Search results for: linear regression models

Authors: Ferran Paulí Pla, Pere Palacín Farré, Albert Fornells Herrera, Pol Toldrà Fernández

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Poor image acquisition is limiting the promising growth of industrial vision in food control. In recent years, the food industry has witnessed a significant increase in the implementation of automation in quality control through artificial vision, a trend that continues to grow. During the packaging process, some defects may appear, compromising the proper sealing of the products and diminishing their shelf life, sanitary conditions and overall properties. While failure to detect a defective product leads to major losses, food producers also aim to minimize over-rejection to avoid unnecessary waste. Thus, accuracy in the evaluation of the products is crucial, and, given the large production volumes, even small improvements have a significant impact. Recently, efforts have been focused on maximizing the performance of classification neural networks; nevertheless, their performance is limited by the quality of the input data. Monochrome linear backlight systems are most commonly used for online inspections of food packaging thermo-sealing zones. These simple acquisition systems fit the high cadence of the production lines imposed by the market demand. Nevertheless, they provide a limited amount of data, which negatively impacts classification algorithm training. A desired situation would be one where data quality is maximized in terms of obtaining the key information to detect defects while maintaining a fast working pace. This work presents a backlight hyperspectral imaging system designed and implemented replicating an industrial environment to better understand the relationship between visual data quality and spectral illumination range for a variety of packed food products. Furthermore, results led to the identification of advantageous spectral bands that significantly enhance image quality, providing clearer detection of defects.

Keywords: artificial vision, food packaging, hyperspectral imaging, image acquisition, quality control

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Authors: Lily Ingsrisawang, Tasanee Nacharoen

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Introduction: The problems of unbalanced data sets generally appear in real world applications. Due to unequal class distribution, many research papers found that the performance of existing classifier tends to be biased towards the majority class. The k -nearest neighbors’ nonparametric discriminant analysis is one method that was proposed for classifying unbalanced classes with good performance. Hence, the methods of discriminant analysis are of interest to us in investigating misclassification error rates for class-imbalanced data of three diabetes risk groups. Objective: The purpose of this study was to compare the classification performance between parametric discriminant analysis and nonparametric discriminant analysis in a three-class classification application of class-imbalanced data of diabetes risk groups. Methods: Data from a healthy project for 599 staffs in a government hospital in Bangkok were obtained for the classification problem. The staffs were diagnosed into one of three diabetes risk groups: non-risk (90%), risk (5%), and diabetic (5%). The original data along with the variables; diabetes risk group, age, gender, cholesterol, and BMI was analyzed and bootstrapped up to 50 and 100 samples, 599 observations per sample, for additional estimation of misclassification error rate. Each data set was explored for the departure of multivariate normality and the equality of covariance matrices of the three risk groups. Both the original data and the bootstrap samples show non-normality and unequal covariance matrices. The parametric linear discriminant function, quadratic discriminant function, and the nonparametric k-nearest neighbors’ discriminant function were performed over 50 and 100 bootstrap samples and applied to the original data. In finding the optimal classification rule, the choices of prior probabilities were set up for both equal proportions (0.33: 0.33: 0.33) and unequal proportions with three choices of (0.90:0.05:0.05), (0.80: 0.10: 0.10) or (0.70, 0.15, 0.15). Results: The results from 50 and 100 bootstrap samples indicated that the k-nearest neighbors approach when k = 3 or k = 4 and the prior probabilities of {non-risk:risk:diabetic} as {0.90:0.05:0.05} or {0.80:0.10:0.10} gave the smallest error rate of misclassification. Conclusion: The k-nearest neighbors approach would be suggested for classifying a three-class-imbalanced data of diabetes risk groups.

Keywords: error rate, bootstrap, diabetes risk groups, k-nearest neighbors

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Authors: Endeshaw Assefa Derso, Maria Gabriella Campolo, Angela Alibrandi

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Objectives:Early childhood malnutrition can have long-term and irreversible effects on a child's health and development. This study uses the Bayesian method with spatial variation to investigate the flexible trends of metrical covariates and to identify communities at high risk of injury. Methods: Cross-sectional data on underweight are collected from the 2016 Ethiopian Demographic and Health Survey (EDHS). The Bayesian geo-additive model is performed. Appropriate prior distributions were provided for scall parameters in the models, and the inference is entirely Bayesian, using Monte Carlo Markov chain (MCMC) stimulation. Results: The results show that metrical covariates like child age, maternal body mass index (BMI), and maternal age affect a child's underweight non-linearly. Lower and higher maternal BMI seem to have a significant impact on the child’s high underweight. There was also a significant spatial heterogeneity, and based on IDW interpolation of predictive values, the western, central, and eastern parts of the country are hotspot areas. Conclusion: Socio-demographic and community- based programs development should be considered compressively in Ethiopian policy to combat childhood underweight malnutrition.

Keywords: bayesX, Ethiopia, malnutrition, MCMC, semi-parametric bayesian analysis, spatial distribution, P- splines

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Authors: Noorjehan Joosub-Vawda

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Objectives: The aim of this poster presentation is to examine cultural contextual understandings of ABI that could aid conceptualisation and the development of a model for neuropsychological rehabilitation in this context. Characteristics of the South African context that make the implementation of international NR practices difficult include socioeconomic disparities, sociocultural influences, lack of accessibility to healthcare services, and poverty and unemployment levels. NR services in the developed world have characteristics such as low staff-to-patient ratios and interdisciplinary teams that make them unsuitable for the resource-constrained South African context. Methods: An exploratory, descriptive research design based on programme theory is being followed in the development of a South African model of neuropsychological rehabilitation. Results: The incorporation of African traditional understandings and practices, such as beliefs about ancestral spirits in the etiology of Acquired Brain Injury are relevant to the planning of rehabilitation interventions. Community-Based Rehabilitation workers, psychoeducation, and cooperation among the different systemic levels especially in rural settings is also needed to improve services offered to patients living with ABI. Conclusions. The preliminary model demonstrated in this poster will attempt to build on the strengths of South African communities, incorporating valuable evidence from international models to serve those affected with brain injury in this context.

