Miracle-dz/UniFAR-FTUs huggingface dataset:
Memo Has a Novel Role in S1P Signaling and Crucial for Vascular Development

Memo is a conserved protein that was identified as an essential mediator of tumor cell motility induced by receptor tyrosine kinase activation. Here we show that Memo null mouse embryonic fibroblasts (MEFs) are impaired in PDGF-induced migration and this is due to a defect in sphingosine-1-phosphate (S1P) signaling. S1P is a bioactive phospholipid produced in response to multiple stimuli, which regulates many cellular processes. S1P is secreted to the extracellular milieu where it exerts its function by binding a family of G-protein coupled receptors (S1PRs), causing their activation in an autocrine or paracrine manner. The process, termed cell-autonomous S1PR signaling, plays a role in survival and migration. Indeed, PDGF uses cell-autonomous S1PR signaling to promote cell migration; we show here that this S1P pathway requires Memo. Using vascular endothelial cells (HUVECs) with Memo knock-down we show that their survival in conditions of serum-starvation is impaired. Furthermore, Memo loss in HUVECs causes a reduction of junctional VE-cadherin and an increase in sprout formation. Each of these phenotypes is rescued by S1P or S1P agonist addition, showing that Memo also plays an important role in cell-autonomous S1PR signaling in endothelial cells. We also produced conventional and endothelial cell-specific conditional Memo knock-out mouse strains and show that Memo is essential for embryonic development. Starting at E13.5 embryos of both strains display bleeding and other vascular problems, some of the phenotypes that have been described in mouse strains lacking S1PRs. The essential role of Memo in embryonic vascular development may be due in part to alterations in S1P signaling. Taken together our results show that Memo has a novel role in the S1P pathway and that Memo is needed to promote cell-autonomous S1PR activation.
Design of Randomized Experiments in Networks

Over the last decade, the emergence of pervasive online and digitally enabled environments has created a rich source of detailed data on human behavior. Yet, the promise of big data has recently come under fire for its inability to separate correlation from causation-to derive actionable insights and yield effective policies. Fortunately, the same online platforms on which we interact on a day-to-day basis permit experimentation at large scales, ushering in a new movement toward big experiments. Randomized controlled trials are the heart of the scientific method and when designed correctly provide clean causal inferences that are robust and reproducible. However, the realization that our world is highly connected and that behavioral and economic outcomes at the individual and population level depend upon this connectivity challenges the very principles of experimental design. The proper design and analysis of experiments in networks is, therefore, critically important. In this work, we categorize and review the emerging strategies to design and analyze experiments in networks and discuss their strengths and weaknesses.
Banks as Coordinators of Economic Growth and Stability: Microfoundation for Macroeconomy with Externality

Competition among banks promotes growth and stability for an economy with production externality. Following Arrow and Debreu (1954) [6], I formulate a standard growth model with externality—a two-period version of Romer (1986) [39]—as a game among consumers, firms, and intermediaries. The Walrasian equilibrium, with an auctioneer, does not achieve the social optimum. Without an auctioneer or intermediaries, I show that no Nash equilibrium exists. With several banks strategically intermediating capital, a Nash equilibrium emerges with a realistic institution, i.e., an interbank market with a negotiation process in the loan market. The equilibrium outcome is uniquely determined and socially optimal.
Improved resettable integrator control for a bridgeless interleaved AC/DC converter

Plug-in hybrid electric vehicles (PHEVs) consist of a front-end boost rectifier, which incorporates a power factor correction (PFC) circuit for battery charging. Bridgeless interleaved (BLIL) PFC boost converter topology is proved as a standard PFC converter as it has high efficiency, reduced input current ripple, and reduced electromagnetic interference (EMI). This paper proposes a digital nonlinear control technique that employs a resettable integrator to shape the input current of the converter in phase with the input voltage to achieve high input power factor. This control approach rejects power source and load perturbations better than linear feedback control methods. This is accomplished by summing up the sensed input current of a BLIL converter with a fictitious current synthesized with the input voltage. In this work, a BLIL converter is analyzed for its input power factor improvement, voltage stress across the devices, and dynamic response under variable supply and load conditions using simulation. The hardware is tested for a 300 W BLIL boost converter to validate the simulated results. The performance of the proposed controller is compared with that of conventional average current mode control. The experiment and simulation results prove that the resettable integrator controller shows a better performance than the conventional controller.
The effect of breakfast on appetite regulation, energy balance and exercise performance

