Beyond Reality: The Pivotal Role of Generative AI in the Metaverse

Imagine stepping into a virtual world that's as rich, dynamic, and interactive as our physical one. This is the promise of the Metaverse, and it's being brought to life by the transformative power of Generative Artificial Intelligence (AI). This paper offers a comprehensive exploration of how generative AI technologies are shaping the Metaverse, transforming it into a dynamic, immersive, and interactive virtual world. We delve into the applications of text generation models like ChatGPT and GPT-3, which are enhancing conversational interfaces with AI-generated characters. We explore the role of image generation models such as DALL-E and MidJourney in creating visually stunning and diverse content. We also examine the potential of 3D model generation technologies like Point-E and Lumirithmic in creating realistic virtual objects that enrich the Metaverse experience. But the journey doesn't stop there. We also address the challenges and ethical considerations of implementing these technologies in the Metaverse, offering insights into the balance between user control and AI automation. This paper is not just a study, but a guide to the future of the Metaverse, offering readers a roadmap to harnessing the power of generative AI in creating immersive virtual worlds.Comment: 8 pages, 4 figure

Profile Of Animal Bite Cases Attending Urban Health Centers in Surat City: A Cross-Sectional Study

Context: Exposure to dog bites is an important public health problem, these bites not only cause increase morbidity and mortality but also loss of work days and cost for treatment. Moreover, myths and practices amongst people prevent appropriate post exposure treatment. Objectives: The survey was conducted with objectives to study the epidemiological characteristics of victims of animal bite injuries and health seeking behaviour of persons with animal bite. Methodology: It was a cross-sectional study conducted among new cases of animal bites registered at Urban Health Centres of Surat city. Results: Out of total 337 cases of animal bites majority (48%) belongs to 15-45 years of age-group and 79 % were male. Ninety four percent of cases were bitten by stray dog. Children less than 15 years of age were more likely to provoke a bite (P< 0.05).Category II bites were seen in 198(59 %) of cases. In 89.8% cases lower extremities were affected. Only two hundred forty cases had attended the ARV clinic within 24 hours of bite. Only 65 % of cases had done the wound washing. Conclusion: Local treatment of the wound soon after a bite is an important step in the management of a case and this was lacking in most of the subjects. Efforts to eliminate the stray dogs are required

Healthcare in metaverse: a survey on current metaverse applications in healthcare

The COVID-19 pandemic has revealed several limitations of existing healthcare systems. Thus, there is a surge in healthcare innovation and new business models using computer-mediated virtual environments to provide an alternative healthcare system. Today, digital transformation is not limited to virtual communication alone but encompasses digitalizing the network of social connections in the healthcare industry using metaverse technology. The metaverse is a universal and immersive virtual world facilitated by virtual reality (VR) and augmented reality (AR). This paper presents the first effort to offer a comprehensive survey that examines the latest metaverse developments in the healthcare industry, which covers seven domains: telemedicine, clinical care, education, mental health, physical fitness, veterinary, and pharmaceuticals. We review metaverse applications and deeply discuss technical issues and available solutions in each domain that can help develop a self-sustaining, persistent, and future-proof solution for medical healthcare systems. Finally, we highlight the challenges that must be tackled before fully embracing the metaverse for the healthcare industry.Info-communications Media Development Authority (IMDA)National Research Foundation (NRF)Published versionThis work was supported in part by the Singapore University of Technology and Design-Zhejiang University (SUTD-ZJU) IDEA Seed Grant SUTD-ZJU (SD) 202101 and Grant SUTD SRG-ISTD-2021-165; in part by the SUTD-ZJU IDEA Grant SUTD-ZJU (VP) 202102; in part by the National Research Foundation, Singapore; in part by the Infocomm Media Development Authority under its Future Communications Research and Development Program; and in part by Association of Southeast Asian Nations (ASEAN)—India Collaborative Research and Development Scheme (ASEAN-India Science and Technology Development Fund (AISTDF) sponsored) Project under Grant CRD/2020/000369

Smart stock exchange market: A secure predictive decentralized model

Stock exchanges around the world are exploring the best possible solution that can improve trading efficiency, lower the risks and tighten secu- rity levels. The working and functioning of a stock exchange involves very hectic and cumbersome pro- cedures which are time consuming, cost inefficient and can be prone to numerous risks. Machine learning and Blockchain are most popular upcoming technologies. In this paper we present a novel secure and de- centralized intelligent stock market prediction model. We present a blockchain based solution for stock exchange model that uses machine learning accessible smart contracts. The machine learning model makes a prediction on the future of the stock market providing an intelligent solution for secure stock market

Secure Lending: Blockchain and Prospect Theory-Based Decentralized Credit Scoring Model

Credit scoring is a rigorous statistical analysis carried out by lenders and other third parties to access an individual's creditworthiness. Lenders use credit scoring to estimate the degree of risk in lending money to an individual. However, credit score evaluation is primarily based on a transaction record, payment history, professional background, etc. sourced from different credit bureaus. So, evaluating a credit score is a laborious and tedious task involving a lot of paperwork. In this paper, we propose how blockchain can provide the solution to decentralized credit scoring evaluation and reducing the amount of dependence of paperwork. Lending money is not always objective but subjective to every lender. The decision of lending involves different levels of risk and uncertainty, depending on their perspective. This paper uses the prospect theory to model the optimal investment strategy for different risk vs. return scenarios

Epidemiology Of Animal Bite Cases Attending Municipal Tertiary Care Centers in Surat City: A Cross-Sectional Study

