bluuebunny/crossref_metadata_2025 huggingface dataset:
An Introduction to Local Spectral Theory
Authors: Laursen Kjeld B , Neumann Michael M
Published: November 2023

Modern local spectral theory is built on the classical spectral theorem, a fundamental result in single-operator theory and Hilbert spaces. This book provides an in-depth introduction to the natural expansion of this fascinating topic of Banach space operator theory, whose pioneers include Dunford, Bishop, Foias, and others. Assuming only modest prerequisites of its readership, it gives complete coverage of the field, including the fundamental recent work by Albrecht and Eschmeier which provides the full duality theory for Banach space operators. It is highlighted by many characterizations of decomposable operators, and of other related, important classes of operators, as well as an in-depth study of their spectral properties, including identifications of distinguished parts, and results on permanence properties of spectra with respect to several types of similarity. Also found is a thorough and quite elementary treatment of the modern single- operator duality theory; this theory has many applications, both to general issues of classification and to such celebrated problems as the invariant subspace problems. A long chapter - almost a book in itself - is devoted to the use of local spectral theory in the study of spectral properties of multipliers and convolution operators. Another one describes its connections to automatic continuity theory. Written in a careful and detailed style, it contains numerous examples, many simplified proofs of classical results, and extensive references. It concludes with a list of interesting open problems, suitable for continued research.
Decomposable operators
Authors: Laursen Kjeld B , Neumann Michael M
Published: November 2023

The purpose of this chapter is to provide a streamlined introduction to the theory of decomposable operators. We assume that the reader is familiar with the elementary spectral theory of bounded linear operators on Banach spaces and the theory of normal operators on Hilbert spaces, as presented, for instance, in Conway (1990) or Rudin (1991). However, we do not presuppose any knowledge of spectral operators and local spectral theory.
Applied Smoothing Techniques for Data Analysis
Authors: Bowman Adrian W , Azzalini Adelchi
Published: November 2023

The book describes the use of smoothing techniques in statistics, including both density estimation and nonparametric regression. Considerable advances in research in this area have been made in recent years. The aim of this text is to describe a variety of ways in which these methods can be applied to practical problems in statistics. The role of smoothing techniques in exploring data graphically is emphasised, but the use of nonparametric curves in drawing conclusions from data, as an extension of more standard parametric models, is also a major focus of the book. Examples are drawn from a wide range of applications. The book is intended for those who seek an introduction to the area, with an emphasis on applications rather than on detailed theory. It is therefore expected that the book will benefit those attending courses at an advanced undergraduate, or postgraduate, level, as well as researchers, both from statistics and from other disciplines, who wish to learn about and apply these techniques in practical data analysis. The text makes extensive reference to S-Plus, as a computing environment in which examples can be explored. S-Plus functions and example scripts are provided to implement many of the techniques described. These parts are, however, clearly separate from the main body of text, and can therefore easily be skipped by readers not interested in S-Plus.
On the approximation of queueing networks in heavy traffic
Authors: Williams R J
Published: November 2023

This paper reports on the current state of research concerning approximations to the queue length or workload processes in stable but heavily loaded queueing networks. Most of the approximations that have been considered to date are justified by heavy traffic limit theorems that have a certain conventional form, namely (i) the queue length or workload processes in a sequence of heavily loaded networks are normalized by a central limit theorem type of scaling, and (ii) the weak limit of these normalized processes is a reflecting Brownian motion. Such conventional limit theorems for both open and closed networks are surveyed first, with a view to outlining their general form. Whilst there is a reasonable collection of limit theorems for single class networks and some multiclass networks (especially those with feedforward structure), recent developments have indicated that not all multiclass networks with feedback have conventional heavy traffic behavior. These developments are surveyed here and in particular, the Harrison-Williams example of an unconventional heavy traffic limit theorem for a closed analog of the Lu-Kumar/Rybko-Stolyar priority network is described.
Notes on effective bandwidths
Authors: Kelly Frank
Published: November 2023

This paper presents a personal view of work to date on effective bandwidths, emphasizing the unifying role of the concept: as a summary of the statistical characteristics of sources over different time and space scales; in bounds, limits and approximations for various models of multiplexing under quality of service constraints; and as the basis for simple and robust tariffing and connection acceptance control mechanisms for poorly characterized traffic. The framework assumes only stationarity of sources, and illustrative examples include periodic streams, fractional Brownian input, policed and shaped sources, and deterministic multiplexing.
Statistical Modelling in GLIM 4
Authors: Aitkin Murray , Francis Brain , Hinde John
Published: November 2023

