Data reduction in the ITMS system through a data acquisition model with self-adaptive sampling rate

Long pulse or steady state operation of fusion experiments require data acquisition and processing systems that reduce the volume of data involved. The availability of self-adaptive sampling rate systems and the use of real-time lossless data compression techniques can help solve these problems. The former is important for continuous adaptation of sampling frequency for experimental requirements. The latter allows the maintenance of continuous digitization under limited memory conditions. This can be achieved by permanent transmission of compressed data to other systems. The compacted transfer ensures the use of minimum bandwidth. This paper presents an implementation based on intelligent test and measurement system (ITMS), a data acquisition system architecture with multiprocessing capabilities that permits it to adapt the system’s sampling frequency throughout the experiment. The sampling rate can be controlled depending on the experiment’s specific requirements by using an external dc voltage signal or by defining user events through software. The system takes advantage of the high processing capabilities of the ITMS platform to implement a data reduction mechanism based in lossless data compression algorithms which are themselves based in periodic deltas

Black Hole Emission in String Theory and the String Phase of Black Holes

String theory properly describes black-hole evaporation. The quantum string emission by Black Holes is computed. The black-hole temperature is the Hawking temperature in the semiclassical quantum field theory (QFT) regime and becomes the intrinsic string temperature, T_s, in the quantum (last stage) string regime. The QFT-Hawking temperature T_H is upper bounded by the string temperature T_S. The black hole emission spectrum is an incomplete gamma function of (T_H - T_S). For T_H << T_S, it yields the QFT-Hawking emission. For T_H \to T_S, it shows highly massive string states dominate the emission and undergo a typical string phase transition to a microscopic `minimal' black hole of mass M_{\min} or radius r_{\min} (inversely proportional to T_S) and string temperature T_S. The string back reaction effect (selfconsistent black hole solution of the semiclassical Einstein equations) is computed. Both, the QFT and string black hole regimes are well defined and bounded.The string `minimal' black hole has a life time tau_{min} simeq (k_B c)/(G hbar [T_S]^3). The semiclassical QFT black hole (of mass M and temperature T_H) and the string black hole (of mass M_{min} and temperature T_S) are mapped one into another by a `Dual' transform which links classical/QFT and quantum string regimes.Comment: LaTex, 22 pages, Lectures delivered at the Chalonge School, Nato ASI: Phase Transitions in the Early Universe: Theory and Observations. To appear in the Proceedings, Editors H. J. de Vega, I. Khalatnikov, N. Sanchez. (Kluwer Pub

Alleviating the non-ultralocality of coset sigma models through a generalized Faddeev-Reshetikhin procedure

The Faddeev-Reshetikhin procedure corresponds to a removal of the non-ultralocality of the classical SU(2) principal chiral model. It is realized by defining another field theory, which has the same Lax pair and equations of motion but a different Poisson structure and Hamiltonian. Following earlier work of M. Semenov-Tian-Shansky and A. Sevostyanov, we show how it is possible to alleviate in a similar way the non-ultralocality of symmetric space sigma models. The equivalence of the equations of motion holds only at the level of the Pohlmeyer reduction of these models, which corresponds to symmetric space sine-Gordon models. This work therefore shows indirectly that symmetric space sine-Gordon models, defined by a gauged Wess-Zumino-Witten action with an integrable potential, have a mild non-ultralocality. The first step needed to construct an integrable discretization of these models is performed by determining the discrete analogue of the Poisson algebra of their Lax matrices.Comment: 31 pages; v2: minor change

