First report of the chloroplast and mitochondrial genomes of the Indian pitcher plant, Nepenthes khasiana Hook.f.

Objectives: Nepenthes, sometimes known as tropical pitcher plants or monkey cups, is a carnivorous plant genus that contains more than 160 species. Nepenthes khasiana, India's sole representative of the genus, is a rare and endangered dioecious plant endemic to North-east India. Despite the fact that it is a prominent insectivorous plant in the Nepenthaceae family, genomic resources for the species are limited, making genomic breeding and understanding the genetic basis of botanical carnivory difficult.

Development and experimental validation of a machine learning model for the prediction of new antimalarials.

A large set of antimalarial molecules (N ~ 15k) was employed from ChEMBL to build a robust random forest (RF) model for the prediction of antiplasmodial activity. Rather than depending on high throughput screening (HTS) data, molecules tested at multiple doses against blood stages of Plasmodium falciparum were used for model development. The open-access and code-free KNIME platform was used to develop a workflow to train the model on 80% of data (N ~ 12k).

Assessment of smartphone-based active distraction in association with audioanalgesia for overcoming airotor-related anxiety in children: a randomized controlled trial.

Background: Most children experience distress while visiting a dentist, above which the sound of the airotor and suction machine results in fear and difficulty in performing further procedures.

Methods: This was a randomized controlled parallel-group study of 40 children aged 6-13 years who required cavity preparation via the airotor. The children were randomly allocated to either Group 1 (Piano music app; active distraction combined with audio analgesia) or Group 2 (basic behavioural guidance alone).

Bidirectional approach of Punica granatum natural compounds: reduction in lung cancer and SARS-CoV-2 propagation.

The spreading of COVID-19 has posed a risk to global health, especially for lung cancer patients. An investigation is needed to overcome the challenges of COVID-19 pathophysiology and lung cancer disease. This study was designed to evaluate the phytoconstituents in Punica granatum peel (PGP), its anti-lung cancer activity, and in silico evaluation for antiviral potential.

Biomedical named entity recognition using improved green anaconda-assisted Bi-GRU-based hierarchical ResNet model.

Background: Biomedical text mining is a technique that extracts essential information from scientific articles using named entity recognition (NER). Traditional NER methods rely on dictionaries, rules, or curated corpora, which may not always be accessible. To overcome these challenges, deep learning (DL) methods have emerged.

COVID-19 status and utilisation of essential maternal and child healthcare services during the pandemic in Ahmedabad, India.

Background: Access to essential healthcare services is pertinent to the achievement of universal health coverage in any nation. The COVID-19 lockdown was used to mitigate the spread of the pandemic. Consequently, there was a reduction in the Utilisation of Basic Healthcare Services (UBHS) in diverse dimensions.

Tooth vitality and periapical healing: is Biodentine at par with MTA in regenerative endodontics?

Design: The study is a prospective, double-blinded randomised control trial that compares the mineral trioxide aggregate (MTA) and Biodentine as the pulp space barrier material after induction of a periapical blood clot by over-instrumentation for endodontic regeneration in single-rooted mature permanent anterior tooth (closed apex) with apical periodontitis (periapical pathology of more than 3 mm) and having necrosed pulp. A total of 36 patients were included in the study and after randomisation were allocated equally to both the groups out of which 31 patients returned for follow-up over an 18-month period. The treatment protocol consisted of two separate appointments.

Identification and suppression of low-frequency oscillations using PMU measurements based power system model in smart grid.

Low-frequency oscillations (LFO) are inherent to large interconnected power systems. Timely detection and mitigation of these oscillations is essential to maintain reliable power system operation. This paper presents a methodology to identify and mitigate low-frequency oscillations ( forced and inter-area) using a wide area monitoring system (WAMS) based power system model utilizing phasor measurement units (PMUs).

Optimized convolutional neural network using African vulture optimization algorithm for the detection of exons.

The detection of exons is an important area of research in genomic sequence analysis. Many signal-processing methods have been established successfully for detecting the exons based on their periodicity property. However, some improvement is still required to increase the identification accuracy of exons.

