Miracle-dz/UniFAR-FTUs huggingface dataset:
Oversampled Filter Banks with instantaneous erasures

Oversampled Filter Banks (OFB) can be used for erasure correction due to the redundancy that they insert into the signal. People have studied erasures using a frame-theoretic approach in which erasure is defined as the deletion of the frame expansion coefficients corresponding to a frame element. This approach applies to OFBs and results in an erasure being interpreted as losing all samples in a sub-band. However, a more realistic and flexible scenario is when an erasure is considered as the loss of sub-band samples only for particular time instances. Alternatively in an erasure-free channel, analogous to the concept of puncturing, the sub-band samples might be erased deliberately to change the code rate. In both of these scenarios, the erasure pattern of sub-bands can differ for different time instances. In this paper, we investigate this situation and derive a set of sufficient conditions that should be satisfied by the OFB in order to reconstruct the output. Simulation results will be presented for substantiating the proposed OFB structure which show the efficiency of this method in increasing the resilience of OFB against erasures.
Maximizing determinants under partition constraints

Given a positive semidefinte matrix L whose columns and rows are indexed by a set U, and a partition matroid M=(U, I), we study the problem of selecting a basis B of M such that the determinant of the submatrix of L induced by the rows and columns in B is maximized. This problem appears in many areas including determinantal point processes in machine learning, experimental design, geographical placement problems, discrepancy theory and computational geometry to model subset selection problems that incorporate diversity. Our main result is to give a geometric concave program for the problem which approximates the optimum value within a factor of er+o(r), where r denotes the rank of the partition matroid M. We bound the integrality gap of the geometric concave program by giving a polynomial time randomized rounding algorithm. To analyze the rounding algorithm, we relate the solution of our algorithm as well the objective value of the relaxation to a certain stable polynomial. To prove the approximation guarantee, we utilize a general inequality about stable polynomials proved by Gurvits in the context of estimating the permanent of a doubly stochastic matrix.
Membrane protein retention in the yeast Golgi apparatus: dipeptidyl aminopeptidase A is retained by a cytoplasmic signal containing aromatic residues

The mechanism by which yeast dipeptidyl aminopeptidase (DPAP) A, type II integral membrane protein, is retained in the late Golgi apparatus has been investigated. Prior work demonstrated that the 118-amino acid cytoplasmic domain is both necessary and sufficient for Golgi retention and that mutant or overexpressed DPAP A no longer retained in the Golgi was delivered directly to the vacuolar membrane (Roberts, C. J., S. F. Nothwehr, and T. H. Stevens. 1992. J. Cell Biol. 119:69-83). Replacement of the DPAP A transmembrane domain with a synthetic hydrophobic sequence did not affect either Golgi retention of DPAP A or vacuolar delivery of the retention-defective form of DPAP A. These results indicate that the DPAP A transmembrane domain is not involved in either Golgi retention or targeting of this membrane protein. A detailed mutational analysis of the cytoplasmic domain of DPAP A indicated that the most important elements for retention were within the eight residue stretch 85-92. A 10-amino acid region from DPAP A (81- 90) was sufficient for Golgi retention of alkaline phosphatase, a type II vacuolar membrane protein. Detailed mutational analysis within this 10-amino acid sufficient region demonstrated that a Phe-X-Phe-X-Asp motif was absolutely required for efficient retention. The efficiency of Golgi retention via the DPAP A signal could be diminished by overexpression of wild type but not retention-defective versions of Kex2p, another late Golgi membrane protein, suggesting that multiple Golgi membrane proteins may be retained by a common machinery. These results imply a role for a cytoplasmic signal involving aromatic residues in retention of late Golgi membrane proteins in the yeast Saccharomyces cerevisiae.
ADMM-EM Method for L 1-Norm Regularized Weighted Least Squares PET Reconstruction

The L 1-norm regularization is usually used in positron emission tomography (PET) reconstruction to suppress noise artifacts while preserving edges. The alternating direction method of multipliers (ADMM) is proven to be effective for solving this problem. It sequentially updates the additional variables, image pixels, and Lagrangian multipliers. Difficulties lie in obtaining a nonnegative update of the image. And classic ADMM requires updating the image by greedy iteration to minimize the cost function, which is computationally expensive. In this paper, we consider a specific application of ADMM to the L 1-norm regularized weighted least squares PET reconstruction problem. Main contribution is derivation of a new approach to iteratively and monotonically update the image while self-constraining in the nonnegativity region and the absence of a predetermined step size. We give a rigorous convergence proof on the quadratic subproblem of the ADMM algorithm considered in the paper. A simplified version is also developed by replacing the minima of the image-related cost function by one iteration that only decreases it. The experimental results show that the proposed algorithm with greedy iterations provides a faster convergence than other commonly used methods. Furthermore, the simplified version gives a comparable reconstructed result with far lower computational costs.
A Hybrid Method for Sequence Clustering

