Revealing water structure modification by a sodium-glucose cotransporter-2 inhibitor-type antidiabetic drug with D-(+)-glucose in aqueous media.

In this work, volumetric, acoustic, viscometric, and photon correlation spectroscopic studies of an antidiabetic drug, ertugliflozin L-pyroglutamic acid (E.L-PGA) have been performed in aqueous medium in absence and presence of D-(+)-glucose. E.

Efficient Cr (VI) removal from tannery wastewater using Co-Zn ferrite-modified water hyacinth biochar: mechanisms and optimization.

Chromium contamination from tannery effluents significantly threatens environmental sustainability and public health. This study aims to develop a Co-Zn ferrite-incorporated water hyacinth biochar (Co-ZnF@WHB) for efficient Cr (VI) removal from contaminated water. The biochar was synthesized through pyrolysis of water hyacinth steam at 450 ⁰C, followed by HNO₃ activation to enhance surface functionality.

Chamber design and intensity-modulated ultraviolet-C LEDs for advanced pulsed photonic disinfection.

Objectives: Contaminated apparatus and surgical tools pose serious health risks. For such purpose, disinfection chambers are employed. However, these systems rely on mercury-based UV lamps which comes with various drawbacks.

Nonlinear optical dynamics and complex wave structures in nonlinear dispersive media.

The research focuses on optical solitons and employs the generalized auxiliary equation technique to obtain soliton resolutions for the nonlinear Kairat-X equation. This equation considers wave number groups influenced by time and velocity dispersion in non-linear mediums. Because of their stability and numerous uses in signal processing, telecommunications, and quantum physics, optical solitons are appreciated.

Physicochemical profiling and ranking of parkinson's disease drugs through QSPR and Fuzzy TOPSIS analysis.

Parkinson's disease is a progressive neurological disorder characterized by the degeneration of the nervous system, leading to impaired motor and non-motor functions. Early symptoms include tremors, rigidity, and bradykinesia, with progressive deterioration over time. This study employs a multi-criteria decision-making approach, integrating Fuzzy TOPSIS and Quantitative Structure-Property Relationship (QSPR) analysis, to evaluate and rank 17 Parkinson's disease medications based on their physicochemical properties.

Ocular drug delivery systems based on nanotechnology: a comprehensive review for the treatment of eye diseases.

Ocular drug delivery is a significant challenge due to the intricate anatomy of the eye and the various physiological barriers. Conventional therapeutic approaches, while effective to some extent, often fall short in effectively targeting ocular diseases, resulting in suboptimal therapeutic outcomes due to factors such as poor ocular bioavailability, frequent dosing requirements, systemic side effects, and limited penetration through ocular barriers. This review elucidates the eye's intricate anatomy and physiology, prevalent ocular diseases, traditional therapeutic modalities, and the inherent pharmacokinetic and pharmacodynamic limitations associated with these modalities.

DeepRNA-Twist: language-model-guided RNA torsion angle prediction with attention-inception network.

RNA torsion and pseudo-torsion angles are critical in determining the three-dimensional conformation of RNA molecules, which in turn governs their biological functions. However, current methods are limited by RNA's structural complexity as well as flexibility, with experimental techniques being costly and computational approaches struggling to capture the intricate sequence dependencies needed for accurate predictions. To address these challenges, we introduce DeepRNA-Twist, a novel deep learning framework designed to predict RNA torsion and pseudo-torsion angles directly from sequence.

Enhanced vehicle localization with low-cost sensor fusion for urban 3D mapping.

This research paper presents the design and development of an indigenous low cost Mobile Mapping System (MMS) for urban surveying applications. The MMS is comprised of economical Hokuyo-30LX 2D laser scanners, vision sensors, Global Positioning System (GPS) and various odometric sensors that can be installed on car like moving platform. The run time sensorial data is interfaced, processed and recorded using Robot Operating System (ROS).

Deep learning-based automatic cranial implant design through direct defect shape prediction and its comparison study.

Defects to human crania are one kind of head bone damages, and cranial implants can be used to repair the defected crania. The automation of the implant design process is crucial in reducing the corresponding therapy time. Taking the cranial implant design problem as a special kind of shape completion task, an automatic cranial implant design workflow is proposed, which consists of a deep neural network for the direct shape prediction of the missing part of the defective cranium and conventional post-processing steps to refine the automatically generated implant.

