Miracle-dz/UniFAR-FTUs huggingface dataset:
Chandra AND XMM-Newton OBSERVATIONS OF THE FIRST QUASARS : X-RAYS FROM THE AGE OF COSMIC ENLIGHTENMENT

We report onChandra and XMM-Newton observations of a sample of 13 quasars at z ≈ 4.7–5.4 mostly taken from the Sloan Digital Sky Survey (SDSS). The present sample complements previous X-ray studies of z ≥ 4 quasars, in which the majority of the objects are optically m ore luminous and at lower redshifts. All but two of our quasars have been detected in the X-ray band, thus doubli ng the number of z ≥ 4.8 X-ray detected quasars. The two non-detections are likely to be due to a short exposur e time (SDSSp J033829.31 +002156.3) and to the presence of intrinsic absorption (SDSSp J173744.87 +582829.5). We confirm and extend to the highest redshifts the presence of a correlation between AB1450(1+z) magnitude and soft X-ray flux for z≥ 4 quasars, and the presence of a steeper optical-to-X-ray spectral energy distributio n (parameterized by αox) for high-luminosity, high-redshift quasars than for lower-luminosity, lower-redshift quasar s. The second effect is likely due to the known anticorrelation between αox and rest-frame 2500̊ A luminosity, whose significance is confirmed via partial cor relation analysis. The joint ≈ 2.5–36 keV rest-frame spectrum of the z > 4.8 SDSS quasars observed thus far by Chandra is well parameterized by a power-law with photon index Γ=1.84+0.31 −0.30; this photon index is consistent with those of z ≈ 0–3 quasars and that obtained from joint spectral fitting of z ≈ 4.1–4.5 optically luminous Palomar Digital Sky Survey quasars. No evidence for widespread intrinsic X-ray absorption has been found ( NH < ∼ 4.0×10 22 cm−2 on average at 90% confidence). We also obtained Hobby-Eberly T lescope (HET) photometric observations for eight of our target quasars. None of these shows significant ( > 30%) optical variability over the time interval of a few years (in the observed frame) between the SDSS and HET obs ervations.
Evolution of wind energy generation system using DFIG and FFT analysis

This paper presents a study on the technologies used for doubly fed Induction generator (DFIG) based wind energy generation system (WEGS) till date and the FFT analysis of the same system. Global wind energy statistics are also shown. Preface on WEGS is also given. Various control techniques are discussed in order to revamp the performance and to overcome some problems for WEGS. A 9 MW wind farm was simulated in Matlab R2014a simulink and FFT analysis of this system is studied during fault conditions.
Enhancing the Acquisition of Social Skills through the Interactivity of Multimedia

Autism Spectrum Disorders (ASD) are a group of neuro-developmental disorders caused by brain abnormalities which result in impaired social story. Research on treatment in helping children with ASD to improve social story is growing as the cases of children diagnosed with ASD are on the rise. Social story is one of the proven methods of treatment in helping children with ASD to acquire social story through scenarios written in the form of stories. However, the current approaches to present the social story lack interactivity, consuming more intensive efforts to acquire the social story. Learning is most effectual when motivated; thus, the purpose of this study is to discover a learning tool that children with ASD will be motivated to learn independently, and it is achievable by combining elements that they are interested in. This research utilizes the interactivity of multimedia as a medium to present an interactive pedagogical tool for children with ASD to acquire social story. This combination is anticipated to be an effective tool in teaching social story to children with ASD, as they are naturally drawn to computers and visual cues, combined with the fact that Social StoryTM has been effective in changing the social behavior of children with ASD. Thus, this study has contributed to the emergent research of treatment for children with ASD in social story acquisition. The result of this study is important as it presents a novel assistance that can be used effectively in assisting children with ASD to improve their main deficit, social story.
Hand posture recognition using compositional techniques

