Efficient Architectural Design Space Exploration via Predictive Modeling

Efficiently exploring exponential-size architectural design spaces with many interacting parameters remains an open problem: the sheer number of experiments required renders detailed simulation intractable.We attack this via an automated approach that builds accurate predictive models. We simulate sampled points, using results to teach our models the function describing relationships among design parameters. The models can be queried and are very fast, enabling efficient design tradeoff discovery. We validate our approach via two uniprocessor sensitivity studies, predicting IPC with only 1–2% error. In an experimental study using the approach, training on 1% of a 250-K-point CMP design space allows our models to predict performance with only 4–5% error. Our predictive modeling combines well with techniques that reduce the time taken by each simulation experiment, achieving net time savings of three-four orders of magnitude.

Late-stage, primary open-angle glaucoma in Europe:Social and health care maintenance costs and quality of life of patients from 4 countries

Objective: The purpose of this study was to estimate costs and quality of life (QoL) of late-stage glaucoma patients in 4 European countries. Methods: Retrospective review of medical charts of patients with POAG who were followed in a low-vision or vision rehabilitation center in one of 4 countries for at least 1 year was used to determine patient characteristics, health status, and health care resource use. Visual impairment was measured by best-corrected visual acuity (Snellen score). Patients were also interviewed over the telephone in order to assess their health-related QoL (using EuroQol EQ-5D) and use of resources including: the number of visits to rehabilitation centers, visits to hospital and non-hospital specialists, the use of low-vision devices, medication, tests, and the use of hired home help. The costs associated with resource use were calculated from the perspective of a third-party payer of health and social care based on resource usage and unit costs in each country. Results: Patients undergoing visual rehabilitation in France (n=21), Denmark (n=59), Germany (n=60), and the United Kingdom (n=22) were identified, interviewed and had their medical charts reviewed. Annual maintenance costs of late-stage glaucoma amounted to €830 (±445) on average. Average home help costs were more than 3 times higher. QoL, on average, was 0.65 (±0.28). QoL was positively correlated with the level of visual acuity in the patients' best eye. On the other hand, visual acuity was also positively correlated to health care costs, but negatively correlated to costs of home help. Conclusions: The study was limited by its observational, uncontrolled design. The finding that late-stage glaucoma is associated with higher home help costs than health care maintenance costs suggests that potential savings from a better preventive treatment are to be found for social care payers rather than health care payers. © 2008 Informa UK Ltd All rights reserved.

In silico prediction of the effects of mutations in the human UDP-galactose 4'-epimerase gene:Towards a predictive framework for type III galactosemia

The enzyme UDP-galactose 4'-epimerase (GALE) catalyses the reversible epimerisation of both UDP-galactose and UDP-N-acetyl-galactosamine. Deficiency of the human enzyme (hGALE) is associated with type III galactosemia. The majority of known mutations in hGALE are missense and private thus making clinical guidance difficult. In this study a bioinformatics approach was employed to analyse the structural effects due to each mutation using both the UDP-glucose and UDP-N-acetylglucosamine bound structures of the wild-type protein. Changes to the enzyme's overall stability, substrate/cofactor binding and propensity to aggregate were also predicted. These predictions were found to be in good agreement with previous in vitro and in vivo studies when data was available and allowed for the differentiation of those mutants that severely impair the enzyme's activity against UDP-galactose. Next this combination of techniques were applied to another twenty-six reported variants from the NCBI dbSNP database that have yet to be studied to predict their effects. This identified p.I14T, p.R184H and p.G302R as likely severely impairing mutations. Although severely impaired mutants were predicted to decrease the protein's stability, overall predicted stability changes only weakly correlated with residual activity against UDP-galactose. This suggests other protein functions such as changes in cofactor and substrate binding may also contribute to the mechanism of impairment. Finally this investigation shows that this combination of different in silico approaches is useful in predicting the effects of mutations and that it could be the basis of an initial prediction of likely clinical severity when new hGALE mutants are discovered.

Automated Methods for Virtual Maintainability & Aerospace Maintenance Planning

Abstract. Modern business practices in engineering are increasingly turning to post manufacture service provision in an attempt to generate additional revenue streams and ensure commercial sustainability. Maintainability has always been a consideration during the design process but in the past it has been generally considered to be of tertiary importance behind manufacturability and primary product function in terms of design priorities. The need to draw whole life considerations into concurrent engineering (CE) practice has encouraged companies to address issues such as maintenance, earlier in the design process giving equal importance to all aspects of the product lifecycle. The consideration of design for maintainability (DFM) early in the design process has the potential to significantly reduce maintenance costs, and improve overall running efficiencies as well as safety levels. However a lack of simulation tools still hinders the adaptation of CE to include practical elements of design and therefore further research is required to develop methods by which ‘hands on’ activities such as maintenance can be fully assessed and optimised as concepts develop. Virtual Reality (VR) has the potential to address this issue but the application of these traditionally high cost systems can require complex infrastructure and their use has typically focused on aesthetic aspects of mature designs. This paper examines the application of cost effective VR technology to the rapid assessment of aircraft interior inspection during conceptual design. It focuses on the integration of VR hardware with a typical desktop engineering system and examines the challenges with data transfer, graphics quality and the development of practical user functions within the VR environment. Conclusions drawn to date indicate that the system has the potential to improve maintenance planning through the provision of a usable environment for inspection which is available as soon as preliminary structural models are generated as part of the conceptual design process. Challenges still exist in the efficient transfer of data between the CAD and VR environments as well as the quantification of any benefits that result from the proposed approach. The result of this research will help to improve product maintainability, reduce product development cycle times and lower maintenance costs.

