Search results for: random copolymers

Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Ransford Kwaku Afeadie

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Purpose – The health challenges that characterises most of the migrants’ urban slums raise a lot of concern for their well-being. Health-seeking behaviour becomes an important step towards maintaining a healthy life. The importance of contextual issues is necessary to help meet specific community health needs and programmes. Therefore, this study aims to bridge the knowledge gap by investigating health-seeking behaviour disparity among rural-urban labour migrant slum dwellers before and after migration to the urban slums of Madina in the Greater Accra Region, Ghana. Design/methodology/approach – The author used explanatory sequential approach of research investigation. Questionnaire and interview guides were used to collect data from the respondents; however, in the absence of an existing reliable sampling frame, the various communities were selected by the use of cluster sampling proportional to size. At the second stage, a simple random sampling was used to select the various household heads. A total of 241 questionnaires were retrieved from the respondents representing a response rate of 100%. The author used the purposive sampling technique to conduct eight in-depth interviews and six key informants’ interviews. Findings – The author found various discrepancies in many of the activities that could fulfill substantial health-seeking behaviour in the slum as compared to migrant’s places of origin. The reason for coming to the slum amidst many settlements needs and low education background are the factors that accounted for this. This study, therefore, contradicts the proposition held by the health belief model. It is, therefore, important to note that contextual issues are key, in this case, rural-urban migrant slums present a different dynamic that must be taken into account when designing health programmes for such settings. Originality/value – Many, if not all the, studies on health-seeking behaviour have focused on urban slums without taking into account urban migrants’ slums. Such a failure to take into account the variations of the health needs of migrants’ urban slum settings can eventually lead to a mismatch of health programmes meant to address their challenges. Therefore, this study brings to the fore such variations that must be taken into account when designing health programmes. The study also indicates that even with the same people, there were disparities in terms of health-seeking behaviour in the slum and at places of origin.

Keywords: health-seeking behaviour, rural–urban migration, urban slums, health belief model

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Authors: Japhet N. Mwambusi

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High tropical forests deforestation for solid wood furniture industry is among of climate change contributing agents. This pressure indirectly is caused by furniture joints failure due to poor gluing technology based on improper use of different glues to different wood species which lead to low quality and weak wood-glue joints. This study was carried in order to run performance tests of wood glues on different wood species used in wood workshops: Morogoro Tanzania whereby three popular wood species of C. lusitanica, T. glandis and E. maidenii were tested against five glues of Woodfix, Bullbond, Ponal, Fevicol and Coral found in the market. The findings were necessary on developing a guideline for proper glue selection for a particular wood species joining. Random sampling was employed to interview carpenters while conducting a survey on the background of carpenters like their education level and to determine factors that influence their glues choice. Monsanto Tensiometer was used to determine bonding strength of identified wood glues to different wood species in use under British Standard of testing wood shear strength (BS EN 205) procedures. Data obtained from interviewing carpenters were analyzed through Statistical Package of Social Science software (SPSS) to allow the comparison of different data while laboratory data were compiled, related and compared by the use of MS Excel worksheet software as well as Analysis of Variance (ANOVA). Results revealed that among all five wood glues tested in the laboratory to three different wood species, Coral performed much better with the average shear strength 4.18 N/mm², 3.23 N/mm² and 5.42 N/mm² for Cypress, Teak and Eucalyptus respectively. This displays that for a strong joint to be formed to all tree wood species for soft wood and hard wood, Coral has a first priority in use. The developed table of guideline from this research can be useful to carpenters on proper glue selection to a particular wood species so as to meet glue-bond strength. This will secure furniture market as well as reduce pressure to the forests for furniture production because of the strong existing furniture due to their strong joints. Indeed, this can be a good strategy on reducing climate change speed in tropics which result from high deforestation of trees for furniture production.

Keywords: climate change, deforestation, gluing technology, joint failure, wood-glue, wood species

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Authors: S. D. Kadir

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Background: Antibiotics have always been at the centrum of the revolution of modern microbiology. Micro-organisms and its pathogenicity, resistant organisms, inappropriate or over usage of various types of antibiotic agents are fuelled multidrug-resistant pathogenic organisms. Our present time review report mainly focuses on the therapeutic condition of antibiotic resistance and the possible roots behind the development of antibiotic resistance in Bangladesh in 2019. Methodology: The systemic review has progressed through a series of research analyses on various manuscripts published on Google Scholar, PubMed, Research Gate, and collected relevant information from established popular healthcare and diagnostic center and its subdivisions all over Bangladesh. Our research analysis on the possible assurance of antibiotic resistance been ensured by the selective medical reports and on random assay on the extent of individual antibiotic in 2019. Results: 5 research articles, 50 medical report summary, and around 5 patients have been interviewed while going through the estimation process. We have prioritized research articles where the research analysis been performed by the appropriate use of the Kirby-Bauer method. Kirby-Bauer technique is preferred as it provides greater efficiency, ensures lower performance expenditure, and supplies greater convenience and simplification in the application. In most of the reviews, clinical and laboratory standards institute guidelines were strictly followed. Most of our reports indicate significant resistance shown by the Beta-lactam drugs. Specifically by the derivatives of Penicillin's, Cephalosporin's (rare use of the first generation Cephalosporin and overuse of the second and third generation of Cephalosporin and misuse of the fourth generation of Cephalosporin), which are responsible for almost 67 percent of the bacterial resistance. Moreover, approximately 20 percent of the resistance was due to the fact of drug pumping from the bacterial cell by tetracycline and sulphonamides and their derivatives. Conclusion: 90 percent of the approximate antibiotic resistance is due to the usage of relative and true broad-spectrum antibiotics. The environment has been created by the following circumstances where; the excessive usage of broad-spectrum antibiotics had led to a condition where the disruption of native bacteria and a series of anti-microbial resistance causing a disturbance of the surrounding environments in medium, leading to a state of super-infection.

