Miracle-dz/UniFAR-FTUs huggingface dataset:
Phonemic knowledge and learning to read are reciprocal: A longitudinal study of first grade children.

Explicit knowledge of the phonemic structure of spoken words, or phonemic awareness, has sometimes been seen as necessary for learning to read. But it is suggested that although some phonemic knowledge is important for beginning reading, the relationship between phonemic knowledge and learning to read is reciprocal. The results of a longitudinal study of first grade readers support this claim. Children were tested at four points throughout the year on tasks of syn thesis (phoneme blending) and analysis (deletion and tapping). Analyses of the tasks emphasize the differing cognitive demands of phoneme synthesis and pho neme deletion. According to the results of partial time-lag correlations, the dele tion task in particular taps a phonemic knowledge that is truly reciprocal in its re lation to reading. Gains in reading enable gains in deletion which enable further gains in reading. The synthesis task taps a more primitive phonemic knowledge that has a simple (nonreciprocal) enabling relationship to reading gains.
Thermal Analysis of the Shared Register File in VLIW Architectures

This paper presents a thermal model used to visualize and analyze temperature evolution in the shared register files found on VLIW systems. The model allows the analysis of several factors that have strong impact on the heat transfer: layout topology, placement and access policy. The results obtained can further be used in the design of temperature- aware compilers and place&route tools.
HOMOLOGY SEARCH METHODS

Homology search methods have advanced substantially in recent years. Beginning with the elegant Needleman-Wunsch and Smith-Waterman dynamic programming techiques of the 1970s, algorithms have been developed that were appropriate for the data sets and computer systems of their times. As data sets grew, faster but less sensitive heuristic algorithms, such as FASTA and BLAST, became a dominant force in the late 1980s and 1990s. As datasets have grown still larger in the post-genome era, new technologies have appeared to address these new problems. For example, the optimal spaced seeds of PatternHunter increase speed and sensitivity. Using these ideas, we can achieve BLAST-level speed and sensitivity approaching that of slow algorithms like the Smith-Waterman, bringing us back to a full circle. We wish to take you with us on this round trip, with some detours along the way so as to study both global and local alignment. We present methods for general purpose homology that are widely adopted, not individual programs.
Performance Analysis and Optimization for Interference Alignment Over MIMO Interference Channels With Limited Feedback

In this paper, we address the problem of interference alignment (IA) over MIMO interference channels with limited channel state information (CSI) feedback based on quantization codebooks. Due to limited feedback and, hence, imperfect IA, there are residual interferences across different links and different data streams. As a result, the performance of IA is greatly related to the CSI accuracy (namely number of feedback bits) and the number of data streams (namely transmission mode). In order to improve the performance of IA, it makes sense to optimize the system parameters according to the channel conditions. Motivated by this, we first give a quantitative performance analysis for IA under limited feedback and derive a closed-form expression for the average transmission rate in terms of feedback bits and transmission mode. By maximizing the average transmission rate, we obtain an adaptive feedback allocation scheme, as well as a dynamic mode selection scheme. Furthermore, through asymptotic analysis, we obtain several clear insights on the system performance and provide some guidelines on the system design. Finally, simulation results validate our theoretical claims and show that obvious performance gain can be obtained by adjusting feedback bits dynamically or selecting transmission mode adaptively.
A Novel Hybrid System for Skin Lesion Detection

In this paper, a new intelligent method of classifying benign and malignant melanoma lesions is implemented. The system consists of four stages; image pre-processing, image segmentation, feature extraction, and image classification. As the first step of the image analysis, pre-processing techniques are implemented to remove noise and undesired structures from the images using techniques such as median filtering and contrast enhancement. In the second step, a simple thresholding method is used to segment and localise the lesion, a boundary tracing algorithm is also implemented to validate the segmentation. Then, a wavelet approach is used to extract the features, more specifically wavelet packet transform (WPT). Finally, the dimensionality of the selected features is reduced with principal component analysis (PCA) and later supplied to an artificial neural network and support vector machine classifiers for classification. The ability to correctly discriminate between benign and malignant lesions was about 95% for the Artificial Neural Network and 85% for the Support Vector Machine classifier.
ESTIMATION OF POSTERIOR PROBABILITIES WITH NEURAL NETWORKS : APPLICATION TO MICROCALCIFICATION DETECTION IN BREAST CANCER DIAGNOSIS

