Ultrasonic characterisation of wheel hub/axle interference fit pressures

Railway wheels are secured onto the axle by means of an interference fit. The wheel is press fitted onto a pre-lubricated axle, and the resulting interference fit induces a contact pressure at the interface. Occasionally railway wheels fail by fatigue, with the initiation point for the failure frequently traced to the interference fit. The aim of this work is to use ultrasonic reflection to non-destructively determine contact conditions in the interference fit. The rough surface contact at the interference fit interface behaves like a spring. If the contact pressure is high the interface is conformal with few air gaps, the stiffness is then high and the transmission of an ultrasonic wave is permitted. However, when pressure is low more air gaps exist, interfacial stiffness is then reduced and more of the ultrasound is reflected. Normalised contact pressure was determined from this stiffness. Maps of the interface have been produced which show the contact pressure to peak at the edges of the fit, and to experience a continuous variation about a mean value elsewhere

Cascading water underneath Wilkes Land, East Antarctic ice sheet, observed using altimetry and digital elevation models

We describe a major subglacial lake drainage close to the ice divide in Wilkes Land, East Antarctica, and the subsequent cascading of water underneath the ice sheet toward the coast. To analyse the event, we combined altimetry data from several sources and subglacial topography. We estimated the total volume of water that drained from Lake Cook_E2 by differencing digital elevation models (DEM) derived from ASTER and SPOT5 stereo imagery acquired in January 2006 and February 2012. At 5.2 ± 1.5 km³, this is the largest single subglacial drainage event reported so far in Antarctica. Elevation differences between ICESat laser altimetry spanning 2003–2009 and the SPOT5 DEM indicate that the discharge started in November 2006 and lasted approximately 2 years. A 13 m uplift of the surface, corresponding to a refilling of about 0.6 ± 0.3 km³, was observed between the end of the discharge in October 2008 and February 2012. Using the 35-day temporal resolution of Envisat radar altimetry, we monitored the subsequent filling and drainage of connected subglacial lakes located downstream of Cook_E2. The total volume of water traveling within the theoretical 500-km-long flow paths computed with the BEDMAP2 data set is similar to the volume that drained from Lake Cook_E2, and our observations suggest that most of the water released from Lake Cook_E2 did not reach the coast but remained trapped underneath the ice sheet. Our study illustrates how combining multiple remote sensing techniques allows monitoring of the timing and magnitude of subglacial water flow beneath the East Antarctic ice sheet

Elongation of confined ferrofluid droplets under applied fields

Ferrofluids are strongly paramagnetic liquids. We study the behavior of ferrofluid droplets confined between two parallel plates with a weak applied field parallel to the plates. The droplets elongate under the applied field to reduce their demagnetizing energy and reach an equilibrium shape where the magnetic forces balance against the surface tension. This elongation varies logarithmically with aspect ratio of droplet thickness to its original radius, in contrast to the behavior of unconfined droplets. Experimental studies of a ferrofluid/water/surfactant emulsion confirm this prediction.Comment: 12 pages, 7 figures. Submitted to Phys. Rev.

Quantitative stratigraphic analysis in a source-to-sink numerical framework

The sedimentary architecture at continental margins reflects the interplay between the rate of change of accommodation creation (δA) and the rate of change of sediment supply (δS). Stratigraphic interpretation increasingly focuses on understanding the link between deposition patterns and changes in δA=δS, with an attempt to reconstruct the contributing factors. Here, we use the landscape modelling code pyBadlands to (1) investigate the development of stratigraphic sequences in a source-to-sink context; (2) assess the respective performance of two well-established stratigraphic interpretation techniques: the trajectory analysis method and the accommodation succession method; and (3) propose quantitative stratigraphic interpretations based on those two techniques. In contrast to most stratigraphic forward models (SFMs), pyBadlands provides self-consistent sediment supply to basin margins as it simulates erosion, sediment transport and deposition in a source-to-sink context. We present a generic case of landscape evolution that takes into account periodic sea level variations and passive margin thermal subsidence over 30 million years, under uniform rainfall. A set of post-processing tools are provided to analyse the predicted stratigraphic architecture. We first reconstruct the temporal evolution of the depositional cycles and identify key stratigraphic surfaces based on observations of stratal geometries and facies relationships, which we use for comparison to stratigraphic interpretations. We then apply both the trajectory analysis and the accommodation succession methods to manually map key stratigraphic surfaces and define sequence units on the final model output. Finally, we calculate shoreline and shelf-edge trajectories, the temporal evolution of changes in relative sea level (proxy for δA) and sedimentation rate (proxy for δS) at the shoreline, and automatically produce stratigraphic interpretations. Our results suggest that the analysis of the presented model is more robust with the accommodation succession method than with the trajectory analysis method. Stratigraphic analysis based on manually extracted shoreline and shelf-edge trajectory requires calibrations of time-dependent processes such as thermal subsidence or additional constraints from stratal terminations to obtain reliable interpretations. The 3-D stratigraphic analysis of the presented model reveals small lateral variations of sequence formations. Our work provides an efficient and flexible quantitative sequence stratigraphic framework to evaluate the main drivers (climate, sea level and tectonics) controlling sedimentary architectures and investigate their respective roles in sedimentary basin development. © Author(s) 2019.Acknowledgements. Xuesong Ding, Tristan Salles and Patrice Rey were supported by Australian Research Council grant IH130200012 (Basin GENESIS Hub), and Nicolas Flament was supported by Australian Research Council grant DE160101020. Ding acknowledges supports from the International Association for Mathematical Geosciences (IAMG) grant. This research was undertaken with the assistance of resources and services from the National Computational Infrastructure (NCI), which is supported by the Australian Government. We thank Zoltan Sylvester and Jack Neal for their constructive comments on this paper. We also thank Kyle Straub, Cornel Olariu and Jack Neal for their valuable comments on an earlier version of the manuscript. Australian Research Council (grant nos. IH130200012 and DE160101020)

