Miracle-dz/UniFAR-FTUs huggingface dataset:
Divisive Topics as Social Threats

The current work provides evidence for a psychological obstacle to the resolution of divisive social issues (e.g., affirmative action, drug legalization); specifically, people approach discussions of these issues with a threatened mind-set. Across three studies, it is shown that the prospect of discussing topics which divide social opinion is associated with threatened responding (the dissensus effect). Divisive discussion topics are associated with both a greater level of self-reported threat (Studies 1 and 3) and a greater tendency to perceive neutral faces as threatening (Study 2). Furthermore, the effect is shown to be robust across manipulations of social opinion (ratings of multiple social issues in Studies 1 and 2; fictional polling data in Study 3), and was not reducible to individual attitude extremity (Studies 1 and 3) or a valence effect (Study 2).
Quantitative prediction of 3D solution shape and flexibility of nucleic acid nanostructures

DNA nanotechnology enables the programmed synthesis of intricate nanometer-scale structures for diverse applications in materials and biological science. Precise control over the 3D solution shape and mechanical flexibility of target designs is important to achieve desired functionality. Because experimental validation of designed nanostructures is time-consuming and cost-intensive, predictive physical models of nanostructure shape and flexibility have the capacity to enhance dramatically the design process. Here, we significantly extend and experimentally validate a computational modeling framework for DNA origami previously presented as CanDo [Castro,C.E. , Kilchherr,F. , Kim,D. -N. , Shiao,E.L. , Wauer,T. , Wortmann,P., Bathe,M. , Dietz,H. (2011) A primer to scaffolded DNA origami. Nat. Meth. , 8, 221–229. ]. 3D solution shape and flexibility are predicted from basepair connectivity maps now accounting for nicks in the DNA double helix, entropic elasticity of single-stranded DNA, and distant crossovers required to model wireframe structures, in addition to previous modeling (Castro,C.E., et al.) that accounted only for the canonical twist, bend and stretch stiffness of double-helical DNA domains. Systematic experimental validation of nanostructure flexibility mediated by internal crossover density probed using a 32-helix DNA bundle demonstrates for the first time that our model not only predicts the 3D solution shape of complex DNA nanostructures but also their mechanical flexibility. Thus, our model represents an important advance in the quantitative understanding of DNA-based nanostructure shape and flexibility, and we anticipate that this model will increase significantly the number and variety of synthetic nanostructures designed using nucleic acids.
An Approach to Aid the Understanding and Maintenance of Input Validation

Input validation is an essential and a very important feature in any software system that has intensive interaction with its users. In this paper, we introduce some invariant properties with regards to input validation through analyzing the control and data dependency among inputs accessed and effects raised in a program. We then propose a method for the automated recovery of input validation from program source code. Based on the information recovered, we present the techniques to aid the understanding and maintenance of the feature using program slicing. A prototype tool has been implemented to validate the approach, and the empirical results show that the proposed approach can be very useful and effective for both experienced and inexperienced programmers
Blind Source Separation of Instantaneous Mixtures

Blind source separation of images and voice signals is a well known and well studied subject. Solutions for this problem have various applications, such as separation of voices of multiple speakers in the same room, denoising, separation of reflections superimposed on images, and more. Classical time/position invariant Blind Source Separation is usually solved using Independent Component Analysis (ICA), which attempts to find statistically independent signals as a linear combination of the mixed signals, or by using Sparse Component Analysis (SCA) that estimates the mixing matrix by analyzing the geometry of the problem and uses scatter plots of the mixed signals to estimate co-linear centroids of the scattered data, where each centroid corresponds to a column of the mixing matrix. Most of the studies in the field assume time/position invariant signal combinations, although many real life problems are not such. Recently, in his PhD thesis, Ran Kaftory has proposed an extension of the SCA method to solve multiple families of the time/position varying problems. He has shown that for instantaneous time/position varying mixtures, the problem of lines estimation transforms to estimation of nonlinear curves. In this work we explore the separation of instantaneous time/position varying mixtures for which the parametric structure of the mixtures family is known apriori . We show that the geometric approach can also be viewed as Maximum Likelihood (ML) problem, when sparsification is applied to the mixed signals. We propose a multi-staged SCA algorithm for separation of time/position invariant mixtures and extend the solution to a subset of time/position varying mixtures where the reconstruction is performed by curve fitting techniques and nearest neighbor clustering. In addition to the geometric approach, we extend the wellknown technique of ICA by the ML approach, to the case of time/position varying instantaneous mixtures. We show that ML approach to the time/position varying separation problem can be developed from an information theoretic perspective as a joint Entropy minimization of the unmixed signals. We prove that although the problem is non-convex, and may require non-linear optimization techniques to solve, under certain conditions the correct signals separation constitutes a global maximum of the ML optimization problem. We conclude by showing that the ML approach provides promising results, but due to the non-linear nature of the problem, its optimization is challenging and SCA-based approaches can be used as a complimentary technique to circumvent some of the difficulties originating from the non-linearities of the problem.
A comparative study of Genetic Algorithms for its applications in Object oriented testing

