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Nucleic acid testing is an effective method of accurate prevention and control and a key measure to block the spread of the epidemic. However, the fraud in nucleic acid testing occurred frequently during epidemics. This paper aims to provide a viable scheme for the government to strengthen the supervision of nucleic acid testing and to provide a new condition for the punishment for the negative act of the government and the upper limit of the reward for nucleic acid testing institution of no data fraud.

This paper formulates an evolutionary game model between the government and nucleic acid testing institution under four different mechanisms of reward and punishment to solve the issue of nucleic acid testing supervision. The authors discuss the stability of equilibrium points under the four distinct strategies and conduct simulation experiments.

The authors find that the strategy of dynamic reward and static penalty outperforms the strategies of static reward and static penalty, dynamic reward and static penalty, static reward and dynamic penalty, dynamic reward and dynamic penalty. The results reveal the appropriate punishment for the negative act of the government can enhance the positivity of the government's supervision in the strategy of dynamic reward and static penalty, while the upper limit of the reward for nucleic acid testing institution of no data fraud cannot be too high. Otherwise, it will backfire. Another interesting and counterintuitive result is that in the strategy of dynamic reward and dynamic penalty, the upper limit of the penalty for data fraud of nucleic acid testing institution cannot be augmented recklessly. Otherwise, it will diminish the government's positivity for supervision.

Most of the existing evolutionary game researches related to the reward and punishment mechanism and data fraud merely highlight that increasing the intensity of reward and punishment can help improve the government's supervision initiative and can minimize data fraud of nucleic acid institution, but they fall short of the boundary conditions for the punishment and reward mechanism. Previous literature only study the supervision of nucleic acid testing qualitatively and lacks quantitative research. Moreover, they do not depict the problem scenario of testing data fraud of nucleic acid institution regulated by the government via the evolutionary game model. Thus, this study effectively bridges these gaps. This research is universal and can be extended to other industries.

The purpose of this paper is to propose a debt rating index system for small industrial enterprises that significantly distinguishes the default state. This debt rating system is constructed using the F-test and correlation analysis method, with the small industrial enterprise loans of a Chinese commercial bank as the data sample. This study establishes the weighting principle for the debt scoring model: “the more significant the default state, the larger is the weight.” The debt rating system for small industrial enterprises is constructed based on the standard “the higher the debt rating, the lower is the loss given default.”

In this study, the authors selected indexes that pass the homogeneity of variance test based on the principle that a greater deviation of the default sample’s mean from the whole sample’s mean leads to greater significance in distinguishing the default samples from the non-default samples. The authors removed correlated indexes based on the results of the correlation analysis and constructed a debt rating index system for small industrial enterprises that included 23 indexes.

Among the 23 indexes, the weights of 12 quantitative indexes add up to 0.547, while the weights of the remaining 11 qualitative indexes add up to 0.453. That is, in the debt rating of the small industry enterprises, the financial indexes are not capable of reflecting all the debt situations, and the qualitative indexes play a more important role in debt rating. The weights of indexes “X17 Outstanding loans to all assets ratio” and “X59 Date of the enterprise establishment” are 0.146 and 0.133, respectively; both these are greater than 0.1, and the indexes are ranked first and second, respectively. The weights of indexes “X6 EBIT-to- current liabilities ratio,” “X13 Ratio of capital to fixed” and “X78 Legal dispute number” are between 0.07 and 0.09, these indexes are ranked third to fifth. The weights of indexes “X3 Quick ratio” and “X50 Per capital year-end savings balance of Urban and rural residents” are both 0.013, and these are the lowest ranked indexes.

The data of index i are divided into two categories: default and non-default. A greater deviation in the mean of the default sample from that of the whole sample leads to greater deviation from the non-default sample’s mean as well; thus, the index can easily distinguish the default and the non-default samples. Following this line of thought, the authors select indexes that pass the F-test for the debt rating system that identifies whether or not the sample is default. This avoids the disadvantages of the existing research in which the standard for selecting the index has nothing to do with the default state; further, this presents a new way of debt rating. When the correlation coefficient of two indexes is greater than 0.8, the index with the smaller F-value is removed because of its weaker prediction capacity. This avoids the mistake of eliminating an index that has strong ability to distinguish default and non-default samples. The greater the deviation of the default sample’s mean from the whole sample’s mean, the greater is the capability of the index to distinguish the default state. According to this rule, the authors assign a larger weight to the index that exhibits the ability to identify the default state. This is different from the existing index system, which does not take into account the ability to identify the default state.

