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The purpose of this paper is to demonstrate the effect of δ-ferrite on the susceptibility to hydrogen embrittlement of type 304 stainless steel in hydrogen gas environment.

The mechanical properties of as-received and solution-treated specimens were investigated by the test of tensile and fatigue crack growth (FCG) in 5 MPa argon and hydrogen.

The presence of δ-ferrite reduced the relative elongation and the relative reduction area (H₂/Ar) of 304 stainless steel, indicating that δ-ferrite increased the susceptibility of hydrogen embrittlement in 304 stainless steel. Moreover, δ-ferrite promoted the fatigue crack initiation and propagation at the interface between δ-ferrite and austenite. The FCG tests were used to investigate the effect of δ-ferrite on the FCG rate in hydrogen gas environment, and it was found that δ-ferrite accelerated the FCG rate, which was attributed to rapid diffusion and accumulation of hydrogen around the fatigue crack tip through δ-ferrite in high-pressure hydrogen gas environment.

The dependence of the susceptibility to hydrogen embrittlement on δ-ferrite was first investigated in type 304 steel in hydrogen environment with high pressures, which provided the basis for the design and development of a high strength, hydrogen embrittle-resistant austenitic stainless steel.

Fall accidents can cause casualties and economic losses in the construction industry. Fall portents, such as loss of balance (LOB) and sudden sways, can result in fatal, nonfatal or attempted fall accidents. All of them are worthy of studying to take measures to prevent future accidents. Detecting fall portents can proactively and comprehensively help managers assess the risk to workers as well as in the construction environment and further prevent fall accidents.

This study focused on the postures of workers and aimed to directly detect fall portents using a computer vision (CV)-based noncontact approach. Firstly, a joint coordinate matrix generated from a three-dimensional pose estimation model is employed, and then the matrix is preprocessed by principal component analysis, K-means and pre-experiments. Finally, a modified fusion K-nearest neighbor-based machine learning model is built to fuse information from the x, y and z axes and output the worker's pose status into three stages.

The proposed model can output the worker's pose status into three stages (steady–unsteady–fallen) and provide corresponding confidence probabilities for each category. Experiments conducted to evaluate the approach show that the model accuracy reaches 85.02% with threshold-based postprocessing. The proposed fall-portent detection approach can extract the fall risk of workers in the both pre- and post-event phases based on noncontact approach.

First, three-dimensional (3D) pose estimation needs sufficient information, which means it may not perform well when applied in complicated environments or when the shooting distance is extremely large. Second, solely focusing on fall-related factors may not be comprehensive enough. Future studies can incorporate the results of this research as an indicator into the risk assessment system to achieve a more comprehensive and accurate evaluation of worker and site risk.

The proposed machine learning model determines whether the worker is in a status of steady, unsteady or fallen using a CV-based approach. From the perspective of construction management, when detecting fall-related actions on construction sites, the noncontact approach based on CV has irreplaceable advantages of no interruption to workers and low cost. It can make use of the surveillance cameras on construction sites to recognize both preceding events and happened accidents. The detection of fall portents can help worker risk assessment and safety management.

Existing studies using sensor-based approaches are high-cost and invasive for construction workers, and others using CV-based approaches either oversimplify by binary classification of the non-entire fall process or indirectly achieve fall-portent detection. Instead, this study aims to detect fall portents directly by worker's posture and divide the entire fall process into three stages using a CV-based noncontact approach. It can help managers carry out more comprehensive risk assessment and develop preventive measures.

The purpose of this paper is to study the pressure response characteristics of the cartridge electromagnetic relief valve, which offers the problems caused by low pressure response and low efficiency in hydraulic plate shearing machines.

First of all the mathematical model of the cartridge electromagnetic relief valve is deduced to analyze the influence of the relevant parameters on the system pressure response. Then experiments are conducted to research the dynamic characteristics on building and relieving pressure. Through comparison of theoretical and experimental research, the results are found.

The results show that the input flow, working pressure, diameter of adjacent damping hole, and spring stiffness of the main valve have great influence on building pressure of the system, and have no influence on relieving pressure, while diameter of damping hole of control cover plate has influence on the building and relieving pressure of the system.

The research results provide powerful theoretical support for the parametric design of the cartridge electromagnetic relief valve in the hydraulic system of plate shearing machine.

To promote the cultural communication and art appreciation of Inscriptions and calligraphy which are important cultural heritages in China, with a broad crowd base and educational appreciation value, by using digital humanities methods and technologies, the paper aims to discuss how to develop a new user-oriented knowledge base according to user needs for inscription rubbings research and appreciation.

The paper investigates user needs and current problems on the basis of status quo and summation of extensive service experience; validates the rationality of requirements and user scenarios with user research methods including focus groups, interviews and behavior observations; then designs and develops the technical solution of data process, knowledge base construction and service platform through experimental research methods based on agile project management.

The paper proposes a new reading mode for browsing and appreciation inscription rubbing works, a diverse knowledge-integrated knowledge organizational structure, a systematic user experience and service guiding framework which can be widely applicable to the development of other cultural heritage knowledge bases. Apart from that, the paper puts forward intelligent service development goals for the future.

The paper proposes a new reading mode with the overall functions and user experience design and development for browsing and appreciation inscription rubbing works, a diverse knowledge-integrated knowledge organizational structure, a systematic user experience and service guiding framework which can be widely applicable to the development of other cultural heritage knowledge bases. Apart from that, the paper puts forward intelligent service development goals for the future.