Keywords: antibiotics, antibiotic resistance, Kirby Bauer method, microbiology

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Authors: Jakob Krause

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Past Financial Crisis has shown that contemporary risk management models provide an unjustified sense of security and fail miserably in situations in which they are needed the most. In this paper, we start from the assumption that risk is a notion that changes over time and therefore past data points only have limited explanatory power for the current situation. Our objective is to derive the optimal amount of representative information by optimizing between the two adverse forces of estimator convergence, incentivizing us to use as much data as possible, and the aforementioned non-representativeness doing the opposite. In this endeavor, the cornerstone assumption of having access to identically distributed random variables is weakened and substituted by the assumption that the law of the data generating process changes over time. Hence, in this paper, we give a quantitative theory on how to perform statistical analysis in non-ergodic systems. As an application, we discuss the impact of a paragraph in the last iteration of proposals by the Basel Committee on Banking Regulation. We start from the premise that the severity of assumptions should correspond to the robustness of the system they describe. Hence, in the formal description of physical systems, the level of assumptions can be much higher. It follows that every concept that is carried over from the natural sciences to economics must be checked for its plausibility in the new surroundings. Most of the probability theory has been developed for the analysis of physical systems and is based on the independent and identically distributed (i.i.d.) assumption. In Economics both parts of the i.i.d. assumption are inappropriate. However, only dependence has, so far, been weakened to a sufficient degree. In this paper, an appropriate class of non-stationary processes is used, and their law is tied to a formal object measuring representativeness. Subsequently, that data set is identified that on average minimizes the estimation error stemming from both, insufficient and non-representative, data. Applications are far reaching in a variety of fields. In the paper itself, we apply the results in order to analyze a paragraph in the Basel 3 framework on banking regulation with severe implications on financial stability. Beyond the realm of finance, other potential applications include the reproducibility crisis in the social sciences (but not in the natural sciences) and modeling limited understanding and learning behavior in economics.

Keywords: banking regulation, non-ergodicity, risk management, semimartingale modeling

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Authors: Rong Li, Brian D. Wirth, Bing Liu

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Graphite is the matrix, and structural material in the high temperature gas-cooled reactor exhibits an irradiation response. It is of significant importance to analyze the defect production and evaluate the role of graphite under irradiation. A vast experimental literature exists for graphite on the dimensional change, mechanical properties, and thermal behavior. However, simulations have not been applied to the atomistic perspective. Remarkably few molecular dynamics simulations have been performed to study the irradiation response in graphite. In this paper, irradiation-induced damage cascades in graphite were investigated with molecular dynamics simulation. Statistical results of the graphite defects were obtained by sampling a wide energy range (1–30 KeV) and 10 different runs for every cascade simulation with different random number generator seeds to the velocity scaling thermostat function. The chemical bonding in carbon was described using the adaptive intermolecular reactive empirical bond-order potential (AIREBO) potential coupled with the standard Ziegler–Biersack–Littmack (ZBL) potential to describe close-range pair interactions. This study focused on analyzing the number of defects, the final cascade morphology and the distribution of defect clusters in space, the length-scale cascade properties such as the cascade length and the range of primary knock-on atom (PKA), and graphite mechanical properties’ variation. It can be concluded that the number of surviving Frenkel pairs increased remarkably with the increasing initial PKA energy but did not exhibit a thermal spike at slightly lower energies in this paper. The PKA range and cascade length approximately linearly with energy which indicated that increasing the PKA initial energy will come at expensive computation cost such as 30KeV in this study. The cascade morphology and the distribution of defect clusters in space mainly related to the PKA energy meanwhile the temperature effect was relatively negligible. The simulations are in agreement with known experimental results and the Kinchin-Pease model, which can help to understand the graphite damage cascades and lifetime span under irradiation and provide a direction to the designs of these kinds of structural materials in the future reactors.

Keywords: graphite damage cascade, molecular dynamics, cascade morphology, cascade distribution

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Authors: Ngoc-Hieu Vu

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Dairy production in Vietnam is a relatively new agricultural activity and milk production increased remarkably in recent years. Smallholders are still the main drivers for this development, especially in the southern part of the country. However, information on the farming practices is very limited. Therefore, this study aimed to determine factors influencing milk yield and quality (milk fat, total solids, solids-not-fat, total number of bacteria, and somatic cell count) and revenue of dairy farms in Southern Vietnam. The collection of data was at the farm level; individual animal records were unavailable. The 539 studied farms were located in the provinces Lam Dong (N=111 farms), Binh Duong (N=69 farms), Long An (N=174 farms), and Ho Chi Minh city (N=185 farms). The dataset included 9221 monthly test-day records of the farms from January 2013 to May 2015. Seasons were defined as rainy and dry. Farms sizes were classified as small (< 10 milking cows), medium (10 to 19 milking cows) and large (≥ 20 milking cows). The model for each trait contained year-season and farm region-farm size as subclass fixed effects, and individual farm and residual as random effects. Results showed that year-season, region, and farm size were determining sources of variation affecting all studied traits. Milk yield was higher in dry than in rainy seasons (P < 0.05), while it tended to increase from years 2013 to 2015. Large farms had higher yields (445.6 kg/cow) than small (396.7 kg/cow) and medium (428.0 kg/cow) farms (P < 0.05). Small farms, in contrast, were superior to large farms in terms of milk fat, total solids, solids-not-fat, total number of bacteria, and somatic cell count than large farms (P < 0.05). Revenue per cow was higher in large compared with medium and small farms. In conclusion, large farms achieved higher milk yields and revenues per cow, while small farms were superior in milk quality. Overall, milk yields were low and better training, financial support and marketing opportunities for farmers are needed to improve dairy production and increase farm revenues in Southern Vietnam.

Keywords: farm size, milk yield and quality, season, Southern Vietnam

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Authors: Estibe Dagne Mekonnen

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In recent years, the prevalence of undernourishment was 30 percent for sub-Saharan Africa, compared with 16 percent for Asia and the Pacific (Ali, 2011). In Ethiopia, almost 40 percent of the total population in the country and 57 percent of Addis Ababa population lives below the international poverty line of US$ 1.25 per day (UNICEF, 2009). This study aims to analyze the determinant of household food secrity in Addis Ababa city administration. Primary data were collected from a survey of 256 households in the selected sub-city, namely Addis Ketema, Arada, and Kolfe Keranio, in the year 2022. Both Purposive and multi-stage cluster random sampling procedures were employed to select study areas and respondents. Descriptive statistics and order logistic regression model were used to test the formulated hypotheses. The result reveals that out of the total sampled households, 25% them were food secured, 13% were mildly food insecure, 26% were moderately food insecure and 36% were severely food insecure. The study indicates that household family size, house ownership, household income, household food source, household asset possession, household awareness on inflation, household access to social protection program, household access to credit and saving and household access to training and supervision on food security have a positive and significant effect on the likelihood of household food security status. However, marital status of household head, employment sector of household head, dependency ratio and household’s nonfood expenditure has a negative and significant influence on household food security status. The study finally suggests that the government in collaboration with financial institutions and NGO should work on sustaining household food security by creating awareness, providing credit, facilitate rural-urban linkage between producer and consumer and work on urban infrastructure improvement. Moreover, the governments also work closely and monitor consumer good suppliers, if possible find a way to subsidize consumable goods to more insecure households and make them to be food secured. Last but not least, keeping this country’s peace will play a crucial role to sustain food security.

