Miracle-dz/UniFAR-FTUs huggingface dataset:
Multifrequency Analysis of the New Wide-Separation Gravitational Lens Candidate RX J0921+4529

We report the discovery of a new two-image gravitational lens candidate. The system RX J0921+4529 contains two zs = 1.66 quasars separated by 6. ″93 with an H-band magnitude difference of Δm = 1.39. The HST NIC2 H-band images reveal an H = 18.2 spiral galaxy between the quasar images, which is probably a member of a zl = 0.32 X-ray cluster centered on the field. We detect an extended source near the fainter quasar image but not in the brighter image. If this extended source is the host galaxy of the fainter quasar, then the system is a binary quasar rather than a gravitational lens. VLA observations at 3.6 cm reveal emission from the lens galaxy at the flux level of 1 mJy and a marginal detection of the brighter quasar.
Applying conformal geometry for creating a 3D model spatial-consistent texture map

The aim of this research is to achieve spatial consistency of the UV map. We present an approach to produce a fully spatially consistent UV mapping based on the planar parameterisation of the mesh. We apply our method on a 3D digital replica of an ancient Greek Lekythos vessel. We parameterise the mesh of a 3D model onto a unit square 2D plane using computational conformal geometry techniques. The proposed method is genus independent, due to an iterative 3D mesh cutting procedure. Having now the texture of a 3D model depicted on a spatially continuous two dimensional structure enables us to efficiently apply a vast range of image processing based techniques and algorithms.
2 Objects of Expertise

Why is face recognition so interesting? Within the realm of visual cognition, faces have been afforded a degree of analysis that surpasses most other object categories. There are several reasons for this intense scrutiny. First, faces are critical to us as social beings. Thus, we are inherently interested the mental and neural processes responsible for our ability to recognize, interpret, and remember faces. Second, face recognition is one of the most difficult visual discrimination tasks we routinely (and almost universally) perform. As such, vision researchers often view face recognition as the most extreme task our visual systems can support. Third, in part motivated by the first two reasons, face recognition is often considered a likely candidate for cognitive and neural specialization. Consequently, face processing makes an interesting litmus test with regard to the nature versus nurture debate. Although these factors do make faces an interesting subject, here we argue that the study of face recognition in and of itself is not nearly as informative as face recognition studied in the context of the recognition of nonface objects. Reviewing the literature, one would not get this impression. Faces have often been specifically studied for two independent reasons. First, they constitute a convenient, complex stimulus category that can be used to probe questions about object processing and recognition. For example, important questions of viewpoint and illumination invariance have been studied using faces (Braje, Kersten, Tarr, & Troje, 1998; Hill, Schyns, & Akamatsu, 1997), not because these problems are unique to faces, but because face stimuli satisfy the need for objects that are not trivially discriminable and because they are convenient to researchers in terms of availability (e.g., http:// www.face-rec.org/databases/). To be clear, we are not suggesting that this is necessarily a bad thing. As we have already acknowledged, faces are highly relevant objects and present a challenging recognition problem worthy of study in its own right. However, research motivated by such logic should not be construed as an attempt to ‘‘prove’’ that faces are ‘‘special. ’’ In contrast, the second reason that faces have been targeted as objects of study is intrinsically
The Impact of Government R & D Subsidy on Firm Performance : Evidence from Korean SMEs

This paper empirically explores the R&D promotion policy effects on SME performance measured by value-added productivity. We use a unique large panel data set on public R&D subsidy for Korean manufacturing firms. Econometrically, we control for counter-factual outcomes employing the DID (difference in differences) estimation procedure as well as for endogeneity of the R&D subsidy using the 2-stage Tobit/Logit-DPD (dynamic panel data) procedure. We find significant evidence for positive productivity effect of the public R&D subsidy. The subsidy has successfully raised the R&D expenditure and value added productivity of Korean manufacturing SMEs. It is thus fostering entrepreneurial activity and economic growth. [Forthcoming Small Business Economics] 1 Professor, Department of Economics, Kyonggi University, Suwon, Korea. E-mail: bccin@kyonggi.ac. kr 2 (Corresponding Author) Professor, Department of Management of Technology, Graduate School of Management of Technology, Korea University, Seoul, Korea. Email: youngjkim@korea.ac. kr 3 (Corresponding Author) Professor, Center for International Science and Technology Policy & Department of Economics, The George Washington University, Washington, DC, USA. Email: vonortas@gwu.edu Acknowledgement We are grateful for helpful comments from Prof. Kuhlmann and participants in the Asian Research Policy Symposium 2013, “Asian Model of Innovation: Innovation and Creative Economy,” Seoul, Korea.
Male responses to jealousy as a function of sex-role identity in gay male and heterosexual couple relationships

