Spatially Adaptive Stochastic Methods for Fluid-Structure Interactions Subject to Thermal Fluctuations in Domains with Complex Geometries

We develop stochastic mixed finite element methods for spatially adaptive simulations of fluid-structure interactions when subject to thermal fluctuations. To account for thermal fluctuations, we introduce a discrete fluctuation-dissipation balance condition to develop compatible stochastic driving fields for our discretization. We perform analysis that shows our condition is sufficient to ensure results consistent with statistical mechanics. We show the Gibbs-Boltzmann distribution is invariant under the stochastic dynamics of the semi-discretization. To generate efficiently the required stochastic driving fields, we develop a Gibbs sampler based on iterative methods and multigrid to generate fields with $O(N)$ computational complexity. Our stochastic methods provide an alternative to uniform discretizations on periodic domains that rely on Fast Fourier Transforms. To demonstrate in practice our stochastic computational methods, we investigate within channel geometries having internal obstacles and no-slip walls how the mobility/diffusivity of particles depends on location. Our methods extend the applicability of fluctuating hydrodynamic approaches by allowing for spatially adaptive resolution of the mechanics and for domains that have complex geometries relevant in many applications

Ownership influence and CSR disclosure in China

© 2018, Emerald Publishing Limited. Purpose: This paper aims to examine the relationship between ownership type and the likelihood of publication of a corporate social responsibility (CSR) report. Design/methodology/approach: Drawing on stakeholder salience theory, the probit model is used for a sample of 1,839 Chinese listed firms to study how different types of owners influence firm CSR engagement. Findings: The analysis reveals that the Chinese stock exchanges exert a positive influence on the likelihood of a firm producing a CSR report, an effect which is more significant in state-owned enterprises (SOEs). Foreign investors lead to a greater likelihood of publication of a CSR report, though this effect is weaker in SOEs. In contrast, the holdings of state and domestic institutional investors are broadly neutral. Practical implications: The study helps corporate managers to recognise how particular types of shareholders will value their efforts regarding CSR activities and disclosure and also assists policymakers in improving the level of CSR disclosure through the development of new policy. Social implications: Apposite CSR disclosure enhances trust and facilitates the shared values on which to build a more cohesive society. Originality/value: The novelty of this study is that it addresses the effect of institutional investors on Chinese firm CSR engagement and thus provides an important insight for firms, investors and other stakeholders into the interplay of portfolio investment and CSR

Asphericity, Interaction, and Dust in the Type II-P/II-L Supernova 2013ej in Messier 74

SN 2013ej is a well-studied core-collapse supernova (SN) that stemmed from a directly identified red supergiant (RSG) progenitor in galaxy M74. The source exhibits signs of substantial geometric asphericity, X-rays from persistent interaction with circumstellar material (CSM), thermal emission from warm dust, and a light curve that appears intermediate between supernovae of Types II-P and II-L. The proximity of this source motivates a close inspection of these physical characteristics and their potential interconnection. We present multi-epoch spectropolarimetry of SN 2013ej during the first 107 days, and deep optical spectroscopy and ultraviolet through infrared photometry past ~800 days. SN 2013ej exhibits the strongest and most persistent continuum and line polarization ever observed for a SN of its class during the recombination phase. Modeling indicates that the data are consistent with an oblate ellipsoidal photosphere, viewed nearly edge-on, and probably augmented by optical scattering from circumstellar dust. We suggest that interaction with an equatorial distribution of CSM, perhaps the result of binary evolution, is responsible for generating the photospheric asphericity. Relatedly, our late-time optical imaging and spectroscopy shows that asymmetric CSM interaction is ongoing, and the morphology of broad H-alpha emission from shock-excited ejecta provides additional evidence that the geometry of the interaction region is ellipsoidal. Alternatively, a prolate ellipsoidal geometry from an intrinsically bipolar explosion is also a plausible interpretation of the data, but would probably require a ballistic jet of radioactive material capable of penetrating the hydrogen envelope early in the recombination phase (abridged).Comment: Post-proof edit. Accepted to ApJ on Nov. 23 2016; 21 pages, 16 figure

Histoplasma capsulatum yeast phase-specific protein Yps3p induces Toll-like receptor 2 signaling

Histoplasma capsulatum is a common cause of fungal infection in certain geographic areas, and although most infections are asymptomatic, it is capable of causing histoplasmosis, a disseminated, life-threatening disease, especially in immunocompromised individuals. A deeper understanding of this host-pathogen interaction is needed to develop novel therapeutic strategies to counter lethal infection. Although several lines of evidence suggest that this fungus is neurotropic in HIV patients, little is known about the immunobiology of Histoplasma infection in the central nervous system [CNS]. The goal of the present study was to understand the innate neuroimmune mechanisms that recognize H. capsulatum during the initial stages of infection. Using a 293T stable cell line expressing murine Toll-like receptor 2 [TLR2], we show here that TLR2 recognizes H. capsulatum cell wall protein Yps3p and induces the activation of NF-κB. In further experiments, we tested the ability of Yps3p to induce signaling from TLR2 in primary microglial cells, the resident brain macrophages of the CNS. Our data show that H. capsulatum Yps3p induced TLR2 signaling in wild-type microglia, but not in microglia isolated from TLR2 KO mice, confirming that Yps3p is a ligand for TLR2. Furthermore, Yps3p-induced TLR2 signaling was suppressed by vaccinia virus-encoded TLR inhibitors. This is the first demonstration of a fungal protein serving as a TLR ligand and mediating signaling in primary brain cells

