Influence of soil plasticity models on offshore wind turbine response

While recent numerical modelling advances have enabled robust simulation of foundation hysteresis behaviour, uptake of these models has been limited in the offshore wind industry. This is partially due to modelling complexity and the unknown influence of including such soil constitutive models within a design philosophy. This paper addresses this issue by outlining a framework of an aero-hydro-servo-elastic offshore wind turbine model that is fully coupled with a multisurface plasticity 1D Winkler foundation model. Comparisons between this model and industry standard aeroelastic tools, such as OpenFAST, are shown to be in good agreement. The hysteretic soil predictions are also shown to be in good agreement with CM6 Cowden PISA test piles, in terms of secant stiffness and loop shape. This tool has then been used to address the unknown influence of hysteretic soil reactions on the design of monopile supported offshore wind turbines against extreme conditions. This study demonstrates that a significant reduction in ultimate and service limit state utilization is observed when a multisurface plasticity foundation model is adopted, as opposed to industry standard pile–soil interaction models

Clinical Association of White Matter Hyperintensities Localization in a Mexican Family with Spastic Paraparesis Carrying the PSEN1 A431E Mutation

Presenilin 1 gene (PSEN1) mutations are the most common cause of familial Alzheimer’s disease (FAD). One of the most abundant FAD mutations, PSEN1 A431E, has been reported to be associated with spastic paraparesis in about half of its carriers, but the determining mechanisms of this phenotype are still unknown. In our study we characterized three A431E mutation carriers, one symptomatic and two asymptomatic, from a Mexican family with a history of spastic paraparesis in all of its affected members. At cognitive assessment and MRI, the symptomatic subject showed an atypical non-amnestic mild cognitive impairment with visuospatial deficits, olfactory dysfunction and significant parieto-occipital brain atrophy. Furthermore, we found several periventricular white matter hyperintensities whose progression pattern and localization correlated with their motor impairment, cognitive profile, and non-motor symptoms. Together, our data suggests that in this family the A431E mutation leads to a divergent neurological disorder in which cognitive deterioration was clinically exceeded by motor impairment and that it involves early glial and vascular pathological changes

Blind Biological Sequence Denoising with Self-Supervised Set Learning

Biological sequence analysis relies on the ability to denoise the imprecise output of sequencing platforms. We consider a common setting where a short sequence is read out repeatedly using a high-throughput long-read platform to generate multiple subreads, or noisy observations of the same sequence. Denoising these subreads with alignment-based approaches often fails when too few subreads are available or error rates are too high. In this paper, we propose a novel method for blindly denoising sets of sequences without directly observing clean source sequence labels. Our method, Self-Supervised Set Learning (SSSL), gathers subreads together in an embedding space and estimates a single set embedding as the midpoint of the subreads in both the latent and sequence spaces. This set embedding represents the "average" of the subreads and can be decoded into a prediction of the clean sequence. In experiments on simulated long-read DNA data, SSSL methods denoise small reads of $\leq 6$ subreads with 17% fewer errors and large reads of $>6$ subreads with 8% fewer errors compared to the best baseline. On a real dataset of antibody sequences, SSSL improves over baselines on two self-supervised metrics, with a significant improvement on difficult small reads that comprise over 60% of the test set. By accurately denoising these reads, SSSL promises to better realize the potential of high-throughput DNA sequencing data for downstream scientific applications

Methyl-CpG-binding protein 2 mediates overlapping mechanisms across brain disorders

