Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a complexity theory for local distributed computing

A central theme in distributed network algorithms concerns understanding and coping with the issue of <i>locality</i>. Yet despite considerable progress, research efforts in this direction have not yet resulted in a solid basis in the form of a fundamental computational complexity theory for locality. Inspired by sequential complexity theory, we focus on a complexity theory for <i>distributed decision problems</i>. In the context of locality, solving a decision problem requires the processors to independently inspect their local neighborhoods and then collectively decide whether a given global input instance belongs to some specified language. We consider the standard LOCAL model of computation and define LD(<i>t</i>) (for <i>local decision</i>) as the class of decision problems that can be solved in <i>t</i> communication rounds. We first study the intriguing question of whether randomization helps in local distributed computing, and to what extent. Specifically, we define the corresponding randomized class BPLD(<i>t</i>,<i>p</i>,<i>q</i>), containing all languages for which there exists a randomized algorithm that runs in <i>t</i> rounds, accepts correct instances with probability at least <i>p</i>, and rejects incorrect ones with probability at least <i>q</i>. We show that <i>p</i><sup>2</sup> + q = 1 is a threshold for the containment of LD(<i>t</i>) in BPLD(<i>t</i>,<i>p</i>,<i>q</i>). More precisely, we show that there exists a language that does not belong to LD(<i>t</i>) for any <i>t</i>=<i>o</i>(<i>n</i>) but does belong to BPLD(<i>0</i>,<i>p</i>,<i>q</i>) for any <i>p</i>,<i>q</i> ∈ (0,1) such that <i>p</i><sup>2</sup> + q ≤ 1. On the other hand, we show that, restricted to hereditary languages, BPLD(<i>t</i>,<i>p</i>,<i>q</i>)=LD(<i>O</i>(<i>t</i>)), for any function <i>t</i>, and any <i>p</i>, <i>q</i> ∈ (0,1) such that <i>p</i><sup>2</sup> + q > 1. In addition, we investigate the impact of nondeterminism on local decision, and establish several structural results inspired by classical computational complexity theory. Specifically, we show that nondeterminism does help, but that this help is limited, as there exist languages that cannot be decided locally nondeterministically. Perhaps surprisingly, it turns out that it is the combination of randomization with nondeterminism that enables to decide all languages <i>in constant time</i>. Finally, we introduce the notion of local reduction, and establish a couple of completeness results.
Successive NBI Cancellation Using Soft Decisions for OFDM Systems

Recently, we proposed a successive narrowband interference (NBI) cancellation method for orthogonal frequency-division multiplexing (OFDM) systems, which empowers the conventional one-tap frequency-domain equalizer to gain in robustness against NBI. In this letter, we generalize such an approach by using soft (instead of hard) feedback from the decoding unit, when the digitally-modulated NBI is (possibly) improper. It is shown that, with respect to our previous work, the devised equalizers allow one to achieve a significant performance gain, with a moderate increase in computational complexity.
A Latent Profile Analysis of the Criterion-related Validity of a Divergent Thinking Test

The criterion-related validity of divergent thinking (DT) tests has been questioned because of relatively low correlations between DT test scores and creative performance. A possible inhibiting factor in previous correlations—heterogeneity of the sample—has been ignored. If groups with different DT profiles are involved in this line of research, low correlations would not necessarily be indicative of actual relationships, and criterion-related validity would appear to be lower than it is. Thus, this study identified groups with their own unique DT profiles and examined their creative performance. To this end, elementary children’s (N = 325) responses in 3 DT tasks were analyzed using latent profile analysis. Results suggested 3 groups with unique DT profiles: One group scored moderate on fluency and low on originality; another group scored moderate on fluency and high on originality; the third group scored uniformly low across fluency, originality, and flexibility. Surprisingly, only the low-originality group excelled in creative achievement, but the hypothesis of this investigation was supported by the fact that only the high-originality group significantly excelled in ideation. These results confirm that low correlations between DT indices and creative performance do not necessarily indicate a lack of the criterion-related validity of DT tests. Differences between the creative achievement and the ideation criterion measures are detailed, and idiosyncratic properties in DT profiles and their corresponding creative strengths are discussed as educational implications.
MMS entertainment system based on mobile phone

An online MMS (Multimedia Message Service) system is designed and implemented based on the technologies of automatic caricature generation and animation. Users upload a facial image and a piece of speech, and specify some parameters, then, the MMS with personalized caricature animation will be generated and sent to the predefined mobile phone. Two main procedures, caricature generating and animation synthesizing are involved. For caricature generating, which is from face image to caricature, we proposed automatic caricature generation method based on Manifold Regularization. For animation synthesizing, which is from caricature to animation, we developed speech driven animation approach based on Hidden Markov Model. The real online running system proved that our methods can provide people attractive MMS for mobile entertainment successfully.
Unemployment, human capital depreciation and pension benefits: an empirical evaluation of German data*

