The hamiltonian particle-mesh method for the spherical shallow water equations

The Hamiltonian particle-mesh (HPM) method is generalized to the spherical shallow water equations, utilizing constrained particle dynamics on the sphere and smoothing with Merilees' double-periodic FFT formulation of O(J2 log J) in the latitudinal gridsize. The time step for the explicit, symplectic integrator depends only on the uniform smoothing length

Hamiltonian particle-mesh method for two-layer shallow-water equations subject to the rigid-lid approximation

We develop a particle-mesh method for two-layer shallow-water equations subject to the rigid-lid approximation. The method is based on the recently proposed Hamiltonian particle-mesh (HPM) method and the interpretation of the rigid-lid approximation as a set of holonomic constraints. The suggested spatial discretization leads to a constrained Hamiltonian system of ODEs which is integrated in time using a variant of the symplectic SHAKE/RATTLE algorithm. It is demonstrated that the elimination of external gravity waves by the rigid-lid approximation can be achieved in a computationally stable and efficient way

Media consumption and creation in attitudes toward and knowledge of inflammatory bowel disease: web-based survey

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic gastrointestinal condition affecting over 5 million people globally and 1.6 million in the United States but currently lacks a precisely determined cause or cure. The range of symptoms IBD patients experience are often debilitating, and the societal stigmas associated with some such symptoms can further degrade their quality of life. Better understanding the nature of this public reproach then is a critical component for improving awareness campaigns and, ultimately, the experiences of IBD patients. OBJECTIVE: The objective of this study was to explore and assess the public's awareness and knowledge of IBD, as well as what relationship, if any, exists between the social stigma surrounding IBD, knowledge of the disease, and various media usage, including social media. METHODS: Utilizing a Web-based opt-in platform, we surveyed a nationally representative sample (n=1200) with demographics mirroring those of the US Census figures across baseline parameters. Using constructed indices based on factor analysis, we were able to build reliable measures of personal characteristics, media behaviors, and perceptions and knowledge of IBD. RESULTS: Among the American public, IBD is the most stigmatized of seven diseases, including genital herpes and human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS). Additionally, IBD knowledge is generally low with 11.08% (133/1200) of the sample indicating no familiarity with the disease and 85.50% (1026/1200) of participants inaccurately answering two-thirds of the IBD index questions with which their knowledge was assessed. Increased knowledge of IBD is associated with lower levels of stigma. However, social media use is currently related to lower levels of IBD knowledge (P<.05). Furthermore, findings indicate that participants who most frequently engaged in producing social media content are less knowledgeable about IBD (P<.10), highlighting the potential for a dangerous cycle should they be contributing to a Web-based IBD dialogue. CONCLUSIONS: Greater efforts must be taken to stymie IBD misinformation across all media, but especially in social media channels, to increase IBD knowledge and reduce stigma surrounding IBD. These findings pave the way for further research qualitatively examining the pervasiveness of specific IBD messages found in today's social media landscape and their impact on enacted stigmas so as to better equip providers and patient advocacy organizations with impactful communication solutions

Hydrostatic Hamiltonian particle-mesh (HPM) methods for atmospheric modelling

We develop a hydrostatic Hamiltonian particle-mesh (HPM) method for efficient long-term numerical integration of the atmosphere. In the HPM method, the hydrostatic approximation is interpreted as a holonomic constraint for the vertical position of particles. This can be viewed as defining a set of vertically buoyant horizontal meshes, with the altitude of each mesh point determined so as to satisfy the hydrostatic balance condition and with particles modelling horizontal advection between the moving meshes. We implement the method in a vertical-slice model and evaluate its performance for the simulation of idealized linear and nonlinear orographic flow in both dry and moist environments. The HPM method is able to capture the basic features of the gravity wave to a degree of accuracy comparable with that reported in the literature. The numerical solution in the moist experiment indicates that the influence of moisture on wave characteristics is represented reasonably well and the reduction of momentum flux is in good agreement with theoretical analysis. Copyright © 2011 Royal Meteorological Societ

