Miracle-dz/UniFAR-FTUs huggingface dataset:
STATUS OF THIS MEMO Sampling of the Group Membership in RTP

In large multicast groups, the size of the group membership table maintained by RTP (Real Time Transport Protocol) participants may become unwieldy, particularly for embedded devices with limited memory and processing power. This document discusses mechanisms for sampling of this group membership table in order to reduce the memory requirements. Several mechanisms are proposed, and the performance of each is considered.
Arc Statistics with Realistic Cluster Potentials. I. Method and First Results

{}From the lensing properties of a numerically simulated cluster, from the statistical properties of the giant arcs produced by the cluster, and from comparing the cluster properties derived both from lensing and from the X-ray properties of the intracluster gas, we conclude (1) that clusters may be significantly more efficient for lensing than estimated from their velocity dispersion on the basis of iso- thermal-sphere models, (2) that the discrepancy between cluster core radii derived from lensing and from their X-ray surface brightness may be understood assuming that the intracluster gas was expelled from the cluster galaxies when the dark `body' of the cluster had already formed, and (3) that clusters may be efficient in producing giant arcs even if they have extended cores and a fairly shallow sur- face-density profile. This may mean that arcs may be much easier to produce, and therefore more abundant, than previously estimated.
Correlating Neuropsychiatric Symptoms with Regional Beta-Amyloid Load in the Alzheimer’s Disease Brain Using [11C]SB-13 Positron Emission Tomography

Correlations between neuropsychiatric symptoms and beta-amyloid (Aβ) burden in specific brain regions in living Alzheimer’s disease (AD) patients remain to be elucidated. Ten mild AD patients underwent MR and [ 11 C]SB-13 PET imaging. Neuropsychiatric symptoms were quantified with the Neuropsychiatric Inventory (NPI). NPI-depression/dysphoria, -apathy, agitation/aggression, -anxiety, and -appetite/eating disorders scores were hypothesized to correlate with Aβ burden in particular brain regions. Pearson’s correlation coefficient revealed that depression/dysphoria scores positively correlated (p<0.05) with standardized uptake values (SUVs) from left medial temporal lobe (r=0.67), and agitation/aggression correlated with SUVs from bilateral anterior cingulate (right, r=0.71; left, r=0.78), temporal (right, r=0.71; left, r=0.75), parietal (right, r=0.77; left, r=0.81), and dorsolateral prefrontal cortex (right, r=0.74; left, r=0.73). However, NPI scores did not significantly correlate with better estimates of Aβ burden that use the cerebellum as reference region. Overall, our results confirm the lack of association between Aβ burden and neuropsychiatric symptoms reported in autopsy studies.
A cloud-based recommendation model

The recommendation systems aim to minimize information overload by helping user's in searching desired information. Faced with this scenario, we investigate the use of cloud factors able to have a positive influence on generating recommendations. Thus, we present a new, simple model based on cloud features which is associated with the content-based technique of recommendation. The practical applicability of data storage environments in the cloud provides the best use of cloud resources and meets user's preferences.
A tandem affinity purification tag of TGA2 for isolation of interacting proteins in Arabidopsis thaliana

Tandem affinity purification (TAP) tagging provides a powerful tool for isolating interacting proteins in vivo. TAP-tag purification offers particular advantages for the identification of stimulus-induced protein interactions. Type II bZIP transcription factors (TGA2, TGA5 and TGA6) play key roles in pathways that control salicylic acid, ethylene, xenobiotic and reactive oxylipin signaling. Although proteins interacting with these transcription factors have been identified through genetic and yeast 2-hybrid screening, others are still elusive. We have therefore generated a C-terminal TAP-tag of TGA2 to isolate additional proteins that interact with this transcription factor. Three lines most highly expressing TAP-tagged TGA2 were functional in that they partially complemented reactive oxylipin-responsive gene expression in a tga2 tga5 tga6 triple mutant. TAP-tagged TGA2 in the most strongly overexpressing line was proteolytically less stable than in the other 2 lines. Only this overexpressing line could be used in a 2-step purification process, resulting in isolation of co-purifying bands of larger molecular weight than TGA2. TAP-tagged TGA2 was used to pull down NPR1, a protein known to interact with this transcription factor. Mass spectrometry was used to identify peptides that co-purified with TAP-tagged TGA2. Having generated this TGA2 TAP-tag line will therefore be an asset to researchers interested in stimulus-induced signal transduction processes.
Photometric stereo through an adapted alternation approach

