Miracle-dz/UniFAR-FTUs huggingface dataset:
Groups of galaxies: relationship between environment and galaxy properties

We analyse how the properties of galaxies in groups identified in the Sloan Digital Sky Survey depend on the environment. In particular, we study the relationship between galaxy properties and group mass and group-centric distance. Among the galaxy properties we have considered here, we find that the g - r colour is the most predictive parameter for group mass, while the most predictive pair of properties are g - r colour and r-band absolute magnitude. Regarding the position inside the systems, the g - r colour is the best tracer of group-centric distance and the most predictive pair of properties are g - r colour and spectral type taken together. These results remain unchanged when a subsample of high-mass groups is analysed. The same happens if the brightest group galaxies are excluded.
Differential subcellular localization of forward and feedback interareal inputs to parvalbumin expressing GABAergic neurons in rat visual cortex

In rat visual cortex, forward and feedback interareal pathways innervate both pyramidal and gamma‐aminobutyric acid (GABA)ergic (Johnson and Burkhalter [1996] J. Comp. Neurol. 368:383–398). GABAergic neurons consist of different cell types of which the largest group expresses parvalbumin (PV; Gonchar and Burkhalter [1997] Cereb. Cortex 4:347–358). Here, we report that PV neurons in layers 2/3 are synaptic targets of forward and feedback projections between area 17 and the lateromedial area (LM) of rat visual cortex.
Preference Grammars and Soft Syntactic Constraints for GHKM Syntax-based Statistical Machine Translation

In this work, we investigate the effectiveness of two techniques for a featurebased integration of syntactic information into GHKM string-to-tree statistical machine translation (Galley et al., 2004): (1.) Preference grammars on the target language side promote syntactic wellformedness during decoding while also allowing for derivations that are not linguistically motivated (as in hierarchical translation). (2.) Soft syntactic constraints augment the system with additional sourceside syntax features while not modifying the set of string-to-tree translation rules or the baseline feature scores. We conduct experiments with a stateof-the-art setup on an English! German translation task. Our results suggest that preference grammars for GHKM translation are inferior to the plain targetsyntactified model, whereas the enhancement with soft source syntactic constraints provides consistent gains. By employing soft source syntactic constraints with sparse features, we are able to achieve improvements of up to 0.7 points BLEU and 1.0 points TER.
Incrementality in Deterministic Dependency Parsing

Deterministic dependency parsing is a robust and efficient approach to syntactic parsing of unrestricted natural language text. In this paper, we analyze its potential for incremental processing and conclude that strict incrementality is not achievable within this framework. However, we also show that it is possible to minimize the number of structures that require non-incremental processing by choosing an optimal parsing algorithm. This claim is substantiated with experimental evidence showing that the algorithm achieves incremental parsing for 68.9% of the input when tested on a random sample of Swedish text. When restricted to sentences that are accepted by the parser, the degree of incrementality increases to 87.9%.
XML Documents Clustering Research Based on Weighted Cosine Measure

Recently, a large amount of work has been done in XML data mining. However, most of the existing work focuses on the snapshot XML data, while XML data is dynamic in practical application. In order to mine knowledge hidden in the frozen structures (FS) which are not changed or very little changed during the historical changing process of an XML document, we present a method for clustering XML documents via FS. Also, a novel algorithm called weighted cosine measure (WCM) improved from the traditional algorithm has been proposed, and using which we can calculate the similarity between two clusters. Otherwise, we propose a method using the agglomerative hierarchical during the cluster process. Experiments results on our new algorithm indicate that the proposed solution performs significantly. XML documents can be effectively clustered and the results of using the WCM are better than using the traditional cosine measure. Then, XML documents in each cluster have similar structures not often changed.
Membrane-type 1 matrix metalloproteinase-mediated progelatinase A activation in non-tumorigenic and tumorigenic humaneratinocytes

Elevated expression of type IV collagenases (MMP-2 and MMP-9) has been strongly correlated with tumour progression and metastasis in various tumours. Here, we analysed expression and activation of these MMPs in non-tumourigenic HaCaT cells and the malignant HaCaT variant II-4rt. In monolayer cultures, both cell types secreted latent MMP-2 (proMMP-2) in comparable amounts, while MMP-9 production was clearly higher in II-4rtcells. Upon contact with fibrillar collagen type I the malignant II-4rtcells, but not the HaCaT cells, gained the capability to activate proMMP-2. This process is shown to be membrane-associated and mediated by MT1-MMP. Surprisingly, all membrane preparations from either HaCaT cells or II-4rtcells grown as monolayers, as well as within collagen gels, contained considerable amounts of active MT1-MMP. However, within collagen gels HaCaT cells showed significantly higher TIMP-2 levels compared to II-4rtcells. This indicates that TIMP-2 might play a central role for MT1-MMP-mediated gelatinolytic activity. Indeed, collagen type I-induced MT1-MMP-mediated proMMP-2 activation by II-4rtmembranes could be completely abolished by an excess of TIMP-2. In conclusion, our data suggest that MT1-MMP-mediated proMMP-2 activation might be associated with malignant progression of epidermal tumour cells. © 2000 Cancer Research Campaign
Tightening data analysis and feature extraction for micro-blog recommendation

