bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ellectromotlve Force Between Bodies In Contact
Authors: Maxwell James Clerk 
Published: November 2023

Abstract
The Potentials of Different Substances in Contact.
246.J If we define the potential of a hollow conducting vessel as the potential of the air inside the vessel, we may ascertain this potential by means of an electrometer as described in Part I, Art. 221.
If we now take two hollow vessels of different metals, say copper and zinc, and put them in metallic contact with each other, and then test the potential of the air inside each vessel, the potential of the air inside the zinc vessel will be positive as compared with that inside the copper vessel. The difference of potentials depends on the nature of the surface of the insides of the vessels, being greatest when the zinc is bright and when the copper is coated with oxide.
Resistance and conductivity in three dimensions
Authors: Maxwell James Clerk 
Published: November 2023

Abstract
297.J Let the components of the current at any point be u, v,w.
Let the components of the electromotive intensity be X, Y, Z. The electromotive intensity at any point is the resultant force on a unit of positive electricity placed at that point. It may arise (1) from electrostatic action, in which case if Vis the potential,
On the induction of electric currents.
Authors: Maxwell James Clerk 
Published: November 2023

Abstract
The discovery by Örsted of the magnetic action of an electric current led by a direct process of reasoning to that of magnetization by electric currents, and of the mechanical action between electric currents. It was not, however, till 1831 that Faraday, who had been for some time endeavouring to produce electric currents by magnetic or electric action, discovered the conditions of magneto-electric induction. The method which Faraday employed in his researches consisted in a constant appeal to experiment as a means of testing the truth of his ideas, and a constant cultivation of ideas under the direct influence of experiment. In his published researches we find these ideas expressed in language which is all the better fitted for a nascent science, because it is somewhat alien from the style of physicists who have been accustomed to establish mathematical forms of thought.
General equations of the electromagnetic field.
Authors: Maxwell James Clerk 
Published: November 2023

Abstract
In our theoretical discussion of electrodynamics we began by assuming that a system of circuits carrying electric currents is a dynamical system, in which the currents may be regarded as velocities, and in which the coordinates corresponding to these velocities do not themselves appear in the equations. It follows from this that the kinetic energy of the system, in so far as it depends on the currents, is a homogeneous quadratic function of the currents, in which the coefficients depend only on the form and relative position of the circuits. Assuming these coefficients to be known, by experiment or otherwise, we deduced, by purely dynamical reasoning, the laws of the induction of currents, and of electromagnetic attraction. In this investigation we introduced the conceptions of the electrokinetic energy of a system of currents, of the electromagnetic momentum of a circuit, and of the mutual potential of two circuits.
Lattice Bhatnagar–Gross–Krook
Authors: Succi Sauro 
Published: November 2023

Abstract
In the previous chapter, we have learned how to cut down the complexity of the LBE collision process by formulating a discrete scattering version of the collision operator. This scattering version is de-facto a multi-relaxation model equation in which, owing to the discreteness of velocity space, it becomes possible to analyze the spectrum of the scattering operator in full depth. This analysis delivers an exact expression for the fluid viscosity via the single eigenvalue associated with the slowest non-conserved quantity, namely the momentum flux tensor. In light of this, it is natural to wonder whether the scattering operator can be simplified further and brought down to a single-time relaxation form. The idea is again patterned after continuum kinetic theory, in particular after the celebrated Bhatnagar–Gross–Krook (BGK) model Boltzmann introduced as early as 1954. Its transcription to the discrete lattice world proves exceedingly fruitful, and it leads to a hydrodynamic-compliant kinetic equation of great simplicity and efficiency. In this chapter we shall describe the Lattice Bhatnagar–Gross–Krook scheme, LBGK for short, the ultimate LBE model in terms of simplicity and effectiveness. The main lesson taught by the self-standing LBE of the previous chapter is that the scattering matrix and local equilibria can be regarded as free parameters of the theory, to be tuned to our best purposes within the limits set by the conservation laws and numerical stability. Within this picture, the viscosity of the LB fluid is entirely controlled by a single parameter, namely the leading nonzero eigenvalue of the scattering matrix Aij . The remaining eigenvalues are then set so as to minimize the interference of non-hydrodynamic modes (ghosts) with the dynamics of macroscopic observables. This spawns a very natural question: since transport is related to a single nonzero eigenvalue, why not simplify things further by choosing a one parameter scattering matrix? The point, raised almost simultaneously by a number of authors [54], is indeed well taken.
Lbe In The Framework Of Computational Fluid Dynamics
Authors: Succi Sauro 
Published: November 2023

