Estimation of Mean Glandular Dose Using Breast-Equivalent Phantoms: A Foundational Study for Regional DRL Formulation in Mammography in India.

Purpose This foundational study aims to support the development of regional Diagnostic Reference Levels (DRLs) for mammography screening in India by estimating Mean Glandular Dose (MGD) using appropriate breast-equivalent phantoms across Computed Mammography (CR), Digital Mammography (DR), and Digital Breast Tomosynthesis (DBT) systems. Additionally, system-displayed MGD values were compared with calculated MGDs to evaluate their accuracy for routine clinical use. Methods A total of 5,000 mammographic views were collected across CR, DR, and DBT units.

Design and test of analog-to-digital converters with enhanced test strategies using built in self test.

Analog and Mixed Signal Integrated Circuits (AMS ICs), which have many different components on a single chip, can now be integrated due to technological advancements. However, controllability and observability both decline with increasing circuit complexity, making testing more difficult and expensive. The real time signals are analog in nature and hence ADCs are used to convert them to digital signals for further processing in all the mixed signal circuits.

A metagenomic approach to predict the role of microbiome in a plant-microbe system for degrading the model azo dye methyl red.

Azo dye contamination poses significant environmental challenges due to its persistence and toxicity. Plant-microbe integrated systems offer a sustainable solution for dye bioremediation, yet the functional roles of microbial communities and their interactions within community and with host plants during bioremediation remain underexplored. This study presents an integrated, multi omics approach to dissect the microbial diversity, functional potential, and plant-microbe interactions within a plant-microbe integrated bioremediation system for model azo dye, methyl red degradation.

Enhanced production of stem bromelain in Pichia pastoris by coexpression of unfolded protein response activator gene HAC1P.

Expression of heterologous proteins and metabolites at high titers mounts several stress responses on the recombinant host. Stem Bromelain is a cysteine protease enzyme present in the stem and fruit of the pineapple plant Ananas comosus. The enzyme has a broad range of industrial application ranging from food, nutraceutical, cosmetic and pharmaceutical.

‑Alkylated 5,5-Diphenylhydantoin Derivatives: Synthesis, X‑ray, Spectroscopic Characterization, Hirshfeld Surface Analysis, DFT, Molecular Docking, Molecular Dynamics Simulations, and Cholesterol Oxidase Binding Affinity Estimation.

This study presents the synthesis and characterization of nine -alkylated phenytoin derivatives -. These compounds were synthesized and characterized using spectroscopic techniques including C and H nuclear magnetic resonance spectroscopy, UV-visible spectroscopy, infrared spectroscopy, and liquid chromatography-mass spectrometry. The structures of - were confirmed by X-ray crystallography.

Technoeconomic assessment of a sorghum-based biorefinery using DWSIM Pro: A comparative study with Aspen Plus.

Purpose Of The Research: This study evaluates the techno-economic feasibility of using DWSIM Pro, an extension to the open-source process simulation software DWSIM, for modelling a bio-refinery co-producing bio-ethanol and biodiesel from genetically modified lipid-producing sorghum. The primary aim is to compare its performance and economic analysis capabilities with the Aspen Plus.

Basic Procedures Followed: A detailed flowsheet was designed in DWSIM to simulate key unit operations.

Novel Azole-Modified Porphyrins for Mitochondria-Targeted Photodynamic Therapy.

Photodynamic therapy is a non-invasive treatment strategy for various types of cancer, based on the use of light to activate a photosensitizer which triggers processes leading to cell death. Given the increasing interest in the development of mitochondria-targeted photosensitizers, in this study we synthesized two novel thiadiazol-substituted porphyrins, 5,10,15,20-tetra(2,1,3-benzothiadiazol-5-yl) porphyrin () and 5,10,15,20-tetra(1,2,3-thiadiazol-4-yl) porphyrin (), designed to target mitochondria in cancer cells thanks to the azole residues present in their structure. The two porphyrinic compounds were characterized in terms of structural and photophysical properties, revealing high yields of singlet oxygen production.

Optimization and biocompatibility analyses of fused filament fabrication-printed polylactic acid-silicon nitride scaffolds with enhanced mechanical properties.

