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Path planning is an important part of three-dimensional (3D) printing data processing technology. This study aims to propose a new path planning method based on a discontinuous grid partition algorithm of point cloud for in situ printing.

Three types of parameters (i.e. structural, process and path interruption parameters) were designed to establish the algorithm model with the path error and the computation amount as the dependent variables. The path error (i.e. boundary error and internal error) was further studied and the influence of each parameter on the path point density was analyzed quantitatively. The feasibility of this method was verified by skin in situ printing experiments.

Path point density was positively correlated with Grid_size and negatively related to other parameters. Point_space, Sparsity and Line_space had greater influence on path point density than Indentation and Grid_size. In skin in situ printing experiment, two layers of orthogonal printing path were generated, and the material was printed accurately in the defect, which proved the feasibility of this method.

This study proposed a new path planning method that converted 3D point cloud data to a printing path directly, providing a new path planning solution for in situ printing. The discontinuous grid partition algorithm achieved controllability of the path planning accuracy and computation amount that could be applied to different processes.

This paper aims to overcome the defect of single-source temperature measurement method and improve the measurement accuracy of FTR. The friction temperature rise (FTR) of brake affects braking performance seriously. However, it was mainly detected by single-source indirect thermometry, which has obvious deviations.

A three-point temperature measurement system was built based on three kinds of single-resource thermometry. Temperature characteristics of these thermometry were analyzed to achieve a standard FTR curve. Two fusion-monitoring models for FTR based on multi-source information were established by artificial neural network (ANN) and support vector machine (SVM).

Finally, the two models were verified based on the experimental results. The results showed that the fusion-monitoring model of SVM was more accurate than that of ANN in monitoring of FTR.

Then the temperature characteristics of the three single-source thermometry were analyzed, and the fusion-monitoring models based on multi-source information were established by ANN and SVM. Finally, the accuracy of the two models was compared by the experimental results. The more suitable fusion-monitoring model for FTR monitoring was determined which would be of theoretical and practical significance for remedying the monitoring defect of FTR.

This study associated consumers' food choice motives and socio-demographic characteristics with their attitudes and consumptions towards food shopping with four e-commerce modes: business-to-consumer (B2C), online-to-offline delivery (O2O Delivery), online-to-offline in-store (O2O In-store) and New Retail. It also explored consumer preferences for specific food categories within the four e-commerce modes.

An online survey was administered to 954 participants from three Chinese cities: Beijing, Shanghai and Shenzhen. Descriptive analysis and linear regression were used in the data analysis.

The following food choice motives (FCMs) and socio-demographic characteristics had a significant effect on food e-commerce attitudes and/or consumption, with some or all of the four e-commerce modes: Taste Appeal, Value for Money, Safety Concerns, Quality Concerns, Processed Convenience, Purchase Convenience, Others' Reviews, City, Gender, Household Size, Age, Income, Occupation and Marital Status. Consumers also have different consumption preferences for food categories in the four e-commerce modes.

This is the first study to associate consumer FCMs and socio-demographics with their e-commerce attitudes and consumption regarding food in four e-commerce modes: B2C, O2O Delivery, O2O In-store and New Retail.

The purpose of this paper is to elaborate upon the notion of counter accounting, to assess the potentiality of online reports for counter accounting and hence for counter accounting's emancipatory potential as online reporting, to assess the extent to which this potential is being realised and to suggest ways forward from a critical perspective.

There are several components to a critical interpretive analysis: critical evaluative analysis, informed to some extent by prior literature in diverse fields; web survey; questionnaire survey; case study.

Web‐based counter accounting may be understood as having emancipatory potential, some of which is being realised in practice. Not all the positive potential is, however, being realised as one might hope: things that might properly be done are not always being done. And there are threats to progress in the future.

Clarification of a notion of counter accounting incorporating the activity of groups such as pressure groups and NGOs; rare study into practices and opinions in this context through a critical evaluative lens.

This paper aims to assess precise correlations between intermetallic compounds (IMCs) microstructure evolutions and the reliability of micro-joints with a Cu/SAC305solder/Ni structure using thermal shock (TS) tests.

This paper uses 200-µm pitch silicon flip chips with nickel (Ni) pads and stand-off height of approximately 60 µm, assembled on substrates with copper (Cu) pads. After assembly, the samples were subjected to air-to-air thermal shock testing from 55 to 125 per cent. The transfer time was less than 5 s, and the dwell time at each temperature extreme was 15 min. To investigate the microstructure evolution and crack growth, two samples were removed from the thermal shock chamber at 0, 400, 1,200, 2,000, 5,800 and 7,000 cycles.

