Unveiling the Interactions between Water Molecule Clusters and Conical Structures via Molecular Dynamics Simulations.

Water scarcity presents a pressing global challenge, necessitating innovative solutions, such as the collection of water from the air using conical structures. However, current research primarily focuses on mist collection rather than on nanoscale clusters of water molecules. Under standard atmospheric conditions, water vapor predominantly exists as imperceptible clusters.

A comparative environmental analysis of conventional and organic rice farming in Thailand in a life cycle perspective using a stochastic modeling approach.

System stochasticity is an inherent characteristic of agricultural systems. Many studies have been conducted in Thailand to analyze the rice production systems. However, most of the prior work just focused on deterministic approach to investigate the rice production systems while disregarding the system variability.

End-to-End Deep Learning Method for Detection of Invasive Parkinson's Disease.

Parkinson's disease directly affects the nervous system are causes a change in voice, lower efficiency in daily routine tasks, failure of organs, and death. As an estimate, nearly ten million people are suffering from Parkinson's disease worldwide, and this number is increasing day by day. The main cause of an increase in Parkinson's disease patients is the unavailability of reliable procedures for diagnosing Parkinson's disease.

Automatic Detection of Liver Cancer Using Hybrid Pre-Trained Models.

Liver cancer is a life-threatening illness and one of the fastest-growing cancer types in the world. Consequently, the early detection of liver cancer leads to lower mortality rates. This work aims to build a model that will help clinicians determine the type of tumor when it occurs within the liver region by analyzing images of tissue taken from a biopsy of this tumor.

A Novel Binary Hybrid PSO-EO Algorithm for Cryptanalysis of Internal State of RC4 Cipher.

Cryptography protects privacy and confidentiality. So, it is necessary to guarantee that the ciphers used are secure and cryptanalysis-resistant. In this paper, a new state recovery attack against the RC4 stream cipher is revealed.

Study of Different Deep Learning Methods for Coronavirus (COVID-19) Pandemic: Taxonomy, Survey and Insights.

COVID-19 has evolved into one of the most severe and acute illnesses. The number of deaths continues to climb despite the development of vaccines and new strains of the virus have appeared. The early and precise recognition of COVID-19 are key in viably treating patients and containing the pandemic on the whole.

Insight into single-element nobel metal anisotropic silver nanoparticle shape-dependent selective ROS generation and quantification.

The biocidal action mechanism of single element noble metal anisotropic nanoparticles has remained a perplexing challenge. Herein, we investigated the photogenerated anisotropic AgNP ROS production kinetics and each ROS species' direct impact on Gram-negative and Gram-positive bacteria. Three shapes (Triangular, Cubes, Rods) of AgNP with excellent morphology were fabricated plasmon mediated synthesis.

Under-oil superhydrophilic salt particle filter for the efficient separation of water-in-oil emulsions.

In this study, a surfactant stabilized water-in-oil emulsion has been successfully separated by using only NaCl particles as a filter. This novel strategy is suitable for continuous filtration of a large quantity of water-in-oil emulsion with a volume of up to 1500 mL. Moreover, a filtration flux of up to 40 000 L m h is reported, which is around ten times higher than the conventional filtration methods.

Corrigendum to "Tabu Search and Machine-Learning Classification of Benign and Malignant Proliferative Breast Lesions".

[This corrects the article DOI: 10.1155/2020/4671349.].

Underoil Superhydrophilic Metal Felt Fabricated by Modifying Ultrathin Fumed Silica Coatings for the Separation of Water-in-Oil Emulsions.

Although various superhydrophobic/superoleophilic porous materials have been developed and successfully applied to separate water-in-oil emulsions through the size-sieving mechanism, the separation performance is restricted by their nanoscale pore size severely. In this study, the wettability of underoil water on fumed silica was experimentally observed, and the underlying mechanism was investigated by carrying out theoretical analysis and molecular dynamic (MD) simulations. Further, we present a novel, facile, and an inexpensive technique to fabricate an underoil superhydrophilic metal felt with microscale pores for the separation of water-in-oil emulsions using SiO nanoparticles (NPs) as building blocks.

