Challenges, Solutions, and Opportunities in Chiral Perovskites: From Synthesis Strategies to Technological Advancements.

The unique chiroptical characteristics of chiral perovskites are essential for controlling a range of optoelectronics and biological reactions. Designing and refining devices that depend on the interaction of chiral molecules with circularly polarized light require a thorough understanding of the principles of chiroptical characteristics. By adding appropriate chiral organic cations, these materials can be precisely tailored to provide tunable structural and optical properties that satisfy the unique needs of a variety of cutting-edge applications.

A study on different methods to change the Rayleigh number in the analysis of heat transfer.

This study provides awareness about natural convection and associated non-dimensional numbers like the Prandtl number, Grashof number, Rayleigh number, and Reynolds number. The main focus of this research is to present the different methods employed to vary the Rayleigh number [Formula: see text] in an extensive range. The research concludes that changing the gravity value to obtain the considerable variation in [Formula: see text] is also a possible method for conducting the numerical analysis and observing the impact of the Rayleigh number.

Enhanced production and structural characterization of exopolysaccharide from Sporocarcina psychrophile MTCC 2908 through two step optimization for therapeutic evaluation.

The production and extraction of Exopolysaccharide (EPS) from the bacterial strain Sporocarcina psychrophila (MTCC-2908) was carried out in submerged fermentation conditions, yielding 1.22 g/L in 48 h at unoptimized conditions. To enhance EPS yield, a two-stage optimization strategy was employed using Plackett-Burman design (PBD) for parameter screening, followed by central composite design (CCD) for optimization.

Contextual information based anomaly detection for multi-scene aerial videos.

Aerial video surveillance using Unmanned Aerial Vehicles (UAV) is gaining much interest worldwide due to its extensive applications in monitoring wildlife, urban planning, disaster management, anomaly detection, campus security, etc. These videos are processed and analyzed for strange/odd/anomalous patterns, which are essential requirements of surveillance. But manual analysis of these videos is tedious, subjective, and laborious.

Design, synthesis and evaluation of benzodioxole and bromofuran tethered 1,2,4-triazole hybrids as potential anti breast cancer agents with computational insights.

1,2,4-Triazole derivatives are the focus of extensive research in medicinal chemistry because of their diverse biological activities, particularly their potential as anticancer agents. In this study, we designed and synthesized six compounds featuring benzo[d][1,3]dioxole and 5-bromofuran tethered to 1,2,4-triazole hybrids. This was achieved through an efficient four-step protocol with reproducible results.

Adsorptive removal of fluoride from water using hydroxyapatite synthesized from marine shell waste.

Fluoride contamination in groundwater threatens human health and ecological systems, necessitating cost-effective and efficient remediation strategies. This study synthesized hydroxyapatite (MRS-HAp) from Marcia recens shells through chemical precipitation to serve as a potential adsorbent for the removal of fluoride. The prepared MRS-HAp exhibited a specific surface area of 100.

Waste-derived Ag@Cu-MOF with semiconductor functionalized nano-hybrid heterostructures for photocatalytic CO conversion to methanol fuel.

Photocatalytic reduction of carbon dioxide (CO) presents an inspiring strategy to mitigate climate change and produce solar fuels. Incorporating green synthesis materials into photocatalysis presents substantial promise for sustainable environmental solutions, particularly in the process of turning CO to solar fuels. Green-synthesised compounds, such as copper oxide (CuO), silver (Ag), and copper-1,4-benzenedicarboxylate (CuBDC), are investigated for the photocatalytic reduction method of producing solar fuels from CO.

Q‑Learning-Based Multivariate Nonlinear Model Predictive Controller: Experimental Validation on Batch Reactor for Temperature Trajectory Tracking.

This study introduces a Q-learning-based nonlinear model predictive control (QL-NMPC) framework for temperature control in batch reactors. A reinforcement learning agent is trained in simulation to learn optimal control strategies using coolant flow rate and heater current as inputs. The resulting policy, represented as a Q-table, is implemented in real time on a physical reactor setup using the NVIDIA Jetson Orin platform.

PCNA in Pan-Cancer: A Prognostic Biomarker Unveiled Through a Data-Driven, Multidimensional Analysis of Transcriptomics, Immunity, and Functional Profiling.

