Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultra compact objects in the Fornax cluster of galaxies: Globular clusters or dwarf galaxies?

The relation between the Ultra Compact Objects (hereafter UCOs) recently discovered in the Fornax cluster (Drinkwater et al. [CITE]; Hilker et al. [CITE]) and the brightest globular clusters associated with the central galaxy NGC 1399 has been investigated. The question was adressed whether the UCOs constitute a distinct population of objects not linked to globular clusters or whether there is a smooth transition between both populations. Therefore, a spectroscopic survey on compact objects in the central region of the Fornax cluster was carried out with the 2.5 m du Pont telescope (LCO). UCOs and the bright NGC 1399 globular clusters with similar brightness were inspected. 12 GCs from the bright end of the globular cluster luminosity function have been identified as Fornax members. Eight are new members, four were known as members from before. Their magnitude distribution supports a smooth transition between the faint UCOs and the bright globular clusters. There is no evidence for a magnitude gap between both populations. However, the brightest UCO clearly stands out; it is too bright and too large to be accounted for by globular clusters. For the only UCO included in our survey, a relatively high metallicity of $[\frac{\rm Fe}{\rm H}]\simeq -0.5$ dex is measured.
The impact of naturalization on civic integration: an empirical study on TCNs in Italy

The main objective of this dissertation is that of exploring the relationship between naturalization and civic integration from an empirical standpoint. Most existing studies have focused on the impact of naturalization on the specifically economic dimension of integration, whereas the non-economic aspects have been much more neglected. Here the question of the impact of naturalization is developed with regards to first-generation, third-country nationals (TCNs) residing in Italy, and focusing the attention on civic integration. The latter is provided a working definition characterized by three dimensions (“vertical”, “horizontal” and “subjective”). The research is based on interviews with fifty individuals carried out between 2012 and 2014. Interviews featured both a structured questionnaire and an open-ended talk. The methodology of analysis of the data was both quantitative and qualitative. The objective of mixing the two methods was to enable me, on the one hand, to define the relationship between the “citizenship variable” and the other main ones, and on the other, to gather a deeper understanding the mechanisms at work behind the process of integration in relation to citizenship acquisition. Overall, this research finds that notwithstanding the pervasive effects on the economic, social and political life that globalization, deterritorialization and increased cross-country mobility have had on nation-states and on individuals living within their borders, national citizenship is still a powerful drive in shaping first-generation immigrants’ chances for civic integration into the host country.
Rules in play: On the complexity of routing tables and firewalls

Networking infrastructure, such as routers and firewalls, consist of a policy (i.e., where to forward which packets) and a mechanism that implements it. As the correctness of the policy is critical, it is a natural candidate for formal verification. Indeed, several verification algorithms have been developed, that detect anomalies, conflicts, and redundancies in practical firewalls and flow tables. However, theory suggests that the problem is intractable in general: the decision tree for a policy is of size O((2n)d), where n is the number of rules and d is the number of observed features used in making the decision. (In a typical firewall, n = 1000 and d = 10.) In this paper, we show why the verification of practical firewalls is not as hard as previously thought. Using a new concept, “rules in play,” we find a new, tight bound on the size of the decision tree, and suggest three other factors - narrow fields, singletons, and all-matches - that make the problem tractable in practice. We also present an algorithm to solve an open problem: pruning a policy to the minimum possible number of rules, without changing its meaning.
End-to-end delay analysis of videoconferencing over packet-switched networks

Videoconferencing is an important global application-it enables people around the globe to interact when distance separates them. In order for the participants in a videoconference call to interact naturally, the end-to-end delay should be below human perception; even though an objective and unique figure cannot be set, 100 ms is widely recognized as the desired one-way delay requirement for interaction. Since the global propagation delay can be about 100 ms, the actual end-to-end delay budget available to the system designer (excluding propagation delay) can be no more than 10 ms. We identify the components of the end-to-end delay in various configurations with the objective of understanding how it can be kept below the desired 10-ms bound. We analyze these components step-by-step through six system configurations obtained by combining three generic network architectures with two video encoding schemes. We study the transmission of raw video and variable bit rate (VBR) MPEG video encoding over (1) circuit switching; (2) synchronous packet switching; and (3) asynchronous packet switching. In addition, we show that constant bit rate (CBR) MPEG encoding delivers unacceptable delay-on the order of the group of pictures (GOP) time interval-when maximizing the quality for static scenes. This study aims at showing that having a global common time reference, together with time-driven priority (TDP) and VBR MPEG video encoding, provides adequate end-to-end delay, which is (1) below 10 ms; (2) independent of the network instant load; and (3) independent of the connection rate. The resulting end-to-end delay (excluding propagation delay) can be smaller than the video frame period, which is better than what can be obtained with circuit switching.
Inhibition of the renin-angiotensin system and cardio-renal protection: focus on losartan and angiotensin receptor blockade

