Green Synthesis of Silver Nanoparticles (CM-AgNPs) from the Root of for Improving the Cytotoxicity Effect in Cancer Cells with Antibacterial and Antioxidant Activities.

The unique properties of silver nanoparticles (AgNPs), such as size, surface charge, and the ability to release silver ions, contribute to DNA damage, inducing of oxidative stress, and apoptosis in cancer cells. Thus, the potential application of AgNPs in the field of biomedicine, and cancer therapy are rapidly increasing day by day. Therefore, in this study, AgNPs were synthesized by extract of , and then the synthesized CM-AgNPs were fully characterized.

Optimization of waste biomass demineralization through response surface methodology and enhancement of thermochemical and fusion properties.

This study examines the impact of leaching with dilute hydrochloric acid solution on the reduction of ash content and the thermal degradation behavior of sugarcane bagasse. Response surface methodology (RSM) was used to statistically design the experiments and investigate the effect of three independent variables: treatment time, solid-to-liquid ratio, and reagent concentration. The leaching conditions were further optimized and experimentally validated for maximum ash reduction for suitability of treated biomass as feedstock for thermochemical conversion technologies.

Facial Expression Recognition for Healthcare Monitoring Systems Using Neural Random Forest.

Facial expressions vary with different health conditions, making a facial expression recognition (FER) system valuable within a healthcare framework. Achieving accurate recognition of facial expressions is a considerable challenge due to the difficulty in capturing subtle features. This research introduced an ensemble neural random forest method that utilizes convolutional neural network (CNN) architecture for feature extraction and optimized random forest for classification.

NeuroDots: From Single-Target to Brain-Network Modulation: Why and What Is Needed?

Objectives: Current techniques in brain stimulation are still largely based on a phrenologic approach that a single brain target can treat a brain disorder. Nevertheless, meta-analyses of brain implants indicate an overall success rate of 50% improvement in 50% of patients, irrespective of the brain-related disorder. Thus, there is still a large margin for improvement.

Discharge planning and resource utilization for minimizing readmissions in acute exacerbation of chronic heart failure: Insights from an observational study in a community hospital.

This cross-sectional study analyzed discharge disposition in 1,584 readmitted patients aged 65 or older with acute exacerbation of chronic heart failure (AECHF) in a large community hospital from April 2021 to April 2022. The study aimed to explore the relationship between age (65-74, 75-85, and 85 or older) and gender (male, female) with discharge disposition. Results revealed that 55.

sp. nov., isolated from rhizospheric soil of eggplant.

A Gram-stain-negative, aerobic, short rod-shaped and motile bacterial strain, designated MAH-33, was isolated from rhizospheric soil of eggplant. The colonies were observed to be yellow-coloured, smooth, spherical and 0.1-0.

Improving Alzheimer's Disease Classification in Brain MRI Images Using a Neural Network Model Enhanced with PCA and SWLDA.

The examination of Alzheimer's disease (AD) using adaptive machine learning algorithms has unveiled promising findings. However, achieving substantial credibility in medical contexts necessitates a combination of notable accuracy, minimal processing time, and universality across diverse populations. Therefore, we have formulated a hybrid methodology in this study to classify AD by employing a brain MRI image dataset.

Development of a Smart Signalization for Emergency Vehicles.

As the population increases, the number of motorized vehicles on the roads also increases. As the number of vehicles increases, traffic congestion occurs. Traffic lights are used at road junctions, intersections, pedestrian crossings, and other places where traffic needs to be controlled to avoid traffic chaos.

Isolation and Characterization of Sphingomonas telluris, Sphingomonas caseinilyticus Isolated from Wet Land Soil.

Two novel bacterial strains, designated as SM33 and NSE70-1, were isolated from wet soil in South Korea. To get the taxonomic positions, the strains were characterized. The genomic information (both 16S rRNA gene and draft genome sequence analysis) show that both novel isolates (SM33 and NSE70-1) belong to the genus Sphingomonas.

FAIR Health Informatics: A Health Informatics Framework for Verifiable and Explainable Data Analysis.

The recent COVID-19 pandemic has hit humanity very hard in ways rarely observed before. In this digitally connected world, the health informatics and investigation domains (both public and private) lack a robust framework to enable rapid investigation and cures. Since the data in the healthcare domain are highly confidential, any framework in the healthcare domain must work on real data, be verifiable, and support reproducibility for evidence purposes.

Isolation and characterization of a novel glycoside hydrolase positive bacterial strain named sp. nov. with ginsenoside-converting activity.

A novel yellow-pigmented catalase- and oxidase-positive bacterial strain (designated NA20) was isolated from wetland soil and characterized. Results of 16S rRNA and draft genome sequence analysis placed strain NA20 within the genus of the family . Strain NA20 showed ≤97.

Characterization of four novel bacterial species of the genus , , and sp.nov., isolated from wet land.

Four novel bacterial strains, designated as RG327, SE158, RB56-2 and SE220, were isolated from wet soil in the Republic of Korea. To determine their taxonomic positions, the strains were fully characterized. On the basis of genomic information (16S rRNA gene and draft genome sequences), all four isolates represent members of the genus .

Ketonization of Ginsenoside C-K by Novel Recombinant 3-β-Hydroxysteroid Dehydrogenases and Effect on Human Fibroblast Cells.

Background And Objective: The ginsenoside compound K (C-K) (which is a de-glycosylated derivative of major ginsenosides) is effective in the treatment of cancer, diabetes, inflammation, allergy, angiogenesis, aging, and has neuroprotective, and hepatoprotective than other minor ginsenosides. Thus, a lot of studies have been focused on the conversion of major ginsenosides to minor ginsenosides using glycoside hydrolases but there is no study yet published for the bioconversion of minor ginsenosides into another high pharmacological active compound. Therefore, the objective of this study to identify a new gene (besides the glycoside hydrolases) for the conversion of minor ginsenosides C-K into another highly pharmacological active compound.

