Future of the Virginia Oyster Industry

CHESAPEAKE BAY has long been famous for its oysters. Shared by Maryland and Virginia, this natural resource contributes greatly to the economic life of about thirty Tidewater counties. Virginia oyster grounds extend approximately half way up the bay and reach far up the numerous tributaries. In addition, there are thousands of acres of oyster grounds on the Sea Side of the Eastern Shore. Despite the magnitude of the acreage adapted for growing oysters, comparatively little effort has been made to find out just how valuable the industry is to the state or to explore its possibilities for development. Federal statistics indicate that Virginia ranks as the No. 1 oyster-producing state, the yield amounting to at least 5,000,000 bushels annually. Still, it is recognized that the state\u27s oyster grounds are capable of a much higher level of production than is witnessed toda

A simple graphical way of evaluating coverage and directional non-coverages

Evaluation of the coverage probability and, more recently, of the intervalar location of con dence intervals, is a useful procedure if exact and asymptotic methods for constructing con dence intervals are used for some populacional parameter. In this paper, a simple graphical procedure is presented to execute this kind of evaluation in con dence methods for linear combinations of k independent binomial proportions. Our proposal is based on the representation of the mesial and distal non-coverage probabilities on a plane. We carry out a simulation study to show how this graphical representation can be interpreted and used as a basis for the evaluation of intervalar location of con dence interval methods

Proving Determinacy of the PharOS Real-Time Operating System

International audienceExecutions in the PharOS real-time system are deterministic in the sense that the sequence of local states for every process is independent of the order in which processes are scheduled. The essential ingredient for achieving this property is that a temporal window of execution is associated with every instruction. Messages become visible to receiving processes only after the time window of the sending message has elapsed. We present a high-level model of PharOS in TLA+ and formally state and prove determinacy using the TLA+ Proof System

FroDO: From Detections to 3D Objects

Object-oriented maps are important for scene understanding since they jointly capture geometry and semantics, allow individual instantiation and meaningful reasoning about objects. We introduce FroDO, a method for accurate 3D reconstruction of object instances from RGB video that infers their location, pose and shape in a coarse to fine manner. Key to FroDO is to embed object shapes in a novel learnt shape space that allows seamless switching between sparse point cloud and dense DeepSDF decoding. Given an input sequence of localized RGB frames, FroDO first aggregates 2D detections to instantiate a 3D bounding box per object. A shape code is regressed using an encoder network before optimizing shape and pose further under the learnt shape priors using sparse or dense shape representations. The optimization uses multi-view geometric, photometric and silhouette losses. We evaluate on real-world datasets, including Pix3D, Redwood-OS, and ScanNet, for single-view, multi-view, and multi-object reconstruction

Approximate confidence intervals for a linear combination of binomial proportions: A new variant

We propose a new adjustment for constructing an improved version of theWald interval for linear combinations of binomial proportions, which addresses the presence of extremal samples. A comparative simulation study was carried out to investigate the performance of this new variant with respect to the exact coverage probability, expected interval length, and mesial and distal noncoverage probabilities. Additionally, we discuss the application of a criterion for interpreting interval location in the case of small samples and/or in situations in which extremal observations exist. The confidence intervals obtained from the new variant performed better for some evaluation measures

Apolipoprotein E4 Polymorphism and Outcomes from Traumatic Brain Injury : A Living Systematic Review and Meta-Analysis

The mortality of traumatic brain injury (TBI) has been largely static despite advances in monitoring and imaging techniques. Substantial variance exists in outcome, not fully accounted for by baseline characteristics or injury severity, and genetic factors likely play a role in this variance. The aims of this systematic review were to examine the evidence for a link between the apolipoprotein E4 (APOE4) polymorphism and TBI outcomes and where possible, to quantify the effect size via meta-analysis. We searched EMBASE, MEDLINE, CINAHL, and gray literature in December 2017. We included studies of APOE genotype in relation to functional adult TBI outcomes. Methodological quality was assessed using the Quality in Prognostic Studies Risk of Bias Assessment Instrument and the prognostic studies adaptation of the Grading of Recommendations Assessment, Development and Evaluation tool. In addition, we contacted investigators and included an additional 160 patients whose data had not been made available for previous analyses, giving a total sample size of 2593 patients. Meta-analysis demonstrated higher odds of a favorable outcome following TBI in those not possessing an ApoE e4 allele compared with e4 carriers and homozygotes (odds ratio 1.39, 95% confidence interval 1.05 to 1.84; p = 0.02). The influence of APOE4 on neuropsychological functioning following TBI remained uncertain, with multiple conflicting studies. We conclude that the ApoE e4 allele confers a small risk of poor outcome following TBI, with analysis by TBI severity not possible based on the currently available published data. Further research into the long-term neuropsychological impact and risk of dementia is warranted.Peer reviewe

Performance of Small Cluster Surveys and the Clustered LQAS Design to estimate Local-level Vaccination Coverage in Mali

<p>Abstract</p> <p>Background</p> <p>Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required.</p> <p>Methods</p> <p>We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A.</p> <p>Results</p> <p>VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans.</p> <p>Conclusions</p> <p>Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.</p