With the popularity of high-rise buildings, wall inspection and cleaning are becoming more difficult and associated with danger. The best solution is to replace manual work with wall-climbing robots. Therefore, this paper proposes a design method for a rolling-adsorption wall-climbing robot (RWCR) based on vacuum negative pressure adsorption of the crawler. It can improve the operation efficiency while solving the safety problems.

The pulleys and tracks are used to form a dynamic sealing chamber to improve the dynamic adsorption effect and motion flexibility of the RWCR. The mapping relationship between the critical minimum adsorption force required for RWCR downward slip, longitudinal tipping and lateral overturning conditions for tipping and the wall inclination angle is calculated using the ultimate force method. The pressure and gas flow rate distribution of the negative pressure chamber under different slit heights of the negative pressure mechanism is analysed by the fluid dynamics software to derive the minimum negative pressure value that the fan needs to provide.

Simulation and test results show that the load capacity of the RWCR can reach up to 6.2 kg on the smooth glass wall, and the maximum load in the case of lateral movement is 4.2 kg, which verifies the rationality and effectiveness of the design.

This paper presents a new design method of a RWCR for different rough wall surfaces and analyses the ultimate force state and hydrodynamic characteristics.

The uniformity of electrodeposition is the key to successful application of pattern plating because the quality of electrodeposited copper layer has a huge impact on the performance of printed circuit boards (PCBs). The multi-physics coupling technology was used to accurately analyze and forecast the characteristics of electrochemical system. Further, an optimized plating bath was used to achieve a uniform electrodeposition.

A multi-physics coupling numerical simulation based on the finite element method was used to optimize electrodeposition conditions in pattern plating process. The influences of geometric and electrochemical factors on uniformity of current distribution and electrodeposited layer thickness were discussed by multi-physics coupling.

The model results showed that the distance between cathode and anode and the insulating shield had a great impact on uniformity of electrodeposition. By numerical simulation, it had been proved that using an auxiliary cathode was an effective and simple way to improve uniformity of electrodeposition due to redistributing of the current. This helped to achieve more uniform surface of the copper patterns by preventing the edge effect and the roughness of the copper layer was reduced to 1 per cent in the secondary current distribution model.

The research is still in progress with the development of high-performance computers.

A multi-physics coupling platform is an excellent tool for quickly and cheaply studying the process behaviors under a variety of operating conditions.

The numerical simulation method has laid the foundation for the design and improvement of the plating bath.

By multi-physics coupling technology, we built a bridge between theoretical and experimental study for control of uniformity of pattern plating in PCB manufacturing. This method can help optimize the design of plating bath and uniformity of pattern plating in PCB manufacturing.

This research aims to propose a comparative environmental analysis of conventional and prefabricated construction techniques utilizing a building information modelling (BIM) technique.

A set of indicators are selected to assess the environmental emissions throughout the construction life cycle, based on BIM platform. An existing project involving ten apartment buildings in Shanghai is selected as a case study.

The results reveal that prefabricated construction demonstrates environment-friendly performance with some exceptions of acidification and mineral resource consumption. Environmental impacts can also be further reduced by increasing the projected area ratio and percentage of project prefabrication.

Overall, the proposed method can be used to identify relevant environmental merits and for decision-making of appropriate construction techniques in building construction projects.

To examine the nature of Chinese business negotiating style in Sino‐Western business negotiations in business‐to‐business markets involving large industrial projects from a social cultural point of view.

A conceptual approach developed from personal interviews.

This study reveals that the Chinese negotiator does not possess an absolute negotiating style but rather embraces a mixture of different roles together: “Maoist bureaucrat in learning”, “Confucian gentleman”, and “Sun Tzu‐like strategist”. The Chinese negotiating strategy is essentially a combination of cooperation and competition (termed as the “coop‐comp” negotiation strategy in this study). Trust is the ultimate indicator of Chinese negotiating propensities and role choices.

The focus of this study is on Chinese negotiating style shown in large B2B negotiations with Chinese SOEs.

Differing from most other studies on Chinese negotiating style which tend to depict the Chinese negotiator as either sincere or deceptive, this study points out that there exists an intrinsic paradox in Chinese negotiating style which reflects the Yin Yang thinking. The Chinese negotiator has a cultural capacity to negotiate both sincerely and deceptively and he/she changes coping strategies according to situation and context, all depending on the level of trust between negotiating partners.

