Read Alouds and Their Impact on Students\u27 Literacy Development

This qualitative study explores the impact of reading aloud to upper or intermediate elementary students. The purpose of this study is to research how fourth grade students respond to a variety of read aloud texts, and how these rich literacy experiences impact students’ literacy development. This study gives background information about read alouds in the classroom and explores one fourth grade class\u27s responses to read aloud text including the impact of these read alouds on students\u27 literacy development

Aluminum-26 Enrichment in the Surface of Protostellar Disks Due to Protostellar Cosmic Rays

The radioactive decay of aluminum-26 ($^{26}$Al) is an important heating source in early planet formation. Since its discovery, there have been several mechanisms proposed to introduce $^{26}$Al into protoplanetary disks, primarily through contamination by external sources. We propose a local mechanism to enrich protostellar disks with $^{26}$Al through irradiation of the protostellar disk surface by cosmic rays accelerated in the protostellar accretion shock. We calculate the $^{26}$Al enrichment, [$^{26}$Al/$^{27}$Al], at the surface of the protostellar disk in the inner AU throughout the evolution of low-mass stars, from M-dwarfs to proto-Suns. Assuming constant mass accretion rates, $\dot{m}$, we find that irradiation by MeV cosmic rays can provide significant enrichment on the disk surface if the cosmic rays are not completely coupled to the gas in the accretion flow. Importantly, we find that low accretion rates, $\dot{m} < 10^{-7}$ M$_{\odot}$ yr$^{-1}$, are able to produce canonical amounts of $^{26}$Al, $[^{26}{\rm Al}/^{27}{\rm Al}] \approx 5\times10^{-5}$. These accretion rates are experienced at the transition from Class I- to Class II-type protostars, when it is assumed that calcium-aluminum-rich inclusions condense in the inner disk. We conclude that irradiation of the inner disk surface by cosmic ray protons accelerated in accretion shocks at the protostellar surface may be an important mechanism to produce $^{26}$Al. Our models show protostellar cosmic rays may be a viable model to explain the enrichment of $^{26}$Al found in the Solar System.Comment: Accepted to ApJ, in pres

Theoretical studies of the potential surface for the F - H2 greater than HF + H reaction

The F + H2 yields HF + H potential energy hypersurface was studied in the saddle point and entrance channel regions. Using a large (5s 5p 3d 2f 1g/4s 3p 2d) atomic natural orbital basis set, a classical barrier height of 1.86 kcal/mole was obtained at the CASSCF/multireference CI level (MRCI) after correcting for basis set superposition error and including a Davidson correction (+Q) for higher excitations. Based upon an analysis of the computed results, the true classical barrier is estimated to be about 1.4 kcal/mole. The location of the bottleneck on the lowest vibrationally adiabatic potential curve was also computed and the translational energy threshold determined from a one-dimensional tunneling calculation. Using the difference between the calculated and experimental threshold to adjust the classical barrier height on the computed surface yields a classical barrier in the range of 1.0 to 1.5 kcal/mole. Combining the results of the direct estimates of the classical barrier height with the empirical values obtained from the approximation calculations of the dynamical threshold, it is predicted that the true classical barrier height is 1.4 + or - 0.4 kcal/mole. Arguments are presented in favor of including the relatively large +Q correction obtained when nine electrons are correlated at the CASSCF/MRCI level

Using Machine Learning to estimate the technical potential of shallow ground-source heat pumps with thermal interference

The increasing use of ground-source heat pumps (GSHPs) for heating and cooling of buildings raises questions regarding the technical potential of GSHPs and their impact on the temperature in the shallow subsurface. In this paper, we develop a method using Machine Learning to estimate the technical potential of shallow GSHPs, which enables such an estimation for Switzerland with limited data and computational resources. A training dataset is constructed based on meteorological and geological data across Switzerland. We analyse correlations and the importance of each of the input data for estimating the GSHP potential and compare different input feature sets and Machine Learning models. The Random Forest algorithm, trained on the full dataset, provides the best performance to estimate the GSHP potential. The resulting model yields an R2 score of 0.95 for the annual energy potential, 0.86 for the heat extraction rate, and 0.82 for the potential number of boreholes per GSHP system

