Miracle-dz/UniFAR-FTUs huggingface dataset:
Embedded star clusters in the W51 giant molecular cloud

We present sub-arcsecond (0.35-0.9 arcsec), near-infrared J-, H- and K-band photometric observations of six fields along the W51 giant molecular cloud (W51 GMC). Our observations reveal four new, embedded clusters and provide a new high-resolution (0.35 arcsec) view of the W51 IRS2 (G49.5 - 0.4) region. The cluster associated with G48.9 - 0.3 is found to be a double cluster enclosed in a nest of near-infrared nebulosity. We construct stellar surface density maps for four major clusters in the W51 GMC. These unveil the underlying hierarchical structure. Colour-colour and colour-magnitude diagrams for each of these clusters show clear differences in the embedded stellar populations and indicate the relative ages of these clusters. In particular, the clusters associated with the H II regions G48.9 - 0.3 and G49.0 - 0.3 are found to have a high fraction of young stellar objects and are therefore considered the youngest of all the near-infrared clusters in the W51 GMC. The estimated masses of the individual clusters, when summed, yield a total stellar mass of ∼10 4 M ○. in the W51 GMC, implying a star formation efficiency of 5-10 per cent. These results, in comparison with the CO observations of the W51 GMC, suggest for the first time that star formation in the W51 GMC is probably triggered by a galactic spiral density wave.
Combining heterogeneous classifiers for stock selection

Combining unbiased forecasts of continuous variables necessarily reduces the error variance below that of the median individual forecast. However, this does not necessarily hold for forecasts of discrete variables, or where the costs of errors are not directly related to the error variance. This paper investigates empirically the benefits of combining forecasts of outperforming shares, based on five linear and nonlinear statistical classification techniques, including neural network and recursive partitioning methods. We find that simple “Majority Voting” improves accuracy and profitability only marginally. Much greater gains come from applying the “Unanimity Principle”, whereby a share is not held in the high-performing portfolio unless all classifiers agree.
Nature inspired techniques for data clustering

Nature is always a source of inspiration. In last few decades, the research is stimulated on new computing paradigms and result of this effort is emergence of new problem solving techniques like Nature Inspired Computing, Evolutionary Computing. Nature inspired problem solving techniques are widely used to solve complex problems. These techniques are widely used due to their decentralized and self-organized behavior. Such behavior is observed in social systems such as artificial bee colony algorithm, particle swarm optimization, ant colony optimization, bat algorithm, firefly algorithm, glowworm swarm optimization etc. In this paper we have given overview of nature inspired techniques used for data clustering, hybridization with traditional clustering techniques and their effectiveness.
PPARγ2 Regulates a Molecular Signature of Marrow Mesenchymal Stem Cells

Bone formation and hematopoiesis are anatomically juxtaposed and share common regulatory mechanisms. Bone marrow mesenchymal stromal/stem cells (MSC) contain a compartment that provides progeny with bone forming osteoblasts and fat laden adipocytes as well as fibroblasts, chondrocytes, and muscle cells. In addition, marrow MSC provide an environment for support of hematopoiesis, including the development of bone resorbing osteoclasts. The PPARγ2 nuclear receptor is an adipocyte-specific transcription factor that controls marrow MSC lineage allocation toward adipocytes and osteoblasts. Increased expression of PPARγ2 with aging correlates with changes in the MSC status in respect to both their intrinsic differentiation potential and production of signaling molecules that contribute to the formation of a specific marrow micro-environment. Here, we investigated the effect of PPARγ2 on MSC molecular signature in respect to the expression of gene markers associated exclusively with stem cell phenotype, as well as genes involved in the formation of a stem cell supporting marrow environment. We found that PPARγ2 is a powerful modulator of stem cell-related gene expression. In general, PPARγ2 affects the expression of genes specific for the maintenance of stem cell phenotype, including LIF, LIF receptor, Kit ligand, SDF-1, Rex-1/Zfp42, and Oct-4. Moreover, the antidiabetic PPARγ agonist TZD rosiglitazone specifically affects the expression of “stemness” genes, including ABCG2, Egfr, and CD44. Our data indicate that aging and anti-diabetic TZD therapy may affect mesenchymal stem cell phenotype through modulation of PPARγ2 activity. These observations may have important therapeutic consequences and indicate a need for more detailed studies of PPARγ2 role in stem cell biology.
Heat Shock Factor Genes of Tall Fescue and Perennial Ryegrass in Response to Temperature Stress by RNA-Seq Analysis