Linear PDEs and numerical methods that preserve a multi-symplectic conservation law

Multisymplectic methods have recently been proposed as a generalization of symplectic ODE methods to the case of Hamiltonian PDEs. Their excellent long time behavior for a variety of Hamiltonian wave equations has been demonstrated in a number of numerical studies. A theoretical investigation and justification of multisymplectic methods is still largely missing. In this paper, we study linear multisymplectic PDEs and their discretization by means of numerical dispersion relations. It is found that multisymplectic methods in the sense of Bridges and Reich Phys. Lett. A, 284 (2001), pp. 184-193] and Reich J. Comput. Phys., 157 (2000), pp. 473-499], such as Gauss-Legendre Runge-Kutta methods, possess a number of desirable properties such as nonexistence of spurious roots and conservation of the sign of the group velocity. A certain CFL-type restriction on $\Delta t/\Delta x$ might be required for methods higher than second order in time. It is also demonstrated by means of the explicit midpoint method that multistep methods may exhibit spurious roots in the numerical dispersion relation for any value of $\Delta t/\Delta x$ despite being multisymplectic in the sense of discrete variational mechanics [J. E. Marsden, G. P. Patrick, and S. Shkoller, Commun. Math. Phys., 199 (1999), pp. 351-395]

Speculate: discovering conditional equations and inequalities about black-box functions by reasoning from test results

This paper presents Speculate, a tool that automatically conjectures laws involving conditional equations and inequalities about Haskell functions. Speculate enumerates expressions involving a given collection of Haskell functions, testing to separate those expressions into apparent equivalence classes. Expressions in the same equivalence class are used to conjecture equations. Representative expressions of different equivalence classes are used to conjecture conditional equations and inequalities. Speculate uses lightweight equational reasoning based on term rewriting to discard redundant laws and to avoid needless testing. Several applications demonstrate the effectiveness of Speculate

Projected impacts of climate and land use changes on the habitat of Atlantic Forest plants in Brazil

Aim: To provide novel evidence on the average impact of climate and land use changes on habitat suitability for tropical plants and to test previous conclusions on the relative importance of these two drivers in shaping future availability of habitat for tropical plant species. Location: Brazil’s Atlantic Forest domain. Time period: Plant occurrences recorded between 1960 and 2014. Baseline climate from 1960 to 2000 and land use from 2015. Projected scenarios of climate for 2041–2060 and land use for 2050. Major taxa studied: Angiosperms. Methods: We modelled the habitat suitability of 2,232 species of angiosperms from the Atlantic Forest domain, endemic to Brazil, and estimated how future climate and land use may affect species-level habitat suitability under a moderate and a business-as-usual scenario for the year 2050. Results: Our results suggest that climate change alone will, surprisingly, have only a modest negative impact on the mean habitat suitability, decreasing it by 2% (median = −5 to −7%, variation associated with scenarios). Land use change alone had a more consistent negative impact on habitat suitability, causing mean and median reductions of 4 to 6%. When the effects of climate and land use are combined, the mean habitat suitability was reduced by 4% (median = −9 to −11%). Main conclusions: The combined impacts of climate and land use changes were substantial, although smaller than expected. Habitat suitability decreased for most species, but it increased substantially for some species, suggesting that the distribution of impacts across species is markedly right skewed. The impacts were typically detrimental to small-ranged species and neutral or beneficial to widespread species. Land use change rather than climate change will likely cause more losses to the habitat of Atlantic Forest plant species within the next several decades

Segmentation of Multiple Sclerosis Lesions across Hospitals: Learn Continually or Train from Scratch?

