Cooling Radiation and the Lyman-alpha Luminosity of Forming Galaxies

We examine the cooling radiation from forming galaxies in hydrodynamic simulations of the LCDM model (cold dark matter with a cosmological constant), focusing on the Ly-alpha line luminosities of high-redshift systems. Primordial composition gas condenses within dark matter potential wells, forming objects with masses and sizes comparable to the luminous regions of observed galaxies. As expected, the energy radiated in this process is comparable to the gravitational binding energy of the baryons, and the total cooling luminosity of the galaxy population peaks at z ~= 2. However, in contrast to the classical picture of gas cooling from the \sim 10^6 K virial temperature of a typical dark matter halo, we find that most of the cooling radiation is emitted by gas with T < 20,000 K. As a consequence, roughly 50% of this cooling radiation emerges in the Ly-alpha line. While a galaxy's cooling luminosity is usually smaller than the ionizing continuum luminosity of its young stars, the two are comparable in the most massive systems, and the cooling radiation is produced at larger radii, where the Ly-alpha photons are less likely to be extinguished by dust. We suggest, in particular, that cooling radiation could explain the two large (\sim 100 kpc), luminous (L_{Ly-alpha} \sim 10^{44} erg s^{-1}) ``blobs'' of Ly-alpha emission found in Steidel et al.'s (1999) narrow band survey of a z = 3 proto-cluster. Our simulations predict objects of the observed luminosity at about the right space density, and radiative transfer effects can account for the observed sizes and line widths. We discuss observable tests of this hypothesis for the nature of the Ly-alpha blobs, and we present predictions for the contribution of cooling radiation to the Ly-alpha luminosity function of galaxies as a function of redshift.Comment: Submitted to ApJ. 28 pages including 9 PS figures. Version with color figures available at http://donald.astro.umass.edu/~fardal/papers/cooling/cooling.htm

Testing Cosmological Models Against the Abundance of Damped Lyman-Alpha Absorbers

We calculate the number of damped Lyman-alpha absorbers expected in various popular cosmological models as a function of redshift and compare our predictions with observed abundances. The Press-Schechter formalism is used to obtain the distribution of halos with circular velocity in different cosmologies, and we calibrate the relation between circular velocity and absorption cross-section using detailed gas dynamical simulations of a ``standard'' cold dark matter (CDM) model. Because of this calibration, our approach makes more realistic assumptions about the absorption properties of collapsed objects than previous, analytic calculations of the damped Lyman-alpha abundance. CDM models with Omega_0=1, H_0=50, baryon density Omega_b=0.05, and scale-invariant primeval fluctuations reproduce the observed incidence and redshift evolution of damped Lyman-alpha absorption to within observational uncertainty, for both COBE normalization (sigma_8=1.2) and a lower normalization (sigma_8=0.7) that better matches the observed cluster abundance at z=0. A tilted (n=0.8, sigma_8=0.7) CDM model tends to underproduce absorption, especially at z=4. With COBE normalization, a CDM model with Omega_0=0.4, Omega_{Lambda}=0.6 gives an acceptable fit to the observed absorption; an open CDM model is marginally acceptable if Omega_0 is at least 0.4 and strongly inconsistent with the z=4 data if Omega_0=0.3. Mixed dark matter models tend not to produce sufficient absorption, being roughly comparable to tilted CDM models if Omega_{nu} = 0.2 and failing drastically if Omega_{nu} = 0.3.Comment: AASlatex, 13 pages w/ 2 embedded ps figures. To be published in ApJ, Sept. 1, 199

Back to School in the Pandemic: Observations of the Influences of Prevention Measures on Relationships, Autonomy, and Learning of Preschool Children

Background: The COVID-19 pandemic has had a global impact on societies, economies, and education. In Spain, one of the countries most affected by the COVID-19 in the initial year, the virus began to spread at the end of February 2020. When the Spanish government declared a state of emergency, the first restrictive measure was the closure of all educational centers on the 14th of March. All schools and universities were closed until September 2020, when students returned to classes with preventative health measures in place to prevent the spread of the virus. Methods: This study focuses on the observation of children in pre-school education. Specifically, it focuses on studying how preventative health measures that were taken in the pre-schools may have influenced children’s social relationships, basic autonomy, and learning. We used a mixed method in which field notes were taken and observational scores were assigned. Results: The following prevention measures appear to have influenced children’s relationships, autonomy, and learning: bubble groups, handwashing, teachers wearing masks, divided playgrounds so different classes cannot mix, and no toys from home or shared personal objects. Conclusions: The results of the study suggest that new health measures such as the use of masks and social distancing do appear to be affecting the communication and development of pre-school children. Continued research is needed to understand and minimize the potential negative impacts of pandemic measures on children’s development

