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To address the problem that the current train operation mode that train selects one of several offline pre-generated control schemes before the departure and operates following the scheme after the departure, energy-saving performance of the whole metro system cannot be guaranteed.

A cooperative train control framework is formulated to regulate a novel train operation mode. The classic train four-phase control strategy is improved for generating specific energy-efficient control schemes for each train. An improved brute force (BF) algorithm with a two-layer searching idea is designed to solve the optimisation model of energy-efficient train control schemes.

Case studies on the actual metro line in Guangzhou, China verify the effectiveness of the proposed train control methods compared with four-phase control strategy under different kinds of train operation scenarios and calculation parameters. The verification on the computation efficiency as well as accuracy of the proposed algorithm indicates that it meets the requirement of online optimisation.

Most existing studies optimised energy-efficient train timetable or train control strategies through an offline process, which has a defect in coping with the disturbance or delays effectively and promptly during real-time train operation. This paper studies an online optimisation of cooperative train control based on the rolling optimisation idea, where energy-efficient train operation can be realised once train running time is determined, thus mitigating the impact of unpredictable operation situations on the energy-saving performance of trains.

Past studies show that companies’ connection with the government (or politically connected companies (PCCs)) contributed negatively to their financial performance. The grabbing hand theory suggests that political connection demand companies to serve political and social obligation that exhaust companies’ financial resources. The purpose of this paper is to extend the previous studies by examining the role of monitoring mechanisms, specifically corporate governance mechanism and institutional ownership (IO), whether they weaken or strengthen the financial performance of PCCs in Malaysia.

The sample consists of all companies listed on the Main Board of Bursa Malaysia (previously known as Kuala Lumpur Stock Exchange) for the year of 2004-2007. The time periods were chosen because there were no significant economic and political events that could possibly distorted the financial and non-financial data.

The findings show that companies’ political connection (the presence of political figure or government representative as members of board of director) has consistently showing negative relationship with performance. The result is consistent with the grabbing hand theory that argues that companies’ connection with government would actually destroy companies’ value. The monitoring role of corporate governance as measured by the percentage of independent board members does not have any significant effect on firm’s performance. The monitoring role of corporate governance as measured by the composition of independent board members have shown a positive significant effect on the company’s performance. However the second monitoring mechanism, the percentage of institutional investors, have a tendency to weaken the company’s performance.

The findings of this study provide an additional understanding of the consequence of government intervention on companies’ performance. This study also highlights the role of monitoring mechanism (independence board members and IO) in strengthening or weakening the performance. The findings suggest that the proper appointment criteria for board members should be seriously considered to ensure better corporate governance structure. Therefore, the formation of the nomination committee as suggested by the current Malaysian Code of Corporate Governance play an important contribution to ensure candidates nominated as board members have proper credentials and qualifications to carry out responsibilities as board members.

This paper develops a debt-run model to study the effects of liquidity injections on debt markets in the presence of a renegotiation option. In the model, creditors decide when to withdraw their funding and equityholders can renegotiate the contract terms of debt. We show that when equityholders have a large bargaining power, liquidity injections into distressed firms can rather cause more aggressive runs from their creditors, hurting the debt value. This outcome occurs because equityholders can strategically utilize the renegotiation option as a bankruptcy threat, pushing down the debt value below the potential liquidation value of the firm. In such a scenario, a deterred default resulting from emergency capital injections could be detrimental to creditors.

Simulation-based optimisation (SO) is a popular optimisation approach for building and civil engineering construction planning. However, in the framework of SO, the simulation is continuously invoked during the optimisation trajectory, which increases the computational loads to levels unrealistic for timely construction decisions. Modification on the optimisation settings such as reducing searching ability is a popular method to address this challenge, but the quality measurement of the obtained optimal decisions, also termed as optimisation quality, is also reduced by this setting. Therefore, this study aims to develop an optimisation approach for construction planning that reduces the high computational loads of SO and provides reliable optimisation quality simultaneously.

This study proposes the optimisation approach by modifying the SO framework through establishing an embedded connection between simulation and optimisation technologies. This approach reduces the computational loads and ensures the optimisation quality associated with the conventional SO approach by accurately learning the knowledge from construction simulations using embedded ensemble learning algorithms, which automatically provides efficient and reliable fitness evaluations for optimisation iterations.

A large-scale project application shows that the proposed approach was able to reduce computational loads of SO by approximately 90%. Meanwhile, the proposed approach outperformed SO in terms of optimisation quality when the optimisation has limited searching ability.

The core contribution of this research is to provide an innovative method that improves efficiency and ensures effectiveness, simultaneously, of the well-known SO approach in construction applications. The proposed method is an alternative approach to SO that can run on standard computing platforms and support nearly real-time construction on-site decision-making.

The purpose of this paper is to examine key macroeconomic determinants on Cameroon's economic growth from 1970 to 2018.

Data were obtained from the World Development Indicators and applied on time series data econometric techniques. The auto-regressive distributed lag (ARDL) bounds model analyzed the data since the variables had different order of integration.

The results showed long and short runs’ positive and significant connection between economic growth in Cameroon and government expenditure; trade openness, gross capital formation and exchange rate. Human capital development, foreign aid, money supply, inflation and foreign direct investment negatively and significantly affected economic growth in the short and long-runs. Hence, the macroeconomic indicators are not death.

The present research paper has tried to capture the impact of nine macroeconomic determinants on economic growth such as the government expenditure (LNGOVEXP), human capital development (LNHCD), foreign aids (AID), trade openness (LNTOP), foreign direct investment (LNFDI), gross capital formation (INVEST), broad money (LNM2), official exchange rate (LNEXHRATE) and Inflation (LNINFLA). However, these variables have the tendency to affect each other in a unidirectional or bidirectional manner. Further, the present research paper is unable to capture the impact of other macroeconomic variable due to the unavailability of data.