This new edition of the successful multi-disciplinary text Statistical Modelling in GLIM takes into account new developments in both statistical software and statistical modelling. Including three new chapters on mixture and random effects models, it provides a comprehensive treatment of the theory of statistical modelling with generalised linear models with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is also provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions. This book is ideal for graduates and research students in applied statistics and a wide range of quantitative disciplines, including biology, medicine and the social sciences. Professional statisticians at all levels will also find it an invaluable desktop companion.
Neural Networks for Unsupervised Learning Based on Information Theory
Authors: Kay Jim
Published: November 2023

We consider the statistical and information-theoretic basis of a class of artificial neural networks for unsupervised learning and processing. Taking a single processing unit as the basic component of the networks, we define information-theoretic objective functions and a class of activation functions, and derive the gradient-ascent learning rules. Several versions of the processor are considered, namely, the case in which the processor has a single binary output, the case in which the outputs are multinomial-winner-take-all, and that in which they are multivariate binary. In this latter case, local versions of the objective function are developed and these lead to local learning rules. Finally, the issue of computational complexity is briefly discussed, an alternative approach to the modelling is developed, and approximations are mentioned.
Cognitive slowing among older adults: what kind and how much?
Authors: Fisher Donald L , Duffy Susan A , Katsikopoulos Konstantinos V
Published: November 2023

Older adults generally perform more poorly than younger adults on a variety of different measures of performance. These measures include the large range of reaction time tasks so prevalent today (e.g. Sternberg 1969), as well as the many different tests of memory, reasoning and spatial abilities first administered back in the 1940s (e.g. Hebb 1942; Cattell 1943). The argument has been made that much of the decline in performance among older adults can be traced to a single factor, cognitive slowing. Birren (e.g. 1965, 1974) was the first to propose this general line of argument, an argument which has since been vigorously pursued by a number of different investigators (e.g. Cerella 1985; Salthouse 1980, 1985). Although cognitive slowing is not the only factor that has been put forward as an explanation for the differences between younger and older adults, it has remained the dominant one and is the one upon which we will focus (for a review of the alternative potential mediators, see Salthouse 1991).
New directions for research into aging and intelligence: the development of expertise
Authors: Horn John L , Masunaga Hiromi
Published: November 2023

In this article we will review and critically evaluate what is believed, scientifically, about human cognitive capabilities and their development through adulthood. We will then discuss a major concern about this information – what appears to be wrong with it - and put forth some ideas about what is needed to fill in information that is more nearly correct. We will argue that the major thrust in research aimed at understanding the nature of human intelligence (viewed behaviourally) should be directed at understanding capabilities that emerge in adulthood. This argument stems from research findings that, for the most part, have been directed at describing cognitive declines that occur in adulthood. Yet this research has netted evidence of abilities that are maintained or that improve with advancing age. These findings have forced modifications in reductionistic assumptions that the maintenance of human intelligence is determined only by physiological (largely neurological) functions that inevitably decline in adulthood. The findings have led to questions about what, indeed, are the physiological/neurological functions that support expressions of different cognitive abilities: which of these functions are likely to deteriorate over adulthood and why. But most pertinent to the argument of this chapter, the findings have raised anew questions about what human intelligence is – in particular, what is intelligence at its highest level of expression. Here it is reasoned that development (through childhood into adulthood) i directed at realizing that highest level and that probably that apex is reached in adulthood. Thus, the question of what is intelligence becomes one of what is it that emerges in adulthood that is both different from what is called intelligence in childhood and that can be recognized as the sine qua non of human intelligence?
Hippocampal synaptic plasticity: role in spatial learning or the automatic recording of attended experience?
Authors: Morris Richard G M , Frey Uwe
Published: November 2023

This paper outlines a new hypothesis about the function of associative synaptic plasticity in the hippocampal formation, namely that it is essential for what is referred to here as the ‘ automatic recording of attended experience’ . This constitutes one component of a larger episodic memory system involving a number of brain regions (Tulving 1983; Tulving & Schacter 1994) and likely to be implemented by several neurophysiological mechanisms of plasticity. The idea is that this part of the episodic memory system of the brain is automatic in the sense that it cannot be switched off in a voluntary manner, although it can be subject to selective disruption by certain kinds of brain damage. Being automatic, it can potentially record everything to which attention is directed, including context, but this recording may only be of markers that an event has happened at a particular place rather than a detailed encoding of sensory or perceptual information. To operate effectively, such a system needs a mechan¬ ism of neuronal plasticity that can register event-context associations rapidly in a strictly correlational manner, i.e. without regard to their consistency to an organism’ s goal-directed actions.
Hippocampal and parietal involvement in human topographical memory:evidence from functional neuroimaging
Authors: Maguire Eleanor A
Published: November 2023

