Influence of alkali metals on water dynamics inside imidazolium-based ionic liquid nano-domains.

The global need to expand the design of energy-storage devices led to the investigation of alkali metal - Ionic Liquid (IL) mixtures as a possible class of electrolytes. In this study, 1D and 2D Nuclear Magnetic Resonance (NMR) and Electrochemical Impedance Spectroscopy (EIS) as well as Molecular Dynamics (MD) simulations were used to study the intermolecular interactions in imidazolium-based IL - water - alkali halide ternary mixtures. The H and Na 1D and H DOSY NMR spectra revealed that the presence of small quantities of NaCl does not influence the aggregation of water molecules in the IL nano-domains.

Is Deep Brain Stimulation an Effective Treatment for Psychostimulant Dependency? A Preclinical and Clinical Systematic Review.

Addiction to psychostimulants significantly affects public health. Standard medical therapy is often not curative. Deep brain stimulation (DBS) is a promising treatment that has attracted much attention for addiction treatment in recent years.

Detecting diseases in medical prescriptions using data mining methods.

Every year, the health of millions of people around the world is compromised by misdiagnosis, which sometimes could even lead to death. In addition, it entails huge financial costs for patients, insurance companies, and governments. Furthermore, many physicians' professional life is adversely affected by unintended errors in prescribing medication or misdiagnosing a disease.

Home Health Care Problem with Synchronization Visits and Considering Samples Transferring Time: A Case Study in Tehran, Iran.

Health care facilities have not increased in response to the growing population. Therefore, government and health agencies are constantly seeking cost-effective alternatives so they can provide effective health care to their constituents. Around the world, health care organizations provide home health care (HHC) services to patients, especially the elderly, as an efficient alternative to hospital care.

Extraction of discriminative features from EEG signals of dyslexic children; before and after the treatment.

Dyslexia is a neurological disorder manifested as difficulty reading and writing. It can occur despite adequate instruction, intelligence, and intact sensory abilities. Different electroencephalogram (EEG) patterns have been demonstrated between dyslexic and healthy subjects in previous studies.

A diagnostic miRNA panel to detect recurrence of ovarian cancer through artificial intelligence approaches.

Background: Ovarian Cancer (OC) is the deadliest gynecology malignancy, whose high recurrence rate in OC patients is a challenging object. Therefore, having deep insights into the genetic and molecular mechanisms of OC recurrence can improve the target therapeutic procedures. This study aimed to discover crucial miRNAs for the detection of tumor recurrence in OC by artificial intelligence approaches.

Magnetic chitosan-silk fibroin hydrogel/graphene oxide nanobiocomposite for biological and hyperthermia applications.

This work represents a biocompatible magnetic nanobiocomposite prepared by the composition of chitosan (CS) hydrogel, silk fibroin (SF), graphene oxide (GO), and FeO NPs. Terephthaloyl thiourea was applied as a cross-linking agent to cross-link the CS strings. The CS hydrogel/SF/GO/FeO nanobiocomposite with many characteristics, such as high structural uniformity, thermal stability, biocompatibility, and stability in an aqueous solution.

Simulation of nerve fiber based on anti-resonant reflecting optical waveguide.

Light and optical techniques are widely used for the diagnosis and treatment of neurological diseases as advanced methods. Understanding the optical properties of nervous tissue and nerve cells is vital. Using light sources in these methods raises significant challenges, such as finding the place of light transmission in nerve fibers that could be an appropriate substrate for neural signaling.

Influence of the coiling porosity on the risk reduction of the cerebral aneurysm rupture: computational study.

The formation and progress of cerebral aneurysm is highly associated with hemodynamic factors and blood flow feature. In this study, comprehensive efforts are done to investigate the blood hemodynamic effects on the creation and growth of the Internal Carotid Artery. The computational fluid dynamic method is used for the visualization of the bloodstream inside the aneurysm.

