Search results for: survival predictive values
Commenced in January 2007
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Paper Count: 8798

Search results for: survival predictive values

8378 Values in Higher Education: A Case Study of Higher Education Students

Authors: Bahadır Erişti

Abstract:

Values are the behavioral procedures of society based communication and interaction process that includes social and cultural backgrounds. The policy of learning and teaching in higher education is oriented towards constructing knowledge and skills, based on theorist framework of cognitive and psychomotor aspects. This approach makes people not to develop generosity, empathy, affection, solidarity, justice, equality and so on. But the sensorial gains of education system provide the integrity of society interaction. This situation carries out the necessity of values education’s in higher education. The current study aims to consider values education from the viewpoint of students in higher education. Within the framework of the current study, an open ended survey based scenario of higher education students was conducted with the students’ social, cognitive, affective and moral developments. In line with this purpose, the following situations of the higher education system were addressed based on the higher education students’ viewpoint: The views of higher education students’ regarding values that are tried to be gained at the higher education system; The higher education students’ suggestions regarding values education at the higher education system; The views of the higher education students’ regarding values that are imposed at the higher education system. In this study, descriptive qualitative research method was used. The study group of the research is composed of 20 higher education postgraduate students at Curriculum and Instruction Department of Educational Sciences at Anadolu University. An open-ended survey was applied for the purpose of collecting qualitative data. As a result of the study, value preferences, value judgments and value systems of the higher education students were constructed on prioritizes based on social, cultural and economic backgrounds and statues. Multi-dimensional process of value education in higher education need to be constructed on higher education-community-cultural background cooperation. Thus, the act of judgement upon values between higher education students based on the survey seems to be inherent in the system of education itself. The present study highlights the students’ value priorities and importance of values in higher education. If the purpose of the higher education system gains on values, it is possible to enable society to promote humanity.

Keywords: higher education, value, values education, values in higher education

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8377 Performance and Limitations of Likelihood Based Information Criteria and Leave-One-Out Cross-Validation Approximation Methods

Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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8376 Assessing P0.1 and Occlusion Pressures in Brain-Injured Patients on Pressure Support Ventilation: A Study Protocol

Authors: S. B. R. Slagmulder

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Monitoring inspiratory effort and dynamic lung stress in patients on pressure support ventilation in the ICU is important for protecting against self inflicted lung injury (P-SILI) and diaphragm dysfunction. Strategies to address the detrimental effects of respiratory drive and effort can lead to improved patient outcomes. Two non-invasive estimation methods, occlusion pressure (Pocc) and P0.1, have been proposed for achieving lung and diaphragm protective ventilation. However, their relationship and interpretation in neuro ICU patients is not well understood. P0.1 is the airway pressure measured during a 100-millisecond occlusion of the inspiratory port. It reflects the neural drive from the respiratory centers to the diaphragm and respiratory muscles, indicating the patient's respiratory drive during the initiation of each breath. Occlusion pressure, measured during a brief inspiratory pause against a closed airway, provides information about the inspiratory muscles' strength and the system's total resistance and compliance. Research Objective: Understanding the relationship between Pocc and P0.1 in brain-injured patients can provide insights into the interpretation of these values in pressure support ventilation. This knowledge can contribute to determining extubation readiness and optimizing ventilation strategies to improve patient outcomes. The central goal is to asses a study protocol for determining the relationship between Pocc and P0.1 in brain-injured patients on pressure support ventilation and their ability to predict successful extubation. Additionally, comparing these values between brain-damaged and non-brain-damaged patients may provide valuable insights. Key Areas of Inquiry: 1. How do Pocc and P0.1 values correlate within brain injury patients undergoing pressure support ventilation? 2. To what extent can Pocc and P0.1 values serve as predictive indicators for successful extubation in patients with brain injuries? 3. What differentiates the Pocc and P0.1 values between patients with brain injuries and those without? Methodology: P0.1 and occlusion pressures are standard measurements for pressure support ventilation patients, taken by attending doctors as per protocol. We utilize electronic patient records for existing data. Unpaired T-test will be conducted to compare P0.1 and Pocc values between both study groups. Associations between P0.1 and Pocc and other study variables, such as extubation, will be explored with simple regression and correlation analysis. Depending on how the data evolve, subgroup analysis will be performed for patients with and without extubation failure. Results: While it is anticipated that neuro patients may exhibit high respiratory drive, the linkage between such elevation, quantified by P0.1, and successful extubation remains unknown The analysis will focus on determining the ability of these values to predict successful extubation and their potential impact on ventilation strategies. Conclusion: Further research is pending to fully understand the potential of these indices and their impact on mechanical ventilation in different patient populations and clinical scenarios. Understanding these relationships can aid in determining extubation readiness and tailoring ventilation strategies to improve patient outcomes in this specific patient population. Additionally, it is vital to account for the influence of sedatives, neurological scores, and BMI on respiratory drive and occlusion pressures to ensure a comprehensive analysis.

