Two sister republics, the United States and France : Grant--Bancroft--Bismarck /

Title on added t.p. and running title: Alsace-Lorraine, monument to Grant.

Educational reading guide for the partially seeing.

Cover title.

Discours et rapport veritable de la conférence tenue entre les députez de la part de M. le duc de Mayenne, lieutenant général de l'estat & coronne de France, princes, prélats et Éstats generaux assemblez à Paris, avec les députez de MM. les princes, prélate, seigneurs & autres catholiques estants du party du roy de Navarre.

Paging irregular between p. 129-145.

La corporeidad del actor : ¿simulacro, contagio o creación?

Se discuten aquí los conceptos de creatividad e imitación vinculados al análisis de la práctica teatral. Los debates surgidos a finales de la década del setenta alrededor de estos conceptos se retoman aquí, pues los mismos representaban dos tendencias opuestas, pero conciliables, de la práctica teatral. La noción antropológica de corporeidad (Duch y col., 2005) nos posibilita revitalizar en términos semiológicos el debate en torno a la materialidad corpórea de los significantes y los sentidos sociales que estos conllevan para la formación y el entrenamiento actoral, las cuales se realizan mediante el estudio y la adaptación de los patrones corporales de movimiento que caracterizan las distintas comunidades. En consecuencia, proponemos pensar el aprendizaje de la gestualidad, de los movimientos corporales, y del sentido con que éstos son empleados en la vida cotidiana como un proceso que implica a la creatividad y a la imitación, operaciones que configuran un eje a lo largo del cual se establecen puntos de contacto y puntos de fuga entre la corporeidad característica de un grupo social y la específicamente personal, momento este último en donde la tarea creativa del actor tiene lugar

Evaluating Neural Futures: Good Technoscience and the Challenge of Co-Production

Thesis (Ph.D.)--University of Washington, 2016-06

Cognitive deficits associated with cancer: A model of subjective and objective outcomes

Cancer and its treatment can affect many different aspects of quality of life. As a construct measured subjectively, quality of life shows an inconsistent relationship with objective outcome measures. That is, sometimes subjective and objective outcomes correspond with each other and sometimes they show little or no relationship. In this article, we propose a model for the relationship between subjective and objective outcomes using the example of cognitive function in people with cancer. The model and the research findings on which it is based help demonstrate that, in some circumstances, subjective measures of cognitive function correlate more strongly with psychosocial variables such as appraisal, coping, and emotions than with objective cognitive function. The model may provide a useful framework for research and clinical practice in quality of life for people with cancer.

Epidemiology of recreational exposure to freshwater cyanobacteria - an international prospective cohort study

Background: Case studies and anecdotal reports have documented a range of acute illnesses associated with exposure to cyanobacteria and their toxins in recreational waters. The epidemiological data to date are limited; we sought to improve on the design of some previously conducted studies in order to facilitate revision and refinement of guidelines for exposure to cyanobacteria in recreational waters. Methods: A prospective cohort study was conducted to investigate the incidence of acute symptoms in individuals exposed, through recreational activities, to low ( cell surface area < 2.4 mm(2)/mL), medium ( 2.4 - 12.0 mm(2)/mL) and high (> 12.0 mm(2)/mL) levels of cyanobacteria in lakes and rivers in southeast Queensland, the central coast area of New South Wales, and northeast and central Florida. Multivariable logistic regression analyses were employed; models adjusted for region, age, smoking, prior history of asthma, hay fever or skin disease ( eczema or dermatitis) and clustering by household. Results: Of individuals approached, 3,595 met the eligibility criteria, 3,193 (89%) agreed to participate and 1,331 (37%) completed both the questionnaire and follow-up interview. Respiratory symptoms were 2.1 (95% CI: 1.1 - 4.0) times more likely to be reported by subjects exposed to high levels of cyanobacteria than by those exposed to low levels. Similarly, when grouping all reported symptoms, individuals exposed to high levels of cyanobacteria were 1.7 ( 95% CI: 1.0 - 2.8) times more likely to report symptoms than their low-level cyanobacteria-exposed counterparts. Conclusion: A significant increase in reporting of minor self-limiting symptoms, particularly respiratory symptoms, was associated with exposure to higher levels of cyanobacteria of mixed genera. We suggest that exposure to cyanobacteria based on total cell surface area above 12 mm(2)/mL could result in increased incidence of symptoms. The potential for severe, life-threatening cyanobacteria-related illness is likely to be greater in recreational waters that have significant levels of cyanobacterial toxins, so future epidemiological investigations should be directed towards recreational exposure to cyanotoxins.

