Automatic classification of signal regions in H Nuclear Magnetic Resonance spectra.

The identification and characterization of signal regions in Nuclear Magnetic Resonance (NMR) spectra is a challenging but crucial phase in the analysis and determination of complex chemical compounds. Here, we present a novel supervised deep learning approach to perform automatic detection and classification of multiplets in H NMR spectra. Our deep neural network was trained on a large number of synthetic spectra, with complete control over the features represented in the samples.

Electronic and optical properties of thiogermanate AgGaGeS: theory and experiment.

The electronic and optical properties of an AgGaGeS crystal were studied by first-principles calculations, where the full-potential augmented plane-wave plus local orbital (APW+lo) method was used together with exchange-correlation pseudopotential described by PBE, PBE+, and TB-mBJ+ approaches. To verify the correctness of the present theoretical calculations, we have measured for the AgGaGeS crystal the XPS valence-band spectrum and the X-ray emission bands representing the energy distribution of the electronic states with the biggest contributions in the valence-band region and compared them on a general energy scale with the theoretical results. Such a comparison indicates that, the calculations within the TB-mBJ+ approach reproduce the electron-band structure peculiarities (density of states - DOS) of the AgGaGeS crystal which are in fairly good agreement with the experimental data based on measurements of XPS and appropriate X-ray emission spectra.

Machine Learning-Based Quantitative Structure-Property Relationships for the Electronic Properties of Cyano Polycyclic Aromatic Hydrocarbons.

In this study, quantitative structure-property relationships (QSPR) based on a machine learning (ML) methodology and the truncated degree of π-orbital overlap (DPO) to predict the electronic properties, namely, the bandgaps, electron affinities, and ionization potentials of the cyano polycyclic aromatic hydrocarbon (CN-PAH) chemical class were developed. The level of theory B3LYP/6-31+G(d) of density functional theory (DFT) was used to calculate a total of 926 data points for the development of the QSPR model. To include the substituents effects, a new descriptor was added to the DPO model.

Contrasting impacts of dry versus humid heat on US corn and soybean yields.

The impact of extreme heat on crop yields is an increasingly pressing issue given anthropogenic climate warming. However, some of the physical mechanisms involved in these impacts remain unclear, impeding adaptation-relevant insight and reliable projections of future climate impacts on crops. Here, using a multiple regression model based on observational data, we show that while extreme dry heat steeply reduced U.

Vortex Motions in the Solar Atmosphere: Definitions, Theory, Observations, and Modelling.

Vortex flows, related to solar convective turbulent dynamics at granular scales and their interplay with magnetic fields within intergranular lanes, occur abundantly on the solar surface and in the atmosphere above. Their presence is revealed in high-resolution and high-cadence solar observations from the ground and from space and with state-of-the-art magnetoconvection simulations. Vortical flows exhibit complex characteristics and dynamics, excite a wide range of different waves, and couple different layers of the solar atmosphere, which facilitates the channeling and transfer of mass, momentum and energy from the solar surface up to the low corona.

Graphene Oxide Deposited with Transition Metal Chalcogenide for Selective Extraction and Determination of Hg(II): Experimental and Computational Analysis.

A graphene oxide (GO/CdS) nanocomposite was synthesized by an in situ hydrothermal process and studied to develop a micro solid phase extraction procedure. Microscopic and spectroscopic characterizations have confirmed the successful preparation of the GO/CdS composite. The prepared nanocomposite selectively extracts Hg(II) ions from various water samples (tap, river, and groundwater).

Molecular dynamics simulation of cancer cell membrane perforated by shockwave induced bubble collapse.

It has been widely accepted that cancer cells are softer than their normal counterparts. This motivates us to propose, as a proof-of-concept, a method for the efficient delivery of therapeutic agents into cancer cells, while normal cells are less affected. The basic idea of this method is to use a water jet generated by the collapse of the bubble under shockwaves to perforate pores in the cell membrane.

Binding mechanism and SERS spectra of 5-fluorouracil on gold clusters.

The adsorption behaviour of the 5-fluorouracil (5FU) on small gold clusters Au with = 6, 8, 20 was evaluated by means of density functional theory using the PBE-D3 functional in combination with a mixed basis set, i.e. cc-pVDZ-PP for gold atoms and cc-pVTZ for non-metal elements.

Covalently linked mercaptoacetic acid on ZrO coupled cellulose nanofibers for solid phase extraction of Hg(ii): experimental and DFT studies.

Zirconium oxide (ZrO) nanoparticles were introduced onto cellulose nanofibers after being covalently functionalized with mercaptoacetic acid. We experimentally demonstrate that the nanocomposite is capable of selectively capturing Hg(ii) from aqueous samples down to trace level concentrations. Density functional theory (DFT) calculations indicate that energetically favorable R-S → Hg ← O-R bidentate complex formation enhances the rapid adsorption, leading to selective extraction of Hg(ii).

Computational Study on the Nature of Bonding between Silver Ions and Nitrogen Ligands.

In this paper, the nature of silver ion-nitrogen atom bonding in the complexation with ammonia, azomethine, pyridine, and hydrogen cyanide from one to four coordinations is studied at the B97-1 level of density functional theory. The results indicate that the two-coordinated complex of the silver ion with different nitrogen ligands representing sp, sp, and sp orbital hybridizations is the most stable form having the shortest Ag-N bond distance, highest vibrational frequencies, largest bond order, and favorable Gibbs free energy of formation. Natural bond orbital analyses further show that σ-donation from the nitrogen lone pair to the silver empty 5s orbital is dominant in the dative metal-ligand bonding character with N-sp having the largest contribution among the different N atomic orbital hybridizations.

