'an actual present alive with multiple futures': Narrative, Memory and Time in Ben Lerner's "10:04"

This essay reads Ben Lerner’s second novel, 10:04, alongside contemporary accounts of narrative time and digital memory technologies, and argues that this narrative reflects on a shift in temporality, whereby present experience is increasingly relegated to future recollection. Bernard Stiegler provides a useful analysis of this situation, as his philosophical account of technics foregrounds memory’s reliance on technology, whereby the present is increasingly archived as a future memory. Stiegler also insists that every tool carries within itself a capacity for re-invention and projection into different futures, and this essay reads narrative form in this sense of an inventive technics capable of projecting us not into actual futures, but into a sense of future possibility. Lerner’s narrator may be read as seeking to open up the future by revisiting possibilities which his past self once imagined, and also by imagining future moments of retrospect from which he will one day have recounted his experience. It is in the mode of the anticipation of retrospection that a sense of the future is kept open in this novel, despite the temporally foreclosed structure of an already written narrative

Time resolving imaging spectroscopy applied to the analysis of plasmas generated by pulsed lasers

Start your abstract here... Time resolved imaging spectroscopy were used to study the spatial and temporal evolution of LIBS (Laser Induced Breakdown Spectroscopy) plasmas generated in Cu substrates by laser pulses of different duration. Long laser pulses (microsecond) and short laser pulses (nanosecond) as well as multipulse emission were used for excitation. Analysis was made by using an imaging spectrometer with time resolved detection. Results show that the use of long laser excitation pulses produce emission spectra with the same signal to noise ratio, but with lower resolution than those produced with shorter ones. The different species generated in LIBS experiments as neutral or single ionized have a different spatial distribution inside the plasma. We demonstrated that using spatial discrimination procedures is possible to obtain spectra with the same signal to noise ratio than those obtained with a gating detector. In this case an appreciable advantage in cost reduction is obtained by replacing the gating detector by a cheap screen.Facultad de Ingenierí

Time resolving imaging spectroscopy applied to the analysis of plasmas generated by pulsed lasers

Start your abstract here... Time resolved imaging spectroscopy were used to study the spatial and temporal evolution of LIBS (Laser Induced Breakdown Spectroscopy) plasmas generated in Cu substrates by laser pulses of different duration. Long laser pulses (microsecond) and short laser pulses (nanosecond) as well as multipulse emission were used for excitation. Analysis was made by using an imaging spectrometer with time resolved detection. Results show that the use of long laser excitation pulses produce emission spectra with the same signal to noise ratio, but with lower resolution than those produced with shorter ones. The different species generated in LIBS experiments as neutral or single ionized have a different spatial distribution inside the plasma. We demonstrated that using spatial discrimination procedures is possible to obtain spectra with the same signal to noise ratio than those obtained with a gating detector. In this case an appreciable advantage in cost reduction is obtained by replacing the gating detector by a cheap screen.Facultad de Ingenierí

Time resolving imaging spectroscopy applied to the analysis of plasmas generated by pulsed lasers

Start your abstract here... Time resolved imaging spectroscopy were used to study the spatial and temporal evolution of LIBS (Laser Induced Breakdown Spectroscopy) plasmas generated in Cu substrates by laser pulses of different duration. Long laser pulses (microsecond) and short laser pulses (nanosecond) as well as multipulse emission were used for excitation. Analysis was made by using an imaging spectrometer with time resolved detection. Results show that the use of long laser excitation pulses produce emission spectra with the same signal to noise ratio, but with lower resolution than those produced with shorter ones. The different species generated in LIBS experiments as neutral or single ionized have a different spatial distribution inside the plasma. We demonstrated that using spatial discrimination procedures is possible to obtain spectra with the same signal to noise ratio than those obtained with a gating detector. In this case an appreciable advantage in cost reduction is obtained by replacing the gating detector by a cheap screen.Facultad de Ingenierí

Implementing EM and Viterbi algorithms for Hidden Markov Model in linear memory

<p>Abstract</p> <p>Background</p> <p>The Baum-Welch learning procedure for Hidden Markov Models (HMMs) provides a powerful tool for tailoring HMM topologies to data for use in knowledge discovery and clustering. A linear memory procedure recently proposed by <it>Miklós, I. and Meyer, I.M. </it>describes a memory sparse version of the Baum-Welch algorithm with modifications to the original probabilistic table topologies to make memory use independent of sequence length (and linearly dependent on state number). The original description of the technique has some errors that we amend. We then compare the corrected implementation on a variety of data sets with conventional and checkpointing implementations.</p> <p>Results</p> <p>We provide a correct recurrence relation for the emission parameter estimate and extend it to parameter estimates of the Normal distribution. To accelerate estimation of the prior state probabilities, and decrease memory use, we reverse the originally proposed forward sweep. We describe different scaling strategies necessary in all real implementations of the algorithm to prevent underflow. In this paper we also describe our approach to a linear memory implementation of the Viterbi decoding algorithm (with linearity in the sequence length, while memory use is approximately independent of state number). We demonstrate the use of the linear memory implementation on an extended Duration Hidden Markov Model (DHMM) and on an HMM with a spike detection topology. Comparing the various implementations of the Baum-Welch procedure we find that the checkpointing algorithm produces the best overall tradeoff between memory use and speed. In cases where sequence length is very large (for Baum-Welch), or state number is very large (for Viterbi), the linear memory methods outlined may offer some utility.</p> <p>Conclusion</p> <p>Our performance-optimized Java implementations of Baum-Welch algorithm are available at <url>http://logos.cs.uno.edu/~achurban</url>. The described method and implementations will aid sequence alignment, gene structure prediction, HMM profile training, nanopore ionic flow blockades analysis and many other domains that require efficient HMM training with EM.</p