Genetic Algorithms are heuristic approach for forming the bases of search based algorithms. It applies the mechanism of the natural selection of genes & the phenomena's associated with the genetics like mutation, crossover, and replication to provide solutions in some complex searches. In this paper, we have reviewed their applications in context of the Object oriented paradigm thus proving their usefulness in providing solutions to the various issues related to their testing.
The Group Lasso for Stable Recovery of Block-Sparse Signal Representations

Group Lasso is a mixed l1/l2-regularization method for a block-wise sparse model that has attracted a lot of interests in statistics, machine learning, and data mining. This paper establishes the possibility of stably recovering original signals from the noisy data using the adaptive group Lasso with a combination of sufficient block-sparsity and favorable block structure of the overcomplete dictionary. The corresponding theoretical results about the solution uniqueness, support recovery and representation error bound are derived based on the properties of block-coherence and subcoherence. Compared with the theoretical results on the parametrized quadratic program of conventional sparse representation, our stability results are more general. A comparison with block-based orthogonal greedy algorithm is also presented. Numerical experiments demonstrate the validity and correctness of theoretical derivation and also show that in case of noisy situation, the adaptive group Lasso has a better reconstruction performance than the quadratic program approach if the observed sparse signals have a natural block structure.
Motor functions of the Brocas region

Brocas region in the dominant cerebral hemisphere is known to mediate the production of language but also contributes to comprehension. This region evolved only in humans and is constituted of Brodmanns areas 44 and 45 in the inferior frontal gyrus. There is, however, evidence that Brocas region overlaps, at least in part, with the ventral premotor cortex. We summarize the evidence that the motor related part of Brocas area is localized in the opercular portion of the inferior frontal cortex, mainly in area 44 of Brodmann. According to our own data, there seems to be a homology between Brodmann area 44 in humans and the monkey area F5. The non-language related motor functions of Brocas region comprise complex hand movements, associative sensorimotor learning and sensorimotor integration. Brodmanns area 44 is also a part of a specialized parieto-premotor network and interacts significantly with the neighboring premotor areas.
L Earning with a Dversary

In this paper, we propose a method, learning with adversary, to learn a robust network. Our method takes finding adversarial examples as its mediate step. A new and simple way of finding adversarial examples are presented and experimentally shown to be more ‘efficient’. Lastly, experimental results shows our learning method greatly improves the robustness of the learned network.
Pervasive privacy: A practical context-aware system to preserve privacy on android smartphones

Advent of instant messaging systems has increased the concerns about privacy violation. Although, smartphones contain a lot of personal information, their operating systems have not provided a complete compliance with privacy preserving principles. As a result, providing a smart guard for private information on smartphones is required. The proposed system should be able to detect which information could be shared with other users and warn in the case of unintended sensitive information leakages, as well. In this paper, we propose a context-aware real-time system to preserve privacy on android smartphones with mentioned properties using information flow tracking techniques. The proposed system detects privacy violation in Android phones based on users relations in a social network created by the system itself.
Centaurus A: constraints on the nature of the giant lobe filaments from XMM-Newton observations

We report on deep XMM-Newton observations of the vertex filament in the southern giant lobe of the Fanaroff–Riley class I radio galaxy Centaurus A. We find no X-ray excess from the filament region and place a 3? upper limit on the 1 keV flux density of the filament of 9.6 nJy. This directly constrains the electron density and magnetic field strength in the filament. For the first time in an individual filament, we show that so long as the particle index ? 2, the excess in synchrotron emissivity cannot be produced purely by excess electrons: the filament magnetic field strength must be higher than in the giant lobes as a whole, and close to or above the equipartition value for the filament. The filaments are not significantly overpressured with respect to the surrounding lobe with a pressure provided by relativistic electrons.
Rethinking offload: How to intelligently combine WiFi and small cells?

