Search results for: binary logistic regression

Authors: Jay Martin L. Dionaldo

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This study aimed to develop a causal model on the performance of the basic education teachers in the Division of Malaybalay City for the school year 2018-2019. This study used the responses of 300 randomly selected basic education teachers of Malaybalay City, Bukidnon. They responded to the three sets of questionnaires patterned from the National Education Association (2018) on instructional leadership of teachers, the questionnaire of Caluza et al., (2017) for information and communications technology competencies and the questionnaire on the teachers’ performance using the Individual Performance Commitment and Review Form (IPCRF) adopted by the Department of Education (DepEd). Descriptive statistics such as mean for the description, correlation for a relationship, regression for the extent influence, and path analysis for the model that best fits teachers’ performance were used. Result showed that basic education teachers have a very satisfactory level of performance. Also, the teachers highly practice instructional leadership practices in terms of coaching and mentoring, facilitating collaborative relationships, and community awareness and engagement. On the other hand, they are proficient users of ICT in terms of technology operations and concepts and basic users in terms of their pedagogical indicators. Furthermore, instructional leadership, coaching and mentoring, facilitating collaborative relationships and community awareness and engagement and information and communications technology competencies; technology operations and concept and pedagogy were significantly correlated toward teachers’ performance. Coaching and mentoring, community awareness and engagement, and technology operations and concept were the best predictors of teachers’ performance. The model that best fit teachers’ performance is anchored on coaching and mentoring of the teachers, embedded with facilitating collaborative relationships, community awareness, and engagement, technology operations, and concepts, and pedagogy.

Keywords: information and communications technology, instructional leadership, coaching and mentoring, collaborative relationship

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Authors: Ange Meghane Hakizimana, Landry Ndikuriyo

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Retention of employees in the hospitality industry is a recurrent agenda in the organization involving all the combined efforts to maintain the best available laborer. The general objective of this research is to assess the impact of effective employee retention strategies on the success of the hotel industry at Galileo Hotel, Huye District in Rwanda, for the period of 2019-2021. Herzberg Two Factor Theory and Equity Theory were used. The study adopted a descriptive research design. Descriptive research design allowed us to study the elements in their natural form without making any alterations to them. Secondary data and primary data and the data collected were sorted and entered into the statistical packages for social sciences for analysis (SPSS) version 26. Frequencies, descriptive statistics and percentages were used to analyze and establish extent to which employee retention strategies impact the success of the hotel industry of Rwanda and this was analyzed using regression and correlation analysis. The results revealed that employee training and development had an influence of 24.8% on the success of the hotel industry in Rwanda. According to the results of our study, the employee reward system contributes 20.7% to the success of the hotel industry in Rwanda, the value of t is 3.475 and this is greater than the standard t value score of 1.96, p-value is 0.002. Therefore the employee reward system has a great positive impact on the success of the hotel industry in Rwanda. The results also show that 15.7% of the success of the hospitality industry in Rwanda is due to the work environment of employees. With a t-value of 4.384 and a p-value of 0.000, the above statistics show a positive impact of the employees' working environment on success of the hospitality industry in Rwanda. A priority to the retention of their employees should be given by the hotel industry and its managers because it has already been proven that it is an effective approach to offering good customer service. In addition, employee retention reduces expenses associated with employee recruitment and turnover.

Keywords: success, hotel industry, training and development, employee reward system, employee work environment

Procedia PDF Downloads 77

Authors: F. Lazzeri, I. Reiter

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Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

Procedia PDF Downloads 281

Authors: Osamah S. Alanazi, Mohammad G. Kotbi, Mohammed O. AlFadil

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While renewable energy technology is developing in Saudi Arabia, and the ambitious 2030 vision encourages the shift towards more efficient and clean energy usage. The research on the application of geothermal resources in residential use for the Saudi Arabian context will contribute towards a more sustainable environment. This paper is a part of an ongoing master's thesis, which its main goal is to investigate the possibility of achieving a zero-carbon house in Riyadh by applying a ground-coupled system into a current sustainable house that uses a grid-tied solar system. The current house was built and designed by King Saud University for the 2018 middle east solar decathlon competition. However, it failed to reach zero-carbon operation due to the high cooling demand. This study will redesign and validate the house using Revit and Carriers Hourly Analysis 'HAP' software with the use of ordinary least square 'OLS' regression. After that, a ground source ventilation system will be designed using the 'GCV Tool' to reduce cooling loads. After the application of the ground source system, the new electrical loads will be compared with the current house. Finally, a simple economic analysis that includes the cost of applying a ground source system will be reported. The findings of this study will indicate the possibility and feasibility of reaching a zero-carbon house in Riyadh, Saudi Arabia, using a ground-coupled ventilation system. While cooling in the residential sector is the dominant energy consumer in the Gulf region, this work will certainly help in moving towards using renewable sources to meet those demands. This paper will be limited to highlight the literature review, the methodology of the research, and the expected outcome.

Keywords: renewable energy, zero-carbon houses, sustainable buildings, geothermal energy, solar PV, GCV Tool

