Bansal Institute Of Research Technology & Science

Farmers’ perceptions of risks related to climate change significantly influence their adaptation behaviour and their responses to climatic stressors. The present study sought to develop and standardize a valid and reliable scale to quantify farmers’ risk perception of climate change. Using the Likert summated rating technique, an initial pool of 70 statements was generated based on a review of the literature and consultation with experts. After systematic editing and relevancy testing through expert judgment, 45 statements were screened, and 28 statements were subjected to item analysis using responses from 40 farmers in a non-sampled area. Based on discriminating power (‘t’ value > 1.75) and reliability criteria, 22 statements were finally selected for inclusion in the scale. The reliability of the scale was established using Cronbach’s alpha, which exceeded the acceptable threshold of 0.70, representing high internal consistency. Content validity was ensured through comprehensive coverage of climate-related risks affecting crop, livestock and livelihood systems. The final scale enables categorization of farmers into low, medium and high levels of climate change risk perception. The developed scale is a useful tool for researchers, extension professionals and policymakers to assess farmers’ risk perception and to design location-specific, evidence-based climate change adaptation and extension interventions.

This work presents a hybrid framework combining Adaptive Resonance Theory (ART) clustering with deep neural network–based molecular restoration for efficient, target-specific drug optimization. Drug–protein pairs are first encoded into vector representations and clustered using ART to form interpretable prototype classes. For a new protein target, the nearest ART prototype serves as an initial candidate. A Protein-Guided Drug Restoration (PGDR) module then refines these candidates by learning to reconstruct optimal drug vectors from perturbed, protein-conditioned inputs. The restored molecules are further optimized in latent space under efficacy and pharmacological constraints. Experiments on benchmark DTI datasets show that the framework enhances interpretability and candidate quality, providing a scalable and biologically grounded approach to drug repurposing and de novo design.

The rapid development of electronics and instrumentation in recent years has raised increasing concerns about electromagnetic interference (EMI). To address this issue, the present study investigates the potential of carbon foam for EMI shielding applications. The aim is to enhance the EMI shielding effectiveness of carbon foam by integrating three distinct types of magnetic oxide (MO) nanoparticles (NPs). Graphene-incorporated carbon foam (Gr@CF) was primarily synthesized by impregnating phenolic resin and 2 wt% of graphene into polyurethane (PU) foam, then stabilization and carbonization at 1000°C in a nitrogen atmosphere. To further enhance the EMI shielding properties of the carbon foam, graphene-decorated MO-NPs (Gr@MO-NPs), specifically NiO, Co₃O₄, and Fe₃O₄, were individually incorporated. The addition of these Gr@MO-NPs resulted in a significant improvement in the EMI shielding performance. Among the various combinations tested, the carbon foam reinforced with graphene-decorated Fe₃O₄ NPs (Gr@Fe₃O₄-CF) exhibited an outstanding total EMI shielding effectiveness (SE T ) of 86.6 dB, a high absorption efficiency (SE A ) of 83.1 dB, and a low reflection efficiency (SE R ) of 3.5 dB. The remarkable EMI shielding absorption was attributed to the increased number of interfaces, defects, and dipole polarization within the foam, which facilitated the absorption and scattering of electromagnetic waves, enhancing the overall shielding performance. • Synthesis of carbon foams reinforced with graphene-decorated magnetic oxide nanoparticles, specifically NiO, Co₃O₄ and Fe₃O₄. • The resulting foams exhibited notable improvements in compressive strength, thermal stability, and EMI shielding properties. • Among them, the Gr@Fe₃O₄-CF achieved an SET of 86.6 dB, primarily attributed to the SE A of 83.1 dB and SE R of 3.5 dB. • These foams show strong potential for use as radar-absorbing materials, particularly in stealth and defense technologies.

The cyber threat environment, which was characterized by comparatively static and centralized attacks in form of botnets, has transformed with the explosive proliferation of IoT-enabled infrastructures. The proposed work presents an Edge-AI enabled hybrid deep learning architecture, being the first of its kind to combine both Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks in a single architecture to identify spatial traffic patterns and to capture the intricate temporal relationships between network flows, respectively. The proposed architecture targets the deployment of resource-constrained edge environments and satisfies the current cyber-physical systems with a compelling demand to have decentralized and low-latency threat intelligence. As compared to conventional cloud-based intrusion detection systems, we have reduced communication overhead and local intelligence allows detection in real-time. Broad empirical evaluation of hybrid CNN-LSTM model against current botnet datasets shows that hybrid network has an advantage over deep learning models employed alone in detecting stealthy and polymorphic botnet behaviors, displaying better accuracy, early-stage detection, and false positives. Potentially, this work goes beyond improving the existing paradigm of edge-enabled cybersecurity to create a basis of autonomous and adaptive threat detection systems in changing IoT-driven environments.

