Field-winding fault detection in synchronous machines with static excitation through frequency response analysis.

Frequency Response Analysis is a well-known technique for the diagnosis of power transformers. Currently, this technique is under research for its application in rotary electrical machines. This paper presents significant results on the application of Frequency Response Analysis to fault detection in field winding of synchronous machines with static excitation. First, the influence of the rotor position on the frequency response is evaluated. Secondly, some relevant test results are shown regarding ground fault and inter-turn fault detection in field windings at standstill condition. The influence of the fault resistance value is also taken into account. This paper also studies the applicability of Frequency Response Analysis in fault detection in field windings while rotating. This represents an important feature because some defects only appear with the machine rated speed. Several laboratory test results show the applicability of this fault detection technique in field windings at full speed with no excitation current.

A consistent method of analysis of RC shell structures

In this paper some topics related to the design of reinforced concrete (RC) shells are addressed. The influence of the reinforcement layout on the service and ultimate behavior of the shell structure is commented. The well established methodology for dimensioning and verifying RC sections of beam structures is extended. In this way it is possible to treat within a unified procedure the design and verification of RC two dimensional structures, in particular membrane and shell structures. Realistic design situations as multiple steel farnilies and non orthogonal reinforcement layout can be handled. Finally, some examples and applications of the proposed methodology are presented.

A Toolbox for Quantitative Gene Expression in Varroa destructor : RNA Degradation in Field Samples and Systematic Analysis of Reference Gene Stability

Funding: This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 613960 (SMARTBEES) (http://www.smartbees-fp7.eu/) and Veterinary Medicines Directorate, Department for Environment Food & Rural Affairs (Project # VM0517) (https://www.gov.uk/government/organisations/veterinary-medicines-directorate). CHM was supported by a Biosciences Knowledge Transfer Network Biotechnology and Biological Sciences Research Council (KTN-BBSRC CASE) Studentship (BB/L502467/1) (http://www.bbsrc.ac.uk/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgments We gratefully acknowledge Mr Sebastian Bacz’s expert help and advice with beekeeping.

Sources of selection bias in evaluating social programs: An interpretation of conventional measures and evidence on the effectiveness of matching as a program evaluation method

This paper decomposes the conventional measure of selection bias in observational studies into three components. The first two components are due to differences in the distributions of characteristics between participant and nonparticipant (comparison) group members: the first arises from differences in the supports, and the second from differences in densities over the region of common support. The third component arises from selection bias precisely defined. Using data from a recent social experiment, we find that the component due to selection bias, precisely defined, is smaller than the first two components. However, selection bias still represents a substantial fraction of the experimental impact estimate. The empirical performance of matching methods of program evaluation is also examined. We find that matching based on the propensity score eliminates some but not all of the measured selection bias, with the remaining bias still a substantial fraction of the estimated impact. We find that the support of the distribution of propensity scores for the comparison group is typically only a small portion of the support for the participant group. For values outside the common support, it is impossible to reliably estimate the effect of program participation using matching methods. If the impact of participation depends on the propensity score, as we find in our data, the failure of the common support condition severely limits matching compared with random assignment as an evaluation estimator.

Patterned library analysis: A method for the quantitative assessment of hypotheses concerning the determinants of protein structure

Site-directed mutagenesis and combinatorial libraries are powerful tools for providing information about the relationship between protein sequence and structure. Here we report two extensions that expand the utility of combinatorial mutagenesis for the quantitative assessment of hypotheses about the determinants of protein structure. First, we show that resin-splitting technology, which allows the construction of arbitrarily complex libraries of degenerate oligonucleotides, can be used to construct more complex protein libraries for hypothesis testing than can be constructed from oligonucleotides limited to degenerate codons. Second, using eglin c as a model protein, we show that regression analysis of activity scores from library data can be used to assess the relative contributions to the specific activity of the amino acids that were varied in the library. The regression parameters derived from the analysis of a 455-member sample from a library wherein four solvent-exposed sites in an α-helix can contain any of nine different amino acids are highly correlated (P < 0.0001, R2 = 0.97) to the relative helix propensities for those amino acids, as estimated by a variety of biophysical and computational techniques.