Procedia PDF Downloads 160

Authors: Usha Barahmand, Ruhollah Heydari Sheikh Ahmad, Sara Alaie Khoraem

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Introduction: The association of epilepsy with several psychological disorders and reduced quality of life has long been recognized. The present study aimed at comparing the personality profiles, quality of life and symptomatology of anxiety and depression in patients with epilepsy and healthy controls. Materials and Methods: Forty seven patients (29 men and 18 women) with diagnosed epilepsy participated in this study. Forty seven healthy controls who matched the patients in age and gender were also recruited. The participants’ personality and psychological profiles were assessed using the Depression, Anxiety, and Stress Scale (DASS-21), the Short-Form Health Survey (SF-36) and the HEXACO Personality Inventory (HEXACO-PI). Scoring algorithms were applied to the SF-36 produce the physical and mental component scores (PCS and MCS). Results: There were statistically significant differences in the total SF-36 score, anxiety, depression and stress scores of the DASS-21 between patients and controls. Anxiety, stress and depression scores significantly correlated inversely with the PCS and MCS. Data analysis showed that females had higher depression scores than males in both patients and controls, while males in both groups scored higher on stress. Patients’ personality scores were also different from those reported by controls on emotional, agreeableness and extroversion. Patients scored higher on emotionality, and lower on agreeableness and extraversion. Patients also scored lower on indices of quality of life. Regression analysis revealed that emotionality, anxiety, stress and MCS accounted for a significant proportion of the variance in severity of epileptic seizures. Conclusion: Stressful situations and psychological conditions as well as the personality trait of neuroticism were related to the occurrence of recurrent epileptic seizures.

Keywords: anxiety, depression, epilepsy, neuroticism, personality, quality of life, stress

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Authors: Sony Subedi, Colleen Davison, Susan Bartels

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Objective: The aim of this study is to i) investigate the socio-demographics and living conditions of households in Haiti pre- and post 2010 earthquake, ii) determine the household prevalence of emotional and physical abuse in children (aged 2-14) after the earthquake, and iii) explore the association between earthquake-related loss and experience of emotional and physical child abuse in the household while considering potential confounding variables and the interactive effects of a number of social, economic, and demographic factors. Methods: A nationally representative sample of Haitian households from the 2005/6 and 2012 phases of the Demographic and Health Surveys (DHS) was used. Descriptive analysis was summarized using frequencies and measures of central tendency. Chi-squared and independent t-tests were used to compare data that was available pre-earthquake and post-earthquake. The association between experiences of earthquake-related loss and emotional and physical child abuse was assessed using log-binomial regression models. Results: Comparing pre-post-earthquake, noteworthy improvements were observed in the educational attainment of the household head (9.1% decrease in “no education” category) and in possession of the following household items: electricity, television, mobile-phone, and radio post-earthquake. Approximately 77.0% of children aged 2-14 experienced at least one form of physical abuse and 78.5% of children experienced at least one form of emotional abuse one month prior to the 2012 survey period. Analysis regarding the third objective (association between experiences of earthquake-related loss and emotional and physical child abuse) is in progress. Conclusions: The extremely high prevalence of emotional and physical child abuse in Haiti indicates an immediate need for improvements in the enforcement of existing policies and interventions aimed at decreasing child abuse in the household.

Keywords: Haiti earthquake, physical abuse, emotional abuse, natural disasters, children

Procedia PDF Downloads 163

Authors: Paola Montenegro, Maria de los Angeles Balaguera Villa

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In February 2022 Colombia achieved a historic milestone in ensuring universal access to abortion rights with ruling C-055 of 2022 decriminalising abortion up to 24 weeks of gestation. In the context of this triumph and the expansion of telemedicine services in the wake of the COVID-19 pandemic, this research studied the acceptability of self-care abortion in young people (13 - 28 years) through a telemedicine service and also explored the primary needs that should be the focus of such care. The results shine light on a more comprehensive understanding of opportunities and challenges of teleabortion practices in a context that combines overall higher access to technology and low access to reliable information of safe abortion, stigma, and scarcity especially felt by transnational migrants, racialised people, trans men and non-binary people. Through a mixed methods approach, this study collected 5.736 responses to a virtual survey disseminated nationwide in Colombia and 47 in-person interviews (24 of them with people who were assigned female at birth and 21 with local key stakeholders in the abortion ecosystem). Quantitative data was analyzed using Stata SE Version 16.0 and qualitative analysis was completed through NVivo using thematic analysis. Key findings of the research suggest that self-care abortion is practice with growing acceptability among young people, but important adjustments must be made to meet quality of care expectations of users. Elements like quick responses from providers, lower costs, and accessible information were defined by users as decisive factors to choose over the abortion service provider. In general, the narratives in participants about quality care were centred on the promotion of autonomy and the provision of accompaniment and care practices, also perceived as transformative and currently absent of most health care services. The most staggering findings from the investigation are related to current barriers faced by young people in abortion contexts even when the legal barriers have: high rates of scepticism and distrust associated with pitfalls of telehealth and structural challenges associated with lacking communications infrastructure, among a few of them. Other important barriers to safe self-care abortion identified by participants surfaced like lack of privacy and confidentiality (especially in rural areas of the country), difficulties accessing reliable information, high costs of procedures and expenses related to travel costs or having to cease economic activities, waiting times, and stigma are among the primary barriers to abortion identified by participants. Especially in a scenario marked by unprecedented social, political and economic disruptions due to the COVID-19 pandemic, the commitment to design better care services that can be adapted to the identities, experiences, social contexts and possibilities of the user population is more necessary than ever. In this sense, the possibility of expanding access to services through telemedicine brings us closer to the opportunity to rethink the role of health care models in transforming the role of individuals and communities to make autonomous, safe and informed decisions about their own health and well-being.

