Spatial variability of ocean waves, from in-situ measurements

notes: Detailed statistical analysis of unique concurrent wave measurements Physical processes distort natural homogeneity of waves at typical wave energy site Physical processes can have a significant effect on wave energy assessments Differences greatest for low freq’s, 8.6% difference in Mean incident wave power Short-term spatial variability was largest for high-frequencies, and parameter Tm02publication-status: Publishedtypes: ArticleThis paper describes the analysis of the spatial properties of ocean waves using measurements from an array of four directional wave buoys installed in a square formation, with side 500 m, in the Celtic Sea, UK. Wave measurements in this area have been installed to support resource assessment and design for wave energy devices at the Wave Hub site off the North Cornwall coast. This unique deployment of multiple directional sensors provides high quality direct measurements of the spatial properties of the wave field. Spectral parameters measured simultaneously by all four buoys within the array are compared and it is demonstrated that wave conditions cannot be considered stationary across the measurement area. Differences in the measured wave fields were observed primarily in the low frequencies and are observed to be of a level sufficient to impact the assessment of site characteristics. Theoretical estimations of refraction and bottom friction indicate that these physical processes contribute to the observed measurements. The results demonstrate the potential effect of spatial variability in wave fields on the monitoring of wave energy sites, and highlight the requirement for accurate evaluation of physical processes

Sustained Release Drug Delivery Devices

A method and device for treating a mammalian organism to obtain a desired local or systemic physiological or pharmacological effect is provided. The method includes administering a sustained release drug delivery system to a mammalian organism in need of such treatment at an area wherein release of an effective agent is desired and allowing the effective agent to pass through the device in a controlled manner. The device includes an inner core or reservoir comprising the effective agent; a first coating layer, which is essentially impermeable to the passage of the effective agent; and a second coating layer, which is permeable to the passage of the effective agent. The first coating layer covers at least a portion of the inner core; however, at least a small portion of the inner core is not coated with the first coating layer. The second coating layer essentially completely covers the first coating layer and the uncoated portion of the inner core

Massively parallel Bayesian inference for transient gravitational-wave astronomy

Understanding the properties of transient gravitational waves (GWs) and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astrophysical measurement in transient GW astronomy. Usually, stochastic sampling algorithms are used to estimate posterior probability distributions over the parameter spaces of models describing experimental data. The most physically accurate models typically come with a large computational overhead which can render data analsis extremely time consuming, or possibly even prohibitive. In some cases highly specialized optimizations can mitigate these issues, though they can be difficult to implement, as well as to generalize to arbitrary models of the data. Here, we investigate an accurate, flexible, and scalable method for astrophysical inference: parallelized nested sampling. The reduction in the wall-time of inference scales almost linearly with the number of parallel processes running on a high-performance computing cluster. By utilizing a pool of several hundreds or thousands of CPUs in a high-performance cluster, the large wall times of many astrophysical inferences can be alleviated while simultaneously ensuring that any GW signal model can be used ‘out of the box’, i.e. without additional optimization or approximation. Our method will be useful to both the LIGO-Virgo-KAGRA collaborations and the wider scientific community performing astrophysical analyses on GWs. An implementation is available in the open source gravitational-wave inference library pBilby (parallel bilby)

Flowbec

publication-status: UnpublishedThis document provides an overview of the resources available for the description of the natural environment at the Wave Hub site, and surrounding region. It aims to provide the reader with an understanding of the mechanisms that have led to the collection of the data resources, and details on how to access them. Detailed information for key research areas is then presented. The document does not aim to provide results of the data collection and analysis, and the reader is referred to the data sources reviewed.NERC FLOWBE

Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology

Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical tech- nique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy carries a degree of morbidity and mortality and on occasion may even be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm−1. To begin development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random Forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spec- tral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Fur- thermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete frequency collection, this approach is import to allow future clinical translation and enables IR to achieve its potential

Testosterone replacement in young male cancer survivors: A 6-month double-blind randomised placebo-controlled trial

