Miracle-dz/UniFAR-FTUs huggingface dataset:
The racial state and resistance in Ferguson and beyond

This virtual special issue considers the empirical and theoretical resources that the back catalogue of Urban Studies specifically, and the discipline of urban studies more broadly, has to offer our understanding of the rapidly evolving contemporary moment in the USA, usefully dubbed ‘The Age of Ferguson’ (Bernard (2015); Derickson (forthcoming). Mobilising the concept of the ‘racial state’, this article considers Ferguson in the context of state rescaling and globalisation to continue to flesh out the role that difference and its geographical expression play in smoothing out and justifying the neoliberalisation of urban governance (see Derickson (2014)), and to begin to develop ‘countertopographies’ (Katz (2001)) that link up the margins of the Global North and South. In so doing, I engage each of the papers included in the special issue to consider how they contribute to and stretch our understanding of the present racial conjuncture, and to provide a first cut at thinking the Age of Ferguson relationally (Derickson, forthcoming; Jacobs (2012), through urban governance, racialisation, territorial stigmatisation’ (Garbin and Millington (2012)), policing and urban social movements.
Allogeneic transplantation for relapsed and refractory Hodgkin lymphoma: long-term outcomes and graft-versus-host disease-free/relapse-free survival

Abstract This monocentric retrospective study included 70 consecutive relapsed/refractory Hodgkin lymphoma (RR-HL) patients receiving reduced-intensity allogeneic stem cell transplantation (alloSCT). We evaluated overall and progression-free survival (OS, PFS), graft-versus host disease/relapse-free survival (GFRS), and chronic GVHD-free OS (cGVHD-free OS) defined as OS without moderate-to-severe cGVHD. Patients had a median age of 33 years (range, 18–60 years), 23% had refractory disease (SD/PD). Donors were HLA identical (39%), unrelated (30%), or haploidentical (31%). Median follow-up was 6.2 years. Five-year OS was 59% and PFS was 49%. NRM was 16% at 1 year. 44% of patients had cGVHD, and 14% moderate-to-severe cGVHD at last follow-up. GFRS and cGVHD-free OS were 26 and 48% at 5 years. In multivariate analysis, resistant disease at alloSCT impacted survival and GFRS. In conclusion, disease response before alloSCT impacts survival and GFRS. GVHD outcomes may help comparing the long-term effects of the new salvage treatments that bridge patients to alloSCT.
Self-face recognition in attended and unattended conditions: an event-related brain potential study

This study investigated whether neural mechanisms of self-face recognition are modulated by attention by recording event-related brain potentials associated with self-face recognition. Participants identified head orientations of self-faces and familiar or unfamiliar other faces presented briefly at the center of the visual field. Event-related brain potentials to self-faces and other faces were recorded when self-faces and familiar or unfamiliar other faces were either task relevant (attended) or irrelevant (unattended) in separate blocks of trials. We found that early face-specific event-related brain potential components such as the N170 and vertex positive potential did not differ between self-faces and other faces. Relative to familiar faces, however, self-faces induced an increased positivity over the frontocentral area at 220–700 ms. The increased positivity to self-faces relative to familiar faces between 500 and 700 ms was reduced in the attended relative to the unattended conditions, which arose from the fact that the amplitude to familiar faces during this time window was increased in the attended relative to the unattended conditions, whereas the event-related brain potential amplitude to self-faces was not influenced by attention. The event-related brain potential results suggest an automatic process of self-face recognition in human brains that occurs after face structure encoding and is independent of task relevance.
Support, opposition, emotion and contentious issue risk perception

