Intelligent laser scanning for computer aided manufacture.

Reverse engineering requires the acquisition of large amounts of data describing the surface of an object, sufficient to replicate that object accurately using appropriate fabrication techniques. This is important within a wide range of commercial and scientific fields where CAD models may be unavailable for parts that must be duplicated or modified, or where a physical model is used as a prototype. The three-dimensional digitisation of objects is an essential first step in reverse engineering. Optical triangulation laser sensors are one of the most popular and common non-contact methods used in the data acquisition process today. They provide the means for high resolution scanning of complex objects. Multiple scans of the object are usually required to capture the full 3D profile of the object. A number of factors, including scan resolution, system optics and the precision of the mechanical parts comprising the system may affect the accuracy of the process. A single perspective optical triangulation sensor provides an inexpensive method for the acquisition of 3D range image data

The construction of a Solanum habrochaites LYC4 introgression line population and the identification of QTLs for resistance to Botrytis cinerea

Tomato (Solanum lycopersicum) is susceptible to grey mold (Botrytis cinerea). Partial resistance to this fungus has been identified in accessions of wild relatives of tomato such as Solanum habrochaites LYC4. In a previous F2 mapping study, three QTLs conferring resistance to B. cinerea (Rbcq1, Rbcq2 and Rbcq4a) were identified. As it was probable that this study had not identified all QTLs involved in resistance we developed an introgression line (IL) population (n = 30), each containing a S. habrochaites introgression in the S. lycopersicum cv. Moneymaker genetic background. On average each IL contained 5.2% of the S. habrochaites genome and together the lines provide an estimated coverage of 95%. The level of susceptibility to B. cinerea for each of the ILs was assessed in a greenhouse trial and compared to the susceptible parent S. lycopersicum cv. Moneymaker. The effect of the three previously identified loci could be confirmed and seven additional loci were detected. Some ILs contains multiple QTLs and the increased resistance to B. cinerea in these ILs is in line with a completely additive model. We conclude that this set of QTLs offers good perspectives for breeding of B. cinerea resistant cultivars and that screening an IL population is more sensitive for detection of QTLs conferring resistance to B. cinerea than the analysis in an F2 population

A comparison of self reported air pollution problems and GIS-modeled levels of air pollution in people with and without chronic diseases

<p>Abstract</p> <p>Objective</p> <p>To explore various contributors to people's reporting of self reported air pollution problems in area of living, including GIS-modeled air pollution, and to investigate whether those with respiratory or other chronic diseases tend to over-report air pollution problems, compared to healthy people.</p> <p>Methods</p> <p>Cross-sectional data from the Oslo Health Study (2000–2001) were linked with GIS-modeled air pollution data from the Norwegian Institute of Air Research. Multivariate regression analyses were performed. 14 294 persons aged 30, 40, 45, 60 or 75 years old with complete information on modeled and self reported air pollution were included.</p> <p>Results</p> <p>People who reported air pollution problems were exposed to significantly higher GIS-modeled air pollution levels than those who did not report such problems. People with chronic disease, reported significantly more air pollution problems after adjustment for modeled levels of nitrogen dioxides, socio-demographic variables, smoking, depression, dwelling conditions and an area deprivation index, even if they had a non-respiratory disease. No diseases, however, were significantly associated with levels of nitrogen dioxides.</p> <p>Conclusion</p> <p>Self reported air pollution problems in area of living are strongly associated with increased levels of GIS-modeled air pollution. Over and above this, those who report to have a chronic disease tend to report more air pollution problems in area of living, despite no significant difference in air pollution exposure compared to healthy people, and no associations between these diseases and NO₂. Studies on the association between self reported air pollution problems and health should be aware of the possibility that disease itself may influence the reporting of air pollution.</p

