Miracle-dz/UniFAR-FTUs huggingface dataset:
A MODEL FOR GRAVITATIONAL WAVE EMISSION FROM NEUTRINO-DRIVEN CORE-COLLAPSE SUPERNOVAE

Using a suite of progenitor models, neutrino luminosities, and two-dimensional simulations, we investigate the matter gravitational wave (GW) emission from postbounce phases of neutrino-driven core-collapse supernovae. These phases include prompt and steady-state convection, the standing accretion shock instability (SASI), and asymmetric explosions. For the stages before explosion, we propose a model for the source of GW emission. Downdrafts of the postshock-convection/SASI region strike the protoneutron star “surface” with large speeds and are decelerated by buoyancy forces. We find that the GW amplitude is set by the magnitude of deceleration and, by extension, the downdraft's speed and the vigor of postshock-convective/SASI motions. However, the characteristic frequencies, which evolve from ∼100 Hz after bounce to ∼300–400 Hz, are practically independent of these speeds (and turnover timescales). Instead, they are set by the deceleration timescale, which is in turn set by the buoyancy frequency at the lower boundary of postshock convection. Consequently, the characteristic GW frequencies are dependent upon a combination of core structure attributes, specifically the dense-matter equation of state (EOS) and details that determine the gradients at the boundary, including the accretion-rate history, the EOS at subnuclear densities, and neutrino transport. During explosion, the high frequency signal wanes and is replaced by a strong low frequency, ∼10s of Hz, signal that reveals the general morphology of the explosion (i.e., prolate, oblate, or spherical). However, current and near-future GW detectors are sensitive to GW power at frequencies ≳50 Hz. Therefore, the signature of explosion will be the abrupt reduction of detectable GW emission.
On the Emerging of Scaling Law, Fractality and Small-World in Cellular Networks

In conventional cellular networks, for base stations (BSs) that are deployed far away from each other, it is general to assume them to be mutually independent. Nevertheless, after long-term evolution of cellular networks in various generations, the assumption no longer holds. Instead, the BSs, which seem to be gradually deployed by operators in a casual manner, have embedded many fundamental features in their locations, coverage and traffic loading. Their features can be leveraged to analyze the intrinstic pattern in BSs and even human community. According to large-scale measurement datasets, we build spatial correlation model of BSs by utilizing one of the most important features, that is, traffic. Coupling with the theory of complex networks, we make further analysis on the structure and characteristics of this spatial correlation model. Simulation results show that its degree distribution follows scale-free property. Moreover, the datasets also unveil the characteristics of fractality and smallworld. Furthermore, we study how to choose the appropriate metric to measure the importance of each BS with a combination of network efficiency and demonstrate that degree is relatively more important.
Mapping the Relationships Among Basic Facts, Concepts and Application, and Common Core Curriculum-Based Mathematics Measures

Abstract. There is a paucity of evidence supporting the use of curriculum-based mathematics measures (M-CBMs) at the middle school level, which makes data-based decisions challenging for school professionals. The purpose of this study was to examine the relationships among three existing M-CBM indices: (a) basic facts, (b) concepts/application, and (c) measures aligned with Common Core. In a sample of 408 sixth, seventh, and eighth graders, cross-lagged panel analyses were used to examine the temporal relationships of the M-CBM indices over three screening occasions. Latent growth models were also used to investigate (a) patterns of annual growth on the indices and (b) predictive validity of M-CBM level and slope on a high-stakes state assessment. Results indicated that (a) concepts/application scores predicted change in the Common Core measure with mixed evidence that basic facts predicted change on the concepts/application and Common Core tools; (b) growth was positive in all grades but nonlinear in some grades; and (c) fall scores on all measures, but only slopes on the Common Core tool, were related to performance on the high-stakes assessment.
Combining Relevance Language Modeling and Clarity Measure for Extractive Speech Summarization

Extractive speech summarization, which purports to select an indicative set of sentences from a spoken document so as to succinctly represent the most important aspects of the document, has garnered much research over the years. In this paper, we cast extractive speech summarization as an ad-hoc information retrieval (IR) problem and investigate various language modeling (LM) methods for important sentence selection. The main contributions of this paper are four-fold. First, we explore a novel sentence modeling paradigm built on top of the notion of relevance, where the relationship between a candidate summary sentence and a spoken document to be summarized is discovered through different granularities of context for relevance modeling. Second, not only lexical but also topical cues inherent in the spoken document are exploited for sentence modeling. Third, we propose a novel clarity measure for use in important sentence selection, which can help quantify the thematic specificity of each individual sentence that is deemed to be a crucial indicator orthogonal to the relevance measure provided by the LM-based methods. Fourth, in an attempt to lessen summarization performance degradation caused by imperfect speech recognition, we investigate making use of different levels of index features for LM-based sentence modeling, including words, subword-level units, and their combination. Experiments on broadcast news summarization seem to demonstrate the performance merits of our methods when compared to several existing well-developed and/or state-of-the-art methods.
Intelligence and its impact on managerial effectiveness and career success (evidence from insurance sector of Pakistan)

