Identifying higher-order interactions in wave time-series

Reliable design and reanalysis of coastal and offshore structures requires, amongst other things, characterisation of extreme crest elevation corresponding to long return periods, and of the evolution of a wave in space and time conditional on an extreme crest. Extreme crests typically correspond to focussed wave events enhanced by wave-wave interactions of different orders. Higher-order spectral analysis can be used to identify wave-wave interactions in time-series of water surface elevation. The bispectrum and its normalised form (the bicoherence) have been reported by numerous authors as a means to characterise three-wave interactions in laboratory, field and simulation experiments. The bispectrum corresponds to a frequency-domain representation of the third order cumulant of the time-series, and can be thought of as an extension of the power spectrum (itself the frequency-domain representation of the second order cumulant). The power spectrum and bispectrum can both be expressed in terms of the Fourier transforms of the original time-series. The Fast Fourier transform (FFT) therefore provides an efficient means of estimation. However, there are a number of important practical considerations to ensuring reasonable estimation. To detect four-wave interactions, we need to consider the trispectrum and its normalised form (the tricoherence). The trispectrum corresponds to a frequency-domain (Fourier) representation of the fourth-order cumulant of the time-series. Four-wave interactions between Fourier components can involve interactions of the type where f1 + f2 + f3 = f4 and where f1 + f2 = f3 + f4, resulting in two definitions of the trispectrum, depending on which of the two interactions is of interest. We consider both definitions in this paper. Both definitions can be estimated using the FFT, but it’s estimation is considerably more challenging than estimation of the bispectrum. Again, there are important practicalities to bear in mind. In this work, we consider the key practical steps required to correctly estimate the trispectrum and tricoherence. We demonstrate the usefulness of the trispectrum and tricoherence for identifying wave-wave interactions in synthetic (based on combinations of sinusoids and on the HOS model) and measured wave time-series

A multivariate pseudo-likelihood approach to estimating directional ocean wave models

Ocean buoy data in the form of high frequency multivariate time series are routinely recorded at many locations in the world's oceans. Such data can be used to characterise the ocean wavefield, which is important for numerous socio-economic and scientific reasons. This characterisation is typically achieved by modelling the frequency-direction spectrum, which decomposes spatiotemporal variability by both frequency and direction. State-of-the-art methods for estimating the parameters of such models do not make use of the full spatiotemporal content of the buoy observations due to unnecessary assumptions and smoothing steps. We explain how the multivariate debiased Whittle likelihood can be used to jointly estimate all parameters of such frequency-direction spectra directly from the recorded time series. When applied to North Sea buoy data, debiased Whittle likelihood inference reveals smooth evolution of spectral parameters over time. We discuss challenging practical issues including model misspecification, and provide guidelines for future application of the method

Did the Draupner wave occur in a crossing sea?

The ‘New Year Wave’ was recorded at the Draupner platform in the North Sea and is a rare high quality measurement of a ‘freak’ or ‘rogue’ wave. The wave has been the subject of much interest and numerous studies. Despite this, the event has still not been satisfactorily explained. One piece of information which was not directly measured at the platform, but which is vital to understanding the nonlinear dynamics is the wave’s directional spreading. This paper investigates the directionality of the Draupner wave and concludes it might have resulted from two wave-groups crossing, whose mean wave directions were separated by about 90◦ or more. This result has been deduced from a set-up of the low frequency second order difference waves under the giant wave, which can be explained only if two wave systems are propagating at such an angle. To check whether second order theory is satisfactory for such a highly non-linear event, we have run numerical simulations using a fully non-linear potential flow solver, which confirm the conclusion deduced from the second order theory. This is backed up by a hindcast from ECMWF which shows swell waves propagating at ∼ 80◦ to the wind sea. Other evidence which supports our conclusion are the measured forces on the structure, the magnitude of the second order sum waves and some other instances of freak waves occurring in crossing sea states

The rise of linear borders in world politics

This article argues that the dominance of precise, linear borders as an ideal in the demarcation of territory is an outcome of a relatively recent and ongoing historical process, and that this process has had important effects on international politics since circa 1900. Existing accounts of the origins of territorial sovereignty are in wide disagreement largely because they fail to specify the relationship between territory and borders, often conflating the two concepts. I outline a history of the linearization of borders which is separate from that of territorial sovereignty, having a very different timeline and featuring different actors, and offer an explanation for the dominance of this universalizing system of managing and demarcating space, based on the concept of rationalization. Finally I describe two broad ways in which linearizing borders has affected international politics, by making space divisible in new ways, and underpinning hierarchies by altering the distribution of geographical knowledge resources

Effects of vitamin E supplementation on renal non-enzymatic antioxidants in young rats submitted to exhaustive exercise stress

