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The safety and reliability of high-speed trains rely on the structural integrity of their components and the dynamic performance of the entire vehicle system. This paper aims to define and substantiate the assessment of the structural integrity and dynamical integrity of high-speed trains in both theory and practice. The key principles and approaches will be proposed, and their applications to high-speed trains in China will be presented.

First, the structural integrity and dynamical integrity of high-speed trains are defined, and their relationship is introduced. Then, the principles for assessing the structural integrity of structural and dynamical components are presented and practical examples of gearboxes and dampers are provided. Finally, the principles and approaches for assessing the dynamical integrity of high-speed trains are presented and a novel operational assessment method is further presented.

Vehicle system dynamics is the core of the proposed framework that provides the loads and vibrations on train components and the dynamic performance of the entire vehicle system. For assessing the structural integrity of structural components, an open-loop analysis considering both normal and abnormal vehicle conditions is needed. For assessing the structural integrity of dynamical components, a closed-loop analysis involving the influence of wear and degradation on vehicle system dynamics is needed. The analysis of vehicle system dynamics should follow the principles of complete objects, conditions and indices. Numerical, experimental and operational approaches should be combined to achieve effective assessments.

The practical applications demonstrate that assessing the structural integrity and dynamical integrity of high-speed trains can support better control of critical defects, better lifespan management of train components and better maintenance decision-making for high-speed trains.

This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the continuous development of various technologies for autonomous vehicles, the LIDAR-based Simultaneous localization and mapping (SLAM) system is becoming increasingly important. However, in SLAM systems, effectively addressing the challenges of point cloud degradation scenarios is essential for accurate localization and mapping, with dynamic obstacle removal being a key component.

This paper proposes a method that combines adaptive feature extraction and loop closure detection algorithms to address this challenge. In the SLAM system, the ground point cloud and non-ground point cloud are separated to reduce the impact of noise. And based on the cylindrical projection image of the point cloud, the intensity features are adaptively extracted, the degradation direction is determined by the degradation factor and the intensity features are matched with the map to correct the degraded pose. Moreover, through the difference in raster distribution of the point clouds before and after two frames in the loop process, the dynamic point clouds are identified and removed, and the map is updated.

Experimental results show that the method has good performance. The absolute displacement accuracy of the laser odometer is improved by 27.1%, the relative displacement accuracy is improved by 33.5% and the relative angle accuracy is improved by 23.8% after using the adaptive intensity feature extraction method. The position error is reduced by 30% after removing the dynamic target.

Compared with LiDAR odometry and mapping algorithm, the method has greater robustness and accuracy in mapping and localization.

Petroleum hydrocarbons are naturally occurring flammable fossil fuels used as conventional energy sources. It has carcinogenic, mutagenic properties and is considered a hazardous pollutant. Soil contaminated with petroleum hydrocarbons adversely affects the properties of soil. This paper aim to remove pollutants from the environment is an urgent need of the hour to maintain the proper functioning of soil ecosystems.

The ability of micro-organisms to degrade petroleum hydrocarbons makes it possible to use these microorganisms to clean the environment from petroleum pollution. For preparing this review, research papers and review articles related to petroleum hydrocarbons degradation by micro-organisms were collected from journals and various search engines.

Various physical and chemical methods are used for remediation of petroleum hydrocarbons contaminants. However, these methods have several disadvantages. This paper will discuss a novel understanding of petroleum hydrocarbons degradation and how micro-organisms help in petroleum-contaminated soil restoration. Bioremediation is recognized as the most environment-friendly technique for remediation. The research studies demonstrated that bacterial consortium have high biodegradation rate of petroleum hydrocarbons ranging from 83% to 89%.

Proper management of petroleum hydrocarbons pollutants from the environment is necessary because of their toxicity effects on human and environmental health.

This paper discussed novel mechanisms adopted by bacteria for biodegradation of petroleum hydrocarbons, aerobic and anaerobic biodegradation pathways, genes and enzymes involved in petroleum hydrocarbons biodegradation.

This paper aims to identify the different system approach using Building Information Modelling (BIM) technology that is equipped with decision making processes. Maintenance planning and management are integral components of the construction sector, serving the broader purpose of post-construction activities and processes. However, as Precast Concrete (PC) construction projects increase in scale and complexity, the interconnections among these activities and processes become apparent, leading to planning and performance management challenges. These challenges specifically affect the monitoring of façade components for corrective and preventive maintenance actions.

The concept of maintenance planning for façades, along with the main features of information and communication technology tools and techniques using building information modeling technology, is grounded in the analysis of numerous literature reviews in PC building scenarios.

This research focuses on an integrated system designed to analyze information and support decision-making in maintenance planning for PC buildings. It is based on robust data collection regarding concrete façades' failures and causes. The system aims to provide appropriate planning decisions and minimize the risk of façade failures throughout the building's lifetime.

The study concludes that implementing a research framework to develop such a system can significantly enhance the effectiveness of maintenance planning for façade design, construction and maintenance operations.

This study aims to investigate the viewpoints of heterodox economic thoughts and Islamic economic thought concerning the concept of waste. Additionally, it explores the shared criticisms that both perspectives hold against mainstream economic thought in relation to waste.

