Grafting enhances drought stress tolerance by regulating the proteome and targeted gene regulatory networks in tomato.

Tomato (), a widely cultivated yet perishable crop, depends heavily on adequate sunlight and water for optimal growth and productivity. However, due to unavoidable environmental and climatic changes-particularly drought-its productivity has declined in recent years. Grafting, an ancient horticultural practice, is known to enhance yield and combat abiotic stress by regulating physiological and cellular processes.

A specialized training program enhances university students' knowledge, attitudes, and practices on volunteering: evidence from Oman.

The decreasing involvement of youth in voluntary practices necessitates training and mobilizing them for voluntary activities. Therefore, the present study aimed to develop and test the efficacy of a culture-sensitive training program on enhancing knowledge, attitude, and practice (KAP) of volunteering among university students in Oman. We adopted a quasi-experimental design with a pre-post-test on the KAP of volunteering and designed a specialized training program spanning 10 weeks.

Multilayered SDN security with MAC authentication and GAN-based intrusion detection.

Computer networks are highly vulnerable to cybersecurity intrusions. Likewise, software-defined networks (SDN), which enable 5G users to broadcast sensitive data, have become a primary target for vulnerability. To protect the network security against attacks, various security protocols, including authorization, the authentication process, and intrusion detection techniques, are essential.

Synthesis of a MXene/Metal-Organic Framework Composite for Efficient Supercapacitor and Electrocatalytic CO Reduction.

Metal-organic frameworks (MOFs) are remarkable electroactive materials for energy storage and electrochemical CO reduction (CORR) due to their high surface area and tunable pore structures. However, challenges such as stability, conductivity, and product selectivity at high current densities must be addressed to realize their full potential. We crossbreed a zeolite imidazolate framework-8 (ZIF-8)-based MOF with MXene using a simple layer-by-layer deposition technique and investigate the supercapacitive and CORR performances.

Dosimetric accuracy of low dose rate volumetric modulated arc therapy delivery in an Elekta Versa HD linear accelerator for pulsed low dose rate treatment of recurrent high-grade glioma using Monaco planning system: Low dose rate VMAT-based PLDR in Elekta Linac.

Background And Purpose: Reducing the dose rate enhances efficacy in radiation therapy by allowing increased repair of sub-lethal damage. Pulsed low-dose radiation therapy (PLDR) is an innovative approach that is safe and effective for the reirradiation of recurrent gliomas and radioresistant tumors. In this study, the accuracy of the low dose rate volumetric modulated arc therapy (VMAT) delivery is tested in an Elekta Versa HD linear accelerator (linac) for delivering PLDR.

Whitlockite nanoparticles: A multifaceted magnesium calcium phosphate ceramic.

Bioceramics are widely used in tissue engineering due to their tremendous potential in tissue regeneration and biomedical applications. Of all bioceramics, the "Whitlockite" is an ideal material with remarkable potential and distinctive properties. Over the past decade, Whitlockite (nWH), a magnesium-containing calcium phosphate, has gained intense attention in biomedical research.

QSPR graph model to explore physicochemical properties of potential antiviral drugs of dengue disease through novel coloring-based topological indices.

Dengue is a viral disease transmitted to humans through mosquito bites. Researchers have investigated various drugs with potential antiviral properties against it. Some of the promising antiviral drugs include UV-4B (N-9-methoxynonyl-1-deoxynojirimycin), Lycorine, ST-148, 4-HPR, Silymarin, Baicalein, Quercetin, Naringenin, Nelfinavir, Ivermectin, Mosnodenvir (JNJ-1802), NITD-688, Metoclopramide, JNJ-A07 and Betulinic acid.

Development of 1,2,3-Triazoles as Dual Enzyme Inhibitors Targeting α-Amylase and α-Glucosidase for Type 2 Diabetes Intervention.

A series of fifteen 1,2,3-triazole derivatives 6(a-o) were developed and evaluated for their inhibitory effects on carbohydrate-hydrolyzing enzymes implicated in Type 2 diabetes management. The compounds were assessed through in silico studies (including molecular docking and ADME predictions) and in vitro assays such as α-amylase, α-glucosidase, and antioxidant activities. Notably, the compounds 6a, 6d, 6g, 6h, 6k, 6l, and 6n exhibited dual inhibition against both enzymes.

RGB image dataset for okra maturity classification to enhance agricultural quality and market readiness.

