Miracle-dz/UniFAR-FTUs huggingface dataset:
Euclidean Reconstruction by means of an Uncalibrated Structured Light Sensor

A method of uncalibrated reconstruction through structured lighting is presented in this paper. The co-ordinates of 3-D points and the projection matrices are simultaneously determined in a parameter estimation approach. The reconstruction is performed in a projective frame, up to a projective transformation, by only using pixel correspondences. It is shown that an Euclidean reconstruction can be recovered by constraining the projective transformation by using geometrical knowledge about the scene. Moreover, it is described how the pattern projection is used to grab this kind of knowledge. This method provides our sensor with adaptive capabilities and permits to be used in mobile robotics. Experimental results realised both on simulated and real data are presented.
Local supermassive black holes, relics of active galactic nuclei and the X-ray background

We quantify the importance of mass accretion during AGN phases in the growth of supermassive black holes (BH) by comparing the mass function of black holes in the local universe with that expected from AGN relics, which are black holes grown entirely with mass accretion during AGN phases. The local BH mass function (BHMF) is estimated by applying the well-known correlations between BH mass, bulge luminosity and stellar velocity dispersion to galaxy luminosity and velocity functions. We find that different correlations provide the same BHMF only if they have the same intrinsic dispersion. The density of supermassive black holes in the local universe which we estimate is ρBH = 4.6 +1.9 −1.4 h 2.7 × 10 5 M⊙ Mpc −3 . The relic BHMF is derived from the continuity equation with the only assumption that AGN activity is due to accretion onto massive BH’s and that merging is not important. We find that the relic BHMF at z = 0 is generated mainly at z 10 9 M⊙ but can become as large as ∼ 10 9 yr for the lowest acceptable ǫ and λ values.
Evidence-Based, Pharmacological Treatment Guideline for Depression in Korea, Revised Edition

This paper aims to introduce, summarize, and emphasize the importance of the 'Evidence-Based, Pharmacological Treatment Guideline for Depression in Korea, Revised Edition'. The guideline broadly covers most aspects of the pharmacological treatment of patients in Korea diagnosed with moderate to severe major depression according to the DSM-IV TR. The guideline establishment process involved determining and answering a number of key questions, searching and selecting publications, evaluating recommendations, preparing guideline drafts, undergoing external expert reviews, and obtaining approval. A guideline adaptation process was conducted for the revised edition. The guideline strongly recommends pharmacological treatment considered appropriate to the current clinical situation in Korea, and should be considered helpful when selecting the appropriate pharmacological treatment of patients diagnosed with major depressive disorder. Therefore, the wide distribution of this guideline is recommended.
Social Media Analytics: The Kosmix Story

Kosmix was a Silicon Valley startup founded in 2005 by Anand Rajaraman and Venky Harinarayan. Initially targeting Deep Web search, in early 2010 Kosmix shifted its main focus to social media, and built a large infrastructure to perform social media analytics, for a variety of real-world applications. In 2011 Kosmix was acquired by Walmart and converted into @WalmartLabs, the advanced research and development arm of Walmart. The goals of the acquisition were to provide a core of technical people in the Valley and attract more, to help improve traditional e-commerce for Walmart, and to explore the future of e-commerce. This future looks increasingly social, mobile, and local. Accordingly, @WalmartLabs continues to develop the social media analytics infrastructure pioneered by Kosmix, and uses it to explore a range of social e-commerce applications. In this paper we describe social media analytics, as carried out at Kosmix. While our framework can handle many types of social media data, for concreteness we will focus mostly on tweets. Section 2 describes the analytics architecture, the applications, and the challenges. We describe in particular the Social Genome, a large real-time social knowledge base that lied at the heart of Kosmix and powered most of its applications. Section 3 describes how the Social Genome was built, using Wikipedia, a set of other data sources, and social media data. Section 4 describes how we classify and tag tweets, and extract entities from tweets and link them to a knowledge base. Section 5 describes how we detect and monitor events in the Twittersphere. Section 6 discusses how we process the high-speed Twitter stream using Muppet, a scalable distributed stream processing engine built in house [1]. Section 7 discusses lessons learned and related work, and Section 8 concludes. Parts of the work described here have been open sourced [1] and described in detail in recent papers [18, 23, 25, 32].
Finding coordinated paths for multiple holonomic agents in 2-d polygonal environment