Purpose – The purpose of this paper is to investigate the theoretical linear model on intelligence, i.e. emotional, social, cognitive, and cultural intelligence and its impact on managerial effectiveness and career success in the perspective of insurance sector of Pakistan. Design/methodology/approach – Data collected from 202 managers of insurance companies by using structured questionnaires’ and simple random sampling technique. Multiple regression analysis has used to check the simultaneous effect of multiple types of intelligence on managerial job outcomes. Findings – The results of research revealed that emotional, social, and cognitive intelligence have positive effect on managerial effectiveness and career success. Emotional intelligence is one of the strongest predictor that has significant impact of managerial effectiveness compared to other types of intelligence. Conversely, cultural intelligence has insignificant relation with managerial effectiveness and career success. There are very rare stu.
Cylindrical shell buckling: a characterization of localization and periodicity

A hypothesis for the prediction of the circumferential wavenumber of buckling of the thin axially-compressed cylindrical shell is presented, based on the addition of a length effect to the classical (Koiter circle) critical load result. Checks against physical and numerical experiments, both by direct comparison of wavenumbers and via a scaling law, provide strong evidence that the hypothesis is correct.
A parameterless method for efficiently discovering clusters of arbitrary shape in large datasets

Clustering is the problem of grouping data based on similarity and consists of maximizing the intra-group similarity while minimizing the inter-group similarity. The problem Of clustering data sets is also known as unsupervised classification, since no class labels are given. However, all existing clustering algorithms require some parameters to steer the clustering process, such as the famous k for the number of expected clusters, which constitutes a supervision of a sort. We present in this paper a new, efficient, fast and scalable clustering algorithm that clusters over a range of resolutions and finds a potential optimum clustering without requiring any parameter input. Our experiments show that our algorithm outperforms most existing clustering algorithms in quality and speed for large data sets.
The chemokine scavenging receptor D6/ACKR2 is a target of miR-146a in thyroid cancer

We have previously shown that miR-146a, a NF-κB-regulated microRNA, is strongly expressed in human specimens and cell lines derived from anaplastic thyroid carcinomas (ATC) where it mediates some of the NF-κB pro-tumorigenic functions. By using a bioinformatic analysis, we identified the chemokine scavenger receptor D6/ ACKR2 as a target of miR146a in human ATC. We found that the expression of D6/ ACKR2 was up-regulated in miR-146a-null ATC cell lines and that the 3’ UTR of D6/ ACKR2 mRNA was able to inhibit its expression in parental, but not in miR-146a-null ATC cells. Since human specimens from primary ATC showed a low expression of D6/ ACKR2 compared to normal thyroid tissues, we analyzed the effects of D6/ACKR2 over-expression in ATC cells. Different chemokines added to the conditioned medium of D6/ACKR2 over-expressing ATC cells partially failed to drive in vitro monocyte migration, and tumors derived from the injection of the same cells in nude mice showed a decreased number of infiltrating macrophages. Taken together, these results indicate that ATC cells down-regulate D6/ACKR2 expression through miR-146a activity to sustain leukocyte trafficking inside tumor microenvironment and shed light on a novel mechanism by which NF-κB indirectly inhibits the expression and the function of anti-tumorigenic gene in thyroid cancer.
English learning as a means of self-fulfilment : a grounded theory of language learning behaviour

In this thesis I present an original theory of language learning behaviour derived from a grounded theory analysis of interview testimony from five Japanese learners of English. The theory takes the form of the basic English Learning as a Means of Self-fulfilment (ELMS) model. This model explains English-learning behaviour in terms of the engagement of four types of self-fulfilment drive: a drive for intellectual and affective stimulation (entertainment drive); a drive to ‘expand one’s horizons’ (perspective drive); a drive to make a ‘success’ of oneself (status drive); and a drive to engage in interaction with others (communication drive). Two additional models built on the foundation of the basic ELMS model are also introduced: the expanded ELMS model explains how learning behaviour is mediated by cultural and institutional context, and by the individual’s attempts to make sense of, and control, experience; and the Learning as a Means of Self-fulfilment (LMS) model is a hypothetical general model of learning which incorporates existing concepts from the literature. The results of the analysis demonstrate the importance of structure, rather than agency, in shaping language-learning behaviour. The theoretical rendering of motivation that emerges from the analysis is differentiated from that of motivation as a force constantly underlying behaviour. Instead, motivation is seen to make only sporadic appearances on the stage of consciousness, and to be responsible for behavioural change rather than behavioural routine. It follows that unexpected events that stimulate changes in beliefs about the self or about language learning may have much to tell us about motivation. This research does not so much build upon existing theory as problematise it. The results challenge prevailing conceptualisations of motivation, dominant discourses and practices associated with the term within applied linguistics and Japanese English language education, and the utility of the concept itself. It is a methodologically innovative investigation into the relationship between motivation and English learning in the Japanese context, with implications that extend beyond this context.
Structural and Electrostatic Properties of the 5-HT3Receptor Pore Revealed by Substituted Cysteine Accessibility Mutagenesis*

