Search results for: logistic regression model

Authors: Selvamuthukumaran Thirunavukkarasu, Arivudainambi Sundararajan

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The plant active molecules with their known mode of action are important leads to the development of newer insecticides. Lactone glycoside was identified earlier as the active principle in Cleistanthus collinus (Roxb.) Benth. (Fam: Euphorbiaceae). It possessed feeding deterrent, insecticidal and insect growth regulatory actions at varying concentrations. Deducing its mode of action opens a possibility of its further development. A no-choice leaf disc bioassay was carried out with lactone glycoside at different doses for different instars and Deterrence Indices were worked out. Using regression analysis concentrations imparting 10, 30 and 50 per cent deterrence (DI10, DI30 & DI50) were worked out. At these doses, effect on nutritional indices like Relative Consumption and Growth Rates (RCR & RGR), Efficiencies of Conversion of Ingested and Digested food (ECI & ECD) and Approximate Digestibility (AD) were worked out. The Relative Consumption and Growth Rate of control and lactone glycoside larva were compared by regression analysis. Regression analysis of deterrence indices revealed that the concentrations needed for imparting 50 per cent deterrence was 60.66, 68.47 and 71.10 ppm for third, fourth and fifth instars respectively. Relative consumption rate (RCR) and relative growth rate (RGR) were reduced. This confirmed the antifeedant action of the fraction. Approximate digestibility (AD) was found greater in treatments indicating reduced faeces because of poor digestibility and retention of food in the gut. Efficiency of conversion of both ingested and digested (ECI and ECD) food was also found to be greatly reduced. This indicated presence of toxic action. This was proved by comparing growth efficiencies of control and lactone glycoside treated larvae. Lactone glycoside was found to possess both feeding deterrent and toxic modes of action. Studies on molecular targets based on this preliminary site of action lead to new insecticide development.

Keywords: Spodoptera litura Fabricius, Cleistanthus collinus (Roxb.) Benth, feeding deterrence, mode of action

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Authors: Mayowa Saheed Sanusi A, Musiliu Olushola Sunmonua, Abdulquadri Alakab Owolabi Raheema, Adeyemi Ikimot Adejokea

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The development of healthy cookies for health-conscious consumers cannot be overemphasized in the present global health crisis. This study was aimed to evaluate and model the influence of ripeness levels of papaya puree (unripe, ripe and overripe), oven temperature (130°C, 150°C and 170°C) and oven rack speed (stationary, 10 and 20 rpm) on physicochemical properties of papaya-based cookies using Response Surface Methodology (RSM). The physicochemical properties (baking time, cookies mass, cookies thickness, spread ratio, proximate composition, Calcium, Vitamin C and Total Phenolic Content) were determined using standard procedures. The data obtained were statistically analysed at p≤0.05 using ANOVA. The polynomial regression model of response surface methodology was used to model the physicochemical properties. The adequacy of the models was determined using the coefficient of determination (R²) and the response optimizer of RSM was used to determine the optimum physicochemical properties for the papaya-based cookies. Cookies produced from overripe papaya puree were observed to have the shortest baking time; ripe papaya puree favors cookies spread ratio, while the unripe papaya puree gives cookies with the highest mass and thickness. The highest crude protein content, fiber content, calcium content, Vitamin C and Total Phenolic Content (TPC) were observed in papaya based-cookies produced from overripe puree. The models for baking time, cookies mass, cookies thickness, spread ratio, moisture content, crude protein and TPC were significant, with R2 ranging from 0.73 – 0.95. The optimum condition for producing papaya based-cookies with desirable physicochemical properties was obtained at 149°C oven temperature, 17 rpm oven rack speed and with the use of overripe papaya puree. The Information on the use of puree from unripe, ripe and overripe papaya can help to increase the use of underutilized unripe or overripe papaya and also serve as a strategic means of obtaining a fat substitute to produce new products with lower production cost and health benefit.

Keywords: papaya based-cookies, modeling, response surface methodology, physicochemical properties

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Authors: Irene Carter, Roy Hanes, Judy MacDonald