Purpose – Research on emotion in the context of risk perception has historically focused on negative emotions, and has emphasized the effect of these negative emotions on the perception of risk amongst those who oppose (rather than support) contentious issues. Drawing on theory, the purpose of this paper is to hypothesize that both positive and negative emotions are correlated with risk perceptions regarding contentious public issues and that this occurs amongst supporters and opponents alike. Design/methodology/approach – The paper explores the relationship between emotions and perceived risk through consideration of the highly contentious case of nuclear energy in Saskatchewan, Canada. The analysis uses data from a representative telephone survey of 1,355 residents. Findings – The results suggest that positive emotions, like negative emotions, are related to nuclear energy risk perceptions. Emotions are related to risk perception amongst both supporters and opponents. Research limitations/implications –.
Efficiently Learning Nonstationary Gaussian Processes for Real World Impact

Most real world phenomena such as sunlight distribution under a forest canopy, minerals concentration, stock valuation, exhibit nonstationary dynamics i.e. phenomenon variation changes depending on the locality. Nonstationary dynamics pose both theoretical and practical challenges to statistical machine learning algorithms that aim to accurately capture the complexities governing the evolution of such processes. Typically the nonstationary dynamics are modeled using nonstationary Gaussian Process models (NGPS) that employ local latent dynamics parameterization to correspondingly model the nonstationary real observable dynamics. Recently, an approach based on most likely induced latent dynamics representation attracted research community's attention for a while. The approach could not be employed for large scale real world applications because learning a most likely latent dynamics representation involves maximization of marginal likelihood of the observed real dynamics that becomes intractable as the number of induced latent points grows with problem size. We have established a direct relationship between informativeness of the induced latent dynamics and the marginal likelihood of the observed real dynamics. This opens up the possibility of maximizing marginal likelihood of observed real dynamics indirectly by near optimally maximizing entropy or mutual information gain on the induced latent dynamics using greedy algorithms. Therefore, for an efficient yet accurate inference, we propose to build an induced latent dynamics representation using a novel algorithm LISAL that adaptively maximizes entropy or mutual information on the induced latent dynamics and marginal likelihood of observed real dynamics in an iterative manner. The relevance of LISAL is validated using real world datasets.
D Landmark Localisation

In this work we examine in detail the landmark localisation algorithm proposed by Gupta et al. [9]. This algorithm automatically localises 10 facial fiducial points using both texture and range images, in conjunction with anthropometric information. For six of the landmarks detected a modified version of the EBGM technique developed by Wisott et al. is used [8]. The landmark localisation performance of this system is determined as the original authors only provide 2D standard deviation results. While the nose tip localisation performs poorly with a 3D mean error of 6.15mm, the remaining landmarks are all localised with an error of under 3.35mm, with the outer eye corner and mouth corner detections performing particularly well. The influence of the inclusion of texture and/or range information when localising landmarks is examined. It is determined that best performance is achieved when both texture and range information is used. Finally, the relative localisation performance improvement achieved by using the modified EBGM technique determined. For all landmarks examined the use of EBGM improves localisation.
Somatosensory Cross-Modal Reorganization in Adults With Age-Related, Early-Stage Hearing Loss

Under conditions of profound sensory deprivation, the brain has the propensity to reorganize. For example, intact sensory modalities often recruit deficient modalities’ cortices for neural processing. This process is known as cross-modal reorganization and has been shown in congenitally and profoundly deaf patients. However, much less is known about cross-modal cortical reorganization in persons with less severe cases of age-related hearing loss (ARHL), even though such cases are far more common. Thus, we investigated cross-modal reorganization between the auditory and somatosensory modalities in older adults with normal hearing (NH) and mild-moderate ARHL in response to vibrotactile stimulation using high density electroencephalography (EEG). Results showed activation of the somatosensory cortices in adults with NH as well as those with hearing loss (HL). However, adults with mild-moderate ARHL also showed robust activation of auditory cortical regions in response to somatosensory stimulation. Neurophysiologic data exhibited significant correlations with speech perception in noise outcomes suggesting that the degree of cross-modal reorganization may be associated with functional performance. Our study presents the first evidence of somatosensory cross-modal reorganization of the auditory cortex in adults with early-stage, mild-moderate ARHL. Our findings suggest that even mild levels of ARHL associated with communication difficulty result in fundamental cortical changes.
Dual processes and moral conflict: Evidence for deontological reasoners’ intuitive utilitarian sensitivity