Synthesis and evaluation of new designed multiple ligands directed towards both peroxisome proliferator-activated receptor-γ and angiotensin II type 1 receptor

Because of the complex biological networks, many pathologic disorders fail to be treated with a molecule directed towards a single target. Thus, combination therapies are often necessary, but they have many drawbacks. An alternative consists in building molecules intended to interact with multiple targets, called designed multiple ligands. We followed such a strategy in order to treat metabolic syndrome, by setting up molecules directed towards both type 1 angiotensin II (AT1) receptor and peroxisome proliferator-activated receptor-γ (PPAR-γ). For this purpose, many molecules were prepared by merging both pharmacophores following three different strategies. Their ability to activate PPAR-γ and to block AT1 receptors were evaluated in vitro. This strategy led to the preparation of many new PPAR-γ activating and AT1 blocking molecules. Among them, some exhibited both activities, highlighting the convenience of this approach

A tectonic-rules-based mantle reference frame since 1 billion years ago - implications for supercontinent cycles and plate-mantle system evolution

Understanding the long-term evolution of Earth\u27s plate-mantle system is reliant on absolute plate motion models in a mantle reference frame, but such models are both difficult to construct and controversial. We present a tectonic-rules-based optimization approach to construct a plate motion model in a mantle reference frame covering the last billion years and use it as a constraint for mantle flow models. Our plate motion model results in net lithospheric rotation consistently below 0.25g g€Myr-1, in agreement with mantle flow models, while trench motions are confined to a relatively narrow range of -2 to +2g€cmg€yr-1 since 320g€Ma, during Pangea stability and dispersal. In contrast, the period from 600 to 320g€Ma, nicknamed the zippy tricentenary here, displays twice the trench motion scatter compared to more recent times, reflecting a predominance of short and highly mobile subduction zones. Our model supports an orthoversion evolution from Rodinia to Pangea with Pangea offset approximately 90g eastwards relative to Rodinia - this is the opposite sense of motion compared to a previous orthoversion hypothesis based on paleomagnetic data. In our coupled plate-mantle model a broad network of basal mantle ridges forms between 1000 and 600g€Ma, reflecting widely distributed subduction zones. Between 600 and 500g€Ma a short-lived degree-2 basal mantle structure forms in response to a band of subduction zones confined to low latitudes, generating extensive antipodal lower mantle upwellings centred at the poles. Subsequently, the northern basal structure migrates southward and evolves into a Pacific-centred upwelling, while the southern structure is dissected by subducting slabs, disintegrating into a network of ridges between 500 and 400g€Ma. From 400 to 200g€Ma, a stable Pacific-centred degree-1 convective planform emerges. It lacks an antipodal counterpart due to the closure of the Iapetus and Rheic oceans between Laurussia and Gondwana as well as due to coeval subduction between Baltica and Laurentia and around Siberia, populating the mantle with slabs until 320g€Ma when Pangea is assembled. A basal degree-2 structure forms subsequent to Pangea breakup, after the influence of previously subducted slabs in the African hemisphere on the lowermost mantle structure has faded away. This succession of mantle states is distinct from previously proposed mantle convection models. We show that the history of plume-related volcanism is consistent with deep plumes associated with evolving basal mantle structures. This Solid Earth Evolution Model for the last 1000 million years (SEEM1000) forms the foundation for a multitude of spatio-temporal data analysis approaches

Deep learning-based survival prediction for multiple cancer types using histopathology images

Prognostic information at diagnosis has important implications for cancer treatment and monitoring. Although cancer staging, histopathological assessment, molecular features, and clinical variables can provide useful prognostic insights, improving risk stratification remains an active research area. We developed a deep learning system (DLS) to predict disease specific survival across 10 cancer types from The Cancer Genome Atlas (TCGA). We used a weakly-supervised approach without pixel-level annotations, and tested three different survival loss functions. The DLS was developed using 9,086 slides from 3,664 cases and evaluated using 3,009 slides from 1,216 cases. In multivariable Cox regression analysis of the combined cohort including all 10 cancers, the DLS was significantly associated with disease specific survival (hazard ratio of 1.58, 95% CI 1.28-1.70, p<0.0001) after adjusting for cancer type, stage, age, and sex. In a per-cancer adjusted subanalysis, the DLS remained a significant predictor of survival in 5 of 10 cancer types. Compared to a baseline model including stage, age, and sex, the c-index of the model demonstrated an absolute 3.7% improvement (95% CI 1.0-6.5) in the combined cohort. Additionally, our models stratified patients within individual cancer stages, particularly stage II (p=0.025) and stage III (p<0.001). By developing and evaluating prognostic models across multiple cancer types, this work represents one of the most comprehensive studies exploring the direct prediction of clinical outcomes using deep learning and histopathology images. Our analysis demonstrates the potential for this approach to provide prognostic information in multiple cancer types, and even within specific pathologic stages. However, given the relatively small number of clinical events, we observed wide confidence intervals, suggesting that future work will benefit from larger datasets