Spatio-temporal estimation of wind speed and wind power using extreme learning machines: predictions, uncertainty and technical potential

With wind power providing an increasing amount of electricity worldwide, the quantification of its spatio-temporal variations and the related uncertainty is crucial for energy planners and policy-makers. Here, we propose a methodological framework which (1) uses machine learning to reconstruct a spatio-temporal field of wind speed on a regular grid from spatially irregularly distributed measurements and (2) transforms the wind speed to wind power estimates. Estimates of both model and prediction uncertainties, and of their propagation after transforming wind speed to power, are provided without any assumptions on data distributions. The methodology is applied to study hourly wind power potential on a grid of 250×250 m2 for turbines of 100 m hub height in Switzerland, generating the first dataset of its type for the country. We show that the average annual power generation per turbine is 4.4 GWh. Results suggest that around 12,000 wind turbines could be installed on all 19,617 km2 of available area in Switzerland resulting in a maximum technical wind potential of 53 TWh. To achieve the Swiss expansion goals of wind power for 2050, around 1000 turbines would be sufficient, corresponding to only 8% of the maximum estimated potential

Shallow geothermal energy potential for heating and cooling of buildings with regeneration under climate change scenarios

Shallow ground-source heat pumps (GSHPs) are a promising technology for contributing to the decarbonisation of the energy sector. In heating-dominated climates, the combined use of GSHPs for both heating and cooling increases their technical potential, defined as the maximum energy that can be exchanged with the ground, as the re-injection of excess heat from space cooling leads to a seasonal regeneration of the ground. This paper proposes a new approach to quantify the technical potential of GSHPs, accounting for effects of seasonal regeneration, and to estimate the useful energy to supply building energy demands at regional scale. The useful energy is obtained for direct heat exchange and for district heating and cooling (DHC) under several scenarios for climate change and market penetration levels of cooling systems. The case study in western Switzerland suggests that seasonal regeneration allows for annual maximum heat extraction densities above 300 kWh/m2 at heat injection densities above 330 kWh/m2. Results also show that GSHPs may cover up to 55% of heating demand while covering 57% of service-sector cooling demand for individual GSHPs in 2050, which increases to around 85% with DHC. The regional-scale results may serve to inform decision making on strategic areas for installing GSHPs

The evolution of HCO+^{+} in molecular clouds using a novel chemical post-processing algorithm

Modeling the internal chemistry of molecular clouds is critical to accurately simulating their evolution. To reduce computational expense, 3D simulations generally restrict their chemical modeling to species with strong heating and cooling effects. We address this by post-processing tracer particles in the SILCC-Zoom molecular cloud simulations. Using a chemical network of 39 species and 299 reactions (including freeze-out of CO and H$_2$O), and a novel iterative algorithm to reconstruct a filled density grid from sparse tracer particle data, we produce time-dependent density distributions for various species. We focus upon the evolution of HCO$^+$, which is a critical formation reactant of CO but is not typically modeled on-the-fly. We analyse the evolution of the tracer particles to assess the regime in which HCO$^+$ production preferentially takes place. We find that the HCO$^+$ content of the cold molecular gas forms in situ around n_\textrm{HCO^+}\simeq10^3-$10^4$ cm$^{-3}$, over a time-scale of approximately 1 Myr, rather than being distributed to this density regime via turbulent mixing from deeper in the cloud. We further show that the dominant HCO$^+$ formation pathway is dependent on the visual extinction, with the reaction H$_3^+$ + CO contributing 90% of the total HCO$^+$ production flux above $A_\textrm{V,3D}=3$. Using our novel grid reconstruction algorithm, we produce the very first maps of the HCO$^+$ column density, $N$(HCO$^+$), and show that it reaches values as high as $10^{15}$ cm$^{-2}$. We find that 50% of the HCO$^+$ mass is located in an $A_\textrm{V}$-range of $\sim$10-30, and in a density range of $10^{3.5}$-$10^{4.5}$ cm$^{-3}$. Finally, we compare our $N$(HCO$^+$) maps to recent observations of W49A and find good agreement.Comment: 23 pages including appendix, 20 figures, submitted to MNRAS, comments are welcom

