MANAGEMENT OF QUADRIPLEGIA INDUCED BY SPINAL CORD INJURY WITH PANCHAKARMA - A CASE STUDY

A 30 year old male patient with quadriplegia induced by spinal cord injury was treated with ayurvedic medicine and Panchkarma therapies. Patient presented with quadriplegia and inability to sit/stand even with support and having no bladder/bowel control. Spinal Cord Independence Measure (SCIM) was 16 showing high dependence and also muscle wasting was present. Patient had history of swimming pool accident causing fracture C4-C5 spine and fixation through surgery in 2011. Ayurveda explains this disease as Vatavyadhi. Snehana and Svedana formed the first line of treatment to pacify the vitiated Vata while Shalishashtikapindasveda and Matravasti worked as Balya for Mansa and Asthi dhatu and also Anulomana. Snehadhara improves motor and sensory system resulting in improved function of all limbs. Management was done with repeated admissions for Panchakarma therapy during which overall strength and reflexes improved with Spinal Cord Independence Measure (SCIM) score reaching 47 from original 16 indicating improvement in independence of patient from complete dependence to partial independence in six months time

MANAGEMENT OF SCIATICA THROUGH AYURVEDA: A CASE STUDY

In India low back ache is one of the most common emerging diseases which are affecting day to day life of people physically as well as psychologically. Low back ache is the second most common disorder causing disability. Among its various causes the most commonly appearing one is Sciatica. Sciatica is a condition in which pain starts from low back and radiates to leg mostly unilateral but in some, it may be bilateral also. In Ayurvedic perspective its features resemble to those of Gridhrasi. In Ayurvedic classics two types of Gridhrasi have been described namely Vataja and Vata-kaphaja. The case study being presented is of a 44yr old male patient suffering from Vataja gridharsi. Basti karma is the choice of treatment in cases of Gridhrasi where as Snehana/ Snigdha svedana is choice of treatment for any Vataja disorder. So, Panchakarma therapy in this case includes Patrapindasveda, Sarvang vashpasveda and Basti therapy along with oral medication assessed on the basis of Oswestry disability index. The results indicate that the patient improved in presenting features up to 68.75% as well as day to day activities were also performed effectively by him

Machine Learning-based Linear regression way to deal with making data science model for checking the sufficiency of night curfew in Maharashtra, India

The birthplace of the novel Covid-19 sickness or COVID-19 began its spread around Wuhan city, China. The spread of this novel infection sickness began toward the start of December 2019. The Covid-19 illness spreads from one individual to another through hacking, sniffling, etc. To stop the spreading of the novel Covid-19 infection the distinctive nation has presented diverse strategies. Some regularly utilized methods are lockdown, night curfew, etc. The fundamental intention of the systems was to stop the social events and leaving homes without serious issues. Utilizing a diverse system Covid-19 first stage can address for saving individuals. Presently the second influx of this novel Covid illness has begun its top from the mid of April-May. The second convergence of this novel Covid disorder flooded all through the world and in India too. To stop the spread of this novel Covid sickness India's richest state Maharashtra government constrained the decision of night curfew. In this paper, we are taking as a relevant examination the night curfew on a schedule of Maharashtra. Here, we study that this system may or may not be able to stop the spread of pandemics. We are using the Machine learning(ML) approach to managing regulate study this case. ML has various systems yet among all of those here we use Linear Regression for the current circumstance. The reproduced insight that readies the plan orchestrated to learn with no other person. Linear Regression is the affirmed strategy for looking over the connection between two sections. Between the two segments, one is astute and another is a seen variable

Machine learning-based Naive Bayes approach for divulgence of Spam Comment in Youtube station

In the 21st Century, web-based media assumes an indispensable part in the interaction and communication of civilization. As an illustration of web-based media viz. YouTube, Facebook, Twitter, etc., can increase the social regard of a person just as a gathering. Yet, every innovation has its pros as well as cons. In some YouTube channels, a machine-made spam remark is produced on that recordings, moreover, a few phony clients additionally remark a spam comment which creates an adverse effect on that YouTube channel.  The spam remarks can be distinguished by using AI (artificial intelligence) which is based on different Algorithms namely Naive Bayes, SVM, Random Forest, ANN, etc. The present investigation is focussed on a machine learning-based Naive Bayes classifier ordered methodology for the identification of spam remarks on YouTub

Machine learning-based Naive Bayes approach for divulgence of Spam Comment in Youtube station

In the 21st Century, web-based media assumes an indispensable part in the interaction and communication of civilization. As an illustration of web-based media viz. YouTube, Facebook, Twitter, etc., can increase the social regard of a person just as a gathering. Yet, every innovation has its pros as well as cons. In some YouTube channels, a machine-made spam remark is produced on that recordings, moreover, a few phony clients additionally remark a spam comment which creates an adverse effect on that YouTube channel.  The spam remarks can be distinguished by using AI (artificial intelligence) which is based on different Algorithms namely Naive Bayes, SVM, Random Forest, ANN, etc. The present investigation is focussed on a machine learning-based Naive Bayes classifier ordered methodology for the identification of spam remarks on YouTub

Ethyl 3-oxo-2-(2-phenyl­hydrazinyl­idene)butano­ate: a re-determination

The previous crystallographic studies [Wang et al. (2005 ▶). Huaxue Yanjiu 16, 29–32; Wang et al. (2007 ▶). Youji Huaxue, 27, 524] of the title compound, C12H14N2O3, gave only the unit-cell dimensions and an R factor with no other details available: the full structure is presented here. The eth­oxy group is disordered over two orientations with refined occupancies of 0.642 (15):0.358 (15). The nine C atoms and two N atoms of the 1-phenyl-2-(propan-2-yl­idene)hydrazine segment of the mol­ecule are close to being coplanar, with a maximum deviation of 0.0779 (14) Å for the phenyl­amino N atom and an intra­molecular N—H⋯O hydrogen bond generates an S(6) ring. In the crystal, pairs of C—H⋯O hydrogen bonds link mol­ecules into inverson dimers, generating R 2 2(16) loops