Miracle-dz/UniFAR-FTUs huggingface dataset:
FOCUSED INFORMATION CRITERION BASED PARTITIONED ITERATIVE X-MEANS DICE CORRELATION CLUSTERING FOR BIG GEO-SOCIAL DATA

Geo-social data is location-based social media data which is generated by people on social network (i.e. face book, twitter etc.,) that is related to specific locations. There are lot of social users who are generates very large amount of data called Big Data that is difficult to be analyzed and make real-time decisions. Few research works have been designed for clustering geo-social data using different techniques. However, clustering performance of conventional algorithms was not higher to exactly find frequently visited location of users in social network when taking big geo-social dataset as input. In order to overcome such drawbacks, a Focused Information Criterion based Partitioned Iterative X-means Dice Correlation Data Clustering (FIC-PIXDCDC) Method is proposed in this work. The FIC-PIXDCDC Method groups the similar geo-social data with higher accuracy and lesser time. In FIC-PIXDCDC method, geo-social data (i.e., user, location and time) from Weeplaces dataset is initially taken as an input. After obtaining input, FIC-PIXDCDC method chooses number of clusters and centroids randomly. Then, FIC-PIXDCDC calculates dice correlation between each input geo-social data and cluster centroids. Subsequently, FIC-PIXDCDC method applies Focused Information Criterion to construct optimal number of clusters for a given big dataset. This process of FIC-PIXDCDC method is repetitive until no deviation in cluster centroids. Accordingly, FIC-PIXDCDC method groups interrelated geo-social data together with higher accuracy and lower time to precisely discover location information of frequently visited users in social network. Experimental evaluation of FIC-PIXDCDC method is carried out on factors such as clustering time, clustering accuracy, error rate with respect to number of geo-social data.
Extracellular Vesicles Reveal Abnormalities In Neuronal Iron Metabolism In Restless Legs Syndrome.

Study ObjectivesDetermine abnormalities in levels of iron-management proteins in neuronal origin-enriched extracellular vesicles (nEVs) in Restless Legs Syndrome (RLS). METHODS We used immunoprecipitation for neuronal marker L1CAM to isolate nEVs from the serum of 20 RLS subjects from a study including MRI determinations of iron deposition in the substantia nigra and hematologic parameters and 28 age- and sex-matched Controls. RESULTS RLS compared to Control subjects showed higher levels of nEV total ferritin but similar levels of transferrin receptor and ferroportin. Western blot analysis showed that heavy- but not light-chain ferritin was increased in nEVs of RLS compared to Control subjects. In RLS but not Control subjects, nEV total ferritin was positively correlated with systemic iron parameters; the two groups also differed in the relation of nEV total ferritin to MRI-measures of iron deposition in substantia nigra. CONCLUSIONS Given the neuronal origin and diversity of EV cargo, nEVs provide an important platform for exploring the underlying pathophysiology and possible biomarkers of RLS.
Still a long way to go

Drawing on 178 video-recorded lessons from 47 lower-secondary classrooms with high technological infrastructure in Norway, the present study sheds light on how and for what purposes teachers use technology in their everyday instruction, providing important insights into what kind of digital literacy practices students experience in a classroom context. Key findings are that teachers’ implementation and uptake of technology in everyday instruction was narrow and limited. Despite good access and high national ambitions for the development of students’ digital competence, teachers’ uptake of the available digital technology was very often limited to supporting traditional teacher-centered practices, with low student participation, suggesting that information and communications technology (ICT) was used for traditional transmissive pedagogy. Teachers’ discourse around ICT in class was practical and technical, rather than conceptual. Further, students’ use of technology mainly revolved around writing digital texts, individually, not the promising pedagogical practices associated with ICT in previous research. These findings show that the implementation of digital technology and the development of digital competence in schools require far more than an ambitious curriculum and a basic digital infrastructure. Structures at a national level are not enough, and there is an urgent need for professional development at the local level to increase the instructional repertoire and the didac-tical motivation of teachers in relation to digital technology.
On the Relationship(s) Between Color and Taste/Flavor