Keywords: brain damage, diaphragm dysfunction, occlusion pressure, p0.1, respiratory drive

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8375 Economic Integration vs. Conflicts in Northeast Asia

Authors: Heeho Kim, Byeong-Hae Sohn

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This study has examined the culture commonality of Northeast Asian countries based on Confucian values, and their relations to institutional economic integration. This study demonstrates that Confucian values inherent in the Northeast Asian countries have served as the cultural ethos for the rapid economic growth of this region since the 1960s and will be able to form the foundation of Northeast Asian values in the future. This paper re-appreciates these cultural values as a necessary condition for regional integration to catalyze the stagnated discussions about economic integration and extends its inter-weaving connection role for intra-regional transaction among China, Japan and Korea.

Keywords: Confucianism, Northeast Asia, economic integration, economic growth, regional conflicts

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8374 Modelling of Moisture Loss and Oil Uptake during Deep-Fat Frying of Plantain

Authors: James A. Adeyanju, John O. Olajide, Akinbode A. Adedeji

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A predictive mathematical model based on the fundamental principles of mass transfer was developed to simulate the moisture content and oil content during Deep-Fat Frying (DFF) process of dodo. The resulting governing equation, that is, partial differential equation that describes rate of moisture loss and oil uptake was solved numerically using explicit Finite Difference Technique (FDT). Computer codes were written in MATLAB environment for the implementation of FDT at different frying conditions and moisture loss as well as oil uptake simulation during DFF of dodo. Plantain samples were sliced into 5 mm thickness and fried at different frying oil temperatures (150, 160 and 170 ⁰C) for periods varying from 2 to 4 min. The comparison between the predicted results and experimental data for the validation of the model showed reasonable agreement. The correlation coefficients between the predicted and experimental values of moisture and oil transfer models ranging from 0.912 to 0.947 and 0.895 to 0.957, respectively. The predicted results could be further used for the design, control and optimization of deep-fat frying process.

Keywords: frying, moisture loss, modelling, oil uptake

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8373 Classification of Red, Green and Blue Values from Face Images Using k-NN Classifier to Predict the Skin or Non-Skin

Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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8372 Design and Development of Real-Time Optimal Energy Management System for Hybrid Electric Vehicles

Authors: Masood Roohi, Amir Taghavipour

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This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.

Keywords: hybrid electric vehicles, energy management system, nonlinear model predictive control, real-time

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8371 Diabetes Mellitus and Blood Glucose Variability Increases the 30-day Readmission Rate after Kidney Transplantation

Authors: Harini Chakkera

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Background: Inpatient hyperglycemia is an established independent risk factor among several patient cohorts with hospital readmission. This has not been studied after kidney transplantation. Nearly one-third of patients who have undergone a kidney transplant reportedly experience 30-day readmission. Methods: Data on first-time solitary kidney transplantations were retrieved between September 2015 to December 2018. Information was linked to the electronic health record to determine a diagnosis of diabetes mellitus and extract glucometeric and insulin therapy data. Univariate logistic regression analysis and the XGBoost algorithm were used to predict 30-day readmission. We report the average performance of the models on the testing set on five bootstrapped partitions of the data to ensure statistical significance. Results: The cohort included 1036 patients who received kidney transplantation, and 224 (22%) experienced 30-day readmission. The machine learning algorithm was able to predict 30-day readmission with an average AUC of 77.3% (95% CI 75.30-79.3%). We observed statistically significant differences in the presence of pretransplant diabetes, inpatient-hyperglycemia, inpatient-hypoglycemia, and minimum and maximum glucose values among those with higher 30-day readmission rates. The XGBoost model identified the index admission length of stay, presence of hyper- and hypoglycemia and recipient and donor BMI values as the most predictive risk factors of 30-day readmission. Additionally, significant variations in the therapeutic management of blood glucose by providers were observed. Conclusions: Suboptimal glucose metrics during hospitalization after kidney transplantation is associated with an increased risk for 30-day hospital readmission. Optimizing the hospital blood glucose management, a modifiable factor, after kidney transplantation may reduce the risk of 30-day readmission.

