The HBTU was named after Sir Spencer Harcourt Butler, Governor of the United Provinces in British India. Its programs have been conferred in autonomous status under the university. It is one of the oldest engineering institutes in the country and holds the ISO 9001:2000 certification. It offers Bachelors, Masters, and Doctoral programs in engineering, natural sciences and humanities as well as Masters programs in Computer Application (MCA) and Business Administration (MBA).HBTU is the mother institute of the National Sugar Institute (in 1936, then known as Imperial Institute of Sugar Technology), the Government Central Textile Institute (in 1937), now known as the Uttar Pradesh Textile Technology Institute, Indian Institute of Technology Kanpur (IIT/K) in 1960, the Glass Institute and Rajkiya Engineering College Mainpuri (also known as Government Engineering College, GEC/M) in 2015. It was also one of the 127 technical institutions in India which were the recipients of funding from World Bank's International Development Association (IDA) in the phase one (2004–2009) of the Technical Engineering Educational Quality Improvement Project – the first World Bank project in Higher education in India.
A range of Ni-based catalysts were prepared by supporting nickel on gamma-Al2O3, SiO2, zeolites, and mesoporous materials using simple wet impregnation and co-precipitation techniques. Bimetallic and promoted systems (Ni-M = Co, Mo, W, Sn, La, and Cu) were systematically evaluated, with particular emphasis on Ni-Mo catalysts of varying Ni/Mo molar ratios. The catalysts were examined using techniques such as XRD, BET surface area analysis, H-2-TPR, H(2)pulse chemisorption, SEM, and(1)H NMR spectroscopy. The hydrodearomatization reactions were carried out in a fixed-bed continuous reactor under relatively mild operating conditions (200-250 degrees C, 10-30 bar H-2). Catalytic performance was strongly dependent on support nature, promoter metal, preparation method, and thermal pretreatment. Among monometallic systems, Ni/gamma-Al(2)O(3)exhibited superior activity compared to Ni/SiO(2)and zeolite-supported catalysts. Mo promotion significantly enhanced Ni dispersion and hydrogenation efficiency, with the Ni-Mo/gamma-Al(2)O(3)catalyst at a Ni/Mo molar ratio of 15:1 delivering the highest performance. Under optimized conditions, aromatic content in LAB raffinate was reduced from similar to 24 vol% to similar to 2.6 vol% with overall conversion exceeding 90%. The co-precipitated Ni-Al (2:1) catalyst demonstrated excellent stability during a 100-h continuous run, retaining similar to 80-90% activity and showing effective regeneration. The developed Ni-Al and Ni-Mo/Al(2)O(3)catalysts enable efficient, stable, and economically attractive upgrading of LAB raffinate into jet/rocket fuel-compatible products under relatively mild operating conditions, offering a viable alternative to noble-metal-based hydrotreating catalysts.
A new technique enabling to improve feature selection process based on weighted intuitionistic fuzzy (IF) similarity relation (WIFSR) is suggested in the present study. Firstly, we discuss a novel WIFSR by improving the idea of IF similarity relation. Secondly, IF granular structure (IFGS) is established on the basis of WIFSR. Thirdly, IF rough set model is outlined based on the idea of aforesaid IFGS. Next, positive region is computed based on the lower approximation of IF rough set. Then, dependency of decision dimension over set of conditional dimension is calculated based on positive region and cardinality of the decision system. With granular structures, features/dimensions can be represented with different levels of abstraction to provide a dynamic and flexible selection approach. Moreover, we present a WIFSR designed to measure the similarity between features by taking into account their relevancy and non-redundancy. Proposed approach effectively addresses the problem of feature selection by measuring degree of dependency between features in IFGS framework. Mathematical validation is illustrated for all the established notions. Proposed method is experimentally evaluated on various datasets, and we successfully demonstrate its efficiency in terms of determining the inherent features while safeguarding them from later uncertainty and noise. Our experimental results illustrate that the suggested approach, in the context of accuracy and standard deviation, outperforms the existing feature selection methods. At the end, a new scheme is demonstrated to enhance the overall prediction performances of machine learning methods for antiviral peptides.