Development of Urdu Speech Audiometry Material for the Deaf and Hard of Hearing Community.

Purpose: This study aimed to develop standardized Urdu speech materials for assessing speech recognition threshold (SRT) and word recognition score (WRS) for clinical use in Pakistan.

Method: The development of Urdu speech materials followed four key parameters: phonemic coverage, phonetic dissimilarity, familiarity with the participants, and homogeneity in terms of audibility. Bisyllabic words for SRT measurement and monosyllabic words for WRS measurement were selected.

An EEG signal smoothing algorithm using upscale and downscale representation.

Effective smoothing of electroencephalogram (EEG) signals while maintaining the original signal's features is important in EEG signal analysis and brain-computer interface. This paper proposes a novel EEG signal-smoothing algorithm and its potential application in cognitive conflict (CC) processing.Instead of being processed in the time domain, the input signal is visualized in increasing line width, the representation frame of which is converted into a binary image.

In-silico investigation integrated with machine learning to identify potential inhibitors targeting AKT2: Key driver of cancer cell progression and metastasis.

Background And Objective: In search of a key driver for the invasive growth of cancer metastasis, AKT2 is found to be exceptionally expressed in colorectal cancer and its metastasis. Again, exceeding genomic arrangements of AKT2 can be held responsible for HGSC (High-grade serous ovarian cancer) and breast cancer cell metastasis. FDA-approved capivasertib, a potential drug targeting the AKT signaling pathway, has a few side effects such as plausible alterations of liver function and gastrointestinal issues.

Eco-Friendly Biomass-Based Carbon Dots, Carbon Nanotubes, Graphene, and Their Derivatives for Enhanced Oil Recovery: A New Horizon for Petroleum Industry.

Oil extraction from reservoirs has never been easy, particularly when easily accessible oil sources run out. Enhanced oil recovery (EOR) is a dynamic area of petroleum engineering that seeks to maximize the quantity of crude oil that can be retrieved from an oil field. Researchers and oil producers have emphasized assessing tertiary-stage recovery approaches, such as chemical EOR (CEOR), due to the problems posed by the diverse carbonate rocks.

Indoor fire and smoke detection based on optimized YOLOv5.

Ensuring safety and safeguarding indoor properties require reliable fire detection methods. Traditional detection techniques that use smoke, heat, or fire sensors often fail due to false positives and slow response time. Existing deep learning-based object detectors fall short of improved accuracy in indoor settings and real-time tracking, considering the dynamic nature of fire and smoke.

The use of eye-tracking technology in supporting children and adolescents with attention deficit/hyperactivity disorder: a comprehensive review.

Purpose: Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurodevelopmental conditions marked by symptoms of inattention, impulsivity, and hyperactivity. These symptoms significantly impact affected individuals, particularly children and adolescents, who benefit from timely assessment, diagnosis, and intervention. In recent years, eye movement research has increasingly provided insights into neurological function, presenting eye-tracking technology as a valuable tool for supporting ADHD.

Development and characterization of gelatin microgel-stabilized silver nanoparticles loaded with curcumin: Evaluation of antibacterial, antioxidant, and antiproliferative activities.

ObjectiveCurcumin is a polyphenol extracted from the roots of . It is a multifunctional biological substance that has notable antioxidant, anti-inflammatory, anti-cancer, and antibacterial properties, as reported in numerous previous papers. However, curcumin has limited bioavailability due to its low water solubility.

Automatic smart brain tumor classification and prediction system using deep learning.

A brain tumor is a serious medical condition characterized by the abnormal growth of cells within the brain. It can cause a range of symptoms, including headaches, seizures, cognitive impairment, and changes in behavior. Brain tumors pose a significant health concern, imposing a substantial burden on patients.

Spatio-temporal CNN-BiLSTM dynamic approach to emotion recognition based on EEG signal.

In this paper, a hybrid CNN-BiLSTM model for EEG-based emotion detection system is presented. The proposed technique is developed by extracting features using Power Spectral Density (PSD) signal. The proposed approach is carried out by combining CNN and bidirectional LSTM models to increase the comprehension of context in sequential data.

