Miracle-dz/UniFAR-FTUs huggingface dataset:
Multifrequency VLA observations of the FR I radio galaxy 3C 31: morphology, spectrum and magnetic field

We present high-quality Very Large Array (VLA) images of the Fanaroff‐Riley Class I (FR I) radio galaxy 3C 31 in the frequency range 1365‐8440 MHz with angular resolutions from 0.25 to 40 arcsec. Our new images reveal complex, well resolved filamentary substructure in the radio jets and tails. We also use these images to explore the spectral structure of 3C 31 on large and small scales. We infer the apparent magnetic field structure by correcting for Faraday rotation. Some of the intensity substructure in the jets is clearly related to structure in their apparent magnetic field: there are arcs of emission where the degree of linear polarization increases, with the apparent magnetic field parallel to the ridges of the arcs. The spectra of the jets between 1365 and 8440 MHz are consistent with power laws within 60 arcsec of the nucleus. The spectral indices, α (flux density ∝ ν −α ) are significantly steeper (α = 0.62) within ≈7 arcsec of the nucleus than between 7 and 50 arcsec (α = 0.52‐0.57). The spectra of the arcs and of the jet edges are also slightly flatter than the average for their surroundings. At larger distances, the jets are clearly delimited from surrounding larger scale emission both by their flatter radio spectra and by sharp brightness gradients. The spectral index of 0.62 in the first 7 arcsec of 3C 31’s jets is very close to that found in other FR I galaxies where their jets first brighten in the radio and where X-ray synchrotron emission is most prominent. Farther from the nucleus, where the spectra flatten, X-ray emission is fainter relative to the radio. The brightest X-ray emission from FR I jets is therefore not associated with the flattest radio spectra, but with a particle acceleration process whose characteristic energy index is 2α + 1 = 2.24. The spectral flattening with distance from the nucleus occurs where our relativistic jet models require deceleration, and the flatter spectra at the jet edges may be associated with transverse velocity shear.
Exploiting Competition Relationship for Robust Visual Recognition

Joint learning of similar tasks has been a popular trend in visual recognition and proven to be beneficial. Between-task similarity often provides useful cues, such as feature sharing, for learning visual classifiers. By contrast, the competition relationship between visual recognition tasks (e.g., content independent writer identification and handwriting recognition) remains largely under-explored. A key challenge in visual recognition is to select the most discriminating features and remove irrelevant features related to intra-class variations. With the help of auxiliary competing tasks, we can identify such features within a joint learning model exploiting the competition relationship.Motivated by this intuition, we propose a novel way to exploit competition relationship for solving visual recognition problems. Specifically, given a target task and its competing tasks, we jointly model them by a generalized additive regression model with a competition constraint. This constraint effectively discourages choosing of irrelevant features (weak learners) that support the auxiliary competing tasks. We name the proposed algorithm CompBoost. In our study, CompBoost is applied to two visual recognition applications: (1) content-independent writer identification from handwriting scripts by exploiting competing tasks of handwriting recognition, and (2) actor-independent facial expression recognition by exploiting competing tasks of face recognition. In both experiments our approach demonstrates promising performance gains by exploiting the between-task competition.
Modified Variable Step Size Power Control Algorithm for CDMA Systems

Power control mechanism is an important issue for Code Division Multiple Access (CDMA) systems which helps in achieving higher capacity, combating against near far effect and provides high link performance. Unless a suitable power control mechanism is developed cellular systems cannot perform better. Power control allows to minimize the transmit power while keeping the system performance above the required value. In previous research [4], variable step size for closed loop power control system has been studied and results showed an increase in convergence speed and stability by properly choosing the step size. The new algorithm presented in this paper shows that it can perform better than variable step size power control algorithm and can obtain higher stability and convergence speed for step size δ at 0.1.
Functional and biological properties of the nuclear receptor coregulator PELP1/MNAR