Neural networks (NNs) are customarily used as classifiers aimed at minimizing classification error rates. However, it is known that the NN architectures that compute soft decisions can be used to estimate posterior class probabilities; sometimes, it could be useful to implement general decision rules other than the maximum a posteriori (MAP) decision criterion. In addition, probabilities provide a confidence measure of the classifier decisions, a fact that is essential in applications in which a high risk is involved. This chapter is devoted to the general problem of estimating posterior class probabilities using NNs. Two components of the estimation problem are discussed: Model selection, on one side, and parameter learning, on the other. The analysis assumes an NN model called the generalized softmax perceptron (GSP), although most of the discussion can be easily extended to other schemes, such as the hierarchical mixture of experts (HME) [1], which has inspired part of our work, or even the well-known multilayer perceptron. The use of posterior probability estimates is applied in this chapter to a medical decision support system; the testbed used is the detection of microcalcifications (MCCs) in mammograms, which is a key step in breast cancer early diagnosis. The chapter is organized as follows: Section 3.2 discusses the estimation of posterior class probabilities with NNs, with emphasis in a medical application; Section 3.3 discusses learning and model selection algorithms for the GSP networks; Section 3.4 proposes a system for MCC detection based on the GSP; Section 3.5 shows some simulation results on detection performance using a mammogram database; and Section 3.6 provides some conclusions and future trends.
Cryptococcus laurentii Diarrhea in a Neoplastic Patient

We present a rare case of diarrhea and neutropenia caused by Cryptococcus laurentii (C. laurentii) infection in old patient with metastatic rectal cancer who underwent FOLFOX plus Cetuximab chemotherapy. C. laurentii is an extremely rare human pathogen. To the best of our knowledge, here, we report the first case of diarrhea and neutropenia caused by C. laurentii in a 74-year-old man with metastatic rectal cancer and hepatic metastases who underwent FOLFOX plus Cetuximab chemotherapy.
Interaction and control with the auxiliary of hand gesture

This paper presents method used hand gesture recognition in human-computer interaction and control. Nowadays in dataglove-driven motion capture field, researchers preprocess the raw sensor data of the glove with calibration methods for acquiring a high precision in the VR environment. But there are still alternative solutions. Some machine learning algorithms, for example the self-organizing map method, offer a powerful capacity in the case of hand gesture recognition with uncalibrated glove data. We present the reason we introduced the SOM into the recognition process and how it works. Our goal is to construct a stable and robust mechanism to recognize hand gesture and then put it into hand gesture control system as an interaction platform for virtual reality.
Modelling the knowledge and reasoning of users in a knowledge-based authoring tool

This paper describes the domain-independent user modelling capabilities of a knowledge-based authoring tool. User modelling is primarily based on a cognitive theory that models human reasoning and is called Human Plausible Reasoning. Moreover the cognitive theory is combined with the overlay modelling technique that aims to model students' knowledge as a subset of the domain knowledge. This method is used in the authoring tool to help the instructors create Intelligent Tutoring Systems (ITS) that may model both the learners' level of factual knowledge on a particular domain and their reasoning abilities within this domain. The resulting ITSs aim to allow the learners justify their answers to questions related to the domain taught. In this way, the system may assess the students' knowledge by taking into account the reasoning that the students have used. On the other hand, the students have the opportunity to consolidate what they have learned by elaborating on their knowledge. At the user interface level,.
Position control of VTOL UAVs using IMU and GPS measurements

