Narrow Pass-Band Optical Filters for Space-Borne Remote Sensing Applications

Optical characterisation of 532 nm, 200 pm passband and 1064 nm, I mn passband LkD filters after exposure to proton irradiation, temperature cycling and angle tuning

Identification of Enterobacter sakazakii from closely related species: The use of Artificial Neural Networks in the analysis of biochemical and 16S rDNA data

BACKGROUND: Enterobacter sakazakii is an emergent pathogen associated with ingestion of infant formula and accurate identification is important in both industrial and clinical settings. Bacterial species can be difficult to accurately characterise from complex biochemical datasets and computer algorithms can potentially simplify the process. RESULTS: Artificial Neural Networks were applied to biochemical and 16S rDNA data derived from 282 strains of Enterobacteriaceae, including 189 E. sakazakii isolates, in order to identify key characteristics which could improve the identification of E. sakazakii. The models developed resulted in a predictive performance for blind (validation) data of 99.3 % correct discrimination between E. sakazakii and closely related species for both phenotypic and genotypic data. Three main regions of the partial rDNA sequence were found to be key in discriminating the species. Comparison between E. sakazakii and other strains also constitutively positive for expression of the enzyme α-glucosidase resulted in a predictive performance of 98.7 % for 16S rDNA sequence data and 100% for phenotypic data. CONCLUSION: The computationally based methods developed here show a remarkable ability in reducing data dimensionality and complexity, in order to eliminate noise from the system in order to facilitate the speed and reliability of a potential strain identification system. Furthermore, the approaches described are also able to provide valuable information regarding the population structure and distribution of individual species thus providing the foundations for novel assays and diagnostic tests for rapid identification of pathogens

BIM in facilities management applications: a case study of a large university complex

Purpose – Building information modelling (BIM) in facilities management (FM) applications is an emerging area of research based on the theoretical proposition that BIM information, generated and captured during the lifecycle of a facility, can improve its management. Using this proposition as a starting point, the purpose of this paper is to investigate the value of BIM and the challenges affecting its adoption in FM applications. Design/methodology/approach – Two inter-related research methods are utilised. The literature is utilised to identify the application areas, value and challenges of BIM in FM. Due to the lack of case studies identified in the literature review, and to provide empirical evidence of the value and challenges of BIM in FM, a case study of Northumbria University’s city campus, is used to empirically explore the value and challenges of BIM in FM. Findings – The results demonstrated that BIM value in FM stems from improvement to current manual processes of information handover; improvement to the accuracy of FM data, improvement to the accessibility of FM data and efficiency increase in work order execution. The main challenges were the lack of methodologies that demonstrate the tangible benefits of BIM in FM, the limited knowledge of implementation requirement including BIM for FM modelling requirements, the interoperability between BIM and FM technologies, the presence of disparate operational systems managing the same building and finally, the shortage of BIM skills in the FM industry. Originality/value – There is lack of real-life cases on BIM in FM especially for existing assets despite new constructions representing only 1-2 per cent of the total building stock in a typical year. The originality of this paper stems from both adding a real-life case study of BIM in FM and providing empirical evidence of both the value and challenges of BIM in FM applications

Fiber lasers and amplifiers for science and exploration at NASA Goddard Space Flight Center

We discuss present and near-term uses for high-power fiber lasers and amplifiers for NASA- specific applications including planetary topography and atmospheric spectroscopy. Fiber lasers and amplifiers offer numerous advantages for both near-term and future deployment of instruments on exploration and science remote sensing orbiting satellites. Ground-based and airborne systems provide an evolutionary path to space and a means for calibration and verification of space-borne systems. We present experimental progress on both the fiber transmitters and instrument prototypes for ongoing development efforts. These near-infrared instruments are laser sounders and lidars for measuring atmospheric carbon dioxide, oxygen, water vapor and methane and a pseudo-noise (PN) code laser ranging system. The associated fiber transmitters include high-power erbium, ytterbium, neodymium and Raman fiber amplifiers. In addition, we will discuss near-term fiber laser and amplifier requirements and programs for NASA free space optical communications, planetary topography and atmospheric spectroscopy

The Next Decade of Astroinformatics and Astrostatistics

Over the past century, major advances in astronomy and astrophysics have been largely driven by improvements in instrumentation and data collection. With the amassing of high quality data from new telescopes, and especially with the advent of deep and large astronomical surveys, it is becoming clear that future advances will also rely heavily on how those data are analyzed and interpreted. New methodologies derived from advances in statistics, computer science, and machine learning are beginning to be employed in sophisticated investigations that are not only bringing forth new discoveries, but are placing them on a solid footing. Progress in wide-field sky surveys, interferometric imaging, precision cosmology, exoplanet detection and characterization, and many subfields of stellar, Galactic and extragalactic astronomy, has resulted in complex data analysis challenges that must be solved to perform scientific inference. Research in astrostatistics and astroinformatics will be necessary to develop the state-of-the-art methodology needed in astronomy. Overcoming these challenges requires dedicated, interdisciplinary research. We recommend: (1) increasing funding for interdisciplinary projects in astrostatistics and astroinformatics; (2) dedicating space and time at conferences for interdisciplinary research and promotion; (3) developing sustainable funding for long-term astrostatisics appointments; and (4) funding infrastructure development for data archives and archive support, state-of-the-art algorithms, and efficient computing