Proline-, glutamic acid-, and leucine-rich protein (PELP)1, also known as modulator of nongenomic actions of the estrogen receptor (MNAR), is a novel nuclear receptor coregulator with a multitude of functions. PELP1/MNAR serves as a scaffolding protein that couples various signaling complexes with nuclear receptors and participates in genomic and nongenomic functions. Recent data suggest that PELP1/MNAR expression is deregulated in several cancers, including breast, endometrial, prostate, and ovarian cancer, and that PELP1/MNAR interacts with several oncogenes. In this review, we summarize the emerging biological properties and functions of PELP1/MNAR.
Social choice meets graph drawing: How to get subexponential time algorithms for ranking and drawing problems

We analyze a common feature of p-Kemeny AGGregation (p-KAGG) and p-One-Sided Crossing Minimization (p-OSCM) to provide new insights and findings of interest to both the graph drawing community and the social choice community. We obtain parameterized subexponential-time algorithms for p-KAGG—a problem in social choice theory—and forp-OSCM—a problem in graph drawing. These algorithms run in time O.2 O. p k logk/ /, where k is the parameter, and significantly improve the previous best algorithms with running times O.1. 403 k / and O.1. 4656 k /, respectively. We also study natural "above-guarantee" versions of these problems and show them to be fixed parameter tractable. In fact, we show that the above-guarantee versions of these problems are equivalent to a weighted variant of p-directed feedback arc set. Our results for the above-guarantee version of p-KAGG reveal an interesting contrast. We show that when the number of "votes" in the input top-KAGG is odd the above guarantee version can still be solved in time O.2 O. p k logk/ /, while if it is even then the problem cannot have a subexponential time algorithm unless the exponential time hypothesis fails (equivalently, unless FPTD Ma1c).
A Robust Approach to Schema Matching overWeb Query Interfaces

In recent years, more and more data sources are available on the Web, where data can be accessed only via web interfaces. To make these data sources sharable, holistic schema matching which benefits from a large number of schemas has attracted much attention. However, current holistic approaches still suffer from the following limitations: a). They are sensitive to noisy data; b). While different types of information about attributes (e.g. attribute names, text descriptions, domain values) have been used, it remains an issue to effectively merge these types of information. In this paper, we propose a re-sampling method for handling noisy data across multiple web interfaces in the same domain. Furthermore, we propose a novel method to utilize different types of information about attributes, which is robust for resolving homonyms. Our experimental results show that our proposed methods are highly effective.
Estimating Ratios of Normalizing Constantsfor Densities with Di erent

In Bayesian inference, a Bayes factor is deened as the ratio of posterior odds versus prior odds where posterior odds is simply a ratio of the normalizing constants of two posterior densities. In many practical problems, the two posteriors have diierent dimensions. For such cases, the current Monte Carlo methods such as the bridge sampling method (Meng and Wong 1996), the path sampling method (Gelman and Meng 1994), and the ratio importance sampling method (Chen and Shao 1994) cannot directly be applied. In this article, we extend importance sampling, bridge sampling, and ratio importance sampling to problems of diierent dimensions. Then we nd global optimal importance sampling, bridge sampling, and ratio importance sampling in the sense of minimizing asymptotic relative mean-square errors of estimators. Implementation algorithms, which can asymptotically achieve the optimal simulation errors, are developed and two illustrative examples are also provided.
Co-Occurrence of Haematoloechus complexus and Rhabdias joaquinensis in the Plains Leopard Frog from Nebraska

Abstract: Species of Haematoloechus and Rhabdias both are ubiquitous lung parasites of frogs, yet surprisingly little research has been conducted on the interactions between these worms. In a small Nebraska stream, 256 Rhabdias joaquinensis and 225 Haematoloechus complexus were found in the lungs of Lithobates (=Rana) blairi. Thirty-six of the 44 (82%) frogs were co-infected with H. complexus and R. joaquinensis whereas 5 (11%) frogs were infected with only 1 species and 3 (7%) frogs were uninfected. Tests for association between H. complexus and R. joaquinensis found a significant positive relationship between the 2 parasites. Significant positive relationships in intensity of infection were found when both lungs were combined but not when lungs were considered individually. Tests for association between H. complexus and R. joaquinensis found no relationship between the worms in the anterior and posterior portions of the lungs. These data suggest that H. complexus and R. joaquinensis do not competitively exclude each other from the lungs of L. blairi in southeastern Nebraska.
Voice conversion based on style and content separation with dual latent variable model