Information explosion in micro-blog services brings bad experience to users. Therefore, approaches that leverage users' preferences in applications of messages filtering, recommendation and searching were proposed by scholars in recent years. In general, features extraction is critical process in applying these approaches to applications. However, current researches have been focused on finding better models on varied features, but ignored why these features were used. To answer this question, we make an intuitive assumption that directly applying the result of data analysis, especially using the result of data analysis as features in our proposal, might lead to better performance than general raw features. In this paper, we propose to use these new features in a naive approach and a learning to rank approach for application of messages recommendation in micro-blog service. The experiments by the two approaches over a large real-world data set, which compare performance of proposed new features and raw features, support our assumption.
X−SOM: Ontology Mapping and Inconsistency Resolution

Data integration is an old but still open issue in the database research area, where Semantic Web technologies, such as ontologies, may be of great help. Aim of the Context-ADDICT project is to provide support for the integration and context-aware reshaping of data coming from heterogeneous data sources. Within this framework, we use ontology extraction, alignment and tailoring to find and solve conflicts due to data source heterogeneity. In this paper we present X-SOM: an ontology mapping tool developed within the Context-ADDICT project. The contribution of this high precision mapping tool is twofold: (i) a modular and extensible architecture that automatically combines several matching techniques by means of a neural network,and (ii) a subsystem for the (semi)-automatic resolution of semantic inconsistencies. Besides describing the tool components, we discuss the prototype implementation, which has been tested against the OAIE 2006 benchmark with promising results, and effectively exploited within the ContextADDICT project.
Computational Pp Olya Theory

A permutation group G of degree n has a natural induced action on words of length n over a nite alphabet , in which the image x g of x under permutation g 2 G is obtained by permuting the positions of symbols in x according to g. The key result in \PP olya theory" is that the number of orbits of this action is given by an evaluation of the cycle-index polynomial P G (z 1 ; : : :; z n) of G at the point z 1 = = z n = j j. In many cases it is possible to count the number of essentially distinct instances of a combinatorial structure of a given size by evaluating the cycle-index polynomial of an appropriate symmetry group G. We address the question \to what extent can PP olya theory be mech-anised? " There are compelling complexity-theoretic reasons for believing that there is no eecient, uniform procedure for computing the cycle-index polynomial exactly, but less is known about approximate evaluation, say to within a speciied relative error. The known results | positive and negative | will be surveyed. 1 Preliminaries This article is concerned with a topic in computational algebra, which combines aspects of combinatorics, algorithmics, and computational complexity. On the assumption that most readers will be unfamiliar with at least one of these, the rst section aims to give a brief account of key facts.
Single depth image super resolution and denoising via coupled dictionary learning with local constraints and shock filtering

Recently, consumer depth cameras have gained significant popularity due to their affordable cost. However, the limited resolution and quality of the depth map generated by these cameras are still problems for several applications. In this paper, we propose a new algorithm for depth image super resolution using a single depth image as input. We reconstruct the corresponding high resolution depth map through a robust coupled dictionary learning algorithm with local coordinate constraints. The local constraints remove the prediction uncertainty and prevent the dictionary from over-fitting. We also incorporate an adaptively regularized Shock filter to simultaneously reduce the noise and sharpen the edges. Experimental results demonstrate the effectiveness of our proposed algorithm compared to previously reported methods.
A model of hierarchical real-time virtual resources

A real-time virtual resource is an abstraction for resource sharing where application task groups must meet timing constraints and knowledge of all the timing requirements may not be available for a global schedulability analysis, such as is the case in the open system environment. In a 2001 paper, we introduced the notion of a real-time virtual resource which operates at a fraction of the rate of the shared physical resource and whose rate of service provision varies with time but is bounded. The shared resource is partitioned into real-time virtual resources by a resource-level scheduler such that each real-time virtual resource is accessible only by an individual application task group; tasks within the same task group are scheduled by an application-task-level scheduler that is specialized to the real-time requirements of the tasks in the group. In this paper we propose a hierarchical real-time virtual resource model that permits resource partitioning to be extended to multiple levels. Through this model, partitions on each level are scheduled as if they had access to a dedicated resource and there is minimal interference between neighboring partition levels. We also investigate the partitioning of real-time virtual resources subject to scheduling quantum requirements.
Kernelized LRR on Grassmann Manifolds for Subspace Clustering

