A Study of the Implications of the Piagetian Theory of Moral Development for Seventh-day Adventist Schools : Based on a Comparison of Selected Schools in Hong Kong, Michigan and Indiana

Problem. The Seventh-day Adventist Church is losing a great number of youth. The unfavorable attitudes on the part of many youth toward god\u27s commandments are thought to have been partially responsible for this apostasy phenomenon. Method. This study was designed to find out whether the Piagetian theory of moral judgment development can give some insight into this problem and its solution. Two Piagetian paired-stories sets were used to test children\u27s moral judgment. Chi Square tests were employed to analyze data. The following hypotheses were tested: 1. There will be no differences between the various age levels in the way American or Hong Kong subjects respond to stories containing moral themes. 2. There will be no difference between the Seventh-day Adventist and the non-Seventh-day Adventist subjects in America or in Hong Kong in the way they respond to stories containing moral themes. 3. There will be no difference between American Seventh-day Adventist and Hong Kong Seventh-day Adventist subjects in the way they respond to the stories containing moral themes. 4. There will be no difference between American public school and hong Kong public school subjects in the way they respond to stories containing moral themes. 5. There will be no difference between total Hong Kong response and total American response. Results. The comparison of a selected sample of American and Hong Kong children\u27s response to Piagetian-type stories indicated that his theory of moral judgment is applicable in the United States of America and overseas. From the sample tested it was found that moral judgment development is sequential, age related, and cognitively geared. American and Hong Kong subjects, both Seventh-day Adventists and non-Seventh-day Adventists, made similar responses to stories containing moral themes. The only exception was found among Seventh-Day Adventist subjects of the five-to-nine age group in both populations who showed greater moral maturity compared to their public school counterparts. Conclusion. Data from the sample studied lead to the conclusion that the universality of the applicability of Piagetian theory on moral judgment development can contribute to Seventh-day Adventist moral education practices. The developmental approach should help to make Seventh-day Adventist moral education programs more efficient and effective

Dehydroepiandrosterone (DHEA) replacement decreases insulin resistance and lowers inflammatory cytokines in aging humans

Plasma dehydroepiandrosterone (DHEA) decreases ~80% between ages 25 and 75 yr. In a preliminary study, we found that 6 mo of DHEA replacement improved insulin action in elderly individuals. The purpose of the present larger, randomized double-blind study was to determine whether a longer period of DHEA replacement improves glucose tolerance. Fifty-seven men and 68 women aged 65 to 75 yr were randomly assigned to 50 mg DHEA or placebo once daily. Year one was a randomized, double blind trial. Year 2 was an open label continuation. DHEA replacement improved glucose tolerance in participants who had abnormal GT initially, reduced plasma triglycerides, and the inflammatory cytokines IL6 and TNFα

DeepSynth: Three-dimensional nuclear segmentation of biological images using neural networks trained with synthetic data

The scale of biological microscopy has increased dramatically over the past ten years, with the development of new modalities supporting collection of high-resolution fluorescence image volumes spanning hundreds of microns if not millimeters. The size and complexity of these volumes is such that quantitative analysis requires automated methods of image processing to identify and characterize individual cells. For many workflows, this process starts with segmentation of nuclei that, due to their ubiquity, ease-of-labeling and relatively simple structure, make them appealing targets for automated detection of individual cells. However, in the context of large, three-dimensional image volumes, nuclei present many challenges to automated segmentation, such that conventional approaches are seldom effective and/or robust. Techniques based upon deep-learning have shown great promise, but enthusiasm for applying these techniques is tempered by the need to generate training data, an arduous task, particularly in three dimensions. Here we present results of a new technique of nuclear segmentation using neural networks trained on synthetic data. Comparisons with results obtained using commonly-used image processing packages demonstrate that DeepSynth provides the superior results associated with deep-learning techniques without the need for manual annotation

