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Based on the conceptual design of seismic resistance in buildings, this study aims to put forward a new construction structure energy-saving block structure with invisible multiribbed frame.

The structure is composed of energy-saving block wall panels with invisible multiribbed frames, lightweight partition wall plates and cast-in-place reinforced concrete floor slabs. The structure design is simple and the construction is convenient and fast. The comprehensive economic index of the structure is better than that of brick-and-concrete composite construction. The self-weight of the energy-saving blocks that make up the wall is only about 25% of that of solid clay bricks. The thermal insulation and energy-saving effects of the structure can meet the national energy-saving requirements of buildings.

This new structure meets the requirements of national technology and economy, wall deformation, thermal insulation and energy-saving, and can be used mainly for multistory and mid- to high-rise residential buildings. For the core components of the new structure energy-saving block and invisible multiribbed frame composite wall, as the axial compression ratio increases in the test parameters range, the peak bearing capacity and ductility of the wall increase and the initial stiffness of the wall decreases. The axial compression ratio has a significant effect on the energy dissipation capacity of the wall. The displacement ductility coefficients ν are all greater than 2, indicating the optimal seismic performance of the wall.

This structure is a new, economical, lightweight, energy-saving, seismic resistant, multistory and mid- to high-rise structure that fully conforms to national conditions.

The purpose of this paper is to explore the heterogeneity and correlations of agricultural greenhouse gas (GHG) emissions among provinces in China, and then policy implications are proposed.

After agricultural GHG accounting and a pre-analysis of inter-provincial heterogeneity, improved gravity model and the Social Network Analysis (SNA) methods are introduced to construct the network, being carried out from three aspects of the whole network, individual provincial characteristics and cluster analysis.

(1) There are significant regional variations in agricultural GHG scale among provinces owing to the layout of agricultural production, and the temporal trends show that the direction and speed of agricultural GHG scale change vary among provinces; (2) In terms of inter-provincial correlations, there exists a complex spatial network of agricultural GHG among provinces, which tends to be more complex, intensive and stable, while the status of the provinces in the network also has gradually become more balanced. All provinces played their respective roles in the four clusters of the network with agricultural layout and comparative advantages, and the distribution has continuously optimized.

The inter-provincial network characteristics of agricultural GHG emissions and its evolution have practical implications for differentiated and coordinated agricultural GHG reduction policies at the provincial levels.

This paper innovatively study inter-provincial agricultural GHG correlations in China with the SNA methods used to study economic and social connections in the past. There is some originality in the introduction of network theory and application of the SNA methods, which can provide some reference for researches in similar fields.

This paper aims to construct a spatio-temporal emotional framework (STEF) for digital humanities from a quantitative perspective, applying knowledge extraction and mining technology to promote innovation of humanities research paradigm and method.

The proposed STEF uses methods of information extraction, sentiment analysis and geographic information system to achieve knowledge extraction and mining. STEF integrates time, space and emotional elements to visualize the spatial and temporal evolution of emotions, which thus enriches the analytical paradigm in digital humanities.

The case study shows that STEF can effectively extract knowledge from unstructured texts in the field of Chinese Qing Dynasty novels. First, STEF introduces the knowledge extraction tools – MARKUS and DocuSky – to profile character entities and perform plots extraction. Second, STEF extracts the characters' emotional evolutionary trajectory from the temporal and spatial perspective. Finally, the study draws a spatio-temporal emotional path figure of the leading characters and integrates the corresponding plots to analyze the causes of emotion fluctuations.

The STEF is constructed based on the “spatio-temporal narrative theory” and “emotional narrative theory”. It is the first framework to integrate elements of time, space and emotion to analyze the emotional evolution trajectories of characters in novels. The execuability and operability of the framework is also verified with a case novel to suggest a new path for quantitative analysis of other novels.

This study aims to improve understanding of how coastal maritime transport system of Vancouver Island would be disrupted in disaster events, and the strategies could be used to address such risks. Any transport disruption at the maritime leg of the supply chain can affect the needs of vulnerable residents and thus, the supply of many goods to coastal communities.

