Errors Associated to Keratoconus Grading using Systems based on Corneal Power

Purpose: To analyze and define the possible errors that may be introduced in keratoconus classification when the keratometric corneal power is used in such classification. Materials and methods: Retrospective study including a total of 44 keratoconus eyes. A comprehensive ophthalmologic examination was performed in all cases, which included a corneal analysis with the Pentacam system (Oculus). Classical keratometric corneal power (Pk), Gaussian corneal power (Pc Gauss), True Net Power (TNP) (Gaussian power neglecting the corneal thickness effect), and an adjusted keratometric corneal power (Pkadj) (keratometric power considering a variable keratometric index) were calculated. All cases included in the study were classified according to five different classification systems: Alió-Shabayek, Amsler-Krumeich, Rabinowitz-McDonnell, collaborative longitudinal evaluation of keratoconus (CLEK), and McMahon. Results: When Pk and Pkadj were compared, differences in the type of grading of keratoconus cases was found in 13.6% of eyes when the Alió-Shabayek or the Amsler-Krumeich systems were used. Likewise, grading differences were observed in 22.7% of eyes with the Rabinowitz-McDonnell and McMahon classification systems and in 31.8% of eyes with the CLEK classification system. All reclassified cases using Pkadj were done in a less severe stage, indicating that the use of Pk may lead to the classification of a cornea as keratoconus, being normal. In general, the results obtained using Pkadj, Pc Gauss or the TNP were equivalent. Differences between Pkadj and Pc Gauss were within ± 0.7D. Conclusion: The use of classical keratometric corneal power may lead to incorrect grading of the severity of keratoconus, with a trend to a more severe grading.

Notes of proceedings and cases determined in the high court of errors and appeals, the court of chancery, and the orphans court of the state of Delaware, 1792-1832

Contains summaries of cases heard by the Delaware Supreme Court and the Delaware Appeals Court in the counties of Sussex, Kent, and Newcastle covering a variety of legal topics. Supposedly based on Wilson's Red Book.

Economics of Policy Errors and Learning in the European Union. Bruges European Economic Policy (BEEP) Briefing 31/2013

Policy errors occur regularly in EU Member States. Learning from these errors can be beneficial. This paper explains how the European Union can facilitate this learning. At present, much attention is given to “best practices”. But learning from mistakes is also valuable. The paper develops the concept of “avoidable error” and examines evidence from infringement proceedings and special reports of the European Court of Auditors which indicate that Member States do indeed commit avoidable errors. The paper considers how Member States may take measures not to repeat avoidable or predictable errors and makes appropriate proposals.

MOREMATA: Stata module (Mata) to provide various functions

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().

Gasterosteus aculeatus egg traits and fish lengths vs. experiment setup

1) Our study addresses the role of non-genetic and genetic inheritance in shaping the adaptive potential of populations under a warming ocean scenario. We used a combined experimental approach (transgenerational plasticity and quantitative genetics) to partition the relative contribution of maternal vs. paternal (additive genetic) effects to offspring body size (a key component of fitness), and investigated a potential physiological mechanism (mitochondrial respiration capacities) underlying whole organism growth/size responses. 2) In very early stages of growth (up to 30 days), offspring body size of marine sticklebacks benefited from maternal transgenerational plasticity (TGP): offspring of mothers acclimated to17°C were larger when reared at 17°C, and offspring of mothers acclimated to 21°C were larger when reared at 21°C. The benefits of maternal TGP on body size were stronger and persisted longer (up to 60 days) for offspring reared in the warmer (21°C) environment, suggesting that maternal effects will be highly relevant for climate change scenarios in this system. 3) Mitochondrial respiration capacities measured on mature offspring (F1 adults) matched the pattern of TGP for juvenile body size, providing an intuitive mechanistic basis for the maternal acclimation persisting into adulthood. Size differences between temperatures seen at early growth stages remained in the F1 adults, linking offspring body size to maternal inheritance of mitochondria. 4) Lower maternal variance components in the warmer environment were mostly driven by mothers acclimated to ambient (colder) conditions, further supporting our tenet that maternal effects were stronger at elevated temperature. Importantly, all parent-offspring temperature combination groups showed genotype x environment (GxE) interactions, suggesting that reaction norms have the potential to evolve. 5) To summarise, transgenerational plasticity and genotype x environment interactions work in concert to mediate impacts of ocean warming on metabolic capacity and early growth of marine sticklebacks. TGP can buffer short-term detrimental effects of climate warming and may buy time for genetic adaptation to catch up, therefore markedly contributing to the evolutionary potential and persistence of populations under climate change.

Tri-level study: modification. Task 5: an examination of driver characteristics and collision producing errors of accident and traffic violation repeaters. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

The inaccuracy of movement with special reference to constant errors;

Also published as: Columbia University contributions to philosophy and psychology.

Reports of cases argued and determined in the Supreme court of judicature; and in the Court for the trial of impeachments and the correction of errors in the state of New York. [1806-1823]

Imprint varies.

A methodology for analyzing general categorical data with misclassification errors with an application in studying seat belt effectiveness. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

The Scholar armed against the errors of the time ; or, A collection of tracts on the principles and evidences of Christianity, the constitution of the Church, and the authority of civil government ... /

Edited by William Jones. Cf. Halkett & Laing.

Reports of cases, argued and determined in the Supreme Court of Errors of the State of Connecticut : prepared and published in pursuance of a statute law of the State.

"Reprint. Originally published: Hartford : G. Goodwin & Sons, 1817-[1852]

Analysis of angular misalignment errors in mounting linear acclerometers to anatomical subjects. Technical report.

Mode of access: Internet.

Memorials of St. Ann's Church, Manchester, in the last century : an attempt to rectify several popular errors; to which is added a short history of church building and Sunday school work in the same town.

Mode of access: Internet.

Remarks on the round-off errors in iterative processes for fixed-point computers /

"May 10, 1962."

An interactive analysis system for execution-time errors /

Bibliography: p. 65-66.