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Distributed photovoltaic (DPV) projects generally have output risks, and the production effort of the supplier is often private information, so the buyer needs to design the optimal procurement contract to maximise its procurement utility.

Based on the principal-agent theory, we design optimal procurement contracts for DPV projects with fixed payments and incentive factors under three situations, i.e. symmetry information, asymmetry information without monitoring and asymmetry information with monitoring. We obtain the optimal production effort and expected utility of the supplier, the expected output and expected utility of the buyer and analyse the value of the information and monitoring.

The results show that under asymmetric information without monitoring, risk-averse suppliers need to take some risk due to output risk, which reduces the optimal production effort of the supplier and the expected output and expected utility of the buyer. Therefore, when the monitoring cost is below a certain threshold value, the buyer can introduce a procurement contract with monitoring to address the asymmetry information. In addition, under asymmetric information without monitoring, the buyer should choose a supplier with a low-risk aversion.

Considering the output risk of DPV projects, we study the optimal procurement contract design for the buyer under asymmetric information. The results provide some theoretical basis and management insights for the buyer to design optimal procurement contracts in different situations.

Wire and arc additive manufacturing (WAAM) technology-based cold metal transfer (CMT) to produce large aluminum alloy parts has become more and more popular. In WAAM, wire is the only raw material. The purpose of this paper is to study the effect of wire composition on the microstructure and properties of the ZAlCu5MnCdVA alloy deposited by WAAM.

Two thin-walled ZAlCu5MnCdVA alloys with different wire compositions were prepared by WAAM. The copper contents were 4.7% (Al-4.7Cu) and 5.0% (Al-5.0Cu), respectively. The microstructure, element distribution and evolution of precipitated phases of the two samples were characterized and analyzed by optical microscopy, scanning electron microscopy and transmission electron microscopy. Hardness and tensile properties of samples were tested, and strengthening mechanism was analyzed in detail.

The results show that grain sizes of Al-4.7Cu and Al-5.0Cu are less than 40 μm. The average mass fraction of Cu in Al matrix and the number of nanometer scale θ'' and θ' phases are the main factors affecting the tensile properties of Al-Cu alloy. Tensile properties of two materials show different characteristics at room temperature and high temperature. Al-5.0Cu is better at room temperature and Al-4.7Cu is better at high temperature. The yield strength (YS), ultimate tensile strength (UTS) and elongation in the x direction of Al-5.0Cu at room temperature are 451 ± 10.2 MPa, 486 ± 10.2 MPa and 9 ± 0.5%, respectively. The YS, UTS and elongation in the x direction of Al-4.7Cu at high temperature are 290 ± 4.5 MPa, 356 ± 7.0 MPa and 13% ± 0.2%, respectively.

Experiments show that the increase of Cu element can improve the properties at room temperature of the ZAlCu5MnCdVA alloy by WAAM, but its properties at high temperature decrease.

This method will become a new development trend in subgrade structure design for high speed railways.

This paper summarizes the structural types and design methods of subgrade bed for high speed railways in China, Japan, France, Germany, the United States and other countries based on the study and analysis of existing literature and combined with the research results and practices of high speed railway subgrade engineering at home and abroad.

It is found that in foreign countries, the layered reinforced structure is generally adopted for the subgrade bed of high speed railways, and the unified double-layer or multi-layer structure is adopted for the surface layer of subgrade bed, while the simple structure is adopted in China; in foreign countries, different inspection parameters are adopted to evaluate the compaction state of fillers according to their respective understanding and practice, while in China, compaction coefficient, subsoil coefficient and dynamic deformation modulus are adopted for such evaluation; in foreign countries, the subgrade top deformation control method, the subgrade bottom deformation control method, the subsurface fill strength control method are mainly adopted in subgrade bed structure design of high speed railways, while in China, dynamic deformation control of subgrade surface and dynamic strain control of subgrade bed bottom layer is adopted in the design. However, the cumulative deformation of subgrade caused by train cyclic vibration load is not considered in the existing design methods.

This paper introduces a new subgrade structure design method based on whole-process dynamics analysis that meets subgrade functional requirements and is established on the basis of the existing research at home and abroad on prediction methods for cumulative deformation of subgrade soil.

This paper aims to anticipate the possible development direction of WAAM. For large-scale and complex components, the material loss and cycle time of wire arc additive manufacturing (WAAM) are lower than those of conventional manufacturing. However, the high-precision WAAM currently requires longer cycle times for correcting dimensional errors. Therefore, new technologies need to be developed to achieve high-precision and high-efficiency WAAM.

This paper analyses the innovations in high-precision WAAM in the past five years from a mechanistic point of view.

Controlling heat to improve precision is an effective method. Methods of heat control include reducing the amount of heat entering the deposited interlayer or transferring the accumulated heat out of the interlayer in time. Based on this, an effective and highly precise WAAM is achievable in combination with multi-scale sensors and a complete expert system.

