Highly effective and selective FeBr-promoted deuterium bromination/cyclization of 1,-enynes.

A highly effective and selective FeBr-promoted deuterium bromination/cyclization of 1,-enynes is reported. On the one hand, the Lewis acid FeBr as a catalyst promotes cyclization of 1,-enynes to afford deuterium heterocyclic frameworks with high efficiency. On the other hand, FeBr serves as the bromine source (with DO as the deuterium source) to promote the formation of the desired deuterated pyrrole derivatives containing alkenyl bromide groups.

Effects of isotropic strain on the structure and transport properties of half-Heusler alloy BiBaK: a first-principles investigation.

In this study, using density functional and Boltzmann transport theories, we systematically investigated the effects of tensile and compressive strains on the elastic properties, phonon dispersion relation, electronic structure, and transport properties of the half-Heusler compound BiBaK. We calculated the elastic constants and phonon dispersion curves for BiBaK, which demonstrated its mechanical and thermodynamic stability, respectively, under different isotropic strains. Further, calculations showed that the electronic structure and energy bandgap of BiBaK changed with the application of isotropic strain.

Analysis and pollution evaluation of heavy metal content in soil of the Yellow River Wetland Reserve in Henan.

Objective: This study aims to assess the contamination levels of six heavy metals, namely arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), and lead (Pb), in the soil of the Henan Yellow River Wetland Reserve. It seeks to reveal the spatial distribution and trends of heavy metal pollution, providing a scientific basis for the rational utilization and effective protection of soil. Additionally, it aims to propose targeted management and remediation recommendations to mitigate or prevent soil pollution.

A DFT Investigation of B-Doped C N as Single Atom Electrocatalysts for N -to-NH Conversion.

The NH synthesis from N plays an important role in the ecological cycle and industrial production. Different from industrial NH synthesis with high pollution and energy consumption, electrocatalytic NH synthesis is favored because of its environmental protection, energy saving, ambient reaction conditions and other characteristics. However, due to the low efficiency and poor reaction selectivity of the existing electrocatalysts, which can not be used actually, the development of new electrocatalysts for nitrogen reduction reaction (NRR) is particularly urgent.

Effect of A- or B-Site Sc Doping on Sintering Temperature, Crystal Structure, Microstructure, and Properties of BaZrTiO Ceramics.

BaZrTiO (BZT) ceramics with different concentrations of Sc ions were prepared, and the effect of doping concentration on the crystal substitution type of BZT was studied. The substitution position of the Sc ion in BZT was related to its concentration. When the concentration of Sc ions was low (<1.

Phytoremediation for antibiotics removal from aqueous solutions: A meta-analysis.

Antibiotics are widely used as drugs and enter water bodies through various routes, leading to environmental pollution. As a green in-situ remediation technology, phytoremediation has been proven to be highly effective in removing antibiotics present in the aqueous phase. However, these data are distributed in various studies and lack systematic analysis, which could provide a more comprehensive understanding of the current status and trends in the research field.

Molecular nitrogen induced structural evolution of single transition metal atoms supported by B/N co-doped graphene for enhanced nitrogen electroreduction performance.

The structural evolution of local coordination environments of single-atom catalysts (SACs) under reaction conditions plays an important role in the catalytic performance of SACs. Using density functional theory calculations, the possible structural evolution of transition metal single atoms supported by B/N codoped-graphene (TM-BN/G) under nitrogen reduction reaction (NRR) conditions is explored and the catalytic performance based on reconstructed SACs is theoretically evaluated. A novel nitrogen adsorption mode on TM-BN/G is discovered and the protonation of one of the N atoms results in the TM atoms binding with three N atoms, among which one associates with two B atoms (TM-NB/G).

An investigation into the response of the soil ecological environment to tourist disturbance in Baligou.

The purpose of this study is to understand the response patterns of the soil ecological environment of the Macau Wetland Park to different levels of tourist interference and to provide a scientific basis for the rational development of the Bali Gou ecological tourism plan and the protection and management of the scenic area's ecological environment. Combine the methods of field collection and laboratory physical and chemical data analysis to analyze the impact of the strength of tourism disturbance on the soil ecological environment of Baligou. During the tourist activities in Baligou, the human factors in the process have an impact on the physical aspects of the scenic area's soil, such as soil bulk density, color tone, porosity, compactness, capacity, and leaf litter.