Keywords: neuropsychological rehabilitation, South Africa, acquired brain injury, developing context

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Authors: Umi Pudji Astuti, Dedi Sugandi

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The effectiveness of agricultural extension is determined by the component in the agricultural extension system among others are agricultural extension methods. Effective methods should be selected and defined based on the characteristics of the target, the resources, the materials, and the objectives to be achieved. Citrus agribusiness development in Lebong is certainly supported by the role of stakeholders and citrus farmers, as well as the proper dissemination methods. Adoption in the extension process substantially can be interpreted as the changes of behavior process such as knowledge (cognitive), attitudes (affective), and skill (psycho-motoric) in a person after receiving "innovation" from extension submitted by target communities. Knowledge and perception are needed as a first step in adopting a innovation, especially of citrus agribusiness development in Lebong. The process of Specific technology adoption is influenced by internal factors and farmer perceptions of technological innovation. Internal factors such as formal education, experience trying to farm, owned land, production farm goods. The output of this study: 1) to analyze the effectiveness of field trial methods in improving cognitive and affective farmers; 2) Knowing the relationship of adoption level and knowledge of farmers; 3) to analyze the factors that influence farmers' adoption of citrus technology innovation. The method of this study is through the survey to 40 respondents in Rimbo Pengadang Sub District, Lebong District in 2014. Analyzing data is done by descriptive and statistical parametric (multiple linear functions). The results showed that: 1) Field trip method is effective to improve the farmer knowledge (23,17% ) and positively affect the farmer attitude; 2) the knowledge level of PTKJS innovation farmers "positively and very closely related".; 3) the factors that influence the level of farmers' adoption are internal factors (education, knowledge, and the intensity of training), and external factors respondents (distance from the house to the garden and from the house to production facilities shop).

Keywords: affect, adoption technology, citrus gerga, effectiveness dissemination

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Authors: Henry Ataburo, Dominic Essuman, Emmanuel Kwabena Anin

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Recent trends of catastrophic events, such as the Covid-19 pandemic, the Suez Canal blockage, the Russia-Ukraine conflict, the Israel-Hamas conflict, and the climate change crisis, continue to devastate supply chains and the broader society. Prior authors have advocated for a simultaneous pursuit of resilience and sustainability as crucial for navigating these challenges. Nevertheless, the relationship between resilience and sustainability is a rather complex one: resilience and sustainability are considered unrelated, substitutes, or complements. Scholars also suggest that different firms prioritize resilience and sustainability differently for varied strategic reasons. However, we know little about whether, how, and when these choices produce different typologies of firms to explain differences in financial and market performance outcomes. This research draws inferences from the systems configuration approach to organizational fit to contend that a taxonomy of firms may emerge based on how firms configure resilience and environmental sustainability. The study further examines the effects of these taxonomies on financial and market performance in differing transportation disruption conditions. Resilience is operationalized as a firm’s ability to adjust current operations, structure, knowledge, and resources in response to disruptions, whereas environmental sustainability is operationalized as the extent to which a firm deploys resources judiciously and keeps the ecological impact of its operations to the barest minimum. Using primary data from 199 firms in Ghana and cluster analysis as an analytical tool, the study identifies four clusters of firms based on how they prioritize resilience and sustainability: Cluster 1 - "strong, moderate resilience, high sustainability firms," Cluster 2 - "sigh resilience, high sustainability firms," Cluster 3 - "high resilience, strong, moderate sustainability firms," and Cluster 4 - "weak, moderate resilience, strong, moderate sustainability firms". In addition, ANOVA and regression analysis revealed the following findings: Only clusters 1 and 2 were significantly associated with both market and financial performance. Under high transportation disruption conditions, cluster 1 firms excel better in market performance, whereas cluster 2 firms excel better in financial performance. Conversely, under low transportation disruption conditions, cluster 1 firms excel better in financial performance, whereas cluster 2 firms excel better in market performance. The study provides theoretical and empirical evidence of how resilience and environmental sustainability can be configured to achieve specific performance objectives under different disruption conditions.

Keywords: resilience, environmental sustainability, developing economy, transportation disruption

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Authors: Kayijuka Idrissa

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This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: statistical methods, traffic flow, Poisson distribution, car moving technics

