Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Second Neurological Attack in Patients with Clinically Isolated Syndrome Using Support Vector Machines

The aim of this study is to predict the conversion from clinically isolated syndrome to clinically definite multiple sclerosis using support vector machines. The two groups of converters and non-converters are classified using features that were calculated from baseline data of 73 patients. The data consists of standard magnetic resonance images, binary lesion masks, and clinical and demographic information. 15 features were calculated and all combinations of them were iteratively tested for their predictive capacity using polynomial kernels and radial basis functions with leave-one-out cross-validation. The accuracy of this prediction is up to 86.4% with a sensitivity and specificity in the same range indicating that this is a feasible approach for the prediction of a second clinical attack in patients with clinically isolated syndromes, and that the chosen features are appropriate. The two features gender and location of onset lesions have been used in all feature combinations leading to a high accuracy suggesting that they are highly predictive. However, it is necessary to add supporting features to maximise the accuracy.
Enhanced deformable part model for pedestrian detection via joint state inference

Part-based approaches, such as Deformable Part Model (DPM), have been actively studied for pedestrian detection in recent years. However, the overall pedestrian detection performance heavily depends on the detection accuracy of a single part detector, which is not so discriminative that usually easily affected by occlusions and deformations. To address this problem, in this paper, we propose a novel method enhancing the pedestrian detection performance by capturing the dependencies between different part detectors. Our attempt is to refine the overall detection accuracy by exploiting the joint state distribution of relevant part detectors. Firstly, we estimate the parameters for the joint state distribution, which expresses the dependencies between different part detectors, on the training set. Afterwards, a linear classifier is trained on the scores of the part detectors to assign them with different weights. At last, given a testing image, the joint state is inferred and the scores of part detectors are integrated to output the refined score. The experimental results carried out on the commonly used benchmark datasets show that the proposed method outperforms other state-of-the-art methods on pedestrian detection accuracy.
Fractional Persistence and Common Persistence in the Conditional Variance of US Bond Yields

This paper examines persistence and common persistence in US monthly zero coupon bond yields by utilising fractionally integrated GARCH and fractionally integrated stochastic volatility models. Both conventional maximum likelihood and indirect estimation procedures are considered for these models. Simulation results are then reported on the effectiveness of the alternative estimators before empirical results are presented. The concept of cointegation in conditional variance is examined by estimating the extent of co-persistence in the bond yield spread series. The empirical results suggest that the conditional variances of the yields and spreads are best characterised as fractionally integrated, or persistent, processes.
Understanding and Measuring Patients' Assessment of the Quality of Nursing Care

Background: Traditionally, patients have been considered incapable of evaluating the quality of care they receive, leading to their minimal involvement. Objective: To develop the Patient's Assessment of Quality Scale-Acute Care Version (PAQS-ACV) to provide a mechanism through which patients can evaluate meaningfully the nursing care they receive. Methods: Developed from qualitative interviews with patients, the original 90-item PAQS-ACV was tested with 1,470 medical surgical patients in 43 units across seven hospitals. The typical patient was a married, 50-year-old, high school-educated patient hospitalized for the fourth time. Every 10th patient was asked to complete the PAQS-ACV 2 weeks later. Results: After exploratory factor analysis, 45 items remained in five factors, accounting for 54% of the variance. Internal consistency estimates were above.83 for four of the five factors, with the fifth factor being.68. Test-retest reliability ranged from . 58 to . 71. Content validity was established and construct validity has been explored preliminarily by examining the relationship between the PAQS-ACV scores and patients' compliance. Discussion: Although the PAQS-ACV is a relatively new measure of quality nursing care, it has met many criteria for an adequate measure of quality care. The instrument fills a void in the assessment of quality by including patients in the direct evaluation of the care received.
The TropiSAR Airborne Campaign in French Guiana: Objectives, Description, and Observed Temporal Behavior of the Backscatter Signal

