Absorbing boundary conditions for numerical simulation of waves

In practical calculations, it is often essential to introduce artificial boundaries to limit the area of computation. Here we develop a systematic method for obtaining a hierarchy of local boundary conditions at these artifical boundaries. These boundary conditions not only guarantee stable difference approximations, but also minimize the (unphysical) artificial reflections that occur at the boundaries.     

A consistent course of events or a series of coincidences: nursing in Poland from the 19th to the 21st century

The development of nursing began in Poland much later than it did elsewhere, for instance in the United Kingdom, the United States, or Germany, and it came up against difficult conditions. After a brief twenty‐year period of development between 1918 and 1939, it almost stalled during the war (1939–45), only to be followed by nearly twenty years of chaos. Nursing started to come out of this difficult period at the beginning of the 1960s. The turn of the 21st century saw the emergence of extensive professional development and training opportunities for nurses. This change was brought about as much by political, social and economic issues, health care requirements, and the advancement of science, medicine, the birth of humanitarism, the growth of the feminist movement, the European Agreement on the Instruction and Education of Nurses, the WHO European Strategy for Nursing and Midwifery Education, the Bologna declaration, as well as the activities undertaken by the European Union, the International Council of Nurses, the American and Polish Red Cross, the Rockefeller Foundation, the Polish Association of Nurses, and the professional self‐governing body. The transformation of nursing into an independent profession was further boosted by physicians deeply involved in the issue and female pioneers of nursing.     

Stochastic and mesoscopic models for tropical convection

A new way to parametrize certain aspects of tropical convection through stochastic and mesoscopic models is developed here. The technical idea is to adapt tools from statistical physics and materials science to model important unresolved features of tropical convection. This new strategy consists of modeling the unresolved effects of convective inhibition in a coarse mesh mesoscopic parametrization through a "heat bath" model involving a stochastic spin flip model with very natural interaction rules for convective inhibition combined with a suitable external potential defined by the coarse mesh values. In turn, the values of the order parameter from this heat bath alter the vertical mass flux in regions of deep convection. Both stochastic and systematic deterministic mesoscopic parametrizations are developed here. The deterministic mesoscopic models derived in this fashion exhibit new phenomena such as multiple radiative equilibria in suitable parameter regimes. The simplest first numerical experiments reported here with the mesoscopic deterministic parametrization qualitatively reproduce several key features of the observational record regarding convectively coupled tropical waves. The systematic stochastic modeling strategy proposed here could also be very useful for capturing other features of tropical convection such as those involving cloud radiation feedbacks.     

Coarse-grained stochastic processes for microscopic lattice systems

Diverse scientific disciplines ranging from materials science to catalysis to biomolecular dynamics to climate modeling involve nonlinear interactions across a large range of physically significant length scales. Here a class of coarse-grained stochastic processes and corresponding Monte Carlo simulation methods, describing computationally feasible mesoscopic length scales, are derived directly from microscopic lattice systems. It is demonstrated below that the coarse-grained stochastic models can capture large-scale structures while retaining significant microscopic information. The requirement of detailed balance is used as a systematic design principle to guarantee correct noise fluctuations for the coarse-grained model. The coarse-grained stochastic algorithms provide large computational savings without increasing programming complexity or computer time per executive event compared to microscopic Monte Carlo simulations.     

Distinct metastable atmospheric regimes despite nearly Gaussian statistics: a paradigm model

A controversial topic in the recent climate modeling literature is the fashion in which metastable low-frequency regimes in the atmosphere occur despite nearly Gaussian statistics for these planetary waves. Here a simple 57-mode paradigm model for such metastable atmospheric regime behavior is introduced and analyzed through hidden Markov model (HMM) analysis of the time series of suitable low-frequency planetary waves. The analysis of this paradigm model elucidates how statistically significant metastable regime transitions between blocked and zonal statistical states occur despite nearly Gaussian behavior in the associated probability distribution function and without a significant role for the low-order truncated nonlinear dynamics alone; turbulent backscatter onto the three-dimensional subspace of low-frequency modes is responsible for these effects. It also is demonstrated that suitable stochastic mode reduction strategies, which include both augmented cubic nonlinearity and multiplicative noise, are also capable of capturing the metastable low-frequency regime behavior through a single stochastic differential equation compared with the full turbulent chaotic 57-mode model. This feature is attractive for issues such as long-term weather predictability. Although there have been many applications of HMM in other sciences, this work presents a previously undescribed application of HMM analysis to atmospheric low-frequency variability and points the way for further applications including their use in extended range predictability.     

