Parametric vision simulation study, part 2 Final report

Effects of landing site redesignation on visibility during manned lunar landin

Observation of HCN hyperfine line anomalies towards low- and high-mass star-forming cores

HCN is becoming a popular choice of molecule for studying star formation in both low- and high-mass regions and for other astrophysical sources from comets to high-redshift galaxies. However, a major and often overlooked difficulty with HCN is that it can exhibit non-local thermodynamic equilibrium (non-LTE) behaviour in its hyperfine line structure. Individual hyperfine lines can be strongly boosted or suppressed. In low-mass star-forming cloud observations, this could possibly lead to large errors in the calculation of opacity and excitation temperature, while in massive star-forming clouds, where the hyperfine lines are blended due to turbulent broadening, errors will arise in infall measurements that are based on the separation of the peaks in a self-absorbed profile. The underlying line shape cannot be known for certain if hyperfine anomalies are present. We present a first observational investigation of these anomalies across a range of conditions and transitions by carrying out a survey of low-mass starless cores (in Taurus & Ophiuchus) and high-mass protostellar objects (in the G333 giant molecular cloud) using hydrogen cyanide (HCN) J=1-0 and J=3-2 emission lines. We quantify the degree of anomaly in these two rotational levels by considering ratios of individual hyperfine lines compared to LTE values. We find that all the cores observed show some degree of anomaly while many of the lines are severely anomalous. We conclude that HCN hyperfine anomalies are common in both lines in both low-mass and high-mass protostellar objects, and we discuss the differing hypotheses for the generation of the anomalies. In light of the results, we favour a line overlap effect for the origins of the anomalies. We discuss the implications for the use of HCN as a dynamical tracer and suggest in particular that the J=1-0, F=0-1 hyperfine line should be avoided in quantitative calculations.Comment: 17 pages, 8 figure

Linearisation Method of DML-Based Transmitters for Optical Communications Part I: Theory and Simulation Studies

The performance of directly-modulated lasers (DMLs) is severely impaired by nonlinear behaviour when operating at high symbol rates. We propose a new linearization method for DML-based transmitters which can significantly reduce nonlinearity. This method, named the Stretched A (StrA) method, relies on the generation of an approximation to the ideal modulating current that generates a linear optical output waveform. In Part I of this work, the theoretical framework of the proposed method is presented and detailed simulation studies illustrate its implementation and demonstrate the benefits it offers. Although the method is applicable to any type of DML, the simulation studies presented herein focus on optical links based on vertical-cavity surface-emitting lasers (VCSELs) as these comprise the vast majority of short-reach optical links. Part II of this work presents the proof-of-principle experimental demonstration of this new linearization method and discusses its possible implementations using either analog or digital electronics

Subsonic aerodynamic and flutter characteristics of several wings calculated by the SOUSSA P1.1 panel method

The SOUSSA (steady, oscillatory, and unsteady subsonic and supersonic aerodynamics) program is the computational implementation of a general potential flow analysis (by the Green's function method) that can generate pressure distributions on complete aircraft having arbitrary shapes, motions and deformations. Some applications of the initial release version of this program to several wings in steady and oscillatory motion, including flutter are presented. The results are validated by comparisons with other calculations and experiments. Experiences in using the program as well as some recent improvements are described

Between Treewidth and Clique-width

Many hard graph problems can be solved efficiently when restricted to graphs of bounded treewidth, and more generally to graphs of bounded clique-width. But there is a price to be paid for this generality, exemplified by the four problems MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set that are all FPT parameterized by treewidth but none of which can be FPT parameterized by clique-width unless FPT = W[1], as shown by Fomin et al [7, 8]. We therefore seek a structural graph parameter that shares some of the generality of clique-width without paying this price. Based on splits, branch decompositions and the work of Vatshelle [18] on Maximum Matching-width, we consider the graph parameter sm-width which lies between treewidth and clique-width. Some graph classes of unbounded treewidth, like distance-hereditary graphs, have bounded sm-width. We show that MaxCut, Graph Coloring, Hamiltonian Cycle and Edge Dominating Set are all FPT parameterized by sm-width

Monolithic in-based III-V compound semiconductor focal plane array cell with single stage CCD output

