Differential modulation on neural activity related to flankers during face processing: A visual crowding study.

In this visual crowding study, we manipulated the perceivability of a central crowded face (a fearful or a neutral face) by varying the similarity between the central face and the surrounding flanker stimuli. We presented participants with pairs of visual clutters and recorded their electroencephalography during an emotion judgement task. In an upright flanker condition where both the central target face and flanker faces were upright faces, participants were less likely to report seeing the target face, and their P300 was weakened, compared to a scrambled flanker condition where scrambled face images were used as flankers. Additionally, at âˆ¼ 120 ms post-stimulus, a posterior negativity was found for the upright compared to scrambled flanker condition, however only for fearful face targets. We concluded that early neural responses seem to be affected by the perceptual characteristics of both target and flanker stimuli whereas later-stage neural activity is associated with post-perceptual evaluation of the stimuli in this visual crowding paradigm.

New Gradient Correction Scheme for Electronically Nonadiabatic Dynamics Involving Multiple Spin States.

It has been recommended that the best representation to use for trajectory surface hopping (TSH) calculations is the fully adiabatic basis in which the Hamiltonian is diagonal. Simulations of intersystem crossing processes with conventional TSH methods require an explicit computation of nonadiabatic coupling vectors (NACs) in the molecular-Coulomb-Hamiltonian (MCH) basis, also called the spin-orbit-free basis, in order to compute the gradient in the fully adiabatic basis (also called the diagonal representation). This explicit requirement destroys some of the advantages of the overlap-based algorithms and curvature-driven algorithms that can be used for the most efficient TSH calculations. Therefore, although these algorithms allow one to perform NAC-free simulations for internal conversion processes, one still requires NACs for intersystem crossing. Here, we show that how the NAC requirement is circumvented by a new computation scheme called the time-derivative-matrix scheme.

Bibliometrics Analysis of Research Progress of Electrochemical Detection of Tetracycline Antibiotics.

Tetracycline is a broad-spectrum class of antibiotics. The use of excessive doses of tetracycline antibiotics can result in their residues in food, posing varying degrees of risk to human health. Therefore, the establishment of a rapid and sensitive field detection method for tetracycline residues is of great practical importance to improve the safety of food-derived animal foods. Electrochemical analysis techniques are widely used in the field of pollutant detection because of the simple detection principle, easy operation of the instrument, and low cost of analysis. In this review, we summarize the electrochemical detection of tetracycline antibiotics by bibliometrics. Unlike the previously published reviews, this article reviews and analyzes the development of this topic. The contributions of different countries and different institutions were analyzed. Keyword analysis was used to explain the development of different research directions. The results of the analysis revealed that developments and innovations in materials science can enhance the performance of electrochemical detection of tetracycline antibiotics. Among them, gold nanoparticles and carbon nanotubes are the most used nanomaterials. Aptamer sensing strategies are the most favored methodologies in electrochemical detection of tetracycline antibiotics.

Monitoring the respiratory behavior of multiple cows based on computer vision and deep learning.

Automatic respiration monitoring of dairy cows in modern farming not only helps to reduce manual labor but also increases the automation of health assessment. It is common for cows to congregate on farms, which poses a challenge for manual observation of cow status because they physically occlude each other. In this study, we propose a method that can monitor the respiratory behavior of multiple cows. Initially, 4,000 manually labeled images were used to fine-tune the YOLACT (You Only Look At CoefficienTs) model for recognition and segmentation of multiple cows. Respiratory behavior in the resting state could better reflect their health status. Then, the specific resting states (lying resting, standing resting) of different cows were identified by fusing the convolutional neural network and bidirectional long and short-term memory algorithms. Finally, the corresponding detection algorithms (lying and standing resting) were used for respiratory behavior monitoring. The test results of 60 videos containing different interference factors indicated that the accuracy of respiratory behavior monitoring of multiple cows in 54 videos was >90.00%, and that of 4 videos was 100.00%. The average accuracy of the proposed method was 93.56%, and the mean absolute error and root mean square error were 3.42 and 3.74, respectively. Furthermore, the effectiveness of the method was analyzed for simultaneous monitoring of respiratory behavior of multiple cows under movement, occlusion disturbance, and behavioral changes. It was feasible to monitor the respiratory behavior of multiple cows based on the proposed algorithm. This study could provide an a priori technical basis for respiratory behavior monitoring and automatic diagnosis of respiratory-related diseases of multiple dairy cows based on biomedical engineering technology. In addition, it may stimulate researchers to develop robots with health-sensing functions that are oriented toward precision livestock farming.