Improving MTM-UAS to predetermine automotive maintenance times

The preventive knowledge of serviceability times is a critical factor for the quantification of after-sales services costs of a vehicle. Predetermined motion time system are frequently used to set labor rates in industry by quantifying the amount of time required to perform specific tasks. The first such system is known as Methods-time measurement (MTM). Several variants of MTM have been developed differing from each other on their level of focus. Among them MTM-UAS is suitable for processes that average around 1-3 min. However experimental tests carried out by the authors in Elasis (Research Center of FIAT Group) demonstrate that MTM-UAS is not the optimal approach to measure serviceability times. The reason is that it doesn't take into account ergonomic factors. In the present paper the authors propose to correct the MTM-UAS method including in the task analysis the study of human postures and efforts. The proposed approach allows to estimate with an "acceptable" error the time needed to perform maintenance tasks since the first phases of product design, by working on Digital Mock-up and human models in virtual environment. As a byproduct of that analysis, it is possible to obtain a list of maintenance times in order to preventively set after-sales service costs. © 2012 Springer-Verlag.

Role of nitric oxide in maintenance of basal oral tissue blood flow in anesthetized cats

Experiments were undertaken to determine if nitric oxide (NO) plays a role in regulation of basal blood flow in the oral cavity of pentobarbital anesthetized cats and, if so, to quantify this effect using dose-response relationships. Blood flow was continuously measured from the surface of the tongue and mandibular gingiva (laser-Doppler flowmetry) and from the lingual artery (ultrasonic flowmetry). Cardiovascular parameters also were recorded. Administration of the nonselective inhibitor of nitric oxide synthase (NOS), L-NAME (0.08-20 mg/kg i.v.), produced a dose-related increase of blood pressure associated with decreases of blood flow at all three measurement sites. Maximal blood flow depression of 50-60% was seen 30-60 min after administration of 1.25 mg/kg of L-NAME. D-NAME (1.25 mg/kg i.v.) was inactive at all sites. Subsequent administration of L-arginine partially reversed effects of L-NAME in the lingual artery and tongue, but not in the gingival circulation. The neuronally selective NOS inhibitor, 7-nitroindazole (7-NI, 30 mg/kg i.p.), was devoid of effect on any of the measured parameters. These results suggest that endothelial (but not neuronally derived) NO plays an important role in control of basal blood flow in oral tissues of the cat.

The predictive science of community ecology

Body mass measures provide a tantalizing tool for explaining both variation in emergent community-level patterns and as a mechanistic basis for fundamental processes such as metabolism, consumption and competition. The unification of body mass, abundance and food web (ecological network) structure in community ecology is an effective way to explore future scenarios of environmental change. However, constraints over the availability of data against which to validate model predictions limit the application of size-based approaches. Here, I explore issues over the use of body size for predicting interaction strengths and hence the dynamics of natural ecosystems. The advantages, disadvantages, opportunities and limitations of such approaches are explored. © 2011 The Author. Journal of Animal Ecology © 2011 British Ecological Society.

Earthmoving trucks condition level prediction using neural networks

Purpose: The purpose of this paper is to present an artificial neural network (ANN) model that predicts earthmoving trucks condition level using simple predictors; the model’s performance is compared to the respective predictive accuracy of the statistical method of discriminant analysis (DA).

Design/methodology/approach: An ANN-based predictive model is developed. The condition level predictors selected are the capacity, age, kilometers travelled and maintenance level. The relevant data set was provided by two Greek construction companies and includes the characteristics of 126 earthmoving trucks.

Findings: Data processing identifies a particularly strong connection of kilometers travelled and maintenance level with the earthmoving trucks condition level. Moreover, the validation process reveals that the predictive efficiency of the proposed ANN model is very high. Similar findings emerge from the application of DA to the same data set using the same predictors.

Originality/value: Earthmoving trucks’ sound condition level prediction reduces downtime and its adverse impact on earthmoving duration and cost, while also enhancing the maintenance and replacement policies effectiveness. This research proves that a sound condition level prediction for earthmoving trucks is achievable through the utilization of easy to collect data and provides a comparative evaluation of the results of two widely applied predictive methods.

Identification of a BRCA1-mRNA Splicing Complex Required for Efficient DNA Repair and Maintenance of Genomic Stability

Mutations within BRCA1 predispose carriers to a high risk of breast and ovarian cancers. BRCA1 functions to maintain genomic stability through the assembly of multiple protein complexes involved in DNA repair, cell-cycle arrest, and transcriptional regulation. Here, we report the identification of a DNA damage-induced BRCA1 protein complex containing BCLAF1 and other key components of the mRNA-splicing machinery. In response to DNA damage, this complex regulates pre-mRNA splicing of a number of genes involved in DNA damage signaling and repair, thereby promoting the stability of these transcripts/proteins. Further, we show that abrogation of this complex results in sensitivity to DNA damage, defective DNA repair, and genomic instability. Interestingly, mutations in a number of proteins found within this complex have been identified in numerous cancer types. These data suggest that regulation of splicing by the BRCA1-mRNA splicing complex plays an important role in the cellular response to DNA damage.