ART: A machine learning Automated Recommendation Tool for synthetic biology

Biology has changed radically in the last two decades, transitioning from a descriptive science into a design science. Synthetic biology allows us to bioengineer cells to synthesize novel valuable molecules such as renewable biofuels or anticancer drugs. However, traditional synthetic biology approaches involve ad-hoc engineering practices, which lead to long development times. Here, we present the Automated Recommendation Tool (ART), a tool that leverages machine learning and probabilistic modeling techniques to guide synthetic biology in a systematic fashion, without the need for a full mechanistic understanding of the biological system. Using sampling-based optimization, ART provides a set of recommended strains to be built in the next engineering cycle, alongside probabilistic predictions of their production levels. We demonstrate the capabilities of ART on simulated data sets, as well as experimental data from real metabolic engineering projects producing renewable biofuels, hoppy flavored beer without hops, and fatty acids. Finally, we discuss the limitations of this approach, and the practical consequences of the underlying assumptions failing

Vector Systems for Prenatal Gene Therapy: Principles of Adenovirus Design and Production

Adenoviruses have many attributes, which have made them one of the most widely investigated vectors for gene therapy applications. These include ease of genetic manipulation to produce replication-deficient vectors, ability to readily generate high titer stocks, efficiency of gene delivery into many cell types, and ability to encode large genetic inserts. Recent advances in adenoviral vector engineering have included the ability to genetically manipulate the tropism of the vector by engineering of the major capsid proteins, particularly fiber and hexon. Furthermore, simple replication-deficient adenoviral vectors deleted for expression of a single gene have been complemented by the development of systems in which the majority of adenoviral genes are deleted, generating sophisticated Ad vectors which can mediate sustained transgene expression following a single delivery. This chapter outlines methods for developing simple transgene over expressing Ad vectors and detailed strategies to engineer mutations into the major capsid proteins

Results of the eruptive column model inter-comparison study

This study compares and evaluates one-dimensional (1D) and three-dimensional (3D) numerical models of volcanic eruption columns in a set of different inter-comparison exercises. The exercises were designed as a blind test in which a set of common input parameters was given for two reference eruptions, representing a strong and a weak eruption column under different meteorological conditions. Comparing the results of the different models allows us to evaluate their capabilities and target areas for future improvement. Despite their different formulations, the 1D and 3D models provide reasonably consistent predictions of some of the key global descriptors of the volcanic plumes. Variability in plume height, estimated from the standard deviation of model predictions, is within ~20% for the weak plume and ~10% for the strong plume. Predictions of neutral buoyancy level are also in reasonably good agreement among the different models, with a standard deviation ranging from 9 to 19% (the latter for the weak plume in a windy atmosphere). Overall, these discrepancies are in the range of observational uncertainty of column height. However, there are important differences amongst models in terms of local properties along the plume axis, particularly for the strong plume. Our analysis suggests that the simplified treatment of entrainment in 1D models is adequate to resolve the general behaviour of the weak plume. However, it is inadequate to capture complex features of the strong plume, such as large vortices, partial column collapse, or gravitational fountaining that strongly enhance entrainment in the lower atmosphere. We conclude that there is a need to more accurately quantify entrainment rates, improve the representation of plume radius, and incorporate the effects of column instability in future versions of 1D volcanic plume models.AC was partially supported by a grant of the International Research Promotion Office Earthquake Research Institute, the University of Tokyo. AC, GM, AN, MdMV, TEO and MC were partially supported by the EU-funded project MEDiterranean SUpersite Volcanoes (MEDSUV) (grant n. 308665). AVE acknowledges NSF Postdoctoral Fellowship EAR1250029 and a USGS Mendenhall Fellowship. MIB was supported partially by NSF-IDR and AFOSR. AJH, MJW, and JCP were partially supported by the NERC-funded project Vanaheim (grant no. NE/I01554X/1) and the EU-funded project FutureVolc (grant no. 308377). FG, GC, ST, and EK were partially supported by INSU-CNRS. We wish to thank T. ACCEPTED MANUSCRIPT ACCEPTED MANUSCRIPT 43 Koyaguchi, S. Solovitz, and an anonymous reviewer for constructive suggestions that improved the quality of the manuscript.This is the author accepted manuscript. The final version is available from Elsevier via https://doi.org/10.1016/j.jvolgeores.2016.01.01