Inertial drag and lift forces for coarse grains on rough alluvial beds measured using in-grain accelerometers

Quantifying the force regime that controls the movement of a single grain during fluvial transport has historically proven to be difficult. Inertial micro-electromechanical system (MEMS) sensors (sensor assemblies that mainly comprise micro-accelerometers and gyroscopes) can used to address this problem using a “smart pebble”: a mobile inertial measurement unit (IMU) enclosed in a stone-like assembly that can measure directly the forces on a particle during sediment transport. Previous research has demonstrated that measurements using MEMS sensors can be used to calculate the dynamics of single grains over short time periods, despite limitations in the accuracy of the MEMS sensors that have been used to date. This paper develops a theoretical framework for calculating drag and lift forces on grains based on IMU measurements. IMUs were embedded a spherical and an ellipsoidal grain and used in flume experiments in which flow was increased until the grain moved. Acceleration measurements along three orthogonal directions were then processed to calculate the threshold force for entrainment, resulting in a statistical approximation of inertial impulse thresholds for both the lift and drag components of grain inertial dynamics. The ellipsoid IMU was also deployed in a series of experiments in a steep stream (Erlenbach, Switzerland). The inertial dynamics from both sets of experiments provide direct measurement of the resultant forces on sediment particles during transport, which quantifies (a) the effect of grain shape and (b) the effect of varied-intensity hydraulic forcing on the motion of coarse sediment grains during bedload transport. Lift impulses exert a significant control on the motion of the ellipsoid across hydraulic regimes, despite the occurrence of higher-magnitude and longer-duration drag impulses. The first-order statistical generalisation of the results suggests that the kinetics of the ellipsoid are characterised by low- or no-mobility states and that the majority of mobility states are controlled by lift impulses

Mass movement susceptibility mapping using satellite optical imagery compared with InSAR monitoring: Zigui County, Three Gorges region, China

Mass movements on steep slopes are a major hazard to communities and infrastructure in the Three Gorges region, China. Developing susceptibility maps of mass movements is therefore very important in both current and future land use planning. This study employed satellite optical imagery and an ASTER GDEM (15 m) to derive various parameters (namely geology; slope gradient; proximity to drainage networks and proximity to lineaments) in order to create a GIS-based map of mass movement susceptibility. This map was then evaluated using highly accurate deformation signals processed using the Persistent Scatterer (PS) InSAR technique. Areas of high susceptibility correspond well to points of high subsidence, which provides a strong support of our susceptibility map

A microphysiological model of bone development and regeneration

Endochondral ossification (EO) is an essential biological process than underpins how human bones develop, grow, and heal in the event of a fracture. So much is unknown about this process, thus clinical manifestations of dysregulated EO cannot be adequately treated. This can be partially attributed to the absence of predictive in vitro models of musculoskeletal tissue development and healing, which are integral to the development and preclinical evaluation of novel therapeutics. Microphysiological systems, or organ-on-chip devices, are advanced in vitro models designed for improved biological relevance compared to traditional in vitro culture models. Here we develop a microphysiological model of vascular invasion into developing/regenerating bone, thereby mimicking the process of EO. This is achieved by integrating endothelial cells and organoids mimicking different stages of endochondral bone development within a microfluidic chip. This microphysiological model is able to recreate key events in EO, such as the changing angiogenic profile of a maturing cartilage analogue, and vascular induced expression of the pluripotent transcription factors SOX2 and OCT4 in the cartilage analogue. This system represents an advanced in vitro platform to further EO research, and may also serve as a modular unit to monitor drug responses on such processes as part of a multi-organ system

Evaluating sub-pixel offset techniques as an alternative to D-InSAR for monitoring episodic landslide movements in vegetated terrain

Spaceborne Synthetic Aperture Radar (SAR) sensors obtain regular and frequent radar images from which ground motion can be precisely detected using a variety of different techniques. The ability to measure slope displacements remotely over large regions can have many uses, although the limitations of the most commonplace technique, differential InSAR (D-InSAR), must be considered prior to interpreting the final results. One such limitation is the assumption that different rates of movement over a given distance cannot exceed a threshold value, dependent upon the pixel spacing of the SAR images and the radar wavelength. Characteristic features of landslides (i.e. the sharp boundary between stable/active ground and the range of temporally-variable velocities) can exhibit high spatial displacement gradients, breaking a fundamental assumption for reliable D-InSAR analysis. Areas of low coherence are also known to hinder the exploitation of InSAR data. This study assesses the capability of TerraSAR-X Spotlight, TerraSAR-X Stripmap and Envisat Stripmap images for monitoring the slow-moving Shuping landslide in the densely vegetated Three Gorges region, China. In this case study, the episodic nature of movement is shown to exceed the measurable limit for regular D-InSAR analysis even for the highest resolution 11-day TSX Spotlight interferograms. A Sub-Pixel Offset Time-series technique applied to corner reflectors (SPOT-CR) using only the SAR amplitude information is applied as a robust method of resolving time-varying displacements, with verifiable offset measurements presented from TSX Spotlight and TSX Stripmap imagery. Care should be exercised when measuring potentially episodic landslide movements in densely vegetated areas such as the Three Gorges region and corner reflectors are shown to be highly useful for SPOT techniques even when the assumptions for valid D-InSAR analysis are broken. Finally the capability to derive two-dimensional movements from sub-pixel offsets (in range and along-track directions) can be used to derive estimates of the vertical and northwards movements to help infer the landslide failure mechanism

