NACA Research Memorandums

Report presenting an investigation in the stability tunnel of the use of spoilers for obtaining static longitudinal stability of a model of a canard missile in reverse flight. Results indicated that stable pitching-moment slopes can be obtained at angles of attack up to 11 degrees in the low speed range of the tests, but further investigation of high subsonic speeds will be necessary

Glacial cycles drive rapid divergence of cryptic field vole species

Understanding the factors that contribute to the generation of reproductively isolated forms is a fundamental goal of evolutionary biology. Cryptic species are an especially interesting challenge to study in this context since they lack obvious morphological differentiation that provides clues to adaptive divergence that may drive reproductive isolation. Geographical isolation in refugial areas during glacial cycling is known to be important for generating genetically divergent populations, but its role in the origination of new species is still not fully understood and likely to be situation dependent. We combine analysis of 35,434 single‐nucleotide polymorphisms (SNPs) with environmental niche modeling (ENM) to investigate genomic and ecological divergence in three cryptic species formerly classified as the field vole (Microtus agrestis). The SNPs demonstrate high genomic divergence (pairwise FST values of 0.45–0.72) and little evidence of gene flow among the three field vole cryptic species, and we argue that genetic drift may have been a particularly important mechanism for divergence in the group. The ENM reveals three areas as potential glacial refugia for the cryptic species and differing climatic niches, although with spatial overlap between species pairs. This evidence underscores the role that glacial cycling has in promoting genetic differentiation and reproductive isolation by subdivision into disjunct distributions at glacial maxima in areas relatively close to ice sheets. Future investigation of the intrinsic barriers to gene flow between the field vole cryptic species is required to fully assess the mechanisms that contribute to reproductive isolation. In addition, the Portuguese field vole (M. rozianus) shows a high inbreeding coefficient and a restricted climatic niche, and warrants investigation into its conservation status

Sharks of the order Carcharhiniformes from the British Coniacian, Santonian and Campanian (Upper Cretaceous).

Bulk sampling of phosphate-rich horizons within the British Coniacian to Campanian (Upper Cretaceous) yielded very large samples of shark and ray teeth. All of these samples yielded teeth of diverse members of the Carcharhiniformes, which commonly dominate the fauna. The following species are recorded and described: Pseudoscyliorhinus reussi (Herman, 1977) comb. nov., Crassescyliorhinus germanicus (Herman, 1982) gen. nov., Scyliorhinus elongatus (Davis, 1887), Scyliorhinus brumarivulensis sp. nov., ? Palaeoscyllium sp., Prohaploblepharus riegrafi (Müller, 1989) gen. nov., ? Cretascyliorhinus sp., Scyliorhinidae inc. sedis 1, Scyliorhinidae inc. sedis 2, Pteroscyllium hermani sp. nov., Protoscyliorhinus sp., Leptocharias cretaceus sp. nov., Palaeogaleus havreensis Herman, 1977, Paratriakis subserratus sp. nov., Paratriakis tenuis sp. nov., Paratriakis sp. indet. and ? Loxodon sp. Taxa belonging to the families ?Proscylliidae, Leptochariidae, and Carcharhinidae are described from the Cretaceous for the first time. The evolutionary and palaeoecological implications of these newly recognised faunas are discussed

Implementation of an Optimal First-Order Method for Strongly Convex Total Variation Regularization

We present a practical implementation of an optimal first-order method, due to Nesterov, for large-scale total variation regularization in tomographic reconstruction, image deblurring, etc. The algorithm applies to $\mu$-strongly convex objective functions with $L$-Lipschitz continuous gradient. In the framework of Nesterov both $\mu$ and $L$ are assumed known -- an assumption that is seldom satisfied in practice. We propose to incorporate mechanisms to estimate locally sufficient $\mu$ and $L$ during the iterations. The mechanisms also allow for the application to non-strongly convex functions. We discuss the iteration complexity of several first-order methods, including the proposed algorithm, and we use a 3D tomography problem to compare the performance of these methods. The results show that for ill-conditioned problems solved to high accuracy, the proposed method significantly outperforms state-of-the-art first-order methods, as also suggested by theoretical results.Comment: 23 pages, 4 figure

A multivariate logistic regression equation to screen for dysglycaemia: development and validation

Aims  To develop and validate an empirical equation to screen for dysglycaemia [impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and undiagnosed diabetes]. Methods  A predictive equation was developed using multiple logistic regression analysis and data collected from 1032 Egyptian subjects with no history of diabetes. The equation incorporated age, sex, body mass index (BMI), post-prandial time (self-reported number of hours since last food or drink other than water), systolic blood pressure, high-density lipoprotein (HDL) cholesterol and random capillary plasma glucose as independent covariates for prediction of dysglycaemia based on fasting plasma glucose (FPG) ≥ 6.1 mmol/l and/or plasma glucose 2 h after a 75-g oral glucose load (2-h PG) ≥ 7.8 mmol/l. The equation was validated using a cross-validation procedure. Its performance was also compared with static plasma glucose cut-points for dysglycaemia screening. Results  The predictive equation was calculated with the following logistic regression parameters: P  = 1 + 1/(1 + e −X ) = where X = −8.3390 + 0.0214 (age in years) + 0.6764 (if female) + 0.0335 (BMI in kg/m 2 ) + 0.0934 (post-prandial time in hours) + 0.0141 (systolic blood pressure in mmHg) − 0.0110 (HDL in mmol/l) + 0.0243 (random capillary plasma glucose in mmol/l). The cut-point for the prediction of dysglycaemia was defined as a probability ≥ 0.38. The equation's sensitivity was 55%, specificity 90% and positive predictive value (PPV) 65%. When applied to a new sample, the equation's sensitivity was 53%, specificity 89% and PPV 63%. Conclusions  This multivariate logistic equation improves on currently recommended methods of screening for dysglycaemia and can be easily implemented in a clinical setting using readily available clinical and non-fasting laboratory data and an inexpensive hand-held programmable calculator. Diabet. Med. 22, 599–605 (2005)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75603/1/j.1464-5491.2005.01467.x.pd