Keywords: determinants, household, food security, order logit model, Addis Ababa

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Authors: Wipakon Sonsnam, Kanya Napapongsa

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The quantitative aim of the study; 1) health conditions, to examine the state of health of the aging, 2) perceived of self-efficacy, self-care of aging ,3) perceived of social support of the aging, 4) to examine factors associated with self-efficacy in enhancing the health and self-care when illness. 100 samples selected from communities in Dusit, Bangkok, 2014 by random sampling. The questionnaires were used to collect data have 5-point rating scale, consisting of strongly agree, agree, undecided, disagree, and strongly disagree; approved content valid by 3 experts, reliability coefficients alpha was .784 for perceived of self-efficacy, self-care of aging and .827 for perceived of social support of the aging. ST-5, 2Q used for collect mental health. The ability to engage in a daily routine was collected by Barthel ADL index. Founding, the sample group were female (68%). (33%) of them were in the age of 60-65. Most of them were married and still live with their spouse (55%) and do not work (38%). The average annual income was less than 10,000 baht supported by child. Most people think that income was adequate (49.0%) and Satisfaction (61.0%). Most of aging caring them-self, followed by them spouse (26%). Welfare of the public had supported, living for the aging (100%), followed by Join and health volunteers in communities (23%). In terms of health, (53%) of the sample group feels health was fair, hypertension was the most common health condition among sample group (68%), following by diabetes (55%). About eyesight, (42%) have visual acuity. (59.0%) do not need hearing aids. 84% have more than 20 teeth remaining, and have no problem with chewing (61%). In terms of Ability to engage in a daily routine, most of people (84%) in sample group are in type 1. (91%) of the participants don’t have bladder incontinence. For mental condition, (82%) do not have insomnia. (87%) do not have anxiety. (96%) do not have depression. However, (77%) of the sample group is facing stress. In terms of environment in home, bathroom in the home (90.0%) and floor of bathroom was slippery (91.0%). (48%) of the sample group has the skills of how to look after themselves while being sick, and how to keep up healthy lifestyle. Besides, some other factors, such as gender, age and educational background are related to the health perception. The statistical significance was <0.05. Suggestion: The instruments available to national standards such as ST-5, 2Q and Barthel ADL index. Reliability coefficients alpha was .784 for perceived of self-efficacy, self-care of aging and .827 for perceived of social support of the aging. The instrument used to collect perceived of social support must be further developed to study level of influence of social support that affect the health of elderly.

Keywords: ้health status, perception of aging, self-efficacy, social support

Procedia PDF Downloads 543

Authors: Hebah M. Musalem, Jeylan El-Mansoury, Lin M. Tuleimat, Selwa Alhazza, Abdul-Aziz A. Al Zoba

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Background: Amblyopia is a condition that affects the visual system triggering a decrease in visual acuity without a known underlying pathology. It is due to abnormal vision development in childhood or infancy. Most importantly, vision loss is preventable or reversible with the right kind of intervention in most of the cases. Strabismus, sensory defects, and anisometropia are all well-known causes of amblyopia. However, ocular misalignment in Strabismus is considered the most common form of amblyopia worldwide. The risk of developing amblyopia increases in premature children, developmentally delayed or children who had brain lesions affecting the visual pathway. The prevalence of amblyopia varies between 2 to 5 % in the world according to the literature. Objective: To determine the different causes of Amblyopia in pediatric patients seen in ophthalmology clinic of a tertiary care center, i.e. King Faisal Specialist Hospital and Research Center (KFSH&RC). Methods: This is a hospital based, random retrospective, based on reviewing patient’s files in the Ophthalmology Department of KFSH&RC in Riyadh city, Kingdom of Saudi Arabia. Inclusion criteria: amblyopic pediatric patients who attended the clinic from 2015 to 2016, who are between 6 months and 18 years old. Exclusion Criteria: patients above 18 years of age and any patient who is uncooperative to obtain an accurate vision or a proper refraction. Detailed ocular and medical history are recorded. The examination protocol includes a full ocular exam, full cycloplegic refraction, visual acuity measurement, ocular motility and strabismus evaluation. All data were organized in tables and graphs and analyzed by statistician. Results: Our preliminary results will be discussed on spot by our corresponding author. Conclusions: We focused on this study on utilizing various examination techniques which enhanced our results and highlighted a distinguished correlation between amblyopia and its’ causes. This paper recommendation emphasizes on critical testing protocols to be followed among amblyopic patient, especially in tertiary care centers.

Keywords: amblyopia, amblyopia causes, amblyopia diagnostic criterion, amblyopia prevalence, Saudi Arabia

Procedia PDF Downloads 159

Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Gabriel A. Juma, Adiel M. Magana, Githaiga N. Michael, James G. Kairo

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Seagrass meadows are important carbon sinks, thus understanding this role and their conservation provides opportunities for their applications in climate change mitigation and adaptation. This study aimed at understanding seagrass contribution to ecosystem carbon at Gazi Bay; by comparing carbon stocks in seagrass beds of two mangroves fringed creeks of the bay. Specifically, the objectives included assessing the distribution and abundance of seagrass in the fringed creeks, and estimating above and below-ground biomass. Results obtained would be added to the mangrove and open bay carbon in estimating total ecosystem carbon of Gazi bay. The stratified random sampling strategy was applied in this study. Transects were laid perpendicular to the waterline at intervals of 50 meters from the upper region near the mangroves to the deeper end of the creek across seagrass meadows. Along these transects, 0.25m2 square quadrats were laid at 10 m to assess distribution and composition of seagrasses in the creeks. A total of 80 plots were sampled. Above-ground biomass was sampled by harvesting all the seagrass materials within the quadrat while four sediment cores were obtained from each quarter of the quadrat and then sorted into necromass, rhizomes and roots to determine below ground biomass. Samples were cleaned and dried in the oven for 72 hours at 60˚C in the laboratory. Total biomass was determined by multiplying biomass with carbon conversion factor of 0.34. In all the statistical tests, a significant level was set at α = 0.05. Eight species of seagrass were encountered in Western creek (WC) while seven in the Eastern creek (EC). Based on importance value, the dominant species in WC were Cymodocea rotundata and Halodule uninervis while Thalassodendron ciliatum and Enhalus acoroides dominated the eastern creek. The cover of seagrass in EC was 67.97% compared to 56.45% in WC. There was a significance difference in abundance of seagrass species between the two creeks (t = 1.97, D.F = 35, p < 0.05). Similarly, there was significance differences between total seagrass biomass (t= -8.44, D.F. = 53, p < 0.05) and species composition (F(7,79) = 14.6, p < 0.05) in the two creeks. Mean seagrass in the creeks was 7.25 ± 4.2 Mg C ha-1, (range: 4.1 - 12.9 Mg C ha-1). The findings of the current study reveal variations in biomass stocks of the two creeks of Gazi bay that have varying biophysical features. It is established that habitat heterogeneity between the creeks contributes to the variation in seagrass abundance and biomass stocking. This enhances understanding of these ecosystems hence the establishment of carbon offset project in seagrass for livelihood improvement and increased conservation.