This paper presents a novel method for voice conversion based on style and content separation, which is solved by using dual latent variable model (D-LVM). Based on D-LVM, the vocal tract spectrum of speech represented by line spectral frequencies (LSF) is explicitly decomposed into so-called style and content factors, which are used to represent the speech meaning and the speaker individuality respectively. On the basis of reasonable separation of style and content for speech, voice conversion is performed successfully by reproducing converted speech using the initial speech content and the target speaker style. The objective and subjective tests show that, under the condition of limited training dataset, the method proposed in the paper gets better conversion performance compared to the conventional mapping based GMM system and SVD based bilinear model.
A Literature Survey of Speech Recognition and Hidden Markov Models

This article highlights Hidden Markov Models (HMM) and their use in Automatic Speech Recognition (ASR) Systems. Hidden Markov Models is the most widely used speech recognition technique. Speech recognition is a field that involves a lot of different disciplines. As more and more research is being done in this field, the application possibilities of speech recognition increases, this includes military uses as well as health care usage. This paper presents a high level view description of the basic speech recognition categories. It then goes on to discuss Hidden Markov Models and its use in ASR. Finally the paper looks briefly at some ways in which Speech Recognition Technology may be applied. ” Keywords--Automatic Speech Recognition (ASR) Hidden Markov Models
An IMM-based method for reentry-phase tracking of unknown ballistic missiles

In this paper, the tracking system which is related to the ballistic missile defense (BMD) is considered. In BMD system, it is necessary to track the fast and unknown objects. Furthermore, priori information about the hostile missile is not provided. Without the priori information like aerodynamic parameters, it is hard to make the filter dynamic model of the hostile missile. To solve this problem, in many researches, IMM filter is selected as a tracking filter of BMD system. But IMM filter itself is not a perfect tool for tracking the unknown target. If the IMM filter mode set does not subsume the true dynamic model, the tracking filter may have large error. So, the mode revision method is suggested. With this method, the IMM mode set is adaptively changed and then subsumes the true dynamic model.
QoS-Aware Automatic Service Composition by Applying Functional Clustering

With the steadily growing number of service providers the competition becomes more and more intense. In order to find a distinctive edge over other competitors, automatic service composition can be applied to further adapt to the requirements of the users. Most of the current composition approaches can be categorized as either planning or selection algorithms. The former automatically create workflows and tend to neglect Quality-of-Service (QoS) concerns, drawing compositions useless if user constraints are violated. Selection algorithms on the other hand optimize the QoS but provide no functional flexibility. In this paper we show how the strengths of both approaches can be combined by leveraging common characteristics of service registries. Therefore we utilize a data structure which arranges functionally similar services in clusters and computes the QoS of each cluster. Our planning tool composes workflows consisting of these clusters, taking the QoS of the clusters into account. This way, the utility in general and the reliability of the composed workflows are significantly increased. We prove the feasibility and the benefits of our functional clustering in our detailed evaluation.
Single Pass Spectrogram Inversion

We present a computationally efficient real-time algorithm for constructing time-domain audio signals from spectrograms. The Single-Pass Spectrogram Inversion (SPSI) algorithm is similar to the synthesis step in phaselocked vocoders, but with phase rates at spectral peaks determined solely from the magnitude spectra using quadratic interpolation. The algorithm provides good quality results in a single fully-deterministic pass, and can also provide excellent initial phase estimates for improved results with iterative spectrogram inversion techniques such as the Griffin-Lim algorithm.
Feature extraction and classification for underwater target signals based on Hilbert-Huang transform theory

