Miracle-dz/UniFAR-FTUs huggingface dataset:
Blood volume of gliomas determined by double-echo dynamic perfusion-weighted MR imaging: a preliminary study.

BACKGROUND AND PURPOSE After bolus injection, gadopentetate dimeglumine causes a T2* rate change in permeable tissue that is contaminated by the T1 shortening effect due to the leakage of contrast agent. Therefore, tumor vascularity as reported in previous single-echo perfusion-weighted MR imaging studies has been underestimated. Our aim was to quantitatively and qualitatively evaluate the degree of blood volume of glioblastoma multiformes (GBMs) underestimated by this T1 shortening effect. METHODS We used double-echo dynamic MR imaging after a bolus injection of gadopentetate dimeglumine (double-echo perfusion-weighted MR imaging) to simultaneously determine tumor blood volume without (V(T1U)) and with (V(T1C)) T1 shortening correction. MR imaging was performed in five consecutive patients with GBMs. The ratios of V(T1U) and V(T1C) were calculated and compared by means of quantitative analysis. The degree of tumor blood volume as determined by V(T1U) and V(T1C) maps were qualitatively compared using a three-point scale. RESULTS All GBMs showed contrast enhancement on postcontrast T1-weighted images. In all subjects, the values of V(T1U) were significantly lower than those of V(T1C) (mean +/- SD, 2.05 +/- 1.01 vs. 3.62 +/- 1.40, respectively [P <.05]), indicating that tumor blood volume obtained by double-echo perfusion-weighted MR imaging was significantly higher than that by single-echo imaging. In the qualitative analysis, tumor blood volume on the V(T1U) map was less conspicuous than that on the V(T1C) map. CONCLUSION Careful attention should be paid to the underestimation of tumor blood volume resulting from T1 shortening effects when using single-echo perfusion-weighted MR imaging. Double-echo imaging may be more suitable for the analysis of blood volume in GBMs.
Effective Use of Linguistic and Contextual Information for Statistical Machine Translation

Current methods of using lexical features in machine translation have difficulty in scaling up to realistic MT tasks due to a prohibitively large number of parameters involved. In this paper, we propose methods of using new linguistic and contextual features that do not suffer from this problem and apply them in a state-of-the-art hierarchical MT system. The features used in this work are non-terminal labels, non-terminal length distribution, source string context and source dependency LM scores. The effectiveness of our techniques is demonstrated by significant improvements over a strong base-line. On Arabic-to-English translation, improvements in lower-cased BLEU are 2.0 on NIST MT06 and 1.7 on MT08 newswire data on decoding output. On Chinese-to-English translation, the improvements are 1.0 on MT06 and 0.8 on MT08 newswire data.
Detection of Prohibited Fish Drugs Using Silver Nanowires as Substrate for Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering or surface-enhanced Raman spectroscopy (SERS) is a promising detection technology, and has captured increasing attention. Silver nanowires were synthesized using a rapid polyol method and optimized through adjustment of the molar ratio of poly(vinyl pyrrolidone) and silver nitrate in a glycerol system. Ultraviolet-visible spectrometry, X-ray diffraction, and transmission electron microscopy were used to characterize the silver nanowires. The optimal silver nanowires were used as a SERS substrate to detect prohibited fish drugs, including malachite green, crystal violet, furazolidone, and chloramphenicol. The SERS spectra of crystal violet could be clearly identified at concentrations as low as 0.01 ng/mL. The minimum detectable concentration for malachite green was 0.05 ng/mL, and for both furazolidone and chloramphenicol were 0.1 μg/mL. The results showed that the as-prepared Ag nanowires SERS substrate exhibits high sensitivity and activity.
Invariant content-based image retrieval by wavelet energy signatures