Effect of Sedentary and Physical Activities on Children’s Food Choice

International Journal of Exercise Science 10(5): 702-712, 2017. Childhood obesity is a growing public health concern. Research has shown sedentary behavior (SB) increases children’s unhealthy food consumption, while physical activity (PA) decreases caloric intake and increases energy expenditure. The purpose of this study was to examine child snack choice following a bout of active, SB, and a mix of SB and active (SB-A). Participants included a volunteer sample of children (n=24) ranging from 9-13 years of age. A within-subjects simple experimental design was used, and children participated in three conditions: active, SB, and SB-A. After each condition, the children were asked to choose one snack from two healthy and two unhealthy options. The children were randomized into one of the six possible condition sequences (4 children per group) based on when they enrolled in the study. Data were analyzed in SPSS (v21) using the Friedman, Wilcoxon Signed-Rank, and Kruskal-Wallis tests. There was not a statistically significant difference in the overall model comparing the three conditions on snack choice (p=0.15). Overweight/obese children were significantly more likely than normal weight children to choose a healthier snack option after the active condition (p=0.02). There was no difference between boys and girls for snack choice following the active (p\u3e0.05), SB (p\u3e0.05), and SB-A (p\u3e0.05). Our overall findings suggest SB and active had no effect on children’s snack choice. Promoting PA to children who are overweight/obese could lead to decreased energy intake and increased energy expenditure combating the obesity epidemic

Taking Blockchain Seriously

In the present techno-political moment it is clear that ignoring or dismissing the hype surrounding blockchain is unwise, and certainly for regulatory authorities and governments who must keep a grip on the technology and those promoting it, in order to ensure democratic accountability and regulatory legitimacy within the blockchain ecosystem and beyond. Blockchain is telling (and showing) us something very important about the evolution of capital and neoliberal economic reason, and the likely impact in the near future on forms and patterns of work, social organization, and, crucially, on communities and individuals who lack influence over the technologies and data that increasingly shape and control their lives. In this short essay I introduce some of the problems in the regulation of blockchain and offer counter-narratives aimed at cutting through the hype fuelling the ascendency of this most contemporary of technologies

Synthetic C18O observations of fibrous filaments: the problems of mapping from PPV to PPP

Molecular-line observations of filaments in star-forming regions have revealed the existence of elongated coherent features within the filaments; these features are termed fibres. Here we caution that, since fibres are traced in PPV space, there is no guarantee that they represent coherent features in PPP space. We illustrate this contention using simulations of the growth of a filament from a turbulent medium. Synthetic C$^{18}$O observations of the simulated filaments reveal the existence of fibres very similar to the observed ones, i.e. elongated coherent features in the resulting PPV data-cubes. Analysis of the PPP data-cubes (i.e. 3D density fields) also reveals elongated coherent features, which we term sub-filaments. Unfortunately there is very poor correspondence between the fibres and the sub-filaments in the simulations. Both fibres and sub-filaments derive from inhomogeneities in the turbulent accretion flow onto the main filament. As a consequence, fibres are often affected by line-of-sight confusion. Similarly, sub-filaments are often affected by large velocity gradients, and even velocity discontinuities. These results suggest that extreme care should be taken when using velocity coherent features to constrain the underlying substructure within a filament.Comment: 15 pages + appendices, 26 figures. Accepted to MNRA