As future small cell base stations (SCBSs) are set to be multi-mode capable (i.e., transmitting on both licensed and unlicensed bands), a cost-effective integration of both technologies coping with peak data demands is crucial. Using tools from reinforcement learning, a distributed cross-system traffic steering framework is proposed whereby SCBSs leverage WiFi, to autonomously optimize their long-term performance over the licensed spectrum band, as a function of the traffic load and users' heterogeneous Quality of Service (QoS) requirements. The proposed traffic steering solution is validated in a Long-Term Evolution (LTE) simulator augmented with WiFi hotspots. Remarkably, it is shown that the proposed cross-system learning-based approach outperforms several benchmark algorithms and traffic steering policies, with gains reaching up to 200% when using a traffic-aware scheduler as compared to the classical proportional fair (PF) scheduler.
Hyperoxic Vasoconstriction of Human Pulmonary Arteries: A Novel Insight into Acute Ventricular Septal Defects

Objectives. Acute rises in pulmonary artery pressures following postinfarction ventricular septal defects present a challenge. We hypothesised that the abnormally high oxygen content exposure to the pulmonary arteries may be a factor. We investigated the contractile responses of human pulmonary arteries to changes in oxygen tension. Methods. Isometric tension was measured in large and medium sized pulmonary artery rings obtained from lung resections for patients with bronchial carcinoma (n = 30). Fresh rings were mounted in organ baths bubbled under basal conditions with hyperoxic or normoxic gas mixes and the gas tensions varied during the experiment. We studied whether voltage-gated calcium channels and nitric oxide signalling had any role in responses to oxygen changes. Results. Hypoxia caused a net mean relaxation of 18.1% ± 15.5 (P < 0.005) from hyperoxia. Subsequent hyperoxia caused a contraction of 19.2% ± 13.5 (P < 0.005). Arteries maintained in normoxia responded to hyperoxia with a mean constriction of 14.8% ± 3.9 (P < 0.005). Nifedipine inhibited the vasoconstrictive response (P < 0.05) whilst L-NAME had no effect on any hypoxic vasodilatory response. Conclusions. We demonstrate that hyperoxia leads to vasoconstriction in human pulmonary arteries. The mechanism appears to be dependent on voltage-gated calcium channels. Hyperoxic vasoconstriction may contribute to acute rises in pulmonary artery pressures.
Spatial-Temporal Event Detection from Geo-Tagged Tweets

As one of the most popular social networking services in the world, Twitter allows users to post messages along with their current geographic locations. Such georeferenced or geo-tagged Twitter datasets can benefit location-based services, targeted advertising and geosocial studies. Our study focused on the detection of small-scale spatial-temporal events and their textual content. First, we used Spatial-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN) to spatially-temporally cluster the tweets. Then, the word frequencies were summarized for each cluster and the potential topics were modeled by the Latent Dirichlet Allocation (LDA) algorithm. Using two years of Twitter data from four college cities in the U.S., we were able to determine the spatial-temporal patterns of two known events, two unknown events and one recurring event, which then were further explored and modeled to identify the semantic content about the events. This paper presents our process and recommendations for both finding event-related tweets as well as understanding the spatial-temporal behaviors and semantic natures of the detected events.
Knowledge Base Reduction for Verifying Rule Bases Containing Equations

The use of Knowledge Base Reduction to verify rule bases was first developed for propositional rule bases, and then extended to handle quantified variables in rules. However, these techniques did not reason about equations. This paper gives a formal specification of KB-Reducer3, an analysis tool for rule bases containing equations. The algorithm for KB-Reducer3 is described, and a brief discussion on its use and limitations is provided.
TAX MIMICKING AMONG BELGIAN MUNICIPALITIES

Recent empirical studies show that U.S. states' and local governments' tax policy is copied among neighboring jurisdictions. We present empirical evidence on such tax mimicking among Belgian municipalities. Belgian data offer important advantages. The (589) municipalities operate within an institutionally homogeneous setting. Moreover, the data allow us to concentrate on tax rates (instead of tax burdens). Our results support the previous findings, suggesting that mimicking behavior is not an artifact of the U.S. system. We also find that mimicking effects extend beyond municipalities' immediate neighbors.
N fertilizer and harvest impacts on bioenergy crop contributions to SOC

