Miracle-dz/UniFAR-FTUs huggingface dataset:
A Market Based Solution to Price Externalities: A Generalized Framework

Pecuniary externalities have regained the interest of researchers as they seek policy interventions and regulations to remedy externality-induced distortions, e.g., balance sheet effects, amplifiers and fire sales. In this paper we go back to first principles and show how to design financial contracts and markets in such a way that ex ante competition can achieve a constrained-efficient allocation. The key as in general equilibrium theory is to extend the commodity space in such a way that bundling, exclusivity and additional markets internalize these pecuniary externalities. We devise in this paper a general way of proceeding that covers as a general case the large variety of example-economies which differ from one another in the particular source of the constraint generating the externality. A key take away from our approach is that we do not need to identify and quantify some policy intervention. With the appropriate ex ante design we can let markets solve the problem.
Validation of qualitative microbiological test methods

This paper considers a statistical model for the detection mechanism of qualitative microbiological test methods with a parameter for the detection proportion (the probability to detect a single organism) and a parameter for the false positive rate. It is demonstrated that the detection proportion and the bacterial density cannot be estimated separately, not even in a multiple dilution experiment. Only the product can be estimated, changing the interpretation of the most probable number estimator. The asymptotic power of the likelihood ratio statistic for comparing an alternative method with the compendial method, is optimal for a single dilution experiment. The bacterial density should either be close to two CFUs per test unit or equal to zero, depending on differences in the model parameters between the two test methods. The proposed strategy for method validation is to use these two dilutions and test for differences in the two model parameters, addressing the validation parameters specificity and accuracy. Robustness of these two parameters might still be required, but all other validation parameters can be omitted. A confidence interval‐based approach for the ratio of the detection proportions for the two methods is recommended, since it is most informative and close to the power of the likelihood ratio test. Copyright © 2014 John Wiley & Sons, Ltd.
Low-mass Binaries in the Hyades - A scarcity of brown dwarfs

We have obtained HST Planetary Camera observations of a total of fifty-three low-mass (M < 0.3 M_solar) members of the Hyades cluster. Nine of these stars are resolved as binaries, with separations between 0.1 and 3.1 arcseconds, while a further three are probably equal-mass systems at smaller separations. Allowing for observational selection effects, this corresponds to an observed binary fraction of 11.3 plus or minus 4.6% for systems with separations in the range 14 to 825 a.u. , consistent with observations of solar neighbourhood M-dwarfs. The mass-ratio distribution is only consistent marginally with the secondary stars being drawn from a Psi(M) proportioal to M^{-1} mass function, with three equal-mass systems amongst the six binaries with observed separations in the regime where our observations extend below the hydrogen-burning limit. Considering the entire sample, the absence of any brown dwarf companions amongst our sample makes it unlikely that the mass function of stellar/brown dwarf companions rises as steeply as M^{-1}. If the Hyades has an age of 600 Myrs, our results are consistent only at the 2 sigma level with a flat (M^0) mass function.
Temporal pattern of C1q deposition after transient focal cerebral ischemia

Recent studies have focused on elucidating the contribution of individual complement proteins to post‐ischemic cellular injury. As the timing of complement activation and deposition after cerebral ischemia is not well understood, our study investigates the temporal pattern of C1q accumulation after experimental murine stroke. Brains were harvested from mice subjected to transient focal cerebral ischemia at 3, 6, 12, and 24 hr post reperfusion. Western blotting and light microscopy were employed to determine the temporal course of C1q protein accumulation and correlate this sequence with infarct evolution observed with TTC staining. Confocal microscopy was utilized to further characterize the cellular localization and characteristics of C1q deposition. Western Blot analysis showed that C1q protein begins to accumulate in the ischemic hemisphere between 3 and 6 hr post‐ischemia. Light microscopy confirmed these findings, showing concurrent C1q protein staining of neurons. Confocal microscopy demonstrated co‐localization of C1q protein with neuronal cell bodies as well as necrotic cellular debris. These experiments demonstrate the accumulation of C1q protein on neurons during the period of greatest infarct evolution. This data provides information regarding the optimal time window during which a potentially neuroprotective anti‐C1q strategy is most likely to achieve therapeutic success. © 2006 Wiley‐Liss, Inc.
Linear model predictive control for lane keeping and obstacle avoidance on low curvature roads

This paper presents a control architecture based on a linear MPC formulation that addresses the lane keeping and obstacle avoidance problems for a passenger car driving on low curvature roads. The proposed control design decouples the longitudinal and lateral dynamics in two successive stages. First, plausible braking or throttle profiles are defined over the prediction horizon. Then, based on these profiles, linear time-varying models of the vehicle lateral dynamics are derived and used to formulate the associated linear MPC problems. The solutions of the optimization problems are used to determine for every time step, the optimal braking or throttle command and the corresponding steering angle command. Simulations show the ability of the controller to overcome multiple obstacles and keep the lane. Experimental results on an autonomous passenger vehicle driving on slippery roads show the effectiveness of the approach.
A Large-scale Dataset and Benchmark for Similar Trademark Retrieval

