Experimental arrangement to study the impact of atmospheric turbulence on user-defined beams.

In the present work, we propose an experimental setup to investigate the effect of atmospheric turbulence on user-defined beams. The user-defined beams were formed by writing reconfigurable patterns on a spatial light modulator, allowing the impact of atmospheric turbulence to be investigated simultaneously and in real time. The programmable controllability provides several flexibilities to the system, such as the ability to create different beam types simultaneously, control the separation between different beams, compensate for aberrations, and easily switch between different beam types.

Upcycling Graphite from Apent Li-Ion Battery with SiO via Mechano-Chemical Process as Next-Generation Anode for Li-Ion Capacitors.

Hybrid supercapacitors such as Lithium-ion capacitors (LICs) are one of the most modern energy storage devices of great research interest. The hybridization of the battery-type anode with the capacitive-type cathode brings out the synergic effect of enhanced energy density, power capability, long cycle life, and wide operating temperature. Herein, we introduce a simultaneous alloying-intercalation process from the recovered graphite: silicon monoxide (RG: SiO) composite as a negative electrode for the LIC applications with the activated carbon (AC) as a counter electrode.

Surface electromyographic analysis of the bilateral abdomen and back muscle during selected yoga posture.

Unlabelled: Sedentary lifestyles lead to postural deformities, Lower Back Pain(LBP) and Colorectal cancer(CRC). Practicing Yoga attains definite strength in muscles by activating muscle fibers. The Yoga poses analyzed are often used in strengthening and stability programs for the abdomen and back muscles.

Analysis of mcr family of colistin resistance genes in Gram-negative isolates from a tertiary care hospital in India.

Aim: Colistin serves as the drug of last resort for combating numerous multidrug-resistant (MDR) Gram-negative infections. Its efficacy is hampered by the prevalent issue of colistin resistance, which severely limits treatment options for critically ill patients. Identifying resistance genes is crucial for controlling resistance spread, with horizontal gene transfer being the primary mechanism among bacteria.

Comparing Mid-Upper Arm Circumference With Body Mass Index for Assessing Nutritional Status in Indian Adults: Evidence From the National Family Health Survey 2015-16 (NFHS-4).

Background The surge in the twin burden of malnutrition - undernutrition and overweight/obesity - poses a severe threat worldwide including India. The adult group, primarily considered as an economic pillar of the society, suffered significant health problems, yet their nutritional issues are often neglected. Screening of nutritional status through anthropometric measurements is widely accepted.

Investigation on the structural, magnetic, magnetocaloric and magnetotransport behaviour of LaSrMnO manganites synthesised by different routes.

In the present investigation, we present the comparison of the structural, magnetic, magnetocaloric and magnetoresistance behavior of solid state and sol-gel derived LaSrMnO. X-ray diffraction together with Rietveld refinement confirms the rhombohedral structure of the synthesised samples with the 3̄ space group. The ferromagnetic-to-paramagnetic transition temperature decreases from 360 K to 346 K for the nanocrystalline sample.

Exposure to imipenem at sub-minimum inhibitory concentration leads to altered expression of major outer membrane proteins in Acinetobacter baumannii.

Aims: Acinetobacter baumannii is a nosocomial pathogen known to be multidrug-resistant (MDR), especially to drugs of the carbapenem class. Several factors contribute to resistance, including efflux pumps, β-lactamases, alteration of target sites, and permeability defects. In addition, outer membrane proteins (OMPs), like porins are involved in the passage of antibiotics, and their alteration could lead to resistance development.

Power consumption prediction for electric vehicle charging stations and forecasting income.

Electric vehicles (EVs) are the future of the automobile industry, as they produce zero emissions and address environmental and health concerns caused by traditional fuel-poared vehicles. As more people shift towards EVs, the demand for power consumption forecasting is increasing to manage the charging stations effectively. Predicting power consumption can help optimize operations, prevent grid overloading, and power outages, and assist companies in estimating the number of charging stations required to meet demand.

Machine Learning-Based Classification of Transcriptome Signatures of Non-Ulcerative Bladder Pain Syndrome.