The ability of humans to orient and navigate successfully in the large-scale spatially-extended environments that constitute the real-world is commonly referred to as topographical orientation. Way-finding is complex and not a unitary process; there are many aspects to it including attentional, perceptual and mnestic components. Topographical disorientation, therefore, can occur because of disturbance to one or more component processes. Occasionally cases of topographical disorientation are reported and are typically described in terms of perceptual or mnestic difficulties, such as perceptual disturbance where there is an agnosia for landmarks and buildings even in well-known surroundings, often found in association with prosopagnosia (Patterson and Zangwill 1944; Landis et al. 1986); or a topographical memory disturbance, where buildings and landmarks can be recognized and recalled, but the memory for their place in space and spatial relationships is dysfunctional (DeRenzi et al. 1977; Habib and Sirigu 1987; Bottini et al. 1990; Maguire et al. 1996a). Some general conclusions about the neural basis of topographical orientation systems can be drawn from the patient literature. Damage to several brain regions can produce topographic deficits of one sort or another.
Parietal cortex and hippocampus: from visual affordances to the world graph
Authors: Arbib Michael A
Published: November 2023

Gibson (1966) observed that the pattern of optic flow, the movement of features across the retina from moment to moment, contains valuable information that could be used to guide navigation through the environment without prior recognition of objects. We adopt Gibson’ s term ‘ affordances’ for parameters for motor interactions signalled by sensory cues without the necessary intervention of ‘ high-level processes’ of object recognition. Neurological data relate human parietal function not only to impairment of a variety of affordances but also to impairment of ‘ cognitive maps’ . Bilateral parietal lobe damage often yields ‘ global spatial disorientation’ (Kase et al. 1977), a symptom complex which involves the three systems whose parietal roles are modelled in this paper: the control of eye movements; the control of the grasping of objects; and the use of ‘ cognitive maps’ in navigation. Some of these deficits can also be seen in relatively pure isolated form.
Visuospatial processing in a pure case of visual-form agnosia
Authors: Milner A David , Dijkerman H Chris , Carey David P
Published: November 2023

Visual form agnosia refers to a variety of apperceptive agnosia in which the patient’ s ability to perceive, discriminate and recognize the shape of objects is grossly impaired (Benson & Greenberg 1969). Detailed case descriptions of such patients have been given by Goldstein & Gelb (1918), Adler (1944), Benson & Greenberg (1969), Landis et al. (1982) and Milner et al. (1991), and extensive experimental studies of their perceptual abilities have been presented by the same authors, as well as by Gelb & Goldstein (1938), Efron (1969), and Campion & Latto (1985). There is a remarkable similarity among these patients, both in their pathology and in their visual symptoms. In all cases the brain damage has been bilateral and in most cases caused by carbon monoxide poisoning, the principal exceptions being the patients of Goldstein & Gelb (missile injury) and Landis et al. (mercury poisoning). Also in all cases the profound deficit in form perception is seen without any appreciable deficit in auditory or tactile perception, and in most cases without any appreciable deficit in other domains of visual perception, including colour, motion, stereopsis and even visual acuity.
Introduction
Authors: Humphreys Glyn W , Duncan John , Treisman Anne
Published: November 2023

Over the past 15 years or so there have been substantial and important developments in the cognitive neuroscience of selective perception and action. We review the role played in these developments by the component disciplines of experimental psychology, neuropsychology, electrophysiology, mathematical and computational modelling, and functional imaging. We argue that interdisciplinary work in this field has played a major part in advancing our understanding, and that there are benefits to be gained from gathering converging evidence at different levels of analysis. We discuss the relations between these arguments and the chapters presented in book.
Neural coding of 3D features of objects for hand action in the parietal cortex of the monkey
Authors: Sakata Hideo , Taira Masato , Kusunoki Makoto , Murata Akira , Tanaka Yi ji , Tsutsui Ken-ichiro
Published: November 2023

In our previous studies of hand manipulation task-related neurons, we found many neurons of the parietal association cortex which responded to the sight of three-dimensional (3D) objects. Most of the task-related neurons in the AIP area (the lateral bank of the anterior intraparietal sulcus) were visually responsive and half of them responded to objects for manipulation. Most of these neurons were selective for the 3D features of the objects. More recently, we have found binocular visual neurons in the lateral bank of the caudal intraparietal sulcus (c-IPS area) that preferentially respond to a luminous bar or plate at a particular orientation in space. We studied the responses of axis-orientation selective (AOS) neurons and surface 01ientation selective (SOS) neurons in this area with stimuli presented on a 3D computer graphics display. The AOS neurons showed a stronger response to elongated stimuli and showed tuning to the orientation of the longitudinal axis. Many of them prefe1Ted a tilted stimulus in depth and appeared to be sensitive to orientation disparity and/or width disparity. The SOS neurons showed a stronger response to a flat than to an elongated stimulus and showed tuning to the 3D orientation of the surface. Their responses increased with the width or length of the stimulus. A considerable number of SOS neurons responded to a square in a random dot stereogram and were tuned to orientation in depth, suggesting their sensitivity to the gradient of disparity. We also found several SOS neurons that responded to a square with tilted or slanted contours, suggesting their sensitivity to orientation disparity and/or width disparity. Area c-IPS is likely to send visual signals of the 3D features of an object to area AIP for the visual guidance of hand actions.
Neuropsychological studies of perception and visuomotor control
Authors: Milner A D
Published: November 2023