Context: Animal bite, especially dog bite is an important public health problem in urban India. Socio-cultural practices and myths consider as major problem for post-exposure prophylaxis of animal bites. Objectives: To study the epidemiological characteristics and determinants of post-exposure prophylaxis of animal bite victims. Methodology: It was a cross-sectional study conducted among new cases of animal bites registered at Tertiary Care Centres of Surat city. Results: Out of total 382 cases of animal bites majority (58%) belongs to 15-45 years of age-group and 83 % were male. Stray dogs were involved in 94% animal bite cases. Majority (81%) of bites were unprovoked. Category II bites were seen in 204(54 %) of cases. In 81.4% cases lower extremities were affected. Only two hundred ninety two cases had attended the ARV clinic within 24 hours of bite. Only 75 % of cases had done the wound washing. Conclusion: Wound washing immediate after bite form the prime step of management of any animal bite which was absent in majority of cases

Lightweight Mutual Authentication Protocol for V2G Using Physical Unclonable Function

Electric vehicles (EVs) have been slowly replacing conventional fuel based vehicles since the last decade. EVs are not only environment-friendly but when used in conjunction with a smart grid, also open up new possibilities and a Vehicle-Smart Grid ecosystem, commonly called V2G can be achieved. This would not only encourage people to switch to environment-friendly EVs or Plug-in Hybrid Electric Vehicles (PHEVs), but also positively aid in load management on the power grid, and present new economic benefits to all the entities involved in such an ecosystem. Nonetheless, privacy and security remain a serious concern of smart grids. The devices used in V2G are tiny, inexpensive, and resource constrained, which renders them susceptible to multiple attacks. Any protocol designed for V2G systems must be secure, lightweight, and must protect the privacy of the vehicle owner. Since EVs and charging stations are generally not guarded by people, physical security is also a must. To tackle these issues, we propose Physical Unclonable Functions (PUF) based Secure User Key-Exchange Authentication (SUKA) protocol for V2G systems. The proposed protocol uses PUFs to achieve a two-step mutual authentication between an EV and the Grid Server. It is lightweight, secure, and privacy preserving. Simulations show that the proposed protocol performs better and provides more security features than state-of-the-art V2G authentication protocols. The security of the proposed protocol is shown using a formal security model and analysis.This work was supported by the Singapore Ministry of Education Academic Research Fund Tier 1 (R-263-000-D62-114)

Socio-Demographic, Clinical and Laboratory Profile of Leptospirosis Cases Registered At SMIMER, Surat

Context: Leptospirosis is a zoonotic disease with worldwide distribution caused by pathogenic leptospira. Leptospirosis is more prevalent in South Gujarat due to heavy rain fall and clay soil structure. The current study was conducted to analyse the profile of patients with Leptospirosis admitted in Surat Municipal Institute of Medical Education and Research (SMIMER), Surat. Methods and Material: This prospective study, involves patients visiting SMIMER hospital during the time period of 1st August to 31st October 2011 who were suspected for Leptospirosis. Their presenting complaints, examination findings, lab findings, treatment and outcome were recorded and analyzed based on the modified Faine’s criteria. Results: Among the 24 suspected cases of Leptospirosis, 14 (59%) were males and age of patients ranged from 10 to 65 years with mean age of 34 years. Fever, myalgia, and headache were predominant complaints and all had history of contact with animals or contaminated environment. Liver functions and renal functions were deranged in 96% and 63% cases respectively. Fifteen patients were found positive for Leptospirosis. Fifteen (63%) patients had Weil’s syndrome and 8 had ARDS. There were 4 deaths, all were males, had ARF and presented with systolic hypotension. Conclusions: The disease prevalence usually increases during rainy season. Most cases were from rural origin and all had history of contact with animals. Myalgia (calf tenderness), jaundice and conjunctival suffusion were characteristic physical examination findings. Jaundice and renal failure are associated with severity of the disease and are considered bad prognostic signs with high mortality rate (16%)

ViSHWaS: Violence Study of Healthcare Workers and Systems—a global survey

Objective To provide insights into the nature, risk factors, impact and existing measures for reporting and preventing violence in the healthcare system. The under-reporting of violence against healthcare workers (HCWs) globally highlights the need for increased public awareness and education.Methods The Violence Study of Healthcare Workers and Systems study used a survey questionnaire created using Research Electronic Data Capture (REDCap) forms and distributed from 6 June to 9 August 2022. Logistic regression analysis evaluated violence predictors, including gender, age, years of experience, institution type, respondent profession and night shift frequency. A χ2 test was performed to determine the association between gender and different violence forms.Results A total of 5405 responses from 79 countries were analysed. India, the USA and Venezuela were the top three contributors. Female respondents comprised 53%. The majority (45%) fell within the 26–35 age group. Medical students (21%), consultants (20%), residents/fellows (15%) and nurses (10%) constituted highest responders. Nearly 55% HCWs reported firsthand violence experience, and 16% reported violence against their colleagues. Perpetrators were identified as patients or family members in over 50% of cases, while supervisor-incited violence accounted for 16%. Around 80% stated that violence incidence either remained constant or increased during the COVID-19 pandemic. Among HCWs who experienced violence, 55% felt less motivated or more dissatisfied with their jobs afterward, and 25% expressed willingness to quit. Univariate analysis revealed that HCWs aged 26–65 years, nurses, physicians, ancillary staff, those working in public settings, with &gt;1 year of experience, and frequent night shift workers were at significantly higher risk of experiencing violence. These results remained significant in multivariate analysis, except for the 55–65 age group, which lost statistical significance.Conclusion This global cross-sectional study highlights that a majority of HCWs have experienced violence, and the incidence either increased or remained the same during the COVID-19 pandemic. This has resulted in decreased job satisfaction