Keywords: contraception, family planning, premarital fertility, unplanned pregnancy

Procedia PDF Downloads 58

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

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The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

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Authors: Auwal Garba, Rabiu Maijama’a, Abdullahi Muhammad Jalam

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Variability in climate has affected the agricultural production all over the globe. This concern has motivated important changes in the field of research during the last decade. Climate variability is believed to have declining effects towards rice production in Nigeria. This study examined climate variability and its impact on rice productivity in Dass Local Government Area, Bauchi State, by employing Linear Trend Model (LTM), analysis of variance (ANOVA) and regression analysis. Annual seasonal data of the climatic variables for temperature (min. and max), rainfall, and solar radiation from 1990 to 2015 were used. Results confirmed that 74.4% of the total variation in rice yield in the study area was explained by the changes in the independent variables. That is to say, temperature (minimum and maximum), rainfall, and solar radiation explained rice yield with 74.4% in the study area. Rising mean maximum temperature would lead to reduction in rice production while moderate increase in mean minimum temperature would be advantageous towards rice production, and the persistent rise in the mean maximum temperature, in the long run, will have more negatively affect rice production in the future. It is, therefore, important to promote agro-meteorological advisory services, which will be useful in farm planning and yield sustainability. Closer collaboration among the meteorologist and agricultural scientist is needed to increase the awareness about the existing database, crop weather models among others, with a view to reaping the full benefits of research on specific problems and sustainable yield management and also there should be a special initiative by the ADPs (State Agricultural Development Programme) towards promoting best agricultural practices that are resilient to climate variability in rice production and yield sustainability.

Keywords: climate variability, impact, productivity, rice

Procedia PDF Downloads 87

Authors: Hyelim Park, Juan Martin Zorrilla

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Climate change influences very widely and in various ways ocean ecosystem functioning. The consequences of climate change on marine ecosystems are an increase in temperature and irregular behavior of some solute concentrations. These changes would affect fisheries catches in several ways. Our aim is to assess the quantitative contribution change of fishery catches along the time and express them through four environment variables: Sea Surface Temperature (SST4) and the concentrations of Chlorophyll (CHL), Particulate Inorganic Carbon (PIC) and Particulate Organic Carbon (POC) at two spatial scales: Global and the nineteen FAO Major Fishing Areas divisions. Data collection was based on the FAO FishStatJ 2014 database as well as MODIS Aqua satellite observations from 2002 to 2012. Some data had to be corrected and interpolated using some existing methods. As the results, a multivariable regression model for average Global fisheries captures contained temporal mean of SST4, standard deviation of SST4, standard deviation of CHL and standard deviation of PIC. Global vector auto-regressive (VAR) model showed that SST4 was a statistical cause of global fishery capture. To accommodate varying conditions in fishery condition and influence of climate change variables, a model was constructed for each FAO major fishing area. From the management perspective it should be recognized some limitations of the FAO marine areas division that opens to possibility to the discussion of the subdivision of the areas into smaller units. Furthermore, it should be treated that the contribution changes of fishery species and the possible environment factor for specific species at various scale levels.

Keywords: fisheries-catch, FAO FishStatJ, MODIS Aqua, sea surface temperature (SST), chlorophyll, particulate inorganic carbon (PIC), particulate organic carbon (POC), VAR, granger causality

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Authors: Aihong Zhao, Priya Sastry, Mark L Field, Mohamad Bashir, Arvind Singh, David Richens

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Objectives: Intramural haematoma (IMH) is one of the pathologies, along with acute aortic dissection, that present as Acute Aortic Syndrome (AAS). Evidence suggests that unlike aortic dissection, some intramural haematomas may regress with medical management. However, intramural haematomas have been traditionally managed like acute aortic dissections. Given that some of these pathologies may regress with conservative management, it would be useful to be able to identify which of these may not need high risk emergency intervention. A computational aortic model was used in this study to try and identify intramural haematomas with risk of progression to aortic dissection. Methods: We created a computational model of the aorta with luminal blood flow. Reports in the literature have identified 11 mm as the radial clot thickness that is associated with heightened risk of progression of intramural haematoma. Accordingly, haematomas of varying sizes were implanted in the modeled aortic wall to test this hypothesis. The model was exposed to physiological blood flows and the stresses and strains in each layer of the aortic wall were recorded. Results: Size and shape of clot were seen to affect the magnitude of aortic stresses. The greatest stresses and strains were recorded in the intima of the model. When the haematoma exceeded 10 mm in all dimensions, the stress on the intima reached breaking point. Conclusion: Intramural clot size appears to be a contributory factor affecting aortic wall stress. Our computer simulation corroborates clinical evidence in the literature proposing that IMH diameter greater than 11 mm may be predictive of progression. This preliminary report suggests finite element modelling of the aortic wall may be a useful process by which to examine putative variables important in predicting progression or regression of intramural haematoma.

Keywords: intramural haematoma, acute aortic syndrome, finite element analysis,

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Authors: Nathalie Bolding, Marta Montero, Joaquim Cevallos, Juan F. Martin-Lazaro

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Background: Inhaled epoprostenol (iEPO) have been shown to improve PaO2:FiO2 (PF) in combination with bronchodilators (BD). However, there is not an available device to deliver these two therapies concomitantly. We describe a new method to provide this therapy successfully. Objective: To evaluate the response to continuous nebulization of iEPO and intermittent nebulization of Salbutamol/Ipratropium bromide in adults with severe respiratory failure through a double mesh nebulisation in tandem. Methods: This observational study included two mechanical ventilated adults under hourly ventilatory, gasometrical and clinical measurements during 48h. Both had severe respiratory failure treated with continuous iEPO (50 – 200 micrograms/h) and BD (Salbutamol 2.5 mg and Ipratropium bromide 500 mcg every 6 hours) through double mesh nebulisation (Aerogen solo®) placed in tandem in the dry side of the humidificator. The primary endpoints were the variables associated with a positive response to this tandem nebulised therapy (PaFiO2 index, ROX index). Secondary endpoints were laboratory (ABG) clinical and ventilatory variables. Statistical analysis (SPSS v29) included linear regression and ANOVA. Results: The patients included (n=2) survived, both extubated, one after ECMO therapy. Severe acute respiratory failure had a positive response rate to continuous iEPO and intermittent BD: PaFiO2 increased (7.40 to 30.91; P75: 27%) as well as ROX index (2.91 to 11.43; P75: 33%). There was a linear correlation of improvement between iEPO with PaFiO2 (ANOVA, r=0.393, p<0.002) and ROX (r=0.419, p<0.001). iEPO+BD therapy did not show any complications. Conclusion: Continuous and intermittent mesh tandem nebulisation can be effectively delivered with this method with a positive effect in ventilatory parameters without observed complications. Randomised studies will be able to provide reassurance in this new therapy.

