Integrated process of images and acceleration measurements for damage detection

The use of mobile robots and UAV to catch unthinkable images together with on-site global automated acceleration measurements easy achievable by wireless sensors, able of remote data transfer, have strongly enhanced the capability of defect and damage evaluation in bridges. A sequential procedure is, here, proposed for damage monitoring and bridge condition assessment based on both: digital image processing for survey and defect evaluation and structural identification based on acceleration measurements. A steel bridge has been simultaneously inspected by UAV to acquire images using visible light, or infrared radiation, and monitored through a wireless sensor network (WSN) measuring structural vibrations. First, image processing has been used to construct a geometrical model and to quantify corrosion extension. Then, the consistent structural model has been updated based on the modal quantities identified using the acceleration measurements acquired by the deployed WSN. © 2017 The Authors. Published by Elsevier Ltd

A novel method for comparing topological models of protein structures enhanced with ligand information

This article is available open access through the publisher’s website through the link below. Copyright @ 2008 The Authors.We introduce TOPS+ strings, a highly abstract string-based model of protein topology that permits efficient computation of structure comparison, and can optionally represent ligand information. In this model, we consider loops as secondary structure elements (SSEs) as well as helices and strands; in addition we represent ligands as first class objects. Interactions between SSEs and between SSEs and ligands are described by incoming/outgoing arcs and ligand arcs, respectively; and SSEs are annotated with arc interaction direction and type. We are able to abstract away from the ligands themselves, to give a model characterized by a regular grammar rather than the context sensitive grammar of the original TOPS model. Our TOPS+ strings model is sufficiently descriptive to obtain biologically meaningful results and has the advantage of permitting fast string-based structure matching and comparison as well as avoiding issues of Non-deterministic Polynomial time (NP)-completeness associated with graph problems. Our structure comparison method is computationally more efficient in identifying distantly related proteins than BLAST, CLUSTALW, SSAP and TOPS because of the compact and abstract string-based representation of protein structure which records both topological and biochemical information including the functionally important loop regions of the protein structures. The accuracy of our comparison method is comparable with that of TOPS. Also, we have demonstrated that our TOPS+ strings method out-performs the TOPS method for the ligand-dependent protein structures and provides biologically meaningful results. Availability: The TOPS+ strings comparison server is available from http://balabio.dcs.gla.ac.uk/mallika/WebTOPS/topsplus.html.University of Glasgo

The Extended Star Formation History of the Andromeda Spheroid at 35 Kpc on the Minor Axis

Using the HST ACS, we have obtained deep optical images reaching well below the oldest main sequence turnoff in fields on the southeast minor-axis of the Andromeda Galaxy, 35 kpc from the nucleus. These data probe the star formation history in the extended halo of Andromeda -- that region beyond 30 kpc that appears both chemically and morphologically distinct from the metal-rich, highly-disturbed inner spheroid. The present data, together with our previous data for fields at 11 and 21 kpc, do not show a simple trend toward older ages and lower metallicities, as one might expect for populations further removed from the obvious disturbances of the inner spheroid. Specifically, the mean ages and [Fe/H] values at 11 kpc, 21 kpc, and 35 kpc are 9.7 Gyr and -0.65, 11.0 Gyr and -0.87, and 10.5 Gyr and -0.98, respectively. In the best-fit model of the 35 kpc population, one third of the stars are younger than 10 Gyr, while only ~10% of the stars are truly ancient and metal-poor. The extended halo thus exhibits clear evidence of its hierarchical assembly, and the contribution from any classical halo formed via early monolithic collapse must be small.Comment: Accepted for publication in The Astrophysical Journal Letters. 4 pages, latex, 2 color figure

Lagrangian approach and dissipative magnetic systems

A Lagrangian is introduced which includes the coupling between magnetic moments $\mathbf{m}$ and the degrees of freedom $\boldsymbol{\sigma}$ of a reservoir. In case the system-reservoir coupling breaks the time reversal symmetry the magnetic moments perform a damped precession around an effective field which is self-organized by the mutual interaction of the moments. The resulting evolution equation has the form of the Landau-Lifshitz-Gilbert equation. In case the bath variables are constant vector fields the moments $\mathbf{m}$ fulfill the reversible Landau-Lifshitz equation. Applying Noether's theorem we find conserved quantities under rotation in space and within the configuration space of the moments.Comment: 12 pages, 1 figur

A photometric and spectroscopic study of the new dwarf spheroidal galaxy in Hercules

Our aim is to provide as clean and as complete a sample as possible of red giant branch stars that are members of the Hercules dSph galaxy. With this sample we explore the velocity dispersion and the metallicity of the system. Stromgren photometry and multi-fibre spectroscopy are combined to provide information about the evolutionary state of the stars (via the Stromgren c_1 index) and their radial velocities. Based on this information we have selected a clean sample of red giant branch stars, and show that foreground contamination by Milky Way dwarf stars can greatly distort the results. Our final sample consists of 28 red giant branch stars in the Hercules dSph galaxy. Based on these stars we find a mean photometric metallicity of -2.35 dex which is consistent with previous studies. We find evidence for an abundance spread. Using those stars for which we have determined radial velocities we find a systemic velocity of 45.2 km/s with a dispersion of 3.72 km/s, this is lower than values found in the literature. Furthermore we identify the horizontal branch and estimate the mean magnitude of the horizontal branch of the Hercules dSph galaxy to be V_0=21.17, which corresponds to a distance of 147 kpc. We have shown that a proper cleaning of the sample results in a smaller value for the velocity dispersion of the system. This has implications for galaxy properties derived from such velocity dispersions.Comment: 24 pages, 28 figure

