Cluster-mining: An approach for determining core structures of metallic nanoparticles from atomic pair distribution function data

We present a novel approach for finding and evaluating structural models of small metallic nanoparticles. Rather than fitting a single model with many degrees of freedom, the approach algorithmically builds libraries of nanoparticle clusters from multiple structural motifs, and individually fits them to experimental PDFs. Each cluster-fit is highly constrained. The approach, called cluster-mining, returns all candidate structure models that are consistent with the data as measured by a goodness of fit. It is highly automated, easy to use, and yields models that are more physically realistic and result in better agreement to the data than models based on cubic close-packed crystallographic cores, often reported in the literature for metallic nanoparticles

I-WALK: An Innovative Approach to Community Walkability

One way of combating rising obesity rates and decreasing physical activity levels among children is to promote active transportation to and from schools. The award-winning I-WALK program provides a comprehensive framework for addressing community walkability and related infrastructure. The program uses a unique and innovative methodology that combines volunteer data collection workshops; classroom-based teacher tallies; and a dynamic Web-based survey that brings parents and children together to discuss school transportation issues. The program\u27s success demonstrates the benefits of coalition-building and community-based participatory research approaches to designing healthy and safe local environments

Ionically-Driven Synthesis and Exchange Bias in Mn4_{4}N/MnNx_{x} Heterostructures

Ferrimagnets have received renewed attention as a promising platform for spintronic applications. Of particular interest is the Mn4N from the ${\epsilon}$-phase of the manganese nitride as an emergent rare-earth-free spintronic material due to its perpendicular magnetic anisotropy, small saturation magnetization, high thermal stability, and large domain wall velocity. We have achieved high-quality (001)-ordered Mn$_{4}$N thin film by sputtering Mn onto ${\eta}$-phase Mn$_{3}$N$_{2}$ seed layers on Si substrates. As the deposited Mn thickness varies, nitrogen ion migration across the Mn$_{3}$N$_{2}$/Mn layers leads to a continuous evolution of the layers to Mn$_{3}$N$_{2}$/Mn$_{2}$N/Mn$_{4}$N, Mn$_{2}$N/Mn$_{4}$N, and eventually Mn$_{4}$N alone. The ferrimagnetic Mn$_{4}$N indeed exhibits perpendicular magnetic anisotropy, and forms via a nucleation-and-growth mechanism. The nitrogen ion migration is also manifested in a significant exchange bias, up to 0.3 T at 5 K, due to the interactions between ferrimagnetic Mn$_{4}$N and antiferromagnetic Mn$_{3}$N$_{2}$ and Mn$_{2}$N. These results demonstrate a promising all-nitride magneto-ionic platform with remarkable tunability for device applications.Comment: 21 pages, 5 figures, 7 pages of supplementary material with 5 figure

ELECTROMYOGRAPHICAL ANALYSIS OF PLYOMETRIC EXERCISES

The purpose of this study was to evaluate integrated electromyographic (IEMG) activity of the quadriceps (Q), hamstring (H), and gastrocnemius (G) muscle groups during the performance of 10 randomly ordered plyometric (P) exercises. Subjects included 23 adults who routinely performed P. A one way Repeated Measures ANOVA indicated Q-IEMG activity was significantly different (p 0.05) were found for the G-IEMG for female subjects and those with vertical jumps less than 50 cm, or for the H muscle group. Bonferonni adjusted pairwise comparisons of main effects revealed differences in IEMG between specific P exercises

The mitochondrial citrate/isocitrate carrier plays a regulatory role in glucose-stimulated insulin secretion.

Glucose-stimulated insulin secretion (GSIS) is mediated in part by glucose metabolism-driven increases in ATP/ADP ratio, but by-products of mitochondrial glucose metabolism also play an important role. Here we investigate the role of the mitochondrial citrate/isocitrate carrier (CIC) in regulation of GSIS. Inhibition of CIC activity in INS-1-derived 832/13 cells or primary rat islets by the substrate analogue 1,2,3-benzenetricarboxylate (BTC) resulted in potent inhibition of GSIS, involving both first and second phase secretion. A recombinant adenovirus containing a CIC-specific siRNA (Ad-siCIC) dose-dependently reduced CIC expression in 832/13 cells and caused parallel inhibitory effects on citrate accumulation in the cytosol. Ad-siCIC treatment did not affect glucose utilization, glucose oxidation, or ATP/ADP ratio but did inhibit glucose incorporation into fatty acids and glucose-induced increases in NADPH/NADP+ ratio relative to cells treated with a control siRNA virus (Ad-siControl). Ad-siCIC also inhibited GSIS in 832/13 cells, whereas overexpression of CIC enhanced GSIS and raised cytosolic citrate levels. In normal rat islets, Ad-siCIC treatment also suppressed CIC mRNA levels and inhibited GSIS. We conclude that export of citrate and/or isocitrate from the mitochondria to the cytosol is an important step in control of GSIS

R-modes in Neutron Stars with Crusts: Turbulent Saturation, Spin-down, and Crust Melting

Rossby waves (r-modes) have been suggested as a means to regulate the spin periods of young or accreting neutron stars, and also to produce observable gravitational wave radiation. R-modes involve primarily transverse, incompressive motions of the star's fluid core. However, neutron stars gain crusts early in their lives: therefore, r-modes also imply shear in the fluid beneath the crust. We examine the criterion for this shear layer to become turbulent, and derive the rate of dissipation in the turbulent regime. Unlike dissipation from a viscous boundary layer, turbulent energy loss is nonlinear in mode energy and can therefore cause the mode to saturate at amplitudes typically much less than unity. This energy loss also reappears as heat below the crust. We study the possibility of crust melting as well as its implications for the spin evolution of low-mass X-ray binaries. Lastly, we identify some universal features of the spin evolution that may have observational consequences.Comment: 12 pages, 4 figures, submitted to Ap

A Structured Narrative Prompt for Prompting Narratives from Large Language Models: Sentiment Assessment of ChatGPT-Generated Narratives and Real Tweets

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents\u27 perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt for sending queries to LLMs, we experiment with the narrative generation process using OpenAI\u27s ChatGPT, and we assess statistically significant differences across 11 Positive and Negative Affect Schedule (PANAS) sentiment levels between the generated narratives and real tweets using chi-squared tests and Fisher\u27s exact tests. The narrative prompt structure effectively yields narratives with the desired components from ChatGPT. In four out of forty-four categories, ChatGPT generated narratives which have sentiment scores that were not discernibly different, in terms of statistical significance (alpha level α = 0.05), from the sentiment expressed in real tweets. Three outcomes are provided: (1) a list of benefits and challenges for LLMs in narrative generation; (2) a structured prompt for requesting narratives of an LLM chatbot based on simulated agents\u27 information; (3) an assessment of statistical significance in the sentiment prevalence of the generated narratives compared to real tweets. This indicates significant promise in the utilization of LLMs for helping to connect a simulated agent\u27s experiences with real people