Keywords: tandem, mesh, nebulisers, pulmonary, vasoldilators, bronchodilators, respiratory, failure

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Authors: M. Naimi, M. B. Khaled

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The present study consisted of an applied test in meat system to assess the effectiveness of three bio agents bacteriocinproducing strains: Lm24: Lactobacillus sakei, Lm14and Lm25: Pediococcus spp. Two tests were carried out: The ex-situ test was intended for three batches added with crude bacteriocin solutions at 12.48 AU/ml for Lm25 and 8.4 AU/ml for Lm14 and Lm24. However, the in situ one consisted of four batches; three of them inoculated with one bacteriocinogenic Lm25, Lm14, Lm24, respectively. The fourth one was used in mixture: Lm14+m24 at approximately of 107 CFU/ml. The two used tests were done in the presence of the pathogen St. aureus ATCC 6538, as a test strain at 103 CFU/ml. Another batch served as a positive or a negative control was used too. The incubation was performed at 7°C. Total viable counts, staphylococci and lactic acid bacteria, at the beginning and at selected times with interval of three days were enumerated. Physicochemical determinations (except for in situ test): pH, dry mater, sugars, fat and total protein, at the beginning and at end of the experiment, were done, according to the international norms. Our results confirmed the ex situ effectiveness. Furthermore, the batches affected negatively the total microbial load over the incubation days, and showed a significant regression in staphylococcal load at day seven, for Lm14, Lm24, and Lm25 of 0.73, 2.11, and 2.4 log units. It should be noticed that, at the last day of culture, staphylococcal load was nil for the three batches. In the in situ test, the cultures displayed less inhibitory attitude and recorded a decrease in staphylococcal load, for Lm14, Lm24, Lm25, Lm14+m24 of 0.73, 0.20, 0.86, 0.032 log units. Therefore, physicochemical analysis for Lm14, Lm24, Lm25, Lm14+m24 showed an increase in pH from 5.50 to 5.77, 6.18, 5.96, 7.22, a decrease in dry mater from 7.30% to 7.05%, 6.87%, 6.32%, 6.00%.This result reflects the decrease in fat ranging from 1.53% to 1.49%, 1.07%, 0.99%, 0.87%; and total protein from 6.18% to 5.25%, 5.56%, 5.37%, 5.5%. This study suggests that the use of selected strains as Lm25 could lead to the best results and would help in preserving and extending the shelf life of lamb meat.

Keywords: biocontrol, in situ, ex situ, meat system, St. aureus, Lactobacillus sakei, Pediococcus spp.

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Authors: Rosana Goncalves Das Dores, Maira Fonseca, Fernando Finger, Vicente Casali

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Equisetum hyemale L. (horsetail, Equisetaceae) is a medicinal plant used and commercialized in simple paper bags or non-ecological packaging in Brazil. The aim of this work was to evaluate the relation between the bioactive compounds of horsetail stems stored in ecological packages (multi-ply paper sacks) at room temperature. Stems in primary and secondary stage were harvested from an organic estate, on December 2016, selected, measured (length from the soil to the apex (cm), stem diameter at ground level (DGL mm) and breast height (DBH mm) and cut into 10 cm. For the post-harvest evaluations, stems were stored in multi-ply paper sacks and evaluated daily to the respiratory rate, fresh weight loss, pH, presence of fungi / mold, phenolic compounds and antioxidant activity. The analyses were done with four replicates, over time (regression) and compared at 1% significance (Tukey test). The measured heights were 103.7 cm and 143.5 cm, DGL was 2.5mm and 8.4 mm and DBH of 2.59 and 6.15 mm, respectively for primary and secondary stems stage. At both stages of development, in storage in multi-ply paper sacks, the greatest mass loss occurred at 48 h, decaying up to 120 hours, stabilizing at 192 hours. The peak respiratory rate increase occurred in 24 hours, coinciding with a change in pH (temperature and mean humidity was 23.5°C and 55%). No fungi or mold were detected, however, there was loss of color of the stems. The average yields of ethanolic extracts were equivalent (approximately 30%). Phenolic compounds and antioxidant activity were higher in secondary stems stage in up to 120 hours (AATt0 = 20%, AATt30 = 45%), decreasing at the end of the experiment (240 hours). The packaging used allows the commercialization of fresh stems of Equisetum for up to five days.

Keywords: paper sacks, phenolic content, antioxidant activity, medicinal plants, post-harvest, ecological packages, Equisetum

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Authors: Chernet Mulugeta, Girma Seyoum, Yeshineh Demrew, Kehabtimer Shiferaw