Background Young male cancer survivors have lower testosterone levels, higher fat mass, and worse quality of life (QoL) than age-matched healthy controls. Low testosterone in cancer survivors can be due to orchidectomy or effects of chemotherapy and radiotherapy. We have undertaken a double-blind, placebo-controlled, 6-month trial of testosterone replacement in young male cancer survivors with borderline low testosterone (7–12 nmol/l). Methods and findings This was a multicentre United Kingdom study conducted in secondary care hospital outpatients. Male survivors of testicular cancer, lymphoma, and leukaemia aged 25–50 years with morning total serum testosterone 7–12 nmol/l were recruited. A total of 136 men were randomised between July 2012 and February 2015 (42.6% aged 25–37 years, 57.4% 38–50 years, 88% testicular cancer, 10% lymphoma, matched for body mass index [BMI]). Participants were randomised 1:1 to receive testosterone (Tostran 2% gel) or placebo for 26 weeks. A dose titration was performed after 2 weeks. The coprimary end points were trunk fat mass and SF36 Physical Functioning score (SF36-PF) at 26 weeks by intention to treat. At 26 weeks, testosterone treatment compared with placebo was associated with decreased trunk fat mass (−0.9 kg, 95% CI −1.6 to −0.3, p = 0.0073), decreased whole-body fat mass (−1.8 kg, 95% CI −2.9 to −0.7, p = 0.0016), and increased lean body mass (1.5 kg, 95% CI 0.9–2.1, p < 0.001). Decrease in fat mass was greatest in those with a high truncal fat mass at baseline. There was no treatment effect on SF36-PF or any other QoL scores. Testosterone treatment was well tolerated. The limitations of our study were as follows: a relatively short duration of treatment, only three cancer groups included, and no hard end point data such as cardiovascular events. Conclusions In young male cancer survivors with low-normal morning total serum testosterone, replacement with testosterone is associated with an improvement in body composition. Trial registration ISRCTN: 70274195, EudraCT: 2011-000677-31

Permeable, Non-irritating Prodrugs of Nonsteroidal and Steroidal Agents

Prodrugs containing an active drug molecule linked to a polyethylene glycol group, and a method of use thereof are described. Exemplary soluble ester prodrugs contain naproxen, triamcinolone acetonide, gancyclovir, taxol, cyclosporin, dideoxyinosine, trihydroxy steroids, and flurbiprofen molecules linked to polyethylene glycol (PEG) groups. Pharmaceutical compositions containing these prodrugs, and a method of using these esters for treating disease states or symptoms are also described

Clinical and budget impacts of changes in oral anticoagulation prescribing for atrial fibrillation

OBJECTIVE: To assess temporal clinical and budget impacts of changes in atrial fibrillation (AF)-related prescribing in England. METHODS: Data on AF prevalence, AF-related stroke incidence and prescribing for all National Health Service general practices, hospitals and registered patients with hospitalised AF-related stroke in England were obtained from national databases. Stroke care costs were based on published data. We compared changes in oral anticoagulation prescribing (warfarin or direct oral anticoagulants (DOACs)), incidence of hospitalised AF-related stroke, and associated overall and per-patient costs in the periods January 2011-June 2014 and July 2014-December 2017. RESULTS: Between 2011-2014 and 2014-2017, recipients of oral anticoagulation for AF increased by 86.5% from 1 381 170 to 2 575 669. The number of patients prescribed warfarin grew by 16.1% from 1 313 544 to 1 525 674 and those taking DOACs by 1452.7% from 67 626 to 1 049 995. Prescribed items increased by 5.9% for warfarin (95% CI 2.9% to 8.9%) but by 2004.8% for DOACs (95% CI 1848.8% to 2160.7%). Oral anticoagulation prescription cost rose overall by 781.2%, from £87 313 310 to £769 444 028, (£733,466,204 with warfarin monitoring) and per patient by 50.7%, from £293 to £442, giving an incremental cost of £149. Nevertheless, as AF-related stroke incidence fell by 11.3% (95% CI -11.5% to -11.1%) from 86 467 in 2011-2014 to 76 730 in 2014-2017 with adjustment for AF prevalence, the overall per-patient cost reduced from £1129 to £840, giving an incremental per-patient saving of £289. CONCLUSIONS: Despite nearly one million additional DOAC prescriptions and substantial associated spending in the latter part of this study, the decline in AF-related stroke led to incremental savings at the national level