Low-energy-demand buildings are increasingly using "mechanical ventilation with heat recovery (MVHR)" applications to improve thermal comfort and reduce ventilation energy loss. MVHRs are often used in conjunction with an additional air heater to satisfy the need for room heating in retrofitted buildings. Therefore, it is crucial to assess how MVHR and heat emitters interact and how this affects the features of indoor airflow. In this study, the effects of a combination MVHR-fan-coil unit in the heating phase on thermal comfort parameters in a retrofitted room are investigated via "a computational fluid dynamic (CFD)" simulation. Numerical simulation results allow for the assessment of indoor thermal comfort as well as the resolution of the fan coil and MVHR interactions. Additionally, investigate the turbulent airflow characteristics in winter and summer season. The result indicate that relocate the fan coil position from left side to middle of the external wall increases the room temperature. Installing the inlet vent in ceiling shows a no changes in the room temperature. It observed that Case 2 exhibited the highest temperature inside the room at 23.3 ºC, while Case 1 and Case 3 both had a room temperature of 22.6 ºC and 22.5 ºC respectively. The average temperature across all six planes followed a similar pattern, Case 2 consistently showing higher temperatures.

The tribological behaviour of powder metallurgy-synthesised aluminium/Al2O3/Graphene has been investigated. The crystal structure, mechanical, and dry sliding wear behaviour of the manufactured composite were investigated. Advanced characterisation techniques like optical microscopy, SEM, and optical profilometer analysis were employed to investigate microstructure and worn surface morphology. The Universal Testing Machine's die and punch assembly was used to create four different cylindrical pre-forms with different Al2O3 content levels (0 wt.% %, 1 wt.% %, 3 wt.% %, and 5 wt.% %) at a compaction pressure of 120 KN. Different sintering temperatures of 490°C, 520°C, and 550°C have been achieved by using an Electrical Muffle Furnace. A pin-on-disc wear tester was used to study the sliding wear behaviour of a cylinder with a diameter of 12 mm against an EN-32 steel disc at a speed of 300 rpm and a distance of 4000 m in dry circumstances. Rockwell's Hardness machine with a 100 kg load applied at ball point is used to test hardness. Scanning Electron Microscopy (SEM) is used for micro-structural characterisation in order to look into the grain structure. Elevating the sintering temperature and adding more Al2O3 and 1% graphene made the specimen harder. Increasing the Al2O3 concentration and sintering temperature in experiments reduced wear. Microscopy by SEM showed that the Al2O3 particles were evenly dispersed throughout the aluminium matrix. Major Findings: Density increases with 5% Al2O3 content from 450°C to 490°C compared to 0%, 1%, and 3%. The specimen at 5% Al2O3 has low friction due to reduced wear than at 1%, 3%, and 5%. Innovative framework integration for mechanical and dry sliding behaviour enhancement.

This is to report a rare case of a large uterine mesothelial cyst that was previously misdiagnosed as hydrosalpinx in transvaginal ultrasound and that was diagnosed in a primary infertility patient. In a 31-year-old, primary infertility case, transvaginal sonography revealed an oblong, anechoic, partially septate complex lesion, which was located behind the uterus towards the left side of it, and it was preoperatively diagnosed as left hydrosalpinx measuring about 7.24 cm × 3.3 cm. Laparoscopic surgery revealed a large cystic lesion on the posterior wall of the uterus. Laparoscopic uterine cystectomy was performed after aspiration of the fluid, which was found to be straw coloured. The patient’s recovery was good. Histopathological examination confirmed the diagnosis of uterine mesothelial cyst. Uterine mesothelial cysts are not common, and they are abnormal pelvic masses. Clinicians should be aware of these lesions, and this awareness can contribute to better diagnosis as well as better and timely management of the case.

A series of 4-N-arylsubstituted semicarbazones of menthone was designed and synthesized to meet the structural requirements essential for anticonvulsant activity. All the compounds were evaluated for anticonvulsant activity. Anticonvulsant activity was determined after intraperitoneal (ip) administration to mice by maximal electroshock (MES) and minimal motor impairment was determined by convulsometer (Medicraft convulsometer). All the compounds were tested for anticonvulsant activity employing Maximal Electroshock method. As compared to standard phenytoin, the test compounds exhibited significant anticonvulsant activity ranging from 72.06%-184.33%. The order of potency of the test compounds was as follows 2 > 4 > 6 > 5 > 1 > 3. The effects of all these drugs were well comparable with standard drug phenytoin. However, the compound 2 was the most potent.