Trademark retrieval (TR) has become an important yet challenging problem due to an ever increasing trend in trademark applications and infringement incidents. There have been many promising attempts for the TR problem, which, however, fell impracticable since they were evaluated with limited and mostly trivial datasets. In this paper, we provide a large-scale dataset with benchmark queries with which different TR approaches can be evaluated systematically. Moreover, we provide a baseline on this benchmark using the widely-used methods applied to TR in the literature. Furthermore, we identify and correct two important issues in TR approaches that were not addressed before: reversal of contrast, and presence of irrelevant text in trademarks severely affect the TR methods. Lastly, we applied deep learning, namely, several popular Convolutional Neural Network models, to the TR problem. To the best of the authors, this is the first attempt to do so.
Paschen beta emission as a tracer of outflow activity from T-Tauri stars, as compared to optical forbidden emission

The Paschen beta (1.2822 μ m) emission line found in the near-infrared spectra of T-Tauri stars (TTSs) is believed to trace the accretion of material onto the central star. We present spectroscopic data which suggests that this may not always be the case. The technique of spectro-astrometry is used by us to measure positional displacements in the Pa β emission from four T-Tauri stars, namely DG Tau, V536 Aql, LkH α 321 and RW Aur. We also observed the optical forbidden emission from these sources, for example the [SII]$\lambda\lambda$6716, 6731, [OI]$\lambda\lambda$6300, 6363 and [NII]$\lambda\lambda$6548, 6583 lines. Forbidden emission lines are formed in the outflows that accompany the evolution of protostars and so are ideal to use as a comparison to confirm that the measured offsets in the Pa β emission are indeed due to outflowing material. Models based on the magnetospheric accretion theory have been the most successful to date in explaining the origin of atomic hydrogen emission lines. Yet we see that the line profiles of the sources showing displacement in their Pa β emission all have features that the magnetospheric accretion model has so far failed to explain, such as broad full width half maxima, large wings and an absence of red shifted absorption features. The failure of the models to explain the presence of large extended wings in the line profiles is particularly interesting in the context of this study as in all cases it is in the extended wings that we measure offsets in position with respect to the source.
A novel particle swarm and genetic algorithm hybrid method for improved heuristic optimization of diesel engine performance

This study explores a novel application of the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) heuristic methods in a hybrid construction on a 4 cylinder medium-duty diesel engine at part-load conditions. The application of the hybrid PSO-GA approach is compared with a basic PSO in the optimization of the control parameters of a diesel engine utilizing high EGR capability, modestly high fuel pressure capability, and a two-injection fuel strategy. The results indicate that the application of the GA to the basic PSO method improved the search breadth and convergence rate when compared to the basic PSO method alone. The novel approach of applying the GA to the fuel schedule is found to be worthy of further investigation. Applying the GA to specific parameters as way to improve optimizations on was effective in reducing the iterations and time taken to achieve satisfactory objective values. The hybrid method showed up to a 49% improvement in objective value over the basic PSO with less operational time in testing.
The Role of Economic Development and Firm Internationalization in Internet Business Practices

Firms in emerging economies are rapidly becoming formidable competitors to long-established industry leaders from developed economies. In some cases, emerging-economy firms are acquiring developed-economy firms, such as the recent acquisitions of Jaguar by Tata Motors and Gateway by Acer. Aside from anecdotal reports of high-level corporate strategies adopted by certain emerging-economy firms, there is little scholarly evidence concerning the operational details of how emerging-economy firms are becoming competitive with developed-economy firms. A common explanation is labor cost or currency advantages in emerging economies. As emerging-economy firms also compete effectively in developed economies using developed-economy resources, this cannot be the entire explanation. We propose another explanation, based on dissimilar adaptation of the Internet to enable and reinforce business practices related to customer relationships and supply chain integration.This paper draws on original survey data from over 450 firms across 10 countries as well as case examples to illuminate three key ways that Internet business practices differ between developed- and emerging-economy firms. First, compared with developed-economy firms, emerging-economy firms place a relatively higher priority on using the Internet to achieve strong customer relationships via service and support. Second, emerging-economy firms place a relatively higher priority on using the Internet to integrate processes with suppliers than do developed-economy firms. Finally, emerging-economy firms are relatively more driven to adopt Internet business practices to expand existing markets and enter new markets, and accordingly report a relatively greater impact to international sales growth compared with developed-economy firms. Our findings suggest that managers in developed-economy firms would be wise to re-assess and re-evaluate their use of Internet business practices - in particular, in the areas of customer relationships and supply chain integration - to retain competitiveness in the dynamic global economy.
Fast iterative five point relative pose estimation