Avoiding collisions is one of the vital tasks for systems of autonomous mobile agents. We focus on the problem of finding continuous coordinated paths for multiple mobile disc agents in a 2-d environment with polygonal obstacles. The problem is PSPACE-hard, with the state space growing exponentially in the number of agents. Therefore, the state of the art methods include mainly reactive techniques and sampling-based iterative algorithms. We compare the performance of a widely-used reactive method ORCA with three variants of a popular planning algorithm RRT* applied to multi-agent path planning and find that an algorithm combining reactive collision avoidance and RRT* planning, which we call ORCA-RRT* can be used to solve instances that are out of the reach of either of the techniques. We experimentally show that: 1) the reactive part of the algorithm can efficiently solve many multi-agent path finding problems involving large number of agents, for which RRT* algorithm is often unable to find a solution in limited time and 2) the planning component of the algorithm is able to solve many instances containing local minima, where reactive techniques typically fail.
Spark plasma sintering of TiN-cubic BN composites

TiN-cubic boron nitride (cBN) composites were prepared from TiN and cBN powders by spark plasma sintering at temperatures from 1600 to 1800°C for 600 s under a uniaxial pressure of 100 MPa. The densification, phase transformation, microstructure and mechanical properties of the TiN-cBN composites were investigated. TiN-BN composites originally containing 10 to 30 vol% cBN without a phase transformation from cBN to hexagonal BN (hBN) were obtained at a sintering temperature of 1600°C. The densification of the TiN-BN composites was retarded with increasing cBN content. The phase transformation from cBN to hBN in the TiN-BN composites started at 1650°C and was completed at 1800°C. The Vickers hardness and fracture toughness of TiN-BN composite, originally containing 10 vol% cBN, prepared at 1600°C were 17 GPa and 3.6 MPa·m1/2, respectively.
Comparative Genomic Analysis of Soybean Flowering Genes

Flowering is an important agronomic trait that determines crop yield. Soybean is a major oilseed legume crop used for human and animal feed. Legumes have unique vegetative and floral complexities. Our understanding of the molecular basis of flower initiation and development in legumes is limited. Here, we address this by using a computational approach to examine flowering regulatory genes in the soybean genome in comparison to the most studied model plant, Arabidopsis. For this comparison, a genome-wide analysis of orthologue groups was performed, followed by an in silico gene expression analysis of the identified soybean flowering genes. Phylogenetic analyses of the gene families highlighted the evolutionary relationships among these candidates. Our study identified key flowering genes in soybean and indicates that the vernalisation and the ambient-temperature pathways seem to be the most variant in soybean. A comparison of the orthologue groups containing flowering genes indicated that, on average, each Arabidopsis flowering gene has 2-3 orthologous copies in soybean. Our analysis highlighted that the CDF3, VRN1, SVP, AP3 and PIF3 genes are paralogue-rich genes in soybean. Furthermore, the genome mapping of the soybean flowering genes showed that these genes are scattered randomly across the genome. A paralogue comparison indicated that the soybean genes comprising the largest orthologue group are clustered in a 1.4 Mb region on chromosome 16 of soybean. Furthermore, a comparison with the undomesticated soybean (Glycine soja) revealed that there are hundreds of SNPs that are associated with putative soybean flowering genes and that there are structural variants that may affect the genes of the light-signalling and ambient-temperature pathways in soybean. Our study provides a framework for the soybean flowering pathway and insights into the relationship and evolution of flowering genes between a short-day soybean and the long-day plant, Arabidopsis.
Education for Sustainable Development and Global Citizenship adult and community learning in Wales : from policy to pedagogy

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THE INFLUENCE OF DIRECT WRITTEN CORRECTIVE FEEDBACK TOWARD EFL STUDENTS’ ESSAY WRITING

This research referred to the experiences of the researchers in providing students writing courses in the context of EFL (English as Foreign Language) in Batam. It was found that students’ essay writing contained several grammatical errors to plagiarism. This study aimed to determine the level of effectiveness of written corrective feedback (WCF) on the quality of students’ essay writing. The research method was quasiexperimental where the control class was given treatment by using no WCF and the experimental class was given WCF. Both scores from control and experiment classes were different. The mean of experiment class was higher than the mean from control class. After analyzing them statistically, it was found that the hypothesis (Ha) was accepted. It meant that WCF had a significant effect on the quality of essay writing. It was concluded that WCF is a better way in improving the quality of students' essay writing.
Observing the fluctuating stripes in high-Tc superconductors

Superfluids and superconductors have been around for a long time and their explanation in terms of the Bogoliubov theory for bosons and the BCS theory for fermions belong to the highlights of twentieth century physics. However, it appears that these theories are too primitive to address the high-Tc superconductivity found in copper oxides. These electron systems seem to behave more like a dense, strongly correlated liquid contrasting markedly with the conventional quantum gasses: these show strong dynamical correlations on mesoscopic length and time scales associated with stripes, a particular form of electron crystallization. Resting on the gauge theory of topological quantum melting in 2+1 dimensions relevant for the cuprates, we describe the limit which is exactly opposite to the gas limit: the superconductor with the maximum possible amount of transient translational order. We predict that in this “orderly limit” an extra collective mode appears, and this “massive shear photon” can be regarded as a universal fingerprint of the fluctuating stripes. This mode is visible in the electrodynamic response and the ramification of our theory is that electron energy loss spectroscopy can be employed to prove or disprove the existence of dynamical stripes in cuprate superconductors.
VOLATILITY FORECASTS, TRADING VOLUME, AND THE ARCH VERSUS OPTION-IMPLIED VOLATILITY TRADE-OFF

