Mathematical models and time-frequency heat maps for surface gravity waves generated by thin ships

Recent research suggests that studying the time-frequency response of ship wave signals has potential to shed light on a range of applications, such as inferring the dynamical and geometric properties of a moving vessel based on the surface elevation data detected at a single point in space. We continue this line of research here with a study of mathematical models for thin ships using standard Wigley hulls and Wigley transom-stern hulls as examples. Mathematical models of varying sophistication are considered. These include basic minimal models which use applied pressure distributions as proxies for the ship hull. The more complicated models are Michell's thin ship theory and the Hogner model, both of which explicitly take into account the shape of the hull. We outline a methodology for carefully choosing the form and parameter values in the minimal models such that they reproduce the key features of the more complicated models in the time-frequency domain. For example, we find that a two-pressure model is capable of producing wave elevation signals that have a similar time-frequency profile as that for Michell's thin ship theory applied to the Wigley hull, including the crucially important features caused by interference between waves created at the bow and stern of the ship. One of the key tools in our analysis is the spectrogram, which is a heat-map visualisation in the time-frequency domain. Our work here extends the existing knowledge on the topic of spectrograms of ship waves. The theoretical results in this study are supported by experimental data collected in a towing tank at the Australian Maritime College using model versions of the standard Wigley hulls and Wigley transom-stern hulls

[Comment] Redefine statistical significance

The lack of reproducibility of scientific studies has caused growing concern over the credibility of claims of new discoveries based on “statistically significant” findings. There has been much progress toward documenting and addressing several causes of this lack of reproducibility (e.g., multiple testing, P-hacking, publication bias, and under-powered studies). However, we believe that a leading cause of non-reproducibility has not yet been adequately addressed: Statistical standards of evidence for claiming discoveries in many fields of science are simply too low. Associating “statistically significant” findings with P < 0.05 results in a high rate of false positives even in the absence of other experimental, procedural and reporting problems. For fields where the threshold for defining statistical significance is P<0.05, we propose a change to P<0.005. This simple step would immediately improve the reproducibility of scientific research in many fields. Results that would currently be called “significant” but do not meet the new threshold should instead be called “suggestive.” While statisticians have known the relative weakness of using P≈0.05 as a threshold for discovery and the proposal to lower it to 0.005 is not new (1, 2), a critical mass of researchers now endorse this change. We restrict our recommendation to claims of discovery of new effects. We do not address the appropriate threshold for confirmatory or contradictory replications of existing claims. We also do not advocate changes to discovery thresholds in fields that have already adopted more stringent standards (e.g., genomics and high-energy physics research; see Potential Objections below). We also restrict our recommendation to studies that conduct null hypothesis significance tests. We have diverse views about how best to improve reproducibility, and many of us believe that other ways of summarizing the data, such as Bayes factors or other posterior summaries based on clearly articulated model assumptions, are preferable to P-values. However, changing the P-value threshold is simple and might quickly achieve broad acceptance

Tree rings reveal globally coherent signature of cosmogenic radiocarbon events in 774 and 993 CE

This study was funded by the WSL-internal COSMIC project (5233.00148.001.01), the ETHZ (Laboratory of Ion Beam Physics), the Swiss National Science Foundation (SNF Grant 200021L_157187/1), and as the Czech Republic Grant Agency project no. 17-22102s.Though tree-ring chronologies are annually resolved, their dating has never been independently validated at the global scale. Moreover, it is unknown if atmospheric radiocarbon enrichment events of cosmogenic origin leave spatiotemporally consistent fingerprints. Here we measure the 14C content in 484 individual tree rings formed in the periods 770–780 and 990–1000 CE. Distinct 14C excursions starting in the boreal summer of 774 and the boreal spring of 993 ensure the precise dating of 44 tree-ring records from five continents. We also identify a meridional decline of 11-year mean atmospheric radiocarbon concentrations across both hemispheres. Corroborated by historical eye-witness accounts of red auroras, our results suggest a global exposure to strong solar proton radiation. To improve understanding of the return frequency and intensity of past cosmic events, which is particularly important for assessing the potential threat of space weather on our society, further annually resolved 14C measurements are needed.Publisher PDFPeer reviewe

The influence of obesity-related factors in the etiology of renal cell carcinoma-A mendelian randomization study.

