Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical Feature Map Characterization in Fashion Interpretation

Recent advances in computer vision have been driven by the introduction of convolutional neural networks (ConvNets). Almost all existing methods that use hand-crafted features have been re-examined by ConvNets and achieved state of-the-art results on various tasks. However, how ConvNets features lead to outstanding performance is not completely interpretable to humans yet. In this paper, we propose a Hierarchical Feature Map Characterization (HFMC) pipeline in which semantic concepts are mapped to subsets of kernels based on feature maps and corresponding filter responses. We take a closer look at ConvNets feature maps and analyze how taking different sets of feature maps into account affect output accuracy. We first determine a set of kernels named Generic kernels and prune them from the network. We then extract a set of Semantic kernels and analyze their effects on the results. Generic kernels and Semantic kernels are extracted based on the co-occurrence and energy activation levels of feature maps in the network. To evaluate our proposed method, we design a visual recommendation system and apply our HFMC network to retrieve similar styles to query clothing items on the DeepFashion dataset. Extensive experiments demonstrate the effectiveness of our approach to the task of style retrieval on fashion products.
Comment on Schosser (2018) "Incentive Systems for Risky Investment Decisions under Unknown Preferences: Ortner et al. Revisited"

Schosser (Games 2018, 9, 26) claims to have found an alternative solution to design appropriate performance measures than the State-Contingent Relative Benefit Cost Allocation (RBCA) introduced by Ortner et al. (Management Accounting Research 2017, 36, 43–50), which he states is simpler and more powerful. However, this note reveals that the performance measures proposed by Schosser are, in fact, a specific subset of State-Contingent Robust RBCA performance measures and thus do not represent a new solution.
Non-fragile synchronisation of mixed delayed neural networks with randomly occurring controller gain fluctuations

ABSTRACT This study is concerned with the problem of non fragile synchronisation of mixed delayed neural networks with randomly occurring controller gain fluctuations. By using a novel mathematical approach and considering the neuron activation functions, improved delay-dependent stability results are formulated in terms of linear matrix inequalities (LMIs). An augmented new Lyapunov-Krasovskii functional (LKF) that contains double and triple integral terms is constructed to ensure the asymptotic stability of the error system which guarantees the master system synchronise with the slave system. Finally, numerical examples are provided to show the effectiveness of the proposed theoretical results.
Satisfiability Modulo Theories: state-of-the-art, contributions, project. (Satisfaisabilité Modulo Théories: état de l'art, contributions, projet)

The efficiency of Satisfiability Modulo Theories (SMT) solvers is dependent on the capability of theory reasoners to provide small conflict sets, i.e. small unsatisfiable subsets from unsatisfiable sets of literals. Decision procedures for uninterpreted symbols (i.e. congruence closure algorithms) date back from the very early days of SMT. Nevertheless, to the best of our knowledge, the complexity of generating smallest conflict sets for sets of literals with uninterpreted symbols and equalities had not yet been determined, although the corresponding decision problem was believed to be NP-complete. We provide here an NP-completeness proof, using a simple reduction from SAT.
From Social Information to Social Norms: Evidence from Two Experiments on Donation Behaviour

While preferences for conformity are commonly seen as an important driver of pro-social behaviour, only a small set of previous studies has explicitly tested the behavioural mechanisms underlying this proposition. In this paper, we report on two interconnected experimental studies that jointly provide a more thorough and robust understanding of a causal mechanism that links social information (i.e., information about the generosity of others) to donations via changing the perception of a descriptive social norm. In a modified dictator game, Experiment 1 re-investigates this mechanism adding further robustness to prior results by eliciting choices from a non-student sample and by implementing an additional treatment that controls for potential anchoring effects implied by the methods used in previous investigations. Experiment 2 adds further robustness by investigating the link between social information, (descriptive) norm perception and giving at the individual, rather than the group average, level. We find that an exogenous variation of social information influences beliefs about others’ contributions (descriptive social norm) and, through this channel, actual giving. An exploratory analysis indicates that this causal relationship is differently pronounced among the two sexes. We rule out anchoring effects as a plausible confound in previous investigations. The key findings carry over to the individual level.
Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net