The belief that breakfast is the most important meal of day has been derived from cross-sectional studies that have associated breakfast consumption with a lower BMI. This suggests that breakfast omission either leads to an increase in energy intake or a reduction in energy expenditure over the remainder of the day, resulting in a state of positive energy balance. However, observational studies do not imply causality. A number of intervention studies have been conducted, enabling more precise determination of breakfast manipulation on indices of energy balance. This review will examine the results from these studies in adults, attempting to identify causal links between breakfast and energy balance, as well as determining whether consumption of breakfast influences exercise performance. Despite the associations in the literature, intervention studies have generally found a reduction in total daily energy intake when breakfast is omitted from the daily meal pattern. Moreover, whilst consumption of breakfast supresses appetite during the morning, this effect appears to be transient as the first meal consumed after breakfast seems to offset appetite to a similar extent, independent of breakfast. Whether breakfast affects energy expenditure is less clear. Whilst breakfast does not seem to affect basal metabolism, breakfast omission may reduce free-living physical activity and endurance exercise performance throughout the day. In conclusion, the available research suggests breakfast omission may influence energy expenditure more strongly than energy intake. Longer term intervention studies are required to confirm this relationship, and determine the impact of these variables on weight management.
New Flexible Regression Models Generated by Gamma Random Variables with Censored Data

We propose and study a new log-gamma Weibull regression model. We obtain explicit expressions for the raw and incomplete moments, quantile and generating functions and mean deviations of the log-gamma Weibull distribution. We demonstrate that the new regression model can be applied to censored data since it represents a parametric family of models which includes as sub-models several widely-known regression models and therefore can be used more effectively in the analysis of survival data. We obtain the maximum likelihood estimates of the model parameters by considering censored data and evaluate local influence on the estimates of the parameters by taking different perturbation schemes. Some global-influence measurements are also investigated. Further, for different parameter settings, sample sizes and censoring percentages, various simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We demonstrate that our extended regression model is very useful to the analysis of real data and may give more realistic fits than other special regression models.
EE 291 E Lecture Notes 11 : Optimization-Based Control Part 2

In last lecture, we saw how we can represent trajectory optimization problems as finite-dimensional optimization problems. We briefly touched on some methods for computing trajectories for a couple specific problem instances. Particularly, we saw how control policies can be computed for the linear dynamics, quadratic cost problem (LQR) by formulating it as a Quadratic Program. Similarly, we saw how we can solve for locally optimal trajectories for systems with nonlinear dynamics by iteratively solving Quadratic Programs that represent Linear-Quadratic approximations of our problem. We showed that this method was nearly equivalent to Sequential Quadratic Programming. In this lecture, we will expand upon these ideas to show how we can use Sequential Quadratic Programming to handle problems with more general constraint and cost terms, including unilateral constraints. We will demonstrate how, by using solvers based on SQP and similar ideas, we can compute trajectories for complicated systems. Specifically, we will dive into a particular application of generating trajectories for mechanical systems with hybrid dynamics. This example will bring together many of the components we have seen so far in the course in a very practical way.
Biological Crystallography Crystallographic Data Processing for Free-electron Laser Sources

A processing pipeline for diffraction data acquired using the 'serial crystallography' methodology with a free-electron laser source is described with reference to the crystallographic analysis suite CrystFEL and the pre-processing program Cheetah. A detailed analysis of the nature and impact of indexing ambiguities is presented. Simulations of the Monte Carlo integration scheme, which accounts for the partially recorded nature of the diffraction intensities, are presented and show that the integration of partial reflections could be made to converge more quickly if the bandwidth of the X-rays were to be increased by a small amount or if a slight convergence angle were introduced into the incident beam.
First, Do No Harm: Effective, Ineffective and Counterproductive Teaching Methods

and concrete representations Positive. While students may appreciate concrete examples, without the underlying theory students have trouble generalizing an idea. Both abstract and concrete examples help students understand and generalize. This has been tested mainly in mathematics instruction. (De Bock, Deprez, Van Dooren, Roelens, & Verschaffel, 2011; Kaminski, Sloutsky, & Heckler, 2008). This recommendation is included in the Practice Guide. Level: 2 Incorporating frequent retrieval tasks such as quizzes Positive. Retrieving information from memory with quizzes or flashcards, rather than just studying or rereading material, improves retention of material. (Butler, 2010; Dunlosky et al., 2013; Karpicke & Blunt, 2011; Pashler et al., 2008; Roediger & Karpicke, 2006; Vaughn & Rawson, 2011; Weinstein et al., 2010). This recommendation is included in the Practice Guide. Level: 2 Unknown
A prospective study of recreational physical activity and breast cancer risk.

