Blockchain-based cryptocurrencies, such as Bitcoin (BTC) and Ethereum (ETH), are newly emerging financial assets. Cryptocurrency exchanges are marketplaces for cryptocurrency circulation while becoming a new venue for money laundering. In this work, we cooperate with a cryptocurrency exchange to investigate new solutions for anti-money laundering in cryptocurrency exchanges. First, we learn the domain knowledge of cryptocurrency transactions and summarize data analytical requirements of transaction supervisors in their daily work of anti-money laundering. Then, we propose a visual analysis approach to support their daily work. The approach consists of a new algorithm that automatically detects suspicious money laundering accounts and a multiviewed user interface that visualizes the algorithm results and relevant transaction data. An abacus-inspired visualization is designed in the interface to depict transaction patterns contained in numerous cryptocurrency transactions, which can help supervisors find money laundering clues and deduce the trading tactic adopted by launderers. Finally, an algorithm performance experiment, a case study, and a field study are conducted with real-world data to demonstrate the effectiveness of our solution.

The service performance of an industrial bearing may deteriorate sharply after a sudden transition which is very difficult to be captured prior to its appearance. It is accordingly valuable to estimate this critical transition for avoiding serious catastrophes caused by the faulty bearing. To address this issue, an asynchronous gated recurrent network (AGRN) is proposed to estimate the critical transition of the bearing deterioration. A gated recurrent unit (GRU) is first developed to extract prognostic data as features using few early samples. Chi-square distributions of the squared prediction error of the residuals and the variation of principal components calculated from the features are fused as a statistic series, where the critical threshold is calculated adaptively. Another GRU is proposed to forecast deterioration process using fused statistic series. The forthcoming transition can be estimated by the process with the critical threshold at the initial operation. The present AGRN is evaluated by lifecycle experiments of three bearings, all from public benchmark datasets. Results show that the proposed method is robust in offering maintenance response time for bearings before transiting to critical failures.

ABSTRACT This study investigates the impact of foreign institutional investors (FIIs) on corporate green innovation. We manually collected data on foreign institutional ownership (FIO) from 34 international jurisdictions between 2009 and 2020. We find that FIO has a positive, robust, and causal effect on the green innovation practices of Chinese listed companies. Moreover, our heterogeneity analyses indicate that this positive effect is more pronounced for FIIs originating from jurisdictions exhibiting greater environmental consciousness of and advancements in green technology as well as for those FIIs committed to the United Nations—supported Principles of Responsible Investment. Furthermore, we provide evidence suggesting that environmental information disclosure and monitoring serve as potential mechanisms through which FIIs catalyze corporate green innovation.

From the emergence of the new coronavirus pandemic to extreme climatic catastrophes, the development and enhancement of urban ecological resilience has evolved into a critical and strategic imperative. Investigating the capacity of digital finance to promote urban ecological resilience bears substantial relevance to the sustainable advancement of urban centers. This study examines the influence of digital finance on urban ecological resilience by applying a benchmark regression model on data from 107 prefecture-level cities within the Yangtze River Economic Belt across 2011-2020. Additionally, this study delves into its mechanism and spatial spillover impacts via a mediating effect model and a spatial effect model. The findings revealed that (1) digital finance strengthens the ecological resilience of the locale and beneficially impacts the surrounding regions; (2) digital finance enhances urban ecological resilience by fostering technological innovation and reducing energy intensity; and (3) in the lower reaches of the Yangtze River, digital finance plays a greater role in improving urban ecological resilience. Cities with high level of traditional financial development, high level of economic development and high intensity of environmental regulation have a more obvious role in promoting urban ecological resilience. Within the paradigm of ecological civilization, it is advisable for governmental bodies to fortify inter-regional digital financial collaboration, refine the green financial infrastructure, and advocate for sustainable, low-carbon, high-quality urban development.

Abstract To address the technical bottleneck of autonomous vision guidance for the initial weld position of medium-thickness plate in robot welding. This paper proposes a high accuracy and stability initial weld position segmentation method for medium-thickness plate, this method is developed by integrating the Bottleneck Transformer (BoT) into YOLOv8, termed as BoT-YOLOv8. Firstly, aim to filter out redundant information in the image and enhance the model's capability to express features, the BoT is added behind the last bottleneck layer in the residual module of the YOLOv8 neck structure. Subsequently, in order to obtain the multi-scale information of the target, the atrous convolution is incorporated as the spatial pyramid pooling structure to establish connections between the backbone and the neck of this model. Furthermore, to facilitate the learning of weld position characteristics for the welding robot, the Hue-Saturation-Value (HSV) space region segmentation method is utilized to postprocess the weld seam features. Finally, ablation experiments are conducted on the self-created weld dataset. The results demonstrate that the proposed method achieves a trade-off between detection accuracy (93.1% \({mAP}^{0.5}\)) and detection speed (26.5 \(FPS\)) on a 12GB NVIDIA GeForce RTX 3060 GPU. In addition, compared with the existing methods, the presented method exhibits stronger anti-interference capability.

ABSTRACT Ozone is widely used in industrial production, disinfection, and pollution control. To improve the ozone generation ability of dielectric barrier discharge (DBD), micro-holes with a diameter of about 50 µm in dielectric were introduced to optimize the discharge process. Experimental results indicate that the micro-holes in dielectric can increase the ozone concentration by lowering the inception voltage and boosting the intensity of electric discharge of the DBD device. A voltage of 16.7 kV and flow rate of 3 L/min, the DBD device with 40 micro-holes has an ozone concentration of 680 mg / L and provides an ozone yield of 320 g / kWh, while the device without micro-holes has an ozone concentration of only 150 mg/L and provides an ozone yield of only 180 g/kWh. The micro-hole in the dielectric plays the effect similar to that of micro hollow cathode, which can not only directly affect the ozone generation ability, but also affect the effect of other factors on ozone generation, such as discharge voltage, air flow rate, and gap space between dielectrics. The promotion of ozone generation by micro-hole can be used to design high-performance ozone generators and provide ideas for reusing ozone generators damaged by dielectric breakdown.

Biofouling deteriorates the performance of sensors operated in biofluids. Protein adsorption is believed to be the first step of biofouling, which also reduces biocompatibility by further inducing cell adhesion, platelet activation, and even inflammation. Current studies of antifouling coatings are focused on polymers and hydrogels, which have succeeded in remaining resistant to protein adsorption, but their application on sensor electrodes is limited due to low conductivity and biocompatibility. Here, we report a spontaneous antibiofouling strategy for sensor electrodes by controlling oxygen vacancies in WO3 nanosheets. Irreversible adsorption of proteins was reduced by 76% in unprocessed human plasma when electrodes were coated with WO3 rich in surface oxygen vacancy. These electrodes maintained 91% of the initial current density after 1 month of incubation in human plasma.