Stellar Kinematics of the Andromeda II Dwarf Spheroidal Galaxy

We present kinematical profiles and metallicity for the M31 dwarf spheroidal (dSph) satellite galaxy Andromeda II (And II) based on Keck DEIMOS spectroscopy of 531 red giant branch stars. Our kinematical sample is among the largest for any M31 satellite and extends out to two effective radii (r_eff = 5.3' = 1.1 kpc). We find a mean systemic velocity of -192.4+-0.5 km/s and an average velocity dispersion of sigma_v = 7.8+-1.1 km/s. While the rotation velocity along the major axis of And II is nearly zero (<1 km/s), the rotation along the minor axis is significant with a maximum rotational velocity of v_max=8.6+-1.8 km/s. We find a kinematical major axis, with a maximum rotational velocity of v_max=10.9+-2.4 km/s, misaligned by 67 degrees to the isophotal major axis. And II is thus the first dwarf galaxy with evidence for nearly prolate rotation with a v_max/sigma_v = 1.1, although given its ellipticity of epsilon = 0.10, this object may be triaxial. We measured metallicities for a subsample of our data, finding a mean metallicity of [Fe/H] = -1.39+- 0.03 dex and an internal metallicity dispersion of 0.72+-0.03 dex. We find a radial metallicity gradient with metal-rich stars more centrally concentrated, but do not observe a significant difference in the dynamics of two metallicity populations. And II is the only known dwarf galaxy to show minor axis rotation making it a unique system whose existence offers important clues on the processes responsible for the formation of dSphs.Comment: 14 pages, 10 figures, 4 tables, accepted for publication in Ap

Clean Kinematic Samples in Dwarf Spheroidals: An Algorithm for Evaluating Membership and Estimating Distribution Parameters When Contamination is Present

(abridged) We develop an algorithm for estimating parameters of a distribution sampled with contamination, employing a statistical technique known as ``expectation maximization'' (EM). Given models for both member and contaminant populations, the EM algorithm iteratively evaluates the membership probability of each discrete data point, then uses those probabilities to update parameter estimates for member and contaminant distributions. The EM approach has wide applicability to the analysis of astronomical data. Here we tailor an EM algorithm to operate on spectroscopic samples obtained with the Michigan-MIKE Fiber System (MMFS) as part of our Magellan survey of stellar radial velocities in nearby dwarf spheroidal (dSph) galaxies. These samples are presented in a companion paper and contain discrete measurements of line-of-sight velocity, projected position, and Mg index for ~1000 - 2500 stars per dSph, including some fraction of contamination by foreground Milky Way stars. The EM algorithm quantifies both dSph and contaminant distributions, returning maximum-likelihood estimates of the means and variances, as well as the probability that each star is a dSph member. Applied to our MMFS data, the EM algorithm identifies more than 5000 probable dSph members. We test the performance of the EM algorithm on simulated data sets that represent a range of sample size, level of contamination, and amount of overlap between dSph and contaminant velocity distributions. The simulations establish that for samples ranging from large (N ~3000) to small (N~30), the EM algorithm distinguishes members from contaminants and returns accurate parameter estimates much more reliably than conventional methods of contaminant removal (e.g., sigma clipping).Comment: Accepted for publication in The Astronomical Journal. Download pdf with full-resolution figures from http://www.ast.cam.ac.uk/~walker/dsph_em.pd

Applying Neural ODEs to Derive a Mechanism‐Based Model for Characterizing Maturation‐Related Serum Creatinine Dynamics in Preterm Newborns

Serum creatinine in neonates follows complex dynamics due to maturation processes, most pronounced in the first few weeks of life. The development of a mechanism‐based model describing complex dynamics requires high expertise in pharmacometric (PMX) modeling and substantial model development time. A recently published machine learning (ML) approach of low‐dimensional neural ordinary differential equations (NODEs) is capable of modeling such data from newborns automatically. However, this efficient data‐driven approach in itself does not result in a clinically interpretable model. In this work, an approach to deriving an interpretable model with reasonable PMX‐type functions is presented. This “translation” was applied to derive a PMX model for serum creatinine in neonates considering maturation processes and covariates. The developed model was compared to a previously published mechanism‐based PMX model whereas both models had similar mechanistic structures. The developed model was then utilized to simulate serum creatinine concentrations in the first few weeks of life considering different covariate values for gestational age and birth weight. The reference serum creatinine values derived from these simulations are consistent with observed serum creatinine values and previously published reference values. Thus, the presented NODE‐based ML approach to model complex serum creatinine dynamics in newborns and derive interpretable, mathematical‐statistical components similar to those in a conventional PMX model demonstrates a novel, viable approach to facilitate the modeling of complex dynamics in clinical settings and pediatric drug development

Pattern matching and pattern discovery algorithms for protein topologies

We describe algorithms for pattern matching and pattern learning in TOPS diagrams (formal descriptions of protein topologies). These problems can be reduced to checking for subgraph isomorphism and finding maximal common subgraphs in a restricted class of ordered graphs. We have developed a subgraph isomorphism algorithm for ordered graphs, which performs well on the given set of data. The maximal common subgraph problem then is solved by repeated subgraph extension and checking for isomorphisms. Despite the apparent inefficiency such approach gives an algorithm with time complexity proportional to the number of graphs in the input set and is still practical on the given set of data. As a result we obtain fast methods which can be used for building a database of protein topological motifs, and for the comparison of a given protein of known secondary structure against a motif database