BACKGROUND Increased physical activity has been hypothesized to prevent breast cancer, largely by reducing cumulative lifetime exposure to circulating ovarian hormones. However, epidemiologic findings are inconsistent, and there is no consensus on the best way to quantify physical activity. We thus examined this issue in a large cohort of women, using several different measures of adult physical activity. METHODS We analyzed data from the Nurses' Health Study, a prospective study of women aged 30 to 55 years in 1976. In 1980 and on subsequent surveys, women were asked about the average number of hours per week spent in various moderate and vigorous recreational physical activity during the past year. We computed a "baseline-only" (1980) measure of hours per week of physical activity, as well as a cumulative average measure that used updated reports on physical activity. During 16 years of follow-up, we identified 3137 cases of invasive breast cancer (1036 premenopausal and 2101 postmenopausal women). Data were analyzed by use of multivariate pooled logistic regression to produce relative risks of breast cancer, and the associated confidence intervals. RESULTS Women who were more physically active in adulthood had a lower risk of breast cancer than those who were less physically active. Comparing those who reported engaging in moderate or vigorous physical activity for 7 or more hours per week with those who engaged in such physical activity for less than 1 hour per week, the relative risk was 0.82 (95% confidence interval, 0.70-0.97), using the cumulative average updating. The dose-response trend was statistically significant (P = .004). Using the baseline-only measure of physical activity produced slightly weaker relative risks. CONCLUSION These results contribute to the body of evidence suggesting that higher levels of adult physical activity afford modest protection against breast cancer.
From Focused Elements to Snippets A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY Supraja Nagalla IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE

Information Retrieval is a field of computing which traditionally deals with searching a large collection of documents and retrieving documents based on their similarity to the query. INEX [10] provides a platform (e.g., document collection, queries and uniform evaluation metrics) for the development and evaluation of retrieval algorithms for XML documents. The focus of INEX is to reduce the granularity of search results from the entire document to the element level. In 2011, INEX introduced a new track, called the Snippet Retrieval Track. In 2012, INEX improved this track to make the task of assessment easier. Its goal is to determine how best to generate informative snippets for search results. Such snippets should provide sufficient information to allow the user to determine the relevance of each document without viewing the document itself. The Snippet Retrieval track uses the 50.7GB INEX Wikipedia collection of about 2.7 million articles. We use the Smart [15] experimental retrieval system, based on the Vector Space Model [16], for indexing and retrieval. This thesis describes the approaches taken by UMD to generate runs to participate in the INEX 2011 and 2012 Snippet Retrieval track. We use our method of dynamic element retrieval [7] to generate the element vectors of the XML document tree at run time, thus producing a rank-ordered list of elements from each highly correlated document. These elements are further processed using our methods to generate snippets. The methods used, experimental results, and conclusions are described herein.
Long elastic open neck acoustic resonator in flow

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Long elastic open neck acoustic resonator in flow Frank Simon
Un hombre de San Juan: aproximación facial en antropología

Dentro de la antropologia y la identificacion forense, la aproximacion facial (tambien conocida como "reconstruccion facial") se presenta frecuentemente como un hecho consumado, con evidencia minima de las investigaciones y los metodos usados para alcanzar los resultados. Este trabajo presenta un panorama detallado de la investigacion y los metodos usados para realizar una aproximacion facial grafica en 2D de un hombre prehistorico del valle de Jachal, provincia de San Juan, Argentina. Se entiende que corresponde a un miembro del extinto grupo Huarpe. El craneo del individuo muestra numerosos rasgos morfologicos que son consistentes con lo que se conoce acerca de este grupo de agricultores tempranos americanos. Debido a que muchos de los metodos utilizados en esta reconstruccion facial aun no han sido verificados y aquellos que han sido debidamente probados se basan en promedios estadisticos de la variacion humana, los resultados presentados deben ser vistos como indicativos de la posible apariencia facial del individuo dado el nivel actual de conocimiento, mas que como un resultado definitivo.
Developing a Framework for Evaluating Ethical Outcomes of Good Participatory Practices in TB Clinical Drug Trials

