Miracle-dz/UniFAR-FTUs huggingface dataset:
University of Waterloo Department of Statistics and Actuarial Science Computationally Efficient Bootstrap Prediction Intervals for Returns and Volatilities in Arch and Garch Processes

We propose a novel, simple, efficient and distribution-free re-sampling technique for developing prediction intervals for returns and volatilities following ARCH/GARCH models. In particular, our key idea is to employ a Box-Jenkins linear representation of an ARCH/GARCH equation and then to adapt a sieve bootstrap procedure to the non-linear GARCH framework. Our simulation studies indicate that the new re-sampling method provide sharp and well calibrated prediction intervals for both returns and volatilities while reducing computational costs up to 100 times, compared to other available re-sampling techniques for ARCH/GARCH models. The proposed procedure is illustrated by application to Yen/U.S dollar daily exchange rate data.
A framework for visual saliency detection with applications to image thumbnailing

We propose a novel framework for visual saliency detection based on a simple principle: images sharing their global visual appearances are likely to share similar salience. Assuming that an annotated image database is available, we first retrieve the most similar images to the target image; secondly, we build a simple classifier and we use it to generate saliency maps. Finally, we refine the maps and we extract thumbnails. We show that in spite of its simplicity, our framework outperforms state-of-the art approaches. Another advantage is its ability to deal with visual pop-up and application/task-driven saliency, if appropriately annotated images are available.
Energy Consumption Estimation in Hybrid Sensor Networks Running Assisted Navigation Algorithms

Hybrid sensor networks (HSNs), made up of many static sensors interacting with a limited number of mobile robotic sensors, can support a variety of applications in which assisted navigation, implemented for mobile robotic sensors, performs requested operations in hostile environments, where the human presence is impracticable. On the other hand, the limited on-board battery energy of the sensor nodes imposes hard constraints to the wireless communication and computing capabilities of such nodes, thus limiting the capacity of a HSN to run an application for a period of interest without human intervention. These considerations have motivated this paper, which describes a method to estimate the energy consumption under changeable working conditions in a HSN running an assisted navigation algorithm based on the "credit field" concept.
Clustering sequence sets for motif discovery

Most of existing methods for DNA motif discovery consider only a single set of sequences to find an over-represented motif. In contrast, we consider multiple sets of sequences where we group sets associated with the same motif into a cluster, assuming that each set involves a single motif. Clustering sets of sequences yields clusters of coherent motifs, improving signal-to-noise ratio or enabling us to identify multiple motifs. We present a probabilistic model for DNA motif discovery where we identify multiple motifs through searching for patterns which are shared across multiple sets of sequences. Our model infers cluster-indicating latent variables and learns motifs simultaneously, where these two tasks interact with each other. We show that our model can handle various motif discovery problems, depending on how to construct multiple sets of sequences. Experiments on three different problems for discovering DNA motifs emphasize the useful behavior and confirm the substantial gains over existing methods where only a single set of sequences is considered.
Evolved multi-resolution transforms for optimized image compression and reconstruction under quantization

State-of-the-art image compression and reconstruction techniques utilize wavelets. Recently published research demonstrated that a genetic algorithm (GA) is capable of evolving non-wavelet transforms that consistently outperform wavelets when applied to a broad class of images under conditions subject to quantization error. This paper describes new results that build upon previous research by demonstrating that a GA can evolve a single set of coefficients describing a matched forward and inverse transform pair that can be used at each level of a multi-resolution analysis (MRA) transform to simultaneously minimize the compressed file size (FS) and the squared error (SE) in the reconstructed file. Test results indicate that the benefits of using evolved transforms instead of wavelets increases in proportion to quantization level. Furthermore, coefficients evolved against a single representative training image generalize to effectively reduce SE for a broad class of reconstructed images.
Assessment of sequential Boltmann machines on a lexical processing task

