Big data technologies are of tremendous interest to businesses, corporations and many large and small sectors. Its wide volume characterizes the critical need to manage big data. In particular, several conventional data processing methods and capabilities have proven unsatisfactory. The immediate need to control and cure the COVID-19 pandemic needed knowledge exchange between national and international organizations (e.g., virus and treatment data, contact tracing, multimedia data generated by telepresence applications such as Zoom, Google meet, etc.). The exchanging of details will contribute to the transmission of vast records, which will undoubtedly impact the privacy of the user. Thus, the transmission of big data, whether admissible under appropriate conditions or not, needs extra liability and cannot disregard the need to maintain privacy. This is only one indication of a recent pandemic usage of big data, and in an age of COVID-19 we will need better operational and technological steps to resolve protection and privacy concerns in the sense of big data applications. Big data protection issues are multifaceted with organizations working on cloud infrastructure. Security experts today are busier than ever before. But what is good quality protection and secrecy when it comes to a solution for business information? The emphasis of this paper is on protection and privacy concerns relating to Big Data in the cloud.

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The intersection of artificial intelligence (AI) and cognitive neuroscience has revolutionized the study of human memory, addressing longstanding challenges in data complexity and theoretical exploration. Human memory, a multifaceted cognitive process, has traditionally been studied through diverse scientific methodologies, yet these methods often struggle with the intricacies of memory-related data. AI, leveraging advanced computational capabilities such as machine learning and deep learning, offers unprecedented opportunities to decipher complex datasets from neuroimaging, electrophysiological recordings, and behavioral experiments. These technologies excel in pattern recognition, predictive modeling, and simulation, essential for unraveling the mechanisms underlying memory formation, consolidation, and retrieval..

Zoological parks and rescue centers in India serve as critical institutions for biodiversity conservation, education, research, and rescue efforts. This abstract explores their multifaceted roles and contributions to wildlife conservation in the country. In India, zoological parks and rescue centers play a pivotal role in the conservation of endangered species through species recovery programs and captive breeding initiatives. These institutions collaborate with research organizations and government agencies to conduct scientific research on animal behavior, genetics, and health, contributing valuable insights into species management and conservation strategies. They also serve as educational hubs, raising public awareness about the importance of biodiversity conservation through interactive exhibits, guided tours, and educational programs for schools and local communities. Furthermore, zoological parks and rescue centers in India are instrumental in the rescue and rehabilitation of injured, orphaned, or trafficked wildlife, providing veterinary care and temporary shelter to animals in need. They work closely with government bodies and non-governmental organizations to advocate for wildlife protection laws and support habitat restoration projects and wildlife corridors. Despite facing challenges such as funding constraints and ethical concerns related to captivity, these institutions continue to make significant strides in wildlife conservation and public engagement. Moving forward, they must prioritize animal welfare, expand conservation efforts, enhance visitor experiences, and strengthen collaborations to address these challenges effectively..