Gay males are described as having to surmount various psycho-social obstacles in order to establish and main tain enduring couple relationships. The relationshipsacrificing style of the typical male response to Jealousy is shown to be one such obstacle. Hypotheses are developed which (1) suggest different patterns of responses to Jealousy by gay and heterosexual males in long—term couple relationships, (2) relate these responses to sex-role identity, and (3) suggest a differential sex-role identification between gay and heterosexual males. Forty gay males and forty heterosexual males, all in long-term couple relationships, were surveyed using a questionnaire. As hypothesized, results confirmed different patterns of responses to Jealousy by the gay and heterosexual samples. However, significant differences in sex-role identity between the two samples were not observed, nor were correlations between response styles and four sexrole identity types demonstrated. Implications for couples counseling and for future research are discussed.
A Computationally Efficient Procedure for the Design of Robust Broadband Beamformers

Broadband beamformers using superdirective arrays are sensitive to errors in the sensor characteristics. Recently, a method that considers the probability distributions of errors to synthesize a robust optimal beamformer has been proposed. Unfortunately, the entire synthesis process may become unacceptably long due to the computational burden of the cost function. Here, we present an alternative procedure for computing the same cost function, drastically reducing such a problem.
ProBDNF Collapses Neurite Outgrowth of Primary Neurons by Activating RhoA

Background Neurons extend their dendrites and axons to build functional neural circuits, which are regulated by both positive and negative signals during development. Brain-derived neurotrophic factor (BDNF) is a positive regulator for neurite outgrowth and neuronal survival but the functions of its precursor (proBDNF) are less characterized. Methodology/Principal Findings Here we show that proBDNF collapses neurite outgrowth in murine dorsal root ganglion (DRG) neurons and cortical neurons by activating RhoA via the p75 neurotrophin receptor (p75NTR). We demonstrated that the receptor proteins for proBDNF, p75NTR and sortilin, were highly expressed in cultured DRG or cortical neurons. ProBDNF caused a dramatic neurite collapse in a dose-dependent manner and this effect was about 500 fold more potent than myelin-associated glycoprotein. Neutralization of endogenous proBDNF by using antibodies enhanced neurite outgrowth in vitro and in vivo, but this effect was lost in p75NTR−/− mice. The neurite outgrowth of cortical neurons from p75NTR deficient (p75NTR−/−) mice was insensitive to proBDNF. There was a time-dependent reduction of length and number of filopodia in response to proBDNF which was accompanied with a polarized RhoA activation in growth cones. Moreover, proBDNF treatment of cortical neurons resulted in a time-dependent activation of RhoA but not Cdc42 and the effect was absent in p75NTR−/− neurons. Rho kinase (ROCK) and the collapsin response mediator protein-2 (CRMP-2) were also involved in the proBDNF action. Conclusions proBDNF has an opposing role in neurite outgrowth to that of mature BDNF. Our observations suggest that proBDNF collapses neurites outgrowth and filopodial growth cones by activating RhoA through the p75NTR signaling pathway.
Constraining Pictures with Pictures

This paper presents a visual language called Miro for specifying and restricting operating system security configurations. A Miro picture specifies exactly what rights users have on files. A Miro constraint, also stated visually, restricts the set of Miro pictures which are considered legal. Such constraints on pictures give an exact specification of security policies and a practical method for alerting users to potential security holes. The language is easy to use and succinct. This research was sponsored by IBM and the Maryland Procurement Office under Contract No. MDA904-88-C-6005. Additional support for J. Wing was provided in part by the National Science Foundation under grant CCR-8620027 and for J. D. Tygar under a Presidential Young Investigator Award, Contract No, CCR-8858087. M. Maimone (under contract N00014-88-K-0641) and A. Moormann are also supported by fellowships from the Office of Naval Research. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency or the US Government.
The Bayesian Elastic Net: Classifying Multi-Task Gene-Expression Data

Highly correlated relevant features are frequently encountered in variable-selection problems, with gene-expression analysis an important example. It is desirable to select all of these highly correlated features simultaneously as a group, for better model interpretation and robustness. Further, irrelevant features should be excluded, resulting in a sparse solution (of importance for avoiding over-fitting with limited data). We address the problem of sparse and grouped variable selection by introducing a new Bayesian Elastic Net model. One advantage of the proposed model is that by imposing priors on individual parameters in the Laplace distribution, we reduce the number of tuning parameters to one, as compared with two such parameters in the original Elastic Net. In addition, we extend the new Bayesian Elastic Net model to the problem of probit regression, in order to deal with classification problems with a sparse but correlated set of covariates (features). Extension to multi-task learning is also considered, with inference performed using variational Bayesian analysis. The model is validated by first performing experiments on simulated data and on previously published gene-expression data; in these experiments we also perform comparisons to the original Elastic Net and to Bayesian Lasso. Finally, we present and analyze a new gene-expression data set for the time-evolving properties of influenza, measured using blood samples from human subjects in a recent challenge study.
Managerial Coordination Challenges in the Alignment of Capabilities and New Subsidiary Charters in MNEs