BACKGROUND: Several obesity-related factors have been associated with renal cell carcinoma (RCC), but it is unclear which individual factors directly influence risk. We addressed this question using genetic markers as proxies for putative risk factors and evaluated their relation to RCC risk in a mendelian randomization (MR) framework. This methodology limits bias due to confounding and is not affected by reverse causation. METHODS AND FINDINGS: Genetic markers associated with obesity measures, blood pressure, lipids, type 2 diabetes, insulin, and glucose were initially identified as instrumental variables, and their association with RCC risk was subsequently evaluated in a genome-wide association study (GWAS) of 10,784 RCC patients and 20,406 control participants in a 2-sample MR framework. The effect on RCC risk was estimated by calculating odds ratios (ORSD) for a standard deviation (SD) increment in each risk factor. The MR analysis indicated that higher body mass index increases the risk of RCC (ORSD: 1.56, 95% confidence interval [CI] 1.44-1.70), with comparable results for waist-to-hip ratio (ORSD: 1.63, 95% CI 1.40-1.90) and body fat percentage (ORSD: 1.66, 95% CI 1.44-1.90). This analysis further indicated that higher fasting insulin (ORSD: 1.82, 95% CI 1.30-2.55) and diastolic blood pressure (DBP; ORSD: 1.28, 95% CI 1.11-1.47), but not systolic blood pressure (ORSD: 0.98, 95% CI 0.84-1.14), increase the risk for RCC. No association with RCC risk was seen for lipids, overall type 2 diabetes, or fasting glucose. CONCLUSIONS: This study provides novel evidence for an etiological role of insulin in RCC, as well as confirmatory evidence that obesity and DBP influence RCC risk

Comparison of experimental and numerical ship wakes using time-frequency analysis

Ships travelling steadily cause three-dimensional V-shaped wave patterns which can be observed far away from the sailing line of the ship. Since it is difficult to accurately measure these waves across large domains, we are exploring the quantity of information that can be gathered from recording the surface elevation at single point in space as the ship travels by. The approach used involves time-frequency analysis with spectrograms. We compare experimental data from ship model basin experiments using aWigley hull with numerical simulations from a thin-ship model and show that only the far-field component of the numerical solution is necessary for generating spectrograms from signals gathered three ship lengths from the sailing line of the ship. This result is useful since it is much easier to simulate the far field from the thin-ship model than the near field. The spectrograms constructed using the thin-ship model and the experimental results are shown to match well

Polygenic score modifies risk for Alzheimer\u27s disease in ε4 homozygotes at phenotypic extremes

Introduction: Diversity in cognition among apolipoprotein E () ε4 homozygotes can range from early-onset Alzheimer\u27s disease (AD) to a lifetime with no symptoms. Methods: We evaluated a phenotypic extreme polygenic risk score (PRS) for AD between cognitively healthy ε4 homozygotes aged ≥75 years (n = 213) and early-onset ε4 homozygote AD cases aged ≤65 years (n = 223) as an explanation for this diversity. Results: The PRS for AD was significantly higher in ε4 homozygote AD cases compared to older cognitively healthy ε4/ε4 controls (odds ratio [OR] 8.39; confidence interval [CI] 2.0-35.2; = .003). The difference in the same PRS between ε3/ε3 extremes was not as significant (OR 3.13; CI 0.98-9.92; = .053) despite similar numbers and power. There was no statistical difference in an educational attainment PRS between these age extreme case-controls. Discussion: A PRS for AD contributes to modified cognitive expression of the ε4/ε4 genotype at phenotypic extremes of risk