Efficient photocatalytic degradation of Malachite Green in seawater by the hybrid of Zinc-Oxide Nanorods Grown on Three-Dimensional (3D) reduced graphene oxide(RGO)/Ni foam

A hybrid of ZnO nanorods grown onto three-dimensional (3D) reduced graphene oxide (RGO)@Ni foam (ZnO/RGO@NF) is synthesized by a facile hydrothermal method. The as-prepared hybrid material is physically characterized by SEM, XRD, Raman, and X-ray photoelectron spectroscopy (XPS).When the as-prepared 3D hybrid is investigated as a photocatalyst, it demonstrates significant high photocatalytic activity for the degradation of methylene blue (MB), rhodamine (RhB), and mixed MB/RhB as organic dye pollutants. In addition, the practical application and the durability of the as-prepared catalyst to degradation of malachite green (MG) in seawater are firstly assessed in a continuous flow system. The catalyst shows a high degradation efficiency and stable photocatalytic activity for 5 h continuous operation, which should be a promising catalyst for the degradation of organic dyes in seawater

Gut microbiome-based noninvasive diagnostic model to predict acute coronary syndromes

BackgroundPrevious studies have shown that alterations in the gut microbiota are closely associated with Acute Coronary Syndrome (ACS) development. However, the value of gut microbiota for early diagnosis of ACS remains understudied.MethodsWe recruited 66 volunteers, including 29 patients with a first diagnosis of ACS and 37 healthy volunteers during the same period, collected their fecal samples, and sequenced the V4 region of the 16S rRNA gene. Functional prediction of the microbiota was performed using PICRUSt2. Subsequently, we constructed a nomogram and corresponding webpage based on microbial markers to assist in the diagnosis of ACS. The diagnostic performance and usefulness of the model were analyzed using boostrap internal validation, calibration curves, and decision curve analysis (DCA).ResultsCompared to that of healthy controls, the diversity and composition of microbial community of patients with ACS was markedly abnormal. Potentially pathogenic genera such as Streptococcus and Acinetobacter were significantly increased in the ACS group, whereas certain SCFA-producing genera such as Blautia and Agathobacter were depleted. In addition, in the correlation analysis with clinical indicators, the microbiota was observed to be associated with the level of inflammation and severity of coronary atherosclerosis. Finally, a diagnostic model for ACS based on gut microbiota and clinical variables was developed with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.963 (95% CI: 0.925–1) and an AUC value of 0.948 (95% CI: 0.549–0.641) for bootstrap internal validation. The calibration curves of the model show good consistency between the actual and predicted probabilities. The DCA showed that the model had a high net clinical benefit for clinical applications.ConclusionOur study is the first to characterize the composition and function of the gut microbiota in patients with ACS and healthy populations in Southwest China and demonstrates the potential effect of the microbiota as a non-invasive marker for the early diagnosis of ACS

OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System

Automated machine learning (AutoML) seeks to build ML models with minimal human effort. While considerable research has been conducted in the area of AutoML in general, aiming to take humans out of the loop when building artificial intelligence (AI) applications, scant literature has focused on how AutoML works well in open-environment scenarios such as the process of training and updating large models, industrial supply chains or the industrial metaverse, where people often face open-loop problems during the search process: they must continuously collect data, update data and models, satisfy the requirements of the development and deployment environment, support massive devices, modify evaluation metrics, etc. Addressing the open-environment issue with pure data-driven approaches requires considerable data, computing resources, and effort from dedicated data engineers, making current AutoML systems and platforms inefficient and computationally intractable. Human-computer interaction is a practical and feasible way to tackle the problem of open-environment AI. In this paper, we introduce OmniForce, a human-centered AutoML (HAML) system that yields both human-assisted ML and ML-assisted human techniques, to put an AutoML system into practice and build adaptive AI in open-environment scenarios. Specifically, we present OmniForce in terms of ML version management; pipeline-driven development and deployment collaborations; a flexible search strategy framework; and widely provisioned and crowdsourced application algorithms, including large models. Furthermore, the (large) models constructed by OmniForce can be automatically turned into remote services in a few minutes; this process is dubbed model as a service (MaaS). Experimental results obtained in multiple search spaces and real-world use cases demonstrate the efficacy and efficiency of OmniForce

Spatial Effects of Digital Economy on Tourism Development: Empirical Research Based on 284 Cities at the Prefecture and Higher Levels in China

