841 resultados para Third-party Joinder


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Background—Mutations of the APC gene cause familial adenomatous polyposis (FAP), a hereditary colorectal cancer predisposition syndrome.Aims—To conduct a cost comparison analysis of predictive genetic testing versus conventional clinical screening for individuals at risk of inheriting FAP, using the perspective of a third party payer. Methods—All direct health care costs for both screening strategies were measured according to time and motion, and the expected costs evaluated using a decision analysis model.Results—The baseline analysis predicted that screening a prototype FAP family would cost $4975/£3109 by molecular testingand $8031/£5019 by clinical screening strategy, when family members were monitored with the same frequency of clinical surveillance (every two to three years). Sensitivity analyses revealed that the genetic testing approach is cost saving for key variables including the kindred size, the age of screening onset, and the cost of mutation identification in a proband. However, if the APC mutation carriers were monitored at an increased (annual) frequency, the cost of the genetic screening strategy increased to $7483/ £4677 and was especially sensitive to variability in age of onset of screening, family size, and cost of genetic testing of at risk relatives. Conclusions—In FAP kindreds, a predictive genetic testing strategy costs less than conventional clinical screening, provided that the frequency of surveillance is identical using either strategy. An additional significant benefit is the elimination of unnecessary colonic examinations for those family members found to be noncarriers.

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Wireless LAN (WLAN) market consists of IEEE 802.11 MAC standard conformant devices (e.g., access points (APs), client adapters) from multiple vendors. Certain third party certifications such as those specified by the Wi-Fi alliance have been widely used by vendors to ensure basic conformance to the 802.11 standard, thus leading to the expectation that the available devices exhibit identical MAC level behavior. In this paper, however, we present what we believe to be the first ever set of experimental results that highlight the fact that WLAN devices from different vendors in the market can have heterogeneous MAC level behavior. Specifically, we demonstrate with examples and data that in certain cases, devices may not be conformant with the 802.11 standard while in other cases, they may differ in significant details that are not a part of mandatory specifications of the standard. We argue that heterogeneous MAC implementations can adversely impact WLAN operations leading to unfair bandwidth allocation, potential break-down of related MAC functionality and difficulties in provisioning the capacity of a WLAN. However, on the positive side, MAC level heterogeneity can be useful in applications such as vendor/model level device fingerprinting.

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We consider the problem of developing privacy-preserving machine learning algorithms in a dis-tributed multiparty setting. Here different parties own different parts of a data set, and the goal is to learn a classifier from the entire data set with-out any party revealing any information about the individual data points it owns. Pathak et al [7]recently proposed a solution to this problem in which each party learns a local classifier from its own data, and a third party then aggregates these classifiers in a privacy-preserving manner using a cryptographic scheme. The generaliza-tion performance of their algorithm is sensitive to the number of parties and the relative frac-tions of data owned by the different parties. In this paper, we describe a new differentially pri-vate algorithm for the multiparty setting that uses a stochastic gradient descent based procedure to directly optimize the overall multiparty ob-jective rather than combining classifiers learned from optimizing local objectives. The algorithm achieves a slightly weaker form of differential privacy than that of [7], but provides improved generalization guarantees that do not depend on the number of parties or the relative sizes of the individual data sets. Experimental results corrob-orate our theoretical findings.

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We present a multipartite protocol in a counterfactual paradigm. In counterfactual quantum cryptography, secure information is transmitted between two spatially separated parties even when there is no physical travel of particles transferring the information between them. We propose here a tripartite counterfactual quantum protocol for the task of certificate authorization. Here a trusted third party, Alice, authenticates an entity Bob (e.g., a bank) that a client Charlie wishes to securely transact with. The protocol is counterfactual with respect to either Bob or Charlie. We prove its security against a general incoherent attack, where Eve attacks single particles.

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In this paper we present a combination of technologies to provide an Energy-on-Demand (EoD) service to enable low cost innovation suitable for microgrid networks. The system is designed around the low cost and simple Rural Energy Device (RED) Box which in combination with Short Message Service (SMS) communication methodology serves as an elementary proxy for Smart meters which are typically used in urban settings. Further, customer behavior and familiarity in using such devices based on mobile experience has been incorporated into the design philosophy. Customers are incentivized to interact with the system thus providing valuable behavioral and usage data to the Utility Service Provider (USP). Data that is collected over time can be used by the USP for analytics envisioned by using remote computing services known as cloud computing service. Cloud computing allows for a sharing of computational resources at the virtual level across several networks. The customer-system interaction is facilitated by a third party Telecom Service provider (TSP). The approximate cost of the RED Box is envisaged to be under USD 10 on production scale.

