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The purpose of this paper is to empirically examine the impact of closing mechanism changes on market quality, investor trading behavior and market manipulation in the Shanghai stock market.

A dummy variable is constructed indicating whether the closing mechanism is call auction or continuous auction. Market quality is measured from aspects of liquidity, volatility and price continuity; investor trading behavior is scaled by order timing and order aggressiveness, and a price deviation indicator is the proxy of manipulation. Using panel regression, this study examines the impact of closing mechanism changes based on intraday transaction data from the Shanghai stock market.

The conclusions are as follows: First, market quality improves after the closing mechanism is reformed in terms of liquidity, volatility and price continuity. Second, order strategy changes significantly in the closing call market, and investors trade more aggressively in the continuous trading period before closing. Third, the closing call mechanism restrains the closing price manipulation and thus prompts an efficient closing price.

This paper examines the policy effects of closing mechanism changes from aspects of market quality, trading behavior and price manipulation, providing pieces of evidence for trading mechanism design and market supervision in emerging markets.

This paper aims to evaluate and compare the performance of different computer vision algorithms in the context of visual servoing for augmented robot perception and autonomy.

The authors evaluated and compared three different approaches: a feature-based approach, a hybrid approach and a machine-learning-based approach. To evaluate the performance of the approaches, experiments were conducted in a simulated environment using the PyBullet physics simulator. The experiments included different levels of complexity, including different numbers of distractors, varying lighting conditions and highly varied object geometry.

The experimental results showed that the machine-learning-based approach outperformed the other two approaches in terms of accuracy and robustness. The approach could detect and locate objects in complex scenes with high accuracy, even in the presence of distractors and varying lighting conditions. The hybrid approach showed promising results but was less robust to changes in lighting and object appearance. The feature-based approach performed well in simple scenes but struggled in more complex ones.

This paper sheds light on the superiority of a hybrid algorithm that incorporates a deep neural network in a feature detector for image-based visual servoing, which demonstrates stronger robustness in object detection and location against distractors and lighting conditions.

Project schedules have a vital role in the effective management of time, cost, scope and resources in construction projects, and creating schedules requires schedulers with construction knowledge and experience. The increase in the complexity of building projects and the emergence of building information modeling (BIM) in the architecture, engineering and construction industry have encouraged researchers to explore BIM capabilities for automated schedule generation. The scope and capabilities of the developed systems, however, are limited and the link between design and scheduling is still underdeveloped. This paper aims to investigate methods to develop a BIM-based framework to automatically generate schedules for concrete-framed buildings.

This system first extracts the required data from the building information model, including elements’ dimensions, quantities, spatial information, materials and other related attributes. It then applies construction rules, prior knowledge and production rate data to create project work-packages, calculate their durations and determine their relationships. Finally, it organizes these results into a schedule using project management software.

This system provides an automated and easy-to-use approach to generate schedules for concrete-framed buildings that are modeled in a BIM platform. It provides two schedules for each project, both a sequential and an overlapped solution, which the schedulers can modify into a practical schedule based on conditions and available resources.

This research project presents an innovative approach to use BIM-based attributes of structural elements to develop list of work-packages and estimate their durations, and then it uses a combination of rule-based and case-based reasoning to generate the schedules.

Digital healthcare has become one of the most important Internet applications in the recent years, and digital platforms have been acting as interfaces between the patients and physicians. Although these technologies enhance patient convenience, they create new challenges in platform management. For instance, on physician rating websites, information overload negatively influences patients' decision-making in relation to selecting a physician. This scenario calls for an automated mechanism to provide real-time rankings of physicians. Motivated by an online healthcare platform, this study develops a method to deliver physician ranking on platforms by considering patients' browse behaviors and the capacities of service resources.

The authors use a probabilistic model for explicitly capturing the browse behaviors of patients. Since the large volume of information in digital systems makes it intractable to solve the dynamic ranking problem, we design a ranking with value approximation algorithm that combines a greedy ranking policy and the value function approximation methods.

The authors found that the approximation methods are quite effective in dealing with the ranking optimization on the digital healthcare system, and it is mainly because the authors incorporate the patient behaviors and patient availability in the model.

To the best of the authors’ knowledge, this is one of the first studies to present solutions to the dynamic physician ranking problem. The ranking algorithms can also help platforms improve system and operational performance.

The purpose of this study is to extend the classical noncentral F-distribution under normal settings to noncentral closed skew F-distribution for dealing with independent samples from multivariate skew normal (SN) distributions.

Based on generalized Hotelling's T² statistics, confidence regions are constructed for the difference between location parameters in two independent multivariate SN distributions. Simulation studies show that the confidence regions based on the closed SN model outperform the classical multivariate normal model if the vectors of skewness parameters are not zero. A real data analysis is given for illustrating the effectiveness of our proposed methods.