Segmentation of Multiple Sclerosis (MS) lesions is a challenging problem. Several deep-learning-based methods have been proposed in recent years. However, most methods tend to be static, that is, a single model trained on a large, specialized dataset, which does not generalize well. Instead, the model should learn across datasets arriving sequentially from different hospitals by building upon the characteristics of lesions in a continual manner. In this regard, we explore experience replay, a well-known continual learning method, in the context of MS lesion segmentation across multi-contrast data from 8 different hospitals. Our experiments show that replay is able to achieve positive backward transfer and reduce catastrophic forgetting compared to sequential fine-tuning. Furthermore, replay outperforms the multi-domain training, thereby emerging as a promising solution for the segmentation of MS lesions. The code is available at this link: https://github.com/naga-karthik/continual-learning-msComment: Accepted at the Medical Imaging Meets NeurIPS (MedNeurIPS) Workshop 202

Plant diversity, CO2 and N influence inorganic and organic N leaching in grasslands

In nitrogen (N)-limited systems, the potential to sequester carbon depends on the balance between N inputs and losses as well as on how efficiently N is used, yet little is known about responses of these processes to changes in plant species richness, atmospheric CO2 concentration ([CO2]), and N deposition. We examined how plant species richness (1 or 16 species), elevated [CO2] (ambient or 560 ppm), and inorganic N addition (0 or 4 g·m−2·yr−1) affected ecosystem N losses, specifically leaching of dissolved inorganic N (DIN) and organic N (DON) in a grassland field experiment in Minnesota, USA. We observed greater DIN leaching below 60 cm soil depth in the monoculture plots (on average 1.8 and 3.1 g N·m−2·yr−1 for ambient N and N-fertilized plots respectively) than in the 16-species plots (0.2 g N·m−2·yr−1 for both ambient N and N-fertilized plots), particularly when inorganic N was added. Most likely, loss of complementary resource use and reduced biological N demand in the monoculture plots caused the increase in DIN leaching relative to the high-diversity plots. Elevated [CO2] reduced DIN concentrations under conditions when DIN concentrations were high (i.e., in N-fertilized and monoculture plots). Contrary to the results for DIN, DON leaching was greater in the 16-species plots than in the monoculture plots (on average 0.4 g N·m−2·yr−1 in 16-species plots and 0.2 g N·m−2·yr−1 in monoculture plots). In fact, DON dominated N leaching in the 16-species plots (64% of total N leaching as DON), suggesting that, even with high biological demand for N, substantial amounts of N can be lost as DON. We found no significant main effects of elevated [CO2] on DIN or DON leaching; however, elevated [CO2] reduced the positive effect of inorganic N addition on DON leaching, especially during the second year of observation. Our results suggest that plant species richness, elevated [CO2], and N deposition alter DIN loss primarily through changes in biological N demand. DON losses can be as large as DIN loss but are more sensitive to organic matter production and turnover.Dijkstra, Feike A; West, Jason B; Hobbie, Sarah E; Reich, Peter B; Trost, Jared. (2007). Plant diversity, CO2 and N influence inorganic and organic N leaching in grasslands. Retrieved from the University Digital Conservancy, 10.1890/06-0733

Atomic-resolution visualization and doping effects of complex structures in intercalated bilayer graphene

Molecules intercalating two-dimensional materials form complex structures that have been characterized primarily by spatially averaged techniques. Here we use aberration-corrected scanning transmission electron microscopy and density-functional-theory (DFT) calculations to study the atomic structure of bilayer graphene (BLG) and few-layer graphene (FLG) intercalated with FeCl3. In BLG, we discover two distinct intercalated structures that we identify as monolayer FeCl3 and monolayer FeCl2. The two structures are separated by atomically sharp boundaries and induce large free-carrier densities on the order of 1013cm−2 in the graphene layers. In FLG, we observe multiple FeCl3 layers stacked in a variety of possible configurations with respect to one another. Finally, we find that the microscope's electron beam can convert the FeCl3 monolayer into FeOCl monolayers in a rectangular lattice. These results reveal the need for a combination of atomically resolved microscopy, spectroscopy, and DFT calculations to identify intercalated structures and study their properties