Heavy consumption of energy devoted to reliance on fossil fuel sources, which resulted in a detrimental impact on the environment and health. These challenges can be effectively addressed through a sustainable-driven approach that prioritizes the utilization of visible light as a renewable energy source with green chemistry protocols for the production of H2 and value-added chemicals. MOF-based semiconductors are versatile photocatalysts with tunable band structure, abundant active sites, imp...

The abnormal cleavage of Amyloid Precursor Protein (APP), and the subsequent aggregation of the cleaved fragments, i.e. beta-Amyloid Polypeptides (Aβ40/42), are linked to the pathogenesis of Alzheimer’s disease (AD)(1). Although molecular chaperones of the proteostasis network look after the fragments and consequent aggregates, they become inefficient with age and stress that result in the accumulation of Aβ40/42 peptides(2,3). Herein, by combining different techniques, we report the impact o...

Financial misconduct within banks shows a persistent tension between the formal adoption of governance mechanisms and their substantive capacity to prevent illicit practices. The study investigates whether corporate governance quality reduces financial misconduct in Indian banks, a context characterised by strong regulatory oversight, persistent concerns about misconduct, and the coexistence of private and public ownership. Following agency and fraud diamond theory, this study argues that gov...

The global pursuit towards net-zero has intensified the demand for corporate transparency, with environmental disclosure emerging as a cornerstone of accountability. While scholarly attention has traditionally gravitated towards high-emitting manufacturing sectors, the banking industry occupies a unique yet underexamined position in the climate arena. Banks, despite having negligible direct emissions, are substantially exposed to climate risk through their lending portfolios, i.e., Scope 3 em...

High-frequency (>500 MHz) solar Type II radio bursts are rare and are believed to be manifes-tations of coronal shocks produced by explosive solar surface phenomena, such as solar flares and coronal mass ejections (CME). However, the exact cause of high-frequency Type II bursts remains debatable. The high-frequency burst events, observed from the limb, present a sce-nario where a comprehensive multi-wavelength and multi-vantage point approach could help to pinpoint the exact cause. We present...

On a few occasions, when the solar wind density near L1 drops by two orders of magnitude for a period exceeding 24 hours, the phenomenon is known as a disappearing solar wind (DSW) event. On 23 December 2022, Solar Orbiter (SolO) and STEREO-A (STA), positioned near 1 AU, detected such a DSW condition with an unusually low solar wind density (Np < 1 cm−3). Two days later, on 25 December 2022, Earth and Mars also encountered the similar DSW condition (Np ∼0.1-0.4 cm−3). In the present study, we...

Early and accurate disease diagnosis remains a critical bottleneck in modern healthcare due to scarcity of precise and sensitive detection methods [1]. Carbon quantum dots(CD) present finest sensing platforms due to their exceptional photostability, biocompatibility, and surface-engineering versatility [2,3]. Herein, unique surface-engineered biosensors are introduced; Zn-CD@Eu, CD@Tb and LysoDot for multiplexed detection of DPA,UA, EP, PPi, lysosomal-microviscosity; possessing excellent bioi...

Accurate and timely identification of breast cancer (BC) is crucial for effective clinical decision-making and treat-ment planning. Histopathological image analysis provides valu-able information for BC diagnosis, although manual assessment is labour-intensive and subject to differences between observers. In this work, a deep learning-based framework is developed to automatically classify breast histopathological images from the BreakHis dataset. The framework leverages an EfficientNet-based ...

Dental implants are widely used for oral rehabilitation, however their long-term success is often compromised by inadequate osseointegration and peri-implantitis. Ti–6Al–4V is a commonly used implant material due to its excellent mechanical properties, corrosion resistance, and biocompatibility. Nevertheless, bacterial colonization and the release of alloying ions may trigger inflammation and impair bone healing. This work aims to develop a functionalized titanium surface featuring strontium-...

