Search results for: multivariate regression tree

Authors: Haftay Abraha Tadesse, Atsebaha Gebrekidan Kahsay, Mahumd Abdulkader

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Background: Salmonella species and Escherichia coli are important foodborne pathogens affecting humans and animals. They are among the most important causes of infection that are associated with the consumption of contaminated food. This study was aimed to determine the prevalence, antimicrobial susceptibility patterns and associated risk factors for Salmonella species and E. coli in raw meat from butchery houses of Mekelle, Northern Ethiopia. Methodology: A cross-sectional study was conducted from January to September 2019. Socio-demographic data and risk factors were collected using a predesigned questionnaire. Meat samples were collected aseptically from the butchery houses and transported using icebox to Mekelle University, College of Veterinary Sciences for the isolation and identification of Salmonella species and E. coli, Antimicrobial susceptibility patterns were determined using Kirby disc diffusion method. Data obtained were cleaned and entered into Statistical Package for the Social Sciences version 22 and logistic regression models with odds ratio were calculated. P-value < 0.05 was considered as statistically significant. Results: A total of 153 out of 384 (39.8%) of the meat specimens were found to be contaminated. The contamination of Salmonella species and E. coli were 15.6% (n=60) and 20.8%) (n=80), respectively. Mixed contamination (Salmonella species and E. coli) was observed in 13 (3.4 %) of the analyzed. Poor washing hands regularly (AOR = 8.37; 95% CI: 2.75-25.50) and not using gloves during meat handling (AOR=11. 28; 95% CI: (4.69 27.10) were associated with an overall bacterial contamination.About 95.5% of the tested isolates were sensitive to chloramphenicol and norfloxacin while the resistance of amoxyclav_amoxicillin and erythromycin were both isolated bacteria species. The overall multidrug resistance pattern for Salmonella and E. coli were 51.4% (n=19) and 31.8% (14), respectively. Conclusion: Of the 153 (153/384) contaminated raw meat, 60 (15.6%) and 80 (20.8%) were contaminated by Salmonella species and E. coli, respectively. Poor hand washing practice and not using glove during meat handling showed significant association with bacterial contamination. Multidrug-resistant showed in Salmonella species and E. coli were 19 (51.4%) and 14 (31.8%), respectively.

Keywords: antimicrobial susceptibility test, butchery houses, e. coli, salmonella species

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Authors: Caroline Dupre, David Hupin, Christ Goumou, Francois Belan, Frederic Roche, Thomas Celarier, Bienvenu Bongue

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Background: Previous cohorts have been notably criticized for not studying the different type of physical activity and not investigating household activities. The objective of this work was to analyse the relationship between physical activity and cognitive decline in older people living in the community. Impact of type of physical activity on the results has been realised. Methods: The study used data from the longitudinal and observational study , FrèLE (FRagility: Longitudinal Study of Expressions). The collected data included: socio-demographic variables, lifestyle, and health status (frailty, comorbidities, cognitive status, depression). Cognitive decline was assessed by using: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Physical activity was assessed by the Physical Activity Scale for the Elderly (PASE). This tool is structured in three sections: the leisure activity, domestic activity, and professional activity. Logistic regressions and proportional hazards regression models (Cox) were used to estimate the risk of cognitive disorders. Results: At baseline, the prevalence of cognitive disorders was 6.9% according to MMSE. In total, 1167 participants without cognitive disorders were included in the analysis. The mean age was 77.4 years, and 52.1% of the participants were women. After a 2 years long follow-up, we found cognitive disorders on 53 participants (4.5%). Physical activity at baseline is lower in older adults for whom cognitive decline was observed after two years of follow-up. Subclass analyses showed that leisure and domestic activities were associated with cognitive decline, but not professional activities. Conclusions: Analysis showed a relationship between cognitive disorders and type of physical activity. The current study will be completed by the MoCA for mild cognitive impairment. These findings compared to other ongoing studies, will contribute to the debate on the beneficial effects of physical activity on cognition.

Keywords: aging, cognitive function, physical activity, mixed models

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Authors: C. A. Bradley, D. Patsios, D. Berridge

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This paper presents evidence to better understand the risk and protective factors related to sibling conflict and the patterns of association between sibling conflict and negative adjustment outcomes by incorporating additional familial and societal factors within statistical models of risk and adjustment. It was conducted through the secondary analysis of a large representative cross-sectional dataset of children in the UK. The original study includes proxy interviews for young children and self-report interviews for adolescents. The study applies an ecological systems framework for the analyses. Hierarchical regression models assess risk and protective factors and adjustment outcomes associated with sibling conflict. Interactions reveal differential effect between contextual risk factors and the social context of influence. The general pattern of findings suggested that, although factors affecting likelihood of experiencing sibling conflict were often determined by child age, some remained consistent across childhood. These factors were often conditional on each other, reinforcing the importance of an ecological framework. Across both age-groups, sibling conflict was associated with siblings closer in age; male sibling groups; most advantaged socio-economic group; and exposure to community violence, such as witnessing violent assault or robbery. The study develops the evidence base on the influence of ethnicity and socio-economic group on sibling conflict by exploring interactions between social context. It also identifies key new areas of influence – such as family structure, disability, and community violence in exacerbating or reducing risk of conflict. The study found negative associations between sibling conflict and young children’s mental well-being and adolescents' mental well-being and anti-social behaviour, but also more context specific associations – such as sibling conflict moderating the negative impact of adversity and high risk experiences for young children such as parental violence toward the child.

