Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of the radio-loud galaxy population

A catalogue of 14453 radio-loud active galactic nuclei (AGN) with 1.4 GHz fluxes above 3.5 mJy in the redshift range 0.4 < z < 0.8, has been constructed from the cross-correlation of the National Radio Astronomy Observatory Very Large Array Sky Survey (NVSS) and Faint Images of the Radio Sky at Twenty centimetres (FIRST) radio surveys with the MegaZ-luminous red galaxy (MegaZ-LRG) catalogue of LRGs derived from Sloan Digital Sky Survey imaging data. The NVSS provides accurate flux measurements for extended sources, while the angular resolution of FIRST allows the host galaxy to be identified accurately. New techniques were developed for extending the cross-correlation algorithm to FIRST detections that are below the nominal 1 mJy signal-to-noise ratio limit of the catalogued sources. The matching criteria were tested and refined using Monte Carlo simulations, leading to an estimated reliability of ∼98.3 per cent and completeness level (for LRGs) of about 95 per cent for our new catalogue. We present a new determination of the luminosity function of radio AGN at z ∼ 0.55 and compare this to the luminosity function of nearby (z ∼ 0.1) radio sources from the Sloan Digital Sky Survey main survey. The comoving number density of radio AGN with luminosities less than 10 25 W Hz -1 increases by a factor of ∼1.5 between z = 0.1 and 0.55. At higher luminosities, this factor increases sharply, reaching values of more than 10 at radio luminosities larger than 10 26 W Hz -1 . We then study how the relation between radio AGN and their host galaxies evolves with redshift. Our main conclusion is that the fraction of radio-loud AGN increases towards higher redshift in all massive galaxies, but the evolution is particularly strong for the lower mass galaxies in our sample. These trends may be understood if there are two classes of radio galaxies (likely associated with the 'radio' and 'quasar mode' dichotomy) that have different fuelling/triggering mechanisms and hence evolve in different ways.
Measuring RF‐induced currents inside implants: Impact of device configuration on MRI safety of cardiac pacemaker leads

Radiofrequency (RF)‐related heating of cardiac pacemaker leads is a serious concern in magnetic resonance imaging (MRI). Recent investigations suggest such heating to be strongly dependent on an implant's position within the surrounding medium, but this issue is currently poorly understood. In this study, phantom measurements of the RF‐induced electric currents inside a pacemaker lead were performed to investigate the impact of the device position and lead configuration on the amount of MRI‐related heating at the lead tip. Seven hundred twenty device position/lead path configurations were investigated. The results show that certain configurations are associated with a highly increased risk to develop MRI‐induced heating, whereas various configurations do not show any significant heating. It was possible to precisely infer implant heating on the basis of current intensity values measured inside a pacemaker lead. Device position and lead configuration relative to the surrounding medium are crucial to the amount of RF‐induced heating in MRI. This indicates that a considerable number of implanted devices may incidentally not develop severe heating in MRI because of their specific configuration in the body. Small variations in configuration can, however, strongly increase the risk for such heating effects, meaning that hazardous situations might appear during MRI. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.
An approach for virtual machine image security

Cloud security being the main hindrance in adoption of cloud computing has some most vulnerable security concerns as: virtualization, data and storage. Here, to provide virtualization security, the components of virtualization (such as hypervisors, virtual machines, and virtual machine images) must be secured using some improvised security mechanisms. Amongst all components, Virtual machine images (VM images) are considered to be the fundamental of whole cloud security. Hence must be secured from every possible attack. In this paper, a security protocol is proposed to mainly protect the VM images from two of the possible attacks. One is the channel attack like man-in-the-middle attack (MITM attack) and second is the attack by a malicious executing environment. It is using a concept of symmetric key's component distribution providing an integrity based confidentiality and self-protection. This protection is based on an encapsulated mobile agent. Here one key component is generated and distributed in a secure manner and the other key component is derived by host platform itself using its own available resource configuration information. In order to verify the validity of this approach in overcoming different kind of security attacks, BAN logic based formal representation is presented.
Abductive Completion of Plan Sketches

Most work on AI planning has focused on the development of fully automated methods for generating plans that satisfy user-specified goals. However, users in many domains want the ability to influence the nature of the solutions that are generated. With the objective of fostering increased user participation in the planning process, this paper presents an HTN-based framework for the abductive completion of plan sketches. Within this framework, user-supplied outlines of partial plans (possibly spanning multiple abstraction levels) are interpreted and completed. The processing of plan sketches employs an initial abductive plan recognition phase to formulate candidate sets of intended user goals, followed by a plan refinement stage that generates sketch-compliant final plans for those goals. A prototype sketch-based planner based on this approach has been implemented and applied to a crisis action planning domain.
In vitro 3D Spheroids and Microtissues: ATP-based Cell Viability and Toxicity Assays