Constructing a Predator Exclusionary Fence to Protect Hawaiian Petrels (Pterodroma sandwichensis) at Hawai῾i Volcanoes National Park

Reports were scanned in black and white at a resolution of 600 dots per inch and were converted to text using Adobe Paper Capture Plug-in.Remnant nesting colonies of endangered Hawaiian Petrels, or ‘Ua’u (Pterodroma sandwichensis), on Mauna Loa, Hawai’i Island, are primarily threatened by feral cats. At Hawai῾i Volcanoes National Park, trapping success has been variable due several challenges, including the difficulty of accessing remote, subalpine (9,000’) sites. To create a core area free from cat predation, the park, with support from multiple partners, constructed a five mile barrier fence encircling 640 acres of the richest known concentration of subalpine Hawaiian Petrel nests on Mauna Loa. We report on key fence design elements, pilot studies, step by step construction details, concurrent and subsequent monitoring, and lessons learned throughout the project for the benefit of other managers considering exclusionary fencing

Generative Language Models Exhibit Social Identity Biases

The surge in popularity of large language models has given rise to concerns about biases that these models could learn from humans. In this study, we investigate whether ingroup solidarity and outgroup hostility, fundamental social biases known from social science, are present in 51 large language models. We find that almost all foundational language models and some instruction fine-tuned models exhibit clear ingroup-positive and outgroup-negative biases when prompted to complete sentences (e.g., "We are..."). A comparison of LLM-generated sentences with human-written sentences on the internet reveals that these models exhibit similar level, if not greater, levels of bias than human text. To investigate where these biases stem from, we experimentally varied the amount of ingroup-positive or outgroup-negative sentences the model was exposed to during fine-tuning in the context of the United States Democrat-Republican divide. Doing so resulted in the models exhibiting a marked increase in ingroup solidarity and an even greater increase in outgroup hostility. Furthermore, removing either ingroup-positive or outgroup-negative sentences (or both) from the fine-tuning data leads to a significant reduction in both ingroup solidarity and outgroup hostility, suggesting that biases can be reduced by removing biased training data. Our findings suggest that modern language models exhibit fundamental social identity biases and that such biases can be mitigated by curating training data. Our results have practical implications for creating less biased large-language models and further underscore the need for more research into user interactions with LLMs to prevent potential bias reinforcement in humans.Comment: supplementary material, data, and code see https://osf.io/9ht32/?view_only=f0ab4b23325f4c31ad3e12a7353b55f

High Efficiency Permanent Magnet Machine

The present invention is a high efficiency permanent magnet machine capable of maintaining high power density. The machine is operable over a wide range of power output. The improved efficiency is due in part to copper wires with a current density lower than traditional designs and larger permanent magnets coupled with a large air gap. In a certain embodiment wide stator teeth are used to provide additional improved efficiency through significantly reducing magnetic saturation resulting in lower current. The machine also has a much smaller torque angle than that in traditional design at rated load and thus has a higher overload handling capability and improved efficiency. In addition, when the machine is used as a motor, an adaptive phase lag compensation scheme helps the sensorless field oriented control (FOC) scheme to perform more accurately

Computational Fluid Dynamics (CFD) modelling and experimental confirmation of hollow fiber tangential flow filtration (HFTFF) and alternating tangential flow filtration (ATF) In a perfusion bioreactor

Hollow fiber tangential flow filtration (HFTFF) and Alternating tangential flow filtration (HFATF) are technologies of choice in continuous (perfusion) bioreactor operations. A major drawback of these technologies is membrane fouling and associated reduction in membrane permeability. Membrane fouling leads to a gradual decline in trans-membrane flux and the sieving of the protein product. Additionally, experimental data suggests that under otherwise similar conditions protein sieving may be different in TFF vs. ATF, indicating that flow behavior patterns in the two technologies may be different. Many models of fouling and protein sieving have been reported in the literature for HFTFF. In comparison, however, there is limited research work on HFATF, making it hard to compare mechanisms of fouling and product sieving between HFTFF and HFATF. Additionally, almost all mechanisms of fouling and predictive models make sweeping assumptions with regards to the complex flow patterns prevailing in HFTFF and HFATF. In this study, we provide experimental data and computational fluid dynamics (CFD) information to gain insight into factors that impact fouling and product sieving. Specifically, first we present the confirmation of CFD model outputs by comparing experimentally measured trans-membrane flux and pressure with model predictions. Next, we compare the CFD model predictions of pressure drop, shear rate profile and axial and radial fluid velocity distributions between HFTFF and HFATF. Subsequently, we investigate the shear effect on cell damage, using the concept of constant Camp number, defined as Gt = constant, where G is the prevailing shear rate and t is the exposure time. Our CFD model predicts that shear rate (G) and hence the resulting stress experienced by cells in HFATF has a distribution that is determined by the operation of the diaphragm pump. Finally, we use CFD to compare Gt profile generated by imposing different pump condition