Proliferating cell nuclear antigen (PCNA) is a central regulator of numerous cellular processes impacting DNA metabolism and genetic integrity, including DNA damage, cell cycle progression, and transcriptional regulation. PCNA aberrations manifest in different disease phenotypes, including neoplastic proliferation, chromatin disassembly, genomic instability, and impaired DNA repair. Although the role of PCNA in control of DNA homeostasis has been extensively studied in some cancers, its pan-cancer relevance in tumorigenesis, immune interactions, and therapeutic resistance remains underexplored.

Enhanced and proficient chitosan membranes embedded with polyaniline-TiO core-shell nanocomposites for fuel-cell hydrogen storage.

This study investigates the preparation and properties of aniline polymerized in situ onto a nanosized TiO surface to form core-shell nanoparticles at ambient temperatures. The in situ polymerization of aniline to polyaniline (PANI), in conjunction with the utilization of an anionic surfactant, was employed in this investigation. The prepared PANI-TiO core-shell nanoparticles were integrated with chitosan at a gravimetric ratio and cast as core-shell nanocomposite membranes.

Sodium hexafluorophosphate mediated enhancement of electrical and electrochemical properties of poly(vinyl alcohol)-chitosan solid polymer electrolytes for EDLCs.

A free-standing, flexible and biodegradable biopolymer electrolyte (BPE) derived from a poly(vinyl alcohol) (PVA)-chitosan (CS) blend immobilizing sodium hexafluorophosphate (NaPF) salt was fabricated solution casting method. The effect of salt concentration on the structural, electrical, and electrochemical properties of the electrolyte was systematically investigated. X-ray diffraction (XRD) and Fourier-transform infrared (FTIR) spectroscopy were used to ascertain the microstructural changes in the polymer matrix including the complexation of PVA, CS, and NaPF.

Evaluation of Artificial Intelligent Systems Based Analysis in Dental Periapical Lesions - A Radiological Study.

Background: This study evaluated AI-based analysis of dental periapical lesions using CBCT scans, conducted at the Department of Oral Medicine and Radiology, New Horizon Dental College, Bilaspur, Chhattisgarh.

Method: A total of 500 CBCT scans were analyzed, with 400 scans used to train AI software and 100 scans assessed by two radiologists to test the software's performance. The AI classified lesions into periapical cysts, abscesses, or granulomas.

Probing the microRNA landscape in cadmium chloride induced renal toxicity through an in silico approach.

Cadmium chloride (CdCl₂), a highly toxic environmental pollutant, significantly impacts kidney health, particularly in the proximal tubular cells, where it induces oxidative stress and lipid peroxidation. The specific mechanisms underlying cadmium toxicity remain unclear. It is hypothesized that it is mediated by microRNAs (miRNAs).

Bayesian approach for localizing cardiac sources in Magnetocardiography using Vectorcardiography based total variational priors.

The human heart produces electrical signals to contract and relax its muscles that helps in its blood pumping activities. These electrical impulses give rise to electric potentials on the body surface and tiny magnetic field around the thorax. These functional activities can be investigated using Electro/Magnetocardiogram (E/MCG).

Current state of AI for shockwave lithotripsy: a systematic review from YAU and EAU endourology.

Purpose: To consolidate the current evidence of artificial intelligence (AI) for management of nephrolithiasis using extracorporeal shock-wave lithotripsy (ESWL), and to look at its feasibility into integration in clinical practice.

Methods: In March 2025, the sytematic search was conducted across several databases, including, PubMed, Google Scholar, ACM Digital Library, CINAHL, and IEEE Xplore via Boolean operators with the use of the dedicated terms. Studies that described the development and validation and/or testing of AI-based models for ESWL, regardless of clinical scenario, published in English were included.

A machine learning approach to assess the climate change impacts on single and dual-axis tracking photovoltaic systems.

Solar tracking system efficiency is affected by climate variability, and adaptive mechanisms must be employed to maximize energy output. Conventional fixed-tilt, single-axis, and dual-axis tracking techniques are not real-time adaptive, resulting in energy loss. This paper introduces COMLAT (Climate-Optimized Machine Learning Adaptive Tracking), an AI solar tracking system that employs climate prediction using CNN-LSTM for climate prediction, XGBoost for estimation of energy yield, and Deep Q-Learning (DQL) for real-time tracking control for solar efficiency optimization.

Risk group-4 virus emergent threats.

