Miracle-dz/UniFAR-FTUs huggingface dataset:
Cost-Efficient Throughput Maximization in Multi-Carrier Cognitive Radio Systems

Cognitive radio (CR) systems allow opportunistic, secondary users (SUs) to access portions of the spectrum that are unused by the network’s licensed primary users (PUs), provided that the induced interference does not compromise the PU’ performance guarantees. To account for interference constraints of this type, we consider a flexible spectrum access pricing scheme that charges SUs based on the interference that they cause to the system’s PUs (individually, globally, or both), and we examine how SUs can maximize their achievable transmission rate in this setting. We show that the resulting non-cooperative game admits a unique Nash equilibrium under very mild assumptions on the pricing mechanism employed by the network operator, and under both static and ergodic (fast-fading) channel conditions. In addition, we derive a dynamic power allocation policy that converges to equilibrium within a few iterations (even for large numbers of users), and which relies only on local signal-to-interference-plus-noise ratio (SINR) measurements; importantly, the proposed algorithm retains its convergence properties even in the ergodic channel regime, despite the inherent stochasticity thereof. Our theoretical analysis is complemented by extensive numerical simulations which illustrate the performance and scalability properties of the proposed pricing scheme under realistic network conditions.
C6-Ceramide Nanoliposomes Target the Warburg Effect in Chronic Lymphocytic Leukemia

Ceramide is a sphingolipid metabolite that induces cancer cell death. When C6-ceramide is encapsulated in a nanoliposome bilayer formulation, cell death is selectively induced in tumor models. However, the mechanism underlying this selectivity is unknown. As most tumors exhibit a preferential switch to glycolysis, as described in the “Warburg effect”, we hypothesize that ceramide nanoliposomes selectively target this glycolytic pathway in cancer. We utilize chronic lymphocytic leukemia (CLL) as a cancer model, which has an increased dependency on glycolysis. In CLL cells, we demonstrate that C6-ceramide nanoliposomes, but not control nanoliposomes, induce caspase 3/7-independent necrotic cell death. Nanoliposomal ceramide inhibits both the RNA and protein expression of GAPDH, an enzyme in the glycolytic pathway, which is overexpressed in CLL. To confirm that ceramide targets GAPDH, we demonstrate that downregulation of GAPDH potentiates the decrease in ATP after ceramide treatment and exogenous pyruvate treatment as well as GAPDH overexpression partially rescues ceramide-induced necrosis. Finally, an in vivo murine model of CLL shows that nanoliposomal C6-ceramide treatment elicits tumor regression, concomitant with GAPDH downregulation. We conclude that selective inhibition of the glycolytic pathway in CLL cells with nanoliposomal C6-ceramide could potentially be an effective therapy for leukemia by targeting the Warburg effect.
A new list of extra-galactic radio jets

A catalogue of extra-galactic jets is very useful both in observational and theoretical studies of active galaxies. With the use of new powerful radio instruments, the detailed structures of very compact or weak radio sources are investigated observationally and many new radio jets are detected. In this paper, we give a list of 661 radio sources with detected radio jets known to us prior to the end of December 2000. All references are collected for the observations of jets in radio, IR, optical, UV and X-ray wave-bands.
A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model

In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.
Combining top-down and bottom-up approaches for building detection in a single very high resolution satellite image

Building detection from geospatial optical images has been a popular topic of research for the last twenty years and in particular with the emergence of very high resolution satellites. Existing methods exhibit various flaws and prevent them from being efficient at large scales of space and time: they are context-dependent, require a tedious parameter tuning or several data sources. In this paper, we propose a fully automatic method that alleviates some of these issues by combining the strengths of bottom-up and top-down approaches, i.e., of both classification and pattern recognition algorithms. This allows to correctly detect the objects by geometric prior knowledge while finely delineating their borders and preserving their shapes. The method is evaluated over a complex area of more than 230 buildings using a 0.5 m multispectral pansharpened Pleiades image.
Neutrino Astrophysics

A general overview of neutrino physics and astrophysics is given, starting with a historical account of the development of our understanding of neutrinos and how they helped to unravel the structure of the Standard Model. We discuss why it is so important to establish if neutrinos are massive and introduce the main scenarios to provide them a mass. The present bounds and the positive indications in favor of non-zero neutrino masses are discussed, including the recent results on atmospheric and solar neutrinos. The major role that neutrinos play in astrophysics and cosmology is illustrated.
Carotid Plaque 3D Compound Imaging and Echo-Morphology Analysis: a Bayesian Approach

