Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the fixation quality of cementless hip prostheses using a vibrational technique

Vibration analysis can be used as a more sensitive alternative to conventional techniques for the detection of loosening of total hip replacement (THR) components. The vibration modes of the human femur and of selected THR prosthetic stems were studied by experimental modal analysis using a CADA-X system and by finite element simulation using MARC/Mentat software. Two hypotheses were formulated: (1) the differences between the vibrational behaviour of an intact femur and of the system formed by a femur and an implanted prosthesis will increase with increasing complexity of the mode shapes of the system; (2) when a prosthesis is implanted in a femur, the vibration modes of the prosthesis will be more affected by this interaction than the modes of the femur. After confirming these hypotheses, a method for peroperative assessment of the fixation quality of a THR stem was derived, based on the frequency shifts of the vibration modes of the system.
Non-contiguous finished genome sequence of Phocaeicola abscessus type strain 7401987T

Phocaeicola abscessus strain 7401987T is the sole member of the genus Phocaeicola. This bacterium is Gram-negative, non-spore-forming, coccoid to rod-shaped and motile by lophotrichous flagella. It was isolated from a human brain abscess sample. In this work, we describe a set of features of this organism, together with the complete genome sequence and annotation. The 2,530,616 bp long genome contains 2,090 protein-coding genes and 54 RNA genes, including 4 rRNA operons.
Relationship of SELE A561C and G98T Variants With the Susceptibility to CAD

AbstractPublished genetic association studies have produced controversial results regarding the association of SELE gene polymorphisms (A516C and G98T) and CAD susceptibility. We therefore chose to perform a meta-analysis to determine the association.Twenty-seven eligible articles were identified through electronic databases, providing 5170 CAD cases and 4996 controls. Fixed-effects or random-effects summary ORs were calculated to estimate the risk of CAD in relation to A516C and G98T. Forest plots and funnel plots were constructed by Stata software 12.0. A strong association was observed between A516C and susceptibility of CAD among 4757 cases and 4272 controls. The summary OR was greatest in individuals carrying the CC genotype (OR = 1.91, 95% CI, 1.12–3.25). A significantly increased risk was indicated in both Caucasians and Asians. The analyses by disease type showed a significant increase in the risk of AP and MI. We also noted a strong association in population-based studies. In the analyses of G98T, data were available for 1422 cases and 1625 controls. We saw a markedly increased risk of CAD associated with G98T. The highest risk was indicated in individuals with the TT genotype (OR = 2.82, 95% CI, 1.15–6.89). A similar trend was seen in Asians and population-based studies.These findings provide consistent evidence that A516C and G98T polymorphisms of the SELE gene may be associated with increased susceptibility of CAD.
Unemployment in the European Union: Institutions, Prices, and Growth

This paper presents a reappraisal of unemployment movements in the European Union. Our analysis is based on the chain reaction theory of unemployment, which focuses on (a) the interaction among labor market adjustment processes, (b) the interplay between these adjustment processes and the dynamic structure of labor market shocks, and (c) the interaction between the adjustment processes and economic growth. We divide the shocks into institutional variables, price variables, and growth drivers. Estimating a system of labor market equations for a panel of EU countries, we derive the dynamic unemployment responses to each shock. Our analysis permits us to distinguish between the short- and long-run effects of the shocks. Different shocks generate different degrees of "unemployment persistence" (responses to temporary shocks) and "unemployment responsiveness" (responses to permanent shocks). We find that the growth drivers play a dominant role in accounting for the main swings in EU unemployment.
RASS-SDSS Galaxy clusters survey I. The catalog and the correlation of X-ray and optical properties

For a detailed comparison of the appearance of cluster of galaxies in X-rays and in the optical, we have compiled a comprehensive database of X-ray and optical properties of a sample of clusters based on the largest available X-ray and optical surveys: the ROSAT All Sky Survey (RASS) and the Sloan Digital Sky Survey (SDSS). The X-ray galaxy clusters of this RASS-SDSS catalog cover a wide range of masses, from groups of 10 12.5 M ○. to massive clusters of 10 15 M ○. in the redshift range 0.002-0.45. The RASS-SDSS sample comprises all the X-ray selected objects already observed by the Sloan Digital Sky Survey (114 clusters). For each system we have uniformly determined the X-ray (luminosity in the ROSAT band, bolometric luminosity, center coordinates) and optical properties (Schechter luminosity function parameters, luminosity, central galaxy density, core, total and half-light radii). For a subsample of 53 clusters we have also compiled the temperatures and the iron abundances from the literature. The total optical luminosity can be determined with a typical uncertainty of 20% independent of the choice of local or global background subtraction. We searched for parameters which provide the best correlation between the X-ray luminosity and the optical properties and found that the z band luminosity determined within a cluster aperture of 0.5 Mpc h -1 70 provides the best correlation, with a scatter of about 60-70%. The scatter decreases to less than 40% if the correlation is limited to the bright X-ray clusters. The resulting correlation of L X and L op in the 2 and i bands shows a logarithmic slope of 0.38, a value not consistent with the assumption of a constant M/L. Consistency is found, however, for an M/L increasing with luminosity as suggested by other observations. We also investigated the correlation between L op and the X-ray temperature, obtaining the same result.
A Clustering-Based Obstacle Segmentation Approach for Urban Environments

