Miracle-dz/UniFAR-FTUs huggingface dataset:
Causal Memory: Implementation, Programming Support and Experiences

Distributed Shared Memory (DSM) has become an accepted abstraction for programming distributed systems. Although DSM simpliies the programming of distributed applications, maintaining a consistent shared memory can be expensive. Weakly ordered systems which use synchronization information have been proposed to reduce the frequency of communication between processors. We have implemented a weakly ordered system based on the Causal memory model. We provide language and runtime support which allow programs to run eeciently on Causal memory. Actual implementation results show a signiicant reduction in the number of messages when compared to a system maintaining a consistent shared memory.
Model Based Vehicle Tracking for Autonomous Driving in Urban Environments

Situational awareness is crucial for autonomous driving in urban environments. This paper describes moving vehicle tracking module that we developed for our autonomous driving robot Junior. The robot won second place in the Urban Grand Challenge, an autonomous driving race organized by the U.S. Government in 2007. The tracking module provides reliable tracking of moving vehicles from a high-speed moving platform using laser range finders. Our approach models both dynamic and geometric properties of the tracked vehicles and estimates them using a single Bayes filter per vehicle. We also show how to build efficient 2D representations out of 3D range data and how to detect poorly visible black vehicles. Experimental validation includes the most challenging conditions presented at the UGC as well as other urban settings.
Aqua: A Fast Decision Support Systems Using Approximate Query Answers

Aqua is a system for providing fast, approximate answers to aggregate queries, which are very common in OLAP applications. It has been designed to run on top of any commercial relational DBMS. Aqua precomputes synopses (special statistical summaries) of the original data and stores them in the DBMS. It provides approximate answers (with quality guarantees) by rewriting the queries to run on these synopses. Finally, Aqua also incrementally keeps the synopses up-to-date as the database changes.
Long-term effects of mindfulness-based psychological intervention for coping with pain in endometriosis: A six-year follow-up on a pilot study

Abstract Objective: Development of chronic pain problems in endometriosis is frequent. Until now there has been no alternative treatment offered when medical and surgical treatment has been unhelpful in relieving the pain. The aim of this study was to evaluate the long-term effects of a mindfulness-based psychological intervention on chronic pain and quality of life in endometriosis when conducting a six-year follow-up on a pilot study. Materials and methods: In the original study, participants were recruited through Aarhus University Hospital and included ten women with diagnosed endometriosis and chronic pelvic pain. The women participated in 10 sessions of mindfulness-based psychological intervention. When contacted after 6 years all ten women agreed to participate in the follow-up study. Quality of life was measured by the endometriosis specific questionnaire EHP-30 and the generic form SF-36. Results: When comparing data from the 12 months follow-up with data from the six year follow-up, results showed no significant differences in mean scores on all scales of the EHP-30 and almost all scales of the SF-36 scale scores. The results indicate lasting improvement on almost all scales of the EHP-30 and the SF-36. Conclusion: Although conclusions remain preliminary until tested in a randomized controlled trial, results presented in this article indicate that mindfulness-based psychological treatment of chronic pain seems very relevant to women with endometriosis with the potential to improve quality of life.
DARK MATTER HALO PROFILES IN SCALE-FREE COSMOLOGIES

We explore the dependence of the central logarithmic slope of dark matter halo density profiles a on the spectral index n of the linear matter power spectrum P(k) using cosmological N-body simulations of scale-free models [i.e. P(k) oc k n ]. These simulations are based on a set of clear, reproducible and physically motivated criteria that fix the appropriate starting and stopping times for runs, and allow one to compare haloes across models with different spectral indices and mass resolutions. For each of our simulations we identify samples of well-resolved haloes in dynamical equilibrium and we analyse their mass profiles. By parametrizing the mass profile using a 'generalized' Navarro, Frenk & White profile in which the central logarithmic slope a is allowed to vary while preserving the r -3 asymptotic form at large radii, we obtain preferred central slopes for haloes in each of our models. There is a strong correlation between a and n, such that a becomes shallower as n becomes steeper. However, if we normalize our mass profiles by r- 2 , the radius at which the logarithmic slope of the density profile is -2, we find that these differences are no longer present. This is apparent if we plot the maximum slope γ = 3(1 - p/p) as a function of r/r -2 - we find that the profiles are similar for haloes forming in different n models. This reflects the importance of concentration, and reveals that the concentrations of haloes forming in steep-n cosmologies tend to be smaller than those of haloes forming in shallow-n cosmologies. We conclude that there is no evidence for convergence to a unique central asymptotic slope, at least on the scales that we can resolve.
An Overview of Recent Algorithms for AI Planning