Measuring Discrimination Against Transgender People at the University of the Basque Country and in a Non-University Sample in Spain

Transgender people suffer from others&rsquo; negative attitudes in many situations. The university context is one environment where further progress has to be made to ensure the inclusion of transgender people. In this study, a sample of 376 undergraduate students was collected and their attitudes towards transgender people were analyzed. A comparison was made between number of years in university, and a sample from the general public. In addition, comparisons were made by gender, since the literature shows more negative attitudes toward transgender people in men than in women. The results show relatively positive attitudes toward transgender people among higher education students, but they have little knowledge of transgender identity. In turn, researchers found significant differences between different years in the university and between genders. These results support the need to expand knowledge about transgender people in the university environment

Improvement in Gender and Transgender Knowledge in University Students Through the Creative Factory Methodology

In Spain, Social Educators, similar to both social workers and educators in the United States, help coordinate social change through educational interventions and mobilization of social groups to benefit marginalized people and overall societal welfare. They are trained to work with diverse populations, and it is important that they have awareness and training on gender and transgender issues given the extensive discrimination that transgender people endue. Research has begun to identify the important role that knowledge and attitudes of health and educational professionals may play in providing a supportive, healing context to combat the harmful effects of this discrimination and how educational trainings may foster improved knowledge and attitudes in helping professions. This study describes a program to improve knowledge and positive attitudes toward gender and especially transgender people in university students who study Social Education. The researchers measured knowledge and attitudes toward gender and transgender people issues of 64 students before and after receiving a 4-month interactive training. They used the Short Form of the Genderism and Transphobia Scale, a 12-item scale of transphobia and gender ideology variables. The researchers also asked participants about their knowledge of gender and transgender issues before and after training. The methodological experience "Creative Factory" was employed as an interactive training program. The main goal of this methodology is to enable students in a formative context to analyze social realities to generate discussion and innovate ideas to design successful practices. After 4 months of training with a weekly session on gender and transgender learning, students showed improvements in knowledge and attitudes toward both gender and transgender people. Specifically, students demonstrated more knowledge about gender and transgender issues and more positive attitudes toward transgender people. The study demonstrates that training in gender education using the Creative Factory methodology improved knowledge and attitudes in students

Deep learning features encode interpretable morphologies within histological images.

Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotypes from hematoxylin and eosin (H&E) whole slide images (WSIs), but the interpretation of CNNs remains difficult. Most studies have considered interpretability in a post hoc fashion, e.g. by presenting example regions with strongly predicted class labels. However, such an approach does not explain the biological features that contribute to correct predictions. To address this problem, here we investigate the interpretability of H&E-derived CNN features (the feature weights in the final layer of a transfer-learning-based architecture). While many studies have incorporated CNN features into predictive models, there has been little empirical study of their properties. We show such features can be construed as abstract morphological genes ( mones ) with strong independent associations to biological phenotypes. Many mones are specific to individual cancer types, while others are found in multiple cancers especially from related tissue types. We also observe that mone-mone correlations are strong and robustly preserved across related cancers. Importantly, linear mone-based classifiers can very accurately separate 38 distinct classes (19 tumor types and their adjacent normals, AUC = [Formula: see text] for each class prediction), and linear classifiers are also highly effective for universal tumor detection (AUC = [Formula: see text]). This linearity provides evidence that individual mones or correlated mone clusters may be associated with interpretable histopathological features or other patient characteristics. In particular, the statistical similarity of mones to gene expression values allows integrative mone analysis via expression-based bioinformatics approaches. We observe strong correlations between individual mones and individual gene expression values, notably mones associated with collagen gene expression in ovarian cancer. Mone-expression comparisons also indicate that immunoglobulin expression can be identified using mones in colon adenocarcinoma and that immune activity can be identified across multiple cancer types, and we verify these findings by expert histopathological review. Our work demonstrates that mones provide a morphological H&E decomposition that can be effectively associated with diverse phenotypes, analogous to the interpretability of transcription via gene expression values. Our work also demonstrates mones can be interpreted without using a classifier as a proxy

