Miracle-dz/UniFAR-FTUs huggingface dataset:
DARKNESS: A Microwave Kinetic Inductance Detector Integral Field Spectrograph for High-contrast Astronomy

We present DARKNESS (the DARK-speckle Near-infrared Energy-resolving Superconducting Spectrophotometer), the first of several planned integral field spectrographs to use optical/near-infrared Microwave Kinetic Inductance Detectors (MKIDs) for high-contrast imaging. The photon counting and simultaneous low-resolution spectroscopy provided by MKIDs will enable real-time speckle control techniques and post-processing speckle suppression at frame rates capable of resolving the atmospheric speckles that currently limit high-contrast imaging from the ground. DARKNESS is now operational behind the PALM-3000 extreme adaptive optics system and the Stellar Double Coronagraph at Palomar Observatory. Here, we describe the motivation, design, and characterization of the instrument, early on-sky results, and future prospects.
An extended XMM-Newton observation of the Seyfert galaxy NGC 4051 - I. Evidence for a shocked outflow

An extended XMM–Newton observation of the Seyfert 1 galaxy NGC 4051 has revealed a rich absorption line spectrum indicating the presence of a photoionized outflow with a wide range of velocities and ionization parameter. At low continuum fluxes an emission line spectrum is well defined with both narrow and broad emission components of several abundant metal ions. The absorption line velocity structure and a broad correlation of velocity with ionization parameter are consistent with an outflow scenario where a highly ionized, high-velocity wind, perhaps launched during intermittent super-Eddington accretion, runs into the interstellar medium or previous ejecta, losing much of its kinetic energy in the resultant strong shock. We explore the possibility that a quasi-constant soft X-ray component may be evidence of post-shock cooling. This revised view of active galactic nuclei (AGN) outflows is consistent with multiple minor Eddington accretion episodes creating a momentum-driven feedback linking black hole and host galaxy growth.
Erasmus Q-Intelligence Forecasting Dutch GDP Incorporating Sentiment from Dutch News

To facilitate stable economic development and prevent bankruptcy both businessand governmental institutions need reliable estimates of current GDP. In the Netherlands, however, official GDP estimates have a significant publication lag of 45 days after the end of a quarter. The EICIE model developed by de Groot and Franses (2006) made the first step by using staffing data from a temp agency. This data is available a week after the end of a quarter. To improve the predictive accuracy of EICIE, a novel approach to utilize news articles by applying sentiment analysis techniques is developed in this thesis. The approach reduces the publication lag while improving the accuracy of the estimates. Moreover, some dimensionality reduction and variable selection methods have been shown to considerably boost predictive performance, when faced with the sparse data sets generated by the approach adopted in this thesis. The prediction accuracy is significantly improved upon with a 65.4% improvement compared to the EICIE model if both models are re-estimated after each forecast and an 81.6% improvement in prediction accuracy if the models are only estimated once with the training data.
Alaskan brown bears, humans, and habituation

Abstract We present a new paradigm for understanding habituation and the role it plays in brown bear (Ursus arctos) populations and interactions with humans in Alaska. We assert that 3 forms of habituation occur in Alaska: bear-to-bear, bear-to-human, and human-to-bear. We present data that supports our theory that bear density is an important factor influencing a bear's overt reaction distance (ORD); that as bear density increases, overt reaction distance decreases, as does the likelihood of bear–human interactions. We maintain that the effects of bear-to-bear habituation are largely responsible for not only shaping bear aggregations but also for creating the relatively safe environment for bear viewing experienced at areas where there are high densities of brown bears. By promoting a better understanding of the forces that shape bear social interactions within populations and with humans that mingle with them, we can better manage human activities and minimize bear–human conflict.
ONE- AND TWO-STAGE IMPLICIT INTERVAL METHODS OF RUNGE-KUTTA TYPE

Interval methods for solving the initial value problem are interesting due to interval-solutions obtained by such methods which contain their errors. Computer implementations of interval methods in floating-point interval arithmetic together with the representation of initial data in the form of minimal machine intervals, i. e. by intervals which ends are equal or neighboring machine numbers, yield interval solutions which contain all possible numerical errors. Explicit interval methods of Runge-Kutta type have been considered and analysed by Šokin [3,7]. In this paper we try to extend his approach for implicit methods. A reason to do this follows from a well-known fact concerning convential implicit Runge-Kutta methods higher orders of accuracy can be obtained than for explicit methods. This paper is dealt with oneand two-stage implicit interval methods of Runge-Kutta type, which are presented in sections 3 and 4. We prove that the exact solution of the initial value problem belongs to interval-solutions obtained by both kinds of these methods (section 5). In section 6 some approximations of the widths of interval-solution are given.
Crop Yield and Temperature Changes in North China during 601–900 AD