Several Filovirus outbreaks occurred during 2021-2025 in Africa. The case fatality ratios (CFRs) were elevated as expected for these viruses. After outbreaks were termed terminated, nonetheless, due to virus pathogenicity and transmissibility, epidemics continued unabated.

SIC based RL for massive MIMO NOMA signal detection for different modulation schemes under diverse channel conditions.

Massive-multiple input and Multiple Outputs Non orthogonal multiple access (M-MIMO-NOMA) systems require efficient signal detection techniques to mitigate interference and enhance spectral efficiency, especially under diverse channel conditions and varying modulation schemes. This study investigates the performance of the Successive Interference Cancellation with Reinforcement Learning (SIC-RL) detector compared to conventional methods, including the Minimum Mean Square Error (MMSE), Maximum Likelihood Detection (MLD), Approximate Message Passing (AMP), Gauss-Seidel (GS), Conjugate Gradient (CG), and zero-forcing equalizer (ZFE). The analysis was conducted for 16-QAM, 64- Quadrature Amplitude Modulation (QAM), and 256-QAM in Rayleigh fading channels with 10% error.

Dual drug delivery of Paclitaxel and Curcumin via hyaluronic acid functionalized nanoparticles for improved breast cancer therapy.

Breast cancer has high mortality rate among women. Though paclitaxel is one of the important drugs used, but frequent use will lead to drug resistance. Nuclear factor kappa B (NFƘB) a transcription factor will be up regulated with frequent use of paclitaxel, and this increases drug resistance in cancer cells.

Deciphering the role of crucial miRNAs involved in diabetic cardiomyopathy through a multiomics approach.

Conventional drug discovery routes take decades to identify critical gene signatures involved in a disease. Though in silico platforms and software have simplified the process by reducing the time and energy needed to arrive at significant molecular targets for disease conditions, they are not accessible to everyone. Here, we propose a systematic strategic protocol to identify critical players in the disease pathogenesis using the vast amount of molecular omics data available on various public domains, setting diabetic cardiomyopathy as the case study.

A Golden Jackal based optimal operation and optimization of a virtual power plant involving renewable resources.

This paper reports the optimum operation of a virtual power plant (VPP) to reduce the reliance on coal and gas-based energy generation. This practice not only promotes the incorporation of renewable-based energy sources but also reduces the reliance on fossil-based resources which are limited in the reserves. The selected VPP system comprises small hydropower, wind turbine, solar photovoltaics and fuel cells accompanied by a co-generation unit.

Synergetic effects of hemp-banana-bamboo hybridization on mechanical, fracture and dynamic properties of cellulose-rich natural fiber composites.

This study investigates the mechanical, fracture, and vibrational properties of hybrid natural fiber reinforced composites, incorporating hemp, banana, and bamboo-based Cellulose-rich fibers. Combining cellulose-rich fibers with complementary properties, seven different composites (pure and hybrid) with epoxy as the matrix were prepared using compression molding method. Unlike prior studies focusing on single fiber composites, this work systematically examines two and tri-fiber hybrid composites to optimize mechanical and dynamic performance.

Explainable artificial intelligence driven insights into smoking prediction using machine learning and clinical parameters.

Smoking is a leading cause of various health conditions, including cancer and respiratory diseases. Smokers often face medical restrictions such as limitations in blood and organ donation, reduced effectiveness of medications, and increased surgical complications. These impacts underscore the need for early detection of smoking status to enable timely intervention.

Atom bond connectivity index for graph with self-loops and its application to structure property relationships in anticancer drugs.

Let [Formula: see text] be a graph derived from a simple graph G by adding a self-loop to each vertex in a subset [Formula: see text]. In this paper, we define the atom bond connectivity index of the graph [Formula: see text] as [Formula: see text] and the atom bond connectivity energy of [Formula: see text] as [Formula: see text]. We obtained upper bounds for the ABC spectral radius of the graph [Formula: see text] as well as bounds for [Formula: see text] and [Formula: see text] in terms of m, n, Δ and δ.

Design of a compact multistubs resonator based dual-band flexible wearable antenna with low SAR for sub-6 GHz ISM applications.

In this paper, a small size multistubs resonator based flexible wearable antenna is demonstrated for dual-band operation. The proposed antenna is composed of vertically aligned multistubs resonator, a 50 Ω microstrip feed and a defected ground structure (DGS). This configuration of antenna resonates at 2.