Tunable electronic and optical properties of ferroelectric WS/GaOheterostructures.

To integrate two-dimensional (2D) materials into van der Waals heterostructures (vdWHs) is regarded as an effective strategy to achieve multifunctional devices. The vdWHs with strong intrinsic ferroelectricity is promising for applications in the design of new electronic devices. The polarization reversal transitions of 2D ferroelectric GaOlayers provide a new approach to explore the electronic structure and optical properties of modulated WS/GaOvdWHs.

transcription factor family identification, phylogeny, and its response to abiotic stress in .

The second-largest transcription factor superfamily in plants is that of the basic helix-loop-helix (bHLH) family, which plays an important complex physiological role in plant growth, tissue development, and environmental adaptation. Systematic research on the bHLH family will enable a better understanding of this species. Herein, authors used a variety of bioinformatics methods and quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) to explore the evolution and function of the 218 genes identified.

A series of two-dimensional carbon allotropes with Dirac cone structure.

By combining a hexagon and square carbon ring, a series of two-dimensional (2D) carbon allotropes, named (HS)-graphene, can be obtained. Based on the first-principles calculations, the energetic, dynamical and mechanical stability were evaluated. Importantly, we predicted that some carbon allotropes possess the Dirac cone structure.

Micro-Shaping of Pure Aluminum in Long-Duration Wire Electrochemical Micromachining Using Bipolar Nanosecond Pulses.

With the increasing application of three-dimensional pure aluminum microstructures in micro-electromechanical systems (MEMS) and for fabricating terahertz components, high-quality micro-shaping of pure aluminum has gradually attracted attention. Recently, high-quality three-dimensional microstructures of pure aluminum with a short machining path have been obtained through wire electrochemical micromachining (WECMM), owing to its sub-micrometer-scale machining precision. However, machining accuracy and stability decrease owing to the adhesion of insoluble products on the surface of the wire electrode in long-duration WECMM, which limits the application of pure aluminum microstructures with a long machining path.

COVID-19 disease identification network based on weakly supervised feature selection.

The coronavirus disease 2019 (COVID-19) outbreak has resulted in countless infections and deaths worldwide, posing increasing challenges for the health care system. The use of artificial intelligence to assist in diagnosis not only had a high accuracy rate but also saved time and effort in the sudden outbreak phase with the lack of doctors and medical equipment. This study aimed to propose a weakly supervised COVID-19 classification network (W-COVNet).

An intelligent scheduling control method for smart grid based on deep learning.

Nowadays, data analysis is been the most important means to realize power scheduling in smart grids. However, the sharp increase in business data of grids has posed great challenges for this purpose. To deal with such issue, this paper utilizes deep learning to discover hidden rules from massive large-scale big data and particle swarm optimization (PSO) algorithm for generation of control decision.

Assessing financial performance through green bond markets and energy reliance in Asian economies.

This article's overarching goal is to learn more about the effects of financial performance on the reliance upon or migration to energy efficiency sources in Asian countries using data envelopment analysis (DEA) and system GMM from 2017 to 2022. The results demonstrated the importance of relying on renewable energy sources when expanding the electricity sector effectively in an Asian environment. This same influence of green bond financing on energy investment during an eco-friendly improving economy is in addition to the proportion of renewable energy demands, power usage to gross domestic product, power manufacturing stretchability, electricity usage stretchability, or the overall impact of renewable energy transformation.

Single-Atom Anchored g-CN Monolayer as Efficient Catalysts for Nitrogen Reduction Reaction.

Electrochemical N reduction reaction (NRR) is a promising approach for NH production under mild conditions. Herein, the catalytic performance of 3d transition metal (TM) atoms anchored on s-triazine-based g-CN (TM@g-CN) in NRR is systematically investigated by density functional theory (DFT) calculations. Among these TM@g-CN systems, the V@g-CN, Cr@g-CN, Mn@g-CN, Fe@g-CN, and Co@g-CN monolayers have lower ΔG(*NNH) values, especially the V@g-CN monolayer has the lowest limiting potential of -0.

Effect of Final Thermomechanical Treatment on the Mechanical Properties and Microstructure of T Phase Hardened Al-5.8Mg-4.5Zn-0.5Cu Alloy.

