Miracle-dz/UniFAR-FTUs huggingface dataset:
Harmonium Models for Video Classification

Accurate and efficient video classification demands the fusion of multimodal information and the use of intermediate representations. Combining the two ideas into one framework, we propose a series of probabilistic models for video representation and classification using intermediate semantic representations derived from multimodal features of video. On the basis of a class of bipartite undirected graphical models named harmonium, we propose dual‐wing harmonium (DWH) model that represents video shots as latent semantic topics derived by jointly modeling the transcript keywords and color‐histogram features of the data. Our family‐of‐harmonium (FoH) and hierarchical harmonium (HH) model extends DWH by introducing variables representing category labels of data, which allows data representation and classification to be performed in the same model. Our models are among the few attempts of using undirected graphical models for representing and classifying video data. Experiments on a benchmark video collection show different semantic interpretations of video data under our models, as well as superior classification performance in comparison with several directed models. Copyright © 2008 Wiley Periodicals, Inc., A Wiley Company Statistical Analy Data Mining 1: 000‐000, 2008
Analyzing web text association to disambiguate abbreviation in queries

We introduce a statistical model for abbreviation disambiguation in Web search, based on analysis of Web data resources, including anchor text, click log and query log. By combining evidence from multiple sources, we are able to accurately disambiguate the abbreviation in queries. Experiments on real Web search queries show promising results.
OLego: fast and sensitive mapping of spliced mRNA-Seq reads using small seeds

A crucial step in analyzing mRNA-Seq data is to accurately and efficiently map hundreds of millions of reads to the reference genome and exon junctions. Here we present OLego, an algorithm specifically designed for de novo mapping of spliced mRNA-Seq reads. OLego adopts a multiple-seed-and-extend scheme, and does not rely on a separate external aligner. It achieves high sensitivity of junction detection by strategic searches with small seeds (∼14 nt for mammalian genomes). To improve accuracy and resolve ambiguous mapping at junctions, OLego uses a built-in statistical model to score exon junctions by splice-site strength and intron size. Burrows–Wheeler transform is used in multiple steps of the algorithm to efficiently map seeds, locate junctions and identify small exons. OLego is implemented in C++ with fully multithreaded execution, and allows fast processing of large-scale data. We systematically evaluated the performance of OLego in comparison with published tools using both simulated and real data. OLego demonstrated better sensitivity, higher or comparable accuracy and substantially improved speed. OLego also identified hundreds of novel micro-exons (<30 nt) in the mouse transcriptome, many of which are phylogenetically conserved and can be validated experimentally in vivo. OLego is freely available at http://zhanglab.c2b2. columbia.edu/index.php/OLego.
SDSS J090334.92+502819.2: A New Gravitational Lens

We report the discovery of a new gravitationally lensed quasar from the Sloan Digital Sky Survey, SDSS J090334.92+502819.2. This object was targeted for SDSS spectroscopy as a luminous red galaxy, but manual examination of the spectrum showed the presence of a quasar at z ≃ 3.6 in addition to a red galaxy at z = 0.388, and the SDSS image showed a second possible quasar image nearby. Follow-up imaging and spectroscopy confirmed the lensing hypothesis. In images taken at the Astrophysical Research Consortium 3.5 m telescope, two quasars are separated by 2. ″8; the lensing galaxy is clearly seen and is blended with one of the quasar images. Spectroscopy taken at the Keck II telescope shows that the quasars have identical redshifts of z ≃ 3.6, and both show the presence of the same broad absorption line–like troughs. We present simple lens models that account for the geometry and magnifications. The lens galaxy lies near two groups of galaxies and may be a part of them. The models suggest that the groups may contribute considerable shear that has a strong effect on the lens configuration.
Accelerating adaptive directional lifting based wavelet decomposition on GPU using CUDA

Because of high data dependency between ADL (adaptive directional lifting) steps, such as interpolation, directional prediction and update, the existing CUDA (Compute Unified Device Architecture) configuration method for traditional rectilinear transform is difficult to be used for ADL-based transform. This paper proposed a new configuration method so-called Slice for implementation of the ADL-based transforms on GPUs (Graphics Processing Units). Compared with the existing configuration for the conventional rectilinear lifting algorithm, the proposed method makes each step being handled by a different kernel both for horizontal and vertical passes to avoid unnecessary waiting time between threads. Meanwhile the interpolation and decomposition are executed in an interleaving manner on the pixel level. Moreover, the coalesced memory accesses are exploited to the greatest extent by reading and writing a slice of image data from or back to global memory. The results show that the Slice method overcomes the limitation of high data dependency between ADL steps, and achieves more than 10 times speedup compared to the optimized CPU implementation.
From Axial to Road-Centre Lines: A New Representation for Space Syntax and a New Model of Route Choice for Transport Network Analysis

