is limited to seeds only, which retain their viability for only a short period. Hence, a biotechnological approach might have an advantage edging over traditional breeding as well as the genetic improvement of M. koenigii within a short period. The development of a reproducible regeneration protocol is the prerequisite for ex situ conservation and micropropagation. An efficient protocol for high frequency regeneration of in vitro plants of Murraya koenigii via different explants such as- nodal segments, intermodal segments, leaf, root segments, hypocotyle, cotyledons and cotyledonary node explants is described. In the present investigation, assessment of clonal fidelity in the micropropagated plantlets of Murraya koenigii was attempted using RAPD and ISSR markers at different pathways of plant tissue culture technique. About 20 ISSR and 40 RAPD primers were used for all the samples. Genomic DNA was extracted by CTAB method. ISSR primer were found to be more suitable as compared to RAPD for the analysis of clonal fidelity of M. koenigii. The amplifications however, were finally performed using RAPD, ISSR markers owing to their better performance in terms of generation of amplification products. In RAPD primer maximum 75% polymorphism was recorded in OPU-2 series which exhibited out of 04 scorable bands, three bands were polymorphic with a band range of size 600-1500 bp. In ISSR primers the UBC 857 showed 50% polymorphism with 02 band were polymorphic of band range size between 400-1000 bp.

Keywords: genetic fidelity, Murraya koenigii, aromatic plants, ISSR primers

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Authors: M. Amparo Núñez-Andrés, Felipe Buill, Albert Prades

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More and more frequently, geomatics techniques such as terrestrial laser scanning or digital photogrammetry, either terrestrial or from drones, are being used to obtain digital terrain models (DTM) used for the monitoring of geological phenomena that cause natural disasters, such as landslides, rockfalls, debris-flow. One of the main multitemporal analyses developed from these models is the quantification of volume changes in the slopes and hillsides, either caused by erosion, fall, or land movement in the source area or sedimentation in the deposition zone. To carry out this task, it is necessary to filter the point clouds of all those elements that do not belong to the slopes. Among these elements, vegetation stands out as it is the one we find with the greatest presence and its constant change, both seasonal and daily, as it is affected by factors such as wind. One of the best-known indexes to detect vegetation on the image is the NVDI (Normalized Difference Vegetation Index), which is obtained from the combination of the infrared and red channels. Therefore it is necessary to have a multispectral camera. These cameras are generally of lower resolution than conventional RGB cameras, while their cost is much higher. Therefore we have to look for alternative indices based on RGB. In this communication, we present the results obtained in Georisk project (PID2019‐103974RB‐I00/MCIN/AEI/10.13039/501100011033) by using the GLI (Green Leaf Index) and ExG (Excessive Greenness), as well as the change to the Hue-Saturation-Value (HSV) color space being the H coordinate the one that gives us the most information for vegetation filtering. These filters are applied both to the images, creating binary masks to be used when applying the SfM algorithms, and to the point cloud obtained directly by the photogrammetric process without any previous filter or the one obtained by TLS (Terrestrial Laser Scanning). In this last case, we have also tried to work with a Riegl VZ400i sensor that allows the reception, as in the aerial LiDAR, of several returns of the signal. Information to be used for the classification on the point cloud. After applying all the techniques in different locations, the results show that the color-based filters allow correct filtering in those areas where the presence of shadows is not excessive and there is a contrast between the color of the slope lithology and the vegetation. As we have advanced in the case of using the HSV color space, it is the H coordinate that responds best for this filtering. Finally, the use of the various returns of the TLS signal allows filtering with some limitations.

Keywords: RGB index, TLS, photogrammetry, multispectral camera, point cloud

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

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Authors: Jasper C. Dioco

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The study was done to investigate the relationship of taxi company safety climate and drivers’ safety motivation and knowledge on taxi drivers’ safety performance. Data were collected from three Taxi Companies with taxi drivers as participants (N = 84). The Hiligaynon translated version of Transportation Companies’ Climate Scale (TCCS), Safety Motivation and Knowledge Scale, Occupational Safety Motivation Questionnaire and Global Safety Climate Scale were used to study the relationships among four parameters: (a) Taxi company safety climate; (b) Safety motivation; (c) Safety knowledge; and (d) Safety performance. Correlational analyses found that there is no relation between safety climate and safety performance. A Hierarchical regression demonstrated that safety motivation predicts the most variance in safety performance. The results will greatly impact how taxi company can increase safe performance through the confirmation of the proximity of variables to organizational outcome. A strong positive safety climate, in which employees perceive safety to be a priority and that managers are committed to their safety, is likely to increase motivation to be safety. Hence, to improve outcomes, providing knowledge based training and health promotion programs within the organization must be implemented. Policy change might include overtime rules and fatigue driving awareness programs.