5-HT3 receptors are members of the Cys loop family of ligand-gated ion channels. We used the substituted cysteine accessibility method to identify amino acid residues in the channel forming domain, M2 that face the water-accessible surface and to locate their position in the ion conduction pathway. Cysteine was substituted for each residue, one at a time, in the M2 segment (Asp274–Asp298). 5-Hydroxytryptamine EC50 values for functional mutants did not vary from wild type (1.4 ± 0.2 μm) by more than 10-fold, and five mutants were nonfunctional. Covalent modification of the mutant receptors with sulfydryl reagents revealed 11 residues to be water-accessible, with a pattern consistent with an α-helix except at Leu285 and Leu293. The data suggest that charge selectivity begins at a more cytoplasmic level than Val291. Modification at some positions (Val291, Leu293, Ile294, Leu287, and Ser280) resulted in channels that were locked open. Reaction rates with accessible cysteines were voltage-dependent at some residues, suggesting that access occurs via the ion channel. Overall the data observed are similar but not identical to that reported for other members of the family and confirms the high degree of structural and functional homology between receptors in the Cys loop receptor family.
Chemokine Expression in Inflamed Adipose Tissue Is Mainly Mediated by NF-κB

Immune cell infiltration of expanding adipose tissue during obesity and its role in insulin resistance has been described and involves chemokines. However, studies so far have focused on a single chemokine or its receptor (especially CCL2 and CCL5) whereas redundant functions of chemokines have been described. The objective of this work was to explore the expression of chemokines in inflamed adipose tissue in obesity. Human and mouse adipocytes were analyzed for expression of chemokines in response to inflammatory signal (TNF-α) using microarrays and gene set enrichment analysis. Gene expression was verified by qRT-PCR. Chemokine protein was determined in culture medium with ELISA. Chemokine expression was investigated in human subcutaneous adipose tissue biopsies and mechanism of chemokine expression was investigated using chemical inhibitors and cellular and animal transgenic models. Chemokine encoding genes were the most responsive genes in TNF-α treated human and mouse adipocytes. mRNA and protein of 34 chemokine genes were induced in a dose-dependent manner in the culture system. Furthermore, expression of those chemokines was elevated in human obese adipose tissue. Finally, chemokine expression was reduced by NF-κB inactivation and elevated by NF-κB activation. Our data indicate that besides CCL2 and CCL5, numerous other chemokines such as CCL19 are expressed by adipocytes under obesity-associated chronic inflammation. Their expression is regulated predominantly by NF-κB. Those chemokines could be involved in the initiation of infiltration of leukocytes into obese adipose tissue.
The Diagnostic Value of Skin Disease Diagnosis Expert System

Background: Evaluation is a necessary measure to ensure the effectiveness and efficiency of all systems, including expert systems. The aim of this study was to determine the diagnostic value of expert system for diagnosis of complex skin diseases. Methods: A case-control study was conducted in 2015 to determine the diagnostic value of an expert system. The study population included patients who were referred to Razi Specialized Hospital, affiliated to Tehran University of Medical Sciences. The control group was selected from patients without the selected skin diseases. Data collection tool was a checklist of clinical signs of diseases including pemphigus vulgaris, lichen planus, basal cell carcinoma, melanoma, and scabies. The sample size formula estimated 400 patients with skin diseases selected by experts and 200 patients without the selected skin diseases. Patient selection was undertaken with randomized stratified sampling and their sign and symptoms were logged into the system. Physician’s diagnosis was determined as the gold standard and was compared with the diagnosis of expert system by SPSS software version 16 and STATA. Kappa statistics, indicators of sensitivity, specificity, accuracy and confidence intervals were calculated for each disease. An accuracy of 90% was considered appropriate. Results: Comparing the results of expert system and physician’s diagnosis at the evaluation stage showed an accuracy of 97.1%, sensitivity of 97.5% and specificity of 96.5% The Kappa test indicated a high agreement of 93.6%. Conclusion: The expert system can diagnose complex skin diseases. Development of such systems is recommended to identify all skin diseases.
Chromosome order in HeLa cells changes during mitosis and early G1, but is stably maintained during subsequent interphase stages

