Backwater effects of piers and abutments

Prepared by the Civil Engineering Section, Colorado State University, Fort Collins, Colo. in cooperation with the U.S. Dept. of Commerce, Bureau of Public Roads.October 1957.CER57HKL10.Bibliography: pages 299-302

The Sunyaev-Zel'dovich Effect by Cocoons of Radio Galaxies

We estimate the deformation of the cosmic microwave background radiation by the hot region (``cocoon'') around a radio galaxy. A simple model is adopted for cocoon evolution while the jet is on, and a model of evolution is constructed after the jet is off. It is found that at low redshift the phase after the jet is off is longer than the lifetime of the jets. The Compton y-parameter generated by cocoons is calculated with a Press-Schechter number density evolution. The resultant value of y is of the same order as the COBE constraint. The Sunyaev-Zeldovich effect due to cocoons could therefore be a significant foreground source of small angular scale anisotropies in the cosmic microwave background radiation.Comment: Published version, 23 pages with 5 figure

Room temperature spin-orbit torque switching induced by a topological insulator

Recent studies on the magneto-transport properties of topological insulators (TI) have attracted great attention due to the rich spin-orbit physics and promising applications in spintronic devices. Particularly the strongly spin-moment coupled electronic states have been extensively pursued to realize efficient spin-orbit torque (SOT) switching. However, so far current-induced magnetic switching with TI has only been observed at cryogenic temperatures. It remains a controversial issue whether the topologically protected electronic states in TI could benefit spintronic applications at room temperature. In this work, we report full SOT switching in a TI/ferromagnet bilayer heterostructure with perpendicular magnetic anisotropy at room temperature. The low switching current density provides a definitive proof on the high SOT efficiency from TI. The effective spin Hall angle of TI is determined to be several times larger than commonly used heavy metals. Our results demonstrate the robustness of TI as an SOT switching material and provide a direct avenue towards applicable TI-based spintronic devices

Functional analysis of the theobroma cacao NPR1 gene in arabidopsis

<p>Abstract</p> <p>Background</p> <p>The <it>Arabidopsis thaliana NPR1 </it>gene encodes a transcription coactivator (NPR1) that plays a major role in the mechanisms regulating plant defense response. After pathogen infection and in response to salicylic acid (SA) accumulation, NPR1 translocates from the cytoplasm into the nucleus where it interacts with other transcription factors resulting in increased expression of over 2000 plant defense genes contributing to a pathogen resistance response.</p> <p>Results</p> <p>A putative <it>Theobroma cacao NPR1 </it>cDNA was isolated by RT-PCR using degenerate primers based on homologous sequences from <it>Brassica</it>, <it>Arabidopsis </it>and <it>Carica papaya</it>. The cDNA was used to isolate a genomic clone from <it>Theobroma cacao </it>containing a putative <it>TcNPR1 </it>gene. DNA sequencing revealed the presence of a 4.5 kb coding region containing three introns and encoding a polypeptide of 591 amino acids. The predicted TcNPR1 protein shares 55% identity and 78% similarity to <it>Arabidopsis </it>NPR1, and contains each of the highly conserved functional domains indicative of this class of transcription factors (BTB/POZ and ankyrin repeat protein-protein interaction domains and a nuclear localization sequence (NLS)). To functionally define the <it>TcNPR1 </it>gene, we transferred <it>TcNPR1 </it>into an <it>Arabidopsis npr1 </it>mutant that is highly susceptible to infection by the plant pathogen <it>Pseudomonas syringae </it>pv. tomato DC3000. Driven by the constitutive CaMV35S promoter, the cacao <it>TcNPR1 </it>gene partially complemented the <it>npr1 </it>mutation in transgenic <it>Arabidopsis </it>plants, resulting in 100 fold less bacterial growth in a leaf infection assay. Upon induction with SA, <it>TcNPR1 </it>was shown to translocate into the nucleus of leaf and root cells in a manner identical to <it>Arabidopsis </it>NPR1. Cacao NPR1 was also capable of participating in SA-JA signaling crosstalk, as evidenced by the suppression of JA responsive gene expression in <it>TcNPR1 </it>overexpressing transgenic plants.</p> <p>Conclusion</p> <p>Our data indicate that the <it>TcNPR1 </it>is a functional ortholog of <it>Arabidopsis NPR1</it>, and is likely to play a major role in defense response in cacao. This fundamental knowledge can contribute to breeding of disease resistant cacao varieties through the application of molecular markers or the use of transgenic strategies.</p

