1,792 research outputs found

    Detecting phase transitions in community structures using big data analysis of the engineering education research landscape: a European perspective

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    Comunicação apresentada na 44th SEFI Conference, 12-­15 September 2016, Tampere, Finlan

    Airborne mapping of complex obstacles using 2D Splinegon

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    This paper describes a recently proposed algorithm in mapping the unknown obstacle in a stationary environment where the obstacles are represented as curved in nature. The focus is to achieve a guaranteed performance of sensor based navigation and mapping. The guaranteed performance is quantified by explicit bounds of the position estimate of an autonomous aerial vehicle using an extended Kalman filter and to track the obstacle so as to extract the map of the obstacle. This Dubins path planning algorithm is used to provide a flyable and safe path to the vehicle to fly from one location to another. This description takes into account the fact that the vehicle is made to fly around the obstacle and hence will map the shape of the obstacle using the 2D-Splinegon technique. This splinegon technique, the most efficient and a robust way to estimate the boundary of a curved nature obstacles, can provide mathematically provable performance guarantees that are achievable in practice

    Anatomy of the Trading Process Empirical Evidence on the Behavior of Institutional Traders

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    This paper examines the behavior of institutional traders. We use unique data on the equity transactions of 21 institutions of differing investment styles which provide a detailed account of the anatomy of the trading process. The data include information on the number of days needed to fill an order and types of order placement strategies employed. We analyze the motivations for trade, the determinants of trade duration, and the choice of order type. The analysis provides some support for the predictions made by theoretical models, but suggests that these models fail to capture important dimensions of trading behavior

    The Relation Between Stock Market Movements and NYSE Seat Prices

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    Exchange seat prices are widely reported and followed as measures of market sentiment. This paper analyzes the information content of NYSE seat prices using: (1) annual seat prices from 1869 to 1998, and (2) the complete record of trades, bids and offers for the seat market from 1973 to 1994. Seat market volumes have predictive power regarding future stock market returns, consistent with a model where seat market activity is a proxy for unobserved factors affecting expected returns. We find abnormally large price movements in seats prior to October 1987, consistent with the hypothesis that seat prices capture market sentiment

    A Local-Time Semantics for Negotiations

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    Negotiations, introduced by Esparza et al., are a model for concurrent systems where computations involving a set of agents are described in terms of their interactions. In many situations, it is natural to impose timing constraints between interactions -- for instance, to limit the time available to enter the PIN after inserting a card into an ATM. To model this, we introduce a real-time aspect to negotiations. In our model of local-timed negotiations, agents have local reference times that evolve independently. Inspired by the model of networks of timed automata, each agent is equipped with a set of local clocks. Similar to timed automata, the outcomes of a negotiation contain guards and resets over the local clocks. As a new feature, we allow some interactions to force the reference clocks of the participating agents to synchronize. This synchronization constraint allows us to model interesting scenarios. Surprisingly, it also gives unlimited computing power. We show that reachability is undecidable for local-timed negotiations with a mixture of synchronized and unsynchronized interactions. We study restrictions on the use of synchronized interactions that make the problem decidable.Comment: A shorter version appears in FORMATS 202

    Depression treatment in individuals with cancer: a comparative analysis with cardio-metabolic conditions

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    A clear picture of the current state of nationwide depression treatment practices in individuals with cancer and depression does not exist in the United States (US). Therefore, the primary objective of this study was to examine rates of any depression treatment among individuals with cancer and depression in the US. To better understand the relationship between any treatment for depression and presence of cancer, we used a comparison group of individuals with cardio-metabolic conditions owing to the similar challenges faced in management of depression in individuals with these conditions. We used a retrospective cross-sectional design and data from multiple years of the Medical Expenditure Panel Survey, a nationally representative household-survey on healthcare utilization and expenditures. Study sample consisted of adults aged 21 or older with self-reported depression and cancer (n=528) or self-reported depression and diabetes, heart disease or hypertension (n=1643). Depression treatment comprised of any use of antidepres- sants and/or any use of mental health counseling services. Treatment rates for depression were 78.0% and 81.7% among individuals with cancer and cardio-metabolic conditions respectively. After controlling for socio-demographic, access-to-care, number of physician-visits, health-status, and lifestyle risk-factors related variables; individuals with cancer were less likely to report any treatment for depression (Adjusted Odds Ratio=0.67; 95% Confidence Interval=0.49, 0.92) compared to individuals with cardio-metabolic conditions (P≤0.01). Our findings highlight the possibility that competing demands may crowd out treatment for depression and that cancer diagnosis may be a barrier to depression treatment

    Long-Term Bidirectional Neuron Interfaces for Robotic Control, and In Vitro Learning Studies

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    There are two fundamentally different goals for neural interfacing. On the biology side, to interface living neurons to external electronics allows the observation and manipulation of neural circuits to elucidate their fundamental mechanisms. On the engineering side, neural interfaces in animals, people, or in cell culture have the potential to restore missing functionality, or someday, to enhance existing functionality. At the Laboratory for NeuroEngineering at Georgia Tech, we are developing new technologies to help make both goals attainable. We culture dissociated mammalian neurons on multi-electrode arrays, and use them as the brain of a 'Hybrot', or hybrid neural-robotic system. Distributed neural activity patterns are used to control mobile robots. We have created the hardware and software necessary to feed the robots' sensory inputs back to the cultures in real time, as electrical stimuli. By embodying cultured networks, we study learning and memory at the cellular and network level, using 2-photon laser-scanning microscopy to image plasticity while it happens. We have observed a very rich dynamical landscape of activity patterns in networks of only a few thousand cells. We can alter this landscape via electrical stimuli, and use the hybrot system to study the emergent properties of networks in vitro

    INSIGHTS ON DRUG TARGETING OF TOXOPLASMA GONDII HOST INVASION PROTEINS: A REVIEW

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    Toxoplasma gondii is an obligate intracellular parasite that infects homoeothermic animals. It is also the major cause of retinochoroiditis in humans.Drugs targeting T. gondii proteins involved in the establishment of host-pathogen interactions is well documented to be an efficient way to combatthe infections. Basically, parasitic invasion of T. gondii occurs by the sequential secretion of apical membrane antigen 1 and rhoptry neck proteins onthe parasite and host cell surfaces, respectively. These proteins operate synergistically and form the moving junction (MJ) complex, thereby, enablingattachment and penetration of the parasite into the host cell. Better understanding of molecular interactions of these proteins is essential to develophighly efficient therapeutic modalities. Hence, by this review it is intended to update the current status of rhoptry and other MJ complex proteins asideal candidates for targeting T. gondii.Keywords: Toxoplasma gondii, Rhoptry proteins, Moving junction complex, Toxoplasmosis
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