Miracle-dz/UniFAR-FTUs huggingface dataset:
The Star Formation History and Stellar Assembly of High Redshift Galaxies

Abstract I discuss current observational constraints on the star-formation and stellar-assembly histories of galaxies at high redshifts. The data on massive galaxies at z < 1 implies that their stellar populations formed at z>2, and that their morphological configuration was in place soon thereafter. Spitzer Space Telescope 24 μ observations indicate that a substantial fraction of massive galaxies at z ~ 1.5–3 have high IR luminosities, suggesting they are rapidly forming stars, accreting material onto supermassive black holes, or both. I compare how observations of these IR–active phases in the histories of massive galaxies constrain current galaxy–formation models.
A low-complexity successive cancellation decoder for polar codes

Polar codes are particularly aractive from a theoretical point of view because they are the rst codes that are both highly structured and provably optimal for a wide range of applications (in the sense of optimality that pertains to each application). Moreover, they can be decoded using an elegant, albeit suboptimal, successive cancellation (SC) algorithm, which has low computational and memory complexity. Even though the SC decoder is suboptimal, it is sucient in order to prove that polar codes are capacity achieving in the limit of innite blocklength. Unfortunately, the error correcting performance of SC decoding at nite blocklengths is not as good as that of other modern codes, such as LDPC codes. To improve the nite blocklength performance, more sophisticated algorithms, such as SC list decoding and SC stack decoding, were introduced recently. ese algorithms use SC as the underlying decoder, but improve its performance by exploring multiple paths on a decision tree simultaneously, with each path resulting in one candidate codeword. e computational and memory complexities of SC list decoding are though much higher than simple SC decoder. In this diploma thesis, we describe a new SC-based decoding algorithm, called SC ip, which retains the memory complexity of the original SC algorithm and has an average computational complexity that, at high SNR, is practically the same as the computational complexity of the simple SC decoder, while still providing a signicant gain in terms of error correcting performance.
2016 Ieee International Conference on Big Data (big Data) Using Machine Learning to Identify Major Shifts in Human Gut Microbiome Protein Family Abundance in Disease

—Inflammatory Bowel Disease (IBD) is an autoim-mune condition that is observed to be associated with major alterations in the gut microbiome taxonomic composition. Here we classify major changes in microbiome protein family abundances between healthy subjects and IBD patients. We use machine learning to analyze results obtained previously from computing relative abundance of ∼10,000 KEGG orthologous protein families in the gut microbiome of a set of healthy individuals and IBD patients. We develop a machine learning pipeline, involving the Kolomogorv-Smirnov test, to identify the 100 most statistically significant entries in the KEGG database. Then we use these 100 as a training set for a Random Forest classifier to determine ∼5% the KEGGs which are best at separating disease and healthy states. Lastly, we developed a Natural Language Processing classifier of the KEGG description files to predict KEGG relative over-or under-abundance. As we expand our analysis from 10,000 KEGG protein families to one million proteins identified in the gut microbiome, scalable methods for quickly identifying such anomalies between health and disease states will be increasingly valuable for biological interpretation of sequence data.
Popularity Effect ” in User-Generated Contents : Evidence from Online Product

Online product reviews are increasingly important for consumer decisions, yet we still know little about how reviews are generated in the first place. In an effort to gather more reviews, many websites encourage user interactions such as allowing one user to subscribe to another. Do these interactions actually facilitate the generation of product reviews, and more important, what kind of reviews do such interactions induce? We study these questions using data from epinions.com, one of the largest product review websites where users can subscribe to one another. By applying both panel data and flexible matching methods, we find that as users become more popular, they produce more reviews and more objective reviews; however, their numeric ratings systematically change, and become more negative and more varied. Such tradeoff has not been previously documented, and has important implications for not just product review websites, but user-generated content sites as well.
Empty Category Detection With Joint Context-Label Embeddings

This paper presents a novel technique for empty category (EC) detection using distributed word representations. A joint model is learned from the labeled data to map both the distributed representations of the contexts of ECs and EC types to a low dimensional space. In the testing phase, the context of possible EC positions will be projected into the same space for empty category detection. Experiments on Chinese Treebank prove the effectiveness of the proposed method. We improve the precision by about 6 points on a subset of Chinese Treebank, which is a new state-ofthe-art performance on CTB.
MECHANICAL PROPERTIES OF ACTIVATED CARBON (