The Recurrent Temporal Restricted Boltzmann Machine is a promising probabilistic model for processing temporal data. It has been shown to learn physical dynamics from videos (e.g. bouncing balls), but its ability to process sequential data has not been tested on symbolic tasks. Here we assess its capabilities on learning sequences of letters correspond- ing to English words. It emerged that the model is able to extract local transition rules between items of a sequence (i.e. English graphotactic rules), but it does not seem to be suited to encode a whole word.
Synthesis, alkylating activity and physicochemical study of nitrogen mustard agent for brain delivery

On the structural pattern of nikethamide which is a potent central nervous system (CNS) stimulant, it was designed to link N,N-bis(2-chloroethyl)amino moiety as alkylating agent to nicotinic acid by an amide bond in the hope to obtain a CNS antitumor agent (Nicotinic-mustard). The Nicotinic-mustard agent was solid at room temperature and stable for more than one week when stored at less than 0 o C. The in vitro chemical alkylation activity (NBP) of Nicotinic-mustard was comparable to that of N,N-bis(2-chloroethyl)amine as standard alkylating agent. The log P value of Nicotinic-mustard was analyzed (miLogP and MlogP) and found to be increased lipophilicity for the Nicotinic-mustard construct compared with the parent compound nicotinic acid. Value of polar surface area for the Nicotinic-mustard agent (33 A 2 ) predicts that >90% of any amount present in the intestinal tract will be absorbed. The physicochemical potential of this compound to penetrate the BBB such as Log BB, Polar surface area, rule of five, number of NH or OH hydrogen bond donors and no value was computed through online software program and the values obtained for the Nicotinic-mustard suggest a good brain penetration.
Pitch Marking Using the Fundamental Signal for Speech Modifications via TDPSOLA

The quality of synthetic speech offered by pitch and duration modifications via Time Domain Pitch Synchronous Overlap Add method (TD-PSOLA) relies on an accurate positioning of pitch marks. In this paper, we propose a new pitch marking technique of voiced regions based on the fundamental signal of the speech waveform. By using the valleys of the fundamental signal, we locate a set of precise intervals where the exact instants of pitch marks are expected to be found. The fundamental signal is composed only from the fundamental frequency (pitch) of speech. It is represented by a specific signal named "mean based signal" (MBS). The optimal pitch marks are found by extracting the set of global peak instants within the obtained intervals. To improve the performance of the proposed technique, we have proposed a post processing stage which allows us to correct the erroneous pitch marks that may occur due to some synchronization problems. The proposed technique is evaluated on CMU ACRTIC database by using objective and subjective measures. The experiments demonstrate that the proposed technique allows pitch and duration modifications via TD-PSOLA with high quality.
Effectiveness beyond the first crawl tier

Modern Web crawlers seek to visit quality documents first, and re-visit them more frequently than other documents. As a result, the first-tier crawl of a Web corpus is typically of higher quality compared to subsequent crawls. In this paper, we investigate the impact of first-tier documents on adhoc retrieval performance. In particular, we analyse the retrieval performance of runs submitted to the adhoc task of the TREC 2009 Web track in terms of how they rank first-tier documents and how these documents contribute to the performance of each run. Our results show that the performance of these runs is heavily dependent on their ability to rank first-tier documents. Moreover, we show that, different from leading Web search engines, their attempt to go beyond the first tier almost always results in decreased performance. Finally, we show that selectively removing spam from different tiers can be a direction for fully exploiting documents beyond the first tier.
A Data-Driven Light Scattering Model for Hair

We present an implementation of the [Marschner et al. 2003] model for importance sampling light reflected from hair. The implementation makes use of a version of Adaptive Importance Sampling (AIS), specialized to fit easily sampled distributions to BCSDFs. Our model is novel among importance sampling implementations in that it includes all the features of Marschner such as eccentricity for elliptical cross-sections, and extends them by adding azimuthal roughness control, and natural fiber torsion. It is also fully energy preserving. We compare with the implementations in both [d’Eon et al. 2013] and [Ou et al. 2012] as well as a ground truth, physical model which directly evaluates light-cylinder interactions. Our model well approximates the ground truth, and is significantly faster than other implementations.
Analysis of mRNA Expression by Real-time PCR