The TropiSAR campaign has been conducted in August 2009 in French Guiana with the ONERA airborne radar system SETHI. The main objective of this campaign was to collect data to support the Phase A of the 7th Earth Explorer candidate mission, BIOMASS. Several specific questions needed to be addressed to consolidate the mission concept following the Phase 0 studies, and the data collection strategy was constructed accordingly. More specifically, a tropical forest data set was required in order to provide test data for the evaluation of the foreseen inversion algorithms and data products. The paper provides a description of the resulting data set which is now available through the European Space Agency website under the airborne campaign link. First results from the TropiSAR database analysis are presented with two in-depth analyses about both the temporal radiometric variation and temporal coherence at P-band. The temporal variations of the backscatter values are less than 0.5 dB throughout the campaign, and the coherence values are observed to stay high even after 22 days. These results are essential for the BIOMASS mission. The observed temporal stability of the backscatter is a good indicator of the expected robustness of the biomass estimation in tropical forests, from cross-polarized backscatter values as regarding environmental changes such as soil moisture. The high temporal coherence observed after a 22-day period is a prerequisite for SAR Polarimetric Interferometry and Tomographic applications in a single satellite configuration. The conclusion then summarizes the paper and identifies the next steps in the analysis.
Source Enumeration in Array Processing Using a Two-Step Test

We investigate the problem of enumerating source signals impinging on an array of sensors given noisy, limited observations. The assumption of a large sample size is indispensable for most of the existing approaches so that they suffer significant performance degradation when only a small number of samples is available. Random matrix theory can capture the asymptotic distributions of the eigenvalues accurately and provide good approximations even for a finite sample size. In this paper, we take into account the relationship and distributions of the noise and signal eigenvalues based on random matrix theory and derive a simple two-step test. Numerical simulations demonstrate that it is capable of correctly determining the number of sources in the case of small sample sizes.
A simple method for the determination of qPlus sensor spring constants

qPlus sensors are widely used to measure forces at the atomic scale, however, confidence in these measurements is limited by inconsistent reports of the spring constant of the sensor and complications from finite tip heights. Here we combine a numerical investigation of the force reconstruction with an experimental characterization of the flexural mechanics of the qPlus sensor. Numerical studies reveal significant errors in reconstructed force for tip heights exceeding 400 μm or one sixth of the cantilever length. Experimental results with a calibrated nanoindenter reveal excellent agreement with an Euler–Bernoulli beam model for the sensor. Prior to the attachment of a tip, measured spring constants of 1902 ± 29 N/m are found to be in agreement with theoretical predictions for the geometry and material properties of the sensor once a peaked ridge in the beam cross section is included. We further develop a correction necessary to adjust the spring constant for the size and placement of the tip.
Flexibility of Crab Chemosensory Sensilla Enables Flicking Antennules to Sniff

The first step in smelling is capture of odorant molecules from the surrounding fluid. We used lateral flagella of olfactory antennules of crabs Callinectes sapidus to study the physical process of odor capture by antennae bearing dense tufts of hair-like chemosensory sensilla (aesthetascs). Fluid flow around and through aesthetasc arrays on dynamically scaled models of lateral flagella of C. sapidus was measured by particle image velocimetry to determine how antennules sample the surrounding water when they flick. Models enabled separate evaluation of the effects of flicking speed, aesthetasc spacing, and antennule orientation. We found that crab antennules, like those of other malacostracan crustaceans, take a discrete water sample during each flick by having a rapid downstroke, during which water flows into the aesthetasc array, and a slow recovery stroke, when water is trapped in the array and odorants have time to diffuse to aesthetascs. However, unlike antennules of crustaceans with sparse aesthetasc arrays, crabs enhance sniffing via additional mechanisms: 1) Aesthetascs are flexible and splay as a result of the hydrodynamic drag during downstrokes, then clump together during return strokes; and 2) antennules flick with aesthetascs on the upstream side of the stalk during downstrokes, but are hidden downstream during return strokes. Aiming aesthetascs into ambient flow maintains sniffing. When gaps between aesthetascs are wide, changes in antennule speed are more effective at altering flow through the array than when gaps are narrow. Nonetheless, if crabs had fixed gap widths, their ability to take discrete samples of their odorant environment would be diminished.
Compilation Techniques for Fair Execution of Shared Memory Parallel Programs over a Network of Workstations