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Background: Obstetric fistula (OF) is a serious medical condition that includes an abnormal opening between the vagina and bladder (vesico-vaginal fistula) or the vagina and rectum (recto-vaginal fistula). It is usually caused by prolonged obstructed labour. Despite its serious health and psychosocial consequences, there is a paucity of evidence regarding the time it takes to heal from OF. Objective: The aim of this study was to assess the time to cure from obstetric fistula and its predictors among women admitted to Addis Ababa Hamlin Fistula Hospital, Addis Ababa, Ethiopia. Methodology: An institution-based retrospective cohort study was conducted from January 2015 to December 2020 among a randomly selected 434 women with OF in Addis Ababa Hamlin Fistula Hospital. Data was collected using a structured checklist adapted from a similar study. The open data kit (ODK) collected data was exported and analyzed by using STATA (14.2). Kaplan Meir was used to compare the recovery time from OF. To identify the predictors of OF, a Cox regression model was fitted, and an adjusted hazard ratio with a 95% confidence interval was used to estimate the strength of the associations. Results: The average time to recover from obstetric fistula was 3.95 (95% CI: 3.0-4.6) weeks. About ¾ of the women [72.8% (95% CI - 0.65-1.2)] were physically cured of obstetric fistula. Having secondary education and above [AHR=3.52; 95% CI (1.98, 6.25)] compared to no formal education, having a live birth [AHR=1.64; 95% CI (1.22, 2.21)], having an intact bladder [AHR=2.47; 95% CI (1.1, 5.54)] compared to totally destructed, and having a grade 1 fistula [AHR=1.98; 95% CI (1.19, 3.31)] compared to grade 3 were the significant predictors of shorter time to cure from an obstetric fistula. Conclusion and recommendation: Overall, the proportion of women with OF who were not being cured was unacceptably high. The time it takes for them to recover from the fistula was also extended. It connotes us to work on the identified predictors to improve the time to recovery from OF.

Keywords: time to recovery, obstetric fistula, predictors, Ethiopia

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Authors: Huang Ying

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The present study was to investigate factors affecting children's improvement through the first two years of elementary school on a population-based sample of children with autism in Taiwan. All the children were diagnosed with autism spectrum disorder (ASD) by clinical psychologists according to DSM-IV. Children's development was assessed by the Vineland Adaptive Behavior Scales-Chinese version (VABS-C) on the first and the third grade. Children's improvement was measured by the difference between the standardized total score of the third and the first year. In Taiwan, school-age children with special-education needs will be arranged into different classes, including normal classes (NC), resource classes (RC), and special classes (SC) by the government. Therefore, type of class was one of the independent variables. Moreover, as early intervention is considered to be crucial, the earliest age when intervention begins was collected from parents. Attention was also included in the analysis. Teachers were asked to evaluate children's attention with a 3-item Likert Scale. The frequency of paying attention to the class or the task was recorded and scores were summed up. Additionally, standardized scores of the VABS-C in the first grade were used as pretest scores representing children's developmental level at the beginning of elementary school. Multiple regression was conducted with improvement as the dependent variable. Results showed that children in special classes had smaller improvement compared to those in normal or resource classes. Attention positively predicted improvement yet the effect of earliest intervention age was not significant. Furthermore, scores in the first grade negatively predicted improvement, which indicated that children with higher developmental levels would make less progress in the following years. Results were to some degree consistent with previous findings through meta-analysis that the effectiveness of conventional intervention methods lacked sufficient evidence to support.

Keywords: attention, early intervention, elementary school, special education in Taiwan

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Authors: John Adebayo Oloyhede

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This paper examines effect of financial liberalization on the stability of the demand for money function and its implication for exchange rate behaviour of three African countries. As the demand for money function is regarded as one of the two main building blocks of most exchange rate determination models, the other being purchasing power parity, its stability is required for the monetary models of exchange rate determination to hold. To what extent has the liberalisation policy of these countries, for instance liberalised interest rate, affected the demand for money function and what has been the consequence on the validity and relevance of floating exchange rate models? The study adopts the Autoregressive Instrumental Package (AIV) of multiple regression technique and followed the Almon Polynomial procedure with zero-end constraint. Data for the period 1986 to 2011 were drawn from three developing countries of Africa, namely: Gambia, Ghana and Nigeria, which did not only start the liberalization and floating system almost at the same period but share similar and diverse economic and financial structures. Its findings show that the demand for money was a stable function of income and interest rate at home and abroad. Other factors such as exchange rate and foreign interest rate exerted some significant effect on domestic money demand. The short-run and long-run elasticity with respect to income, interest rates, expected inflation rate and exchange rate expectation are not greater than zero. This evidence conforms to some extent to the expected behaviour of the domestic money function and underscores its ability to serve as good building block or assumption of the monetary model of exchange rate determination. This will, therefore, assist appropriate monetary authorities in the design and implementation of further financial liberalization policy packages in developing countries.

Keywords: financial liberalisation, exchange rates, demand for money, developing economies

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Authors: Vaishali Joshi, Pallav Joshi

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The main objective of this study is to examine the fashion consumption behavior of females with respect to their age group. Differences were studied in the pre-purchase, purchase and post-purchase behavior of females belonging to three age cohorts such as Generation X, Generation Y, and Generation Z. Quantitative approach was used to conduct this research. Data was collected through structured questionnaire. The questionnaire consisted of three sections. Section one included a question of the source of information of purchasing fashion apparels which measure the pre-purchase behavior. Section two measures purchase behavior which included two questions: i. motivations for purchasing fashion apparel and ii. important attributes considered for purchasing fashion apparel. The last section included a question regarding disposal of fashion apparel which measures the post-purchase behavior. Hundred females were selected as the respondents for this study through convenience sampling in the fashion streets. They were categorized into three age groups and then the results were analyzed. Four hypotheses were developed after reviewing the existing literature. Regression analysis was conducted for testing the hypothesis. Hypothesis one was accepted which stated that ‘social influence’ as a source of information for purchasing fashion apparels decreases with age. Hypothesis two was accepted which suggested that motivation of ‘Attention seeking’ for purchasing fashion apparel decreases with age. Hypothesis three and four also accepted which suggested that the importance of ‘Quality’ and ‘Price’ increases with age but hypothesis five was rejected which suggested that the importance of ‘Fit’ increases with age and last but not the least hypothesis six was accepted which suggested that the ‘duration’ of using fashion apparel increases with age. Limitation of the study deals with the sample of only female respondents. Implication can be made from this research in the field of Fashion apparel industry with respect to consumer segmentation and better marketing approaches can be implemented by the marketers form this study. Further research can be concluded by including male respondents also.