Experimental psychologists, psychophysicists, food/sensory scientists, and marketers have long been interested in, and/or speculated about, what exactly the relationship, if any, might be between color and taste/flavor. While several influential early commentators argued against there being any relationship, a large body of empirical evidence published over the last 80 years or so clearly demonstrates that the hue and saturation, or intensity, of color in food and/or drink often influences multisensory flavor perception. Interestingly, the majority of this research has focused on vision’s influence on the tasting experience rather than looking for any effects in the opposite direction. Recently, however, a separate body of research linking color and taste has emerged from the burgeoning literature on the crossmodal correspondences. Such correspondences, or associations, between attributes or dimensions of experience, are thought to be robustly bidirectional. When talking about the relationship between color and taste/flavor, some commentators would appear to assume that these two distinct literatures describe the same underlying empirical phenomenon. That said, a couple of important differences (in terms of the bidirectionality of the effects and their relative vs. absolute nature) are highlighted, meaning that the findings from one domain may not necessarily always be transferable to the other, as is often seemingly assumed.
Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension

We propose a multi-task learning framework to learn a joint Machine Reading Comprehension (MRC) model that can be applied to a wide range of MRC tasks in different domains. Inspired by recent ideas of data selection in machine translation, we develop a novel sample re-weighting scheme to assign sample-specific weights to the loss. Empirical study shows that our approach can be applied to many existing MRC models. Combined with contextual representations from pre-trained language models (such as ELMo), we achieve new state-of-the-art results on a set of MRC benchmark datasets. We release our code at https://github.com/xycforgithub/MultiTask-MRC.
Space Weathering of FeS Induced via Pulsed Laser Irradiation

Here we present results from pulsed laser irradiation of troilite samples in an effort to simulate space weathering on airless bodies via micrometeorite impacts. We find that the spectral trends observed in directly irradiated samples and samples with a vapor‐deposited coating are different than those found in silicate minerals previously studied. For instance, direct laser irradiation causes our troilite samples to initially brighten, but continued irradiation causes darkening and a decrease in spectral slope. In contrast, our samples with a vapor‐deposited coating show a continuous increase in spectral slope and overall albedo as the deposit thickness increases. Observation using both digital imaging and electron microscopy of our directly irradiated samples leads us to conclude that topography effects likely become important after a relatively high number of laser pulses in our directly irradiated samples, causing the apparent darkening and decrease in spectral slope. Thus, we conclude that the spectral changes observed relevant to space weathering via micrometeorite impacts are an increase in spectral slope and an increase in the albedo of troilite. Future studies will investigate whether these trends are generally representative of other sulfide‐bearing minerals and of weathering trends in other components found in the asteroid regolith.
Some personal and professional variables as identifiers of teachers’ lifelong learning tendencies and professional burnout

In this study, it is aimed to determine teachers’ lifelong learning (LLL) tendencies. It is also aimed to reveal the variables that are associated to the LLL tendencies and to predict its levels. This research, which was a relational model, was utilised in spring term of 2017–2018 academic year. The participants of the study consisted of 199 teachers working at various school levels associated with the Ministry of National Education. According to the results of the study, it was found that demographic, occupational variables and the burnout in the multiple linear regression analysis were significant predictors of LLL tendency. When the variables are considered one by one, it is concluded that the predictors of teachers’ LLL tendencies are age, occupational seniority and burnout. Keywords: Teachers, lifelong learning tendency, personal variables, occupational variables, occupational burnout.
The VANDELS survey: the role of ISM and galaxy physical properties in the escape of Lyα emission in z ∼ 3.5 star-forming galaxies

