An open labeled clinical trail on the effect of Vrikshamla in Sthaulya (obesity) w.s.r to hyperlipidaemia

Obesity is one of the leading cause for more than 53 diseases and in India around 30 million peoples are suffering with Sthaulya (obesity), individual habits with stressful life, wrong dietary habits and sedentary life is the main cause of disease and no satisfactory treatment is available in conventional system. Hence there is need explore alternative system of Indian medicine like Ayurveda for the benefits of sufferers Ayurveda dealt this disease as Sthaulya (obesity) under Medoroga (Adipose tissue disorder) and many treatment modalities have been explained number of drugs in Brahatrayi (Charaka, Sushruta & Vagbhat) were cited Bhavamishra was the author of Bhavaprakash Nighantu (Lexicon) which is one of the Laghutrayis (Sharanghadara, Madhavanidhana & Bhavaprakash) text is highlighted with Karmaoushadi (action based drug) such as Amradi Phala Varga explained Vrikshamla considered as drug index of Ayurveda, thus present study was designed to screen the drug with properties of Kapha Medohara (ability to reduce Kapha & Fat), Medorogahara (reduces Adipose tissue), Sthaulyanashaka (Anti obesity) and Karshyakara (ability to make lean) from Bhavaprakasha Nighantu in Ayurveda

GESTURE BASED TOUCHPAD SECURITY SYSTEM WITH DESIGN OF TOUCH SCREEN CONTROLLER

The purpose of the project is to present a new approach on the design of security systems by using a touch sensitive device. Security is a permanent concern in a variety of environments ranging from physical access restriction in home and industrial settings to information security in digital systems. Numeric passwords, fingerprint recognition, and many other techniques have been extensively implemented in the past but they present certain drawbacks. The proposed technique makes use of a touch device to recognize symbols as passwords and takes time into account to add a new dimension and prevent password theft. We implemented a prototype that demonstrates the capabilities of the proposed security approach by showing one direct application in physical access restriction systems

Ayurvedic understanding and management of Trigeminal Neuralgia w.s.r. to Anantavaata - A Case Study

Trigeminal Neuralgia is one of the painful disorders involving fifth cranial nerve, causes severe unilateral pain over regions supplied by the branches of trigeminal nerve associated with tempero mandibular joint stiffness. Trigeminal neuralgia nearly can be correlated to Anantavaata, one of the 11 types of Shirorogas explained by Acharya Sushruta and is Vaatapradhaana Tridoshaja Vyadhi. Present study is conducted to know the efficacy of ayurvedic line of management in TN. A female patient of age 46 years, diagnosed with Trigeminal Neuralgia was treated with allopathy medications. But did not get satisfactory results. Hence patient approached our hospital and got Vaatahara and Brihmana line of management involving Nasya with Karpasasthyaadi Taila for 7 days, Shiropichu and Karnapoorana with Ksheerabala Taila, Gandoosha with Murchita Tila Taila and oral medications. Patient’s complaints were assessed before and after treatment with VAS pain scale and verbal descriptor scale for TMJ stiffness After Follow up patient had got relieved with the complaints and got satisfactory results with ayurvedic line of management

Sphinx 4 Speech Recognition in ATC

Speech Recognition plays a very important role in day to day life. Speech Recognition is widely used and addicted by this world as it allows users to communicate with computers by recognizing their spoken language. Communication with Speech Recognition made our lives easy. There are many types of open source Speech Recognition Engine. Different types of application are built using Speech Recognition Engine. An Application is built for Air Traffic Controller. A new Software library with good grammar is proposed according to Air Traffic Controller commands. This Software library is used to build successful working application

Semi-Supervised Domain Adaptation and Collaborative Deep Learning for Dual Sentiment Analysis