In vitro models continuously evolve to more closely mimic and predict biological responses of living organisms. Just in the past years many novel three dimensional (3D) organotypic models, which resemble tissue structure, function and even disease progression, have been developed. However, application of more complex models and technologies may increase the risk of compromising assay robustness and reproducibility. Consequently, the first developmental stage of cell-based assays is to combine complex tissue models with standard assays a combination that already provides more physiologically insightful information when compared to twodimensional (2D) systems. The final goal should be to exploit the full potential of tissue-like in vitro models by investigating them with modern assays such as –Omics and imaging technologies. Furthermore, organotypic models will allow for a design of novel assay concepts that utilize the whole tool box of models and endpoints. In this chapter we focus on assessment of spheroid viability by measuring intracellular ATP content. This primary assay performed on 3D cell culture system is a powerful tool to predict with high confidence health, growth and energy status of tissue of interest. The 3D spheroid model is particularly useful to mimic solid-tumors from a physiologically relevant architectural perspective, when they are grown with multiple cell types prevalent in these tumors. However, this assay is equally applicable for other non-spheroid 3D tissue models to quantify viability and toxicity. Asay G uance M aual
Marketing de relaciones: un análisis del contenido de sus fundamentos teóricos

El proposito del presente trabajo de investigacion es analizar los fundamentos teoricos del Marketing de Relaciones, concretamente identificar las Ciencias Sociales, ya sean las Ciencias de la Sociologia, Psicologia, Economicas, Politicas, Organizacionales y de la Comunicacion y ver como han influido en el desarrollo teorico del nuevo Paradigma del Marketing. Mediante un analisis de contenido en diversos trabajos de investigacion pudimos comprobar que las distintas Ciencias han contribuido de alguna manera para asentar las bases del Marketing de Relaciones.
Three-dimensional interest point detection and description using Speeded-Up Robust Features and histograms of oriented points

This article presents a novel systematic methodology for the detection of interest points in 3D point clouds and its corresponding descriptors by using the information of an RGB camera and a structured-light sensor. This is achieved by fusing Speeded-Up Robust Features (SURF) in the image space, and histograms that statistically represent the relationship of three dimensional geometric data around the interest points. The SURF algorithm is implemented over an image whose pixel coordinates have a direct corresponding 3D point, thus allowing the fusion of both approaches. By combining both methodologies, it is intent to define a set of interest points whose descriptors are able to maintain the intrinsic characteristics of its constituent parts such as repeatability, distinctiveness and robustness while remaining compact and fast to compute. The detected points will be use for both, localization and mapping of mobile robots in partially unknown environments.
Spline curve matching with sparse knot sets: applications to deformable shape detection and recognition

Splines can be used to approximate noisy data with a few control points. This paper presents a new curve matching method for deformable shapes using two-dimensional splines. In contrast to the residual error criterion [F.S. Cohen et al., 1992], which is based on relative locations of corresponding knot points such that is reliable primarily for dense point sets, we use deformation energy of thin-plate-spline mapping between sparse knot points and normalized local curvature information. This method has been tested successfully for the detection and recognition of deformable shapes.
Security and Privacy in E-Healthcare Monitoring with WBAN: A Critical Review

In the current scenario Wireless Body Area network (WBAN) has made its prominent place among technological advancements to improve human health. Since WBAN uses a wireless technique for communication, it has various positive & striking features such as its unattended nature, unobtrusiveness, mobility and cost effectiveness. These WBANs are extremely essential for people with severe diseases. For example, Heart patients, pregnant women, mentally challenged people, etc. need a continuous observation. Thus, WBAN, on the one hand, is working as a virtual safeguard for its users. WBAN, on the other hand, exploits wireless media during its realization. All the constraints specially related to insecurity (openness) have also been elaborated here. Since health related information is tremendously crucial and confidential and also liable to the patient’s life. Therefore, we need to take care of mechanisms applied to WBANs to overcome all the issues and drawbacks related to security and privacy. This paper focuses on various limitations and their possible solutions available within WBANs in order to provide secure and private information management to its dependents and users.
An Artificial Emotion Imitator

In the last decade, face analysis, e.g. face recognition, face detection, face tracking, facial expression recognition, is a very lively and expanding research field. As computer animated agents and robots bring a social dimension to human computer interaction, interest in this research field is increasing rapidly. In this paper, we introduce an artificial emotion mimic system which can recognize human facial expressions and also imitate the recognized facial expression. And also we propose a classifier that is based on weak classifiers obtained by using modified rectangular features to recognize human facial expression in real-time. Next, we introduce our robot that is manipulated by a distributed control algorithm. Finally, experimental results of facial expression recognition and emotion expression are shown for the validity of our artificial emotion imitator. Keywordsfacial expression recognition; AdaBoost; emotionexpression; face detection; active vision
A Novel Italic Detection and Rectification Method for Chinese Advertising Images