Abstract
The LBE lies at the crossroad between two distinct lines of thought, one that views it as an appealing method to compete with numerical fluid mechanics and the other that sees it rather as a sort of ‘telescope’ of molecular dynamics. This ‘dual’ nature of LBE is a potential source of richness and of some confusion too. Therefore, after having covered the basic theory of LBE and a set of representative fluid dynamics applications, it is now time to try to put LBE in a critical perspective within the broader framework of Computational Fluid Dynamics (CFD).
Microsatellites and other simple sequences: genomic context and mutational mechanisms
Authors: Hancock John M 
Published: November 2023

Abstract
'Microsatellite' is now the commonest term used to describe tandem repeats of short sequence motifs (no more than six bases long). Microsatellites have been found in every organism investigated so far. They may be highly polymorphic, especially if long and uninterrupted, and they are therefore useful genetic markers. Microsatellite-like sequences made up of concentrations of specific motifs that are not tandemly repeated are known as cryptically simple, and such sequences are also widespread, although generally more common in organisms with large genomes. The functional significance of such sequences is still unknown although they are sometimes found within exons and have been associated with diseases. Microsatellites appear to be more or less uniformly distributed across eukaryotic genomes, but are under-represented in coding regions, and perhaps telomeres. Repeats of poly(A)/poly(T) are the most common microsatellites in all genomes, but beyond that different genomes show subtly different frequency distributions. Genetic and other studies suggest that slipped-strand mispairing during replication is the predominant mechanism of mutation of microsatellites, but recently an increasing amount of circumstantial evidence has also implicated recombination.
Trinucleotide expansion mutations cause diseases which do not conform to classical Mendelian expectations
Authors: Rubinsztein David C 
Published: November 2023

Abstract
Trinucleotide repeat diseases are caused by expansions of normally polymorphic trinucleotide repeat sequences in various genes. These diseases are associated with the clinical phenomenon of anticipation, where the age-at-onset tends to decrease in successive generations. This phenomenon can be explained by a tendency for mutant alleles to increase repeat number when transmitted through the germline and by the inverse correlation between age-at-onset and repeat number. This review will introduce the clinical and molecular characteristics of these diseases and consider the mutation processes of both normal and mutant alleles at these loci.
Using microsatellites to measure the fitness consequences of inbreeding and outbreeding
Authors: Pemberton J M , Coltman D W , Coulson T N , Slate J 
Published: November 2023

Abstract
Due to the practical difficulties of measuring inbreeding in the field, the fitness consequences of inbreeding and outbreeding have been poorly documented in natural populations. In this chapter we explore the use of microsatellite variation as a tool for measuring how inbred or outbred an individual is. We first point out that average heterozygosity of an individual measured from microsatellite data should more closely reflect inbreeding than previous estimates using allozymes. Second, assuming the stepwise mutation model for microsatellite mutation, we propose that allele lengths can be used to estimate an individual internal distance measure, mean d2, which represents the average time to coalescence for the microsatellites carried by the two gametes giving rise to an individual. Using two vertebrate data sets, we show that mean d2 explains variation in neonatal fitness-related traits which is not explained by individual heterozygosity. We speculate that the most likely source of allele-length variation in natural populations is migration between diverged populations, and that individuals with high mean d2 are fitter because
Riemann surfaces and integrable systems
Authors: Hitchin Nigel 
Published: November 2023

