A topological realization of the congruence subgroup Kernel A

A number of years ago, Kumar Murty pointed out to me that the computation of the fundamental group of a Hilbert modular surface ([7],IV,${\S}$6), and the computation of the congruence subgroup kernel of SL(2) ([6]) were surprisingly similar. We puzzled over this, in particular over the role of elementary matrices in both computations. We formulated a very general result on the fundamental group of a Satake compactification of a locally symmetric space. This lead to our joint paper [1] with Lizhen Ji and Les Saper on these fundamental groups. Although the results in it were intriguingly similar to the corresponding calculations of the congruence subgroup kernel of the underlying algebraic group in [5], we were not able to demonstrate a direct connection (cf. [1], ${\S}$7). The purpose of this note is to explain such a connection. A covering space is constructed from inverse limits of reductive Borel-Serre compactifications. The congruence subgroup kernel then appears as the group of deck transformations of this covering. The key to this is the computation of the fundamental group in [1]

Atmospheric rivers contribution to the snow accumulation over the southern Andes (26.5° S–37.5° S)

This paper quantifies the climatological contribution of atmospheric rivers (ARs) to annual snow accumulation in the Andes Cordillera between 26.5° S and 36.5° S. An AR identification algorithm, and a high-resolution (0.01°) snow reanalysis dataset, both especially developed for this mountainous region, are used for this quantification over the 1984–2014 period. Results show that AR snowfall events explain approximately 50% of the annual snow accumulation over the study area, and are 2.5 times more intense than non-AR snowfall events. Due to orographic precipitation enhancement on the western slopes and a prominent rain shadow effect on the eastern slopes, annual snow accumulation and AR storms contribution to this accumulation are, on average, 7 and 12 times larger on western than on eastern slopes of the mountain range, respectively. Areas with lower peak elevations see more spillover snowfall over the eastern slopes of the mountain range, especially south of 35° S. Analysis of teleconnections with El Niño Southern Oscillation shows a reduction in the AR frequency across the study area during La Niña episodes and, consequently, a lower contribution to snow accumulation. Conversely, weak and moderate El Niño episodes show an increase in AR frequency, and consequently more snowfall.Fil: Saavedra, Felipe. Universidad de Chile; ChileFil: Cortés, Gonzalo. Centro Tecnológico del Agua; ChileFil: Viale, Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Margulis, Steven. University of California at Los Angeles; Estados UnidosFil: McPhee, James. Universidad de Chile; Chil

Evaluation of the Snow CCI Snow Covered Area Product within a Mountain Snow Water Equivalent Reanalysis

An accurate characterization of global snow water equivalent (SWE) is essential in the study of climate and water resources. The current global SWE dataset from the European Space Agency Snow Climate Change Initiative is derived from the assimilation of passive microwave satellite data and in situ snow depth measurements. However, gaps exist in the current Snow CCI SWE dataset in complex terrain due to difficulties in characterizing mountain SWE via the passive microwave sensing approach and limitations of the in situ snow depth measurements. This study applies a Bayesian snow reanalysis approach with the existing Snow CCI snow cover fraction (SCF) dataset (1 km resolution) to develop a SWE dataset over four mountainous domains in Western North America for WYs 2001–2019. The reanalysis SWE estimates are evaluated through comparisons with independent SWE datasets, and a parallel SWE reanalysis generated using snow extent retrieved from Landsat imagery (30 m resolution). Biases in Snow CCI reanalysis SWE were diagnosed by comparing Snow CCI snow cover with the Landsat reference. Both the number of SCF images and their characteristics (such as zenith angle) significantly affect the accuracy of SWE estimation. Overall, the Snow CCI SCF inputs produce reanalysis SWE of sufficient quality to fill the mountain SWE gap in the current Snow CCI SWE climate data record. A better characterization of the SCF uncertainty and a bias correction could further improve the accuracy of the reanalysis SWE estimates

Remote Sensing Of The Cryosphere In High Mountain Asia

High Mountain Asia (HMA), often referred to as the "third pole" of the world because its high elevation glaciers, contains the largest amount of fresh water outside the polar ice sheets. The region's hydrology is strongly controlled by variations in the timing and distribution of runoff from snow and glacier melt. Recent improvements in remote sensing technologies and atmospheric / land surface models provides new approaches for assessing the HMA cryosphere. A recently-funded NASA program aims to apply these tools to advance understanding of HMA cryospheric processes. Here we present an overview of planned team activities during the three-year project

The future of human nature: a symposium on the promises and challenges of the revolutions in genomics and computer science, April 10, 11, and 12, 2003

This repository item contains a single issue of the Pardee Conference Series, a publication series that began publishing in 2006 by the Boston University Frederick S. Pardee Center for the Study of the Longer-Range Future. This was the Center's Symposium on the Promises and Challenges of the Revolutions in Genomics and Computer Science took place during April 10, 11, and 12, 2003. Co-organized by Charles DeLisi and Kenneth Lewes; sponsored by Boston University, the Frederick S. Pardee Center for the Study of the Longer-Range Future.This conference focused on scientific and technological advances in genetics, computer science, and their convergence during the next 35 to 250 years. In particular, it focused on directed evolution, the futures it allows, the shape of society in those futures, and the robustness of human nature against technological change at the level of individuals, groups, and societies. It is taken as a premise that biotechnology and computer science will mature and will reinforce one another. During the period of interest, human cloning, germ-line genetic engineering, and an array of reproductive technologies will become feasible and safe. Early in this period, we can reasonably expect the processing power of a laptop computer to exceed the collective processing power of every human brain on the planet; later in the period human/machine interfaces will begin to emerge. Whether such technologies will take hold is not known. But if they do, human evolution is likely to proceed at a greatly accelerated rate; human nature as we know it may change markedly, if it does not disappear altogether, and new intelligent species may well be created