This study’s approach is the first one in literature for the inferences in difference of location parameters under multivariate SN settings. Real data analysis shows the preference of this new approach than the classical method.

For the real data applications, the authors need to remove outliers first before applying this approach.

This study’s approach may apply many multivariate skewed data using SN fittings instead of classical normal fittings.

This paper is the research paper and the authors’ new approach has many applications for analyzing the multivariate skewed data.

In order to extend the application of the original octagonal Goodman–Smith fatigue limit diagram, which is commonly used for the evaluation of structure fatigue stress in engineering, a modification of it is proposed for the structure made of S355 steel (commonly used in high-speed electric multiple units (EMUs) bogie frame).

The modification is made based on Deutscher Verband für Schweißen und verwandte Verfahren e. V. (DVS) 1612 standard and the γ-P-S-N curve, with consideration of the fatigue evaluation requirements of different survival rates and confidence levels. The verification of the modification is performed for three welded joints and for the comparison with the experimental data.

The results indicate that the design survival rate, the design safety margin and the fatigue stress evaluation of welded joint types are all improved by using the modified diagram.

There are relatively few studies on modifying octagonal Goodman–Smith fatigue limit diagram. In this paper, a modified diagram is proposed and applied in order to ensure the safety and durability of key welded structures of rail vehicles.

This study aims to test the link between enterprise digital transformation and technological innovation and the mechanisms and channels behind this link.

This study systematically examines whether and how enterprise digital transformation affects technological innovation in China.

Enterprise digital transformation effectively improves technological innovation. This result remains stable in robustness and endogeneity checks. The channel mechanisms of this promoting effect are internal (improvement of internal control quality and alleviation of agency costs) and external (increased attention of analysts and reduction of customer concentration). Moreover, this promoting effect is more significant for state-owned enterprises, small and medium-sized enterprises, enterprises in areas with low marketization and enterprises that do not enjoy digital subsidies from the government.

Enterprises need to attend to the mechanisms behind the link between digital transformation and technological innovation and to the unique effects of different enterprise attributes and capital markets, such as size, the ownership nature, the degree of regional marketization and government subsidies. Doing so will effectively promote digital transformation and technological innovation and strengthen core competitiveness.

This study provides systemic evidence of the link between enterprise digital transformation and technological innovation. The findings enrich the research literature on enterprise digitization and the factors of influencing enterprises’ technological innovation and provide a reasonable explanation for how enterprise digital transformation affects technological innovation.

This paper aims to overcome the limitations of low efficiency, low power density and strong electromagnetic interference (EMI) of the existing pulsed melt inert gas (MIG) welding power supply. So a novel and simplified implementation of digital high-power pulsed MIG welding power supply with LLC resonant converter is proposed in this work.

A simple parallel full-bridge LLC resonant converter structure is used to design the digital power supply with high welding current, low arc voltage, high open-circuit voltage and a wide range of arc loads, by effectively exploiting the variable load and high-power applications of LLC resonant converter.

The efficiency of each converter can reach up to 92.3%, under the rated operating condition. Notably, with proposed scheme, a short-circuit current mutation of 300 A can stabilize at 60 A within 8 ms. Furthermore, the pulsed MIG welding test shows that a stable welding process with 280 A peak current can be realized and a well-formed weld bead can be obtained, thereby verifying the feasibility of LLC resonant converter for pulsed MIG welding power supply.

The high efficiency, high power density and weak EMI of LLC resonant converter are conducive to the further optimization of pulsed MIG welding power supply. Consequently, a high performance welding power supply is implemented by taking adequate advantages of LLC resonant converter, which can provide equipment support for exploring better pulsed MIG welding processes.

This paper aims to focus on the high-speed rotary lip seal in aircraft engines, combining its service parameters, its own structure and application conditions, to study the influence of different eccentric forms, eccentricity, rotational speed and other factors on the performance of the rotary lip seal.

A numerical simulation model for high-speed eccentric rotary lip seals has been developed based on the theory of elastic hydrodynamic lubrication. This model comprehensively considers the coupling of multiple physical fields, including interface hydrodynamics, macroscopic solid mechanics and surface microscopic contact mechanics, under the operating conditions of rotary lip seals. The model takes into account eccentricity and uses the hazardous cross-sectional method to quantitatively predict sealing performance parameters, such as leakage rate and friction force.

Eccentricity has a large impact on lip seal performance; lips are more susceptible to wear failure under static eccentricity and to leakage failure under dynamic eccentricity.

This study provides a new idea for the design of rotary lip seal considering eccentricity, which is of guiding significance for the engineering application of rotary lip seal.