Pupil Examination in Children

Pupillary evaluation is a crucial part of every pediatric eye exam. It provides information about the structure of the eye as well as the afferent and efferent function of the eyes. It remains a quick and efficient test in the ocular evaluation. This chapter reviews the relevant neuroanatomy and the different components of the pupillary exam. The light-reflex and swinging flashlight tests are reviewed, as well as how a reverse afferent pupillary defect is detected. Clinical examples and pearls are provided to help the reader better understand the different aspects of the exam.

When to Use Different Tests for Power Analysis and Data Analysis for Mediation

Several options exist for conducting inference on indirect effects in mediation analysis. While methods which use bootstrapping are the preferred inferential approach for testing mediation, they are time consuming when the test must be performed many times for a power analysis. Alternatives which are more computationally efficient are not as robust, meaning accuracy of the inferences from these methods are more affected by nonnormal and heteroskedastic data (Biesanz et al., 2010). While previous research focused on how different sample sizes would be needed to achieve the same amount of power for different inferential approaches (Fritz & MacKinnon, 2007), we explore how similar power estimates are at the same sample size. We compare the power estimates from six tests using a Monte Carlo simulation study, varying the path coefficients and tests of the indirect effect. If tests produce similar power estimates, the more computationally efficient test could be used for power analysis and the more intensive test involving resampling can be used for data analysis. We found that when the assumptions of linear regression are met, three tests consistently perform similarly: the joint significance test, the Monte Carlo confidence interval, and the percentile bootstrap confidence interval. Based on these results, we recommend using the more computationally efficient joint significance test for power analysis then using the percentile bootstrap confidence interval for the data analysis.

SARS-CoV2 serology assays: utility and limits of different antigen based tests through the evaluation and the comparison of four commercial tests

Introduction: SARS-CoV2 serology testing is multipurpose provided to choose an efficient test. We evaluated and compared 4 different commercial serology tests, three of them had the Food and Drug Administration (FDA) approval. Our goal was to provide new data to help to guide the interpretation and the choice of the serological tests. Methods: Four commercial tests were evaluated: Cobas®Roche®(total anti-N antibodies), VIDAS®Biomerieux®(IgM and IgG anti-RBD antibodies), Mindray®(IgM and IgG anti-N and anti-RBD antibodies) and Access®Beckman Coulter®(IgG anti-RBD antibodies). Were tested: a positive panel (n=72 sera) obtained from COVID-19 confirmed patients and a negative panel (n=119) of pre-pandemic sera. Were determined the analytical performances and was drawn the ROC curve to assess the manufacturer's threshold. Results: A large range of variability between the tests was found. Mindray®IgG and Cobas® tests showed the best overall sensitivity 79,2%CI95%[67,9-87,8]. Cobas® showed the best sensitivity after D14; 85,4%CI95%[72,2-93,9]. The best specificity was noted for Cobas®, VIDAS®IgG and Access® IgG(100%CI95%[96,9-100]). Access® had the lower sensitivity even after D14 (55,5% CI95%[43,4-67,3]). VIDAS®IgM and Mindray®IgM tests showed the lowest specificity and sensitivity rates. Overall, only 43 out of 72 sera gave concordant results (59,7%). Retained cut-offs for a significantly better sensitivity and accuracy, without altering significantly the specificity, were: 0,87 for Vidas®IgM(p=0,01), 0,55 for Vidas®IgG(p=0,05) and 0,14 for Access®(p<10-4). Conclusion: Although FDA approved, each laboratory should realize its own evaluation for commercial tests. Tests variability may raise some concerns that seroprevalence studies may vary significantly based on the used serology test.

Thermal Testing and Analysis Techniques for Wires and Wire Bundles

Determining wire and wire bundle amperage capacity (i.e., “ampacity”) currently relies on the use of standards to derate wire ampacity when in a bundle configuration. The feasibility of developing physics-based and regression thermal models of single wires and wire bundles to determine ampacity using a customized test apparatus was investigated during a pathfinder study. A test facility was developed and various wire and wire bundle articles were tested under a variety of temperature and pressure conditions using an efficient test matrix formulated using Design of Experiments (DOE) techniques. Physics-based models were developed and correlated to the test results. Regression models were formulated and compared to test results and standards.