Keywords: seagrass, above-ground, below-ground, creeks, Gazi bay

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Authors: Debamitra Chakravorty, Pratap K. Parida

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Cold-adapted proteases enhance wash performance in low-temperature laundry resulting in a reduction in energy consumption and wear of textiles and are also used in the dehairing process in leather industries. Unfortunately, the possible drawbacks of using cold-adapted proteases are their instability at higher temperatures. Therefore, proteases with broad temperature stability are required. Unfortunately, wild-type cold-adapted proteases exhibit instability at higher temperatures and thus have low shelf lives. Therefore, attempts to engineer cold-adapted proteases by protein engineering were made previously by directed evolution and random mutagenesis. The lacuna is the time, capital, and labour involved to obtain these variants are very demanding and challenging. Therefore, rational engineering for cold stability without compromising an enzyme's optimum pH and temperature for activity is the current requirement. In this work, mutations were rationally designed with the aid of high throughput computational methodology of network analysis, evolutionary conservation scores, and molecular dynamics simulations for Savinase from Bacillus lentus with the intention of rendering the mutants cold stable without affecting their temperature and pH optimum for activity. Further, an attempt was made to incorporate a mutation in the most stable mutant rationally obtained by this method to introduce oxidative stability in the mutant. Such enzymes are desired in detergents with bleaching agents. In silico analysis by performing 300 ns molecular dynamics simulations at 5 different temperatures revealed that these three mutants were found to be better in cold stability compared to the wild type Savinase from Bacillus lentus. Conclusively, this work shows that cold adaptation without losing optimum temperature and pH stability and additionally stability from oxidative damage can be rationally designed by in silico enzyme engineering. The key findings of this work were first, the in silico data of H5 (cold stable savinase) used as a control in this work, corroborated with its reported wet lab temperature stability data. Secondly, three cold stable mutants of Savinase from Bacillus lentus were rationally identified. Lastly, a mutation which will stabilize savinase against oxidative damage was additionally identified.

Keywords: cold stability, molecular dynamics simulations, protein engineering, rational design

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Authors: Bantie Getnet Yirsaw, Muluken Chanie Agimas, Gebrie Getu Alemu, Tigabu Kidie Tesfie, Nebiyu Mekonnen Derseh, Habtamu Wagnew Abuhay, Meron Asmamaw Alemayehu, Getaneh Awoke Yismaw

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Introduction: Hepatitis B virus (HBV) is one of the major public health problems globally and needs an urgent response. It is one of the most responsible causes of mortality among the five hepatitis viruses, and it affects almost every class of individuals. Thus, the main objective of this study was to determine the pooled prevalence and its determinants among pregnant women in East Africa. Methods: We searched studies using PubMed, Scopus, Embase, ScienceDirect, Google Scholar, and grey literature that were published between January 01/2020 to January 30/2024. The studies were assessed using the Newcastle Ottawa Scale (NOS) quality assessment scale. The random-effect (DerSimonian) model was used to determine the pooled prevalence and associated factors of HBV among pregnant women. Heterogeneity was assessed by I² statistic, sub-group analysis, and sensitivity analysis. Publication bias was assessed by the Egger test, and the analysis was done using STATA version 17. Result: A total of 45 studies with 35639 pregnant women were included in this systematic review and meta-analysis. The overall pooled prevalence of HBV among pregnant women in East Africa was 6.0% (95% CI: 6.0%−7.0%, I² = 89.7%). The highest prevalence of 8% ((95% CI: 6%, 10%), I² = 91.08%) was seen in 2021, and the lowest prevalence of 5% ((95% CI: 4%, 6%) I² = 52.52%) was observed in 2022. A pooled meta-analysis showed that history of surgical procedure (OR = 2.14 (95% CI: 1.27, 3.61)), having multiple sexual partners (OR = 3.87 (95% CI: 2.52, 5.95), history of body tattooing (OR = 2.55 (95% CI: 1.62, 4.01)), history of tooth extraction (OR = 2.09 (95% CI: 1.29, 3.39)), abortion history(OR = 2.20(95% CI: 1.38, 3.50)), history of sharing sharp material (OR = 1.88 (95% CI: 1.07, 3.31)), blood transfusion (OR = 2.41 (95% CI: 1.62, 3.57)), family history of HBV (OR = 4.87 (95% CI: 2.95, 8.05)) and history needle injury (OR = 2.62 (95% CI: 1.20, 5.72)) were significant risk factors associated with HBV infection among pregnant women. Conclusions: The pooled prevalence of HBV infection among pregnant women in East Africa was at an intermediate level and different across countries, ranging from 1.5% to 22.2%. The result of this pooled prevalence was an indication of the need for screening, prevention, and control of HBV infection among pregnant women in the region. Therefore, early identification of risk factors, awareness creation of the mode of transmission of HBV, and implementation of preventive measures are essential in reducing the burden of HBV infection among pregnant women.