Abstract This paper investigates empirically how unemployment-induced employment-breaks at different career stages influence pension benefits. The analysis is based on German data. I distinguish four different career phases and investigate to what extent the prevailing social security policy compensated for earning losses. The results suggest that (1) losses in pension benefits were the greatest if unemployment occurred in the middle of a career (between 31 and 50); (2) social security policies have had a mitigating effect on losses in pension benefits. These findings indicate that institutions have a decided influence on how career patterns translate into pension benefits.
‘Both/And’ Not ‘Either/Or’: Reconciling Rights to Protection and Participation in Working with Child Sexual Exploitation

Analysis of data from a two-year evaluation of the piloting of a child-centred framework for addressing child sexual exploitation (CSE) in England revealed an intrinsic practice dilemma, whereby many practitioners experienced profound ontological, ethical, emotional and intellectual dilemmas in reconciling young people’s rights to voice, privacy and autonomy with their rights to safety, guidance and protection. ‘No-win’ scenarios left practitioners in a ‘double-bind’, whereby acting protectively might alienate a young person, paradoxically encouraging them to engage in further risky behaviours. An individual commitment to child-centred and participatory approaches, relational practice and reflective use of self was found to support professionals in exploring this tension with young people themselves, involving them as partners in reducing the risk of exploitation. However, practitioners will struggle to achieve this without manageable workloads, good supervision and organisational support for the emotional content of the work. Transformational learning is required across the disciplinary practice systems to achieve a more integrated practice of ‘both/and’ thinking and feeling. The tensions between protection and participation can then be surfaced in a way that is constructive rather than divisive.
An XMM-Newton view of the dipping low-mass X-ray binary XTE J1710-281

Context. Studying the spectral changes during the dips exhibited by almost edge-on, low-mass X-ray binaries (LMXBs) is a powerful means of probing the structure of accretion disks. The XMM-Newton, Chandra, or Suzaku discovery of absorption lines from Fe xxv and other highly-ionized species in many dippers has revealed a highly-ionized atmosphere above the disk. A highly (but less strongly) ionized plasma is also present in the vertical structure causing the dips, together with neutral material. Aims. We aim to investigate the spectral changes during the dips of XTE J1710-281, a still poorly studied LMXB known to exhibit bursts, dips, and eclipses. Methods. We analyze the archived XMM-Newton observation of XTE J1710-281 performed in 2004 that covered one orbital period of the system (3.8 h). We modeled the spectral changes between persistent and dips in the framework of the partial covering model and the ionized absorber approach. Results. The persistent spectrum can be fit by a power law with a photon index of 1.94 ± 0.02 affected by absorption from cool material with a hydrogen column density of (0.401 ± 0.007)$\times$10 22 cm -2 . The spectral changes from persistent to deep-dipping intervals are consistent with the partial covering of the power-law emission. Twenty-six percent of the continuum is covered during shallow dipping, and 78% during deep dipping. The column density decreases from $77_{\rm -38}^{+67}$ $\times$ 10 22 cm -2 during shallow dipping to (14 ± 2) $\times$ 10 22 cm -2 during the deep-dipping interval. We do not detect any absorption line from highly ionized species such as Fe xxv. However, the upper-limits we derive on their equivalent width (EW) are not constraining. Despite not detecting any narrow spectral signatures of a warm absorber, we show that the spectral changes are consistent with an increase in column density and a decrease in ionization state of a highly-ionized absorber, associated with an increase in column density of a neutral absorber, in agreement with the recent results found in other dippers. In XTE J1710-281, the column density of the ionized absorber increases from $4. 3_{\rm -0.5}^{+0.4}$ $\times$ 10 22 cm -2 during shallow dipping to $11. 6_{\rm -0.6}^{+0.4}$ $\times$ 10 22 cm -2 during deep dipping, while the ionization parameter decreases from 10 2.52 to 10 2.29 erg s -1 cm. The parameters of the ionized absorber are not constrained during persistent emission. The neutral absorber only slightly increases from (0.410 ± 0.007) $\times$ 10 22 cm -2 during persistent emission to (0.420 ± 0.009) $\times$ 10 22 cm -2 during shallow dipping and to (0.45 ± 0.03) $\times$ 10 22 cm -2 during deep dipping. The warm absorber model better accounts for the ~1 keV depression visible in the pn dipping spectra, and naturally explains it as a blend of lines and edges unresolved by pn. A deeper observation of XTE J1710-281 would enable this interpretation to be confirmed.
Open Information Extraction: The Second Generation