Belowground root biomass is infrequently measured and simply represented in models that predict landscape‐level changes to soil carbon stocks and greenhouse gas balances. Yet, crop‐specific responses to N fertilizer and harvest treatments are known to impact both plant allocation and tissue chemistry, potentially altering decomposition rates and the direction and magnitude of soil C stock changes and greenhouse gas fluxes. We examined switchgrass (Panicum virgatum L.) and corn (Zea mays L.,) yields, belowground root biomass, C, N and soil particulate organic matter‐C (POM‐C) in a 9‐year rainfed study of N fertilizer rate (0, 60, 120 and 180 kg N ha−1) and harvest management near Mead, NE, USA. Switchgrass was harvested with one pass in either August or postfrost, and for no‐till (NT) corn, either 50% or no stover was removed. Switchgrass had greater belowground root biomass C and N (6.39, 0.10 Mg ha−1) throughout the soil profile compared to NT‐corn (1.30, 0.06 Mg ha−1) and a higher belowground root biomass C:N ratio, indicating greater recalcitrant belowground root biomass C input beneath switchgrass. There was little difference between the two crops in soil POM‐C indicating substantially slower decomposition and incorporation into SOC under switchgrass, despite much greater root C. The highest N rate decreased POM‐C under both NT‐corn and switchgrass, indicating faster decomposition rates with added fertilizer. Residue removal reduced corn belowground root biomass C by 37% and N by 48% and subsequently reduced POM‐C by 22% compared to no‐residue removal. Developing productive bioenergy systems that also conserve the soil resource will require balancing fertilization that maximizes aboveground productivity but potentially reduces SOC sequestration by reducing belowground root biomass and increasing root and soil C decomposition.
XSEM-A Conceptual Model for XML Data

Recently XML is the standard format used for the exchange of data between information systems and is also frequently applied as a logical database model. If we use XML as a logical database model we need a conceptual model for the description of its semantics. In this paper, we describe our work on a new conceptual model for XML called XSEM created as a combination of several approaches applied in the area of conceptual modeling for XML.
Molecular Characterization of Recent and Archived Erysipelothrix rhusiopathiae Isolates

Cases of erysipelas have increased considerably in 2001–2002. Diagnosis of erysipelas is typically confirmed by culture and in a limited number of cases the isolates are serotyped. Reagents for serotyping are limited and are available only at National Veterinary Service Laboratory (NVSL). In this study, we utilize pulsed-field gel electrophoresis (PFGE) to differentiate genotypes and compare archived and recent isolates. Seventy-three erysipelas field isolates (58 recent, 15 historical) and four live vaccine strains were genetically characterized. Fortysix isolates were found to belong to genotype 1A(I), three were genotype 1A(III), each one was genotype 1A(IV), 1A(V), 1A(VI), and two isolates were designated as 1A(VII). Nine different genotypes were identified among the serotype 1b isolates [1B(I-IX)]. Within serotype 2, three genotypes were identified: 2A, 2B, and 2C. The four vaccine strains tested in this study belong to the genotype group 1A(II), closely related to genotype 1A. The vaccine strains and the most common field isolates genotype 1A(I) shared 78.6% identity based on PFGE pattern.
How Can Corticospinal Tract Neurons Contribute to Ipsilateral Movements? A Question With Implications for Recovery of Motor Functions

In this review, the authors discuss some recent findings that bear on the issue of recovery of function after corticospinal tract lesions. Conventionally the corticospinal tract is considered to be a crossed pathway, in keeping with the clinical findings that damage to one hemisphere, for example, in stroke, leads to a contralateral paresis and, if the lesion is large, a paralysis. However, there has been great interest in the possibility of compensatory recovery of function using the undamaged hemisphere. There are several substrates for this including ipsilaterally descending corticospinal fibers and bilaterally operating neuronal networks. Recent studies provide important evidence bearing on both of these issues. In particular, they reveal networks of neurons interconnecting two sides of the gray matter at both brainstem and spinal levels, as well as intrahemispheric transcallosal connections. These may form “detour circuits” for recovery of function, and here the authors will consider some possibilities for exploiting these networks for motor control, even though their analysis is still at an early stage.
NUCLEOSYNTHESIS MODES IN THE HIGH-ENTROPY WIND OF TYPE II SUPERNOVAE: COMPARISON OF CALCULATIONS WITH HALO-STAR OBSERVATIONS

While the high-entropy wind (HEW) of Type II supernovae remains one of the more promising sites for the rapid neutron-capture (r-) process, hydrodynamic simulations have yet to reproduce the astrophysical conditions under which the latter occurs. We have performed large-scale network calculations within an extended parameter range of the HEW, seeking to identify or to constrain the necessary conditions for a full reproduction of all r-process residuals Nr,☉ = N☉−Ns,☉ by comparing the results with recent astronomical observations. A superposition of weighted entropy trajectories results in an excellent reproduction of the overall Nr,☉ pattern beyond Sn. For the lighter elements, from the Fe group via Sr–Y–Zr to Ag, our HEW calculations indicate a transition from the need for clearly different sources (conditions/sites) to a possible co-production with r-process elements, provided a range of entropies are contributing. This explains recent halo-star observations of a clear noncorrelation of Zn and Ge and a weak correlation of Sr–Zr with heavier r-process elements. Moreover, new observational data on Ru and Pd also seem to confirm a partial correlation with Sr as well as the main r-process elements (e.g., Eu).