Three Dimensional Fluorescence Microscopy Image Synthesis and Segmentation

Advances in fluorescence microscopy enable acquisition of 3D image volumes with better image quality and deeper penetration into tissue. Segmentation is a required step to characterize and analyze biological structures in the images and recent 3D segmentation using deep learning has achieved promising results. One issue is that deep learning techniques require a large set of groundtruth data which is impractical to annotate manually for large 3D microscopy volumes. This paper describes a 3D deep learning nuclei segmentation method using synthetic 3D volumes for training. A set of synthetic volumes and the corresponding groundtruth are generated using spatially constrained cycle-consistent adversarial networks. Segmentation results demonstrate that our proposed method is capable of segmenting nuclei successfully for various data sets

Center-Extraction-Based Three Dimensional Nuclei Instance Segmentation of Fluorescence Microscopy Images

Fluorescence microscopy is an essential tool for the analysis of 3D subcellular structures in tissue. An important step in the characterization of tissue involves nuclei segmentation. In this paper, a two-stage method for segmentation of nuclei using convolutional neural networks (CNNs) is described. In particular, since creating labeled volumes manually for training purposes is not practical due to the size and complexity of the 3D data sets, the paper describes a method for generating synthetic microscopy volumes based on a spatially constrained cycle-consistent adversarial network. The proposed method is tested on multiple real microscopy data sets and outperforms other commonly used segmentation techniques

Biotransformed Metabolites of the Hop Prenylflavanone Isoxanthohumol

A metabolic conversion study on microbes is known as one of the most useful tools to predict the xenobiotic metabolism of organic compounds in mammalian systems. The microbial biotransformation of isoxanthohumol (1), a major hop prenylflavanone in beer, has resulted in the production of three diastereomeric pairs of oxygenated metabolites (2–7). The microbial metabolites of 1 were formed by epoxidation or hydroxylation of the prenyl group, and HPLC, NMR, and CD analyses revealed that all of the products were diastereomeric pairs composed of (2S)- and (2R)- isomers. The structures of these metabolic compounds were elucidated to be (2S,200S)- and (2R,200S)-40 -hydroxy-5-methoxy-7,8-(2,2-dimethyl-3-hydroxy-2,3-dihydro-4H-pyrano)-flavanones (2 and 3), (2S)- and (2R)-7,40 -dihydroxy-5-methoxy-8-(2,3-dihydroxy-3-methylbutyl)-flavanones (4 and 5) which were new oxygenated derivatives, along with (2R)- and (2S)-40 -hydroxy-5-methoxy-200 - (1-hydroxy-1-methylethyl)dihydrofuro[2,3-h]flavanones (6 and 7) on the basis of spectroscopic data. These results could contribute to understanding the metabolic fates of the major beer prenylflavanone isoxanthohumol that occur in mammalian system

CMB-HD: an Ultra-Deep, High-Resolution Millimeter-Wave Survey over Half the Sky

A millimeter-wave survey over half the sky, that spans frequencies in the range of 30 to 350 gigahertz, and that is both an order of magnitude deeper and of higher-resolution than currently funded surveys would yield an enormous gain in understanding of both fundamental physics and astrophysics. By providing such a deep, high-resolution millimeter-wave survey (about 0.5 microK-arcminutes noise and 15 arcseconds resolution at 150 gigahertz), CMB-HD (Cosmic Microwave Background - Henry Draper catalog entry) will enable major advances. It will allow 1) the use of gravitational lensing of the primordial microwave background to map the distribution of matter on small scales (k approximately equal to 10 h per megaparsec), which probes dark matter particle properties. It will also allow 2) measurements of the thermal and kinetic Sunyaev-Zeldovich effects on small scales to map the gas density and gas pressure profiles of halos over a wide field, which probes galaxy evolution and cluster astrophysics. In addition, CMB-HD would allow us to cross critical thresholds in fundamental physics: 3) ruling out or detecting any new, light (less than 0.1 electronvolts), thermal particles, which could potentially be the dark matter, and 4) testing a wide class of multi-field models that could explain an epoch of inflation in the early Universe. Such a survey would also 5) monitor the transient sky by mapping the full observing region every few days, which opens a new window on gamma-ray bursts, novae, fast radio bursts, and variable active galactic nuclei. Moreover, CMB-HD would 6) provide a census of planets, dwarf planets, and asteroids in the outer Solar System, and 7) enable the detection of exo-Oort clouds around other solar systems, shedding light on planet formation. The combination of CMB-HD with contemporary ground and space-based experiments will also provide powerful synergies. CMB-HD will deliver this survey in 5 years of observing 20,000 square degrees, using two new 30-meter-class off-axis cross-Dragone telescopes to be located at Cerro Toco in the Atacama Desert. The telescopes will field about 2.4 million detectors (600,000 pixels) in total. The CMB-HD survey will be made publicly available, with usability and accessibility a priority