The purpose of this paper was to synthesise a thermally expandable microsphere (TEMS) with fast thermal response property and small expansion temperature range, and investigate the factors affecting the expansion properties of the microspheres.

A new kind of TEMS with fast thermal response property was synthesised by suspension polymerisation method, using acrylonitrile, ethyl methacrylate and methacrylic acid as the main monomers; Mg(OH)₂ as the main dispersing agent; and isooctane or n-hexane or n-pentane as the blowing agent.

The TEMS possessed the best expansion capacity when encapsulated isooctane and n-hexane were about 18.5 Wt.%. The expansion process of the TEMS could be finished by raising the temperature to 18°C from the expansion onset, much less than the reported 30-50°C. The morphology of the TEMS turned from sphere to irregular concave shape following the content increase of the blowing agent.

A new kind of TEMS composed of acrylonitrile/ethyl methacrylate/methacrylic acid as the polymer shell was synthesised. These TEMS showed the fastest thermal response speed reported.

The purpose of this paper is to propose a hybrid decision-making model for optimizing the initial design strategies of pre-sales housing, identifying factors affecting the initial design of housing, and developing different initial design approaches and strategies based on buyers’ preferences.

Indicators and factors in line with the local initial planning and design are created according to the design quality indicator framework. The important indicators and factors are screened out preliminarily with the fuzzy Delphi method and decision-making trial and evaluation laboratory based analytic network process. The performances of two actual cases under similar site conditions are checked with regard to the overall residential sales rate and time on the market (TOM).

The result shows that the proposed model can effectively improve the sales rate, shorten the TOM and better complies with buyer design strategy demands, and thus positively correlating to economic value.

Pre-sales make possible the customized strategy of allowing future residents to participate in the housing design process. However, buyers’ participation in the design process is highly limited, and developers usually determine their planning and initial residential design strategies based on experience and intuition. With the proposed approach, the initial residential design of a project can be effectively intervened, so that home users can truly participate in the design, and the residential construction service can be provided in a unique, but non-universal way.

The study aims to discuss how the attributes of Chinese tea beverage brands influence consumers' evaluations of brand positioning and the differences and competition among brands.

A perceptual map, developed using probabilistic discriminant analysis algorithms, depicts the relative position of each brand and illustrates their attractive properties. This statistical technique can enhance managers' ability to identify promising brand positions and enhance the overall brand design process.

The study finds that Chinese tea beverage brands pursue various goals, such as quenching thirst, attractive advertising, or reliable quality, to develop their positions. Brand positioning implies that consumers remember particular information conveyed by the brand. The study illustrates consumers' brand awareness attributes, potential market demand, and brand competition conditions.

Brand positioning, when linked with market segmentation, can yield effective guidelines for the design and coordination of a marketing strategy. The scope of this study, however, does not enable elaboration on segmented differences in product positioning.

The study provides a useful source of information for managers, who should introduce brands to the market carefully and deliberately and choose a position that is both appealing and sustainable over time.

The study provides a unique method to understand the current market structure and determine a target brand and its best competitive position.

Automatic segmentation of brain tumor from medical images is a challenging task because of tumor's uneven and irregular shapes. In this paper, the authors propose an attention-based nested segmentation network, named DAU-Net. In total, two types of attention mechanisms are introduced to make the U-Net network focus on the key feature regions. The proposed network has a deep supervised encoder–decoder architecture and a redesigned dense skip connection. DAU-Net introduces an attention mechanism between convolutional blocks so that the features extracted at different levels can be merged with a task-related selection.

In the coding layer, the authors designed a channel attention module. It marks the importance of each feature graph in the segmentation task. In the decoding layer, the authors designed a spatial attention module. It marks the importance of different regional features. And by fusing features at different scales in the same coding layer, the network can fully extract the detailed information of the original image and learn more tumor boundary information.

To verify the effectiveness of the DAU-Net, experiments were carried out on the BRATS 2018 brain tumor magnetic resonance imaging (MRI) database. The segmentation results show that the proposed method has a high accuracy, with a Dice similarity coefficient (DSC) of 89% in the complete tumor, which is an improvement of 8.04 and 4.02%, compared with fully convolutional network (FCN) and U-Net, respectively.

The experimental results show that the proposed method has good performance in the segmentation of brain tumors. The proposed method has potential clinical applicability.