Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating each component weight during the nonlinear propagation stage an approximation of the true pdf can be successfully reconstructed. Particle filtering (PF) methods have gained popularity recently for solving nonlinear estimation problems due to their straightforward approach and the processing capabilities mentioned above. The basic concept behind PF is to represent any pdf as a set of random samples. As the number of samples increases, they will theoretically converge to the exact, equivalent representation of the desired pdf. When the estimated qth moment is needed, the samples are used for its construction allowing further analysis of the pdf characteristics. However, filter performance deteriorates as the dimension of the state vector increases. To overcome this problem Ref. [5] applies a marginalization technique for PF methods, decreasing complexity of the system to one linear and another nonlinear state estimation problem. The marginalization theory was originally developed by Rao and Blackwell independently. According to Ref. [6] it improves any given estimator under every convex loss function. The improvement comes from calculating a conditional expected value, often involving integrating out a supportive statistic. In other words, Rao-Blackwellization allows for smaller but separate computations to be carried out while reaching the main objective of the estimator. In the case of improving an estimator's variance, any supporting statistic can be removed and its variance determined. Next, any other information that dependents on the supporting statistic is found along with its respective variance. A new approach is developed here by utilizing the strengths of the adaptive Gaussian sum propagation in Ref. [2] and a marginalization approach used for PF methods found in Ref. [7]. In the following sections a modified filtering approach is presented based on a special state-space model within nonlinear systems to reduce the dimensionality of the optimization problem in Ref. [2]. First, the adaptive Gaussian sum propagation is explained and then the new marginalized adaptive Gaussian sum propagation is derived. Finally, an example simulation is presented

Eficiencia en el uso del agua en trigo y lino oleaginoso con distintos aportes de nitrógeno en la región semiárida pampeana central

La región agrícola de la provincia de La Pampa con aptitud para el cultivo de trigo, posee también condiciones agro-ecológicas adecuadas para el desarrollo de lino oleaginoso, ofreciendo excelentes posibilidades, con lo cual esta especie surge como un interesante cultivo invernal alternativo al trigo u otros cereales de invierno. Los cereales de invierno experimentan limitaciones para expresar su rendimiento potencial en regiones semiáridas. Estas limitaciones pueden deberse al genotipo, a los factores ambientales y/o a la interacción de ambos. El propósito de este trabajo fue analizar el efecto de la fertilización nitrogenada sobre los distintos componentes del rendimiento y su impacto en la eficiencia en el uso del agua (EUA) en trigo pan y lino oleaginoso En el campo experimental de la Facultad de Agronomía de la Universidad Nacional de La Pampa se condujo el ensayo, en el cual se compararon las dos especies: trigo pan y lino oleaginoso, bajo cuatro condiciones de fertilidad. En las condiciones en las cuales se llevó a cabo el ensayo no se pudo comprobar la hipótesis de que el agregado de fertilizante nitrogenado aumenta la EUA. Por el contrario, parece que en condiciones de sequía tendría un efecto inverso. Se encontró que el trigo presenta una mayor eficiencia en el uso del agua que el lino en cuanto a la producción de materia seca, y este último no presentó ninguna respuesta significativa en a EUA frente al agregado de fertilizante nitrogenado

SEXTANT X-Ray Pulsar Navigation Demonstration: Additional On-Orbit Results

The Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) is a technology demonstration enhancement to the Neutron-star Interior Composition Explorer (NICER) mission, a NASA Astrophysics Explorer Mission of Opportunity to the International Space Station, launched in June of 2017. In late 2017, SEXTANT successfully completed a first demonstration of in-space and autonomous X-ray pulsar navigation (XNAV). This form of navigation relies on processing faint signals from millisecond pulsars-rapidly rotating neutron stars that appear to pulsate in the X-ray band-and could potentially provide a GPS-like navigation capability applicable throughout the solar-system and beyond. In this work, we briefly review prior SEXTANT results and then present new results focusing on: making use of the high- flux but rotationally unstable Crab pulsar, and using XNAV to estimate position, velocity, and time in the presence of an imperfect local clock

A mass spectrometry guided approach for the identification of novel vaccine candidates in gram-negative pathogens

Vaccination is the most effective method to prevent infectious diseases. However, approaches to identify novel vaccine candidates are commonly laborious and protracted. While surface proteins are suitable vaccine candidates and can elicit antibacterial antibody responses, systematic approaches to define surfomes from gram-negatives have rarely been successful. Here we developed a combined discovery-driven mass spectrometry and computational strategy to identify bacterial vaccine candidates and validate their immunogenicity using a highly prevalent gram-negative pathogen, Helicobacter pylori, as a model organism. We efficiently isolated surface antigens by enzymatic cleavage, with a design of experiment based strategy to experimentally dissect cell surface-exposed from cytosolic proteins. From a total of 1,153 quantified bacterial proteins, we thereby identified 72 surface exposed antigens and further prioritized candidates by computational homology inference within and across species. We next tested candidate-specific immune responses. All candidates were recognized in sera from infected patients, and readily induced antibody responses after vaccination of mice. The candidate jhp_0775 induced specific B and T cell responses and significantly reduced colonization levels in mouse therapeutic vaccination studies. In infected humans, we further show that jhp_0775 is immunogenic and activates IFN gamma secretion from peripheral CD4(+) and CD8(+) T cells. Our strategy provides a generic preclinical screening, selection and validation process for novel vaccine candidates against gram-negative bacteria, which could be employed to other gram-negative pathogens

Serological profile of first SARS-CoV-2 reinfection cases detected within the SIREN study.