Physico-chemical properties of the association of cetyltrimethylammonium bromide and bovine serum albumin mixture in aqueous-organic mixed solvents.

Herein, we have investigated the association behavior of bovine serum albumin (BSA) and cetyltrimethylammonium bromide (CTAB) using the conductivity method in HO and HO + organic mixed solvents at different temperatures. The association phenomenon was detected from the deviation of the conductivity changes with enhancing the surfactant concentration and changes of numerous physico-chemical properties, such as CMC, α, β and thermodynamic variables (∆G, ∆H and ∆S). The values of CMC for the CTAB + BSA system in 10 % (v/v) solvents follow the trend: CMC < CMC < CMC < CMC < CMC.

Numerical study of transient aerodynamic forces acting on a ski jumper considering dynamic posture change from takeoff to landing.

This study was designed to develop a computational fluid dynamics (CFD) method for unsteady analysis of a series of ski jump movements with attitude changes, and to analyse the aerodynamic characteristics of an expert jumper over the entire ski jump movement. Two ski jumpers participated in this study. A sensor-based motion capture suit was used to capture the jumper's posture during the actual ski jump.

Optimization for a New XY Positioning Mechanism by Artificial Neural Network-Based Metaheuristic Algorithms.

This paper devotes a new method in modeling and optimizing to handle the optimization of the XY positioning mechanism. The fitness functions and constraints of the mechanism are formulated via proposing a combination of artificial neural network (ANN) and particle swarm optimization (PSO) methods. Next, the PSO is hybridized with the grey wolf optimization, namely PSO-GWO, which is applied to three scenarios in handling the single objective function.

Biologically Active Peptides from Venoms: Applications in Antibiotic Resistance, Cancer, and Beyond.

Peptides are potential therapeutic alternatives against global diseases, such as antimicrobial-resistant infections and cancer. Venoms are a rich source of bioactive peptides that have evolved over time to act on specific targets of the prey. Peptides are one of the main components responsible for the biological activity and toxicity of venoms.

Predicting CO2 trapping in deep saline aquifers using optimized long short-term memory.

A sustainable environment by decreasing fossil fuel utilization and anthropogenic greenhouse gases is a globally main goal due to climate change and serious air pollution. Carbon dioxide (CO2) is a heat-trapping (greenhouse) that is released into the earth's atmosphere from natural processes, such as volcanic respiration and eruptions, as well as human activities, such as burning fossil fuels and deforestation. Due to this fact, underground carbon storage (UCS) is a promising technology to cut carbon emissions.

Mexican-hat dispersions and high carrier mobility of γ-SnX (X = O, S, Se, Te) single-layers: a first-principles investigation.

The shape of energy dispersions near the band-edges plays a decisive role in the transport properties, especially the carrier mobility, of semiconductors. In this work, we design and investigate the γ phase of tin monoxide and monochalcogenides γ-SnX (X = O, S, Se, and Te) through first-principles simulations. γ-SnX is found to be dynamically stable with phonon dispersions containing only positive phonon frequencies.

Bacterial resistance to antibacterial agents: Mechanisms, control strategies, and implications for global health.

The spread of bacterial drug resistance has posed a severe threat to public health globally. Here, we cover bacterial resistance to current antibacterial drugs, including traditional herbal medicines, conventional antibiotics, and antimicrobial peptides. We summarize the influence of bacterial drug resistance on global health and its economic burden while highlighting the resistance mechanisms developed by bacteria.

Evaluating the Applications of Dendritic Neuron Model with Metaheuristic Optimization Algorithms for Crude-Oil-Production Forecasting.

The forecasting and prediction of crude oil are necessary in enabling governments to compile their economic plans. Artificial neural networks (ANN) have been widely used in different forecasting and prediction applications, including in the oil industry. The dendritic neural regression (DNR) model is an ANNs that has showed promising performance in time-series prediction.

Fruit-CoV: An efficient vision-based framework for speedy detection and diagnosis of SARS-CoV-2 infections through recorded cough sounds.

COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This deadly virus has spread worldwide, leading to a global pandemic since March 2020. A recent variant of SARS-CoV-2 named Delta is intractably contagious and responsible for more than four million deaths globally.

Gagones A-F: Six prenylated chalcones from the heartwood of Mansonia gagei.

Six undescribed prenylated chalcones gagones A-F were isolated from the acetone fraction of Mansonia gagei heartwood. Their structures were unambiguously established based on spectroscopic analysis (HRESIMS, 1D and 2D NMR), as well as comparison to literature data. Their absolute configurations were elucidated using DP4 and electronic circular dichroism calculations.

Design and Optimization for a New XYZ Micropositioner with Embedded Displacement Sensor for Biomaterial Sample Probing Application.

An XYZ compliant micropositioner has been widely mentioned in precision engineering, but the displacements in the X, Y, and Z directions are often not the same. In this study, a design and optimization for a new XYZ micropositioner are developed to obtain three same displacements in three axes. The proposed micropositioner is a planar mechanism whose advantage is a generation of three motions with only two actuators.

First-principles study on the structural properties of 2D MXene SnSiGeN and its electronic properties under the effects of strain and an external electric field.

The MXene SnSiGeN monolayer as a new member of the MoSiN family was proposed for the first time, and its structural and electronic properties were explored by applying first-principles calculations with both PBE and hybrid HSE06 approaches. The layered hexagonal honeycomb structure of SnSiGeN was determined to be stable under dynamical effects or at room temperature of 300 K, with a rather high cohesive energy of 7.0 eV.