According to recent conceptualizations, there are two separate cortical visual systems-each with its own distinctive cortical and subcortical links—and these two systems respectively serve the functions of perception and of motor control. These ideas have been arrived at through a confluence of neuroanatomical, electrophysiological, behavioural, and neuropsychological research. It is proposed that this distinction between two broad purposes of vision and their neural bases can provide useful working procedures for analysing both (i) the nature of visuomotor processing in the normal brain and also (ii) the abnormal patterns of visual processing that are seen in certain neurological conditions.
Sustained attention deficits in time and space
Authors: Robertson Ian H , Manly Tom
Published: November 2023

We review critically the influential framework of attentional systems developed by Posner and Petersen (1990). Their proposal that three independent supramodal attentional control systems exist in the brain-selection, alertness and spatial attention respectively—is examined in the light of evidence accumulated over the last decade. We conclude that while evidence for differentiable supramodal selection and alertness systems is quite strong, the notion of a posterior supramodal spatial attention system centred in the parietal lobes is much V.’eaker. We review evidence showing that unilateral neglect consequent on parietal lesions is both strongly associated with non-lateralized attentional deficits, and strongly modifiable by manipulation of these non-spatial variables. Spatial selective attention may be better conceived of as an emergent property of competition between distributed but integrated representations of objects and space between the two hemispheres. The role of the parietal lobes in spatial selection may be related to the integration of cross¬ modal representations and motor preparation in the organisation of responses towards the environment. But the parietal lobe of the right hemisphere appears to have an additional, but as yet inadequately specified role, in the maintenance of the alert state over time and other non-lateralized aspects of attention.
Random effects models
Authors: Diggle Peter J , Heagerty Patrick J , Liang Kung-yee. , Zeger Scott L
Published: November 2023

Chapter 8 has dealt with marginal models whose regression parameters have population average interpretations. In this chapter we consider random effects models in which the regression coeficients measure the more direct infiuence of explanatory variables on the responses for heterogeneous individuals. Linear models with random effects were discussed in Section 5.2 in the context of a general framework for parametric modelling of correlation in longitudinal data.
Likelihood-based methods for categorical data
Authors: Diggle Peter J , Heagerty Patrick J , Liang Kung-yee. , Zeger Scott L
Published: November 2023

In a study of the natural history of schizophrenia, first-episode patients had disease symptoms recorded monthly for up to 10 years following initial hospitalization (Thara et al., 1994). In studies of the health effects of air pollution, asthmatic children recorded the presence or absence of wheezing each day for approximately 60 days (Yu et al., 2000). To determine whether maternal employment correlates with paediatric care utilization and both maternal stress and childhood illness, daily measurements of maternal stress (yes, no) and childhood illness (yes, no) were recorded for 28 consecutive days (Alexander and Markowitz, 1986). Lunn, et al. (2001) analyse ordinal allergic severity scores collected daily for 3 months on subjects assigned either to placebo or to one of three doses of active drug.
Time-dependent covariates
Authors: Diggle Peter J , Heagerty Patrick J , Liang Kung-yee. , Zeger Scott L
Published: November 2023

One of the main scientific advantages of conducting a longitudinal study is the ability to observe the temporal order of key exposure and outcome events. Specifically, we can determine whether changes in a covariate precede changes in the outcome of interest. Such data provide crucial evidence for a causal role of the exposure (see Chapter 2 in Rothman and Greenland, 1998).
Kinetics analysis of DNA-protein interactions by time-resolved synchrotron X-ray footprinting
Authors: Dhavan Gauri M , Chance Mark R , Brenowitz Michael
Published: November 2023

The binding of proteins to specific sequences of DNA is often the first step in the regulation of cellular events essential to cell function and growth such as transcription, DNA replication, site-specific recombination, and other processes that require DNA binding. The rates at which these protein-DNA complexes assemble is dependent upon the kinetics of each individual binding event as well as additional cooperative interactions between two or more protein molecules required for biological function. The study of the kinetics of association and dissociation of site-specific DNA contact events provides insight into the mechanism by which the complexes are formed and the role of each player in a larger nucleo-protein assembly.
Weyl and Schur Modules
Authors: Boffi Giandomenico , Buchsbaum David A
Published: November 2023

In earlier chapters we introduced a very small dose of representation theory of the general linear group when we discussed, in particular, the hook shapes. In this chapter, we will deal more comprehensively with representations of that group, over an arbitrary commutative ring, R. Our discussion will help place the material in earlier chapters in proper perspective, and will move us forward to some interesting observations relating to determinantal ideals and other matters.
Plants as insect food: not the ideal
Authors: Schoonhoven Louis M , Loon Joop J A van , Dicke Marcel
Published: November 2023