Good Participatory Practice Guidelines for TB Drug Trials (GPP-TB) were issued in 2012, based on similar guidelines for HIV prevention and reflecting growing acceptance of the importance of community engagement and participatory strategies in clinical research. Though the need for such strategies is clear, evaluation of the benefits and burdens are needed. Working with a diverse group of global TB stakeholders including advocates, scientists, and ethicists, we used a Theory of Change approach to develop an evaluation framework for GPP-TB that includes a clearly defined ethical goal, a set of powerful strategies derived from GPP-TB practices for achieving the goal, and outcomes connecting strategies to goal. The framework is a first step in systematically evaluating participatory research in clinical trials.
Estimation for L\'{e}vy processes from high frequency data within a long time interval

In this paper, we study nonparametric estimation of the L\'{e}vy density for L\'{e}vy processes, with and without Brownian component. For this, we consider $n$ discrete time observations with step $\Delta$. The asymptotic framework is: $n$ tends to infinity, $\Delta=\Delta_n$ tends to zero while $n\Delta_n$ tends to infinity. We use a Fourier approach to construct an adaptive nonparametric estimator of the L\'{e}vy density and to provide a bound for the global ${\mathbb{L}}^2$-risk. Estimators of the drift and of the variance of the Gaussian component are also studied. We discuss rates of convergence and give examples and simulation results for processes fitting in our framework.
Which Variables Explain Decisions on IMF Credit? An Extreme Bounds Analysis

This paper analyses which economic and political factors affect the chance that a country receives IMF credit or signs an agreement with the Fund. We use a panel model for 128 countries over the period 1972-1998. Our results, based on Extreme Bounds Analysis, suggest that it are mostly economic variables that are robustly related to IMF lending activity, while most political variables that have been put forward in previous studies on IMF involvement are non-significant. To the extent that political factors matter, they seem more closely related to the conclusion of IMF agreements than to the disbursement of IMF credits.
Freedom and unanticipated consequences

Freedom is commonly taken to consist in the absence of constraints. Dowding and van Hees (U˝˝fi) defend an instance of this view according to which an agent fails to be free to perform a particular action (if and) only if she is intentionally prevented from carrying out that action. Here I consider two ways of understanding what intentional prevention might mean, roughly either intended or anticipated pre- vention. I defend the latter weaker interpretation and argue that it creates a problem for the conception of freedom that Dowding and van Hees defend. I also suggest that the analysis presented can be used to add further detail to the moral responsibility conception of freedom according to which a constraint restricts someone's freedom exactly if someone is morally responsible for creating or not removing it.
Filles et garçons en école d’ingénieurs. Les trajets sociaux et scolaires des élèves de l’Institut National des Télécommunications

Cette recherche, menee aupres d'eleves ingenieurs de l'Institut National des Telecommunications (INT), a pour objectif d'une part de comparer entre les filles et les garcons les facteurs pouvant rendre compte de ce choix d'orientation et d'autre part les raisons de leur choix pour cette ecole d'ingenieurs. Les resultats de l'etude montrent que les filles doivent encore posseder des atouts scolaires et sociaux plus importants que leurs homologues masculins pour s'engager dans ce type de formation. En revanche, les motifs evoques par les filles pour leur choix d'integrer l'INT ne se demarquent pas de ceux des garcons.
Deep convolutional neural networks for LVCSR

Convolutional Neural Networks (CNNs) are an alternative type of neural network that can be used to reduce spectral variations and model spectral correlations which exist in signals. Since speech signals exhibit both of these properties, CNNs are a more effective model for speech compared to Deep Neural Networks (DNNs). In this paper, we explore applying CNNs to large vocabulary speech tasks. First, we determine the appropriate architecture to make CNNs effective compared to DNNs for LVCSR tasks. Specifically, we focus on how many convolutional layers are needed, what is the optimal number of hidden units, what is the best pooling strategy, and the best input feature type for CNNs. We then explore the behavior of neural network features extracted from CNNs on a variety of LVCSR tasks, comparing CNNs to DNNs and GMMs. We find that CNNs offer between a 13-30% relative improvement over GMMs, and a 4-12% relative improvement over DNNs, on a 400-hr Broadcast News and 300-hr Switchboard task.