Angiotensin II plays a central role in the pathogenesis and progression of proteinuric nephropathies and related cardiovascular complications. Losartan is a selective non-peptide angiotensin Type 1-receptor blocker (ARB) with unique uricosuric effect, not shared by other ARBs. Losartan has demonstrated renoprotective effects in animals and humans with diabetic and non-diabetic renal diseases similar to those of angiotensin-converting enzyme inhibitors, with a lower incidence of dry cough and angioneurotic oedema. A reduced incidence of cerebrovascular events and diabetes has been reported in hypertensive patients with left ventricular hypertrophy on losartan therapy compared with patients treated with atenolol. Whether ARBs have superior cardioprotective effects, compared with other blood pressure medications, is still unknown. Combined angiotensin-converting enzyme inhibitor and ARB therapy improves renal outcomes in non-diabetic nephropathies more than single drug renin-angiotensin system inhibition. Whether this also applies to diabetic nephropathy and related cardiovascular outcomes is still unknown.
Ética profissional e Formação de Professores

This article focuses on issues related to ethics and training, part of a research project on ethical and deontological thinking in which, during its early stages, thirty six teachers from a variety of teaching levels were interviewed. We have identified some aspects related to the ethical training of teachers which are connected to other dimensions under study, namely the regulation and creation of a deontological code and the ethical, personal and professional conceptions of teachers. In addition to an interpretative analysis of data and a brief review of current legislation and studies, we have reflected on the perspectives and strategies to be considered in the ethical training of teachers.
Grounding spatial named entities for information extraction and question answering

The task of named entity annotation of unseen text has recently been successfully automated with near-human performance.But the full task involves more than annotation, i.e. identifying the scope of each (continuous) text span and its class (such as place name). It also involves grounding the named entity (i.e. establishing its denotation with respect to the world or a model). The latter aspect has so far been neglected.In this paper, we show how geo-spatial named entities can be grounded using geographic coordinates, and how the results can be visualized using off-the-shelf software. We use this to compare a "textual surrogate" of a newspaper story, with a "visual surrogate" based on geographic coordinates.
Oxidative stress markers are associated with persistent atrial fibrillation.

BACKGROUND Atrial fibrillation (AF) has been associated with myocardial oxidative stress, and antioxidant agents have demonstrated antiarrhythmic benefit in humans. We compared serum markers of oxidation and associated inflammation in individuals with or without AF. METHODS Serum markers of oxidative stress and inflammation were compared in a cross-sectional, case-control design study of 40 male individuals, with or without persistent or permanent AF, who were matched for age, sex, diabetes, and smoking status, known confounding variables for the measurement of oxidative stress. We used derivatives of reactive oxidative metabolites (DROMs) and ratios of oxidized to reduced glutathione (E(h) GSH) and cysteine (E(h) CySH) to quantify oxidative stress. We also measured inflammatory markers, including high-sensitivity C-reactive protein, interleukins 1beta and 6, and tumor necrosis factor alpha. RESULTS Univariate, conditional logistical regression analysis showed that oxidative stress but not inflammatory markers were statistically associated with AF (P <0.05). The increase in the odds ratios for AF for E(h) GSH, E(h) CySH, and DROMs were 6.1 (95% CI, 1.3-28.3; P = 0.02), 13.6 (95% CI, 2.5-74.1; P = 0.01), and 15.9 (95% CI, 1.7-153.9; P = 0.02), respectively. There was a stronger correlation between E(h) GSH and E(h) CySH (r = 0.66) than between E(h) GSH and DROMs (r = 0.41). In multivariate analysis corrected for statins and other AF risk factors differing between the groups, the association of AF and oxidative stress remained significant. CONCLUSIONS These data suggest that oxidative stress markers may have predictive value in AF management.
Enseñanza del español lengua extranjera a través de la literatura

Los textos literarios son documentos auténticos en los que se encuentra unagran variedad de géneros (poesía, cuento corto, teatro, narraciones, leyendas,novelas, etc.), y en este artículo se partirá de ejemplos que ilustren la manera deutilizarlos en el aula de ELE. Un elemento adicional que brinda soporte al uso detextos literarios es el apoyo auditivo. Debido a que las narraciones en audioproporcionan herramientas comunicativas que los textos escritos no poseen,como son la entonación, el énfasis de la voz en una palabra o frase, el tonojocoso, irónico, alegre, las pausas, los silencios y hasta el acento del hablante.
Rates and drivers of mangrove deforestation in Southeast Asia, 2000–2012

