Neural Decoder for Topological Codes using Pseudo-Inverse of Parity Check Matrix

Recent developments in the field of deep learning have motivated many researchers to apply these methods to problems in quantum information. Torlai and Melko first proposed a decoder for surface codes based on neural networks. Since then, many other researchers have applied neural networks to study a variety of problems in the context of decoding. An important development in this regard was due to Varsamopoulos et al. who proposed a two-step decoder using neural networks. Subsequent work of Maskara et al. used the same concept for decoding for various noise models. We propose a similar two-step neural decoder using inverse parity-check matrix for topological color codes. We show that it outperforms the state-of-the-art performance of non-neural decoders for independent Pauli errors noise model on a 2D hexagonal color code. Our final decoder is independent of the noise model and achieves a threshold of $10 \%$. Our result is comparable to the recent work on neural decoder for quantum error correction by Maskara et al.. It appears that our decoder has significant advantages with respect to training cost and complexity of the network for higher lengths when compared to that of Maskara et al.. Our proposed method can also be extended to arbitrary dimension and other stabilizer codes.Comment: 12 pages, 12 figures, 2 tables, submitted to the 2019 IEEE International Symposium on Information Theor

A review on recent advancement in liquisolid techology

Liquisolid technique is a novel process in which a liquid can be converted into a material that flows freely, is readily compressible. The carrier material in liquisolid compact comprises the liquid part, which is the liquid drug or a drug solution in liquid vehicles that are non-volatile. Solubility is the main parameter in the circulation of blood to achieve the whole concentration of the drug for pharmacological action. The rate of dissolution of drugs enhances in liquisolid technology. This in turn increases absorption and bioavailability subsequently. This review discusses the different advances and changes to improve liquisolid technology formulations and enhancement of dissolution rate of poorly soluble drugs. Most of the new chemical entities have high lipophilicity and poor water solubility, resulting in poor bioavailability. The release rate of these drugs should be increased in order to improve bioavailability. The technique is based on dissolving the insoluble drug in the solution loaded with non-volatile solvent. Then the dissolution rate of drug which is poorly soluble will rise. The enhanced bioavailability is due to the increased surface area of drug for release, increased drug aqueous solubility or improved wetting capacity

ANALGESIC AND ANTI-INFLAMMATORY ACTIVITIES OF ETHANOLIC EXTRACT OF LEAVES OF PUNICA GRANATUM L. ON EXPERIMENTAL ANIMAL MODELS

Objective: The aim of the study is to evaluate the analgesic and anti-inflammatory activities of the ethanolic extract of Punica granatum L. (EEPG) on experimental animal models. Methods: Tail-flick method was used to test the central analgesic activity, using Pethidine as standard drug. The tail flick latencies or the basal reaction time of the animals were assessed using an analgesiometer. Glacial acetic acid induced writhing response was used to test the peripheral analgesic activity, using Aspirin as standard drug. Number of writhing responses was counted for 20 min in each group and the percentage protection was calculated. And Carrageenan induced rat paw edema method was used to test anti-inflammatory activity of EEPG against acute inflammation, using Aspirin as standard drug. The inhibition of rat paw edema was calculated in percentage. Results: In central analgesic activity, the extract and pethidine showed significant increase in the reaction time. In peripheral analgesic activity, the extract and aspirin significantly reduced the number of writhes induced by acetic acid. And in anti-inflammatory activity, the extract produced significant reduction of the carrageenan induced paw edema. Conclusion: The EEPG has demonstrated significant analgesic and anti-inflammatory activity

Opinion-Mining on Marglish and Devanagari Comments of YouTube Cookery Channels Using Parametric and Non-Parametric Learning Models

YouTube is a boon, and through it people can educate, entertain, and express themselves about various topics. YouTube India currently has millions of active users. As there are millions of active users it can be understood that the data present on the YouTube will be large. With India being a very diverse country, many people are multilingual. People express their opinions in a code-mix form. Code-mix form is the mixing of two or more languages. It has become a necessity to perform Sentiment Analysis on the code-mix languages as there is not much research on Indian code-mix language data. In this paper, Sentiment Analysis (SA) is carried out on the Marglish (Marathi + English) as well as Devanagari Marathi comments which are extracted from the YouTube API from top Marathi channels. Several machine-learning models are applied on the dataset along with 3 different vectorizing techniques. Multilayer Perceptron (MLP) with Count vectorizer provides the best accuracy of 62.68% on the Marglish dataset and Bernoulli Naïve Bayes along with the Count vectorizer, which gives accuracy of 60.60% on the Devanagari dataset. Multilayer Perceptron and Bernoulli Naïve Bayes are considered to be the best performing algorithms. 10-fold cross-validation and statistical testing was also carried out on the dataset to confirm the results

Flow Anlaysis on Hal Tejas Aircraft using Computational Fluid Dynamics with Different Angle of Attack

In the current globalization, we can see many innovations being introduced or implemented in every aspect of field that are considered to be existed. Every country is aiming to develop its power over all the aspects that considered for comparison with other countries in order to stand at same level of competition with others. One such power considered by all countries to develop every possible way to have a healthy competition is the military power which involves basically innovations of fast moving aircraft having a high lift coefficient and low drag coefficient. Such an aircraft having the high lift and low drag coefficient is TEJAS (HAL) developed by country India on which the purpose of paper mainly sustains. The paper mainly focuses on steady-state flow analysis over aircraft TEJAS using the computer aided modelling techniques and also the comparison of the results obtained from the modelled techniques. The paper also outlines the designing of the structural model of the TEJAS in a modelling software, creation of a finite computational domain, segmentation of this domain into discrete intervals, applying boundary conditions such as velocity in order to obtain plots and desired results determining the coefficient of pressure, lift and drag coefficient, velocity magnitude etc. This paper also aims in creating awareness to the future students about the techniques involved and knowledge required for developing a designed modelled. This paper also highlights the use of CFD techniques involved for the purpose of fluid flow simulation of the aircraft especially performing the meshing techniques, pre and post processing techniques and finally the evaluation of the simulation. Finally this paper can be seen as source by future generation students in gaining knowledge about design, analysis and simulation of the structured model on various conditions, about the field of aerospace engineering and new innovations being developed and also about the career involved when the above fields were chosen foe specialization purpose

Leveraging Text Mining for Trend Analysis and Comparison of Sustainability Reports: Evidence from Fortune 500 Companies

In the recent upsurge in environmental concerns, business sustainability has become more prominent than ever. Organizations worldwide are expected to function sustainably, causing the least negative impact on the environment and promoting harmony among the firm, environment, and society. Most firms report their actions related to sustainability in corporate social responsibility (CSR) reports. This research aims to understand and analyze contemporary trends in CSR reports by Fortune 500 companies using text mining. It compares how the focus of sustainability reports varies across countries and industries along key dimensions of sustainability (i.e., environmental, economic, social, and government). Findings from the study suggest variations in the focus of sustainability reports based on various factors, such as country of origin and company size, sector, and tenure, on the Fortune 500 list. Thus, it helps to gain a deeper understanding of the company’s motivations for focusing on various dimensions of corporate sustainability