In order to realize feature extraction and classification for underwater target signals, instead of the empirical mode decomposition (EMD) method, a new Ensemble EMD (EEMD) is used in the Hilbert-Huang transform when underwater target signals are analyzed. By the EEMD and Hilbert-huang transform, some feature parameters are extracted and applied to the classification of underwater target signals from actual measure. These features include (i) the center frequency of the strongest intrinsic mode function, (ii) the energy difference between the high and low frequency, (iii) the instantaneous energy variation range. Simulation and experimental results show that there exist some differences between the different types of target signals. Those may offer a good solution for automatic recognition of underwater target signals.
Blind Adaptive Reduced-Rank Detectors for DS-UWB Systems Based on Joint Iterative Optimization and the Constrained Constant Modulus Criterion

A novel linear blind adaptive receiver based on joint iterative optimization (JIO) and the constrained constant modulus (CCM) design criterion is proposed for interference suppression in direct-sequence ultra-wideband (DS-UWB) systems. The proposed blind receiver consists of two parts, a transformation matrix that performs dimensionality reduction and a reduced-rank filter that produces the output. In the proposed receiver, the transformation matrix and the reduced-rank filter are updated jointly and iteratively to minimize the constant modulus (CM) cost function subject to a constraint. Adaptive implementations for the JIO receiver are developed by using the normalized stochastic gradient (NSG) and recursive least-squares (RLS) algorithms. In order to obtain a low-complexity scheme, the columns of the transformation matrix with the RLS algorithm are updated individually. Blind channel estimation algorithms for both versions (NSG and RLS) are implemented. Assuming the perfect timing, the JIO receiver only requires the spreading code of the desired user and the received data. Simulation results show that both versions of the proposed JIO receivers have excellent performance in suppressing the inter-symbol interference (ISI) and multiple access interference (MAI) with a low complexity.
A State Space Error Estimate for POD-DEIM Nonlinear Model Reduction

This paper derives state space error bounds for the solutions of reduced systems constructed using proper orthogonal decomposition (POD) together with the discrete empirical interpolation method (DEIM) recently developed for nonlinear dynamical systems [SIAM J. Sci. Comput. , 32 (2010), pp. 2737-2764]. The resulting error estimates are shown to be proportional to the sums of the singular values corresponding to neglected POD basis vectors both in Galerkin projection of the reduced system and in the DEIM approximation of the nonlinear term. The analysis is particularly relevant to ODE systems arising from spatial discretizations of parabolic PDEs. The derivation clearly identifies where the parabolicity is crucial. It also explains how the DEIM approximation error involving the nonlinear term comes into play.
Guest Login - Visitor-centred Information Design

Projection of 3D space onto a 2D surface relies on the computer graphics camera, which is designed like the camera obscura. The procedure follows the laws of perspective projection and does not explicitly consider the viewer of the rendered image. Our approach is to extend this camera model in order to involve human perception into the rendering of 3D scenes. The aim is to create a user-centred spatial impression by a 2D image. By integrating the user into this process, implicit interactions can be applied to provide interfaces for an efficient and coherent communication of information in virtual environments. This paper introduces user-specific and context-specific parameters that must be taken into account when designing presence-aware applications. To this end, we present a concept of an interactive exhibition based on implicit interaction and point out its applicability in information design of three-dimensional scenes.
The Far-Reaching Effects of Believing People Can Change: Implicit Theories of Personality Shape Stress, Health, and Achievement During Adolescence

The belief that personality is fixed (anentity theoryof personality) can give rise to negative reactions to social adversities. Three studies showed that when social adversity is common—at the transition to high school—an entity theory can affect overall stress, health, and achievement. Study 1 showed that an entity theory of personality, measured during the 1st month of 9th grade, predicted more negative immediate reactions to social adversity and, at the end of the year, greater stress, poorer health, and lower grades in school. Studies 2a nd 3, both experiments, tested ab rief intervention that taught am alleable (incremental )t heory of personality—the belief that people can change. The incremental theory group showed less negative reactions to an immediate experience of social adversity and, 8 months later, reported lower overall stress and physical illness. They also achieved better academic performance over the year. Discussion centers on the power of targeted psychological interventions to effect far-reaching and long-term change by shifting interpretations of recurring adversities during developmental transitions.
A Modular System for Rule-based Text Categorisation