The detection of obstacles is a fundamental issue in autonomous navigation, as it is the main key for collision prevention. This paper presents a method for the segmentation of general obstacles by stereo vision with no need of dense disparity maps or assumptions about the scenario. A sparse set of points is selected according to a local spatial condition and then clustered in function of its neighborhood, disparity values and a cost associated with the possibility of each point being part of an obstacle. The method was evaluated in hand-labeled images from KITTI object detection benchmark and the precision and recall metrics were calculated. The quantitative and qualitative results showed satisfactory in scenarios with different types of objects.
Elastic Medical Image Registration using Orientation Attributes at Landmarks

Abstract. A new algorithm is proposed to incorporate orientation attributes at landmarks in an elastic medicalimage registration scheme. The approach is based on a minimizing functional and can cope with images ofarbitrary dimensions. Constraints due to orientations are incorporated through scalar products between thetransformed orientations in the sourceimageand vectorswhich are perpendicularto the orientations in the targetimage. For synthetic data sets we show that the structure of a rigid object in an otherwise elastically deformedimage can be preserved. The application of our approach to tomographic data sets shows that improvementsw.r. t. accuracy can be achieved provided a sufﬁcient number of landmarks is well-distributed over the image. 1 Introduction Landmark-based elastic registration relies on the information associated with landmark points. To improve the re-sultsof landmark-based approaches whilemaintaining theirefﬁciency, work in thepast has been doneon includingadditional landmark attributes, like orientation. Especially in medical applications it is desirable to improve theregistration result without adding further landmarks.Bookstein and Green [1] incorporate orientationsby approximating them through two landmarks. Mardia et al. [2,3] use a kriging method to include derivative information. Their interpolation scheme yields an exact solution, butorientation vectors are required to be unit vectors. In this paper, we describe a new approach which i) is based on aminimizing functionaland ii) allowsto incorporateorientationattributes. As in the approach of Mardia et al. [2,3],exact orientations at landmarks are incorporated. However, in our case the directional constraints are representedthrough scalar products and therefore the lengths of the orientation vectors need not to be normalized to unitvectors. Another advantage of our approach is that it covers the full range from interpolation to approximationusing a regularization parameter
The Dynamic Topology Changes model for unsupervised image segmentation

Deformable Models are a popular family of image segmentation techniques, which has been gaining significant focus in the last two decades, serving both for real-world applications as well as the base for research work. One of the features that the Deformable Models offer and that is considered a much desired one, is the ability to change their topology during the segmentation process. Using this characteristic it is possible to perform segmentation of objects with discontinuities in their bodies or to detect an undefined number of objects in the scene. In this paper we present our model for handling the topology changes in image segmentation methods based on the Active Volumes solution. The said model is capable of performing the changes in the structure of objects while the segmentation progresses, what makes it efficient and suitable for implementations over powerful execution environment, like multi-core architectures or computer clusters.
Coalgebraic Trace Semantics for Continuous Probabilistic Transition Systems

Coalgebras in a Kleisli category yield a generic definition of trace semantics for various types of labelled transition systems. In this paper we apply this generic theory to generative probabilistic transition systems, short PTS, with arbitrary (possibly uncountable) state spaces. We consider the sub-probability monad and the probability monad (Giry monad) on the category of measurable spaces and measurable functions. Our main contribution is that the existence of a final coalgebra in the Kleisli category of these monads is closely connected to the measure-theoretic extension theorem for sigma-finite pre-measures. In fact, we obtain a practical definition of the trace measure for both finite and infinite traces of PTS that subsumes a well-known result for discrete probabilistic transition systems. Finally we consider two example systems with uncountable state spaces and apply our theory to calculate their trace measures.
Width Distributions for Shape Description

