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Understanding the layout of China’s fintech policy planning from the perspective of policy science theory will help policy makers to fully understand the current development stage and evolutionary path of fintech and improve the implementation of fintech policies and the promotion of their effects. This study examines 120 fintech policies issued at the national level from 2017 to 2022; unifies policy tools, policy organizational structure, and policy effectiveness into a three-dimensional scientific policy analysis framework; and uses a text content mining method to provide a quantitative analysis of China’s current fintech policy system. In terms of the choice of policy tools, there is an unbalanced proportion, with environmental-type policy tools being overused and demand-type policy tools being underused; a network of core institutions for policy promulgation has been formed, with diversified types of subjects. However, overall, the degree of cooperation among various subjects is not high, and some departments closely related to the development of fintech are not involved enough in the publication of cooperation documents. Policy effectiveness depends on the number of policies and their average effectiveness, and the latter has insufficient growth momentum. Given the existing problems, some suggestions are made for optimising policies to develop fintech.

Abstract In this work, we examine the photoelectrochemical response of TiO2 layers prepared by reactive DC sputter deposition on conductive glass (FTO). We show that adequate conditioning of the FTO by a very thin (few nm thick) Ti interlayer and optimizing the sputter parameters, compact TiO2 anatase layers can be produced that reach incident photocurrent conversion efficiencies (IPCE) maxima peaking at 75%. This is outperforming many of the best titania photoanode structures (including high surface area 1D and 3D titania structures). The key role of the interlayer is to promote the crystallization of titania in the anatase form during the annealing process (as opposed to rutile in the interlayer-free case). Without this interlayer, an IPCE maxima of ≈43% is obtained for otherwise identically processed electrodes. The present work thus describes a most simple straightforward approach for fabricating compact, high-efficiency TiO2 (anatase) photoanodes. Graphical abstract

[Abstract:] Hydrological and sediment dynamics have changed considerably on the Chinese Loess Plateau during the last six decades due to large scale land use changes and numerous water regulation actions. Understanding the mechanism of sediment transport change and its effects is of great importance to food and environmental security. Numerical approaches are useful to map and assess spatio-temporal patterns in sediment dynamics. This study evaluates monthly and annual sediment connectivity in the Wei River Basin (134,800 km2) at the basin and sub-basin scales using the aggregated index of sediment connectivity (AIC). For the first time, this index is applied on this relatively large regional scale. The two objectives were to (1) evaluate the performance of the AIC at the regional scale, addressing substantial differences among areas, and (2) analyze how each AIC sub-factor co-determines the monthly sediment and connectivity patterns. Results show that AIC has strong or moderate positive correlation with sediment yield from 15 out of 23 stations in the Wei and Jing sub-basin. The Jing sub-basin has the highest sediment connectivity due to degraded vegetation, while the Beiluo sub-basin has the lowest sediment connectivity on average due to better ecological restoration. Within the year, sediment connectivity is highest in April and lowest in January, due to the rainfall regime and intra-annual land cover variations. Among the AIC factors, the rainfall factor has the highest effect on sediment connectivity, implying that functional connectivity (graded by rainfall and soil cover) determines sediment dynamics more than structural connectivity (mainly determined by topography and soil permeability). This study provides one of the first large-scale estimates of spatial and temporal sediment connectivity from hillslopes to river stream and including large reservoirs, which can be further employed to implement regional ecological construction works and environmental catchment management. China Scholarship Council; 201906300050

Constructing an efficient photocatalyst for H2 production generally requires the integration of several functional features in and on a semiconductor platform. This is conventionally done by a classic step-by-step synthesis. Here, we report the self-assembly of an amorphous titania nanotube based system when illuminated for extended time in suitable aqueous solutions. Over time, not only photodeposition of a co-catalyst can take place, but also in situ crystallization and morphology changes occur that can provide a higher H2 production than observed for a classically assembled photocatalyst.

ACS catalysis 12, 33 - 41 (2022). doi:10.1021/acscatal.2c04481, Trapping sites in single atom (SA) catalysts are critical to the stabilization and reactivity of isolated atoms. Herein, we show that anchoring of Pt SAs on TiO$_2$ nanosheets is strongly aided by lattice incorporated fluorine species. Tailoring the speciation of fluorine on TiO$_2$ nanosheets is a key factor for uniform and stable dispersion of the Pt SAs and high efficiency in Pt SA co-catalyzed photocatalytic H$_2$ production. Fluorine-stabilized uniformly dispersed Pt SAs on the (001) surface of TiO$_2$ can provide a remarkable photocatalytic activity (a H$_2$ production rate of 45.3 mmol h$^{–1}$ mg$^{–1}$ Pt for 65 mW/cm2 365 nm light). This high (maximized) efficiency can be achieved with a remarkably low loading amount of Pt SAs on TiO$_2$ nanosheets (0.03 wt %), which is far superior to Pt nanoparticles on a TiO$_2$ nanosheet with the same or a higher loading amount. F-stabilized Pt SAs on TiO$_2$ nanosheets also exhibit an excellent stability in long-term photocatalytic reactions., Published by ACS, Washington, DC

Single atom (SA) catalysis, over the last 10 years, has become a forefront in heterogeneous catalysis, electrocatalysis, and most recently also in photocatalysis. Pt SAs on titania have been reported to be a highly effective co-catalyst in photocatalytic H2 generation. Most recently, for the synthesis of SA loading on titania surfaces some simple immersion techniques have been described. Here we introduce a so far unexplored but evidently very effective approach to enhance the effectivity of Pt SA co-catalysts on anodic TiO2 layers. For this, we first decorate TiO2 surfaces with a partial coverage of headgroups of silane self-assembled monolayers (SAMs) and then deposit Pt SAs on this SAM modified surface. We observe a significantly enhanced photocatalytic activity for H2 generation using this sensitization of the surface with a modified SAM.