Bodies in translation: French feminist influences on anglophone feminist theory: Review article

Review of the following books: French Feminist Theory. Dani Cavallaro, 2003. London and New York, Continuum. The Sex of Knowing, Miche` le Le Doeuff, 2003. translated by Kathryn Hamer and Lorraine Code. New York and London, Routledge. Touching Thought: Ontology and Sexual Difference . Ellen Mortensen, 2003. Lanham, Boulder, New York and Oxford, Lexington.

Pattern-based reuse of successful designs: usability ofsafety-critical systems

Users of safety-critical systems are expected to effectively control or monitor complex systems, with errors potentially leading to catastrophe. For such systems, safety is of paramount importance and must be designed into the human-machine interface. While many case studies show how inadequate design practice led to poor safety and usability, concrete guidance on good design practices is scarce. The paper argues that the pattern language paradigm, widely used in the software design community, is a suitable means of documenting appropriate design strategies. We discuss how typical usability-related properties (e.g., flexibility) need some adjustment to be used for assessing safety-critical systems, and document a pattern language, based on corresponding "safety-usability" principles

The functional organisation of the fronto-temporal language system:evidence from syntactic and semantic ambiguity

Spoken language comprehension is known to involve a large left-dominant network of fronto-temporal brain regions, but there is still little consensus about how the syntactic and semantic aspects of language are processed within this network. In an fMRI study, volunteers heard spoken sentences that contained either syntactic or semantic ambiguities as well as carefully matched low-ambiguity sentences. Results showed ambiguity-related responses in the posterior left inferior frontal gyrus (pLIFG) and posterior left middle temporal regions. The pLIFG activations were present for both syntactic and semantic ambiguities suggesting that this region is not specialised for processing either semantic or syntactic information, but instead performs cognitive operations that are required to resolve different types of ambiguity irrespective of their linguistic nature, for example by selecting between possible interpretations or reinterpreting misparsed sentences. Syntactic ambiguities also produced activation in the posterior middle temporal gyrus. These data confirm the functional relationship between these two brain regions and their importance in constructing grammatical representations of spoken language.

Correcting errors in optical data transmission using neural networks

Optical data communication systems are prone to a variety of processes that modify the transmitted signal, and contribute errors in the determination of 1s from 0s. This is a difficult, and commercially important, problem to solve. Errors must be detected and corrected at high speed, and the classifier must be very accurate; ideally it should also be tunable to the characteristics of individual communication links. We show that simple single layer neural networks may be used to address these problems, and examine how different input representations affect the accuracy of bit error correction. Our results lead us to conclude that a system based on these principles can perform at least as well as an existing non-trainable error correction system, whilst being tunable to suit the individual characteristics of different communication links.

Suitability of dysphonia measurements for telemonitoring of Parkinson's disease

We present an assessment of the practical value of existing traditional and non-standard measures for discriminating healthy people from people with Parkinson's disease (PD) by detecting dysphonia. We introduce a new measure of dysphonia, Pitch Period Entropy (PPE), which is robust to many uncontrollable confounding effects including noisy acoustic environments and normal, healthy variations in voice frequency. We collected sustained phonations from 31 people, 23 with PD. We then selected 10 highly uncorrelated measures, and an exhaustive search of all possible combinations of these measures finds four that in combination lead to overall correct classification performance of 91.4%, using a kernel support vector machine. In conclusion, we find that non-standard methods in combination with traditional harmonics-to-noise ratios are best able to separate healthy from PD subjects. The selected non-standard methods are robust to many uncontrollable variations in acoustic environment and individual subjects, and are thus well-suited to telemonitoring applications.

Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support vector machines. We use an existing database consisting of 263 samples from 43 subjects, and demonstrate that these new dysphonia measures can outperform state-of-the-art results, reaching almost 99% overall classification accuracy using only ten dysphonia features. We find that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects. We see these results as an important step toward noninvasive diagnostic decision support in PD.

Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.