Measuring the similarity between articulated shapes is a fundamental yet challenging problem. This paper proposes a novel shape descriptor based on Width Distributions (WD), which is robust to articulations. We show that the width distributions are articulation insensitive yet descriptive to distinguish different shapes with varied part structures. With measurements on distributions only, the proposed method does not require any alignment between two objects and thus is more robust than correspondence-based measurements. First, the medial axes of the objects are extracted and fitted to B-Splines to remove outliners. The width of the object shape perpendicular to the medial axis can be calculated for each position on the medial axis. The histograms of those widths are compared using chi-square method for similarity. Experiments on standard 2D shape database show that the proposed method performed better than standard shape distribution algorithms and similarly to other articulation-robust shape descriptors, such as inner-distance. The speed of the proposed method is much faster than the more sophisticated inner-distance, as the proposed method is much simpler in nature and requires limited image processing and pattern classification. These results suggested it could be an efficient and effective method to describe and to match articulated shapes.
BESPA: Software Tools for Three-Dimensional Structure Reconstruction from Single Particle Images of Proteins

Single particle analysis is a straightforward method for structural studies of protein and biological macromolecules developed in image analysis on electron microscopy [1]. It is a predominant structural probe for proteins which decline to crystallize and exceed the limit in molecular weight for NMR analysis. Furthermore, it allows to examine structural changes and molecular complex of proteins at work, which will become a great advantage for the next generation in structural biology after static structures of proteins are all determined. Our system, named BESPA (Backplane for Electron microscopic Single Particle Analysis) will be packaged soon featuring new algorithms and techniques together with practically useful programs. The single particle analysis has also raised topics for a computational science both in practical algorithm and in establishment of theoretical background.
Sorting on a parallel pointer machine with applications to set expression evaluation

Optimal algorithms for sorting on parallel CREW (concurrent read, exclusive write) and EREW (exclusive read, exclusive write) versions of the pointer machine model are presented. Intuitively, these methods can be viewed as being based on the use of linked lists rather than arrays (the usual parallel data structure). It is shown how to exploit the 'locality' of the approach to solve a problem with applications to database querying and logic programming (set-expression evaluation) in O(log n) time using O(n) processors. <<ETX>>
Uncertainty Visualization for Multi-resolution Volume Data with Regular Grids Using Volume Ray Casting-based Iso-surface Rendering

With the continuous growth of computer hardware and software performance, and the increasing advance of high-speed bandwidth of computer networking, data acquired from complex simulation, experiment and internet continues to increase and outpace hardware advantages. Visualization and analysis of such large size of data sets remains a significant challenge to the visualization community. Over the past years, various data reduction techniques that deal with large data sets have been proposed to solve the problem. However, these proposed data reduction techniques lead to another issue with regard to integrity of the data. In this paper we address this issue by presenting two new uncertainty visualization methods using volume ray casting-based iso-surface rendering. We apply them to the multi-resolution (MR) data sets from the medical domain to visualize both the data and error information. The results have proved that our methods are promising.
A 16MHz BW 75dB DR CT ΔΣ ADC compensated for more than one cycle excess loop delay

An 800MS/s CT ΔΣ ADC with 16MHz/32MHz bandwidths consumes 47.6mW from 1.8V and occupies 1mm2 in a 0. 18µm CMOS process. The DR/SNR/SNDR for the two bandwidths are 75/67/65 dB and 64/57/57 dB respectively. Excess loop delay (ELD) of more than one cycle is compensated using a fast path outside the flash ADC. This and a low latency flash ADC and delay free DAC calibration result in the highest reported sampling rate in this process.
Implementation of Differential Optical Flow Algorithms in Natural Rigid Video Motion

— Computing the optical flow of a sequence of images still remains a challenge in low-level video processing. Till present, none of the existing techniques has sufficiently generated accurate and dense optical flow fields to robustly represent video motion. In this paper we implement the optical flow algorithms through different lengths of displacements that exist in video motion of natural objects. We investigate the outcome of the differential optical flow algorithms based on Lukas-Kanade, Horn-Schunck and Brox’s warping techniques. Experiments on natural images show that the warping technique produces smoother and consistent pattern of optical flow compared to the outputs of Lukas-Kanade and Horn-Schunck. The behaviors of optical flow fields for each algorithm can be observed accordingly with respect to their displacements.
Effects of On- and Off-Ramps in Cellular Automata Models for Traffic Flow

We present results on the modeling of on- and off-ramps in cellular automata for traffic flow, especially the Nagel–Schreckenberg model. We study two different types of on-ramps that cause qualitatively the same effects. In a certain density regime ρlow < ρ < ρhigh one observes plateau formation in the fundamental diagram. The plateau value depends on the input-rate of cars at the on-ramp. The on-ramp acts as a local perturbation that separates the system into two regimes: A regime of free flow and another one where only jammed states exist. This phase separation is the reason for the plateau formation and implies a behavior analogous to that of stationary defects. This analogy allows to perform very fast simulations of complex traffic networks with a large number of on- and off-ramps because one can parametrise on-ramps in an exceedingly easy way.
An overlap-contention free true-single-phase clock dual-edge-triggered flip-flop