Keywords: kidney, transplant, diabetes, insulin

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8370 Assessment of the Fertility Status of the Fadama Soils Found along Five Major River Catchments in Kano

Authors: Garba K. Adamu

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This research was carried out in the catchments of five major rivers in Kano State. The catchments have considerable Fadama lands; these include: River Gari which is located in the northwestern part of Kano state, Rivers Challawa and Watari from southernparts of Kano and Katsina states. River Tomas from the northern parts of Kano state, River Jakara which has its source from the Old Kano city, part of Central Business Districts and Industrial Estates. The study was carried out with aim of assessing the fertility status of the Fadama soils found in these major river catchments. A transect was designed to collect samples along farming villages in the five river channels for the study. The findings indicate that the soils are predominantly sandy. The bulk density values vary significantly and range from 0.98mg/m to 1.36mg/m. The pH values for all the sites studied ranges from slightly acidic to slightly alkaline. The OC ranged from low to very low in the sites. The EC ranges from 66.3µs/cm to 198µs/cm for all the sites. The mean CEC ranges from 3.864 cm/kg to 10.114 Cmol/kg. The range of values for the SAR was 0.0106 to 0.069. Nitrogen ranges from0.03 to 0.1230ppm. The range of P value fell between 9.9 to 41.1mg/kg.Ca values ranges from 1.0170 to 14.9850 and K values ranges from 4.6550 – 64.40.Mg values range from 0.1380 to 1.8580 and Zn values range from 1.0170 to 14.9850. The Fe values ranged from 15.6500mg/kg to 69.8000mg/kg. The B values range from0.2060 to13.5450. Generally, the values obtained shows a low to medium fertility levels for all the parameters tested and the areas will require the in cooperation of organic manure and chemical fertilizers to improve soil structure and supplements other macro nutrients.

Keywords: assessment, Fadama soils, fertility status, river catchment

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8369 A Comparative Study: Comparison of Two Different Fluorescent Stains -Auramine and Rhodamine- with Ehrlich-Ziehl-Neelsen, Kinyoun Staining, and Culture in the Determination of Acid Resistant Bacilli

Authors: Recep Keşli, Hayriye Tokay, Cengiz Demir, İsmail Ceyhan

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Objective: In many countries, tuberculosis (TB) is still one of the most important diseases. Tuberculosis is among top 10 causes of death worldwide. The early diagnosis of active tuberculosis still depends on the presence of acid resistant bacilli (ARB) in stained smears. In this study, we aimed to investigate the diagnostic performances of Erlich Ziehl Neelsen (EZN), Kinyoun and two different fluorescent stains. Methods: The specimens were obtained from the patients who applied to Chest Diseases Departments of Ankara Atatürk Chest Diseases and Thoracic Surgery Training and Research Hospital, and Afyon Kocatepe University, ANS Research and Practice Hospital. The study was carried out in the Medical Microbiology Laboratory, School of Medicine, Afyon Kocatepe University. All the non-sterile specimens were homogenized and decontaminated according to the EUCAST instructions. Samples were inoculated onto the Löwenstein-Jensen agars (bio-Merieux Marcy l'Etoile, France) and then incubated at 37˚C, for 40 days. Four smears were prepared from each specimen. Slides were stained with commercial EZN (BD, Sparks, USA), Kinyoun (SALUBRIS Istanbul, Turkey), Auramine (SALUBRIS Istanbul, Turkey) and Rhodamine (SALUBRIS Istanbul, Turkey) kit. While EZN and Kinyoun stainings were examined by light microscope, Auramine and Rhodamine slides were examined by fluorescence microscopy. Results: A total of 158 respiratory system samples (sputum, broncho alveolar lavage fluid…etc) were enrolled into the study. A hundred and two of the samples that processed were found as culture positive. The sensitivity, specificity, positive predictive, and negative predictive values were detected as 100%, 67.5%, 73.5%, and 100% for EZN, 100%, 70.9%, 77.4%, and 100% for Kinyoun, 100%,77.8%, 84.3%, 100% for Auramine, and 100%, 80% , 86.3%, and 100% for Rhodamine respectively. Conclusions: According to our study auramine and rhodamine staining methods showed the best diagnostic performance among the four investigated staining methods. In conclusion, the fluorochrome staining method may be accepted as the most reliable, rapid and useful method for diagnosis of the mycobacterial infections truly.

Keywords: acid resistant bacilli (ARB), auramine, Ehrlich-Ziehl-Neelsen (EZN), Kinyoun, Rhodamine

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8368 Analysis of Dust Particles in Snow Cover in the Surroundings of the City of Ostrava: Particle Size Distribution, Zeta Potential and Heavy Metal Content

Authors: Roman Marsalek

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In this paper, snow samples containing dust particles from several sampling points around the city of Ostrava were analyzed. The pH values of sampled snow were measured and solid particles analyzed. Particle size, zeta potential and content of selected heavy metals were determined in solid particles. The pH values of most samples lay in the slightly acid region. Mean values of particle size ranged from 290.5 to 620.5 nm. Zeta potential values varied between -5 and -26.5 mV. The following heavy metal concentration ranges were found: copper 0.08-0.75 mg/g, lead 0.05-0.9 mg/g, manganese 0.45-5.9 mg/g and iron 25.7-280.46 mg/g. The highest values of copper and lead were found in the vicinity of busy crossroads, and on the contrary, the highest levels of manganese and iron were detected close to a large steelworks. The proportion between pH values, zeta potentials, particle sizes and heavy metal contents was established. Zeta potential decreased with rising pH values and, simultaneously, heavy metal content in solid particles increased. At the same time, higher metal content corresponded to lower particle size.

