Sensitivity analysis of the space shuttle to ascent wind profiles

A parametric sensitivity analysis of the space shuttle ascent flight to the wind profile is presented. Engineering systems parameters are obtained by flight simulations using wind profile models and samples of detailed (Jimsphere) wind profile measurements. The wind models used are the synthetic vector wind model, with and without the design gust, and a model of the vector wind change with respect to time. From these comparison analyses an insight is gained on the contribution of winds to ascent subsystems flight parameters

Analyzing Machupo virus-receptor binding by molecular dynamics simulations

In many biological applications, we would like to be able to computationally predict mutational effects on affinity in protein-protein interactions. However, many commonly used methods to predict these effects perform poorly in important test cases. In particular, the effects of multiple mutations, non-alanine substitutions, and flexible loops are difficult to predict with available tools and protocols. We present here an existing method applied in a novel way to a new test case; we interrogate affinity differences resulting from mutations in a host-virus protein-protein interface. We use steered molecular dynamics (SMD) to computationally pull the machupo virus (MACV) spike glycoprotein (GP1) away from the human transferrin receptor (hTfR1). We then approximate affinity using the maximum applied force of separation and the area under the force-versus-distance curve. We find, even without the rigor and planning required for free energy calculations, that these quantities can provide novel biophysical insight into the GP1/hTfR1 interaction. First, with no prior knowledge of the system we can differentiate among wild type and mutant complexes. Moreover, we show that this simple SMD scheme correlates well with relative free energy differences computed via free energy perturbation. Second, although the static co-crystal structure shows two large hydrogen-bonding networks in the GP1/hTfR1 interface, our simulations indicate that one of them may not be important for tight binding. Third, one viral site known to be critical for infection may mark an important evolutionary suppressor site for infection-resistant hTfR1 mutants. Finally, our approach provides a framework to compare the effects of multiple mutations, individually and jointly, on protein-protein interactions.Comment: 33 pages, 8 figures, 5 table

The space shuttle launch vehicle aerodynamic verification challenges

The Space Shuttle aerodynamics and performance communities were challenged to verify the Space Shuttle vehicle (SSV) aerodynamics and system performance by flight measurements. Historically, launch vehicle flight test programs which faced these same challenges were unmanned instrumented flights of simple aerodynamically shaped vehicles. However, the manned SSV flight test program made these challenges more complex because of the unique aerodynamic configuration powered by the first man-rated solid rocket boosters (SRB). The analyses of flight data did not verify the aerodynamics or performance preflight predictions of the first flight of the Space Transportation System (STS-1). However, these analyses have defined the SSV aerodynamics and verified system performance. The aerodynamics community also was challenged to understand the discrepancy between the wind tunnel and flight defined aerodynamics. The preflight analysis challenges, the aerodynamic extraction challenges, and the postflight analyses challenges which led to the SSV system performance verification and which will lead to the verification of the operational ascent aerodynamics data base are presented

Remaking the IT Management Curriculum: A Novel Approach

We report on an experiment in redesign of curriculum for Information Technology (IT) management courses, a synthetic approach that attempts to combine the best features of explanation- and experience-based approaches. The IVK case series is a fictitious though realitybased story about the struggles of a newly appointed, not-technically-trained CIO in his first year on the job. The series constitutes a true-to-life novel, intended to involve students in an engaging story that simultaneously explores the nuances of major IT management issues. Three principles guided our development of this curriculum: 1) Emphasis on the business aspects of IT, independent of underlying technologies; 2) Student derivation of cumulative management frameworks arrived at via inductive in-class discussion; and 3) Identification of a set of core issues most vital in IT management practice, as a business discipline. We report results from using the curriculum with undergraduate and graduate students, and with executives at a multinational corporation

Evaluation of candidate probiotic strains for gilthead sea bream larvae (Sparus aurata) using an in vivo approach

Aims: The aim of this study was to evaluate the effect of six bacterial strains on gilthead sea bream larvae (Sparus aurata). Methods and Results: Six bacterial strains isolated from well-performing live food cultures were identified by sequencing fragments of their 16s rDNA genome to the genus level as Cytophaga sp., Roseobacter sp., Ruergeria sp., Paracoccus sp., Aeromonas sp. and Shewanella sp. Survival rates of gilthead sea bream larvae transferred to seawater added these bacterial strains at concentrations of 6 +/- 0.3 x 10(5) bacteria ml(-1) were similar to those of larvae transferred to sterilized seawater and showed an average of 86% at 9 days after hatching, whereas, survival rates of larvae transferred to filtered seawater were lower (P < 0.05), and showed an average of 39%, 9 days after hatching. Conclusion: Several bacterial strains isolated from well-performing live food cultures showed a positive effect for sea bream larvae when compared with filtered seawater. Significance and Impact of the Study: The approach used in this study could be applied as an in vivo evaluation method of candidate probiotic strains used in the rearing of marine fish larvae

Automatic Nonnutritive Suck Waveform Discrimination and Feature Extraction in Preterm Infants