Market expectations of future return volatility play a crucial role in finance; so too does our understanding of the process by which information is incorporated in security prices through the trading process. This paper seeks to learn something about both of these issues by investigating empirically the role of trading volume (a) in predicting the relative informativeness of volatility forecasts produced by ARCH models versus the volatility forecasts derived from option prices, and (b) in improving volatility forecasts produced by ARCH and option models and combinations of models.
Importance of High-Order N-Gram Models in Morph-Based Speech Recognition

Speech recognition systems trained for morphologically rich languages face the problem of vocabulary growth caused by prefixes, suffixes, inflections, and compound words. Solutions proposed in the literature include increasing the size of the vocabulary and segmenting words into morphs. However, in many cases, the methods have only been experimented with low-order n-gram models or compared to word-based models that do not have very large vocabularies. In this paper, we study the importance of using high-order variable-length n-gram models when the language models are trained over morphs instead of whole words. Language models trained on a very large vocabulary are compared with models based on different morph segmentations. Speech recognition experiments are carried out on two highly inflecting and agglutinative languages, Finnish and Estonian. The results suggest that high-order models can be essential in morph-based speech recognition, even when lattices are generated for two-pass recognition. The analysis of recognition errors reveal that the high-order morph language models improve especially the recognition of previously unseen words.
Minimization of Reversible Wave Cascades

In this paper two algorithms for the synthesis and minimization of a CA (cellular array architecture) are proposed. Starting from a completely specified single-output switching function, our methods produce rectangularly shaped arrays of cells, interconnected in chains, with an effort to minimize the number of the produced chains (cascades). This kind of cellular topology is known throughout the bibliography as Maitra cellular arrays. The significance of those algorithms is underlined by the fact that this particular type of cellular architecture can be mapped to reversible circuits and gates (generalized Toffoli gates), which are the type of logic used in quantum circuits. The proposed methodologies include use of ETDDs (EXOR ternary decision diagrams), and switching function decompositions (including new types of boolean expansions).
An Interior Point Algorithm for Large-Scale Nonlinear Programming

The design and implementation of a new algorithm for solving large nonlinear programming problems is described. It follows a barrier approach that employs sequential quadratic programming and trust regions to solve the subproblems occurring in the iteration. Both primal and primal-dual versions of the algorithm are developed, and their performance is illustrated in a set of numerical tests.
Sharp k-order Sobolev inequalities in the hyperbolic space ${\Bbb H}^n$

In this paper, we obtain the sharp $k$-th order Sobolev inequalities in the hyperbolic space ${\H}^n$ for all $k=1,2,3,\cdots$. This gives an answer to an open question raised by Aubin in [5, p.$\;$176-177] for $W^{k,2}({\H}^n)$ with $k>1$. In addition, we prove that the associated Sobolev constants are optimal.
Faster than Weighted A*: An Optimistic Approach to Bounded Suboptimal Search

Planning, scheduling, and other applications of heuristic search often demand we tackle problems that are too large to solve optimally. In this paper, we address the problem of solving shortest-path problems as quickly as possible while guaranteeing that solution costs are bounded within a specified factor of optimal. 38 years after its publication, weighted A* remains the best-performing algorithm for general-purpose bounded suboptimal search. However, it typically returns solutions that are better than a given bound requires. We show how to take advantage of this behavior to speed up search while retaining bounded suboptimality. We present an optimistic algorithm that uses a weight higher than the user's bound and then attempts to prove that the resulting solution adheres to the bound. While simple, we demonstrate that this algorithm consistently surpasses weighted A* in four different benchmark domains including temporal planning and gridworld pathfinding.
The impact of stakeholder collaboration on effectiveness of health program implementation in Ghana

Healthcare providers increasingly recognize the importance of collaboration among stakeholders in cost-effective healthcare delivery. While collaborative relationships offer great advantages, little research has addressed their relevance in an international development aid context, particularly in sub-Saharan Africa. The region is a major recipient of international development support, yet health indicators on HIV/AIDS, malaria, tuberculosis, and child and maternal mortality indicate the health of the region is among the weakest worldwide. This sequential mixed method, descriptive study of a USAID-funded community health program in Ghana examined the nature of collaboration among six stakeholders and impact of this collaboration on effectiveness of program implementation. Stakeholder and resource dependence theories provided conceptual frameworks for analysis. Data were collected through surveys and interviews of officers of participating organizations (POs) and community health officers (CHOs). Surveys were analyzed using means, standard deviations, and t tests, while coding and themes determination were adopted for the interview data analysis. Results from both sources were integrated. Findings indicate both POs and CHOs perceived human relationship factors as more critical than physical resources. Collaboration, shared decision making, and frequency of communication in the relationship were perceived to substantially improve CHO skills and rural healthcare quality. Recommendations include active development of strong trust and dialogue in future relationships. These results could have important implications for positive social change by identifying the bases for collaborative success in providing impoverished rural communities with cost-effective and quality healthcare to address critical community health needs. The Impact of Stakeholder Collaboration on Effectiveness of Health Program Implementation in Ghana by Samuel Kwami Agbanu Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Applied Management and Decision Sciences Walden University May 2010
Comparing Focus on Forms and Task-Based Language Teaching in the Acquisition of Russian as a Foreign Language