Keywords: dust, snow, zeta potential, particles size distribution, heavy metals

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8367 Thermalytix: An Advanced Artificial Intelligence Based Solution for Non-Contact Breast Screening

Authors: S. Sudhakar, Geetha Manjunath, Siva Teja Kakileti, Himanshu Madhu

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Diagnosis of breast cancer at early stages has seen better clinical and survival outcomes. Survival rates in developing countries like India are very low due to accessibility and affordability issues of screening tests such as Mammography. In addition, Mammography is not much effective in younger women with dense breasts. This leaves a gap in current screening methods. Thermalytix is a new technique for detecting breast abnormality in a non-contact, non-invasive way. It is an AI-enabled computer-aided diagnosis solution that automates interpretation of high resolution thermal images and identifies potential malignant lesions. The solution is low cost, easy to use, portable and is effective in all age groups. This paper presents the results of a retrospective comparative analysis of Thermalytix over Mammography and Clinical Breast Examination for breast cancer screening. Thermalytix was found to have better sensitivity than both the tests, with good specificity as well. In addition, Thermalytix identified all malignant patients without palpable lumps.

Keywords: breast cancer screening, radiology, thermalytix, artificial intelligence, thermography

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8366 Significance of Life Values in Relationship: A Detailed Analysis of Teenage Population

Authors: Preeti Nakhat

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Background: Values are essential part of one's life. They are inculcated since the early years of life and shape the personality of the individual. They play a tremendous role in decision making. Teenagers are seen perplexed about the values of their life. The challenge faced by majority of the teenage population in choosing between a positive and negative value is high. The values they adopt remain throughout their life and in every decision, hence it is a crucial topic of research. Research Methodology: This research aimed at finding out the value conflict of teenagers in relations. Hypothesis of the study are: H₀- There is no significant association between the life values and value conflict of higher secondary students; H₁– There is a significant association between the life values and value conflict of higher secondary students. For the same, the standardized tool, value conflict scale by R. L. Bhardwaj has been used. The tool consists 24 questions of different life situations with multiple choice options. Findings: There is 96% variation in value conflict due to evasion vs. fortitude, dependence vs. self-reliance, selfishness vs. probity, hate vs. love, fear vs. assertion and pragmatism vs. idealism life values. There is a positive association between all the life values and value conflict of higher secondary school students. Percentages of association are: 0.17% between value conflict and evasion vs. fortitude value, 0.16% between value conflict and dependence vs. self-reliance value, 0.17% between value conflict and selfishness vs. probity value, 0.16% between value conflict and hate vs. love value, 0.17% between value conflict and fear vs. assertion, 0.17% between value conflict and pragmatism vs. idealism value. Discussions: The dilemma faced by the students regarding value conflict is high. Bewilderment of being honest or lying, of loving or hating family and friends, being pragmatic or idealistic in life decision, being selfish or selfless is seen among the students. It is the challenge for the future. Teaching of values with a practical aspect should be added in the school curriculum.

Keywords: dilemma, conflict, school, values

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8365 Development of a Predictive Model to Prevent Financial Crisis

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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8364 Global Capitalism and Commodification of Breastfeeding: An Investigation of Its Impact on the “Traditional” African Conception of Family Life and Motherhood

Authors: Mosito Jonas Seabela

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Breastfeeding in public has become a contentious issue in contemporary society. Mothers are often subjected to unfair discrimination and harassment for simply responding to their maternal instinct to breastfeed their infants. The unwillingness of society to accept public breastfeeding as a natural, non-sexual act is partly influenced by the imposition of a pornified and hypersexualised Western culture, which was imported to Africa through colonisation, enforced by the apartheid regime, and is now perpetuated by Western media. The imposition of the modern nuclear family on Africans, and the coerced aspiration to subscribe to bourgeois values, has eroded the moral standing of the traditional African family and its cultural values. Western-centric perceptions of African women have altered the experience of motherhood for many, commodifying the practice of breastfeeding. As a result, the use of bottles and infant formulas is often perceived as the preferred method, while breastfeeding in public is viewed as primitive, immoral, and unacceptable. This normative study seeks to answer the question of what ought to be done to preserve the dignity of African motherhood and protect their right to breastfeed in public. The African philosophy of Ubuntu is employed to advocate for the right to breastfeed in public. This moral philosophy posits that the western perception of a person seeks to isolate people from their environment and culture, thereby undermining the process of acquiring humanity, which fosters social cohesion. The Ubuntu philosophy embodies the aphorism, “umuntu ngumuntu nga bantu”, meaning “a person is a person through other persons”, signifying people’s interconnectedness and interdependence. The application of the key principles of Ubuntu, such as “survival, the spirit of solidarity, compassion, respect, and dignity” can improve human interaction and unite the public to support the government’s efforts to increase exclusive breastfeeding rates and reduce infant mortality rates. A doctrine called “Ubuntu Lactivism” is what the author proposes as a means to advocate for breastfeeding rights in fulfilment of African traditional values.