Cottonseed hulls are abundant byproducts of the cottonseed oil industry and are rich in cellulose fibers (30-50 %). In this research, cellulose nanocrystals were synthesized from cottonseed hulls via acid hydrolysis followed by ultrasonication. We investigated two acid concentrations (50 % and 60 % (v/v)) and ultrasound amplitudes (30 % and 50 %) in the synthesis of cellulose nanocrystals. The effects of treatment conditions on the physical, thermal, and structural properties were assessed us...

The present study investigated the antidiabetic and hematinic potential of a millet-based rice analogue (MBRA) in streptozotocin (STZ)-induced diabetic Wistar albino rats. Diabetes was induced using STZ (50 mg/kg body weight), and animals were divided into five groups, namely normal control (G1), diabetic control (G2), STZ + white rice (G3), STZ + metformin (G4), and STZ + MBRA (G5). MBRA was supplemented at 20 g/day, and its effects on body weight, urinary glucose, serum biochemical paramete...

Vehicular Ad-Hoc Networks (VANETs) are the foun-dation of communication for the smart transportation of the future, but their efficiency is frequently hindered by the rapid change of topology and high mobility. An intriguing dilemma is that an effective routing process is affected by both fleeting topological transitions and high mobility. To mitigate the issues in this paper, a two step solution is proposed that integrates Machine Learning (ML) and Reinforecement Learning (RL). Initially, a ...

The rapid evolution of Intelligent Transportation Systems (ITS) has necessitated resilient Vehicular Ad Hoc Networks (VANETs) capable of maintaining high-reliability communication under extreme mobility and unpredictable urban topologies. While traditional protocols like AODV and GPSR struggle with control overhead and communication voids, existing Deep Reinforcement Learning (DRL) routing methods often suffer from catastrophic forgetting and ignore critical cross-layer physical constraints. ...

Windows Portable Executable (PE) malware detec-tion based on static feature extraction remains vulnerable to adversarial evasion attacks that manipulate file structure without altering functionality. Prior work demonstrated that a single deep neural network (DNN) trained with Fast Gradient Sign Method (FGSM) adversarial examples achieves improved robustness, but evaluated only one architecture and one attack type. In this paper, we present a systematic study extending that foundation across f...

Traditional VANETs struggle with coverage gaps and routing instability due to high mobility and static infrastructure. This paper proposes a congestion-aware, UAV-assisted framework integrating Predictive K-Means clustering for deployment and Deep Q-Network (DQN) routing with Conservative Q-Learning (CQL). The deployment strategy uses vehicle velocity vectors to proactively position UAVs at forecasted network hotspots. Simultaneously, the routing agent utilizes a multi-objective reward functi...

Euryale ferox Salisb. (fox nut) is an important aquatic crop cultivated in the stagnant water bodies of northeastern India, particularly in Bihar, Manipur, West Bengal, Assam, Uttar Pradesh, and Madhya Pradesh. Bihar contributes nearly 80% of global fox nut production; however, exploring the popping potential of seeds from other regions is essential for expanding sustainable production. This study investigated the influence of seed maturity on the popping quality characteristics of fox nut se...

The growing demand for sustainable and functional protein ingredients has intensified the search for alternative food biopolymers capable of replacing conventional animal-derived emulsifiers. Edible insect proteins offer a promising solution owing to their high nutritional value and low environmental footprint; however, limited knowledge of their techno-functional properties restricts their commercial utilization. Aligned with the United Nations Sustainable Development Goals (SDGs 9, and 12),...

Time Sensitive Networking (TSN) is currently highly needed in cyber-physical and Industrial Internet of Things (IIoT) domains. However, deploying it in harsh and changing environments such as underground mines is very difficult due to frequent node and link failures, interference, and unpredictable changes in the network structure. This research presents GDRL-MORP, a Graph-Driven Reinforcement Learning framework for Multi-Objective redundant path planning. The proposed model uses a Graph Neur...

The process of detecting and classifying malware has remained an ongoing challenge in cybersecurity since its incep-tion. Adversaries use dynamic code transformation techniques and malicious code concealment methods to defeat standard security measures. Signature-based systems display operational maturity yet function as reactive systems because their per-formance depends on previously obtained data. This paper presents a malware classification framework combining sandbox dynamic testing and ...