The Andes Cordillera, which runs the length of South America and rises up to 5,000 m MSL within 200 km of the Pacific coast, dramatically influences the distribution of winter precipitation and snowpack over Chile and Argentina. The study of orographic precipitation processes, particularly along the western slopes of the Andes, is important to improve forecasts of severe flooding and snowpack in a region that depends on snowmelt for water resources. While orographic effects have been investigated on synoptic scales in the Andes, the lack of operational radar coverage and high-elevation, long-term precipitation records have, before the present study, precluded an in-depth investigation into the mesoscale and microphysical processes that affect the distribution of precipitation in the region.
This dataset was collected during the Chilean Orographic and Mesoscale Precipitation Study (ChOMPS), which, from May-October 2016, investigated the evolution of precipitation amounts, dropsize distribution, and the vertical profile of radar echoes along an east-west transect that stretched from the Pacific coast to the windward slope of the Andes. The transect, at ~36°S, was made up of a coastal site upstream of the coastal mountain range (Concepción), a central valley site (Chillán), and a mountain site (Las Trancas). Instrumentation along the transect included three vertically pointing Micro-Rain-Radars, two Parsivel Disdrometers, and several meteorological stations.
The dataset documents the evolution of Doppler velocity and reflectivity profiles with inland extent during early, middle, and late storm sectors. Additionally, the transect provides a season-long record of the inland evolution of melting layer height as well as the prevalence and structure of shallow non-brightband rain and the characteristics of its inland penetration to the central valley. This dataset, the first of its kind in the Chilean Andes, provides unique insight into mesoscale and orographic precipitation processes that also have applicability to the west coast of the United States and other mountainous regions.
The dynamic properties of freestanding rock landforms are a function of fundamental material and mechanical parameters, facilitating non-invasive vibration-based structural assessment. Characterization of resonant frequencies, mode shapes, and damping ratios, however, can be challenging at culturally-sensitive geologic features, such as rock arches, where physical access is limited. Using sparse ambient vibration measurements, we describe three resonant modes between 1 and 40 Hz for 17 natural arches in Utah spanning a range of lengths from 3 – 88 m. Modal polarization data are evaluated to combine field observations with 3-D numerical models. We find outcrop-scale elastic moduli vary from 0.8 to 8.0 GPa, correlated with diagenetic processes, and identify low damping at all sites. Dense-array cross-correlation results from an additional arch validate predictions of simple bending modes and fixed boundary conditions. Our results establish use of sparse ambient resonance measurements for structural assessment and monitoring of arches and similar freestanding geologic features.
Light-scattering spectroscopy (LSS) is an established optical approach for nondestructive characterization of biological tissue. Here, we investigated the capabilities of LSS and convolutional neural networks (CNNs) to quantitatively characterize the composition and arrangement of cardiac tissues. We assembled tissue constructs from 200 µm thick sections of fixed right ventricular myocardium and aortic wall. In the assembled constructs, the aortic sections represented fibrotic tissue and the depth and volume fraction of these fibrotic insets were varied. We gathered spectra from the constructs at multiple locations relative to a light source. We used single and combinations of two spectra for training of CNNs. With independently measured spectra, we assessed the accuracy of the trained CNNs for classification of tissue constructs from single spectra and combined spectra. Classification accuracy with single spectra was smaller than with combined spectra. Overall classification accuracy was highest (mean ± standard deviation: 94.17±8.0%) for combined spectra from collection fibers most proximal to and distal from the illumination. Our studies demonstrate the reliability of quantitative characterization of tissue composition and arrangements using a combination of LSS and CNNs. Potential clinical applications of the developed approach include intraoperative quantification of atrial fibrosis and identification of conduction tissue in the heart.
Subglacial water pressures influence groundwater conditions in proximal alpine valley rock slopes, varying with glacier advance and retreat in parallel with changing ice thickness. Fluctuating groundwater pressures in turn increase or reduce effective joint normal stresses, affecting the yield strength of discontinuities. Here we extend simplified assumptions of glacial debuttressing to investigate how glacier loading cycles together with changing groundwater pressures generate rock slope damage and prepare future slope instabilities. Using hydromechanical coupled numerical models closely based on the Aletsch Glacier valley in Switzerland, we simulate Late Pleistocene and Holocene glacier loading cycles including long-term and annual groundwater fluctuations. Measurements of transient subglacial water pressures from ice boreholes in the Aletsch Glacier ablation area, as well as continuous monitoring of bedrock deformation from permanent GNSS stations helps verify our model assumptions. While purely mechanical glacier loading cycles create only limited rock slope damage in our models, introducing a fluctuating groundwater table generates substantial new fracturing. Superposed annual groundwater cycles increase predicted damage. The cumulative effects are capable of destabilizing the eastern valley flank of our model in toppling-mode failure, similar to field observations of active landslide geometry and kinematics. We find that hydromechanical fatigue is most effective acting in combination with long-term loading and unloading of the slope during glacial cycles. Our results demonstrate that hydromechanical stresses associated with glacial cycles are capable of generating substantial rock slope damage and represent a key preparatory factor for paraglacial slope instabilities.
