6,211 research outputs found
The 2-Dimensional Quantum Euclidean Algebra
The algebra dual to Woronowicz's deformation of the 2-\-di\-men\-sion\-al
Euclidean group is constructed. The same algebra is obtained from
via contraction on both the group and algebra levels.Comment: 8 pages, LBL-31711 and UCB-PTH-92/0
Reconfigurable ferromagnetic liquid droplets.
Solid ferromagnetic materials are rigid in shape and cannot be reconfigured. Ferrofluids, although reconfigurable, are paramagnetic at room temperature and lose their magnetization when the applied magnetic field is removed. Here, we show a reversible paramagnetic-to-ferromagnetic transformation of ferrofluid droplets by the jamming of a monolayer of magnetic nanoparticles assembled at the water-oil interface. These ferromagnetic liquid droplets exhibit a finite coercivity and remanent magnetization. They can be easily reconfigured into different shapes while preserving the magnetic properties of solid ferromagnets with classic north-south dipole interactions. Their translational and rotational motions can be actuated remotely and precisely by an external magnetic field, inspiring studies on active matter, energy-dissipative assemblies, and programmable liquid constructs
Ammonia oxidation at high pressure and intermediate temperatures
This article describes ammonia oxidation experiments conducted at high pressure (30 bar and 100 bar) under oxidizing and stoichiometric conditions, respectively, and temperatures ranging from 450 to 925 K
Def6 Is Required for Convergent Extension Movements during Zebrafish Gastrulation Downstream of Wnt5b Signaling
During gastrulation, convergent extension (CE) cell movements are regulated through the non-canonical Wnt signaling pathway. Wnt signaling results in downstream activation of Rho GTPases that in turn regulate actin cytoskeleton rearrangements essential for co-ordinated CE cell movement. Rho GTPases are bi-molecular switches that are inactive in their GDP-bound stage but can be activated to bind GTP through guanine nucleotide exchange factors (GEFs). Here we show that def6, a novel GEF, regulates CE cell movement during zebrafish gastrulation. Def6 morphants exhibit broadened and shortened body axis with normal cell fate specification, reminiscent of the zebrafish mutants silberblick and pipetail that lack Wnt11 or Wnt5b, respectively. Indeed, def6 morphants phenocopy Wnt5b mutants and ectopic overexpression of def6 essentially rescues Wnt5b morphants, indicating a novel role for def6 as a central GEF downstream of Wnt5b signaling. In addition, by knocking down both def6 and Wnt11, we show that def6 synergises with the Wnt11 signaling pathway
Dynamic Control Flow in Large-Scale Machine Learning
Many recent machine learning models rely on fine-grained dynamic control flow
for training and inference. In particular, models based on recurrent neural
networks and on reinforcement learning depend on recurrence relations,
data-dependent conditional execution, and other features that call for dynamic
control flow. These applications benefit from the ability to make rapid
control-flow decisions across a set of computing devices in a distributed
system. For performance, scalability, and expressiveness, a machine learning
system must support dynamic control flow in distributed and heterogeneous
environments.
This paper presents a programming model for distributed machine learning that
supports dynamic control flow. We describe the design of the programming model,
and its implementation in TensorFlow, a distributed machine learning system.
Our approach extends the use of dataflow graphs to represent machine learning
models, offering several distinctive features. First, the branches of
conditionals and bodies of loops can be partitioned across many machines to run
on a set of heterogeneous devices, including CPUs, GPUs, and custom ASICs.
Second, programs written in our model support automatic differentiation and
distributed gradient computations, which are necessary for training machine
learning models that use control flow. Third, our choice of non-strict
semantics enables multiple loop iterations to execute in parallel across
machines, and to overlap compute and I/O operations.