Compiler technologies are crucial for the eecient execution of sequential programs. This is not yet true for parallel programs, where the operating system performs most of the work, resulting in increased overhead for scheduling and distributed shared memory simulation. In this work we suggest simple compilation techniques that can be used to guarantee eecient execution of shared memory parallel programs. In particular, we address the diiculties involved in supporting preemption of activities in compiled code, which is crucial for fair execution of shared memory programs. The main novelty of this work is a comprehensive approach for compilation, where eeciency is guaranteed whenever preemption is not really needed. The compiler is used to insert explicit context-switch instructions, so that preemption is supported only where required. In addition, our compilation scheme guarantees that the cactus stack is embedded in the regular stack of each machine, such that most of the activities are spawned as regular function calls or loop iterations. Finally, the virtual address space is partitioned between the diierent machines, and shared memory is supported by inserting \special" code before \heavy" loops. This code samples the iteration space of these heavy loops before they are executed, so that most of the memory pages that are used by the loops can be fetched. The number of page-faults occurring as a result of the DSM simulation is thus reduced. The virtual memory mechanism is also used to get rid of the unused frames (\holes") that are left on the stack. The page-table in each machine is managed using special assembler instructions inserted by the compiler.
Toward a higher level, output analysis interface

To match the greatly increasing power of scientific engineering workstations with the slowly changing capability of the simulation practitioner, the authors examine the possibilities for a high-level output analysis interface. The goal is an interface which considers a parametric family of models and accepts commands stated in terms of understanding model characteristics over this family and for making practical decisions with respect to it. The interfaces considered must exploit the unique features of the simulation environment: the fact that additional data are readily available and that these data can be immediately incorporated into the analysis and presented to the user. Thus, many of the classical considerations of statistics involving making optimum use of limited data become eclipsed by questions of what additional data are needed to make the necessary decisions and how to present the results as the data are being acquired so as to maximize the power of the combination of practitioner and machine. <<ETX>>
Solving inverse kinematics problem of robot arm with adjustable Snap-width A-star algorithm

Playing an important role in our everyday life, robot arms need the controlling systems for effectively moving each part in the desired movement, and their manipulation varies across their physical structures. To be precise, arms of the industrial robots used for welding consist of the sequence of jointed arms called kinematic chains and the arm tip called end effector. Such construction typically leads to problems about inverse kinematics in terms of its calculation for adjusting the angle size of each joint to have the end effector reach the desired target accurately and to minimize the movements in each joint. Therefore, this paper has presented a solution for those problems about inverse kinematics based on gradient following procedure and A-star algorithm in order to achieve the best practice. To suggest a solution, this paper has concerned about the accuracy and the minimum movement by carrying out a simulation on the simulative model with MATLAB program. According to the result, it was possible to calculate the proper degrees of the joint angles for creating the most accurate reach range of the end effector.
Functional topology in a network of protein interactions

MOTIVATION The building blocks of biological networks are individual protein-protein interactions (PPIs). The cumulative PPI data set in Saccharomyces cerevisiae now exceeds 78 000. Studying the network of these interactions will provide valuable insight into the inner workings of cells. RESULTS We performed a systematic graph theory-based analysis of this PPI network to construct computational models for describing and predicting the properties of lethal mutations and proteins participating in genetic interactions, functional groups, protein complexes and signaling pathways. Our analysis suggests that lethal mutations are not only highly connected within the network, but they also satisfy an additional property: their removal causes a disruption in network structure. We also provide evidence for the existence of alternate paths that bypass viable proteins in PPI networks, while such paths do not exist for lethal mutations. In addition, we show that distinct functional classes of proteins have differing network properties. We also demonstrate a way to extract and iteratively predict protein complexes and signaling pathways. We evaluate the power of predictions by comparing them with a random model, and assess accuracy of predictions by analyzing their overlap with MIPS database. CONCLUSIONS Our models provide a means for understanding the complex wiring underlying cellular function, and enable us to predict essentiality, genetic interaction, function, protein complexes and cellular pathways. This analysis uncovers structure-function relationships observable in a large PPI network.
Acute Inactivation of Tau Has No Effect on Dynamics of Microtubules in Growing Axons of Cultured Sympathetic Neurons

Tau is a developmentally regulated microtubule (MT)-associated protein in neurons that has been implicated in neuronal morphogenesis. On the basis of test tube studies, tau has been proposed to function in axon growth by stabilizing MTs and thereby promoting MT assembly. We have tested this hypothesis by examining the effects of acute inactivation of tau on axonal MTs. Tau was inactivated by microinjecting purified antibodies against recombinant tau into neurons before they extended axons. The injected antibodies quantitatively precipitated tau into aggregates in the soma. With these conditions the neurons elaborate normal-appearing axons, and MTs extend throughout the axons and into the growth cones, but the axons and their MTs are depleted of tau. The immunodepletion of tau had no detectable effect on several parameters of the dynamics of axonal MTs. Depletion of tau also was not accompanied by a reorganization of other major MT-associated proteins or actin filaments in these neurons. Thus, neurons effectively depleted of tau can extend axons that resemble those of control cells, and the axons contain normal-appearing MT arrays with normal dynamic behavior. These observations are exactly the opposite of those expected on the basis of the hypothesis that the stability of axonal MTs is a direct function of their content of tau, indicating that tau in growing axons of cultured sympathetic neurons is not specialized to promote microtubule assembly and stability.
Updating Structural Properties using Vibration-based Nondestructive Testing with Modal Parameters