Hyperspectral imaging can help better understand the characteristics of different materials, compared with traditional image systems. However, only high-resolution multispectral (HrMS) and low-resolution hyperspectral (LrHS) images can generally be captured at video rate in practice. In this paper, we propose a model-based deep learning approach for merging an HrMS and LrHS images to generate a high-resolution hyperspectral (HrHS) image. In specific, we construct a novel MS/HS fusion model which takes the observation models of low-resolution images and the low-rankness knowledge along the spectral mode of HrHS image into consideration. Then we design an iterative algorithm to solve the model by exploiting the proximal gradient method. And then, by unfolding the designed algorithm, we construct a deep network, called MS/HS Fusion Net, with learning the proximal operators and model parameters by convolutional neural networks. Experimental results on simulated and real data substantiate the superiority of our method both visually and quantitatively as compared with state-of-the-art methods along this line of research.
Risk of Cascading Blackouts Given Correlated Component Outages

Cascading blackouts typically occur when nearly simultaneous outages occur in <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> out of <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula> components in a power system, triggering subsequent failures that propagate through the network and cause significant load shedding. While large cascades are rare, their impact can be catastrophic, so quantifying their risk is important for grid planning and operation. A common assumption in previous approaches to quantifying such risk is that the <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> initiating component outages are statistically independent events. However, when triggered by a common exogenous cause, initiating outages may actually be correlated. Here, copula analysis is used to quantify the impact of correlation of initiating outages on the risk of cascading failure. The method is demonstrated on two test cases; a 2383-bus model of the Polish grid under varying load conditions and a synthetic 10 000-bus model based on the geography of the Western US. The large size of the Western US test case required development of new approaches for bounding an estimate of the total number of <inline-formula><tex-math notation="LaTeX">$N-3$</tex-math></inline-formula> blackout-causing contingencies. The results suggest that both risk of cascading failure, and the relative contribution of higher order contingencies, increase as a function of spatial correlation in component failures.
Minimizing The Age of Information: NOMA or OMA?

In this paper, we examine the potentials of Non-Orthogonal Multiple Access (NOMA), currently rivaling Orthogonal Multiple Access (OMA) in 3rd Generation Partnership Project (3GPP) standardization for future 5G networks Machine Type Communications (MTC), in the framework of minimizing the average Age of Information (AoI). By leveraging the notion of Stochastic Hybrid Systems (SHS), we find the total average AoI of the network in simple NOMA and conventional OMA environments. Armed with this, we provide a comparison between the two schemes in terms of average AoI. Interestingly, it will be shown that even when NOMA achieves better spectral efficiency in comparison to OMA, this does not necessarily translates into a lower average AoI in the network.
Redactable Blockchain in the Permissionless Setting

Bitcoin is an immutable permissionless blockchain system that has been extensively used as a public bulletin board by many different applications that heavily relies on its immutability. However, Bitcoin's immutability is not without its fair share of demerits. Interpol exposed the existence of harmful and potentially illegal documents, images and links in the Bitcoin blockchain, and since then there have been several qualitative and quantitative analysis on the types of data currently residing in the Bitcoin blockchain. Although there is a lot of attention on blockchains, surprisingly the previous solutions proposed for data redaction in the permissionless setting are far from feasible, and require additional trust assumptions. Hence, the problem of harmful data still poses a huge challenge for law enforcement agencies like Interpol (Tziakouris, IEEE S&P'18). We propose the first efficient redactable blockchain for the permissionless setting that is easily integrable into Bitcoin, and that does not rely on heavy cryptographic tools or trust assumptions. Our protocol uses a consensus-based voting and is parameterised by a policy that dictates the requirements and constraints for the redactions; if a redaction gathers enough votes the operation is performed on the chain. As an extra feature, our protocol offers public verifiability and accountability for the redacted chain. Moreover, we provide formal security definitions and proofs showing that our protocol is secure against redactions that were not agreed by consensus. Additionally, we show the viability of our approach with a proof-of-concept implementation that shows only a tiny overhead in the chain validation of our protocol when compared to an immutable one.
Wide-Scale Continuous Quality Improvement: A Study of Stakeholders' Use of Quality of Care Reports at Various System Levels, and Factors Mediating Use

