Measurement of population agglomeration, dynamic change characteristics, and motivations in metropolitan agglomerations-A case study of the Xi'an metropolitan area.

This article compares the population agglomeration characteristics of the Xi'an metropolitan area in western China with those of metropolitan areas in other regions officially approved by the Chinese government. The kernel density estimation method and Markov chain model were used to conduct the study. The results revealed that from 2010 to 2020, the population agglomeration level of the Xi'an metropolitan area showed a trend of first increasing and then decreasing.

Competitive Effect of Surface Hydrophobicity-Hydrophilicity and the Number of Accessible Protons on Water-Assisted Proton Conductivity in Metal-Organic Frameworks: Dielectric σ-Relaxation Triggered by Disordered Guest Ionic Migration and Its Mechanism.

The rapid upsurge of metal-organic frameworks (MOFs) has sparked profound interest in their potential as proton conductors for proton exchange membrane fuel cells. However, proton-conducting behaviors of hydrophobic MOFs remain poorly understood compared with their hydrophilic counterparts, largely due to the absence of a microscopic phase separation structure akin to that found in Nafion membranes. Herein, we demonstrate a strategy for regulating the structures and proton conductivities of MOFs by separately incorporating hydrophobic -C(CF)- group alongside hydrophilic -O- and -SO- groups into organic ligands as linkers.

Metasurface-Coated Liquid Microlens for Super Resolution Imaging.

Inspired by metasurfaces' control over light fields, this study created a liquid microlens coated with a layer of Au@TiO, Core-Shell nanospheres. Utilizing the surface plasmon resonance (SPR) effect of Au@TiO, Core-Shell nanospheres, and the formation of photonic nanojets (PNJs), this study aimed to extend the imaging system's cutoff frequency, improve microlens focusing, enhance the capture capability of evanescent waves, and utilize nanospheres to improve the conversion of evanescent waves into propagating waves, thus boosting the liquid microlens's super-resolution capabilities. The finite difference time domain (FDTD) method analyzed the impact of parameters including nanosphere size, microlens sample contact width, and droplet's initial contact angle on super-resolution imaging.

Sustainable application of waste gangue mortar in coal mine tunnel support.

With the increase in coal mining depths, soft and fractured roadway surrounding rocks require grouting and a sprayed protective layer for maintenance. Simultaneously, extensive accumulation of coal gangue causes diverse environmental issues. To enhance on-site coal gangue utilization, this study replaced river sand and cement with coal gangue to develop a novel cement-based mortar for supporting coal mine roadways.

Temperature dynamics and mechanical properties analysis of carbon fiber epoxy composites radiated by nuclear explosion simulated light source.

The impact of light radiation, a predominant energy release mechanism in nuclear explosions, on material properties is of critical importance. This investigation employed an artificial light source to replicate the effects of nuclear explosion radiation and utilized a physical information neural network (PINN) to examine the temperature evolution and corresponding changes in the mechanical properties of carbon fiber/epoxy composites (CFEC). A light source simulating nuclear explosion's light radiation was built to irradiate the CFEC, then measure the reflection spectrum and temperature of samples.

Study on the modulation mechanism of the optoelectronic properties based on common electrode metal atom adsorption on graphene/MoTe.

Context: The two-dimensional graphene/MoTe heterostructure holds extensive potential applications in optoelectronic devices, sensors, and catalysts. To expand its optical applications, this study systematically investigates the adsorption stability of metal atoms (Au, Pt, Pd, and Fe) on the graphene/MoTe and their influence on its optoelectronic properties employing first-principles methods. The findings indicate that after the adsorption of Au and Pd, the structure retains its direct bandgap properties, while the adsorption of Pt and Fe exhibits indirect bandgap characteristics.

HandFI: Multilevel Interacting Hand Reconstruction Based on Multilevel Feature Fusion in RGB Images.

Interacting hand reconstruction presents significant opportunities in various applications. However, it currently faces challenges such as the difficulty in distinguishing the features of both hands, misalignment of hand meshes with input images, and modeling the complex spatial relationships between interacting hands. In this paper, we propose a multilevel feature fusion interactive network for hand reconstruction (HandFI).

Enterprise chart question and answer method based on multi modal cross fusion.

To enhance enterprises' interactive exploration capabilities for unstructured chart data, this paper proposes a multimodal chart question-answering method. Facing the challenge of recognizing curved and irregular text in charts, we introduce Gaussian heatmap encoding technology to achieve character-level precise text annotation. Additionally, we combine a key point detection algorithm to extract numerical information from the charts and convert it into structured table data.

Study on regional differences and causes of emergency logistics responsiveness under the impact of public emergencies-findings from Chinese samples.

Introduction: In recent years, the frequency and intensity of natural disasters and public emergencies around the world have been steadily increasing. Emergency logistics plays an irreplaceable role in providing rapid material and service support in the aftermath of disasters. Therefore, systematically analyzing the differences in emergency logistics responsiveness across various regions of China and understanding their underlying causes are of great significance for optimizing emergency logistics systems and improving disaster responsiveness.

Immobilization of snailase and β-glucosidase on L-aspartic acid-modified magnetic amorphous ZIF for efficiently and sustainably producing ginsenoside compound K.

Improving the catalytic efficiency and recyclability of immobilized enzyme remained a serious challenge in industrial applications. Enzyme immobilization in the amorphous zeolite imidazolate framework (aZIF) preserved high enzyme activity, but still faced separation difficulties and a low catalytic efficiency in practice. In this study, a one-pot co-precipitation method was used to form the enzyme-aZIF/magnetic nanoparticle (MNP) biocomposite by rapidly precipitating snailase (Sna) and β-glucosidase (β-G) with metal/ligand on MNP and modifying with L-aspartic acid (Asp).