The problem of sequence clustering is one of the fundamental research topics. However, most algorithms are dedicated to the case of single-label clustering. In this paper, we propose sequence clustering algorithms which can be applied for finding multi labels with respect to variable-length sequences. In our research, we first map sequences as vectors in the feature space by applying DCT transformation on each sliding window of sequences. A large amount of feature vectors could be further reduced by using the histogram concept and the quantization technique. Then, we use the hierarchical clustering algorithm to determine sequence labels. We also apply minimum bounding rectangle (MBR) techniques to approximate the distribution of feature vectors, and the elapsed time can be reduced accordingly. According to our experiment, the accuracy in the Rand index validity can be up to 88% for the single-label clustering of equal-length case. By applying the MBR techniques, the elapsed time of improved approach can be reduced as much as one sixth of the original approach, and the accuracy remains 86%. For the multi-label clustering, the accuracy can be up to 85%, and the elapsed time is about one fifth of the single-label case.
Emergency Tracheal Intubation: Complications Associated with Repeated Laryngoscopic Attempts

Repeated conventional tracheal intubation attempts may contribute to patient morbidity. Criticallyill patients (n = 2833) suffering from cardiovascular, pulmonary, metabolic, neurologic, or trauma-related deterioration were entered into an emergency intubation quality improvement database. This practice analysis was evaluated for airway and hemodynamic-related complications based on a set of defined variables that were correlated to the number of attempts required to successfully intubate the trachea outside the operating room. There was a significant increase in the rate of airway-related complications as the number of laryngoscopic attempts increased (≤2 versus >2 attempts): hypoxemia (11.8% versus 70%), regurgitation of gastric contents (1.9% versus 22%), aspiration of gastric contents (0.8% versus 13%) bradycardia (1.6% versus 21%), and cardiac arrest (0.7% versus 11%; P < 0.001). Although predictable, this analysis provides data that confirm the number of laryngoscopic attempts is associated with the incidence of airway and hemodynamic adverse events. These data support the recommendation of the ASA Task Force on the Management of the Difficult Airway to limit laryngoscopic attempts to three in lieu of the considerable patient injury that may occur.
Adaptive learning for complex-valued data

In this paper we propose a variant of the Generalized Matrix Learning Vector Quantization (GMLVQ) for dissimilarity learning on complex-valued data. Complex features can be encountered in various data domains, e.g. Fourier transformed mass spectrometry or image analysis data. Current approaches deal with complex inputs by ignoring the imaginary parts or concatenating real and imaginary parts in one real valued vector. In this contribution we propose a prototype based classification method, which allows to deal with complex-valued data directly. The algorithm is tested on a benchmark data set and for leaf recognition using Zernike moments. We observe that the complex version converges much faster than the original GMLVQ evaluated on the real parts only. The complex version has fewer free parameters than using a concatenated vector and is thus computationally more efficient than original GMLVQ
A Constraint-based Framework for the Cascade Vulnerability Problem

Establishing network security is based not just on the security of its component systems but also on how they are configured to interoperate. In this paper we consider how soft constraints provide an approach to detecting the cascade vulnerability problem: whether system interoperation provides circuitous or cascading routes across the network that increase the risk of violation of multilevel security. Taking the constraints approach means that we are building on techniques that have proven success in solving large-scale problems from other domains.
The predictive value of echocardiographic parameters associated with left ventricular diastolic dysfunction on short- and long-term outcomes of catheter ablation of atrial fibrillation.

AIMS Recurrence of atrial fibrillation (AF) is frequently observed after AF catheter ablation. However, the predictive value of echocardiographic parameters associated with left ventricular diastolic dysfunction (LVDD) has not been well studied. METHODS AND RESULTS In 124 consecutive patients (mean age 61 ± 10 years, 60% male) with paroxysmal (n = 70) or persistent AF (n = 54) undergoing AF catheter ablation, mitral early diastolic peak (E-wave) and late peak (A-wave) velocities, E/A ratio, deceleration time (DT) of mitral early velocity, early diastolic mitral annulus peak velocity (e'), and E/e' ratio were determined by transthoracic echocardiography. Early (ERAF) and late AF recurrence (LRAF) were monitored with 7-day Holter electrocardiograms directly after catheter ablation and after 6 and 12 months. Early AF recurrence occurred in 34% of the patients, while LRAF was observed in 27% of the patients. Patients with ERAF had higher E-wave (0.9 ± 0.2 vs. 0.8 ± 0.2 m/s, P = 0.035) and lower A-wave velocity (0.5 ± 0.2 vs. 0.6 ± 0.2 m/s, P = 0.038), higher E/A ratio (1.8 ± 0.9 vs. 1.5 ± 0.9, P = 0.089), and slower DT (214 ± 67 vs. 243 ± 68 ms, P = 0.073), while E/e', left atrial diameter, and left ventricular ejection fraction were similar. In multivariable regression analysis, the E/A ratio was the only independent predictor of ERAF (odds ratio 2.905, 95% confidence interval 1.072-7.870, P = 0.036). None of the echocardiographic parameters influenced the late therapy outcome. CONCLUSION Early results of the catheter ablation, but not the late rhythm outcome, are influenced by an impaired mitral inflow pattern, which is associated with LVDD.
Population coding of tone stimuli in auditory cortex: dynamic rate vector analysis