Keywords: fashion, consumption behavior, age cohorts, motivation

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Authors: Michael Luc Andre, Célia Maintenant

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Theory of mind is a milestone in child development which allows children to understand that others could have different mental states than theirs. Understanding the developmental stages of theory of mind in children leaded researchers on two Connected research problems. In one hand, the link between executive function and theory of mind, and on the other hand, the relationship of theory of mind and syntax processing. These two lines of research involved a great literature, full of important results, despite certain level of disagreement between researchers. For a long time, these two research perspectives continue to grow up separately despite research conclusion suggesting that the three variables should implicate same developmental period. Indeed, our goal was to study the relation between theory of mind, executive function, and language via a unique research question. It supposed that between executive function and language, one of the two variables could play a critical role in the relationship between theory of mind and the other variable. Thus, 112 children aged between three and six years old were recruited for completing a receptive and an expressive vocabulary task, a syntax understanding task, a theory of mind task, and three executive function tasks (inhibition, cognitive flexibility and working memory). The results showed significant correlations between performance on theory of mind task and performance on executive function domain tasks, except for cognitive flexibility task. We also found significant correlations between success on theory of mind task and performance in all language tasks. Multiple regression analysis justified only syntax and general abilities of language as possible predictors of theory of mind performance in our preschool age children sample. The results were discussed in the perspective of a great role of language abilities in theory of mind development. We also discussed possible reasons that could explain the non-significance of executive domains in predicting theory of mind performance, and the meaning of our results for the literature.

Keywords: child development, executive function, general language, syntax, theory of mind

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Oyetunji John Adenuga

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This study on the comparative analysis of the performance of teachers in private and public schools was carried out in Ibadan North West Local Government Area of Oyo State. This study examined the justification for the claim that there is difference in the performance of teachers in private and public primary schools and at the same time identified factors responsible for the difference in the performance of these teachers. A descriptive survey research design was used for the study. Data generated were analysed using t-test and regression analysis. The findings of the study revealed that there is significant difference in the performance of teachers in private and private primary schools in Ibadan North West Local Government Area of Oyo State (t=64.09; df=459; p,.05). The findings also revealed that the method of teaching in private primary schools is significantly different from the method of teaching in public primary schools in Ibadan North West Local Government Area of Oyo State (t=73.08; df=459; p,.05). Findings revealed that school leadership and management have significant contribution on the performance of private and public primary school teachers in Ibadan North West Local Area of Oyo State. Based on the finding, the following recommendations were made: Primary school teachers need to be motivated and rewarded for excellent performance. Primary schools should be properly equipped with teaching-aid facilities, laboratories and libraries. Government should use the findings of this study to improve on teaching materials provided to the primary school teachers in Nigeria. Public primary schools should be designed by education planners, administrators and government. Headmasters, proprietors and teachers of primary schools should look inward and give a performance appraisal and evaluation of themselves form time to time based on subject they taught. Finally, school administrators should be conscious of the way they manage the teachers in schools not only in informal situations but also in formal settings.

Keywords: private education, public education, school leadership, school management, teachers performance

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: Hui-Chi Huang, Su-Ju Yang, Ching-Wei Lin, Jui-Yao Tsai, Liang-Yiang

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Background: The most common serious complication following acute stroke is pneumonia. It has been associated with the increased morbidity, mortality, and medical cost after acute stroke in elderly patients. Purpose: The aim of this retrospective study was to investigate the relationship between stroke patients, risk factors of pneumonia, and one-year survival rates in a group of patients, in a tertiary referal center in Northern Taiwan. Methods: From January 2012 to December 2013, a total of 1730 consecutively administered stroke patients were recruited. The Survival analysis and multivariate regression analyses were used to examine the predictors for the one-year survival in stroke patients of a stroke registry database from northern Taiwan. Results: The risk of stroke mortality increased with age≧ 75 (OR=2.305, p < .0001), cancer (OR=3.221, p=<.0001), stayed in intensive care unit (ICU) (OR=2.28, p <.0006), dysphagia (OR=5.026, p<.0001), without speech therapy(OR=0.192, p < .0001),serum albumin < 2.5(OR=0.322, p=.0053) , eGFR > 60(OR=0.438, p <. 0001), admission NIHSS >11(OR=1.631, p=.0196), length of hospitalization (d) > 30(OR=0.608, p=.0227), and stroke subtype (OR=0.506, p=.0032). After adjustment of confounders, pneumonia was not significantly associated with the risk of mortality. However, it is most likely to develop in patients who are age ≧ 75, dyslipidemia , coronary artery disease , albumin < 2.5 , eGFR <60 , ventilator use , stay in ICU , dysphagia, without speech therapy , urinary tract infection , Atrial fibrillation , Admission NIHSS > 11, length of hospitalization > 30(d) , stroke severity (mRS=3-5) ,stroke Conclusion: In this study, different from previous research findings, we found that elderly age, severe neurological deficit and rehabilitation therapy were significantly associated with Post-stroke Pneumonia. However, specific preventive strategies are needed to target the high risk groups to improve their long-term outcomes after acute stroke. These findings could open new avenues in the management of stroke patients.