This research is to develop a carbon composite prepared from carbon coir fibers that is reinforced with epoxy resin. Carbon coir fibers were taken from three types of coir fiber specifically designated as CKCF, CYCF and CRCF. The samples were prepared using epoxy resin reinforced with carbon at different weight percentages for three types of coir fiber starting with 0wt. %, 2wt. %, 4wt. %, 6wt. %, 8wt. % and 10wt. %. The mechanical properties such as tensile stress and impact strength were used to characterize all the samples. The morphological study of reinforced samples was also conducted in this research using a SEM machine. The characteristics of all the composite materials were also investigated and discussed. It was determined that the CKCF sample exhibited better mechanical properties than the other coir fiber composites, having a higher average tensile stress value at 11.80MPa and higher impact strength values ranging from 268J to 276J at different carbon content. CKCF with 10wt% AC content had a tremendous impact strength compared with CYCF and CRCF.
Digital Enhancement of Palm Leaf Manuscript Images using Normalization Techniques

Palm leaves were one of the earliest forms of writing media and their use as writing material in South and Southeast Asia has been recorded from as early as the fifth century B.C. until as recently as the late 19th century. Palm leaf manuscripts relating to art and architecture, mathematics, astronomy, astrology, and medicine dating back several hundreds of years are still available for reference today thanks to many ongoing efforts for preservation of ancient documents by libraries and universities around the world. Palm leaf manuscripts typically last a few centuries but with time the palm leaves degrade and the writing becomes illegible to be useful in any form. Image processing techniques can help enhance the images of these manuscripts so as to enable retrieval of the written text from these degraded documents. In this paper we propose a transform based method for enhancing digital images of palm leaf manuscripts. The method uses a dynamically selected pivoting background color in a linear transform to enhance the legibility of the foreground text. Then a combination of two other image processing algorithms viz., histogram normalization and background normalization developed in our earlier research, are applied to the transformed image. The algorithms can be mathematically combined into one or two transformations for computational efficiency. The method is tested on a set of palm leaf images from various sources and the preliminary results show significant improvement in readability. The techniques can also be used to enhance images of ancient, historical, degraded papyrus and paper documents.
Detecting Digital Image Forgeries by Measuring Inconsistencies of Blocking Artifact

Digital images can be forged easily with today's widely available image processing software. In this paper, we describe a passive approach to detect digital forgeries by checking inconsistencies of blocking artifact. Given a digital image, we find that the blocking artifacts introduced during JPEG compression could be used as a "natural authentication code". A blocking artifact measure is then proposed based on the estimated quantization table using the power spectrum of the DCT coefficient histogram. Experimental results also demonstrate the validity of the proposed approach.
Workforce retention: what do IT employees really want?

The purpose of this study is to present and test an integrated model of turnover intentions that addresses the unique nature of the IT profession. We identified a multidimensional set of HR practices likely to increase retention among IT employees and considered citizenship behaviors as well as two distinct types of organizational commitment as key antecedents of turnover intentions. A questionnaire was developed and sent to the Quebec members of the Canadian Information Processing Society. Data from 394 respondents were used to validate the measures and test the research hypotheses. We present and discuss the results and make a series of recommendations for IT and HR executives.
Comparisons on different sEMG-features with dimension-reduction methods in hand motion recognition

Hand motion recognition based on surface electromyography (sEMG) has drawn much attention over last decades. Generally, sEMG can be non-invasively measured on the skin, and then different stable features directly relating to hand motion are extracted from the preprocessed sEMG. In order to improve computational efficiency, some dimension-reduction methods, such as PCA, LDA, are always employed to reduce the high-dimensional sEMG-features into a proper low-dimensional space. Afterwards, hand motions can be classified by a trained classification model. The proper sEMG-features and dimension-reduced data are keys for accurately identifying hand motions. This paper provides performance comparisons on different features combining with different dimension-reduction methods.
Parameter setting for quantum annealers

We develop and apply several strategies for setting physical parameters on quantum annealers for application problems that do not fit natively on the hardware graph. The strategies are tested with a culled random set of mixed satisfiability problems, yielding results that generalize to guidelines regarding which parameter setting strategies to use for different classes of problems, and how to choose other necessary hardware quantities as well. Alternate methods of changing the hardware implementation of an application problem are also considered and their utility discussed.
On the relevance of parents and TV as socializers of 6–19 year-olds’ expressions of emotion: representative data from Germany

Abstract This study examines joint influences of parental socialization and socialization via mass media on children’s expression of emotions. The effect of parental approval of their child’s expression of emotions, on the child’s approval of TV characters expressing the emotion, and the influence of both on the child’s expression of emotions within the past seven days is tested for the emotions fear, sadness, anger, and happiness with a representative survey of children (N = 1458) aged 6–19 in Germany. Moderating age and gender effects were also considered. Consistent across the four emotions, results showed that socialization of emotions via mass media is driven by internalized parental socialization but has a comparably strong effect of its own on the child’s expression of emotion that adds to the variance explained, especially with regard to anger and happiness. Implications for the conceptualization of parental emotion socialization and emotional socialization via media are discussed.
Design of RF to DC converter in 90nm CMOS technology for ultra-low power application