Keywords: hepatitis B virus, prevalence, determinants, pregnant women, meta-analysis, East Africa

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Authors: Maria Belen C. Costa, Liza C. Costa

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Teachers have an important influence on students’ academic achievement. Teachers play a crucial role in educational attainment because they stand in the interface of the transmission of knowledge, values, and skills in the learning process through the instructional strategies they employ in the classroom. The level of achievement of students in school depends on the degree of effectiveness of instructional strategies used by the teacher. Thus, this study was conceptualized and conducted to examine the instructional strategies preferred and used by the Science and Mathematics teachers and the impact of those strategies in their teaching performance and students’ academic achievement in Science and Mathematics. The participants of the study comprised a total enumeration of 61 teachers who were chosen through total enumeration and 610 students who were selected using two-stage random sampling technique. The descriptive correlation design was used in this study with a self-made questionnaire as the main tool in the data gathering procedure. Relationship among variables was tested and analyzed using Spearman Rank Correlation Coefficient and Wilcoxon Signed Rank statistics. The teacher participants under study mainly belonged to the age group of ‘young’ (35 years and below) and most were females having ‘very much experienced’ (16 years and above) in teaching. Teaching performance was found to be ‘very satisfactory’ while academic achievement in Science and Mathematics was found to be ‘satisfactory’. Demographic profile and teaching performance of teacher participants were found to be ‘not significant’ to their instructional strategy preferences. Results implied that age, sex, level of education and length of service of the teachers does not affect their preference on a particular instructional strategy. However, the teacher participants’ extent of use of the different instructional strategies was found to be ‘significant’ to their teaching performance. The instructional strategies being used by the teachers were found to have a direct effect on their teaching performance. Academic achievement of student participants was found to be ‘significant’ to the teacher participants’ instructional strategy preferences. The preference of the teachers on instructional strategies had a significant effect on the students’ academic performance. On the other hand, teacher participants’ extent of use of instructional strategies was showed to be ‘not significant’ to the academic achievement of students in Science and Mathematics. The instructional strategy being used by the teachers did not affect the level of performance of students in Science and Mathematics. The results of the study revealed that there was a significant difference between the teacher participants’ preference of instructional strategy and the student participants’ instructional strategy preference as well as between teacher participants’ extent of use and student participants’ perceived level of use of the different instructional strategies. Findings found a discrepancy between the teaching strategy preferences of students and strategies implemented by teachers.

Keywords: academic achievement, extent of use, instructional strategy, preferences

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Authors: Caroline Nnokwe, Iheanyi Eneremadu

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Teachers and principals are vital and integral parts of the educational system. For educational objectives to be met, the role of teachers and the functions of the principals are not to be overlooked. However, the inability of teachers and principals to carry out their roles effectively has impacted the outcome of the students’ performance. The study, therefore, examined teachers’ roles and principal’s administrative functions as correlates of effective academic performance of public secondary school students in Imo state, Nigeria. Four research questions and two hypotheses guided the study. The study adopted a correlation research design. The sample size was 5,438 respondents via the Yaro-Yamane technique, which consists of 175 teachers, 13 principals and 5,250 students using the proportional stratified random sampling technique. The instruments for data collection were a researcher-made questionnaire titled Teachers’ Role/Principals’ Administrative Functions Questionnaire (TRPAFQ) with a Cronbach Alpha coefficient of .82 and student's internal results obtained from the school authorities. Data collected were analyzed using the Pearson product-moment correlation coefficient and simple linear regression. Research questions were answered using Pearson Product Moment Correlation statistics, while the hypotheses were tested at 0.05 level of significance using regression analysis. The findings of the study showed that the educational qualification of teachers, organizing, and planning correlated student’s academic performance to a great extent, while availability and proper use of instructional materials by teachers correlated the academic performance of students to a very high extent. The findings also revealed that there is a significant relationship between teachers’ role, principals’ administrative functions and student’s academic performance of public secondary schools in Imo State, The study recommended among others that there is the need for government, through the ministry of education, and education authorities to adequately staff their supervisory department in order to carry out proper supervision of secondary school teachers, and also provide adequate instructional materials to ensure greater academic performance among secondary school students of Imo state, Nigeria.

Keywords: instructional materials, principals’ administrative functions, students’ academic performance, teacher role

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Authors: Adebayo-Victoria Tobi Dada, Dada Emmanuel

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This study assessed households’ food security and hunger levels among different communities with varying educational and economic background in Ile-Ife, Nigeria, and its environment. It also examined the impacts of varying demography on the household food security level in the area. This was with a view to providing information on the food security status of the subjects within the study area. Ten different communities with varying demography (Parakin, Mokuro, Ilare, Obafemi Awolowo University (OAU) Staff Quarters, Ibadan Road, Aba-Iya Gani, Eleweran, Iraye, Boosa, and Eku-Isobo) were identified within the study area. Fieldwork was then carried out from 7th to 14th of March, 2016 in each of these communities through survey of market prices of food stuff, diet, and nutrition, social well-being, food accessibility and affordability as well as price fluctuation and variation in household’s social background. Selection of households for the survey was done using stratified random sampling method. Key informants included community heads, landlords, tenants, and household heads. Similarly, information on food security levels with respect to demographic backgrounds was obtained from the use of modified Food and Hunger Insecurity Module (FHIM) structured questionnaire. The questionnaire was administered to one percent of the households’ population per community. The results showed that communities such as Parakin and OAU Senior Staff Quarters were dominated by civil servants, while community such as Boosa was dominated by artisans. Respondents earning between ₦11,000 and ₦20,000 per month, during the study period, had the highest percentage across the selected communities. The household food security indices showed that about 41% of the investigated respondents could not guarantee their household food for a month, while 18% reduced or skipped meals. There were positive significant relationships between monthly income (F-value = 132.04), educational status (F-value = 102.30), occupation (F-value = 104.05) and food budget (F-value = 122.09), all at p < 0.05. However, there was no significant relationship between the monthly food budget and household sizes (t-value = -1.4074, p > 0.05). Food secured households’ had the household heads with a higher level of educational attainment. The study concluded that large variations which existed between socio-economic and educational background among the communities had significant effects on households’ food security level in the study area.

Keywords: food security, households, hunger level, market prices

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Authors: Lakshmi Sujeesh, Aaron Ramzeen, Ricky Ziming Guo, Abhishek Agrawal

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Introduction: Range of motion (ROM) is often measured by physiotherapists using hand-held goniometer as part of mobility assessment for diagnosis. Due to the nature of hand-held goniometer measurement procedure, readings often tend to have some variations depending on the physical therapist taking the measurements (Riddle et al.). This study aims to validate computer vision software readings against goniometric measurements for quick and consistent ROM measurements to be taken by clinicians. The use of this computer vision software hopes to improve the future of musculoskeletal space with more efficient diagnosis from recording of patient’s ROM with minimal human error across different physical therapists. Methods: Using the hand-held long arm goniometer measurements as the “gold-standard”, healthy study participants (n = 20) were made to perform 4 exercises: Front elevation, Abduction, Internal Rotation, and External Rotation, using both arms. Assessment of active ROM using computer vision software at different angles set by goniometer for each exercise was done. Interclass Correlation Coefficient (ICC) using 2-way random effects model, Box-Whisker plots, and Root Mean Square error (RMSE) were used to find the degree of correlation and absolute error measured between set and recorded angles across the repeated trials by the same rater. Results: ICC (2,1) values for all 4 exercises are above 0.9, indicating excellent reliability. Lowest overall RMSE was for external rotation (5.67°) and highest for front elevation (8.00°). Box-whisker plots showed have showed that there is a potential zero error in the measurements done by the computer vision software for abduction, where absolute error for measurements taken at 0 degree are shifted away from the ideal 0 line, with its lowest recorded error being 8°. Conclusion: Our results indicate that the use of computer vision software is valid and reliable to use in clinical settings by physiotherapists for measuring shoulder ROM. Overall, computer vision helps improve accessibility to quality care provided for individual patients, with the ability to assess ROM for their condition at home throughout a full cycle of musculoskeletal care (American Academy of Orthopaedic Surgeons) without the need for a trained therapist.