Buried interface management toward high-performance perovskite solar cells.

The interface between the perovskite layer and the electron transport layer is an extremely important factor that cannot be ignored in achieving high-performance perovskite photovoltaic technology. However, the void defects of the interface pose a serious challenge for high performance perovskite solar cells (PSCs). To address this, we report a polydentate ligand reinforced chelating strategy to strengthen the stability of the buried interface by managing interfacial defects and stress.

The Lattice Mismatch-Driven Photochemical Self-Assembly of Supported Heterostructures for Stable and Enhanced Electrocatalytic Carbon Dioxide Reduction Reaction.

Metallic heterostructural nanocrystals (HNCs) hold immense potential in electrocatalytic carbon dioxide reduction reaction (CORR) owing to their abundant active sites and high intrinsic activity. However, a significant challenge still remains in achieving controlled nucleation and growth sites for HNCs on supports and comprehending the influence of the structure-activity relationship on electrocatalytic CORR performance. This work presents a photochemical self-assembly technique without the necessity for reducing agents or facet-specific capping agents.

Enhanced irradiation-resistance in NbMoTaW refractory high-entropy alloy via rhenium addition.

The He irradiation-induced mechanical and microstructural evolutions were studied in NbMoTaW (at.%) and NbMoTaWRe (at.%) refractory high-entropy alloys (RHEAs) films, respectively.

Cascade Reaction Enables Heterointerfaces-Enriched Nanoarrays for Ampere-Level Hydrogen Production.

Designing high-performance electrocatalysts with superior catalytic activity and stability is essential for large-scale hydrogen production via water electrolysis. Heterostructure nanoarrays are promising candidates, though achieving both high activity and stability simultaneously, especially under high current densities, remains challenging. To this end, we have developed a cascade reaction process that constructs a series of heterostructure nanoarrays with rich heterointerfaces.

A butterfly metasurface with efficient multi-functional polarization conversion operating in the Ku-Ka band.

A highly efficient and multi-functional butterfly polarization conversion metasurface is proposed for the Ku-Ka frequency range, designed to reduce the radar cross-section. The suggested converter enables dual frequency bands linear-to-cross (LX) and linear-to-circular (LC) polarization transformations. The efficiency of cross-polarization conversion exceeds 90% over the frequency ranges of 14.

Biochar-based Bacillus subtilis inoculants promote plant growth: Regulating microbial community to improve soil properties.

Numerous studies support the synergistic use of biochar (BC) and plant growth-promoting rhizobacteria to enhance plant growth. Despite this, the complex and dynamic nature of soil environments necessitates further exploration of the interactions between soil microorganisms and soil properties under BC-based inoculants. This study investigated their combined effects using a BC-based inoculant, Bacillus subtilis SL-44 (BC@SL), to explore the relationship between microorganisms and soil properties.

Immobilization of snailase on glutamate modified MIL-88B(Fe) to efficiently convert the rare ginsenoside CK with high enzyme recyclability and stability.

The carboxyl groups on MIL-88B(Fe) are crucial for the covalent immobilization of snailase, and the enzyme can convert common ginsenoside Rb1 into the rare ginsenoside compound K (CK) with higher bioavailability. The present study proposed glutamate-modified MIL-88B(Fe) for the immobilization of snailase to improve enzymatic activity and loading capacity. The surface topography characterized by SEM and CLSM indicated snailase was successfully encapsulated and uniformly distributed in the Sna@MIL-88B(Fe).

Hydrated Magnesium Ion-Uracil and Magnesium Chloride-Uracil Clusters Revealed by Ab Initio Study.

The study focuses on the interaction between canonical uracil and its rare tautomers with Mg and MgCl in the microcosmic water environment and aims to elucidate how ions interact with nucleobase and the cation-anion correlation effect involved using density functional theory calculations. The structures of the Ura-Mg(HO) and Ura-MgCl(HO) clusters are characterized and show that the water molecules preferentially interact with Mg/MgCl, and Mg adopts a hexacoordination pattern in both Ura-Mg(HO) and Ura-MgCl(HO) clusters. When uracil interacts with Mg in (HO) environments, it tends to favor the formation of keto-enol structures.

Wet-spun Ag/PEDOT: PSS composite fibers for high-sensitive SERS sensing and high electrical conducting.

Nanometal-based composite fibers have been widely explored in flexible sensors due to their outstanding optical and electrical properties. However, the weak binding force between metallic nanomaterial and fiber greatly limits the real application. In this work, nano silver (Ag) are strongly bonded with poly(3,4-ethylenedioxythiophene)-poly (styrene sulfonate) (PEDOT: PSS) fiber by the wet-spun process.

Research on transformer fault diagnosis models with feature extraction.

To address the challenge of low accuracy in traditional transformer fault diagnosis algorithms, this paper introduces a novel approach that utilizes the Artificial Hummingbird Algorithm (AHA) to optimize both Kernel Principal Component Analysis (KPCA) and Extreme Learning Machine (ELM). We propose the use of various gas concentration ratio features and apply the AHA algorithm to fine-tune the kernel function parameters of KPCA, thus establishing an AHA-KPCA feature extraction model. This model takes the expanded gas concentration ratio features as input and selects the top N principal components with a cumulative contribution rate above 95% to form the feature vectors for fault classification.