We introduce a modular rule-based approach to text categorisation which is more flexible and less time consuming to build than a standard rule-based system because it works with a hierarchical structure and allows for re-usability of rules. When compared to currently more wide-spread machine learning models on a case study, our modular system shows competitive results, and it has the advantage of reducing manual effort over time, since only fewer rules must be written when moving to a (partially) new domain, while annotation of training data is always required in the same amount.
Harnessing the power of P2P technology to build PC2 — An open and free cloud computing platform

Peer-to-Peer (P2P) systems are generally known as open and free systems since resources are often contributed from voluntary participants. Their limitation, however, is that they only support simple resource sharing such as file (storage) sharing and bandwidth sharing. On the other hand, based on virtualization techniques, cloud computing provides a more flexible mechanism to share all types of resources with no limitations. Nevertheless, the use of cloud computing usually requires a fee and is often locked-in to services of cloud computing providers (i.e., vendor lock-in). In this paper, we aim to combine P2P and cloud computing technologies to design and develop PC2, an open and free cloud computing platform that allows users to participate in any time to contribute as well as to consume sharing resources. While this combination inherits good advantages of these two technologies, it also avoid their disadvantages. As a proof-of-concept, we have developed a prototype for PC2 based on Eucalyptus, the most popular open source for building cloud computing platforms.
Abstract²a Semi-analytic Boundary Discretization Method, The

Method of Auxiliary Sources (MAS) is used to analyze Optical Antennas consisting of metallic parts. In addition to standard dipole-type antennas, consisting of two pieces of metal, a new structure consisting of a single metal piece with a tiny groove in the center is analyzed. It is demonstrated that difficult numerical problems are caused because optical antennas exhibit strong material dispersion, loss, and plasmon-polariton effects that require a very accurate numerical simulation. This structure takes advantage of the Channel Plasmon-Polariton (CPP) effect and exhibits a strong enhancement of the electric field in the groove. Also primitive 3D antenna model with spherical nano particles is analyzed.
Neurotrophin Signaling through the p75 Receptor Is Deficient in traf6-/- Mice

Activation of the neurotrophin receptor p75 has been shown to elicit opposing cellular signals. Depending on the context of the cell, p75 will either promote survival or induce apoptosis after neurotrophin stimulation. p75-induced apoptosis occurs through activation of c-Jun N-terminal kinase (JNK), whereas the survival signal is mediated by nuclear factor κB (NFκB). The receptor proximal signals that produce these responses are unknown, although several molecules have been identified that associate with the intracellular domain of p75. One such interactor, TRAF6, a member of the tumor necrosis factor receptor-associated factor family, has been implicated in p75 signaling. To assess the role of TRAF6 in p75 signaling, we analyzed mice with this gene deleted. In Schwann cells isolated from traf6+/+ animals, NGF elicited an 80% increase in transcription of an NFκB reporter; however, in traf6-/- cells, the NGF response was abrogated. Similarly, NGF activation of JNK was not apparent in Schwann cells from mice lacking traf6. Deficiencies in p75 signaling in traf6-/- animals resulted in a loss of p75-mediated apoptosis. In sympathetic neurons cultured from traf6+/+ superior cervical ganglia (SCGs), there was an increase in JNK activation and apoptosis after BDNF binding to p75; however, traf6-/- neurons did not respond. In vivo during naturally occurring cell death, there was a 55.6% reduction in TUNEL (terminal deoxynucleotidyl transferase-mediated biotinylated UTP nick end labeling)-positive cells in the SCG of postnatal day 4 traf6-/- animals relative to traf6+/+ littermates. These results indicate that TRAF6 plays an essential role in mediating p75 signal transduction and induction of apoptosis.