The italic detection and slant rectification is a key step of optical character recognition (OCR). In this paper, a novel method is proposed to detect and rectify italic characters in Chinese advertising images. Based on observations on structures of many characters, the centroid angle is proposed and a statistical study on it is presented. According to the statistical results, the centroid angle of a Chinese character approximately obeys a Gaussian distribution with its slant angle. Moreover, a Markov Random Field (MRF) model, considering the font-face similarity of neighboring characters and the strong correlation between the centroid angle and the slant angle of a character, is then presented to estimate the slant angle of a character. The italic characters can be detected and rectified by the estimated angle. The experimental results demonstrate the proposed method is effective and applicable.
A 695 pW standby power optical wake-up receiver for wireless sensor nodes

We propose an ultra-low power optical wake-up receiver with a novel front-end circuit and communication scheme suitable for miniature wireless sensor node applications. Named “FLOW” for Free-space Low-Power Optical Wake-up, the receiver consumes 695pW in standby mode, which is ~6,000× lower than previously reported RF and ultrasound wake-up radios. In active mode, it consumes 140pJ/bit at 91bps. A pulse width modulated communication encoding scheme is used, and chip-ID masking enables selective batch-programming and synchronization of multiple sensor nodes.
A Hybrid Method for Feature Selection Based on Mutual Information and Canonical Correlation Analysis

Mutual Information (MI) is a classical and widely used dependence measure that generally can serve as a good feature selection algorithm. However, under-sampled classes or rare but certain relations are overlooked by this measure, which can result in missing relevant features that could be very predictive of variables of interest, such as certain phenotypes or disorders in biomedical research, rare but dangerous factors in ecology, intrusions in network systems, etc. On the other hand, Kernel Canonical Correlation Analysis (KCCA) is a nonlinear correlation measure effectively used to detect independence but its use for feature selection or ranking is limited due to the fact that its formulation is not intended to measure the amount of information (entropy) of the dependence. In this paper, we propose Predictive Mutual Information (PMI), a hybrid measure of relevance not only is based on MI but also accounts for predictability of signals from one another as in KCCA. We show that PMI has more improved feature detection capability than MI and KCCA, especially in catching suspicious coincidences that are rare but potentially important not only for subsequent experimental studies but also for building computational predictive models which is demonstrated on two toy datasets and a real intrusion detection system dataset.
The President’s Expression: Analyzing the Psychological Aspects of Susilo Bambang Yudhoyono’s Lyrics

Word and text analysis has become an alternative method to examine social and psychological problems when other common methods could not access the internal workings of a participant’s psyche. This study shows that text analysis, as an alternative method, is capable to identify important psychological aspects contained in the song lyrics written by Susilo Bambang Yudhoyono (SBY) with regard to his strategic role as a country and political leader. Three main aspects are identified: emotion, achievement, and harmony. The lyrics of 23 Indonesian songs written by SBY have been gathered for the purpose of analysis. Three studies were carried out to analyze the psychological aspects contained in SBY’s song lyrics. Firstly, the author applied algoritma kata (AK – word algorithm) to identify the degrees of valence and arousal in each song using the word count method. Secondly, the author applied analisis lirik keseluruhan (ALK – the whole lyric analysis) to assess the valence and arousal in every song by means of human judgment. Third, the author applied expert judgment (EJ) to analyze the dominant words that emerge in all song lyrics. This study shows that SBY’s song albums have consistently shown a positive valence and an increasing level of arousal from 2006 to 2014. In addition to that, EJ method shows that those dominant words represent SBY’s two most prominent psychological aspects: achievement and harmony.
Automatic Approach to Understanding Mathematical Expressions Using MathML Parallel Markup Corpora (人工知能学会全国大会(第26回)文化,科学技術と未来) -- (International Organized Session「Application Oriented Principles of Machine Learning and Data Mining」)

This paper explores the use of MathML Parallel Markup Corpora for automatic understanding of mathematical expressions, the task of which is formulated as a translation from Presentation to Content MathML Markups. In contrast to previous research that mainly relied on manually encoded transformation rules, we use a statisticalmachine-translation-based method to automatically extract translation rules from parallel markup corpora. Our study shows that the structural features embedded in the MathML tree can be effectively exploited in the subtree alignment and the translation rules extracted from the alignment give a boost to the translation system. Experimental results on the Wolfram Function Site show that our approach is an improvement over a prior rulebased system.
Preventive analgesia in thoracic surgery: controlled, randomized, double-blinded study.