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Authors: Cagdas Agirdas

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Background: The Affordable Care Act (ACA) requires non-grandfathered private insurance plans, starting with plan years on or after September 23rd, 2010, to provide certain preventive care services without any cost sharing in the form of deductibles, copayments or co-insurance. This requirement may affect racial and ethnic disparities in preventive care as it provides the largest copay reduction in preventive care. Objectives: We ask whether the ACA’s free preventive care benefits are associated with a reduction in racial and ethnic disparities in the utilization of four preventive services: cholesterol screenings, colonoscopies, mammograms, and pap smears. Methods: We use a data set of over 6,000 individuals from the 2009, 2010, and 2013 Medical Expenditure Panel Surveys (MEPS). We restrict our data set only to individuals who are old enough to be eligible for each preventive service. Our difference-in-differences logistic regression model classifies privately-insured Hispanics, African Americans, and Asians as the treatment groups and 2013 as the after-policy year. Our control group consists of non-Hispanic whites on Medicaid as this program already covered preventive care services for free or at a low cost before the ACA. Results: After controlling for income, education, marital status, preferred interview language, self-reported health status, employment, having a usual source of care, age and gender, we find that the ACA is associated with increases in the probability of the median, privately-insured Hispanic person to get a colonoscopy by 3.6% and a mammogram by 3.1%, compared to a non-Hispanic white person on Medicaid. Similarly, we find that the median, privately-insured African American person’s probability of receiving these two preventive services improved by 2.3% and 2.4% compared to a non-Hispanic white person on Medicaid. We do not find any significant improvements for any racial or ethnic group for cholesterol screenings or pap smears. Furthermore, our results do not indicate any significant changes for Asians compared to non-Hispanic whites in utilizing the four preventive services. These reductions in racial/ethnic disparities are robust to reconfigurations of time periods, previous diagnosis, and residential status. Conclusions: Early effects of the ACA’s provision of free preventive care are significant for Hispanics and African Americans. Further research is needed for the later years as more individuals became aware of these benefits.

Keywords: preventive care, Affordable Care Act, cost sharing, racial disparities

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Authors: Fredrik Hartwig, Peter Lindberg

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In 2004, the International Accounting Standards Board (IASB) issued new accounting standards for impairment testing of goodwill. IFRS 3 Business Combinations and IAS 36 Impairment of Assets prohibited amortization of acquired goodwill and instead required companies to test goodwill for impairment annually or more often if necessary. The goodwill impairment test is based on management’s judgement and estimations, making the impairment-only-approach subjective and unreliable. Management can use the discretion opportunistically by managing goodwill impairments. The IASB’s remedy to the reliability problem has been to demand transparent financial reports. IAS 36 paragraph 134 requires detailed disclosures regarding the impairment test in order to make potentially unreasonable assumptions and estimations visible. The disclosure requirements should thus (in theory) make it more difficult for management to ‘choose’ assumptions and estimations that suit an agenda. Whether the requirement to disclose detailed disclosures regarding the impairment test leads to less opportunism is however an empirical question. This work analyses whether one of the required disclosures in IAS 36 paragraph 134, the reported discount rate, differs from an independently estimated risk-adjusted discount rate. Estimates of discount rates that are either lower or higher than the independently estimated discount rate are here defined as opportunism. In the former case - i.e. when the reported discount rate is lower - the objective may be to avoid profit reducing impairment charges. In the latter case - i.e. when the reported discount rate is higher - the objective may be to reduce profits or take ‘big baths’. This paper differs in one important respect from previous similar studies, the majority of which are based on purely descriptive statistics; we use multivariate regression analysis to analyze what factors affect deviations between disclosed discount rates and independently estimated discount rates. The sample consists of Swedish and Finnish listed companies. Swedish and Finnish listed companies are analysed since the accounting oversight bodies differ between the two countries. The results show that discount rate deviations in Swedish and Finnish listed companies are significantly related to accounting oversight, size and industry but not financial risk, business risk and goodwill intensity.

Keywords: discount rate, manipulation, goodwill impairment test, disclosures

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Authors: Araya Yordchim, Rosjana Chandhasa, Suwaree Yordchim

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This research aims to study guidelines on the development of management process for research journals in order to develop Suan Sunandha Rajabhat University to international standards. This research investigated affecting elements ranging from the format of the article, evaluation form for research article quality, the process of creating a scholarly journal, satisfaction level of those with knowledge and competency to conduct research, arisen problems, and solutions. Drawing upon the sample size of 40 persons who had knowledge and competency in conducting research and creating scholarly journal articles at an international level, the data for this research were collected using questionnaires as a tool. Through the usage of computer software, data were analyzed by using the statistics in the forms of frequency, percentage, mean, standard deviation, and multiple regression analysis. The majority of participants were civil servants with a doctorate degree, followed by civil servants with a master's degree. Among them, the suitability of the article format was rated at a good level while the evaluation form for research articles quality was assessed at a good level. Based on participants' viewpoints, the process of creating scholarly journals was at a good level, while the satisfaction of those who had knowledge and competency in conducting research was at a satisfactory level. The problems encountered were the difficulty in accessing the website. The solution to the problem was to develop a website with user-friendly accessibility, including setting up a Google scholar profile for the purpose of references counting and the articles being used for reference in real-time. Research article format influenced the level of satisfaction of those who had the knowledge and competency to conduct research with statistical significance at the 0.01 level. The research article quality assessment form (preface section, research article writing section, preparation for research article manuscripts section, and the original article evaluation form for the author) affected the satisfaction of those with knowledge and competency to conduct research with the statistical significance at the level of 0.01. The process of establishing journals had an impact on the satisfaction of those with knowledge and ability to conduct research with statistical significance at the level of .05

Keywords: guidelines, development of management, research journals, international standards

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Authors: Sabri Mrayed, David Maccioni, Greg Leslie

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Seawater desalination has been accepted as one of the most effective solutions to the growing problem of a diminishing clean drinking water supply. Currently, two desalination technologies dominate the market – the thermally driven multi-stage flash distillation (MSF) and the membrane based reverse osmosis (RO). However, in recent years membrane distillation (MD) has emerged as a potential alternative to the established means of desalination. This research project intended to determine the viability of MD as an alternative process to MSF and RO for seawater desalination. Specifically the project involves conducting a thermodynamic analysis of the process based on the second law of thermodynamics to determine the efficiency of the MD. Data was obtained from experiments carried out on a laboratory rig. In order to determine exergy values required for the exergy analysis, two separate models were built in Engineering Equation Solver – the ’Minimum Separation Work Model’ and the ‘Stream Exergy Model’. The efficiency of MD process was found to be 17.3 %, and the energy consumption was determined to be 4.5 kWh to produce one cubic meter of fresh water. The results indicate MD has potential as a technique for seawater desalination compared to RO and MSF. However, it was shown that this was only the case if an alternate energy source such as green or waste energy was available to provide the thermal energy input to the process. If the process was required to power itself, it was shown to be highly inefficient and in no way thermodynamically viable as a commercial desalination process.