El presente estudio explora el impacto en la adquisicion del ruso como lengua extranjera de TSLT (Task-supported language teaching) y TBLT (Task-based language teaching). El objeto de analisis es la adquisicion de los casos y de los verbos de movimiento en la produccion oral y escrita en los parametros de la complejidad, correccion y fluidez. El estudio experimental sigue el diseno de pre-test ‒ post-test inmediato ‒ post-test diferido. Los datos han sido obtenidos a partir del trabajo con estudiantes de primer y segundo curso de la Universidad de Barcelona (n=54) con un nivel elemental de competencia en lengua rusa. Dos grupos de estudiantes han trabajado con la metodologia TSLT y otros dos con TBLT. Cada uno de los 4 grupos ha recibido 14 horas de formacion. Los datos analizados se han obtenido a partir de tests gramaticales (espacios en blanco, seleccion multiple y tests de gramaticalidad), una tarea escrita consistente en escribir una carta a un amigo, y dos tareas orales (la descripcion de una habitacion y una Map task). El analisis estadistico de la adquisicion de las preposiciones y las formas declinadas muestra que tanto con TSLT como TBLT se consiguen resultados satisfactorios en el post-test inmediato, pero no en el post-test diferido. En cambio, independientemente del tipo de instruccion, los participantes si han demostrado progresos significativos en su competencia de los verbos de movimiento. En la produccion escrita, la complejidad sintactica medida en proposiciones por T-unit y la complejidad lexica aumentan significativamente despues de la instruccion. La correccion mejora significativamente en ambos grupos en el post-test inmediato y en el post-test diferido del grupo TBLT. En la produccion oral, los estudiantes de ambos grupos mejoran su correccion en la tarea Map task, la complejidad lexica y fluidez en ambas tareas orales, pero no consiguen progresos significativos en lo que respecta a la complejidad sintactica en ninguna de las dos tareas. La comparacion de los dos tipos de instruccion muestra que los estudiantes de los grupos TBLT consiguen mejores resultados que los de TSLT en lo que se refiere a complejidad lexica y verbos de movimiento.
Bootstrapping Sequential Tests for Multiple Structural Breaks

We show how . nite sample bootstrapping methods can help to detect multiple breaks in systems of equations with long time series. The method of Banerjee and Urga (1995, 1996), where single breaks in the marginal models are imposed in the conditional model and then the conditional model estimated, is extended to cover the case of multiple (> 2) breaks in marginal and conditional models by using the technique of dominant break dating. An empirical investigation of a small monetary system for the United Kingdom establishes the viability of our method in developing congruent dynamic regression models. ¤European University Institute (Florence, Italy) and Institute of Economics and Statistics (Oxford, U.K.), London School of Economics (U.K.) and Cass Business School (106, Bunhill Row, London, EC1Y 8TZ,UK, g.urga@city.ac.uk) respectively. The authors are grateful to Niels Buhl for his help in developing the initial versions of the programmes used in this paper. We are also grateful to Rasche for providing the data used by them in Ho¤man and Rasche (1995) and to G. Williams at CEF-LBS for help with updating the series. Responsibility for any errors remaining rests with us. Giovanni Urga thanks the ESRC under grant number R000238145 for funding this reserach.
A Three-Step Heckit Estimator for Panel Data with Fixed Effects and an Application to Bidders’ Advisor Choice and Returns in Acquisition Sequences

The study extents the literature of the advising bank’s positive influence on the performance in mergers and acquisitions by modeling the double endogeneity arising from the banks’ selection by their expertise and advisory relationships along acquisition sequences. The double endogeneity arising in the selection of banks as advisors, which is observed in advised deals only, by their industry expertise and advisory relationship strength is solved with a new Three-step Heckit estimator. The Three-step Heckit estimator is an extension of the (Heckman, 1976, 1979) Two-step Heckit estimator for panel data developed by (Wooldridge, 1995). The analysis shows that the matching of the most experienced banks with the strongest advisory relationships and highest past performance with serial acquirers in the most complex transactions is efficient in terms of higher returns.