Introduction: Increasing the use of evidence in healthcare policy and practice requires greater understanding of how stakeholders use evidence to inform policy, refine systems and change practice. Drawing on implementation theory, we have used system-focused participatory research to engage diverse stakeholders in using aggregated continuous quality improvement (CQI) data from Australian Indigenous primary health care settings to identify priority evidence-practice gaps, barriers/enablers and strategies for improvement. This article reports stakeholders' use or intended use of evidence at various levels of the system, and factors mediating use. Material and Methods: Interviews were undertaken with a purposeful sample of 30 healthcare stakeholders in different roles, organization types and settings in one Australian jurisdiction and with national participants, as part of the project's developmental evaluation. Qualitative data were analyzed to identify themes and categories relating to use of evidence. Results: Context-specific aggregated CQI data that were relatable to the diverse professional roles and practices provided an effective starting point for sharing perspectives, generating practice-based evidence and mobilizing evidence-use. Interviewees perceived the co-produced findings as applicable at different levels and useful for planning, policy development, supporting best practice and reflection, capacity strengthening and developing new research. Factors mediating use were commitment to best practice; the credibility of the evidence and its perceived relevance to work roles, contexts and decision needs; report format and language; facilitation and communication; competing work pressures and the organizational environment for change. Conclusions: This study found that primary health care stakeholders used evidence on quality of care for a variety of purposes. This could be linked to the interactive research processes used to engage stakeholders in different roles and settings in interpreting data, sharing and generating knowledge. Findings indicate that system-based participatory research using CQI data and iterative, interactive and systematic CQI-based methods can be applied at scale to support concurrent action for healthcare improvement at different system levels. Factors known to influence implementation should be addressed within the research design to optimize evidence use. Further research is needed to explore the utility of interactive dissemination for engaging healthcare stakeholders in informing policy and system change.
A Pilot Study of Behavioral, Physiological, and Subjective Responses to Varying Mental Effort Requirements in Attention-Deficit/Hyperactivity Disorder

Background: Attention-deficit/hyperactivity disorder (ADHD) is presumed to involve mental effort application difficulties. To test this assumption, we manipulated task difficulty and measured behavioral, as well as subjective and psychophysiological indices of effort. Methods: Fifteen adolescent ADHD boys and 16 controls performed two tasks. First, subjective estimates and behavioral and pupillary measures of effort were recorded across five levels of N-back task difficulties. Second, effort discounting was assessed. In the latter, participants made repeated choices between performing a difficult N-back task for a high reward versus an easier N-back task for a smaller reward. Results: Increasing task difficulty led to similar deteriorations in performance for both groups – although ADHD participants performed more poorly at all difficulty levels than controls. While ADHD and control participants rated the tasks equally difficult and discounted effort similarly, those with ADHD displayed slightly different pupil dilation patterns with increasing task difficulty. Conclusion: The behavioral results did not provide evidence for mental effort problems in adolescent boys with ADHD. The subtle physiological effects, however, suggest that adolescents with ADHD may allocate effort in a different way than controls.
Current Status and Issues Regarding Pre-processing of fNIRS Neuroimaging Data: An Investigation of Diverse Signal Filtering Methods Within a General Linear Model Framework

Functional near-infrared spectroscopy (fNIRS) research articles show a large heterogeneity in the analysis approaches and pre-processing procedures. Additionally, there is often a lack of a complete description of the methods applied, necessary for study replication or for results comparison. The aims of this paper were (i) to review and investigate which information is generally included in published fNIRS papers, and (ii) to define a signal pre-processing procedure to set a common ground for standardization guidelines. To this goal, we have reviewed 110 fNIRS articles published in 2016 in the field of cognitive neuroscience, and performed a simulation analysis with synthetic fNIRS data to optimize the signal filtering step before applying the GLM method for statistical inference. Our results highlight the fact that many papers lack important information, and there is a large variability in the filtering methods used. Our simulations demonstrated that the optimal approach to remove noise and recover the hemodynamic response from fNIRS data in a GLM framework is to use a 1000th order band-pass Finite Impulse Response filter. Based on these results, we give preliminary recommendations as to the first step toward improving the analysis of fNIRS data and dissemination of the results.
Identification, Functional Characterization, and Regulon Prediction of the Zinc Uptake Regulator (zur) of Bacillus anthracis – An Insight Into the Zinc Homeostasis of the Pathogen