Keywords: physiotherapy, frozen shoulder, joint range of motion, computer vision

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Authors: Francisco J. García-de-Quirós, Gianmarco Radice

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When considering small robots working in a cooperative community for Moon surface exploration, navigation and inter-nodes communication aspects become a critical issue for the mission success. For this approach to succeed, it is necessary however to deploy the required infrastructure for the robotic community to achieve efficient self-localization as well as relative positioning and communications between nodes. In this paper, an exploration mission concept in which two cooperative robotic systems co-exist is presented. This paradigm hinges on a community of reference agents that provide support in terms of communication and navigation to a second agent community tasked with exploration goals. The work focuses on the role of the agent community in charge of the overall support and, more specifically, will focus on the positioning and navigation methods implemented in RF microwave bands, which are combined with the communication services. An analysis of the different methods for range and position calculation are presented, as well as the main limiting factors for precision and resolution, such as phase and frequency noise in RF reference carriers and drift mechanisms such as thermal drift and random walk. The effects of carrier frequency instability due to phase noise are categorized in different contributing bands, and the impact of these spectrum regions are considered both in terms of the absolute position and the relative speed. A mission scenario is finally proposed, and key metrics in terms of mass and power consumption for the required payload hardware are also assessed. For this purpose, an application case involving an RF communication network in UHF Band is described, in coexistence with a communications network used for the single agents to communicate within the both the exploring agents as well as the community and with the mission support agents. The proposed approach implements a substantial improvement in planetary navigation since it provides self-localization capabilities for robotic agents characterized by very low mass, volume and power budgets, thus enabling precise navigation capabilities to agents of reduced dimensions. Furthermore, a common and shared localization radiofrequency infrastructure enables new interaction mechanisms such as spatial arrangement of agents over the area of interest for distributed sensing.

Keywords: cooperative robotics, localization, robot navigation, surface exploration

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Authors: Bedilu Tafesse

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Home gardens are important social and cultural spaces where knowledge related to agricultural practice is transmitted and through which households may improve their income and livelihood. High levels of inter- and intra-specific plant genetic diversity are preserved in home gardens. Plant diversity is threatened by rapid and unplanned urbanization, which increases environmental problems such as heating, pollution, loss of habitats and ecosystem disruption. Tropical home gardens have played a significant role in conserving plant diversity while providing substantial benefits to households. This research aimed to understand the relationship between household characteristics and plant diversity in western Ethiopia home gardens and the contributions of plants to the household economy. Plant diversity and different uses of plants were studied in a random sample of 111 suburban home gardens in the Ilu Ababora, Jima and Wellega suburban area, western Ethiopia, based on complete garden inventories followed by household surveys on socio-economic status during 2012. A total of 261 species of plants were observed, of which 41% were ornamental plants, 36% food plants, and 22% medicinal plants. Of these 16% were sold commercially to produce income. Avocado, bananas, and other fruits produced in excess. Home gardens contributed the equivalent of 7% of total annual household income in terms of food and commercial sales. Multiple regression analysis showed that education, time spent in gardening, land for cultivation, household expenses, primary conservation practices, and uses of special techniques explained 56% of the total plant diversity. Food, medicinal and commercial plant species had significant positive relationships with time spent gardening and land area for gardening. Education and conservation practices significantly affected food and medicinal plant diversity. Special techniques used in gardening showed significant positive relations with ornamental and commercial plants. Reassessments in different suburban and urban home gardens and proper documentation using same methodology is essential to build a firm policy for enhancing plant diversity and related values to households and surroundings.

Keywords: plant genetic diversity, urbanization, suburban home gardens, Ethiopia

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Authors: Elizabeth B. Katana, Brenda N. Simbwa, Josephine Namayanja, Bob O. Amodan, Edirisa J. Nsubuga, Eva A. O. Laker

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Background: Understanding stakeholders’ perceptions towards the implementation of a mass vaccination campaign is important to ensure the design of better strategies to address challenges. We explored stakeholders’ perceptions of the implementation of a nationwide door-to-door mass vaccination campaign for the oral polio vaccine (nOPV2) in Uganda for the two rounds that occurred in January and November 2022. Methods: A qualitative study was conducted among stakeholders who participated in the campaign implementation from 8 districts in Uganda using random sampling. We conducted 46 In-depth interviews lasting 30 – 40 minutes with 6 national/central supervisors, 12 district, 14 sub-county, and 14 parish-level supervisors. Stakeholders were asked about their experiences in the campaign implementation, including challenges faced and their opinions of the campaign impact and use of the door-to-door strategy. Data were analyzed thematically in line with the major campaign activities. Results: Most of the stakeholders were primarily concerned about poor planning, inadequate training of vaccination teams, community resistance including schools, challenges with recruitment and teaming of vaccinators, poor and delayed payments, lack of logistics and motivation for vaccination teams, the timing of the activities and implementing amidst COVID-19 and Ebola. The stakeholders believed that the first round was not well planned and implemented, while the second round was leveraged in their previous experiences. On the other hand, some positive experiences were noted with regard to communication, advocacy and mobilization, vaccine delivery and distribution, district readiness assessments, and cold chain management. Conclusion: This study identified many challenges that were faced in the implementation of the door-to-door mass campaign for nOPV2 in Uganda. This study identified that more needs to be done to improve door-to-door mass campaigns with a focus on motivating the implementers. These findings highlight the need for conducting performance reviews, improved planning, especially routine updates and verification of target populations and training in microplanning, and adequate mapping of community resistance to inform the implementation of future mass campaigns.