This case study focuses on the disruption that can be expected to occur for ferries that serves coastal communities of Vancouver Island in Canada. A landslide scenario in the Fraser River (which connects coastal communities) is developed, and interviews and focus groups are used to gain understanding of the vulnerability and resilience of shipping.

The findings show that the maritime leg of the supply chain for the coastal communities of Vancouver Island is resilient to a landslide disruption of ferries. Besides, there would be no impact on the operability of tugs and barges. This study also offers suggestions for creating the conditions for increasing resilience of maritime supply chains to any such disruption.

A research gap exists with respect to minimizing disruption in maritime supply chains, mainly in regard to lessening the impact on the vulnerable residents of coastal communities. This study contributes to filling this gap in the literature.

The findings have significant implications for maritime service providers and for people working on disaster preparedness, emergency response and recovery.

Studies which focus on alleviating the impact of disruptions in the maritime supply chains and the mitigation strategies for coastal communities are scarce in the literature.

To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

The purpose of this paper is to develop an equation for the synergistic corrosion of SRB and CO₂ based on the D-W model.

The bacterial types in the a and ß pipelines were studied by the most probable number method, and the corrosion morphology of L360 in pipeline water samples was studied by surface analysis. The corrosion rate of L360 was studied using the weight loss method. The gray correlation method was used to calculate the degree of correlation between the influencing factors of corrosion under the synergistic effect of CO₂ and SRB. The curve obtained from PIPESIM software and experiments data was then fitted using multiple non-linear regression method by MATLAB software.

The equation was used to predict the corrosion of the ß pipeline for verification, and it was found that seven out of ten excavation sites were within a 20% error range.

Using the gray correlation method, an equation that considers synergistic corrosion of SRB and CO₂ has been developed based on the D-W model. The equation could be used to predict the corrosion rate of shale gas gathering pipelines through SRB and CO₂ synergistic corrosion.

The purpose of this paper is to implement the strategies selection process in a proposed formulated mathematical framework to prioritize selected strategies with the interaction of other groups of strategies, known as the strategies interaction model (SIM).

SWOT analysis is a popular useful strategic planning tool, which analyzes organizations internal and external factors. The traditional SWOT procedure lists internal and external factors and derives four groups of strategies based on the organization’s strategic position. SWOT is easy to use as a business analyzing tool, while it is not competent enough for strategic formulation. With the emergence of the economy’s vicissitudes, undulations in the markets and multiple changes, and various variables in the industrial competitive environment, selection of the organization strategies confront uncertainty in decision making. The SIM framework presents a solution to select alternative strategies for organizations in unpredictable situations.

The findings show that SIM is a reliable approach to evaluate, select and rank organization’ strategies. SIM proposes alternative strategies due to the uncertainty of the organization’ environment with respect to the four strategic positions. The SIM’ proposed ranking process is in accordance with the highest impact of each strategy on each other. Furthermore, it possesses advantages of AHP, ANP and other applied multiple criteria decision-making (MCDM) techniques in SWOT analysis.

In this paper SIM is applied within a dairy company located in the north of Iran.

SIM has the advantages of the classic SWOT and fills the gaps of MCDM methods application in the SWOT analysis. Moreover, it provides a formulated algorithm for the organizations to face the uncertainty of the environment. SIM philosophy can be widely used in the decision and managerial implications.

This paper aims to systematically expound the theory and development background of supply chain finance and blockchain, design a railway freight supply chain financial platform based on blockchain, determine the risk management system and business support system of supply chain finance business and analyze the value generated by the combination of supply chain finance business and blockchain.

Investigation and research method; Prototype method; Model method; Value analysis.

The business model integrating supply chain finance and blockchain technology will bring great changes to freight industry. The development of supply chain finance is beneficial to the healthy development of the core participants of railway freight transport business and its upstream and downstream ecosystems. It links commerce, logistics, warehousing and financial services together and builds an industry-integrated ecological service platform through information technology platform and supporting system, taking data as the basis and combining information technology such as blockchain as innovative means.

This paper will provide important reference value for related research. This paper innovatively designs the supply chain financial platform of freight transportation industry-integrating blockchain technology and analyzes its business model, technical system, risk management and control system and value system in detail, which will provide technical support for the innovative reform of freight information technology and realize the stable and high-speed development of freight logistics informationization.