This work proposes a compositional approach to hand posture recognition, using sparse features. The hand posture is decomposed into relevant compositions which are learned for each hand posture class without supervision; no hand segmentations or localization during training is needed. To learn relevant composition prototypes, an entropy range maximization loop was introduced, by performing k-means clustering several times. Experimental results compare favorably with results of both image categorization and hand posture recognition reported in literature.
Domain morphology, boundaries, and topological defects in biophotonic gyroid nanostructures of butterfly wing scales

Coherent X-rays reveal defects in photonic crystals of butterfly wings. Many organisms in nature have evolved sophisticated cellular mechanisms to produce photonic nanostructures and, in recent years, diverse crystalline symmetries have been identified and related to macroscopic optical properties. However, because we know little about the distributions of domain sizes, the orientations of photonic crystals, and the nature of defects in these structures, we are unable to make the connection between the nanostructure and its development and functionality. We report on nondestructive studies of the morphology of chitinous photonic crystals in butterfly wing scales. Using spatially and angularly resolved x-ray diffraction, we find that the domains are highly oriented with respect to the whole scale, indicating growth from scale boundaries. X-ray coherent diffractive imaging reveals two types of crystalline domain interfaces: abrupt changes between domains emerging from distinct nucleation sites and smooth transitions with edge dislocations presumably resulting from internal stresses during nanostructure development. Our study of the scale structure reveals new aspects of photonic crystal growth in butterfly wings and shows their similarity to block copolymer materials. It opens new avenues to exploration of fundamental processes underlying the growth of biological photonic nanostructures in a variety of species.
TQDL: Integrated Models for Cross-Language Document Retrieval

This paper proposed an integrated approach for Cross-Language Information Retrieval (CLIR), which integrated with four statistical models: Translation model, Query generation model, Document retrieval model and Length Filter model. Given a certain document in the source language, it will be translated into the target language of the statistical machine translation model. The query generation model then selects the most relevant words in the translated version of the document as a query. Instead of retrieving all the target documents with the query, the length-based model can help to filter out a large amount of irrelevant candidates according to their length information. Finally, the left documents in the target language are scored by the document searching model, which mainly computes the similarities between query and document.Different from the traditional parallel corpora-based model which relies on IBM algorithm, we divided our CLIR model into four independent parts but all work together to deal with the term disambiguation, query generation and document retrieval. Besides, the TQDL method can efficiently solve the problem of translation ambiguity and query expansion for disambiguation, which are the big issues in Cross-Language Information Retrieval. Another contribution is the length filter, which are trained from a parallel corpus according to the ratio of length between two languages. This can not only improve the recall value due to filtering out lots of useless documents dynamically, but also increase the efficiency in a smaller search space. Therefore, the precision can be improved but not at the cost of recall.In order to evaluate the retrieval performance of the proposed model on cross-languages document retrieval, a number of experiments have been conducted on different settings. Firstly, the Europarl corpus which is the collection of parallel texts in 11 languages from the proceedings of the European Parliament was used for evaluation. And we tested the models extensively to the case that: the lengths of texts are uneven and some of them may have similar contents under the same topic, because it is hard to be distinguished and make full use of the resources.After comparing different strategies, the experimental results show a significant performance of the method. The precision is normally above 90% by using a larger query size. The length-based filter plays a very important role in improving the F-measure and optimizing efficiency.This fully illustrates the discrimination power of the proposed method. It is of a great significance to both cross-language searching on the Internet and the parallel corpus producing for statistical machine translation systems. In the future work, the TQDL system will be evaluated for Chinese language, which is a big changing and more meaningful to CLIR.
SP140L, an Evolutionarily Recent Member of the SP100 Family, Is an Autoantigen in Primary Biliary Cirrhosis