Keywords: ubuntu, breastfeeding, Afrocentric, colonization, culture, motherhood, imperialism, objectification

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8363 Influence of Farnesol on Growth and Development of Dysdercus koenigii

Authors: Shailendra Kumar, Kamal Kumar Gupta

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Dysdercus koenigii is an economically important pest of cotton worldwide. The pest damages the crop by sucking sap, staining lint, reducing the oil content of the seeds and deteriorating the quality of cotton. Plant possesses a plethora of secondary metabolites which are used as defense mechanism against herbivores. One of the important categories of such chemicals is insect growth regulators and the intermediates in their biosynthesis. Farnesol belongs to sesquiterpenoid. It is an intermediate in Juvenile hormone biosynthetic pathway in insects has been widely reported in the variety of plants. This chemical can disrupt the normal metabolic function and therefore, affects various life processes of the insects. Present study tested the efficacy of farnesol against Dysdercus koenigii. 2μl of 5% (100µg) and 10% (200µg) of the farnesol was applied topically on the dorsum of thoracic region of the newly emerged fifth instar nymphs of Dysdercus. The treated insects were observed daily for their survival, weight gain, and developmental anomalies for a period of ten days. The results indicated that treatment with 200µg farnesol decreased survival of the insects to 70% after 24h of exposure. At lower doses, no significant decrease in the survival was observed. However, the surviving nymphs showed alteration in growth, development, and metamorphosis. The weight gain in the treated nymphs showed deviation from control. The treated nymphs showed an increase in mortality during subsequent days and increase in the nymphal duration. The number of nymphs undergoing metamorphosis decreased to 46% and 88% in the treatments with the dose of 200µg and 100µg respectively. Severe developmental anomalies were also observed in the treated nymphs. The treated nymphs moulted into supernumerary nymphs, adultoids, adults with exuviae attached and adults with wing deformities. On treatment with 200µg; 26% adultoid, 4% adults with exuviae attached and 12% adults with wing deformed were produced. Treatment with 100µg resulted in production of 34% adultoid, 26% adults with deformed wing and 4% adults with exuviae attached. Many of the treated nymphs did not metamorphose into adults, remained in nymphal stage and died. Our results indicated potential application plant-derived secondary metabolites like farnesol in the management of Dysdercus population.

Keywords: development, Dysdercus koenigii, farnesol, survival

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8362 Influence of Catharanthus roseus, Ocimum sanctum and Lantana camara Extracts on Survival and Longevity of Dysdercus koenigii

Authors: Sunil Kayesth, Kamal Kumar Gupta

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The development of resistance among insects and pests, environmental contamination and adverse effects on non-target organisms is contributed by the indiscriminate use of chemical based insecticides. To overcome these environmental and other ecological issues that are need to replace these harmful toxic compounds. The present study was designed to evaluate the effect of Catharanthus roseus, Ocimum sanctum and Lantana camara plants volatiles on survival and longevity of Dysdercus koenigii. The hexane extract and ethanol extracts of these three plants were used. The fifth instars were exposed to hexane extract with concentrations of 10%, 5%, 2.5% 1.25%, 0.1%, 0.5% 0.25%, 0.125% and 0.0625% while, adults were treated with10%, 5%, 2.5% and 1.25%. 1-ml of each of these concentrations was used to make a thin film in sterilized glass jars of 500 ml capacity. Fifteen- newly emerged fifth instar nymphs and adult bugs were treated separately with the extracts for 24- hour exposure to the plant volatiles. For ethanol extracts cottonseed were treated with ethanol extracts of 10%, 5%, 2.5% and 1.25% concentrations. The treated seeds were provided to the Dysdercus for a period of 24 hours and their feeding behaviour was observed. The effect of hexane and ethanol extract of these plants was observed and readings were recorded for 15 days. Survival and longevity of both fifth instars and adults were in correlation with the concentrations of the plant extracts. Among three plant extracts, Ocimum hexane extract was most toxic and Catharanthus was moderate while Lantana was least toxic. The ethanol extracts of Lantana was highly antifeedent while Ocimum was moderate and Catharanthus was least antifeedent. Both Catharanthus and Ocimum appeared to have potential molecules, which possessed insecticidal activity while Ocimum and Lantana showed antifeedent activities. These insecticidal and antifeedent properties may be used in IPM.

