EFFICACY OF INTEGRATED APPROACH OF YOGA THERAPY (IAYT) ON OLD DESTITUTE WOMEN

The geriatric population is highly prone to decreased quality of life, stress along with various other issues. There is a greater risk involved when it comes to both communicable and non-communicable diseases. With rapid urbanisation the elderly face age related psychological and physiological issues. The aim of the present study is to evaluate the change in Quality Of Life (QOL) and Perceived Stress (PS) when the old destitute women were subjected to practice of Integrated Approach of Yoga Therapy. A pre-post study was conducted. The Yoga module included loosening exercises, breathing practises, Asanas, Pranayama, MSRT Meditation, Bhajans. The data collected was assessed after 2 months of Yoga intervention. The questionnaire used were WHO QOL-BREF and PSS. The Yoga group reported reduction in Perceived Stress Scale score and increase in score in 3 domains of Quality Of Life Questionnaire namely Physical parameter, Psychological parameter and Environment parameter. There was a marginal decrease in the score of social relationship domain of Quality Of Life Questionnaire. Hence destitute women showed marginal improvement in QOL and PSS. However, additional research and long term yoga intervention is needed to further evaluate the efficacy of yoga to improvise the QOL and stress levels

EFFICACY OF YOGA ON TRAUMA IN ORPHAN CHILDREN DWELLING IN ORPHANAGE HOMES: An EXPERIMENTAL PRE POST STUDY

Orphans and vulnerable children (OVC) are at increased risk for post-traumatic stress disorder (PTSD), depression and anxiety. They are at a substantially greater risk for developmental problems in cognitive, physiological, social, emotional, and behavioural domains. The aim of present study is to diagnosed the presence of trauma and  to study the effect of Integrated Approach of Yoga therapy on participants with post trauma stress disorder. Three orphanages were chosen for the study. The children were divided in to two groups experimental (n=21) and control group (n=21). The children were in the age group 7 to 12. CAPS-CA-5 for DSM-5 (Clinician Administered PTSN Scale child/Adolescent version for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) was administered prior to the intervention. Only children who satisfied the diagnostic criteria were selected. Yoga group underwent three months of Yoga program in a schedule of 90 min per day, five days per week whereas the Control group followed the routine activities Intervention was given by trained Yoga teachers at the Orphanage. The yoga module included Loosening Practices, Breathing practices, Asanas, Surya Namaskaras, Pranayama, Yogic Games, Devotional songs and Bhajans. Practices were given on weekdays and the participants were assessed after three months

YOGIC MANAGEMENT FOR HYPOTHYROIDISM: A CASE STUDY

The thyroid is butterfly shaped gland, and the pituitary gland (another gland located in the brain) regulates it. Hypothyroidism (underactive thyroid) refers to any state in which a person's thyroid hormone production is below normal. In Modern medicine Standard treatment for hypothyroidism involves daily use of the synthetic thyroid hormone levothyroxine (Levothroid, Synthroid, others). A patient might become dependent on these drugs for life.. We present a case where a patient was suffering from hypothyroidism for the last 6 months and got positive results by integrated approach with yoga therapy. The Patient was suffering for hypothyroidism with TSH level of 36.6. After the end of the yoga therapy the TSH level was reduced to 5.82.The patient did not undergo treatment with modern medicine

IMPROVING DETERMINISM OF WIRELESS/WI-FI USING CRITICAL NETWORK PARAMETERS

Techniques are described herein for improving wireless determinism by enhancing the Access Point (AP) join and client association processes. The AP join process may be enhanced by considering several factors to improve the determinism of wireless service. These factors include reliability, controller availability, network availability, and value-added services. Similarly, the client association process may also be enhanced by considering these factors to select a better AP / Service Set Identifier (SSID)

NODE AND SERVICE DISCOVERY IN WIRELESS LOCAL AREA NETWORK CONTROLLER CLUSTER ARCHITECTURES USING HYPERLEDGER

In the wireless cluster deployments, node discovery is a challenge. Further, it can be more challenging to discover the services running in such deployments. There are existing methods which use client side discovery and server side discovery that need a centralized Service Registry to maintain all available service instances. Presented herein are techniques that provide for the utilization of a private blockchain and HyperLedger in order to discover nodes and their services in wireless cluster deployments. Techniques of this proposal may provide for de‑centralizing node and service discovery in wireless cluster deployments without compromising authentication and security aspects. In one example, when a node comes up, it can authenticate itself with a Blockchain provider to be recognized as a legitimate node for a deployment. The node and services associated therewith would be added to the Ledger. The Ledger can be made available to all nodes in the deployment, which allows members to learn the node and service details and further communicate with the respective nodes for various services

SECURE INTERNET OF THINGS ONBOARDING USING PUBLIC KEY CRYPTOGRAPHY AND DIFFIE-HELLMAN INTEGRATED ENCRYPTION SCHEME

Techniques are described for using public key cryptography and blockchain methods to automatically and securely on-board Internet of Things (IOT) devices. This is an improvement over typical approaches in which IOT devices are on-boarded to Wi-Fi® networks with a pre-shared key that could be built-in or configured through out-of-band connectivity (e.g., Bluetooth®, Wi-Fi Protected Setup (WPS), etc.)