Keywords: adjustment, conflict, ecological systems, family systems, risk and protective factors, sibling

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Authors: Samuel Oye Bandele

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A policy is a system of principles to guide activities and strategic decisions of an organisation in order to achieve stated objectives and meeting expected outcomes. A Computer Based Test (CBT) policy is therefore a statement of intent to drive the CBT programmes, and should be implemented as a procedure or protocol. Policies are hence generally adopted by an organization or a nation. The concern here, in this paper, is the consideration and analysis of issues that are significant to evolving the acceptable policy that will drive the new CBT innovation in Nigeria. Public examinations and internal examinations in higher educational institutions in Nigeria are gradually making a radical shift from Paper Based or Paper-Pencil to Computer-Based Testing. The need to make an objective and empirical analysis of Policy issues relating to CBT became expedient. The following are some of the issues on CBT evolution in Nigeria that were identified as requiring policy backing. Prominent among them are requirements for establishing CBT centres, purpose of CBT, types and acquisition of CBT equipment, qualifications of staff: professional, technical and regular, security plans and curbing of cheating during examinations, among others. The descriptive research design was employed based on a population consisting of Principal Officers (Policymakers), Staff (Teaching and non-Teaching-Policy implementors), and CBT staff ( Technical and Professional- Policy supports) and candidates (internal and external). A fifty-item researcher-constructed questionnaire on policy issues was employed to collect data from 600 subjects drawn from higher institutions in South West Nigeria, using the purposive and stratified random sampling techniques. Data collected were analysed using descriptive (frequency counts, means and standard deviation) and inferential (t-test, ANOVA, regression and Factor analysis) techniques. Findings from this study showed, among others, that the factor loadings had significantly weights on the organizational and National policy issues on CBT innovation in Nigeria.

Keywords: computer-based testing, examination, innovation, paper-based testing, paper pencil based testing, policy issues

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Authors: Calogero Lo Destro

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Numerous nations around the world are facing exceptional challenges in employing measures to stop the spread of COVID-19. Following the recommendations of the World Health Organization, a series of preventive measures have been adopted. However, individuals must comply with these rules and recommendations in order to make these measures effective. While COVID-19 was climaxing, it seemed of crucial importance to analyze which psychosocial factors contribute to the acceptance of such preventive behavior, thus favoring the management of COVID-19 worldwide health crisis. In particular, the identification of aspects related to obstacles and facilitation of adherence to social distancing has been considered crucial in the containment of the virus spread. Since the virus was firstly detected in China, Asian people could be considered a relevant outgroup targeted for exclusion. We also hypothesized social distance could be influenced by characteristics of the target, such as smiling or coughing. 260 participants participated in this research on a voluntary basis. They filled a survey designed to explore a series of COVID-19 measures (such as exposure to virus and fear of infection). We also assessed participants state and trait anxiety. The dependent variable was social distance, based on a measure of seating distance designed ad hoc for the present work. Our hypothesis that participants could report greater distance in response to Asian people was not confirmed. On the other hand, significantly lower distance in response to smiling compared to coughing targets was reported. Adopting a regression analysis model, we found that participants' social distance, in response to both coughing and smiling targets, was predicted by fear of infection and by the perception COVID-19 could become a pandemic. Social distance in response to the coughing target was also significantly and positively predicted by age and state anxiety. In summary, the present work has sought to identify a set of psychological variables, which may still be predictive of social distancing.

Keywords: COVID-19, social distancing, health, preventive behaviors, risk of infection

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Authors: Tasneem Imam, Justine S. Gibson, Mohammad Foysal, Shetu B. Das, Rashed Mahmud, Suman D. Gupta, Ahasanul Hoque, Guillaume Fournie, Joerg Henning

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Commercial chicken production is an import livestock industry in Bangladesh. Antimicrobials are commonly used to control and prevent infectious diseases. It was hypothesized that inadequate biosecurity practices might promote antimicrobial usage on commercial chicken farms. A cross-sectional study was carried out to evaluate antimicrobial usage and farm biosecurity practices implemented on 57 layer and 83 broiler farms in eight sub-districts of the Chattogram district in Bangladesh. A questionnaire was used to collect data on antimicrobial usage and biosecurity practices on these farms. A causal framework was used to guide the development of a multi-level mixed-effects logistic regression analysis to evaluate the total and direct effects of practiced biosecurity management on prophylactic and therapeutic administration of antimicrobials. A total of 24 antimicrobials were administered in the current production cycle at the time of the survey. The most administered antimicrobials on layer farms were ciprofloxacin (37.0% of farms), amoxicillin (33.3%), and tiamulin (31.5%); however, on broiler farms, colistin (56.6% of farms), doxycycline (50.6%), and neomycin (38.6%) were most used. Only 15.3% of commercial farmers used antimicrobials entirely for therapeutic purposes, whereas 84.7% administered antimicrobials prophylactically. Inadequate biosecurity practices were more common among commercial broiler farmers compared to layer farmers. For example, only 2.4% of broiler farmers used footbaths before entering sheds compared to 22.2% of the layer farmers (p < 0.001). Farms that used antimicrobials only for therapeutic purposes (vs prophylactic) implemented more frequently adequate disease control measures, such as separating sick birds from healthy birds. This research highlighted that the prophylactic application of antimicrobials is often conducted to substitute poor biosecurity practices on commercial chicken farms. Awareness programs for farmers are crucial to inform them about the risk associated with antimicrobial usage and to highlight the economic benefits of implementing cost-effective biosecurity measures to control infectious poultry diseases.

Keywords: antimicrobial, biosecurity, broiler, layer

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, new methodologies to analyze investment risk are needed. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. This study modeled the economics and risk strategies of cradle-to-cradle linkages to incorporate the value-chain effects on capital/operational expenditures and investment risk reductions using a proprietary techno-economic model that incorporates investment risk scenarios utilizing the Monte Carlo methodology. The study calculated the sequential increases in profitability for each additional co-host on an operating forestry-based biomass energy plant in West Enfield, Maine. Phase I starts with the base-line of forestry biomass to electricity only and was built up in stages to include co-hosts of a greenhouse and a land-based shrimp farm. Phase I incorporates CO2 and heat waste streams from the operating power plant in an analysis of lowering and stabilizing the operating costs of the agriculture and aquaculture co-hosts. Phase II analysis incorporated a jet-fuel biorefinery and its secondary slip-stream of biochar which would be developed into two additional bio-products: 1) A soil amendment compost for agriculture and 2) A biochar effluent filter for the aquaculture. The second part of the study applied the Monte Carlo risk methodology to illustrate how co-location derisks investment in an integrated Bio-Hub versus individual investments in stand-alone projects of energy, agriculture or aquaculture. The analyzed scenarios compared reductions in both Capital and Operating Expenditures, which stabilizes profits and reduces the investment risk associated with projects in energy, agriculture, and aquaculture. The major findings of this techno-economic modeling using the Monte Carlo technique resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. In 2018, the site was designated as an economic opportunity zone as part of a Federal Program, which allows for Capital Gains tax benefits for investments on the site. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. The Bio-hub Ecosystems techno-economic analysis model is a critical model to expedite new standards for investments in circular zero-waste projects. Profitable projects will expedite adoption and advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable Bio-Economy paradigm that supports local and rural communities.