OBJECTIVES Preventive analgesia is defined as a treatment that is commenced before the surgical procedure in order to diminish the physiological consequences of afferent nociceptive transmission caused by the procedure and prevent central sensitization. The analysis of randomized studies of preventive analgesia is controversial. The aim of this study was to check the analgesic efficacy of preoperative administration of dextromethorphan associated with intercostal nerve block with levobupivacaine in thoracotomy patients who refused or had a contraindication to epidural analgesia. METHODS This study was a four-arm, double-blinded, randomized placebo-controlled trial. Patients were allocated following close block randomization into four arms: 'Group A' preoperative dextromethorphan and preoperative intercostal block (IB), 'Group B' preoperative placebo and preoperative IB, 'Group C' preoperative dextromethorphan and postoperative IB, 'Group D' preoperative placebo and postoperative block. The primary end-point was the cumulative morphine consumption (CMC) within the first 14 days after surgery. RESULTS A total of 400 patients were enrolled and 395 completed the study. There were no statistical differences among the groups in terms of demographic and surgical data; in contrast, preoperative quality-of-life scores were heterogeneous. The mean CMCs were as follows: Group A 111.4 mg, Group B 121.5 mg, Group C 126.8 mg, Group D 138.3 mg. Group A mean was lower than the maximum (P = 0.0001). The CMC value did not correlate with age, sex, body mass index, education, type of surgery, length or width of the incision and rib fracture. Postoperative functional data and post-thoracotomy syndrome prevalence were homogeneous; female gender resulted predictive for post-thoracotomy syndrome. CONCLUSIONS Results indicate that preoperative administration of dextromethorphan associated with preoperative IB with levobupivacaine provided preventive analgesia, decreasing analgesic administration during the early postoperative period compared with placebo and/or postoperative IB. This study failed in detecting any effect of preventive analgesia on functional items and post-thoracotomy syndrome.
Generalized covariation and extended Fukushima decompositions for Banach valued processes. Application to windows of Dirichlet processes.

This paper concerns a class of Banach valued processes which have finite quadratic variation. The notion introduced here generalizes the classical one, of Metivier and Pellaumail which is quite restrictive. We make use of the notion of $\chi$-covariation which is a generalized notion of covariation for processes with values in two Banach spaces $B_{1}$ and $B_{2}$. $\chi$ refers to a suitable subspace of the dual of the projective tensor product of $B_{1}$ and $B_{2}$. We investigate some $C^{1}$ type transformations for various classes of stochastic processes admitting a $\chi$-quadratic variation and related properties. If $\X^1$ and $\X^2$ admit a $\chi$-covariation, $F^i: B_i \rightarrow \R$, $i = 1, 2$ are of class $C^1$ with some supplementary assumptions then the covariation of the real processes $F^1(\X^1)$ and $F^2(\X^2)$ exist. \\ A detailed analysis will be devoted to the so-called window processes. Let $X$ be a real continuous process; the $C([-\tau,0])$-valued process $X(\cdot)$ defined by $X_t(y) = X_{t+y}$, where $y \in [-\tau,0]$, is called {\it window} process. Special attention is given to transformations of window processes associated with Dirichlet and weak Dirichlet processes. In fact we aim to generalize the following properties valid for $B=\R$. If $\X=X$ is a real valued Dirichlet process and $F:B \rightarrow \R$ of class $C^{1}(B)$ then $F(\X)$ is still a Dirichlet process. If $\X=X$ is a weak Dirichlet process with finite quadratic variation, and $F: C^{0,1}([0,T]\times B)$ is of class $C^{0,1}$, then $[ F(t, \X_t) ] $ is a weak Dirichlet process. We specify corresponding results when $B=C([-\tau,0])$ and $\X=X(\cdot)$. This will consitute a significant Fukushima decomposition for functionals of windows of (weak) Dirichlet processes. As applications, we give a new technique for representing path-dependent random variables.
Another look at Swedish business cycles, 1861–1988

This paper considers nine long Swedish macroeconomic time series whose business cycle properties were discussed by Englund, Persson, and Svensson (1992) using frequency domain techniques. It is found by testing that all but two of the logarithmed and differenced series are nonlinear. The observed nonlinearity is characterized by STAR models. The statistical and dynamic properties of the estimated STAR models are investigated using, among other things, parametrically estimated 'local' or 'sliced' spectra. Cyclical variation at business cycle frequencies does not seem to be constant over time for all series, and it is difficult to find a 'Swedish business cycle'. Only two series may be regarded as having genuinely asymmetric cyclical variation. Standard Granger noncausality tests are adapted to the nonlinear (STAR) case, and the null hypothesis of noncausality is tested for pairs of series. The results point at strong temporal interactions between series. They also indicate that the assumption of functional form (linear or STAR) strongly affects the outcome of these pairwise tests.