The effect of final thermomechanical treatment (FTMT) on the mechanical properties and microstructure of a T-Mg(Al Zn) phase precipitation hardened Al-5.8Mg-4.5Zn-0.

Exploring structural, mechanical, and thermoelectric properties of half-Heusler compounds RhBiX (X = Ti, Zr, Hf): A first-principles investigation.

In this study, the full potential linearization enhanced plane wave method in density functional theory is used. Additionally, the structure, mechanical, and thermoelectric properties of half-Heusler compounds RhBiX (X = Ti, Zr, Hf) are investigated for the first time. The indirect semiconductors RhBiTi and RhBiZr have 0.

Improving the Reaction Kinetics by Annealing MoS/PVP Nanoflowers for Sodium-Ion Storage.

Under the ever-growing demand for electrochemical energy storage devices, developing anode materials with low cost and high performance is crucial. This study established a multiscale design of MoS/carbon composites with a hollow nanoflower structure (MoS/C NFs) for use in sodium-ion batteries as anode materials. The NF structure consists of several MoS nanosheets embedded with carbon layers, considerably increasing the interlayer distance.

Hydrogel of HEMA, NVP, and Morpholine-Derivative Copolymer for Sulfate Ion Adsorption: Behaviors and Mechanisms.

SO-containing compounds are widely present in wastewater generated from various industries and mining industries, such as slag leachate, pulp and paper wastewater, modified starch wastewater, etc. When the concentration of SO is too high, it will not only be corrosive to metal equipment but also accumulate in the environmental media. Based on this, a novel cationic hydrogel HNM was synthesized in this study by introducing morpholine groups into the conventional hydrogel HEMA-NVP system for the adsorption of SO in aqueous solutions.

Automatic polyp image segmentation and cancer prediction based on deep learning.

The similar shape and texture of colonic polyps and normal mucosal tissues lead to low accuracy of medical image segmentation algorithms. To solve these problems, we proposed a polyp image segmentation algorithm based on deep learning technology, which combines a HarDNet module, attention module, and multi-scale coding module with the U-Net network as the basic framework, including two stages of coding and decoding. In the encoder stage, HarDNet68 is used as the main backbone network to extract features using four null space convolutional pooling pyramids while improving the inference speed and computational efficiency; the attention mechanism module is added to the encoding and decoding network; then the model can learn the global and local feature information of the polyp image, thus having the ability to process information in both spatial and channel dimensions, to solve the problem of information loss in the encoding stage of the network and improving the performance of the segmentation network.

Intelligent Sensors for POI Recommendation Model Using Deep Learning in Location-Based Social Network Big Data.

Aiming at the problem that the existing Point of Interest (POI) recommendation model in social network big data is difficult to extract deep feature information, a POI recommendation model based on deep learning in social networks and big data is proposed in this article. The input data are all gathered through intelligent sensors to apply some raw data pre-processing tasks and thus reduce the computational burden on the model. First, a POI static feature extraction method based on symmetric matrix decomposition is designed to capture the geographical location and POI category features in Location-Based Social Networking (LBSN).

Levy Equilibrium Optimizer algorithm for the DNA storage code set.

The generation of massive data puts forward higher requirements for storage technology. DNA storage is a new storage technology which uses biological macromolecule DNA as information carrier. Compared with traditional silicon-based storage, DNA storage has the advantages of large capacity, high density, low energy consumption and high durability.

A novel and ultrasensitive fluorescent probe derived from labeled carbon dots for recognitions of copper ions and glyphosate.

Labeling materials with special functional groups are very valuable for the creation of novel probes. Hence, a novel fluorescent probe was constructed by conjugating 4-butyl-3-thiosemicarbazide (BTSC) with carbon dots (CDs). The CDs labeled by BTSC (BTSC-CDs) displayed a strong capability for recognition of Cu and Cu could quench the emission of BTSC-CDs significantly.

Predicting DNA-binding protein and coronavirus protein flexibility using protein dihedral angle and sequence feature.

The flexibility of protein structure is related to various biological processes, such as molecular recognition, allosteric regulation, catalytic activity, and protein stability. At the molecular level, protein dynamics and flexibility are important factors to understand protein function. DNA-binding proteins and Coronavirus proteins are of great concern and relatively unique proteins.