On the perturbative S-matrix of generalized sine-Gordon models

Motivated by its relation to the Pohlmeyer reduction of AdS_5 x S^5 superstring theory we continue the investigation of the generalized sine-Gordon model defined by SO(N+1)/SO(N) gauged WZW theory with an integrable potential. Extending our previous work (arXiv:0912.2958) we compute the one-loop two-particle S-matrix for the elementary massive excitations. In the N = 2 case corresponding to the complex sine-Gordon theory it agrees with the charge-one sector of the quantum soliton S-matrix proposed in hep-th/9410140. In the case of N > 2 when the gauge group SO(N) is non-abelian we find a curious anomaly in the Yang-Baxter equation which we interpret as a gauge artifact related to the fact that the scattered particles are not singlets under the residual global subgroup of the gauge group

On semiclassical approximation for correlators of closed string vertex operators in AdS/CFT

We consider the 2-point function of string vertex operators representing string state with large spin in AdS_5. We compute this correlator in the semiclassical approximation and show that it has the expected (on the basis of state-operator correspondence) form of the strong-coupling limit of the 2-point function of single trace minimal twist operators in gauge theory. The semiclassical solution representing the stationary point of the path integral with two vertex operator insertions is found to be related to the large spin limit of the folded spinning string solution by a euclidean continuation, transformation to Poincare coordinates and conformal map from cylinder to complex plane. The role of the source terms coming from the vertex operator insertions is to specify the parameters of the solution in terms of quantum numbers (dimension and spin) of the corresponding string state. Understanding further how similar semiclassical methods may work for 3-point functions may shed light on strong-coupling limit of the corresponding correlators in gauge theory as was recently suggested by Janik et al in arXiv:1002.4613.Comment: 19 pages, 1 figure; minor corrections, references added, footnote below eq. (4.5) adde

Series Solution and Minimal Surfaces in AdS

According to the Alday-Maldacena program the strong coupling limit of Super Yang-Mills scattering amplitudes is given by minimal area surfaces in AdS spacetime with a boundary consisting of a momentum space polygon. The string equations in AdS systematically reduce to coupled Toda type equations whose Euclidean classical solutions are then of direct relevance. While in the simplest case of AdS_3 exact solutions were known from earlier studies of the sinh-Gordon equation, there exist at present no similar exact forms for the generalized Toda equations related to AdS_d with d>=4. In this paper we develop a series method for the solution to those equations and evaluate their contribution to the finite piece of the worldsheet area. For the known sinh-Gordon case the method is seen to give results in excellent agreement with the exact answer.Comment: 19 pages, no figures; references added, one note adde

Paradigm of tunable clustering using binarization of consensus partition matrices (Bi-CoPaM) for gene discovery

Copyright @ 2013 Abu-Jamous et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Clustering analysis has a growing role in the study of co-expressed genes for gene discovery. Conventional binary and fuzzy clustering do not embrace the biological reality that some genes may be irrelevant for a problem and not be assigned to a cluster, while other genes may participate in several biological functions and should simultaneously belong to multiple clusters. Also, these algorithms cannot generate tight clusters that focus on their cores or wide clusters that overlap and contain all possibly relevant genes. In this paper, a new clustering paradigm is proposed. In this paradigm, all three eventualities of a gene being exclusively assigned to a single cluster, being assigned to multiple clusters, and being not assigned to any cluster are possible. These possibilities are realised through the primary novelty of the introduction of tunable binarization techniques. Results from multiple clustering experiments are aggregated to generate one fuzzy consensus partition matrix (CoPaM), which is then binarized to obtain the final binary partitions. This is referred to as Binarization of Consensus Partition Matrices (Bi-CoPaM). The method has been tested with a set of synthetic datasets and a set of five real yeast cell-cycle datasets. The results demonstrate its validity in generating relevant tight, wide, and complementary clusters that can meet requirements of different gene discovery studies.National Institute for Health Researc

Highly localized interactions between sensory neurons and sprouting sympathetic fibers observed in a transgenic tyrosine hydroxylase reporter mouse

