SeeCarbon: a review of digital approaches for revealing and reducing infrastructure, building and City's carbon footprint

Dealing with climate change and its consequences on the environment have been one of the biggest challenges nowadays, where reducing the carbon footprint has been the focus of most sustainable strategies. The infrastructure is the dominant sector responsible for the total carbon footprint, accounting for approximately 70% of global carbon emissions. This study aims to illustrate the state-of-the-art of digital development and transformation of revealing and reducing carbon footprint in the Architecture, Engineering, Construction and Facility Management (AEC/FM) sectors. The digital tools for revealing and reducing infrastructure’s carbon footprint would be summarized and also compared with other sectors, namely the tools for building and city. Current challenges and future development are also included

Digital Tools for Revealing and Reducing Carbon Footprint in Infrastructure, Building, and City Scopes

The climate change issue has been striking and bringing pressure on all countries and industries. The responsibility of the Architecture, Engineering, Construction and Facility Management (AEC/FM) industry is heavy because it accounts for over one-third of global energy use and greenhouse gas emissions. At the same time, the development of digital technology brings the opportunity to mitigate environmental issues. Therefore, this study intended to examine the state-of-the-art of digital development and transformation in the AEC/FM industry by collecting and reviewing the developed digital carbon footprint analysis tools in infrastructure, building, and city scopes. Specifically, this study (1) generated a review methodology for carbon footprint analysis results; (2) demonstrated the review results from the infrastructure, building, and city scopes, analysed and compared the results crossing the scopes from four aspects: carbon footprint analysis strategy, standards and protocols, rating systems, and general development level of digital tools; and (3) discussed the potential directions in the industry to address the environmental issues. This study indicated that the digitalisation level regarding carbon-related areas is still at an early stage, and efforts should be taken both academically and practically to drive the digital development confronting the harsh climate change issue

Gemini Principles-Based Digital Twin Maturity Model for Asset Management

Various maturity models have been developed for understanding the diffusion and implementation of new technologies/approaches. However, we find that existing maturity models fail to understand the implementation of emerging digital twin technique comprehensively and quantitatively. This research aims to develop an innovative maturity model for measuring digital twin maturity for asset management. This model is established based on Gemini Principles to form a systematic view of digital twin development and implementation. Within this maturity model, three main dimensions consisting of nine sub-dimensions have been defined firstly, which were further articulated by 27 rubrics. Then, a questionnaire survey with 40 experts involved is designed and conducted to examine these rubrics. This model is finally illustrated and validated by two case studies in Shanghai and Cambridge. The results show that the digital twin maturity model is effective to qualitatively evaluate and compare the maturity of digital twin implementation at the project level. It can also initiate the roadmap for improving the performance of digital twin supported asset management

SRSF5‐Mediated Alternative Splicing of M Gene is Essential for Influenza A Virus Replication: A Host‐Directed Target Against Influenza Virus

Abstract: Splicing of influenza A virus (IAV) RNA is an essential process in the viral life cycle that involves the co‐opting of host factors. Here, it is demonstrated that induction of host serine and arginine‐rich splicing factor 5 (SRSF5) by IAV facilitated viral replication by enhancing viral M mRNA splicing. Mechanistically, SRSF5 with its RRM2 domain directly bounds M mRNA at conserved sites (M mRNA position 163, 709, and 712), and interacts with U1 small nuclear ribonucleoprotein (snRNP) to promote M mRNA splicing and M2 production. Mutations introduced to the three binding sites, without changing amino acid code, significantly attenuates virus replication and pathogenesis in vivo. Likewise, SRSF5 conditional knockout in the lung protects mice against lethal IAV challenge. Furthermore, anidulafungin, an approved antifungal drug, is identified as an inhibitor of SRSF5 that effectively blocks IAV replication in vitro and in vivo. In conclusion, SRSF5 as an activator of M mRNA splicing promotes IAV replication and is a host‐derived antiviral target

Integrated schedule of order picking and delivery for instant delivery

In this study, we introduce an integrated schedule of order picking and delivery for instant delivery. Order picking, including order batching and picking sequencing, is scheduled online under real-time order arrival, which integrates order delivery by depicting order location dispersion in an online order picking strategy. Order delivery, including delivery person assignment and route planning, is modeled to minimize the total duration of order fulfillment by considering the influence of the order picking completion time. A rule-based online order picking strategy is established, and a customized ant colony optimization (ACO) algorithm is proposed to optimize order delivery. Experiments on 16 simulated instances of different scales demonstrate that our online order picking schedule considering order delivery outperforms existing approaches and that the customized ACO algorithm for order delivery is effective

A semi-automatic image-based object recognition system for constructing as-is IFC BIM objects based on fuzzy-MAUT