Photometric stereo aims at finding the surface normal and reflectance at every point of an object from a set of images obtained under different lighting conditions. The obtained intensity image data are stacked into a matrix that can be approximated by a low-dimensional linear subspace, under the Lambertian model. The current paper proposes to use an adaptation of the Alternation technique to tackle this problem when the images contain missing data, which correspond to pixels in shadow and saturated regions. Experimental results considering both synthetic and real images show the good performance of the proposed Alternation-based strategy.
Distributed consensus-based tracking in Wireless Sensor Networks: A practical approach

Tracking is a key application in Wireless Sensor and Ad-hoc Networks. The development of distributed, energy-efficient strategies for target tracking is of practical importance. In this contribution we propose a distributed tracking strategy based on cooperative localization using consensus. Nodes do not need to care about the network topology or the number of nodes present in the network. They use their own measurements as well as the jointly estimated position of the target in order to track it. The proposed approach appears to be robust against small errors in the node positions as well as in the presence of biased or misbehaving nodes.
Estimating site amplification factors from ambient noise

We present a methodology to obtain frequency‐dependent relative site amplification factors using ambient seismic noise. We treat a seismic network or array as a forced damped harmonic oscillator system where each station responds to a forcing function obtained from frequency‐wavenumber beams of the ambient noise field. A network or array beam is necessary to estimate the forcing function. Taken over long time periods, each station responds to the forcing function showing a frequency‐dependent resonance peak whose amplitude and spectral width depends upon the elastic and anelastic properties of the underlying medium. Our results are encouraging in that hard rock sites show little variability and have narrower resonance peaks with reduced amplitudes relative to soft rock sites in sedimentary basins. There is much more variability observed at soft rock sites and a tendency for spectral peaks to shift to higher frequencies and become broader as the site amplification increases. This could be due to due to lower densities and/or small‐strain nonlinearity at stations having high site amplification.
Mental illness and addictions: Our responsibility to support the family

Mental health and addictions is a field within the realms of social work practice that appears to be consistently growing. This article seeks to discuss the importance of social work practice with the families that come into contact with mental health and addiction services. It will also draw attention to the questions of whether social workers are effectively supporting and engaging family and how we can work alongside or in partnerships with family. It will seek to highlight the importance of having a clear understanding of the experiences of the family who have been affected by mental illness or addiction in order to more effectively work towards recovery.
Some Benefits of Reducing Inflation in Transition Economies

We analyse welfare effects of the interactions between the tax system and inflation in Poland and in Ukraine, using the framework developed by Feldstein (1997, 1999). This approach stresses the fact that inflation increases distortions created by the tax system, in particular distortions to intertemporal saving decisions. We find that the effects are much smaller in the two transition countries than in developed marketeconomies. The reason is that taxation of investment returns is much more limited. Our results suggest that taxes on investment returns should be avoided in any future redesign of the tax system.
Hybrid millimeter-wave push-push oscillators using silicon-germanium HBTs

Push-push design has proven to be an efficient way to extend the usable frequency range of active devices for oscillator applications. In this paper, the basic principles of push-push oscillator design are explained and various possibilities to realize this concept are shown. Several examples of hybrid millimeter-wave push-push oscillators using SiGe HBTs as active devices are discussed. Details on large-signal modeling of the SiGe HBTs using both a vertical bipolar integrated-circuit model, as well as a customized large-signal model are given. Measured key performance data of microstrip resonator oscillators at 57 and 58 GHz are output power levels of +1 dBm and single-sideband phase-noise figures (1-MHz offset from carrier) of -106 and -108 dBm/Hz, respectively. For the dielectric-resonator oscillators, a maximum output power of -8 dBm and an optimum phase noise of -112 dBc/Hz (-14-dBm output power), as well as a mechanical tuning range of 500 MHz were measured.
Sequential bayesian updating for big data

Author(s): Oravecz, Z; Huentelman, M; Vandekerckhove, J | Editor(s): Jones, M | Abstract: © 2017 Taylor a Francis. The velocity, volume, and variety of Big Data present both challenges and opportunities for cognitive science. We introduce sequential Bayesian updating as a tool to mine these three core properties. In the Bayesian approach, we summarize the current state of knowledge regarding parameters in terms of their posterior distributions, and use these as prior distributions when new data become available. Crucially, we construct posterior distributions in such a way that we avoid having to repeat computing the likelihood of old data as new data become available, allowing the propagation of information without great computational demand. As a result, these Bayesian methods allow continuous inference on voluminous information streams in a timely manner. We illustrate the advantages of sequential Bayesian updating with data from the MindCrowd project, in which crowd-sourced data are used to study Alzheimer’s dementia. We fit an extended LATER (“Linear Approach to Threshold with Ergodic Rate”) model to reaction time data from the project in order to separate two distinct aspects of cognitive functioning: speed of information accumulation and caution.
Two C‐C Family Chemokines, Eotaxin and RANTES, Are Novel Independent Plasma Biomarkers for Abdominal Aortic Aneurysm