MECP2 and its product, Methyl-CpG binding protein 2 (MeCP2), are mostly known for their association to Rett Syndrome (RTT), a rare neurodevelopmental disorder. Additional evidence suggests that MECP2 may underlie other neuropsychiatric and neurological conditions, and perhaps modulate common presentations and pathophysiology across disorders. To clarify the mechanisms of these interactions, we develop a method that uses the binding properties of MeCP2 to identify its targets, and in particular, the genes recognized by MeCP2 and associated to several neurological and neuropsychiatric disorders. Analysing mechanisms and pathways modulated by these genes, we find that they are involved in three main processes: neuronal transmission, immuno-reactivity, and development. Also, while the nervous system is the most relevant in the pathophysiology of the disorders, additional systems may contribute to MeCP2 action through its target genes. We tested our results with transcriptome analysis on Mecp2-null models and cells derived from a patient with RTT, confirming that the genes identified by our procedure are directly modulated by MeCP2. Thus, MeCP2 may modulate similar mechanisms in different pathologies, suggesting that treatments for one condition may be effective for related disorders

The role of galaxies and AGN in reionising the IGM -- III : IGM-galaxy cross-correlations at z~6 from 8 quasar fields with DEIMOS and MUSE

We present improved results of the measurement of the correlation between galaxies and the intergalactic medium transmission at the end of reionization. We have gathered a sample of 13 spectroscopically confirmed Lyman-break galaxies (LBGs) and 21 Lyman-α emitters (LAEs) at angular separations 20 arcsec ≲ θ ≲ 10 arcmin (∼0.1–4 pMpc at z ∼ 6) from the sightlines to eight background z ≳ 6 quasars. We report for the first time the detection of an excess of Lyman-α transmission spikes at ∼10–60 cMpc from LAEs (3.2σ) and LBGs (1.9σ). We interpret the data with an improved model of the galaxy–Lyman-α transmission and two-point cross-correlations, which includes the enhanced photoionization due to clustered faint sources, enhanced gas densities around the central bright objects and spatial variations of the mean free path. The observed LAE(LBG)–Lyman-α transmission spike two-point cross-correlation function (2PCCF) constrains the luminosity-averaged escape fraction of all galaxies contributing to reionization to ⟨fesc⟩MUV−20(2σ)⁠) is necessary to reproduce the observed 2PCCF and that reionization might be driven by different sub-populations around LBGs and LAEs at z ∼ 6

Environmental Exposure Assessment of Pesticides in Farmworker Homes

Farmworkers and their families are exposed to pesticides both at work and in their homes. Environmental exposure assessment provides a means to evaluate pesticides in the environment and human contact with these chemicals through identification of sources and routes of exposure. To date, a variety of methods have been used to assess pesticide exposure among farmworker families, mostly focusing on dust and handwipe samples. While many of the methods are similar, differences in the collection, chemical analysis, and statistical analysis, can limit the comparability of results from farm-worker studies. This mini-monograph discusses the strategies used to assess pesticide exposures, presents limitations in the available data for farmworkers, and suggests research needs for future studies of pesticide exposure among farmworker families

A biophysical model of cell adhesion mediated by immunoadhesin drugs and antibodies

A promising direction in drug development is to exploit the ability of natural killer cells to kill antibody-labeled target cells. Monoclonal antibodies and drugs designed to elicit this effect typically bind cell-surface epitopes that are overexpressed on target cells but also present on other cells. Thus it is important to understand adhesion of cells by antibodies and similar molecules. We present an equilibrium model of such adhesion, incorporating heterogeneity in target cell epitope density and epitope immobility. We compare with experiments on the adhesion of Jurkat T cells to bilayers containing the relevant natural killer cell receptor, with adhesion mediated by the drug alefacept. We show that a model in which all target cell epitopes are mobile and available is inconsistent with the data, suggesting that more complex mechanisms are at work. We hypothesize that the immobile epitope fraction may change with cell adhesion, and we find that such a model is more consistent with the data. We also quantitatively describe the parameter space in which binding occurs. Our results point toward mechanisms relating epitope immobility to cell adhesion and offer insight into the activity of an important class of drugs.Comment: 13 pages, 5 figure