The last few years have witnessed the transformation of the real-time, fluorescence-based reverse transcription polymerase chain reaction (RT-qPCR) from an experimental technology into a mainstream scientific tool for the detection and quantification of RNA with an enormous range of uses in basic research, molecular medicine and biotechnology. The continuous improvement of reagents and instruments, combined with the trend towards high throughput and miniaturisation, is likely to reinforce that pre-eminence and continue to open up new application areas. Nonetheless, although in principle undoubtedly a straightforward technology, the reliability of RT-qPCR assays depends a series of sequential steps that include careful experimental design, optimisation and validation, which must be implemented pragmatically to obtain meaningful, biologically relevant data.
Use of amoxicillin in the treatment of patients with septic abortion.

Amoxicillin (a-amino-p-hydroxybenzylpenicillin), a new semisynthetic antibiotic with chemical and antimicrobial activity similar to that of ampicillin, was used in the treatment of 30 patients with septic abortion. An oral dose of 500 mg was administered every 8 hr after removal of the contents of the uterus by suction. The average duration of therapy was six days, with an average dose of 27.8 mg/ kg per day. There were 28 cures and two failures. There were no significant adverse effects directly attributable to amoxicillin, with the exception of one extensive erythematous and maculopapular cutaneous reaction. Amoxicillin (a-amino-p-hydroxybenzylpenicillin) has a chemical structure very similar to that of ampicillin, and it has essentially the same spectrum of antibacterial action in vitro [1]. Administered orally, amoxicillin is absorbed more rapidly, and the serum levels are twice those obtained with equal doses of ampicillin [2].
Histopathologic characterization of lung adenocarcinoma in relation to fluorine-18-fluorodeoxyglucose uptake on positron emission tomography.

BACKGROUND Fluorine-18-fluorodeoxyglucose uptake on positron emission tomography is reported to have prognostic significance in patients after resection of lung adenocarcinoma. However, its relationship with histopathologic features remains unknown. METHODS We conducted a retrospective analysis of 205 patients who had undergone surgical resection of primary lung adenocarcinoma (> 1.0 cm) after preoperative fluorine-18-fluorodeoxyglucose-positron emission tomography between January 1999 and December 2008 at Hokkaido University Hospital. Fluorine-18-fluorodeoxyglucose uptake was measured by the maximum standardized uptake value. A histopathologic review was performed according to the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, and various histopathologic factors were evaluated semi-quantitatively. Correlations between these clinicopathologic factors and the maximum standardized uptake value (high ≥ 2.0 vs low < 2.0) were analyzed. RESULTS Univariate analysis of clinicopathologic factors demonstrated that the following were significantly correlated with a high maximum standardized uptake value: an elevated carcinoembryonic antigen level, larger tumor size, upgraded pT, pN, pStage, non-lepidic histology, abundant fibroblastic/hyalinized stroma, necrosis, presence of pleural involvement, lymphatic and vascular invasion and more intra- and extracellular mucin. Multivariate analysis demonstrated that a tumor size of > 2.0 cm, non-lepidic histology and abundant fibroblastic/hyalinized stroma were significantly correlated with the high maximum standardized uptake value. CONCLUSION More histopathologic factors are known to correlate with poor prognosis in lung adenocarcinomas showing high maximum standardized uptake values than in those showing low maximum standardized uptake values. Therefore, prognostication of patients with a resectable lung adenocarcinoma on the basis of preoperative fluorine-18-fluorodeoxyglucose uptake is histopathologically valid. Such observations may also help us to clarify the pathobiological mechanism responsible for the increased fluorine-18-fluorodeoxyglucose uptake in lung adenocarcinomas with a poor prognosis.
Interactive Volume Visualization of General Polyhedral Grids

