Theoretical studies of the phase transition in the anisotropic 2-D square spin lattice

The phase transition occurring in a square 2-D spin lattice governed by an anisotropic Heisenberg Hamiltonian has been studied according to two recently proposed methods. The first one, the Dressed Cluster Method, provides excellent evaluations of the cohesive energy, the discontinuity of its derivative around the critical (isotropic) value of the anisotropy parameter confirms the first-order character of the phase transition. Nevertheless the method introduces two distinct reference functions (either N\'eel or XY) which may in principle force the discontinuity. The Real Space Renormalization Group with Effective Interactions does not reach the same numerical accuracy but it does not introduce a reference function and the phase transition appears qualitatively as due to the existence of two domains, with specific fixed points. The method confirms the dependence of the spin gap on the anisotropy parameter occurring in the Heisenberg-Ising domain

Nystr\"om methods for high-order CQ solutions of the wave equation in two dimensions

We investigate high-order Convolution Quadratures methods for the solution of the wave equation in unbounded domains in two dimensions that rely on Nystr\"om discretizations for the solution of the ensemble of associated Laplace domain modified Helmholtz problems. We consider two classes of CQ discretizations, one based on linear multistep methods and the other based on Runge-Kutta methods, in conjunction with Nystr\"om discretizations based on Alpert and QBX quadratures of Boundary Integral Equation (BIE) formulations of the Laplace domain Helmholtz problems with complex wavenumbers. We present a variety of accuracy tests that showcase the high-order in time convergence (up to and including fifth order) that the Nystr\"om CQ discretizations are capable of delivering for a variety of two dimensional scatterers and types of boundary conditions

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Global sensitivities of reactive N and S gas and particle concentrations and deposition to precursor emissions reductions

The reduction of fine particles (PM2.5) and reactive N (Nr) and S (Sr) species is a key objective for air pollution control policies because of their major adverse effects on human health, ecosystem diversity, and climate. The sensitivity of global and regional Nr, Sr, and PM2.5 to 20 % and 40 % individual and collective reductions in anthropogenic emissions of NH3, NOx, and SOx (with respect to a 2015 baseline) is investigated using the EMEP MSC-W atmospheric chemistry transport model with WRF meteorology. Regional comparisons reveal that the individual emissions reduction has multiple co-benefits and small disbenefits on different species, and those effects are highly geographically variable. Reductions in NH3 emissions are effective at decreasing NH3 concentrations and deposition but much less so for NH4+. A 40 % NH3 emissions reduction decreases regional average NH3 concentrations by 47&ndash;49 %, while sensitivities of NH4+ concentrations decrease in the order Euro_Medi (Europe and Mediterranean, 18 %), East Asia (15 %), North America (12 %), and South Asia (4 %), reflecting the increasing regional ammonia-richness. A disbenefit is the increased SO2 concentrations in these regions (10&ndash;16 % for 40 % NH3 emissions reductions) because reduced NH3 levels decrease SO2 deposition by altering atmospheric acidity. The 40 % NOx emissions reductions decrease NOx concentrations in East Asia by 45 %, Euro_Medi and North America by ~38 %, and South Asia by 22 %, whilst decreases in fine NO3- are regionally reversed, which is related to enhanced O3 levels in East Asia (and also, but by less, in Euro_Medi), and decreased O3 levels in South Asia (and also, but by less, in North America). Consequently, the oxidation of NOx to NO3- and of SO2 to SO42- is enhanced in East Asia but decreased in South Asia, which in East Asia causes a more effective decrease in NOx and SO2 but a less effective decrease in NO3- and even an increase in SO42-; in South Asia it causes a less effective decrease in NOx and an increase in SO2 but a more effective decrease in NO3- and SO42-. For regional policy making, it is thus important to reduce NH3, NOx and SOx emissions together and/or go for stronger reductions to minimise such adverse effects in East Asia and Euro_Medi. Reductions in SOx emissions are slightly more effective for SO2 than SO42-. A disbenefit is that SOx emissions reductions increase NH3 total deposition and ecosystem eutrophication (~12 % increase for 40 % emissions reduction). PM2.5 mitigation in South Asia is most sensitive to 40 % SOx reduction (3.10 &mu;g m-3, 10 %) and least sensitive to NH3 reduction (0.29 &mu;g m-3, 1 %), which is because South Asia is so ammonia-rich that reducing NH3 has little impact. The most effective measure for North America is reducing NOx emissions with an 8 % (0.63 &mu;g m-3) decrease in PM2.5 in response to a 40 % reduction. In Euro_Medi, the sensitivities of PM2.5 to 40 % individual emissions reductions range 5&ndash;8 % (0.55&ndash;0.82 &mu;g m-3). In the UK and Scandinavia PM2.5 is more sensitive to NH3, in central Europe it is more sensitive to NOx, while in the Mediterranean it is more sensitive to SOx. In East Asia, reductions in SOx, NOx and NH3 emissions are almost equally effective with PM2.5 sensitivities to 40 % reductions of 7&ndash;8 % (1.89&ndash;2.33 &mu;g m-3). Due to the varying contributions of SIA, PM2.5 sensitivities to 40 % collective reductions in all 3 precursors decrease in the order East Asia (20 %), Euro_Medi and North America (17 %), South Asia (13 %). The geographically-varying non-linear chemical responses of Nr, Sr, and PM2.5 to emissions reductions revealed by this work show the importance of both prioritising emissions strategies in different regions and combining several precursor reductions together to maximise the policy effectiveness.</p

Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters

In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement

Kinetic energy-free Hartree–Fock equations: an integral formulation

We have implemented a self-consistent feld solver for Hartree–Fock calculations, by making use of Multiwavelets and Multiresolution Analysis. We show how such a solver is inherently a preconditioned steepest descent method and therefore a good starting point for rapid convergence. A distinctive feature of our implementation is the absence of any reference to the kinetic energy operator. This is desirable when Multiwavelets are employed, because diferential operators such as the Laplacian in the kinetic energy are challenging to represent correctly. The theoretical framework is described in detail and the implemented algorithm is both presented in the paper and made available as a Python notebook. Two simple examples are presented, highlighting the main features of our implementation: arbitrary predefned precision, rapid and robust convergence, absence of the kinetic energy operator

Checks and Balances in Autoimmune Vasculitis

Age-associated changes in the immune system including alterations in surface protein expression are thought to contribute to an increased susceptibility for autoimmune diseases. The balance between the expression of coinhibitory and costimulatory surface protein molecules, also known as immune checkpoint molecules, is crucial in fine-tuning the immune response and preventing autoimmunity. The activation of specific inhibitory signaling pathways allows cancer cells to evade recognition and destruction by the host immune system. The use of immune checkpoint inhibitors (ICIs) to treat cancer has proven to be effective producing durable antitumor responses in multiple cancer types. However, one of the disadvantages derived from the use of these agents is the appearance of inflammatory manifestations termed immune-related adverse events (irAEs). These irAEs are often relatively mild, but more severe irAEs have been reported as well including several forms of vasculitis. In this article, we argue that age-related changes in expression and function of immune checkpoint molecules lead to an unstable immune system, which is prone to tolerance failure and autoimmune vasculitis development. The topic is introduced by a case report from our hospital describing a melanoma patient treated with ICIs and who subsequently developed biopsy-proven giant cell arteritis. Following this case report, we present an in-depth review on the role of immune checkpoint pathways in the development and progression of autoimmune vasculitis and its relation with an aging immune system