Background and Objective: +e emergence of the nonnutritive suck (NNS) pattern in preterm infants reflects the integrity of the brain and is used by clinicians in the neonatal intensive care unit (NICU) to assess feeding readiness and oromotor development. A critical need exists for an integrated software platform that provides NNS signal preprocessing, adaptive waveform discrimination, feature detection, and batch processing of big data sets across multiple NICU sites. +us, the goal was to develop and describe a crossplatform graphical user interface (GUI) and terminal application known as NeoNNS for single and batch file time series and frequency-domain analyses of NNS compression pressure waveforms using analysis parameters derived from previous research on NNS dynamics. Methods. NeoNNS was implemented with Python and the Tkinter GUI package. +e NNS signal-processing pipeline included a low-pass filter, asymmetric regression baseline correction, NNS peak detection, and NNS burst classification. Data visualizations and parametric analyses included time- and frequency-domain view, NNS spatiotemporal index view, and feature cluster analysis to model oral feeding readiness. Results. 568 suck assessment files sampled from 30 extremely preterm infants were processed in the batch mode (\u3c50 minutes) to generate time- and frequency-domain analyses of infant NNS pressure waveform data. NNS cycle discrimination and NNS burst classification yield quantification of NNS waveform features as a function of postmenstrual age. Hierarchical cluster analysis (based on the Tsfresh python package and NeoNNS) revealed the capability to label NNS records for feeding readiness. Conclusions. NeoNNS provides a versatile software platform to rapidly quantify the dynamics of NNS development in time and frequency domains at cribside over repeated sessions for an individual baby or among large numbers of preterm infants at multiple hospital sites to support big data analytics. +e hierarchical cluster feature analysis facilitates modeling of feeding readiness based on quantitative features of the NNS compression pressure waveform

Automatic Nonnutritive Suck Waveform Discrimination and Feature Extraction in Preterm Infants

Background and Objective: The emergence of the nonnutritive suck (NNS) pattern in preterm infants reflects the integrity of the brain and is used by clinicians in the neonatal intensive care unit (NICU) to assess feeding readiness and oromotor development. A critical need exists for an integrated software platform that provides NNS signal preprocessing, adaptive waveform discrimination, feature detection, and batch processing of big data sets across multiple NICU sites. Thus, the goal was to develop and describe a crossplatform graphical user interface (GUI) and terminal application known as NeoNNS for single and batch file time series and frequency-domain analyses of NNS compression pressure waveforms using analysis parameters derived from previous research on NNS dynamics. Methods. NeoNNS was implemented with Python and the Tkinter GUI package. The NNS signal-processing pipeline included a low-pass filter, asymmetric regression baseline correction, NNS peak detection, and NNS burst classification. Data visualizations and parametric analyses included time- and frequency-domain view, NNS spatiotemporal index view, and feature cluster analysis to model oral feeding readiness. Results. 568 suck assessment files sampled from 30 extremely preterm infants were processed in the batch mode (\u3c50 minutes) to generate time- and frequency-domain analyses of infant NNS pressure waveform data. NNS cycle discrimination and NNS burst classification yield quantification of NNS waveform features as a function of postmenstrual age. Hierarchical cluster analysis (based on the Tsfresh python package and NeoNNS) revealed the capability to label NNS records for feeding readiness. Conclusions. NeoNNS provides a versatile software platform to rapidly quantify the dynamics of NNS development in time and frequency domains at cribside over repeated sessions for an individual baby or among large numbers of preterm infants at multiple hospital sites to support big data analytics. The hierarchical cluster feature analysis facilitates modeling of feeding readiness based on quantitative features of the NNS compression pressure waveform

The impact of ocean acidification on the functional morphology of foraminifera

This work was supported by the NERC UK Ocean Acidification Research Programme grant NE/H017445/1. WENA acknowledges NERC support (NE/G018502/1). DMP received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland). MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions.Culturing experiments were performed on sediment samples from the Ythan Estuary, N. E. Scotland, to assess the impacts of ocean acidification on test surface ornamentation in the benthic foraminifer Haynesina germanica. Specimens were cultured for 36 weeks at either 380, 750 or 1000 ppm atmospheric CO2. Analysis of the test surface using SEM imaging reveals sensitivity of functionally important ornamentation associated with feeding to changing seawater CO2 levels. Specimens incubated at high CO2 levels displayed evidence of shell dissolution, a significant reduction and deformation of ornamentation. It is clear that these calcifying organisms are likely to be vulnerable to ocean acidification. A reduction in functionally important ornamentation could lead to a reduction in feeding efficiency with consequent impacts on this organism’s survival and fitness.Publisher PDFPeer reviewe

Long-range coupling and scalable architecture for superconducting flux qubits

Constructing a fault-tolerant quantum computer is a daunting task. Given any design, it is possible to determine the maximum error rate of each type of component that can be tolerated while still permitting arbitrarily large-scale quantum computation. It is an underappreciated fact that including an appropriately designed mechanism enabling long-range qubit coupling or transport substantially increases the maximum tolerable error rates of all components. With this thought in mind, we take the superconducting flux qubit coupling mechanism described in PRB 70, 140501 (2004) and extend it to allow approximately 500 MHz coupling of square flux qubits, 50 um a side, at a distance of up to several mm. This mechanism is then used as the basis of two scalable architectures for flux qubits taking into account crosstalk and fault-tolerant considerations such as permitting a universal set of logical gates, parallelism, measurement and initialization, and data mobility.Comment: 8 pages, 11 figure