Robust estimation of the relative pose between two cameras is a fundamental part of Structure and Motion methods. For calibrated cameras, the five point method together with a robust estimator such as RANSAC gives the best result in most cases. The current state-of-the-art method for solving the relative pose problem from five points is due to Nistér [9], because it is faster than other methods and in the RANSAC scheme one can improve precision by increasing the number of iterations. In this paper, we propose a new iterative method, which is based on Powell's Dog Leg algorithm. The new method has the same precision and is approximately twice as fast as Nister's algorithm. The proposed method is easily extended to more than five points while retaining a efficient error metrics. This makes it also very suitable as an refinement step. The proposed algorithm is systematically evaluated on three types of datasets with known ground truth.
Disrespect and abuse during facility based childbirth: The experience of mothers in Kano, Northern Nigeria

Context: An important but little understood concept that retards the goal to reduce maternal mortality and increase universal access to reproductive health is disrespect and abuse (D&A) during childbirth. Aim: This study aims to determine the prevalence, pattern, perpetrators, and determinants of D&A during childbirth among recently parturient women in Kano, north western Nigeria. Settings and Design: Using a cross-sectional design, 332 women accessing child immunization and postnatal services at Murtala Muhammad Specialist Hospital, Kano, were selected. Subjects and Methods: Respondents were selected using systematic sampling technique and data collected using an adapted, interviewer administered tool. Statistical Analysis: Data was analysed using IBM SPSS version 21.0 and level of significance set at 0.05. Results: Respondents (n = 306) had a mean age of 27.7 ± 6.3 years and more than half (55.9%; n = 171) had experienced at least one form of D&A during childbirth. Commonest forms of abuse were abandonment and nonconfidential care (84.5%, n = 142; 67.9%, n = 114, respectively). Main perpetrators were nurses/midwives (83.0%, n = 142). The experience during the last childbirth was significantly higher among respondents of non-Hausa/Fulani ethnic group (χ2 = 6.10; P = 0.014), of the Christian faith (χ2 = 8.62; P = 0.003), and with formal education (χ2 = 19.94; P = 0.0001). After controlling for confounders, formal education remained a predictor for experiencing abuse at childbirth (AOR = 2.43; 95% confidence interval = 1.11--5.32). Conclusions: D&A during childbirth is prevalent in our setting. Educating healthcare providers and women about their responsibilities and rights will enhance provision and utilization of quality maternal health services.
Molecular analysis of cerebrospinal fluid: potential for the study of HIV-1 infection of the central nervous system.

The molecular analysis of cerebrospinal fluid (CSF) provides an inestimable tool for the study of HIV infection of the central nervous system (CNS). Current nucleic acid amplification techniques enable the measurement of CSF HIV-1 RNA levels which can be predictive of HIV-associated neurological damage. CSF HIV-1 RNA levels do not necessarily correlate with the corresponding plasma levels, thus supporting the possibility of an intrathecal virus production, i.e., from brain macrophages. However, in early stages of HIV infection, as well as during some opportunistic CNS diseases, CNS or CSF infiltrating lymphocytes might be the main source of CSF virus. A drastic decrease in CSF viral load is usually observed along with a decrease in plasma levels in patients receiving highly active antiretroviral therapy (HAART), with durable suppression of CSF viral load over months. However, during the first weeks of therapy, the dynamics of response may differ in the CSF as compared to plasma, again suggesting that virus replication may be compartmentalised in the CSF. A number of mechanisms are likely to be involved in the response to therapy in CSF, including among the others the trafficking of cell populations supporting viral replication between blood, CNS and CSF, and the role of the anatomical brain barriers in limiting the access of antiretroviral drugs into the CSF. A potential risk associated with compartmentalisation of HIV infection is of an incomplete suppression of virus replication in the CSF, thus creating the ground for local development of anti-HIV drug resistance. In order to assess this occurrence, long-term studies of viral load and genotypic analyses on paired CSF and plasma will be necessary and these will also help elucidate the complex interrelationship between viral replication in these compartments.
Towards an Enhanced Learning Management System for Blended Learning in Higher Education Incorporating Distinct Learners' Profiles

In a blended education context, Learning Management Systems (LMS) can be thought to integrate collaborative and interactive learning activities; this, however, requires a strong institutional and sociocultural commitment from all stakeholders. Consequently, an empirical study that aims at identifying learners' profiles and uses them as an optimization feedback-like process to the LMS towards effective blended (b-)learning was adopted here. The latter involved 36 undergraduate students with variant b-learning activity at a public Higher Education Institution. In a synergetic combination of qualitative and quantitative evidences, semi-structured face-to-face interviews were conducted and validated, and a systematic multivariate content analysis was articulated. Results revealed three distinct students' profiles oriented to interactive learning environment, Information and Communication Technologies (ICTs) teachers' beliefs, and students' training. Under this multifaceted scenario, a rethinking of the LMS within the b-learning environment could be approached through the enhancement of interactivity, fostering users' ICT acquaintance, and incorporating further training.
Crowdsourced query augmentation through semantic discovery of domain-specific jargon