The prominent dual process model of moral cognition suggests that reasoners intuitively detect that harming others is wrong (deontological System-1 morality) but have to engage in demanding deliberation to realize that harm can be acceptable depending on the consequences (utilitarian System-2 morality). But the nature of the interaction between the processes is not clear. To address this key issue we tested whether deontological reasoners also intuitively grasp the utilitarian dimensions of classic moral dilemmas. In three studies subjects solved moral dilemmas in which utilitarian and deontological considerations cued conflicting or non-conflicting decisions while performing a demanding concurrent load task. Results show that reasoners’ sensitivity to conflicting moral perspectives, as reflected in decreased decision confidence and increased experienced processing difficulty, was unaffected by cognitive load. We discuss how these findings argue for a hybrid dual process model interpretation in which System-1 cues both a deontological and utilitarian intuition.
Sensor Fault Detection and System Reconfiguration for DC-DC Boost Converter

This paper presents a effective sensor fault detection and system reconfiguration approach for DC-DC Boost converter. We consider to design a Luenberger observer to solve the problem of the sensor fault detection of the DC-DC Boost converter. We establish mathematical model according to the state of the switch . Luenberger observer is designed to produce residual errors and analyse faults. We detect three types of sensor faults online and compare residuals with thresholds. The system is able to maintain stability by taking system reconfiguration approach. The effectiveness of this approach is demonstrated by simulations.
Approximate Temporal Difference Learning is a Gradient Descent for Reversible Policies

In reinforcement learning, temporal difference (TD) is the most direct algorithm to learn the value function of a policy. For large or infinite state spaces, exact representations of the value function are usually not available, and it must be approximated by a function in some parametric family. However, with \emph{nonlinear} parametric approximations (such as neural networks), TD is not guaranteed to converge to a good approximation of the true value function within the family, and is known to diverge even in relatively simple cases. TD lacks an interpretation as a stochastic gradient descent of an error between the true and approximate value functions, which would provide such guarantees. We prove that approximate TD is a gradient descent provided the current policy is \emph{reversible}. This holds even with nonlinear approximations. A policy with transition probabilities $P(s,s')$ between states is reversible if there exists a function $\mu$ over states such that $\frac{P(s,s')}{P(s',s)}=\frac{\mu(s')}{\mu(s)}$. In particular, every move can be undone with some probability. This condition is restrictive; it is satisfied, for instance, for a navigation problem in any unoriented graph. In this case, approximate TD is exactly a gradient descent of the \emph{Dirichlet norm}, the norm of the difference of \emph{gradients} between the true and approximate value functions. The Dirichlet norm also controls the bias of approximate policy gradient. These results hold even with no decay factor ($\gamma=1$) and do not rely on contractivity of the Bellman operator, thus proving stability of TD even with $\gamma=1$ for reversible policies.
Exploring the Computational Explanatory Gap

While substantial progress has been made in the field known as artificial consciousness, at the present time there is no generally accepted phenomenally conscious machine, nor even a clear route to how one might be produced should we decide to try. Here, we take the position that, from our computer science perspective, a major reason for this is a computational explanatory gap: our inability to understand/explain the implementation of high-level cognitive algorithms in terms of neurocomputational processing. We explain how addressing the computational explanatory gap can identify computational correlates of consciousness. We suggest that bridging this gap is not only critical to further progress in the area of machine consciousness, but would also inform the search for neurobiological correlates of consciousness and would, with high probability, contribute to demystifying the “hard problem” of understanding the mind–brain relationship. We compile a listing of previously proposed computational correlates of consciousness and, based on the results of recent computational modeling, suggest that the gating mechanisms associated with top-down cognitive control of working memory should be added to this list. We conclude that developing neurocognitive architectures that contribute to bridging the computational explanatory gap provides a credible and achievable roadmap to understanding the ultimate prospects for a conscious machine, and to a better understanding of the mind–brain problem in general.
Synergistic NGF/B27 Gradients Position Synapses Heterogeneously in 3D Micropatterned Neural Cultures