Keywords: bio-economy, investment risk, circular design, economic modelling

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Authors: Abbas Ali Husseini, Ali Mohammad Yazdani, Fatemeh Ghadiri, Alper Şişman

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We developed a microchip device that uses surface acoustic waves for rapid lysis of low level of cell samples. The device incorporates sharp-edge glass microparticles for improved performance. We optimized the lysis conditions for high efficiency and evaluated the device's feasibility for point-of-care applications. The microchip contains a 13-finger pair interdigital transducer with a 30-degree focused angle. It generates high-intensity acoustic beams that converge 6 mm away. The microchip operates at a frequency of 16 MHz, exciting Rayleigh waves with a 250 µm wavelength on the LiNbO3 substrate. Cell lysis occurs when Candida albicans cells and glass particles are placed within the focal area. The high-intensity surface acoustic waves induce centrifugal forces on the cells and glass particles, resulting in cell lysis through lateral forces from the sharp-edge glass particles. We conducted 42 pilot cell lysis experiments to optimize the surface acoustic wave-induced streaming. We varied electrical power, droplet volume, glass particle size, concentration, and lysis time. A regression machine-learning model determined the impact of each parameter on lysis efficiency. Based on these findings, we predicted optimal conditions: electrical signal of 2.5 W, sample volume of 20 µl, glass particle size below 10 µm, concentration of 0.2 µg, and a 5-minute lysis period. Downstream analysis successfully amplified a DNA target fragment directly from the lysate. The study presents an efficient microchip-based cell lysis method employing acoustic streaming and microparticle collisions within microdroplets. Integration of a surface acoustic wave-based lysis chip with an isothermal amplification method enables swift point-of-care applications.

Keywords: cell lysis, surface acoustic wave, micro-glass particle, droplet

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Authors: Sofia Nilsson, Alicia Ohlsson, Linda-Marie Lundqvist, Aida Alvinius, Peder Hyllengren, Gerry Larsson

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In irregular warfare contexts, military personnel are often presented with morally ambiguous situations where they are aware of the morally correct choice but may feel prevented to follow through with it due to organizational demands. Moral stress and/or injury can be the outcome of the individual’s experienced dissonance. These types of challenges put a large demand on the individual to manage their own emotions and the emotions of others, particularly in the case of a leader. Both the ability and inability for emotional regulation can result in different combinations of short and long term reactions after morally stressful events, which can be either positive or negative. Our study analyzed the combination of these reactions based upon the types of morally challenging events that were described by the subjects. 1)What institutionalized norms concerning emotion regulation are favorable in short-and long-term perspectives after a morally stressful event? 2)What individual emotion-focused coping strategies are favorable in short-and long-perspectives after a morally stressful? To address these questions, we conducted a quantitative study in military contexts in Sweden and Norway on upcoming or current military officers (n=331). We tested a theoretical model built upon a recently developed qualitative study. The data was analyzed using factor analysis, multiple regression analysis and subgroup analyses. The results indicated that an individual’s restriction of emotion in order to achieve an organizational goal, which results in emotional dissonance, can be an effective short term strategy for both the individual and the organization; however, it appears to be unfavorable in a long-term perspective which can result in negative reactions. Our results are intriguing because they showed an increased percentage of reported negative long term reactions (13%), which indicated PTSD-related symptoms in comparison to previous Swedish studies which indicated lower PTSD symptomology.

Keywords: emotion culture, emotion coping, emotion management, military

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Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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Authors: Pramika J. Muthya

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This paper investigates the impact of web graphics and interface design on building visitor trust in websites. A quantitative survey approach was used to examine how aesthetic and usability elements of website design influence user perceptions of trustworthiness. 133 participants aged 18-25 who live in urban Bangalore and engage in online transactions were recruited via convenience sampling. Data was collected through an online survey measuring trust levels based on website design, using validated constructs like the Visual Aesthetic of Websites Inventory (VisAWI). Statistical analysis, including ordinal regression, was conducted to analyze the results. The findings show a statistically significant relationship between web graphics and interface design and the level of trust visitors place in a website. The goodness-of-fit statistics and highly significant model fitting information provide strong evidence for rejecting the null hypothesis of no relationship. Well-designed visual aesthetics like simplicity, diversity, colorfulness, and craftsmanship are key drivers of perceived credibility. Intuitive navigation and usability also increase trust. The results emphasize the strategic importance for companies to invest in appealing graphic design, consistent with existing theoretical frameworks. There are also implications for taking a user-centric approach to web design and acknowledging the reciprocal link between pre-existing user trust and perception of visuals. While generalizable, limitations include possible sampling and self-report biases. Further research can build on these findings to deepen understanding of nuanced cultural and temporal factors influencing online trust. Overall, this study makes a significant contribution by providing empirical evidence that reinforces the crucial impact of thoughtful graphic design in fostering lasting user trust in websites.

