Private industrial project management: a systems-based case study

The technique of linear responsibility analysis is used for a retrospective case study of a private industrial development consisting of an extension to existing buildings to provide a warehouse, services block and packing line. The organizational structure adopted on the project is analysed using concepts from systems theory which are included in Walker's theoretical model of the structure of building project organizations (Walker, 1981). This model proposes that the process of building provision can be viewed as systems and subsystems which are differentiated from each other at decision points. Further to this, the subsystems can be viewed as the interaction of managing system and operating system. Using Walker's model, a systematic analysis of the relationships between the contributors gives a quantitative assessment of the efficacy of the organizational structure used. The causes of the client's dissatisfaction with the outcome of the project were lack of integration and complexity of the managing system. However, there was a high level of satisfaction with the completed project and this is reflected by the way in which the organization structure corresponded to the model's propositions.

The basis of valuations for secured commercial property lending in the UK

In the context of the financial crash and the commercial property market downturn, this paper examines the basis of valuation used in the UK commercial property lending process. Post-crisis there is discussion of countercyclical measures including the monitoring of asset prices; however there is no consideration of a different approach to property valuation. This paper questions this omission, given the role that valuations play in the bank regulatory process. The different bases of valuation available to lenders within International Valuation Standards are identified as Market Value (MV), Mortgage Lending Value (MLV) and Investment Value (IV), with MV being the most used in the UK. Using the different bases in the period before the financial crisis, the UK property market is modelled at a national office, retail and industrial/warehouse sector level to determine the performance of each alternative valuation basis within the context of counter-cyclical pressures on lending. Both MLV and IV would have produced lower valuations and could have provided lenders with tools for more informed and prudent lending. The paper concludes by recognising some of the practical issues involved in adopting the different bases for the bank lending role but recommends a change to IV.

Towards data warehousing and mining of protein unfolding simulation data

OBJECTIVES: The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. METHODS: To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. RESULTS: To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. CONCLUSIONS: Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

Grid warehousing of molecular dynamics protein unfolding data

With the increasing awareness of protein folding disorders, the explosion of genomic information, and the need for efficient ways to predict protein structure, protein folding and unfolding has become a central issue in molecular sciences research. Molecular dynamics computer simulations are increasingly employed to understand the folding and unfolding of proteins. Running protein unfolding simulations is computationally expensive and finding ways to enhance performance is a grid issue on its own. However, more and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. This paper describes efforts to provide a grid-enabled data warehouse for protein unfolding data. We outline the challenge and present first results in the design and implementation of the data warehouse.

Grid computing solutions for distributed repositories of protein folding and unfolding simulations

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories --- this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.

P-found: grid-enabling distributed repositories of protein folding and unfolding simulations for data mining

The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform data mining and other analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data that is used to populate the second component, and a data warehouse that contains important molecular properties. These properties may be used for data mining studies. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular, we look at two aspects: firstly, how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories — this is an important and challenging aspect of P-found, due to the large data volumes involved and the desire of scientists to maintain control of their own data. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling scientific discovery.

Whole life carbon – a building case study

There is potential to reduce both operational and embodied greenhouse gas emission from buildings. To date the focus has been on reducing the operational element, although given the urgency of carbon reductions, it may be more beneficial to consider upfront embodied carbon reductions. This paper describes a case study on the whole life carbon cycle of a warehouse building in Swindon, UK. It examines the relationship between embodied carbon (Ec) and operational carbon (Oc), the proportions of Ec from the structural and non-structural elements, carbon benchmarking of the structure, the value of ‘cradle to site’ or ‘cradle to grave’ assessments and the significance of the timing of emissions during the life of the building. The case study indicates that Ec was dominant for the building and that the structure was responsible for more than half of the Ec. Weighting of future emissions appears to be an important factor to consider. The PAS 2050 reduction factors had only a modest effect but weighting to allow for future decarbonisation of the national grid energy supply had a large effect. This suggests that future operational carbon emissions are being overestimated compared to embodied.

On the predictive content of leading indicators: the case of U.S. real estate markets

This paper employs a probit and a Markov switching model using information from the Conference Board Leading Indicator and other predictor variables to forecast the signs of future rental growth in four key U.S. commercial rent series. We find that both approaches have considerable power to predict changes in the direction of commercial rents up to two years ahead, exhibiting strong improvements over a naïve model, especially for the warehouse and apartment sectors. We find that while the Markov switching model appears to be more successful, it lags behind actual turnarounds in market outcomes whereas the probit is able to detect whether rental growth will be positive or negative several quarters ahead.