During the past several years, AI planning has made major steps forward in terms of the size and difficulty of problems that can be solved. In this article we give an overview of the techniques that have been part of the recent developments. Instead of concentrating on individual planning systems, we review the underlying principles behind many of the successful planners. Most of the overview is devoted to classical planning, that is fully deterministic planning with one initial state, and we discuss more general forms of planning only briefly in the end of the article.
Pose VariantFace Recognition Based on Linear Mapping

Under uncontrolled image conditions, one of the greatest remaining research challenges in face recognition is to recognize faces across different poses. For multi-views face recognition problem either by means of difficult practical three-dimensional methods, either by means of a complex nonlinear transform algorithm. In order to overcome the poses problem, this paper analyzed the spatial change of different pose, regarded the faces with different pose space as a kind of approximate linear relationship by discretion of face pose space. As a consequence, a pose invariant face recognition method based on Orthogonal Procrustes analysis and sparse representation is proposed in this paper. Experimental results demonstrate that the presented algorithm possesses good robustness for the face variation of poses.
Sampling and Topological Inference For General Shapes

In many practical situations, the object of study is only known through a finite set of possibly noisy sample points. It is then desirable to try to recover the geometry and the topolog y of the object from this information. The most obvious example is probably surface reconstruc tion, where the points are measured on the surface of a real world object. Also, a current re search topic in cosmology is to study the large scale structure formed by the galaxies, which seems to be a n int rconnected network of walls and filaments [13]. In other applications, the shape of inter est may live in a higher dimensional space, as for instance in machine learning and in particular in m nifold learning. This is also the case in time series analysis, when the shape of study is the attractor o f a dynamical system sampled by a sequence of observations [12]. In this context, an important question is to find a sampling condition guaranteeing that the object can be reconstructed correctly. Besides providing theoretical g uarantees, such a condition may be used to drive the recontruction process itself. Indeed, a possible reconstruction strategy is to look for the shapes that are best sampled by the data points. In what fo llows, we investigate these questions in a fairly general setting, assuming a very simple reconstru ction process.
Impact of θ13 on lepton flavour violating processes within SUSY seesaw

We study the impact of neutrino masses and mixings on LFV processes within the context of the supersymmetric seesaw scenario, where the CMSSM is extended by three right-handed (s)neutrinos. A hierarchical spectrum is considered for both heavy and light neutrinos. We systematically analyse the interesting relation between the leptonic mixing angle �13 and LFV muon and tau decays, namely lj → li and lj → 3li, and discuss the interplay with the other relevant parameters. We require compatibility with low energy neutrino data, bounds on both LFV decays and charged lepton electric dipole moments, and impose a successful baryogenesis via thermal leptogenesis. Particular emphasis is given to the implications that a future �13 measurement can have on our knowledge of the heavy neutrino sector.
Reduction in laboratory turnaround time decreases emergency room length of stay

Objective Laboratory tests are an important contributor to treatment decisions in the emergency department (ED). Rapid turnaround of laboratory tests can optimize ED throughout by reducing the length of stay (LOS) and improving patient outcomes. Despite evidence supporting the effect of shorter turnaround time (TAT) on LOS and outcomes, there is still a lack of large retrospective studies examining these associations. Here, we evaluated the effect of a reduction in laboratory TAT on ED LOS using retrospective analysis of Electronic Health Records (EHR). Materials and methods Retrospective analysis of ED encounters from a large, US-based, de-identified EHR database and a separate analysis of ED encounters from the EHR of an ED at a top-tier tertiary care center were performed. Additionally, an efficiency model calculating the cumulative potential LOS time savings and resulting financial opportunity due to laboratory TAT reduction was created, assuming other factors affecting LOS are constant. Results Multivariate regression analysis of patients from the multisite study showed that a 1-minute decrease in laboratory TAT was associated with 0.50 minutes of decrease in LOS. The single-site analysis confirmed our findings from the multisite analysis that a positive correlation between laboratory TAT and ED LOS exists in the ED population as a whole, as well as across different patient acuity levels. In addition, based on the calculations from the efficiency model, for a 5-, 10- and 15-minute TAT reduction, the single-site ED can potentially admit a total of 127, 256 and 386 additional patients, respectively, annually. Conclusion A positive correlation between laboratory TAT and ED LOS was observed in a broad patient population and across distinct acuity levels.
Protein Expression Analysis: From ‘Tip of the Iceberg’ to a Global Method

In this review I will describe the advances that have recently been made in ‘traditional’ two-dimensional gel based protein expression analysis. A major jump has been made toward the automation of gel image analysis and comparison, one of the major bottlenecks in the analysis chain as well as the automation of spot excision and preparation for mass spectrometric analysis. Currently the gel-based ‘proteome mapping’ approach is highly effective and 300 gels and over 10,000 spots a week can be analysed. Very recently, viable alternatives to the use of two-dimensional gel electrophoresis have emerged and these approaches are discussed here. In combination with the recently developed stable isotopic tagging methods for peptide quantitation and new mass spectrometers, this emerging technology will be a rapid and highly effective alternative to gel-based methods with few of the latter's shortcomings.
Synthesis of a Novel Series of Amino Acid Prodrugs Based on Thienopyridine Scaffolds and Evaluation of Their Antiplatelet Activity