Axial analysis is one of the fundamental components of space syntax. The space syntax community has suggested that it picks up qualities of configurational relationships between spaces not illuminated by other representations. However, critics have questioned the absolute necessity of axial lines to space syntax, as well as the exact definition of axial lines. Why not another representation? In particular, why not road-centre lines, which are easily available in many countries for use within geographical information systems? Here I propose that a recently introduced method of analysis, angular segment analysis, can marry axial and road-centre line representations, and in doing so reflect a cognitive model of how route choice decisions may be made. I show that angular segment analysis can be applied generally to road-centre line segments or axial segments, through a simple length-weighted normalisation procedure that makes values between the two maps comparable. I make comparative quantitative assessments for a real urban system, not just investigating angular analysis between axial and road-centre line networks, but also including more intuitive measures based on metric (or block) distances between locations. I show that the new angular segment analysis algorithm produces better correlation with observed vehicular flow than both standard axial analysis and metric distance measures. The results imply that there is no reason why space syntax inspired measures cannot be combined with transportation network analysis representations in order to create a new, cognitively coherent, model of movement in the city.
Fiber attenuation irregularities and simulation of Raman amplification band

Analytical expression of wavelength dependence of signal attenuation coefficient in the range of S+L+C telecommunication window is obtained using polynomial approximation in single-mode silica fibers: DCF, TrueWaveRSTM and pure SMF. It allowed correcting the threshold conditions of Raman amplification. It is shown that Raman gain threshold increased adjusted for wavelength irregularity of attenuation in comparison with threshold at constant attenuation of optical wave. It led to significant narrowing of Raman amplification band by-turn, especially up to a few THz in DCF. Presented technique of simulation of Raman amplification band is useful for designing of wideband fiber Raman amplifiers.
Ratchet Effects in Active Matter Systems

Ratchet effects can arise for single or collectively interacting Brownian particles on an asymmetric substrate when a net dc transport is produced by an externally applied ac driving force or by periodically flashing the substrate. Recently, a new class of active ratchet systems has been realized through the use of active matter, which are self-propelled units that can be biological or non-biological in nature. When active materials such as swimming bacteria interact with an asymmetric substrate, a net dc directed motion can arise even without external driving, opening a wealth of possibilities such as sorting, cargo transport, or micromachine construction. We review the current status of active matter ratchets for swimming bacteria, cells, active colloids, and swarming models, focusing on the role of particle-substrate interactions. We describe ratchet reversals produced by collective effects and the use of active ratchets to transport passive particles. We discuss future directions including deformable substrates or particles, the role of different swimming modes, varied particle-particle interactions, and non-dissipative effects.
A WBC segmentation methord based on HSI color space

Fast and accurate segmentation for color images are important and difficult in computer vision and image analysis. To improve the quality of image recognition, take into account pixel color information and adjacency relationship between pixels based on spatial information, integrate color histogram-based method and region growing and merging-based segmentation method, proposed a new algorithm for color image segmentation. First, select an appropriate color space; followed by saturation threshold segmentation to extract nucleus from white blood cell; after that, according to certain rules, using region growing of color information to extract the cytoplasm; Finally, do region merging. Compared to similar methods, the segmentation results show that this method is faster and more accurate.
An Empirical Evaluation of the Utility of Convex Hull and Standard Ellipse Areas for Assessing Population Niche Widths from Stable Isotope Data