The purpose of this paper is to study the influence of different cross-sectional shapes (rectangular, trapezoidal, oval and triangular) and layout forms of oil grooves (radial, circumferential, inclined, compound, helical and double-helical), and determine the optimal section shape and layout form of oil grooves on the temperature field.

Heat conduction theory model was established based on startup characteristics and friction heat principle of hydro-viscous clutch (HVC), and then the theoretical expression of angular velocity of the friction pair and control pressure were deduced, and the heat flux and its distribution on friction disk and separator disk were calculated. Finally, the finite element method was used to solve the temperature field of the friction pair.

The studies show that the circumferential oil groove got the highest temperature, and on the surface of all other structures, hot spots appear with different sizes and temperatures, and the maximum temperature difference in the friction zone is about 3°C, and in the oil groove zone is about 16°C, wherein the compound oil groove has the lowest average temperature. This research shows that the compound oil groove with rectangular cross-section is the best choice for the friction pair.

In this paper, it was found that the compound oil groove with rectangular cross-section is the best choice for the friction pair, and it provided a favorable theory reference and technical support for the structural design of the friction pair and optimized design of the high-power HVC.

This paper aims to study whether the upstream foundry in the original design manufacturer (ODM) supply chain will violate the commission contract and engage in the production of pirated products. Based on the conclusion, this study hopes to explain the phenomenon of pirated products in reality and provide management enlightenment for related companies.

To understand when will foundry violates the processing contract, this paper constructs a five-stage decision-making model, this study derives a model to get three situations and draw data images to describe the characteristics of decision-making by the foundry. Finally, this paper also considers some external supervision.

The results show that processing fee and other parameters (special cost, common cost, weakening factor and product difference) jointly determine the possibility of piracy by the foundry. Moreover, the external supervision mechanism has a significant effect on the piracy behavior of the foundry.

The research provides some support for real business activities, which actually involve many participants and mechanisms. Thus, it could be interesting to explore more multi-stage and complex business methods in reality.

The analysis highlights less-concerned moral hazard behaviors in the ODM supply chain. By recreating the complex interactions of participants, the conclusion shed light on how should different roles deal with their risks and take actions in a real business environment.

The biggest contribution of this study is to discuss the issue of moral hazard in the ODM supply chain. Piracy initiated by foundries may be a new type of supply chain risk and should be paid attention to.

The purpose of this paper is to contribute to the aforementioned literature on the linkage between economic activity and human preference by estimating the cross-sectional determinants of farmers’ participation in participation in crop insurance programs (CIPs) and identifying the impediments preventing the remaining farmers from participating.

Using the unique data sets of risk preference experiments and maize producer surveys pertaining to the maize production areas of China, this paper explores the determinants of farmers’ CIPs and scrutinizes the role of risk aversion in farmers’ CIP purchase decisions under the expected utility maximization framework. And a “non-zero threshold probit model” is used for the analysis.

The results show that risk aversion plays an important role in CIP purchase decision-making, not only in the form of its direct effect but also with regard to the interaction term and expected loss. Furthermore, if the insured amount is high enough, then risk aversion will no longer affect insurance purchase. Additionally, purchase experience, CIP environment (village purchase ratio), and contract items (insured amounts) are significant determinates in these decisions. There is no significant evidence to suggest that serious adverse selection exists in the sampling areas.

One theoretical model is established which considered not only general variables like farmers’ production and household information, but also conditions and terms in the insurance policies. The unique experimental method is used to measure farmers’ risk aversion. Both the role of risk aversion and its’ interaction terms with others in CIP participation are scrutinized to identify complicated influences under the context of real society.

The main purpose of this paper is to calculate the analytical solution or a closed-form solution for the temperature distribution in the heterogeneous casting-mould system.

First, the authors formulate and analyze the mathematical formulation of heat conduction equation in the heterogeneous casting-mould system, with an arbitrary assumption of the ideal contact at the cast-mould contact point. Then, He-Laplace method, based on variational iteration method (VIM), Laplace transform and homotopy perturbation method (HPM), is used to elaborate the analytical solution of this system. The main focus of He-Laplace method is to find the Lagrange multiplier with an easy approach which enables the implementation of HPM very smoothly and provides the series solution very close to the exact solution.

An example is considered to show that He-Laplace method provides the efficient results for calculating the temperature distribution in the casting-mould heterogeneous system. Graphical representation and error distribution represents that He-Laplace method is very simple to implement and effective for casting-mould heterogeneous system.

The work in this paper is original and advanced. Specially, calculation of Lagrange multiplier for casting-mould system has not been reported in the literature for this work.

The purpose of this paper is to weigh up the effect of index-based livestock insurance (IBLI) on loan take up behavior of the pastoral households in the Borena zone of Southern Ethiopia. Although the insurance was introduced over the last decade and it appears to have promising welfare benefit, there is a lack of pragmatic evidence on its effect in leveraging the household’s future wealth for the hope of better productivity in the present.

The authors analyze household-level unique panel data collected in three rounds using descriptive statistics and the fixed effect model estimated by least squares dummy variable analysis.

The authors found that the IBLI appears to have a positive and significant effect on the loan uptake behavior of the herding households.

This increased likelihood of loan uptake suggests that the insurance can reduce the cognitive cost of loan default that would occur due to weather shocks and build-up of the household’s confidence to uptake loan. Consequently, this likelihood can promote the creditworthiness of the insured and reduce his/her fear and worry regarding the possibility of loan delinquency.

The paper is, except where otherwise stated, entirely new work.

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.

This model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.

The experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 10^–3, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 10^–3. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.

This study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.