Snow metamorphism: a fractal approach

Snow is a porous disordered medium consisting of air and three water phases: ice, vapour and liquid. The ice phase consists of an assemblage of grains, ice matrix, initially arranged over a random load bearing skeleton. The quantitative relationship between density and morphological characteristics of different snow microstructures is still an open issue. In this work, a three-dimensional fractal description of density corresponding to different snow microstructure is put forward. First, snow density is simulated in terms of a generalized Menger sponge model. Then, a fully three-dimensional compact stochastic fractal model is adopted. The latter approach yields a quantitative map of the randomness of the snow texture, which is described as a three-dimensional fractional Brownian field with the Hurst exponent H varying as continuous parameter. The Hurst exponent is found to be strongly dependent on snow morphology and density. The approach might be applied to all those cases where the morphological evolution of snow cover or ice sheets should be conveniently described at a quantitative level

Measurement of trapped proton fluences in main stack of P0006 experiment

We have measured directional distribution and Eastward directed mission fluence of trapped protons at two different energies with plastic nuclear track detectors (CR-39 with DOP) in the main stack of the P0006 experiment on LDEF. Results show arriving directions of trapped protons have very high anisotropy with most protons arriving from the West direction. Selecting these particles we have determined the mission fluence of Eastward directed trapped protons. We found experimental fluences are slightly higher than results of the model calculations of Armstrong and Colborn

Antibiotic treatment-induced dysbiosis differently affects BDNF and TrkB expression in the brain and in the gut of juvenile mice

Antibiotic use during adolescence may result in dysbiosis-induced neuronal vulnerability both in the enteric nervous system (ENS) and central nervous system (CNS) contributing to the onset of chronic gastrointestinal disorders, such as irritable bowel syndrome (IBS), showing significant psychiatric comorbidity. Intestinal microbiota alterations during adolescence influence the expression of molecular factors involved in neuronal development in both the ENS and CNS. In this study, we have evaluated the expression of brain-derived neurotrophic factor (BDNF) and its high-affinity receptor tropomyosin-related kinase B (TrkB) in juvenile mice ENS and CNS, after a 2-week antibiotic (ABX) treatment. In both mucosa and mucosa-deprived whole-wall small intestine segments of ABX-treated animals, BDNF and TrKB mRNA and protein levels significantly increased. In longitudinal muscle-myenteric plexus preparations of ABX-treated mice the percentage of myenteric neurons staining for BDNF and TrkB was significantly higher than in controls. After ABX treatment, a consistent population of BDNF-and TrkB-immunoreactive neurons costained with SP and CGRP, suggesting up-regulation of BDNF signaling in both motor and sensory myenteric neurons. BDNF and TrkB protein levels were downregulated in the hippocampus and remained unchanged in the prefrontal cortex of ABX-treated animals. Immunostaining for BDNF and TrkB decreased in the hippocampus CA3 and dentate gyrus subregions, respectively, and remained unchanged in the prefrontal cortex. These data suggest that dysbiosis differentially influences the expression of BDNF-TrkB in the juvenile mice ENS and CNS. Such changes may potentially contribute later to the development of functional gut disorders, such as IBS, showing psychiatric comorbidity

Improving Phase Change Memory Performance with Data Content Aware Access

A prominent characteristic of write operation in Phase-Change Memory (PCM) is that its latency and energy are sensitive to the data to be written as well as the content that is overwritten. We observe that overwriting unknown memory content can incur significantly higher latency and energy compared to overwriting known all-zeros or all-ones content. This is because all-zeros or all-ones content is overwritten by programming the PCM cells only in one direction, i.e., using either SET or RESET operations, not both. In this paper, we propose data content aware PCM writes (DATACON), a new mechanism that reduces the latency and energy of PCM writes by redirecting these requests to overwrite memory locations containing all-zeros or all-ones. DATACON operates in three steps. First, it estimates how much a PCM write access would benefit from overwriting known content (e.g., all-zeros, or all-ones) by comprehensively considering the number of set bits in the data to be written, and the energy-latency trade-offs for SET and RESET operations in PCM. Second, it translates the write address to a physical address within memory that contains the best type of content to overwrite, and records this translation in a table for future accesses. We exploit data access locality in workloads to minimize the address translation overhead. Third, it re-initializes unused memory locations with known all-zeros or all-ones content in a manner that does not interfere with regular read and write accesses. DATACON overwrites unknown content only when it is absolutely necessary to do so. We evaluate DATACON with workloads from state-of-the-art machine learning applications, SPEC CPU2017, and NAS Parallel Benchmarks. Results demonstrate that DATACON significantly improves system performance and memory system energy consumption compared to the best of performance-oriented state-of-the-art techniques.Comment: 18 pages, 21 figures, accepted at ACM SIGPLAN International Symposium on Memory Management (ISMM