To improve the accuracy of the assessment for existing bridge performance, evaluating upto-date structural properties is essential. In this paper, we propose a methodology to update the structural properties of a bridge using modal data. Modal data can be easily extracted from a vibration testing conducted on a bridge, making the proposed methodology of practical value. There are three steps in the developed framework for an existing bridge: 1) to build a preliminary finite element model (FEM) based on the bridge design drawings; 2) to update the preliminary FEM to a baseline model using a Bayesian model updating approach with the modal parameters measured from the existing bridge; and 3) to identify local structural stiffness damage using the damage index method with the mode shapes of the existing bridge and of the baseline structure found in the previous step. The proposed framework makes use of the advantages of the Bayesian model updating method and the damage index method, compensating for their drawbacks. Then the proposed framework is illustrated with a simulated finite element model of the Lavic Road Overcrossing bridge, a typical box-girder RC highway bridge in California. Résumé Pour améliorer la précision de l'évaluation de la performance des ponts existants, évaluer des propriétés structurelles à jour est essentiel. Dans ce papier, nous proposons une méthodologie pour mettre à jour les propriétés structurelles d'un pont utilisant des données modales. Les données modales peuvent être facilement extraites d'un test de vibration conduit sur un pont, faisant de la méthodologie proposée une valeur pratique. Il y a trois étapes dans le cadre développé pour un pont existant : 1) construire un modèle d'élément fini préliminaire (FEM) basé sur les plans d'étude du pont ; 2) mettre à jour le modèle d’élément fini préliminaire sur la base d’un modèle Bayesian de mise à jour avec les paramètres modaux mesurés à partir du pont existant ; et 3) identifier les dégâts structurels locaux en utilisant la méthode d’index des dégâts avec les déformées modales du pont existant et la structure de base trouvée dans l'étape précédente. Le cadre proposé se sert des avantages du modèle Bayesian de mise à jour et de la méthode d’index des dégâts, et compense leurs inconvénients respectifs. Le cadre proposé est ensuite illustré avec un modèle simulé éléments finis du pont traversant de la Route Lavic, un pont à poutres à caisson typique du pont d'autoroute RC en Californie.
Studies on Covariance Selection Models : Stepwise Procedure and Local Influence

Analysis of covariance selection models is a useful multivariate method to analyze the covariance structure of a multivariate normal distribution. It is used to reveal cause-and-effect relationships. In the present paper we review the theory and study numerically how the stepwise procedure of covariance selection works in actual data analysis. Then we try to develop a method of influence analysis in covariance selection, and show a numerical example to illustrate the usefulness of the method of influence analysis.
Boosting contextual information in content-based image retrieval

We present a new framework for characterizing and retrieving objects in cluttered scenes. Objects are best represented by characterizing both their parts and the mutual spatial relations among them. This CBIR system is based on a new representation describing every object taking into account the local properties of its parts and their mutual spatial relations, without relying on accurate segmentation. For this purpose, a new multi-dimensional histogram is used that measures the joint distribution of local properties and relative spatial positions. Instead of using a single descriptor for all the image, we represent the image by a set of histograms covering the object from different perspectives. We integrate this representation in a whole framework which has two stages. The first one is to allow an efficient retrieval based on the geometric properties (shape) of objects in images with clutter. This is achieved by i) using a contextual descriptor that incorporates the distribution of local structures, and ii) taking a proper distance that disregards the clutter of the images. At a second stage, we introduce a more discriminative descriptor that characterizes the parts of the objects by their color and their local tructure. By sing relevant-feedback and boosting as a feature selection algorithm, the system is able to learn simultaneously the information that characterize each part of the object along with their mutual spatial relations. Results are reported on two known databases and are quantitatively compared to other successful approaches