16 resultados para Ordered Va-file
Resumo:
BACKGROUND: Ibopamine is a non-selective dopamine- and adrenalin-receptor agonist that has been shown to cause pupillary dilation and an increase in aqueous humour secretion. This novel drug can be used as a mydriatic agent, as a provocative test in open-angle glaucoma, and for the treatment of persisting ocular hypotony. HISTORY AND SIGNS: This 47-year-old man had a history of uveitis associated with Crohn's disease. Six years after deep sclerectomy for uveitic secondary glaucoma, he developed severe hypotony in his left eye with drop of visual acuity (VA). The hypotony did not respond to topical steroid treatment. 2 % Ibopamine solution was ordered t. i. d. concomitant to 1 % prednisolone acetate. THERAPY AND OUTCOME: Intraocular pressure (IOP) began to rise after 3 weeks of Ibopamine treatment and returned to normal (12 mmHg) with continuous recovery of VA after 8 weeks. Ibopamine was discontinued at an IOP of 16 mmHg after a course of 12 weeks. IOP and VA remained stable during the 12-month follow-up period. CONCLUSIONS: Ibopamine 2 % eye drops in combination with topical steroids are a therapeutic option in uveitis-associated ocular hypotony.
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We describe the case of a 16-year-old woman with a surgically corrected tetralogy of Fallot presenting with recurrent wide-QRS-complex tachycardia. The tachycardia could be induced and terminated with ventricular stimulation only. QRS morphology during sinus rhythm and tachycardia was identical and variable VA-conduction was observed. Mapping of the tachycardia showed that variations of HH intervals preceded VV intervals. Therefore, a mechanism involving re-entry within the bundle branches was suggested. However, detailed mapping showed cranial to caudal depolarization of the His bundle, leading to the diagnosis of atrioventricular node re-entrant tachycardia. The tachycardia was abolished by radiofrequency catheter ablation of the slow AV nodal pathway. We conclude that variable VA conduction can occur in patients with atrioventricular node re-entrant tachycardia. The atrial tissue is not always an integral part of the re-entrant circuit.
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The first part of this paper provides a comprehensive and self-contained account of the interrelationships between algebraic properties of varieties and properties of their free algebras and equational consequence relations. In particular, proofs are given of known equivalences between the amalgamation property and the Robinson property, the congruence extension property and the extension property, and the flat amalgamation property and the deductive interpolation property, as well as various dependencies between these properties. These relationships are then exploited in the second part of the paper in order to provide new proofs of amalgamation and deductive interpolation for the varieties of lattice-ordered abelian groups and MV-algebras, and to determine important subvarieties of residuated lattices where these properties hold or fail. In particular, a full description is given of all subvarieties of commutative GMV-algebras possessing the amalgamation property.
Resumo:
We study representations of MV-algebras -- equivalently, unital lattice-ordered abelian groups -- through the lens of Stone-Priestley duality, using canonical extensions as an essential tool. Specifically, the theory of canonical extensions implies that the (Stone-Priestley) dual spaces of MV-algebras carry the structure of topological partial commutative ordered semigroups. We use this structure to obtain two different decompositions of such spaces, one indexed over the prime MV-spectrum, the other over the maximal MV-spectrum. These decompositions yield sheaf representations of MV-algebras, using a new and purely duality-theoretic result that relates certain sheaf representations of distributive lattices to decompositions of their dual spaces. Importantly, the proofs of the MV-algebraic representation theorems that we obtain in this way are distinguished from the existing work on this topic by the following features: (1) we use only basic algebraic facts about MV-algebras; (2) we show that the two aforementioned sheaf representations are special cases of a common result, with potential for generalizations; and (3) we show that these results are strongly related to the structure of the Stone-Priestley duals of MV-algebras. In addition, using our analysis of these decompositions, we prove that MV-algebras with isomorphic underlying lattices have homeomorphic maximal MV-spectra. This result is an MV-algebraic generalization of a classical theorem by Kaplansky stating that two compact Hausdorff spaces are homeomorphic if, and only if, the lattices of continuous [0, 1]-valued functions on the spaces are isomorphic.
Resumo:
A compact and planar donor–acceptor molecule 1 comprising tetrathiafulvalene (TTF) and benzothiadiazole (BTD) units has been synthesised and experimentally characterised by structural, optical, and electrochemical methods. Solution-processed and thermally evaporated thin films of 1 have also been explored as active materials in organic field-effect transistors (OFETs). For these devices, hole field-effect mobilities of μFE=(1.3±0.5)×10−3 and (2.7±0.4)×10−3 cm2 V s−1 were determined for the solution-processed and thermally evaporated thin films, respectively. An intense intramolecular charge-transfer (ICT) transition at around 495 nm dominates the optical absorption spectrum of the neutral dyad, which also shows a weak emission from its ICT state. The iodine-induced oxidation of 1 leads to a partially oxidised crystalline charge-transfer (CT) salt {(1)2I3}, and eventually also to a fully oxidised compound {1I3}⋅1/2I2. Single crystals of the former CT compound, exhibiting a highly symmetrical crystal structure, reveal a fairly good room temperature electrical conductivity of the order of 2 S cm−1. The one-dimensional spin system bears compactly bonded BTD acceptors (spatial localisation of the LUMO) along its ridge.
