997 resultados para Simple Gases


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Analysis by reduction is a method used in linguistics for checking the correctness of sentences of natural languages. This method is modelled by restarting automata. Here we study a new type of restarting automaton, the so-called t-sRL-automaton, which is an RL-automaton that is rather restricted in that it has a window of size 1 only, and that it works under a minimal acceptance condition. On the other hand, it is allowed to perform up to t rewrite (that is, delete) steps per cycle. We focus on the descriptional complexity of these automata, establishing two complexity measures that are both based on the description of t-sRL-automata in terms of so-called meta-instructions. We present some hierarchy results as well as a non-recursive trade-off between deterministic 2-sRL-automata and finite-state acceptors.

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Characteristics of DIRS-1 Mediated Knock-Downs __ We have previously shown that the most abundant Dictyostelium discoideum retroelement DIRS-1 is suppressed by RNAi mechanisms. Here we provide evidence that both inverted terminal repeats have strong promoter activity and that bidirectional expression apparently generates a substrate for Dicer. A cassette containing the inverted terminal repeats and a fragment of a gene of interest was sufficient to activate the RNAi response, resulting in the generation of ~21 nt siRNAs, a reduction of mRNA and protein expression of the respective endogene. Surprisingly, no transitivity was observed on the endogene. This was in contrast to previous observations, where endogenous siRNAs caused spreading on an artificial transgene. Knock-down was successful on seven target genes that we examined. In three cases a phenotypic analysis proved the efficiency of the approach. One of the target genes was apparently essential because no knock-out could be obtained; the RNAi mediated knock-down, however, resulted in a very slow growing culture indicating a still viable reduction of gene expression.

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Research on autonomous intelligent systems has focused on how robots can robustly carry out missions in uncertain and harsh environments with very little or no human intervention. Robotic execution languages such as RAPs, ESL, and TDL improve robustness by managing functionally redundant procedures for achieving goals. The model-based programming approach extends this by guaranteeing correctness of execution through pre-planning of non-deterministic timed threads of activities. Executing model-based programs effectively on distributed autonomous platforms requires distributing this pre-planning process. This thesis presents a distributed planner for modelbased programs whose planning and execution is distributed among agents with widely varying levels of processor power and memory resources. We make two key contributions. First, we reformulate a model-based program, which describes cooperative activities, into a hierarchical dynamic simple temporal network. This enables efficient distributed coordination of robots and supports deployment on heterogeneous robots. Second, we introduce a distributed temporal planner, called DTP, which solves hierarchical dynamic simple temporal networks with the assistance of the distributed Bellman-Ford shortest path algorithm. The implementation of DTP has been demonstrated successfully on a wide range of randomly generated examples and on a pursuer-evader challenge problem in simulation.

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Various studies of asset markets have shown that traders are capable of learning and transmitting information through prices in many situations. In this paper we replace human traders with intelligent software agents in a series of simulated markets. Using these simple learning agents, we are able to replicate several features of the experiments with human subjects, regarding (1) dissemination of information from informed to uninformed traders, and (2) aggregation of information spread over different traders.

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Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence (Felleman and Van Essen, 1991; Hubel and Wiesel, 1962; Livingstone and Hubel, 1988; Tso et al., 2001; Zeki, 1993), a general class of recognition models has emerged which is based on a hierarchical organization of visual processing, with succeeding stages being sensitive to image features of increasing complexity (Hummel and Biederman, 1992; Riesenhuber and Poggio, 1999; Selfridge, 1959). However, these models appear to be incompatible with some well-known psychophysical results. Prominent among these are experiments investigating recognition impairments caused by vertical inversion of images, especially those of faces. It has been reported that faces that differ "featurally" are much easier to distinguish when inverted than those that differ "configurally" (Freire et al., 2000; Le Grand et al., 2001; Mondloch et al., 2002) ??finding that is difficult to reconcile with the aforementioned models. Here we show that after controlling for subjects' expectations, there is no difference between "featurally" and "configurally" transformed faces in terms of inversion effect. This result reinforces the plausibility of simple hierarchical models of object representation and recognition in cortex.

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In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

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Se desconoce en la actualidad en Colombia la calidad de la interpretación de los gases arteriales por parte de los residentes de medicina de emergencias. Los gases arteriales es una de las ayudas diagnósticas de más rápida consecución en el servicio de urgencias y más utilizadas por ser indispensable en la valoración de patologías de alta prevalencia como son las enfermedades respiratorias y la sepsis. Su mala interpretación puede llevar a mal direccionamiento del manejo de pacientes en estado crítico por lo que es indefectible que los residentes logren un buen entrenamiento en la interpretación de los mismos. Por esta razón se realiza este estudio analítico de concordancia con recolección prospectiva, de corte transversal que busca determinar el grado de concordancia en la interpretación de gases arteriales de los residentes del programa de Medicina de Emergencias de la Universidad del Rosario y especialista en cuidado crítico, así como la interpretación entre ellos según su nivel de entrenamiento y describir cuáles son los hallazgos que encuentran en la interpretación de los mismos. Se recolectaron 60 gases arteriales realizados a paciente hospitalizados en la unidad de cuidados intensivos de la Fundación Santa Fe de Bogotá y se halló la concordancia entre la lectura de los residentes del programa de Medicina de Emergencias y un intensivista. Encontrando una concordancia moderada (r 0.445 y 0.442, ) en las respuestas identificadas en los residentes de segundo y tercer año de residencia(p:0,000y0,01).(MESH: Blood Gas Análisis, Emergency Medical Services, Education, Medical, Graduate)

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Resumen tomado de la publicación. Contiene imágenes de la página web capturadas de la pantalla del ordenador

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Linux commands that are generally useful for analyzing data; it is very easy to reduce phenomena such as links, nodes, URLs or downloads, to multiply repeating identifiers and then sorting and counting appearances.

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Practical introduction to building simple electronic circuits and small robots; aimed at computer scientists.q

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Keep it simple data collection dissemination

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Stars Keep it simple animation. HTML5 compliat. No IOS or android player