Background Inflammation of the aortic wall is recognised as a key pathogenesis of abdominal aortic aneurysm (AAA). This study was undertaken to determine whether inflammatory cytokines could be used as biomarkers for the presence of AAA. Methods and Results Tissue profiles of 27 inflammatory cytokine were examined in AAA (n=14) and nonaneurysmal (n=14) aortic tissues. Three cytokines, regulated upon activation normally T‐cell expressed and secreted (RANTES), eotaxin, and macrophage inflammatory protein 1 beta (MIP‐1b), had increased expression in AAA, particularly within the adventitial layer of the aortic wall. Basic fibroblast growth factor (bFGF) had reduced expression in all layers of the AAA wall. Examination of the circulating plasma profiles of AAA (n=442) and AAA‐free controls (n=970) suggested a (risk factor adjusted) AAA‐association with eotaxin, RANTES, and high sensitivity C‐reactive protein (hsCRP). A plasma inflammatory cytokine score, calculated using these three markers, suggested a strong risk association with AAA (odds ratio, 4.8; 95% CI, 3.5–6.7; P<0.0001), independent of age, sex, history of ischemic heart disease, and smoking. Conclusions Contrary to reports suggesting a distinct T helper 2–associated inflammatory profile in AAA, this current study suggests a more‐generalized pattern of inflammation, albeit with some potentially distinct features, including elevated plasma eotaxin and decreased plasma RANTES. In combination with hsCRP, these markers may have potential utility as AAA biomarkers.
Regular homogeneous T-models with vacuum dark fluid

We present the class of regular homogeneous T-models with vacuum dark fluid, associated with a variable cosmological term. The vacuum fluid is defined by the symmetry of its stress–energy tensor, i.e., its invariance under Lorentz boosts in a distinguished spatial direction (pj = −ρ), which makes this fluid essentially anisotropic and allows its density to evolve. Typical features of homogeneous regular T-models are: the existence of a Killing horizon; beginning of the cosmological evolution from a null bang at the horizon; the existence of a regular static pre-bang region visible to cosmological observers; creation of matter from anisotropic vacuum, accompanied by very rapid isotropization. We study in detail the spherically symmetric regular T-models on the basis of a general exact solution for a mixture of the vacuum fluid and dust-like matter and apply it to give numerical estimates for a particular model which illustrates the ability of cosmological T-models to satisfy the observational constraints.
Fast Density Based Clustering Algorithm

Clustering problem is an unsupervised learning problem. It is a procedure that partition data objects into matching clusters. The data objects in the same cluster are quite similar to each other and dissimilar in the other clusters. The traditional algorithms do not meet the latest multiple requirements simultaneously for objects. Density-based clustering algorithms find clusters based on density of data points in a region. DBSCAN algorithm is one of the density-based clustering algorithms. It can discover clusters with arbitrary shapes and only requires two input parameters.In this paper, we propose a new algorithm based on DBSCAN. We design a new method for automatic parameters generation that create clusters with different densities and generates arbitrary shaped clusters. The kd-tree is used for increasing the memory efficiency. The performance of proposed algorithm is compared with DBSCAN. Experimental results indicate the superiority of proposed algorithm.
ADAPTIVE CVT-BASED REDUCED-ORDER MODELING OF BURGERS EQUATION

In this article, we consider a weighted CVT-based reduced-order modelling for Burgers equation. Brief review of the CVT (centroidal Voronoi tessellation) approaches to reduced-order bases are provided. In CVT-reduced order modelling, we start with a snapshot set just as is done in a POD (Proper Orthogonal Decomposition)-based setting. So far, the CVT was researched with uniform density ( (y) = 1) to determine the basis elements for the approx- imating subspaces. Here, we shall investigate the technique of CVT with nonuniform density as a procedure to determine the basis elements for the approximating subspaces. Some numeri- cal experiments including comparison of two CVT (CVT-uniform and CVT-nonuniform)-based algorithm with numerical results obtained from FEM(finite element method) and POD-based algorithm are reported.
In-Hand Object Pose Estimation Using Covariance-Based Tactile To Geometry Matching