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In today's API-rich world, programmer productivity depends heavily on the programmer's ability to discover the required APIs. In this paper, we present a technique and tool, called MATHFINDER, to discover APIs for mathematical computations by mining unit tests of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code to compute the expression by mapping its subexpressions to API method calls. For each subexpression, MATHFINDER searches for a method such that there is a mapping between method inputs and variables of the subexpression. The subexpression, when evaluated on the test inputs of the method under this mapping, should produce results that match the method output on a large number of tests. We implemented MATHFINDER as an Eclipse plugin for discovery of third-party Java APIs and performed a user study to evaluate its effectiveness. In the study, the use of MATHFINDER resulted in a 2x improvement in programmer productivity. In 96% of the subexpressions queried for in the study, MATHFINDER retrieved the desired API methods as the top-most result. The top-most pseudo-code snippet to implement the entire expression was correct in 93% of the cases. Since the number of methods and unit tests to mine could be large in practice, we also implement MATHFINDER in a MapReduce framework and evaluate its scalability and response time.

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Today's programming languages are supported by powerful third-party APIs. For a given application domain, it is common to have many competing APIs that provide similar functionality. Programmer productivity therefore depends heavily on the programmer's ability to discover suitable APIs both during an initial coding phase, as well as during software maintenance. The aim of this work is to support the discovery and migration of math APIs. Math APIs are at the heart of many application domains ranging from machine learning to scientific computations. Our approach, called MATHFINDER, combines executable specifications of mathematical computations with unit tests (operational specifications) of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code comprised of API methods to compute the expression by mining unit tests of the API methods. We present a sequential version of our unit test mining algorithm and also design a more scalable data-parallel version. We perform extensive evaluation of MATHFINDER (1) for API discovery, where math algorithms are to be implemented from scratch and (2) for API migration, where client programs utilizing a math API are to be migrated to another API. We evaluated the precision and recall of MATHFINDER on a diverse collection of math expressions, culled from algorithms used in a wide range of application areas such as control systems and structural dynamics. In a user study to evaluate the productivity gains obtained by using MATHFINDER for API discovery, the programmers who used MATHFINDER finished their programming tasks twice as fast as their counterparts who used the usual techniques like web and code search, IDE code completion, and manual inspection of library documentation. For the problem of API migration, as a case study, we used MATHFINDER to migrate Weka, a popular machine learning library. Overall, our evaluation shows that MATHFINDER is easy to use, provides highly precise results across several math APIs and application domains even with a small number of unit tests per method, and scales to large collections of unit tests.

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Designing and implementing thread-safe multithreaded libraries can be a daunting task as developers of these libraries need to ensure that their implementations are free from concurrency bugs, including deadlocks. The usual practice involves employing software testing and/or dynamic analysis to detect. deadlocks. Their effectiveness is dependent on well-designed multithreaded test cases. Unsurprisingly, developing multithreaded tests is significantly harder than developing sequential tests for obvious reasons. In this paper, we address the problem of automatically synthesizing multithreaded tests that can induce deadlocks. The key insight to our approach is that a subset of the properties observed when a deadlock manifests in a concurrent execution can also be observed in a single threaded execution. We design a novel, automatic, scalable and directed approach that identifies these properties and synthesizes a deadlock revealing multithreaded test. The input to our approach is the library implementation under consideration and the output is a set of deadlock revealing multithreaded tests. We have implemented our approach as part of a tool, named OMEN1. OMEN is able to synthesize multithreaded tests on many multithreaded Java libraries. Applying a dynamic deadlock detector on the execution of the synthesized tests results in the detection of a number of deadlocks, including 35 real deadlocks in classes documented as thread-safe. Moreover, our experimental results show that dynamic analysis on multithreaded tests that are either synthesized randomly or developed by third-party programmers are ineffective in detecting the deadlocks.