Whether chromosomes maintain their nuclear positions during interphase and from one cell cycle to the next has been controversially discussed. To address this question, we performed long-term live-cell studies using a HeLa cell line with GFP-tagged chromatin. Positional changes of the intensity gravity centers of fluorescently labeled chromosome territories (CTs) on the order of several μm were observed in early G1, suggesting a role of CT mobility in establishing interphase nuclear architecture. Thereafter, the positions were highly constrained within a range of ∼1 μm until the end of G2. To analyze possible changes of chromosome arrangements from one cell cycle to the next, nuclei were photobleached in G2 maintaining a contiguous zone of unbleached chromatin at one nuclear pole. This zone was stably preserved until the onset of prophase, whereas the contiguity of unbleached chromosome segments was lost to a variable extent, when the metaphase plate was formed. Accordingly, chromatin patterns observed in daughter nuclei differed significantly from the mother cell nucleus. We conclude that CT arrangements were stably maintained from mid G1 to late G2/early prophase, whereas major changes of CT neighborhoods occurred from one cell cycle to the next. The variability of CT neighborhoods during clonal growth was further confirmed by chromosome painting experiments.
Evolution of the early-type galaxy fraction in clusters since z = 0.8

We study the morphological content of a large sample of high-redshift clusters to determine its dependence on cluster mass and redshift. Quantitative morphologies are based on PSF-convolved, 2D bulge+disk decompositions of cluster and field galaxies on deep Very Large Telescope FORS2 images of eighteen, optically-selected galaxy clusters at 0.45 < z < 0.80 observed as part of the ESO Distant Cluster Survey (“EDisCS”). Morphological content is characterized by the early-type galaxy fraction f_(et) , and early-type galaxies are objectively selected based on their bulge fraction and image smoothness. This quantitative selection is equivalent to selecting galaxies visually classified as E or S0. Changes in early-type fractions as a function of cluster velocity dispersion, redshift and star-formation activity are studied. A set of 158 clusters extracted from the Sloan Digital Sky Survey is analyzed exactly as the distant EDisCS sample to provide a robust local comparison. We also compare our results to a set of clusters from the Millennium Simulation. Our main results are: (1) the early-type fractions of the SDSS and EDisCS clusters exhibit no clear trend as a function of cluster velocity dispersion. (2) Mid-z EDisCS clusters around σ = 500 km s^(-1) have f_(et) ≃ 0.5 whereas high-z EDisCS clusters have f_(et) ≃ 0.4. This represents a ~25% increase over a time interval of 2 Gyr. (3) There is a marked difference in the morphological content of EDisCS and SDSS clusters. None of the EDisCS clusters have early-type galaxy fractions greater than 0.6 whereas half of the SDSS clusters lie above this value. This difference is seen in clusters of all velocity dispersions. (4) There is a strong and clear correlation between morphology and star formation activity in SDSS and EDisCS clusters in the sense that decreasing fractions of [OII] emitters are tracked by increasing early-type fractions. This correlation holds independent of cluster velocity dispersion and redshift even though the fraction of [OII] emitters decreases from z ~ 0.8 to z ~ 0.06 in all environments. Our results pose an interesting challenge to structural transformation and star formation quenching processes that strongly depend on the global cluster environment (e.g., a dense ICM) and suggest that cluster membership may be of lesser importance than other variables in determining galaxy properties.
Corporate Elite Networks and Governance Changes in the 1980s

Changes in corporate governance practices can be analyzed by linking the adaptations of individual firms to the structures of the networks in which firms' decision makers are embedded. Network structures determine the speed of adaptation and ultimate patterns of prevalence of governance practices by exposing a firm to particular role models and standards of appropriateness. The authors compare the spreads of two governance innovations adopted in response to the 1980s takeover wave: poison pills (which spread rapidly through a board‐to‐board diffusion process) and golden parachutes (which spread slowly through geographic proximity). The study closes with a discussion of networks as links between individual adaptation and collective structures.
On the misuse of the profits-sales ratio to infer monopoly power

The common use of the profits-sales ratio as a measure of the Lerner index of monopoly power is flawed, even with the assumption of constant returns, because of problems connected with the valuation of capital. The size of the error is related to the cost of capital, the growth rate of the firm, the depreciation method used, and, most important, the shape of the stream of benefits resulting from an investment. Examples show that the error can be quite large; further, the error is likely to be systematically related to the variables used in regression studies.
Cesàro convergence of spherical averages for measure-preserving actions of Markov semigroups and groups

Ces aro convergence of spherical averages is proven for measure-preserving actions of Markov semigroups and groups. Convergence in the mean is established for functions in L p , 1 ≤ p < ∞, and pointwise convergence for functions in L ∞. In particular, for measure-preserving actions of word hyperbolic groups (in the sense of Gromov) we obtain Ces aro convergence of spherical averages with respect to any symmetric set of generators.