The digital economy, an essential engine for the high-quality development of China's economy, has the potential to become a breakthrough in promoting the rapid recovery of tourism. From a spatial perspective, this study used panel data from 284 prefecture-level and higher cities in China from 2011 to 2019 and constructed a spatial Durbin model (SDM) to empirically test the spatial effect and mechanism of the digital economy on tourism development. (1) Digital economy and tourism development showed significant positive global spatial autocorrelation during the study period. Hotspots of the digital economy have long been located in southeastern coastal areas, and cold spots in central and western China have shrunk significantly. Tourism development hotspots are mainly distributed in the Yangtze River Delta urban agglomerations and in Yunnan, Guangxi, Guizhou, and Chongqing. Cold spots were distributed in the central and western cities of the Shandong Peninsula and gradually expanded southward. (2) In China, the digital economy has a significant direct effect and positive spatial spillover effect, which was confirmed by a series of robustness tests were conducted. From the perspective of different regions, although the direct effect was significantly positive in all regions, the influence coefficient in the eastern region was significantly larger than that in the central, western, and northeastern regions. The spatial spillover effect is entirely significant in the eastern region, partly significant in the central and northeastern regions, and not significant in the western region, indicating that "digital segregation" exists in the western region. (3) The positive spatial spillover effect of the digital economy on tourism development is optimal at 300 km. Subsequently, the spatial spillover effect followed the law of geographical distance attenuation. The spatial spillover effect reaches the critical point of the practical effect at 800 km and almost disappears at 1500 km. (4) Among the digital economy components, digital infrastructure, digital industry development, and digital inclusive finance can significantly promote local tourism development. However, only digitally inclusive finance has a significant positive spatial spillover effect, and the effects of the remaining components are insignificant. This study constructs an analytical framework for the spatial effects of the digital economy on tourism development and conducts rigorous empirical research to compensate for the limitations of current research from a local perspective. This study also examined the spatial effects of various components of the digital economy, which helped identify the source of the impact of the digital economy on tourism development more accurately. In addition, the regional heterogeneity and distance attenuation law of the spatial effect of the digital economy on tourism development were analyzed, and customized policy implications were proposed based on the research conclusions. Overall, this study has essential reference value for achieving high-quality tourism development and expanding the scope of digital economy application

Does the Digital Economy Improve Urban Tourism Development? An Examination of the Chinese Case

The digital economy, a new economic form based on Information and Communications Technology (ICT), has profoundly changed the tourism industry. Based on a theoretical analysis framework, this paper measured the digital economy index and urban tourism development index. It empirically tested the impact of the digital economy on urban tourism development through the benchmark regression model, panel threshold model (PTM), and spatial Durbin model (SDM) according to panel data of 284 prefecture-level and above cities in China from 2011 to 2019. The results show that the digital economy can directly drive urban tourism development. The positive impact in mid-western, non-tourist, key urban agglomerations, and low-level cities is more fully realised. Moreover, the digital economy has positive, nonlinear effects on urban tourism development, and the marginal effects are increasing. Additionally, the impact of the digital economy on the tourism development of neighbouring cities can be realised through spatial spillover effects, which are more dependent on inclusive digital finance; this impact has a boundary effect, reaching a maximum at 300 km. Furthermore, the conclusions are still valid after a robustness test and quasi-natural implementation based on smart cities. Finally, specific recommendations are proposed for the digital economy to improve urban tourism development according to the above findings

Can Tourism Development Help Improve Urban Liveability? An Examination of the Chinese Case

The emergence of “urban diseases” has aroused people’s widespread concern about urban liveability. Therefore, it is worth studying whether tourism, as a “smokeless industry” can improve it. In this article, the benchmark model, the spatial Durbin model (SDM), and the panel threshold model (PTM) are constructed to test the impact of tourism development on urban liveability based on the data from 284 prefecture-level and above cities in China for the period 2004–2019. The results show that tourism development can significantly contribute to the improvement of urban liveability. Meanwhile, the positive impact of tourism development on the liveability of neighboring cities through spatial spillover effects is still valid in eastern, central, and western China, but the effect is much larger in the eastern and central cities than in the western cities. Moreover, tourism development has positive nonlinear effects on urban liveability, and the marginal effects are clearly decreasing after crossing the first and second thresholds. Finally, specific recommendations are proposed for tourism development to improve urban liveability

Tourism Development, Carbon Emission Intensity and Urban Green Economic Efficiency from the Perspective of Spatial Effects