Sentiment classification is a much needed topic that has grabbed the interest of many researchers. Especially, classification of data from customer reviews on various commercial products has been an important source of research. A model called supervised dual sentiment analysis is used to handle the polarity shift problem that occurs in sentiment classification. Labeling the reviews is a tedious and time consuming process. Even, a classifier trained on one domain may not perform well on the other domain. To overcome these limitations, in this paper we propose semi-supervised domain adaptive dual sentiment analysis that train a domain independent classifier with few labeled data. Reviews are of varying length and hence, classification is more accurate if long term dependency between the words is considered. We propose a collaborative deep learning approach to the dual sentiment analysis. Long short term memory (LSTM) recurrent neural network is used to handle sequence prediction to classify the reviews more accurately. LSTM takes more time to extract features from the reviews. Convolution neural network is used before LSTM layers to extract features resulting in the reduction of training time compared to LSTM alone

Factors influencing customer’s buying decisions on mobile phone buyers : a study on Bijapur City, India

The mobile phone has turned out to be a basic necessity in today world with multi-tasking ability based on user’s convenience and need. With staggering increase in mobile phone usage in India in recent years, people consider various factors before the purchase decision. This study is an effort to uncover the underlying factors that might affect customers in purchasing a mobile phone. Data were collected from those people those who live in Bijapur city maintaining equal ratios of various groups like male, female, businessmen, employees, students and others (housewives). To choose desired respondents, convenient sampling method was used. A structured questionnaire was designed based on the previous study with five points Likert scale was used to get responses. Factor analysis was used to elicit the underlying Factors that affect a mobile phone purchasing decision. The results show that the most important factor are physical attributes, pricing, battery life and service facilities, size and weight, friends and social group recommendations and advertising.peer-reviewe

Pregnancy with pancytopenia: an observational study

Background: Pancytopenia is the reduction in all three major cellular elements of blood; hence it is the simultaneous presence of anaemia, leukopenia and thrombocytopenia. Pancytopenia is associated with many maternal and foetal complications during pregnancy like maternal sepsis, postpartum haemorrhage, pre-eclampsia and preterm labour, IUGR and intrauterine foetal demise.Methods: The study was conducted at BLDE (Deemed to be) University, Shri B. M. Patil Medical College Hospital and Research Centre. It’s an observational study done from November 2019-April 2020. The participants enrolled in the study were subjected for further clinical and laboratory evaluation and followed for feto-maternal outcome.Results: The incidence of pancytopenia with pregnancy in this study was 3% and all the patients were vegetarian by diet along with vitamin B12 and folic acid deficiency. They were associated with different maternal and foetal complications.Conclusions: Proper dietary counselling and well-balanced dietary plans even with plant originate food can prevent the micronutrients deficiency and avoid the deleterious consequences like pancytopenia

PERFORMANCE ANALYSIS OF SYSTEM RESOURCES BY SERVER MONITORING

Abstract: Aiming at many monitoring systems focusing on real-time monitoring and so being difficult to more directly and conveniently understand the system performance issues by the data analysis and remote monitoring, this paper presents a system performance monitoring system, as servers being the core position in network, server monitors to the resources of systems and use multi-threading technology to collect data and process them, which can improve the collection efficiency. From the collected data of the system resources, the analysis has been done based on its usage and work load carried out in the system

Development of a rapid screen for the endodermal differentiation potential of human pluripotent stem cell lines.

A challenge facing the human pluripotent stem cell (hPSC) field is the variability observed in differentiation potential of hPSCs. Variability can lead to time consuming and costly optimisation to yield the cell type of interest. This is especially relevant for the differentiation of hPSCs towards the endodermal lineages. Endodermal cells have the potential to yield promising new knowledge and therapies for diseases affecting multiple organ systems, including lung, thymus, intestine, pancreas and liver, as well as applications in regenerative medicine and toxicology. Providing a means to rapidly, cheaply and efficiently assess the differentiation potential of multiple hPSCs is of great interest. To this end, we have developed a rapid small molecule based screen to assess the endodermal potential (EP) of hPSCs, based solely on definitive endoderm (DE) morphology. This drastically reduces the cost and time to identify lines suitable for use in deriving endodermal lineages. We demonstrate the efficacy of this screen using 10 different hPSCs, including 4 human embryonic stem cell lines (hESCs) and 6 human induced pluripotent stem cell lines (hiPSCs). The screen clearly revealed lines amenable to endodermal differentiation, and only lines that passed our morphological assessment were capable of further differentiation to hepatocyte like cells (HLCs)