Classical confinement of test particles in higher-dimensional models: stability criteria and a new energy condition

We review the circumstances under which test particles can be localized around a spacetime section \Sigma_0 smoothly contained within a codimension-1 embedding space M. If such a confinement is possible, \Sigma_0 is said to be totally geodesic. Using three different methods, we derive a stability condition for trapped test particles in terms of intrinsic geometrical quantities on \Sigma_0 and M; namely, confined paths are stable against perturbations if the gravitational stress-energy density on M is larger than that on \Sigma_0, as measured by an observed travelling along the unperturbed trajectory. We confirm our general result explicitly in two different cases: the warped-product metric ansatz for (n+1)-dimensional Einstein spaces, and a known solution of the 5-dimensional vacuum field equation embedding certain 4-dimensional cosmologies. We conclude by defining a confinement energy condition that can be used to classify geometries incorporating totally geodesic submanifolds, such as those found in thick braneworld and other 5-dimensional scenarios.Comment: 9 pages, REVTeX4, in press in Phys. Rev.

Development and validation of a deep learning model to quantify glomerulosclerosis in kidney biopsy specimens

Importance: A chronic shortage of donor kidneys is compounded by a high discard rate, and this rate is directly associated with biopsy specimen evaluation, which shows poor reproducibility among pathologists. A deep learning algorithm for measuring percent global glomerulosclerosis (an important predictor of outcome) on images of kidney biopsy specimens could enable pathologists to more reproducibly and accurately quantify percent global glomerulosclerosis, potentially saving organs that would have been discarded. Objective: To compare the performances of pathologists with a deep learning model on quantification of percent global glomerulosclerosis in whole-slide images of donor kidney biopsy specimens, and to determine the potential benefit of a deep learning model on organ discard rates. Design, Setting, and Participants: This prognostic study used whole-slide images acquired from 98 hematoxylin-eosin-stained frozen and 51 permanent donor biopsy specimen sections retrieved from 83 kidneys. Serial annotation by 3 board-certified pathologists served as ground truth for model training and for evaluation. Images of kidney biopsy specimens were obtained from the Washington University database (retrieved between June 2015 and June 2017). Cases were selected randomly from a database of more than 1000 cases to include biopsy specimens representing an equitable distribution within 0% to 5%, 6% to 10%, 11% to 15%, 16% to 20%, and more than 20% global glomerulosclerosis. Main Outcomes and Measures: Correlation coefficient (r) and root-mean-square error (RMSE) with respect to annotations were computed for cross-validated model predictions and on-call pathologists\u27 estimates of percent global glomerulosclerosis when using individual and pooled slide results. Data were analyzed from March 2018 to August 2020. Results: The cross-validated model results of section images retrieved from 83 donor kidneys showed higher correlation with annotations (r = 0.916; 95% CI, 0.886-0.939) than on-call pathologists (r = 0.884; 95% CI, 0.825-0.923) that was enhanced when pooling glomeruli counts from multiple levels (r = 0.933; 95% CI, 0.898-0.956). Model prediction error for single levels (RMSE, 5.631; 95% CI, 4.735-6.517) was 14% lower than on-call pathologists (RMSE, 6.523; 95% CI, 5.191-7.783), improving to 22% with multiple levels (RMSE, 5.094; 95% CI, 3.972-6.301). The model decreased the likelihood of unnecessary organ discard by 37% compared with pathologists. Conclusions and Relevance: The findings of this prognostic study suggest that this deep learning model provided a scalable and robust method to quantify percent global glomerulosclerosis in whole-slide images of donor kidneys. The model performance improved by analyzing multiple levels of a section, surpassing the capacity of pathologists in the time-sensitive setting of examining donor biopsy specimens. The results indicate the potential of a deep learning model to prevent erroneous donor organ discard

Combined TRPC3 and TRPC6 blockade by selective small-molecule or genetic deletion inhibits pathological cardiac hypertrophy