Keywords: desalination, exergy, membrane distillation, second law efficiency

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Surabhi Gautam, Uma Kumar, Rima Dada

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A sustained acute-phase response in Rheumatoid Arthritis (RA) is associated with increased joint damage and inflammation leading to progressive disability. It is induced continuously by consecutive stimuli of proinflammatory cytokines, following a wide range of pathophysiological reactions, leading to increased synthesis of acute phase proteins like C - reactive protein (CRP) and dysregulation in levels of immunomodulatory soluble Human Leukocyte Antigen-G (HLA-G) molecule. This study was designed to explore the effect of yoga and meditation based lifestyle intervention (YMLI) on inflammatory markers in RA patients. Blood samples of 50 patients were collected at baseline (day 0) and after 30 days of YMLI. Patients underwent a pretested YMLI under the supervision of a certified yoga instructor for 30 days including different Asanas (physical postures), Pranayama (breathing exercises), and Dhayna (meditation). Levels of CRP, IL-6, IL-17A, soluble HLA-G and erythrocyte sedimentation rate (ESR) were measured at day 0 and 30 interval. Parameters of disease activity, disability quotient, pain acuity and quality of life were also assessed by disease activity score (DAS28), health assessment questionnaire (HAQ), visual analogue scale (VAS), and World Health Organization Quality of Life (WHOQOL-BREF) respectively. There was reduction in mean levels of CRP (p < 0.05), IL-6 (interleukin-6) (p < 0.05), IL-17A (interleukin-17A) (p < 0.05) and ESR (p < 0.05) and elevation in soluble HLA-G (p < 0.05) at 30 days compared to baseline level (day 0). There was reduction seen in DAS28-ESR (p < 0.05), VAS (p < 0.05) and HAQ (p < 0.05) after 30 days with respect to the base line levels (day 0) and significant increase in WHOQOL-BREF scale (p < 0.05) in all 4 domains of physical health, psychological health, social relationships, and environmental health. The present study has demonstrated that yoga practices are associated with regression of inflammatory processes by reducing inflammatory parameters and regulating the levels of soluble HLA-G significantly in active RA patients. Short term YMLI has significantly improved pain perception, disability quotient, disease activity and quality of life. Thus this simple life style intervention can reduce disease severity and dose of drugs used in the treatment of RA.

Keywords: inflammation, quality of life, rheumatoid arthritis, yoga and meditation

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Authors: L. Khalfa, M. Bagane, M. L. Cervera, S. Najjar

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The aim of this work is to present a low cost adsorbent for removing toxic heavy metals from aqueous solutions. Therefore, we are interested to investigate the efficiency of natural clay minerals collected from south Tunisia and their modified form using sulfuric acid in the removal of toxic metal ions: Zn(II) and Pb(II) from synthetic waste water solutions. The obtained results indicate that metal uptake is pH-dependent and maximum removal was detected to occur at pH 6. Adsorption equilibrium is very rapid and it was achieved after 90 min for both metal ions studied. The kinetics results show that the pseudo-second-order model describes the adsorption and the intraparticle diffusion models are the limiting step. The treatment of natural clay with sulfuric acid creates more active sites and increases the surface area, so it showed an increase of the adsorbed quantities of lead and zinc in single and binary systems. The competitive adsorption study showed that the uptake of lead was inhibited in the presence of 10 mg/L of zinc. An antagonistic binary adsorption mechanism was observed. These results revealed that clay is an effective natural material for removing lead and zinc in single and binary systems from aqueous solution.

Keywords: heavy metal, activated clay, kinetic study, competitive adsorption, modeling

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Authors: Navpreet Kaur, Himkusha Thakur, Nirmal Prabhakar

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The most controversial issue in crop production is the use of Organophosphate insecticides. This is evident in many reports that Organophosphate (OP) insecticides, among the broad range of pesticides are mainly involved in acute and chronic poisoning cases. OPs detection is of crucial importance for health protection, food and environmental safety. In our study, a nanocomposite of poly (3,4 ethylenedioxythiophene) (PEDOT) and multi-walled carbon nanotubes (MWCNTs) has been deposited electrochemically onto the surface of fluorine doped tin oxide sheets (FTO) for the analysis of malathion OP. The -COOH functionalization of MWCNTs has been done for the covalent binding with amino groups of AChE enzyme. The use of PEDOT-MWCNT films exhibited an excellent conductivity, enables fast transfer kinetics and provided a favourable biocompatible microenvironment for AChE, for the significant malathion OP detection. The prepared biosensors were characterized by Fourier transform infrared spectrometry (FTIR), Field emission-scanning electron microscopy (FE-SEM) and electrochemical studies. Various optimization studies were done for different parameters including pH (7.5), AChE concentration (50 mU), substrate concentration (0.3 mM) and inhibition time (10 min). Substrate kinetics has been performed and studied for the determination of Michaelis Menten constant. The detection limit for malathion OP was calculated to be 1 fM within the linear range 1 fM to 1 µM. The activity of inhibited AChE enzyme was restored to 98% of its original value by 2-pyridine aldoxime methiodide (2-PAM) (5 mM) treatment for 11 min. The oxime 2-PAM is able to remove malathion from the active site of AChE by means of trans-esterification reaction. The storage stability and reusability of the prepared biosensor is observed to be 30 days and seven times, respectively. The application of the developed biosensor has also been evaluated for spiked lettuce sample. Recoveries of malathion from the spiked lettuce sample ranged between 96-98%. The low detection limit obtained by the developed biosensor made them reliable, sensitive and a low cost process.