Keywords: Catharanthus roseus, Ocimum sanctum, Lantana camara, Dysdercus koenigii

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8361 Hsa-miR-192-5p, and Hsa-miR-129-5p Prominent Biomarkers in Regulation Glioblastoma Cancer Stem Cells Genes Microenvironment

Authors: Rasha Ahmadi

Abstract:

Glioblastoma is one of the most frequent brain malignancies, having a high mortality rate and limited survival in individuals with this malignancy. Despite different treatments and surgery, recurrence of glioblastoma cancer stem cells may arise as a subsequent tumor. For this reason, it is crucial to research the markers associated with glioblastoma stem cells and specifically their microenvironment. In this study, using bioinformatics analysis, we analyzed and nominated genes in the microenvironment pathways of glioblastoma stem cells. In this study, an appropriate database was selected for analysis by referring to the GEO database. This dataset comprised gene expression patterns in stem cells derived from glioblastoma patients. Gene clusters were divided as high and low expression. Enrichment databases such as Enrichr, STRING, and GEPIA were utilized to analyze the data appropriately. Finally, we extracted the potential genes 2700 high-expression and 1100 low-expression genes are implicated in the metabolic pathways of glioblastoma cancer progression. Cellular senescence, MAPK, TNF, hypoxia, zimosterol biosynthesis, and phosphatidylinositol metabolism pathways were substantially expressed and the metabolic pathways were downregulated. After assessing the association between protein networks, MSMP, SOX2, FGD4 ,and CNTNAP3 genes with high expression and DMKN and SBSN genes with low were selected. All of these genes were observed in the survival curve, with a survival of fewer than 10 percent over around 15 months. hsa-mir-192-5p, hsa-mir-129-5p, hsa-mir-215-5p, hsa-mir-335-5p, and hsa-mir-340-5p played key function in glioblastoma cancer stem cells microenviroments. We introduced critical genes through integrated and regular bioinformatics studies by assessing the amount of gene expression profile data that can play an important role in targeting genes involved in the energy and microenvironment of glioblastoma cancer stem cells. Have. This study indicated that hsa-mir-192-5p, and hsa-mir-129-5p are appropriate candidates for this.

Keywords: Glioblastoma, Cancer Stem Cells, Biomarker Discovery, Gene Expression Profiles, Bioinformatics Analysis, Tumor Microenvironment

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8360 Length-Weight and Length-Length Relationships of Oreochromis aureus in Relation to Body Size from Pakistan

Authors: Muhammad Naeem, Amina Zubari, Abdus Salam, Summera Yasmeen, Syed Ali Ayub Bukhari, Abir Ishtiaq

Abstract:

In the present study, eighty three wild Oreochromis aureus of different body size ranging 5.3-14.6 cm in total length were collected from the River Chenab, District Muzzafer Garh, Pakistan to investigate the parameters of length –weight, length-length relationships and condition factor in relation to size. Each fish was measured and weighed on arrival at laboratory. Log transformed regressions were used to test the allometric growth. Length-weight relationship was found highly significant (r = 0.964; P < 0.01). The values of exponent “ b” in Length–weight regression (W=aLb), deviated from 3, showing isometric growth (b = 2.75). Results for LLRs indicated that these are highly correlated (P< 0.001). Condition factor (K) found constant with increasing body weight, however, showed negative influence with increasing total length.

Keywords: Oreochromis aureus, weight-length relationship, condition factor, predictive equations

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8359 Online Learning for Modern Business Models: Theoretical Considerations and Algorithms

Authors: Marian Sorin Ionescu, Olivia Negoita, Cosmin Dobrin

Abstract:

This scientific communication reports and discusses learning models adaptable to modern business problems and models specific to digital concepts and paradigms. In the PAC (probably approximately correct) learning model approach, in which the learning process begins by receiving a batch of learning examples, the set of learning processes is used to acquire a hypothesis, and when the learning process is fully used, this hypothesis is used in the prediction of new operational examples. For complex business models, a lot of models should be introduced and evaluated to estimate the induced results so that the totality of the results are used to develop a predictive rule, which anticipates the choice of new models. In opposition, for online learning-type processes, there is no separation between the learning (training) and predictive phase. Every time a business model is approached, a test example is considered from the beginning until the prediction of the appearance of a model considered correct from the point of view of the business decision. After choosing choice a part of the business model, the label with the logical value "true" is known. Some of the business models are used as examples of learning (training), which helps to improve the prediction mechanisms for future business models.

Keywords: machine learning, business models, convex analysis, online learning

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8358 Multiple Fault Diagnosis in Digital Circuits using Critical Path Tracing and Enhanced Deduction Algorithm

Authors: Mohamed Mahmoud

Abstract:

This paper has developed an effect-cause analysis technique for fault diagnosis in digital circuits. The main algorithm of our technique is based on the Enhanced Deduction Algorithm, which processes the real response of the CUT to the applied test T to deduce the values of the internal lines. An experimental version of the algorithm has been implemented in C++. The code takes about 7592 lines. The internal values are determined based on the logic values under the permanent stuck-fault model. Using a backtracking strategy guarantees that the actual values are covered by at least one solution, or no solution is found.