Level-Set field re-initialization: A computational model with finite element method on complicated domains.

This paper introduces a proficient re-initialization method for the Level-Set (LS) field with the Finite Element Method (FEM) framework on unstructured meshes. The technique can retain the LS field's signed distance (SD) property but exploits the Eulerian-Lagrange multiplier technique. The scheme is based on geometric re-initialization and integrated with the FEM to higher-degree polynomials on complex domains.

Optimal vaccination model of airborne infection under variable humidity and demographic heterogeneity for hybrid fractional operator technique.

Airborne respiratory tract infection typically occurs seasonally in subtropical countries, particularly during winter, when transmission and fatality rates considerably rise, indicating that low humidity and freezing temperatures facilitate the transmission of viral strains in age heterogeneity. Despite this, the atmospheric elements that contribute to periodic influenza occurrences and their critical influence on the spread of influenza stay ambiguous in various age groups. The oversight of undetected cases amid a widespread outbreak of transmissible illnesses results in an underappreciation of the prevalence of infection and the basic recurrence rate.

Exploring the Synthetic Potential of Horner-Wadsworth-Emmons Reaction Toward the Synthesis of Polyketide Based Natural Products: A Review.

The Horner-Wadsworth-Emmons (HWE) reaction is a commonly used and reliable phenomenon for carbon-carbon olefination in organic chemistry, carried out by treating aldehyde or ketones with phosphonate esters to afford the substituted alkenes. HWE reaction has also been observed to be involved in the stereo-controlled syntheses of naturally occurring compounds that acquire pharmaceutical profiles against various diseases. In this article, recent implementations of Horner-Wadsworth-Emmons reaction towards the notable total syntheses of naturally occurring compounds such as polyketides have been summarized.

Mechanical, Thermal, and Flammability Properties of Eco-Friendly Nanocomposites from Recycled PET/PA-11 Blends Reinforced with Graphene Nanoplatelets.

This study investigates the development of sustainable nanocomposites using recycled polyethylene terephthalate (RPET) and polyamide 11 (PA-11) blends reinforced with graphene nanoplatelets (GNPs). RPET/PA-11 blends were compatibilized with 2 phr Joncryl and processed using melt blending followed by injection moulding. The effects of varying GNP contents (1-4 phr) on mechanical, thermal, and flame-retardant properties were analysed.

A novel integration of Hodrick-Prescott filter (Hp-filter) and wavelet transform (WT) with optimize support vector machine (PSO-SVM) in predicting solar radiation.

Previous research has shown that predicting solar radiation is a challenging issue due to highly nonlinear and noisy climate data. Various hybrid approaches have been applied earlier for solar radiation prediction, which integrates the Wavelet Transform with various Machine Learning models. This research, therefore, intends to further improve the performance of these existing hybrid models.

Deep Learning-Based Detection of Aflatoxin B1 Contamination in Almonds Using Hyperspectral Imaging: A Focus on Optimized 3D Inception-ResNet Model.

Aflatoxin B1, a toxic carcinogen frequently contaminating almonds, nuts, and food products, poses significant health risks. Therefore, a rapid and non-destructive detection method is crucial to detect aflatoxin B1-contaminated almonds to ensure food safety. This study introduces a novel deep learning approach utilizing 3D Inception-ResNet architecture with fine-tuning to classify aflatoxin B1-contaminated almonds using hyperspectral images.

Hydrothermal ZnO Nanomaterials: Tailored Properties and Infinite Possibilities.

This review presents a comprehensive and precise summary of the hydrothermal synthesis and morphology control of zinc oxide (ZnO) nanomaterials, the advantages of hydrothermal synthesis, and the wide range of applications. ZnO nanomaterials have garnered significant attention in recent years for their diverse applications across various industries owing to their unique properties and versatility, with practical applications in healthcare, cosmetics, textiles, automotive, and other sectors. Specifically, the ability of ZnO-based nanomaterials to promote the production of reactive oxygen species, release of Zn ions, and induce cell apoptosis makes them well-suited for bio-medicinal applications such as cancer treatment and microorganism control.