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Considering that disability is universal and people with disabilities are part of all societies; that there is a connection between the disabled individual and the societal; and that it is society and social arrangements that disable people with impairments, contemporary disability discourse emphasizes the social model of disability to counter medical and rehabilitative models of disability. However, the social model does not go far enough in addressing the issues of oppression and inclusion. The authors indicate that the social model does not specifically or adequately denote the oppression of persons with disabilities, which is a central component of progressive social work practice with people with disabilities. The social model of disability does not go far enough in deconstructing disability and offering social workers, as well as people with disabilities a way of moving forward in terms of practice anchored in individual, familial and societal change. The social model of disability is expanded by incorporating principles of anti-oppression social work practice. Although the contextual analysis of the social model of disability is an important component there remains a need for social workers to provide service to individuals and their families, which will be illustrated through anti-oppressive practice (AOP). By applying an anti-oppressive model of practice to the above definitions, the authors not only deconstruct disability paradigms but illustrate how AOP offers a framework for social workers to engage with people with disabilities at the individual, familial and community levels of practice, promoting an emancipatory focus in working with people with disabilities. An anti- social- oppression social work model of disability connects the day-to-day hardships of people with disabilities to the direct consequence of oppression in the form of ableism. AOP theory finds many of its basic concepts within social-oppression theory and the social model of disability. It is often the case that practitioners, including social workers and psychologists, define people with disabilities’ as having or being a problem with the focus placed upon adjustment and coping. A case example will be used to illustrate how an AOP paradigm offers social work a more comprehensive and critical analysis and practice model for social work practice with and for people with disabilities than the traditional medical model, rehabilitative and social model approaches.

Keywords: anti-oppressive practice, disability, people with disabilities, social model of disability

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Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However, these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: software quality, quality assurance, software certification model, software assessment

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Authors: Hui Wei, Zheng Dong

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Object recognition has long been a challenging task in computer vision. Yet the human brain, with the ability to rapidly and accurately recognize visual stimuli, manages this task effortlessly. In the past decades, advances in neuroscience have revealed some neural mechanisms underlying visual processing. In this paper, we present a novel model inspired by the visual pathway in primate brains. This multi-layer neural network model imitates the hierarchical convergent processing mechanism in the visual pathway. We show that local image features generated by this model exhibit robust discrimination and even better generalization ability compared with some existing image descriptors. We also demonstrate the application of this model in an object recognition task on image data sets. The result provides strong support for the potential of this model.

Keywords: biological model, feature extraction, multi-layer neural network, object recognition

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Authors: Olga Santesteban, Glorisa Canino, Hector R. Bird, Cristiane S. Duarte

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Objective: To address whether harsh discipline is associated with disruptive behavior disorders (DBD) in Puerto Rican children over time. Background: Both cross-sectional and longitudinal studies report that rates of DBD vary by gender, age and other demographics, being more frequent among boys, later in life and among those who live in urban areas. Also, the literature supports the direct, positive association between harsh discipline and externalizing behaviors. Nevertheless, scholars have underscored the important role of race and ethnicity in understanding discipline effects on children. The impact of harsh discipline in a Puerto Rican population remains to be studied. Methods: Sample: This is a secondary analysis of the Boricua Youth Study which assessed yearly (3 times) Puerto Rican children aged 5-15 in two different sites: San Juan (Puerto Rico) and the South Bronx (NY), N=2951. Participants that did not have scores of harsh discipline in the 3 waves were excluded for this analysis (N=2091). Main Measures: a) Harsh Discipline (Parent report) was measured using 6 items from the “Parental Discipline Scale” that measures various forms of punishment, including physical and verbal abuse, and withholding affection; b) Disruptive Behavior Disorder (Parent report): Parent version of the Diagnostic Interview Schedule for Children-IV (DISC-IV) was used to asses children’s conduct disorders; c) Demographic factors: Child gender, child age, family income, marital status; d) Parental factors: parental psychopathology, parental monitoring, familism, parent support; e) Children characteristics: Controlling for any diagnostic at wave 1 (internalizing or externalizing). Data Analysis: Logistic regression was carried out relating the likelihood of DBD to harsh discipline along waves controlling for potential confounders as demographics, child and parent characteristics. Results: There were no significant differences in harsh discipline by site in wave 1 and wave 2 but there was a significant difference in wave 3. Also, there were no significant differences in DBD by site in wave 1 and wave 2 but there was a significant difference in wave 3. There was a significant difference of discipline by gender and age in all the waves. We calculated unadjusted (OR) and adjusted (AOD) and 95% confidence intervals (95%CI) showing the relation between harsh discipline at wave 1 and the presence of child disruptive behavior disorder at wave 3 for both South Bronx and Puerto Rico. There was an association between harsh discipline and the likelihood of having DBD in The Bronx (AOR=1.76; 95%CI=1.13-2.74, p.013) and in Puerto Rico (AOR=2.17; 95%CI=1.28-3.67, p.004) having controlled for demographic, parental and individual factors. Conclusions: Context may be an important differential factor shaping the potential risk of harsh discipline toward DBD for Puerto Rican children.

Keywords: disruptive behavior disorders, harsh discipline, puerto rican, psychological education

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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Authors: Irsha Dhotre

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Cymbopogon citratus is generally known as Indian Lemongrass and is widely applicable in the cosmetic, pharmaceutical, dairy puddings, and food industries. To enhance the quality of extraction, microwave-oven-aided hydro distillation processes were implemented. The basic parameter which influences the rate of extraction is considered, such as the temperature of extraction, the time required for extraction, and microwave-oven power applied. Locally available CKP 25 Cymbopogon citratus was used for the extraction of essential oil. Optimization of Extractions Parameters and full factorial Box–Behnken design (BBD) evaluated by using Design expert 13 software. The regression model revealed that the optimum parameters required for extractions are a temperature of 35℃, a time of extraction of 130 minutes, and microwave-oven power of 700 W. The extraction efficiency of yield is 4.76%. Gas Chromatography-Mass Spectroscopy (GC-MS) analysis confirmed the significant components present in the extraction of lemongrass oil.