Keywords: PEDOT-MWCNT, malathion, organophosphates, acetylcholinesterase, biosensor, oxime (2-PAM)

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Authors: Bhumika Wadhwa, Fayaz Malik

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The serine/threonine protein kinase B (PKB) also known as Akt, is one of the multifaceted kinase in human kinome, existing in three isoforms. Akt plays a vital role in phosphoinositide 3-kinase (PI3K) mediated oncogenesis in various malignancies and is one of the attractive targets for cancer drug discovery. The functional significance of an individual isoform of Akt is not redundant in cancer cell proliferation and metastasis instead Akt isoforms play distinct roles during metastasis; thereby regulating EMT. This study aims to determine isoform specific functions of Akt in cancer. The results obtained suggest that Akt1 restrict tumor invasion, whereas Akt2 promotes cell migration and invasion by various techniques like MTT, wound healing and invasion assay. Similarly, qRT-PCR also revealed that Akt3 has shown promising results in promoting cancer cell migration. Contrary to pro-oncogenic properties attributed to Akt, it is to be understood how various isoforms of Akt compensates each other in the regulation of common pathways during cancer progression and drug resistance. In conclusion, this study aims to target selective isoforms which is essential to inhibit cancer. However, the question now is whether, and how much, Akt inhibition will be tolerated in the clinic remains to be answered and the experiments will have to address the question of which combinations of newly devised Akt isoform specific inhibitors exert a favourable therapeutic effect in in vivo models of cancer to provide the therapeutic window with minimal toxicity.

Keywords: Akt isoforms, cancer, drug resistance, epithelial mesenchymal transition

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Authors: Imad Khan, Imran Shafi, Sarmad Farooq

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Large diameter pipes, barrels, tubes, and ducts are used in a variety of applications covering civil and defense-related technologies. This may include heating/cooling networks, sign poles, bracing, casing, and artillery and tank gun barrels. These large diameter assemblies require regular inspection and cleaning to increase their life and reduce replacement costs. This paper describes the design, development, and testing results of an efficient yet simplified, low maintenance mechanical design controlled with minimal essential electronics using an electric motor for a non-technical staff. The proposed solution provides a simplified user interface and an automated cleaning mechanism that requires a single user to optimally clean pipes and barrels in the range of 105 mm to 203 mm caliber. The proposed system employs linear motion of specially designed brush along the barrel using a chain of specific strength and a pulley anchor attached to both ends of the barrel. A specially designed and manufactured gearbox is coupled with an AC motor to allow movement of contact brush with high torque to allow efficient cleaning. A suitably powered AC motor is fixed to the front adapter mounted on the muzzle side whereas the rear adapter has a pulley-based anchor mounted towards the breach block in case of a gun barrel. A mix of soft nylon and hard copper bristles-based large surface brush is connected through a strong steel chain to motor and anchor pulley. The system is equipped with limit switches to auto switch the direction when one end is reached on its operation. The testing results based on carefully established performance indicators indicate the superiority of the proposed user-friendly cleaning mechanism vis-à-vis its life cycle cost.

Keywords: pipe cleaning mechanism, limiting switch, pipe cleaning robot, large pipes

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Authors: Sakina Fatima, Joseph-Patrick W. E. Clarke, Patricia A. Thibault, Subha Kalyaanamoorthy, Michael Levin, Aravindhan Ganesan

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Heteronuclear ribonucleoprotein (hnRNPA1 or A1) is associated with the pathology of different diseases, including neurological disorders and cancers. In particular, the aggregation and dysfunction of A1 have been identified as a critical driver for neurodegeneration (NDG) in Multiple Sclerosis (MS). Structurally, A1 includes a low-complexity domain (LCD) and two RNA-recognition motifs (RRMs), and their interdomain coordination may play a crucial role in A1 aggregation. Previous studies propose that RNA-inhibitors or nucleoside analogs that bind to RRMs can potentially prevent A1 self-association. Therefore, molecular-level understanding of the structures, dynamics, and nucleotide interactions with A1 RRMs can be useful for developing therapeutics for NDG in MS. In this work, a combination of computational modelling and biochemical experiments were employed to analyze a set of RNA-A1 RRM complexes. Initially, the atomistic models of RNA-RRM complexes were constructed by modifying known crystal structures (e.g., PDBs: 4YOE and 5MPG), and through molecular docking calculations. The complexes were optimized using molecular dynamics simulations (200-400 ns), and their binding free energies were computed. The binding affinities of the selected complexes were validated using a thermal shift assay. Further, the most important molecular interactions that contributed to the overall stability of the RNA-A1 RRM complexes were deduced. The results highlight that adenine and guanine are the most suitable nucleotides for high-affinity binding with A1. These insights will be useful in the rational design of nucleotide-analogs for targeting A1 RRMs.