In recent years, China has increasingly emphasized green development. Therefore, it is of theoretical and practical significance to study the green economic effect and carbon reduction effect of tourism development for the transformation of economic development. Using the superefficient EBM to measure the green economic efficiency of 280 cities from 2007–2019, we rely on the spatial Durbin model to explore the spatial spillover utility and nonlinear characteristic relationship of tourism development on green economic efficiency and carbon emission intensity and test the mediating effect of carbon emission intensity. The findings are as follows: (1) Under the exogenous shock test of the “low-carbon city” pilot policy, the spatial spillover effect of tourism development on urban green economic efficiency and carbon emission intensity is robust to spatial heterogeneity. (2) The spatial spillover effects of tourism development on the green economic efficiency and carbon emission intensity of cities show a nonlinear characteristic relationship of “U” and “M” shapes. After tourism development reaches a certain high level, the green economy effect and carbon emission reduction effect are significantly increased. (3) Carbon emission intensity has a significant mediating effect on the impact of tourism development on urban green economic efficiency

Effects of Atomic Ratio on the Mechanical Properties of Amorphous Silicon Carbon Nitride

This paper evaluates the mechanical properties of amorphous silicon carbon nitride (a-SiCxNy) films with different atomic ratios via molecular dynamics simulation. The Si-C-N ternary amorphous model is constructed using ReaxFF potential and melt-quenching method. The results demonstrate that the density range of constructed model spans a wide range of densities (2.247–2.831 g/cm3). The short- and medium-range order of the constructed a-SiCxNy structures show a good correlation with the experimental observations. Based on the structural feasibility, the elastoplastic performance is analyzed. There is significant ductility during the uniaxial tension process of a-SiCxNy, except for Si(CN2)2. The calculated elastic modulus ranges from 206.80 GPa to 393.58 GPa, close to the experimental values of coating films. In addition, the elastic modulus of a-SiCxNy does not change monotonically with the carbon or silicon content but is related to the atomic ratio. This article provides an understanding of the chemical composition dependence of the mechanical properties of amorphous compounds at the molecular level

Highly flexible reduced graphene oxide@polypyrrole-polyethylene glycol foam for supercapacitors

© 2020 The Royal Society of Chemistry. A flexible and free-standing 3D reduced graphene oxide@polypyrrole-polyethylene glycol (RGO@PPy-PEG) foam was developed for wearable supercapacitors. The device was fabricated sequentially, beginning with the electrodeposition of PPy in the presence of a PEG-borate on a sacrificial Ni foam template, followed by a subsequent GO wrapping and chemical reduction process. The 3D RGO@PPy-PEG foam electrode showed excellent electrochemical properties with a large specific capacitance of 415 F g-1 and excellent long-term stability (96% capacitance retention after 8000 charge-discharge cycles) in a three electrode configuration. An assembled (two-electrode configuration) symmetric supercapacitor using RGO@PPy-PEG electrodes exhibited a remarkable specific capacitance of 1019 mF cm-2 at 2 mV s-1 and 95% capacitance retention over 4000 cycles. The device exhibits extraordinary mechanical flexibility and showed negligable capacitance loss during or after 1000 bending cycles, highlighting its great potential in wearable energy devices

Multiphoton Absorption Simulation of Sapphire Substrate under the Action of Femtosecond Laser for Larger Density of Pattern-Related Process Windows

It is essential to develop pattern-related process windows on substrate surface for reducing the dislocation density of wide bandgap semiconductor film growth. For extremely high instantaneous intensity and excellent photon absorption rate, femtosecond lasers are currently being increasingly adopted. However, the mechanism of the femtosecond laser developing pattern-related process windows on the substrate remains to be further revealed. In this paper, a model is established based on the Fokker–Planck equation and the two-temperature model (TTM) equation to simulate the ablation of a sapphire substrate under the action of a femtosecond laser. The transient nonlinear evolutions such as free electron density, absorption coefficient, and electron–lattice temperature are obtained. This paper focuses on simulating the multiphoton absorption of sapphire under femtosecond lasers of different wavelengths. The results show that within the range of 400 to 1030 nm, when the wavelength is large, the number of multiphoton required for ionization is larger, and wider and shallower ablation pits can be obtained. When the wavelength is smaller, the number of multiphoton is smaller, narrower and deeper ablation pits can be obtained. Under the simulation conditions presented in this paper, the minimum ablation pit depth can reach 0.11 μm and the minimum radius can reach 0.6 μm. In the range of 400 to 1030 nm, selecting a laser with a shorter wavelength can achieve pattern-related process windows with a smaller diameter, which is beneficial to increase the density of pattern-related process windows on the substrate surface. The simulation is consistent with existing theories and experimental results, and further reveals the transient nonlinear mechanism of the femtosecond laser developing the pattern-related process windows on the sapphire substrate