Keywords: Box–Behnken design, Cymbopogon citratus, hydro distillation, microwave-oven, response surface methodology

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Authors: Myungjin Lee, Daegun Han, Jongsung Kim, Soojun Kim, Hung Soo Kim

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Recently, the localized heavy rainfall and typhoons are frequently occurred due to the climate change and the damage is becoming bigger. Therefore, we may need a more accurate prediction of the rainfall and runoff. However, the gauge rainfall has the limited accuracy in space. Radar rainfall is better than gauge rainfall for the explanation of the spatial variability of rainfall but it is mostly underestimated with the uncertainty involved. Therefore, the ensemble of radar rainfall was simulated using error structure to overcome the uncertainty and gauge rainfall. The simulated ensemble was used as the input data of the rainfall-runoff models for obtaining the ensemble of runoff hydrographs. The previous studies discussed about the accuracy of the rainfall-runoff model. Even if the same input data such as rainfall is used for the runoff analysis using the models in the same basin, the models can have different results because of the uncertainty involved in the models. Therefore, we used two models of the SSARR model which is the lumped model, and the Vflo model which is a distributed model and tried to simulate the optimum runoff considering the uncertainty of each rainfall-runoff model. The study basin is located in Han river basin and we obtained one integrated runoff hydrograph which is an optimum runoff hydrograph using the blending methods such as Multi-Model Super Ensemble (MMSE), Simple Model Average (SMA), Mean Square Error (MSE). From this study, we could confirm the accuracy of rainfall and rainfall-runoff model using ensemble scenario and various rainfall-runoff model and we can use this result to study flood control measure due to climate change. Acknowledgements: This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 18AWMP-B083066-05).

Keywords: radar rainfall ensemble, rainfall-runoff models, blending method, optimum runoff hydrograph

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Authors: Saba Rahman, Arvind K. Jain, S. D. Bharti, T. K. Datta

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The present study compares the semi-empirical wake-oscillator models that are used to predict vortex-induced vibration of structures. These models include those proposed by Facchinetti, Farshidian, and Dolatabadi, and Skop and Griffin. These models combine a wake oscillator model resembling the Van der Pol oscillator model and a single degree of freedom oscillation model. In order to use these models for estimating the top displacement of chimneys, the first mode vibration of the chimneys is only considered. The modal equation of the chimney constitutes the single degree of freedom model (SDOF). The equations of the wake oscillator model and the SDOF are simultaneously solved using an iterative procedure. The empirical parameters used in the wake-oscillator models are estimated using a newly developed approach, and response is compared with experimental data, which appeared comparable. For carrying out the iterative solution, the ode solver of MATLAB is used. To carry out the comparative study, a tall concrete chimney of height 210m has been chosen with the base diameter as 28m, top diameter as 20m, and thickness as 0.3m. The responses of the chimney are also determined using the linear model proposed by E. Simiu and the deterministic model given in Eurocode. It is observed from the comparative study that the responses predicted by the Facchinetti model and the model proposed by Skop and Griffin are nearly the same, while the model proposed by Fashidian and Dolatabadi predicts a higher response. The linear model without considering the aero-elastic phenomenon provides a less response as compared to the non-linear models. Further, for large damping, the prediction of the response by the Euro code is relatively well compared to those of non-linear models.

Keywords: chimney, deterministic model, van der pol, vortex-induced vibration

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Authors: Tengqin Han

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Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

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Authors: Semra Çoruh, Yusuf Tibet

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Dyes are widely used in industries such as textiles, paper, paints, leather, rubber, plastics, cosmetics, food, and drug etc, to color their products. Due to their chemical structures, dyes are resistant to fading on exposure to light, water and many chemicals and, therefore, are difficult to be decolorized once released into the aquatic environment. Many of the organic dyes are hazardous and may affect aquatic life and even the food chain. This study deals with the adsorption of malachite green dye onto fly ash and red mud. The effects of experimental factors (adsorbent dosage, initial concentration, pH and temperature) on the adsorption process were examined by using 24 full factorial design. The results were statistically analyzed by using the student’s t-test, analysis of variance (ANOVA) and an F-test to define important experimental factors and their levels. A regression model that considers the significant main and interaction effects was suggested. The results showed that initial dye concentration an pH is the most significant factor that affects the removal of malachite green.