The subject of this Chapter-plants as food for herbivorous insects-touches the heart of insectplant biology. Its theme can be captured in two basic questions. First, what do plants offer to insects by way of nutrition? And second, what do insects need for optimal growth and reproduction? Answering these two questions is seriously hindered by the fact that (1) the chemical composition of plants, as noted before, varies among species in both space and time, and (2) the nutritional requirements of insects vary between species and with developmental stage and environmental conditions.
Functional magnetic resonance imaging (fMRI)
Authors: Honey Garry D , McGuire Phillip K , Bullmore Edward T
Published: November 2023

The first report of localized changes in cerebral blood oxygenation in the occipital cortex following visual stimulation in humans (Belliveau et al. 1991) was of seminal importance to neuropsychiatric research. Only 3 years following this technological development, which enabled non-invasive visualization of in vivo human brain function, the application of the technique was first reported in psychiatric patients (Renshaw et al. 1994; Wenz et al. 1994). This ushered in a new era in functional neuroimaging, and provided a powerful tool in cognitive neuroscience to explore both normal and abnormal brain function, complementing earlier techniques such as positron emission tomography (PET), single-photon emission computed tomography (SPECT), and non-topographic electrophysiological procedures such as electron-cephalography (EEG) and evoked response potentials (ERPs).
Bayesian Treed Generalized Linear Models
Authors: Chipman Hugh A , George Edward I , Mcculloch Roberte.E
Published: November 2023

For the standard regression setup, conventional tree models partition the predictor space into regions where the variable of interest Y, can be approximated by a constant. A treed model extends this idea by allowing a functional relationship between Y and the predictors within each region. As opposed to using a single model to describe the global variation of the response, treed models allow for local modelling across the predictor space. In this paper, we consider treed versions of generalized linear models (GLMs) and propose a Bayesian approach to finding and fitting such models. The potential of this approach is illustrated with a treed Poisson regression.
Bayesian Harmonic Models for Musical Signal Analysis
Authors: Davy Manuel , Godsill Simon J
Published: November 2023

This paper is concerned with the Bayesian analysis of musical signals. The ultimate aim is to use Bayesian hierarchical structures in order to infer quantities at the highest level, including such things as musical pitch, dynamics, timbre, instrument identity, etc. Analysis of real musical signals is complicated by many things, including the presence of transient sounds, noises, and the complex structure of musical pitches in the frequency domain. The problem is truly Bayesian in that there is a wealth of (often subjective) prior knowledge about how musical signals are constructed, which can be exploited in order to achieve more accurate inference about the musical structure. Here we propose developments to an earlier Bayesian model that describes each component “note” at a given time in terms of a fundamental frequency, partials (“harmonics”), and amplitude. This basic model is modified for greater realism to include non-white residuals, time-varying amplitudes and partials “detuned” from the natural linear relationship. The unknown parameters of the new model are simulated using a variable dimension MCMC algorithm, leading to a highly sophisticated analysis tool. We discuss how the models and algorithms can be applied for feature extraction, polyphonic music transcription, source separation, and restoration of musical sources.
Exact Bayesian Inference for a Class of Nonlinear Systems with Application to Robotic Assembly
Authors: Lefebvre Tyne , Gadeyne Klaas , Bruyninckx Herman , Schutter Joris De
Published: November 2023

This paper presents a new finite-dimensional Bayesian filter. The filter calculates the exact analytical expression for the posterior probability density function (pdf) of static systems with any kind of nonlinear measurement equation subject to Gaussian measurement uncertainty. The paper also extends this filter to a limited class of dynamic systems. The filter is applied to the estimation of the inaccurately known position and orientation of two mating parts during autonomous robotic assembly. The sufficient statistics of the posterior pdf are obtained by Kalman Filter formulas, making online estimation possible. Exact finite-dimensional filters exist only for a small class of systems. The best known example is the Kalman Filter for linear systems (i.e., systems for which both the process equation and the measurement equation are linear) with Gaussian uncertainties. In this case, the posterior pdf is a Gaussian represented by its mean and its covariance matrix. Other examples are the filters of Benes (1981), which requires the measurement equation to be linear, and Daum (1988), applicable to a more general class of systems with nonlinear process and measurement equations for which the posterior pdf is any exponential distribution.
Density Modeling and Clustering Using Dirichlet Diffusion Trees
Authors: Neal Radford M
Published: November 2023