Keywords: web graphics, interface design, visitor trust, website design, aesthetics, user experience, online trust, visual design, graphic design, user perceptions, user expectations

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Authors: Igbekoyi Olusola Esther, Olurankinse Felix

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This paper examined the factors that militate against Will writing among entrepreneurs in Ondo State Nigeria and the effect of intestate death on business continuity after the exit of the entrepreneurs. The paper was written with a view to providing information on the reasons why intestate death is common among entrepreneurs in Ondo State and the effects on continuity of business after death of the initial owners. Data were obtained from primary source through the administration of questionnaires to entrepreneurs drawn from 50 registered manufacturing companies. These companies have been in existence for a minimum of 10 years with minimum staff strength of 20 workers each. These companies were selected using the purposive random sampling technique in order to capture firms that meet the requirements of this paper. Data obtained were analyzed using descriptive statistics, chi-square and regression analysis. The findings of the paper revealed that administration of Will, traditional beliefs, Will execution procedures, age and non- admissibility of Wills in court are the major factors that militates against Will writing among entrepreneurs in Ondo State. It was also discovered that chaos and instability in business, reduction in sales and productivity, poor succession planning, polygamous nature of marriages, difficulty in sourcing for funds and gender preference are joint predictors of business continuity in event intestate death which is evident in the result where R2 =.954;(F 6, 26)= 89.644; (P < 0.01). The individual beta co-efficient, t- statistics and significance of each variable revealed that gender preference (.735; 7.031; .000) and poor succession plan (.402; 2.840; .009) have significant positive effect on business continuity; while reduction in sales and productivity (-.059; -.335; .740) and difficulty in sourcing for funds (-.217; -1.367; .188) have negative effect; other variables also have positive relationship but they are not significant. It is therefore concluded that business continuity after the exit of the entrepreneur is highly dependent on the rebuilding of confidence on Wills administration in ondo state Nigeria, proper succession planning and elimination of gender preferences.

Keywords: intestacy, business continuity, entrepreneurs, will, succession planning

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Authors: Uche Lucy Onyekwelu, Uche B. Ugwuanyi

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Suffice to say that socio-economic disruptions of any form is likely to affect the wellbeing of the citizenry. The upsurge of social disequilibrium caused by the incessant disruptive tendencies exhibited by youths and some others in Nigeria are not helping matters. In Nigeria the social unrest has caused different forms of draw backs in Socio Economic Development. This study has empirically evaluated the impact of insecurity and insurgency on the Economic Development of Nigeria. The paper noted that the different forms of insecurity in Nigeria are namely: Insurgency and Banditry as witnessed in Northern Nigeria; Militancy: Niger Delta area and self-determination groups pursuing various forms of agenda such as Sit –at- Home Syndrome in the South Eastern Nigeria and other secessionist movements. All these have in one way or the other hampered Economic development in Nigeria. Data for this study were collected through primary and secondary sources using questionnaire and some existing documentations. Cost of investment in different aspects of security outfits in Nigeria represents the independent variable while the differentials in the Gross Domestic Product(GDP) and Human Development Index(HDI) are the measures of the dependent variable. Descriptive statistics and Simple Linear Regression analytical tool were employed in the data analysis. The result revealed that Insurgency/Insecurity negatively affect the economic development of the different parts of Nigeria. Following the findings, a model to analyse the effect of insecurity and insurgency was developed, named INSECUREDEVNIG. It implies that the economic development of Nigeria will continue to deteriorate if insurgency and insecurity continue. The study therefore recommends that the government should do all it could to nurture its human capital, adequately fund the state security apparatus and employ individuals of high integrity to manage the various security outfits in Nigeria. The government should also as a matter of urgency train the security personnel in intelligence cum Information and Communications Technology to enable them ensure the effectiveness of implementation of security policies needed to sustain Gross Domestic Product and Human Capital Index of Nigeria.

Keywords: insecurity, insurgency, gross domestic product, human development index, Nigeria

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Authors: Xie Xiaobin, Zhang Yan, Shi Yipeng, Sun Wenying, Chen Shuang, Cai Zhipeng, Zhang Hong, Zhang Lixia, Xie Like

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Objective: The objective of this research is to compare the efficacy of the late in-situ surgical revision augmented with continuous infusion and needle revision on failed trabeculectomy blebs. Methods From December 2018 to December 2021, a prospective randomized controlled trial was performed on 44 glaucoma patients with failed bleb ≥ 6months with medically uncontrolled in Eye Hospital, China Academy of Chinese Medical Sciences. They were randomly divided into two groups. 22 eyes of 22 patients underwent the late in-situ surgical revision with continuous anterior chamber infusion in the study group, and 22 of 22 patients were treated with needle revision in the control group. Main outcome measures include preoperative and postoperative intraocular pressure (IOP), the number of anti-glaucoma medicines, the operation success rate, and the postoperative complications. Results The postoperative IOP values decreased significantly from the baseline in both groups (both P<0.05). IOP was significantly lower in the study group than in the control group at one week, 1, and 3 months postoperatively (all P<0.05). IOP reductions in the study group were substantially more prominent than in the control group at all postoperative time points (all P<0.05). The complete success rate in the study group was significantly higher than in the control group (71.4% vs. 33.3%, P<0.05), while the complete failure rate was significantly lower in the study group (0% vs. 28.5%, P<0.05). According to Cox’s proportional hazards regression analysis, high IOP at baseline was independently associated with increased risks of complete failure (adjusted hazard ratio=1.141, 95% confidence interval=1.021-1.276, P<0.05). There was no significant difference in the incidence of postoperative complications between the two groups (P>0.05). Conclusion: Both in-situ surgical and needle revision have acceptable success rates and safety for the late failed trabeculectomy blebs, while the former is likely to have a higher level of efficacy over the latter. Needle revision may be insufficient for eyes with low target IOP.