Non-targeted metabolomics reveals fatty acid and associated pathways driving resistance to whitefly and tomato leafminer in wild tomato accessions.

Wild tomato species exhibit natural insect resistance, yet the specific secondary metabolites and underlying mechanisms governing the resistance remain unclear. Moreover, defense expression dynamically adapts to insect herbivory, causing significant metabolic changes and species-specific secondary metabolite accumulation. The present study aims to identify the resistance-related metabolites in wild tomato accessions that influence the defense mechanism against whitefly (Bemisia tabaci Asia II 7) and leafminer (Phthorimaea absoluta).

Blockchain enabled traceability in the jewel supply chain.

This article examines the potential of blockchain technology to revolutionize the jewelry supply chain by enhancing trust, transparency, and efficiency. Utilizing Ethereum, we developed a blockchain network tailored to the industry's needs. Blockchain operates as a secure, immutable ledger, ensuring data integrity and transparency while preventing fraud and tampering due to its decentralized nature.

Forecasting of virtual power plant generating and energy arbitrage economics in the electricity market using machine learning approach.

Over time, the importance of virtual power plants (VPP) has markedly risen to seamlessly incorporate the sporadic nature of renewable energy sources into the existing smart grid framework. Simultaneously, there is a growing need for advanced forecasting methods to bolster the grid's stability, flexibility, and dispatchability. This paper presents a dual-pronged, innovative approach to maximize income in the day-ahead power market through VPP.

Optimized PID controller and model order reduction of reheated turbine for load frequency control using teaching learning-based optimization.

Load frequency control (LFC) systems in power grids face challenges in maintaining stability while managing computational complexity. This research presents an optimized approach combining model order reduction techniques with Teaching Learning-Based Optimization (TLBO) for PID controller tuning in single-area LFC systems. Three reduction methods-Routh Approximation, Balanced Truncation, and Hankel Norm Approximation-were implemented to reduce system order from 4th to 2nd order, achieving a 47.

Essential oils modulate virulence phenotypes in a multidrug-resistant pyomelanogenic Pseudomonas aeruginosa clinical isolate.

Pyomelanogenic P. aeruginosa, frequently isolated from patients with urinary tract infections and cystic fibrosis, possesses the ability to withstand oxidative stress, contributing to virulence and resulting in persistent infections. Whole genome sequence analysis of U804, a pyomelanogenic, multidrug-resistant, clinical isolate, demonstrates the mechanism underlying pyomelanin overproduction.

Advancing ex vivo functional whole-organ prostate gland model for regeneration and drug screening.

Model organisms are vital for biomedical research and drug testing but face high costs, complexity, and ethical issues. While newer techniques like organoids and assembloids have shown improvements, they still remain inadequate in addressing all research needs. In this study, we present a new method for maintaining the prostate gland of the earthworm, Eudrilus eugeniae ex vivo and examine its potential for regeneration and drug screening.

Artificial intelligence based prediction and multi-objective RSM optimization of tectona grandis biodiesel with Elaeocarpus Ganitrus.

Meta-heuristic optimization algorithms are widely applied across various fields due to their intelligent behavior and fast convergence, but their use in optimizing engine behavior remains limited. This study addresses this gap by integrating the Design of Experiments-based Response Surface Methodology (RSM) with meta-heuristic optimization techniques to enhance engine performance and emissions characteristics using Tectona Grandi's biodiesel with Elaeocarpus Ganitrus as an additive. Advanced Machine Learning (ML) models, including Artificial Neural Networks (ANN), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGB), and Random Trees (RT), were employed for predictive analysis, with ANN outperforming RSM in accuracy.

Applying YOLOv6 as an ensemble federated learning framework to classify breast cancer pathology images.

The most common carcinoma-related cause of death among women is breast cancer. Early detection is crucial, and the manual screening method may lead to a delayed diagnosis, which would delay treatment and put lives at risk. Mammography imaging is advised for routine screening to diagnose breast cancer at an early stage.