This paper presents a novel framework for visualizing volumetric data specified on complex polyhedral grids, without the need to perform any kind of a priori tetrahedralization. These grids are composed of polyhedra that often are non-convex and have an arbitrary number of faces, where the faces can be non-planar with an arbitrary number of vertices. The importance of such grids in state-of-the-art simulation packages is increasing rapidly. We propose a very compact, face-based data structure for representing such meshes for visualization, called two-sided face sequence lists (TSFSL), as well as an algorithm for direct GPU-based ray-casting using this representation. The TSFSL data structure is able to represent the entire mesh topology in a 1D TSFSL data array of face records, which facilitates the use of efficient 1D texture accesses for visualization. In order to scale to large data sizes, we employ a mesh decomposition into bricks that can be handled independently, where each brick is then composed of its own TSFSL array. This bricking enables memory savings and performance improvements for large meshes. We illustrate the feasibility of our approach with real-world application results, by visualizing highly complex polyhedral data from commercial state-of-the-art simulation packages.
The Rise of Data Capital

If exploited correctly, data can offer economic advantage, spur innovations, and generate revenue to enterprises. Cloud computing and big data are often intertwined. In fact, "cloud-based big data services" is becoming a general phrase, with examples including cloud-based big data analytics and cloud-based big data storage services. This issue looks at various topics in cloud computing, from the emerging cloud of sensors, which builds on the Internet of Things and wireless sensors, to cloud brokering and its challenges when deploying in an enterprise, to a unique method to classify and grade security aspects.
An Interactive Internet-Based Plate for Assessing Lunchtime Food Intake: A Validation Study on Male Employees

Background Misreporting food intake is common because most health screenings rely on self-reports. The more accurate methods (eg, weighing food) are costly, time consuming, and impractical. Objectives We developed a new instrument for reporting food intake—an Internet-based interactive virtual food plate. The objective of this study was to validate this instrument’s ability to assess lunch intake. Methods Participants were asked to compose an ordinary lunch meal using both a virtual and a real lunch plate (with real food on a real plate). The participants ate their real lunch meals on-site. Before and after pictures of the composed lunch meals were taken. Both meals included identical food items. Participants were randomized to start with either instrument. The 2 instruments were compared using correlation and concordance measures (total energy intake, nutritional components, quantity of food, and participant characteristics). Results A total of 55 men (median age: 45 years, median body mass index [BMI]: 25.8 kg/m2) participated. We found an overall overestimation of reported median energy intake using the computer plate (3044 kJ, interquartile range [IQR] 1202 kJ) compared with the real lunch plate (2734 kJ, IQR 1051 kJ, P<.001). Spearman rank correlations and concordance correlations for energy intake and nutritional components ranged between 0.58 to 0.79 and 0.65 to 0.81, respectively. Conclusion Although it slightly overestimated, our computer plate provides promising results in assessing lunch intake.
Quantum Hamiltonian complexity and the detectability lemma

Quantum Hamiltonian complexity studies computational complexity aspects of local Hamiltonians and ground states; these questions can be viewed as generalizations of classical computational complexity problems related to local constraint satisfaction (such as SAT), with the additional ingredient of multi-particle entanglement. This additional ingredient of course makes generalizations of celebrated theorems such as the PCP theorem from classical to the quantum domain highly non-trivial; it also raises entirely new questions such as bounds on entanglement and correlations in ground states, and in particular area laws. We propose a simple combinatorial tool that helps to handle such questions: it is a simplified, yet more general version of the detectability lemma introduced by us in the more restricted context on quantum gap amplification a year ago. Here, we argue that this lemma is applicable in much more general contexts. We use it to provide a simplified and more combinatorial proof of Hastings' 1D area law, together with a less than 1 page proof of the decay of correlations in gapped local Hamiltonian systems in any constant dimension. We explain how the detectability lemma can replace the Lieb-Robinson bound in various other contexts, and argue that it constitutes a basic tool for the study of local Hamiltonians and their ground states in relation to various questions in quantum Hamiltonian complexity.
A new higher order differential of Camellia