Keywords: hnRNPA1, molecular docking, molecular dynamics, RNA-binding proteins

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Authors: J. M. Mayoral, M. Anaya

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The urban and economic development of cities demands the construction of water use and flood control infrastructure. Likewise, it is necessary to determine the safety level of the structures built with the current standards and if it is necessary to define the reinforcement actions. The foregoing is even more important in structures of great importance, such as dams, since they imply a greater risk for the population in case of failure or undesirable operating conditions (e.g., seepage, cracks, subsidence). This article presents a methodology for determining the seismic integrity of dams in urban areas. From direct measurements of the dynamic properties using geophysical exploration and ambient seismic noise measurements, the seismic integrity of the concrete-faced rockfill dam selected as a case of study is evaluated. To validate the results, two accelerometer stations were installed (e.g., free field and crest of the dam). Once the dynamic properties were determined, three-dimensional finite difference models were developed to evaluate the dam seismic performance for different intensities of movement, considering the site response and soil-structure interaction effects. The seismic environment was determined from the uniform hazard spectra for several return periods. Based on the results obtained, the safety level of the dam against different seismic actions was determined, and the effectiveness of ambient seismic noise measurements in dynamic characterization and subsequent evaluation of the seismic integrity of urban dams was evaluated.

Keywords: risk, seismic, soil-structure interaction, urban dams

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Authors: Nadzeya Marozkina, Joe Zein, Benjamin Gaston

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Introduction: We have observed that many patients with Primary Ciliary Dyskinesia (PCD) benefit from asthma medications. In healthy airways, the ciliary function is normal. Antigens and irritants are rapidly cleared, and NO enters the gas phase normally to be exhaled. In the PCD airways, however, antigens, such as Dermatophagoides, are not as well cleared. This defect leads to oxidative stress, marked by increased DUOX1 expression and decreased superoxide dismutase [SOD] activity (manuscript under revision). H₂O₂, in high concentrations in the PCD airway, injures the airway. NO is oxidized rather than being exhaled, forming cytotoxic peroxynitrous acid. Thus, antigen stasis on PCD airway epithelium leads to airway injury and may predispose PCD patients to asthma. Indeed, recent population genetics suggest that PCD genes may be associated with asthma. We therefore hypothesized that PCD patients would be predisposed to having asthma. Methods. We analyzed our database of 18 million individual electronic medical records (EMRs) in the Indiana Network for Patient Care research database (INPCR). There is not an ICD10 code for PCD itself; code Q34.8 is most commonly used clinically. To validate analysis of this code, we queried patients who had an ICD10 code for both bronchiectasis and situs inversus totalis in INPCR. We also studied a validation cohort using the IBM Explorys® database (over 80 million individuals). Analyses were adjusted for age, sex and race using a 1 PCD: 3 controls matching method in INPCR and multivariable logistic regression in the IBM Explorys® database. Results. The prevalence of asthma ICD10 codes in subjects with a code Q34.8 was 67% vs 19% in controls (P < 0.0001) (Regenstrief Institute). Similarly, in IBM*Explorys, the OR [95% CI] for having asthma if a patient also had ICD10 code 34.8, relative to controls, was =4.04 [3.99; 4.09]. For situs inversus alone the OR [95% CI] was 4.42 [4.14; 4.71]; and bronchiectasis alone the OR [95% CI] =10.68 (10.56; 10.79). For both bronchiectasis and situs inversus together, the OR [95% CI] =28.80 (23.17; 35.81). Conclusions: PCD causes antigen stasis in the human airway (under review), likely predisposing to asthma in addition to oxidative and nitrosative stress and to airway injury. Here, we show that, by several different population-based metrics, and using two large databases, patients with PCD appear to have between a three- and 28-fold increased risk of having asthma. These data suggest that additional studies should be undertaken to understand the role of ciliary dysfunction in the pathogenesis and genetics of asthma. Decreased antigen clearance caused by ciliary dysfunction may be a risk factor for asthma development.

Keywords: antigen, PCD, asthma, nitric oxide

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Authors: Erika K. Méndez, Carlos E. Orrego, Diana L. Manrique, Juan D. Gonzalez, Doménica Vallejo

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High moisture content in fruits generates post-harvest problems such as mechanical, biochemical, microbial and physical losses. Dehydration, which is based on the reduction of water activity of the fruit, is a common option for overcoming such losses. However, regular hot air drying could affect negatively the quality properties of the fruit due to the long residence time at high temperature. Power ultrasound (US) application during the convective drying has been used as a novel method able to enhance drying rate and, consequently, to decrease drying time. In the present study, a new approach was tested to evaluate the effect of US on the drying time, the final antioxidant activity (AA) and the total polyphenol content (TPC) of banana slices (BS), mango slices (MS) and guava slices (GS). There were also studied the drying kinetics with nine different models from which water effective diffusivities (Deff) (with or without shrinkage corrections) were calculated. Compared with the corresponding control tests, US assisted drying for fruit slices showed reductions in drying time between 16.23 and 30.19%, 11.34 and 32.73%, and 19.25 and 47.51% for the MS, BS and GS respectively. Considering shrinkage effects, Deff calculated values ranged from 1.67*10-10 to 3.18*10-10 m2/s, 3.96*10-10 and 5.57*10-10 m2/s and 4.61*10-10 to 8.16*10-10 m2/s for the BS, MS and GS samples respectively. Reductions of TPC and AA (as DPPH) were observed compared with the original content in fresh fruit data in all kinds of drying assays.