Keywords: malachite green, adsorption, red mud, fly ash, full factorial design

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Authors: Mustafa Kamoona, Mohamed El-Sharkawy

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Although the latest Wireless Local Area Network technology Wi-Fi 802.11i standard addresses many of the security weaknesses of the antecedent Wired Equivalent Privacy (WEP) protocol, there are still scenarios where the network security are still vulnerable. The first security model that 802.11i offers is the Personal model which is very cheap and simple to install and maintain, yet it uses a Pre Shared Key (PSK) and thus has a low to medium security level. The second model that 802.11i provide is the Enterprise model which is highly secured but much more expensive and difficult to install/maintain and requires the installation and maintenance of an authentication server that will handle the authentication and key management for the wireless network. A central issue with the personal model is that the PSK needs to be shared with all the devices that are connected to the specific Wi-Fi network. This pre-shared key, unless changed regularly, can be cracked using offline dictionary attacks within a matter of hours. The key is burdensome to change in all the connected devices manually unless there is some kind of algorithm that coordinate this PSK update. The key idea of this paper is to propose a new algorithm that proactively and effectively coordinates the pre-shared key generation, management, and distribution in the cheap WPA/WPA2 personal security model using only a DD-WRT router.

Keywords: Wi-Fi, WPS, TLS, DD-WRT

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Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

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In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

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Authors: Dena Alhaloul

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The Middle East and North Africa (MENA) region is characterized by diverse cultures, economies, and social structures. Fertility rates in MENA have seen significant changes over time, with variations among countries and subregions. Understanding fertility patterns in this region is essential due to its impact on demographic dynamics, healthcare, labor markets, and social policies. Rising or declining fertility rates have far-reaching consequences for the region's socioeconomic development. The main thrust of this study is to comprehensively examine fertility rates in the Middle East and North Africa (MENA) region. It aims to understand the distribution, determinants, and temporal trends of fertility rates in MENA countries. The study seeks to provide insights into the factors influencing fertility decisions, assess how fertility rates have evolved over time, and potentially develop statistical models to characterize these trends. As for the methodology of the study, the study uses descriptive statistics to summarize and visualize fertility rate data. It also uses regression analyses to identify determinants of fertility rates as well as statistical modeling to characterize temporal trends in fertility rates. The conclusion of this study The research will contribute to a deeper understanding of fertility dynamics in the MENA region, shedding light on the distribution of fertility rates, their determinants, and historical trends.

Keywords: fertility, distribution, modeling, regression

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Authors: Keerthi S. Shetty, Annappa Basava

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In recent years, modelling of biological systems represented by biochemical reactions has become increasingly important in Systems Biology. Biological systems represented by biochemical reactions are highly stochastic in nature. Probabilistic model is often used to describe such systems. One of the main challenges in Systems biology is to combine absolute experimental data into probabilistic model. This challenge arises because (1) some molecules may be present in relatively small quantities, (2) there is a switching between individual elements present in the system, and (3) the process is inherently stochastic on the level at which observations are made. In this paper, we describe a novel idea of combining absolute experimental data into probabilistic model using tool R2. Through a case study of the Transcription Process in Prokaryotes we explain how biological systems can be written as probabilistic program to combine experimental data into the model. The model developed is then analysed in terms of intrinsic noise and exact sampling of switching times between individual elements in the system. We have mainly concentrated on inferring number of genes in ON and OFF states from experimental data.

Keywords: systems biology, probabilistic model, inference, biology, model

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Authors: Elena Puica

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This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

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Authors: Ana Rahma Yuniarti, Ki Moo Lim

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Slowed myocardial conduction velocity (CV) and shortened action potential duration (APD) due to some reason are associated with an increased risk of re-entrant excitation, predisposing to cardiac arrhythmia. That is because both of CV reduction and APD shortening induces shortening of wavelength. In this study, we investigated quantitatively the cardiac mechanical responses under various CV and APD using multi-scale computational model of the heart. The model consisted of electrical model coupled with the mechanical contraction model together with a lumped model of the circulatory system. The electrical model consisted of 149.344 numbers of nodes and 183.993 numbers of elements of tetrahedral mesh, whereas the mechanical model consisted of 356 numbers of nodes and 172 numbers of elements of hexahedral mesh with hermite basis. We performed the electrical simulation with two scenarios: 1) by varying the CV values with constant APD and 2) by varying the APD values with constant CV. Then, we compared the electrical and mechanical responses for both scenarios. Our simulation showed that faster CV and longer APD induced largest resultants wavelength and generated better cardiac pumping efficacy by increasing the cardiac output and consuming less energy. This is due to the long wave propagation and faster conduction generated more synchronous contraction of whole ventricle.