Tabu Search and Machine-Learning Classification of Benign and Malignant Proliferative Breast Lesions.

Breast cancer is the most diagnosed cancer among women around the world. The development of computer-aided diagnosis tools is essential to help pathologists to accurately interpret and discriminate between malignant and benign tumors. This paper proposes the development of an automated proliferative breast lesion diagnosis based on machine-learning algorithms.

Spontaneous propulsion of a water nanodroplet induced by a wettability gradient: a molecular dynamics simulation study.

The directional propulsion of liquid droplets at the nanoscale is quite an interesting topic of research in the fields of micro/nano-fluidics, water filtration, precision medicine, and cooling of electronics. In this study, the unidirectional spontaneous transport of a water nanodroplet on a solid surface with a multi-gradient surface (MGS) inspired by natural species is modeled and analyzed using molecular dynamics (MD) simulations. There are three different MGSs considered in this study containing different wedge angles of the hydrophilic region of the solid surface.

Unidirectional transport of water nanodroplets entrapped inside a nonparallel smooth surface: a molecular dynamics simulation study.

The unidirectional transport of liquid nanodroplets is an important topic of research in the field of drug delivery, labs on chips, micro/nanofluidics, and water collection. Inspired by nature a nonparallel surface (NPS) is modelled in this study for pumpless water transport applications. The dynamics of water transport is analyzed with the aid of Molecular Dynamics (MD) simulations.

Automated Breast Cancer Diagnosis Based on Machine Learning Algorithms.

There have been several empirical studies addressing breast cancer using machine learning and soft computing techniques. Many claim that their algorithms are faster, easier, or more accurate than others are. This study is based on genetic programming and machine learning algorithms that aim to construct a system to accurately differentiate between benign and malignant breast tumors.

Life-Like Motion of Oil Drops at the Air-Liquid Interface.

Generally, interactions of oil drops at the air-liquid interface mainly have two features, namely, attraction and repulsion. However, in our study, we find that the oil drops at the air-liquid interface have other interacting features, that is, the atomic-like motion and the "capture" motion. For the atomic-like motion, oil drops attract each other at a long distance, but repel when they are about to come into contact with each other.

Development of Durable, Fluorine-free, and Transparent Superhydrophobic Surfaces for Oil/Water Separation.

Although artificial superhydrophobic materials have extensive and significant applications in antifouling, self-cleaning, anti-icing, fluid transport, oil/water separation, and so forth, the poor robustness of these surfaces has always been a bottleneck for their development in practical industrial applications. Here, we report a facile, economical, efficient, and versatile strategy to prepare environmentally friendly, mechanically robust, and transparent superhydrophobic surfaces by combining adhesive and hydrophobic paint, which is applicable for both hard and soft substrates. The coated substrates exhibit excellent superhydrophobic property and ultralow adhesion with water (contact angle ≈ 160° and sliding angle <2°).

Vapor-Driven Transport of Different Types of Objects at the Air-Liquid Interface.

Transportation and position control of objects on the surface of liquids is an important part of automation. To drive an object on the surface of a liquid, many methods have been proposed. However, these methods mainly focus on the driving of the object itself, and it is still difficult to precisely control its position.

Separation Mechanism and Construction of Surfaces with Special Wettability for Oil/Water Separation.

Oil leakage and the discharge of oil/water mixtures by domestic and industrial consumers have caused not only severe environmental pollution and a threat to all species in the ecosystem but also a huge waste of precious resources. Therefore, the separation of oil/water mixtures, especially stable emulsion, has become an urgent global issue. Recently, materials containing a special wettability feature for oil and water have drawn immense attention because of their potential applications for oil/water separation application.

Multidirectional regression (MDR)-based features for automatic voice disorder detection.

Background And Objective: Objective assessment of voice pathology has a growing interest nowadays. Automatic speech/speaker recognition (ASR) systems are commonly deployed in voice pathology detection. The aim of this work was to develop a novel feature extraction method for ASR that incorporates distributions of voiced and unvoiced parts, and voice onset and offset characteristics in a time-frequency domain to detect voice pathology.