Most work in semantic search has thus far focused upon either manually building language-specific taxonomies/ontologies or upon automatic techniques such as clustering or dimensionality reduction to discover latent semantic links within the content that is being searched. The former is very labor intensive and is hard to maintain, while the latter is prone to noise and may be hard for a human to understand or to interact with directly. We believe that the links between similar user's queries represent a largely untapped source for discovering latent semantic relationships between search terms. The proposed system is capable of mining user search logs to discover semantic relationships between key phrases in a manner that is language agnostic, human understandable, and virtually noise-free.
Direct numerical simulations of helical dynamo action: MHD and beyond

Magnetohydrodynamic dynamo action is often invoked to explain the existence of magnetic fields in several astronomical objects. In this work, we present direct numerical simulations of MHD helical dynamos, to study the exponential growth and saturation of magnetic fields. Simulations are made within the framework of incompressible flows and using periodic boundary conditions. The statistical properties of the flow are studied, and it is found that its helicity displays strong spatial fluctuations. Regions with large kinetic helicity are also strongly concentrated in space, forming elongated structures. In dynamo simulations using these flows, we found that the growth rate and the saturation level of magnetic energy and magnetic helicity reach an asymptotic value as the Reynolds number is increased. Finally, extensions of the MHD theory to include kinetic effects relevant in astrophysical environments are discussed.
CEO Compensation and Performance in Family Firms

This study examines CEO compensation in family firms, with a particular focus on the effects exerted by governance characteristics such as ownership concentration, wedge between voting and cash-flow rights rights, and the presence of shareholder agreements. On a sample of Italian listed companies over the period 1998-2002, we provide empirical evidence that family firms pay CEOs systematically more then other firms, and that the ownership structure exerts a significant effect on CEO compensation. In family firms, CEO pay is indeed positively affected by low ownership concentration, as well as a low wedge between voting and cash flow rights. Moreover, the presence of shareholders agreements has a moderating role on the level of CEO compensation. These effects are more pronounced in family than in non-family firms.The analysis of the relationship between excess compensation and future firm performance reveals that the higher compensation granted to the CEO by family firms is related to worse stock and accounting returns and could therefore be interpreted as a form of rent extraction. This result holds only for lower degrees of ownership concentration, higher wedge and in the absence of shareholders’ agreements, and supports the hypothesis that the prevalent agency conflict within Italian-listed family firms is between family owners and minority shareholders, instead of between shareholders and managers. The higher compensation granted to the CEO could be interpreted as the premium for the loyalty of the CEO to the family and for allowing the family to extract private benefits of control.
WORKING PAPER SERIES OVERBORROWING , FINANCIAL CRISES AND ' MACROPRUDENTIAL ' TAXES

We study overborrowing and financial crises in an equilibrium model of business cycles and asset prices with collateral constraints. Private agents in a decentralized competitive equilibrium do not internalize the effects of their individual borrowing plans on the market price of assets at which collateral is valued and on the wage costs relevant for working capital financing. Compared with a constrained social planner who internalizes these effects, they undervalue the benefits of an increase in net worth when the constraint binds and hence they borrow "too much" ex ante. Quantitatively, average debt and leverage ratios are only slightly larger in the competitive equilibrium, but the incidence and magnitude of financial crises is much larger. Excess asset returns, Sharpe ratios and the market price of risk are also much larger. A state-contingent tax on debt of about 1 percent on average supports the planner's allocations as a competitive equilibrium and increases social welfare. Javier Bianchi University of Maryland, College Park bianchi@econ.umd. edu Enrique G. Mendoza Department of Economics University of Maryland College Park, MD 20742 and NBER mendozae@econ.umd. edu
Combining Lexical Resources: Mapping Between PropBank and VerbNet

A wide variety of lexical resources have been created to allow automatic semantic processing of novel text. However, each resource has its own practical and theoretical idiosyncracies, making it difficult to combine the information from different resources. We discuss the form that these differences can take, and describe how we overcame some of them in creating a mapping between two important resources: PropBank and VerbNet. Furthermore, we present experimental results that show that this mapping improves performance for PropBank-style semantic role labeling. Since PropBank was designed on a verb-by-verb basis, the argument labels Arg2 Arg5 get used for a wide variety of argument roles. As a result, it can be difficult for automatic classifiers to learn to distinguish these arguments. But by using the mapping that we have created between PropBank and VerbNet, we can train a classifier based on VerbNet argument labels, which are more consistent and therefore easier to learn.