Keywords: glaucoma, trabeculectomy blebs, in-situ surgical revision, needle revision

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Irsa Ejaz, Siyang He, Wei Li, Naiyue Hu, Chaochen Tang, Songbo Li, Meng Li, Boubacar Diallo, Guanghui Xie, Kang Yu

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Background: Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. Previously reported NIR model calibrations using the whole grain spectra had moderate accuracy. Improved predictions are achievable by using the spectra of whole grains, when compared with the use of spectra collected from the flour samples. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Objectives: To evaluate the feasibility of using NIRS and the influence of four sample types (whole grains, flours, hulled grain flours, and hull-less grain flours) on the prediction of chemical components to improve the grain sorting efficiency for human food, animal feed, and biofuel. Methods: NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. Results: The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. Conclusion: The established PLSR models could enable food, feed, and fuel producers to efficiently evaluate a large number of samples by predicting the required biochemical components in sorghum grains without destruction.

Keywords: FT-NIR, sorghum grains, biochemical composition, food, feed, fuel, PLSR

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Authors: Sophie Kroeling, Agnetha Schuchardt

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Striving for sustainability brings a lot of challenges for different fields of interest, e. g. security or health concerns. In Germany, civil protection is predominantly carried out by emergency responders who perform essential tasks of civil protection. Based on theoretical concepts of different psychological stress theories this contribution focuses on the question, how the resilience of emergency responders can be improved. The goal is to identify resources and successful coping strategies that help to prevent and reduce negative outcomes during or after stressful events. The paper will present results from a qualitative analysis of semi-structured qualitative interviews with 20 emergency responders. These results provide insights into the complexity of coping processes (e. g. controlling the situation, downplaying perceived personal threats through humor) and show the diversity of stressors (like complexity of the disastrous situation, intrusive press and media, or lack of social support within the organization). Self-efficacy expectation was a very important resource for coping with stressful situations. The results served as a starting point for a quantitative survey (that was conducted in March 2017), the development of education and training tools for emergency responders and the improvement of critical incident stress management processes. First results from the quantitative study with more than 700 participants show that, e. g., the emergency responders use social coping within their private social network and also within their aid organization and that both are correlated to resilience. Moreover, missing information, bureaucratic problems and social conflicts within the organization are events that the majority of the participants considered very onerous. Further results from regression analysis will be presented. The proposed paper will combine findings from the qualitative study with the quantitative results, illustrating figures and correlations with respective statements from the interviews. At the end, suggestions for the improvement of the emergency responder’s resilience are given and it is discussed how this can make a contribution to strive for civil security and furthermore a sustainable development.

Keywords: civil security, emergency responders, stress, resilience, resources

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Authors: Wenyan Xu, Rundong Wang, Chen Li, Yonghong Hu, Zhonghua Lu

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In the field of quantitative trading, it is common to find patterns in short-term volatile trends of the market. These patterns are known as High-Frequency (HF) risk factors, serving as effective indicators of future stock price volatility. However, in the past, these risk factors were usually generated by traditional financial models, and the validity of these risk factors is heavily based on domain-specific knowledge manually added instead of extensive market data. Inspired by symbolic regression (SR), the task of inferring mathematical laws from existing data, we take the extraction of formulaic risk factors from high-frequency trading (HFT) market data as an SR task. In this paper, we challenge the procedure of manually constructing risk factors and propose an end-to-end methodology, Intraday Risk Factor Transformer (IRFT) to directly predict the full formulaic factors, constants included. Specifically, we utilize a hybrid symbolic-numeric vocabulary where symbolic tokens denote operators/stock features and numeric tokens denote constants. Then, we train a Transformer model on the HFT dataset to directly generate complete formulaic HF risk factors without relying on the skeleton, which is a parametric function using a pre-defined list of operators – typically, the math operations (+, ×, /) and functions(√x, log x, cos x). It determines the general shape of the stock volatility law up to a choice of constants, e.g., f(x) = tan(ax+b) (x is the stock price). We further refine predicted constants(a,b) using the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) as informed guesses to mitigate non-linear issues. Compared to the 10 approaches in SRBench, which is a living benchmark for SR, IRFT gains a 30% excess investment return on the HS300 and S&P500 datasets, with inference times orders of magnitude faster than theirs in HF risk factor mining tasks.

Keywords: transformer, factor-mining language model, highfrequency risk factor collections

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Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

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Authors: Margarida Matos, João Pereira dos Santos, José Tavares

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Anti-minority discrimination is a persistent phenomenon with long-run effects. While there is a vast literature in economics and psychology that shows that personality and beliefs are not fixed and can be altered by experience, particularly in the so-called impressionable years in early adulthood, less is known about the long-lasting impacts of major events occurring during this time on minority attitudes. In this paper, we study the impact of serving in the military on long-term attitudes towards minorities. For many, military conscription and serving in war are unique life-shaping events. In the context of military service, individuals from different socioeconomic backgrounds interact and learn with each other, potentially changing their views and attitudes in a persistent manner. A prominent theory about the change of attitudes is the contact theory. It suggests that prejudice can be decreased if members of the groups interact with one another. The present paper adds to the literature by providing evidence from a more complicated setting involving the exposure to combat. We study the attitudes of veterans of the Portuguese Colonial War between 1961 and 1974, what was the latest war between African independence movements and Europeans. More than 70 percent of military age Portuguese men were drafted every year and sent to fight in Africa in the widest draft in post-World War II Western Europe. The contact between Portuguese and African soldiers was both cooperative as well as adversarial. Portuguese fought against but also alongside locally recruited African men, who represented half of the Portuguese contingent for substantial periods. We use data from the European Social Survey to identify Portuguese citizens likely to have been drafted and were send to fight in the former Portuguese colonies in Africa. We show that men likely to have fought in African wars are more accepting of immigrants than women of their same cohort, as well as than males from younger and older cohorts. The use of corresponding cohorts from Spain as placebo tests confirms our results. Our findings also hold in a regression discontinuity design setting.