Keywords: conduction velocity, action potential duration, mechanical contraction model, circulatory model

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Authors: Sree Sanyal

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Research in ageing often highlights the age-related health dimension more than the psycho-social characteristics of the elderly, which also influences and challenges the health outcomes. Multimorbidity is defined as the person having more than one chronic non-communicable diseases and their prevalence increases with ageing. The study aims to evaluate the influence of social ties on self-reported prevalence of multimorbidity (selected chronic non-communicable diseases) among the selected states of elderly population in India. The data is accessed from Building Knowledge Base on Population Ageing in India (BKPAI), collected in 2011 covering the self-reported chronic non-communicable diseases like arthritis, heart disease, diabetes, lung disease with asthma, hypertension, cataract, depression, dementia, Alzheimer’s disease, and cancer. The data of the above diseases were taken together and categorized as: ‘no disease’, ‘one disease’ and ‘multimorbidity’. The predicted variables were demographic, socio-economic, residential types, and the variable of social ties includes social support, social engagement, perceived support, connectedness, and importance of the elderly. Predicted probability for multiple logistic regression was used to determine the background characteristics of the old in association with chronic morbidities showing multimorbidity. The finding suggests that 24.35% of the elderly are suffering from multimorbidity. Research shows that with reference to ‘no disease’, according to the socio-economic characteristics of the old, the female oldest old (80+) from others in caste and religion, widowed, never had any formal education, ever worked in their life, coming from the second wealth quintile standard, from rural Maharashtra are more prone with ‘one disease’. From the social ties background, the elderly who perceives they are important to the family, after getting older their decision-making status has been changed, prefer to stay with son and spouse only, satisfied with the communication from their children are more likely to have less single morbidity and the results are significant. Again, with respect to ‘no disease’, the female oldest old (80+), who are others in caste, Christian in religion, widowed, having less than 5 years of education completed, ever worked, from highest wealth quintile, residing in urban Kerala are more associated with multimorbidity. The elderly population who are more socially connected through family visits, public gatherings, gets support in decision making, who prefers to spend their later years with son and spouse only but stays alone shows lesser prevalence of multimorbidity. In conclusion, received and perceived social integration and support from associated neighborhood in the older days, knowing about their own needs in life facilitates better health and wellbeing of the elderly population in selected states of India.

Keywords: morbidity, multi-morbidity, prevalence, social ties

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Authors: M. Mohsin Munir, Taimoor Ahmad, Javed Munir, Usman Rashid

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Determination of maximum elevation of a flowing fluid due to sudden rejection of load in a hydropower facility is of great interest to hydraulic engineers to ensure safety of the hydraulic structures. Several mathematical models exist that employ one-dimensional modeling for the determination of surge but none of these perfectly simulate real-time circumstances. The paper envisages investigation of surge inception and propagation for a Low Head Hydropower project using Computational Fluid Dynamics (CFD) analysis on FLOW-3D software package. The fluid dynamic model utilizes its analysis for surge by employing Reynolds’ Averaged Navier-Stokes Equations (RANSE). The CFD model is designed for a case study at Taunsa hydropower Project in Pakistan. Various scenarios have run through the model keeping in view upstream boundary conditions. The prototype results were then compared with the results of physical model testing for the same scenarios. The results of the numerical model proved quite accurate coherence with the physical model testing and offers insight into phenomenon which are not apparent in physical model and shall be adopted in future for the similar low head projects limiting delays and cost incurred in the physical model testing.

Keywords: surge, FLOW-3D, numerical model, Taunsa, RANSE

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Authors: Ting Shen

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Whether resource matters to school has been a topic of intense debate since 1960s. Educational researchers and policy makers have been particularly interested in knowing the return or payoff of Per-Pupil Expenditure (PPE) on improving students’ achievement. However, the evidence on the effect of PPE has been mixed and the size of the effect is also unknown. With regard to the methods, it is well-known that meta-analysis study is superior to individual study and it is also preferred to vote counting method in terms of scientifically weighting the evidence by the sample size. This meta-analysis study aims to provide a synthesized evidence on the correlation between PPE and student academic achievement using recent study data from 1990s to 2010s. Meta-analytical approach of fixed- and random-effects models will be utilized in addition to a meta regression with predictors of year, location, region and school type. A preliminary result indicates that by and large there is no statistically significant relationship between per pupil expenditure and student achievement, but location seems to have a mediating effect.

Keywords: per pupil expenditure, student academic achievement, multilevel model, meta-analysis

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Authors: Zuoyong Zhang, Min Yu, Jinlong Zhao, Shudong He

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The Maillard reaction can produce the flavor enhancing substance through the chemical crosslinking between free amino group of the protein or polypeptide with the carbonyl of the reducing sugar. In this research, solutions of rapeseed meal peptide and D-xylose with or without L-cysteine (RXC or RX) were heated over a range of temperatures (80-140 °C) for 2 h. It was observed that RXs had a severe browning,while RXCs accompanied by more pH decrement with the temperature increasing. Then the correlation among data of quantitative sensory descriptive analysis, free amino acid (FAA) and GC–MS of RXCs and RXs were analyzed using the partial least square regression method. Results suggested that the Maillard reaction product (MRPs) with cysteine formed at 120 °C (RXC-120) had greater sensory properties especially meat-like flavor compared to other MRPs. Meanwhile, it revealed that glutamic and glycine not only had a positive contribution to meaty aroma but also showed a significant and positive influence on umami taste of RXs based on the FAA data. Moreover, the sulfur-containing compounds showed a significant positive correlation with the meat-like flavor of RXCs, while RXs depended on furans and nitrogenous-containing compounds with more caramel-like flavor. Therefore, a MRP with strong meaty flavor could be obtained at 120 °C by addition of cysteine.