Depending on the descriptions of crop yield and social response to crop failure/harvest from Chinese historical documents, we classified the crop yield of North China during 601–900 AD into six categories and quantified each category to be the crop yield grades. We found that the regional mean crop yield had a significant () negative trend at the rate of −0.24% per decade. The interannual, multiple-decadal, and century-scale variability accounted for ~47%, ~30%, and ~20% of the total variations of crop yield, respectively. The interannual variability was significantly () persistent across the entire period. The multiple-decadal variability was more dominant after 750 AD than that before 750 AD, while the century-scale variability was more dominant before 750 AD than that after 750 AD. The variations of crop yield could be partly explained by temperature changes. On one hand, the declining trend of crop yield cooccurred with the climate cooling trend from 601 to 900 AD; on the other hand, the crop yield was positively correlated with temperature changes at 30-year resolution with the correlation coefficient of 0.59 (). These findings supported that high (low) crop yield occurred in the warming (cooling) climate.
An Agent Based Model of Tularemia

Francisella tularensis is a formidable intracellular pathogen. Upon inhalation it leads to systemic disease (tularemia) with a high mortality rate. We sought here to develop a computational tool for infections with this class. A bio-threat microbe for which extensive datasets are not available to infer parameters that might determine the outcome of the infection. We present a two-compartment agent based model that simulates inhalational tularemia with subsequent dissemination to the liver and incorporates experimental data and validated general parameters of host defense mechanisms. This systems approach suggests that the initial number of macrophages, the probability of dissemination, and the initial clearance rate of bacteria correlate with the outcome of infections with Francisella. These findings underline the importance of early innate immune defense mechanisms in the prevention of tularemia.
Enhancement of Under-Exposed Image for Object Tracking Algorithm Through Homomorphic Filtering and Mean Histogram Matching

Object tracking through video or image becomes more popular in recent years. Indeed, clear and high contrast images are essential to attain good tracking results. The problem arises when the object in an image or video is under-exposed, resulting it to be hardly visible and differentiated from the background. Existing methods are able to solve some of the aforementioned problems, but produce other problems such as over-enhanced effect and color distortion. Thus, the object of interest may become untraceable due to these distortions. This paper proposes an image enhancement method to improve under-exposed images or videos through homomorphic filtering and mean histogram matching, in order to produce more visible and traceable objects. This method integrates homomorphic filtering method and histogram modification technique which consists of histogram matching and dual-histogram stretching. The proposed method is designed to reduce non-uniform illumination while increasing image/video contrast and visibility. The experiment results show that the proposed method outperforms some state-of-the-art methods in terms of visibility and contrast level on some standard benchmark database.
Teleoperated Semi-Autonomous Control of the LWR and a Humanoid Hand via the Myo Armband

In this paper we describe a teleoperation system, which controls a semi-autonomous 7 degrees-of-freedom robot arm equipped with a five-finger hand via a myo armband, utilizing the gyroscope and EMG sensor data. An object manipulation scenario including grasping and object moving are used to pre-evaluate the benefits of such a setup.
An Iterative Approach to Model Merging for Speech Pattern Discovery

This paper introduces a novel approach to automatically discover recurrent speech patterns from multi-speaker corpus without a priori knowledge. The proposed approach is based on the sub-word acoustic units and it iteratively concatenates the most-likely joint sub-word units to produce a longer acoustic unit till our proposed stop criterion is satisfied. Among the resulting acoustic units, the units with the most stable number of occurrences are selected as the lexicon. The proposed approach has been applied to automatically discover English words from TIDIGIT corpus. The experimental results measured by F1 score showed the proposed approach can effectively detect and extract the recurrent patterns. This technique can be used for lexicon generation from an unknown speech corpus or in audio content summarization.
Capacity, Control, or Both – Which Aspects of Working Memory Contribute to Children’s General Fluid Intelligence?

: Starting from the assumption that working memory capacity is an important predictor of general fluid intelligence, we asked which aspects of working memory account for this relationship. Two theoretical stances are discussed. The first one posits that the important explanatory factor is storage capacity, roughly defined as the number of chunks possible to hold in the focus of attention. The second one claims that intelligence is explained by the efficiency of executive control, for instance, by prepotent response inhibition. We investigated 96 children at the age between 10 and 13. They completed a version of the n-back task that allows assessment of both storage capacity and inhibitory control. They also completed Raven’s Progressive Matrices as the fluid intelligence test and the Test for Creative Thinking – Drawing Production, for control purposes. We found that Raven’s scores correlated negatively with the number of unnecessary responses to irrelevant stimuli but they did not correlate with the number of signal detections. We conclude that children’s fluid intelligence depends on inhibitory control, with no relationship with storage capacity.
Cyanobacterial bloom termination: the disappearance of Planktothrix rubescens from Lake Bourget (France) after restoration