A monolithic semiconductor imager includes an indium-based III-V compound semiconductor monolithic active layer of a first conductivity type, an array of plural focal plane cells on the active layer, each of the focal plane cells including a photogate over a top surface of the active layer, a readout circuit dedicated to the focal plane cell including plural transistors formed monolithically with the monolithic active layer and a single-stage charge coupled device formed monolithically with the active layer between the photogate and the readout circuit for transferring photo-generated charge accumulated beneath the photogate during an integration period to the readout circuit. The photogate includes thin epitaxial semiconductor layer of a second conductivity type overlying the active layer and an aperture electrode overlying a peripheral portion of the thin epitaxial semiconductor layer, the aperture electrode being connectable to a photogate bias voltage

Cluster Editing: Kernelization based on Edge Cuts

Kernelization algorithms for the {\sc cluster editing} problem have been a popular topic in the recent research in parameterized computation. Thus far most kernelization algorithms for this problem are based on the concept of {\it critical cliques}. In this paper, we present new observations and new techniques for the study of kernelization algorithms for the {\sc cluster editing} problem. Our techniques are based on the study of the relationship between {\sc cluster editing} and graph edge-cuts. As an application, we present an ${\cal O}(n^2)$-time algorithm that constructs a $2k$ kernel for the {\it weighted} version of the {\sc cluster editing} problem. Our result meets the best kernel size for the unweighted version for the {\sc cluster editing} problem, and significantly improves the previous best kernel of quadratic size for the weighted version of the problem

Estimation of Absolute States of Human Skeletal Muscle via Standard B-Mode Ultrasound Imaging and Deep Convolutional Neural Networks

Objective: To test automated in vivo estimation of active and passive skeletal muscle states using ultrasonic imaging. Background: Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimation of skeletal muscle states. Ultrasound (US) allows non-invasive imaging of muscle, yet current computational approaches have never achieved simultaneous extraction nor generalisation of independently varying, active and passive states. We use deep learning to investigate the generalizable content of 2D US muscle images. Method: US data synchronized with electromyography of the calf muscles, with measures of joint moment/angle were recorded from 32 healthy participants (7 female, ages: 27.5, 19-65). We extracted a region of interest of medial gastrocnemius and soleus using our prior developed accurate segmentation algorithm. From the segmented images, a deep convolutional neural network was trained to predict three absolute, driftfree, components of the neurobiomechanical state (activity, joint angle, joint moment) during experimentally designed, simultaneous, independent variation of passive (joint angle) and active (electromyography) inputs. Results: For all 32 held-out participants (16-fold cross-validation) the ankle joint angle, electromyography, and joint moment were estimated to accuracy 55±8%, 57±11%, and 46±9% respectively. Significance: With 2D US imaging, deep neural networks can encode in generalizable form, the activitylength-tension state relationship of these muscles. Observation only, low power, 2D US imaging can provide a new category of technology for non-invasive estimation of neural output, length and tension in skeletal muscle. This proof of principle has value for personalised muscle assessment in pain, injury, neurological conditions, neuropathies, myopathies and ageing

The conserved arginine 380 of Hsp90 is not a catalytic residue, but stabilizes the closed conformation required for ATP hydrolysis

Hsp90, a dimeric ATP‐dependent molecular chaperone, is required for the folding and activation of numerous essential substrate “client” proteins including nuclear receptors, cell cycle kinases, and telomerase. Fundamental to its mechanism is an ensemble of dramatically different conformational states that result from nucleotide binding and hydrolysis and distinct sets of interdomain interactions. Previous structural and biochemical work identified a conserved arginine residue (R380 in yeast) in the Hsp90 middle domain (MD) that is required for wild type hydrolysis activity in yeast, and hence proposed to be a catalytic residue. As part of our investigations on the origins of species‐specific differences in Hsp90 conformational dynamics we probed the role of this MD arginine in bacterial, yeast, and human Hsp90s using a combination of structural and functional approaches. While the R380A mutation compromised ATPase activity in all three homologs, the impact on ATPase activity was both variable and much more modest (2–7 fold) than the mutation of an active site glutamate (40 fold) known to be required for hydrolysis. Single particle electron microscopy and small‐angle X‐ray scattering revealed that, for all Hsp90s, mutation of this arginine abrogated the ability to form the closed “ATP” conformational state in response to AMPPNP binding. Taken together with previous mutagenesis data exploring intra‐ and intermonomer interactions, these new data suggest that R380 does not directly participate in the hydrolysis reaction as a catalytic residue, but instead acts as an ATP‐sensor to stabilize an NTD‐MD conformation required for efficient ATP hydrolysis.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92411/1/2103_ftp.pd