India’s Emerging Technology Commercialization Policy: Lessons From The American Model

India, the world’s 4th largest economy (PPP) is riddled with dichotomies. It can be called the IT capital of the world, though 200 million people go without enough food each day. Is India using its scientific and technological prowess for national good? America has had a rich set of experiences in the areas of \u27Technology Commercialization and Licensing\u27. We present recommendations for India’s upcoming legislative deliberations. These are based on India’s current landscape and the success factors in America’s experiences in this arena. We see the following as essential immediate impact points: Policy Harmonization; Steady Budget Increase & Enforcement Institutions

A light shed on Lepton flavor universality in B decays

At the back of succeeding measurements of anomalies in semileptonic decays at several collider experiments hinting at the possible violation of lepton universality, we undertake a concise review of theoretical foundations of the tree- and loop-level b-hadron decays along with experimental environments. We revisit the world averages for $R_{D(D^*)}$, $R_{K(K^*)}$, $R_{J/\psi}$ and $R_{\eta_c}$, and provide results within the framework of the relativistic independent quark model in addition to the results from model-independent studies. A confirmation of these measurements would soon turn out to be the first observation of physics beyond the Standard Model giving a wider outlook on the better understanding of new physics.Comment: 8 pages, 3 figures, review pape

Purification and characterization of a Bacillus subtilis keratinase and its prospective application in feed industry

We have isolated a Bacillus subtilis strain (RSE163) from soil and explored for keratinase production. Keratinase was purified using chromatographic methods (Sephadex G-75 and Q Sepharose) resulting in 8.42-fold purification with 3303 U/mg specific activity.The purified enzyme displayed 3 bands in close proximity between 20 to 22 kDa in SDS-PAGE which were apparent to the zone of hydrolysis in gelatin zymogram. Enzyme was stable over a wide pH (7.0-10.0) and temperature (30 °C to 70 °C) range with optimum activity at pH 9.0 and 60 °C. Keratinase activity was stimulated in presence of Mn2+, β-mercaptoethanol and surfactants (Triton-X and Tween-80) and inhibited by Fe3+, Cd2+, K+, PMSF (phenyl methane sulfonyl fluoride) and other chelating and reducing agents. The enzyme efficiently hydrolyzed a variety of complex protein substrates (chicken feather, keratin hydrolyzate and casein) and enzyme kinetics parameters were determined using Lineweaver Burk plot (Km = 6.6 mg/ml, Vmax = 5 U/ml/min). Hydrolyzed feather keratin obtained through fermentation with B. subtilis RSE163 has been explored for its cytotoxicity using liver cell line (HepG2). No cytotoxicity has been determined up to 0.015% concentration of hydrolyzed product indicating its potential applicability as feed supplement

Exploiting Large Language Models (LLMs) through Deception Techniques and Persuasion Principles

With the recent advent of Large Language Models (LLMs), such as ChatGPT from OpenAI, BARD from Google, Llama2 from Meta, and Claude from Anthropic AI, gain widespread use, ensuring their security and robustness is critical. The widespread use of these language models heavily relies on their reliability and proper usage of this fascinating technology. It is crucial to thoroughly test these models to not only ensure its quality but also possible misuses of such models by potential adversaries for illegal activities such as hacking. This paper presents a novel study focusing on exploitation of such large language models against deceptive interactions. More specifically, the paper leverages widespread and borrows well-known techniques in deception theory to investigate whether these models are susceptible to deceitful interactions. This research aims not only to highlight these risks but also to pave the way for robust countermeasures that enhance the security and integrity of language models in the face of sophisticated social engineering tactics. Through systematic experiments and analysis, we assess their performance in these critical security domains. Our results demonstrate a significant finding in that these large language models are susceptible to deception and social engineering attacks.Comment: 10 pages, 16 tables, 5 figures, IEEE BigData 2023 (Workshops

RescueAlert-an accident detection and rescue mechanism

With the increase of vehicles and cars of different kind and the large movement that occurs every day on the roads it was natural to observe an increase in traffic accidents, but the real dilemma lies in how to make the rescue process efficient. The problem that we want to solve is the response of ambulances towards accidents and the lengthy registration process of patients in hospitals. In the above two scenarios, the manual process of calling the ambulance leads to delay in rescue of patients from an accident and the delay in registration of patient leads to delay in medication or treatment of the patient. We want to make the process more efficient by automating accident detection for increasing the efficiency of the ambulance rescue process and by sending the details of the patient before the patient reaches the hospitals for faster treatment of patients. Along with this, alert messages will be sent to the family or friends of the patients to notify them as soon as an accident is detected