We have done our work in the context of TensorFlow, and it has been used
extensively in research and production. We evaluate it using several real-world
applications, and demonstrate its performance and scalability.Comment: Appeared in EuroSys 2018. 14 pages, 16 figure
QPACE 2 and Domain Decomposition on the Intel Xeon Phi
We give an overview of QPACE 2, which is a custom-designed supercomputer
based on Intel Xeon Phi processors, developed in a collaboration of Regensburg
University and Eurotech. We give some general recommendations for how to write
high-performance code for the Xeon Phi and then discuss our implementation of a
domain-decomposition-based solver and present a number of benchmarks.Comment: plenary talk at Lattice 2014, to appear in the conference proceedings
PoS(LATTICE2014), 15 pages, 9 figure
Different activation signatures in the primary sensorimotor and higher-level regions for haptic three-dimensional curved surface exploration
Haptic object perception begins with continuous exploratory contact, and the human brain needs to accumulate sensory information continuously over time. However, it is still unclear how the primary sensorimotor cortex (PSC) interacts with these higher-level regions during haptic exploration over time. This functional magnetic resonance imaging (fMRI) study investigates time-dependent haptic object processing by examining brain activity during haptic 3D curve and roughness estimations. For this experiment, we designed sixteen haptic stimuli (4 kinds of curves x 4 varieties of roughness) for the haptic curve and roughness estimation tasks. Twenty participants were asked to move their right index and middle fingers along the surface twice and to estimate one of the two features -roughness or curvature -depending on the task instruction. We found that the brain activity in several higher-level regions (e.g., the bilateral posterior parietal cortex) linearly increased as the number of curves increased during the haptic exploration phase. Surprisingly, we found that the contralateral PSC was parametrically modulated by the number of curves only during the late exploration phase but not during the early exploration phase. In contrast, we found no similar parametric modulation activity patterns during the haptic roughness estimation task in either the contralateral PSC or in higher-level regions. Thus, our findings suggest that haptic 3D object perception is processed across the cortical hierarchy, whereas the contralateral PSC interacts with other higher-level regions across time in a manner that is dependent upon the features of the object
Dual focus polarisation splitting lens
We have successfully designed and measured a unique polarisation splitting lens which focuses the orthogonal linear polarisations side-by-side in the lens focal plane. This concept can find application in situations where there is limited space for the beam splitters and focusing optics that are required for incoherent detectors
Shed urinary ALCAM is an independent prognostic biomarker of three-year overall survival after cystectomy in patients with bladder cancer.
Proteins involved in tumor cell migration can potentially serve as markers of invasive disease. Activated Leukocyte Cell Adhesion Molecule (ALCAM) promotes adhesion, while shedding of its extracellular domain is associated with migration. We hypothesized that shed ALCAM in biofluids could be predictive of progressive disease. ALCAM expression in tumor (n = 198) and shedding in biofluids (n = 120) were measured in two separate VUMC bladder cancer cystectomy cohorts by immunofluorescence and enzyme-linked immunosorbent assay, respectively. The primary outcome measure was accuracy of predicting 3-year overall survival (OS) with shed ALCAM compared to standard clinical indicators alone, assessed by multivariable Cox regression and concordance-indices. Validation was performed by internal bootstrap, a cohort from a second institution (n = 64), and treatment of missing data with multiple-imputation. While ALCAM mRNA expression was unchanged, histological detection of ALCAM decreased with increasing stage (P = 0.004). Importantly, urine ALCAM was elevated 17.0-fold (P < 0.0001) above non-cancer controls, correlated positively with tumor stage (P = 0.018), was an independent predictor of OS after adjusting for age, tumor stage, lymph-node status, and hematuria (HR, 1.46; 95% CI, 1.03-2.06; P = 0.002), and improved prediction of OS by 3.3% (concordance-index, 78.5% vs. 75.2%). Urine ALCAM remained an independent predictor of OS after accounting for treatment with Bacillus Calmette-Guerin, carcinoma in situ, lymph-node dissection, lymphovascular invasion, urine creatinine, and adjuvant chemotherapy (HR, 1.10; 95% CI, 1.02-1.19; P = 0.011). In conclusion, shed ALCAM may be a novel prognostic biomarker in bladder cancer, although prospective validation studies are warranted. These findings demonstrate that markers reporting on cell motility can act as prognostic indicators
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