307 research outputs found
Detection of p73 antibodies in patients with various types of cancer: immunological characterization
p53 antibodies have been found in the sera of patients with various types of cancer. The presence of these antibodies is generally associated with p53 accumulation in the tumour that is believed to trigger this humoral response. The recent discovery of 2 new members of the p53 family, p73 and p63, led us to study the specificity of this immune response towards the 3 proteins. Serum samples from 148 patients with various types of cancer were tested for antibodies against p73 and p63 using immunoprecipitation. 72 patients were previously shown to have p53 antibodies whereas 76 were negative. The control group consisted of 50 blood donors. p73 were detected in 22/148 (14.9%) of the cancer patients (11/72 in the group with p53-antibodies and 11/76 in the negative group). Only two sera from the control (4%) were positive. p63 antibodies were detected in only 4/148 (2.7%) of the cancer patients. Epitope mappings were performed and demonstrate that p73 antibodies are directed toward the central region of the p73 protein whereas p53 antibodies react predominantly toward the amino- and the carboxy-terminus of p53. Our results indicate that there is a specific immune response toward the p73 protein in cancer patients, a finding supported by an increasing number of publications describing p73 accumulation in tumoral cells. © 2001 Cancer Research Campaign http://www.bjcancer.co
Ground-truth prediction to accelerate soft-error impact analysis for iterative methods
Understanding the impact of soft errors on applications can be expensive. Often, it requires an extensive error injection campaign involving numerous runs of the full application in the presence of errors. In this paper, we present a novel approach to arriving at the ground truth-the true impact of an error on the final output-for iterative methods by observing a small number of iterations to learn deviations between normal and error-impacted execution. We develop a machine learning based predictor for three iterative methods to generate ground-truth results without running them to completion for every error injected. We demonstrate that this approach achieves greater accuracy than alternative prediction strategies, including three existing soft error detection strategies. We demonstrate the effectiveness of the ground truth prediction model in evaluating vulnerability and the effectiveness of soft error detection strategies in the context of iterative methods.This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research under Award Number 66905, program manager Lucy Nowell. Pacific Northwest National Laboratory is operated by Battelle for DOE under Contract DE-AC05-76RL01830.Peer ReviewedPostprint (author's final draft
Turkish Pediatric Rheumatology Society consensus statements on systemic onset juvenile idiopathic arthritis in Turkey
Implications of non-volatile memory as primary storage for database management systems
Traditional Database Management System (DBMS) software relies on hard disks for storing relational data. Hard disks are cheap, persistent, and offer huge storage capacities. However, data retrieval latency for hard disks is extremely high. To hide this latency, DRAM is used as an intermediate storage. DRAM is significantly faster than disk, but deployed in smaller capacities due to cost and power constraints, and without the necessary persistency feature that disks have. Non-Volatile Memory (NVM) is an emerging storage class technology which promises the best of both worlds. It can offer large storage capacities, due to better scaling and cost metrics than DRAM, and is non-volatile (persistent) like hard disks. At the same time, its data retrieval time is much lower than that of hard disks and it is also byte-addressable like DRAM. In this paper, we explore the implications of employing NVM as primary storage for DBMS. In other words, we investigate the modifications necessary to be applied on a traditional relational DBMS to take advantage of NVM features. As a case study, we have modified the storage engine (SE) of PostgreSQL enabling efficient use of NVM hardware. We detail the necessary changes and challenges such modifications entail and evaluate them using a comprehensive emulation platform. Results indicate that our modified SE reduces query execution time by up to 40% and 14.4% when compared to disk and NVM storage, with average reductions of 20.5% and 4.5%, respectively. © 2016 IEEE
Discretized Bayesian pursuit – A new scheme for reinforcement learning