Fused filament fabrication (FFF) in additive manufacturing has emerged as a potential technology in the development of tissue engineering scaffolds of precise, complex geometries. The choice of material and process parameters is significant in determining their properties, such as mechanical strength. Polymer-ceramic composites with exceptional bioactivity have the potential for FFF applications in fabricating scaffolds.

Miniaturization of Sub 6 GHZ Band 5G Monopole Antenna with Manganese Assisted CoFeO Nano Self-Assembly Magneto-Dielectric Coating.

This paper proposes a miniaturized monopole antenna for sub-6 GHz 5G mobile applications by integrating a magneto-dielectric superstrate. The Magneto dielectric material is composed of manganese-assisted CoFeO ferrite-based nanoself-assembly materials. The Gel Matrix method is utilized to synthesize MnFeO, CoFeO, and Mn-doped CoFeO magneto-dielectric ferrite nanoparticles.

Miniaturized Dual and Quad Port MIMO Antenna Variants Featuring Elevated Diversity Performance for UWB and 5G-Midband Applications.

The growing demand for high-speed and high-capacity wireless communication has intensified the need for compact, wideband, and efficient MIMO antenna systems, particularly for 5G mid-band and UWB applications. This article presents a miniaturized dual and quad port MIMO antenna design optimized for 5G mid-band (n77/n78/n79/n96/n102) and Ultra-Wideband (UWB) applications without employing any decoupling structures between the radiating elements. The 2-port configuration features two closely spaced symmetric monopole elements (spacing < λ/2), promoting efficient use of space without degrading performance.

Polyester/cotton blended fabrics coated with natural rubber latex containing lignin nanoparticles and molybdenum disulfide nanosheets for medical and protective applications.

Coating fabrics with natural rubber latex (NRL) dispersions containing various nanofillers offers a versatile approach for developing multifunctional fabrics. In this study, polyester/cotton blended fabrics were coated with NRL by incorporating 3 phr (parts per hundred rubber) of molybdenum disulfide-tannic acid dispersion (MT) and 7 phr of lignin nanoparticles (LNP) using a dipping method. Two types of coated fabric samples were prepared: single-cycle and double-cycle coated fabrics.

A sun flower optimization based modified high step up SEPIC converter for electric vehicle applications.

A High step-up modified SEPIC converter is proposed in this research work with Sun Flower Optimization (SFO) based maximum power tracing controller under dynamic operating condition to trace maximum power from solar PV. The proposed converter is designed to perform under various working conditions like steady state condition, variable solar irradiance condition and variable load condition. The proposed converter is designed to handle a 100W, 24 V solar panel.

Comprehensive analysis of Syzygium cumini L. pomace extract as an α-amylase inhibitor: In vitro inhibition, kinetics, and computational studies.

Type 2 diabetes mellitus (T2DM) is a widespread metabolic disorder characterized by impaired regulation of blood glucose levels. Jamun (Syzygium cumini L.) fruits and seeds have been traditionally used in Ayurveda to manage diabetes.

Domain knowledge-infused pre-trained deep learning models for efficient white blood cell classification.

White blood cell (WBC) classification is a crucial step in assessing a patient's health and validating medical treatment in the medical domain. Hence, efficient computer vision solutions to the classification of WBC will be an effective aid to medical practitioners. Computer-aided diagnosis (CAD) reduces manual intervention, avoids errors, speeds up medical analysis, and provides accurate medical reports.

Mexican axolotl optimization algorithm with a recalling enhanced recurrent neural network for modular multilevel inverter fed photovoltaic system.

This manuscript presents a grid-connected photovoltaic (PV) system employing a modular multilevel inverter (MMI) topology with an advanced hybrid control technique. The proposed MAO-RERNN control method integrates the Mexican Axolotl Optimization (MAO) algorithm with a Recalling-Enhanced Recurrent Neural Network (RERNN) to achieve optimal power conversion, improved stability, and reduced total harmonic distortion (THD). Unlike traditional multilevel inverters (MLI), the MMI structure utilized in this work requires fewer power electronic components, reducing cost and complexity.

Multi-Omics Approaches Against Abiotic and Biotic Stress-A Review.