Heat shock factors (Hsfs) are important regulators of stress-response in plants. However, our understanding of Hsf genes and their responses to temperature stresses in two Pooideae cool-season grasses, Festuca arundinacea, and Lolium perenne, is limited. Here we conducted comparative transcriptome analyses of plant leaves exposed to heat or cold stress for 10 h. Approximately, 30% and 25% of the genes expressed in the two species showed significant changes under heat and cold stress, respectively, including subsets of Hsfs and their target genes. We uncovered 74 Hsfs in F. arundinacea and 52 Hsfs in L. perenne, and categorized these genes into three subfamilies, HsfA, HsfB, and HsfC based on protein sequence homology to known Hsf members in model organisms. The Hsfs showed a strong response to heat and/or cold stress. The expression of HsfAs was elevated under heat stress, especially in class HsfA2, which exhibited the most dramatic responses. HsfBs were upregulated by the both temperature conditions, and HsfCs mainly showed an increase in expression under cold stress. The target genes of Hsfs, such as heat shock protein (HSP), ascorbate peroxidase (APX), inositol-3-phosphate synthase (IPS), and galactinol synthase (GOLS1), showed strong and unique responses to different stressors. We comprehensively detected Hsfs and their target genes in F. arundinacea and L. perenne, providing a foundation for future gene function studies and genetic engineering to improve stress tolerance in grasses and other crops.
Posterior Pseudo-Probabilities Estimation of Posterior Class Probabilities to Maximize Class Separability

The estimation of the posterior class probabilities is desirable for optimal decision, decision confidence measure, and accurate performance evaluation of a classifier. In this paper, we address the problem of estimating posterior class probabilities by learning from samples for producing optimal classifiers. We introduce a posterior pseudo-probability function based on Bayes’ formula to transform class-conditional probability values into posterior class probability values. The parameters in this function are trained from the data using the proposed max-min posterior pseudo-probability method in which the optimization objective is to maximize the posterior pseudo-probabilities for positive samples, at the same time to minimize those for negative samples. We show the effectiveness of our estimator in learning pattern classification through the experimental results in three applications: content-based image retrieval, text extraction, and handwritten digit recognition.
Inter-vehicle communication systems: a survey

Inter-vehicle communication (IVC) systems (i.e., systems not relying on roadside infrastructure) have the potential to radically improve the safety, efficiency, and comfort of everyday road travel. Their main advantage is that they bypass the need for expensive infrastructure; their major drawback is the comparatively complex networking protocols and the need for significant penetration before their applications can become effective. In this article we present several major classes of applications and the types of services they require from an underlying network. We then proceed to analyze existing networking protocols in a bottom-up fashion, from the physical to the transport layers, as well as security aspects related to IVC systems. We conclude the article by presenting several projects related to IVC as well as a review of common performance evaluation techniques for IVC systems.
k-FFNN: A priori knowledge infused Feed-forward Neural Networks