Stable isotope analyses are increasingly employed to characterise population niche widths. The convex hull area (TA) in a δ13C–δ15N biplot has been used as a measure of isotopic niche width, but concerns exist over its dependence on sample size and associated difficulties in among-population comparisons. Recently a more robust method was proposed for estimating and comparing isotopic niche widths using standard ellipse areas (SEA), but this approach has yet to be tested with empirical stable isotope data. The two methods measure different kind of isotopic niche areas, but both are now widely used to characterise isotopic niche widths of populations. We used simulated data and an extensive empirical dataset from two fish populations to test the influence of sample size on the observed isotopic niche widths (TA and SEA). We resampled the original datasets to generate 5000 new samples for different numbers of observations from 5 to 80 to examine the statistical distributions of niche area estimates for increasing sample size. Our results illustrate how increasing sample size increased the observed TA; even sample sizes much higher than n = 30 did not improve the precision for the TA method. SEA was less sensitive to sample size, but the natural variation in our empirical fish δ13C and δ15N data still resulted in considerable uncertainty around the mean estimates of niche width, reducing the precision particularly with sample sizes n<30. These results confirm that the TA method is less appropriate for estimating population isotopic niche areas using small samples, especially when considerable population level isotope variation is expected. The results also indicate a need for caution when using SEA as a measure of trophic niche widths for consumers, particularly with low sample sizes and when the distribution and range for population isotope values are not known.
Constant Round Maliciously Secure 2PC with Function-independent Preprocessing using LEGO

Secure two-party computation (S2PC) allows two parties to compute a function on their joint inputs while leaking only the output of the function. At TCC 2009 Orlandi and Nielsen proposed the LEGO protocol for maliciously secure 2PC based on cut-and-choose of Yao’s garbled circuits at the gate level and showed that this is asymptotically more efficient than on the circuit level. Since then the LEGO approach has been improved upon in several theoretical works, but never implemented. In this paper we describe further concrete improvements and provide the first implementation of a protocol from the LEGO family. Our protocol has a constant number of rounds and is optimized for the offline/online setting with function-independent preprocessing. We have benchmarked our prototype and find that our protocol can compete with all existing implementations and that it is often more efficient. As an example, in a LAN setting we can evaluate an AES-128 circuit with online latency down to 1.13ms, while if evaluating 128 AES-128 circuits in parallel the amortized cost is 0.09ms per AES-128. This online performance does not come at the price of offline inefficiency as we achieve comparable performance to previous, less general protocols, and significantly better if we ignore the cost of the function-independent preprocessing. Also, as our protocol has an optimal 2-round online phase it is significantly more efficient than previous protocols when considering a high latency network. Keywords—Secure Two-party Computation, Implementation, LEGO, XOR-Homomorphic Commitments, Selective OT-Attack
Continuous Gait Velocity Estimation using Houseohld Motion Detectors

Gait velocity has been consistently shown to be an important indicator and predictor of health status, especially in older adults. Gait velocity is often assessed clinically, but the assessments occur infrequently and thus do not allow optimal detection of key health changes when they occur. In this paper, we show the time it takes a person to move between rooms in their home denoted 'transition times' can predict gait velocity when estimated from passive infrared motion detectors installed in a patient's own home. Using a support vector regression approach to model the relationship between transition times and gait velocities, we show that velocity can be predicted with an average error less than 2.5 cm/sec. This is demonstrated with data collected over a 5 year period from 74 older adults monitored in their own homes. This method is simple and cost effective, and has advantages over competing approaches such as: obtaining 20 to100x more gait velocity measurements per day, and offering the fusion of location specific information with time stamped gait estimates. These advantages allow stable estimates of gait parameters (maximum or average speed, variability) at shorter time scales than current approaches. This also provides a pervasive in home method for context aware gait velocity sensing that allows for monitoring of gait trajectories in space and time.
Discrete Sibson interpolation

Natural-neighbor interpolation methods, such as Sibson's method, are well-known schemes for multivariate data fitting and reconstruction. Despite its many desirable properties, Sibson's method is computationally expensive and difficult to implement, especially when applied to higher-dimensional data. The main reason for both problems is the method's implementation based on a Voronoi diagram of all data points. We describe a discrete approach to evaluating Sibson's interpolant on a regular grid, based solely on finding nearest neighbors and rendering and blending d-dimensional spheres. Our approach does not require us to construct an explicit Voronoi diagram, is easily implemented using commodity three-dimensional graphics hardware, leads to a significant speed increase compared to traditional approaches, and generalizes easily to higher dimensions. For large scattered data sets, we achieve two-dimensional (2D) interpolation at interactive rates and 3D interpolation (3D) with computation times of a few seconds.
Bounded Conditional Mean Imputation with Observation Uncertainties and Acoustic Model Adaptation