A green protocol for the one-pot synthesis of 3,4-disubstituted isoxazole-5(4H)-ones using modified β-cyclodextrin as a catalyst.

This manuscript reports an impressive and facile strategy for synthesizing isoxazole derivatives using immobilized Cu (I) in metformin-functionalized β-cyclodextrin as a catalyst. The architecture of this catalyst was characterized by different analytical techniques such as Fourier transform infrared spectroscopy, Thermogravimetric analysis, X-ray diffraction, Field emission scanning electron microscopy, and Energy-dispersive X-ray spectroscopy. The catalyst showed remarkable reusability even after 7 consecutive runs.

Application of Meta-Heuristic Algorithms for Training Neural Networks and Deep Learning Architectures: A Comprehensive Review.

The learning process and hyper-parameter optimization of artificial neural networks (ANNs) and deep learning (DL) architectures is considered one of the most challenging machine learning problems. Several past studies have used gradient-based back propagation methods to train DL architectures. However, gradient-based methods have major drawbacks such as stucking at local minimums in multi-objective cost functions, expensive execution time due to calculating gradient information with thousands of iterations and needing the cost functions to be continuous.

A novel magnetic nanocomposite based on alginate-tannic acid hydrogel embedded with silk fibroin with biological activity and hyperthermia application.

In the current study, sodium alginate (SA) and tannic acid (TA), in the presence of calcium chloride as a cross-linker, were used to fabricate a nanocomposite scaffold. With the addition of silk fibroin (SF), the strength of the synthesized composite was increased. FeO magnetic nanoparticles (MNPs) led to the usage of this magnetic nanocomposite in hyperthermia applications.

Synergies in antimicrobial treatment by a levofloxacin-loaded halloysite and gold nanoparticles with a conjugation to a cell-penetrating peptide.

Herein, a novel designed antimicrobial therapeutic drug delivery system is presented, in which halloysite nanotubes (HNTs) encapsulate a determined dosage of levofloxacin (lvx). Moreover, gold nanoparticles (AuNPs) have been embedded into the structure for plasmonic heating under irradiation of the green LED light (7 W, 526 nm). It was revealed that the plasmonic heating of the AuNPs leads to a controlled trend in the lvx release process.

Co-design Optimization of a Novel Multi-identity Drone Helicopter (MICOPTER).

Delivery drones have always faced challenges when it comes to reliably deliver packages. This paper introduces a novel concept of a hybrid drone called "MICOPTER" to alleviate this issue. Being able to fly in three modes of aircraft, helicopter, and gyrocopter, the proposed model of the multi-identity helicopter comprises a 2DOF tilting mechanism of rotors and a folding wing system leading to better performance and controllability.

Multi-scale model of lumen formation via inverse membrane blebbing mechanism during sprouting angiogenesis process.

Cancer is one of the leading causes of mortality and morbidity among people worldwide. Cancer appears as solid tumors in many cases. Angiogenesis is the growth of blood vessels from the existing vasculature and is one of the imperative processes in tumor growth.

A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning.

Background: Selecting and prioritizing candidate disease genes is necessary before conducting laboratory studies as identifying disease genes from a large number of candidate genes using laboratory methods, is a very costly and time-consuming task. There are many machine learning-based gene prioritization methods. These methods differ in various aspects including the feature vectors of genes, the used datasets with different structures, and the learning model.

Introducing a Linear Empirical Correlation for Predicting the Mass Heat Capacity of Biomaterials.

This study correlated biomass heat capacity (Cp) with the chemistry (sulfur and ash content), crystallinity index, and temperature of various samples. A five-parameter linear correlation predicted 576 biomass Cp samples from four different origins with the absolute average relative deviation (AARD%) of ~1.1%.

A numerical approach for preventing the dispersion of infectious disease in a meeting room.