Keywords: rapeseed meal, Maillard reaction, sensory characteristics, FAA, GC–MS, partial least square regression

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Authors: Wisam Ismail, Chole Wright, Elizabeth Baker, Cathy Tait, Mohamed Salhab, Richard Linforth

Abstract:

Background: Post-mastectomy breast reconstruction is an important treatment option for women with breast cancer with psychosocial, emotional and quality of life benefits. Despite this, Asian patients are one-fifth as likely as Caucasian patients to undergo reconstruction after mastectomy. Aim: This study aimed to assess the difference in breast reconstruction rates between Asian and Caucasian patients treated at Bradford Teaching Hospitals between May 2011 – December 2015.The long-term goal is to equip healthcare professionals to improve breast cancer treatment outcome by increasing breast reconstruction rates in this sub-population. Methods: All patients undergoing mastectomy were identified using a prospectively collected departmental database. Further data was obtained via retrospective electronic case note review. Bradford city population is about 530.000 by the end of 2015, with 67.44% of the city's population was White ethnic groups and 26.83% Asian Ethnic Groups (UK population consensus). The majority of Asian population speaks Urdu, hence an Urdu speaking breast care nurse was appointed to facilitate communications and deliver a better understanding of the reconstruction options and pathways. Statistical analysis was undertaken using the SAS program. Patients were stratified by age, self-reported ethnicity, axillary surgery and reconstruction. Relative odds were calculated using univariate and multivariate logistic regression analyses with adjustment for known confounders. An Urdu speaking breast care nurse was employed throughout this period to facilitate communication and patient decision making. Results: 506 patients underwent Mastectomy over 5 years. 72 (14%) Asian v. 434 (85%) Caucasian. Overall median age is 64 years (SD1.1). Asian median age is 62 (SD0.9), versus Caucasian 65 (SD1.2). Total axillary clearance rate was 30% (42% Asian v.30% Caucasian). Overall reconstruction rate was 126 patients (28.9%).Only 6 of 72 Asian patients (<1%) underwent breast reconstruction versus 121of 434 Caucasian (28%) (p < 0.04), Odds ratio 0.68, (95% confidence interval 0.57-0.79). Conclusions: There is a significant difference in post-mastectomy reconstruction rates between Asian and Caucasian patients. This difference is likely to be multi-factorial. Higher rates of axillary clearance in Asian patients might suggest later disease presentation and/or higher rates of subsequent adjuvant therapy, both of which, can impact on the suitability of breast reconstruction. Strategies aimed at reducing racial disparities in breast reconstruction should include symptom awareness to enable earlier presentation and facilitated communication to ensure informed decision-making.

Keywords: aesthetic, Asian, breast, reconstruction

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Authors: Fagner O. Serrano, Danielle R. Bouchard, Todd A. Duhame

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Walking cadence (steps/min) is an effective way to prescribe exercise so an individual can reach a moderate intensity, which is recommended to optimize health benefits. To our knowledge, there is no study on the required walking cadence to reach a moderate intensity for people that present chronic conditions or risk factors for chronic conditions such as Cardiovascular Diseases (CVD). The objectives of this study were: 1- to identify the walking cadence needed for people at risk of CVD to a reach moderate intensity, and 2- to develop and test an equation using clinical variables to help professionals working with individuals at risk of CVD to estimate the walking cadence needed to reach moderate intensity. Ninety-one people presenting a minimum of two risk factors for CVD completed a medically supervised graded exercise test to assess maximum oxygen consumption at the first visit. The last visit consisted of recording walking cadence using a foot pod Garmin FR-60 and a Polar heart rate monitor, aiming to get participants to reach 40% of their maximal oxygen consumption using a portable metabolic cart on an indoor flat surface. The equation to predict the walking cadence needed to reach moderate intensity in this sample was developed as follows: The sample was randomly split in half and the equation was developed with one half of the participants, and validated using the other half. Body mass index, height, stride length, leg height, body weight, fitness level (VO2max), and self-selected cadence (over 200 meters) were measured using objective measured. Mean walking cadence to reach moderate intensity for people age 64.3 ± 10.3 years old at risk of CVD was 115.8  10.3 steps per minute. Body mass index, height, body weight, fitness level, and self-selected cadence were associated with walking cadence at moderate intensity when evaluated in bivariate analyses (r ranging from 0.22 to 0.52; all P values ≤0.05). Using linear regression analysis including all clinical variables associated in the bivariate analyses, body weight was the significant predictor of walking cadence for reaching a moderate intensity (ß=0.24; P=.018) explaining 13% of walking cadence to reach moderate intensity. The regression model created was Y = 134.4-0.24 X body weight (kg).Our findings suggest that people presenting two or more risk factors for CVD are reaching moderate intensity while walking at a cadence above the one officially recommended (116 steps per minute vs. 100 steps per minute) for healthy adults.