Keywords: enhanced deduction algorithm, backtracking strategy, automatic test equipment, verfication

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8357 Green Wave Control Strategy for Optimal Energy Consumption by Model Predictive Control in Electric Vehicles

Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

Abstract:

Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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8356 Corporate Governance and Business Ethical Values in Organisation: A Study of Unilag Holdings

Authors: Ogunmayi Bamidele, Aribisala Oluwadamilare Olufolarin

Abstract:

The objective of this research was to examine how corporate governance and ethical business values impact both the performance of the organization and its employees, as it is essential for any organization to uphold good ethics and corporate governance. The study was conducted at Unilag Holdings Limited (UniHOLDs) to demonstrate that organizations may experience losses if they do not have proper corporate governance and business ethical values in place. The employees' perception of corporate governance and ethics is crucial for the organization. The research indicated a connection between corporate governance and business ethics values, and therefore, correlation analysis was utilized, making it statistically reliable. The results of the test show a strong positive correlation (r=.812, N=94, P<.01) between corporate governance and business ethical values. A questionnaire was distributed to employees at Unilag Holdings Limited (UniHOLDs), with 94 out of 130 completed and returned. The findings indicate that ethical values contribute to employee productivity, and productive employees have a beneficial impact on the organization's performance. Additionally, the study revealed that employees tend to adhere to rules regardless of their ethical nature. To address this, the organization should ensure that top-level managers do not assign unethical tasks to their subordinates. The study recommends that the organization should consistently practice corporate governance and business ethics. The company needs to make sure that its stakeholders continue to support its way of doing things.

Keywords: business ethical values, corporate governance, organization, business ethics

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8355 Maternal Health Care Utilization and Its Effect on Pregnancy Outcome in Nepal

Authors: Adrita Banerjee, Ajeet Kumar Singh

Abstract:

Antenatal care (ANC) from a skilled provider is important to monitor the pregnancy and reduce the risk of morbidity for mother and baby during pregnancy and delivery. The quality of antenatal care can be monitored through the content of services received and the kind of information mothers are given during their visit. Objective: The paper tries to examine the association between ANC check-ups and size/ birth weight. It also focuses on investigating the relationship between utilization of recommended prenatal care for mothers and its effect on infant survival in Nepal. Data and methods: This paper uses data from Nepal demographic Health Survey 2011. To understand the relationship bi-variate statistical analysis and logistic regressions has been done. Maternal health care utilization include ANC check-ups i.e. the type of ante-natal care providers, the number and timing of the visit. The various components of the check-ups include intake of iron tablets/syrups, intestinal parasitic drugs, etc. Results: The results show that women who had no antenatal care visits about 40% had small sized babies at the time of birth compared to women to had at least 3 ANC check up. Women who had at least 3 check-ups 17% of the babies have a small size. It has also been found that about 50 % of the women prefer ANC check-ups during pregnancies which have resulted in lowering the infant mortality by about 40% during 1996-2011. Conclusion: Ante natal care check is care and monitoring of the pregnant woman and her foetus throughout pregnancy. ANC checks have an effect on the infant health and child survival. A woman who had at least three check-ups the possibilities of adverse effect on infant health and infant survival was significantly lower. The findings argue for a more enhanced focus on ANC check-ups for improving the maternal and child health in Nepal.

Keywords: maternal, health, pregnancy, outcome

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8354 Comparative Analysis of Predictive Models for Customer Churn Prediction in the Telecommunication Industry

Authors: Deepika Christopher, Garima Anand

Abstract:

To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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8353 Evaluation of Entomopathogenic Fungi Strains for Field Persistence and Its Relationship to in Vitro Heat Tolerance

Authors: Mulue Girmay Gebreslasie

Abstract:

Entomopathogenic fungi are naturally safe and eco-friendly biological agents. Their potential of host specificity and ease handling made them appealing options to substitute synthetic pesticides in pest control programs. However, they are highly delicate and unstable under field conditions. Therefore, the current experiment was held to search out persistent fungal strains by defining the relationship between invitro heat tolerance and field persistence. Current results on leaf and soil persistence assay revealed that strains of Metarhizium species, M. pingshaense (F2685), M. pingshaense (MS2) and M. brunneum (F709) exhibit maximum cumulative CFUs count, relative survival rate and least percent of CFUs reductions showed significant difference at 7 days and 28 days post inoculations (dpi) in hot seasons from sampled soils and leaves and in cold season from soil samples. Whereas relative survival of B. brongniartii (TNO6) found significantly higher in cold weather leaf treatment application as compared to hot season and found as persistent as other fungal strains, while higher deterioration of fungal conidia seen with M. pingshaense (MS2). In the current study, strains of Beauveria brongniartii (TNO6) and Cordyceps javanica (Czy-LP) were relatively vulnerable in field condition with utmost colony forming units (CFUs) reduction and least survival rates. Further, the relationship of the two parameters (heat tolerance and field persistence) was seen with strong linear positive correlations elucidated that heat test could be used in selection of field persistent fungal strains for hot season applications.

