An efficient surrogate model for emulation and physics extraction of large eddy simulations

In the quest for advanced propulsion and power-generation systems, high-fidelity simulations are too computationally expensive to survey the desired design space, and a new design methodology is needed that combines engineering physics, computer simulations and statistical modeling. In this paper, we propose a new surrogate model that provides efficient prediction and uncertainty quantification of turbulent flows in swirl injectors with varying geometries, devices commonly used in many engineering applications. The novelty of the proposed method lies in the incorporation of known physical properties of the fluid flow as {simplifying assumptions} for the statistical model. In view of the massive simulation data at hand, which is on the order of hundreds of gigabytes, these assumptions allow for accurate flow predictions in around an hour of computation time. To contrast, existing flow emulators which forgo such simplications may require more computation time for training and prediction than is needed for conducting the simulation itself. Moreover, by accounting for coupling mechanisms between flow variables, the proposed model can jointly reduce prediction uncertainty and extract useful flow physics, which can then be used to guide further investigations.Comment: Submitted to JASA A&C

Serotonin receptor HTR6-mediated mTORC1 signaling regulates dietary restriction-induced memory enhancement

Dietary restriction (DR; sometimes called calorie restriction) has profound beneficial effects on physiological, psychological, and behavioral outcomes in animals and in humans. We have explored the molecular mechanism of DR-induced memory enhancement and demonstrate that dietary tryptophan-a precursor amino acid for serotonin biosynthesis in the brain-and serotonin receptor 5-hydroxytryptamine receptor 6 (HTR6) are crucial in mediating this process. We show that HTR6 inactivation diminishes DR-induced neurological alterations, including reduced dendritic complexity, increased spine density, and enhanced long-term potentiation (LTP) in hippocampal neurons. Moreover, we find that HTR6-mediated mechanistic target of rapamycin complex 1 (mTORC1) signaling is involved in DR-induced memory improvement. Our results suggest that the HTR6-mediated mTORC1 pathway may function as a nutrient sensor in hippocampal neurons to couple memory performance to dietary intake

Transcriptomic analyses of regenerating adult feathers in chicken

Transcriptome Expression Data. Table of mapped reads to Galgal4 transcripts for all 15 data sets. FPKM (Fragments per kilobase of exon per million fragments mapped): normalized transcript abundance values for each gene in the indicated tissues. (CSV 1314 kb

First Data Release of the Hyper Suprime-Cam Subaru Strategic Program

The Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) is a three-layered imaging survey aimed at addressing some of the most outstanding questions in astronomy today, including the nature of dark matter and dark energy. The survey has been awarded 300 nights of observing time at the Subaru Telescope and it started in March 2014. This paper presents the first public data release of HSC-SSP. This release includes data taken in the first 1.7 years of observations (61.5 nights) and each of the Wide, Deep, and UltraDeep layers covers about 108, 26, and 4 square degrees down to depths of i~26.4, ~26.5, and ~27.0 mag, respectively (5sigma for point sources). All the layers are observed in five broad bands (grizy), and the Deep and UltraDeep layers are observed in narrow bands as well. We achieve an impressive image quality of 0.6 arcsec in the i-band in the Wide layer. We show that we achieve 1-2 per cent PSF photometry (rms) both internally and externally (against Pan-STARRS1), and ~10 mas and 40 mas internal and external astrometric accuracy, respectively. Both the calibrated images and catalogs are made available to the community through dedicated user interfaces and database servers. In addition to the pipeline products, we also provide value-added products such as photometric redshifts and a collection of public spectroscopic redshifts. Detailed descriptions of all the data can be found online. The data release website is https://hsc-release.mtk.nao.ac.jp/.Comment: 34 pages, 20 figures, 7 tables, moderate revision, accepted for publication in PAS

The Hyper Suprime-Cam SSP survey: Overview and survey design

Hyper Suprime-Cam (HSC) is a wide-field imaging camera on the prime focus of the 8.2-m Subaru telescope on the summit of Mauna Kea in Hawaii. A team of scientists from Japan, Taiwan, and Princeton University is using HSC to carry out a 300-night multi-band imaging survey of the high-latitude sky. The survey includes three layers: the Wide layer will cover 1400 deg2 in five broad bands (grizy), with a 5 σ point-source depth of r ≈ 26. The Deep layer covers a total of 26 deg2 in four fields, going roughly a magnitude fainter, while the UltraDeep layer goes almost a magnitude fainter still in two pointings of HSC (a total of 3.5 deg2). Here we describe the instrument, the science goals of the survey, and the survey strategy and data processing. This paper serves as an introduction to a special issue of the Publications of the Astronomical Society of Japan, which includes a large number of technical and scientific papers describing results from the early phases of this survey

Common proper orthogonal decomposition-based emulation and system identification for model-based analysis of combustion dynamics

