Ramakrishna Mission

Electrochemical C-N coupling offers a sustainable route for the synthesis of urea from CO2 and N2. However, it is challenged by the scarcity of active and highly selective catalysts. In this study, we present a rational strategy to design transition metal (TM)-doped single-atom alloy (SAA) electrocatalysts. We investigated a CuFe bimetallic alloy as a host to enable facile coactivation of CO2 and N2. Through a multistep process using quantum mechanical calculations, 3d, 4d, and 5d TM dopants on the CuFe surface were screened to assess catalyst synthesizability, activity, and selectivity against competing pathways, including hydrogen evolution reaction, ammonia formation, and C2 product formation. Among all TMs, Ti, Cr, Mo, and W were identified as promising candidates that can form thermodynamically stable SAAs in the CuFe bimetallic alloy. W-doped CuFe emerged as the most selective and favorable candidate for urea production, and the electronic structure analysis revealed the origin of the high selectivity. While Cr and Ti catalysts showed overbinding due to high d-band centers, strong hybridization, and excessive charge transfer, the W dopant achieves an optimal electronic balance, enabling controlled back-donation to both N2 and CO2 molecules, facilitating dual activation. Mechanistic investigation revealed the reaction pathway involving a C-N coupling step to form the *NCON intermediate, with an activation free-energy barrier of 1.08 eV on W SAA. Cr, Mo, and Ti were relatively less active and selective. This work presents a rational strategy for designing SAAs for targeted C-N bond formation.

Major financial losses and a decrease in trust among consumers have resulted from the problem of credit card theft being exacerbated by the quick expansion of digital payments. Concerns regarding privacy, security, and regulatory compliance are raised by the expectation that sensitive data be gathered in one place by traditional centralized fraud detection systems. This study combines Horizontal Federated Learning (HFL) with Secure Multi-Party Computation (SMPC) to provide a privacy-preserving fraud detection framework that solves these problems. Institutions with different sample spaces can work together to train models using HFL without exchanging raw data, while SMPC keeps intermediate computation secret to stop data leaks during transmission and aggregation. Through experimental evaluation on a benchmark credit card fraud dataset, the best Post-SMPC global model achieved an accuracy of 96.00

Financial crimes involving money laundering present serious risks to the world financial system, which underscores the importance of accurate and private tools for detection. In order to identify money laundering while ensuring client privacy, this research recommends combining Horizontal Federated Learning (HFL) with Differential Privacy (DP). Following the training of a local logistic regression model on its specific dataset, each client combines the model parameters to produce a global model. Clients share updates after iteratively improving their local models with shared parameters. The highest overall individual performance was achieved by client-1 with an F1-score of 67.47

Atopic dermatitis (AD) is a chronic inflammatory skin disease with significant morbidity. Recognising the need for region-specific guidance, the Skin Allergy Research Society and Society for Eczema Studies have collaborated to develop updated, evidence-based guidelines tailored to the Indian context. These guidelines address AD management across all age groups, special populations while considering local epidemiology, healthcare infrastructure, and treatment accessibility. A structured Delphi consensus process was conducted among 23 dermatology experts over 3 months through virtual and in-person meetings. Literature from MEDLINE, Cochrane, and Google Scholar was systematically reviewed, and the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) approach was used to assess evidence quality. Clinical recommendations were refined through multiple voting rounds, leading to consensus statements. Recommendations are based on an extensive literature review up to December 2024. This document updates the 2019 Skin Allergy Society guidelines, reinforcing global recommendations while allowing local adaptability. These guidelines provide updated recommendations for topical, systemic, phototherapy, and biologic therapies in AD. Key advancements include the introduction of topical crisaborole and JAK inhibitors for mild to moderate AD, along with a focus on emerging systemic therapies, such as biologics and systemic JAK inhibitors. In the Indian context, the guidelines define the roles of dupilumab and abrocitinib while also addressing the off-label use of tofacitinib and baricitinib in resource-limited settings. Specific recommendations are provided for children, elderly patients, and pregnant women, emphasising safety considerations for systemic and biologic therapies. These guidelines align with global AD management while incorporating India-specific adaptations based on epidemiology, accessibility, and affordability. They serve as a key reference for dermatologists, pediatricians, and general practitioners in India and other resource-limited settings. Though tailored for India, they are also relevant to dermatologists in developing countries, guiding treatment selection based on disease patterns, environmental factors, and medication availability.