Bergenia ciliata a himalayan medicinal herb, which has been traditionally used due to its extensive pharmacological properties. Nevertheless, the possible anticancer application on the molecular level has not been fully explored. This experiment was developed to determine the phytochemicals of B. ciliata as natural inhibitors of the epidermal growth factor receptor (EGFR), which is a major target in most epithelial cancers. Phytochemical data on the IMPPAT and PubChem databases were collected. The compounds were using SwissADME and ProTox-II on drug-likeness, absorption, and toxicity. Then six candidates with Lipinski rule and pharmacokinetics conditions were docked to EGFR (PDB ID: 4HJO) with AutoDock vina. The binding affinities of cianidanol and Leucocianidol were the highest, − 8.8 kcal/mol and − 8.7 kcal/mol respectively, as compared to the reference drug erlotinib which has a binding affinity of − 8.3 kcal/Mol. There were several hydrogen bonds and hydrophobic interactions with such critical residues as Lys_721, Thr_766, Asp_831 and Phe_832.Simulations of 100 ns of molecular dynamics showed constant RMSD (0.10–0.20 nm), low fluctuations of residues, and small radius of gyration of all the complexes. MM/PBSA required interactions revealed that the stabilization was dominated by van der Waals forces and electrostatic repulsions with the total binding energies of − 51 kJ/mol, − 46 kJ/mol, and − 34 kJ/mol with cianidanol, leucocianidol, and erlotinib respectively. The studies suggests that EGFR is strongly bound by B. ciliata phytochemicals, and their biocompatible profiles are safer and more inclined to biocompatibility compared to the conventional inhibitor. These findings have indicated that these compounds can be useful lead scaffolds in the development of anticancer drugs in future as they have been shown to possess promising properties that would be further validated by studies conducted in in vitro and in vivo.
In this study, a sustainable hybrid adsorbent based on chitosan (CS) and sodium carboxymethyl cellulose (Na-CMC) was successfully synthesized through solvent exchange and freeze-drying for dual applications in carbon dioxide capture and acid dye removal. The Na-CMC/CS hybrid was systematically characterized and evaluated for its multifunctional environmental remediation performance. Compared with pristine CS, the hybrid exhibited enhanced CO(2)uptake, reaching 0.18 mmol g(-1)at 298 K and 0.35 mmol g(-1)at 273 K. The higher uptake at lower temperature suggests exothermic adsorption behavior, while the isosteric heat of adsorption (Q(st)) provided additional insight into the interaction strength between CO(2)and the hybrid surface. In aqueous adsorption experiments using Acid Orange 56 (AO-56) as a model anionic dye, the hybrid showed superior removal efficiency (similar to 96% within 120 min) compared with pristine CS (similar to 83%). The maximum adsorption capacity reached approximately 99 mg g(-1)under acidic and neutral conditions, while adsorption decreased markedly under alkaline conditions (pH 12) due to electrostatic repulsion. Kinetic analysis showed that the pseudo-second-order model provided the best fit (R-2 > 0.98), indicating that chemisorption plays a dominant role in dye uptake. Intra-particle diffusion analysis suggested that diffusion contributes to the adsorption process but is not the sole rate-limiting step, while Elovich modeling confirmed surface heterogeneity and variable activation energies. In addition, the CO(2)adsorption energetics were assessed through isosteric heat of adsorption (Q(st)), providing insight into the interaction strength between CO(2)molecules and the hybrid adsorbent. Overall, the Na-CMC/CS hybrid demonstrates strong potential as an eco-friendly multifunctional sorbent for integrated CO(2)capture and dye-laden wastewater treatment.
Plant-based milk analogues are suitable substitutes for animal milk, more environmentally friendly, and sustainable. The microbiological stability, quality, anti-nutritional elements, and techno-functional properties of plant analogues and their proteins need to be considered. The type and concentration of reactive plasma species are influenced by parameters such as frequency, voltage, electrode spacing, treatment time, and gas composition. These factors regulate the efficacy of cold plasma in microbial disinfection and enzyme inactivation. The results indicate that cold plasma enhances the solubility, emulsifying properties, hydrophilicity, and foaming characteristics of plant-based analogues and proteins. In this study, the most potential sources of cold plasma and their impact on the functional characteristics of plant milk and proteins are thoroughly discussed. The work presents current insights into cold plasma for plant-based milk analogues and highlights their prospective applications, recent research, and developments in the field.