This paper presents an RF to DC converter circuit design implemented and simulated in 90nm 1P9M CMOS process technology. The system employs a voltage rectifier that converts a very low RF signal of up to -2.4dBm into a useable DC voltage. The converted DC voltage was stored in a battery with a protection circuit. The battery was then used as a supply voltage of the low dropout (LDO) regulator which is composed of a bandgap voltage reference circuit with an output voltage of 0.5V and an error amplifier with a gain of 74.9dB and phase margin of 62° that provides a stable system performance. The system yields a regulated output voltage of 0.9V.
Conformal curvature ows : from phase transitions toactive visionSatyanad

In this paper, we analyze geometric active contour models from a curve evolution point of view and propose some modi cations based on gradient ows relative to certain new feature-based Riemannian metrics. This leads to a novel edge-detection paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus an edge-seeking curve is attracted very naturally and e ciently to the desired feature. Comparison with the Allen-Cahn model clari es some of the choices made in these models, and suggests inhomogeneous models which may in return be useful in phase transitions. We also consider some 3-D active surface models based on these ideas. The justi cation of this model rests on the careful study of the viscosity solutions of evolution equations derived from a level-set approach.
Solar p-mode excitation: further insight from recent low-ℓ BiSON helioseismological data

We present measurements of low-degree solar p-mode velocity powers, energies and energy supply rates between similar to 1600 mu Hz and similar to 4700 mu Hz, as derived from the analysis of several years of high-quality helioseismological data collected by the Birmingham Solar-Oscillations Network (BiSON). For the radial (l = 0) modes, we find that the total energy E per mode (kinetic plus potential) peaks at similar to 3200 mu Hz, reaching approximate to 10(28) erg. The rate at which energy is supplied to the modes (E) over dot = 2 pi Delta nu . E, where Delta nu is the FWHM modal line width, is observed to plateau between similar to 3000 and similar to 4000 mu Hz, reaching a maximum of approximate to 10(23) erg s(-1). At frequencies below the plateau, the supply rate follows a simple power law with a dependence of (E) over dot proportional to nu(7.0+/-0.4); and at very-high frequencies the data follow (E) over dot proportional to nu(-4.5+/-1.1). These assume modal inertias normalized at T = T-eff; with the mode-mass calculation normalized at the optical depth of the BiSON observations, the fitted power laws in (E) over dot are approximately similar to nu(6.5+/-1.1) and similar to nu(-6.2+/-1.1) respectively.
Chapter 4. Immersion into narrative and poetic worlds: A neurocognitive poetics perspective

A key assumption of the neurocognitive poetics model (NCPM; Jacobs, 2015a) of literary reading is the duality of immersive and aesthetic processes being conceived as rival forces driven by different text features and their implicit vs. explicit processing. With regard to the experiential phenomenon of immersion, the NCPM specifies a variety of facilitative processes at both the affective-cognitive and neuronal levels which will be further differentiated here in the light of results from recent neurocognitive and behavioral studies on reading short stories, excerpts from novels, and poems.
A serious game for speech disorder children therapy

Today meaning of games is much more serious than just considering them as an entertainment and free-time activity. Games have begun to be used in many different areas such as education, healthcare, military, corporate management and public policy for different purposes. Several benefits of serious games have been reported in the literature. Studies also show that with a combination of entertainment and education (edutainment) several benefits could be achieved in the rehabilitation process of the disordered individuals. This study reports the advantages of 3D game environments for speech and language therapy of children and benefits of making the treatment process accessible from anywhere and anytime are demonstrated.
Phase I and pharmacokinetic study of DE-310 in patients with advanced solid tumors.

PURPOSE To assess the maximum-tolerated dose, toxicity, and pharmacokinetics of DE-310, a macromolecular prodrug of the topoisomerase I inhibitor exatecan (DX-8951f). in patients with advanced solid tumors. EXPERIMENTAL DESIGN Patients received DE-310 as a 3-hour infusion once every 2 weeks (dose, 1.0-2.0 mg/m(2)) or once every 6 weeks (dose, 6.0-9.0 mg/m(2)). Because pharmacokinetics revealed a drug terminal half-life exceeding the 2 weeks administration interval, the protocol was amended to a 6-week interval between administrations also based on available information from a parallel trial using an every 4 weeks schedule. Conjugated DX-8951 (the carrier-linked molecule), and the metabolites DX-8951 and glycyl-DX-8951 were assayed in various matrices up to 35 days post first and second dose. RESULTS Twenty-seven patients were enrolled into the study and received a total of 86 administrations. Neutropenia and grade 3 thrombocytopenia, and grade 3 hepatotoxicity with veno-occlusive disease, were dose-limiting toxicities. Other hematologic and nonhematologic toxicities were mild to moderate and reversible. The apparent half-life of conjugated DX-8951, glycyl-DX-8951, and DX-8951 was 13 days. The area under the curve ratio for conjugated DX-8951 to DX-8951 was 600. No drug concentration was detectable in erythrocytes, skin, and saliva, although low levels of glycyl-DX-8951 and DX-8951 were detectable in tumor biopsies. One patient with metastatic adenocarcinoma of unknown primary achieved a histologically proven complete remission. One confirmed partial remission was observed in a patient with metastatic pancreatic cancer and disease stabilization was noted in 14 additional patients. CONCLUSIONS The recommended phase II dose of DE-310 is 7.5 mg/m(2) given once every 6 weeks. The active moiety DX-8951 is released slowly from DE-310 and over an extended period, achieving the desired prolonged exposure to this topoisomerase I inhibitor.
Seiberg-Witten-Floer Theory for Homology 3-Spheres