We propose a new position control scheme for vertical take-off and landing (VTOL) unmanned airborne vehicles (UAVs). Traditionally, the control schemes for this type of vehicle assume that the system attitude is accurately known (or measured). Unfortunately, there does not exist any sensor that directly measures the orientation of a rigid body. Instead, to obtain the orientation of the aircraft, separately designed attitude-estimation schemes relying, for instance, on an inertial measurement unit (IMU) must be employed. Consequently, one drawback of this common practice, on top of the possible inaccuracies in recovering the systems attitude, is mainly related to the difficulty of proving the stability of the overall closed-loop system (observer-controller). Motivated by this problem, we propose a new position control scheme that does not require the recovery of the system's attitude. Instead, we rely on a direct use of the vector measurements provided by the IMU. Our approach can efficiently handle large linear accelerations, which is not the case in traditional controllers relying on IMU-based attitude observers that assume that the accelerometer provides a measurement of the gravity vector in the body-attached frame.
Input-Output Structure and Nominal Staggering: The Persistence Problem Revisited

This paper re-examines the conventional wisdom on the equivalence of staggered-wage setting and staggered-price setting in generating persistent real effects of aggregate demand shocks in a dynamic general equilibrium framework with an input-output production structure. Under staggered-wage setting, a relative wage consideration of households induces sluggish wage adjustments and thus sluggish price adjustments as well, just as in the case with no input-output connections. Under staggered-price setting, relative wages are constant, but the presence of the input-output structure creates a real wage effect which prevents nominal wages from deviating too much from the sticky intermediate input prices, resulting in an endogenous nominal wage rigidity; at the same time, the stickiness in the intermediate input prices translates directly into the sluggishness in marginal cost movements, reinforcing the real wage effect to increase the rigidity in firms' pricing decisions. Thus, while not helping the staggered-wage setting, the input-output structure improves the ability of the staggered-price setting in generating persistence. As a result, the conventional wisdom may continue to hold for some reasonable parameter values.
Volumetric Representation for Sparse Multi-Views

In this paper, we propose a novel volumetric representation for a sparse set of calibrated multi-view images of a non-Lambertian scene. The depth map of each reference view is registered into a volume and a simple algorithm to shape the volume is introduced. Particular colours are defined for each voxel to render a smooth and realistic image. Synthesized results demonstrate the good performance with the proposed scheme, both for parallel-camera and non-parallel-camera geometries.
Modeling Structural Change in Money Demand Using a Fourier-Series Approximation 1

The paper develops a simple method that can be used to test for a time-varying intercept and to approximate its form. The test is solidly grounded in asymptotic theory and has good small-sample properties. The methodology is based on the fact that a Fourier approximation can capture the variation in any absolutely integrable function of time. As such, it is possible to use successive applications of the test to ‘back-out” the form of the time-varying intercept. We illustrate the methodology using an extended example concerning the demand for money.
Statistical Signal Processing Methods for the Identification of Clave Structure in Latin American Rhythms

—This paper describes the preliminary investigation into the development of a statistical pattern recognition method for identifying the rhythmic structure known as clave. Autocorrelation is discussed as a way of obtaining the musical signature of the clave form. PSD estimation, cross-correlation and beat-tracking are discussed as potential methods of processing and comparing signals in light of the deterministic and statistical estimates performed. Preliminary results are discussed based on biased estimate plots of autocorrelation and PSD.
neuroanatomy of hemiparesis stroke: implications for the functional Ipsilateral motor dysfunction from unilateral

