Natural and laser-induced cavitation in corn stems: On the mechanisms of acoustic emissions

Water in plant xylem is often superheated, and therefore in a meta-stable state. Under certain conditions, it may suddenly turn from the liquid to the vapor state. This cavitation process produces acoustic emissions. We report the measurement of ultrasonic acoustic emissions (UAE) produced by natural and induced cavitation in corn stems. We induced cavitation and UAE in vivo, in well controlled and reproducible experiments, by irradiating the bare stem of the plants with a continuous-wave laser beam. By tracing the source of UAE, we were able to detect absorption and frequency filtering of the UAE propagating through the stem. This technique allows the unique possibility of studying localized embolism of plant conduits, and thus to test hypotheses on the hydraulic architecture of plants. Based on our results, we postulate that the source of UAE is a transient "cavity oscillation" triggered by the disruptive effect of cavitation inception.Comment: 8 pages, 5 figure

Enhancement of photoacoustic detection of inhomogeneities in polymers

We report a series of experiments on laser pulsed photoacoustic excitationin turbid polymer samples addressed to evaluate the sound speed in the samples and the presence of inhomogeneities in the bulk. We describe a system which allows the direct measurement of the speed of the detected waves by engraving the surface of the piece under study with a fiduciary pattern of black lines. We also describe how this pattern helps to enhance the sensitivity for the detection of an inhomogeneity in the bulk. These two facts are useful for studies in soft matter systems including, perhaps, biological samples. We have performed an experimental analysis on Grilon(R) samples in different situations and we show the limitations of the method.Comment: 8 pages, 7 figure

Photoacoustic characterization of transient defects in potassium dihydrogen phosphate crystals

Transient defects in potassium dihydrogen phosphate ͑KDP͒ were characterized by using the acoustic signals generated in the crystal when it is impinged with pulsed laser radiation. These defects are produced by simultaneous absorption of two ϭ266 nm photons and they show linear absorption in the visible and UV spectral region. The decay kinetics of the defects has been studied by a new method based on the analysis of the acoustic signal generated by visible pulses. The acoustic measurement of the decay time shows a nonexponential decay and it is free from thermal lensing or beam deformation by other causes, effects that can alter the pure optical measurements. We propose that the origin of the photoacoustic signal is the heat released by the deexcitation of the energy levels of the defects when they are excited by visible pulses. This mechanism, optical absorption and nonradiative relaxation of defects, could be the reason for some depletion in the yield of several devices based on KDP. This phenomena must be carefully taken in account, when KDP crystals are used in combination with Nd:YAG ͑YAG, yttrium aluminum garnet͒ lasers for second-harmonic generation from ϭ532 nm to ϭ266 nm

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

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

Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data

Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. Complimentary large data sets of in situ RNA hybridization images for different stages of the fly embryo elucidate the spatial expression patterns. Results: Using a semi-supervised approach, constrained clustering with mixture models, we can find clusters of genes exhibiting spatio-temporal similarities in expression, or syn-expression. The temporal gene expression measurements are taken as primary data for which pairwise constraints are computed in an automated fashion from raw in situ images without the need for manual annotation. We investigate the influence of these pairwise constraints in the clustering and discuss the biological relevance of our results. Conclusion: Spatial information contributes to a detailed, biological meaningful analysis of temporal gene expression data. Semi-supervised learning provides a flexible, robust and efficient framework for integrating data sources of differing quality and abundance

Phase transition in Random Circuit Sampling

Quantum computers hold the promise of executing tasks beyond the capability of classical computers. Noise competes with coherent evolution and destroys long-range correlations, making it an outstanding challenge to fully leverage the computation power of near-term quantum processors. We report Random Circuit Sampling (RCS) experiments where we identify distinct phases driven by the interplay between quantum dynamics and noise. Using cross-entropy benchmarking, we observe phase boundaries which can define the computational complexity of noisy quantum evolution. We conclude by presenting an RCS experiment with 70 qubits at 24 cycles. We estimate the computational cost against improved classical methods and demonstrate that our experiment is beyond the capabilities of existing classical supercomputers

Detection of recurrent copy number alterations in the genome: taking among-subject heterogeneity seriously

Se adjunta un fichero pdf con los datos de investigación titulado "Supplementary Material for \Detection of Recurrent Copy Number Alterations in the Genome: taking among-subject heterogeneity seriously"Background: Alterations in the number of copies of genomic DNA that are common or recurrent among diseased individuals are likely to contain disease-critical genes. Unfortunately, defining common or recurrent copy number alteration (CNA) regions remains a challenge. Moreover, the heterogeneous nature of many diseases requires that we search for common or recurrent CNA regions that affect only some subsets of the samples (without knowledge of the regions and subsets affected), but this is neglected by most methods. Results: We have developed two methods to define recurrent CNA regions from aCGH data. Our methods are unique and qualitatively different from existing approaches: they detect regions over both the complete set of arrays and alterations that are common only to some subsets of the samples (i.e., alterations that might characterize previously unknown groups); they use probabilities of alteration as input and return probabilities of being a common region, thus allowing researchers to modify thresholds as needed; the two parameters of the methods have an immediate, straightforward, biological interpretation. Using data from previous studies, we show that we can detect patterns that other methods miss and that researchers can modify, as needed, thresholds of immediate interpretability and develop custom statistics to answer specific research questions. Conclusion: These methods represent a qualitative advance in the location of recurrent CNA regions, highlight the relevance of population heterogeneity for definitions of recurrence, and can facilitate the clustering of samples with respect to patterns of CNA. Ultimately, the methods developed can become important tools in the search for genomic regions harboring disease-critical genesFunding provided by Fundación de Investigación Médica Mutua Madrileña. Publication charges covered by projects CONSOLIDER: CSD2007-00050 of the Spanish Ministry of Science and Innovation and by RTIC COMBIOMED RD07/0067/0014 of the Spanish Health Ministr