Keywords: banana, drying, effective diffusivity, guava, mango, ultrasound

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Authors: Ofonime U. M. John, Justina I. R. Udotong, Victor O. Nwaugo, Ime R. Udotong

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Oily wastes from oil and gas exploration and production (O&G E&P) activities were remediated for twelve weeks using Soil-Poultry dropping amendment. Culture-dependent microbiological, chemical and enzymatic techniques were employed to assess the efficacy of remediation process. Microbiological activities of the remediated wastes showed increased hydrocarbonoclastic microbial populations with increased remediation time; 2.7±0.1 x 105cfu/g to 8.3 ± 0.04 x106cfu/g for hydrocarbon utilizing bacteria, 1.7 ± 0.2 x103cfu/g to 6.0 ± 0.01 x 104cfu/g for hydrocarbon utilizing fungi and 2.2 ± 0.1 x 102cfu/g to 6.7 ± 0.1 x 103cfu/g for hydrocarbon utilizing actinomycetes. Bacteria associated with the remediated wastes after the remediation period included the genera Bacillus, Psuedomonas, Beijerinckia, Acinetobacter, Alcaligenes and Serratia. Fungal isolates included species of Penicillium, Aspergillus and Cladosporium, while the Actinomycetes included species of Rhodococcus, Nocardia and Streptomyces. Slight fluctuations in pH values between 6.5± 0.2 and 7.1 ± 0.08 were recorded throughout the process, while total petroleum hydrocarbon (TPH) content decreased from 89, 900 ± 0.03mg/kg to 425 ± 0.1 mg/kg after twelve weeks of remediation. The polycyclic aromatic hydrocarbon (PAH) levels decreased with increased remediation time; naphthalene, flourene, pheneanthrene, anthracene, pyrene, chrysene and benzo(b)flouranthene showed decreased values < 0.01 after twelve weeks of remediation. Enzyme activities revealed increased dehydrogenase and urease activities with increased remediation time and decreased phenol oxidase activity with increased remediation period. There was a positive linear correlation between densities of hydrocarbonoclastic microbes and dehydrogenase activity. On the contrary, phenol oxidase and urease activities showed negative correlation with microbial population. Results of this study confirmed that remediation of oily wastes using soil-poultry dropping amendment can result in eco-friendly O&G E&P wastes. It also indicates that urease and phenol oxidase activities can be reliable indices/tools to monitor PAH levels and rates of petroleum hydrocarbon degradation.

Keywords: dehydrogenase activity, oily wastes, remediation, soil-poultry dropping amendment

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Authors: Abdal-Hafeez Alhussein

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Artificial Intelligence (AI) has become a transformative force in the field of information technologies, reshaping how data is processed, analyzed, and utilized across various domains. This paper explores the multifaceted applications of AI within information technology, focusing on three key areas: automation, scalability, and data-driven decision-making. We delve into how AI-powered automation is optimizing operational efficiency in IT infrastructures, from automated network management to self-healing systems that reduce downtime and enhance performance. Scalability, another critical aspect, is addressed through AI’s role in cloud computing and distributed systems, enabling the seamless handling of increasing data loads and user demands. Additionally, the paper highlights the use of AI in cybersecurity, where real-time threat detection and adaptive response mechanisms significantly improve resilience against sophisticated cyberattacks. In the realm of data analytics, AI models—especially machine learning and natural language processing—are driving innovation by enabling more precise predictions, automated insights extraction, and enhanced user experiences. The paper concludes with a discussion on the ethical implications of AI in information technologies, underscoring the importance of transparency, fairness, and responsible AI use. It also offers insights into future trends, emphasizing the potential of AI to further revolutionize the IT landscape by integrating with emerging technologies like quantum computing and IoT.

Keywords: artificial intelligence, information technology, automation, scalability

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Authors: Da Kuang

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Resilience is a hotly debated topic in many research fields (e.g., engineering, ecology, society, psychology). In flood management studies, we are experiencing the paradigm shift from flood resistance to flood resilience. Flood resilience refers to tolerate flooding through adaptation or transformation. It is increasingly argued that our city as a social-ecological system holds the ability to learn from experience and adapt to flood rather than simply resist it. This research aims to investigate what kinds of adaptation knowledge the frequently flooded village learned from past experience and its advantages and limitations in coping with floods. The study area – Xinnongcun village, located in the west of Wuhan city, is a linear village and continuously suffered from both flash flood and drainage flood during the past 30 years. We have a field trip to the site in June 2017 and conducted semi-structured interviews with local residents. Our research summarizes two types of adaptation knowledge that people learned from the past floods. Firstly, at the village scale, it has formed a collective urban form which could help people live during both flood and dry season. All houses and front yards were elevated about 2m higher than the road. All the front yards in the village are linked and there is no barrier. During flooding time, people walk to neighbors through houses yards and boat to outside village on the lower road. Secondly, at individual scale, local people learned tacit knowledge of preparedness and emergency response to flood. Regarding the advantages and limitations, the adaptation knowledge could effectively help people to live with flood and reduce the chances of getting injuries. However, it cannot reduce local farmers’ losses on their agricultural land. After flood, it is impossible for local people to recover to the pre-disaster state as flood emerges during June and July will result in no harvest. Therefore, we argue that learning from past flood experience could increase people’s adaptive capacity. However, once the adaptive capacity cannot reduce people’s losses, it requires a transformation to a better regime.

