Background
Text mining has become a useful tool for biologists trying to understand the genetics of diseases. In particular, it can help identify the most interesting candidate genes for a disease for further experimental analysis. Many text mining approaches have been introduced, but the effect of disease-gene identification varies in different text mining models. Thus, the idea of incorporating more text mining models may be beneficial to obtain more refined and accurate knowledge. However, how to effectively combine these models still remains a challenging question in machine learning. In particular, it is a non-trivial issue to guarantee that the integrated model performs better than the best individual model. 相似文献Background, aim, and scope
In spite of the increasing application of life cycle assessment (LCA) for engineering evaluation of systems and products, the application of LCA in the mining industry is limited. For example, a search in the Engineering Compendex database using the keywords “life cycle assessment” results in 2,257 results, but only 19 are related to the mining industry. Also, mining companies are increasingly adopting ISO 14001 certified environmental management systems (EMSs). A key requirement of ISO certified EMSs is continual improvement, which can be better managed with life cycle thinking. This paper presents a review of the current application of LCA in the mining industry. It discusses the current application, the issues, and challenges and makes relevant recommendations for new research to improve the current situation. 相似文献Purpose
The main purpose of this review is to investigate the methodology of social life cycle assessment (SLCA) through its application to case studies. In addition, the following research aims to define the trends related to the SLCA by researchers and consultants. This study will help to map the current situation and to highlight the hot spots and weaknesses of the application of the SLCA theory.Methods
The SLCA could be considered as a useful methodology to provide decision support in order to compare products and/or improve the social effects of the life cycle of a product. Furthermore, the results of the case studies analyzed may influence decision makers significantly. For this reason, a systematic literature review of case studies was carried out in which SLCA was applied in order to analyze closely the application of the stages of this methodology. In this study, the major phases of the technical framework for a SLCA were analyzed. Specific attention was paid to detect the positive impacts that emerged in the case studies, which were also studied by administering a questionnaire to the authors of the analyzed case studies and to a number of experts in the field of SLCA.Results and discussion
The 35 case studies examined in this paper, even though they do not deviate from the 40 identified by the previous processing, are still significantly different in terms of outcome produced. It is important to clarify that the authors who developed the case studies considered the steps defined in the SETAC/SETAC guidelines, borrowed from the ISO 14044 standard.Conclusions
The data resulting from this analysis could help both practitioners and researchers to understand what the issues are, on which it is still necessary to investigate and work, in order to solidify the SLCA methodology and define its role in the context of life cycle sustainability assessment (LCSA).Background
One of the most neglected areas of biomedical Text Mining (TM) is the development of systems based on carefully assessed user needs. We have recently investigated the user needs of an important task yet to be tackled by TM -- Cancer Risk Assessment (CRA). Here we take the first step towards the development of TM technology for the task: identifying and organizing the scientific evidence required for CRA in a taxonomy which is capable of supporting extensive data gathering from biomedical literature. 相似文献Life Cycle Assessment (LCA) is the process of systematically assessing impacts when there is an interaction between the environment and human activity. Machine learning (ML) with LCA methods can help contribute greatly to reducing impacts. The sheer number of input parameters and their uncertainties that contribute to the full life cycle make a broader application of ML complex and difficult to achieve. Hence a systems engineering approach should be taken to apply ML in isolation to aspects of the LCA. This study addresses the challenge of leveraging ML methods to deliver LCA solutions. The overarching hypothesis is that: LCA underpinned by ML methods and informed by dynamic data paves the way to more accurate LCA while supporting life cycle decision making.
MethodsIn this study, previous research on ML for LCA were considered, and a literature review was undertaken.
ResultsThe results showed that ML can be a useful tool in certain aspects of the LCA. ML methods were shown to be applied efficiently in optimization scenarios in LCA. Finally, ML methods were integrated as part of existing inventory databases to streamline the LCA across many use cases.
ConclusionsThe conclusions of this article summarise the characteristics of existing literature and provide suggestions for future work in limitations and gaps which were found in the literature.
相似文献Purpose
The main aim of the study is to assess the environmental and economic impacts of the lodging sector located in the Himalayan region of Nepal, from a life cycle perspective. The assessment should support decision making in technology and material selection for minimal environmental and economic burden in future construction projects.Methods
The study consists of the life cycle assessment and life cycle costing of lodging in three building types: traditional, semi-modern and modern. The life cycle stages under analysis include raw material acquisition, manufacturing, construction, use, maintenance and material replacement. The study includes a sensitivity analysis focusing on the lifespan of buildings, occupancy rate and discount and inflation rates. The functional unit was formulated as the ‘Lodging of one additional guest per night’, and the time horizon is 50 years of building lifespan. Both primary and secondary data were used in the life cycle inventory.Results and discussion
The modern building has the highest global warming potential (kg CO2-eq) as well as higher costs over 50 years of building lifespan. The results show that the use stage is responsible for the largest share of environmental impacts and costs, which are related to energy use for different household activities. The use of commercial materials in the modern building, which have to be transported mostly from the capital in the buildings, makes the higher GWP in the construction and replacement stages. Furthermore, a breakdown of the building components shows that the roof and wall of the building are the largest contributors to the production-related environmental impact.Conclusions
The findings suggest that the main improvement opportunities in the lodging sector lie in the reduction of impacts on the use stage and in the choice of materials for wall and roof.The main purpose of this review is to describe the state of the art of social impact assessment with a focus on mobility services. Whereas the use phase plays an important role for the assessment of services in general, the evaluation of the use phase has been underrepresented in previous social life cycle assessment studies. For that reason, particular attention has been paid to indicators, which allow the assessment of social impacts during the use phase of mobility services.
MethodsContinuous efforts to mitigate climate change and to improve quality of life in cities result in new mobility solutions based on collective use. This will have a huge impact on our society transforming the use of vehicles. In order to better understand the implications for cities, society and the automotive industry, it is essential to evaluate the social impact generated along a product life cycle with particular attention to the use phase. To reach the goal, a systematic literature review was carried out with a focus on social indicators that allow assessing use phase impacts of mobility services. The indicators were analysed and allocated to stakeholder groups. Based on the analysis, a core set of indicators is proposed under consideration of data availability.
Results and discussionBased on the selected search strings, 51 publications were selected for the literature review, including 579 social indicators. The analysis revealed a wide variety and diversity of indicators that are trying to measure the same aspect. The allocation to the respective stakeholder groups showed that most of the indicators (36%) evaluate impacts regarding the stakeholder group local community. The majority of analysed indicators are of quantitative nature (63%). Nevertheless, a clear assessment method was often missing in the respective publications. Therefore, for the core set of indicators, an assessment method is proposed for every indicator.
ConclusionsThe results from this study can help practitioners as well as researchers in the field of urban mobility assessment as it systematically analyses social sustainability aspects. The presented data gives an overview of various indicators that are suggested in other publications, and the proposed core set of indicators can be used to evaluate different mobility services in further research.
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