Airborne transmission of respiratory aerosols carrying infectious viruses has generated many concerns about cross-contamination risks, particularly in indoor environments. ANSYS Fluent software has been used to investigate the dispersion of the viral particles generated during a coughing event and their transport dynamics inside a safe social-distance meeting room. Computational fluid dynamics based on coupled Eulerian-Lagrangian techniques are used to explore the characteristics of the airflow field in the domain.

Panels of mRNAs and miRNAs for decoding molecular mechanisms of Renal Cell Carcinoma (RCC) subtypes utilizing Artificial Intelligence approaches.

Renal Cell Carcinoma (RCC) encompasses three histological subtypes, including clear cell RCC (KIRC), papillary RCC (KIRP), and chromophobe RCC (KICH) each of which has different clinical courses, genetic/epigenetic drivers, and therapeutic responses. This study aimed to identify the significant mRNAs and microRNA panels involved in the pathogenesis of RCC subtypes. The mRNA and microRNA transcripts profile were obtained from The Cancer Genome Atlas (TCGA), which were included 611 ccRCC patients, 321 pRCC patients, and 89 chRCC patients for mRNA data and 616 patients in the ccRCC subtype, 326 patients in the pRCC subtype, and 91 patients in the chRCC for miRNA data, respectively.

Nickel removal from aqueous solutions using flow-electrode capacitive deionization (Optimization by Response Surface Methodology (RSM)).

Nowadays, wastewater and water treatment with an efficient system for the removal of heavy metals is a serious challenge. Nickel is one of the main heavy metal pollutants that exist in the wastewater of various industries. Several technologies have been developed for removal of nickel, including the new electrochemical processes.

Cell loaded hydrogel containing Ag-doped bioactive glass-ceramic nanoparticles as skin substitute: Antibacterial properties, immune response, and scarless cutaneous wound regeneration.

An ideal tissue-engineered dermal substitute should possess angiogenesis potential to promote wound healing, antibacterial activity to relieve the bacterial burden on skin, as well as sufficient porosity for air and moisture exchange. In light of this, a glass-ceramic (GC) has been incorporated into chitosan and gelatin electrospun nanofibers (240-360 nm), which MEFs were loaded on it for healing acceleration. The GC was doped with silver to improve the antibacterial activity.

Brain functional connectivity analysis in patients with relapsing-remitting multiple sclerosis: A graph theory approach of EEG resting state.

Multiple sclerosis (MS) is an autoimmune disease related to the central nervous system (CNS). This study aims to investigate the effects of MS on the brain's functional connectivity network using the electroencephalogram (EEG) resting-state signals and graph theory approach. Resting-state eyes-closed EEG signals were recorded from 20 patients with relapsing-remitting MS (RRMS) and 18 healthy cases.

Gas Selectivity Enhancement Using Serpentine Microchannel Shaped with Optimum Dimensions in Microfluidic-Based Gas Sensor.

A microfluidic-based gas sensor was chosen as an alternative method to gas chromatography and mass spectroscopy systems because of its small size, high accuracy, low cost, etc. Generally, there are some parameters, such as microchannel geometry, that affect the gas response and selectivity of the microfluidic-based gas sensors. In this study, we simulated and compared 3D numerical models in both simple and serpentine forms using COMSOL Multiphysics 5.

Novel 5-Nitrofuran-Tagged Imidazo-Fused Azines and Azoles Amenable by the Groebke-Blackburn-Bienaymé Multicomponent Reaction: Activity Profile against ESKAPE Pathogens and Mycobacteria.

A chemically diverse set of 13 5-nitrofuran-tagged heterocyclic compounds has been prepared via the Groebke-Blackburn-Bienaymé multicomponent reaction. The testing of these compounds against the so-called ESKAPE panel of pathogens identified an apparent lead compound--cyclohexyl-2-(5-nitrofuran-2-yl)imidazo[1,2-]pyridine-3-amine ()-which showed an excellent profile against and (MIC 0.25, 0.