Search results for: induction hobs

Authors: F. Alaa Ali, S. A. Sherein Abdelgayed, S. Osama. EL-Tawil, M. Adel Bakeer

Abstract:

Tartrazine is an organic azo dyes food additive widely used in foods, drugs, and cosmetics. The present study aimed to investigate the toxic effects of tartrazine on kidneys and liver biomarkers in addition to the investigation of oxidative stress and change of histopathological structure of liver and kidneys in 30 male rats. Tartrazine was orally administrated daily at dose 200 mg/ kg bw (1/ 10 LD₅₀) for sixty days. Serum and tissue samples were collected at the end of the experiment to investigate the underlying mechanism of tartrazine through assessment oxidative stress (Glutathione (GSH), Superoxide dismutase (SOD) and malondialdehyde (MDA) and biochemical markers (alanine aminotransferase (ALT), aspartate aminotransferase (AST), Total protein and Urea). Liver and kidneys tissue were collected and preserved in 10% formalin for histopathological examination. The obtained values were statistically analyzed by one way analysis of variance (ANOVA) followed by multiple comparison test. Biochemical analysis revealed that tartrazine induced significant increase in serum ALT, AST, total protein, urea level compared to control group. Tartrazine showed significant decrease in liver GSH and SOD where their values when compared to control group. Tartrazine induced increase in liver MDA compared to control group. Histopathology of the liver showed diffuse vacuolar degeneration in hepatic parenchyma, the portal area showed sever changes sever in hepatoportal blood vessels and in the bile ducts. The kidneys showed degenerated tubules at the cortex together with mononuclear leucocytes inflammatory cells infiltration. There is perivascular edema with inflammatory cell infiltration surrounding the congested and hyalinized vascular wall of blood vessel. The present study indicates that the subchronic effects of tartrazine have a toxic effect on the liver and kidneys together with induction of oxidative stress by formation of free radicals. Therefore, people should avoid the hazards of consuming tartrazine.

Keywords: Albino rats, tartrazine, toxicity, pathology

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Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

Abstract:

This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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Authors: Wan-Ting Liao, Angela K. Tzeng

Abstract:

Empathy has been an important issue in psychology, education, as well as cognitive neuroscience. Empathy has two major components: cognitive and emotional. Cognitive component refers to the ability to understand others’ perspectives, thoughts, and actions, whereas emotional component refers to understand how others feel. Empathy can be induced, attitude can then be changed, and with enough attitude change, helping behavior can occur. This finding leads us to two questions: is attitude change really necessary for prosocial behavior? And, what roles cognitive and affective empathy play? For the second question, participants with different psychopathic personality (PP) traits are critical because high PP people were found to suffer only affective empathy deficit. Their cognitive empathy shows no significant difference from the control group. 132 college students voluntarily participated in the current three-stage study. Stage 1 was to collect basic information including Interpersonal Reactivity Index (IRI), Psychopathic Personality Inventory-Revised (PPI-R), Attitude Scale, Visual Analogue Scale (VAS), and demographic data. Stage two was for empathy induction with three controversial scenarios, namely domestic violence, depression with a suicide attempt, and an ex-offender. Participants read all three stories and then rewrite the stories by one of two perspectives (empathetic vs. objective). They would then complete the VAS and Attitude Scale one more time for their post-attitude and emotional status. Three IVs were introduced for data analysis: PP (High vs. Low), Responsibility (whether or not the character is responsible for what happened), and Perspective-taking (Empathic vs. Objective). Stage 3 was for the action. Participants were instructed to freely use the 17 tokens they received as donations. They were debriefed and interviewed at the end of the experiment. The major findings were people with higher empathy tend to take more action in helping. Attitude change is not necessary for prosocial behavior. The controversy of the scenarios and how familiar participants are towards target groups play very important roles. Finally, people with high PP tend to show more public prosocial behavior due to their affective empathy deficit. Pre-existing value and belief as well as recent dramatic social events seem to have a big impact and possibly reduce the effect of the independent variables (IV) in our paradigm.

Keywords: Affective empathy, attitude, cognitive empathy, prosocial behavior, psychopathic traits.

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