Low rank representation (LRR) has recently attracted great interest due to its pleasing efficacy in exploring low-dimensional sub- space structures embedded in data. One of its successful applications is subspace clustering, by which data are clustered according to the subspaces they belong to. In this paper, at a higher level, we intend to cluster subspaces into classes of subspaces. This is naturally described as a clustering problem on Grassmann manifold. The novelty of this paper is to generalize LRR on Euclidean space onto an LRR model on Grassmann manifold in a uniform kernelized LRR framework. The new method has many applications in data analysis in computer vision tasks. The proposed models have been evaluated on a number of practical data analysis applications. The experimental results show that the proposed models outperform a number of state-of-the-art subspace clustering methods.
A Cross-Cultural Exploration of Imagination as a Process-Based Concept

The present study explores imagination in a cross-cultural context through an original 25-item questionnaire. A cross-national sample of 940 respondents included 336 participants from North America, 309 from Germany, and 295 from mainland China. Imagination is shown to be a process-based concept consisting of a number of components (factors) rather than a single, reified faculty. A principal component factor analysis yielded a five-factor model including expressive imagination, openness to variations, instrumental imagination, past/future mindedness, and conventionality (in descending order of importance). The central factor, expressive imagination, reflects the intrinsically motivated creation and reception of narratives in everyday life and childhood imaginary worlds. Significant regional differences were found for all five factors. Cultural and social contributors to the study results were discussed.
The magnetic field of M 31 from multi-wavelength radio polarization observations

The configuration of the regular magnetic field in M31 is deduced from radio polarization observations at the wavelengths �� 6, 11 and 20cm. By fitting the observed azimuthal distribution of polarization angles, we find that the regular magnetic field, averaged over scales 1-3kpc, is almost perfectly axisymmetric in the radial range 8 to 14kpc, and follows a spiral pattern with pitch angles of p ≃ −19 ◦ to p ≃ −8 ◦ . In the ring between 6 and 8kpc a perturbation of the dominant axisymmetric mode may be present, having the azimuthal wave number m = 2. A systematic analysis of the observed depolarization allows us to identify the main mechanism for wavelength dependent depolarization - Faraday rotation measure gradients arising in a magneto-ionic screen above the synchrotron disk. Modelling of the depolarization leads to constraints on the relative scale heights of the thermal and synchrotron emitting layers in M31; the thermal layer is found to be up to three times thicker than the synchrotron disk. The regular magnetic field must be coherent over a vertical scale at least similar to the scale height of the thermal layer, estimated to be hth ≃ 1kpc. Faraday effects offer a powerful method to detect thick magneto-ionic disks or halosaround spiral galaxies.
Functional MRI of the zebra finch brain during song stimulation suggests a lateralized response topography

Electrophysiological and activity-dependent gene expression studies of birdsong have contributed to the understanding of the neural representation of natural sounds. However, we have limited knowledge about the overall spatial topography of song representation in the avian brain. Here, we adapt the noninvasive functional MRI method in mildly sedated zebra finches (Taeniopygia guttata) to localize and characterize song driven brain activation. Based on the blood oxygenation level-dependent signal, we observed a differential topographic responsiveness to playback of bird's own song, tutor song, conspecific song, and a pure tone as a nonsong stimulus. The bird's own song caused a stronger response than the tutor song or tone in higher auditory areas. This effect was more pronounced in the medial parts of the forebrain. We found left–right hemispheric asymmetry in sensory responses to songs, with significant discrimination between stimuli observed only in the right hemisphere. This finding suggests that perceptual responses might be lateralized in zebra finches. In addition to establishing the feasibility of functional MRI in sedated songbirds, our results demonstrate spatial coding of song in the zebra finch forebrain, based on developmental familiarity and experience.
Communications in Mathematical Physics Categorified Symplectic Geometry and the Classical String

A Lie 2-algebra is a ‘categorified’ version of a Lie algebra: that is, a category equipped with structures analogous to those of a Lie algebra, for which the usual laws hold up to isomorphism. In the classical mechanics of point particles, the phase space is often a symplectic manifold, and the Poisson bracket of functions on this space gives a Lie algebra of observables. Multisymplectic geometry describes an n-dimensional field theory using a phase space that is an ‘n-plectic manifold’: a finite-dimensional manifold equipped with a closed nondegenerate (n+1)-form. Here we consider the case n = 2. For any 2-plectic manifold, we construct a Lie 2-algebra of observables. We then explain how this Lie 2-algebra can be used to describe the dynamics of a classical bosonic string. Just as the presence of an electromagnetic field affects the symplectic structure for a charged point particle, the presence of a B field affects the 2-plectic structure for the string.
Depression in menopaused and nonmenopaused women.