Keywords: adaptation, flood resilience, tacit knowledge, transformation

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Authors: Ariadne Katsouras, Andrea Chareunsy

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The number of large hydroelectric dams in the world has increased from almost 6,000 in the 1950s to over 45,000 in 2000. Dams are often built to increase the economic development of a country. This can occur in several ways. Large dams take many years to build so the construction process employs many people for a long time and that increased production and income can flow on into other sectors of the economy. Additionally, the provision of electricity can help raise people’s living standards and if the electricity is sold to another country then the money can be used to provide other public goods for the residents of the country that own the dam. Dams are also built to control flooding and provide irrigation water. Most dams are of these types. This paper will give an overview of the environmental and economic theories of the impact of dams in different regions of the world. There is a difference in the degree of environmental and economic impacts due to the varying climates and varying social and political factors of the regions. Production of greenhouse gases from the dam’s reservoir, for instance, tends to be higher in tropical areas as opposed to Nordic environments. However, there are also common impacts due to construction of the dam itself, such as, flooding of land for the creation of the reservoir and displacement of local populations. Economically, the local population tends to benefit least from the construction of the dam. Additionally, if a foreign company owns the dam or the government subsidises the cost of electricity to businesses, then the funds from electricity production do not benefit the residents of the country the dam is built in. So, in the end, the dams can benefit a country economically, but the varying factors related to its construction and how these are dealt with, determine the level of benefit, if any, of the dam. Some of the theories or practices used to evaluate the potential value of a dam include cost-benefit analysis, environmental impacts assessments and regressions. Systems analysis is also a useful method. While these theories have value, there are also possible shortcomings. Cost-benefit analysis converts all the costs and benefits to dollar values, which can be problematic. Environmental impact assessments, likewise, can be incomplete, especially if the assessment does not include feedback effects, that is, they only consider the initial impact. Finally, regression analysis is dependent on the available data and again would not necessarily include feedbacks. Systems analysis is a method that can allow more complex modelling of the environment and the economic system. It would allow a clearer picture to emerge of the impacts and can include a long time frame.

Keywords: comparison, economics, environment, hydroelectric dams

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Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

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Authors: Kanica Goel, Nilam

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Infectious diseases are a leading cause of death worldwide and hence a great challenge for every nation. Thus, it becomes utmost essential to prevent and reduce the spread of infectious disease among humans. Mathematical models help to better understand the transmission dynamics and spread of infections. For this purpose, in the present article, we have proposed a nonlinear time-delayed SVIRS (Susceptible-Vaccinated-Infected-Recovered-Susceptible) mathematical model with nonlinear type incidence rate and nonlinear type treatment rate. Analytical study of the model shows that model exhibits two types of equilibrium points, namely, disease-free equilibrium and endemic equilibrium. Further, for the long-term behavior of the model, stability of the model is discussed with the help of basic reproduction number R₀ and we showed that disease-free equilibrium is locally asymptotically stable if the basic reproduction number R₀ is less than one and unstable if the basic reproduction number R₀ is greater than one for the time lag τ≥0. Furthermore, when basic reproduction number R₀ is one, using center manifold theory and Casillo-Chavez and Song theorem, we showed that the model undergoes transcritical bifurcation. Moreover, numerical simulations are being carried out using MATLAB 2012b to illustrate the theoretical results.

Keywords: nonlinear incidence rate, nonlinear treatment rate, stability, time delayed SVIRS epidemic model

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Authors: Chien-kuo Chang, Bo-wei Wu, Yi-yun Tang, Min-chiu Wu

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This paper proposes a power equipment diagnosis system based on partial discharge (PD), which is characterized by increasing the readability of experimental data and the convenience of operation. This system integrates a variety of analysis programs of different data formats and different programming languages and then establishes a set of interfaces that can follow and expand the structure, which is also helpful for subsequent maintenance and innovation. This study shows a case of using the developed Convolutional Neural Networks (CNN) to integrate with this system, using the designed model architecture to simplify the complex training process. It is expected that the simplified training process can be used to establish an adaptive deep learning experimental structure. By selecting different test data for repeated training, the accuracy of the identification system can be enhanced. On this platform, the measurement status and partial discharge pattern of each equipment can be checked in real time, and the function of real-time identification can be set, and various training models can be used to carry out real-time partial discharge insulation defect identification and insulation state diagnosis. When the electric power equipment entering the dangerous period, replace equipment early to avoid unexpected electrical accidents.

Keywords: partial discharge, convolutional neural network, partial discharge analysis platform, adaptive deep learning

Procedia PDF Downloads 73

Authors: Akwu N. A., Naidoo Y., Salau V. F., Olofinsan K. A.

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Grewia lasiocarpa E. Mey. ex Harv. (Malvaceae) is a Southern African medicinal plant indigenously used with other plants for birthing problems. The anti-diabetic properties of the hexane, chloroform, and methanol extracts of Grewia lasiocarpa stem bark were assessed using in vitro α-glucosidase enzyme inhibition assay. The predictive in silico drug-likeness and toxicity properties of the phytocompounds were conducted using the pKCSM, ADMElab, and SwissADME computer-aided online tools. The highest α-glucosidase percentage inhibition was observed in the hexane extract (86.76%, IC50= 0.24 mg/mL), followed by chloroform (63.08%, IC50= 4.87 mg/mL) and methanol (53.22%, IC50= 9.41 mg/mL); while acarbose, the standard anti-diabetic drug was (84.54%, IC50= 1.96 mg/mL). The α-glucosidase assay revealed that the hexane extract exhibited the strongest carbohydrate inhibiting capacity and is a better inhibitor than the standard reference drug-acarbose. The computational studies also affirm the results observed in the in vitroα-glucosidaseassay. Thus, the extracts of G. lasiocarpa may be considered a potential plant-sourced compound for treating type 2 diabetes mellitus. This is the first study on the anti-diabetic properties of Grewia lasiocarpa hexane, chloroform, and methanol extracts using in vitro and in silico models.

Keywords: grewia lasiocarpa, α-glucosidase inhibition, anti-diabetes, ADMET

Procedia PDF Downloads 101