Keywords: safety climate, safety knowledge, safety motivation, safety performance, taxi drivers

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Authors: Nomakhosi Tshuma, Carley Chetty

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This study employed panel regression analysis to investigate the financial performance determinants of MTN and Vodacom’s rest of Africa businesses between 2012 to 2020. It used net profit margin, return on assets (ROA), and return on equity (ROE) as financial performance proxies. Financial performance determinants investigated were asset size, debt ratio, liquidity, number of subscribers, and exchange rate. Data relating to exchange rates were obtained from the World Bank website, while financial data and subscriber information were obtained from the companies’ audited financial statements. The study found statistically significant negative relationships between debt and both ROA and net profit, exchange rate and both ROA and net profit, and subscribers and ROE. It also found significant positive relationships between ROE and both asset size and exchange rate. The study recommends strategic options that optimise on the above findings, and these include infrastructure sharing to reduce infrastructure costs and the minimisation of foreign-denominated debt.

Keywords: financial performance, determinants of financial performance, business in Africa, telecommunications industry

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Authors: Rizwan Fazal

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This study investigates the behavior of external sector of Pakistan economy and its impact on economic growth, using quarterly data for the period 1990:01-2010:04. External sector indices used in this study are financial integration, net foreign assets and trade integration. Augmented Ducky fuller confirms that all variables of external sector are non-stationary at level, but at first difference it becomes stationary. The co-integration test suggests one co-integrating variables in the study. The analysis is based on Vector Auto Regression model followed by Vector Error Correction Model. The empirical findings show that financial integration play important role in increasing economic growth in Pakistan economy while trade integration has negative effect on economic growth of Pakistan in the long run. However, the short run confirms that output lag accounts for error correction. The estimated CUSUM and CUSUMQ stability test provide information that the period of the study equation remains stable.

Keywords: financial integration, trade integration, net foreign assets, gross domestic product

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Authors: Lingaraju Dumpala, Narasa Raju Gosangi

Abstract:

Friction Stir Welding (FSW) is relatively new, environmentally friendly, versatile, and widely used joining technique for soft materials such as aluminum. FSW has got a lot of attention as a solid-state joining method which avoids many common problems of fusion welding and provides an improved way of producing aluminum joints in a faster way. FSW can be used for various aerospace, defense, automotive and transportation applications. It is necessary to understand the friction stir welded joints and its characteristics to use this new joining technique in critical applications. This study investigated the mechanical properties of friction stir welded aluminum 6063 alloys. FSW is carried out based on the design of experiments using L16 mixed level array by considering tool rotational speeds, tool feed rate and tool tilt angles as process parameters. The optimization of process parameters is carried by Taguchi based regression analysis and the significance of process parameters is analyzed using ANOVA. It is observed that the considered process parameters are high influences the mechanical properties of Al6063.

Keywords: FSW, aluminum alloy, mechanical properties, optimization, Taguchi, ANOVA

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Authors: Sanoj Sahu, Ramakar Jha

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Odisha (India) is in need of reliable, cost-effective power generation. A prolonged electricity crisis and increasing power demand have left over thousands of citizens without access to electricity, and much of the population suffers from sporadic outages. The purpose of this project is to build a methodology to evaluate small hydropower potential, which can be used to alleviate the Odisha’s energy problem among rural communities. This project has three major tasks: the design of a simple SHEP for a single location along a river in the Odisha; the development of water flow prediction equations through a linear regression analysis; and the design of an ArcGIS toolset to estimate the flow duration curves (FDCs) at locations where data do not exist. An explanation of the inputs to the tool, as well has how it produces a suitable output for SHEP evaluation will be presented. The paper also gives an explanation of hydroelectric power generation in the Odisha, SHEPs, and the technical and practical aspects of hydroelectric power. Till now, based on topographical and rainfall analysis we have located hundreds of sites. Further work on more number of site location and accuracy of location is to be done.