In the present work the authors show that anodic TiO

Constructing an efficient photocatalyst for H2 production generally requires the integration of several functional features in and on a semiconductor platform. This is conventionally done by a classic step-by-step synthesis. Here, we report the self-assembly of an amorphous titania nanotube based system when illuminated for extended time in suitable aqueous solutions. Over time, not only photodeposition of a co-catalyst can take place, but also in situ crystallization and morphology changes occur that can provide a higher H2 production than observed for a classically assembled photocatalyst.

In recent years, photocatalytic reactions on anodic TiO2 nanotubes have been intensively investigated. In order to show photocatalytic activity, anodically formed nanotubes need to be crystallized to anatase. This is conventionally done by thermal annealing in air at temperatures 400–600 °C. Recently, a so‐called “water annealing” treatment has been reported to be effective to also create a highly active form for photocatalysis. Here we report on the feasibility of using a water annealing treatment of TiO2 nanotubes to create a photocatalyst for H2 production that is as active as conventional thermal annealing. If the water‐annealed samples are additionally hydrogenated to a so‐called “grey” modification, a further significant improvement of the photocatalytic activity for H2 evolution can be achieved – this without the use of any noble metal co‐catalyst. A combination of water annealing, thermal annealing, followed by hydrogenation can deliver a H2 generation activity that is more than five times higher than that achieved by thermal annealing of anodic TiO2 nanotubes.

In the present work the authors show that anodic TiO2 nanotubes (NT) show excellent harvesting properties for Pt single atoms (Pt SAs) from highly dilute Pt solutions. The tube walls of anodic nanotubes, after adequate annealing to anatase, provide ample of suitable trapping sites—that is, surface Ti3+‐Ov (Ov: oxygen vacancy) defects that are highly effective to extract and accumulate Pt in the form of SAs. A saturated (maximized) SA density can be achieved by an overnight immersion of a TiO2 NT layer to a H2PtCl6 solution with a concentration that is as low as 0.01 mm Pt. Such TiO2 NTs with surface trapped Pt SAs provide a maximized high activity for photocatalytic H2 generation (reaching a turnover frequency (TOF) of 1.24 × 106 h−1 at a density of 1.4 × 105 Pt atoms µm−2)—a higher loading with Pt nanoparticles does not further increase the photocatalytic activity. Overall, these findings show that anodic TiO2 nanotubes provide a remarkable substrate for Pt extraction and recovery from very dilute solutions that directly results in a highly efficient photocatalyst, fabricated by a simple immersion technique.

With the rapid development of computer technology, building pose estimation combined with Augmented Reality (AR) can play a crucial role in the field of urban planning and architectural design. For example, a virtual building model can be placed into a realistic scenario acquired by a Unmanned Aerial Vehicle (UAV)to visually observe whether the building can integrate well with its surroundings, thus optimizing the design of the building. In the work, we contribute a building dataset for pose estimation named BD3D. To obtain accurate building pose, we use a physical camera which can simulate realistic cameras in Unity3D to simulate UAVs perspective and use virtual building models as objects. We propose a novel neural network that combines MultiBin module with PoseNet architecture to estimate the building pose. Sometimes, the building is symmetry and ambiguity causes its different surfaces to have similar features, making it difficult for CNNs to learn the differential features between the different surfaces. We propose a generalized world coordinate system repositioning strategy to deal with it. We evaluate our network with the strategy on BD3D, and the angle error is reduced to [Formula: see text] from [Formula: see text]. Code and dataset have been made available at: https://github.com/JellyFive/Building-pose-estimation-from-the-perspective-of-UAVs-based-on-CNNs .

This paper presents an improved traffic sign detection method based on Faster R-CNN with dataset augmentation and subcategory detection scheme. Firstly, we extract natural scene frames from given videos and determine 20 categories of traffic signs. Secondly, we extend the image dataset and extract regions of interest, then manually annotate all categories. Thirdly, we train the Faster R-CNN model based on TensorFlow, then test the model and obtain the following evaluation indexes: the mean average precision is 99.07%, the recall rate is 99.66%, and the precision rate is 97.54%. Finally, we add the subcategory detection scheme to determine traffic light states, and we get the following evaluation indexes: the mean average precision is 99.50\%, the recall rate is 100%, and the precision rate is 94.40\%. Our experiments prove the robustness and accuracy for both traffic sign detection and subcategory detection of traffic light.

An updated framework based on LDA is provided in this paper to extract features from online user reviews which are in Chinese. This model is an extension of the LDA by introducing the concepts of multi-gram and part of speech into it and it is named PM-LDA. Through this model, features are generated as topics and topic labels can be generated as the sentence that has the max topic probability. Topics in PM-LDA are divided into two different types. The one is some general features such as product brand, color or producing area, and the other is those latent characteristics which customers may be more interested in. Part of speech is used to get the feature object and feature opinion separately, to make it more accurate. Several experiments are carried out to help to evaluate this model and it is indicated that this method has improved performance both in accuracy and the quality of the topic model itself.