Chronic neurohormonal and mechanical stresses are central fea-tures of heart disease. Increasing evidence supports a role forthe transient receptor potential canonical channels TRPC3 andTRPC6 in this pathophysiology. Channel expression for both is nor-mally very low but is increased by cardiac disease, and geneticgain- or loss-of-function studies support contributions to hypertro-phy and dysfunction. Selective small-molecule inhibitors remainscarce, and none target both channels, which may be useful giventhe high homology among them and evidence of redundant sig-naling. Here we tested selective TRPC3/6 antagonists (GSK2332255Band GSK2833503A; IC50,3–21 nM against TRPC3 and TRPC6) andfound dose-dependent blockade of cell hypertrophy signaling trig-gered by angiotensin II or endothelin-1 in HEK293T cells as well as inneonatal and adult cardiac myocytes. In vivo efficacy in mice andrats was greatly limited by rapid metabolism and high protein bind-ing, although antifibrotic effects with pressure overload were ob-served. Intriguingly, although gene deletion of TRPC3 or TRPC6alone did not protect against hypertrophy or dysfunction frompressure overload, combined deletion was protective, support-ing the value of dual inhibition. Further development of thispharmaceutical class may yield a useful therapeutic agent forheart disease management.Fil: Seo, Kinya. Johns Hopkins Medical Institutions. Department of Medicine; Estados UnidosFil: Rainer, Peter P.. Johns Hopkins Medical Institutions. Department of Medicine; Estados Unidos. Medical University of Graz. Department of Medicine; AustriaFil: Shalkey Hahn, Virginia. Johns Hopkins Medical Institutions. Department of Medicine; Estados UnidosFil: Lee, Dong-ik. Johns Hopkins Medical Institutions. Department of Medicine; Estados UnidosFil: Jo, Su-Hyun. Kangwon National University School of Medicine; Corea del Sur. Johns Hopkins Medical Institutions. Department of Medicine; Estados UnidosFil: Andersen, Asger. Aarhus University Hospital. Department of Cardiology; DinamarcaFil: Liu, Ting. Johns Hopkins Medical Institutions. Department of Medicine; Estados UnidosFil: Xu, Xiaoping. GlaxoSmithKline Heart Failure Discovery Performance Unit; Estados UnidosFil: Willette, Robert N.. GlaxoSmithKline Heart Failure Discovery Performance Unit; Estados UnidosFil: Lepore, John J.. GlaxoSmithKline Heart Failure Discovery Performance Unit; Estados UnidosFil: Marino, Joseph P.. GlaxoSmithKline Heart Failure Discovery Performance Unit; Estados UnidosFil: Birnbaumer, Lutz. ational Institute of Environmental Health Sciences; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Biomédicas; ArgentinaFil: Schnackenberg, Christine G.. GlaxoSmithKline Heart Failure Discovery Performance Unit; Estados UnidosFil: Kass, David A.. Johns Hopkins Medical Institutions. Department of Medicine; Estados Unido

The Reliability of Parafoveal Cone Density Measurements

Background Adaptive optics scanning light ophthalmoscopy (AOSLO) enables direct visualisation of the cone mosaic, with metrics such as cone density and cell spacing used to assess the integrity or health of the mosaic. Here we examined the interobserver and inter-instrument reliability of cone density measurements. Methods For the interobserver reliability study, 30 subjects with no vision-limiting pathology were imaged. Three image sequences were acquired at a single parafoveal location and aligned to ensure that the three images were from the same retinal location. Ten observers used a semiautomated algorithm to identify the cones in each image, and this was repeated three times for each image. To assess inter-instrument reliability, 20 subjects were imaged at eight parafoveal locations on one AOSLO, followed by the same set of locations on the second AOSLO. A single observer manually aligned the pairs of images and used the semiautomated algorithm to identify the cones in each image. Results Based on a factorial study design model and a variance components model, the interobserver study\u27s largest contribution to variability was the subject (95.72%) while the observer\u27s contribution was only 1.03%. For the inter-instrument study, an average cone density intraclass correlation coefficient (ICC) of between 0.931 and 0.975 was calculated. Conclusions With the AOSLOs used here, reliable cone density measurements can be obtained between observers and between instruments. Additional work is needed to determine how these results vary with differences in image quality