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

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

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

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

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

An electronic family health history tool to identify and manage patients at increased risk for colorectal cancer: protocol for a randomized controlled trial.

BackgroundColorectal cancer is the fourth most commonly diagnosed cancer in the United States. Approximately 3-10% of the population has an increased risk for colorectal cancer due to family history and warrants more frequent or intensive screening. Yet, &lt; 50% of that high-risk population receives guideline-concordant care. Systematic collection of family health history and decision support may improve guideline-concordant screening for patients at increased risk of colorectal cancer. We seek to test the effectiveness of a web-based, systematic family health history collection tool and decision support platform (MeTree) to improve risk assessment and appropriate management of colorectal cancer risk among patients in the Department of Veterans Affairs primary care practices.MethodsIn this ongoing randomized controlled trial, primary care providers at the Durham Veterans Affairs Health Care System and the Madison VA Medical Center are randomized to immediate intervention or wait-list control. Veterans are eligible if assigned to enrolled providers, have an upcoming primary care appointment, and have no conditions that would place them at increased risk for colorectal cancer (such as personal history, adenomatous polyps, or inflammatory bowel disease). Those with a recent lower endoscopy (e.g. colonoscopy, sigmoidoscopy) are excluded. Immediate intervention patients put their family health history information into a web-based platform, MeTree, which provides both patient- and provider-facing decision support reports. Wait-list control patients access MeTree 12 months post-consent. The primary outcome is the risk-concordant colorectal cancer screening referral rate obtained via chart review. Secondary outcomes include patient completion of risk management recommendations (e.g. colonoscopy) and referral for genetic consultation. We will also conduct an economic analysis and an assessment of providers' experience with MeTree clinical decision support recommendations to inform future implementation efforts if the intervention is found to be effective.DiscussionThis trial will assess the feasibility and effectiveness of patient-collected family health history linked to decision support to promote risk-appropriate screening in a large healthcare system such as the Department of Veterans Affairs.Trial registrationClinicalTrials.gov, NCT02247336 . Registered on 25 September 2014

Application of MJO Simulation Diagnostics to Climate Models

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

Modelling the Madden Julian Oscillation

The MJO has long been an aspect of the global climate that has provided a tough test for the climate modelling community. Since the 1980s there have been numerous studies of the simulation of the MJO in atmospheric general circulation models (GCMs), ranging from Hayashi and Golder (1986, 1988) and Lau and Lau (1986), through to more recent studies such as Wang and Schlesinger (1999) and Wu et al. (2002). Of course, attempts to reproduce the MJO in climate models have proceeded in parallel with developments in our understanding of what the MJO is and what drives it. In fact, many advances in understanding the MJO have come through modeling studies. In particular, failure of climate models to simulate various aspects of the MJO has prompted investigations into the mechanisms that are important to its initiation and maintenance, leading to improvements both in our understanding of, and ability to simulate, the MJO. The initial focus of this chapter will be on modeling the MJO during northern winter, when it is characterized as a predominantly eastward propagating mode and is most readily seen in observations. Aspects of the simulation of the MJO will be discussed in the context of its sensitivity to the formulation of the atmospheric model, and the increasing evidence that it may be a coupled ocean-atmosphere phenomenon. Later, we will discuss the challenges regarding the simulation of boreal summer intraseasonal variability, which is more complex since it is a combination of the eastward propagating MJO and the northward propagation of the tropical convergence zone. Finally some concluding remarks on future directions in modeling the MJO and its relationship with other timescales of variability in the tropics will be made