Limit theorems for von Mises statistics of a measure preserving transformation

For a measure preserving transformation $T$ of a probability space $(X,\mathcal F,\mu)$ we investigate almost sure and distributional convergence of random variables of the form $$x \to \frac{1}{C_n} \sum_{i_1<n,...,i_d<n} f(T^{i_1}x,...,T^{i_d}x),\, n=1,2,...,$$ where $f$ (called the \emph{kernel}) is a function from $X^d$ to $\R$ and $C_1, C_2,...$ are appropriate normalizing constants. We observe that the above random variables are well defined and belong to $L_r(\mu)$ provided that the kernel is chosen from the projective tensor product $$L_p(X_1,\mathcal F_1, \mu_1) \otimes_{\pi}...\otimes_{\pi} L_p(X_d,\mathcal F_d, \mu_d)\subset L_p(\mu^d)$$ with $p=d\,r,\, r\ \in [1, \infty).$ We establish a form of the individual ergodic theorem for such sequences. Next, we give a martingale approximation argument to derive a central limit theorem in the non-degenerate case (in the sense of the classical Hoeffding's decomposition). Furthermore, for $d=2$ and a wide class of canonical kernels $f$ we also show that the convergence holds in distribution towards a quadratic form $\sum_{m=1}^{\infty} \lambda_m\eta^2_m$ in independent standard Gaussian variables $\eta_1, \eta_2,...$. Our results on the distributional convergence use a $T$--\,invariant filtration as a prerequisite and are derived from uni- and multivariate martingale approximations

Profiling the iron, copper and zinc content in primary neuron and astrocyte cultures by rapid online quantitative size exclusion chromatography-inductively coupled plasma-mass spectrometry

Metals often determine the chemical reactivity of the proteins to which they are bound. Each cell in the body tightly maintains a unique metalloproteomic profile, mostly dependent on function. This paper describes an analytical online flow injection quantitative size exclusion chromatography-inductively coupled plasma-mass spectrometry (SEC-ICP-MS) method, which was applied to profiling the metal-binding proteins found in primary cultures of neurons and astrocytes. This method can be conducted using similar amounts of sample to those used for Western blotting (20-150 μg protein), and has a turnaround time of <15 minutes. Metalloprotein standards for Fe (as ferritin), Cu and Zn (as superoxide dismutase-1) were used to construct multi-point calibration curves for online quantification of metalloproteins by SEC-ICP-MS. Homogenates of primary neuron and astrocyte cultures were analysed by SEC-ICP-MS. Online quantification by external calibration with metalloprotein standards determined the mass of metal eluting from the column relative to time (as pg s-1). Total on-column Fe, Cu and Zn detection limits ranged from 0.825 ± 0.005 ng to 13.6 ± 0.7 pg. Neurons and astrocytes exhibited distinct metalloprotein profiles, featuring both ubiquitous and unique metalloprotein species. Separation and detection by SEC-ICP-MS allows appraisal of these metalloproteins in their native state, and online quantification was achieved using this relatively simple external calibration process. © 2013 The Royal Society of Chemistry

Negotiating daughterhood and strangerhood: retrospective accounts of serial migration

Most considerations of daughtering and mothering take for granted that the subjectivities of mothers and daughters are negotiated in contexts of physical proximity throughout daughters’ childhoods. Yet many mothers and daughters spend periods separated from each other, sometimes across national borders. Globally, an increasing number of children experience life in transnational families. This paper examines the retrospective narratives of four women who were serial migrants as children (whose parents migrated before they did) . It focuses on their accounts of the reunion with their mothers and how these fit with the ways in which they construct their mother-daughter relationships. We take a psychosocial approach by using a psychoanalytically-informed reading of these narratives to acknowledge the complexities of the attachments produced in the context of migration and to attend to the multi-layered psychodynamics of the resulting relationships. The paper argues that serial migration positioned many of the daughters in a conflictual emotional landscape from which they had to negotiate ‘strangerhood’ in the context of sadness at leaving people to whom they were attached in order to join their mothers (or parents). As a result, many were resistant to being positioned as daughters, doing daughtering and being mothered in their new homes