Neural representations of even temporally unstructured stimuli can show complex temporal dynamics. In many systems, neuronal population codes show ‘progressive differentiation’, whereby population responses to different stimuli grow further apart during a stimulus presentation. Here we analysed the response of auditory cortical populations in rats to extended tones. At onset (up to 300 ms), tone responses involved strong excitation of a large number of neurons; during sustained responses (after 500 ms) overall firing rate decreased, but most cells still showed statistically significant rate modulation. Population vector trajectories evoked by different tone frequencies expanded rapidly along an initially similar trajectory in the first tens of milliseconds after tone onset, later diverging to smaller amplitude fixed points corresponding to sustained responses. The angular difference between onset and sustained responses to the same tone was greater than between different tones in the same stimulus epoch. No clear orthogonalization of responses was found with time, and predictability of the stimulus from population activity also decreased during this period compared with onset. The question of whether population activity grew more or less sparse with time depended on the precise mathematical sense given to this term. We conclude that auditory cortical population responses to tones differ from those reported in many other systems, with progressive differentiation not seen for sustained stimuli. Sustained acoustic stimuli are typically not behaviorally salient: we hypothesize that the dynamics we observe may instead allow an animal to maintain a representation of such sounds, at low energetic cost.
Successive Blind Detection of DS/CDMA Signals

This paper provides an investigation into the performance of a multi-stages constant-modulus filter/ signal canceller (CMA/SC) for blind detection of direct sequence/code code division multiple-access (DS/CDMA) signals over additive white Gaussian noise (AWGN) channels. A simple stochastic gradient algorithm for implementing the scheme is presented and the convergence properties of the algorithms are analyzed. Simulation examples are given to demonstrate the robustness of the performance of the proposed scheme. The Direct sequence-code division multiple access (DS/CDMA) system implemented by direct-sequence spread spectrum (DS/SS) technique is the most promising multiplexing technology for cellular telecommunications services, such as personal communications, mobile telephony, and indoor wireless networks. The advantages of DS/SS for these services include superior operation in multi-path environments, flexibility in the allocation of channels, the ability to operate asynchronously, privacy, and increased capacity in burst or fading channels [1]. It is well known that the processing gain of a spread spectrum system will provide the system with a sufficient capability of interference rejection [2], [3]. Multiple access interference (MAI), due to many simultaneous users, constitutes the main limitation on the performance of DS/CDMA systems. Multiuser detection techniques can efficiently suppress MAI and substantially increase the capacity of CDMA systems [4], [5]. Various multiuser detection schemes for DS/CDMA systems have been developed over the past decade. More recently, blind adaptive multiuser detection, which requires the prior knowledge of only the spreading waveform and timing of the desired user, has received considerable attention [6]. The main motivation for employing a blind scheme is to avoid the need for a training sequence, to thus offer better spectrum efficiency. The most representative methods of the blind multiuser detection include the minimum output energy (MOE) [7] and subspace approach [8]. However these methods assume a knowledge of the spreading waveform, which is not available in some applications like electronic intelligence (ELINT). The constant-modulus (CM) receiver can perform almost as well as the non-blind/trained receiver except that the CMA captures an arbitrary signal from the combined received CDMA signals, which may be of no interest. In applications like ELINT it is necessary to detect all the active users, either in a parallel or a serial manner. This paper describes a mechanism for the successive blind detection for all the active users in a DS/CDMA system. The principle of operation is based on utilizing identical successive stages for detection. Each stage, CMA detects an arbitrary signal, which is …
APRENDIZAJE DE CUESTIONES GRAMATICALES A TRAVÉS DE LA MÚSICA COMO NEXO INTERCULTURAL. PROPUESTA DIDÁCTICA PARA UN CURSO DE VERANO DE LA UNIVERSIDAD DE LAS PALMAS DE GRAN CANARIA (ULPGC)