Subsidiary-level change requires the alignment of subsidiary charters and capabilities. Yet, the mechanisms through which the alignment of charters and capabilities unfolds are not yet well understood. In this paper, we investigate alignment from the perspective of managerial coordination. Drawing on a longitudinal study of a global IT firm, we identify three coordination mechanisms (charter-, experience-, and interaction-based coordination). By tracing the shifts in these coordination mechanisms over time and by specifying the implications of each mechanism for capability level change, we explain how managerial coordination influences alignment via subsidiary level capability change as well as alignment via the potential renegotiation of charters. This also allows us to provide new insights into situations of misalignment by explaining that particular mechanisms of coordination may become a source of decoupling between subsidiary actions and HQ mandates and may also result in capability level inertia. Moreover, while prior research has already acknowledged the role of interaction-based coordination for capability level change we show how and why such a mechanism of coordination emerges.
Pathogenesis and transmission of swine origin A(H3N2)v influenza viruses in ferrets

Recent isolation of a novel swine-origin influenza A H3N2 variant virus [A(H3N2)v] from humans in the United States has raised concern over the pandemic potential of these viruses. Here, we analyzed the virulence, transmissibility, and receptor-binding preference of four A(H3N2)v influenza viruses isolated from humans in 2009, 2010, and 2011. High titers of infectious virus were detected in nasal turbinates and nasal wash samples of A(H3N2)v-inoculated ferrets. All four A(H3N2)v viruses possessed the capacity to spread efficiently between cohoused ferrets, and the 2010 and 2011 A(H3N2)v isolates transmitted efficiently to naïve ferrets by respiratory droplets. A dose-dependent glycan array analysis of A(H3N2)v showed a predominant binding to α2-6–sialylated glycans, similar to human-adapted influenza A viruses. We further tested the viral replication efficiency of A(H3N2)v viruses in a relevant cell line, Calu-3, derived from human bronchial epithelium. The A(H3N2)v viruses replicated in Calu-3 cells to significantly higher titers compared with five common seasonal H3N2 influenza viruses. These findings suggest that A(H3N2)v viruses have the capacity for efficient replication and transmission in mammals and underscore the need for continued public health surveillance.
Visual detail and its effects on character attachment in video games

Sommer, Carl M.S., Purdue University, August 2016. Visual Detail and its Effects on Character Attachment in Video Games. Major Professor: David Whittinghill. The video game industry has been experiencing a trend toward independent game developers making their own games, as well as large companies opening smaller divisions to work on smaller games. This can be looked at from a purely financial perspective, given that smaller games will inevitably consume a smaller budget; however, there is also good reason to believe there can be substantial creative benefits to companies indulging in this trend. This research is concerned with the effect that visual detail can have on a players emotional attachment to characters in video games-otherwise known as character attachment. While intuition may often tell people that more is more, this paper considers the possibility that less may, in fact be more. However, upon developing a game with four different levels of visual detail and testing participants who were only exposed to one version of the game, no significant relationship was found between character attachment and the level of visual detail. Possible explanations for the lack of observed effects are detailed and discussed.
A case study of data analysis for educational management

The recent technology development introduces many aspects of difficulty in education management. There are many new technologies and new businesses emerging in a single year. As a result of business sectors require a rapid changing of curriculum from academic institutions. However, the curriculum revision has to be done in a very short time comparing to a large amount of data to be processed, resulting in the teaching materials are often lack behind the business requirements. Education management has to be sensitive and responsive to the constantly changing of technology environment. In this paper, data analytic tools are applied for discovering a new dependence between courses, in order to improve the current sequence of prerequisites. The dependence detection is made of a feature importance technique based on an extra-trees classifier. We also compare various types of classifiers for predicting a grade of a next enrollment using the results of prior studies. The grade prediction is designed to suggest the best study path to match individual talent.
Identifying the Generation Gap in Higher Education: Where Do the Differences Really Lie?