Keywords: stroke, risk, pneumonia, survival

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Authors: Mukisa Simon Peter Turker, Etomaru Irene

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This study examined factors determining the success of University-Industry Collaboration (UIC) in the science academic units (SAUs) at Makerere University. This was prompted by concerns about weak linkages between industry and the academic units at Makerere University. The study examined institutional, relational, output, and framework factors determining the success of UIC in the science academic units at Makerere University. The study adopted a predictive cross-sectional survey design. Data was collected using a questionnaire survey from 172 academic staff from the six SAUs at Makerere University. Stratified, proportionate, and simple random sampling techniques were used to select the samples. The study used descriptive statistics and linear multiple regression analysis to analyze data. The study findings reveal a coefficient of determination (R-square) of 0.403 at a significance level of 0.000, suggesting that UIC success was 40.3% at a standardized error of estimate of 0.60188. The strength of association between Institutional factors, Relational factors, Output factors, and Framework factors, taking into consideration all interactions among the study variables, was at 64% (R= 0.635). Institutional, Relational, Output and Framework factors accounted for 34% of the variance in the level of UIC success (adjusted R2 = 0.338). The remaining variance of 66% is explained by factors other than Institutional, Relational, Output, and Framework factors. The standardized coefficient statistics revealed that Relational factors (β = 0.454, t = 5.247, p = 0.000) and Framework factors (β = 0.311, t = 3.770, p = 0.000) are the only statistically significant determinants of the success of UIC in the SAU in Makerere University. Output factors (β = 0.082, t =1.096, p = 0.275) and Institutional factors β = 0.023, t = 0.292, p = 0.771) turned out to be statistically insignificant determinants of the success of UIC in the science academic units at Makerere University. The study concludes that Relational Factors and Framework Factors positively and significantly determine the success of UIC, but output factors and institutional factors are not statistically significant determinants of UIC in the SAUs at Makerere University. The study recommends strategies to consolidate Relational and Framework Factors to enhance UIC at Makerere University and further research on the effects of Institutional and Output factors on the success of UIC in universities.

Keywords: university-industry collaboration, output factors, relational factors, framework factors, institutional factors

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Authors: I GD Yudha Partama, A. Kanno, Y. Akamatsu, R. Inui, M. Goto, M. Sekine

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The aerial photogrammetry of shallow water bottoms has the potential to be an efficient high-resolution survey technique for shallow water topography, thanks to the advent of convenient UAV and automatic image processing techniques Structure-from-Motion (SfM) and Multi-View Stereo (MVS)). However, it suffers from the systematic overestimation of the bottom elevation, due to the light refraction at the air-water interface. In this study, we present an empirical method to correct for the effect of refraction after the usual SfM-MVS processing, using common software. The presented method utilizes the empirical relation between the measured true depth and the estimated apparent depth to generate an empirical correction factor. Furthermore, this correction factor was utilized to convert the apparent water depth into a refraction-corrected (real-scale) water depth. To examine its effectiveness, we applied the method to two river sites, and compared the RMS errors in the corrected bottom elevations with those obtained by three existing methods. The result shows that the presented method is more effective than the two existing methods: The method without applying correction factor and the method utilizes the refractive index of water (1.34) as correction factor. In comparison with the remaining existing method, which used the additive terms (offset) after calculating correction factor, the presented method performs well in Site 2 and worse in Site 1. However, we found this linear regression method to be unstable when the training data used for calibration are limited. It also suffers from a large negative bias in the correction factor when the apparent water depth estimated is affected by noise, according to our numerical experiment. Overall, the good accuracy of refraction correction method depends on various factors such as the locations, image acquisition, and GPS measurement conditions. The most effective method can be selected by using statistical selection (e.g. leave-one-out cross validation).

Keywords: bottom elevation, MVS, river, SfM

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Authors: Yongjiang Zhang, Kallol Barai, Umesh R. Hodeghatta, Trang Tran, Vikas Dhiman

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Detecting water stress on crops early and accurately is crucial to minimize its impact. This study aims to measure water stress in wild blueberry crops non-destructively by analyzing proximal hyperspectral data. The data collection took place in the summer growing season of 2022. A drought experiment was conducted on wild blueberries in the randomized block design in the greenhouse, incorporating various genotypes and irrigation treatments. Hyperspectral data ( spectral range: 400-1000 nm) using a handheld spectroradiometer and leaf water potential data using a pressure chamber were collected from wild blueberry plants. Machine learning techniques, including multiple regression analysis and random forest models, were employed to predict leaf water potential (MPa). We explored the optimal wavelength bands for simple differences (RY1-R Y2), simple ratios (RY1/RY2), and normalized differences (|RY1-R Y2|/ (RY1-R Y2)). NDWI ((R857 - R1241)/(R857 + R1241)), SD (R2188 – R2245), and SR (R1752 / R1756) emerged as top predictors for predicting leaf water potential, significantly contributing to the highest model performance. The base learner models achieved an R-squared value of approximately 0.81, indicating their capacity to explain 81% of the variance. Research is underway to develop a neural vegetation index (NVI) that automates the process of index development by searching for specific wavelengths in the space ratio of linear functions of reflectance. The NVI framework could work across species and predict different physiological parameters.

Keywords: hyperspectral reflectance, water potential, spectral indices, machine learning, wild blueberries, optimal bands

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Authors: Rukia Yosuf

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Diabetes is a national healthcare crisis related to both macrovascular and microvascular complications. We hypothesized that higher levels of physical activity are associated with lower total and visceral fat mass, lower systolic blood pressure, and increased insulin sensitivity. Participant inclusion criteria: 21-50 years old, BMI ≥ 30 kg/m2, hemoglobin A1C 5.7-6.4, fasting glucose 100-125 mg/dL, and HOMA IR ≥ 2.5. Exclusion criteria: history of diabetes, hypertension, HIV, renal disease, hearing loss, alcoholic intake over four drinks daily, use of organic nitrates or PDE5 inhibitors, and decreased cardiac function. Total physical activity was measured using accelerometers, body composition using DXA, and insulin resistance via fsIVGTT. Clinical and biochemical cardiometabolic risk factors, blood pressure and heart rate were obtained using a calibrated sphygmomanometer. Anthropometric measures, fasting glucose, insulin, lipid profile, C-reactive protein, and BMP were analyzed using standard procedures. Within our study, we found correlations between levels of physical activity in a heterogeneous group of prediabetic adults. Patients with more physical activity had a higher degree of insulin sensitivity, lower blood pressure, total visceral adipose tissue, and overall lower total mass. Total physical activity levels showed small, but significant correlations with systolic blood pressure, visceral fat, lean mass and insulin sensitivity. After normalizing for the race, age, and gender using multiple regression, these associations were no longer significant considering our small sample size. More research into prediabetes will decrease the population of diabetics overall. In the future, we could increase sample size and conduct cross sectional and longitudinal studies in various populations with prediabetes.