Summary Like many large freshwater ecosystems in Europe, Lake Bourget suffered from eutrophication during the second part of the 20th century and since the 1980s has been partially restored by reductions in nutrient loadings. Here, we analyse a data set comprised of field measurements of physicochemical and biological variables in Lake Bourget covering the period from 2004 to 2011 and complement this data set with laboratory experiments, to gain an understanding of the changes in phytoplankton community structure during recent years and drivers of these changes. Between 1995 and 2008, Lake Bourget was characterised by the proliferation of the red-coloured filamentous and toxic cyanobacterium Planktothrix rubescens, comprising 34.1–52.6% of the total phytoplanktonic biomass between 2004 and 2008. In 2009, although the contribution of P. rubescens to the total biomass was still considerable (25.3%), it was significantly lower (P < 0.05) compared with previous years. The cyanobacterium disappeared completely during the autumn to winter transition of 2009/2010 and has not been recorded since this time. Concomitantly, total phytoplanktonic biomass declined sharply and a new phytoplanktonic community occurred consisting predominantly of mixotrophic genera, such as Dinobryon spp. , Rhodomonas, Cryptomonas and a variety of different diatoms such as Stephanodiscus, Cyclotella and Fragilaria. Our findings suggest declines in phosphorus concentration as a key variable in bloom termination, although a number of other factors could also be important, such as temperature-dependent water column mixing, light availability, zooplankton grazing and seasonal cyanobacterial inoculums.
Label maps fusion for the marginal segmentation of multi-component images

In this paper, we propose a new technique for merging the label maps obtained by the marginal segmentation of a multi-component image. In the marginal segmentation, each component of the multi component image is independently segmented by labeling the pixels of the same class with the same label. Therefore the number of label maps corresponds to the number of components in the image. It is then necessary to merge them in order to have a single label map, i.e. a single segmented image. In the most merging techniques, the compatibility links between these maps are performed at prior by making the correspondences between their labels. However the various components are segmented and labeled independently, label maps are considered as independent sources. It is then difficult to establish the relationship compatibilities between labels. The method we propose does not assume any compatibility link at prior. The label maps are combined by superposition. Unfortunately, an over-segmentation is produced. To cope with this problem, the insignificant regions and classes are eliminated. Finally, classes are grouped by using hierarchical agglomerative clustering algorithm. Tests performed on color and satellite images show the effectiveness of this method and its superiority compared to the vector segmentation. Self Organizing Maps algorithm is used during the segmentation process in the both marginal and vector segmentations.
The SEEMPAD Dataset for Emphatic and Persuasive Argumentation

English. Emotions play an important role in argumentation as humans mix rational and emotional attitudes when they argue with each other to take decisions. The SEEMPAD project aims at investigating the role of emotions in human argumentation. In this paper, we present a resource resulting from two ﬁeld experiments involving humans in debates, where arguments put forward during such debates are annotated with the emotions felt by the participants. In addition, in the second experiment, one of the debaters plays the role of the persuader , to convince the other participants about the goodness of her viewpoint applying different per-suasion strategies. To the best of our knowledge, this is the ﬁrst dataset of arguments annotated with the emotions collected from the participants of a debate, using facial emotion recognition tools.
Human action recognition in image sequences based on a two-stream convolutional neural network classifier

The technological evolution in the last decades has contributed to the improvement of computers with excellent processing and storage capacity and cameras with higher digital quality. Nowadays, video generation devices are simpler to manipulate, more portable and with lower prices. This allowed easy generation, storage and transmission of large amounts of videos, which demands a form of automatic analysis, independent of human assistance for evaluation and exhaustive search of videos. There are several applications that can benefit from such techniques such as virtual reality, robotics, tele-medicine, human-machine interface, tele-surveillance and assistance to the elderly in timely caregiving. This work describes a method for human action recognition in a sequence of images using two convolutional neural networks (CNNs). The Spatial network stream is trained using frames from a sequence of images with transfer learning techniques from the VGG16 network (pre-trained for classification of objects). The other stream channel, Temporal stream, receives stacks of Dense Optical Flow (DOF) as input and it is trained from scratch. The technique was tested in two public action video datasets: Weizmann and UCF Sports. In the Spatial stream approach we achieve 84.44% of accuracy on Weizmann dataset and 78.46% on UCF Sports dataset. With the Temporal and Spatial streams combined, we obtained an accuracy rate of 91.11% for the Weizmann dataset.
Reheating of Zinc-titanate Sintered Specimens

