Optimizing Micro-Scale Thermoelectric Model using Finite Element Method

The thermoelectric characterization of a micro-scale thermoelectric device using finite element method technique is presented in this paper. Thermoelectric device works on the principle of Seebeck Effect which converts temperature difference across the junction of two different materials into potential difference and hence energy. This work presents the optimization technique for a thermoelectric device by analyzing a single cell structure and proving the concept. A unit cell modeled in our work developed an average output voltage of 5 mV from human-body temperature. The output voltage increases further with increase in temperature difference at a rate of 4 mV/10˚C. The change observed in behavior of thermocouple due to variation in dimensional parameters is evaluated and examined. The simulation results for characterization of thermocouple agreed with the theoretical concepts of operation. A high potential difference for larger lengths of thermocouple and smaller thickness of materials is observed. However, high flow of current was observed in small leg-lengths of larger thickness. The paper presents the characterization techniques and the influencing parameters of thermocouple operation which are important to design a thermoelectric device

An exploration of the causal factors making an online course content popular & engaging

An education system consists of imparting knowledge, assessing the learners, collecting feedback, analysing it, and taking proper measures to improve it. All these measures ultimately improve learner satisfaction which gets reflected in the learner performance and makes the course popular. Due to the corona pandemic, educational institutes and universities have shifted their activities online. In such a scenario, it is challenging to identify a course's popularity and the factors that make it popular. In this work, the authors have performed aspect-based sentiment analysis of learner feedback to identify the essential aspects of creating a popular course. The traditional methods for analysing feedback for sentiment analysis require manual intervention and are tedious. The authors have proposed a framework that identifies learner reviews' aspect level sentiment polarity and selected the significant aspects impacting a course's popularity. Experimental work is conducted over a large-scale real-world education dataset containing around 110 K learner comments (referred to as Educational Dataset now onwards) collected from Coursera1 and learner data from academic institution MSIT2. Different word embeddings viz., FastText, Word2Vec (Word2Vector), GloVe (Global representation of Vectors), and user-created embeddings are used for CNN (Convolution Neural Network) and LSTM (Long Short Term Memory) models. These models are further compared with BERT (Bidirectional Encoder Representation from Transformers), EvoMSA (Evolutionary Multilingual Sentiment Analysis) and ELMo (Embeddings from Language Model) classifiers to find the method that works best for identifying the aspects that impact the popularity of a course. Based on the experimental results over the collected Dataset, BERT based model provides the best results with an accuracy of 94.27

Clinical safety profile of ticagrelor compared to clopidogrel in 1208 patients: Real world evidence

Introduction: Dual antiplatelet treatment is recommended by current clinical practice guidelines for patients undergoing PCI. The PLATO trial showed superiority of ticagrelor to clopidogrel in reducing the rate of death from vascular causes, myocardial infarction and stroke without increase in the rate of overall major bleeding in ACS patients. However, real world evidence in Indian patients is limited. The objective of this study is to compare safety profile of ticagrelor with clopidogrel in real world settings. Methodology: In this single centered retrospective observational study, a total of 1208 serial patient records undergoing PCI (ACS and stable angina patients as well) treated with Ticagrelor or Clopidogrel were collected and analyzed to look into in hospital outcomes. We excluded the patient’s data that were incomplete. Results: In total of 1208 patients, 604 patients received ticagrelor and similarly 604 patient received clopidogrel. No significant differences in the rates of major life threatening bleeding and any major bleeding were observed between ticagrelor and clopidogrel group (0.2% (n = 1) vs. 0.7% (n = 4), p = 0.18 and 2.8% (n = 17) vs. 3% (n = 18), p = 0.86 respectively). There was increase in minor bleeding rate with ticagrelor compared to clopidogrel (21.4% & 13.6%, p = 0.00). Conclusion: In the real world settings, patients undergoing PCI treated with ticagrelor showed similar safety profile compared to clopidogrel but with increase in minor bleeding rate. The observed results were in alignment with PLATO clinical trial. Keywords: Antiplatelet, P2Y12 inhibitors, Percutaneous coronary interventio