Conceptual study on Nidana of Pakshaghata

Health and ailing, pleasure and pain, ease and disease are inborn properties of human life, centuries and centuries succeeded in struggle between man and disease. The infliction of pain, either on mind or body or both is what Vyadhi means. Pakshaghata is one such Vyadhi where mind and body both are inflicted. Pakshaghat can be correlated with hemiplegia (due to hypertension). Hemiplegia is paralysis of one half of the body i.e. upper & lower limbs of the same side. It may be associated with weakness of facial muscle on the same side (ipsilateral hemiplegia) or opposite side (contralateral hemiplegia). Here in the present study an effort is made to better understand nidana of Pakshaghata (hemiplegia)

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

CoCo the Cool Robot Cat - (Home Safety Robot using AI, IoT, and DL).

<p><strong>This paper focuses on the development of a mobile robot cat, named Coco, which serves multiple purposes such as assisting visually impaired individuals, monitoring children while they study, detecting suspicious human activities in living areas, acting as a home security system, and functioning as a pet robot. The robot cat has five subsystems: an Artificial Intelligence (AI) voice assistant, a human activity monitoring system, a live video stream, an obstacle detection system, and a smart sensor module with alert notifications. The first subsystem is responsible for processing voice inputs with an AI voice assistant, which decodes and understands the input before generating voice outputs. This subsystem was implemented using the Python programming language on Raspbian OS. The second subsystem was developed using Keras and TensorFlow and is responsible for monitoring human activities and alerting the user via email if any suspicious activity is detected. The third subsystem streams live video over a network using OpenCV. The fourth subsystem uses backpropagation and forward propagation to control the motion of the robot cat. Finally, the fifth subsystem uses five types of sensors - the PIR sensor, MQ2 sensor, temperature sensor, voltage sensor, and LDR sensor - to detect motion, smoke and toxic gasses, temperature, and light. To implement these subsystems, a combination of Raspbian OS and Nodemcu (Arduino IDE) environment was used.</strong></p&gt