Abstract
To do so requires using the basic language of Riemann surfaces and the first two sections will be taken up with a rapid treatment of the subject. In lectures three and four we shall look at the perhaps less standard material of vector bundles on Riemann surfaces. The fifth lecture is on Lax pairs and their relation to line bundles. In the final lecture we shall look at algebraically completely integrable Hamiltonian systems—a general context of which many of these Lax pair equations form part.
Quantifying Surprise in the Data and Model Verification
Authors: Bayarri M J , Berger James O 
Published: November 2023

Abstract
P-values are often perceived as measurements of the degree of surprise in the data, relative to a hypothesized model. They are also commonly used in model (or hypothesis) verification, i.e., to provide a basis for rejection of a model or hypothesis. We first make a distinction between these two goals: quantifying surprise can be important in deciding whether or not to search for alternative models, but is questionable as the basis for rejection of a model. For measuring surprise, we propose a simple calibration of the p-value which roughly converts a tail area into a Bayes factor or ‘odds’ measure. Many Bayesians have suggested certain modifications of p-values for use in measuring surprise, including the predictive p-value and the posterior predictive p-value. We propose two alternatives, the conditional predictive p-value and the partial posterior predictive p-value, which we argue to be more acceptable from Bayesian (or conditional) reasoning.
Nested Hypothesis Testing: The Bayesian Reference Criterion
Authors: Bernardo José m. 
Published: November 2023

Abstract
It is argued that hypothesis testing problems are best considered as decision problems concerning the choice of a usejul probability model. Decision theory, information measures and reference analysis, are combined to propose a non-subjective Bayesian approach to nested hypothesis testing, the Bayesian Reference Criterion (BRC). The results are compared both with frequentist based procedures, and with the use of Bayes factors. The theory is illustrated with stylized examples, where alternative approaches may easily be compared.
Bayesian Models for Spatially Correlated Disease and Exposure Data
Authors: Best Nicola G , Arnold Richard A , Thomas Andrew , Waller Lance A , Conlon Erin M 
Published: November 2023

Abstract
The study of geographical patterns of disease has a long tradition in epidemiology and is useful for generating and refining aetiological hypotheses. Area-specific incidence/mortality rates or relative risks are estimated using count data on the number of cases of disease and the population at risk in each area within the study region. When the disease of interest is relatively rare and/or the geographical areas are small, the counts tend to be low and associated sampling variation is high. Such data also often exhibit spatial correlation, possibly due to the influence of unmeasured or unknown risk factors which themselves vary systematically in space. Analysis of such data presents a number of statistical problems which have recently been addressed using Bayesian hierarchical models with Markov random field (MRF) priors. These models extend naturally to allow inclusion of area-level covariates, thus facilitating geographical correlation studies. However, the sensitivity of these MRF models to the assumed form of the spatial covariance function, the choice of neighbourhood structure over which the Markov random field extends, and the specification of the hyperprior distributions, is poorly understood. In this paper, we address some of these issues by investigating the properties of a variety of MRF models applied to simulated data on cancer incidence in Scottish districts. We also address some of the convergence problems associated with the Markov chain Monte Carlo algorithms used to implement such MRF models, and discuss methods for model comparison and diagnostics in this context.
Simulated Sintering: Markov Chain Monte Carlo With Spaces of Varying Dimensions
Authors: Liu Jun S , Sabatti Chiara 
Published: November 2023