Strong detection of the CMB lensingxgalaxy weak lensingcross-correlation from ACT-DR4,PlanckLegacy and KiDS-1000

We measure the cross-correlation between galaxy weak lensing data from the Kilo Degree Survey (KiDS-1000, DR4) and cosmic microwave background (CMB) lensing data from the Atacama Cosmology Telescope (ACT, DR4) and the Planck Legacy survey. We use two samples of source galaxies, selected with photometric redshifts, $(0.1<z_{\rm B}<1.2)$ and $(1.2<z_{\rm B}<2)$, which produce a combined detection significance of the CMB lensing/weak galaxy lensing cross-spectrum of $7.7\sigma$. With the lower redshift galaxy sample, for which the cross-correlation is detected at a significance of $5.3\sigma$, we present joint cosmological constraints on the matter density parameter, $\Omega_{\rm m}$, and the matter fluctuation amplitude parameter, $\sigma_8$, marginalising over three nuisance parameters that model our uncertainty in the redshift and shear calibration, and the intrinsic alignment of galaxies. We find our measurement to be consistent with the best-fitting flat $\Lambda$CDM cosmological models from both Planck and KiDS-1000. We demonstrate the capacity of CMB-weak lensing cross-correlations to set constraints on either the redshift or shear calibration, by analysing a previously unused high-redshift KiDS galaxy sample $(1.2<z_{\rm B}<2)$, with the cross-correlation detected at a significance of $7\sigma$. This analysis provides an independent assessment for the accuracy of redshift measurements in a regime that is challenging to calibrate directly owing to known incompleteness in spectroscopic surveys.Comment: 13 pages, 9 figures, 1 tables, submitted to A&

Atacama Cosmology Telescope: Component-separated maps of CMB temperature and the thermal Sunyaev-Zel’dovich effect

Optimal analyses of many signals in the cosmic microwave background (CMB) require map-level extraction of individual components in the microwave sky, rather than measurements at the power spectrum level alone. To date, nearly all map-level component separation in CMB analyses has been performed exclusively using satellite data. In this paper, we implement a component separation method based on the internal linear combination (ILC) approach which we have designed to optimally account for the anisotropic noise (in the 2D Fourier domain) often found in ground-based CMB experiments. Using this method, we combine multifrequency data from the Planck satellite and the Atacama Cosmology Telescope Polarimeter (ACTPol) to construct the first wide-area (≈2100 sq. deg.), arcminute-resolution component-separated maps of the CMB temperature anisotropy and the thermal Sunyaev-Zel’dovich (tSZ) effect sourced by the inverse-Compton scattering of CMB photons off hot, ionized gas. Our ILC pipeline allows for explicit deprojection of various contaminating signals, including a modified blackbody approximation of the cosmic infrared background (CIB) spectral energy distribution. The cleaned CMB maps will be a useful resource for CMB lensing reconstruction, kinematic SZ cross-correlations, and primordial non-Gaussianity studies. The tSZ maps will be used to study the pressure profiles of galaxies, groups, and clusters through cross-correlations with halo catalogs, with dust contamination controlled via CIB deprojection. The data products described in this paper are available on LAMBDA