Camellia was jointly proposed by NTT and Mitsubishi in 2000 [1]. Camellia is a 128-bit block cipher supporting key lengths of 128, 192, 256 bits. The best previous attack is Zero Correlation FFT attack proposed by Bogdanov et. al. [2] and 12-round Camellia with FL/FL-1 is attacked with 2125.7 blocks of known plaintexts and 2188.8 times of data encryption. In this paper, we focused on a higher order differential attack. We present 7-round 120-th order differential by using control transform for the input. We show 12-round Camellia with FL/FL-1 is attackable with 2124.6 blocks of chosen plaintexts and 2190.4 times of data encryption.
Local Hybrid Coding for Image Classification

Sparse coding has received considerable research attentions due to its competitive performance for SPM-based image classification algorithms. In sparse coding, each low-level image descriptor (e.g., SIFT) is quantized into a sparse vector using an over-complete dictionary. Two typical schemes for achieving the code sparsity are imposing ℓ1-sparsity penalty on the coding coefficients, or selecting a set of fc-nearest-neighbor bases from the dictionary for locality-aware encoding. In this paper, we discover that different coding schemes usually produce substantially inconsistent coefficients, each preferring either ℓ1-sparsity or bases-locality. We therefore conjecture that different schemes should be explored simultaneously to further enhance the quantization quality. To this end, we propose a novel ensemble framework, Local Hybrid Coding (LHC), to formalize a unified optimization problem for different coding schemes. Specifically, we quantize each image descriptor using two disjoint sets of dictionaries, fcNN bases and non-fcNN bases, from which we efficiently compute a hybrid representation comprising of local coding and sparse coding, respectively. Extensive experiments on three benchmarks verify that LHC can remarkably outperform several state-of-the-art methods for image classification tasks, and bare comparable complexity to the most efficient coding methods.
Occipital‐Callosal Pathways in Children: Validation and Atlas Development

Diffusion tensor imaging and fiber tracking were used to measure fiber bundles connecting the two occipital lobes in 53 children of 7‐12 years of age. Independent fiber bundle estimates originating from the two hemispheres converge onto the lower half of the splenium. This observation validates the basic methodology and suggests that most occipital‐callosal fibers connect the two occipital lobes. Within the splenium, fiber bundles are organized in a regular pattern with respect to their cortical projection zones. Visual cortex dorsal to calcarine projects through a large band that fills much of the inferior half of the splenium, while cortex ventral to calcarine sends projections through a band at the anterior inferior edge of the splenium. Pathways projecting to the occipital pole and lateral‐occipital regions overlap the dorsal and ventral groups slightly anterior to the center of the splenium. To visualize these pathways in a typical brain, we combined the data into an atlas. The estimated occipital‐callosal fiber paths from the atlas form the walls of the occipital horn of the lateral ventricle, with dorsal paths forming the medial wall and the ventral paths bifurcating into a medial tract to form the inferior‐medial wall and a superior tract that joins the lateral‐occipital paths to form the superior wall of the ventricle. The properties of these fiber bundles match those of the hypothetical pathways described in the neurological literature on alexia.
A Background Sample-Time Error Calibration Technique Using Random Data for Wide-Band High-Resolution Time-Interleaved ADCs

Sample-time error among the channels of a time-interleaved analog-to-digital converter (ADC) is the main reason for significant degradation of the effective resolution of the high-speed time-interleaved ADC. A calibration technique for sample-time mismatches has been proposed and implemented at a low level of complexity. The calibration method uses random data and is especially suitable for ADCs used in digital data communication systems. An 800-MS/s four-channel, time-interleaved ADC system has been implemented to evaluate the performance of the technique. The experimental results show that the spurious-free dynamic range of the ADC system is improved to 58.1 dB at 350 MHz. The ADC system achieves a signal-to-noise and distortion ratio of 59.6 dB at 5 MHz and 50.1 dB at 350 MHz after calibration.