Automatic speech recognition systems use noise compensation and acoustic model adaptation to increase robustness towards speaker and environmental variation. The current work focuses on noise compensation with bounded conditional mean imputation (BCMI). BCMI approaches are missing-data methods which operate on the assumption that noise-corrupted observations can be divided into reliable and unreliable components. BCMI methods substitute the unreliable components with a clean speech posterior distribution. The posterior means can be used as clean speech estimates and the posterior variances can be introduced in acoustic model likelihood calculation as observation uncertainties. In addition, we propose in the current work that similar uncertainties are introduced in acoustic model adaptation. Evaluation with speech data recorded in diverse public and car environments indicates that the proposed uncertainties improve adaptation performance. When uncertainties were used in acoustic model likelihood calculation and adaptation, the proposed imputation and adaptation system introduced 15%-84% relative error reductions to an uncompensated baseline system performance.
Analysis of 4-aminobiphenyl-DNA adducts in human urinary bladder and lung by alkaline hydrolysis and negative ion gas chromatography-mass spectrometry.

Analysis of carcinogen-DNA adducts has been regarded as a useful means of assessing human exposure to chemical carcinogens. We have established a method for quantitation of 4-aminobiphenyl (4-ABP)-DNA adducts by alkaline hydrolysis and gas chromatography with negative ion chemical ionization mass spectrometry (GC-NICI-MS). Aliquots of DNA (typically 100 micrograms/ml) were spiked with an internal standard, d9-4-ABP, and were hydrolyzed in 0.05 N NaOH at 130 degrees C overnight. The liberated 4-ABP was extracted with hexane and derivatized using pentafluoropropionic anhydride in trimethylamine for 30 min at room temperature prior to GC-NICI-MS. With in vitro [3H]N-hydroxy-4-ABP modified DNA standards, we observed 59 +/- 7% (n = 9) recovery of the 4-ABP and a linear correlation between hydrolyzed 4-ABP and the adduct levels ranging from about 1 in 10(8) to 1 in 10(4) nucleotides (r = 0.999, n = 9). The method was further validated by comparison of the results with that obtained by the 32P-postlabeling method. There was excellent agreement (r = 0.994, p < 0.001) between the two methods for quantitation of the adduct in eight samples of Salmonella typhimurium DNA treated with 4-ABP and rat liver S9, although the 32P-postlabeling method gave slightly higher values. The DNA adducts in 11 human lung and 8 urinary bladder mucosa specimens were then determined by our GC-NICI-MS method. The adduct levels were found to be < 0.32 to 49.5 adducts per 10(8) nucleotides in the lungs and < 0.32 to 3.94 adducts per 10(8) nucleotides in the bladder samples. (ABSTRACT TRUNCATED AT 250 WORDS) ImagesFigure 4. AFigure 4. B
Morphing Software for Easier Evolution

One of the biggest challenges in software evolution is maintaining the relationships between existing program structures. Changing a program component (e.g., a class, interface, or method) typically requires changes in multiple other components whose structure or meaning depend on the changed one. The root cause of the problem is redundancy due to lack of expressiveness in programming languages: Extra dependencies exist only because there is no easy way to model one program component after another, so that changes to the latter are automatically reflected in the former. For example, in the Enterprise Java Bean (EJB) standard, local and remote stub interfaces must mirror the bean class structure exactly. A change in the bean interface must be propagated to the stub interfaces, as well. Tools and methods have been developed to support writing code that is immune to changes in program structure (e.g., [10, 11]). But these tools either require separate declarations of a program’s structural properties (e.g., class dictionaries in [11]), or use potentially unsafe runtime reflection [10]. Furthermore, these tools focus on adapting code, and not the static structure of a class or interface, to evolving program structure. Another obstacle in software evolution is the extensibility of software components, particularly when source code is unavailable. Aspect Oriented Programming (AOP) [9] and its flagship tools, such as AspectJ [8] provide a solution approach. AspectJ allows a programmer to extend a software component by specifying extra code to be executed, or even change the component’s original semantics entirely by circumventing the execution of original code, and provide new code to execute in its place. AspectJ is a powerful tool, but often has to sacrifice either discipline or expressiveness. For example, AspectJ aspects are strongly tied to the components they apply to—there is no notion of typechecking an aspect separately from the application where it is used. This means that generic AspectJ aspects (i.e., aspects that are specified so that they can be later applied to multiple, but yet unknown, components) are limited in what they can express. For example, AspectJ cannot express intercepting all calls to the methods of one class, and forwarding them to methods of another class, using the intercepted arguments: the aspect to do so needs to be custom-written