Aims. We wish to investigate the physical properties of a sample of Lyα emitting galaxies in the VANDELS survey, with particular focus on the role of kinematics and neutral hydrogen column density in the escape and spatial distribution of Lyα photons. Methods. From all the Lyα emitting galaxies in the VANDELS Data Release 2 at 3.5 ≲ z ≲ 4.5, we selected a sample of 52 galaxies that also have a precise systemic redshift determination from at least one nebular emission line (HeII or CIII]). For these galaxies, we derived different physical properties (stellar mass, age, dust extinction, and star formation rate) from spectral energy distribution (SED) fitting of the exquisite multiwavelength photometry available in the VANDELS fields, using the dedicated spectral modeling tool BEAGLE and the UV β slope from the observed photometry. We characterized the Lyα emission in terms of kinematics, equivalent width (EW), full width at half-maximum, and spatial extension and then estimated the velocity of the neutral outflowing gas. The ultra-deep VANDELS spectra (up to 80 h on-source integration) enable this for individual galaxies without the need to rely on stacks. We then investigated the correlations between the Lyα properties and the other measured properties to study how they affect the shape and intensity of Lyα emission. Results. We reproduce some of the well-known correlations between Lyα EW and stellar mass, dust extinction, and UV β slope, in the sense that the emission line appears brighter in galaxies with lower mass that are less dusty and bluer. We do not find any correlation with the SED-derived star formation rate, while we find that galaxies with brighter Lyα tend to be more compact in both UV and in Lyα. Our data reveal an interesting correlation between the Lyα velocity offset and the shift of the interstellar absorption lines with respect to the systemic redshift, observed for the first time at high redshifts: galaxies with higher interstellar medium (ISM) outflow velocities show smaller Lyα velocity shifts. We interpret this relation in the context of the shell-model scenario, where the velocity of the ISM and the HI column density contribute together in determining the Lyα kinematics. In support to our interpretation, we observe that galaxies with high HI column densities have much more extended Lyα spatial profiles; this is a sign of increased scattering. However, we do not find any evidence that the HI column density is related to any other physical properties of the galaxies, although this might be due in part to the limited range of parameters that our sample spans.
Circumventing the no-go theorem: A single Weyl point without surface Fermi arcs

Despite a rapidly expanding inventory of possible crystalline Weyl semimetals, all of them are constrained by the Nielsen-Ninomiya no-go theorem, namely, that left- and right-handed Weyl points appear in pairs. With time-reversal ($\mathcal{T}$) symmetry, an even stronger version holds for the semimetals, i.e., all eight time-reversal-invariant points in the Brillouin zone (BZ) simultaneously host Weyl points or not. Accompanying the no-go theorem, the surface of the system features Fermi arc states, which connect pairs of surface projected Weyl points. Here, we explicitly construct a topological phase of a $\mathcal{T}$-invariant crystalline metal, which features a single Weyl point residing at the center of the BZ, surrounded by nodal walls spreading over the entire BZ boundary. In other words, a single Weyl point is realized with the no-go theorem being circumvented. Moreover, the surface Fermi arcs, considered as a hallmark of Weyl semimetals, do not appear for this composite topological phase. We show that this phase can be realized for space groups No. 19 and No. 92, with and without spin-orbit coupling, respectively.
Fundamental Limitations on the Calibration of Redundant 21 cm Cosmology Instruments and Implications for HERA and the SKA

Precise instrument calibration is critical to the success of 21 cm cosmology experiments. Unmitigated errors in calibration contaminate the Epoch of Reionization (EoR) signal, precluding a detection. Barry et al. characterized one class of inherent errors that emerge from calibrating to an incomplete sky model; however, it has been unclear if errors in the sky model affect the calibration of redundant arrays. In this paper, we show that redundant calibration is vulnerable to errors from sky model incompleteness even in the limit of perfect antenna positioning and identical beams. These errors are at a level that can overwhelm the EoR signal and prevent a detection in crucial power spectrum modes. Finally, we suggest error mitigation strategies with implications for the Hydrogen Epoch of Reionization Array and the Square Kilometre Array.
New Neutron Star Equation of State with Quark–Hadron Crossover