Millennials, Electronic Natives, the Net Generation. Many names have been used to describe the new generation of college students, whom population experts have identified as being distinctly different from the previous generations in terms of their technological abilities, teamwork skills, and openness to participatory pedagogies (e.g., Howe and Strauss 2003; Lancaster and Stillman 2002). However, if there is general agreement that younger students do not have have the same attributes as their older counterparts, scholars and commentators still offer divergent assessments of this contrast. For example, Howe and Strauss's (2003) optimistic description of the new generation, based on theories and predictions rather than conclusive evidence, has drawn criticism as educators in colleges and universities have perceived this new wave of students quite differently. Meanwhile, Taylor (2006) offers a much less encouraging characterization of "the Generation NeXt student" (that is, a college student younger than 26 years old) as the "disengaged, entitled, student customer" (48). Such contrasting accounts suggest that even if younger students have greater levels of comfort or proficiency with new technologies, it is still debatable whether such traits necessarily entail more open, progressive, or positive perspectives of the educational process.
Hidden Markovian Modeling and Analysis of Multiple-Event-Sequence-Based Random Processes. Application to Robust Detection of Brain Functional Activation

This paper presents a novel statistical approach for the modeling and analysis of structured random processes observed through multiple event sequences: the hidden Markov multiple event sequence model (HMMESM). This model accounts for several features of these processes: (i) the hidden-observable aspect of the event sequences to be analyzed, (ii) the multiplicity of the observed event sequences, (iii) the non stationary, time-localized character of their events, (iv) the redundancy, complementarity, and strong asynchrony that exist between events across sequences. A first application of this model in functional MRI (fMRI) brain mapping is presented. The developed method shows high robustness to noise and variability of the active fMRI signals
Single Top Quarks at the Tevatron

After many years searching for electroweak production of top quarks, the Tevatron collider experiments have now moved from obtaining first evidence for single top quark production to an impressive array of measurements that test the standard model in several directions. This paper describes measurements of the single top quark cross sections, limits set on the CKM matrix element |Vtb|, searches for production of single top quarks produced via flavor-changing neutral currents and from heavy W-prime and H+ boson resonances, and studies of anomalous Wtb couplings. It concludes with projections for future expected significance as the analyzed datasets grow.
Improved Ant Colony Optimization for Solving Reliability Redundancy Allocation Problems

— This paper presents an improved ant colony optimization (IACO) for solving the reliability redundancy allocation problem (RAP) in order to maximize system reliability. To improve the performance of ACO algorithm, two additional techniques, i.e. neighborhood search, and re-initialization process are presented. To show its efficiency and effectiveness, the proposed IACO is applied to solve three RAPs. Additionally, the results of the proposed IACO are compared with those of the conventional heuristic approaches i.e. genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). The experimental results show that the proposed IACO approach is comparatively capable of obtaining higher quality solution and faster computational time.
Fiber Optic Plasmonic Sensors: Past, Present and Future

We review various fiber optic sensors utilizing both the propagating and localized surface plasmon resonance techniques. The utilization of optical fibers in plasmon based sensing has provided several advantages in sensing of various physical, chemical and biochemical parameters. The article starts with a brief introduction of the propagating surface plasmon resonance (SPR) and localized surface plasmon resonance (LSPR), presents the review of some of the past studies on SPR and LSPR based state-of-the-art fiber optic sensors and finally ends with the future scope of the plasmonics based fiber optic sensors. In addition, we discuss some latest results on the plasmon enhanced whispering gallery mode sensors, which require tapered optical fibers for excitation. The present review may provide the researchers a rigorous and organized literature for the understanding of the basics, utility and trends of fiber optic plasmonic sensor in a chronological order.
Comparison of Material Consumption, Experimental Protocols and Computation Time in DNA Computing

One of the major constraints in DNA computation is the exponential increase in material consumption and computation time for larger computation size in DNA computing particularly in critical stages such as initial pool generation and extraction during gel electrophoresis. In DNA computation, both the hybridization-ligation method and parallel overlap assembly method can be utilized to generate the initial pool of all possible solutions. In this paper, we discuss and compare the implementation of N × N Boolean matrix multiplication via in vitro implementation between Hybridization-Ligation Method and Parallel Overlap Assembly Method to show that selection of tools and protocols affect the cost effectiveness of a computation in terms of the material consumption, protocol steps and execution time to compute. In general, the the parallel overlap assembly method performs better than hybridization-ligation method in terms of the three parameters mentioned. The calculations are based on approximation of unique sequence strands required for the computation and not actual calculations on the nmol concentration.
Self-Distributing Computation

In this thesis, I propose a new model for distributing computational work in a parallel or distributed system. This model relies on exposing the topology and performance characteristics of the underlying architecture to the application. Responsibility for task distribution is divided between a run-time system, which determines when tasks should be distributed or consolidated, and the application, which specifies to the runtime system its first-choice distribution based on a representation of the current state of the underlying architecture. Discussing my experience in implementing this model as a Java-based simulator, I argue for the advantages of this approach as they relate to performance on changing architectures and ease of programming. Thesis Supervisor: Thomas F. Knight, Jr. Title: Senior Research Scientist