Keywords: mass polio vaccination campaigns, door-to-door strategy, stakeholders' perceptions, implementation challenges

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Authors: Abbas Sheikhtaheri, Nasim Hashemi

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Health information systems have great benefits for clinical and managerial processes of health care organizations. However, identifying and removing constraints and barriers of implementing and using health information systems before any implementation is essential. Physicians are one of the main users of health information systems, therefore, identifying the causes of their resistance and concerns about the barriers of the implementation of these systems is very important. So the purpose of this study was to determine the barriers of the development and implementation of health information systems in terms of the Iranian physicians’ perspectives. In this study conducted in 8 selected hospitals affiliated to Tehran and Iran Universities of Medical Sciences, Tehran, Iran in 2014, physicians (GPs, residents, interns, specialists) in these hospitals were surveyed. In order to collect data, a research made questionnaire was used (Cronbach’s α = 0.95). The instrument included 25 about organizational (9), personal (4), moral and legal (3) and technical barriers (9). Participants were asked to answer the questions using 5 point scale Likert (completely disagree=1 to completely agree=5). By using a simple random sampling method, 200 physicians (from 600) were invited to study that eventually 163 questionnaires were returned. We used mean score and t-test and ANOVA to analyze the data using SPSS software version 17. 52.1% of respondents were female. The mean age was 30.18 ± 7.29. The work experience years for most of them were between 1 to 5 years (80.4 percent). The most important barriers were organizational ones (3.4 ± 0.89), followed by ethical (3.18 ± 0.98), technical (3.06 ± 0.8) and personal (3.04 ± 1.2). Lack of easy access to a fast Internet (3.67±1.91) and the lack of exchanging information (3.61±1.2) were the most important technical barriers. Among organizational barriers, the lack of efficient planning for the development and implementation systems (3.56±1.32) and was the most important ones. Lack of awareness and knowledge of health care providers about the health information systems features (3.33±1.28) and the lack of physician participation in planning phase (3.27±1.2) as well as concerns regarding the security and confidentiality of health information (3.15 ± 1.31) were the most important personal and ethical barriers, respectively. Women (P = 0.02) and those with less experience (P = 0.002) were more concerned about personal barriers. GPs also were more concerned about technical barriers (P = 0.02). According to the study, technical and ethics barriers were considered as the most important barriers however, lack of awareness in target population is also considered as one of the main barriers. Ignoring issues such as personal and ethical barriers, even if the necessary infrastructure and technical requirements were provided, may result in failure. Therefore, along with the creating infrastructure and resolving organizational barriers, special attention to education and awareness of physicians and providing solution for ethics concerns are necessary.

Keywords: barriers, development health information systems, implementation, physicians

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Authors: Abbas Ahmadi, Bijan Raie, Mohammad Reza Neyshabouri, Mohammad Ali Ghorbani, Farrokh Asadzadeh

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In recent years, vast areas of Urmia Lake in Dasht-e-Tabriz has dried up leading to saline sediments exposure on the surface lake coastal areas being highly susceptible to wind erosion. This study was conducted to investigate wind erosion and its relevance to soil physicochemical properties and also modeling of wind erodibility (WE) using artificial intelligence techniques. For this purpose, 96 soil samples were collected from 0-5 cm depth in 414000 hectares using stratified random sampling method. To measure the WE, all samples (<8 mm) were exposed to 5 different wind velocities (9.5, 11, 12.5, 14.1 and 15 m s-1 at the height of 20 cm) in wind tunnel and its relationship with soil physicochemical properties was evaluated. According to the results, WE varied within the range of 76.69-9.98 (g m-2 min-1)/(m s-1) with a mean of 10.21 and coefficient of variation of 94.5% showing a relatively high variation in the studied area. WE was significantly (P<0.01) affected by soil physical properties, including mean weight diameter, erodible fraction (secondary particles smaller than 0.85 mm) and percentage of the secondary particle size classes 2-4.75, 1.7-2 and 0.1-0.25 mm. Results showed that the mean weight diameter, erodible fraction and percentage of size class 0.1-0.25 mm demonstrated stronger relationship with WE (coefficients of determination were 0.69, 0.67 and 0.68, respectively). This study also compared efficiency of multiple linear regression (MLR), gene expression programming (GEP), artificial neural network (MLP), artificial neural network based on genetic algorithm (MLP-GA) and artificial neural network based on whale optimization algorithm (MLP-WOA) in predicting of soil wind erodibility in Dasht-e-Tabriz. Among 32 measured soil variable, percentages of fine sand, size classes of 1.7-2.0 and 0.1-0.25 mm (secondary particles) and organic carbon were selected as the model inputs by step-wise regression. Findings showed MLP-WOA as the most powerful artificial intelligence techniques (R2=0.87, NSE=0.87, ME=0.11 and RMSE=2.9) to predict soil wind erodibility in the study area; followed by MLP-GA, MLP, GEP and MLR and the difference between these methods were significant according to the MGN test. Based on the above finding MLP-WOA may be used as a promising method to predict soil wind erodibility in the study area.

Keywords: wind erosion, erodible fraction, gene expression programming, artificial neural network

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Authors: Aayushi Pandey, Manoj Kumar Pandey, Ashutosh Tiwari, Kireet Kumar

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Glaciers play an important role in climate change and are sensitive phenomena of global climate change scenario. Glaciers in Himalayas are unique as they are predominantly valley type and are located in tropical, high altitude regions. These glaciers are often covered with debris which greatly affects ablation rate of glaciers and work as a sensitive indicator of glacier health. The aim of this study is to map high altitude Glacier surface with a focus on glacial lake and debris estimation using different techniques in Nagling glacier of dhauliganga basin in Himalayan region. Different Image Classification techniques i.e. thresholding on different band ratios and supervised classification using maximum likelihood classifier (MLC) have been used on high resolution sentinel 2A level 1c satellite imagery of 14 October 2017.Here Near Infrared (NIR)/Shortwave Infrared (SWIR) ratio image was used to extract the glaciated classes (Snow, Ice, Ice Mixed Debris) from other non-glaciated terrain classes. SWIR/BLUE Ratio Image was used to map valley rock and Debris while Green/NIR ratio image was found most suitable for mapping Glacial Lake. Accuracy assessment was performed using high resolution (3 meters) Planetscope Imagery using 60 stratified random points. The overall accuracy of MLC was 85 % while the accuracy of Band Ratios was 96.66 %. According to Band Ratio technique total areal extent of glaciated classes (Snow, Ice ,IMD) in Nagling glacier was 10.70 km2 nearly 38.07% of study area comprising of 30.87 % Snow covered area, 3.93% Ice and 3.27 % IMD covered area. Non-glaciated classes (vegetation, glacial lake, debris and valley rock) covered 61.93 % of the total area out of which valley rock is dominant with 33.83% coverage followed by debris covering 27.7 % of the area in nagling glacier. Glacial lake and Debris were accurately mapped using Band ratio technique Hence, Band Ratio approach appears to be useful for the mapping of debris covered glacier in Himalayan Region.