Lower urinary tract dysfunction (LUTD) presents a global health challenge with symptoms impacting a substantial percentage of the population. The absence of reliable biomarkers complicates the accurate classification of LUTD subtypes with shared symptoms such as non-ulcerative Bladder Pain Syndrome (BPS) and overactive bladder caused by bladder outlet obstruction with Detrusor Overactivity (DO). This study introduces a machine learning (ML)-based approach for the identification of mRNA signatures specific to non-ulcerative BPS.

De-obstruction of bladder outlet in humans reverses organ remodelling by normalizing the expression of key transcription factors.

Background: Benign prostatic hyperplasia in elderly males often causes bladder outlet obstruction termed benign prostatic obstruction (BPO). BPO induces lower urinary tract symptoms and quantifiable urodynamic alterations in bladder function. When conservative medical treatments are exhausted, surgical interventions like transurethral resection of the prostate (TURP) are employed for bladder outlet de-obstruction.

Unlocking the Gut-Cardiac Axis: A Paradigm Shift in Cardiovascular Health.

The gut-cardiac axis represents an emerging area of research focusing on the relationship between gut health and cardiovascular function. This narrative review examines the Gut-Cardiac Axis, emphasizing its emerging role in cardiovascular health and disease management. Traditionally viewed as a component of the digestive system, the gut is now recognized for its significant influence on cardiac health.

Machine Learning-based Classification of transcriptome Signatures of non-ulcerative Bladder Pain Syndrome.

Lower urinary tract dysfunction (LUTD) presents a global health challenge with symptoms impacting a substantial percentage of the population. The absence of reliable biomarkers complicates the accurate classification of LUTD subtypes with shared symptoms such as non-ulcerative Bladder Pain Syndrome (BPS) and overactive bladder caused by bladder outlet obstruction with Detrusor Overactivity (DO). This study introduces a machine learning (ML)-based approach for the identification of mRNA signatures specific to non-ulcerative BPS.

Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis.

Background: Machine learning (ML) has emerged as a vital asset for researchers to analyze and extract valuable information from complex datasets. However, developing an effective and robust ML pipeline can present a real challenge, demanding considerable time and effort, thereby impeding research progress. Existing tools in this landscape require a profound understanding of ML principles and programming skills.

High-Performance Li-Ion and Na-Ion Capacitors Based on a Spinel LiTiO Anode and Carbonaceous Cathodes.

Lithium-ion hybrid capacitors (LICs) have become promising electrochemical energy storage systems that overcome the limitations of lithium-ion batteries and electrical double-layer capacitors. The asymmetric combination of these devices enhances the overall electrochemical performance by delivering simultaneous energy and power capabilities. Lithium titanate (LiTiO, LTO), a spinel zero-strain material, has been studied extensively as an anode material for LIC applications because of its high-rate capability, negligible volume change, and enhanced cycling performance.

SpheroScan: a user-friendly deep learning tool for spheroid image analysis.

Background: In recent years, 3-dimensional (3D) spheroid models have become increasingly popular in scientific research as they provide a more physiologically relevant microenvironment that mimics in vivo conditions. The use of 3D spheroid assays has proven to be advantageous as it offers a better understanding of the cellular behavior, drug efficacy, and toxicity as compared to traditional 2-dimensional cell culture methods. However, the use of 3D spheroid assays is impeded by the absence of automated and user-friendly tools for spheroid image analysis, which adversely affects the reproducibility and throughput of these assays.

Evaluation of the efficacy of TruNatomy, ProTaper retreatment, and RaCe file systems in retreatment of moderately curved mandibular molars: An study.

Context: Endodontic retreatment is the first line of treatment in cases of failed primary endodontic treatment. Although associated with challenges such as incomplete removal of obturating material, increased clinical time, and extrusion of apical debris, endodontic retreatment still has considerable success rate in the general population.

Aims: The aim of this study was to evaluate and compare the efficacy of TruNatomy, ProTaper retreatment, and RaCe file systems to remove the obturating material, time taken to remove the obturating material, and apical extrusion of debris using cone-beam computed tomography (CBCT).