The SP100 family members comprise a set of closely related genes on chromosome 2q37.1. The widely expressed SP100 and the leukocyte-specific proteins SP110 and SP140 have been associated with transcriptional regulation and various human diseases. Here, we have characterized the SP100 family member SP140L. The genome sequence analysis showed the formation of SP140L gene through rearrangements of the two neighboring genes, SP100 and SP140, during the evolution of higher primates. The SP140L expression is interferon-inducible with high transcript levels in B cells and other peripheral blood mononuclear cells. Subcellularly, SP140L colocalizes with SP100 and SP140 in nuclear structures that are devoid of SP110, PML, or p300 proteins. Similarly to SP100 and SP140 protein, we detected serum autoantibodies to SP140L in patients with primary biliary cirrhosis using luciferase immunoprecipitation system and immunoblotting assays. In conclusion, our results show that SP140L is phylogenetically recent member of SP100 proteins and acts as an autoantigen in primary biliary cirrhosis patients.
Key Management in Mobile Sensor Networks

Wireless sensor networks consist of sensor nodes with limited computational and communication capabilities. This paper deals with mobile sensors which are divided into clusters based on their physical locations. Efficient ways of key distribution among the sensors and inter and intra cluster communications are examined. The security of the entire network is considered through efficient key management by taking into consideration the network's power capabilities.
Causal Inference on Discrete Data Using Additive Noise Models

Inferring the causal structure of a set of random variables from a finite sample of the joint distribution is an important problem in science. The case of two random variables is particularly challenging since no (conditional) independences can be exploited. Recent methods that are based on additive noise models suggest the following principle: Whenever the joint distribution P(X,Y) admits such a model in one direction, e.g., Y = f(X)+N, N ⊥X, but does not admit the reversed model X=g(Y)+Ñ, Ñ ⊥ Y, one infers the former direction to be causal (i.e., X → Y). Up to now, these approaches only dealt with continuous variables. In many situations, however, the variables of interest are discrete or even have only finitely many states. In this work, we extend the notion of additive noise models to these cases. We prove that it almost never occurs that additive noise models can be fit in both directions. We further propose an efficient algorithm that is able to perform this way of causal inference on finite samples of discrete variables. We show that the algorithm works on both synthetic and real data sets.
Parental, Peer, and Tobacco Marketing Influences on Adolescent Smoking in South Africa

REYNOLDS MORRISON Parental, peer, and tobacco marketing influences on adolescent smoking in South Africa. (Under the direction of Michael Eriksen, FACULTY MEMBER) Tobacco use is a major preventable cause of morbidity and mortality worldwide. Most smokers initiate smoking in childhood, become addicted, and continue the habit into adulthood. Various factors have been shown to impact smoking behavior. It is important to determine how these factors impact smoking behavior in developing regions of the world, such as in South Africa. This study examines the association between parental smoking status; peer smoking status; exposure to pro-tobacco marketing; and current smoking status among adolescents in South Africa. It also determines which factor is the most significant predictor of current smoking status among the study population and further examines the trends in these factors among survey populations from 1999 – 2008. Secondary analysis was conducted on data obtained from the Global Youth Tobacco Survey. Logistic regression analyses were conducted to determine the association between the independent variables; parental smoking status, peer smoking status, and exposure to protobacco marketing; and the dependent variable, current smoking status, controlling for other factors. Adolescents who had at least a parent or a friend who smoked had greater odds of being current smokers as compared to those who had neither a parent nor a friend who smoked. Similarly, exposure to average and high levels of pro-tobacco marketing was associated with greater odds of an adolescent being a current smoker as compared to exposure to low levels of pro-tobacco marketing. Maternal smoking appeared to have a greater impact on adolescent smoking behavior as compared to paternal smoking. Also, peer smoking had the greatest impact on smoking behavior as compared to the other independent factors. Smoking rates among South African adolescents has decreased from 23% in 1999 to about 17% in 2008. Similarly, the proportion of adolescents who had a parent or a friend who smoked, or had been exposed to average and high levels of pro-tobacco marketing has also decreased over the same period. Programs must be implemented to educate parents on how their smoking behavior is being transmitted to their children, with a special focus on maternal influences. Tobacco use prevention campaigns aimed at the youth should also be implemented, and laws restricting tobacco marketing must be enforced. INDEX WORDS: smoking, current smoking, adolescent, parent, peer, pro-tobacco marketing, tobacco, South Africa. PARENTAL, PEER, AND TOBACCO MARKETING INFLUENCES ON ADOLESCENT SMOKING IN SOUTH AFRICA
A framework for automatic generation of audio processing applications on a dual-core system