Recurrent neural network (RNN) are being extensively used over feed-forward neural networks (FFNN) because of their inherent capability to capture temporal relationships that exist in the sequential data such as speech. This aspect of RNN is advantageous especially when there is no a priori knowledge about the temporal correlations within the data. However, RNNs require large amount of data to learn these temporal correlations, limiting their advantage in low resource scenarios. It is not immediately clear (a) how a priori temporal knowledge can be used in a FFNN architecture (b) how a FFNN performs when provided with this knowledge about temporal correlations (assuming available) during training. The objective of this paper is to explore k-FFNN, namely a FFNN architecture that can incorporate the a priori knowledge of the temporal relationships within the data sequence during training and compare k-FFNN performance with RNN in a low resource scenario. We evaluate the performance of k-FFNN and RNN by extensive experimentation on MediaEval 2016 audio data ("Emotional Impact of Movies" task). Experimental results show that the performance of k-FFNN is comparable to RNN, and in some scenarios k-FFNN performs better than RNN when temporal knowledge is injected into FFNN architecture. The main contributions of this paper are (a) fusing a priori knowledge into FFNN architecture to construct a k-FFNN and (b) analyzing the performance of k-FFNN with respect to RNN for different size of training data.
To what extent are prudential and accounting arrangements pro- or countercyclical with respect to overall financial conditions?

The 1998 financial turmoil on international capital markets has suggested some weaknesses in the Basel Committee’s 1988 Capital Accord. Criticism has focused not only on the measures of risk used in this framework, but also on its ability to incorporate key insights from the theory of finance, such as the fact that it does not generate any capital advantage for banks that have well diversified portfolios. Moreover, it has also been recognised that bank capital pressures may have led to cyclical movements in banks’ lending, increasing macroeconomic instability.
Statistical Modeling of Spectrum Sensing Energy in Multi-Hop Cognitive Radio Networks

The aim of this letter is to address the statistical modeling of the spectrum sensing energy consumption in cognitive radio networks. A Poisson point process has been shown to yield tractable and accurate results for the modeling of the interference in cognitive radio networks. We adopt this homogeneous stochastic process to develop an unified framework for deriving the energy consumption of the spectrum sensing in clustered cognitive radio networks. Furthermore, we extend the framework to multi-hop networks. The letter demonstrates that the spectrum sensing energy can be modeled as a Gamma-truncated distribution, as a function of the number of secondary users, their spatial density, and the number of hops of the cognitive radio network.
Intravenous dexamethasone to prevent the recurrence of benign headache after discharge from the emergency department: a randomized, double-blind, placebo-controlled clinical trial.

OBJECTIVE To evaluate whether the addition of intravenous (i.v.) dexamethasone to standard emergency department (ED) benign headache therapy would reduce the incidence of headache recurrence at 48-72 hours. METHODS This randomized, double-blind, placebo-controlled clinical trial of adult patients presenting with the chief complaint of headache was conducted in the ED of 2 academic, urban Level 1 hospitals. Headache evaluation and therapy were determined by the treating physician, and, before discharge, patients were administered either 10 mg of IV dexamethasone or placebo. The treatment groups had similar baseline characteristics, abortive therapy, IV fluids and degree of pain relief achieved before discharge. Patients were contacted 48-72 hours following discharge and asked whether their headache was "better," "worse" or "remained unchanged" when compared with their symptoms at discharge. Those whose headaches were "worse" or "unchanged," and those who reported a return of headache after being pain free at discharge were considered to be treatment failures and classified as having had a recurrence. The patient's headache at follow-up was further categorized as severe (i.e., provoking another physician visit or interfering with daily activity) or mild (i.e., requiring self-medication or no treatment). RESULTS Fifty-seven patients met the inclusion criteria and 2 were lost to follow-up, leaving 55 for analysis. At follow-up, 9.7% (3/31) of those receiving dexamethasone had headache recurrence, versus 58.3% (14/24) of those receiving placebo (p < 0.001). Four dexamethasone recipients (12.9%) had severe headaches at follow-up compared with 8 (33.3%) in the placebo group (p = 0.14). CONCLUSIONS In this study, IV dexamethasone reduced headache recurrence at 48-72-hour follow-up. Given its excellent safety profile and likely benefit, IV dexamethasone should be considered for ED headache patients after standard evaluation and therapy.
On the polarization of Hα scattered by neutral hydrogen in active galactic nuclei