How do we scale information extraction to the massive size and unprecedented heterogeneity of the Web corpus? Beginning in 2003, our KnowItAll project has sought to extract high-quality knowledge from the Web. In 2007, we introduced the Open Information Extraction (Open IE) paradigm which eschews hand-labeled training examples, and avoids domain-specific verbs and nouns, to develop unlexicalized, domain-independent extractors that scale to the Web corpus. Open IE systems have extracted billions of assertions as the basis for both common-sense knowledge and novel question-answering systems. This paper describes the second generation of Open IE systems, which rely on a novel model of how relations and their arguments are expressed in English sentences to double precision/recall compared with previous systems such as TEXTRUNNER and WOE.
Burgers' flows as Markovian diffusion processes

We analyze the unforced and deterministically forced Burgers equation in the framework of the (diffusive) interpolating dynamics that solves the so-called Schr\"odinger boundary data problem for random matter transport. This entails an exploration of the consistency conditions that allow one to interpret dispersion of passive contaminants in Burgers flow as a Markovian diffusion process. In general, the usage of a continuity equation ${\mathrm{\ensuremath{\partial}}}_{\mathrm{t}}$\ensuremath{\rho}=-\ensuremath{\nabla}-\ensuremath{\rightarrow}(v-\ensuremath{\rightarrow}\ensuremath{\rho}), where v-\ensuremath{\rightarrow}=v-\ensuremath{\rightarrow}(x-\ensuremath{\rightarrow},t) stands for the Burgers field and \ensuremath{\rho} is the density of transported matter, is at variance with the explicit diffusion scenario. Under these circumstances, we give a complete characterization of the diffusive transport that is governed by Burgers velocity fields. The result extends both to the approximate description of the transport driven by an incompressible fluid and to motions in an infinitely compressible medium. Also, in conjunction with the Born statistical postulate in quantum theory, it pertains to the probabilistic (diffusive) counterpart of the Schr\"odinger picture quantum dynamics. We give a generalization of this dynamical problem to cases governed by nonconservative force fields when it appears indispensable to relax the gradient velocity field assumption. The Hopf-Cole procedure has been appropriately generalized to yield solutions in that case.
Parallel Clustering Coefficient Computation using GPUs

Clustering coefficient is the measure of how tightly vertices are bounded in a network. The Triangle Counting problem is at the core of clustering coefficient computation. We present a new technique for implementing clustering coefficient algorithm on GPUs. It relies on neighbour list being sorted with respect to vertex ID. The algorithm can process very large graphs not seen in the literature for single-node in-memory systems before. Our technique is able to compute clustering coefficient of each vertex in power-law graphs with up to 512M edges on a single GPU. The GPU implementation offers 7x speedup over the best known work for the same graph. For the CPU implementation, we present results for graphs with up to 4B edges. We also investigate performance bottleneck of power-law graphs with skewed vertex degree distribution by analyzing GPU performance counter outputs and interpreting them in terms of GPU memory and thread characteristics.
The Physical Conditions of the X-Ray Emission Line Regions in the Circinus Galaxy

We present a detailed X-ray spectral analysis of the Circinus galaxy using archival data obtained with the ASCA satellite. The spectrum shows numerous emission lines in the soft X-ray band from highly ionized ions, as well as Compton reflection and fluorescent lines from neutral or near-neutral matter. We analyze the spectrum in the context of a self-consistent recombination cascade model and find that a nearly flat differential emission measure (DEM) distribution in ionization parameter fits the data. For a fixed solid angle distribution of matter surrounding a point source, this corresponds to a run of electron density of the form n(r) ~ r-3/2, which is suggestive of Bondi accretion onto a central compact mass. Using this density profile and comparing the resulting emission spectra with the ASCA data, the size of the X-ray emission line region is estimated to be ≲1 kpc. We also show that the derived density as a function of radius is compatible with the X-ray recombination line emission region being the confining medium of the coronal line regions.
ARC-UI: Visualization Tool for Associative Classifiers

The classification of an unknown item based on a training data set is a key data mining task. An important part of this process that is often overlooked is the user's comprehension of the classifier and the results it produces. Associative classifiers begin to address this issue by using sets of simple rules to classify items. However, the size of these rule sets can be an obstacle to understandability. In this work, we present an interactive visualization system that allows the user to visualize various aspects of the classifier's decision process. This system shows the rules that are relevant to the classification of an item, the ways in which the item's characteristics relate to these rules, and connections between the item and the classifier's training data set. The system also contains a speculation component, which allows the user to modify rules within the classifier, and see the impact of these changes. Thus, this component allows the user to contribute domain expertise to the classification process, consequently improving the accuracy of the classifier.
Back-propagation algorithm for relevance feedback in image retrieval