Dual-edge-triggered (DET) synchronous operation is a very attractive option for low-power, high-performance designs. Compared to conventional single-edge synchronous systems, DET operation is capable of providing the same throughput at half the clock frequency. This can lead to significant power savings on the clock network that is often one of the major contributors to total system power. However, in order to implement DET operation, special registers need to be introduced that sample data on both clock-edges. These registers are more complex than their single-edge counterparts, and often suffer from a certain amount of clock-overlap between the main clock and the internally generated inverted clock. This overlap can cause contention inside the cell and lead to logic failures, especially when operating at scaled power supplies and under process variations that characterize nanometer technologies. This paper presents a novel, static DET flip-flop (DET-FF) with a true-single-phase clock that completely avoids clock overlap hazards by eliminating the need for an inverted clock edge for functionality. The proposed DET FF was implemented in a standard 40nm CMOS technology, showing full functionality at low-voltage operating points, where conventional DET-FFs fail. Under a near-threshold, 500mV supply voltage, the proposed cell also provides a 35% lower CK-to-Q delay and the lowest power-delay-product compared to all considered DET-FF implementations.
Teaching Science in an Inquiry-Based Learning Environment: What It Means for Pre-Service Elementary Science Teachers

This research examines Turkish pre-service elementary science teachers' understandings of teaching science in an inquiry-based learning environment. Thirty-five prospective teachers who attended to one of the big teacher training institutions in Istanbul participated in this study. Data were collected via course assignments and inclass activities in teaching science. These were pre- and post-philosophies of teaching science, Nature of Science Card Game and a discussion centered on an inquiry-based teaching scenario. Open-coding of data helped to note patterns to identify categories and form assertions. Inquiry-based learning environment changed participants' traditional views about not the nature of science but teaching science.
A versatile method for trifocal tensor estimation

Reliable estimation of the trifocal tensor is crucial for 3D reconstruction from uncalibrated cameras. The estimation process is based on minimizing the geometric distances between the measurements and the corrected data points, the underlying nonlinear optimization problem being most often solved with the Levenberg-Marquardt (LM) algorithm. We employ for this task the heteroscedastic errors-in-variables (HEIV) estimator and take into account both the singularity of the multivariate tensor constraint and the bifurcation which can appear for noisy data. In comparison to the Gold Standard method, the new approach is significantly faster while having the same performance, and it is less sensitive to initialization when the data is close to degenerate. Analytical expressions for the covariances of the parameter and corrected image point estimates are available for the HEIV estimator and thus the confidence regions of the corrected measurements can be delineated in the images.
Combining visual and text features for learning in multimedia direct marketing domain

Direct marketing companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing process is simple and widely used, recently the direct marketing industry has been under increased pressure to further optimize learning, in particular when facing severe time and space constraints. Taking into account the multimedia nature of offers, which typically comprise both a visual and text component, we propose a two-phase learning strategy based on a cascade of regression methods. This proposed approach takes advantage of visual and text features to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS) show the effectiveness of the proposed methods that improve on classical learn-
Graph-based peak alignment algorithms for multiple liquid chromatography-mass spectrometry datasets

UNLABELLED Liquid chromatography coupled to mass spectrometry (LC-MS) is the dominant technological platform for proteomics. An LC-MS analysis of a complex biological sample can be visualized as a 'map' of which the positional coordinates are the mass-to-charge ratio (m/z) and chromatographic retention time (RT) of the chemical species profiled. Label-free quantitative proteomics requires the alignment and comparison of multiple LC-MS maps to ascertain the reproducibility of experiments or reveal proteome changes under different conditions. The main challenge in this task lies in correcting inevitable RT shifts. Similar, but not identical, LC instruments and settings can cause peptides to elute at very different times and sometimes in a different order, violating the assumptions of many state-of-the-art alignment tools. To meet this challenge, we developed LWBMatch, a new algorithm based on weighted bipartite matching. Unlike existing tools, which search for accurate warping functions to correct RT shifts, we directly seek a peak-to-peak mapping by maximizing a global similarity function between two LC-MS maps. For alignment tasks with large RT shifts (>500 s), an approximate warping function is determined by locally weighted scatterplot smoothing of potential matched features, detected using a novel voting scheme based on co-elution. For validation, we defined the ground truth for alignment success based on tandem mass spectrometry identifications from sequence searching. We showed that our method outperforms several existing tools in terms of precision and recall, and is capable of aligning maps from different instruments and settings. AVAILABILITY Available at https://sourceforge.net/projects/rt-alignment/.