Native functional brain circuits show different numbers of synapses (synaptic densities) in the cerebral cortex. Until now, different synaptic densities could not be studied in vitro using current cell culture methods for primary neurons. Herein, we present a novel microfluidic based cell culture method that combines 3D micropatterning of hydrogel layers with linear chemical gradient formation. Micropatterned hydrogels were used to encapsulate dissociated cortical neurons in laminar cell layers and neurotrophic factors NGF and B27 were added to influence the formation of synapses. Neurotrophic gradients allowed for the positioning of distinguishable synaptic densities throughout a 3D micropatterned neural culture. NGF and B27 gradients were maintained in the microfluidic device for over two weeks without perfusion pumps by utilizing a refilling procedure. Spatial distribution of synapses was examined with a pre-synaptic marker to determine synaptic densities. From our experiments, we observed that (1) cortical neurons responded only to synergistic NGF/B27 gradients, (2) synaptic density increased proportionally to synergistic NGF/B27 gradients; (3) homogeneous distribution of B27 disturbed cortical neurons in sensing NGF gradients and (4) the cell layer position significantly impacted spatial distribution of synapses.
Foreign Language Anxiety among Students Studying Foreign Languages

Background: Learning a foreign language is multi-dimensional and considered a source of stress. The purpose of the present study is to investigate foreign language classroom anxiety among university students in Jordan. The study makes use of a cross-sectional correlation design to collect data from 488 university students, employing a self-reported questionnaire of Foreign Language Anxiety. Results: 63.4% (n = 310) of the 488 students suffer foreign language classroom anxiety; mean score for communication apprehension is 54.7 (SD = 11.0), while the mean score for fear of negative evaluation is 22.8 (SD = 5.6), and mean score of test anxiety is 17.7 (SD = 3.1). The analysis shows that the highest anxiety level is experienced in terms of fear of negative evaluation and testing, while communication apprehension has the lowest level of fear. Conclusion: University students of foreign languages in Jordan have a high level of anxiety, which is undoubtedly associated with the level of academic performance. [Jihad Al-Shuaibi, Ayman M. Hamdan-Mansour, Saleh N Azzeghaiby. Foreign Language Anxiety among Students Studying Foreign Languages. Life Sci J 2014;11(8):197-203]. (ISSN:1097-8135). http://www.lifesciencesite. com. 25
Nitrogen Reduction to Ammonia on a Biomimetic Mononuclear Iron Centre: Insights into the Nitrogenase Enzyme

Abstract Nitrogenases catalyse nitrogen fixation to ammonia on a multinuclear Fe‐Mo centre, but their mechanism and particularly the order of proton and electron transfer processes that happen during the catalytic cycle is still unresolved. Recently, a unique biomimetic mononuclear iron model was developed using tris(phosphine)borate (TPB) ligands that was shown to convert N2 into NH3. Herein, we present a computational study on the [(TPB)FeN2]− complex and describe its conversion into ammonia through the addition of electrons and protons. In particular, we tested the consecutive proton transfer on only the distal nitrogen atom or alternated protonation of the distal/proximal nitrogen. It is found that the lowest energy pathway is consecutive addition of three protons to the same site, which forms ammonia and an iron‐nitrido complex. In addition, the proton transfer step of complexes with the metal in various oxidation and spin states were tested and show that the pK a values of biomimetic mononuclear nitrogenase intermediates vary little with iron oxidation states. As such, the model gives several possible NH3 formation pathways depending on the order of electron/proton transfer, and all should be physically accessible in the natural system. These results may have implications for enzymatic nitrogenases and give insight into the catalytic properties of mononuclear iron centres.
“These Critics (Still) Don’t Write Enough about Women Artists”

