Sequential Monte Carlo with transformations

This paper examines methodology for performing Bayesian inference sequentially on a sequence of posteriors on spaces of different dimensions. For this, we use sequential Monte Carlo samplers, introducing the innovation of using deterministic transformations to move particles effectively between target distributions with different dimensions. This approach, combined with adaptive methods, yields an extremely flexible and general algorithm for Bayesian model comparison that is suitable for use in applications where the acceptance rate in reversible jump Markov chain Monte Carlo is low. We use this approach on model comparison for mixture models, and for inferring coalescent trees sequentially, as data arrives

Time-Dependent Alterations in Liver Oxidative Stress due to Ethanol and Acetaldehyde

Binge drinking is a major public health issue and ethanol-related liver insult may play a major role in the pathology of alcoholic liver disease. However, the degree of oxidative stress, cell death and contribution of acetaldehyde to liver damage over a 24-h period has yet to be determined. Herein, we aimed to investigate the effect of acute alcohol and elevated acetaldehyde levels on hepatic oxidative damage, apoptosis, and antioxidant enzyme activity over a 24-h period. Male Wistar rats were divided into four groups and animals were pre-injected (intraperitonially [i.p.]) with either saline (0.15 mol/L) or cyanamide (5-mmol/kg body weight), followed by either saline (0.15 mol/L) or ethanol (75-mmol/kg bodyweight). After 2.5, 6 and 24 h, hepatic cytosolic and mitochondrial fractions were analysed for indices of oxidative stress. At 2.5 h, cytosolic glutathione and malondialdehyde levels were significantly reduced and increased, respectively, with alcohol treatment. Caspase-3 activity and cytochrome c levels were increased with alcohol treatment at 24 h. The combination of cyanamide and alcohol treatment at 24 h led to a significant increase in serum alanine aminotransferase levels, and reduced albumin and total protein levels. Furthermore, glutathione peroxidase activity and glutathione reductase activity were significantly decreased and increased, respectively. Finally, superoxide dismutase activity was decreased in cytosol and increased in the mitochondria after cyanamide and ethanol treatment, respectively. This study indicates a complex differential effect of alcohol and acetaldehyde, whereby alcohol toxicity in the mitochondria takes place throughout the 24-h period, but raised acetaldehyde has a further detrimental effect on liver function

A bioimpedance-based monitor for real-time detection and identification of secondary brain injury

Secondary brain injury impacts patient prognosis and can lead to long-term morbidity and mortality in cases of trauma. Continuous monitoring of secondary injury in acute clinical settings is primarily limited to intracranial pressure (ICP); however, ICP is unable to identify essential underlying etiologies of injury needed to guide treatment (e.g. immediate surgical intervention vs medical management). Here we show that a novel intracranial bioimpedance monitor (BIM) can detect onset of secondary injury, differentiate focal (e.g. hemorrhage) from global (e.g. edema) events, identify underlying etiology and provide localization of an intracranial mass effect. We found in an in vivo porcine model that the BIM detected changes in intracranial volume down to 0.38 mL, differentiated high impedance (e.g. ischemic) from low impedance (e.g. hemorrhagic) injuries (p \u3c 0.001), separated focal from global events (p \u3c 0.001) and provided coarse ‘imaging’ through localization of the mass effect. This work presents for the first time the full design, development, characterization and successful implementation of an intracranial bioimpedance monitor. This BIM technology could be further translated to clinical pathologies including but not limited to traumatic brain injury, intracerebral hemorrhage, stroke, hydrocephalus and post-surgical monitoring

Spin Dynamics of the LAGEOS Satellite in Support of a Measurement of the Earth's Gravitomagnetism

LAGEOS is an accurately-tracked, dense spherical satellite covered with 426 retroreflectors. The tracking accuracy is such as to yield a medium term (years to decades) inertial reference frame determined via relatively inexpensive observations. This frame is used as an adjunct to the more difficult and data intensive VLBI absolute frame measurements. There is a substantial secular precession of the satellite's line of nodes consistent with the classical, Newtonian precession due to the non-sphericity of the earth. Ciufolini has suggested the launch of an identical satellite (LAGEOS-3) into an orbit supplementary to that of LAGEOS-1: LAGEOS-3 would then experience an equal and opposite classical precession to that of LAGEOS-1. Besides providing a more accurate real-time measurement of the earth's length of day and polar wobble, this paired-satellite experiment would provide the first direct measurement of the general relativistic frame-dragging effect. Of the five dominant error sources in this experiment, the largest one involves surface forces on the satellite, and their consequent impact on the orbital nodal precession. The surface forces are a function of the spin dynamics of the satellite. Consequently, we undertake here a theoretical effort to model the spin ndynamics of LAGEOS. In this paper we present our preliminary results.Comment: 16 pages, RevTeX, LA-UR-94-1289. (Part I of II, postscript figures in Part II

From impulses to maladaptive actions: the insula is a neurobiological gate for the development of compulsive behavior.

Impulsivity is an endophenotype of vulnerability for compulsive behaviors. However, the neural mechanisms whereby impulsivity facilitates the development of compulsive disorders, such as addiction or obsessive compulsive disorder, remain unknown. We first investigated, in rats, anatomical and functional correlates of impulsivity in the anterior insular (AI) cortex by measuring both the thickness of, and cellular plasticity markers in, the AI with magnetic resonance imaging and in situ hybridization of the immediate early gene zif268, respectively. We then investigated the influence of bilateral AI cortex lesions on the high impulsivity trait, as measured in the five-choice serial reaction time task (5-CSRTT), and the associated propensity to develop compulsivity as measured by high drinking levels in a schedule-induced polydipsia procedure (SIP). We demonstrate that the AI cortex causally contributes to individual vulnerability to impulsive-compulsive behavior in rats. Motor impulsivity, as measured by premature responses in the 5-CSRTT, was shown to correlate with the thinness of the anterior region of the insular cortex, in which highly impulsive (HI) rats expressed lower zif268 mRNA levels. Lesions of AI reduced impulsive behavior in HI rats, which were also highly susceptible to develop compulsive behavior as measured in a SIP procedure. AI lesions also attenuated both the development and the expression of SIP. This study thus identifies the AI as a novel neural substrate of maladaptive impulse control mechanisms that may facilitate the development of compulsive disorders.This research was carried-out within the Department of Psychology and the Department of Pharmacology of the University of Cambridge as well as the INSERM AVENIR team Psychobiology of Compulsive Disorders of the University of Poitiers. It was supported by an INSERM AVENIR grant and a FYSSEN foundation grant to DB. MLD was supported by a PhD fellowship from the Fondation pour la Recherche Médicale (FRM) and ABR was supported by a post-doctoral fellowship from the INSERM. BJE was supported by the United Kingdom Medical Research Council (MRC) Grant 9536855.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/mp.2015.14

Spatial search using the discrete time quantum walk

We study the quantum walk search algorithm of Shenvi et al. (Phys Rev A 67:052307, 2003) on data structures of one to two spatial dimensions, on which the algorithm is thought to be less efficient than in three or more spatial dimensions. Our aim is to understand why the quantum algorithm is dimension dependent whereas the best classical algorithm is not, and to show in more detail how the efficiency of the quantum algorithm varies with spatial dimension or accessibility of the data. Our numerical results agree with the expected scaling in 2D of O(√N log N}) , and show how the prefactors display significant dependence on both the degree and symmetry of the graph. Specifically, we see, as expected, the prefactor of the time complexity dropping as the degree (connectivity) of the structure is increased