An effective rotation and scale invariant log-polar wavelet texture feature for image retrieval was proposed. The feature extraction process involves a log-polar transform followed by an adaptive row shift invariant wavelet packet transform. The log-polar transform converts a given image into a rotation and scale invariant but row- shifted image, which is then passed to the adaptive row shift invariant wavelet packet transform to generate adaptively some subbands of rotation and scale invariant wavelet coefficients with respect to an information cost function. An energy signature is computed for each subband of these wavelet coefficients. In order to reduce feature dimensionality, only the most dominant log-polar wavelet energy signatures are selected as feature vector for image retrieval. The whole feature extraction process is quite efficient and involves only O (n/spl middot/log n) complexity. Experimental results show that this rotation and scale invariant texture feature is effective and outperforms the traditional wavelet packet signatures.
OBSERVATION OF EXTENDED VERY HIGH ENERGY EMISSION FROM THE SUPERNOVA REMNANT IC 443 WITH VERITAS

We present evidence that the very high energy (VHE, E > 100 GeV) gamma-ray emission coincident with the supernova remnant IC 443 is extended. IC 443 contains one of the best studied sites of supernova remnant/molecular cloud interaction and the pulsar wind nebula CXOU J061705.3+222127, both of which are important targets for VHE observations. VERITAS observed IC 443 for 37.9 hr during 2007 and detected emission above 300 GeV with an excess of 247 events, resulting in a significance of 8.3 standard deviations (σ) before trials and 7. 5σ after trials in a point-source search. The emission is centered at 6h16m51s + 22°30′11″ (J2000) ±0. °03stat ± 0. °08sys, with an intrinsic extension of 0. °16 ± 0. °03stat ± 0. °04sys. The VHE spectrum is well fit by a power law (dN/dE = N0 × (E/TeV)−Γ) with a photon index of 2.99 ± 0.38stat ± 0.3sys and an integral flux above 300 GeV of (4.63 ± 0.90stat ± 0.93sys) × 10−12 cm−2 s−1. These results are discussed in the context of existing models for gamma-ray production in IC 443.
Evaluating Hebbian Self-Organizing Memories for Lexical Representation and Access

The lexicon is the store of words in long-term memory. Any attempt at modelling lexical competence must take issues of string storage seriously. In the present contribution, we discuss a few desiderata that any biologically-inspired computational model of the mental lexicon has to meet, and detail a multi-task evaluation protocol for their assessment. The proposed protocol is applied to a novel computational architecture for lexical storage and acquisition, the """"Topological Temporal Hebbian SOMs"""" (T2HSOMs), which are grids of topologically organised memory nodes with dedicated sensitivity to time-bound sequences of letters. These maps can provide a rigorous and testable conceptual framework within which to provide a comprehensive, multi-task protocol for testing the performance of Hebbian self-organising memories, and a comprehensive picture of the complex dynamics between lexical processing and the acquisition of morphological structure.
Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization

In this paper, the nearest neighbor method on Chinese text categorization is formulated as an optimization problem. The particle swarm optimization is utilized to optimize a nearest neighbor classifier to solve the Chinese text categorization problem. The parameter k was first optimized to obtain the minimum error, then the categorization problem is formulated as a discrete, constrained, and single objective optimization problem. Each dimension of solution vector is dependent on each other in the solution space. The parameter k and the number of labeled examples for each class are optimized together to reach the minimum categorization error. In the experiment, with the utilization of particle swarm optimization, the performance of a nearest neighbor algorithm can be improved, and the algorithm can obtain the minimum categorization error rate.
ScalParC: a new scalable and efficient parallel classification algorithm for mining large datasets

We present ScalParC (Scalable Parallel Classifier), a new parallel formulation of a decision tree based classification process. Like other state-of-the-art decision tree classifiers such as SPRINT, ScalParC is suited for handling large datasets. We show that existing parallel formulation of SPRINT is unscalable, whereas ScalParC is shown to be scalable in both runtime and memory requirements. We present the experimental results of classifying up to 6.4 million records on up to 128 processors of Cray T3D, in order to demonstrate the scalable behavior of ScalParC. A key component of ScalParC is the parallel hash table. The proposed parallel hashing paradigm can be used to parallelize other algorithms that require many concurrent updates to a large hash table.
splice site usage of rat beta-tropomyosin pre-mRNA . Exonic splicing enhancers contribute to the use of both 3 ' and 5 ' Service Email

The rat b-tropomyosin gene encodes two tissue-specific isoforms that contain the internal, mutually exclusive exons 6 (nonmuscle/smooth muscle) and 7 (skeletal muscle). We previously demonstrated that the 39 splice site of exon 6 can be activated by introducing a 9-nt polyuridine tract at its 3 9 splice site, or by strengthening the 5 9 splice site to a U1 consensus binding site, or by joining exon 6 to the downstream common exon 8. Examination of sequences within exons 6 and 8 revealed the presence of two purine-rich motifs in exon 6 and three purine-rich motifs in exon 8 that could potentially represent exonic splicing enhancers (ESEs). In this report we carried out substitution mutagenesis of these elements and show that some of them play a critical role in the splice site usage of exon 6 in vitro and in vivo. Using UV crosslinking, we have identified SF2/ASF as one of the cellular factors that binds to these motifs. Furthermore, we show that substrates that have mutated ESEs are blocked prior to A-complex formation, supporting a role for SF2/ASF binding to the ESEs during the commitment step in splicing. Using pre-mRNA substrates containing exons 5 through 8, we show that the ESEs within exon 6 also play a role in cooperation between the 39 and 59 splice sites flanking this exon. The splicing of exon 6 to 8 (i.e., 5 9 splice site usage of exon 6) was enhanced with pre-mRNAs containing either the polyuridine tract in the 3 9 splice site or consensus sequence in the 59 splice site around exon 6. We show that the ESEs in exon 6 are required for this effect. However, the ESEs are not required when both the polyuridine and consensus splice site sequences around exon 6 were present in the same pre-mRNA. These results support and extend the exon-definition hypothesis and demonstrate that sequences at the 39 splice site can facilitate use of a downstream 5 9 splice site. In addition, the data support the hypothesis that ESEs can compensate for weak splice sites, such as those found in alternatively spliced exons, thereby providing a target for regulation.
HST and Spitzer Observations of the Host Galaxy of GRB 050904: A Metal-Enriched, Dusty Starburst at z=6.295

, ABSTRACT We present deep Hubble Space Telescope and Spitzer Space Telescope observations of the host galaxy of GRB 050904 at z = 6 . 295. The host is detected in the H -band and marginally at 3 . 6 µ m. From these detections, and limits in the z ′ -band and 4.5 µ m, we infer an extinction-corrected absolute magnitude, M UV ≈ − 20 . 7 mag, or ∼ L *, a substantial star formation rate of ∼ 15 M ⊙ yr − 1 , and a stellar mass of few × 10 9 M ⊙ . A comparison to the published sample of spectroscopically-conﬁrmed galaxies at z > 5 . 5 reveals that the host of GRB 050904 would evade detection and/or conﬁrmation in any of the current surveys due to the lack of detectable Ly α emission, which is likely the result of dust extinction ( A 1200 ∼ 1 . 5 mag). This suggests that not all luminous starburst galaxies at z ∼ 6 are currently being accounted for. Most importantly, using the metallicity of Z ≈ 0 . 05 Z ⊙ inferred from the afterglow absorption spectrum, our observations indicate for the ﬁrst time that the observed evolution in the mass- and luminosity-metallicity relations from z = 0 to z ∼ 2 continues on to z > 6. The ease of measuring redshifts and metallicities from the afterglow emission suggests that in tandem with the next generation ground- and space-based telescopes, a GRB mission with dedicated near-IR follow-up can provide unique information on the evolution of stars and galaxies through the epoch of re-ionization.
Fast automatic liver segmentation combining learned shape priors with observed shape deviation

We present a novel statistical shape model approach for fully automatic CT liver segmentation. Unlike previous techniques, our method combines learned local shape priors with constraints that are directly derived from the current curvature of the model in order to restrict adaptation to regions where large deformations are expected and observed. Our approach is based on a multi-tiered framework that is more robust against model initialization errors than existing methods, because the model's degrees of freedom are step-wise increased. We evaluated our method on a large data base of 86 CT liver scans from different vendors, protocols, varying resolution and contrast enhancement. For comparison, 50 of the scans were taken from 2 public data bases, one of it being the MICCAI'07 liver segmentation challenge data base. Evaluation shows state of the art results with an average mean surface distance between 1.3 mm and 1.85 mm compared to ground truth depending on the image resolution. With an average segmentation time of 45 seconds our approach outperforms other automatic methods.
SBUEI: results for OAEI 2012

In this paper, we describe our system, SBUEI, for instances coreference resolution between various sources even with heterogeneous schemas. It is the first participation of SBUEI in instance matching track of Ontology Alignment Evaluation Initiative campaign. We present the results of SBUEI in the 2012 OAEI competition in two tracks: Sandbox and IIMB. SBUEI considers the instance coreference resolution in both schema and instance levels. The process of matching is applied to both levels consecutively to let the system discover identical instances.
Human Efficiency for Recognizing 3-D Objects Luminance N oise

The purpose of this study was to establish how efficiently humans use visual information to recognize simple 3-D objects. The stimuli were computer-rendered images of four simple 3-D objects-wedge, cone, cylinder, and pyramid~each rendered from 8 randomly chosen viewing positions as shaded objects, line drawings, or silhouettes. The objects were presented in static, 2-D Gaussian luminance noise. The observer's task was to indicate which of the four objects had been presented. We obtained human contrast thresholds for recognition, and compared these to an ideal observer's thresholds to obtain efficiencies. In two auxiliary experiments, we measured efficiencies for object detection and letter recognition. Our results showed that human object-recognition efficiency is low (3-8%) when compared to efficiencies reported for some other visual-information processing tasks. The low efficiency means that human recognition performance is limited primarily by factors intrinsic to the observer rather than the information content of the stimuli. We found three factors that play a large role in accounting for low object-recognition efficiency: stimulus size, spatial uncertainty, and detection efficiency. Four other factors play a smaller role in limiting object-recognition efficiency: observers' internal noise, stimulus rendering condition, stimulus familiarity, and categorization across views.
Human Computation Must Be Reproducible

Human computation is the technique of performing a computational process by outsourcing some of the difficult-toautomate steps to humans. In the social and behavioral sciences, when using humans as measuring instruments, reproducibility guides the design and evaluation of experiments. We argue that human computation has similar properties, and that the results of human computation must be reproducible, in the least, in order to be informative. We might additionally require the results of human computation to have high validity or high utility, but the results must be reproducible in order to measure the validity or utility to a degree better than chance. Additionally, a focus on reproducibility has implications for design of task and instructions, as well as for the communication of the results. It is humbling how often the initial understanding of the task and guidelines turns out to lack reproducibility. We suggest ensuring, measuring and communicating reproducibility of human computation tasks.
Structural equations and divisive normalization for energy-dependent component analysis

Components estimated by independent component analysis and related methods are typically not independent in real data. A very common form of nonlinear dependency between the components is correlations in their variances or energies. Here, we propose a principled probabilistic model to model the energy-correlations between the latent variables. Our two-stage model includes a linear mixing of latent signals into the observed ones like in ICA. The main new feature is a model of the energy-correlations based on the structural equation model (SEM), in particular, a Linear Non-Gaussian SEM. The SEM is closely related to divisive normalization which effectively reduces energy correlation. Our new two-stage model enables estimation of both the linear mixing and the interactions related to energy-correlations, without resorting to approximations of the likelihood function or other non-principled approaches. We demonstrate the applicability of our method with synthetic dataset, natural images and brain signals.
Design of a Compact Cylindrical Loudspeaker Array for Spatial Sound Reproduction