Keywords: attitudes, immigration, war in Africa, veterans, portugal

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Authors: Yuwaratu Syafira, Wahyu K. Y. Putra, Kusharisupeni Djokosujono

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Background/Objective: Body Mass Index (BMI) serves various purposes, including measuring the prevalence of obesity in a population, and also in formulating a patient’s diet at a hospital, and can be calculated with the equation = body weight (kg)/body height (m)². However, the BMI of an individual with difficulties in carrying their weight or standing up straight can not necessarily be measured. The aim of this study was to form a prediction model for the BMI of young adult students of Public Health Faculty of University of Indonesia. Subject/Method: This study used a cross sectional design, with a total sample of 132 respondents, consisted of 58 males and 74 females aged 21- 30. The dependent variable of this study was BMI, and the independent variables consisted of sex and anthropometric measurements, which included ulna length, arm length, tibia length, knee height, mid-upper arm circumference, and calf circumference. Anthropometric information was measured and recorded in a single sitting. Simple and multiple linear regression analysis were used to create the prediction equation for BMI. Results: The male respondents had an average BMI of 24.63 kg/m² and the female respondents had an average of 22.52 kg/m². A total of 17 variables were analysed for its correlation with BMI. Bivariate analysis showed the variable with the strongest correlation with BMI was Mid-Upper Arm Circumference/√Ulna Length (MUAC/√UL) (r = 0.926 for males and r = 0.886 for females). Furthermore, MUAC alone also has a very strong correlation with BMI (r = 0,913 for males and r = 0,877 for females). Prediction models formed from either MUAC/√UL or MUAC alone both produce highly accurate predictions of BMI. However, measuring MUAC/√UL is considered inconvenient, which may cause difficulties when applied on the field. Conclusion: The prediction model considered most ideal to estimate BMI is: Male BMI (kg/m²) = 1.109(MUAC (cm)) – 9.202 and Female BMI (kg/m²) = 0.236 + 0.825(MUAC (cm)), based on its high accuracy levels and the convenience of measuring MUAC on the field.

Keywords: body mass index, mid-upper arm circumference, prediction model, ulna length

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Authors: Ansoné Human, Nantes Kirsten, Tanja Verster, Willem D. Schutte

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Every year the telecommunications industry suffers huge losses due to fraud. Mobile fraud, or generally, telecommunications fraud is the utilisation of telecommunication products or services to acquire money illegally from or failing to pay a telecommunication company. A South African telecommunication operator developed two internal fraud scorecards to mitigate future risks of application fraud events. The scorecards aim to predict the likelihood of an application being fraudulent and surprise fraudsters before they surprise the telecommunication operator by identifying fraud at the time of application. The scorecards are utilised in the vetting process to evaluate the applicant in terms of the fraud risk the applicant would present to the telecommunication operator. Telecommunication providers can utilise these scorecards to profile customers, as well as isolate fraudulent and/or high-risk applicants. We provide the complete methodology utilised in the development of the scorecards. Furthermore, a Determination and Discrimination (DD) ratio is provided in the methodology to select the most influential variables from a group of related variables. Throughout the development of these scorecards, the following was revealed regarding fraudulent cases and fraudster behaviour within the telecommunications industry: Fraudsters typically target high-value handsets. Furthermore, debit order dates scheduled for the end of the month have the highest fraud probability. The fraudsters target specific stores. Applicants who acquire an expensive package and receive a medium-income, as well as applicants who obtain an expensive package and receive a high income, have higher fraud percentages. If one month prior to application, the status of an account is already in arrears (two months or more), the applicant has a high probability of fraud. The applicants with the highest average spend on calls have a higher probability of fraud. If the amount collected changes from month to month, the likelihood of fraud is higher. Lastly, young and middle-aged applicants have an increased probability of being targeted by fraudsters than other ages.

Keywords: application fraud scorecard, predictive modeling, regression, telecommunications

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Authors: Oliver Ikechukwu Inyiama, Boniface Uche Ugwuanyi

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The aim of the research is to evaluate the key financial performance indicators that help both managers and their shareholders of Nigerian Banks to determine the appropriate dividend payout to their ordinary shareholders in an accounting year. Profitability, total asset, and earnings of commercial banks were selected as key performance indicators in Nigeria Banking Sector. They represent the independent variables of the study while dividend per share is the proxy for the dividend paid on ordinary shares which represent the dependent variable. The effect of profitability, total asset and earnings on dividend per share were evaluated through the ordinary least square method of multiple regression analysis. Test for normality of frequency distribution was conducted through descriptive statistics such as Jacque Bera Statistic, skewness and kurtosis. Rate of dividend payout was subsequently applied as an alternate dependent variable to test for robustness of the earlier results. The 64% adjusted R-squared of the pooled data indicates that profitability, total asset, and earnings explain the variation in dividend per share during the period under research while the remaining 36% variation in dividend per share could be explained by changes in other variables not captured by this study as well as the error term. The study concentrated on four leading Nigeria Commercial Banks namely; First Bank of Nigeria Plc, GTBank Plc, United Bank for Africa Plc and Zenith International Bank Plc. Dividend per share was found to be positively affected by total assets and earnings of the commercial banks. However, profitability which was proxied by profit after tax had a negative effect on dividend per share. The implication of the findings is that commercial banks in Nigeria pay more dividend when they are having a dwindling fortune in order to retain the confidence of the shareholders provided their gross earnings and size is on the increase. Therefore, the management and board of directors of Nigeria commercial banks should apply decent marketing strategies to enhance earnings through investment in profitable ventures for an improved dividend payout rate.