The results showed that one (Cu, Ni)₆Sn₅/(Ni, Cu)₃Sn₄ dual-layer structure formed at the Ni pad interface of chip side dominates the micro-joints failure. This is because substantial (Ni, Cu)₃Sn₄ grain boundaries provide a preferential pathway for the catastrophic crack growth. Other IMCs microstructure evolutions that cause the prevalent joints failure as previously reported, i.e. thickened interfacial (Cu, Ni)₆Sn₅ and Ni₃P layer, and coarsened IMCs inside the solder matrix, only contributed to the occurrence of fine cracks. Moreover, the typical interfacial IMCs spalling triggered by thermally induced stress did not take place in this study, showing a positive impact in the micro-joint reliability.

As sustained trends toward multi-functionality and miniaturization of microelectronic devices, the joints size is required to be constantly scaled down in advanced packages. This arises a fact that the reliability of small-size joints is more sensitive to the IMCs because of their high volume proportion and greatly complicated microstructure evolutions. This paper evaluated precise correlations between IMCs microstructure evolutions and the reliability of micro-joints with a Cu/SAC305solder/Ni structure using TS tests. It found that one (Cu, Ni)₆Sn₅/(Ni, Cu)₃Sn₄ dual-layer structure formed at the Ni pad interface dominate the micro-joints failure, whereas other IMCs microstructure evolutions that cause the prevalent joints failure exhibited nearly negligible effects.

Monitoring the real-time temperature, humidity, and physical position status of goods is vital in the cold chain. Diverse logistics technologies and systems have been adopted in the cold chain for monitoring perishable goods. However, these technologies and systems are independent from each other. Data and information in them are not integrated so that information control is not effective. The paper aims to discuss these issues.

By integrating Internet of Things and tracking technologies, this paper proposes an intelligent tracking system, which is designed to achieve effective and fast live monitoring of goods in the cold chain at the lowest cost and with the largest network capacity and simplest protocols.

Structure and information platform design mechanism are introduced. The key part of this system is a wireless sensor network built on Zigbee. Wireless sensors located in cold storages or refrigerated trucks are able to collect and transmit live data quickly and efficiently.

Users of the proposed system can easily monitor goods transported in cold chains. In addition, the system assigns specific servers to save historical data for inquiries.

As productions show characteristics of multi-varieties and small batch in a recent new product system, it is more difficult to acquire its failure rate data. With the help of expert experience information, the authors can get the interval estimation of failure rate data under different methods, so how to make the interval convergence with the new information is an important problem to be solved. The paper aims to discuss this issue.

In this paper, the concept of generalized standard grey number is used to characterize the multi-source heterogeneous uncertainty failure rate data into a unified framework. Then, the engineering construction method is used to calculate the average failure rate and build the grey exponential distribution reliability function, whose image is presented as the possible region of the two-curve envelope.

Further, according to the normal distribution assumption of the regional convergence based on the information supplement, the convergence problem of the reliability function is transformed into the convergence of the area of the curve envelope region, and construct the multi-objective programming model with the minimum envelope area and the lowest total cost of information acquisition, acquire the conclusion that the failure rate is equal to the nuclear of the average failure rate when the envelope region converges.

Through the case analysis of the equipment ejection system of the Harbinger system, five groups of results are obtained by Matlab simulation, which verify the rationality and feasibility of the model described in this paper.

This study attempts to examine the issues relating to corporate financial reporting of Chinese listed companies under specified institutional settings as companies with different share‐categories are required to prepare annual reports under various General Accepted Accounting Principles (GAAP).

This study selects Chinese companies that issue negotiable shares to examine whether corporate disclosure patterns are different under various institutional settings. Negotiable shares can be traded on stock exchanges and are divided into A‐, B‐ and H‐shares. The extent of corporate disclosure is obtained from the content analysis of annual reports for 191 sampled Chinese listed companies with various share categories. The association are hypothesized and tested between the level of corporate disclosure and the following corporate determinants: company size, profitability, auditor, leverage, industry and ownership structure.

The extensive regulations and different standards influence on disclosures of companies with foreign investment participation and overseas listing status. By reconciliation of their annual reports according to the IFRSs or the GAAP of the listing country, these companies increased information disclosure voluntarily in order to enhance their reputation and credibility. Some corporate factors, such as company size, profitability and the size of auditor, have influenced the level of corporate disclosure in annual reports of domestic and foreign share‐based companies. Ownership structure has positive impact on the level of disclosure for companies with domestic investors.

This study advances knowledge of the influence that legislative circumstances and ownership structures can have on disclosure decisions made by management in their annual reports. This information is of high interest to domestic and foreign investors and regulators in understanding of financial reporting in Chinese listed companies.