<p>Abstract</p> <p>Background</p> <p>Exercise stress was shown to increase oxidative stress in rats. It lacks reports of increased protection afforded by dietary antioxidant supplements against ROS production during exercise stress. We evaluated the effects of vitamin E supplementation on renal non-enzymatic antioxidants in young rats submitted to exhaustive exercise stress.</p> <p>Methods</p> <p>Wistar rats were divided into three groups: 1) control group; 2) exercise stress group and; 3) exercise stress + Vitamin E group. Rats from the group 3 were treated with gavage administration of 1 mL of Vitamin E (5 mg/kg) for seven consecutive days. Animals from groups 2 and 3 were submitted to a bout of swimming exhaustive exercise stress. Kidney samples were analyzed for Thiobarbituric Acid Reactive Substances to (TBARS) by malondialdehyde (MDA), reduced glutathione (GSH) and vitamin-E levels.</p> <p>Results</p> <p>The group treated with vitamin E and submitted to exercise stress presented the lowest levels of renal MDA (1: 0.16+0.02 mmmol/mgprot vs. 2: 0.34+0.07 mmmol/mgprot vs. 3: 0.1+0.01 mmmol/mgprot; p < 0.0001), the highest levels of renal GSH (1: 23+4 μmol/gprot vs. 2: 23+2 μmol/gprot vs. 3: 58+9 μmol/gprot; p < 0.0001) and the highest levels of renal vitamin E (1: 24+6 μM/gtissue vs. 2: 28+2 μM/gtissue vs. 3: 43+4 μM/gtissue; p < 0.001).</p> <p>Conclusion</p> <p>Vitamin E supplementation improved non-enzymatic antioxidant activity in young rats submitted to exhaustive exercise stress.</p

Supporting Remote Survey Data Analysis by Co-researchers with Learning Disabilities through Inclusive and Creative Practices and Data Science Approaches

Through a process of robust co-design, we created a bespoke accessible survey platform to explore the role of co-researchers with learning disabilities (LDs) in research design and analysis. A team of co-researchers used this system to create an online survey to challenge public understanding of LDs [3]. Here, we describe and evaluate the process of remotely co-analyzing the survey data across 30 meetings in a research team consisting of academics and nonacademics with diverse abilities amid new COVID-19 lockdown challenges. Based on survey data with >1,500 responses, we first coanalyzed demographics using graphs and art & design approaches. Next, co-researchers co-analyzed the output of machine learningbased structural topic modelling (STM) applied to open-ended text responses. We derived an efficient five-steps STM co-analysis process for creative, inclusive, and critical engagement of data by coresearchers. Co-researchers observed that by trying to understand and impact public opinion, their own perspectives also changed

Different types of disease-causing non-coding variants revealed by genomic and gene expression analyses in families with X-linked intellectual disability

The pioneering discovery research of X-linked intellectual disability (XLID) genes has benefitted thousands of individuals worldwide however, approximately 30% of XLID families still remain unresolved. We postulated that non-coding variants that affect gene regulation or splicing may account for the lack of a genetic diagnosis in some cases. Detecting pathogenic, gene-regulatory variants with the same sensitivity and specificity as structural and coding variants is a major challenge for Mendelian disorders. Here, we describe three pedigrees with suggestive XLID where distinctive phenotypes associated with known genes guided the identification of three different non-coding variants. We used comprehensive structural, single nucleotide and repeat expansion analyses of genome sequencing. RNA-Seq from patient-derived cell lines, RT-PCRs, western blots and reporter gene assays were used to confirm the functional effect of three fundamentally different classes of pathogenic non-coding variants: a retrotransposon insertion, a novel intronic splice donor and a canonical splice variant of an untranslated exon. In one family, we excluded a rare coding variant in ARX, a known XLID gene, in favour of a regulatory non-coding variant in OFD1 that correlated with the clinical phenotype. Our results underscore the value of genomic research on unresolved XLID families to aid novel, pathogenic non-coding variant discovery.Michael J. Field, Raman Kumar, Anna Hackett, Sayaka Kayumi, Cheryl A. Shoubridge, Lisa J. Ewans, Atma M. Ivancevic, Tracy Dudding, Byth, Renée Carroll, Thessa Kroes, Alison E. Gardner, Patricia Sullivan, Thuong T. Ha, Charles E. Schwartz, Mark J. Cowley, Marcel E. Dinger, Elizabeth E. Palmer, Louise Christie, Marie Shaw, Tony Roscioli, Jozef Gecz, Mark A. Corbet

Disorders of sex development : insights from targeted gene sequencing of a large international patient cohort

Background: Disorders of sex development (DSD) are congenital conditions in which chromosomal, gonadal, or phenotypic sex is atypical. Clinical management of DSD is often difficult and currently only 13% of patients receive an accurate clinical genetic diagnosis. To address this we have developed a massively parallel sequencing targeted DSD gene panel which allows us to sequence all 64 known diagnostic DSD genes and candidate genes simultaneously. Results: We analyzed DNA from the largest reported international cohort of patients with DSD (278 patients with 46, XY DSD and 48 with 46, XX DSD). Our targeted gene panel compares favorably with other sequencing platforms. We found a total of 28 diagnostic genes that are implicated in DSD, highlighting the genetic spectrum of this disorder. Sequencing revealed 93 previously unreported DSD gene variants. Overall, we identified a likely genetic diagnosis in 43% of patients with 46, XY DSD. In patients with 46, XY disorders of androgen synthesis and action the genetic diagnosis rate reached 60%. Surprisingly, little difference in diagnostic rate was observed between singletons and trios. In many cases our findings are informative as to the likely cause of the DSD, which will facilitate clinical management. Conclusions: Our massively parallel sequencing targeted DSD gene panel represents an economical means of improving the genetic diagnostic capability for patients affected by DSD. Implementation of this panel in a large cohort of patients has expanded our understanding of the underlying genetic etiology of DSD. The inclusion of research candidate genes also provides an invaluable resource for future identification of novel genes