Zinc has an abounding occurrence in the prokaryotes and plays paramount roles including catalytic, structural, and regulatory. Zinc uptake regulator (Zur), a Fur family transcriptional regulator, is connoted in maintaining zinc homeostasis in the pathogenic bacteria by binding to zinc and regulating the genes involved in zinc uptake and mobilization. Zinc homeostasis has been marginally scrutinized in Bacillus anthracis, the top-rated bio-terror agent, with no decipherment of the role of Zur. Of the three Fur family regulators in B. anthracis, BAS4181 is annotated as a zinc-specific transcriptional regulator. This annotation was further substantiated by our stringent computational and experimental analyses. The residues critical for zinc and DNA binding were delineated by homology modeling and sequence/structure analysis. ba zur existed as a part of a three-gene operon. Purified BaZur prodigiously existed in the dimeric form, indicated by size exclusion chromatography and blue native-polyacrylamide gel electrophoresis (PAGE). Computational and manual strategies were employed to decipher the putative regulon of ba zur, comprising of 11 genes, controlled by six promoters, each harboring at least one Zur box. The DNA binding capability of the purified BaZur to the upstream regions of the ba zur operon, yciC, rpmG, znuA, and genes encoding a GTPase cobalamine synthesis protein and a permease was ascertained by electrophoretic mobility shift assays. The regulon genes, implicated in zinc uptake and mobilization, were mostly negatively regulated by BaZur. The ba zur expression was downregulated upon exposure of cells to an excess of zinc. Conversely, it exhibited a marked upregulation under N, N, N′, N′-Tetrakis (2-pyridylmethyl) ethylenediamine (TPEN) mediated zinc-depleted environment, adding credence to its negative autoregulation. Moreover, an increase in the transcript levels of the regulon genes znuA, rpmG, and yciC upon exposure of cells to TPEN connoted their role in combating hypo-zincemic conditions by bringing about zinc uptake and mobilization. Thus, this study functionally characterizes Zur of B. anthracis and elucidates its role in maintaining zinc homeostasis.
Control of Leukocyte Trafficking by Stress-Associated Hormones

Leukocyte migration is a crucial process in both homeostatic and inflammatory conditions. The spatiotemporal distribution of immune cells is balanced between processes of cellular mobilization into the bloodstream, their adhesion to vascular beds and trafficking into tissues. Systemic regulation of leukocyte mobility is achieved by different signals including neuronal and hormonal cues, of which the catecholamines and glucocorticoids have been most extensively studied. These hormones are often associated with a stress response, however they regulate immune cell trafficking also in steady state, with effects dependent upon cell type, location, time-of-day, concentration, and duration of signal. Systemic administration of catecholamines, such as the sympathetic neurotransmitters adrenaline and noradrenaline, increases neutrophil numbers in the bloodstream but has different effects on other leukocyte populations. In contrast, local, endogenous sympathetic tone has been shown to be crucial for dynamic daily changes in adhesion molecule expression in the bone marrow and skeletal muscle, acting as a key signal to the endothelium and stromal cells to regulate immune cell trafficking. Conversely, glucocorticoids are often reported as anti-inflammatory, although recent data shows a more complex role, particularly under steady-state conditions. Endogenous changes in circulating glucocorticoid concentration induce redistribution of cells and potentiate inflammatory responses, and in many paradigms glucocorticoid action is strongly influenced by time of day. In this review, we discuss the current knowledge of catecholamine and glucocorticoid regulation of leukocyte migration under homeostatic and stimulated conditions.
How Live Music Moves Us: Head Movement Differences in Audiences to Live Versus Recorded Music

A live music concert is a pleasurable social event that is among the most visceral and memorable forms of musical engagement. But what inspires listeners to attend concerts, sometimes at great expense, when they could listen to recordings at home? An iconic aspect of popular concerts is engaging with other audience members through moving to the music. Head movements, in particular, reflect emotion and have social consequences when experienced with others. Previous studies have explored the affiliative social engagement experienced among people moving together to music. But live concerts have other features that might also be important, such as that during a live performance the music unfolds in a unique and not predetermined way, potentially increasing anticipation and feelings of involvement for the audience. Being in the same space as the musicians might also be exciting. Here we controlled for simply being in an audience to examine whether factors inherent to live performance contribute to the concert experience. We used motion capture to compare head movement responses at a live album release concert featuring Canadian rock star Ian Fletcher Thornley, and at a concert without the performers where the same songs were played from the recorded album. We also examined effects of a prior connection with the performers by comparing fans and neutral-listeners, while controlling for familiarity with the songs, as the album had not yet been released. Head movements were faster during the live concert than the album-playback concert. Self-reported fans moved faster and exhibited greater levels of rhythmic entrainment than neutral-listeners. These results indicate that live music engages listeners to a greater extent than pre-recorded music and that a pre-existing admiration for the performers also leads to higher engagement.