Content-based image retrieval (CBIR) usually relies on pre-attentive similarities. Results are often coarse because of the gap between the pre-attentive level and the semantic level of the user's request. The aim of relevance feedback is to refine results by taking user's expertise into account. This paper presents a new feedback architecture for CBIR. Images are compared through a weighted dissimilarity function which can be represented as a "network of dissimilarities". The weights are updated via an error backpropagation algorithm using the user's annotations of the successive set of result images. It allows an iterative refinement of the search through a simple interactive process (the user has just to specify if images are relevant or not). A quality assessment realized with three databases containing about 10,000 images shows the performance improvement after feedback.
How a public interfaces its raison d’être: an interface analysis through the concept of cultural performance

For decades Groningen has been victim to earthquakes induced by gas drillings. In 2009 the Groningen Soil Movement (GBB) was established in order to defend the interests of Groningen citizens who are victim to these earthquakes. The goal of this research is to find out how the GBB interfaces their perception of this public issue, and how these interfaces can be understood. This study is aimed at connecting the theoretical concepts of interface and cultural performance in order to analyze interfaces in a structured and detailed manner. To reach this goal a discourse analysis of written and audio-visual material has been conducted. The analysis shows that while in GBBs written interfaces a careful and strict narrative is repeatedly presented that follows a stable script, the staged interface is where the cultural performance of the GBB really come to life. This is interesting, because exactly in this staged interface the performance derailed from the pre-arranged script. It is argued that this changing role of the script, from mediating between to resembling the background representations, is the reason the staged interface by the GBB can be considered a successful cultural performance. For future research it is recommended to take more concepts of the model of cultural performance into consideration to come to a more detailed understanding of interfaces.
Antibody phage display technologies with special reference to angiogenesis

The presence of blood vessels is a prerequisite for normal development, tissue growth, and tissue repair. However, its abnormal occurrence or absence can also potentiate disease processes. Angiogenic therapies have been used to stimulate blood vessel growth in ischemic conditions such as severe end‐stage peripheral vascular disease, ischemic heart disease and stroke and for inhibition of angiogenesis in tumors. The targeting and identification of novel endothelial cell (EC) markers that can ultimately be used in angiogenic strategies is an expanding field but is limited by the availability of reagents. For instance repeated injection of mouse monoclonal antibodies (Mabs) against angiogenic EC, can result in the production of autoantibodies. Therefore, these mouse Mabs cannot be used for therapeutic purposes. Phage display technology was employed in this context to select antibodies, proteins, and peptides against known or novel EC antigens. Furthermore, technologies have been developed that enable the specific targeting of epitopes on cells including the endothelium with high‐affinity/ avidity antibodies. The focus for these antibody targeting strategies are markers that are unique or up‐regulated on angiogenic EC including the vascular endothelial growth factor receptor (VEGFR) KDR, endoglin (CD105), and the extracellular domain B (ED‐B) domain of fibronectin (FN). These markers are reviewed herein. —Smith, J., Kontermann, R. E. , Embleton, J., Kumar, S. Antibody phage display technologies with special reference to angiogenesis. FASEB J. 19, 331–341 (2005)
The neural correlates of the decoy effect in decisions

Human choices are remarkably susceptible to the context in which options are presented. The introduction of an inferior option (a decoy) into the choice set can make one of the original options (the target) more attractive than and the other original option (the competitor). This so called “decoy effect” represents a striking violation of the “context-invariant” axiom, yet its underlying neural mechanisms are not well understood. Here, we used a novel gambling task in conjunction with functional magnetic resonance imaging (fMRI) to elucidate its neural basis. At both the stimulus and decision phases, choice sets with decoys activated the occipital gyrus and deactivated the inferior parietal gyrus. At the decision phase, choosing the targets vs. the competitors elicited stronger anterior insula activation, suggesting that perceptual salience drives heuristic decision making in the decoy effect. Moreover, across participants, activity in anterior cingulate cortex (ACC) predicted a reduced susceptibility to the decoy effect, indicating that resisting the tendency to make heuristic decisions is taxing. Our findings highlight the power of the decoy effect in laboratory settings and document the neural mechanisms underlying the decoy effect.
Fast training of support vector machines using top-down kernel clustering

How to deal with the very large database in decision-making applications is a very important issue, which sometimes can be addressed using SVMs. This paper presents a new sample reduction algorithm as a sampling preprocessing for SVM training to improve the scalability. We develop a novel top-down kernel clustering approach which tends to fast produce balanced clusters of similar sizes in the kernel space. Owing to this kernel clustering step, the proposed algorithm proves efficient and effective for reducing training samples for nonlinear SVMs. Experimental results on four UCI real data benchmarks show that, with very short sampling time, the proposed sample reduction algorithm dramatically accelerates SVM training while maintaining high test accuracy.