2,546 research outputs found

    Versatile Dye Laser Generator-Amplifier System for Intense Tunable Picosecond Pulse Generation

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    Abstract. Passively mode-locked ruby-laser pulses are used to generate nearly diffraction-limited picosecond light pulses in a dye cell by longitudinally amplified spontaneous emission. The output pulses are amplified in three longitudinally pumped dye cells, then spectrally filtered with a grating spectrometer and finally reamplified in a fourth dye amplifier in order to generate intense frequency tunable picosecond light pulses. PACS: 42.55M, 42.60 Various pulsed dye laser systems are available for tunable picosecond pulse generation [1, 2]. Flash-lamp pumped mode-locked dye lasers [3], synchron-ously pumped lasers [4], short-cavity resonators [5], quenched transient lasers [6], distributed feedback lasers [7], and amplified spontaneous emission sys-tems [8] have been investigated. The arrangements applying amplified spontaneous emission (ASE) may be grouped into longitudinall

    barx1 is necessary for ectomesenchyme proliferation and osteochondroprogenitor condensation in the zebrafish pharyngeal arches

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    AbstractBarx1 modulates cellular adhesion molecule expression and participates in specification of tooth-types, but little is understood of its role in patterning the pharyngeal arches. We examined barx1 expression during zebrafish craniofacial development and performed a functional analysis using antisense morpholino oligonucleotides. Barx1 is expressed in the rhombencephalic neural crest, the pharyngeal arches, the pectoral fin buds and the gut in contrast to its paralogue barx2, which is most prominently expressed in the arch epithelium. Additionally, barx1 transient expression was observed in the posterior lateral line ganglia and developing trunk/tail. We show that Barx1 is necessary for proliferation of the arch osteochondrogenic progenitors, and that morphants exhibit diminished and dysmorphic arch cartilage elements due to reductions in chondrocyte differentiation and condensation. Attenuation of Barx1 results in lost arch expression of osteochondrogenic markers col2a1, runx2a and chondromodulin, as well as odontogenic marker dlx2b. Further, loss of barx1 positively influenced gdf5 and chordin, markers of jaw joint patterning. FGF signaling is required for maintaining barx1 expression, and that ectopic BMP4 induces expression of barx1 in the intermediate region of the second pharyngeal arch. Together, these results indicate an essential role for barx1 at early stages of chondrogenesis within the developing zebrafish viscerocranium

    The role of the basic state in the ENSO-monsoon relationship and implications for predictability

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    The impact of systematic model errors on a coupled simulation of the Asian Summer monsoon and its interannual variability is studied. Although the mean monsoon climate is reasonably well captured, systematic errors in the equatorial Pacific mean that the monsoon-ENSO teleconnection is rather poorly represented in the GCM. A system of ocean-surface heat flux adjustments is implemented in the tropical Pacific and Indian Oceans in order to reduce the systematic biases. In this version of the GCM, the monsoon-ENSO teleconnection is better simulated, particularly the lag-lead relationships in which weak monsoons precede the peak of El Nino. In part this is related to changes in the characteristics of El Nino, which has a more realistic evolution in its developing phase. A stronger ENSO amplitude in the new model version also feeds back to further strengthen the teleconnection. These results have important implications for the use of coupled models for seasonal prediction of systems such as the monsoon, and suggest that some form of flux correction may have significant benefits where model systematic error compromises important teleconnections and modes of interannual variability

    Stroke lesion size:Still a useful biomarker for stroke severity and outcome in times of high-dimensional models

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    BACKGROUND The volumetric size of a brain lesion is a frequently used stroke biomarker. It stands out among most imaging biomarkers for being a one-dimensional variable that is applicable in simple statistical models. In times of machine learning algorithms, the question arises of whether such a simple variable is still useful, or whether high-dimensional models on spatial lesion information are superior. METHODS We included 753 first-ever anterior circulation ischemic stroke patients (age 68.4±15.2 years; NIHSS at 24 h 4.4±5.1; modified Rankin Scale (mRS) at 3-months median[IQR] 1[0.75;3]) and traced lesions on diffusion-weighted MRI. In an out-of-sample model validation scheme, we predicted stroke severity as measured by NIHSS 24 h and functional stroke outcome as measured by mRS at 3 months either from spatial lesion features or lesion size. RESULTS For stroke severity, the best regression model based on lesion size performed significantly above chance (p < 0.0001) with R2 = 0.322, but models with spatial lesion features performed significantly better with R2 = 0.363 (t(752) = 2.889; p = 0.004). For stroke outcome, the best classification model based on lesion size again performed significantly above chance (p < 0.0001) with an accuracy of 62.8%, which was not different from the best model with spatial lesion features (62.6%, p = 0.80). With smaller training data sets of only 150 or 50 patients, the performance of high-dimensional models with spatial lesion features decreased up to the point of being equivalent or even inferior to models trained on lesion size. The combination of lesion size and spatial lesion features in one model did not improve predictions. CONCLUSIONS Lesion size is a decent biomarker for stroke outcome and severity that is slightly inferior to spatial lesion features but is particularly suited in studies with small samples. When low-dimensional models are desired, lesion size provides a viable proxy biomarker for spatial lesion features, whereas high-precision prediction models in personalised prognostic medicine should operate with high-dimensional spatial imaging features in large samples