Electronic structure of strongly correlated systems: recent developments in multiconfiguration pair-density functional theory and multiconfiguration nonclassical-energy functional theory.

Strong electron correlation plays an important role in transition-metal and heavy-metal chemistry, magnetic molecules, bond breaking, biradicals, excited states, and many functional materials, but it provides a significant challenge for modern electronic structure theory. The treatment of strongly correlated systems usually requires a multireference method to adequately describe spin densities and near-degeneracy correlation. However, quantitative computation of dynamic correlation with multireference wave functions is often difficult or impractical. Multiconfiguration pair-density functional theory (MC-PDFT) provides a way to blend multiconfiguration wave function theory and density functional theory to quantitatively treat both near-degeneracy correlation and dynamic correlation in strongly correlated systems; it is more affordable than multireference perturbation theory, multireference configuration interaction, or multireference coupled cluster theory and more accurate for many properties than Kohn-Sham density functional theory. This perspective article provides a brief introduction to strongly correlated systems and previously reviewed progress on MC-PDFT followed by a discussion of several recent developments and applications of MC-PDFT and related methods, including localized-active-space MC-PDFT, generalized active-space MC-PDFT, density-matrix-renormalization-group MC-PDFT, hybrid MC-PDFT, multistate MC-PDFT, spin-orbit coupling, analytic gradients, and dipole moments. We also review the more recently introduced multiconfiguration nonclassical-energy functional theory (MC-NEFT), which is like MC-PDFT but allows for other ingredients in the nonclassical-energy functional. We discuss two new kinds of MC-NEFT methods, namely multiconfiguration density coherence functional theory and machine-learned functionals.

Zero-Field Splitting Calculations by Multiconfiguration Pair-Density Functional Theory.

Zero-field splitting (ZFS) is a fundamental molecular property that is especially relevant for single-molecule magnets (SMMs), electron paramagnetic resonance spectra, and quantum computing. Developing a method that can accurately predict ZFS parameters can be very powerful for designing new SMMs. One of the challenges is to include external correlation in an inherently multiconfigurational open-shell species for the accurate prediction of magnetic properties. Previously available methods depend on expensive multireference perturbation theory calculations to include external correlation. In this paper, we present spin-orbit-inclusive multiconfiguration and multistate pair-density functional theory (MC-PDFT) calculations of ZFSs; these calculations have a cost comparable to complete-active-space self-consistent field (CASSCF) theory, but they include correlation external to the active space. We found that combining a multistate formulation of MC-PDFT, namely, compressed-state multistate pair-density functional theory, with orbitals optimized by weighted-state-averaged CASSCF, yields reasonably accurate ZFS results.

Recent findings and advancements in the detection of designer benzodiazepines: a brief review.