Abstract
In an effort to extend the tempering methodology, we propose simulated sintering as a general framework for designing Markov chain Monte Carlo algorithms. To implement sintering, one identifies a family of probability distributions, all related to the target one and defined on spaces of different dimensions. Then, a Markov chain is constructed to move across these spaces, with the hope that the fast mixing of transitions in lower-dimensional spaces facilitates the simulation from the target distribution. Two types of sintering are discussed: conditional sintering, which is motivated by the multigrid Monte Carlo idea and can be regarded as a generalization of the Gibbs sampler; and marginal sintering, which can be achieved by reversible jump MCMC. To help mixing in a reversible jump MCMC algorithm, we suggest incorporating the dynamic weighting method proposed by Wong and Liang. Examples in graphical modeling and computational biology illustrate how these techniques can be applied.
Computationally Efficient Methods for Selecting Among Mixtures of Graphical Models
Authors: Thiesson B , Meek C , Chickering D M , Heckerman D 
Published: November 2023

Abstract
We describe computationally efficient methods for Bayesian model selection. The methods select among mixtures in which each mixture component is a directed acyclic graphical model (mixtures of DAGs or MDAGs), and can be applied to incomplete data sets. The model-selection criterion that we consider is the posterior probability of the model (structure) given data. Our model-selection problem is difficult because (1) the number of possible model structures grows super-exponentially with the number of random variables and (2) missing data necessitates the use of computationally slow approximations of model posterior probability. We argue that simple search-and-score algorithms are infeasible for a variety of problems, and introduce a feasible approach in which parameter and structure search is interleaved and expected data is treated as real data. Our approach can be viewed as the combination of (1) a modified Cheeseman-Stutz asymptotic approximation for model posterior probability and (2) the Expectation-Maximization algorithm. We evaluate our procedure for selecting among MDAGs on synthetic and real examples.
A Bayesian Proposal for the Analysis of Stationary and Nonstationary AR(1) Time Series
Authors: Marinucci Domenico , Petrella Lea 
Published: November 2023

Abstract
Default Bayesian analysis for the AR(1) model is considered and an improper prior is suggested, the choice being motivated by consideration of the functional relationship between the autoregressive parameter ρ and the variance of the process in a time series framework. We discuss the initialization issue under both stationarity and nonstationarity, and we propose a procedure that avoids discontinuities in statistical inference. We present numerical evidence, based on frequentist criteria, on the performance of the suggested prior and of the fractional Bayes factor when comparing stationary versus nonstationary models.
Bayes Sequential Decision Theory in Clinical Trials
Authors: Qian Wendi , Brown Philip J 
Published: November 2023

Abstract
We give a Bayesian analysis of the group sequential clinical trial to compare an experimental treatment with the standard treatment. Survival time is modelled as exponential. The trial is monitored at specified time points, either after fixed time intervals or after a fixed number of failures. The group sequential trial may consequently be modelled as a straightforward sequential trial in which survival time is the sum of exponential random variables, that is it has a gamma distribution. We use Bayes sequential decision theory to analyse the trial. The feature of this which is technically demanding is the need, after each observation, to look forward to see whether or not to continue sampling or to stop and make a terminal decision. This typically requires the nested sequence of integrations and minimisations. We provide two approximations: firstly taking the logarithm ofthe gamma random variable as normal; secondly making a reduction to logrank statistics. Monte Carlo simulations show both approximations to be comparable with respect to frequentist and Bayesian characteristics and to have good robustness with respect to prior specifications.
The evolution of many-celled organisms
Authors: Maynard Smith John , SzathmáRy EöRs 
Published: November 2023

Abstract
An animal’s body is composed of many millions of cells, of many different kinds—muscle cells, nerve cells, blood cells of various kinds, and so on. Organisms of this kind have evolved independently on three occasions, giving rise to animals, plants, and fungi. The third of these groups is less complex than the other two, but a mushroom is still a fairly elaborate structure. There are in addition many kinds of simpler multicellular organisms, with only a few types of cells: Volvox, a hollow green sphere of ciliated cells, with germinal cells inside, is a charming example.
Animal societies
Authors: Maynard Smith John , SzathmáRy EöRs 
Published: November 2023