Background: The objective of this study was to evaluate the effect of utilising larger lens cubes on phacoemulsification efficiency and chatter using 3 tips of different sizes and 2 ultrasound (US) approaches.
Methods: This was an in vitro laboratory study conducted at the John A. Moran Eye Center Laboratory, University of Utah, Salt Lake City, UT, USA. Porcine lens nuclei were formalin-soaked for 2 hours, then divided into either 2.0 mm or 3.0 mm cubes. 30 degree bent 19 G, 20 G, and 21 G tips were used with a continuous torsional US system; and straight 19 G, 20 G, and 21 G tips were used with a micropulse longitudinal US system. Efficiency and chatter were determined.
Results: Mean phacoemulsification removal time was higher with the 3.0 mm lens cube for all US variations and tip sizes. There were statistically significant differences between the 19 G and 21 G tips with micropulse longitudinal US using the 2.0 mm lens cube and the 3.0 mm lens cube, as well as with continuous transversal US using the 2.0 mm lens cube and the 3.0 mm lens cube. There was no significant difference between 19 G and 20 G tips with either lens cube size in either US approach. However, using both US approaches, trends were identical for both lens cube sizes in which the 19 G tips performed better than the 20 G and 21 G tips.
Conclusion: Regardless of lens size, the 19 G needle was the most efficient, with the fewest outliers and smallest standard deviations.
Localization of the components of the cardiac conduction system (CCS) is essential for many therapeutic procedures in cardiac surgery and interventional cardiology. While histological studies provided fundamental insights into CCS localization, this information is incomplete and difficult to translate to aid in intraprocedural localization. To advance our understanding of CCS localization, we set out to establish a framework for quantifying nodal region morphology. Using this framework, we quantitatively analyzed the sinoatrial node (SAN) and atrioventricular node (AVN) in ovine with menstrual age ranging from 4.4 to 58.3 months. In particular, we studied the SAN and AVN in relation to the epicardial and endocardial surfaces, respectively. Using anatomical landmarks, we excised the nodes and adjacent tissues, sectioned those at a thickness of 4 µm at 100 µm intervals, and applied Masson’s trichrome stain to the sections. These sections were then imaged, segmented to identify nodal tissue, and analyzed to quantify nodal depth and superficial tissue composition. The minimal SAN depth ranged between 20 and 926 µm. AVN minimal depth ranged between 59 and 1192 µm in the AVN extension region, 49 and 980 µm for the compact node, and 148 and 888 µm for the transition to His Bundle region. Using a logarithmic regression model, we found that minimal depth increased logarithmically with age for the AVN (R2=0.818, P=0.002). Also, the myocardial overlay of the AVN was heterogeneous within different regions and decreased with increasing age. Age associated alterations of SAN minimal depth were insignificant. Our study presents examples of characteristic tissue patterns superficial to the AVN and within the SAN. We suggest that the presented framework provides quantitative information for CCS localization. Our studies indicate that procedural methods and localization approaches in regions near the AVN should account for the age of patients in cardiac surgery and interventional cardiology.
: Forests play a major role in the global carbon cycle. Previous studies on the capacity of forests to sequester atmospheric CO2 have mostly focused on carbon uptake, but the roles of carbon turnover time and its spatiotemporal changes remain poorly understood. Here, we used long-term inventory data (1955-2018) from 695 mature forest plots to quantify temporal trends in living vegetation carbon turnover time across tropical, temperate, and cold climate zones, and compared plot data to eight Earth system models (ESMs). Long-term plots consistently showed decreases in living vegetation carbon turnover time, likely driven by increased tree mortality across all major climate zones. Changes in living vegetation carbon turnover time were negatively correlated with CO2 enrichment in both forest plot data and ESM simulations. However, plot-based correlations between living vegetation carbon turnover time and climate drivers such as precipitation and temperature diverged from those of ESM simulations. Our analyses suggest that forest carbon sinks are likely to be constrained by a decrease in living vegetation carbon turnover time, and accurate projections of forest carbon sink dynamics will require an improved representation of tree mortality processes and their sensitivity to climate in ESMs.
Future projections suggest an increase in drought globally with climate change. Current vegetation models typically regulate the plant photosynthetic response to soil moisture stress through an empirical function, rather than a mechanistic response where plant water potentials respond to changes in soil water. This representation of soil moisture stress may introduce significant uncertainty into projections for the terrestrial carbon cycle. We examined the use of the soil moisture limitation function in historical and future emissions scenarios in nine Earth system models. We found that soil moisture-limited productivity across models represented a large and uncertain component of the simulated carbon cycle, comparable to 3-286% of current global productivity. Approximately 40-80% of the intermodel variability was due to the functional form of the limitation equation alone. Our results highlight the importance of implementing mechanistic water limitation schemes in models and illuminate several avenues for improving projections of the land carbon sink.