Disaster preparedness and community helping behaviour in the wake of the 2020 Oregon wildfires.

Extreme weather events are increasing in frequency and severity owing to climate change. Individual-level behavioural responses-notably, disaster preparedness and community helping actions (such as donating and volunteering)-supplement government efforts to respond to such phenomena, but rarely have they been explored together. Using data from a survey administered soon after the 2020 Oregon wildfires, this paper compares a range of socio-demographic, experiential, attitudinal, and communication-related factors associated with these two individual-level behavioural responses.

Arthrobacter hankyongi sp. nov., Isolated From Wet Land.

A Gram-staining-positive, catalase positive and oxidase negative, non-motile, non-flagellated, and oval-shaped bacterium, was designated as I2-34, isolated from wetland in Soul South Korea. Colonies were round, entire, raised, and cream colored after two days of incubation on R2A agar plates at 25 °C. Based on genomes (both 16S rRNA gene and draft genome) sequence analysis, strain I2-34 belongs to the genus Arthrobacter and was most closely related to Arthrobacter deserti YIM CS25 (98.

Low-Complexity Beamforming Design for a Cooperative Reconfigurable Intelligent Surface-Aided Cell-Free Network.

Cell-free (CF) networks are proposed to suppress the interference among collocated cells by deploying several BSs without cell boundaries. Nevertheless, as installing several base stations (BSs) may require high power consumption, cooperative CF networks integrated with a reconfigurable intelligent surface (RIS)/metasurface can avoid this problem. In such cooperative RIS-aided MIMO networks, efficient beamforming schemes are essential to boost their spectral and energy efficiency.

Glanzmann Thrombasthenia in Pakistani Patients: Identification of 7 Novel Pathogenic Variants in the Fibrinogen Receptor αIIbβ3.

Glanzmann thrombasthenia (GT) is a rare autosomal recessive inherited platelet disorder occurring frequently in populations with high incidence of consanguineous marriages. GT is characterized by quantitative and/or qualitative defect of the platelet αIIbβ3 (GPIIb/IIIa) receptor caused by pathogenic variants of the encoding genes: and . Patients present with a moderate to severe bleeding tendency with normal platelet count.

Repressing effect of transformed ginsenoside Rg3-mix against LPS-induced inflammation in RAW264.7 macrophage cells.

Background: Rg3-ginsenoside, a protopanaxadiol saponin, is a well-known adaptogen used for the prevention of cancer and inflammation. However, despite its distinct biological activity, the concentration of Rg3 in the total ginseng extract is insufficient for therapeutic applications. This study aims to convert PPD-class of major ginsenosides into a mixture of minor ginsenoside, to analyze its immune-regulatory role in macrophage cells.

Synergy of 1-MCP and hypobaric treatments prevent fermented flavour and improve consumers' acceptability of 'Shughri' pear.

Development of fermented flavour during storage reduces acceptability of Shughri pear. Therefore, the current study was designed to investigate the combined effect of 1-Methylcyclopropene (1-MCP) and hypobaric treatment on stability of Shughri pear during 120 days of storage. Fruit were treated individually or combinedly with 25, 50, and 75 kilo pascal hypobaric treatments for 4 h and 1-MCP (0.

An Enhanced Machine Learning Approach for Brain MRI Classification.

Magnetic Resonance Imaging (MRI) is a noninvasive technique used in medical imaging to diagnose a variety of disorders. The majority of previous systems performed well on MRI datasets with a small number of images, but their performance deteriorated when applied to large MRI datasets. Therefore, the objective is to develop a quick and trustworthy classification system that can sustain the best performance over a comprehensive MRI dataset.

RTF-RCNN: An Architecture for Real-Time Tomato Plant Leaf Diseases Detection in Video Streaming Using Faster-RCNN.

In today's era, vegetables are considered a very important part of many foods. Even though every individual can harvest their vegetables in the home kitchen garden, in vegetable crops, Tomatoes are the most popular and can be used normally in every kind of food item. Tomato plants get affected by various diseases during their growing season, like many other crops.

Interest rate volatility and financing of Islamic banks.

Despite a direct ban on charging interest, interest-based benchmarks are used as a pricing reference by a majority of Islamic banks, due in part to the absence of stable and widely- published alternatives. Benchmarking interest rate exposes Islamic banks to the problems of conventional banks, particularly the interest rate risk. Against this backdrop, the present study empirically examines the dynamic linkage between the interest rate volatility and the financing of Islamic banks.

A Precise Medical Imaging Approach for Brain MRI Image Classification.

Magnetic resonance imaging (MRI) is an accurate and noninvasive method employed for the diagnosis of various kinds of diseases in medical imaging. Most of the existing systems showed significant performances on small MRI datasets, while their performances decrease against large MRI datasets. Hence, the goal was to design an efficient and robust classification system that sustains a high recognition rate against large MRI dataset.

Signal-to-Noise Ratio Comparison of Several Filters against Phantom Image.

Image denoising methods are important in order to diminish various kinds of noises, which are presented either capturing the image or distorted during image transmission. Signal-to-noise ratio (SNR) is one of the main barriers which avoids the theoretical observations to be accomplished in practice. In this study, we have utilized various kinds of filtering operators against three various noises, which are the signal-to-noise ratio comparison against the phantom image in spatial and frequency domain.

Edge Detection-Based Feature Extraction for the Systems of Activity Recognition.

Human activity recognition (HAR) is a fascinating and significant challenging task. Generally, the accuracy of HAR systems relies on the best features from the input frames. Mostly, the activity frames have the hostile noisy conditions that cannot be handled by most of the existing edge operators.