I introduce a family of prior distributions over multivariate distributions, based on the use of a “Dirichlet diffusion tree” to generate exchangeable data sets. These priors can be viewed as generalizations of Dirichlet processes and of Dirichlet process mixtures, but unlike simple mixtures, they can capture the hierarchical structure present in many distributions, by means of the latent diffusion tree underlying the data. This latent tree also provides a hierarchical clustering of the data, which, unlike ad hoc clustering methods, comes with probabilistic indications of uncertainty. The relevance of each variable to the clustering can also be determined. Although Dirichlet diffusion trees are defined in terms of a continuoustime process, posterior inference involves only finite-dimensional quantities, allowing computation to be performed by reasonably efficient Markov chain Monte Carlo methods. The methods are demonstrated on problems of modelling a two-dimensional density and of clustering gene expression data.
Gaussian Processes to Speed up Hybrid Monte Carlo for Expensive Bayesian Integrals
Authors: Rasmussen Carl Edward
Published: November 2023

Hybrid Monte Carlo (HMC) is often the method of choice for computing Bayesian integrals that are not analytically tractable. However, the success of this method may require a very large number of evaluations of the (un-normalized) posterior and its partial derivatives. In situations where the posterior is computationally costly to evaluate, this may lead to an unacceptable computational load for HMC. I propose to use a Gaussian Process model of the (log of the) posterior for most of the computations required by HMC. Within this scheme only occasional evaluation of the actual posterior is required to guarantee that the samples generated have exactly the desired distribution, even if the GP model is somewhat inaccurate. The method is demonstrated on a 10 dimensional problem, where 200 evaluations suffice for the generation of 100 roughly independent points from the posterior. Thus, the proposed scheme allows Bayesian treatment of models with posteriors that are computationally demanding, such as models involving computer simulation.
Bayesian Factor Regression Models in the “Large p, Small n” Paradigm
Authors: West Mike
Published: November 2023

I discuss Bayesian factor regression models with many explanatory variables. These models are of particular interest and applicability in problems of prediction, but also for elucidating underlying structure in predictor variables. One key motivating application here is in studies of gene expression in functional genomics. I first discuss empirical factor (principal components) regression, and the use of general classes of shrinkage priors, with an example. These models raise foundational questions for Bayesians, and related practical issues, due to the use of design-dependent priors and the need to recover inferences on the effects of the original, high-dimensional predictors. I then discuss latent factor models for high-dimensional variables, and regression approaches in which low-dimensional latent factors are the predictor variables. These models generalize empirical factor regression, provide for more incisive evaluation of factor structure underlying high-dimensional predictors, and resolve the modelling and practical issues in empirical factor models by casting the latter as limiting special cases. Finally, I turn to questions of prior specification in these models, and introduce sparse latent factor models to induce sparsity in factor loadings matrices. Embedding such sparse latent factor models in factor regressions provides a novel approach to variable selection with very many predictors. The paper concludes with an example of sparse factor analysis of gene expression data and comments about further research.
Football Pools, Premium Bonds
Authors: Haigh John
Published: November 2023

In 1923, three telegraphists from Manchester rented offices to launch the first Football Pools competition. Fearing their current employers would disapprove, they disguised their identity through an obscure family link, and used ‘Littlewoods’ as a cover name. They distributed four thousand coupons to fans queuing to watch a Manchester United game, and just 35 people entered that first week. A few weeks later, only one coupon from ten thousand handed out to soccer fans in Hull was returned. At the end of the first season, the venture had made a loss, and two of the original partners dropped out, but John Moores carried on. Despite this unpromising beginning, the idea survived, and today ten million people play the Pools regularly. Although rival organizations run substantial competitions on similar lines, Littlewoods dominates the market and offers the largest prizes.
TV games
Authors: Haigh John
Published: November 2023

Game shows are popular on television world-wide. Some quiz shows rest entirely on the accumulated and arcane knowledge of the contestants while, at the other extreme, some games are completely a matter of chance, with no opportunity to combine luck with skill. I will describe four games where ideas from probability can be used either to improve your winning chances, or to gain a better understanding of the game.
Bookies, the Tote, spread betting
Authors: Haigh John
Published: November 2023

Bookmaking grew up around horse racing, which still accounts for over 70% of the industry’s turnover. Wagers have been struck at racing in York, Doncaster, and Chester since the sixteenth century, but the first known professional bookmaker was a Harry Ogden, who worked at Newmarket Heath in 1794. In 1853, betting houses were banned, and for a hundred years only those who attended race meetings could (legally) place cash bets. Otherwise punters had to use credit, and to communicate with their ‘turf accountant’ by letter, telephone, or telegram. This transparent attempt to confine betting to the wealthier classes was circumvented by the use of runners who collected cash bets in the street. After betting shops were legalized in 1960, illegal bookmaking all but disappeared, and with it went the attempts to bribe the police, protection rackets, and associated gang violence.
Cosmology
Authors: Weinberg Steven
Published: November 2023