Estimation of Seasonal Snow Water Equivalent Using Landsat Observations

This work presents a methodology for estimating seasonal snow water equivalent (SWE) from the use of remotely sensed Visible and Near Infrared observations from the Landsat mission. The method is comprised of two main components: (1) a coupled land surface model and snow depletion curve model, which is used to generate an ensemble of predictions of SWE and snow cover area for a given set of (uncertain) inputs, and (2) a reanalysis step, which updates estimation variables to be consistent with the satellite observed depletion of the fractional snow cover time series. This method was applied over the Sierra Nevada (USA) based on the assimilation of remotely sensed fractional snow covered area data over the Landsat 5-8 record (1985-2016). The verified dataset (based on a comparison with over 9000 station years of in situ data) exhibited mean and root-mean-square errors less than 3 and 13 cm, respectively, and correlations with in situ SWE observations of greater than 0.95. The method (fully Bayesian), resolution (daily, 90-meter), temporal extent (32 years), and accuracy provide a unique dataset for investigating snow processes. In particular, this presentation illustrates how the reanalysis dataset was used to provide climatology of the seasonal snowfall accumulation rates, distributions, and variability over the last three decades

The future of human nature: a symposium on the promises and challenges of the revolutions in genomics and computer science, April 10, 11, and 12, 2003

This repository item contains a single issue of the Pardee Conference Series, a publication series that began publishing in 2006 by the Boston University Frederick S. Pardee Center for the Study of the Longer-Range Future. This was the Center's Symposium on the Promises and Challenges of the Revolutions in Genomics and Computer Science took place during April 10, 11, and 12, 2003. Co-organized by Charles DeLisi and Kenneth Lewes; sponsored by Boston University, the Frederick S. Pardee Center for the Study of the Longer-Range Future.This conference focused on scientific and technological advances in genetics, computer science, and their convergence during the next 35 to 250 years. In particular, it focused on directed evolution, the futures it allows, the shape of society in those futures, and the robustness of human nature against technological change at the level of individuals, groups, and societies. It is taken as a premise that biotechnology and computer science will mature and will reinforce one another. During the period of interest, human cloning, germ-line genetic engineering, and an array of reproductive technologies will become feasible and safe. Early in this period, we can reasonably expect the processing power of a laptop computer to exceed the collective processing power of every human brain on the planet; later in the period human/machine interfaces will begin to emerge. Whether such technologies will take hold is not known. But if they do, human evolution is likely to proceed at a greatly accelerated rate; human nature as we know it may change markedly, if it does not disappear altogether, and new intelligent species may well be created

Objective Characterization of Snow Microstructure for Microwave Emission Modeling

Passive microwave (PM) measurements are sensitive to the presence and quantity of snow, a fact that has long been used to monitor snowcover from space. In order to estimate total snow water equivalent (SWE) within PM footprints (on the order of approx 100 sq km), it is prerequisite to understand snow microwave emission at the point scale and how microwave radiation integrates spatially; the former is the topic of this paper. Snow microstructure is one of the fundamental controls on the propagation of microwave radiation through snow. Our goal in this study is to evaluate the prospects for driving the Microwave Emission Model of Layered Snowpacks with objective measurements of snow specific surface area to reproduce measured brightness temperatures when forced with objective measurements of snow specific surface area (S). This eliminates the need to treat the grain size as a free-fit parameter

Potential function for the Huntingtin protein as a scaffold for selective autophagy

Although dominant gain-of-function triplet repeat expansions in the Huntingtin (HTT) gene are the underlying cause of Huntington disease (HD), understanding the normal functions of nonmutant HTT protein has remained a challenge. We report here findings that suggest that HTT plays a significant role in selective autophagy. Loss of HTT function in Drosophila disrupts starvation-induced autophagy in larvae and conditional knockout of HTT in the mouse CNS causes characteristic cellular hallmarks of disrupted autophagy, including an accumulation of striatal p62/SQSTM1 over time. We observe that specific domains of HTT have structural similarities to yeast Atg proteins that function in selective autophagy, and in particular that the C-terminal domain of HTT shares structural similarity to yeast Atg11, an autophagic scaffold protein. To explore possible functional similarity between HTT and Atg11, we investigated whether the C-terminal domain of HTT interacts with mammalian counterparts of yeast Atg11-interacting proteins. Strikingly, this domain of HTT coimmunoprecipitates with several key Atg11 interactors, including the Atg1/Unc-51–like autophagy activating kinase 1 kinase complex, autophagic receptor proteins, and mammalian Atg8 homologs. Mutation of a phylogenetically conserved WXXL domain in a C-terminal HTT fragment reduces coprecipitation with mammalian Atg8 homolog GABARAPL1, suggesting a direct interaction. Collectively, these data support a possible central role for HTT as an Atg11-like scaffold protein. These findings have relevance to both mechanisms of disease pathogenesis and to therapeutic intervention strategies that reduce levels of both mutant and normal HTT.Hereditary Disease Foundation (U.S.)Cure Huntington’s Disease Initiative, Inc.Fox Family Foundatio