This article addresses the extent and ways in which gender inequality in the newspaper coverage of arts and culture has changed in France, Germany, the Netherlands, and the United States, 1955-2005. Through a quantitative content analysis, we mapped all articles that appeared in two elite newspapers in each country in four sample years 1955, 1975, 1995, and 2005 (n = 15,379). First, despite increasing women’s employment in arts and culture and a quantitative feminization of journalism, elite newspaper coverage of women in arts and culture has hardly changed, making up about 20-25 percent consistently over the last 50 years. Second, our results show surprisingly few cross-national differences in the amount of the newspaper coverage devoted to women in arts and culture. Third, although women are underrepresented in the coverage of all artistic genres, there is some evidence of horizontal sex segregation—particularly in architecture (stereotypical masculine) and modern dance and fashion (stereotypical feminine)—as well as vertical sex segregation—in that attention to women has increased in “highbrow” genres that have declined in status. Finally, as the status of an actor type increases from laymen to artistic directors, the proportion of women decreases in newspaper attention to arts and culture.
Zigzag Learning for Weakly Supervised Object Detection

This paper addresses weakly supervised object detection with only image-level supervision at training stage. Previous approaches train detection models with entire images all at once, making the models prone to being trapped in sub-optimums due to the introduced false positive examples. Unlike them, we propose a zigzag learning strategy to simultaneously discover reliable object instances and prevent the model from overfitting initial seeds. Towards this goal, we first develop a criterion named mean Energy Accumulation Scores (mEAS) to automatically measure and rank localization difficulty of an image containing the target object, and accordingly learn the detector progressively by feeding examples with increasing difficulty. In this way, the model can be well prepared by training on easy examples for learning from more difficult ones and thus gain a stronger detection ability more efficiently. Furthermore, we introduce a novel masking regularization strategy over the high level convolutional feature maps to avoid overfitting initial samples. These two modules formulate a zigzag learning process, where progressive learning endeavors to discover reliable object instances, and masking regularization increases the difficulty of finding object instances properly. We achieve 47.6% mAP on PASCAL VOC 2007, surpassing the state-of-the-arts by a large margin.
Galaxysearch - Discovering the Knowledge of Many by Using Wikipedia as a Meta-Searchindex

We propose a dynamic map of knowledge generated from Wikipedia pages and the Web URLs contained therein. GalaxySearch provides answers to the questions we don’t know how to ask, by constructing a semantic network of the most relevant pages in Wikipedia related to a search term. This search graph is constructed based on the Wikipedia bidirectional link structure, the most recent edits on the pages, the importance of the page, and the article quality; search results are then ranked by the centrality of their network position. GalaxySearch provides the results in three related ways: (1) WikiSearch - identifying the most prominent Wikipedia pages and Weblinks for a chosen topic, (2) WikiMap - creating a visual temporal map of the changes in the semantic network generated by the search results over the lifetime of the returned Wikipedia articles, and (3) WikiPulse - finding the most recent and most relevant changes and updates about a topic.
Text-Independent Speaker Verification Using Long Short-Term Memory Networks

In this paper, an architecture based on Long Short-Term Memory Networks has been proposed for the text-independent scenario which is aimed to capture the temporal speaker-related information by operating over traditional speech features. For speaker verification, at first, a background model must be created for speaker representation. Then, in enrollment stage, the speaker models will be created based on the enrollment utterances. For this work, the model will be trained in an end-to-end fashion to combine the first two stages. The main goal of end-to-end training is the model being optimized to be consistent with the speaker verification protocol. The end- to-end training jointly learns the background and speaker models by creating the representation space. The LSTM architecture is trained to create a discrimination space for validating the match and non-match pairs for speaker verification. The proposed architecture demonstrate its superiority in the text-independent compared to other traditional methods.