We present a much improved equation of state for neutron star matter, QHC19, with a smooth crossover from the hadronic regime at lower densities to the quark regime at higher densities. We now use the Togashi et al. equation of state, a generalization of the Akmal–Pandharipande–Ravenhall equation of state of uniform nuclear matter, in the entire hadronic regime; the Togashi equation of state consistently describes nonuniform as well as uniform matter, and matter at beta equilibrium without the need for an interpolation between pure neutron and symmetric nuclear matter. We describe the quark matter regime at higher densities with the Nambu–Jona–Lasinio model, now identifying tight constraints on the phenomenological universal vector repulsion between quarks and the pairing interaction between quarks arising from the requirements of thermodynamic stability and causal propagation of sound. The resultant neutron star properties agree very well with the inferences of the LIGO/Virgo collaboration, from GW170817, of the pressure versus baryon density, neutron star radii, and tidal deformabilities. The maximum neutron star mass allowed by QHC19 is 2.35 M⊙, consistent with all neutron star mass determinations.
Imprints of mass accretion history on the shape of the intracluster medium and the TX–M relation

We use a statistical sample of galaxy clusters from a large cosmological N-body + hydrodynamics simulation to examine the relation between morphology, or shape, of the X-ray emitting intracluster medium (ICM) and the mass accretion history of the galaxy clusters. We find that the mass accretion rate (MAR) of a cluster is correlated with the ellipticity of the ICM. The correlation is largely driven by material accreted in the last ∼4.5 Gyr, indicating a characteristic time-scale for relaxation of cluster gas. Furthermore, we find that the ellipticity of the outer regions (R ∼ R500c) of the ICM is correlated with the overall MAR of clusters, while ellipticity of the inner regions (≲0.5 R500c) is sensitive to recent major mergers with mass ratios of ≥1:3. Finally, we examine the impact of variations in cluster mass accretion history on the X-ray observable–mass scaling relations. We show that there is a continuous anticorrelation between the residuals in the TX–M relation and cluster MARs, within which merging and relaxed clusters occupy extremes of the distribution rather than form two peaks in a bimodal distribution, as was often assumed previously. Our results indicate that the systematic uncertainties in the X-ray observable–mass relations can be mitigated by using the information encoded in the apparent ICM ellipticity.
Genome-wide association study of leaf chemistry traits in tobacco

Leaf chemistry traits are some of the key factors influencing tobacco quality, which can be significantly reduced by lower chemical components in cured leaf. To improve tobacco quality through breeding, genetic diversity analysis, population structure analysis, and genome-wide association studies were performed in a panel of 347 tobacco germplasms and the markers associated with five leaf chemistry traits, including total sugar (TS), reducing sugar (RS), total nitrogen (TN), nicotine (NIC), and total potassium (TP) contents were identified. Four groups were classified at a genetic distance of 0.316 by genetic diversity analysis based on coefficient parameter NEI72 using a program NTSYS-pc2.10e, whereas four well-differentiated subpopulations were postulated in the 347 tobacco accessions. A total of 47 target trait-associated SNPs was detected in at least three environments as well as the best linear unbiased predictions (BLUPs) across all environments, among which two, two, four, six, and one highly suggestive associated SNPs were repeatedly detected in all environments and BLUPs for TS, RS, TN, NIC, and TP, respectively. On the basis of the phenotypic effects of the alleles corresponding to suggestive associated SNPs, five tobacco accessions harboring favorable alleles with elite phenotypic performance in leaf chemistry traits were identified. The results could facilitate quality tobacco breeding for higher leaf chemistry trait contents through molecular marker-assisted approaches.
A Convex Programming Approach for Discrete-Time Markov Decision Processes under the Expected Total Reward Criterion