The success of Learning Automata (LA)-based estimator algorithms over the classical, Linear Reward-Inaction ( L RI )-like schemes, can be explained by their ability to pursue the actions with the highest reward probability estimates. Without access to reward probability estimates, it makes sense for schemes like the L RI to first make large exploring steps, and then to gradually turn exploration into exploitation by making progressively smaller learning steps. However, this behavior becomes counter-intuitive when pursuing actions based on their estimated reward probabilities. Learning should then ideally proceed in progressively larger steps, as the reward probability estimates turn more accurate. This paper introduces a new estimator algorithm, the Discretized Bayesian Pursuit Algorithm (DBPA), that achieves this. The DBPA is implemented by linearly discretizing the action probability space of the Bayesian Pursuit Algorithm (BPA) [1]. The key innovation is that the linear discrete updating rules mitigate the counter-intuitive behavior of the corresponding linear continuous updating rules, by augmenting them with the reward probability estimates. Extensive experimental results show the superiority of DBPA over previous estimator algorithms. Indeed, the DBPA is probably the fastest reported LA to date
Domain Walls and Metastable Vacua in Hot Orientifold Field Theories
We consider "Orientifold field theories", namely SU(N) gauge theories with
Dirac fermions in the two-index representation at high temperature. When N is
even these theories exhibit a spontaneously broken Z2 centre symmetry. We study
aspects of the domain wall that interpolates between the two vacua of the
theory. In particular we calculate its tension to two-loop order. We compare
its tension to the corresponding domain wall in a SU(N) gauge theory with
adjoint fermions and find an agreement at large-N, as expected from planar
equivalence between the two theories. Moreover, we provide a non-perturbative
proof for the coincidence of the tensions at large-N. We also discuss the
vacuum structure of the theory when the fermion is given a large mass and argue
that there exist N-2 metastable vacua. We calculate the lifetime of those vacua
in the thin wall approximation.Comment: 29 pages, 4 figures. v2: minor changes in the introduction section.
to appear in JHE
Non-Perturbative Planar Equivalence and the Absence of Closed String Tachyons
We consider 'orbifold' and 'orientifold' field theories from the dual closed
string theory side. We argue that a necessary condition for planar equivalence
to hold is the absence of a closed string tachyonic mode in the dual
non-supersymmetric string. We analyze several gauge theories on R3xS1. In the
specific case of U(N) theories with symmetric/anti-symmetric fermions
('orientifold field theories') the relevant closed string theory is
tachyon-free at large compactification radius (due to winding modes), but it
develops a tachyonic mode below a critical radius. Our finding is with
agreement with field theory expectations of a phase transition from a C-parity
violating phase to a C-parity preserving phase as the compactification radius
increases. In the case of U(N)xU(N) theories with bi-fundamental matter
('orbifold field theories') a tachyon is always present in the string spectrum,
at any compactification radius. We conclude that on R4 planar equivalence holds
for 'orientfiold field theories', but fails for 'orbifold field theories'
daughters of N=4 SYM and suggest the same for daughters of N=1 SYM. We also
discuss examples of SO/Sp gauge theories with symmetric/anti-symmetric
fermions. In this case planar equivalence holds at any compactification radius
-in agreement with the absence of tachyons in the string dual.Comment: 14 pages, Latex. 3 eps figures. v2: ref. added. v3: clarifying
sentences added in the abstract and at the end of section 4. version accepted
to JHE
Towards lattice simulation of the gauge theory duals to black holes and hot strings
A generalization of the AdS/CFT conjecture postulates a duality between IIA
string theory and 16 supercharge Yang-Mills quantum mechanics in the large N 't
Hooft limit. At low temperatures string theory describes black holes, whose
thermodynamics may hence be studied using the dual quantum mechanics. This
quantum mechanics is strongly coupled which motivates the use of lattice
techniques. We argue that, contrary to expectation, the theory when discretized
naively will nevertheless recover continuum supersymmetry as the lattice
spacing is sent to zero. We test these ideas by studying the 4 supercharge
version of this Yang-Mills quantum mechanics in the 't Hooft limit. We use both
a naive lattice action and a manifestly supersymmetric action. Using Monte
Carlo methods we simulate the Euclidean theories, and study the lattice
continuum limit, for both thermal and non-thermal periodic boundary conditions,
confirming continuum supersymmetry is recovered for the naive action when
appropriate. We obtain results for the thermal system with N up to 12. These
favor the existence of a single deconfined phase for all non-zero temperatures.
These results are an encouraging indication that the 16 supercharge theory is
within reach using similar methods and resources.Comment: 49 pages, 14 figure
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