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Resumen: Características del amparo y la posibilidad de la intervención de terceros en dicho tipo de procesos; criterios jurisprudenciales, tanto provinciales como nacionales, sobre la intervención en determinados supuestos, vinculados a la posibilidad de una comunidad de controversia con los litigantes principales y a la afectación de algún derecho del pretenso tercero.

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Resumen: El propósito del trabajo es el estudio de uno de los semanarios de teatro radio y cine más leídos de los años cuarenta y cincuenta: Radiolandia. Se trata de una publicación orientada a dar cuenta de la actualidad del campo artístico nacional tanto a través de notas sobre programas radiales, obras teatrales o películas específicas como a través de información sobre quienes el semanario denomina nuestros astros y estrellas. El abordaje de Radiolandia se desarrollará tomando tres ejes: uno descriptivo en el que se da cuenta de las características generales, tales como formato, precio, etc; un segundo vinculado al análisis de los avisos publicitarios y un tercero que se propone investigar el modo en el que son retratadas los actores, actrices y cancionistas como ídolos del espectáculo.

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[ES] Este trabajo aborda el estudio de la formación de la insatisfacción, desde la perspectiva cognitiva y afectiva, y de sus consecuencias en forma de intenciones de comportamientos de queja. El objetivo es investigar la influencia directa e indirecta, a través de los afectos negativos, que ejerce la desconfirmación de expectativas sobre la insatisfacción, y analizar la contribución de estos juicios sobre las intenciones de respuestas de queja, a terceras partes y privadas. A partir de una muestra de clientes insatisfechos con restaurantes que manifiestan distintos niveles de atribución externa, se ha construido un modelo causal para estudiar las relaciones.

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Fundamentally, action potentials in the squid axon are consequence of the entrance of sodium ions during the depolarization of the rising phase of the spike mediated by the outflow of potassium ions during the hyperpolarization of the falling phase. Perfect metabolic efficiency with a minimum charge needed for the change in voltage during the action potential would confine sodium entry to the rising phase and potassium efflux to the falling phase. However, because sodium channels remain open to a significant extent during the falling phase, a certain overlap of inward and outward currents is observed. In this work we investigate the impact of ion overlap on the number of the adenosine triphosphate (ATP) molecules and energy cost required per action potential as a function of the temperature in a Hodgkin–Huxley model. Based on a recent approach to computing the energy cost of neuronal action potential generation not based on ion counting, we show that increased firing frequencies induced by higher temperatures imply more efficient use of sodium entry, and then a decrease in the metabolic energy cost required to restore the concentration gradients after an action potential. Also, we determine values of sodium conductance at which the hydrolysis efficiency presents a clear minimum.

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Erratun publicado en Frontiers in Cellular Neuroscience 7 : (2013) // Article ID 107

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Microglia are the resident brain macrophages and they have been traditionally studied as orchestrators of the brain inflammatory response during infections and disease. In addition, microglia has a more benign, less explored role as the brain professional phagocytes. Phagocytosis is a term coined from the Greek to describe the receptor-mediated engulfment and degradation of dead cells and microbes. In addition, microglia phagocytoses brain-specific cargo, such as axonal and myelin debris in spinal cord injury or multiple sclerosis, amyloid-beta deposits in Alzheimer's disease, and supernumerary synapses in postnatal development. Common mechanisms of recognition, engulfment, and degradation of the different types of cargo are assumed, but very little is known about the shared and specific molecules involved in the phagocytosis of each target by microglia. More importantly, the functional consequences of microglial phagocytosis remain largely unexplored. Overall, phagocytosis is considered a beneficial phenomenon, since it eliminates dead cells and induces an anti-inflammatory response. However, phagocytosis can also activate the respiratory burst, which produces toxic reactive oxygen species (ROS). Phagocytosis has been traditionally studied in pathological conditions, leading to the assumption that microglia have to be activated inorder to become efficient phagocytes. Recent data, however, has shown that unchallenged microglia phagocytose apoptotic cells during development and in adult neurogenic niches, suggesting an overlooked role in brain remodeling throughout the normal lifespan. The present review will summarize the current state of the literature regarding the role of microglial phagocytosis in maintaining tissue homeostasis in health as in disease.