This review article takes a closer look at a new class of psychoactive substances called designer benzodiazepines (DBZs) and the challenges of their detection. These are adinazolam, clonazolam, deschloroetizolam, diclazepam, etizolam, flualprazolam, flubromazepam, flubromazolam, phenazepam, and pyrazolam. They are central nervous system depressants and sedatives that can cause psychomotor impairment and increase the overdose risk when combined with other sedatives. DBZs undergo phase I and II metabolism similar to traditional benzodiazepines, but their specific metabolic pathways and the influence of genetic polymorphisms are yet to be clarified. Advances in liquid chromatography-tandem mass spectrometry (LC-MS/MS) have enhanced the method's sensitivity for DBZs and their metabolites in biological samples and coupled with improved blood sampling methods require less blood for drug monitoring. Further research should focus on elucidating their pharmacokinetic properties and metabolism in humans, especially in view of genetic polymorphisms and drug interactions that could inform clinical treatment choices. Even though we have witnessed important advances in DBZ detection and measurement, further refinements are needed to expand the scope of detectable DBZs and their metabolites. All this should help toxicological research to better identify and characterise the risks of chronic and polydrug abuse and facilitate clinical, forensic, and regulatory responses to this growing issue.

Calculation of the Zeeman Effect for Transition-Metal Complexes by Multiconfiguration Pair-Density Functional Theory.

Spin-orbit coupling is especially critical for the description of magnetic anisotropy, electron paramagnetic resonance spectroscopy of inorganic radicals and transition-metal complexes, and intersystem crossing. Here, we show how spin-orbit coupling may be included in multiconfiguration pair-density functional theory (MC-PDFT), and we apply the resulting formulation to the calculation of magnetic g tensors (which govern the Zeeman effect) of molecules containing transition metals. MC-PDFT is an efficient method for including static and dynamic electronic correlation in the quantum mechanical treatment of molecules; here, we apply it with spin-orbit coupling by using complete active space self-consistent field (CASSCF) and complete active space configuration interaction (CASCI) wave functions and on-top density functionals. We propose a systematic CASCI scheme for the g tensor calculation of the ground state of the systems under consideration, and we show its superiority over the conventional CASSCF scheme. State interaction, which is important for degenerate and nearly degenerate states, is included by extended multi-state PDFT (XMS-PDFT). Applications are reported for the ground doublet states of 25 transition-metal complexes with d1, d5, d7, and d9 configurations. The MC-PDFT methods are shown to be both efficient and accurate as compared with complete active space second-order perturbation theory.

How Accurate Are Approximate Density Functionals for Noncovalent Interaction of Very Large Molecular Systems?

Noncovalent intermolecular interactions are very important in many research areas. Therefore, it is vital to understand the extent to which approximate density functionals give a proper description of noncovalent interactions. Previous research has demonstrated that some approximate density functionals can predict usefully accurate interaction energies for many noncovalent systems; however, most of that work is limited to small and moderate-sized molecules. Very recently though, accurate benchmarks have become available for some very large molecules. The present work applies 21 approximate density functionals to compute the binding energies of seven large molecular systems that have a number of atoms ranging from 200 to 910. The results are judged by comparison to the recently published CIM-DLPNO-CCSD(T) results, which are assumed to provide a reliable benchmark. The five most accurate methods among those tested are found to be PW6B95-D4, PW6B95-D3(BJ), revM11, M06-L, and MN15.

S-Doped N-Rich Carbon Nanosheets with Expanded Interlayer Distance as Anode Materials for Sodium-Ion Batteries.

2D composites with S doping into N-rich carbon nanosheets are fabricated, whose interlayer distance becomes large enough for Na+ insertion and diffusion. The large surface area and stable structure also provide more sites for Na+ adsorption, leading to high Na-storage capacity and excellent rate performance. Moreover, Faradaic reactions between Na+ and tightly bound S is beneficial for further improvement of Na-storage capacity.

MnPSe3 Monolayer: A Promising 2D Visible-Light Photohydrolytic Catalyst with High Carrier Mobility.

The 2D material single-layer MnPSe3 would be a promising photocatalyst for water splitting, as indicated by the proper positions of band edges, strong absorption in visible-light spectrum, broad applicability (pH = 0 - 7), and high carrier mobility.

Computational prediction of the electronic structure and optical properties of graphene-like ß-CuN3.

