Three- and Four-Year Olds Learn about Gears through Arts Incorporation

This research paper explores art integration into a science lesson unit that follows the Next Generation Science Standards (K-PS2-1) and focuses on the effects on memory retention of key concepts along with levels of enjoyment. An experiment was conducted with children ages 3 and 4 teaching scientific concepts about gears while incorporating student-made art products. The children were assigned to alternating experimental (art-integrated) or control (no art) conditions during the four stages of the lesson. The results did not show statistically significant differences at the alpha = 0.05 level between conditions in the amount of information retained based on the pretest, posttest, and distal posttest. However, there were overall knowledge gains for both conditions demonstrated by the gain scores. It appeared that incorporating arts into the curriculum can be beneficial for children, including those of diverse cultural backgrounds, as it provides a more enjoyable learning environment. Arts integration can also facilitate the construction of children’s schema of gears which later may ease the learning of more complex concepts related to motion, stability, forces, and interaction

Preschoolers Explore Greenhouses by Visiting a Greenhouse, Making a Model, and Growing Plants

This practical lesson on greenhouses implements standards of the Next Generation Science Standards (K-2 ETS I-2; K-LS1-1) and the preschool objectives from the Teaching Strategies GOLD. Teaching Strategies GOLD is an assessment tool available online and in print that can be used with any developmentally appropriate early childhood curriculum. The lesson structure follows the 5E’s Learning Cycle Constructivist Model for teaching and the project-based, hands-on approach to learning. The preschool-aged children went on a field trip to a working greenhouse and then collaborated in groups to produce a three-dimensional model of a greenhouse as arts integration into this science project. The children affixed photo stickers from their greenhouse visit onto a recycled plastic container to make the greenhouse building. They used clay, toothpicks, and colored paper leaves to recreate models of plants they had seen and then planted real seeds. The following lesson on plants and greenhouses serves as a successful example of positive arts-integrated science; the children worked together with enjoyment and took pride in their work while the teacher evaluated it as rewarding

Training algorithms for artificial neural network in predicting of the content of chemical elements in the upper soil layer

Models based on Artificial Neural Networks (ANN) in recent years are increasingly being used in environmental studies. Among the many types of ANN, the network type Multilayer Perceptron (MLP) has become most widespread. Such networks are universal, simple, and suitable for most tasks. The main problem when modelling using MLP is the choice of the learning algorithm. In this paper, we compared several learning algorithms: Levenberg-Marquart (LM), LM with Bayes regularization (BR), gradient descent (GD), and GD with the speed parameter setting (GDA). The data for modelling were taken from the results of the soil screening of an urbanized area. The spatial distribution of the chemical element Chromium (Cr) in the surface layer of the soil was simulated. The structure of the MLP network was chosen using computer simulations based on minimization of the root mean squared error (RMSE). The model using the LM training algorithm showed the best accuracy. © 2018 Author(s)

Immersed nano-sized Al dispersoids in an Al matrix; effects on the structural and mechanical properties by Molecular Dynamics simulations

We used molecular dynamics simulations based on a potential model in analogy to the Tight Binding scheme in the Second Moment Approximation to simulate the effects of aluminum icosahedral grains (dispersoids) on the structure and the mechanical properties of an aluminum matrix. First we validated our model by calculating several thermodynamic properties referring to the bulk Al case and we found good agreement with available experimental and theoretical data. Afterwards, we simulated Al systems containing Al clusters of various sizes. We found that the structure of the Al matrix is affected by the presence of the dispersoids resulting in well ordered domains of different symmetries that were identified using suitable Voronoi analysis. In addition, we found that the increase of the grain size has negative effect on the mechanical properties of the nanocomposite as manifested by the lowering of the calculated bulk moduli. The obtained results are in line with available experimental data.Comment: 15 pages, 8 figures. Submitted to J. Phys: Condens. Matte

Mejora de la precisión de la herramienta Frax mediante la adición de una capa de análisis basada en medición de la densidad radiológica con la técnica 'Earth Mover's distance' (EMD)

La herramienta de cálculo FRAX determina la probabilidad a 10 años de que un individuo entre 40 y 90 años sufra una fractura osteoporótica mayor o de cadera computando los factores de riesgo del individuo y, opcionalmente, la densidad mineral ósea determinada por absorciometría de fotón dual (DEXA), en comparación con los de una cohorte de la que se conoce la prevalencia de fractura. Por otra parte, hay datos que sugieren que la medida de la densidad radiológica mediante la técnica Earth Mover’s Distance (EMD) puede mejorar la precisión diagnostica en mamografías y radiología osteoarticular, entre otras

Froth-like minimizers of a non local free energy functional with competing interactions