Plants face an array of environmental stresses, including both abiotic and biotic stresses. These stresses significantly impact plant lifespan and reduce agricultural crop productivity. Abiotic stresses, such as ultraviolet (UV) radiation, high and low temperatures, salinity, drought, floods, heavy metal toxicity, etc.

Optimized heart disease prediction model using a meta-heuristic feature selection with improved binary salp swarm algorithm and stacking classifier.

Despite technological advancements, heart disease continues to be a major global health challenge, emphasizing the importance of developing accurate predictive models for early detection and timely intervention. This study proposes a heart disease prediction model integrating a stacking classifier with a nature-inspired meta-heuristic algorithm. It employs an improved Binary Salp Swarm Algorithm (BSSA) by incorporating a wolf optimizer and opposition-based learning for optimal feature selection.

Investigating critical node identification in water networks through distance Laplacian energy centrality.

Identifying influential nodes in water distribution networks is essential for ensuring efficient and reliable operations. This paper introduces a novel centrality measure called distance Laplacian energy centrality (DLC), designed to evaluate node importance by combining the network's topological structure and hydraulic properties into a unified framework. The DLC measure quantifies the criticality of a node by assessing its influence on the network's Laplacian energy, which represents the network's characteristics, and distance metrics that reflect how the removal of the node affects network connectivity and flow.

Development of an AI-derived, non-invasive, label-free 3D-printed microfluidic SERS biosensor platform utilizing Cu@Ag/carbon nanofibers for the detection of salivary biomarkers in mass screening of oral cancer.

Developing a non-invasive and reliable tool for the highly sensitive detection of oral cancer is essential for its mass screening and early diagnosis, and improving treatment efficacy. Herein, we utilized a label-free surface enhanced Raman spectroscopy (SERS)-based biosensor composed of Cu@Ag core-shell nanoparticle anchored carbon nanofibers (Cu@Ag/CNFs) for highly sensitive salivary biomarker detection in oral cancer mass screening. This SERS substrate provided a Raman signal enhancement of up to 10 and a detection limit as low as 10 M for rhodamine 6G molecules.

Exploring the therapeutic potential of Rhododendron anthopogon D.Don essential oil constituents against lung cancer: A network pharmacology-based analysis with molecular docking and experimental studies.

Rhododendron anthopogon D.Don is an evergreen shrub used by Himalayan healers to treat many ailments most notably lung problems. However, the mechanism by which R.

Mitigation of microfibers in laundry effluent: Investigation of luffa fibers as an eco-friendly filtration system.

Domestic laundry wastewater is a major contributor to microfiber emissions in the aquatic environment. Among several mitigation measures, the use of external filters to capture microfibers from wastewater is one of the most efficient and commercially viable methods. This study attempted to develop an eco-friendly filtration medium to filter microfibers in laundry wastewater using luffa cylindrica fibers.

A novel breath pattern model and analysis to minimize patient discomfort in medical ventilators.

Typical waveforms used for the simulation of pressure and volume-controlled ventilation in medical ventilators have been extensively studied in the literature. The majority of simulation studies reported employ the step pattern or ramp pattern to model the pressure and flow variations in pressure/volume-controlled ventilation. It was observed that the above waveforms tend to add to the discomfort level of patients due to the presence of jerks in derivatives of pressure/flow variations; the pressure/flow variation of air and oxygen mixture should be smooth so that the patient discomfort is kept at a minimal level.

Arithmetic optimization based MPPT for photovoltaic systems operating under nonuniform situations.

Photovoltaic (PV) modules may encounter nonuniform situations that reduce their useable power volume, causing ineffective maximum power point tracking (MPPT). Moreover, due to the incorporation of bypass diodes, power-voltage (P-V) graph has multi-peaks when each component of the module receives different solar irradiation. This paper proposes a solution to this problem using an arithmetic optimization algorithm (AOA) for MPPT in PV systems operating in nonuniform situations.

Towards a Unified Management Interface for 5G Sensor Networks: Interoperability between Yet Another Next Generation and Open Platform Communication Unified Architecture.

Fifth-generation (5G) sensor networks are critical enablers of Industry 4.0, facilitating real-time monitoring and control of industrial processes. However, significant challenges to their deployment in industrial settings remain, such as a lack of support for interoperability and manageability with existing industrial applications and the specialized technical expertise required for the management of private 5G sensor networks.