Nutrition-Related Factors and the Progression of Metabolic Syndrome Characteristics over Time in Older Adults: Analysis of the TUDA Cohort

Metabolic syndrome (MetS) is associated with an increased risk of cardiovascular disease and type 2 diabetes mellitus by an estimated two- and five-fold, respectively. Nutrition intervention could help to prevent the progression of MetS and associated pathologies with age, but the precise dietary components and related factors are not well understood. Therefore, the aim of this study was to evaluate the role of nutrition-related factors in MetS as well as the progression of MetS and its components over a 7-year follow-up period in older adults. This investigation involved the secondary analysis of data from the North–South of Ireland Trinity-Ulster-Department of Agriculture (TUDA) study of community-dwelling older adults (≥60 y), which were sampled at baseline (2008–2012; n = 5186) and follow-up (2015–2018; n = 953). Participants were deemed to have MetS if they met at least three of the following criteria: waist circumference (≥102 cm for males, ≥88 cm for females); HDL cholesterol (<1.0 mmol/L for males, <1.3 mmol/L for females); triglycerides (≥1.7 mmol/L); blood pressure (systolic ≥ 130 and/or diastolic ≥ 85 mmHg); and HbA1c (≥39 mmol/mol). The prevalence of MetS increased with advancing age (67% at baseline vs. 74% at follow-up). The factors at baseline that were predictive of a higher MetS risk at follow-up included waist circumference (OR 1.04, 95% CI 1.00–1.08; p = 0.038) and triglycerides (OR 1.77, 95% CI 1.21–2.59; p = 0.003). In a detailed dietary analysis conducted at the follow-up time point, higher protein intake (g/kg body weight) was associated with a lower risk of MetS (OR 0.06, 95% CI 0.02–0.20; p < 0.001), abdominal obesity (OR 0.10, 95% CI 0.02–0.51; p = 0.006), and hypertension (OR 0.022, 95% CI 0.00–0.80; p = 0.037), and a higher MUFA intake (g/day) was associated with a lower risk of MetS (OR 0.88, 95% CI 0.78–1.00; p = 0.030). No other dietary factors were significantly associated with MetS. In terms of protein quality, participants with MetS compared to those without consumed fewer high-quality protein foods (p = 0.009) and consumed more low-quality protein foods (p < 0.001). Dietary intervention along with other strategies focusing on potentially modifiable risk factors may delay the progression of MetS in older adults. Efforts to enhance the quantity and quality of protein intake may be warranted to reduce MetS in certain at-risk groups

Inter-annual river patterns change detection using machine learning

Copyright © Author(s) 2022. River patterns in the tropics usually exhibit seasonal changes because of strongly seasonal rainfall and its impact on geomorphological processes. However, studies on tropical rivers are much less than those on temperate rivers, and so these seasonal patterns have not been quantified. To fill some of this research gap, this paper employs machine learning methods using Sentinel-2 multispectral remote sensing images to classify geomorphological units in Bislak River, Laoag River and Abra River in west Luzon, the Philippines. In this study, we firstly designed a workflow for river pattern classification, which was validated for the three rivers at different spatial and temporal scales. Then, 5.5 years of river patterns, defined using three morphological units, in the three rivers were generated for further geomorphological analysis. The classification results were analysed in terms of both spatial and temporal aspects. The results show a variety of relationships between channel width and each landform unit (wetted channel; exposed sediment bar; vegetated bar). The analysis shows that channel width has an impact on the area occupied by vegetation (the bigger the river, the stronger the correlation between channel width and vegetation). We present a way to analyse interactions between geomorphic units at seasonal scales using time series of correlations. The rivers were divided into sub-reaches based on observed patterns of water frequency and confinement, and then temporal analysis was undertaken for each sub-reach. This analysis used Ensemble Empirical Mode Decomposition (EEMD) which decomposed the time series and precipitation. The EEMD results indicate that areas occupied by water and vegetation commonly show synchronised fluctuations with precipitation, while sediment bars have an anti-phase oscillation with precipitation. The results suggests that deviations from periodic consistency in patterns may reflect the influence of extreme events and/or human disturbance. Correlation results show that the total area of unvegetated bars is usually the most stable landform unit in all three rivers, and that the vegetated area changes less in narrower channels. Confinement, due to hillslope and terrace topography, and the impact of fault are also considered. The methods for generating time series of landform unit data and time series analysis used here provide a framework for analysis of tropical rivers that are subject to regular, frequent and dynamic changes of planform