We investigate the ground and low energy states of a one dimensional non local free energy functional describing at a mean field level a spin system with both ferromagnetic and antiferromagnetic interactions. In particular, the antiferromagnetic interaction is assumed to have a range much larger than the ferromagnetic one. The competition between these two effects is expected to lead to the spontaneous emergence of a regular alternation of long intervals on which the spin profile is magnetized either up or down, with an oscillation scale intermediate between the range of the ferromagnetic and that of the antiferromagnetic interaction. In this sense, the optimal or quasi-optimal profiles are "froth-like": if seen on the scale of the antiferromagnetic potential they look neutral, but if seen at the microscope they actually consist of big bubbles of two different phases alternating among each other. In this paper we prove the validity of this picture, we compute the oscillation scale of the quasi-optimal profiles and we quantify their distance in norm from a reference periodic profile. The proof consists of two main steps: we first coarse grain the system on a scale intermediate between the range of the ferromagnetic potential and the expected optimal oscillation scale; in this way we reduce the original functional to an effective "sharp interface" one. Next, we study the latter by reflection positivity methods, which require as a key ingredient the exact locality of the short range term. Our proof has the conceptual interest of combining coarse graining with reflection positivity methods, an idea that is presumably useful in much more general contexts than the one studied here.Comment: 38 pages, 2 figure

Energy Landscape and Global Optimization for a Frustrated Model Protein

The three-color (BLN) 69-residue model protein was designed to exhibit frustrated folding. We investigate the energy landscape of this protein using disconnectivity graphs and compare it to a Go model, which is designed to reduce the frustration by removing all non-native attractive interactions. Finding the global minimum on a frustrated energy landscape is a good test of global optimization techniques, and we present calculations evaluating the performance of basin-hopping and genetic algorithms for this system.Comparisons are made with the widely studied 46-residue BLN protein.We show that the energy landscape of the 69-residue BLN protein contains several deep funnels, each of which corresponds to a different β-barrel structure

The Substitutions L50F, E166A, and L167F in SARS-CoV-2 3CLpro Are Selected by a Protease Inhibitor In Vitro and Confer Resistance To Nirmatrelvir.

The SARS-CoV-2 main protease (3CLpro) has an indispensable role in the viral life cycle and is a therapeutic target for the treatment of COVID-19. The potential of 3CLpro-inhibitors to select for drug-resistant variants needs to be established. Therefore, SARS-CoV-2 was passaged in vitro in the presence of increasing concentrations of ALG-097161, a probe compound designed in the context of a 3CLpro drug discovery program. We identified a combination of amino acid substitutions in 3CLpro (L50F E166A L167F) that is associated with a >20× increase in 50% effective concentration (EC50) values for ALG-097161, nirmatrelvir (PF-07321332), PF-00835231, and ensitrelvir. While two of the single substitutions (E166A and L167F) provide low-level resistance to the inhibitors in a biochemical assay, the triple mutant results in the highest levels of resistance (6× to 72×). All substitutions are associated with a significant loss of enzymatic 3CLpro activity, suggesting a reduction in viral fitness. Structural biology analysis indicates that the different substitutions reduce the number of inhibitor/enzyme interactions while the binding of the substrate is maintained. These observations will be important for the interpretation of resistance development to 3CLpro inhibitors in the clinical setting. IMPORTANCE Paxlovid is the first oral antiviral approved for treatment of SARS-CoV-2 infection. Antiviral treatments are often associated with the development of drug-resistant viruses. In order to guide the use of novel antivirals, it is essential to understand the risk of resistance development and to characterize the associated changes in the viral genes and proteins. In this work, we describe for the first time a pathway that allows SARS-CoV-2 to develop resistance against Paxlovid in vitro. The characteristics of in vitro antiviral resistance development may be predictive for the clinical situation. Therefore, our work will be important for the management of COVID-19 with Paxlovid and next-generation SARS-CoV-2 3CLpro inhibitors

Salmonella-Induced Mucosal Lectin RegIIIβ Kills Competing Gut Microbiota

Intestinal inflammation induces alterations of the gut microbiota and promotes overgrowth of the enteric pathogen Salmonella enterica by largely unknown mechanisms. Here, we identified a host factor involved in this process. Specifically, the C-type lectin RegIIIβ is strongly upregulated during mucosal infection and released into the gut lumen. In vitro, RegIIIβ kills diverse commensal gut bacteria but not Salmonella enterica subspecies I serovar Typhimurium (S. Typhimurium). Protection of the pathogen was attributable to its specific cell envelope structure. Co-infection experiments with an avirulent S. Typhimurium mutant and a RegIIIβ-sensitive commensal E. coli strain demonstrated that feeding of RegIIIβ was sufficient for suppressing commensals in the absence of all other changes inflicted by mucosal disease. These data suggest that RegIIIβ production by the host can promote S. Typhimurium infection by eliminating inhibitory gut microbiota