Keywords: assets, banks, indicators, performance, profitability, shares

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Authors: Jeroen De Ceuster

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This study is the first empirical analysis of the link between corporate governance and European Union competition law. Although competition law enforcement is often studied through the lens of competition law, we offer an alternative perspective by looking at a number of corporate governance factor at the level of the board of directors. We find that undertakings where the Chief Executive Officer is also chairman of the board are twice as likely to violate European Union competition law. No significant relationship was found between European Union competition law infringements and gender diversity of the board, the size of the board, the percentage of directors appointed after the Chief Executive Officer, the percentage of independent directors, or the presence of corporate social responsibility (CSR) committee. This contribution is based on a 1-1 matched peer study. Our sample includes all ultimate parent companies with a board that have been sanctioned by the European Commission for either anticompetitive agreements or abuse of dominance for the period from 2004 to 2018. These companies were matched to a company with headquarters in the same country, belongs to the same industry group, is active in the European Economic Area, and is the nearest neighbor to the infringing company in terms of revenue. Our final sample includes 121 pairs. As is common with matched peer studies, we use CLR to analyze the differences within these pairs. The only statistically significant independent variable after controlling for size and performance is CEO/Chair duality. The results indicate that companies whose Chief Executive Officer also functions as chairman of the board are twice as likely to infringe European Union competition law. This is in line with the monitoring theory of the board of directors, which states that its primary function is to monitor top management. Since competition law infringements are mostly organized by management and hidden from board directors, the results suggest that a Chief Executive Officer who is also chairman is more likely to be either complicit in the infringement or less critical towards his day-to-day colleagues and thus impedes proper detection by the board of competition law infringements.

Keywords: corporate governance, competition law, board of directors, board independence, ender diversity, corporate social responisbility

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Authors: Kimberly Samaha

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The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding biomass as a feedstock for power plants. Yet the lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. This study analyzed data and submittals to the Born Global Maine Innovation Challenge. The Innovation Challenge was a global innovation challenge to identify process innovations that could address a ‘whole-tree’ approach of maximizing the products, byproducts, energy value and process slip-streams into a circular zero-waste design. Participating companies were at various stages of developing bioproducts and included biofuels, lignin-based products, carbon capture platforms and biochar used as both a filtration medium and as a soil amendment product. This case study shows the QCA (Qualitative Comparative Analysis) methodology of the prequalification process and the resulting techno-economic model that was developed for the maximizing profitability of the Bio-Hub Ecosystem through continuous expansion of system waste streams into valuable process inputs for co-hosts. A full site plan for the integration of co-hosts (biorefinery, land-based shrimp and salmon aquaculture farms, a tomato green-house and a hops farm) at an operating forestry-based biomass to energy plant in West Enfield, Maine USA. This model and process for evaluating the profitability not only proposes models for integration of forestry, aquaculture and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. In this particular study, profitability is assessed at two levels CAPEX (Capital Expenditures) and in OPEX (Operating Expenditures). Given that these projects start with repurposing facilities where the industrial level infrastructure is already built, permitted and interconnected to the grid, the addition of co-hosts first realizes a dramatic reduction in permitting, development times and costs. In addition, using the biomass energy plant’s waste streams such as heat, hot water, CO₂ and fly ash as valuable inputs to their operations and a significant decrease in the OPEX costs, increasing overall profitability to each of the co-hosts bottom line. This case study utilizes a proprietary techno-economic model to demonstrate how utilizing waste streams of a biomass energy plant and/or biorefinery, results in significant reduction in OPEX for both the biomass plants and the agriculture and aquaculture co-hosts. Economically viable Bio-Hubs with favorable environmental and community impacts may prove critical in garnering local and federal government support for pilot programs and more wide-scale adoption, especially for those living in severely economically depressed rural areas where aging industrial sites have been shuttered and local economies devastated.

Keywords: bio-economy, biomass energy, financing, zero-waste

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Authors: Showkat Ahmad Bhat, M. S. Bhatt

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The study evaluates the ex-post impact of institutional credit on agricultural output. It first examines the key factors that influence the accessibility of institutional credit by farm households. For quantitative analysis both program participant and non-participant respondents were drawn and cross-sectional survey data were collected from 412 households in Pulwama District of Jammu & Kashmir (India). Propensity Score Matching Method was employed to analyze the impact of the institutional credit on agricultural output. Results show that institutional credit has a positive and significant impact on the agricultural output measured in terms of farm income and crop productivity. To estimate the accessibility of credit, an examination of both demand side and supply side factors were carried out. The demand for credit was measured with respect to respondents who applied for credit. Supply side credit allocation measured in terms of the proportion of ‘credit amount’ farmers obtained. Logit and Two-limit Tobit Regression Models were used to investigate the determinants that influence the accessibility of formal credit for Demand for and supply of credit respectively. The estimated results suggested that the demand for credit is positively and significantly affected by the factors such as: age of the household head, formal education, membership, cash crop grown, farm size and saving account. All the variables were found significantly increasing the household’s likelihood to demand for and supply of credit from banks. However, the impact of these factors varies considerably across the credit markets. Factors which were found negatively and significantly influencing the accessibility of credit were: ‘square of the age’, household assets and rate of interest. The credit constraints analysis suggested that square of the age; household assets and rate of interest were the three most important factors that increased the probability of being constrained. The study finally discusses these results in detail and draws some recommendations.

Keywords: institutional credit, agriculture, propensity score matching logit model, Tobit model

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Authors: Zintle Sikhunyana

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Management of public finance in many countries such as South Africa is affected by political decisions and by policies around fiscal decentralization amongst the government spheres. Economic success is said to be determined by efficient management of public finance and by the policies or strategies that are implemented to support efficient public finance management. Policymakers focus on pay attention to how economic policies have been implemented and how they are directed into ensuring stable development. This will allow policymakers to address economic challenges through the usage of fiscal policy parameters that are linked to the achieved rate of economic growth and development. Efficient public finance management reduces the likelihood of corruption and corruption is said to have negative effects on economic growth and development. Corruption in public finance refers to an act of using funds for personal benefits. To achieve macroeconomic objectives, governments make use of government expenditure and government expenditure is financed through tax revenue. The main aim of this paper is to investigate the potential impact of public finance management on economic growth and development in South Africa. The secondary data obtained from the South African Reserve Bank (SARB) and World Bank for 1980- 2020 has been utilized to achieve the research objectives. To test the impact of public finance management on economic growth and development, the study will use Seeming Unrelated Regression Equation (SURE) Modelling that allows researchers to model multiple equations with interdependent variables. The advantages of using SUR are that it efficiently allows estimation of relationships between variables by combining information on different equations and SUR test restrictions that involve parameters in different equations. The findings have shown that there is a positive relationship between efficient public finance management and economic growth/development. The findings also show that efficient public finance management has an indirect positive impact on economic growth and development. Corruption has a negative impact on economic growth and development. It results in an efficient allocation of government resources and thereby improves economic growth and development. The study recommends that governments who aim to stimulate economic growth and development should target and strengthen public finance management policies or strategies.