In this work, we study discrete-time Markov decision processes (MDPs) under constraints with Borel state and action spaces and where all the performance functions have the same form of the expected total reward (ETR) criterion over the infinite time horizon. One of our objective is to propose a convex programming formulation for this type of MDPs. It will be shown that the values of the constrained control problem and the associated convex program coincide and that if there exists an optimal solution to the convex program then there exists a stationary randomized policy which is optimal for the MDP. It will be also shown that in the framework of constrained control problems, the supremum of the expected total rewards over the set of randomized policies is equal to the supremum of the expected total rewards over the set of stationary randomized policies. We consider standard hypotheses such as the so-called continuity-compactness conditions and a Slater-type condition. Our assumptions are quite weak to deal with cases that have not yet been addressed in the literature. An example is presented to illustrate our results with respect to those of the literature.
Efficient Inner Product Approximation in Hybrid Spaces

Many emerging use cases of data mining and machine learning operate on large datasets with data from heterogeneous sources, specifically with both sparse and dense components. For example, dense deep neural network embedding vectors are often used in conjunction with sparse textual features to provide high dimensional hybrid representation of documents. Efficient search in such hybrid spaces is very challenging as the techniques that perform well for sparse vectors have little overlap with those that work well for dense vectors. Popular techniques like Locality Sensitive Hashing (LSH) and its data-dependent variants also do not give good accuracy in high dimensional hybrid spaces. Even though hybrid scenarios are becoming more prevalent, currently there exist no efficient techniques in literature that are both fast and accurate. In this paper, we propose a technique that approximates the inner product computation in hybrid vectors, leading to substantial speedup in search while maintaining high accuracy. We also propose efficient data structures that exploit modern computer architectures, resulting in orders of magnitude faster search than the existing baselines. The performance of the proposed method is demonstrated on several datasets including a very large scale industrial dataset containing one billion vectors in a billion dimensional space, achieving over 10x speedup and higher accuracy against competitive baselines.
Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data

Recent developments in cardiovascular modelling allow us to simulate blood flow in an entire human body. Such model can also be used to create databases of virtual subjects, with sizes limited only by computational resources. In this work, we study if it is possible to estimate cardiovascular health indices using machine learning approaches. In particular, we carry out theoretical assessment of estimating aortic pulse wave velocity, diastolic and systolic blood pressure and stroke volume using pulse transit/arrival timings derived from photopletyshmography signals. For predictions, we train Gaussian process regression using a database of virtual subjects generated with a cardiovascular simulator. Simulated results provides theoretical assessment of accuracy for predictions of the health indices. For instance, aortic pulse wave velocity can be estimated with a high accuracy (r > 0.9) when photopletyshmography is measured from left carotid artery using a combination of foot-to-foot pulse transmit time and peak location derived for the predictions. Similar accuracy can be reached for diastolic blood pressure, but predictions of systolic blood pressure are less accurate (r > 0.75) and the stroke volume predictions are mostly contributed by heart rate.
Photoionization Emission Models for the Cyg X-3 X-Ray Spectrum

We present model fits to the X-ray line spectrum of the well-known high-mass X-ray binary Cyg X-3. The primary observational data set is a spectrum taken with the Chandra X-ray Observatory High Energy Transmission Grating in 2006, though we compare it to all the other observations of this source taken so far by this instrument. We show that the density must be ≥1012 cm−3 in the region responsible for most of the emission. We discuss the influence of the dust scattering halo on the broadband spectrum, and we argue that dust scattering and extinction is not the most likely origin for the narrow feature seen near the Si K edge. We identify the features of a wind in the profiles of the strong resonance lines and show that the wind is more apparent in the lines from the lighter elements. We argue that this wind is most likely associated with the companion star. We show that the intensities of most lines can be fitted, crudely, by a single-component photoionized model. However, the iron K lines do not fit with this model. We show that the iron K line variability as a function of orbital phase is different from the lower-energy lines, which indicates that the lines arise in physically distinct regions. We discuss the interpretation of these results in the context of what is known about the system and similar systems.