Significance This study quantifies the proximate drivers (i.e., replacement land uses) of mangrove deforestation across Southeast Asia between 2000 and 2012. Mangrove forests in the region were lost at an average rate of 0.18% per year. Aquaculture was a major pressure on mangrove systems during this period, but its dominance was lower than expected, contrary to popular development narratives. Rice agriculture has been a major driver of mangrove loss in Myanmar, and oil palm expansion is a key but under-recognized threat in Malaysia and Indonesia. The threat of oil palm to mangroves is likely to increase in the future as new frontiers open up in Papua, Indonesia. Future research and policy responses must consider the diversity of drivers of mangrove deforestation. The mangrove forests of Southeast Asia are highly biodiverse and provide multiple ecosystem services upon which millions of people depend. Mangroves enhance fisheries and coastal protection, and store among the highest densities of carbon of any ecosystem globally. Mangrove forests have experienced extensive deforestation owing to global demand for commodities, and previous studies have identified the expansion of aquaculture as largely responsible. The proportional conversion of mangroves to different land use types has not been systematically quantified across Southeast Asia, however, particularly in recent years. In this study we apply a combined geographic information system and remote sensing method to quantify the key proximate drivers (i.e., replacement land uses) of mangrove deforestation in Southeast Asia between 2000 and 2012. Mangrove forests were lost at an average rate of 0.18% per year, which is lower than previously published estimates. In total, more than 100,000 ha of mangroves were removed during the study period, with aquaculture accounting for 30% of this total forest change. The rapid expansion of rice agriculture in Myanmar, and the sustained conversion of mangroves to oil palm plantations in Malaysia and Indonesia, are identified as additional increasing and under-recognized threats to mangrove ecosystems. Our study highlights frontiers of mangrove deforestation in the border states of Myanmar, on Borneo, and in Indonesian Papua. To implement policies that conserve mangrove forests across Southeast Asia, it is essential to consider the national and subnational variation in the land uses that follow deforestation.
A novel approach to enable semantic and visual image summarization for exploratory image search

In this paper, we have developed a novel scheme to incorporate topic network and representativeness-based sampling for achieving semantic and visual summarization and visualization of large-scale collections of Flickr images. First, topic network is automatically generated for summarizing and visualizing large-scale collections of Flickr images at a semantic level, so that users can select more suitable keywords for more precise query formulation. Second, the diverse visual similarities between the semantically-similar images are characterized more precisely by using a mixture-of-kernels and a representativeness-based image sampling algorithm is developed to achieve similarity-based summarization and visualization of large amounts of images under the same topic, so that users can find some particular images of interest more effectively. Our experiments on large-scale image collections with diverse semantics have provided very positive results.
Anti-collision backscatter sensor networks

Sensor collision (interference) is studied in a large network of low bit-rate sensors that communicate via backscatter, i.e. modulate the reflection of a common carrier transmitted by a central reader. Closed-form analysis is provided, quantifying sensor collision (interference) in high-density, backscatter sensor networks (BSN), as a function of number of tags and aggregate bandwidth. Analysis is applicable to a broad class of sensor subcarrier modulations, propagation environments and reader antenna directivity patterns. It is discovered that anti-collision performance in high-density backscatter sensor networks is feasible provided that appropriate modulation is used at each sensor. That is due to the round-trip nature of backscatter communication as well as the extended target range, which both impose stringent requirements on spectrum efficiency, not easily met by all modulations. Furthermore, aggregate bandwidth savings for given anti-collision performance are quantified, when simple division techniques on subcarrier (modulating) frequency and space (via moderately directive hub antenna) are combined.
A Bayesian approach for inferring neuronal connectivity from calcium fluorescent imaging data

Deducing the structure of neural circuits is one of the central problems of modern neuroscience. Recently-introduced calcium fluorescent imaging methods permit experimentalists to observe network activity in large populations of neurons, but these techniques provide only indirect observations of neural spike trains, with limited time resolution and signal quality. In this work, we present a Bayesian approach for inferring neural circuitry given this type of imaging data. We model the network activity in terms of a collection of coupled hidden Markov chains, with each chain corresponding to a single neuron in the network and the coupling between the chains reflecting the network’s connectivity matrix. We derive a Monte Carlo ExpectationMaximization algorithm for fitting the model parameters; to obtain the sufficient statistics in a computationally-efficient manner, we introduce a specialized blockwise-Gibbs algorithm for sampling from the joint activity of all observed neurons given the observed fluorescence data. We perform large-scale simulations of randomly connected neuronal networks with biophysically realistic parameters and find that the proposed methods can accurately infer the connectivity in these networks given reasonable experimental and computational constraints. In addition, the estimation accuracy may be improved significantly by incorporating prior knowledge about the sparseness of connectivity in the network, via standard L1 penalization methods.
P-HAF: Homography Estimation using Partial Local Affine Frames