Identifying falsified COVID-19 vaccines by analysing vaccine vial label and excipient profiles using MALDI-ToF mass spectrometry.

The rapid development and worldwide distribution of COVID-19 vaccines is a remarkable achievement of biomedical research and logistical implementation. However, these developments are associated with the risk of a surge of substandard and falsified (SF) vaccines, as illustrated by the 184 incidents with SF and diverted COVID-19 vaccines which have been reported during the pandemic in 48 countries, with a paucity of methods for their detection in supply chains. In this context, matrix-assisted laser desorption ionisation-time of flight (MALDI-ToF) mass spectrometry (MS) is globally available for fast and accurate analysis of bacteria in patient samples, offering a potentially accessible solution to identify SF vaccines.

Enhanced multifaceted model for plasmon-driven Schottky solar cells with integrated thermal effects.

This paper explores the development of an opto-thermal-electrical model for plasmonic Schottky solar cells (PSSCs) using a comprehensive multiphysics approach. We simulated the optical properties, power conversion efficiencies, and energy yield of PSSCs with varying nanoparticle (NP) configurations and sizes. Our spectral analysis focused on the absorption characteristics of these solar cells, examining systems sized 3 × 3, 5 × 5, and 7  × 7, with NP radii ranging from 10 to 150 nm.

Condensate droplet roaming on nanostructured superhydrophobic surfaces.

Jumping of coalescing condensate droplets from superhydrophobic surfaces is an interesting phenomenon which yields marked heat transfer enhancement over the more explored gravity-driven droplet removal mode in surface condensation, a phase change process of central interest to applications ranging from energy to water harvesting. However, when condensate microdroplets coalesce, they can also spontaneously propel themselves omnidirectionally on the surface independent of gravity and grow by feeding from droplets they sweep along the way. Here we observe and explain the physics behind this phenomenon of roaming of coalescing condensate microdroplets on solely nanostructured superhydrophobic surfaces, where the microdroplets are orders of magnitude larger than the underlaying surface nanotexture.

Site-specific substitution in atomically precise carboranethiol-protected nanoclusters and concomitant changes in electronic properties.

We report the synthesis of [Ag(o-CBT)] abbreviated as Ag, a stable 8e⁻ anionic cluster with a unique Ag@Ag@Ag core-shell structure, where o-CBT is ortho-carborane-1-thiol. By substituting Ag atoms with Au and/or Cu at specific sites we created isostructural clusters [AuAg(o-CBT)] (AuAg), [AgCu(o-CBT)] (AgCu) and [AuAgCu(o-CBT)] (AuAgCu). These substitutions make systematic modulation of their structural and electronic properties.

Bioconvection of a radiating and reacting nanofluid flow past a nonlinear stretchable permeable sheet in a porous medium.

This study evaluates the unsteady laminar flow and heat and mass transfer of a nanofluid in the appearance of gyrotactic microorganisms. In this analysis, using the Darcy-Forchheimer flow inside the vicinity of a nonlinearly stretched surface with Brownian motion and thermophoresis impacts. Similarity conversion is familiar with reduced governing models into dimensionless variables, and "bvp4c," a MATLAB solver, is employed to find the computational outputs of this analysis.

A Novel Rhodamine Functionalized Schiff Base Type Ratiometric Fluorescent Chemosensor for the Sensing of Hg Ions; Experimental and Theoretical Approach.

A new Rhodamine functionalised Schiff Base sensor 3',6'-bis(diethylamino)-2-((4-hydroxybenzylidene)amino)spiro[isoindoline-1,9'-xanthen]-3-one (SBRB1) was designed and synthesized. The recognition ability of sensor SBRB1 towards Hg was studied by using UV-Vis and fluorescence spectroscopy. The fluorescence results showed that the sensor SBRB1 has specific selectivity as well as sensitivity towards Hg among other competitive metal ions as the fluorescence intensity at 479 nm quenched only in the presence of Hg.