Light-sheet microscopy: a tutorial

This paper is intended to give a comprehensive review of light-sheet (LS) microscopy from an optics perspective. As such, emphasis is placed on the advantages that LS microscope configurations present, given the degree of freedom gained by uncoupling the excitation and detection arms. The new imaging properties are first highlighted in terms of optical parameters and how these have enabled several biomedical applications. Then, the basics are presented for understanding how a LS microscope works. This is followed by a presentation of a tutorial for LS microscope designs, each working at different resolutions and for different applications. Then, based on a numerical Fourier analysis and given the multiple possibilities for generating the LS in the microscope (using Gaussian, Bessel, and Airy beams in the linear and nonlinear regimes), a systematic comparison of their optical performance is presented. Finally, based on advances in optics and photonics, the novel optical implementations possible in a LS microscope are highlighted.Peer ReviewedPostprint (published version

DIONISIO 3.0: Comprehensive 3D nuclear fuel simulation through PCMI cohesive and PLENUM models

We present a new version of the DIONISIO code, extending its capabilities to three-dimensional domains. Adding to the functionality that divides the rod in a user-defined number of segments, the user can now choose the dimensionality of the domain in which a representative pellet-gap-cladding system is solved. To achieve this, we have developed a new algorithm to simulate the contact between pellet and cladding based in Cohesive Finite Elements, a natural mode to approach this issue. We present our results testing this kind of contact element in order to validate the concept. Alongside the contact algorithm, we have included a model of the plenum domain in three dimensions, treated using an external FEM mesh created ad hoc. DIONISIO reads this mesh adapting it to the specific case to be simulated and solves the energy equation inside the plenum following specific boundary conditions. We compare the new models to selected experiments under irradiation, in normal or accident conditions, for validation, with results showing a high correlation with said experiments.Fil: Goldberg, Ezequiel. Comision Nacional de Energía Atómica. Gerencia de Área de Aplicaciones de la Tecnología Nuclear. Gerencia Ciclo del Combustible Nuclear; Argentina. Universidad Nacional de San Martín. Instituto Sabato; ArgentinaFil: Loza Peralta, Matías E.. Comision Nacional de Energía Atómica. Gerencia de Área de Aplicaciones de la Tecnología Nuclear. Gerencia Ciclo del Combustible Nuclear; Argentina. Universidad Nacional de San Martín. Instituto Sabato; ArgentinaFil: Soba, Alejandro. Comision Nacional de Energía Atómica. Gerencia de Área de Aplicaciones de la Tecnología Nuclear. Gerencia Ciclo del Combustible Nuclear; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Latinas in the Legal Academy: Progress and Promise

The 2022 Inaugural Graciela Oliva ́rez Latinas in the Legal Academy (“GO LILA”) Workshop convened seventy-four outstanding and powerful Latina law professors and professional legal educators (collectively, “Latinas in the legal academy,” or “LILAs”) to document and celebrate our individual and collective journeys and to grow stronger together. In this essay, we, four of the Latina law professors who helped to co-found the GO LILA Workshop, share what we learned about and from each other. We invite other LILAs to join our community and share their stories and journeys. We hope that the data and lessons that we share can inspire other Latinas to join the legal academy. We encourage law schools to honor the transformation that our presence and contributions have brought to legal education and scholarship and to join us in considering how our path forward can be even more impactful and sustaining

Variabilité spatiale de la teneur en eau de surface des sols nus par mesures in situ et imagerie radar