This book is unique in the detailed, self-contained, and comprehensive treatment that it gives to the ideas and formulas that are used and tested in modern cosmological research. It divides into two parts, each of which provides enough material for a one-semester graduate course. The first part deals chiefly with the isotropic and homogeneous average universe; the second part concentrates on the departures from the average universe. Throughout the book the author presents detailed analytic calculations of cosmological phenomena, rather than just report results obtained elsewhere by numerical computation. The book is up to date, and gives detailed accounts of topics such as recombination, microwave background polarization, leptogenesis, gravitational lensing, structure formation, and multifield inflation, that are usually treated superficially if at all in treatises on cosmology. Copious references to current research literature are supplied. Appendices include a brief introduction to general relativity, and a detailed derivation of the Boltzmann equation for photons and neutrinos used in calculations of cosmological evolution. Also provided is an assortment of problems.
The Cosmic Microwave Radiation Background
Authors: Weinberg Steven
Published: November 2023

Before the mid-1960s by far the greatest part of our information about the structure and evolution of the universe came from observations of the redshifts and distances of distant galaxies, discussed in the previous chapter. In 1965 a nearly isotropic background of microwave radiation was discovered, which has provided a wealth of new cosmological data. After reviewing the expectations and discovery of this radiation, this chapter will explore some of its implications. We will only be able to give a first look at the anisotropies in this radiation in this chapter. In Chapter 7 we will return to this very important topic, applying the analysis of the evolution of cosmological perturbations presented in Chapters 5 and 6, and in Chapter 10 we will consider the origin of these perturbations in the very early universe.
Islam, neglect and discovery
Authors: Hodgkin Luke
Published: November 2023

It should be clear from the present chapter that the traditional view of the Arabs as mere custodians of Greek learning and transmitters of knowledge is a partial and distorted one. (Joseph 1992, p. 344) A number of medieval thinkers and scientists living under Islamic rule, by no means all of them ‘Moslems’ either nominally or substantially, played a useful role of transmitting Greek, Hindu, and other pre-Islamic fruits of knowledge to Westerners. They contributed to making Aristotle known in Christian Europe. But in doing this, they were but transmitting what they themselves had received from non-Moslem sources.
Modernity and its anxieties
Authors: Hodgkin Luke
Published: November 2023

If in summing up a brief phrase is called for that characterizes the life center of mathematics, one might well say: mathematics is the science of the innite. (Weyl 1949, p. 66) Pure mathematics is the class of all propositions of the form ‘p implies q’, where p and q are propositions each containing at least one or more variables, the same in the two propositions, and neither p nor q contains any constants except logical constants.
Notes and suggestions for further reading
Authors: Coolen A C C , Kühn R , Sollich P
Published: November 2023

In Chapter 5 we dealt with some unsupervised learning techniques, namely vector quantization and self-organized maps. The books by Kohonen [26] and by Ritter et al. [27] are good sources of further information on these; much of the early work on self-organizing maps was done in particular by Amari [28] and Kohonen [29]. We saw for vector quantization that this can be thought as learning a probability distribution from data. This point of view is rather powerful, and in fact lets one integrate unsupervised learning with Bayesian techniques: different probability models for the data can be given prior probabilities and these are combined with likelihood factors to determine how likely a given model is once the data have arrived.
Information theory and neural networks
Authors: Coolen A C C , Kühn R , Sollich P
Published: November 2023

Measuring information

Measuring information at first sight appears to be a somewhat vague and strange concept. Although especially those of us who are reasonably familiar with using computers will be used to thinking about information content (in terms of bits), we will find out that measuring information is not simply counting the number of bits in a data file but involves, somewhat surprisingly, concepts from probability.
Information theory and statistical inference
Authors: Coolen A C C , Kühn R , Sollich P
Published: November 2023

This chapter deals with applications of information theoretic concepts to problems of statistical inference, namely density estimation for a random variable X which is not completely specifield, in the sense that the full set of probabilities { p(x); x ∈ A } or, in the case of a continuous random variable, the probability density function are unknown. We shall consider two fundamentally different cases.
Notes and suggestions for further reading
Authors: Coolen A C C , Kühn R , Sollich P
Published: November 2023

Many interesting phenomena relevant to the information processing capabilities of neural networks are clearly dynamical in nature, and can therefore not be investigated by techniques of equilibrium statistical mechanics because these concentrate on stationary states. However, for a large class of problems one is simply forced to accept this limitation in scope because their full dynamics turns out to be far too complicated to unravel with the analytical techniques currently available. As the present part of the book has demonstrated, a number of interesting properties of neural networks can nevertheless be investigated in some detail using equilibrium theory.
Long-term potentiation, cooperativity and Hebb’s cell assemblies: a personal history
Authors: McNaughton Bruce L
Published: November 2023