The DEEP2 Galaxy Redshift Survey: The Evolution of Void Statistics from z~1 to z~0

We present measurements of the void probability function (VPF) at z~1 using data from the DEEP2 Redshift Survey and its evolution to z~0 using data from the Sloan Digital Sky Survey (SDSS). We measure the VPF as a function of galaxy color and luminosity in both surveys and find that it mimics trends displayed in the two-point correlation function, $\xi$; namely that samples of brighter, red galaxies have larger voids (i.e. are more strongly clustered) than fainter, blue galaxies. We also clearly detect evolution in the VPF with cosmic time, with voids being larger in comoving units at z~0. We find that the reduced VPF matches the predictions of a `negative binomial' model for galaxies of all colors, luminosities, and redshifts studied. This model lacks a physical motivation, but produces a simple analytic prediction for sources of any number density and integrated two-point correlation function, \bar{\xi}. This implies that differences in the VPF across different galaxy populations are consistent with being due entirely to differences in the population number density and \bar{\xi}. The robust result that all galaxy populations follow the negative binomial model appears to be due to primarily to the clustering of dark matter halos. The reduced VPF is insensitive to changes in the parameters of the halo occupation distribution, in the sense that halo models with the same \bar{\xi} will produce the same VPF. For the wide range of galaxies studied, the VPF therefore does not appear to provide useful constraints on galaxy evolution models that cannot be gleaned from studies of \bar{\xi} alone. (abridged)Comment: 17 pages, 15 figures, ApJ accepte

Development and Implementation of Dynamic Scripts to Support Local Model Verification at National Weather Service Weather Forecast Offices

Local modeling with a customized configuration is conducted at National Weather Service (NWS) Weather Forecast Offices (WFOs) to produce high-resolution numerical forecasts that can better simulate local weather phenomena and complement larger scale global and regional models. The advent of the Environmental Modeling System (EMS), which provides a pre-compiled version of the Weather Research and Forecasting (WRF) model and wrapper Perl scripts, has enabled forecasters to easily configure and execute the WRF model on local workstations. NWS WFOs often use EMS output to help in forecasting highly localized, mesoscale features such as convective initiation, the timing and inland extent of lake effect snow bands, lake and sea breezes, and topographically-modified winds. However, quantitatively evaluating model performance to determine errors and biases still proves to be one of the challenges in running a local model. Developed at the National Center for Atmospheric Research (NCAR), the Model Evaluation Tools (MET) verification software makes performing these types of quantitative analyses easier, but operational forecasters do not generally have time to familiarize themselves with navigating the sometimes complex configurations associated with the MET tools. To assist forecasters in running a subset of MET programs and capabilities, the Short-term Prediction Research and Transition (SPoRT) Center has developed and transitioned a set of dynamic, easily configurable Perl scripts to collaborating NWS WFOs. The objective of these scripts is to provide SPoRT collaborating partners in the NWS with the ability to evaluate the skill of their local EMS model runs in near real time with little prior knowledge of the MET package. The ultimate goal is to make these verification scripts available to the broader NWS community in a future version of the EMS software. This paper provides an overview of the SPoRT MET scripts, instructions for how the scripts are run, and example use cases

Post-traumatic stress in children and adolescents during the Covid-19 pandemic: a meta-analysis and intervention approaches to ensure mental health and well-being

Background: Since the World Health Organization (WHO) declared the COVID-19 pandemic in March 2020, many measures have been taken to prevent the spread of the virus. Consequently, many minors have been confined to their homes and have had to subsequently adapt to countless protocol changes. These factors appear to have contributed to post-traumatic stress disorder (PTSD) in many children. Materials and Methods: The authors searched Medline through PubMed and other databases for studies published from 1 December 2019 to 31 December 2021 on the prevalence of PTSD in schoolchildren. The authors used a random-effects model to calculate the pooled prevalence of PTSD. Results: A total of six studies were included in this review. Our results show a pooled prevalence of PTSD of 14% in children and adolescents. Subgroup analyses identify a significantly higher prevalence of PTSD for studies conducted in China and a higher prevalence in boys. The prevalence of PTSD appeared independent of child age or the methodological rigor of the study. Conclusions: Our results suggest that a large number of children may be suffering from PTSD (post-traumatic stress disorder). Public health measures are thus needed to improve children’s mental health during and after the pandemic, so that the suffering is mitigated to prevent long-lasting effects