Keywords: diabetes, kidney disease, nephrology, prediabetes

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Authors: Bello, A., Muhammed Ibrahim Abba., Abdullahi, M., Dauda, Sabo, & Shittu, A. T.

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This study investigated the Predictors of Lecturers Knowledge Sharing Acceptance on Open Educational Resources (OER) in North-East Nigerian in Universities. The study population comprised of 632 lecturers of Federal Universities in North-east Nigeria. The study sample covered 338 lecturers who were selected purposively from Adamawa, Bauchi and Borno State Federal Universities in Nigeria. The study adopted a prediction correlational research design. The instruments used for data collection was the questionnaire. Experts in the field of educational technology validated the instrument and tested it for reliability checks using Cronbach’s alpha. The constructs on lecturers’ acceptance to share OER yielded a reliability coefficient of; α = .956 for Performance Expectancy, α = .925; for Effort Expectancy, α = .955; for Social Influence, α = .879; for Facilitating Conditions and α = .948 for acceptance to share OER. the researchers contacted the Deanery of faculties of education and enlisted local coordinators to facilitate the data collection process at each university. The data was analysed using multiple sequential regression statistic at a significance level of 0.05 using SPSS version 23.0. The findings of the study revealed that performance expectancy (β = 0.658; t = 16.001; p = 0.000), effort expectancy (β = 0.194; t = 3.802; p = 0.000), social influence (β = 0.306; t = 5.246; p = 0.000), collectively indicated that the variables have a predictive capacity to stimulate lecturer’s acceptance to share their resources on OER repository. However, the finding revealed that facilitating conditions (β = .053; t = .899; p = 0.369), does not have a predictive capacity to stimulate lecturer’s acceptance to share their resources on OER repository. Based on these findings, the study recommends among others that the university management should consider adjusting OER policy to be centered around actualizing lecturers career progression.

Keywords: acceptance, lecturers, open educational resources, knowledge sharing

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Authors: Jaime Pizarro, Ximena Castillo

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The intensive use of water in agriculture, industry, human consumption and increasing pollution are factors that reduce the availability of water for future generations; the challenge is to advance in sustainable and low-cost solutions to reuse water and to facilitate the availability of the resource in quality and quantity. The use of new low-cost materials with sorbent capacity for pollutants is a solution that contributes to the improvement and expansion of water treatment and reuse systems. Fly ash, a residue from the combustion of coal in power plants that is produced in large quantities in newly industrialized countries, contains a high amount of silicon oxides and aluminum oxides, whose properties can be used for the synthesis of mesoporous materials. Properly functionalized, this material allows obtaining matrixes with high sorption capacity. The mesoporous materials have a large surface area, thermal and mechanical stability, uniform porous structure, and high sorption and functionalization capacities. The goal of this study was to develop hexagonal mesoporous siliceous material (HMS) for the adsorption of sulphate from industrial and mining waters. The silica was extracted from fly ash after calcination at 850 ° C, followed by the addition of water. The mesoporous structure has a surface area of 282 m2 g-1 and a size of 5.7 nm and was functionalized with ethylene diamine through of a self-assembly method. The material was characterized by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The capacity of sulphate sorption was evaluated according to pH, maximum load capacity and contact time. The sulphate maximum adsorption capacity was 146.1 mg g-1, which is three times higher than commercial sorbents. The kinetic data were fitted according to a pseudo-second order model with a high coefficient of linear regression at different initial concentrations. The adsorption isotherm that best fitted the experimental data was the Freundlich model.

Keywords: fly ash, mesoporous siliceous, sorption, sulphate

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Authors: Cornelius Femi Popoola

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Nigerian manufacturing industry, particularly the flour producing firms play vital roles in Nigerian economy. This sector’s quality management practice is given a little attention along with organizational factors that hinder successful practice of total quality management which needs to be documented. Honeywell Flour Mills Plc operate in Nigeria with an appreciable number of products that serves this sector of the economy. Internal-external disposition of the company and total quality practice of the company deserve some elucidations. Hence, this study examined the influence of organizational factors on total quality management practice of Nigerian manufacturing industry, using Honeywell Flour Mills Plc as a case study. The study employed the correlational type of descriptive survey research design. The population consisted of 656 staff of Honeywell Flour Mills Plc, out of which 235 members were selected through scientific sampling method developed by Paler-Calmorin and Calmorin. A total of 235 copies of questionnaires titled 'Organisational Factors and Total Quality Management Practices (QF-TQM) Questionnaire' were administered with a response rate of 66 copies returned. The following variables were applied internal organisational factors (IOFs), external organizational factors (EOFs) and total quality management (TQM). Data generated were analysed using frequency distribution and regression analysis at 0.05 level. The findings revealed that IOFs positively and significantly related with TQM (r = .147**, N= 64, P(.000) < .01). Also, EOFs negatively and significantly related with TQM (r = -.117, N= 64, P(.000) < .01). Findings showed that internal and external organizational factors jointly influenced TQM practiced in F₍₂,₆₁₎=22.250; R²=.629; Adj.R²=.603; P(.000) < .05). The study concluded that organizational factors are determinants of TQM practice in Nigerian manufacturing industry. It is recommended that both internal and external organizational factors influencing TQM practices should be considered in the development of TQM strategies.

Keywords: external organizational factors, internal organisational factors, Nigerian manufacturing industry, total quality management

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