The aim of the study is to enhance music as a didactic resource for the correct acquisition of grammatical knowledge of Spanish considered problematic at the time of approaching the study of our language: the use of the subjunctive, the unstressed personal pronouns and the verbs ser and estar . We also try to stimulate interest in research and personal autonomy, as well as encouraging intercultural relations and reinforcing the values of tolerance and camaraderie. It is a didactic proposal for the classroom of Spanish as a foreign language (ELE) aimed at students of level B2 in accordance with the guidelines of the Common European Framework of Reference for Languages. Broadly speaking, an active methodology is proposed, where tasks act as acquisition engines of communicative competence, applying the theory of practical assumptions such as songs. Finally, regarding the research methodology, we will stop at the presentation of the theoretical foundations, as well as the methodological approaches, which we consider fundamental, since they are the foundation of our proposal. Regarding the results of our field study, we have been able to meet the aims set at the beginning, that is: the acquisition of fixed grammatical knowledge and the achievement and encouragement of intercultural relations among students, thanks to the mentioned methodology implemented in the ELE classroom. Key words : interculturality, songs, grammar, lexicon.
Intelligent System for Premature Babies Healthcare at Home based on Case-based Reasoning

eHealth is offering a new way of delivering health services through the internet. Most eHealth applications are presented as new business arena with dubious clinical support. This research presents an eHealth system where users use technology within a home care program of patients with early hospital discharge. In particular, our work concerns premature babies’ care that can shorten their recovery period at home, where they can enjoy a more familiar environment. To guarantee the clinical monitoring of the patients, the eHealth system relies on case-based reasoning, an artificial intelligence methodology for developing intelligent systems that enables personalized patient’s treatment. In this paper we review the architecture of our system which has been developed in the framework of the MoSHCA project. It consists of three main components: the mobile, the server and the connection with the Hospital Information System. Case-based reasoning is used in several of the components to provide adequate support to both, babies and their families at home and physicians at the hospital regarding the baby care and follow-up.
Identifying the Development Approach trough a Problem-Oriented Analysis Method

This paper proposes new analysis method, called POAM (Problem-Oriented Analysis Method). POAM has been developed to solve several shortcomings of existing conceptual models (solution orientation and dependence of concrete development approaches). POAM uses a kind of conceptual model unbiased towards any development approach, thus supporting developers to understand the problem and its constraints before any solution is identified. POAM is also able to identify and derive the best classical conceptual model for a given situation, allowing developers to use in design those notations, as data flow diagrams or class diagrams, universally used for software development.
DCU at Generation Challenges 2011 Surface Realisation Track

In this paper we describe our system and experimental results on the development set of the Surface Realisation Shared Task. DCU submitted 1-best outputs for the Shallow sub-task of the shared task, using a surface realisation technique based on dependency-based n-gram models. The surface realiser achieved BLEU and NIST scores of 0.8615 and 13.6841 respectively on the SR development set.
Serotonin activation of a cyclic AMP-dependent sodium current in an identified neuron from Helisoma trivolvis

The mechanisms by which neurotransmitters regulate neurite extension and growth cone motility have been extensively studied using identified Helisoma neurons regenerating in cell culture. Specific neurons, such as buccal neuron B19, display a complex response to the addition of 5- HT involving the generation of action potentials, influx of extracellular calcium, and cessation of neurite extension and growth cone motility. While several studies have addressed the role of calcium in this cascade, little is known about the mechanism underlying the 5- HT-induced excitation of neuron B19. Therefore, we have begun to characterize the ion currents, receptors, and second messengers involved in the 5-HT-dependent depolarization of B19. Exposure of B19 to 5-HT resulted in the activation of a maintained inward current. Ion substitution experiments revealed that this current was carried mainly by sodium ions. The use of 8-bromo-cAMP, forskolin, or the phosphodiesterase inhibitor isobutyl methylxanthine (IBMX) to increase intracellular cAMP levels all resulted in inward current activation in the absence of 5-HT. Moreover, preloading the neuron with 8-bromo-cAMP was sufficient to prevent further current activation by 5-HT. In addition, the IBMX-activated current was greatly enhanced when induced in the presence of 5-HT. Protein kinase inhibitors failed to prevent 5- HT activation of sodium current, suggesting that cAMP may directly activate the current, independent of phosphorylation. Pharmacological experiments showed the B19 5-HT receptor has an EC50 of approximately 10(-7) M and can be activated by various indole analogs of 5-HT. Furthermore, methysergide displayed partial agonist activity. (ABSTRACT TRUNCATED AT 250 WORDS)