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Currently, a common method of reconstructing mannequin is based on the body measurements or body features, which only preserve the body size lacking of the accurate body geometric shape information. However, the same human body measurement does not equal to the same body shape. This may result in an unfit garment for the target human body. The purpose of this paper is to propose a novel scanning-based pipeline to reconstruct the personalized mannequin, which preserves both body size and body shape information.

The authors first capture the body of a subject via 3D scanning, and a statistical body model is fit to the scanned data. This results in a skinned articulated model of the subject. The scanned body is then adjusted to be pose-symmetric via linear blending skinning. The mannequin part is then extracted. Finally, a slice-based method is proposed to generate a shape-symmetric 3D mannequin.

A personalized 3D mannequin can be reconstructed from the scanned body. Compared to conventional methods, the method can preserve both the size and shape of the original scanned body. The reconstructed mannequin can be imported directly into the apparel CAD software. The proposed method provides a step for digitizing the apparel manufacturing.

Compared to the conventional methods, the main advantage of the authors’ system is that the authors can preserve both size and geometry of the original scanned body. The main contributions of this paper are as follows: decompose the process of the mannequin reconstruction into pose symmetry and shape symmetry; propose a novel scanning-based pipeline to reconstruct a 3D personalized mannequin; and present a slice-based method for the symmetrization of the 3D mesh.

This study explores configurations that promote the development of collective economies in China's rural villages and reveals the multiple development pathways that otherwise remain relatively unexamined in the literature.

The authors obtained first-hand representative case data from 20 villages in 12 counties in 5 provinces in East, West and Central China via fieldwork and applied fuzzy set qualitative comparative analysis (fsQCA) to conduct a configurational comparative study of the development of village collective economies.

This paper identifies five factors in the current literature that affect the development of village collectives, based on an “entrepreneur–situation” analytical framework. Using the fsQCA method, this study further obtains two main configurations of conditions that culminate in the growth of rural collective economies in China. The first solution is the “top-down path”: When entrepreneurial leadership (EL), resource endowment (RE) and government assistance (GA) are present, a village collective economy will experience a high level of development, irrespective of policy support (PS) and villagers' participation (VP). The second solution is the “bottom-up path”: When EL, VP and PS are present and GA is not present, a village collective economy will experience a high level of development, irrespective of RE. In both situations, EL stands out as the core condition for the development of village collective economies, implying the need for the government to vigorously cultivate the entrepreneurial skills and aspirations of village cadres.

Taking a configurational perspective and using an fsQCA approach, this research constructs an “entrepreneur–situation” analytical framework to investigate the key combinations of factors and pathways involved in the high level of development of Chinese village collective economies.

The purpose of this paper is to present an automated method for complicated truss structure subassembly identification.

A community-detecting algorithm is introduced and adapted to reach the target. The ratio between oriented bounding boxes of parts is used as the weight to reflect the compact degree of assembly relationships. The authors also propose a method to merge nodes together at cut-vertex in model, by which the solving process could be accelerated.

This method could identify the subassemblies of complex truss structures according to the specific requirements.

This research area is limited to truss structures. This research offers a new method in assembly sequences planning area. It could identify subassemblies in complex truss structures, with which the existing method is not adequate to deal.

This method could facilitate the complex truss structures assembly planning, lower the human errors and reduce the planning time.

The method could inspire general assembly analysis planning.

All authors of this paper confirm that this manuscript is original and has not been submitted or published elsewhere.

The purpose of this paper is to propose a receding horizon control approach for the problem of locating unknown wireless sensor networks by using a mobile robot.

A control framework is used and consists of two levels: one is a decision level, while the other is a control level. In the decision level, a spatiotemporal probability occupancy grid method is used to give the possible positions of all nodes in sensor networks, where the posterior probability distributions of sensor nodes are estimated by capturing the transient signals. In the control level, a virtual robot is designed to move along the edge of obstacles such that the problem of obstacle avoidance can be transformed into a coordination problem of multiple robots. On the basis of the possible positions of sensor nodes and virtual robots, a receding horizon control approach is proposed to control mobile robots to locate sensor nodes, where a temporary target position method is utilized to avoid several special obstacles.