Building information modelling (BIM) could support different activities throughout the life cycle of a building and has been widely applied in design and construction phases nowadays. However, BIM has not been widely implemented in the operation and maintenance (O&M) phase. As-is information for the majority of existing buildings is not complete and even outdated or incorrect. Lack of accurate and complete as-is information is still one of the key reasons leading to the low-level efficiency in O&M. BIM performs as an intelligent platform and a database that stores, links, extracts and exchanges information in construction projects. It has shown promising opportunities and advantages in BIM applications for the improvement in O&M. Hence, an effective and convenient approach to record as-is conditions of the existing buildings and create as-is BIM objects would be the essential step for improving efficiency and effectiveness of O&M, and furthermore possibly refurbishment of the building. Many researchers have paid attention to different systems and approaches for automated and real-time object recognition in past decades. This paper summarizes state-of-the-art statistical matching-based object recognition methods and then presents the image-based Industry Foundation Classes (IFC) BIM object creation application, which extracts object information by simply conducting point-and-click operations. Furthermore, the object recognition research system is introduced, including recognizing structure object types and their corresponding materials. This paper combines the multi-attribute utility theory (MAUT) with the fuzzy set theory to be Fuzzy-MAUT, since the MAUT allows complex and powerful combinations of various criteria and fuzzy set theory assists improving the performance of this system. With the goal of creating an effective method for as-is IFC BIM objects construction, this image-based object recognition system and its recognition process are further validated and tested. Key challenges and promising opportunities are also addressed

Scavenging Vibration Energy from Seismically-isolated Bridges Using an Electromagnetic Harvester

The increasing worldwide efforts in securing renewable energy sources increase incentive for civil engineers to investigate whether the kinetic energy associated with the vibration of larger-scale structures can be harvested. Such a research remains challenging and incomplete despite that hundreds of related articles have been published in the last decade. Base isolation is one of the most popular means of protecting a civil engineering structure against earthquake forces. Seismic isolation hinges on the decoupling of the structure from the shaking ground, hence protecting the structure from stress and damage during an earthquake excitation. The low stiffness isolator inserted between the structure and the ground dominates the response leading to a structural system of longer vibration period. As a consequence of this period shift, the spectral acceleration is reduced, but higher response displacements are produced. To mitigate this side effect, usually isolators are combined with the use of additional energy dissipation. In this study, the feasibility of scavenging the need-to-be dissipated energy from the isolator installed in a seismically isolated bridge using an electromagnetic (EM) energy harvester is investigated. The EM energy harvester consists of an energy harvesting circuit and a capacitor for energy storage. A mathematical model for this proposed EM energy harvester is developed and implemented on an idealized base-isolated single-degree-of-freedom system. The effect of having this EM energy harvester on the performance of this seismic isolated system is analyzed and discussed. The potential of installing such an EM energy harvester on a seismically isolated bridge is also addressed

Learning more than one language across the lifespan: A literature review

This literature review is based on the final assignment of a graduate-level language and literacy theory and research course at the Werklund School of Education, University of Calgary, in Calgary, Alberta. The course is an introduction to the principles of language learning from cognitive, sociocultural and critical perspectives. For the final assignment, students choose a topic of interest and then write, revise and finalize a literature review. Five students in the course, along with the instructor, are the authors of this article. Each student focused on a particular topic in the field of multiple language learning. Here, they present their literature reviews, along with their understandings of the topic, making critical analyses and identifying gaps in the literature. During the course, they discussed their topics with each other and provided feedback on the written work. By the end of the course, they all were not only familiar with all five topics but also acquired the skills needed for writing and revising a literature review, as well as for providing peer- review feedback. Each topic focused on a factor of learning more than one language across the lifespan. The topics were as follows: • Students’ classroom language use in full and partial immersion programs • Assessing depth of vocabulary knowledge in listening comprehension • Language assessment strategies for bilingual children in the diagnostic process for autism spectrum disorders • Parental factors and involvement in children’s English learning in China • Factors that influence the second language socialization of international students The literature reviews that follow represent a cross-section and an overview of the research on language learning. The students explore their topics by presenting empirical studies, synthesizing the main findings, and discussing classroom implications and directions for future research. They then comment on their learning from the course and this assignment, which will be of great value to other teachers who are considering graduate studies, as well as to postsecondary instructors who are framing course formats and assignments

Framing blockchain-integrated digital twins for emergent healthcare management at local and city levels: a proof of concept

It has been witnessed that digital technology has the potential to improve the efficiency of emergent healthcare management in COVID-19, which however has not been widely adopted due to unclear definition and configuration. This research aims to propose a proof of concept of digital twins for emergent healthcare management through configuring the cyber and functional interdependencies of healthcare systems at local and city levels. Critical interdependencies of healthcare systems have been firstly identified at both levels, then the information and associated cyber and functional interdependencies embedded in seven critical hospital information systems (HISs) have been identified and mapped. The proposed conceptual digital twin-based approach has been then developed for information coordination amongst these critical HISs at both local and city levels based on permissioned blockchain to (1) integrate and manage the information from seven critical HISs, and further (2) predict the demands of medical resources according to patient trajectory. A case study has been finally conducted at three hospitals in London during the COVID-19 period, and the results showed that the developed framework of blockchain-integrated digital twins is a promising way to provide more accurate and timely procurement information to decision-makers and can effectively support evidence-based decisions on medical resource allocation in the pandemic