In this paper we describe an open framework for programming a dual-core system whose architecture is designed for ultra low-power audio processing applications. We show how the system’s architecture leads to a model of computation, i.e. a formalism that describes the execution, scheduling and interaction between components in a system. We also show how applications can automatically be created from a set of components that are specifically architected for the dual-core system in terms of resource usage and performance using a set of complexity metrics associated with the model of computation.
Low power 2.4 GHz quadrature generation for body area network applications

This paper presents two implentations of low-power quadrature generation for the new Bluetooth low energy standard in the 2.4 GHz ISM band. Both implementation have been designed in a 90 nm CMOS technology for a 1 V supply voltage and post-layout simulation results are presented. The first implementation is a quadrature voltage controlled oscillator (QVCO) with 180 µW power consumption and a phase noise of −112.7 dBc/Hz @1MHz. It employs a new technique to reduce the influence of magnetic coupling between the two spiral inductors. The second implementation employs a VCO running at twice the frequency with a subsequent divide-by-2 stage. Its total power consumption is 320 µW and the phase noise at the quadrature outputs is −115.7 dBc/Hz @1MHz.
Time-Lag in Responses of Birds to Atlantic Forest Fragmentation: Restoration Opportunity and Urgency

There are few opportunities to evaluate the relative importance of landscape structure and dynamics upon biodiversity, especially in highly fragmented tropical landscapes. Conservation strategies and species risk evaluations often rely exclusively on current aspects of landscape structure, although such limited assumptions are known to be misleading when time-lag responses occur. By relating bird functional-group richness to forest patch size and isolation in ten-year intervals (1956, 1965, 1978, 1984, 1993 and 2003), we revealed that birds with different sensitivity to fragmentation display contrasting responses to landscape dynamics in the Brazilian Atlantic Forest. For non-sensitive groups, there was no time-lag in response: the recent degree of isolation best explains their variation in richness, which likely relates to these species’ flexibility to adapt to changes in landscape structure. However, for sensitive bird groups, the 1978 patch area was the best explanatory variable, providing evidence for a 25-year time-lag in response to habitat reduction. Time-lag was more likely in landscapes that encompass large patches, which can support temporarily the presence of some sensitive species, even when habitat cover is relatively low. These landscapes potentially support the most threatened populations and should be priorities for restoration efforts to avoid further species loss. Although time-lags provide an opportunity to counteract the negative consequences of fragmentation, it also reinforces the urgency of restoration actions. Fragmented landscapes will be depleted of biodiversity if landscape structure is only maintained, and not improved. The urgency of restoration action may be even higher in landscapes where habitat loss and fragmentation history is older and where no large fragment remained to act temporarily as a refuge.
EFFICIENT COMBINATIONAL CIRCUITS DESIGN THROUGH FUZZIFIED ANT COLONY OPTIMIZATION ALGORITHM

With the increasing demand for high quality, more ef ﬁ cient and less area circuits, the problem of logic circuit design has become a multiobjective optimization problem. In this paper, a multiobjective optimization of logic circuits based on a fuzzi ﬁ ed Ant Colony (ACO) algorithm is presented. The results obtained using the proposed algorithm are compared to those obtained using SIS in terms of area, delay and power. It is shown that the circuits produced by the proposed algorithm are better as compared to those obtained by SIS.
Can unstructured P2P protocols survive flash crowds?