Keywords: small hydropower, ArcGIS, rainfall analysis, Odisha’s energy problem

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Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

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People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

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Authors: Ubaidillah Zuhdi, Shunsuke Mori, Kazuhisa Kamegai

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The purpose of this study is to forecast the influences of Information and Communication Technology (ICT) on the structural changes of Japanese economies based on Leontief Input-Output (IO) coefficients. This study establishes a statistical analysis to predict the future interrelationships among industries. We employ the Constrained Multivariate Regression (CMR) model to analyze the historical changes of input-output coefficients. Statistical significance of the model is then tested by Likelihood Ratio Test (LRT). In our model, ICT is represented by two explanatory variables, i.e. computers (including main parts and accessories) and telecommunications equipment. A previous study, which analyzed the influences of these variables on the structural changes of Japanese industrial sectors from 1985-2005, concluded that these variables had significant influences on the changes in the business circumstances of Japanese commerce, business services and office supplies, and personal services sectors. The projected future Japanese economic structure based on the above forecast generates the differentiated direct and indirect outcomes of ICT penetration.

Keywords: forecast, ICT, industrial structural changes, statistical analysis

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Authors: Hugo M. Gonzales, Ke Ni Chai, Deanne Mary King

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International students are underrepresented in Australian health literature, and this population is especially vulnerable to the well-documented negative impacts associated with racial microaggressions in their adjustment to settling in the new society, as well as to the many challenges they already face as international students. This study investigated the prevalence of racial microaggressions among international students and their impact on stress and psychological well-being. This research was conducted during the COVID-19 pandemic, which has been documented to contribute to anti-Asian racism. Participants included 54 international students, of which 72% were Asian. The Racial and Ethnic Microaggressions Scale (REMS), Perceived Stress Scale (PSS), and the Perceived General Wellbeing Indicator (PGWBI) were used to measure the participants’ responses. All participants reported experiencing racial microaggression in the last six months, and significant correlations and regression models were found between REMS, certain elements of the PSS scale, and time in Australia. Despite the small sample size, this research corroborated outcomes from recent studies and provided insight into the prevalence and impact of racial microaggressions among such populations, highlighting the need for further exploration.

Keywords: racial microaggressions, international students, racism, REMS, microaggressions in Australia, stress, psychological wellbeing

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Authors: Ashraf Ward

Abstract:

Effect of calving interval on 305 day milk yield for first three lactations was studied in order to increase efficiency of selection schemes and to more efficiently manage Holstein cows that have been raised on small farms in Libya. Results obtained by processing data of 1476 cows, managed in 935 small scale farms, pointed out that current calving interval significantly affects on milk production for first three lactations (p<0.05). Preceding calving interval affected 305 day milk yield (p<0.05) in second lactation only. Linear regression model accounted for 20-25 % of the total variance of 305 day milk yield. Extension of calving interval over 420, 430, 450 days for first, second and third lactations respectively, did not increase milk production when converted to 305 day lactation. Stochastic relations between calving interval and calving age and month are moderated. Values of Pierson’s correlation coefficients ranged 0.38 to 0.69. Adjustment of milk production in order to reduce effect of calving interval on total phenotypic variance of milk yield is valid for first lactation only. Adjustment of 305 day milk yield for second and third lactations in order to reduce effects of factors “calving age and month” brings about, at the same time, elimination of calving interval effect.

Keywords: milk yield, Holstien, non genetic, calving

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Authors: Olumuyiwa Idowu Ojo, Oluwatobi Peter Olowo

Abstract:

The study developed a Geographical Information Systems (GIS) database and mapped inter-annual changes in crop yields of cassava, cowpea, maize, rice, melon and yam as a response to inter-annual rainfall and temperature variability in Southwest, Nigeria. The aim of this project is to study the comparative analysis of the weather variability impact of six crops yield (Rice, melon, yam, cassava, Maize and cowpea) in South Western States of Nigeria (Oyo, Osun, Ekiti, Ondo, Ogun and Lagos) from 1991 – 2007. The data was imported and analysed in the Arch GIS 9 – 3 software environment. The various parameters (temperature, rainfall, crop yields) were interpolated using the kriging method. The results generated through interpolation were clipped to the study area. Geographically weighted regression was chosen from the spatial statistics toolbox in Arch GIS 9.3 software to analyse and predict the relationship between temperature, rainfall and the different crops (Cowpea, maize, rice, melon, yam, and cassava).

Keywords: GIS, crop yields, comparative analysis, temperature, rainfall, weather variability

Procedia PDF Downloads 309