Thermochemistry of Alane Complexes for Hydrogen Storage: A Theoretical and Experimental Comparison

Knowledge of the relative stabilities of alane (AlH3) complexes with electron donors is essential for identifying hydrogen storage materials for vehicular applications that can be regenerated by off-board methods; however, almost no thermodynamic data are available to make this assessment. To fill this gap, we employed the G4(MP2) method to determine heats of formation, entropies, and Gibbs free energies of formation for thirty-eight alane complexes with NH3-nRn (R = Me, Et; n = 0-3), pyridine, pyrazine, triethylenediamine (TEDA), quinuclidine, OH2-nRn (R = Me, Et; n = 0-2), dioxane, and tetrahydrofuran (THF). Monomer, bis, and selected dimer complex geometries were considered. Using these data, we computed the thermodynamics of the key formation and dehydrogenation reactions that would occur during hydrogen delivery and alane regeneration, from which trends in complex stability were identified. These predictions were tested by synthesizing six amine-alane complexes involving trimethylamine, triethylamine, dimethylethylamine, TEDA, quinuclidine, and hexamine, and obtaining upper limits of delta G for their formation from metallic aluminum. Combining these computational and experimental results, we establish a criterion for complex stability relevant to hydrogen storage that can be used to assess potential ligands prior to attempting synthesis of the alane complex. Based on this, we conclude that only a subset of the tertiary amine complexes considered and none of the ether complexes can be successfully formed by direct reaction with aluminum and regenerated in an alane-based hydrogen storage system.Comment: Accepted by the Journal of Physical Chemistry

Large FHE Gates from tensored homomorphic accumulator

The main bottleneck of all known Fully Homomorphic Encryption schemes lies in the bootstrapping procedure invented by Gentry (STOC’09). The cost of this procedure can be mitigated either using Homomorphic SIMD techniques, or by performing larger computation per bootstrapping procedure.In this work, we propose new techniques allowing to perform more operations per bootstrapping in FHEW-type schemes (EUROCRYPT’13). While maintaining the quasi-quadratic Õ(n2) complexity of the whole cycle, our new scheme allows to evaluate gates with Ω(log n) input bits, which constitutes a quasi-linear speed-up. Our scheme is also very well adapted to large threshold gates, natively admitting up to Ω(n) inputs. This could be helpful for homomorphic evaluation of neural networks.Our theoretical contribution is backed by a preliminary prototype implementation, which can perform 6-to-6 bit gates in less than 10s on a single core, as well as threshold gates over 63 input bits even faster.<p

Quantitation of Cellular Dynamics in Growing Arabidopsis Roots with Light Sheet Microscopy

To understand dynamic developmental processes, living tissues must be imaged frequently and for extended periods of time. Root development is extensively studied at cellular resolution to understand basic mechanisms underlying pattern formation and maintenance in plants. Unfortunately, ensuring continuous specimen access, while preserving physiological conditions and preventing photo-damage, poses major barriers to measurements of cellular dynamics in indeterminately growing organs such as plant roots. We present a system that integrates optical sectioning through light sheet fluorescence microscopy with hydroponic culture that enables us to image at cellular resolution a vertically growing Arabidopsis root every few minutes and for several consecutive days. We describe novel automated routines to track the root tip as it grows, track cellular nuclei and identify cell divisions. We demonstrate the system's capabilities by collecting data on divisions and nuclear dynamics.Comment: * The first two authors contributed equally to this wor

Fast calculation of thermodynamic and structural parameters of solutions using the 3DRISM model and the multi-grid method

In the paper a new method to solve the tree-dimensional reference interaction site model (3DRISM) integral equations is proposed. The algorithm uses the multi-grid technique which allows to decrease the computational expanses. 3DRISM calculations for aqueous solutions of four compounds (argon, water, methane, methanol) on the different grids are performed in order to determine a dependence of the computational error on the parameters of the grid. It is shown that calculations on the grid with the step 0.05\Angstr and buffer 8\Angstr give the error of solvation free energy calculations less than 0.3 kcal/mol which is comparable to the accuracy of the experimental measurements. The performance of the algorithm is tested. It is shown that the proposed algorithm is in average more than 12 times faster than the standard Picard direct iteration method.Comment: the information in this preprint is not up to date. Since the first publication of the preprint (9 Nov 2011) the algorithm was modified which allowed to achieve better results. For the new algorithm see the JCTC paper: DOI: 10.1021/ct200815v, http://pubs.acs.org/doi/abs/10.1021/ct200815