This letter presents a strategy to represent data from a tactile array sensor and match it to an object's geometric features. Using that representation, a method is presented to localise a grasped object within a robot hand. The method consists of computing the covariance matrix in the tactile sensors' pressure data and computing the eigenbasis from its principal axes. A global search is carried out to find a pose in which the object's local geometry in the vicinity of the contact is coherent with that basis, i.e., is aligned with the principal axes and has similar variances. This approach, which can be used as a measurement model for tactile sensors, is compared and outperforms methods using the distance between the tactile sensor elements and object surface.
deFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data

Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes.
g-tries: an efficient data structure for discovering network motifs

In this paper we propose a novel specialized data structure that we call g-trie, designed to deal with collections of subgraphs. The main conceptual idea is akin to a prefix tree in the sense that we take advantage of common topology by constructing a multiway tree where the descendants of a node share a common substructure. We give algorithms to construct a g-trie, to list all stored subgraphs, and to find occurrences on another graph of the subgraphs stored in the g-trie. We evaluate the implementation of this structure and its associated algorithms on a set of representative benchmark biological networks in order to find network motifs. To assess the efficiency of our algorithms we compare their performance with other known network motif algorithms also implemented in the same common platform. Our results show that indeed, g-tries are a feasible, adequate and very efficient data structure for network motifs discovery, clearly outperforming previous algorithms and data structures.
Neural Activation during Covert Processing of Positive Emotional Facial Expressions

Lesion studies indicate distinct neural systems for recognition of facial identity and emotion. Split-brain experiments also suggest that emotional evaluation of a stimulus can occur without conscious identification. The present study tested a hypothesis of a differential neural response, independent of explicit conscious mediation, to emotional compared to nonemotional faces. The experimental paradigm involved holding in mind an image of a face across a 45-s delay while regional cerebral blood flow was measured using positron emission tomography. Prior to the delay, a single face was presented with an explicit instruction to match it to one of two faces, photographed at different angles from the target face, presented at the end of the delay. Repeated blood flow measures were obtained while subjects held happy or neutral faces in mind or during a neutral control fixation condition without initial face presentation. The representation of emotional faces over a delay period, compared to either the nonemotional or the fixation condition, was associated with significant activation in the left ventral prefrontal cortex, the left anterior cingulate cortex, and the right fusiform gyrus. The findings support our hypothesis of a differential neural response to facial emotion, independent of conscious mediation, in regions implicated in the processing of faces and of emotions.
The Birth of the Scientific and Cultural History of Mankind Project

Febvre, Needham and Huxley shared the paternity of the UNESCO's project to publish an Scientific and Cultural History of Mankind (SCHM). The project aimed to give a central part to the sciences and to the techniques in the development of humankind, and to put the exchanges between civilizations into the centre of this history. The project wished to favour the mutual understanding between peoples, which was the proper UNESCO's Charter. The preparation of the project lasted nearly three years, with an astonishing convergence between Needham, Febvre and Huxley. Their project was innovative for the historiographical content as for the methodology, but faced a strong opposition from conservative sectors, whether historians, scientists, or diplomats. The final piece, published by UNESCO in the 1960s, was very far from their project. The following text is the section (1st part of the book) dedicated to the first steps of the SCHM under the aegis of Needham, Febvre, and Huxley
The “1-800 Critique” and the implications of descriptive models of human behavior

It is not always clear how leading theories of human behavior can be used to derive quantitative predictions. Often they are stated with enough qualifications about the applicable domain so that authors might be well advised to supply a 1-800 number for perplexed readers to call when they want to know how a particular theory applies to a novel problem. To demonstrate and address this problem we consider the task of combining theory-based predictions with new observations. We propose a two-stage estimation procedure to derive the initial theory-based prediction for a novel domain, and the best weighting of this initial prediction with accumulating observations. We show that the optimal weighting of the initial prediction and the new data can be summarized with a single number: the model's equivalent number of observations (ENO).
Interns’ perceptions of HR practices and their influence on fit and intentions to join

Abstract This study examines interns’ perceptions of HR practices and their influence on person–organization fit, person–job fit, and intentions to join the organization. The hypotheses are developed with signaling theory and attraction, selection, attrition (ASA) theory. Utilizing a time lagged study design of 71 interns employed in a United States based service firm, we found positive perceptions of HR practices rated early in the internship were related to increased person–organization fit, person–job fit, and intentions to join the organization at the end of the internship. Our findings also showed that person–organization fit and person–job fit fully mediated the relationship between HR practices and intentions to join the organization.