Recently, a new polymorph of the highly energetic phase ß-CuN3 has been synthesized. By hybrid density functional computations, we investigated the structural, electronic and optical properties of ß-CuN3 bulk and layers. Due to the quantum confinement effect, the band gap of the monolayer (2.39 eV) is larger than that of the bulk (2.23 eV). The layer number affects the configuration and the band gap. ß-CuN3 shows both ionic and covalent characters, and could be stable in the infrared and visible spectrum and would decompose under ultraviolet light. The results imply that bulk ß-CuN3 could be used as an energetic material.

High Carrier Mobility and Pronounced Light Absorption in Methyl-Terminated Germanene: Insights from First-Principles Computations.

On the basis of Herd-Scuseria-Emzerhof hybrid functional (HSE06) within the framework of density functional theory (DFT), we have computationally explored the intrinsic electronic and optical properties of 2D methyl-terminated germanene (GeCH3). GeCH3 monolayer possesses an opportune direct band gap of 1.76 eV, which can be effectively tuned by applying elastic strain and decreases with increasing the tensile strain, while it increases with small compressive strain. Also, anisotropic carrier mobility was disclosed in the armchair (x) and zigzag (y) directions of GeCH3 monolayer. Moreover, GeCH3 monolayer shows significant light absorption in the visible and ultraviolet range of solar spectrum and is attractive for light harvesting. The results can help us better understand the intrinsic properties of GeCH3 and provide reliable guidance for its experimental applications to electronics and optoelectronics.

High and anisotropic carrier mobility in experimentally possible Ti2CO2 (MXene) monolayers and nanoribbons.

MXene, a new kind of two-dimensional (2D) material, has a unique combination of excellent physical and chemical properties. Via computations on density functional theory and deformation potential theory, we investigated the electronic structure and predicted the carrier mobility of Ti2CO2 (a typical MXene) monolayers and nanoribbons. The Ti2CO2 monolayer is a semiconductor with a band gap of 0.91 eV, and the hole mobility in the monolayer reaches 10(4) orders of magnitude along both x and y directions, which is much higher than that of MoS2, while the electron mobility is about two orders of magnitude lower. The dramatic difference between the hole and electron mobilities also exists in nanoribbons. Moreover, our results suggest that width controlling and edge engineering would be effective in adjusting the carrier mobility of Ti2CO2 nanoribbons, and endow experimentally available Ti2CO2 with wide applications to field-effect transistors and photocatalysts.

First-principles investigations on delithiation of Li4NiTeO6.

Through first-principles computations, we investigated Li4NiTeO6, which is a new layered Ni-based cathode material for Li ion batteries, by focusing on the sequence of Li removal when it is charged. According to our computations, Li4NiTeO6 exhibits satisfactory structural stability with a volume change of 7.2% and electrical conductivity similar to Li2MnO3. We also examined the electronic configuration of this cathode material during its electrochemical progress and found a weak hybridization of Ni3d and O2p. Moreover, by analyzing the Bader charges of different elements, we confirmed that O and Ni are exclusively responsible for electron loss and gain. In addition, O evolution reactions occur when half of Li(+) ions are extracted. Finally, we investigated Li(+) migration paths and concluded that migration barriers depend on the charge distribution around migration paths.

Enhanced Li Adsorption and Diffusion on MoS2 Zigzag Nanoribbons by Edge Effects: A Computational Study.

By means of density functional theory computations, we systematically investigated the adsorption and diffusion of Li on the 2-D MoS2 nanosheets and 1-D zigzag MoS2 nanoribbons (ZMoS2NRs), in comparison with MoS2 bulk. Although the Li mobility can be significantly facilitated in MoS2 nanosheets, their decreased Li binding energies make them less attractive for cathode applications. Because of the presence of unique edge states, ZMoS2NRs have a remarkably enhanced binding interaction with Li without sacrificing the Li mobility, and thus are promising as cathode materials of Li-ion batteries with a high power density and fast charge/discharge rates.