Highly specific protein sequence motifs for genome analysis

We present a method for discovering conserved sequence motifs from families of aligned protein sequences. The method has been implemented as a computer program called emotif (http://motif.stanford.edu/emotif). Given an aligned set of protein sequences, emotif generates a set of motifs with a wide range of specificities and sensitivities. emotif also can generate motifs that describe possible subfamilies of a protein superfamily. A disjunction of such motifs often can represent the entire superfamily with high specificity and sensitivity. We have used emotif to generate sets of motifs from all 7,000 protein alignments in the blocks and prints databases. The resulting database, called identify (http://motif.stanford.edu/identify), contains more than 50,000 motifs. For each alignment, the database contains several motifs having a probability of matching a false positive that range from 10−10 to 10−5. Highly specific motifs are well suited for searching entire proteomes, while generating very few false predictions. identify assigns biological functions to 25–30% of all proteins encoded by the Saccharomyces cerevisiae genome and by several bacterial genomes. In particular, identify assigned functions to 172 of proteins of unknown function in the yeast genome.

A mean field model of ligand-protein interactions: implications for the structural assessment of human immunodeficiency virus type 1 protease complexes and receptor-specific binding.

We propose a general mean field model of ligand-protein interactions to determine the thermodynamic equilibrium of a system at finite temperature. The method is employed in structural assessments of two human immuno-deficiency virus type 1 protease complexes where the gross effects of protein flexibility are incorporated by utilizing a data base of crystal structures. Analysis of the energy spectra for these complexes has revealed that structural and thermo-dynamic aspects of molecular recognition can be rationalized on the basis of the extent of frustration in the binding energy landscape. In particular, the relationship between receptor-specific binding of these ligands to human immunodeficiency virus type 1 protease and a minimal frustration principle is analyzed.

Pipe3D, a pipeline to analyze integral field spectroscopy DATA: II. Analysis sequence and CALIFA dataproducts

We present PIPE3D, an analysis pipeline based on the FIT3D fitting tool, developed to explore the properties of the stellar populations and ionized gas of integral field spectroscopy (IFS) data. PIPE3D was created to provide coherent, simple to distribute, and comparable dataproducts, independently of the origin of the data, focused on the data of the most recent IFU surveys (e.g., CALIFA, MaNGA, and SAMI), and the last generation IFS instruments (e.g., MUSE). In this article we describe the different steps involved in the analysis of the data, illustrating them by showing the dataproducts derived for NGC 2916, observed by CALIFA and P-MaNGA. As a practical example of the pipeline we present the complete set of dataproducts derived for the 200 datacubes that comprises the V500 setup of the CALIFA Data Release 2 (DR2), making them freely available through the network. Finally, we explore the hypothesis that the properties of the stellar populations and ionized gas of galaxies at the effective radius are representative of the overall average ones, finding that this is indeed the case.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

A Community Analysis of the Implementation for Household Curbside Recycling Programs: A Diversionary Method to Control Municipal Solid Waste

The Municipality of Anchorage (MOA) is required to better manage, operate and control municipal solid waste (MSW) after the Anchorage Assembly instituted a Zero Waste Policy. Two household curbside recycling programs (CRPs), pay-as-you-throw (PAYT) and single-stream, were compared and evaluated to determine an optimal municipal solid waste diversion method for households within the MOA. The analyses find: (1) a CRP must be designed from comprehensive analysis, models and data correlation that combine demographic and psychographic variables; and (2) CRPs can be easily adjusted towards community-specific goals using technology, such as Geographic Information System (GIS) and Radio Frequency Identification (RFID). Combining resources of policy-makers, businesses, and other viable actors are necessary components to produce a sustainable, economically viable curbside recycling program.