    Application of MJO Simulation Diagnostics to Climate Models

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    The ability of eight climate models to simulate the Madden-Julian oscillation (MJO) is examined using diagnostics developed by the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group. Although the MJO signal has been extracted throughout the annual cycle, this study focuses on the boreal winter (November-April) behavior. Initially, maps of the mean state and variance and equatorial space-time spectra of 850-hPa zonal wind and precipitation are compared with observations. Models best represent the intraseasonal space-time spectral peak in the zonal wind compared to that of precipitation. Using the phase-space representation of the multivariate principal components (PCs), the life cycle properties of the simulated MJOs are extracted, including the ability to represent how the MJO evolves from a given subphase and the associated decay time scales. On average, the MJO decay (e-folding) time scale for all models is shorter (~20- 29 days) than observations (~31 days). All models are able to produce a leading pair of multivariate principal components that represents eastward propagation of intraseasonal wind and precipitation anomalies, although the fraction of the variance is smaller than observed for all models. In some cases, the dominant time scale of these PCs is outside of the 30-80-day band. Several key variables associated with the model's MJO are investigated, including the surface latent heat flux, boundary layer (925 hPa) moisture convergence, and the vertical structure of moisture. Low-level moisture convergence ahead (east) of convection is associated with eastward propagation in most of the models. A few models are also able to simulate the gradual moistening of the lower troposphere that precedes observed MJO convection, as well as the observed geographical difference in the vertical structure of moisture associated with the MJO. The dependence of rainfall on lower tropospheric relative humidity and the fraction of rainfall that is stratiform are also discussed, including implications these diagnostics have for MJO simulation. Based on having the most realistic intraseasonal multivariate empirical orthogonal functions, principal component power spectra, equatorial eastward propagating outgoing longwave radiation (OLR), latent heat flux, low-level moisture convergence signals, and vertical structure of moisture over the Eastern Hemisphere, the superparameterized Community Atmosphere Model (SPCAM) and the ECHAM4/Ocean Isopycnal Model (OPYC) show the best skill at representing the MJO.open1149

    Some , And Possibly All, Scalar Inferences Are Not Delayed: Evidence For Immediate Pragmatic Enrichment

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    Scalar inferences are commonly generated when a speaker uses a weaker expression rather than a stronger alternative, e.g., John ate some of the apples implies that he did not eat them all. This article describes a visual-world study investigating how and when perceivers compute these inferences. Participants followed spoken instructions containing the scalar quantifier some directing them to interact with one of several referential targets (e.g., Click on the girl who has some of the balloons). Participants fixated on the target compatible with the implicated meaning of some and avoided a competitor compatible with the literal meaning prior to a disambiguating noun. Further, convergence on the target was as fast for some as for the non-scalar quantifiers none and all. These findings indicate that the scalar inference is computed immediately and is not delayed relative to the literal interpretation of some. It is argued that previous demonstrations that scalar inferences increase processing time are not necessarily due to delays in generating the inference itself, but rather arise because integrating the interpretation of the inference with relevant information in the context may require additional time. With sufficient contextual support, processing delays disappear

    The barycentric motion of exoplanet host stars: tests of solar spin-orbit coupling

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    Empirical evidence suggests a tantalising but unproven link between various indicators of solar activity and the barycentric motion of the Sun. The latter is exemplified by transitions between regular and more disordered motion modulated by the motions of the giant planets, and rare periods of retrograde motion with negative orbital angular momentum. An examination of the barycentric motion of exoplanet host stars, and their stellar activity cycles, has the potential of proving or disproving the Sun's motion as an underlying factor in the complex patterns of short- and long-term solar variability indices, by establishing whether such correlations exist in other planetary systems. A variety of complex patterns of barycentric motions of exoplanet host stars is demonstrated, depending on the number, masses and orbits of the planets. Each of the behavioural types proposed to correlate with solar activity are also evident in exoplanet host stars: repetitive patterns influenced by massive multiple planets, epochs of rapid change in orbital angular momentum, and intervals of negative orbital angular momentum. The study provides the basis for independent investigations of the widely-studied but unproven suggestion that the Sun's motion is somehow linked to various indicators of solar activity. We show that, because of the nature of their barycentric motions, the host stars HD168443 and HD74156 offer particularly powerful tests of this hypothesis.Comment: 7 pages, 3 figures. Accepted for publication in A&
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