Nicotine-Induced Effects on Nicotinic Acetylcholine Receptors (nAChRs), Ca2+ and Brain-Derived Neurotrophic Factor (BDNF) in STC-1 Cells

In addition to the T2R bitter taste receptors, neuronal nicotinic acetylcholine receptors (nAChRs) have recently been shown to be involved in the bitter taste transduction of nicotine, acetylcholine and ethanol. However, at present it is not clear if nAChRs are expressed in enteroendocrine cells other than beta cells of the pancreas and enterochromaffin cells, and if they play a role in the synthesis and release of neurohumoral peptides. Accordingly, we investigated the expression and functional role of nAChRs in enteroendocrine STC-1 cells. Our studies using RT-PCR, qRT-PCR, immunohistochemical and Western blotting techniques demonstrate that STC-1 cells express several α and β nAChR subunits. Exposing STC-1 cells to nicotine acutely (24h) or chronically (4 days) induced a differential increase in the expression of nAChR subunit mRNA and protein in a dose- and time-dependent fashion. Mecamylamine, a non-selective antagonist of nAChRs, inhibited the nicotineinduced increase in mRNA expression of nAChRs. Exposing STC-1 cells to nicotine increased intracellular Ca2+ in a dose-dependent manner that was inhibited in the presence of mecamylamine or dihydro-β-erythroidine, a α4β2 nAChR antagonist. Brain-derived neurotrophic factor (BDNF) mRNA and protein were detected in STC-1 cells using RT-PCR, specific BDNF antibody, and enzyme-linked immunosorbent assay. Acute nicotine exposure (30 min) decreased the cellular content of BDNF in STC-1 cells. The nicotine-induced decrease in BDNF was inhibited in the presence of mecamylamine. We also detected α3 and β4 mRNA in intestinal mucosal cells and α3 protein expression in intestinal enteroendocrine cells. We conclude that STC-1 cells and intestinal enteroendocrine cells express nAChRs. In STC-1 cells nAChR expression is modulated by exposure to nicotine in a doseand time-dependent manner. Nicotine interacts with nAChRs and inhibits BDNF expression in STC-1 cells

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"Hand gesture recognition is a natural way of human computer interaction and an area of very active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research applied to Human-Computer Interaction (HCI) is to create systems, which can identify specific human gestures and use them to convey information or controlling devices. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. This paper presents a solution, generic enough, with the help of machine learning algorithms, allowing its application in a wide range of human-computer interfaces, for real-time gesture recognition. Experiments carried out showed that the system was able to achieve an accuracy of 99.4% in terms of hand posture recognition and an average accuracy of 93.72% in terms of dynamic gesture recognition. To validate the proposed framework, two applications were implemented. The first one is a real-time system able to help a robotic soccer referee judge a game in real time. The prototype combines a vision-based hand gesture recognition system with a formal language definition, the Referee CommLang, into what is called the Referee Command Language Interface System (ReCLIS). The second one is a real-time system able to interpret the Portuguese Sign Language. Sign languages are not standard and universal and the grammars differ from country to country. Although the implemented prototype was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.(undefined

A Novel Skin Disease Detection Technique Using Machine Learning

Skin sicknesses present critical medical care difficulties around the world, requiring precise and opportune location for successful therapy. AI became promising stuff for computerizing the discovery and characterization of skin illnesses. This study presents a clever methodology that uses the choice tree strategy for skin sickness location. In computerized location, we utilize an exhaustive dataset containing different skin sickness pictures, including melanoma, psoriasis, dermatitis, and contagious diseases. Dermatologists skillfully mark the dataset, guaranteeing solid ground truth for precise grouping. Preprocessing strategies like resizing, standardization, and quality improvement are applied to set up the symbolism for the choice tree calculation. Then, we remove applicable elements from the preprocessed pictures, enveloping surface, variety, and shape descriptors to catch infection explicit examples successfully. The choice tree model is prepared utilizing these removed elements and the named dataset. Utilizing the choice tree's capacity to learn progressive designs and choice principles, our methodology accomplishes an elevated degree of exactness in grouping skin sicknesses. Extensive experiments and evaluations on a dedicated validation set demonstrate the effectiveness of our decision tree-based method, achieving a classification accuracy of 96%. Our proposed method provides a reliable and automated solution for skin disease detection, with potential applications in clinical settings. By enabling early and accurate diagnoses, our approach has the capacity to improve patient outcomes, trim down healthcare overheads, and alleviate the burden on dermatologists

Load Flow Solution of Distribution Systems - A Bibliometric Survey

In this paper, Bibliometric Survey has been carried out on ‘Load Flow Solution of Distribution Systems’ from 2012 to 2021. Scopus database has been used for the analysis. There were total 1711 documents found on this topic. The statistical analysis is carried out source wise, year wise, area wise, Country wise, University wise, author wise, and based on funding agency. Network analysis is also carried out based on Co-authorship, Co-occurrence. Results are presented. During 2020 and 2018, there were 263 documents published which is the highest. ‘IEEE Transactions on Power Systems’ has published 90 documents during the period of study which is the highest in terms of articles under the category of sources. Highest citations were received by the article authored by Hung and Mithulanathan with 484 citations in the collected database with the chosen key words. VOSviewer 1.6.16 is the software that is used for the statistical analysis and network analysis on the database. It provides a very effective way to analyze the co-authorship, co-occurrences, citation and bibliometric analysis etc. The Source for all Tables and figures is www.scopus.com, The data is assessed on 6th July, 2021