Today's Internet periodically suffers from hot spots, a.k. a. , flash crowds. A hot spot is typically triggered by an unanticipated news event that triggers an unanticipated surge of users that request data objects from a particular site, temporarily overwhelming the site's delivery capabilities. During this time, the large majority of users that attempt to get these objects face the frustrating experience of not being able to retrieve the content they want while still being able to communicate effectively with all other parts of the network. In this paper, we examine whether simple, undirected peer-to-peer search protocols can be used as a backup to deliver content whose popularity suddenly spikes. We model a simple, representative, undirected peer-to-peer search protocol in which clients cache only those objects they have explicitly requested. Because the object that becomes hot initially has limited popularity, the number of cache points, were they to remain fixed, would be insufficient to handle the level of demand during the flash crowd. However, as searches complete, more copies of the object become available. We analyze this natural scaling phenomenon and show that during the flash crowd, copies are distributed to requesting clients at a fast enough rate such that these simple protocols can indeed be used to scalably retrieve content that suddenly becomes "hot".
PMN transendothelial migration decreases nuclear NFκB in IL-1β–activated endothelial cells

During the systemic inflammatory response, circulating cytokines interact with the vascular endothelium, resulting in activation and nuclear accumulation of the nuclear transcription factor, nuclear factor kappa B (NFκB). In turn, NFκB transactivates relevant proinflammatory genes, resulting in an amplification of the inflammatory response. Because this scenario is potentially detrimental to the host, mechanisms exist to limit this amplification. Using an in vitro system that mimics the vascular–interstitial interface during inflammation (cell culture inserts), we provide evidence for the existence of a novel negative feedback mechanism on NFκB activity. We show that the interleukin 1β–induced accumulation of nuclear NFκB in human umbilical vein endothelial cell monolayers is dramatically reduced when polymorphonuclear leukocytes (PMN) are allowed to migrate across these monolayers. This effect does not appear to be due to PMN-derived elastase or nitric oxide. Fixed PMN (adhere but do not migrate) did not affect nuclear NFκB. Furthermore, cross-linking of platelet-endothelial cell adhesion molecule-1 (PECAM-1), but not intercellular adhesion molecule-1, reduces human umbilical vein endothelial cell nuclear NFκB induced by interleukin 1β. Finally, interaction of PMN with PECAM-1–deficient endothelial cells does not reduce nuclear NFκB. These observations indicate that engagement of PECAM-1 by emigrating PMN is a pivotal event in this negative feedback on NFκB activity.
Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods

Abstract. In the assessment of nodules in CT scans of the lungs, a number of image-derived features are diagnostically relevant. Currently, many of these features are defined only qualitatively, so they are difficult to quantify from first principles. Nevertheless, these features (through their qualitative definitions and interpretations thereof) are often quantified via a variety of mathematical methods for the purpose of computer-aided diagnosis (CAD). To determine the potential usefulness of quantified diagnostic image features as inputs to a CAD system, we investigate the predictive capability of statistical learning methods for classifying nodule malignancy. We utilize the Lung Image Database Consortium dataset and only employ the radiologist-assigned diagnostic feature values for the lung nodules therein, as well as our derived estimates of the diameter and volume of the nodules from the radiologists’ annotations. We calculate theoretical upper bounds on the classification accuracy that are achievable by an ideal classifier that only uses the radiologist-assigned feature values, and we obtain an accuracy of 85.74 (±1.14)%, which is, on average, 4.43% below the theoretical maximum of 90.17%. The corresponding area-under-the-curve (AUC) score is 0.932 (±0.012), which increases to 0.949 (±0.007) when diameter and volume features are included and has an accuracy of 88.08 (±1.11)%. Our results are comparable to those in the literature that use algorithmically derived image-based features, which supports our hypothesis that lung nodules can be classified as malignant or benign using only quantified, diagnostic image features, and indicates the competitiveness of this approach. We also analyze how the classification accuracy depends on specific features and feature subsets, and we rank the features according to their predictive power, statistically demonstrating the top four to be spiculation, lobulation, subtlety, and calcification.