Keywords: cardiovascular disease, moderate intensity, older adults, walking cadence

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Authors: Lennart Dimberg, Lala Joulha Ian

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Introduction: Overweight (BMI 25-30) and obesity (BMI 30+) have consistently been associated with cardiovascular (CV) risk and death since the Framingham heart study in 1948, and BMI was included in the original Framingham risk score (FRS). Background: Myocardial infarction (MI) poses a serious threat to the patient's life. In addition to BMI, several other indices of overweight have been presented and argued to replace FRS as more relevant measures of CV risk. These indices include waist circumference (WC), waist/hip ratio (WHR), sagittal abdominal diameter (SAD), and sagittal abdominal diameter to height (SADHtR). Specific research question: The research question of this study is to evaluate the interrelationship between the various body measurements, BMI, WC, WHR, SAD, and SADHtR, and which measurement is strongly associated with MI and death. Methods: In 1993, 1,000 middle-aged Caucasian, randomly selected working men of the Swedish Volvo-Renault cohort were surveyed at a nurse-led health examination with a questionnaire, EKG, laboratory tests, blood pressure, height, weight, waist, and sagittal abdominal diameter measurements. Outcome data of myocardial infarction over 28 years come from Swedeheart (the Swedish national myocardial infarction registry) and the Swedish death registry. The Aalen-Johansen and Kaplan–Meier methods were used to estimate the cumulative incidences of MI and death. Multiple logistic regression analyses were conducted to compare BMI with the other four body measurements. The risk for the various measures of obesity was calculated with outcomes of accumulated first-time myocardial infarction and death as odds ratios (OR) in quartiles. The ORs between the 4th and the 1st quartile of each measure were calculated to estimate the association between the body measurement variables and the probability of cumulative incidences of myocardial infarction (MI) over time. Double-sided P values below 0.05 will be considered statistically significant. Unadjusted odds ratios were calculated for obesity indicators, MI, and death. Adjustments for age, diabetes, SBP, and the ratio of total cholesterol/HDL-C and blue/white collar status were performed. Results: Out of 1000 people, 959 subjects had full information about the five different body measurements. Of those, 90 participants had a first MI, and 194 persons died. The study showed that there was a high and significant correlation between the five different body measurements, and they were all associated with CVD risk factors. All body measurements were significantly associated with MI, with the highest (OR=3.6) seen for SADHtR and WC. After adjustment, all but SADHtR remained significant with weaker ORs. As for all-cause mortality, WHR (OR=1.7), SAD (OR=1.9), and SADHtR (OR=1.6) were significantly associated, but not WC and BMI. However, after adjustment, only WHR and SAD were significantly associated with death, but with attenuated ORs.

Keywords: BMI, death, epidemiology, myocardial infarction, risk factor, sagittal abdominal diameter, sagittal abdominal diameter to height, waist circumference, waist-hip ratio

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Authors: Yangyang Zhou

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Rapid urbanization has caused the urban heat island effect, which will threaten the physical and mental health of urban dwellers, and blue-green spaces can mitigate the thermal environment effectively. In this study, we calculated the average LST from 2013 to 2022, Northeastmonsoon and Southwestmonsoon of Singapore, and compared the cooling effect differences of the four blue-green spaces. Then, spatial correlation and spatial autoregression model were conducted between cooling distance intensity (CDI) and 11 independent variables. The results reveal that (1) the highest mean land surface temperature (LST) in all years, Northeast monsoon and Southwest monsoon can reach 42.8 ℃, 41.6 ℃, and 42.9 ℃, respectively. (2) the temperature-changing tendency in the three time periods is similar to each other, while the overall LST changing trends of the Southwest monsoon are lower than all year and Northeast monsoon. (3) the cooling distance of the sea can reach 1200 m, and CEI is highly positively correlated with NDBI and BuildD and highly negatively correlated with SVF, NDVI and TreeH. LISA maps showed that the zones that passed the significance test between CDI, NDBI and BuildD were nearly the same locations; the same phenomenon also happened between CDI and SVF, NDVI and TreeH. (4) SLM had better regression results than SEM in all the regions; only 3 independent variables passed the significance test in region 1, and most independent variables can pass the significance test in other regions. Variables DIST and NDBI were significantly affecting the CDI in all the regions. In the whole region, all the variables passed the significance test, and NDBI (1.61), SVF (0.95) and NDVI (0.5) had the strongest influence on CDI.