ABSTRACTBackground: Motor dysfunction in the contralateral handhas been well characterised after stroke. The ipsilateralhand has received less attention, yet may providevaluable insights into the structure of the motor systemand the nature of the recovery process. By tracking motorfunction of both hands beginning in the acute strokeperiod in patients with cortical versus subcortical lesions,we sought to understand the functional anatomy of theipsilateral deficit.Methods: We examined 30 patients with first-everunilateral hemiparetic stroke, 23 with subcortical lesionsaffecting the corticospinal tract, seven with corticalinvolvement. Patients performed hand dynamometry andthe 9-Hole Peg Test (9HPT) with each hand at 24–48 h,1 week, 3 months and 1 year after stroke. Linearregression was used to compare the two different motortasks in each hand. Repeated measures ANOVA wasused to compare recovery rates of the two tasks in thefirst 3 months.Results: Ipsilateral 9HPT scores averaged z=27.1,23.6, 22.5 and 22.3 at the four time points whereasgrip strength was unaffected. The initial degree ofimpairment of grip strength in the contralateral hand didnot correlate with the degree of impairment of 9HPT ineither the contralateral or ipsilateral hand (r=0.001,p=0.98), whereas the initial degree of impairment of9HPT in the contralateral hand correlated with the degreeof impairment of 9HPT in the ipsilateral hand (r=0.79,p=0.035). The rate of recovery also differed for the twotasks (p=0.005). Conclusion: Ipsilateral motor deficits are demonstrableimmediately after stroke and extend into the subacuteand chronic recovery period. Dissociation between gripstrength and dexterity support the notion that dexterityand grip strength operate as anatomically and functionallydistinct entities. Our findings in patients with subcorticallesions suggest that the model of white matter tract injuryneeds to be refined to reflect the influence of asubcortical lesion on bi-hemispheral cortical networks,rather than as a simple ‘‘severed cable’’ model ofdisruption of corticofugal fibres. Our data have implica-tions for both stroke clinical trials and the development ofnew strategies for therapeutic intervention in strokerecovery.Unilateral stroke causing hemiparesis is commonlythought of as affecting only the contralateral hand.What has been much less completely addressed isthe effect of stroke on the hand ipsilateral to thelesioned hemisphere. More than 30 years ago,Norwegian neuroanatomist Brodal observed thathis right side handwriting was impaired after hesuffered a right hemisphere stroke causing lefthemiparesis.
Functional MRI and the Wada test provide complementary information for predicting post-operative seizure control

Prediction of post-surgical seizure relief and potential cognitive deficits secondary to anterior temporal lobectomy (ATL) are important to pre-surgical planning. Although the intracarotid amobarbital test (IAT) is predictive of post-ATL seizure outcome, development of non-invasive and more precise means for determining post-ATL seizure relief are needed. We previously reported on a technique utilizing functional MRI (fMRI) to evaluate the relative functional adequacy of mesial temporal lobe structures in preparation for ATL. In the present study, we report follow-up outcome data on eight temporal lobe epilepsy (TLE) patients 1-year post-ATL who were evaluated pre-surgically using IAT and fMRI. Functional memory lateralization using fMRI predicted post-ATL seizure outcome as effectively as the IAT. In general, asymmetry of functional mTL activation favouring the non-epileptic hemisphere was associated with seizure-free status at 1-year follow-up. Moreover, when combined, fMRI and IAT provided complementary data that resulted in improved prediction of post-operative seizure control compared with either procedure alone.
Decoding Group Vocalizations: The Acoustic Energy Distribution of Chorus Howls Is Useful to Determine Wolf Reproduction

Population monitoring is crucial for wildlife management and conservation. In the last few decades, wildlife researchers have increasingly applied bioacoustics tools to obtain information on several essential ecological parameters, such as distribution and abundance. One such application involves wolves (Canis lupus). These canids respond to simulated howls by emitting group vocalizations known as chorus howls. These responses to simulated howls reveal the presence of wolf litters during the breeding period and are therefore often used to determine the status of wolf populations. However, the acoustic structure of chorus howls is complex and discriminating the presence of pups in a chorus is sometimes difficult, even for experienced observers. In this study, we evaluate the usefulness of analyses of the acoustic energy distribution in chorus howls to identify the presence of pups in a chorus. We analysed 110 Iberian wolf chorus howls with known pack composition and found that the acoustic energy distribution is concentrated at higher frequencies when there are pups vocalizing. We built predictive models using acoustic energy distribution features to determine the presence of pups in a chorus, concluding that the acoustic energy distribution in chorus howls can be used to determine the presence of wolf pups in a pack. The method we outline here is objective, accurate, easily implemented, and independent of the observer's experience. These advantages are especially relevant in the case of broad scale surveys or when many observers are involved. Furthermore, the analysis of the acoustic energy distribution can be implemented for monitoring other social canids that emit chorus howls such as jackals or coyotes, provides an easy way to obtain information on ecological parameters such as reproductive success, and could be useful to study other group vocalizations.
A Performance Model of MPLS Multipath Routing with Failures and Repairs of the LSPs