Abstract
Animal societies with a complex division of labour between the members are of three kinds, and have evolved by three different routes. In this chapter we discuss insect colonies—ants, bees, wasps, and termites—and, more briefly, the colonies formed by some marine invertebrates, which also consist of individuals specialized to perform different roles. In the next chapter we discuss human societies. Apart from the division of labour, and the economic advantages that follow, the three kinds of society have one other thing in common. In all cases, the different kinds of individual are genetically similar: the differences between queen and workers in a bee colony, or between farmer, teacher, and shop-keeper in a human society, arise not from genetics but from the response of similar genotypes to different social circumstances. What a biologist has to explain is how a genotype could have evolved that can respond so differently to different environmental influences.
Connectivity of the rat amygdaloid complex
Authors: Pitkanen Asia 
Published: November 2023

Abstract
The rat amygdala is a nuclear complex composed of 13 nuclei and cortical regions and their subdivisions. Recent anterograde and retrograde studies demonstrate that each nucleus, and even each nuclear subdivision is uniquely interconnected with other amygdaloid nuclei or brain areas. A view emerging from anatomical studies proposes that functional studies of the amygdala, including lesion and imaging studies, would benefit from analyses at the nuclear and subdivisional levels. This review summarizes the principles of amygdala neuronal wiring, and based on that attempts to predict the functional consequences when some of the amygdala nuclei or subdivisions are damaged.
Covalent derivatization of myosin
Authors: Sellers James R 
Published: November 2023

Abstract
Vertebrate skeletal muscle myosin has been covalently modified by many reagents on a limited number of defined residues (Table 14). The most commonly modified residue is Cys 707, termed SH1, which is highly reactive with a variety of sulfhydryl directed compounds (Table 14). The second most commonly modified residue is the nearby Cys 697 which is called SH2. Most studies that have modified these two residues have not confirmed the specificity of labelling with sequence or peptide analysis. Instead, their modification is usually monitored by changes in the high salt, nonphysiological ATPase activities [2909]. Modification of SH1 inhibits the K+EDTA ATPase activity while activating the ca2+ATPase activity. In addition, the actin-activated MgATPase is inhibited and the MgATPase in the absence of actin is activated.
Magnetic microstructures — a paradigm of multiscale problems
Authors: Moran Bill , Avdonin Sergei 
Published: November 2023

Abstract
Ferromagnetic materials display a complex microstructure of magnetic domains, walls, Bloch lines and singular points ranging from 100 pm down to a few nm and beyond (see Fig. 1). Understanding the formation and the overall effects of these structures is crucial for a number of key technology applications. At the same time the rich source of experimental data and the simple mathematical formulation makes the analysis of magnetic microstructures an excellent model problem to develop new mathematical tools for the understanding of multiscale problems, which are ubiquitous in science.
Advancing interfaces: level set and fast marching methods
Authors: Sethian J .A 
Published: November 2023

Abstract
In this article, we review past work on Level Set Methods, introduced by Osher and Sethian in [20], and Fast Marching Methods, introduced by Sethian in [25], for tracking propagating interfaces in two and three space dimensions. Both sets of techniques are based on a partial differential equations view of interface motion, and rely on the use of the theory of viscosity solutions, upwind finite difference schemes for hyperbolic conservation laws, and the theory of curve and surface evolution developed in [23]. Both sets of techniques require an adaptive methodology to obtain computational efficiency. We briefly review some of these methods, and show some examples of some applications.
Cardiovascular Flow Modelling and Measurement with Application to Clinical Medicine
Authors: Nash G B 
Published: November 2023

Abstract
This book is collection of papers on the main topics of cardiovascular modelling and measurements. Some of the results show how to calculate many non-linear aspects of fluid flow and the turbulence in the arteries and the bifurcation junctions of the cardiovascular system. There are three themes to the papers: first, the fundamental concepts of fluid dynamics and turbulence in the system; the second theme is the flow modelling in arteries and bypass graft; the third section is about haemorheology and haemodynamics and explores the factors that play a role in coronary circulation using data from patients with ischaemic heart disease and acute myocardial infarction.