Keywords: cooling effect, land surface temperature, thermal environment mitigation, spatial autoregression model

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Authors: T. M. Ismail, M. A. El-Salam

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A mathematical model study was carried out to investigate gasification of biomass fuels using high-temperature air and steam as a gasifying agent using high-temperature air up to 1000°C. In this study, a 2D computational fluid dynamics model was developed to study the gasification process in an updraft gasifier, considering drying, pyrolysis, combustion, and gasification reactions. The gas and solid phases were resolved using a Euler−Euler multiphase approach, with exchange terms for the momentum, mass, and energy. The standard k−ε turbulence model was used in the gas phase, and the particle phase was modeled using the kinetic theory of granular flow. The results show that the present model giving a promising way in its capability and sensitivity for the parameter effects that influence the gasification process.

Keywords: computational fluid dynamics, gasification, biomass fuel, fixed bed gasifier

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Authors: Dheyaa Wajid Abbood, Hanan Hussien Abood

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Stepped cascade has been utilized as a hydraulic structure for years. It has proven to be the least costly aeration system in replenishing dissolved oxygen. Numerical modeling of stepped cascade with end sill is very complicated and challenging because of the high roughness and velocity re circulation regions. Volume of fluid multiphase flow model (VOF) is used .The realizable k-ξ model is chosen to simulate turbulence. The computational results are compared with lab-scale stepped cascade data. The lab –scale model was constructed in the hydraulic laboratory, Al-Mustansiriya University, Iraq. The stepped cascade was 0.23 m wide and consisted of 3 steps each 0.2m high and 0.6 m long with variable end sill. The discharge was varied from 1 to 4 l/s. ANSYS has been employed to simulate the experimental data and their related results. This study shows that ANSYS is able to predict results almost the same as experimental findings in some regions of the structure.

Keywords: stepped cascade weir, aeration, multiphase flow model, ansys

Procedia PDF Downloads 336

Authors: Debi Konukcu Onal, Tarkan Cavusoglu

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In modern societies, the costs of public goods and services are shared through taxes paid by citizens. However, taxation has always been a frictional issue, as tax obligations are perceived to be a financial burden for taxpayers rather than being merit that fulfills the redistribution, regulation and stabilization functions of the welfare state. The tax compliance literature evolves into discussing why people still pay taxes in systems with low costs of legal enforcement. Related empirical and theoretical works show that a wide range of socially oriented behavioral factors can stimulate voluntary compliance and subversive effects as well. These behavioral motivations are argued to be driven by self-enforcing rules of informal institutions, either independently or through interactions with legal orders set by formal institutions. The main focus of this study is to investigate empirically whether institutional particularities have a significant role in explaining the cross-country differences in the tax noncompliance levels. A part of the controversy about the driving forces behind tax noncompliance may be attributed to the lack of empirical evidence. Thus, this study aims to fill this gap through regression estimates, which help to trace the link between institutional quality and noncompliance on a cross-country basis. Tax evasion estimates of Buehn and Schneider is used as the proxy measure for the tax noncompliance levels. Institutional quality is quantified by three different indicators (percentile ranks of Worldwide Governance Indicators, ratings of the International Country Risk Guide, and the country ratings of the Freedom in the World). Robust Least Squares and Threshold Regression estimates based on the sample of the Organization for Economic Co-operation and Development (OECD) countries imply that tax compliance increases with institutional quality. Moreover, a threshold-based asymmetry is detected in the effect of institutional quality on tax noncompliance. That is, the negative effects of tax burdens on compliance are found to be more pronounced in countries with institutional quality below a certain threshold. These findings are robust to all alternative indicators of institutional quality, supporting the significant interaction of societal values with the individual taxpayer decisions.

Keywords: institutional quality, OECD economies, tax compliance, tax evasion

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Authors: R. Monteiro, A. Abarca

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Large scale seismic risk assessment has become increasingly popular to evaluate the physical vulnerability of a given region to seismic events, by putting together hazard, exposure and vulnerability components. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), explains the steps and expected results for the development of an integrated seismic risk model for assessment of the vulnerability of residential buildings in Northern Algeria. For this purpose, the model foresees the consideration of an updated seismic hazard model, as well as ad-hoc exposure and physical vulnerability models for local residential buildings. The first results of this endeavor, such as the hazard model and a specific taxonomy to be used for the exposure and fragility components of the model are presented, using as starting point the province of Blida, in Algeria. Specific remarks and conclusions regarding the characteristics of the Northern Algerian in-built are then made based on these results.

Keywords: Northern Algeria, risk, seismic hazard, vulnerability

Procedia PDF Downloads 201