First of all, the concept of waste is examined and the global effects of waste are investigated. Criticisms directed in the context of waste in mainstream economics in the context of heterodox school thoughts are examined. Likewise, criticisms directed in the context of waste in mainstream economics in the context of Islamic economic thoughts are examined. Finally, the common and different aspects of heterodox and Islamic economic thoughts were discussed, and the common criticisms of mainstream economic thought’s point of view toward waste were examined. This study is a theoretical, qualitative study.

Although both ideas have different aspects, heterodox and Islamic economic thoughts believe that the mainstream economy, which is based on capitalism and materialism, creates waste by ignoring the long-term social and environmental consequences of economic activity. They argue that the pursuit of profits and growth, without considering the impact on society and the environment, leads to an inefficient and unsustainable use of resources.

The best author’s knowledge, by emphasizing the common and different aspects of Islamic economics and heterodox thoughts, this study is the first to examine the concept of waste in the context of the common aspects of these ideas.

Accurate prediction of the structural condition of urban critical infrastructure is crucial for predictive maintenance. However, the existing prediction methods lack precision due to limitations in utilizing heterogeneous sensing data and domain knowledge as well as insufficient generalizability resulting from limited data samples. This paper integrates implicit and qualitative expert knowledge into quantifiable values in tunnel condition assessment and proposes a tunnel structure prediction algorithm that augments a state-of-the-art attention-based long short-term memory (LSTM) model with expert rating knowledge to achieve robust prediction results to reasonably allocate maintenance resources.

Through formalizing domain experts' knowledge into quantitative tunnel condition index (TCI) with analytic hierarchy process (AHP), a fusion approach using sequence smoothing and sliding time window techniques is applied to the TCI and time-series sensing data. By incorporating both sensing data and expert ratings, an attention-based LSTM model is developed to improve prediction accuracy and reduce the uncertainty of structural influencing factors.

The empirical experiment in Dalian Road Tunnel in Shanghai, China showcases the effectiveness of the proposed method, which can comprehensively evaluate the tunnel structure condition and significantly improve prediction performance.

This study proposes a novel structure condition prediction algorithm that augments a state-of-the-art attention-based LSTM model with expert rating knowledge for robust prediction of structure condition of complex projects.

Due to the rapid increase in environmental degradation and depletion of natural resources, there has been a recent shift in global focus from economic concerns to environmental ones. The purpose of this research is to examine the relevant literature on the use of blockchain technology to promote environmental sustainability through customer integration.

The proposed framework is based on the theoretical lens of systems theory (ST) and knowledge-based view (KBV) theory, and is developed by conducting a systematic literature review of 51 articles, (16) from 2022, (17) from 2021, (10) 2020, (5) 2019, (2) 2018 and (1) from 2017 on blockchain technology (BCT), environmental supply chain performance (ESCP) and customer integration.

Three main propositions are formulated and demonstrated using the developed framework, which shows that BCT has the potential to revolutionize the supply chain from an environmental sustainability perspective through facilitating waste management, reduction of energy consumption and reduction of carbon emissions/pollution. The technology will not only enhance the environmental sustainability but also facilitate customer integration through resolving transparency issues, protecting data/enhancing security, database decentralization, promoting trust and immutability.

The effects of blockchain on supply chain performance has been studied in the past; however, no studies were found which shed light on how BCT can affect ESCP through the mediation of customer integration.

Purpose: The availability of resilient energy infrastructure and services is crucial to achieving sustainable development goals. However, defined and trustworthy definitions of resilience exist solely for engineering and energy systems, particularly in the industrialised world or metropolitan systems. However, no universally accepted definition considers the distinctive characteristics of rural regions in developing economies. To define resilience for rural power systems in developing countries, this chapter synthesises many perspectives on resilience, energy systems, and rural environments.

Methodology: It draws on extensive literature assessments on resilience, particularly concerning energy systems and rural areas, as well as other pre-existing frameworks.

Findings: To account for the unique challenges of electricity supply in rural developing nations, a comprehensive ‘Rural Power System Resilience Framework’ is introduced, including technical, economic, and social resilience.

Social implications: To better understand the elements contributing to the stability of electricity grids in developing nations and rural areas, this resilience framework may be utilised by global markets, system owners and operators, government officials, non-governmental organisations, and communities.

Originality: Through establishing this framework, this study sets the path for developing suitable and ‘effective resilience standards’ tailored for implementation in these rural areas, with the ultimate goal of facilitating the fulfilment of achieving domestic and worldwide sustainability objectives.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

Food systems research is typically focused on productivity and efficiency. But in the face of impending challenges of climate, investment, markets, and incomes small holders may do well to shift to diversity and sufficiency. The transition requires institutions such as Farmer Producer Organisations (FPOs) to play the role of intermediaries. This paper aims to understand this challenging phenomenon using a case from India.

In this article, drawing from the emerging literature of PO as a sustainability transition intermediary, this paper uses the case study of a women-owned FPO and explores its role in contributing to sustainable food systems through practices of non-pesticide management of agriculture. This paper explores, through non-participant observer methods, focus group discussions and interviews with multiple stakeholders how an FPO embeds sustainability in its purpose and the challenges faced in transforming producer and consumers towards sustainable food systems.

The study argues for early articulation of the “sustainability transition intermediary” role in the FPO’s vision and mission. Second, FPOs’ role of being a transition intermediary is impacted by the key stakeholders and the durability of relationship with them.

By studying FPOs in India, from the framework of sustainability transitions, this article adds to the limited literature that looks as POs as sustainability transition intermediaries.