The scope of this work was observing dimensional and heat transfer changes in ZnTiO3 samples during heating in nitrogen and air atmosphere. Interactions of bulk specimens with gaseous surrounding induce microstructure changes during heating. Sintered ZnTiO3 nanopowder samples were submitted to subsequent heating. Dilatation curves and thermogravimetric with simultaneous differential thermal analysis TGA/DTA curves were recorded. Reheating was performed in air and nitrogen atmospheres. Reheated samples obtained at different characteristic temperatures in air were analyzed by X-ray diffraction (XRD). Microstructures obtained by scanning electron microscopy (SEM) of reheated sintered samples are presented and compared. Reheating in a different atmosphere induced different microstructures. The goal was indicating possible causes leading to the microstructure changes.
Red blood cell segmentation using guided contour tracing

We present a model-based contour tracing approach to the problem of automatically segmenting a Scanning Electron Microscope image of red blood cells. These images characteristically have high numbers of overlapping cells and relatively smooth contours. We provide a brief look into what problems conventional algorithms encounter when attempting to segment these images, and go on to show that a model-based contour tracing approach attains high levels of accuracy and almost no false negatives.
Testing if Healthy Perfectionism Enhances Academic Achievement in Australian Secondary School Students

Although considerable evidence has confirmed that measures of intelligence and conscientiousness substantially predict academic achievement, other personality variables have attracted only limited research. The purpose of this study was to test the extent to which intelligence and personality variables, including perfectionism, accounted for academic grades. Participants were 180 (65 males) secondary school students in years 11-12. They completed tests for fluid and crystallised abilities (Gf, Gc), Conscientiousness (C), Openness to Experience (O), Neuroticism (N), Need for Cognition (NFC) and the Frost Multidimensional Perfectionism Scale, which was used to define healthy perfectionism (HP) and unhealthy perfectionism (UHP). Gender differences for all measures were negligible and not considered further. One aspect of HP (personal standards) overlapped moderately with NFC but HP and NFC appeared to be different constructs. Hierarchical regression found that Gf, Gc and C together accounted for 27% of variance in academic grade, with HP explaining an additional 6%. Further contribution from NFC was not statistically significant. N correlated with UHP but did not impact grade. Higher concern about parental criticisms correlated (r = -.27) with lower academic grade.
Dynamics of the Edgeworth-Kuiper Belt beyond 50 AU - Spread of a primordial thin disk

In this paper we report numerical simulations of the dynamical evolution of the region a > 50 AU. We found that some dynamical effects such as high-order secular resonances with the rate of precession of Neptune's node of the form k u Ω − u ΩNep with k = 4,5, . or combined mean motion resonances with Uranus and Neptune of the form knN + jnU +mn ∼ 0m ay increase the area of a very thin primordial disk in this region by a factor of up to 2 after 4.5 Gy of evolution.
Comparison of ablation efficacy with cryoballoon or radiofrequency for the treatment of atrial fibrillation : a meta-analysis of randomized controlled trials

Radiofrequency catheter ablation (RFCA) of pulmonary vein isolation (PVI) has been the standard strategy for treatment of atrial fibrillation (AF). Cryoballoon ablation (CBA) is also frequently adopted. Here, we conducted a meta-analysis of randomized controlled trials (RCTs) to compare the efficacy of CBA and RFCA in the treatment of AF. PubMed, EMBASE and Cochrane Library were searched up to May 2016, using Boolean operators as follows: (atrial fibrillation OR pulmonary vein isolation) AND (cryoballoon OR radiofrequency ablation). All RCTs directly comparing the efficacy between CBA and RFCA were retrieved. Eight out of 367 studies, involving 1849 patients, were included in this study. The fluoroscopic time was significantly lower in the RFCA group compared with the CBA group (mean difference 2.94; 95% confidence interval [95% CI]: 0.34 to 5.54, P=0.03). However, no significant difference in total procedure time between these two groups by mean difference -11.2 (95% CI: -34.53 to 12.13, P=0.35); Total complications were not significantly different between the two groups (relative risk [RR]: 1.21; 95% CI: 0.71 to 2.04, P=0.49); however, almost all phrenic nerve palsies (PNP) occurred in the CBA group. The CBA group had similar proportion of patients free from AF as the RFCA group at the 12-month follow-up (RR: 1.02; 95% CI: 0.90 to 1.16, P=0.74). Our analysis indicates that, compared with RFCA, CBA is not inferior in total procedure time and complications except for the longer fluoroscopic time. There were also similar proportions of patients free from AF in both groups at the one-year follow-up.