Efficient operation of multipath routing is considered as one of the most important aspects for the success of MPLS traffic engineering. Multipath routing has an advantage over the traffic routing based on single shortest paths because single path routing may lead to unbalanced traffic situations and degraded QoS (Quality of Service). This paper proposes a novel analytical queueing model for the performance evaluation of multipath routing in MPLS networks. This paper applies an extension of a generalized Markovian queue, called the HetSigma queue, to model the operation of ingress nodes and derives the performance measures. That extended queue is essentially the MM ∑K k=1 CPPk/GE/c/L queue with heterogeneous servers, and with server-breakdowns and repairs according to an appropriate repair strategy. A case study is done numerically using the developed model. The model-validation is accomplished by comparing the numerical results of the model with those of the simulation of the system. The model is fast with good accuracy, hence useful to network designers in an number of aspects. P13/1
Lifestyle intervention is associated with decreased concentrations of circulating pentraxin 3 independent of CRP decrease

Abstract Objectives. Pentraxin 3 (PTX3) is an acute phase marker, which is produced at the site of infection or inflammation in contrast to CRP that is mainly synthesized by the liver. The aim of the present study was to see if lifestyle interventions/weight loss would lead to decreased blood plasma concentrations of PTX3. Methods. Study subjects (n = 31) were recruited to a lifestyle intervention program aiming at increased physical activity, improved eating habits, and weight loss. High-sensitivity C-reactive protein (CRP) and PTX3 methods were used for analysis of CRP and PTX3 in plasma samples collected at inclusion and after 4 and 8 weeks of treatment. Results. Wilcoxon paired samples test showed a significant decrease in PTX3 concentrations from 2068 pg/mL at start to 2007 pg/mL at 4 weeks (P = 0.002) and 1748 pg/mL at 8 weeks (P = 0.003). The PTX3 decrease was not significantly correlated with a corresponding decrease in CRP or weight reduction. Conclusions. The lifestyle intervention program resulted in a significant reduction of circulating concentrations of pentraxin 3 already after 4 and 8 weeks of treatment.
A 5.8 GHz CMOS LNA for WLAN applications

A novel design methodology was used to design an LNA for WLAN applications in the 5 GHz band. The LNA was implemented in a 0.18 /spl mu/m standard CMOS technology and achieves a gain of 16.7 dB, a noise figure of 1.4 dB and an IIP3 of -2.6 dBm, while dissipating just 4.5 mW from a 1.8 V supply. Compared to previously reported designs, the LNA exhibits good noise figure as well as higher gain and higher linearity at a fraction of the power dissipation.
Content-aware rate adaptation scheme to improve stability in HTTP Adaptive Streaming

HTTP-based adaptive streaming (HAS) has recently been widely deployed on the Internet. In the HAS approach, a video content is encoded at multiple bitrates and the encoded video content is segmented into small parts of fixed durations. The HAS client requests a video segment, and stores it in the playout buffer. Many studies have shown a robust rate adaptation algorithm is critical to ensuring quality-of-experience in HAS systems. However, most existing algorithms use a poorly designed bandwidth estimation method to adjust video bitrates. In this paper, we propose a novel content-aware rate adaptation algorithm that improves stability of the HAS system. In our method, the playout buffer is modeled with content characteristics. Different from previous works, we propose to adapt video bitrates based on the variance in playout buffer length, rather than static buffer information. We evaluate the performance of the proposed algorithm by simulation and subjective tests. Through extensive simulations, we demonstrate that the proposed scheme achieves very high quality smoothness, even under variations of network bandwidth.