When the number of obstacles increases, the average localization errors between the actual locations and the estimated locations significantly increase.

The proposed control approach can guide the mobile robot to avoid obstacles and deal with the corresponding dynamical events so as to locate all sensor nodes for an unknown wireless network.

The aim of this paper is to explore the relationship between digital transformation and corporate fraud.

This paper uses panel data of Chinese listed corporations from 2010 to 2021 and captures digital transformation from the perspectives of awareness and investment by extracting related content from annual reports. Our work investigates whether and how digital transformation influences corporate fraud and examines the moderating effects of the legal environment, media environment and privacy concerns.

Our findings show that digital transformation, captured either from awareness or actual investment, can significantly alleviate corporate fraud. Our results are robust in a set of endogeneity tests and robustness checks. Additionally, we confirm that digital transformation alleviates corporate fraud through two mechanisms: improving internal monitoring and boosting information flow. Additionally, this alleviating effect is more pronounced for corporations with fewer privacy concerns and in worse legal and media environments.

Our findings provide insights for policymakers to motivate corporations to engage in digital transformation for fraud prevention. We also offer guidelines for corporations to improve their awareness and actual investments in digital transformation and take advantage of its governance effect in preventing corporate fraud.

Overall, we highlight the governance role of digital transformation in alleviating corporate fraud and provide policy implications for regulators in emerging economies to regard digital transformation as an effective tool for fraud prevention.

Most source recording device identification models for Web media forensics are based on a single feature to complete the identification task and often have the disadvantages of long time and poor accuracy. The purpose of this paper is to propose a new method for end-to-end network source identification of multi-feature fusion devices.

This paper proposes an efficient multi-feature fusion source recording device identification method based on end-to-end and attention mechanism, so as to achieve efficient and convenient identification of recording devices of Web media forensics.

The authors conducted sufficient experiments to prove the effectiveness of the models that they have proposed. The experiments show that the end-to-end system is improved by 7.1% compared to the baseline i-vector system, compared to the authors’ previous system, the accuracy is improved by 0.4%, and the training time is reduced by 50%.

With the development of Web media forensics and internet technology, the use of Web media as evidence is increasing. Among them, it is particularly important to study the authenticity and accuracy of Web media audio.

This paper aims to promote the development of source recording device identification and provide effective technology for Web media forensics and judicial record evidence that need to apply device source identification technology.

Although high-order smooth reproducing kernel mesh-free approximation enables the analysis of structural vibrations in an efficient collocation formulation, there is still a lack of systematic theoretical accuracy assessment for such approach. The purpose of this paper is to present a detailed accuracy analysis for the reproducing kernel mesh-free collocation method regarding structural vibrations.

Both second-order problems such as one-dimensional (1D) rod and two-dimensional (2D) membrane and fourth-order problems such as Euler–Bernoulli beam and Kirchhoff plate are considered. Staring from a generic equation of motion deduced from the reproducing kernel mesh-free collocation method, a frequency error measure is rationally attained through properly introducing the consistency conditions of reproducing kernel mesh-free shape functions.

This paper reveals that for the second-order structural vibration problems, the frequency accuracy orders are p and (p − 1) for even and odd degree basis functions; for the fourth-order structural vibration problems, the frequency accuracy orders are (p − 2) and (p − 3) for even and odd degree basis functions, respectively, where p denotes the degree of the basis function used in mesh-free approximation.

A frequency accuracy estimation is achieved for the reproducing kernel mesh-free collocation analysis of structural vibrations, which can effectively underpin the practical applications of this method.

This paper aims to examine the relation between managerial ability and stock price crash risk, conditional on managerial overconfidence. In addition, conditional on managerial overconfidence, the authors investigate the effect of managerial ability on firms’ choice of bad news hoarding channels, which result in a stock price crash.

