An excess of HMGB1 in the UF may be associated with infertility in women.

The friction stir welding (FSW) is a comparatively innovative solid-state joining process. This joining mechanism is extremely energy efficient, environment friendly and multitalented. The aim of this manuscript is better improvement to the relationship between in the welding parameters and mechanical properties of the aluminum alloy AA6061T-6 type using for the friction stir welding. The effect of the various processing parameters play an important role in the quality of welded joining and the processing parameters are tool rotational speed, traverse speed, axial force and tool geometry play. This paper examine the effect of the tool pin profile and the friction stir welding parameters that on the microstructure and mechanical properties of the aluminum alloy 6061 type for welded join prepared by friction stir welding . It has been establish that prefect grain microstructure is obtained by cylindrical pin profile but they using the square pin profile is a higher strength welded joints are formed. Index Terms-Friction stir welding, 6061 aluminium alloy, tool pin profile, tensile properties.

Object detection is a computer vision method that allows for the identification and localization of specific classes of objects in images or videos. It goes beyond simple object classification and helps provide a better understanding of the object in question. Object detection has numerous applications, including automating business processes like inventory management in retail [1]. It can detect objects that occupy between 2% and 60% of an image's area and clusters of objects as a single entity. Additionally, it can localize objects at high speeds, typically greater than 15 frames per second. Vehicle detection is a crucial component in the development of autonomous vehicles, enabling them to identify and perceive objects in their environment. It involves identifying and locating vehicles in image or video frames and has various applications in surveillance and security systems. There are different techniques and models for object detection, including traditional image processing methods and modern deep learning networks. Traditional methods like Viola-Jones, SIFT, and histogram of oriented gradients do not require historical data for training and are unsupervised. Popular image processing tools like OpenCV can be used for these techniques. On the other hand, modern deep learning networks like CNN, RCNN, YOLO, ResNet, RetinaNet, and MANet are supervised and efficient for object detection. Key Words: Deep learning, OpenCV, object detection

The post-COVID-19 situation occurs in people with a record of probably or showed SARS-CoV-2 infection, usually, three months from the onset of COVID-19 with signs that last for at least 2 months and it is not always explained by an alternative diagnosis. The global community is concerned about Post Coronavirus disease 2019 (COVID-19) complications and their impact on mental health. It is going to impact various spheres of life such as the economy, industries, worldwide market, human health, health care etc. It has also induced impairments in work and social functioning which leads to the elevation of mental disorders like stress, anxiety and depression among well-being. Objective: Since anxiety is not described specifically in Ayurveda but is only found as a symptomatic description, this article attempt to study the disease Post COVID Anxiety disorder and its symptomatology and pathogenesis (Samprapti) in Ayurveda. Data source: Charaka Samhita, Sushruta Samhita, Vagabhata Samhita and modern medical textbooks, scientific journals and online databases. Review Methods: The classical textbooks and modern textbooks and various scientific journals and other databases were reviewed manually. Results: Post Covid complications of anxiety can cause serious mental health issues, and has a huge impact on societies. Conclusion: The study intends to study the causes of mental health disorders (Chittodvega) in post covid patients.