Evaluating the Environmental Performance of the U.S. Next Generation Air Transportation System

The environmental impacts of several possible U.S. Next Generation Air Transportation scenarios have been quantitatively evaluated for noise, air-quality, fuel-efficiency, and CO2 impacts. Three principal findings have emerged. (1) 2025 traffic levels about 30% higher than 2006 are obtained by increasing traffic according to FAA projections while also limiting traffic at each airport using reasonable ratios of demand to capacity. NextGen operational capabilities alone enable attainment of an additional 10-15% more flights beyond that 2025 baseline level with negligible additional noise, air-quality, and fuel-efficiency impacts. (2) The addition of advanced engine and airframe technologies provides substantial additional reductions in noise and air-quality impacts, and further improves fuel efficiency. 2025 environmental goals based on projected system-wide improvement rates of about 1% per year for noise and fuel-efficiency (an air-quality goal is not yet formulated) are achieved using this new vehicle technology. (3) Overall air-transport "product", as measured by total flown distance or total payload distance, increases by about 50% relative to 2006, but total fuel consumption and CO2 production increase by only about 40% using NextGen operational capabilities. With the addition of advanced engine/airframe technologies, the increase in total fuel consumption and CO2 production can be reduced to about 30%

Environmental impact analysis with the airspace concept evaluation system

The National Aeronautics and Space Administration (NASA) Ames Research Center has developed the Airspace Concept Evaluation System (ACES), which is a fast-time simulation tool for evaluating Air Traffic Management (ATM) systems. This paper describes linking a capability to ACES which can analyze the environmental impact of proposed future ATM systems. This provides the ability to quickly evaluate metrics associated with environmental impacts of aviation for inclusion in multi-dimensional cost-benefit analysis of concepts for evolution of the National Airspace System (NAS) over the next several decades. The methodology used here may be summarized as follows: 1) Standard Federal Aviation Administration (FAA) noise and emissions-inventory models, the Noise Impact Routing System (NIRS) and the Emissions and Dispersion Modeling System (EDMS), respectively, are linked to ACES simulation outputs; 2) appropriate modifications are made to ACES outputs to incorporate all information needed by the environmental models (e.g., specific airframe and engine data); 3) noise and emissions calculations are performed for all traffic and airports in the study area for each of several scenarios, as simulated by ACES; and 4) impacts of future scenarios are compared to the current NAS baseline scenario. This paper also provides the results of initial end-to-end, proof-of-concept runs of the integrated ACES and environmental-modeling capability. These preliminary results demonstrate that if no growth is likely to be impeded by significant environmental impacts that could negatively affect communities throughout the nation

Partitioning the variance between space and time

Here we decompose the space-time variance of near-surface air temperature using monthly observations for the global land surface (excluding Antarctica) from 1901-2000. To do that, we developed a new method for partitioning the total space-time variance, here called the grand variance, into separate spatial and temporal components. The temporal component is, in turn, further partitioned into the variance relating to different time periods and we use monthly data to decompose intra- and inter-annual components of the variance. The results show that the spatial and temporal components of the variance of near-surface air temperature have both, on average, decreased over time primarily because of reductions in the equator-to-pole (northern) temperature gradient, and because in cold regions, winter is generally warming faster than summer. We also found that in most regions, the inter-annual variance in near-surface air temperature has increased

Autofluorescence in eleocytes of some earthworm species.

Immunocompetent cells of earthworms, coelomocytes, comprise adherent amoebocytes and granular eleocytes (chloragocytes). Both cell populations can be expelled via dorsal pores of adult earthworms by exposure to an electric current (4.5 V) for 1 min. Analysis by phase contrast/fluorescence microscopy and flow cytometry demonstrated that eleocyte population of several species exhibits a strong autofluorescence. A high percentage (11-35%) of autofluorescent eleocytes was recorded in Allolobophora chlorotica, Dendrodrilus rubidus, Eisenia fetida, and Octolasion sp. (O. cyaneum, O. tyrtaeum tyrtaeum and O. tyrtaeum lacteum). In contrast, autofluorescent coelomocytes were exceptionally scarce (less than 1%) in representative Aporrectodea sp. (A. caliginosa and A. longa) and Lumbricus sp. (L. castaneus, L. festivus, L. rubellus, L. terrestris). Thus, this paper for the first time describes profound intrinsic fluorescence of eleocytes in some--but not all--earthworm species. The function (if any) and inter-species differences of the autofluorescent coelomocytes still remain elusive