Comparing full-field data from structural components with complicated geometries

A new decomposition algorithm based on QR factorization is introduced for processing and comparing irregularly shaped stress and deformation datasets found in structural analysis. The algorithm improves the comparison of two-dimensional data fields from the surface of components where data is missing from the field of view due to obstructed measurement systems or component geometry that results in areas where no data is present. The technique enables the comparison of these irregularly shaped datasets without the need for interpolation or warping of the data necessary in some other decomposition techniques, for example, Chebyshev or Zernike decomposition. This ensures comparisons are only made between the available data in each dataset and thus similarity metrics are not biased by missing data. The decomposition and comparison technique has been applied during an impact experiment, a modal analysis, and a fatigue study, with the stress and displacement data obtained from finite-element analysis, digital image correlation and thermoelastic stress analysis. The results demonstrate that the technique can be used to process data from a range of sources and suggests the technique has the potential for use in a wide variety of applications

The Wasteland of Random Supergravities

We show that in a general \cal{N} = 1 supergravity with N \gg 1 scalar fields, an exponentially small fraction of the de Sitter critical points are metastable vacua. Taking the superpotential and Kahler potential to be random functions, we construct a random matrix model for the Hessian matrix, which is well-approximated by the sum of a Wigner matrix and two Wishart matrices. We compute the eigenvalue spectrum analytically from the free convolution of the constituent spectra and find that in typical configurations, a significant fraction of the eigenvalues are negative. Building on the Tracy-Widom law governing fluctuations of extreme eigenvalues, we determine the probability P of a large fluctuation in which all the eigenvalues become positive. Strong eigenvalue repulsion makes this extremely unlikely: we find P \propto exp(-c N^p), with c, p being constants. For generic critical points we find p \approx 1.5, while for approximately-supersymmetric critical points, p \approx 1.3. Our results have significant implications for the counting of de Sitter vacua in string theory, but the number of vacua remains vast.Comment: 39 pages, 9 figures; v2: fixed typos, added refs and clarification

Long‐read nanopore sequencing resolves a TMEM231 gene conversion event causing Meckel–Gruber syndrome

The diagnostic deployment of massively parallel short‐read next‐generation sequencing (NGS) has greatly improved genetic test availability, speed, and diagnostic yield, particularly for rare inherited disorders. Nonetheless, diagnostic approaches based on short‐read sequencing have a poor ability to accurately detect gene conversion events. We report on the genetic analysis of a family in which 3 fetuses had clinical features consistent with the autosomal recessive disorder Meckel–Gruber syndrome (MKS). Targeted NGS of 29 known MKS‐associated genes revealed a heterozygous TMEM231 splice donor variant c.929+1A>G. Comparative read‐depth analysis, performed to identify a second pathogenic allele, revealed an apparent heterozygous deletion of TMEM231 exon 4. To verify this result we performed single‐molecule long‐read sequencing of a long‐range polymerase chain reaction product spanning this locus. We identified four missense variants that were absent from the short‐read dataset due to the preferential mapping of variant‐containing reads to a downstream TMEM231 pseudogene. Consistent with the parental segregation analysis, we demonstrate that the single‐molecule long reads could be used to show that the variants are arranged in trans. Our experience shows that robust validation of apparent dosage variants remains essential to avoid the pitfalls of short‐read sequencing and that new third‐generation long‐read sequencing technologies can already aid routine clinical care

Rapid Detection of Chlamydia trachomatis and Typing of the Lymphogranuloma venereum associated L-Serovars by TaqMan PCR

<p>Abstract</p> <p>Background</p> <p>Infection due to <it>Chlamydia trachomatis </it>is the most common sexually transmitted bacterial disease of global health significance, and especially the L-serovars causing lymphogranuloma venereum are increasingly being found in Europe in men who have sex with men.</p> <p>Results</p> <p>The design and evaluation of a rapid, multiplex, real-time PCR targeting the major outer membrane protein (<it>omp-1</it>) -gene and a L-serovar-specific region of the polymorphic protein H (<it>pmp-H</it>) -gene for the detection of <it>Chlamydia trachomatis </it>is reported here. The PCR takes place as a single reaction with an internal control. For L1-, L2- and L3-serovar differentiation a second set of real-time PCRs was evaluated based on the amplification of serovar-specific <it>omp-1</it>-regions. The detection limit of each real-time PCR, multiplexed or not, was 50 genome copies per reaction with an efficiency ranging from 90,5–95,2%.</p> <p>In a retrospective analysis of 50 ocular, rectal and urogenital specimens formerly tested to be positive for <it>C. trachomatis </it>we identified six L2-serovars in rectal specimens of HIV-positive men, one in a double-infection with L3, and one L2 in a urethral specimen of an HIV-negative male.</p> <p>Conclusion</p> <p>This unique real-time PCR is specific and convenient for the rapid routine-diagnostic detection of lymphogranuloma venereum-associated L-serovars and enables the subsequent differentiation of L1, L2 and L3 for epidemiologic studies.</p