This paper describes a method for volume reconstruction of the carotid plaque and presents a novel local characterization of its echo-morphology. The data is composed by a series of nearly parallel ultrasound images (3D Compound Imaging) and the acquisition is performed using traditional noninvasive ultrasound equipment available in most medical facilities, without need of a spatial locator device. The reconstruction algorithm uses the observed pixels inside the plaque, which were obtained in a pre-segmentation stage performed under medical guidance [1]. The paper proposes a Bayesian algorithm which estimates the underlying volume inside the plaque, by filtering and interpolating the data in order to remove speckle noise and fill non- observed regions, respectively. This volume is further used in plaque echo-morphology analysis. The observation model is based on the Rayleigh distribution, commonly used to model speckle noise in ultrasound images. A prior model based on the edge preserving Total Variation Gibbs distribution is also used to fill the gaps on non-evenly spaced observations. An energy function is derived from these models and an iterative algorithm computes its minimizer. The estimated function, defined in a given volume of interest, is used in global and local plaque characterization, namely to estimate its average levels of stenosis, echo-morphology and to identify vulnerable foci inside the plaque. The goal is to make atherosclerosis diagnosis more accurate and complete than using traditional 2D ultrasound analysis.
3D Modeling of Building Indoor Spaces and Closed Doors from Imagery and Point Clouds

3D models of indoor environments are increasingly gaining importance due to the wide range of applications to which they can be subjected: from redesign and visualization to monitoring and simulation. These models usually exist only for newly constructed buildings; therefore, the development of automatic approaches for reconstructing 3D indoors from imagery and/or point clouds can make the process easier, faster and cheaper. Among the constructive elements defining a building interior, doors are very common elements and their detection can be very useful either for knowing the environment structure, to perform an efficient navigation or to plan appropriate evacuation routes. The fact that doors are topologically connected to walls by being coplanar, together with the unavoidable presence of clutter and occlusions indoors, increases the inherent complexity of the automation of the recognition process. In this work, we present a pipeline of techniques used for the reconstruction and interpretation of building interiors based on point clouds and images. The methodology analyses the visibility problem of indoor environments and goes in depth with door candidate detection. The presented approach is tested in real data sets showing its potential with a high door detection rate and applicability for robust and efficient envelope reconstruction.
From the Cajal alumni Achúcarro and Río-Hortega to the rediscovery of never-resting microglia

Under the guidance of Ramón y Cajal, a plethora of students flourished and began to apply his silver impregnation methods to study brain cells other than neurons: the neuroglia. In the first decades of the twentieth century, Nicolás Achúcarro was one of the first researchers to visualize the brain cells with phagocytic capacity that we know today as microglia. Later, his pupil Pío del Río-Hortega developed modifications of Achúcarro's methods and was able to specifically observe the fine morphological intricacies of microglia. These findings contradicted Cajal's own views on cells that he thought belonged to the same class as oligodendroglia (the so called “third element” of the nervous system), leading to a long-standing discussion. It was only in 1924 that Río-Hortega's observations prevailed worldwide, thus recognizing microglia as a unique cell type. This late landing in the Neuroscience arena still has repercussions in the twenty first century, as microglia remain one of the least understood cell populations of the healthy brain. For decades, microglia in normal, physiological conditions in the adult brain were considered to be merely “resting,” and their contribution as “activated” cells to the neuroinflammatory response in pathological conditions mostly detrimental. It was not until microglia were imaged in real time in the intact brain using two-photon in vivo imaging that the extreme motility of their fine processes was revealed. These findings led to a conceptual revolution in the field: “resting” microglia are constantly surveying the brain parenchyma in normal physiological conditions. Today, following Cajal's school of thought, structural and functional investigations of microglial morphology, dynamics, and relationships with neurons and other glial cells are experiencing a renaissance and we stand at the brink of discovering new roles for these unique immune cells in the healthy brain, an essential step to understand their causal relationship to diseases.
On the Construction of Finite Oscillator Dictionary

A finite oscillator dictionary which has important applications in sequences designs and the compressive sensing was introduced by Gurevich, Hadani, and Sochen in [3]. In this paper, closed formulae of the finite split oscillator dictionary 𝔖 s are revisited by a simple proof, the structure of nonsplit tori of the group SL(2, 𝔽 p ) is studied, and an explicit algorithm for computing the finite nonsplit oscillator dictionary 𝔖 ns is described.
Investigating deception in second language speakers: Interviewee and assessor perspectives

Method. For the first experiment, 52 participants told the truth or lied about their identity during a mock border control interview. All of the participants were interviewed in English, for half of the sample this was their native language, and for the other half of the sample English was not their native tongue. Post-interview, all participants completed a self-report questionnaire relating to their perceptions of their interview experience. For the second experiment, 128 participants evaluated the credibility of interviewees from the first experiment. The modality of presentation of interview clips was varied and included ‘Visual and Audio’, ‘Visual Only’, ‘Audio Only’, and ‘Transcript Only’.
Combining Krawtchouk Moments and HMMs for Offline Handwritten Chinese Character Recognition

This paper proposes an approach combining the set of Krawtchouk moments and HMMs (hidden Markov models) for unconstrained offline handwritten Chinese character recognition. The Krawtchouk moments can be effectively used as pattern features in analysis of two-dimensional images. Since the basis set is orthogonal in the discrete domain of the image coordinate space, the implementation of Krawtchouk moments doesn't involve any numerical approximation or coordinate transformation. This property makes Krawtchouk moments superior to conventional, more continuous moments such as Legendre moments and Zernike moments. In the field of character recognition, HMMs architecture has been used widely because of its strong adaptability to written distortion and variability. In this paper, Krawtchouk moments and HMMs are combined to recognize unconstrained offline handwritten Chinese amount in words. Experiments show that the average recognition of Krawtchouk is higher than Zernike and Legendre moments within the HMM framework
Conducting a culturally informed neuropsychological evaluation

http://dx.doi. org/10.1037/15958-001 Conducting a Culturally Informed Neuropsychological Evaluation, by D. Fujii Copyright © 2017 by the American Psychological Association. All rights reserved. Clinical neuropsychologists are well versed in the technical, rote processes of conducting a neuropsychological evaluation. However, neuropsychology is not simply reporting test scores. To be a good neuropsychologist, one must first be a good psychologist, part of which entails making context-dependent clinical judgments. Understanding a client’s background is imperative for collecting accurate data and interpreting it to make useful recommendations. This can be challenging with any client, but especially so with a client from a cultural background different from that of the neuropsychologist. The following example illustrates a scenario that a neuropsychologist might encounter when evaluating a culturally different client (CDC). Maria is a 34-year-old Mexican American woman who sustained a seizure of unknown origin while riding the bus on her way home from her job as a seamstress. She was referred to Dr. Neil for neuropsychological testing to clear her for return to work. Maria is highly motivated to return to work INTRODUCTION
Integrating UML/OCL Derived Properties into Validation and Verification Processes

UML and OCL are rich languages offering a multitude of modeling elements. They provide modelers with simple and effective tools to express and visualize models, but their complex semantics are a great challenge for validation and verification processes, which are often limited by their underlying logic. On the basis of a network topology example model, describing lower physical and logical network levels, we demonstrate applications of derived attributes and associations that help checking network security aspects. This includes finding inconsistencies in an existing network, directing to potential configuration errors and property evaluation, e.g. reachability between components within the network. In addition, a transformation of derived properties into relational logic is presented to enable the use of a modern instance finder for further verification tasks and generation of valid networks configurations.
Carbohydrate intake, obesity, metabolic syndrome and cancer risk? A two-part systematic review and meta-analysis protocol to estimate attributability

Introduction Linkages between carbohydrates, obesity and cancer continue to demonstrate conflicting results. Evidence suggests inconclusive direct linkages between carbohydrates and specific cancers. Conversely, obesity has been strongly linked to a wide range of cancers. The purpose of the study is to explore linkages between carbohydrate intake and cancer types using a two-step approach. First the study will evaluate the linkages between carbohydrate intake and obesity, potentially stratified by metabolic syndrome status. Second, the estimated attributable fraction of obesity ascribed to carbohydrate intake will be multiplied against obesity attributable fractions for cancer types to give estimated overall attributable fraction for carbohydrate versus cancer type. Methods and analysis We will perform a comprehensive search to identify all possible published and unpublished studies that have assessed risk factors for obesity including dietary carbohydrate intake. Scientific databases, namely PubMed MEDLINE, EMBASE, EBSCOhost and ISI Web of Science will be searched. Following study selection, paper/data acquisition, and data extraction and synthesis, we will appraise the quality of studies and risk of bias, as well as assess heterogeneity. Meta-weighted attributable fractions of obesity due to carbohydrate intake will be estimated after adjusting for other potential confounding factors (eg, physical inactivity, other dietary intake). Furthermore, previously published systematic reviews assessing the cancer-specific risk associated with obesity will also be drawn. These estimates will be linked with the attributability of carbohydrate intake in part 1 to estimate the cancer-specific burden that can be attributed to dietary carbohydrates. This systematic review protocol has been developed according to the ‘Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P) 2015’. Ethics and dissemination The current study will be based on published literature and data, and, as such, ethics approval is not required. The final results of this two part systematic review (plus multiplicative calculations) will be published in a relevant international peer-reviewed journal. Trial registration number PROSPERO CRD42015023257.
Validity and repeatability of the EPIC-Norfolk Physical Activity Questionnaire.