We propose an algorithm, called P-HAF, to estimate planar homographies using partially known local affine transformations. This general theory is able to exploit the affine components obtained by the commonly used partially affine covariant detectors, such as SIFT or SURF, in a real time capable way. P-HAF as a minimal solver can estimate the homography using two SIFT correspondences, moreover, it can deal with any number of point pairs as an overdetermined system. It is validated both on synthesized and publicly available datasets that exploiting all information leads to more accurate estimates and makes multi-homography estimation less ambiguous.
Trends in Amphibian Occupancy in the United States

Though a third of amphibian species worldwide are thought to be imperiled, existing assessments simply categorize extinction risk, providing little information on the rate of population losses. We conducted the first analysis of the rate of change in the probability that amphibians occupy ponds and other comparable habitat features across the United States. We found that overall occupancy by amphibians declined 3.7% annually from 2002 to 2011. Species that are Red-listed by the International Union for Conservation of Nature (IUCN) declined an average of 11.6% annually. All subsets of data examined had a declining trend including species in the IUCN Least Concern category. This analysis suggests that amphibian declines may be more widespread and severe than previously realized.
Interpolative self-training approach for sentiment analysis

Sentiment analysis has become one of the fundamental research areas with an objective of estimating the polarity of text documents. While sentiment analysis requires rich training resources, the number of available labeled documents is limited. The proposed interpolative self-training model is an extension of self-training as one of the most common semi-supervised learning algorithms. The proposed method is based on enlarging learning documents by interpolating data in both the training and the test phase. The method also includes a weighting strategy for data selection in each iteration. The method is evaluated using four Twitter datasets for the task of sentiment analysis. The results indicate that the proposed self-training model successfully outperforms the baseline and the standard self-training approach.
Culture and nonverbal cues: how does power distance influence facial expressions in game contexts?

Power distance is one of the most prominent cultural dimensions underlying cultural differences in beliefs and values. However, how power distance is evident in the more tangible domain of behavior, such as nonverbal cues, has not been well-documented. In our study, we recruited Dutch (low power distance culture) and Chinese (high power distance culture) university students to play games against two opponents via an ostensibly real-time internet connection. Unbeknownst to the participants, the two opponents were in fact confederates, who assumed the role of either a highly successful full professor or a down-to-earth undergraduate freshman. Throughout the game, participants were videotaped. Analyses of the resulting recordings showed that Chinese students showed more submission in their nonverbal behavior than Dutch students in general; what was most remarkable was that such a cultural difference in submission was more evident when the opponent was a professor than when the opponent was a fellow student. To the best of our knowledge, these findings are the first to illustrate that the role of power distance could indeed be reflected in nonverbal behavior exhibited in a naturalistic social setting.
A Proof of Lemma 1

1 We use ∇ to denote the Jacobian of a vector-valued and gradient of a scalar-valued function and 2 ∇Φ(a) {b} to represent the directional derivative of Φ along b. We use and ⊗ to denote the 3 Hadamard (entry-wise) product and Kronecker product, respectively. For A ∈ Rm×n and t ∈ Z+, we 4 denote A∗t ∈ Rmt×n with its a-th column defined as vec(xa ⊗ · · · ⊗ xa) ∈ R t . We use lower-case 5 bold font to denote vectors. Sets and scalars are represented by calligraphic and standard fonts, 6 respectively. We use [n] to denote {1, · · · , n} for an integer n. We use Õ and Ω̃ to hide logarithmic 7 factors and use . to ignore terms up to constant and logarithmic factors. 8
I'm too Busy to Reset my LinkedIn Password: On the Effectiveness of Password Reset Emails

A common security practice used to deal with a password breach is locking user accounts and sending out an email to tell users that they need to reset their password to unlock their account. This paper evaluates the effectiveness of this security practice based on the password reset email that LinkedIn sent out around May 2016, and through an online survey conducted on 249 LinkedIn users who received that email. Our evaluation shows that only about 46% of the participants reset their passwords. The mean time taken to reset password was 26.3 days, revealing that a significant proportion of the participants reset their password a few weeks, or even months after first receiving the email. Our findings suggest that more effective persuasive measures need to be added to convince users to reset their password in a timely manner, and further reduce the risks associated with delaying password resets.