Analysis of the zone connecting consecutive sectors in distillation columns by the Ponchon-Savarit method

McCabe-Thiele and Ponchon-Savarit methods are two classical graphical methods for the design of binary distillation columns very useful for didactical purposes and for preliminary calculations. Nevertheless, their description in the literature is not complete and not all the cases are analysed. To complete the academic literature dealing with this subject we have generalized equations for the operating lines or DP that define the change between two consecutive sectors ΔkC for any feed condition, together with the different possibilities to extract products or to add or remove heat. A consistent analysis of what may happen when changing between sectors in the column is presented.

Topological SLAM using a graph-matching based method on omnidirectional images

Comunicación presentada en el XI Workshop of Physical Agents, Valencia, 9-10 septiembre 2010.

Development of a novel pyrolysis-gas chromatography/mass spectrometry method for the analysis of poly(lactic acid) thermal degradation products

Thermal degradation of PLA is a complex process since it comprises many simultaneous reactions. The use of analytical techniques, such as differential scanning calorimetry (DSC) and thermogravimetry (TGA), yields useful information but a more sensitive analytical technique would be necessary to identify and quantify the PLA degradation products. In this work the thermal degradation of PLA at high temperatures was studied by using a pyrolyzer coupled to a gas chromatograph with mass spectrometry detection (Py-GC/MS). Pyrolysis conditions (temperature and time) were optimized in order to obtain an adequate chromatographic separation of the compounds formed during heating. The best resolution of chromatographic peaks was obtained by pyrolyzing the material from room temperature to 600 °C during 0.5 s. These conditions allowed identifying and quantifying the major compounds produced during the PLA thermal degradation in inert atmosphere. The strategy followed to select these operation parameters was by using sequential pyrolysis based on the adaptation of mathematical models. By application of this strategy it was demonstrated that PLA is degraded at high temperatures by following a non-linear behaviour. The application of logistic and Boltzmann models leads to good fittings to the experimental results, despite the Boltzmann model provided the best approach to calculate the time at which 50% of PLA was degraded. In conclusion, the Boltzmann method can be applied as a tool for simulating the PLA thermal degradation.

A Computational Method based on Radio Frequency Technologies for the Analysis of Accessibility of Disabled People in Sustainable Cities

The sustainability strategy in urban spaces arises from reflecting on how to achieve a more habitable city and is materialized in a series of sustainable transformations aimed at humanizing different environments so that they can be used and enjoyed by everyone without exception and regardless of their ability. Modern communication technologies allow new opportunities to analyze efficiency in the use of urban spaces from several points of view: adequacy of facilities, usability, and social integration capabilities. The research presented in this paper proposes a method to perform an analysis of movement accessibility in sustainable cities based on radio frequency technologies and the ubiquitous computing possibilities of the new Internet of Things paradigm. The proposal can be deployed in both indoor and outdoor environments to check specific locations of a city. Finally, a case study in a controlled context has been simulated to validate the proposal as a pre-deployment step in urban environments.

The outburst decay of the low magnetic field magnetar SWIFT J1822.3−1606: phase-resolved analysis and evidence for a variable cyclotron feature

We study the timing and spectral properties of the low-magnetic field, transient magnetar SWIFT J1822.3−1606 as it approached quiescence. We coherently phase-connect the observations over a time-span of ∼500 d since the discovery of SWIFT J1822.3−1606 following the Swift-Burst Alert Telescope (BAT) trigger on 2011 July 14, and carried out a detailed pulse phase spectroscopy along the outburst decay. We follow the spectral evolution of different pulse phase intervals and find a phase and energy-variable spectral feature, which we interpret as proton cyclotron resonant scattering of soft photon from currents circulating in a strong (≳1014 G) small-scale component of the magnetic field near the neutron star surface, superimposed to the much weaker (∼3 × 1013 G) magnetic field. We discuss also the implications of the pulse-resolved spectral analysis for the emission regions on the surface of the cooling magnetar.