BACKGROUND This cross-sectional investigation compared the depressive condition between menopaused and nonmenopasued women in the age of 45-55 in Yazd city in Yazd Province in center of Iran. METHODS The samples were divided into two groups (70 menopaused women and 70 nonmenopaused women) , and were selected by cluster sampling from the city of Yazd. The depressive tendency of participants was examined with the Beck depression inventory. RESULTS About 72% of women were free of any depressive tendency, or very minor depression. Thirty women (21.4%) suffered from intermediate depression and 9 women (6.4%) suffered from sever depression. More than 27% of subjects were suffered from some forms of depression. There was no significant difference between the depression and condition of menopause of women. CONCLUSION It is a need to know the women's condition of depression and counseling as well as guiding them on basis of their needs to prevent any disorders.
Decaying D-branes and moving mirrors

We present an exact time-dependent solution to the effective D-brane world-volume theory which describes an inhomogeneous decay of a brane-antibrane system. We compute the quantum energy flux induced by the particle creation in this inhomogeneous and time-dependent background. We find that this calculation is essentially equivalent to that of the moving mirror system. In the initial stage, the energy flux turns out to be thermal with the temperature given by the inverse of the distance between the brane and the antibrane. Later it changes its sign and becomes a negative energy flux. Our result may be relevant for the (p)reheating process or/and the evolution of cosmic string network after stringy brane inflation.
Ethical Issues in Early Intervention: Voices From the Field

Ethical considerations are integral to our professional lives when we are faced with difficult choices regarding services and supports for children and families. Often, the right choice in service delivery for young children with disabilities ages birth to 5 years is unclear due to a myriad of factors potentially creating ethical dilemmas. This article reports the results of a focus group study with 82 early intervention (EI) professionals serving young children ages birth to 5 years designed to determine EI practitioners' ethical concerns in daily practice and how they are resolved. Professionals shared dilemmas they have experienced related to family–professional and interprofessional conflicts as well as those related to policy and programmatic issues. In addition, resolution strategies used by EI practitioners are highlighted. Guidelines for systematic ethical reflection and problem solving are recommended on the basis of professional Codes of Ethics.
The Influence of the Microbiome on Early-Life Severe Viral Lower Respiratory Infections and Asthma—Food for Thought?

Severe viral lower respiratory infections are a major cause of infant morbidity. In developing countries, respiratory syncytial virus (RSV)-bronchiolitis induces significant mortality, whereas in developed nations the disease represents a major risk factor for subsequent asthma. Susceptibility to severe RSV-bronchiolitis is governed by gene–environmental interactions that affect the host response to RSV infection. Emerging evidence suggests that the excessive inflammatory response and ensuing immunopathology, typically as a consequence of insufficient immunoregulation, leads to long-term changes in immune cells and structural cells that render the host susceptible to subsequent environmental incursions. Thus, the initial host response to RSV may represent a tipping point in the balance between long-term respiratory health or chronic disease (e.g., asthma). The composition and diversity of the microbiota, which in humans stabilizes in the first year of life, critically affects the development and function of the immune system. Hence, perturbations to the maternal and/or infant microbiota are likely to have a profound impact on the host response to RSV and susceptibility to childhood asthma. Here, we review recent insights describing the effects of the microbiota on immune system homeostasis and respiratory disease and discuss the environmental factors that promote microbial dysbiosis in infancy. Ultimately, this knowledge will be harnessed for the prevention and treatment of severe viral bronchiolitis as a strategy to prevent the onset and development of asthma.
Integrating Occupational Complexity Levels to Interest Assessments in Social and Enterprising Areas: Development of the Vertical Social Interest Scale

With the goal of improving assessment of interests toward social and enterprising areas, we developed the Vertical Social Interest Scale (VSIS) by incorporating vertical differentiation between occupations in terms of authority and communication. Social and enterprising occupations, their complexity levels, and work activities were identified using the information in the Dictionary of Occupational Titles and Occupational Information Network. Three studies (N = 515 total), two of which utilized students and one a working adult sample, were conducted to assess the factor structure and validity of VSIS. Construct validity was demonstrated using factor analyses and based on associations with traditional interest assessments and extraversion. Criterion-related validity was demonstrated based on associations with satisfaction with academic domain for the student sample and affective occupational commitment for the adult sample. Results support the validity of VSIS in predicting relevant vocational outcomes.