Building acoustic beamformers is a problem whose solution is hindered by the wide-band nature of audible sound. In order to achieve a consistent directional response over a wide range of frequencies, a conventional acoustic beamformer needs a high number of discrete loudspeakers and be large enough to achieve a desired low-frequency performance. The acoustic beamformer design described in this paper uses measurement-based optimized beamforming for loudspeakers mounted on a rigid cylindrical baffle. Super-directional beamforming enables achieving desired directivity with multiple loudspeakers at low frequencies. High frequencies are reproduced with a single loudspeaker, whose highly directional reproduction---due to the cylindrical baffle---matches the design goals. In addition to the beamformer filter design procedure, it is shown how such loudspeaker array can be used for spatial sound reproduction.
Ontology based framework for news extraction in visual media

Anticipating the increase in video information in future, archiving of news is an important activity in the visual media industry. When the volume of archives increases, it will be difficult for journalists to find the appropriate content using current search tools. This paper provides the details of the study we conducted about the news extraction systems used in different news channels in Kerala. Semantic web technologies can be used effectively since news archiving share many of the characteristics and problems of WWW. Since visual news archives of different media resources follow different metadata standards, interoperability between the resources is also an issue. World Wide Web Consortium has proposed a draft for an ontology framework for media resource which addresses the intercompatiblity issues. In this paper, the w3c proposed framework and its drawbacks is also discussed.
Online Learning of a Dirichlet Process Mixture of Generalized Dirichlet Distributions for Simultaneous Clustering and Localized Feature Selection

Online algorithms allow data instances to be processed in a sequential way, which is important for large-scale and real-time applications. In this paper, we propose a novel online clustering approach based on a Dirichlet process mixture of generalized Dirichlet (GD) distributions, which can be considered as an extension of the nite GD mixture model to the innite case. Our approach is built on nonparametric Bayesian analysis where the determination of the number of clusters is sidestepped by assuming an innite number of mixture components. Moreover, an unsupervised localized feature selection scheme is integrated with the proposed nonparametric framework to improve the clustering performance. By learning the proposed model in an online manner using a variational approach, all the involved parameters and features saliencies are estimated simultaneously and effectively in closed forms. The proposed online innite mixture model is validated through both synthetic data sets and two challenging real-world applications namely text document clustering and online human face detection.
Understanding process for speech recognition

The automatic speech understanding problem could be considered as an association problem between two different languages. At the entry, the request expressed in natural language and at the end, just before the interpretation stage, the same request is expressed in term of concepts. A concept represents a given meaning, it is defined by a set of words sharing the same semantic properties. In this paper, we propose a new Bayesian network based method to automatically extract the underlined concepts. We also propose a new approach for the vector representation of words. We finish this paper by a description of the postprocessing step during which, we label our sentences and we generate the corresponding SQL queries. This step allows us to validate our speech understanding approach by obtaining good results. In fact, a rate of 92.5% of well formed SQL requests has been achieved on the test corpus.
StoryCrate: tabletop storyboarding for live film production

Creating film content for broadcast is a high pressure and complex activity involving multiple experts and highly specialized equipment. Production teams are under continuous pressure to produce ever more creative and groundbreaking content while reducing the budgets and human resources required. While technologies are being developed for digitizing and streamlining sections of the production workflow, a gap remains between creative decisions made on location, and those made during digital editing and post-production. We describe a prototype tangible, tabletop interface to be deployed on a film shoot, which uses a storyboard as a shared data representation to drive team creativity. We define creativity in terms of team production, discuss our implementation and describe a deployment in which the prototype was used by a professional production team during a film shoot. Finally we describe a number of interesting interactions that were observed and consider the implications of our design decisions on the creative process of film making and the benefits of tangible, tabletop collaborative interactive displays in live film production.