<p>Abstract</p> <p>Background</p> <p>Sprouting of sympathetic fibers into sensory ganglia occurs in many preclinical pain models, providing a possible anatomical substrate for sympathetically enhanced pain. However, the functional consequences of this sprouting have been controversial. We used a transgenic mouse in which sympathetic fibers expressed green fluorescent protein, observable in live tissue. Medium and large diameter lumbar sensory neurons with and without nearby sympathetic fibers were recorded in whole ganglion preparations using microelectrodes.</p> <p>Results</p> <p>After spinal nerve ligation, sympathetic sprouting was extensive by 3 days. Abnormal spontaneous activity increased to 15% and rheobase was reduced. Spontaneously active cells had Aαβ conduction velocities but were clustered near the medium/large cell boundary. Neurons with sympathetic basket formations had a dramatically higher incidence of spontaneous activity (71%) and had lower rheobase than cells with no sympathetic fibers nearby. Cells with lower density nearby fibers had intermediate phenotypes. Immunohistochemistry of sectioned ganglia showed that cells surrounded by sympathetic fibers were enriched in nociceptive markers TrkA, substance P, or CGRP. Spontaneous activity began before sympathetic sprouting was observed, but blocking sympathetic sprouting on day 3 by cutting the dorsal ramus in addition to the ventral ramus of the spinal nerve greatly reduced abnormal spontaneous activity.</p> <p>Conclusions</p> <p>The data suggest that early sympathetic sprouting into the sensory ganglia may have highly localized, excitatory effects. Quantitatively, neurons with sympathetic basket formations may account for more than half of the observed spontaneous activity, despite being relatively rare. Spontaneous activity in sensory neurons and sympathetic sprouting may be mutually re-enforcing.</p

Environment, vector, or host? Using machine learning to untangle the mechanisms driving arbovirus outbreaks

Climatic, landscape, and host features are critical components in shaping out-breaks of vector-borne diseases. However, the relationship between the outbreaks of vector-borne pathogens and their environmental drivers is typically complicated, nonlinear, and mayvary by taxonomic units below the species level (e.g., strain or serotype). Here, we aim tountangle how these complex forces shape the risk of outbreaks of Bluetongue virus (BTV); avector-borne pathogen that is continuously emerging and re-emerging across Europe, with sev-ere economic implications. We tested if the ecological predictors of BTV outbreak risk wereserotype-specific by examining the most prevalent serotypes recorded in Europe (1, 4, and 8).We used a robust machine learning (ML) pipeline and 23 relevant environmental features to fitpredictive models to 24,245 outbreaks reported in 25 European countries between 2000 and2019. Our ML models demonstrated high predictive performance for all BTV serotypes (accu-racies>0.87) and revealed strong nonlinear relationships between BTV outbreak risk andenvironmental and host features. Serotype-specific analysis suggests, however, that each of themajor serotypes (1, 4, and 8) had a unique outbreak risk profile. For example, temperature andmidge abundance were as the most important characteristics shaping serotype 1, whereas forserotype 4 goat density and temperature were more important. We were also able to identifystrong interactive effects between environmental and host characteristics that were also sero-type specific. Our ML pipeline was able to reveal more in-depth insights into the complex epi-demiology of BTVs and can guide policymakers in intervention strategies to help reduce theeconomic implications and social cost of this important pathogen

Towards Safer Robot Motion: Using a Qualitative Motion Model to Classify Human-Robot Spatial Interaction

For adoption of Autonomous Mobile Robots (AMR) across a breadth of industries, they must navigate around humans in a way which is safe and which humans perceive as safe, but without greatly compromising efficiency. This work aims to classify the Human-Robot Spatial Interaction (HRSI) situation of an interacting human and robot, to be applied in Human-Aware Navigation (HAN) to account for situational context. We develop qualitative probabilistic models of relative human and robot movements in various HRSI situations to classify situations, and explain our plan to develop per-situation probabilistic models of socially legible HRSI to predict human and robot movement. In future work we aim to use these predictions to generate qualitative constraints in the form of metric cost-maps for local robot motion planners, enforcing more efficient and socially legible trajectories which are both physically safe and perceived as safe