Analysis of the difficulties in reconstructing the infrastructure damaged by natural disasters in New Zealand and Puerto Rico

Once a natural disaster damages essential infrastructure services, such as roads, bridges, electric power and potable water, the priority is to restore these services as soon as possible. Under normal circumstances, the planning, design and construction of complex infrastructure projects requires an extended period of time that in many cases lasts for years. The reconstruction of essential services after a disaster is complex not only because the amount of time that can be devoted to planning is extremely limited, but also because government agencies and their officials are under public scrutiny. The press and political institutions frequently criticize the reaction time and decisions of public officials, which increases the complexity of the projects. This article uses a five-dimensional project management model (5DPM) to identify and manage the sources of complexity in emergency projects. The article describes the sources of complexity in reconstruction projects after natural disasters hit the islands of New Zealand and Puerto Rico causing great devastation. The natural disasters analyzed in this article are the earthquakes of 2010 and 2011 in New Zealand and the hurricanes Irma and Maria in 2017 in Puerto Rico. The islands, due to their geographical location, faced similar challenges in terms of the shortage of workers, and materials and equipment for reconstruction, which had to be imported. The shortage negatively impacted the response time to the emergency, the perception of the press, and public opinion about the proper handling of the emergencies. The article analyzes the sources of complexity in the reconstruction of the damaged infrastructure and concludes that the sociopolitical context is often the most complex dimension when reconstruction projects are carried out in an expeditious manner

A case study of a new tool to identify good performing pavements in New Zealand

With the advancement of digital technology, the collection of pavement performance data has become commonplace. The improvement of tools to extract useful information from pavement databases has become a priority to justify expenditures. This paper presents a case study of PaveMD, a tool that integrates multi-dimensional data structures with a data-driven fuzzy approach to identify good performing pavement sections. Combining this tool with an innovative paradigm where the focus is on repeating success can bring additional value to existing pavement databases. The case study shows that PaveMD can identify pavement sections that are performing well by comparing performance measures for the New Zealand context. In this paper, PaveMD's development is described, and its implementation is showcased using data from the New Zealand Long-Term Pavement Performance (LTPP) database. It is recommended that this approach be further developed and extended to other infrastructure databases internationally

Simulation for Education in Construction and Construction Management

Construction is a complex industry. It is particularly important to educate and train people in the procedures and management of the industry. Such training needs to be very broad in order to provide maximum benefit. It also needs to facilitate faster and more reliable learning than the traditional "learning on the job? which used to be the way of initiating fresh graduates to construction management.Traditional education and training can only improve some aspects, but simulation has been introduced to broaden the spectrum of and improve the effectiveness of learning to cope with more complex issues that face engineers in the industry. Typically simulations are computer-based and designed to tackle the management of technical aspects of construction. The authors have many years of experience of running courses at various levels using such simulations. However, this type of simulation can lead to a false understanding of the effectiveness of the methods being considered. For example, a simulation designed to „teach? planning and control will almost certainly neglect the human influence or model it in a simplistic manner. The learner is then likely to acquire a biased or partial view of the effectiveness of the techniques and not appreciate actions that are necessary to use them in practice.This paper discusses how a computer-based simulation has been used in practice in a number of institutions around the world (U.K., Netherlands, Malaysia, Australia and New Zealand) using simulation. It is based on many years of experience of developing and using IT and non-IT based simulations and examples currently being used are provided to illustrate the arguments. It concludes by suggesting areas for future IT-based development of simulations for education and training

Overview and analysis of digital technologies for construction safety management

Digital technologies are increasingly used to support safety management in the construction industry. Previous efforts were made to identify digital technologies for safety in the construction industry. However, limited research has been done to conceptualize the roles played by digital technologies in safety management and accident prevention. This paper surveys state-of-the-art research between 2000 and 2016 in order to categorize digital technologies for construction safety, identify research trend, and analyse their roles in accident prevention. The research employs a systematic process to review the existing literature on digital technologies in the area of construction safety. Five academic databases, Science Direct, Taylor & Francis, the ASCE Library, Engineering village, and Web of Science, were selected for the survey due to the comprehensive coverage of relevant academic papers. The survey identified 15 digital technologies: real-time location system and proximity warning, building information modelling, augmented reality, virtual reality, game technology, e-safetymanagement-system, case-based reasoning, rule-based reasoning, motion sensor, action/object recognition, laser scanning, physiological status monitoring, virtual prototyping, geographical information system, and ubiquitous sensor network. Three emerging safety functions claimed and/or promoted by DTs were discussed: enhanced safety planning, real-time hazard management, and safety knowledge engineering. It is concluded that DTs have great potential to improve safety performance by engineering resilience and adaptiveness at the individual level, while how DTs embody safety values and how safety values in turn influence the adoption of DTs remain an open question

ALL-tRNAseq enables robust tRNA profiling in tissue samples

Transfer RNAs (tRNAs) are small adaptor RNAs essential for mRNA translation. Alterations in the cellular tRNA population can directly affect mRNA decoding rates and translational efficiency during cancer development and progression. To evaluate changes in the composition of the tRNA pool, multiple sequencing approaches have been developed to overcome reverse transcription blocks caused by the stable structures of these molecules and their numerous base modifications. However, it remains unclear whether current sequencing protocols faithfully capture tRNAs existing in cells or tissues. This is specifically challenging for clinical tissue samples that often present variable RNA qualities. For this reason, we developed ALL-tRNAseq, which combines the highly processive MarathonRT and RNA demethylation for the robust assessment of tRNA expression, together with a randomized adapter ligation strategy prior to reverse transcription to assess tRNA fragmentation levels in both cell lines and tissues. Incorporation of tRNA fragments not only informed on sample integrity but also significantly improved tRNA profiling of tissue samples. Our data showed that our profiling strategy effectively improves classification of oncogenic signatures in glioblastoma and diffuse large B-cell lymphoma tissues, particularly for samples presenting higher levels of RNA fragmentation, further highlighting the utility of ALL-tRNAseq for translational research