Government of India

Indian Railways, the world's second-largest railway system under single management, faces complexity in freight operations due to limited advance visibility of freight railcar (FRC) demand in wagon units. Typically, 80–90% of daily demand is revealed only on day of loading or a day prior, while repositioning empty wagons requires over 72 h. This challenge is further intensified by just-in-time logistics and dynamic shipper behaviour. To address this, the study proposes a deep learning-based Long Short-Term Memory (LSTM) network to forecast short-term, commodity-wise, and location-specific FRC demand. Using historical data from January 2023 to September 2024, covering 83 Cement, 140 Coal, and 40 Iron & Steel commodity locations across 18 Indian Railway zones, the model is retrained weekly and generates daily forecasts using the preceding five days of demand, with each forecast based solely on information available up to the prediction date. Benchmarking against ARIMA, exponential smoothing, Croston's method, and Random Forest shows that the LSTM model consistently outperforms all baseline methods, achieving lower MAPE values of 17.41% (Cement), 15.68% (Coal), and 13.31% (Iron & Steel). It also maintains robust performance during volatile periods such as disruptions, with station-level accuracy ranging from 80.32% to 87.39%. The proposed model is integrated into a GIS-based decision support system that provides daily updated five-day forecasts to assist fleet managers in improving operational efficiency and asset utilization. The study is limited to three commodity groups within Indian Railways; broader external validation remains a future research direction.

Salmonella enterica serovar Richmond is an emerging pathogen from contaminated animal food, posing a risk of global foodborne outbreaks. Few reports have documented this species in live aquatic organisms. In this study, Salmonella Richmond COFI-RLBCAU-I was isolated from live Pangasianodon hypophthalmus, and its pathogenicity was tested on the three most culturable fish species, P. hypophthalmus, Labeo rohita, and Oreochromis niloticus. The results showed that the bacteria are non-pathogenic to these three species. Techniques, including β-hemolytic activity, Gram staining, biochemical tests such as IMViC, nanopore-based whole-genome sequencing, and in silico serotyping, identified this strain as S. enterica subsp. enterica serovar Richmond. The de novo-assembled genome totalled 4,919,008 base pairs with a GC content of 52.06

FLT3 is a critical therapeutic target for acute myeloid leukemia (AML), and its inhibition remains a key strategy in AML management. In this study, we optimized the known compound CHEMBL4444839 to design a novel analogue, CHEMBL4444839-Analogue, showing improved pharmacological and structural characteristics. Pharmacokinetic profiling evaluation revealed that the analogue had enhanced drug-likeness, metabolic stability, and intestinal permeability, along with reduced predicted toxicity. Molecular docking revealed that CHEMBL4444839-Analogue exhibited a binding energy of −10.4 kcal/mol versus −8.7 kcal/mol for the parent compound, forming additional hydrogen bonds and hydrophobic contacts with GLU661, CYS694, LEU818, and PHE830 in the ATP binding pocket. Molecular dynamics simulation over 100 ns demonstrated lower average RMSD (1.78 Å vs 2.34 Å) and reduced RMSF fluctuations at the activation loop and DFG-out region, indicating enhanced conformational stability. Free energy calculations confirmed higher thermodynamic stability of the analogue versus CHEMBL4444839. The analogue also restricted domain motion and improved residue correlation, indicating better stabilization of FLT3 in its inactive conformation. Incorporation of a fluorocyclobutane moiety significantly contributed to enhanced rigidity and optimized interaction geometry, collectively establishing CHEMBL4444839-Analogue as a more promising and selective FLT3 inhibitor for AML therapy. Docking of CHEMBL4444839 and its designed analogue was performed to analyze binding interactions and guide structural modifications. Pharmacokinetic and toxicity parameters were predicted using SwissADME, ADMETlab 2.0, and ProTox-II. Molecular dynamics simulations were executed with GROMACS 2023 using the CHARMM36 force field to assess conformational stability, followed by MM-PBSA and dynamic cross-correlation analyses. The integrated computational results demonstrated that CHEMBL4444839-Analogue achieved stronger binding affinity, reduced flexibility, and superior stability compared to the parent molecule, validating its potential as an optimized FLT3 inhibitor candidate for further biochemical and therapeutic evaluation.

The rising electromagnetic (EM) pollution in the telecommunication sector from electronic gadgets and wireless communication networks, and high demand for RADAR camouflaged technology, has caused an increased need for lightweight, high-efficiency, and wideband EM wave (EMW) absorbers. This review explores dielectric loss-driven recent advancements in microwave absorbing materials (MAMs), emphasising the roles of interfacial polarisation, conductive loss, and defect-dipole loss processes in their efficacy in detail. This article highlights different dielectric losses in a diverse range of materials in detail, including 3D-printed structures, biomass-derived carbon materials, carbon fibers, carbon nanotubes, conductive polymers, core-shell and yolk-shell structures, graphene, metal nanoparticles (NPs), MXenes, and various porous composites. The distinctive structure, electrical conductivity, and interfacial characteristics of these materials are intricately connected to their absorption of EMWs. We especially discussed not only the recent excellent different research outputs, but also the significant roles of different dielectric losses, resulting from the movement of electrons or charge carriers, and generated by polarisation processes, in the wave attenuation process. This review provides valuable mechanistic insights for the development of next-generation, sustainable, high-performing MAMs by summarizing significant breakthroughs and methods. The discussion may inform future efforts in EM pollution mitigation, stealth technology development, and electronic device safeguarding.

We provide the first known upper bounds for the packing dimension of weighted singular and weighted ω-singular matrices. We also prove upper bounds for these sets when intersected with fractal subsets. The latter results, even in the unweighted setting, are already new for matrices. Further, even for row vectors, our results enlarge the class of fractals for which bounds are currently known. We use methods from homogeneous dynamics, in particular we provide upper bounds for the packing dimension of points on the space of unimodular lattices, whose orbits under diagonal flows p-escape on average.