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The paper considers panel data methods for estimating ordered logit models with individual-specific correlated unobserved heterogeneity. We show that a popular approach is inconsistent, whereas some consistent and efficient estimators are available, including minimum distance and generalized method-of-moment estimators. A Monte Carlo study reveals the good properties of an alternative estimator that has not been considered in econometric applications before, is simple to implement and almost as efficient. An illustrative application based on data from the German Socio-Economic Panel confirms the large negative effect of unemployment on life satisfaction that has been found in the previous literature.
Resumo:
This paper proposes a new estimator for the fixed effects ordered logit model. In contrast to existing methods, the new procedure allows estimating the thresholds. The empirical relevance and simplicity of implementation is illustrated in an application on the effect of unemployment on life satisfaction.
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This package includes various Mata functions. kern(): various kernel functions; kint(): kernel integral functions; kdel0(): canonical bandwidth of kernel; quantile(): quantile function; median(): median; iqrange(): inter-quartile range; ecdf(): cumulative distribution function; relrank(): grade transformation; ranks(): ranks/cumulative frequencies; freq(): compute frequency counts; histogram(): produce histogram data; mgof(): multinomial goodness-of-fit tests; collapse(): summary statistics by subgroups; _collapse(): summary statistics by subgroups; gini(): Gini coefficient; sample(): draw random sample; srswr(): SRS with replacement; srswor(): SRS without replacement; upswr(): UPS with replacement; upswor(): UPS without replacement; bs(): bootstrap estimation; bs2(): bootstrap estimation; bs_report(): report bootstrap results; jk(): jackknife estimation; jk_report(): report jackknife results; subset(): obtain subsets, one at a time; composition(): obtain compositions, one by one; ncompositions(): determine number of compositions; partition(): obtain partitions, one at a time; npartitionss(): determine number of partitions; rsubset(): draw random subset; rcomposition(): draw random composition; colvar(): variance, by column; meancolvar(): mean and variance, by column; variance0(): population variance; meanvariance0(): mean and population variance; mse(): mean squared error; colmse(): mean squared error, by column; sse(): sum of squared errors; colsse(): sum of squared errors, by column; benford(): Benford distribution; cauchy(): cumulative Cauchy-Lorentz dist.; cauchyden(): Cauchy-Lorentz density; cauchytail(): reverse cumulative Cauchy-Lorentz; invcauchy(): inverse cumulative Cauchy-Lorentz; rbinomial(): generate binomial random numbers; cebinomial(): cond. expect. of binomial r.v.; root(): Brent's univariate zero finder; nrroot(): Newton-Raphson zero finder; finvert(): univariate function inverter; integrate_sr(): univariate function integration (Simpson's rule); integrate_38(): univariate function integration (Simpson's 3/8 rule); ipolate(): linear interpolation; polint(): polynomial inter-/extrapolation; plot(): Draw twoway plot; _plot(): Draw twoway plot; panels(): identify nested panel structure; _panels(): identify panel sizes; npanels(): identify number of panels; nunique(): count number of distinct values; nuniqrows(): count number of unique rows; isconstant(): whether matrix is constant; nobs(): number of observations; colrunsum(): running sum of each column; linbin(): linear binning; fastlinbin(): fast linear binning; exactbin(): exact binning; makegrid(): equally spaced grid points; cut(): categorize data vector; posof(): find element in vector; which(): positions of nonzero elements; locate(): search an ordered vector; hunt(): consecutive search; cond(): matrix conditional operator; expand(): duplicate single rows/columns; _expand(): duplicate rows/columns in place; repeat(): duplicate contents as a whole; _repeat(): duplicate contents in place; unorder2(): stable version of unorder(); jumble2(): stable version of jumble(); _jumble2(): stable version of _jumble(); pieces(): break string into pieces; npieces(): count number of pieces; _npieces(): count number of pieces; invtokens(): reverse of tokens(); realofstr(): convert string into real; strexpand(): expand string argument; matlist(): display a (real) matrix; insheet(): read spreadsheet file; infile(): read free-format file; outsheet(): write spreadsheet file; callf(): pass optional args to function; callf_setup(): setup for mm_callf().