Therefore, a development direction for intelligent WAAM is proposed. Using the optimised process parameters based on machine learning, adjusting the parameters according to the sensors’ in-process feedback, achieving heat control and high precision manufacturing.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

Indochina has undergone tremendous change in the past decade to achieve good economic performance. However, the continuation of this strong economic performance depends on an efficient logistics infrastructure. Examines the region’s logistics realities. Specifically, the paper finds that the logistics infrastructure is still rather backward with inadequate transportation networks, inefficient customs procedures, and basic materials handling facilities. Based on this, proposals are made regarding some strategies for managers, MNCs and logistics providers who are keen to enter this emerging market.

Observing that people re‐access what they have seen or used in the past is very common in real lives. The purpose of this paper is to review the subject of information re‐finding comprehensively, and introduce to readers the underlying techniques and mechanisms used in information re‐finding.

After analyzing users' information re‐finding behaviors and their requirements, the paper studies the natural way of re‐finding in human memory, and reviews state‐of‐the‐art techniques and tools developed in the fields of web and personal information management for information re‐finding.

Four main re‐finding support techniques on the Web are: re‐finding tools in Web browsers; history service; re‐finding search engine; and voice‐based re‐finding. Three main re‐finding approaches are used in PIM: browse‐based approaches; content‐based search; and context‐based search.

Following the recalling mechanisms in human memory, the method of recall‐by‐context in both fields of web usage and personal information management can make users feel easy to re‐find information.

The paper gives a comprehensive overview of information re‐finding techniques.

Considering the small sample size and non-linear characteristics of historical energy consumption data from certain provinces in Southwest China, the authors propose a hybrid accumulation operator and a hybrid accumulation grey univariate model as a more accurate and reliable methodology for forecasting energy consumption. This method can provide valuable decision-making support for policy makers involved in energy management and planning.

The hybrid accumulation operator is proposed by linearly combining the fractional-order accumulation operator and the new information priority accumulation. The new operator is then used to build a new grey system model, named the hybrid accumulation grey model (HAGM). An optimization algorithm based on the JAYA optimizer is then designed to solve the non-linear parameters θ, r, and γ of the proposed model. Four different types of curves are used to verify the prediction performance of the model for data series with completely different trends. Finally, the prediction performance of the model is applied to forecast the total energy consumption of Southwest Provinces in China using the real world data sets from 2010 to 2020.

The proposed HAGM is a general formulation of existing grey system models, including the fractional-order accumulation and new information priority accumulation. Results from the validation cases and real-world cases on forecasting the total energy consumption of Southwest Provinces in China illustrate that the proposed model outperforms the other seven models based on different modelling methods.

The HAGM is used to forecast the total energy consumption of the Southwest Provinces of China from 2010 to 2020. The results indicate that the HAGM with HA has higher prediction accuracy and broader applicability than the seven comparative models, demonstrating its potential for use in the energy field.

The HAGM(1,1) is used to predict energy consumption of Southwest Provinces in China with the raw data from 2010 to 2020. The HAGM(1,1) with HA has higher prediction accuracy and wider applicability compared with some existing models, implying its high potential to be used in energy field.

Theoretically, this paper presents, for the first time, a hybrid accumulation grey univariate model based on a new hybrid accumulation operator. In terms of application, this work provides a new method for accurate forecasting of the total energy consumption for southwest provinces in China.

In urban planning, sustainability is closely linked to the quality of urban public spaces (UPS). However, some UPS encounter issues of low attractiveness and underutilisation. Vitality serves as a crucial measure in this context. The research perspective on the vitality of UPS centres on the balance between human activities and the built environment. Therefore, this article aims to systematically review critical aspects of UPS vitality evaluation system, including research objects, vitality components and research methods, from the dimensions of crowd activity and the built environment.

A systematic literature review using PRISMA analysed English-language publications from 2008 to 2023 in Scopus and Web of Science (WOS) databases, employing keywords related to UPS and vitality, with defined inclusion and exclusion criteria.

(1) Research objects, including parks, squares, waterfronts, blocks and streets. (2) The factors contributing to crowd activity characteristics originate from five dimensions, namely spatial, temporal, visitor, activity and feedback. Environmental factors, both external (accessibility, surrounding function mix and population density) and internal (service facility mix and water presence), significantly impact vitality. (3) The study primarily relies on quantitative data, including traditional surveys and emerging significant data sources like dynamic location and traffic, social media, geospatial and point of interest (POI) data. Data analysis methods commonly used include correlation analysis and comprehensive evaluation techniques.

The findings contribute to a comprehensive understanding of the vitality evaluation system for UPS from multiple perspectives for urban planners, aiding in identifying key factors and research methods in the vitality evaluation of various types of UPS.