Using a sample of 24,289 firm-years from companies listed on Compustat and CRSP from 1994 to 2018, the authors conduct panel regression analysis.

The authors find that managerial ability is positively associated with stock price crash risk only when managerial overconfidence is high. Furthermore, the authors find that managerial ability seems to exacerbate (attenuate) the bad news withholding by the overconfident managers using the earnings guidance (earnings management) channel. The authors find limited evidence that high-ability managers are likely to withhold bad news through the overinvestment channel and “other channels” when managers are overconfident. Finally, the authors find that the joint effect of managerial overconfidence and managerial ability on firms’ crash risk is more pronounced when there is a material weakness in firms’ internal controls, high investor belief heterogeneity and high information asymmetry. However, this effect appears to dissipate during the recent financial crisis in 2008.

This research reveals that managerial ability is costly to firms by engendering bad news hoardings and stock price crash risk when managers are overconfident. It also sheds light on how managerial overconfidence and managerial ability affect managers’ choice of bad news withholding channels and stock price crash risk. Finally, the paper is of practical value to the board of directors in selecting the prospective executives.

Alternating current (AC) corrosion is a type of corrosion that occurs in buried pipelines under AC stray current interference, which can increase the hydrogen embrittlement sensitivity of pipelines. However, rare research works have been conducted on the hydrogen permeability characteristics of pipeline steel under AC stray current interference. The purpose of this paper is to study hydrogen permeation behavior of X80 steel under AC stray current interference.

In this paper, the hydrogen permeation behavior of X80 steel under AC interference is studied by AC hydrogen charging experiment in a dual electrolytic cell. The relationship between hydrogen evolution rate and hydrogen permeation flux is studied using the gas collection method. The difference between AC hydrogen permeability and direct current (DC) hydrogen permeability is also discussed.

The anodic dissolution caused by AC corrosion promotes the chemical desorption reaction of the adsorbed hydrogen atoms on the surface, reducing the hydrogen atom absorption ratio by 70%. When the AC is smaller than 150░ A/m², the hydrogen permeation process is controlled by the hydrogen atom generation rate, and the hydrogen permeation flux increases with the increase in hydrogen atom generation rate. When the AC exceeds 400░ A/m², the hydrogen permeation process is controlled by the absorption ratio. The hydrogen permeation flux decreases with the decrease in the absorption ratio. Under AC interference, there is a maximum hydrogen permeation flux that linearly correlates to the H⁺ concentration in the solutions.

The high-strength steel is very sensitive to hydrogen embrittlement, and X80 steel has been widely used in oil and gas pipelines. To date, no research has been conducted on the hydrogen permeation behavior of pipeline steel under AC interference, and the hydrogen permeability characteristics of pipeline steel under AC interference are not clear. The research results of this paper are of great significance for ensuring the intrinsic safety of high-strength pipelines under AC stray current interference.

Based on the numerical research on the relationship between the flow pattern transition and the condensation heat transfer in circular microchannels, the purpose of this paper is to bring forward a concept of external separation circular microchannel to regulate and control the flow pattern for enhancing the condensation heat transfer.

The numerical research is based on the volume of fluid method and the vapor-liquid phase change model proposed by the present authors.

By numerical research on the condensation process of water in a general circular microchannel, it is discovered that, with the increase of the inlet velocity and the reduction of the temperature difference between the saturation temperature and the channel wall temperature, the bubble detachment frequency is raised and the water vapor condensation length is extended, representing an exponential growth. Therefore, for the condensation process with low temperature difference and high mass flow rate, it is in urgent need to regulate and control the flow pattern.

To prevent the flow pattern in the general circular microchannel converted from annular flow to slug flow and then to bubble flow, this paper brings forward a concept of external separation circular microchannel, which regulates and controls the flow pattern by discharging partial liquid from the annular wall opening. After regulation and control, the flow pattern is converted from original periodic annular flow/slug flow/bubble flow to current stable annular flow. Accordingly, the heat transfer performance is enhanced and the condensation length is lowered remarkably.