The early history of the experimental work leading to the discovery that long-term potentiation (LTP) embodies Hebb’s principle of association is described. In addition, the fallacy underlying the sometimes presumed distinction between ’cooperativity’ and ’associativity’ in the induction of LTP is pointed out. Keywords: Hebb; cooperativity; associative; kindling; long-term enhancement; cell assembly Few people, perhaps scientists least of all, are able to agree on present reality. The likelihood of there being much agreement about history, especially among those who participated in it, is thus vanishingly small.
The Induction of N-methyl-o-Aspartate Receptor-Dependent long-term Potentiationt
Authors: Collingridge Graham L
Published: November 2023

The role of N-methyl-o-aspartate (NMDA) receptors in the induction of long-term potentiation (LTP) was established during the 1980s. In this article I present a personal reflection upon the role that my colleagues and I played in the discovery of the mechanism of induction of NMDA receptor-dependent LTP. I hope my NMDA receptors were working well in the 1980s as I try to recall the events leading up to the establishment of the mechanism of induction of LTP. My story begins in 1980 as I start my first postdoctoral position in the laboratory of Hugh McLennan, in Vancouver. Hugh was interested in L-glutamate as a neurotransmitter in the brain and was one of the pioneers in the identification of multiple classes of glutamate receptor.
Fusion pore modulation as a presynaptic mechanism contributing to expression of long-term potentiation
Authors: Choi Sukwoo , Klingauf Jurgen , Tsien Richard W
Published: November 2023

Working on the idea that postsynaptic and presynaptic mechanisms of long-term potentiation (LTP) expression are not inherently mutually exclusive, we have looked for the existence and functionality of presynaptic mechanisms for augmenting transmitter release in hippocampal slices. Specifically, we asked if changes in glutamate release might contribute to the conversion of ’silent synapses’ that show N-methyl-o-aspartate (NMDA) responses but no detectable cx-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) responses, to ones that exhibit.
Synaptic plasticity in the mesolimbic dopamine system
Authors: Thomas Mark J , Malenka Robert C
Published: November 2023

Long-term potentiation (LTP) and long-term depression (LTD) are thought to be critical mechanisms that contribute to the neural circuit modifications that mediate all forms of experience-dependent plasticity. It has, however, been difficult to demonstrate directly that experience causes long-lasting changes in synaptic strength and that these mediate changes in behaviour. To address these potential functional roles of LTP and LTD, we have taken advantage of the powerful in vivo effects of drugs of abuse that exert their behavioural effects in large part by acting in the nucleus accumbens (NAC) and ventral tegmental area (VTA); the two major components of the mesolimbic dopamine system.
Synaptic plasticity in animal models of early Alzheimer’s disease
Authors: Rowan Michael J , Klyubin Igor , Cullen William K , Anwyl Roger
Published: November 2023

Amyloid -protein (A ) is believed to be a primary cause of Alzheimer’s disease (AD). Recent research has examined the potential importance of soluble species of A in synaptic dysfunction, long before fibrillary A is deposited and neurodegenerative changes occur. Hippocampal excitatory synaptic transmission and plasticity are disrupted in transgenic mice overexpressing human amyloid precursor protein with early onset familial AD mutations, and in rats after exogenous application of synthetic A both in vitro and in vivo. Recently, naturally produced soluble A was shown to block the persistence of long-term potentiation (LTP) in the intact hippocampus. Sub-nanomolar concentrations of oligomeric A were sufficient to inhibit late LTP, pointing to a possible reason for the sensitivity of hippocampus-dependent memory to impairment in the early preclinical stages of AD. Having identified the active species of A that can play havoc with synaptic plasticity, it is hoped that new ways of targeting early AD can be developed.
Graph Decotnpositions
Authors: Diestel Reinhard
Published: November 2023

Graph Decompositions is the first book on a topic that belongs mainly to infinite graph theory. It offers a complete account of the theory of simplicial decompositions of graphs, from its origins in the 1930s right up to present-day research. In addition to being one of the most important tools in infinite graph theory, simplicial decompositions may be seen as a model for any kind of structural graph decomposition. The currently topical tree-decompositions, for example, have their origin in simplicial decompositions. The text is centred around a few guiding problems and concepts, such as the existence and the uniqueness problem of simplicial decompositions into primes, or the concept of excluded minors as a means of identifying a desired structure. It attempts to give as authentic a picture as possible of research in progress. To this end, it includes discussions of examples, proof strategies on the formation of new concepts, as well as numerous exercises and open problems. Graph Decompositions should prove attractive to any graph theorist or other mathematician interested in a new area of research, as well as to the advanced student looking for a lively and inspiring account of how such research evolves.
Localization and Riemann—Roch type theorems
Authors: Kawakubo Katsuo
Published: November 2023

In this final chapter, we shall deal with recent research by the author assuming some prerequisite reading. Although the topics treated in this chapter seem special, their concepts are quite fundamental and are of wide application.