ABSTRA C T Raman scattering by atomic hydrogen converts the UV continuum around Lyb into optical continuum around Ha, and the basic atomic physics has been discussed in several works on symbiotic stars. We propose that the same process may operate in active galactic nuclei (AGN) and calculate the linear polarization of the broad emission lines Raman-scattered by highcolumn neutral hydrogen component. The conversion efficiency of the Raman scattering process is discussed and the expected scattered flux is computed using the spectral energy distribution of an AGN given by a typical power law. The high-column H i component in AGN is suggested by many observations, encompassing the radio through UV and X-ray ranges. When neutral hydrogen component with a column density ,10 22 cm π2 is present around the active nucleus, it is found that the scattered Ha is characterized by a very broad width ,20 000 km s π1 and that the strength of the polarized flux is comparable to that of the electron-scattered flux expected from a conventional unified model of narrow-line AGN. The width of the scattered flux is mainly determined by the column density of the neutral scatterers where the total scattering optical depth becomes of order unity. The asymmetry in the Raman scattering cross-section around Lyb introduces red asymmetric polarized profiles around Ha. The effects of the blended Lyb and O vi 1034 doublet are also investigated. We briefly discuss the spectropolarimetric observations performed on the Seyfert galaxy IRAS 110548-1131 and the narrow line radio galaxy Cyg A. Several predictions regarding the scattering by the high-column neutral hydrogen component in AGN are discussed.
Fine-Scale Exposure to Allergenic Pollen in the Urban Environment: Evaluation of Land Use Regression Approach

Background: Despite the recent developments in physically and chemically based analysis of atmospheric particles, no models exist for resolving the spatial variability of pollen concentration at urban scale. Objectives: We developed a land use regression (LUR) approach for predicting spatial fine-scale allergenic pollen concentrations in the Helsinki metropolitan area, Finland, and evaluated the performance of the models against available empirical data. Methods: We used grass pollen data monitored at 16 sites in an urban area during the peak pollen season and geospatial environmental data. The main statistical method was generalized linear model (GLM). Results: GLM-based LURs explained 79% of the spatial variation in the grass pollen data based on all samples, and 47% of the variation when samples from two sites with very high concentrations were excluded. In model evaluation, prediction errors ranged from 6% to 26% of the observed range of grass pollen concentrations. Our findings support the use of geospatial data–based statistical models to predict the spatial variation of allergenic grass pollen concentrations at intra-urban scales. A remote sensing–based vegetation index was the strongest predictor of pollen concentrations for exposure assessments at local scales. Conclusions: The LUR approach provides new opportunities to estimate the relations between environmental determinants and allergenic pollen concentration in human-modified environments at fine spatial scales. This approach could potentially be applied to estimate retrospectively pollen concentrations to be used for long-term exposure assessments. Citation: Hjort J, Hugg TT, Antikainen H, Rusanen J, Sofiev M, Kukkonen J, Jaakkola MS, Jaakkola JJ. 2016. Fine-scale exposure to allergenic pollen in the urban environment: evaluation of land use regression approach. Environ Health Perspect 124:619–626; http://dx.doi. org/10.1289/ehp.1509761
Execution Trace Analysis for the Software Development of Safety-Critical Systems

High quality software is an important part of mission critical systems. In order to attain high quality software and detect potential errors, the software must go through a rigorous testing process. Our goal is to automatically relate test failures based on the similarity of their execution traces. Our research involves determining the similarity of execution traces based on appropriate measures. Our approach shows promising results with real data.
Atributos e dimensões de qualidade da informação nas Ciências Contábeis e na Ciência da Informação: um estudo comparativo