National audienceOn présente l'analyse géostatistique de la teneur en eau de surface (0-6 cm de profondeur) collectée les 12 et 13 Mars 2009, sur une quinzaine de parcelles de sol nu d'un petit bassin péri-urbain proche de Lyon. Les mesures in situ, ont été collectées à deux échelles : une échelle locale sur des croix de longueur 20m et un pas d'espace de 1m et une échelle parcellaire sur 3 transects avec un pas de 20m environ. Les résultats montrent une corrélation de quelques m à échelle fine et de 20 à 50m à l'échelle de la parcelle. Après correction du bruit, calibration radiométrique et correction des effets géométriques et de pente, la comparaison des moyennes par parcelles issues de l'image radar TerraSAR-X et des mesures in situ est satisfaisante (R2=0.43) mais l'analyse intra-parcellaire reste à affiner. / This paper presents the geostatistical analysis of surface soil water content (0-6 cm depth), collected on March 12-13 2009, in about 15 bare soil fields located in a small suburban catchment close to Lyon. In situ data were sampled at two scales : a local scale on 20m-long crosses with a space step of about 1m; a field scale, with 3 transects and a space scale of about 20m. The results show a correlation of a few meters at the local scale and of about 20-50m at the field scale. After correction of the noise, radiometric calibration, geometric and slope effect correction, the comparison of the field averages derived from the TerraSAR-X image and of in situ data is satisfactory (R2=0.43), but the intra-field variability should be studied in more details

The effect of a home-based strength training program on type 2 diabetes risk in obese Latino boys

This paper is designed to determine the effects of a home-based strength training (HBST) intervention on insulin sensitivity (SI), compensatory acute insulin response and β-cell function, body composition measures, and maximum strength in obese Latino boys. A total of 26 obese Latino males aged between 14 and 18 years were randomized to either a twice-weekly (n=15) or a control group (C; n=15) for 16 weeks. HBST for 16 weeks, composed of two 1-h sessions per week. Outcome measures were assessed pre-and post-intervention/control condition and included SI, acute insulin response to glucose (AIR) and disposition index (DI), fasting glucose, 2-h glucose, body composition using waist-hip circumferences, body mass index (BMI), dual energy X-ray absorptiometry (DEXA) scan, blood pressure, and strength by 1-repetition maximum. A repeated measures GLM was used to assess differences in changes in outcome measures, between the C and the HBST groups. There were no significant overall intervention effects on any of the outcome variables (p<0.05). These results suggest that an HBST does not improve SI, maximal strength or decrease adiposity in obese Latino boys

Classification of molecular sequence data using Bayesian phylogenetic mixture models

Rate variation among the sites of a molecular sequence is commonly found in applications of phylogenetic inference. Several approaches exist to account for this feature but they do not usually enable the investigator to pinpoint the sites that evolve under one or another rate of evolution in a straightforward manner. The focus is on Bayesian phylogenetic mixture models, augmented with allocation variables, as tools for site classification and quantification of classification uncertainty. The method does not rely on prior knowledge of site membership to classes or even the number of classes. Furthermore, it does not require correlated sites to be next to one another in the sequence alignment, unlike some phylogenetic hidden Markov or change-point models. In the approach presented, model selection on the number and type of mixture components is conducted ahead of both model estimation and site classification; the steppingstone sampler (SS) is used to select amongst competing mixture models. Example applications of simulated data and mitochondrial DNA of primates illustrate site classification via ‘augmented’&nbsp; Bayesian phylogenetic mixtures. In both examples, all mixtures outperform commonly-used models of among-site rate variation and models that do not account for rate heterogeneity. The examples further demonstrate how site classification is readily available from the analysis output. The method is directly relevant to the choice of partitions in Bayesian phylogenetics, and its application may lead to the discovery of structure not otherwise recognised in a molecular sequence alignment. Computational aspects of Bayesian phylogenetic model estimation are discussed, including the use of simple Markov chain Monte Carlo (MCMC) moves that mix efficiently without tempering the chains. The contribution to the field of Bayesian phylogenetics is in (1) the use of mixture models augmented with allocation variables as tools for site classification and quantification of classification uncertainty, (2) the successful application of SS for selection of phylogenetic mixtures, and (3) the development of novel MCMC aspects of relevance to Bayesian phylogenetic models—whether mixtures or not.1&nbsp