Keywords: integrated pest management, biopesticides, Insect pathology and microbial control, entomology

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8352 Biologically Synthesised Silver Nanoparticles Induces Autophagy and JNK Signaling as a Pro-Survival Response by Abrogating Reactive Oxygen Species Accumulation in Cancer Cells

Authors: Sudeshna Mukherjee, Leena Fageria, R. Venkataramana Dilip, Rajdeep Chowdhury, Jitendra Panwar

Abstract:

Metal nanoparticles in recent years have gained importance in cancer therapy due to their enhanced permeability retention effect. Among various nanomaterials, silver nanoparticles (AgNPs) have received considerable attention due to their unique properties like conductivity, chemical stability, relative lower toxicity and outstanding therapeutic potential, such as anti-inflammatory, antimicrobial and anti-cancerous activities. In this study, we took a greener approach to synthesize silver nanoparticle from fungus and analyze its effects on both epithelial and mesenchymal derived cancer cells. Much research has been done on nanoparticle-induced apoptosis, but little is known about its role in autophagy. In our study, the silver nanoparticles were seen to induce autophagy which was analyzed by studying the expression of several autophagy markers like, LC3B-II and ATG genes. Monodansylcadaverine (MDC) assay also revealed the induction of autophagy upon treatment with AgNPs. Inhibition of autophagy by chloroquine resulted in increased cell death suggesting autophagy as a survival strategy adopted by the cells. In parallel to autophagy induction, silver nanoparticles induced ROS accumulation. Interestingly, autophagy inhibition by chloroquine increased ROS level, resulting in enhanced cell death. We further analyzed MAPK signaling upon AgNP treatment. It was observed that along with autophagy, activation of JNK signaling served as pro-survival while ERK signaling served as a pro-death signal. Our results provide valuable insights into the role of autophagy upon AgNP exposure and provide cues to probabilistic strategies to effectively sensitize cancer cells.

Keywords: autophagy, JNK signalling, reactive oxygen species, silver nanoparticles

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8351 A Value-Based Approach to Recognize Authentic Transformational Leaders' Delivering Process of Corporate Social Responsibility Values

Authors: Yi-Jung Chen, Yunshi Liu

Abstract:

To explain how followers can perceive whether or not transformational leaders are authentic on the basis of their leadership behaviors based on value-based leadership theory, this study adopts the dual-focus model of transformational leadership and evaluates leaders’ corporate social responsibility values along with followers’ perceptions of leaders’ values. Using dyadic questionnaires, the final study sample consisted of 252 followers and 43 leaders at a private firm in Taiwan. Results show that followers perceive corporate social responsibility values of transformational leaders through their group-focused leadership behaviors because such group-focused leadership is in line with these values.

Keywords: authentic transformational leadership, corporate social responsibility value, value-based leadership theory, dual-focus leadership

Procedia PDF Downloads 306
8350 Detection of Autistic Children's Voice Based on Artificial Neural Network

Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

Abstract:

In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

Procedia PDF Downloads 457
8349 Effects of Some Legume Flours and Gums on Some Properties of Turkish Noodle

Authors: Kübra Aktaş, Nermin Bilgiçli, Tayyibe Erten, Perihan Kübra Çiçek

Abstract:

In this research, different wheat-legume flour blends were used in Turkish noodle preparation with the aid of some gums (xanthan and guar). Chickpea, common bean and soy flours were used in noodle formulation at 20% level with and without gum (1%) addition. Some physical, chemical and sensory properties of noodles were determined. Water uptake, volume increase and cooking loss values of the noodles changed between 92.03-116.37%, 125.0-187.23% and 4.88-8.10%, respectively. Xanthan or guar gam addition decreased cooking loss values of legume fortified noodles. Both legume flour and gum addition significantly (p<0.05) affected the color values of the noodles. The lowest lightness (L*), redness (a*) and the highest yellowness (b*) values were obtained with soy flour usage in noodle formulation. Protein and ash values of noodles ranged between 15.14 and 21.82%; 1.62 and 2.50%, respectively, and the highest values were obtained with soy flour usage in noodle formulation. As a result of sensory evaluation, noodles containing chickpea flour and guar gum were rated with higher taste, odor, appearance and texture scores compared to other noodle samples.

Keywords: noodle, legume, soy, chickpea, common bean, gum

Procedia PDF Downloads 377