The thienopyridines class of drugs used as P2Y12 receptor antagonists plays a vital role in antiplatelet therapy. To further optimized this compound class, we designed and synthesized a series of amino acid prodrugs of 2-hydroxytetrahydrothienopyridine. All compounds were then evaluated for their inhibitory effect on ADP-induced platelet aggregation in rats and then ED50 and bleeding time of the most potent compounds were compared with commercial drugs. The results showed compound 5c could be a potent and safe candidate for further research.
The convex-concave characteristics of Gaussian channel capacity functions

In this correspondence, we give several inherent properties of the capacity function of a Gaussian channel with and without feedback by using some operator inequalities and matrix analysis. We give a new proof method which is different from the method appearing in: K. Yanagi and H. W. Chen, "Operator inequality and its application to information theory," Taiwanese J. Math., vol. 4, no. 3, pp. 407-416, Sep. 2000. We obtain the following results: C/sub n,Z/(P) and C/sub n,FB,Z/(P) are both concave functions of P, C/sub n,Z/(P) is a convex function of the noise covariance matrix and C/sub n,FB,Z/(P) is a convex-like function of the noise covariance matrix. This new proof method is very elementary and the results shall help study the capacity of Gaussian channel. Finally, we state a conjecture concerning the convexity of C/sub n,FB,/spl middot//(P).
Towards an Evolution Strategy Approach in Binary Image Registration for Solving Digital Signature Recognition Tasks

This paper focuses on the development of an image registration methodology for digital signature recognition. We consider two perturbation models, namely the rigid transformation and a mixture of shear and rigid deformation. The proposed methodology involves three stages. In the first stage, both the acquired image and the stored one are binarized to reduce the computational effort. Then an evolution strategy (ES) is applied to register the obtained binary images. The quality of each chromosome belonging to a certain population is evaluated in terms of mutual information-based fitness function. In order to speed up the computation of fitness values, we propose a computation strategy based on the binary representation of images and the sparsity of the image matrices. Finally, we evaluate the registration capabilities of the proposed methodology by means of quantitative measures as well as qualitative indicators. The experimental results and some conclusions concerning the capabilities of various methods derived from the proposed methodology are reported in the final section of the paper.
An iterative linear quadratic regulator based trajectory tracking controller for wheeled mobile robot

We present an iterative linear quadratic regulator (ILQR) method for trajectory tracking control of a wheeled mobile robot system. The proposed scheme involves a kinematic model linearization technique, a global trajectory generation algorithm, and trajectory tracking controller design. A lattice planner, which searches over a 3D (x, y, θ) configuration space, is adopted to generate the global trajectory. The ILQR method is used to design a local trajectory tracking controller. The effectiveness of the proposed method is demonstrated in simulation and experiment with a significantly asymmetric differential drive robot. The performance of the local controller is analyzed and compared with that of the existing linear quadratic regulator (LQR) method. According to the experiments, the new controller improves the control sequences (ν, ω) iteratively and produces slightly better results. Specifically, two trajectories, ‘S’ and ‘8’ courses, are followed with sufficient accuracy using the proposed controller.
Traffic Monitoring System Development in Jelgava City, Latvia

Smart traffic management and monitoring is one of the key aspects of the modern smart city. Traffic flow estimation is crucial for sustainable traffic planning in the city. A requirement for successful planning and optimization of traffic is vehicle counting on the streets. Surveillance video is a suitable data source for precise vehicle counting. A solution for real-time vehicle traffic monitoring, tracking and counting is proposed in Jelgava city, Latvia. It is based on motion detection using background modeling, which is enhanced by statistical analysis. Two-phase assessment is utilized: motion blobs are detected and tracked using custom state machine implementation, then tracking results are passed through number of statistical filters to eliminate false positive detections. The system demonstrates good performance and acceptable accuracy on given test cases (about 97% accuracy for regular traffic conditions).
Research into Big data for smart grids