Apresenta analise comparativa entre atributos de qualidade da informacao adotados no campo das Ciencias Contabeis (CC) e da Ciencia da Informacao (CI). Parte-se do pressuposto que o conceito de qualidade da informacao e fundamental para as duas areas de conhecimento, mas e um conceito difuso e depende da base epistemologica utilizada para defini-lo. O objetivo foi identificar semelhancas e/ou diferencas entre os pressupostos adotados para qualificar a informacao nos dois campos como base para compreensao das relacoes entre a informacao e seu potencial usuario. Alem da inexistencia de consenso quanto ao conceito de qualidade da informacao, os resultados mostram que tambem nao existe consenso em relacao as categorias, dimensoes e atributos de qualidade utilizados para qualificar a informacao na CI. Tais resultados sugerem que esforcos podem ser feitos na CI para buscar a consolidacao de um framework geral que possa servir como referencia na definicao e analise da qualidade da informacao nessa area do conhecimento. E, que, iniciativas podem ser tomadas no campo das CC visando a revisao de seu framework de qualidade da informacao para incorporar em sua estrutura conceitual atributos de qualidade da informacao considerados pela CI que podem contribuir para a melhoria da qualidade das informacoes contabeis.
Benchmarking the performance of SVMs and HMMs for accelerometer-based biometric gait recognition

Support Vector Machines (SVMs) and Hidden Markov Models (HMMs) have been in use for numerous classification tasks in pattern recognition. HMMs can be considered as a de-facto standard in speaker recognition. For accelerometer-based biometric gait recognition these methods have also shown good classification results, which are, however, not comparable as different data sets and features have been used. The contribution of this paper is a comprehensive benchmarking of the stated methods on a single database composed using a standard cell phone. In total, more than 19 hours of accelerometer data from 36 subjects were collected during two sessions. We analyze the influence of time on the recognition rates and state the results for normal and fast walk. In addition, we compare the results obtained when different amounts of training data are used. We show that SVMs are slightly superior to HMMs yielding an Equal Error Rate (EER) of around 10%.
An Approach to Sharing Legacy TV/Arcade Games for Real-Time Collaboration

Interactive TV/arcade games have been entertaining people for over 50 years. Nowadays a large number of legacy TV/arcade games have been ported to new platforms such as PCs by emulation. However, they generally require that the players be co-located to interact with one computer that emulates the game. This paper proposes a novel approach to turning those single-computer games into multi-computer games such that multiple players can play their favorite legacy games in real time over a computer network. The main challenge in this work is how to synchronize multiple replicas of a game without semantic knowledge about or modifications to the game. We have developed a novel synchronization algorithm and a working system to validate the ideas. In this paper we present the approach, especially the synchronization algorithm, and evaluate its effectiveness under a variety of network conditions. In future research we will extend this work on mobile devices.
Poverty and Fertility: Evidence and Agenda

This paper explores how poverty affects childbearing patterns in the contemporary developing world. In considering the association between poverty and fertility we explore one measure of economic status household asset holdings in Demographic and Health Surveys conducted in 51 countries since 1990. The results show that the association between poverty and fertility differs according to the measure of fertility considered. We conclude there is much to be gained from distinguishing between the impact of poverty on fertility aspirations and the implementation of those aspirations. Differentials in fertility aspirations are less common and smaller in magnitude than differentials in the implementation of aspirations. Fertility aspirations reflect strategizing about fertility that is embedded in broader strategizing about the future well-being of individuals and households. For multiple reasons this strategizing need not result in a sharp and monotonic association between fertility aspirations and household economic status. In exploring the literature on poverty we find a growing interest in the role of social capital and how it contributes to the maintenance or attenuation of poverty. The poverty literature could benefit from the considerable body of work on fertility that has articulated a central role of social capital. Moreover our understanding of the association between poverty and fertility would be strengthened by more attention to the role of social capital. (authors)
Application condition of linearized model uncertainty estimate

This paper studies the application condition of linearized model uncertainty estimate numerically for the Magnetotelluric (MT) problem using Bayesian inference theory, basedX on a three layer case with different parameter combinations. The nonlinear uncertainty estimate is calculated with relatively intensive computation, via Markov chain Monte Carlo method of Metropolis Hastings, giving an unbiased sampling from the posterior probability density (PPD), while the linearized uncertainty estimate which can be achieved cheaply, is based on the Gaussian distribution centered at the optimal model calculated based on a nonlinear optimization method, adaptive simplex simulated annealing (ASSA). The results show that linear uncertainty estimate can be evaluated as an alternative to the nonlinear uncertainty estimate for certain parameter combinations (model structure).