Duration learning for analysis of nanopore ionic current blockades

<p>Abstract</p> <p>Background</p> <p>Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications for DNA sequencing. The alpha-Hemolysin transmembrane channel interacts with a translocating molecule in a nontrivial way, frequently evidenced by a complex ionic flow blockade pattern. Typically, recorded current blockade signals have several levels of blockade, with various durations, all obeying a fixed statistical profile for a given molecule. Hidden Markov Model (HMM) based duration learning experiments on artificial two-level Gaussian blockade signals helped us to identify proper modeling framework. We then apply our framework to the real multi-level DNA hairpin blockade signal.</p> <p>Results</p> <p>The identified upper level blockade state is observed with durations that are geometrically distributed (consistent with an a physical decay process for remaining in any given state). We show that mixture of convolution chains of geometrically distributed states is better for presenting multimodal long-tailed duration phenomena. Based on learned HMM profiles we are able to classify 9 base-pair DNA hairpins with accuracy up to 99.5% on signals from same-day experiments.</p> <p>Conclusion</p> <p>We have demonstrated several implementations for <it>de novo </it>estimation of duration distribution probability density function with HMM framework and applied our model topology to the real data. The proposed design could be handy in molecular analysis based on nanopore current blockade signal.</p

Review of Person Re-identification Techniques

Person re-identification across different surveillance cameras with disjoint fields of view has become one of the most interesting and challenging subjects in the area of intelligent video surveillance. Although several methods have been developed and proposed, certain limitations and unresolved issues remain. In all of the existing re-identification approaches, feature vectors are extracted from segmented still images or video frames. Different similarity or dissimilarity measures have been applied to these vectors. Some methods have used simple constant metrics, whereas others have utilised models to obtain optimised metrics. Some have created models based on local colour or texture information, and others have built models based on the gait of people. In general, the main objective of all these approaches is to achieve a higher-accuracy rate and lowercomputational costs. This study summarises several developments in recent literature and discusses the various available methods used in person re-identification. Specifically, their advantages and disadvantages are mentioned and compared.Comment: Published 201

Computational identification of adaptive mutants using the VERT system

<p/> <p>Background</p> <p>Evolutionary dynamics of microbial organisms can now be visualized using the Visualizing Evolution in Real Time (VERT) system, in which several isogenic strains expressing different fluorescent proteins compete during adaptive evolution and are tracked using fluorescent cell sorting to construct a population history over time. Mutations conferring enhanced growth rates can be detected by observing changes in the fluorescent population proportions.</p> <p>Results</p> <p>Using data obtained from several VERT experiments, we construct a hidden Markov-derived model to detect these adaptive events in VERT experiments without external intervention beyond initial training. Analysis of annotated data revealed that the model achieves consensus with human annotation for 85-93% of the data points when detecting adaptive events. A method to determine the optimal time point to isolate adaptive mutants is also introduced.</p> <p>Conclusions</p> <p>The developed model offers a new way to monitor adaptive evolution experiments without the need for external intervention, thereby simplifying adaptive evolution efforts relying on population tracking. Future efforts to construct a fully automated system to isolate adaptive mutants may find the algorithm a useful tool.</p

Radio Interferometric Calibration Using The SAGE Algorithm

The aim of the new generation of radio synthesis arrays such as LOFAR and SKA is to achieve much higher sensitivity, resolution and frequency coverage than what is available now, especially at low frequencies. To accomplish this goal, the accuracy of the calibration techniques used is of considerable importance. Moreover, since these telescopes produce huge amounts of data, speed of convergence of calibration is a major bottleneck. The errors in calibration are due to system noise (sky and instrumental) as well as the estimation errors introduced by the calibration technique itself, which we call solver noise. We define solver noise as the distance between the optimal solution (the true value of the unknowns, uncorrupted by the system noise) and the solution obtained by calibration. We present the Space Alternating Generalized Expectation Maximization (SAGE) calibration technique, which is a modification of the Expectation Maximization algorithm, and compare its performance with the traditional Least Squares calibration based on the level of solver noise introduced by each technique. For this purpose, we develop statistical methods that use the calibrated solutions to estimate the level of solver noise. The SAGE calibration algorithm yields very promising results both in terms of accuracy and speed of convergence. The comparison approaches we adopt introduce a new framework for assessing the performance of different calibration schemes.Comment: 12 pages, 10 figures, Accepted for publication in MNRA

Effect of Grain Boundary Character Distribution on the Impact Toughness of 410NiMo Weld Metal

Grain boundary character distributions in 410NiMo weld metal were studied in the as-welded, first-stage, and second-stage postweld heat treatment (PWHT) conditions, and these were correlated with the Charpy-V impact toughness values of the material. The high impact toughness values in the weld metal in the as-welded and first-stage PWHT conditions compared to that in the second-stage condition are attributed to the higher fraction of low-energy I pound boundaries. A higher volume fraction of retained austenite and coarser martensite after second-stage PWHT accompanied by the formation of the ideal cube component in the 2-hour heat-treated specimen led to a reduction in the toughness value. A subsequent increase in the PWHT duration at 873 K (600 A degrees C) enhanced the formation of {111}aOE (c) 112 >, which impedes the adverse effect of the cubic component, resulting in an increase in the impact toughness. In addition to this, grain refinement during 4-hour PWHT in the second stage also increased the toughness of the weld metal