Two the largest man-made large-scale systems were created and expanded in the last century: electrical power system and world-wide computer networks, the Internet. Entering the new century, both systems are facing enormous challenges. On the one hand, Smart Grids - modernization of electrical power systems to deal with energy shortage and environment issues - are being developed in accelerating pace. On the other hand, human beings are also facing with unprecedented challenges from collecting, storing, transferring, mining, processing and visualizing massive data: Big data. The advent of a smart grid - the overlay of advanced sensing, communications, and controls on the electric network - is transforming utilities and other power sector players into IT companies. As information technologies are embedded across the entire system - from power plants through transmission lines, substations, distribution circuits, meters, and every device in industrial and residential users. Utilities' operational and information models will increasingly resemble those of telecom, Internet, or even financial trading companies. This will require a fundamentally new approach to interoperability, speed, and managing and making sense of vast new floods of data. Therefore, this paper is to follow this route to address Big data in future power systems. Specifically, in this paper, we report our initial work on predicting wind farm outputs based on historical wind speed data.
Laparoscopic Heller Myotomy for Achalasia Technical Aspects

Esophageal achalasia is a primary esophageal motility disorder defined by the lack of esophageal peristalsis, and by a lower esophageal sphincter that fails to relax in response to swallowing. Patients’ symptoms include dysphagia, regurgitation, aspiration, heartburn, and chest pain. Achalasia is a chronic condition without cure, and treatment options are aimed at providing symptomatic relief, improving esophageal emptying, and preventing the development of megaesophagus. Presently, a laparoscopic Heller myotomy with a partial fundoplication is considered the best treatment modality. A properly executed operation is key for the success of a laparoscopic Heller myotomy.
Object-based rendering and 3D reconstruction using a moveable image-based rendering system

Image-based rendering (IBR) is a promising technology for rendering photo-realistic views of scenes from a collection of densely sampled images or videos, and for developing revolutionary immersive viewing systems. However, most multiple camera systems are designed to be stationary and hence their ability to cope with moving objects and dynamic environment is somewhat limited. This paper studies the design and development of a movable IBR (M-IBR) system for object-based rendering and 3D reconstruction in large environment. To reduce shaky motion due to the movable system, we develop video stabilization algorithm based on scale invariant feature transformation. Also, we propose a new segmentation-based mutual-information matching algorithm to estimate the dense depth maps and preserve discontinuities for better quality of rendering. Using these depth maps and sequential structure from motion technique, we estimate the location of the M-IBR system to obtain a set of fairly reliable 3D point cloud. After detecting and removing possible outliers using Kalman-based tracking, we propose a new robust RBF-based modeling of the 3D surfaces to recover high quality 3D geometry. The effectiveness of the proposed system and algorithms is demonstrated using multi-view videos in an open environment.
The SYSTERS protein family database: Taxon-related protein family size distributions and singleton frequencies

Based on the SYSTERS protein family database, we present taxon-related protein family frequencies and distributions. A set of taxon-related protein families is a subset of the whole family set with respect to one taxon, where taxon is not restricted to the species level but may be any rank in the taxonomy. We examine eight ranks in the lineages of seven organisms. A strong linear correlation is observed between the total number of different families and the number of sequences in the data set under consideration. We fitted the generalised power-law function to protein family distributions in a least-squares sense excluding singleton frequencies. Taxon-related family distributions tend to have the same shape and a negative slope being not larger than -2.1 for large data sets. For smaller data sets, the slope is decreasing down to -3.7. Slopes of family distributions are found to be slowly increasing towards higher taxonomic ranks. Our observations lead to a new estimation of single sequence cluster frequencies. Data sets of various species are studied with respect to being complete or incomplete.
Shaping EXIT functions of turbo codes

This paper investigates the shaping of the extrinsic information transfer (EXIT) functions of parallel turbo codes, when the turbo code is used as an outer code in a serially concatenated scheme. As opposed to other work, we consider the overall EXIT function of the turbo decoder and not the EXIT chart for the component codes. Three methods for shaping are investigated: (i) individual puncturing of the systematic part and the two parity parts of the turbo codes, (ii) puncturing of the overall turbo code, and (iii) repetition of the overall turbo code. For each case, the EXIT function of the resulting turbo code is computed from the EXIT function of its component codes. Exact results are obtained for the binary erasure channel.
Orion II: the second-generation readout multiplexer for largest infrared hybrid focal plane

The Orion program developed a 2048x2048 infrared focal plane using InSb PV diodes for detectors. Several of these focal planes have been produced. However, the yield of the original readout multiplexer was not up to expectations owing to unanticipated shorts in the fabrication process. Since these shorts occurred at the metal 1-metal 2 crossover points and there are over 9 million such crossovers, the design had to be modified to work around these problems. Thus the Orion II readout was developed. The work is being done at the Raytheon Vision Systems (RVS) division (most recently Raytheon Infrared Operations, but better known as SBRC) by many of the same people who created the Orion I and ALADDIN focal planes. The design is very similar to the Orion I design with the addition of circuitry to work around the effect of the metal 1-metal 2 shorts. In this paper we will discuss the unique design features of this device as well as present test data taken from the new devices.