BACKGROUND Physical activity is an important lifestyle which is often poorly assessed in epidemiological studies. The European Prospective Investigation into Cancer Study-Norfolk cohort (EPIC-Norfolk), a large population-based cohort study, has developed a comprehensive questionnaire to assess activity in different domains of life aimed at assessing total energy expenditure. We report the repeatability of this instrument and its validity against repeated objective measures of fitness and energy expenditure undertaken throughout the time frame of reference of the questionnaire. METHODS The validity of the instrument was measured in 173 individuals randomly selected from a continuing population-based cohort study. Energy expenditure was assessed by four separate episodes of 4-day heart-rate monitoring, a method previously validated against whole body calorimetry and doubly-labelled water. Cardio-respiratory fitness was assessed by four repeated measures of sub-maximum oxygen uptake. At the end of the 12-month period, participants completed the physical activity questionnaire that assesses past-year activity at home, work and in recreation. Repeatability was assessed in a separate group of 399 randomly selected participants in EPIC who completed the physical activity questionnaire twice with a 3-month interval. RESULTS The age- and sex-adjusted correlation between the objective measure of daytime energy expenditure and the sum of recreational and occupational reported physical activity (in MET h per week) was 0.28 (P < 0.001). The reported time spent in vigorous activity was correlated with cardio-respiratory fitness (0.16, P < 0.05) and with the proportion of time when energy expenditure was more than five times basal (0.17, P < 0.05). The repeatability of the sum of recreational and occupational reported activity was high, r = 0.73. CONCLUSIONS The indices of physical activity derived from this questionnaire have levels of validity and repeatability comparable to other physical activity instruments that are used in large epidemiological studies and which have undergone such intense development and testing.
Prenatal Polybrominated Diphenyl Ether Exposure and Body Mass Index in Children Up To 8 Years of Age

Background: Prenatal exposure to endocrine disruptors has been associated with increased risk of childhood obesity. However, epidemiologic studies on polybrominated diphenyl ethers (PBDEs) are limited despite animal studies indicating PBDEs’ potential role as an obesogen. Objectives: We investigated whether maternal concentrations of BDEs 28, 47, 99, 100, 153, and ΣPBDEs during pregnancy were associated with anthropometric measures in children aged 1–8 years. Methods: We examined 318 mother–child pairs in the Health Outcomes and Measures of the Environment (HOME) Study, a birth cohort enrolled from 2003 through 2006 (Cincinnati, OH). Serum PBDEs were measured at 16 ± 3 weeks gestation. We measured child height (1–8 years), weight (1–8 years), body mass index (BMI) (2–8 years), waist circumference (4–8 years), and body fat (8 years). To account for repeated measures, we used linear mixed models and generalized estimating equations to estimate associations between maternal PBDEs and child anthropometric measures. Results: We found no statistically significant associations between prenatal PBDEs and height or weight z-score. A 10-fold increase in maternal serum BDE-153 was associated with lower BMI z-score (β = –0.36; 95% CI: –0.60, –0.13) at 2–8 years, smaller waist circumference (β = –1.81 cm; 95% CI: –3.13, –0.50) at 4–8 years, and lower percent body fat (β = –2.37%; 95% CI: –4.21, –0.53) at 8 years. A decrease in waist circumference at 4–8 years was observed with a 10-fold increase in BDE-100 (β = –1.50 cm; 95% CI: –2.93, –0.08) and ΣPBDEs (β = –1.57 cm; 95% CI: –3.11, –0.02). Conclusions: Reverse causality may have resulted in prenatal PBDEs, particularly BDE-153, and decreased BMI, waist circumference, and body fat. Citation: Vuong AM, Braun JM, Sjödin A, Webster GM, Yolton K, Lanphear BP, Chen A. 2016. Prenatal polybrominated diphenyl ether exposure and body mass index in children up to 8 years of age. Environ Health Perspect 124:1891–1897; http://dx.doi. org/10.1289/EHP139