For high-performance power generation and propulsion systems, such as those of airbreathing and rocket engines, physical experiments are expensive due to the harsh requirements of operating conditions. In addition, it is difficult to gain insight into the underlying mechanisms of the physiochemical processes involved because of the typical reliance upon optical diagnostics for experimental measurements. High-fidelity simulations can be employed to capture more salient features of the flow and combustion dynamics in engines, but these computations are often too expensive and time-consuming for design and development purposes. To enable usage of modeling/simulation in the design workflow, the present study proposes a data-driven framework for modeling and analysis to facilitate decision making for combustor designs. Its core is a surrogate model employing a machine-learning technique called kriging, which is combined with data-driven basis functions to extract and model the underlying coherent structures from high-fidelity simulation results. This emulation framework encompasses key design parameter sensitivity analysis, physics-guided classification of design parameter sets, and flow evolution modeling for efficient design survey. A sensitivity analysis using Sobol’ indices and a decision tree are incorporated into the framework to better inform the model. This information improves the surrogate model training process, which employs basis functions as regression functions over the design space for the kriging model. The novelty of the proposed approach is the construction of the surrogate model through Common Proper Orthogonal Decomposition, allowing for data-reduction and extraction of common coherent structures. The accuracy of prediction of mean flow features for new swirl injector designs is assessed and the dynamic flowfield is captured in the form of power spectrum densities. This data-driven framework also demonstrates the uncertainty quantification of predictions, providing a metric for model fit. The significantly reduced computation time required for evaluating new design points enables efficient survey of the design space. To further utilize model results, a data analytic methodology to quantify the combustion dynamics is used to link the component-level simulations to the system-level stability performance. Comprehensive combustion stability analysis and a good understanding of the coupling process would reduce the amount of testing and level of capital required for engine development. The proposed methodology leverages high-fidelity large eddy simulation (LES) in combination with machine-learning techniques to quantify the spatial combustion response, which is intended to serve as an acoustic source term in the generalized wave equation. The acoustic eigenmode analysis can be used to assess the stability of propulsion systems. Treating the extracted coherent structures as time series signals, the combustion response can be deduced through autoregressive model selection, accounting for data sparsity, multicollinearity, and noise. The results show that acoustic-vortical dynamics is the dominant mechanism determining flame stabilization, affecting the acoustic modes of the combustion chamber. The methodology not only accounts for the distributed combustion response through incorporation of proper orthogonal decomposition (POD) analysis, but also uses the data to identify relevant time scales, replacing the need for forcing and focusing on intrinsic dynamics. A design survey of the system stability based on the injector dynamics can then be conducted using the surrogate model for the combustion response.Ph.D

Surgical management and immunohistochemical study of corneal plaques in vernal keratoconjunctivitis

Two children with shield ulcer in vernal keratoconjunctivitis unresponsive to steroid therapy received plaque removal by superficial keratectomy, followed by amniotic membrane transplantation (AMT). Hematoxylin and eosin staining of the excised corneal specimen revealed a thick layer of eosinophilic material attached to the Bowman's layer. These deposits were positive for eosinophil granule major basic protein, as confirmed by an immunohistochemical study. The shield ulcer healed after the amniotic membrane was removed. No recurrent corneal plaque developed, although corneal opacity complicated in both cases. Lamellar keratectomy with AMT offers an effective management by removing the cytotoxic plaques and protecting the denuded stroma from deposition of inflammatory debris

Fluorescence of Size-Fractioned Humic Substance Extracted from Sediment and Its Effect on the Sorption of Phenanthrene

Phenanthrene (Phe) is a toxin and is ubiquitous in the environment. The sediment humic substances (HS) that bind Phe affect the fate, transport, degradation, and ecotoxicology of Phe. This study investigated Phe sorption constants on size-fractioned HS extracted from river sediment. Fractions were identified as HHS (10 kDa to 0.45 μm), MHS (1–10 kDa), and LHS (<1 kDa). A fluorescence quenching (FQ) method was used to determine the Phe log KHS on size-fractioned HS; the values ranged from 3.97 to 4.68 L/kg-C. The sorption constant (log KHS) is a surrogate of the binding capacity between HS and Phe, where a high log KHS reduces the toxicity and degradation of Phe. The log KHS values on HHS and MHS were significantly higher than the values on LHS (p = 0.015). The SUVA254 values of HHS and MHS were also significantly higher than the LHS value (p = 0.047), while fluorescence index (FI) and S275–295 values were significantly lower than the LHS values (p < 0.005). The HHS and MHS had a higher aromaticity and more terrestrial sources than LHS. The log KHS had a significant correlation with the selected optical indicators (p < 0.002), which suggested that the HS-bound Phe was positively affected by high aromaticity, terrestrial sources, and HS molecular weight. The results demonstrated that optical methods successfully obtained log KHS and the chemical properties of fractioned HS as well as the influenced factors of log KHS. Moreover, even the LHS had a capacity to bind with Phe