Okra is a highly nutritious farming product that combats malnutrition issues while supporting sustainable agricultural methods. In order to keep its quality and versatility in preparation applications, it is important to classify its maturity stages into under-mature, mature, and over-mature categories. Classification is vital to identify the best time to harvest, satisfy market demands, minimize post-harvest losses, and optimize cooking uses.

Quinoline derivatives' biological interest for anti-malarial and anti-cancer activities: an overview.

Quinoline is a heterocyclic compound that plays a fundamental role in the study of chemical compounds, highlighting its importance in drug development. Its basic framework is crucial for synthesizing new pharmaceutical substances and facilitating the development of innovative drugs with significant therapeutic potential. A thorough examination of quinoline and its various derivatives, which exhibit a wide range of biological activities, greatly contributes to groundbreaking drug discoveries that can transform the medical industry.

Effect of Pyrolysis Temperature on the Physicochemical Properties and Structural Characteristics of Agricultural Wastes-Derived Biochar.

The efficient handling of agricultural waste is rapidly gaining worldwide recognition. This study analyzes the impact of three distinct pyrolysis temperatures (250, 300, and 350 °C) on the physicochemical properties of the biochar produced from rice husk, sugarcane bagasse, and groundnut shells with a fixed pyrolysis time of 3 h. The influence of the pyrolysis temperature was assessed by calculating the biochar yield, electrical conductivity (EC), pH, proximate analysis, and ultimate analysis.

Mixed-linker approach employing a flexible monomer for constructing highly crystalline multiple-component covalent organic frameworks.

Covalent organic frameworks (COFs) are emerging as promising materials across diverse fields, including catalysis, gas storage, water harvesting, and energy storage. Traditionally, COF development relies on the two-component synthesis approach, where two organic monomers with specific reactive sites are strategically combined to form well-ordered frameworks in specific topologies. Although this approach has been effective, it inherently restricts the structural diversity of COFs unless new linkers are introduced, limiting the range of properties achievable.

In Silico Assessment and Quantitative Estimation of Potential Toxic Impurities From Propafenone (PFN) Through Generic Route and Using UPLC-MS/MS Technique.

The generic and most probable synthetic route for the preparation of propafenone (PFN) has been evaluated, common toxic impurities have been identified, their in silico toxicity has been assessed, and novel UPLC-MS/MS method was developed for the identification and quantification of five potential toxic impurities (PGIs) in the active pharmaceutical ingredients of PFN, a Class 1C antiarrhythmic agent. Five PGIs were identified for this study, namely 1-2-3-amino impurity, 1-2-2-hydroxy impurity, 1-2-oxiran impurity, propafenone, EP-Impurity-C, and EP-Impurity-E and were validated following the International Conference of Harmonization (ICH) guidelines, this methodology is capable of quantifying five PGIs at 1.6 ppm with a sample concentration of 20 mg/mL.

Multi-objective hybrid optimized coil design for enhanced efficiency, improved voltage gain, and compactness for inductive power transfer.

With a rising global population and vehicle usage, electric vehicles (EVs) have emerged as a sustainable solution for carbon neutrality. The paper's main objective is to test the performance of the optimized coil design for the Inductive power transfer (IPT) prototype designed for 48 V light EV (LEV) applications operating at 86 kHz. The coils are optimized for objectives such as compactness and power transfer efficiency, using a hybrid multi-objective optimization algorithm combining Taylor-series tuning and Dove Swarm (DSO) optimization.

Association Between Ambient Air Pollution and Increased Risk of Respiratory Diseases in Vellore and Ranipet, Tamil Nadu, India: A Retrospective Study.

Numerous studies have shown a link between short and long-term exposure to air pollution and a wide range of illnesses. Although the etiology of these illnesses has been identified, modifiable risk factors remain unclear. Furthermore, exposure to environmental toxins does not necessarily result in illness for all individuals.

Targeting Nrf2 in acute myeloid leukemia: an updated review on its role in chemoresistance and emerging therapeutic strategies.

Acute myeloid leukemia (AML) is an aggressive hematologic malignancy characterized by the clonal expansion of primitive hematopoietic stem cells. Despite therapeutic advances, including chemotherapy, hypomethylating agents, and FLT3 inhibitors, resistance and relapse remain major clinical challenges. One of the contributors to chemoresistance in AML is the nuclear factor erythroid 2-related factor 2 (Nrf2), a transcription factor that regulates redox homeostasis and promotes cell survival under oxidative stress.