Keywords: band ratio, Dhauliganga basin, glacier mapping, Himalayan region, maximum likelihood classifier (MLC), Sentinel-2 satellite image

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Thippharat Wongsilarat, Parichat tuntilanon, Chonlakan Prataksitorn

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Recurrent adverse drug reactions are harmful to patients with mild to fatal illnesses, and affect not only patients but also their relatives, and organizations. To compare safe use of medicine among patients before and after using the recurrent adverse drug reaction prevention program . Quasi-experimental research with the target population of 598 patients with drug allergy history. Data were collected through an observation form tested for its validity by three experts (IOC = 0.87), and analyzed with a descriptive statistic (percentage). The research was conducted jointly with a multidisciplinary team to analyze and determine the weak points and strong points in the recurrent adverse drug reaction prevention system during the past three years, and 546, 329, and 498 incidences, respectively, were found. Of these, 379, 279, and 302 incidences, or 69.4; 84.80; and 60.64 percent of the patients with drug allergy history, respectively, were found to have caused by incomplete warning system. In addition, differences in practice in caring for patients with drug allergy history were found that did not cover all the steps of the patient care process, especially a lack of repeated checking, and a lack of communication between the multidisciplinary team members. Therefore, the recurrent adverse drug reaction prevention program was developed with complete warning points in the information technology system, the repeated checking step, and communication among related multidisciplinary team members starting from the hospital identity card room, patient history recording officers, nurses, physicians who prescribe the drugs, and pharmacists. Including in the system were surveillance, nursing, recording, and linking the data to referring units. There were also training concerning adverse drug reactions by pharmacists, monthly meetings to explain the process to practice personnel, creating safety culture, random checking of practice, motivational encouragement, supervising, controlling, following up, and evaluating the practice. The rate of prescribing drugs to which patients were allergic per 1,000 prescriptions was 0.08, and the incidence rate of recurrent drug reaction per 1,000 prescriptions was 0. Surveillance of recurrent adverse drug reactions covering all service providing points can ensure safe use of medicine for patients.

Keywords: recurrent drug, adverse reaction, safety, use of medicine

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Authors: Badru Hasan Segujja, Nassiwa Shamim

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This study “Territorial Influence of Religious Based Armed Conflicts in Africa” was in place to identify the influence of religious based armed conflicts, their parsistance and their impact on African societies. The study employed a qualitative research methodology, as data from respondents was descriptively recorded using random sampling technics. The study discovered that, the world is experiencing religious based armed violence where actors fight under the umbrella of freedom fighters where the African continent in particular has been at the pic of such armed violence almost since each countries independence to date. Because of this situation, the Continent is torn apart as families are traumatized by the memories of their dear ones who never survived in yesterdays’ faith based armed violence. The study disvovered that, some of these faith based armed conflicts are caused by factors ranging from undemocratic practices due to poor governance, poverty, Unemployment, religious extremism and radicalism which later turn into intractable violence. Religious armed groups such as, Holly Spirit Movement (HSM), Allied Democratic Forces (ADF) and Lords Resistance Army (LRA) in Uganda and now Eastern DRC and Central African Republic, ALSHABAB in East Africa, SELEKE and ANTI BALAKA in Central African Republic, BOKO HARAM in Nigeria, JANJAWEED in Sudan and Republic of Chad, Sudaneess Peoples Liberation Army (SPLA) in Southern Sudan, Alqaida Mission in Islamic Magreeb (AQIIM) in Mali coupled with acute racism of Hutu and Tutsi in Rwanda or Burundi and Xenophobic Nationalism in (South Africa). The study futher discovered that, the component of “freedom fighters” has strongly made these groups maintain the ground without fear of any repucation, which situation has resulted into children and women becoming disproportionally victims and the response of international communities to the violence is inadequate. The study concludes that, dialogue for peace is better than going for wars. The study recommends that, in order to restore peace on the African continent and elsewhere in the world, UN should recommend the teaching of peace values in schools, pre-conflict early warnings must be well attended, actors must refrain from using religious lebles, democracy, unemployment and poverty issues should as well be addressed to avoid unnessesary conflicts.

Keywords: influence, religious, armed, conflicts

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Authors: Fatima Muhammad Abdulkadir, D. B. Maikaje, Y. A. Umar

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A study conducted to determine cercariae diversity and prevalence of trematode infection in freshwater snails from six freshwater bodies selected by systematic random sampling in Kaduna State was carried from January 2013 to December 2013. Freshwater snails and cercariae harvested from the study sites were morphologically identified. A total of 23,823 freshwater snails were collected from the six freshwater bodies: Bagoma dam, Gimbawa dam, Kangimi dam, Kubacha dam, Manchok water intake and Saminaka water intake. The observed freshwater snail species were: Melanoides tuberculata, Biomphalaria pfeifferi, Bulinus globosus, Lymnaea natalensis, Physa sp., Cleopatra bulimoides, Bellamya unicolor and Lanistes varicus. The freshwater snails were exposed to artificial bright light from a 100 Watt electric bulb in the laboratory to induce cercarial shedding. Of the total freshwater snails collected, 10.55% released one or more types of cercariae. Seven morphological types of cercariae were shed by six freshwater snail species namely: Brevifurcate-apharyngeate distome, Amphistome, Gymnocephalus, Longifurcate-pharyngeate monostome, Longifurcate-pharyngeate distome, Echinostome and Xiphidio cercariae. Infection was monotype in most of the freshwater snails collected; however, Physa species presented a mixed infection with Gymnocephalus and Longifurcate-pharyngeate distome cercariae. B. globosus and B. pfeifferi were the most preferred intermediate hosts with the prevalence of 13.48% and 13.46%, respectively. The diversity and prevalence of cercariae varied among the six freshwater bodies with Manchok water intake having the highest infestation (14.3%) and the least recorded in Kangimi dam (3.9%). There was a correlation trend between the number of freshwater snails and trematode infection with Manchok exhibiting the highest and Bagoma none. The highest cercarial diversity was observed in B. pfeifferi and B. globosus with four morphotypes each, and the lowest was in M. tuberculata with one morphotype. The general distribution of freshwater snails and the trematode cercariae they shed suggests the risk of human and animals to trematodiasis in Manchok community. Public health education to raise awareness on individual and communal action that may control snail breeding sites, prevent transmission and provide access to treatment should be intensified.

Keywords: Cercariae, diversity, freshwater snails, prevalence, trematodiasis

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Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

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