OBJECTIVES: To describe the serological profile of first two SARS-CoV-2 confirmed reinfections in the national healthcare worker cohort study SARS-CoV-2 Immunity and Reinfection Evaluation (SIREN) and potentially identify correlates of protection against reinfection. METHODS: In addition to routine testing within the SIREN study, viral culture, sequencing and phylogenetic analysis were performed. Total antibody testing (Anti-SARS-CoV-2 nucleocapsid and Anti-SARS-CoV-2 spike) were complemented by receptor binding domain indirect ELISA and neutralising antibody assays. RESULTS: The first two SARS-CoV-2 confirmed reinfections had mild symptomatic illness episodes from which infectious virus was recovered at the time of reinfection. The recovered viruses and their sequences were closely related to viruses circulating locally during the time of reinfection and serology was consistent with reinfection. Prior to reinfection, both cases had ELISA and immunoblot detectable anti-N antibodies, but lacked live virus neutralising antibody. Within days following reinfection, neutralising antibodies became detectable and anti-N and anti-S binding antibodies were boosted. CONCLUSIONS: We hypothesise that titres of neutralising antibody can be used as a correlate of protection against reinfection. Further analysis using a case-control design is essential in order to confirm this hypothesis

Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection

BACKGROUND: SARS-CoV-2 serology is used to identify prior infection at individual and at population level. Extended longitudinal studies with multi-timepoint sampling to evaluate dynamic changes in antibody levels are required to identify the time horizon in which these applications of serology are valid, and to explore the longevity of protective humoral immunity. METHODS: Healthcare workers were recruited to a prospective cohort study from the first SARS-CoV-2 epidemic peak in London, undergoing weekly symptom screen, viral PCR and blood sampling over 16-21 weeks. Serological analysis (n =12,990) was performed using semi-quantitative Euroimmun IgG to viral spike S1 domain and Roche total antibody to viral nucleocapsid protein (NP) assays. Comparisons were made to pseudovirus neutralizing antibody measurements. FINDINGS: A total of 157/729 (21.5%) participants developed positive SARS-CoV-2 serology by one or other assay, of whom 31.0% were asymptomatic and there were no deaths. Peak Euroimmun anti-S1 and Roche anti-NP measurements correlated (r = 0.57, p<0.0001) but only anti-S1 measurements correlated with near-contemporary pseudovirus neutralising antibody titres (measured at 16-18 weeks, r = 0.57, p<0.0001). By 21 weeks' follow-up, 31/143 (21.7%) anti-S1 and 6/150 (4.0%) anti-NP measurements reverted to negative. Mathematical modelling revealed faster clearance of anti-S1 compared to anti-NP (median half-life of 2.5 weeks versus 4.0 weeks), earlier transition to lower levels of antibody production (median of 8 versus 13 weeks), and greater reductions in relative antibody production rate after the transition (median of 35% versus 50%). INTERPRETATION: Mild SARS-CoV-2 infection is associated with heterogeneous serological responses in Euroimmun anti-S1 and Roche anti-NP assays. Anti-S1 responses showed faster rates of clearance, more rapid transition from high to low level production rate and greater reduction in production rate after this transition. In mild infection, anti-S1 serology alone may underestimate incident infections. The mechanisms that underpin faster clearance and lower rates of sustained anti-S1 production may impact on the longevity of humoral immunity. FUNDING: Charitable donations via Barts Charity, Wellcome Trust, NIHR

Time series analysis and mechanistic modelling of heterogeneity and sero-reversion in antibody responses to mild SARS‑CoV-2 infection.

BACKGROUND: SARS-CoV-2 serology is used to identify prior infection at individual and at population level. Extended longitudinal studies with multi-timepoint sampling to evaluate dynamic changes in antibody levels are required to identify the time horizon in which these applications of serology are valid, and to explore the longevity of protective humoral immunity. METHODS: Healthcare workers were recruited to a prospective cohort study from the first SARS-CoV-2 epidemic peak in London, undergoing weekly symptom screen, viral PCR and blood sampling over 16-21 weeks. Serological analysis (n =12,990) was performed using semi-quantitative Euroimmun IgG to viral spike S1 domain and Roche total antibody to viral nucleocapsid protein (NP) assays. Comparisons were made to pseudovirus neutralizing antibody measurements. FINDINGS: A total of 157/729 (21.5%) participants developed positive SARS-CoV-2 serology by one or other assay, of whom 31.0% were asymptomatic and there were no deaths. Peak Euroimmun anti-S1 and Roche anti-NP measurements correlated (r = 0.57, p<0.0001) but only anti-S1 measurements correlated with near-contemporary pseudovirus neutralising antibody titres (measured at 16-18 weeks, r = 0.57, p<0.0001). By 21 weeks' follow-up, 31/143 (21.7%) anti-S1 and 6/150 (4.0%) anti-NP measurements reverted to negative. Mathematical modelling revealed faster clearance of anti-S1 compared to anti-NP (median half-life of 2.5 weeks versus 4.0 weeks), earlier transition to lower levels of antibody production (median of 8 versus 13 weeks), and greater reductions in relative antibody production rate after the transition (median of 35% versus 50%). INTERPRETATION: Mild SARS-CoV-2 infection is associated with heterogeneous serological responses in Euroimmun anti-S1 and Roche anti-NP assays. Anti-S1 responses showed faster rates of clearance, more rapid transition from high to low level production rate and greater reduction in production rate after this transition. In mild infection, anti-S1 serology alone may underestimate incident infections. The mechanisms that underpin faster clearance and lower rates of sustained anti-S1 production may impact on the longevity of humoral immunity. FUNDING: Charitable donations via Barts Charity, Wellcome Trust, NIHR