The study recommends that Cameroon should use proper planning and strategic policy interventions to achieve higher sustainable economic growth with human capital development, foreign aid, money supply, foreign direct investment and moderate inflation.

Macroeconomic indicators, if managed well, increase economic growth.

This paper to the best of the researcher's knowledge presents new background information to both policymakers and researchers on the main macroeconomic determinants using econometric analysis.

The purpose of this paper is to study the unit train make-up scheme for loaded direction in the heavy haul railway.

A 0-1 nonlinear integer programming model with the aim of minimizing the idling period between actual train arrival time and expected train arrival time for all loaded unit trains are proposed.

The proposed model is applied into a case study based on Daqin heavy haul railway. Results show that the proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

The proposed model can offer operators an optimal unit train make-up scheme for loaded direction in heavy haul railway.

This paper aims to provide decision support for precast concrete contractors about both precast concrete supply chain strategies and construction configurations.

This paper proposes a simulation-based optimisation for supply chain and construction (SOSC) during the planning phase of PC building projects. The discrete event simulation is used to capture the characteristics of supply chain and construction processes, and calculate construction objectives under different plans. Particle swarm optimisation is combined with simulation to find optimal supply chain strategies and construction configurations.

The efficiency of SOSC is compared with the parametric simulation approach. Over 70 per cent of time and effort used to simulate and compare alternative plans is saved owing to SOSC.

Building simulation model costs a lot of time and effort. The data requirement of the proposed method is high.

The proposed SOSC approach can provide decision support for PC contractors by optimising supply chain strategies and construction configurations.

This paper has two contributions: one is in providing a decision support tool SOSC to optimise both supply chain strategies and construction configurations, while the other is in building a prototype of SOSC and testing it in a case study.

The application of smart contract can greatly reduce transaction costs and improve transaction efficiency. The existing smart contract are expensive, single application scenario and inefficient. This paper aims to propose a new smart contract model to solve these problems.

By investigating the research history, models and platforms, this paper summarizes the shortcomings of existing smart contracts. Based on the content and architecture of traditional contract, a smart contract model with wider application scope is designed.

In this paper, several models are used to describe the operation mechanism of smart contracts. To facilitate computer execution, a decomposition method is proposed, which divides smart contracts into several sub-contracts. Then, the advantages and deployment methods of smart contract are discussed. On this basis, a specific example is given to illustrate how the application of smart contract will change our life.

Smart contract is gradually applied to more fields. In this paper, the structure and operation mechanism of smart contract system in reality are given, which will be beneficial to the application of smart contract to more complex systems.

Soil nutrient management and fertilizer use by farmers are important for sustainable grain production. The authors examined the effect of an experimental agricultural extension program, the science and technology backyard, in promoting sustainable soil nutrient management in the North China Plain (NCP). The science and technology backyard integrates farmer field schools, field demonstrations, and case-to-case counselling to promote sustainable farming practices among rural smallholders.

The authors conducted a large-scale household survey of more than 2,000 rural smallholders. The authors used a multivariate regression analysis as the benchmark to assess the effect of the science-and-technology backyard on smallholder soil nutrient management. Furthermore, the authors used coarse exact matching (CEM) methods to control for potential bias due to self-selection and the (endogenous) switching regression approach as the main empirical analysis.

The results show that the science-and-technology backyard program increased smallholders' wheat yield by approximately 0.23 standard deviation; however, no significant increase in maize yield was observed. Regarding soil nutrient use efficiency, the authors found a significant improvement in smallholders' phosphorus and potassium use efficiencies for both wheat and maize production, and a significant improvement in nitrogen use efficiency for wheat production, but no significant improvement of nitrogen use efficiency for maize production.

This study evaluated a novel participatory agricultural extension model to improve soil nutrient management practices among smallholders. The integration of agronomists' scientific knowledge and smallholders' local contextual experiences could be an effective way to improve farmers' soil nutrient management. This study provides the first quantitative estimates based on rigorous impact assessment methods of this novel extension approach in rural China.

The author analyzes households' inflation expectations data for India, collected quarterly by the RBI for more than a decade. The contribution of this paper lies in two folds. First, this study examines the relationship between relatively recent inflation expectations survey of households (IESH) and the actual inflation for India. Secondly, the author employs a structural VAR with the time period 2006 Q2 to 2020 Q2 on inflation expectation survey data of India. A short-term non-recursive restriction is imposed in the model in order to capture the simultaneous co-dependence causal effect of inflation expectation and realized inflation.

This paper studies the dynamic behavior of inflation expectations survey data in two folds. First, the author analyzes the time series property of the survey data. The author begins with testing the stationarity property of the series, followed by the casual relationship between the expected and actual inflation. The author further examines the short-run and long-run behavior of the IESH with actual inflation. Employing autoregressive distributed lag and Johansen co-integration, the author tested if a long-run relationship exists between the variables. In the second approach, the author investigates the determinants of inflation expectations by employing a non-recursive SVAR model.

The preliminary explanatory test reveals that inflation expectation is a policy variable and should be used in monetary policy as an instrument variable. The model identifies the price puzzle for India. The author finds that the response of inflation to a monetary policy shock is neutral. The results also indicate that the expectations of the general public are self-fulfilling.

IESH has only commenced from September 2005, hence is relatively new as compared to other survey in developed countries. Being a new data set so far, the author could not locate any study devoted in analyzing the behavior of the data with other macroeconomic variables.