A lightweight multi round confusion-diffusion cryptosystem for securing images using a modified 5D chaotic system.

In recent years, technological advancements have made the transmission of confidential information spooky. This research proposes a modified 5D chaotic map and a new image encryption algorithm based on an integrated chaotic system developed with SHA-512 hashing and a confusion-diffusion architecture. The modified 5D chaotic map provides randomness, and its performance is evaluated through a bifurcation diagram and Lyapunov exponent.

An innovative Squid Game Optimizer for enhanced channel estimation and massive MIMO detection using dilated adaptive RNNs.

The Multiple-Input Multiple-Output (MIMO) system can provide improved spectral efficiency and energy performance. However, the computational demand faced by conventional signal recognition techniques has significantly increased due to the growing number of antennas and higher-order modulations. To overcome these challenges, deep learning approaches are adopted as they offer versatility, nonlinear modelling capabilities, and parallel computation efficiency for large-scale MIMO detection.

Leveraging data analytics to revolutionize cybersecurity with machine learning and deep learning.

The exponential growth of digital technologies has brought about a surge in the complexity and frequency of cyber-attacks, necessitating robust cyber security measures. This study introduces an innovative approach to cyber security data analysis by leveraging Convolutional Neural Network (CNN) technology. The primary objective is to explore the potential of CNNs in accurately and efficiently detecting and classifying cyber security threats.

Emerging nanotherapeutics for HPV-associated cancers: current advances, challenges, and future directions.

Human Papillomavirus or HPV are viruses belonging to the family Papillomaviridae, these have double-stranded circular DNA. HPV is among the most common sexually transmitted infections which affect over 50% of the adult population. It is also responsible for approximately 5% of total cancer cases.

Molecular dynamics simulations of perforin mutations associated with familial hemophagocytic lymphohistiocytosis type 2 among Indian patients.

Cytotoxic lymphocyte pore-forming protein termed perforin-1 (PFP) produced by NK and CD8 T cells plays a critical role in viral and tumor-related immunity. Deleterious mutations in the gene encoding PFP lead to its dysfunction and impaired cytotoxic activity, causing hemophagocytic lymphohistiocytosis. Familial hemophagocytic lymphohistiocytosis type 2 is a rare, life-threatening, hyperinflammatory disorder that predominantly affects infants and children.

Period-doubling cascade to chaos and optimal quadratic harvesting in a prey-predator-scavenger model using Crowley-Martin functional response.

In the present article, a prey-predator-scavenger model is proposed and investigated with quadratic harvesting of predator and scavenger populations. The system is assumed to follow the Crowley-Martin functional response to describe the interaction between prey and predator populations. The positivity and boundedness of the system with respect to positive initial conditions are established.

A novel method for optic disc localization using fast circlet transform and Chan-Vese segmentation.

Accurate localization and segmentation of the optic disc (OD) are considered crucial for the early detection of ophthalmic diseases such as glaucoma and diabetic retinopathy. Challenges such as image quality variability, high background noise, and insufficient edge information are often encountered by existing methods. To address these issues, an adaptive framework is proposed in which Fast Circlet Transformation (FCT) is combined with entropy-based features derived from retinal blood vessels for robust OD localization.

Hybrid Bayesian deep learning model for predicting urban heat island intensity in African cities.

Urban Heat Islands (UHIs), in which urban areas have higher temperatures than adjacent rural areas, lead to increased energy demand, poor air quality, and greater public health risks. These impacts are particularly significant in rapidly urbanizing regions of Africa, where climate-adaptive infrastructure has yet to be fully established. Here, we propose a hybrid predictive model derived from Bayesian Neural Networks (BNNs) for deep learning-based forecasting of Surface Urban Heat Island (SUHI) intensities across the African continent.

Physically crosslinked freeze-thaw cryogels reinforced with functional nanocellulose derivatives (CM-CNFs) derived from biomass for wound dressing applications.

Natural polysaccharides are abundant, cost-effective, renewable, accessible to modification, and possess biodegradable and biocompatible properties. Sugarcane bagasse, a widely available agro-industrial byproduct, was utilized as a source for preparing nanocellulose fibers (NCFs) and carboxymethyl cellulose nanofibers (CM-CNFs). A combination of chemical and mechanical processes was used to isolate the fibers, followed by carboxymethylation to introduce functional groups and enhance dispersion in polymer matrices.