Glycophorin A on normal and leukemia cells detected by monoclonal antibodies, including a new monoclonal antibody reactive with glycophorins A and B

A new hemagglutinating monoclonal antibody, MoAb31, detected glycophorins A and B in Western blots. Results with enzyme-modified erythrocytes indicated the MoAb31 determinants were sialic acid dependent, and resided on glycophorin A on the trypsin-resistant, ficin-sensitive segment, and on glycophorin B on the ficin-sensitive segment. Another new monoclonal antibody, MoAb36, detected the Wrb antigen, located on the non-glycosylated segment of glycophorin A near its insertion into the lipid bilayer. Immunofluorescent staining of normal hematopoietic and leukemia cells with these and other monoclonal antibodies to glycophorin A demonstrated glycophorin A on erythroid cells only. Cytofluorograph analysis showed the majority of cells of the erythroleukemia cell lines K562 and HEL expressed glycophorin A, as indicated by reactivity with the monoclonal glycophorin A antibodies R10, R18, 6A7 and 10F7. However, reactivity with monoclonal antibodies to glycosylated determinants (MoAb31 and R1.3) and to the non-glycosylated segment near the membrane insertion (MoAb36, and R7.1) was reduced or absent. Expression of "missing" glycophorin A antigens on K562 and HEL could not be induced using a variety of chemical and biologically active modifiers. We conclude that glycophorin A of erythroleukemia cell lines K562 and HEL differs from glycophorin A at the surface of normal, mature erythrocytes with respect to reactivity with monoclonal glycophorin A antibodies.     

Persistent high NTpro-BNP concentration as a negative prognostic factor in patients with decompensated heart failure

INTRODUCTION: Monitoring of natriuretic peptide concentration may be useful for the identification of high-risk patients presenting with decompensated chronic heart failure (CHF). AIM: Assessment of the predicting value of a significant decrease (by > or =20% vs. baseline) of N-terminal proBNP (NTpro-BNP, ROCHE) concentration during hospitalisation in patients with decompensated CHF. METHODS: This study involved 54 patients admitted to our centre because of CHF decompensation. Concentration of NTpro-BNP was measured on admission and at discharge from hospital. Primary end-points of this study were overall mortality and mortality with a number of cardiovascular-related readmissions. RESULTS: Mean NTpro-BNP concentration on admission was 7435+/-10040 pg/ml and at the time of discharge from hospital -- 4816+/-7822 pg/ml. In 31 (57%) patients a significant decrease (> or =20% vs baseline value) in NTpro-BNP level (mean: -58%+/-21%) was noted, while in the remainder (23 patients; 43%) neither an increase nor a decrease in NTpro-BNP levels was observed (mean: +72%+/-132%) despite optimal treatment and stabilisation of the clinical status. The mean follow-up duration was 358+/-240 days. Cox analysis showed that the absence of significant NTpro-BNP level decrease was associated with an increased risk of death -- RR: 3.69 (95% CI: 1.10-12.37; p=0.035) and was the single independent risk factor for readmission due to cardiovascular-related reasons and/or death -- RR: 2.29 (95% CI: 1.20-4.35; p=0.01). In the group of 23 patients with an increase or decrease in NTpro-BNP concentration of more than or equal to 20%, the survival rate was 65% vs. 87% in the remainder (p=0.02). CONCLUSIONS: The lack of a significant (> or =20%) decrease of NTpro-BNP level during hospitalisation correlates with a higher mortality and rate of readmissions. NTpro-BNP level monitoring may be of clinical importance for risk stratification in patients hospitalised for decompensated CHF.     

Conceptual dynamical models for turbulence

Understanding the complexity of anisotropic turbulent processes in engineering and environmental fluid flows is a formidable challenge with practical significance because energy often flows intermittently from the smaller scales to impact the largest scales in these flows. Conceptual dynamical models for anisotropic turbulence are introduced and developed here which, despite their simplicity, capture key features of vastly more complicated turbulent systems. These conceptual models involve a large-scale mean flow and turbulent fluctuations on a variety of spatial scales with energy-conserving wave–mean-flow interactions as well as stochastic forcing of the fluctuations. Numerical experiments with a six-dimensional conceptual dynamical model confirm that these models capture key statistical features of vastly more complex anisotropic turbulent systems in a qualitative fashion. These features include chaotic statistical behavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuations whereas the turbulent fluctuations have decreasing energy and correlation times at smaller scales, with nearly Gaussian pdfs for the large-scale fluctuations and fat-tailed non-Gaussian pdfs for the smaller-scale fluctuations. This last feature is a manifestation of intermittency of the small-scale fluctuations where turbulent modes with small variance have relatively frequent extreme events which directly impact the mean flow. The dynamical models introduced here potentially provide a useful test bed for algorithms for prediction, uncertainty quantification, and data assimilation for anisotropic turbulent systems.Understanding the complexity of anisotropic turbulence processes over a wide range of spatiotemporal scales in engineering shear turbulence (1–3) as well as climate atmosphere ocean science (4–6) is a grand challenge of contemporary science. This is especially important from a practical viewpoint because energy often flows intermittently from the smaller scales to affect the largest scales in such anisotropic turbulent flows. The typical features of such anisotropic turbulent flows are the following (2–4):

• (A)The large-scale mean flow is usually chaotic but more predictable than the smaller-scale fluctuations. The overall single point probability distribution function (pdf) of the flow field is nearly Gaussian whereas the mean flow pdf is sub-Gaussian, in other words, with less extreme variability than a Gaussian random variable.
• (B)There are nontrivial nonlinear interactions between the large-scale mean flow and the smaller-scale fluctuations which conserve energy.
• (C)There is a wide range of spatial scales for the fluctuations with features where the large-scale components of the fluctuations contain more energy than the smaller-scale components. Furthermore, these large-scale fluctuating components decorrelate faster in time than the mean-flow fluctuations on the largest scales, whereas the smaller-scale fluctuating components decorrelate faster in time than the larger-scale fluctuating components.
• (D)The pdfs of the larger-scale fluctuating components of the turbulent field are nearly Gaussian, whereas the smaller-scale fluctuating components are intermittent and have fat-tailed pdfs, in other words, a much higher probability of extreme events than a Gaussian distribution (see figures 8.4 and 8.5 from ref. 3 for such experimental features in a turbulent jet).

The goal here is to develop the simplest conceptual dynamical model for anisotropic turbulence that captures all of the features in (A)–(D) in a transparent qualitative fashion. In contrast with deterministic models of turbulence which are derived by Galerkin truncation of the Navier–Stokes equation (7) and do not display all of the features in (A)–(D), the conceptual models developed here are low-dimensional stochastic dynamical systems; the nonlinear interactions between the large-scale mean-flow component and the smaller-scale fluctuating components are completely deterministic but the potential direct nonlinear interactions between the smaller-scale fluctuating components are modeled stochastically by damping and stochastic forcing (6, 8). The conceptual models developed here are not derived quantitatively from the Navier–Stokes equations but are developed to capture the key features in anisotropic turbulent flows listed in (A)–(D) by mimicking key physical processes. Besides aiding the understanding of anisotropic turbulent flows, such conceptual models are useful for designing and testing numerical algorithms for prediction and data assimilation in such complex turbulent systems.