The interest in lean thinking in the UK's civil construction industry is on the rise.The research presented in the paper evaluates the adoption of lean thinking in the highways construction sector by investigating 7 motivation factors, 20 lean techniques and 16 barriers through in-depth interviews with 20 sector managers and a questionnaire survey of 110 responses. The findings show the existence of strong external motivational factors for lean thinking such as clients' push and companies' expectation of winning more contracts alongside lean's operational benefits. Limited adoptions of the lean techniques, mostly in the stepwise process improvement cycle, the Last Planner System and Visual Management, were determined. This raises concerns about "pseudo-lean" practices in the sector. Lack of standardisation, insufficient benefit capturing, insufficient know-how, insufficient control of the entire value stream and limited view to the techniques were found as the top barriers. Small and medium sized enterprises (SMEs) are significantly different than large main contractors and subcontractors with respect to their lean implementations and views to barriers before lean thinking within their organisations.

Tumor necrosis factor (TNF)-alpha-dependent apoptosis of alveolar macrophages (AM) after infection with avirulent Mycobacterium tuberculosis (Mtb) results in bacillary death and the destruction of a growth niche for the pathogen. This response is minimized after infection with virulent strains of Mtb. To study the genetic control of Mtb-induced apoptosis, we used microarrays to interrogate the expression profile of infected human AM. Although we found variation in gene expression between different donors of AM, a set of genes were constant for each condition. A group of proapoptotic genes were downregulated after infection by virulent Mtb strain H37Rv, whereas infection with avirulent Mtb H37Ra led to a gene expression profile that would favor macrophage apoptosis. Neutralizing TNF in macrophage cultures infected with H37Ra changed the gene expression profile to one that resembled the profile of macrophages infected with H37Rv. These data reveal that apoptosis-related genes are regulated differently by virulent or attenuated Mtb strains, and are consistent with the hypothesis that virulent Mtb interfere with TNF death signaling. Given the importance of TNF in host defense against tuberculosis, the ability to repress the expression of genes activated by TNF may constitute a bacillary virulence mechanism.

Purpose This paper aims to explore the current condition of the Big Data concept with its related barriers, drivers, opportunities and perceptions in the architecture, engineering and construction (AEC) industry with an emphasis on facilities management (FM). Design/methodology/approach Following a comprehensive literature review, the Big Data concept was investigated through two scoping workshops with industry experts and academics. Findings The value in data analytics and Big Data is perceived by the industry, yet the industry needs guidance and leadership. Also, the industry recognises the imbalance between data capturing and data analytics. Large IT vendors’ developing AEC industry-focused analytics solutions and better interoperability among different vendors are needed. The general concerns for Big Data analytics mostly apply to the AEC industry as well. Additionally, however, the industry suffers from a structural fragmentation for data integration with many small-sized companies operating in its supply chains. This paper also identifies a number of drivers, challenges and way-forwards that calls for future actions for Big Data in FM in the AEC industry. Originality/value The nature of data in the business world has dramatically changed over the past 20 years. This phenomenon is often broadly dubbed as “Big Data” with its distinctive characteristics, opportunities and challenges. Some industries have already started to effectively exploit “Big Data” in their business operations. However, despite many perceived benefits, the AEC industry has been slow in discussing and adopting the Big Data concept. Empirical research efforts investigating Big Data for the AEC industry are also scarce. This paper aims at outlining the benefits, challenges and future directions (what to do) for Big Data in the AEC industry with an FM focus.

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Table 1. Profile of the interviewees. 3.2. Survey questionnaire To validate, rank and perform further analyses on the statements, a questionnaire survey