We give the definition of the Seiberg-Witten-Floer homology group for a homology 3-sphere. Its Euler characteristic number is a Casson-type invariant. For a four-manifold with boundary a homology sphere, a relative Seiberg-Witten invariant is defined taking values in the Seiberg-Witten-Floer homology group, these relative Seiberg-Witten invariants are applied to certain homology spheres bounding Stein surfaces.
Cognitive Collaboration Found in Cardiac Physiology: Study in Classroom Environment

It is known that periods of intense social interaction result in shared patterns in collaborators’ physiological signals. However, applied quantitative research on collaboration is hindered due to scarcity of objective metrics of teamwork effectiveness. Indeed, especially in the domain of productive, ecologically-valid activity such as programming, there is a lack of evidence for the most effective, affordable and reliable measures of collaboration quality. In this study we investigate synchrony in physiological signals between collaborating computer science students performing pair-programming exercises in a class room environment. We recorded electrocardiography over the course of a 60 minute programming session, using lightweight physiological sensors. We employ correlation of heart-rate variability features to study social psychophysiological compliance of the collaborating students. We found evident physiological compliance in collaborating dyads’ heart-rate variability signals. Furthermore, dyads’ self-reported workload was associated with the physiological compliance. Our results show viability of a novel approach to field measurement using lightweight devices in an uncontrolled environment, and suggest that self-reported collaboration quality can be assessed via physiological signals.
Evaluation of interrupt handling timeliness in real-time Linux operating systems

Several real-time Linux extensions are available nowadays. Two of those extensions that have received special attention recently are Preempt-RT and Xenomai. This paper evaluates to what extent they provide deterministic guarantees when reacting to external events, an essential characteristic when it comes to real-time systems. For this, we define two simple experimental approaches. Our results indicate that Preempt-RT is more prone to temporal variations than Xenomai when the system is subject to overload scenarios.
Performance isolation and scheduler behavior

Performance isolation is desirable in virtual machine based infrastructures to meet S̲ervice L̲evel O̲bjectives (SLO). In performance isolation, ideally, no virtual machine should affect performance of other co hosted virtual machine. Virtual machine scheduler is the key in allocating resources among virtual machines. This fact attracts attention towards scheduling, as fairness and resource isolation are the key requirements for which any user virtualizes the servers. I/O models are the main bottlenecks in sharing resources among virtual machines. This work aims to evaluate the performance isolation achieved by Xen hypervisor in different scheduler configurations with different kind of resource intensive applications. Experiment results show that isolation is critical when we run I/O application in conjunction with CPU intensive applications.
A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning

We consider learning problems over training sets in which both, the number of training examples and the dimension of the feature vectors, are large. To solve these problems we propose the random parallel stochastic algorithm (RAPSA). We call the algorithm random parallel because it utilizes multiple parallel processors to operate on a randomly chosen subset of blocks of the feature vector. We call the algorithm stochastic because processors choose training subsets uniformly at random. Algorithms that are parallel in either of these dimensions exist, but RAPSA is the first attempt at a methodology that is parallel in both the selection of blocks and the selection of elements of the training set. In RAPSA, processors utilize the randomly chosen functions to compute the stochastic gradient component associated with a randomly chosen block. The technical contribution of this paper is to show that this minimally coordinated algorithm converges to the optimal classifier when the training objective is convex. Moreover, we present an accelerated version of RAPSA (ARAPSA) that incorporates the objective function curvature information by premultiplying the descent direction by a Hessian approximation matrix. We further extend the results for asynchronous settings and show that if the processors perform their updates without any coordination the algorithms are still convergent to the optimal argument. RAPSA and its extensions are then numerically evaluated on a linear estimation problem and a binary image classification task using the MNIST handwritten digit dataset.