Keywords: corruption, economic growth, economic development, public finance management, fiscal decentralization

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Authors: Akiko Kondo

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Although the effects of working memory capacity on second/foreign language speaking skills have been researched in depth, few studies have focused on Japanese English as a foreign language (EFL) learners as compared to other languages (Indo-European languages), and the sample sizes of the relevant Japanese studies have been relatively small. Furthermore, comparing the effects of working memory capacity and motivation which is another kind of frequently researched individual factor on L2 speaking skills would add to the scholarly literature in the field of second language acquisition research. Therefore, the purposes of this study were to investigate whether working memory capacity and motivation have significant relationships with Japanese EFL learners’ speaking skills and to investigate the degree to which working memory capacity and motivation contribute to their English speaking skills. One-hundred and ten Japanese EFL students aged 18 to 26 years participated in this study. All of them are native Japanese speakers and have learned English as s foreign language for 6 to 15. They completed the Versant English speaking test, which has been widely used to measure non-native speakers’ English speaking skills, two types of working memory tests (the L1-based backward digit span test and the L1-based listening span test), and the language learning motivation survey. The researcher designed the working memory tests and the motivation survey. To investigate the relationship between the variables (English speaking skills, working memory capacity, and language learning motivation), a correlation analysis was conducted, which showed that L2 speaking test scores were significantly related to both working memory capacity and language learning motivation, although the correlation coefficients were weak. Furthermore, a multiple regression analysis was performed, with L2 speaking skills as the dependent variable and working memory capacity and language learning motivation as the independent variables. The results showed that working memory capacity and motivation significantly explained the variance in L2 speaking skills and that the L2 motivation had slightly larger effects on the L2 speaking skills than the working memory capacity. Although this study includes several limitations, the results could contribute to the generalization of the effects of individual differences, such as working memory and motivation on L2 learning, in the literature.

Keywords: individual differences, motivation, speaking skills, working memory

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Authors: Ilse Gonzalez-Rivera, Rolando Diaz-Loving

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Family, and parents in particular, are the main agents of socialization of children since they transmit values, beliefs, and cultural norms based on their own guidelines, so that children acquire the knowledge on how to interact with others in terms of the interaction with their parents. One way to measure socialization parenting is through parenting styles. Parenting styles are the set of parental behaviors that have a direct effect on the development of specific behaviors of children. The ideal parenting style depends on the cultural characteristics where people develop. In Mexico, the hierarchical structure of the family is built on a model in which men are dominant over women and their power is legitimized. This research explores the effect of parenting styles and the culture of the ambivalent sexism in the Mexican population. 150 men and 150 women participated. The instrument of individualism-collectivism was used to measure culture; participants also answered the instrument of ambivalent sexism and the parenting styles questionnaire. Regression analyses were done using sexism as the dependent variable and individualism-collectivism and parenting styles as independent variables. In addition, an analysis of variance between parental styles and gender of the participants was performed. The results indicate that the permissive style and authoritarian style are predictors of ambivalent sexism and higher levels of collectivism predict higher levels of sexism in both men and women. It is also found that parents tend to use authoritarian parenting style with women and permissive style with males. These results confirm the findings of other studies that indicate that parenting is an important variable that influences the interaction of adults. On the other hand, the effect of collectivism on sexism may be related to the fact that gender Mexican rules are rigid and for people with higher levels of collectivism, the social rules are more important than individual interests. In conclusion, these results indicate that both culture and parenting styles contribute to the maintenance of the status quo and prejudice towards women. Therefore, it is necessary to create proposals that break with this cultural paradigm and to further develop democratic styles of parenting with the aim of reducing prejudice and the legitimization of gender roles.

Keywords: culture, gender, parenting style, sexism

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Authors: Rita Alfattal, Maryam Alfarhan, Adeeb M. Algaith, Buthaina Albash, Reem M. Elshafie, Asma Alshammari, Ahmad Alahmad, Fatima Dashti, Rasha Alsafi, Hind Alsharhan

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Defects of respiratory chain complex III (CIII) result in characteristic but rare mitochondrial disorders associated with distinct neuroradiological findings. The underlying molecular defects affecting mitochondrial CIII assembly factors are few and yet to be identified. LYRM7 assembly factor is required for proper CIII assembly where it acts as a chaperone for the Rieske iron‐sulfur (UQCRFS1) protein in the mitochondrial matrix and stabilizing it. We present here the seventeenth individual with LYRM7-associated mitochondrial leukoencephalopathy harboring a previously reported rare pathogenic homozygous LYRM 7 variant, c.2T>C, (p.Met1?). Like previously reported individuals, our 4-year-old male proband presented with recurrent metabolic and lactic acidosis, encephalopathy, and myopathy. Further, he has additional, previously unreported features, including an acute stroke like episode with bilateral central blindness and optic neuropathy, recurrent hyperglycemia and hypertension associated with metabolic crisis. However, he has no signs of psychomotor regression. He has been stable clinically with residual left-sided reduced visual acuity and amblyopia, and no more metabolic crises for 2-year-period while on the mitochondrial cocktail. Although the reported brain MRI findings in other affected individuals are homogenous, it is slightly different in our index, revealing evidence of bilateral almost symmetric multifocal periventricular T2 hyperintensities with hyperintensities of the optic nerves, optic chiasm, and corona radiata but with no cavitation or cystic changes. This report describes new clinical and radiological findings of LYRM7-associated disease. The report also summarizes the clinical and molecular data of previously reported individuals describing the full phenotypic spectrum.

Keywords: LYRM7 gene defect, mitochondrial disease, , lactic acidosis, , genetic disorder

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