Facile Spin-Coated MoS Thin Films from a Single-Source Precursor for HER Activity.

Hydrogen evolution reaction (HER) is one of the most promising ways to replace the consumption of fossil fuels with a clean and green energy source. HER requires a suitable material as a catalyst to lower overpotential and minimize energy consumption. MoS is an excellent candidate for the HER because of its suitable band structure.

Efficient Nonenzymatic Electrochemical Detection of Glucose Using CuO Nanoparticles@CNT-Wrapped Graphene Oxide Composite Electrode.

A highly sensitive and stable nonenzymatic glucose biosensor has been developed via composite materials composed of CuO and graphene oxide (GO)/carbon nanotube (CNT) nanohybrid (CuO/GO/CNTs). Copper oxide nanoparticle(NP)-modified CNTs were stacked via graphene sheets and synthesized through hydrothermal method, providing a larger surface area with boosted catalytic activity for efficient mass and electron passage, respectively. Scanning electron microscopy (SEM) and energy-dispersive x-ray (EDX) spectroscopy have been used to investigate the morphology and composition of as-prepared nanohybrids, whereas x-ray diffraction (XRD) patterns provide information about the crystal structure and lattice parameters.

Carbon Nanotube Fiber-Based Flexible Microelectrode for Electrochemical Glucose Sensors.

Electrochemical sensors are gaining significant demand for real-time monitoring of health-related parameters such as temperature, heart rate, and blood glucose level. A fiber-like microelectrode composed of copper oxide-modified carbon nanotubes (CuO@CNTFs) has been developed as a flexible and wearable glucose sensor with remarkable catalytic activity. The unidimensional structure of CNT fibers displayed efficient conductivity with enhanced mechanical strength, which makes these fibers far superior as compared to other fibrous-like materials.

An AI-empowered affect recognition model for healthcare and emotional well-being using physiological signals.

Affective Computing is one of the central studies for achieving advanced human-computer interaction and is a popular research direction in the field of artificial intelligence for smart healthcare frameworks. In recent years, the use of electroencephalograms (EEGs) to analyze human emotional states has become a hot spot in the field of emotion recognition. However, the EEG is a non-stationary, non-linear signal that is sensitive to interference from other physiological signals and external factors.

Binder-Free Fabrication of Prussian Blue Analogues Based Electrocatalyst for Enhanced Electrocatalytic Water Oxidation.

Developing a cost-effective, efficient, and stable oxygen evolution reaction (OER) catalyst is of great importance for sustainable energy conversion and storage. In this study, we report a facile one-step fabrication of cationic surfactant-assisted Prussian blue analogues (PBAs) M[Fe(CN)CHCHNH]∙yCHNBr abbreviated as SF[Fe-Tol-M] (where SF = N-tridecyl-3-methylpyridinium bromide and M = Mn, Co and Ni) as efficient heterogeneous OER electrocatalysts. The electrocatalysts have been characterized by Fourier transform infrared (FT-IR) spectroscopy, powder X-ray diffraction (PXRD), scanning electron microscopy (SEM) coupled with energy dispersive X-ray (EDX) analysis, and X-ray photoelectron spectroscopy (XPS).

DFT-Net: Deep Feature Transformation Based Network for Object Categorization and Part Segmentation in 3-Dimensional Point Clouds.

Unlike 2-dimensional (2D) images, direct 3-dimensional (3D) point cloud processing using deep neural network architectures is challenging, mainly due to the lack of explicit neighbor relationships. Many researchers attempt to remedy this by performing an additional voxelization preprocessing step. However, this adds additional computational overhead and introduces quantization error issues, limiting an accurate estimate of the underlying structure of objects that appear in the scene.

Electrochemically Deposited Amorphous Cobalt-Nickel-Doped Copper Oxide as an Efficient Electrocatalyst toward Water Oxidation Reaction.

Production of hydrogen through water splitting is one of the green and the most practical solutions to cope with the energy crisis and greenhouse effect. However, oxygen evolution reaction (OER) being a sluggish step, the use of precious metal-based catalysts is the main impediment toward the viability of water splitting. In this work, amorphous copper oxide and doped binary- and ternary-metal oxides (containing Co, Ni, and Cu) have been prepared on the surface of fluorine-doped tin oxide by a facile electrodeposition route followed by thermal treatment.

AI inspired EEG-based spatial feature selection method using multivariate empirical mode decomposition for emotion classification.

Classification of human emotions based on electroencephalography (EEG) is a very popular topic nowadays in the provision of human health care and well-being. Fast and effective emotion recognition can play an important role in understanding a patient's emotions and in monitoring stress levels in real-time. Due to the noisy and non-linear nature of the EEG signal, it is still difficult to understand emotions and can generate large feature vectors.

An Innovative Multi-Model Neural Network Approach for Feature Selection in Emotion Recognition Using Deep Feature Clustering.

Emotional awareness perception is a largely growing field that allows for more natural interactions between people and machines. Electroencephalography (EEG) has emerged as a convenient way to measure and track a user's emotional state. The non-linear characteristic of the EEG signal produces a high-dimensional feature vector resulting in high computational cost.

Biferrocenyl Schiff bases as efficient corrosion inhibitors for an aluminium alloy in HCl solution: a combined experimental and theoretical study.

The corrosion inhibitive capabilities of some ferrocene-based Schiff bases on aluminium alloy AA2219-T6 in acidic medium were investigated using Tafel polarization, electrochemical impedance spectroscopy (EIS), weight loss measurement, FT-IR spectroscopy and scanning electron microscopic (SEM) techniques. The influence of molecular configuration on the corrosion inhibition behavior has been explored by quantum chemical calculation. Ferrocenyl Schiff bases 4,4'-((((ethane-1,2-diylbis(oxy))bis(4,1-phenylene))bis(methaneylylidene))bis(azaneylylidene))bisferrocene (Fcua), 4,4'-((((ethane-1,2-diylbis(oxy))bis(2-methoxy-1,4-phenylene))bis(methaneylylidene))bis(azaneylylidene))bisferrocene (Fcub) and 4,4'-((((ethane-1,2-diylbis(oxy))bis(2-ethoxy-1,4-phenylene))bis(methaneylylidene))bis(azaneylylidene))bisferrocene (Fcuc) have been synthesized and characterized by FT-IR, H and C NMR spectroscopic studies.

EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach.

Much attention has been paid to the recognition of human emotions with the help of electroencephalogram (EEG) signals based on machine learning technology. Recognizing emotions is a challenging task due to the non-linear property of the EEG signal. This paper presents an advanced signal processing method using the deep neural network (DNN) for emotion recognition based on EEG signals.

Synthesis, characterization and biological evaluation of novel benzimidazole derivatives.

In search of achieving less toxic and more potent chemotherapeutics, three novel heterocyclic benzimidazole derivatives: 2-(1H-benzo[d]imidazol-2-yl)-4-chlorophenol (BM1), 4-chloro-2-(6-methyl-1H-benzo[d]imidazol-2-yl)phenol (BM2) and 4-chloro-2-(6-nitro-1H-benzo[d]imidazol-2-yl)phenol (BM3) with DNA-targeting properties, were synthesized and fully characterized by important physicochemical techniques. The DNA binding properties of the compounds were investigated by UV-Visible absorption titrations and thermal denaturation experiments. These molecules exhibited a good binding propensity to fish sperm DNA (FS-DNA), as evident from the high binding constants () values: 1.