Phenotypic Plasticity and Contemporary Evolution in Introduced Populations: Evidence from Translocated Populations of White Sands Pupfish (Cyrpinodon tularosa)

Contemporary evolution has been shown in a few studies to be an important component of colonization ability, but seldom have researchers considered whether phenotypic plasticity facilitates directional evolution from the invasion event. In the current study, we evaluated body shape divergence of the New Mexico State-threatened White Sands pupfish (Cyprinodon tularosa) that were introduced to brackish, lacustrine habitats at two different time in the recent past (approximately 30 years and 1 year previously) from the same source population (saline river environment). Pupfish body shape is correlated with environmental salinity: fish from saline habitats are characterized by slender body shapes, whereas fish from fresher, yet brackish springs are deep-bodied. In this study, lacustrine populations consisted of an approximately 30-year old population and several 1-year old populations, all introduced from the same source. The body shape divergence of the 30-year old population was significant and greater than any of the divergences of the 1-year old populations (which were for the most part not significant). Nonetheless, all body shape changes exhibited body deepening in less saline environments. We conclude that phenotypic plasticity potentially facilitates directional evolution of body deepening for introduced pupfish populations

Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control

It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for two main reasons: nonlinear recurrent networks often exhibit chaotic behavior and most known learning rules do not work in robust fashion in recurrent networks. Here we address both these problems by demonstrating how random recurrent networks (RRN) that initially exhibit chaotic dynamics can be tuned through a supervised learning rule to generate locally stable neural patterns of activity that are both complex and robust to noise. The outcome is a novel neural network regime that exhibits both transiently stable and chaotic trajectories. We further show that the recurrent learning rule dramatically increases the ability of RRNs to generate complex spatiotemporal motor patterns, and accounts for recent experimental data showing a decrease in neural variability in response to stimulus onset

Neuroimaging of tissue microstructure as a marker of neurodegeneration in the AT(N) framework: defining abnormal neurodegeneration and improving prediction of clinical status

Background: Alzheimer’s disease involves accumulating amyloid (A) and tau (T) pathology, and progressive neurodegeneration (N), leading to the development of the AD clinical syndrome. While several markers of N have been proposed, efforts to define normal vs. abnormal neurodegeneration based on neuroimaging have been limited. Sensitive markers that may account for or predict cognitive dysfunction for individuals in early disease stages are critical. Methods: Participants (n = 296) defined on A and T status and spanning the AD-clinical continuum underwent multi-shell diffusion-weighted magnetic resonance imaging to generate Neurite Orientation Dispersion and Density Imaging (NODDI) metrics, which were tested as markers of N. To better define N, we developed age- and sex-adjusted robust z-score values to quantify normal and AD-associated (abnormal) neurodegeneration in both cortical gray matter and subcortical white matter regions of interest. We used general logistic regression with receiver operating characteristic (ROC) and area under the curve (AUC) analysis to test whether NODDI metrics improved diagnostic accuracy compared to models that only relied on cerebrospinal fluid (CSF) A and T status (alone and in combination). Results: Using internal robust norms, we found that NODDI metrics correlate with worsening cognitive status and that NODDI captures early, AD neurodegenerative pathology in the gray matter of cognitively unimpaired, but A/T biomarker-positive, individuals. NODDI metrics utilized together with A and T status improved diagnostic prediction accuracy of AD clinical status, compared with models using CSF A and T status alone. Conclusion: Using a robust norms approach, we show that abnormal AD-related neurodegeneration can be detected among cognitively unimpaired individuals. Metrics derived from diffusion-weighted imaging are potential sensitive markers of N and could be considered for trial enrichment and as outcomes in clinical trials. However, given the small sample sizes, the exploratory nature of the work must be acknowledged

Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults

INTRODUCTION: Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS: Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aβ)42/Aβ40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS: We observed a significant CSF Aβ42/Aβ40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION: NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment