Viscosity and Diffusion: Crowding and Salt Effects in Protein Solutions

We report on a joint experimental-theoretical study of collective diffusion in, and static shear viscosity of solutions of bovine serum albumin (BSA) proteins, focusing on the dependence on protein and salt concentration. Data obtained from dynamic light scattering and rheometric measurements are compared to theoretical calculations based on an analytically treatable spheroid model of BSA with isotropic screened Coulomb plus hard-sphere interactions. The only input to the dynamics calculations is the static structure factor obtained from a consistent theoretical fit to a concentration series of small-angle X-ray scattering (SAXS) data. This fit is based on an integral equation scheme that combines high accuracy with low computational cost. All experimentally probed dynamic and static properties are reproduced theoretically with an at least semi-quantitative accuracy. For lower protein concentration and low salinity, both theory and experiment show a maximum in the reduced viscosity, caused by the electrostatic repulsion of proteins. The validity range of a generalized Stokes-Einstein (GSE) relation connecting viscosity, collective diffusion coefficient, and osmotic compressibility, proposed by Kholodenko and Douglas [PRE 51, 1081 (1995)] is examined. Significant violation of the GSE relation is found, both in experimental data and in theoretical models, in semi-dilute systems at physiological salinity, and under low-salt conditions for arbitrary protein concentrations

Real-time high-resolution heterodyne-based measurements of spectral dynamics in fibre lasers

Conventional tools for measurement of laser spectra (e.g. optical spectrum analysers) capture data averaged over a considerable time period. However, the generation spectrum of many laser types may involve spectral dynamics whose relatively fast time scale is determined by their cavity round trip period, calling for instrumentation featuring both high temporal and spectral resolution. Such real-time spectral characterisation becomes particularly challenging if the laser pulses are long, or they have continuous or quasi-continuous wave radiation components. Here we combine optical heterodyning with a technique of spatiooral intensity measurements that allows the characterisation of such complex sources. Fast, round-trip-resolved spectral dynamics of cavity-based systems in real-time are obtained, with temporal resolution of one cavity round trip and frequency resolution defined by its inverse (85 ns and 24 MHz respectively are demonstrated). We also show how under certain conditions for quasi-continuous wave sources, the spectral resolution could be further increased by a factor of 100 by direct extraction of phase information from the heterodyned dynamics or by using double time scales within the spectrogram approach

Mathematical modelling of CAD systems in Building Engineering

[EN] There exists a wide range of CAD systems devoted to model three-dimensional objects. Based on an intuitive creation and transformation of basic geometrical objects, the mathematical foundation of such systems is generally unknown to their users. The incorporation of this kind of software in Math classes is a fundamental key to get the attention of students of those degrees for which CAD systems are not only attractive, but also extremely important in the future professional career. The current paper deals with the experience carried out in this regard during the last five years by students of the Building Engineering Degree of the University of Seville. The methodological search of mathematical models that allow them to construct virtually real buildings has improved not only the process of teaching-learning, but also their interest in the subject and their academic efficiency. A virtual tour through their constructions is a perfect excuse to deal also with the mathematical foundation on which they are based on.[ES] Existe una amplia gama de sistemas CAD destinados a modelar objetos tridimensionales. Basados en una creación y transformación intuitiva de objetos geométricos básicos, el fundamento matemático de estas herramientas es generalmente desconocido por sus usuarios. La incorporación de las mismas en el aula de Matemáticas es una pieza clave para lograr captar la atención del alumnado de aquellas titulaciones universitarias en las que los sistemas CAD no sólo son atrayentes, sino que son además de suma importancia para la futura vida profesional. El presente artículo trata acerca de la experiencia docente llevada a cabo en este sentido durante los últimos cinco años en el Grado de Ingeniería de Edificación de la Universidad de Sevilla. La búsqueda metodológica de modelos matemáticos que les permita construir virtualmente edificios reales ha mejorado no sólo el proceso de enseñanza-aprendizaje, sino también su interés en la materia y su rendimiento académico. Un recorrido virtual a través de sus construcciones es una perfecta excusa para tratar también el fundamento matemático en los que se basan los mismosFalcón Ganfornina, RM. (2015). Modelización matemática de sistemas CAD en Edificación. Modelling in Science Education and Learning. 8(2):145-194. doi:10.4995/msel.2015.3258.SWORD1451948

Risk Factors for Canine Osteoarthritis and Its Predisposing Arthropathies: A Systematic Review

Osteoarthritis is a common clinical and pathological end-point from a range of joint disorders, that ultimately lead to structural and functional decline of the joint with associated lameness and pain. Increasing understanding of the risk factors associated with osteoarthritis will assist in addressing the significant threat it poses to the welfare of the dog population and implementing preventive measures. Presented here, is the first comprehensive systematic review and evaluation of the literature reporting risk factors for canine osteoarthritis. This paper aimed to systematically collate, review and critically evaluate the published literature on risk factors for canine osteoarthritis and its predisposing conditions such as developmental joint dysplasias, cruciate ligament degeneration, and patellar luxation. Peer-reviewed publications were systematically searched for both osteoarthritis and predisposing arthropathies on Web of Science and PubMed following PRISMA (2009) guidelines, using pre-specified combinations of keywords. Sixty-two papers met the inclusion criteria and were evaluated and graded on reporting quality. Identified risk factors included both modifiable factors (neuter status and body weight) for which intervention can potentially affect the risk of occurrence of osteoarthritis, and unmodifiable factors (sex, breed, and age) which can be used to identify individuals most “at risk.” Osteoarthritis in dogs frequently develops from predisposing arthropathies, and therefore risk factors for these are also important to consider. Papers evaluated in this study were rated as medium to high-quality; gap analysis of the literature suggests there would be significant benefit from additional research into the interactions between and relative weighting of risk factors. There are a number of examples where research outcomes are conflicting such as age and sex; and further investigation into these factors would be beneficial to attain greater understanding of the nature of these risks. Comprehensively collating the published risk factors for osteoarthritis and its predisposing conditions offers opportunities to identify possible means for control and reduction within the population through preventative methods and control strategies. These factors are highlighted here, as well as current literature gaps where further research is warranted, to aid future research direction

Quantum Computing Without Wavefunctions: Time-Dependent Density Functional Theory for Universal Quantum Computation

We prove that the theorems of TDDFT can be extended to a class of qubit Hamiltonians that are universal for quantum computation. The theorems of TDDFT applied to universal Hamiltonians imply that single-qubit expectation values can be used as the basic variables in quantum computation and information theory, rather than wavefunctions. From a practical standpoint this opens the possibility of approximating observables of interest in quantum computations directly in terms of single-qubit quantities (i.e. as density functionals). Additionally, we also demonstrate that TDDFT provides an exact prescription for simulating universal Hamiltonians with other universal Hamiltonians that have different, and possibly easier-to-realize two-qubit interactions. This establishes the foundations of TDDFT for quantum computation and opens the possibility of developing density functionals for use in quantum algorithms

Adaptive Management and the Value of Information: Learning Via Intervention in Epidemiology

Optimal intervention for disease outbreaks is often impeded by severe scientific uncertainty. Adaptive management (AM), long-used in natural resource management, is a structured decision-making approach to solving dynamic problems that accounts for the value of resolving uncertainty via real-time evaluation of alternative models. We propose an AM approach to design and evaluate intervention strategies in epidemiology, using real-time surveillance to resolve model uncertainty as management proceeds, with foot-and-mouth disease (FMD) culling and measles vaccination as case studies. We use simulations of alternative intervention strategies under competing models to quantify the effect of model uncertainty on decision making, in terms of the value of information, and quantify the benefit of adaptive versus static intervention strategies. Culling decisions during the 2001 UK FMD outbreak were contentious due to uncertainty about the spatial scale of transmission. The expected benefit of resolving this uncertainty prior to a new outbreak on a UK-like landscape would be £45–£60 million relative to the strategy that minimizes livestock losses averaged over alternate transmission models. AM during the outbreak would be expected to recover up to £20.1 million of this expected benefit. AM would also recommend a more conservative initial approach (culling of infected premises and dangerous contact farms) than would a fixed strategy (which would additionally require culling of contiguous premises). For optimal targeting of measles vaccination, based on an outbreak in Malawi in 2010, AM allows better distribution of resources across the affected region; its utility depends on uncertainty about both the at-risk population and logistical capacity. When daily vaccination rates are highly constrained, the optimal initial strategy is to conduct a small, quick campaign; a reduction in expected burden of approximately 10,000 cases could result if campaign targets can be updated on the basis of the true susceptible population. Formal incorporation of a policy to update future management actions in response to information gained in the course of an outbreak can change the optimal initial response and result in significant cost savings. AM provides a framework for using multiple models to facilitate public-health decision making and an objective basis for updating management actions in response to improved scientific understanding

Random-phase approximation and its applications in computational chemistry and materials science

The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of RPA, and its applications to realistic systems. With several illustrating applications, we discuss the implications of RPA for computational chemistry and materials science. The computational cost of RPA is also addressed which is critical for its widespread use in future applications. In addition, current correction schemes going beyond RPA and directions of further development will be discussed.Comment: 25 pages, 11 figures, published online in J. Mater. Sci. (2012

A Measurement of Rb using a Double Tagging Method

The fraction of Z to bbbar events in hadronic Z decays has been measured by the OPAL experiment using the data collected at LEP between 1992 and 1995. The Z to bbbar decays were tagged using displaced secondary vertices, and high momentum electrons and muons. Systematic uncertainties were reduced by measuring the b-tagging efficiency using a double tagging technique. Efficiency correlations between opposite hemispheres of an event are small, and are well understood through comparisons between real and simulated data samples. A value of Rb = 0.2178 +- 0.0011 +- 0.0013 was obtained, where the first error is statistical and the second systematic. The uncertainty on Rc, the fraction of Z to ccbar events in hadronic Z decays, is not included in the errors. The dependence on Rc is Delta(Rb)/Rb = -0.056*Delta(Rc)/Rc where Delta(Rc) is the deviation of Rc from the value 0.172 predicted by the Standard Model. The result for Rb agrees with the value of 0.2155 +- 0.0003 predicted by the Standard Model.Comment: 42 pages, LaTeX, 14 eps figures included, submitted to European Physical Journal

Electronic Structure Calculation by First Principles for Strongly Correlated Electron Systems

Recent trends of ab initio studies and progress in methodologies for electronic structure calculations of strongly correlated electron systems are discussed. The interest for developing efficient methods is motivated by recent discoveries and characterizations of strongly correlated electron materials and by requirements for understanding mechanisms of intriguing phenomena beyond a single-particle picture. A three-stage scheme is developed as renormalized multi-scale solvers (RMS) utilizing the hierarchical electronic structure in the energy space. It provides us with an ab initio downfolding of the global band structure into low-energy effective models followed by low-energy solvers for the models. The RMS method is illustrated with examples of several materials. In particular, we overview cases such as dynamics of semiconductors, transition metals and its compounds including iron-based superconductors and perovskite oxides, as well as organic conductors of kappa-ET type.Comment: 44 pages including 38 figures, to appear in J. Phys. Soc. Jpn. as an invited review pape

Construction of an odds model of coronary heart disease using published information: the Cardiovascular Health Improvement Model (CHIME)

Background: There is a need for a new cardiovascular disease model that includes a wider range of relevant risk factors, in particular lifestyle factors, to aid targeting of interventions and improve population models of the impact of cardiovascular disease and preventive strategies. The model needs to be applicable to a wider population including different ethnic groups, different countries and to those with and without cardiovascular disease. This paper describes the construction of the Cardiovascular Health Improvement Model that aims to meet these requirements. Method: An odds model is used. Information was taken from 2003 mortality statistics for England and Wales, the Health Survey for England 2003 and published data on relative risk in those with and without CVD and mean blood pressure values in hypertensives. The odds ratios used were taken from the INTERHEART study. Results: A worked example is given calculating the 10-year coronary heart disease risk for a 57 year-old non-diabetic male with no personal or family history of cardiovascular disease, who smokes 30 cigarettes a day and has a systolic blood pressure of 137 mmHg, a total cholesterol (TC) of 6.2 mmol/l, a high density lipoprotein (HDL) of 1.3 mol/l, and a body mass index of 21. He neither drinks regularly nor exercises. He can give no reliable information about his mental health or fruit and vegetable intake. His 10-year risk of CHD death is 2.47%. Conclusion: This paper demonstrates a method for developing a CHD risk model. Further improvements could be made to the model with additional information. The method is applicable to other causes of death