SRAM Bitcell Defect Identification Methodology Using Electrical Failure Analysis Data

Static Random Access Memory (SRAM) has long been used for a new technology development vehicle because it is sensitive to process defects due to its high density and minimum feature size. In addition, failure location can be accurately predicted because of the highly structured architecture. Thus, fast and accurate Failure Analysis (FA) of the SRAM failure is crucial for the success of new technology learning and development. It is often quite time consuming to identify defects through conventional physical failure analysis techniques. In this paper, we present an advanced defect identification methodology for SRAM bitcell failures with fast speed and high accuracy based on the bitcell transistor analog characteristics from special design for test (DFT) features, Direct Bitcell Access (DBA). This technique has the advantage to shorten FA throughput time due to a time efficient test method and an intuitive failure analysis method based on Electrical Failure Analysis (EFA) without destructive analysis. In addition, all the defects in a wafer can be analyzed and improved simultaneously utilizing the proposed defect identification methodology. Some successful case studies are also discussed to demonstrate the efficiency of the proposed defect identification methodology.

SRAM Bitcell Defect Identification Methodology Using Electrical Failure Analysis Data

Static Random Access Memory (SRAM) has long been used for a new technology development vehicle because it is sensitive to process defects due to its high density and minimum feature size. In addition, failure location can be accurately predicted because of the highly structured architecture. Thus, fast and accurate Failure Analysis (FA) of the SRAM failure is crucial for the success of new technology learning and development. It is often quite time consuming to identify defects through conventional physical failure analysis techniques. In this paper, we present an advanced defect identification methodology for SRAM bitcell failures with fast speed and high accuracy based on the bitcell transistor analog characteristics from special design for test (DFT) features, Direct Bitcell Access (DBA). This technique has the advantage to shorten FA throughput time due to a time efficient test method and an intuitive failure analysis method based on Electrical Failure Analysis (EFA) without destructive analysis. In addition, all the defects in a wafer can be analyzed and improved simultaneously utilizing the proposed defect identification methodology. Some successful case studies are also discussed to demonstrate the efficiency of the proposed defect identification methodology.

Predictive usefulness of RT-PCR testing in different patterns of Covid-19 symptomatology: analysis of a French cohort of 12,810 outpatients

Reverse transcriptase polymerase chain reaction (RT-PCR) is a key tool to diagnose Covid-19. Yet it may not be the most efficient test in all patients. In this paper, we develop a clinical strategy for prescribing RT-PCR to patients based on data from COVIDOM, a French cohort of 54,000 patients with clinically suspected Covid-19, including 12,810 patients tested by RT-PCR. We use a machine-learning algorithm (decision tree) in order to predict RT-PCR results based on the clinical presentation. We show that symptoms alone are sufficient to predict RT-PCR outcome with a mean average precision of 86%. We identify combinations of symptoms that are predictive of RT-PCR positivity (90% for anosmia/ageusia) or negativity (only 30% of RT-PCR+ for a subgroup with cardiopulmonary symptoms): in both cases, RT-PCR provides little added diagnostic value. We propose a prescribing strategy based on clinical presentation that can improve the global efficiency of RT-PCR testing.

Sensitivity Analysis of Maximum Circulation of Wake Vortex Encountered by En-Route Aircraft

Wake vortex encounters (WVE) can pose significant hazard for en-route aircraft. We studied the sensitivity of wake vortex (WV) circulation and decay to aircraft mass, altitude, velocity, density, time of catastrophic wake demise event, eddy dissipation rate, wing span, span-wise load factor, and WV core radius. Then, a tool was developed to compute circulations of WV generated/encountered by aircraft en-route, while disregarding unrealistic operational conditions. A comprehensive study is presented for most aircraft in the Base of Aircraft Data version 4.1 for different masses, altitudes, speeds, and separation values between generator and follower aircraft. The maximum WV circulation corresponds to A380-861 as generator: 864 and 840 m2/s at horizontal separation of 3 and 5 NM, respectively. In cruise environment, these WV may descend 1000 ft in 2.6 min and 2000 ft in 6.2 min, while retaining 74% and 49% of their initial strength, respectively. The maximum circulation of WV encountered by aircraft at horizontal separation of 3 NM from an A380-861 is 593, 726, and 745 m2/s, at FL200, FL300, and FL395, respectively. At 5 NM, the circulations decrease down to 578, 708, and 726 m2/s. Our results allow reducing WVE simulations only to critical scenarios, and thus perform more efficient test programs for computing aircraft upsets en-route.