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C h all e n g e s a n d d riv e r s fo r d a t a m i ni n g in t h e AEC s e c t o rAh m e d, V, Aziz, Z U H, Tez el, A a n d Ri az, Z h t t p:// dx. doi.o r g/ 1 0. 1 1 0 8/ E CAM-0 1-2 0 1 8-0 0 3 5 Ti t l e C h all e n g e s a n d d riv e r s fo r d a t a m i ni n g in t h e AEC s e c t o r A u t h o r s Ah m e d, V, Aziz, Z U H , Tez el, A a n d Ri az, Z Typ e Articl e U RL This ve r sio n is a v ail a bl e a t : h t t p:// u sir.s alfo r d. a c. u k/id/ e p ri n t/ 4 7 2 9 4/ P u b l i s h e d D a t e 2 0 1 8 U SIR is a di git al c oll e c tio n of t h e r e s e a r c h o u t p u t of t h e U niv e r si ty of S alfo r d. W h e r e c o py ri g h t p e r mi t s, full t e x t m a t e ri al h el d in t h e r e p o si to ry is m a d e fr e ely a v ail a bl e o nli n e a n d c a n b e r e a d , d o w nlo a d e d a n d c o pi e d fo r n o nc o m m e r ci al p riv a t e s t u dy o r r e s e a r c h p u r p o s e s . Pl e a s e c h e c k t h e m a n u s c ri p t fo r a n y fu r t h e r c o py ri g h t r e s t ri c tio n s. Fo r m o r e info r m a tio n, in cl u di n g o u r p olicy a n d s u b mi s sio n p r o c e d u r e , pl e a s e c o n t a c t t h e R e p o si to ry Te a m a t: u si r@ s alfo r d. a c. u k . Abstract: http://mc.manuscriptcentral.com/ecaam Engineering, Construction and Architectural Management Abstract Purpose: This paper explores the current challenges and drivers for data mining in the AEC sector.Design/methodology/approach: Following a comprehensive literature review, the data mining concept was investigated through a workshop with industry experts and academics. Findings:The results showed that the key drivers for using data mining within the AEC sector is associated with the sustainability, process improvement, market intelligence, cost certainty and cost reduction, performance certainty and decision support systems agendas in the sector. As for the processes with the greatest potential for data mining application, design, construction, procurement, forensic analysis, sustainability and energy consumption and reuse of digital components were perceived as the main process areas. While the key challenges were perceived as being, data issues due to the fragmented nature of the construction process, the need for a cultural change, IT systems used in silos, skills requirements and having clearly defined business goals.Originality/value: With the increasing abundance of data, business intelligence and analytics and its related concepts, data mining and big data have captured the attention of practitioners and academics for the last 20 years. On the other hand, and despite the growing amount of data in its business context, the AEC sector still lags behind in utilising those concepts in its end products and daily operations with limited research conducted to explore those issues at the sector level. This paper investigates the main opportunities and barriers for Data Mining in the AEC sector with a practical focus.

Purpose -Effective management of highways requires management of diverse data sets including traffic volume data, roadway, and road edge and road-side data. Like all major infrastructure clients, highways administration authorities are under pressure to use such platforms for better management of data that, in addition to creating other opportunities, allows improved life cycle management of asset data and predictive analytics. This paper aims to review such opportunities and the value that can be generated through integrated life cycle data management by leveraging Big Data and building information modelling (BIM).Design/methodology/approach -A literature review is initially performed to systematically gather information to identify and understand BIM as a collaborative platform. Data management applications in other industries are also reviewed. Interviews were conducted and two industry workshops were organised to understand BIM implementation challenges within highways development projects and the role BIM can play in bridging inefficiencies resulting from loss of information at handover phases. The overall understanding lead to drawing up user needs, gathering system requirements and eventually a system architecture design to promote efficient information management throughout the asset lifecycle.Findings -It is observed that data from the design and construction phases of projects can be used to inform asset registers from an earlier stage. This information can be used to plan maintenance schedules. Moreover, it can also be integrated with data generated from numerous other sensors to develop a better picture of network operations and support key decision-making. Effective road network management involves collection and analysis of huge data from a variety of sources including sensors, mobiles, assets and Open Data. Recent growth in Big Data analytics and data integration technologies provides new opportunities to optimise operations of highways infrastructure.Research limitations/implications -The system architecture designed for this research is translated into a prototype system as a proof of concept. However, it needs to be tested and validated by end users to be transformed into a useful solution for the industry.Originality/value -This paper provides an enhanced understanding of new opportunities created to optimise operations of highways infrastructure using the recent growth in Big Data analytics and data integration technologies.