Neural Network Modelling with Input Uncertainty: Theory and Application

It is generally assumed when using Bayesian inference methods for neural networks that the input data contains no noise. For real-world (errors in variable) problems this is clearly an unsafe assumption. This paper presents a Bayesian neural network framework which accounts for input noise provided that a model of the noise process exists. In the limit where the noise process is small and symmetric it is shown, using the Laplace approximation, that this method adds an extra term to the usual Bayesian error bar which depends on the variance of the input noise process. Further, by treating the true (noiseless) input as a hidden variable, and sampling this jointly with the network’s weights, using a Markov chain Monte Carlo method, it is demonstrated that it is possible to infer the regression over the noiseless input. This leads to the possibility of training an accurate model of a system using less accurate, or more uncertain, data. This is demonstrated on both the, synthetic, noisy sine wave problem and a real problem of inferring the forward model for a satellite radar backscatter system used to predict sea surface wind vectors.

Computational capabilities of multilayer committee machines

We obtained an analytical expression for the computational complexity of many layered committee machines with a finite number of hidden layers (L < 8) using the generalization complexity measure introduced by Franco et al (2006) IEEE Trans. Neural Netw. 17 578. Although our result is valid in the large-size limit and for an overlap synaptic matrix that is ultrametric, it provides a useful tool for inferring the appropriate architecture a network must have to reproduce an arbitrary realizable Boolean function.

A cross-culture, cross-gender comparison of perspective taking mechanisms

Being able to judge another person's visuo-spatial perspective is an essential social skill, hence we investigated the generalizability of the involved mechanisms across cultures and genders. Developmental, cross-species, and our own previous research suggest that two different forms of perspective taking can be distinguished, which are subserved by two distinct mechanisms. The simpler form relies on inferring another's line-of-sight, whereas the more complex form depends on embodied transformation into the other's orientation in form of a simulated body rotation. Our current results suggest that, in principle, the same basic mechanisms are employed by males and females in both, East-Asian (EA; Chinese) and Western culture. However, we also confirmed the hypothesis that Westerners show an egocentric bias, whereas EAs reveal an other-oriented bias. Furthermore, Westerners were slower overall than EAs and showed stronger gender differences in speed and depth of embodied processing. Our findings substantiate differences and communalities in social cognition mechanisms across genders and two cultures and suggest that cultural evolution or transmission should take gender as a modulating variable into account.

Inference of helicopter airframe condition

The goal of this paper is to model normal airframe conditions for helicopters in order to detect changes. This is done by inferring the flying state using a selection of sensors and frequency bands that are best for discriminating between different states. We used non-linear state-space models (NLSSM) for modelling flight conditions based on short-time frequency analysis of the vibration data and embedded the models in a switching framework to detect transitions between states. We then created a density model (using a Gaussian mixture model) for the NLSSM innovations: this provides a model for normal operation. To validate our approach, we used data with added synthetic abnormalities which was detected as low-probability periods. The model of normality gave good indications of faults during the flight, in the form of low probabilities under the model, with high accuracy (>92 %). © 2013 IEEE.

Horizontal genetic transfer in asexual fungi

Four aspects of horizontal genetic transfer during heterokaryon formation were examined in the asexual pathogen Fusarium oxysporum f.sp. cubense (Foc): (1) variability based on method of heterokaryon formation; (2) differences in nuclear and mitochondrial inheritance; (3) the occurrence of recombination without nuclear fusion; (4) the occurrence of horizontal genetic transfer between distantly related isolates. The use of non-pathogenic strains of Fusarium oxysporum as biocontrol agents warrants a closer examination at the reproductive life cycle of this fungus, particularly if drug resistance or pathogenicity genes can be transmitted horizontally. Experiments were divided into three phases. Phase I looked at heterokaryon formation by hyphal anastomosis and protoplast fusion. Phase II was a time course of heterokaryon formation to look at patterns of nuclear and mitochondrial inheritance. Phase III examined the genetic relatedness of the different vegetative compatibility groups using a multilocus analysis approach. Heterokaryon formation was evident within and between vegetative compatibility groups. Observation of non-parental genotypes after heterokaryon formation confirmed that, although a rare event, horizontal genetic transfer occurred during heterokaryon formation. Uniparental mitochondria inheritance was observed in heterokaryons formed either by hyphal anastomosis or protoplast fusion. Drug resistance was expressed during heterokaryon formation, even across greater genetic distances than those distances imposed by vegetative compatibility. Phylogenies inferred from different molecular markers were incongruent at a significant level, challenging the clonal origins of Foc. Mating type genes were identified in this asexual pathogen Polymorphisms were detected within a Vegetative Compatibility Group (VCG) suggesting non-clonal inheritance and/or sexual recombination in Foc. This research was funded in part by a NIH-NIGMS (National Institutes of Health-National Institute of General Medical Sciences) Grant through the MBRS (Minority Biomedical Research Support), the Department of Biological Sciences and the Tropical Biology Program at FIU. ^

Cytokine analysis in Atlantic bottlenose dolphins: Molecular characterization of IL-4, IL-6, and IL-10

The health status of wild and captive Atlantic Bottlenose dolphins ( Tersiops truncatis) is difficult to ascertain. Mass strandings of these animals have been attributed to pollutants, as well as bacterial infections. Using human Enzyme Linked Immuno-Assays (ELISA) for immunological cytokines, I measured soluble cytokine levels with respect to their health status. In a retrospective analysis of dolphin sera, there was a trend of higher cytokine levels in “sick” animals. I cultured dolphin lymphocytes in the presence of a mitogen (PHA), a super antigen (Staph-A), Lipopolysaccharide (LPS), and a calcium flux inducer (PMA). Levels of messenger RNA, from these cultured cells, were assayed with Polymerase Chain Reaction (PCR) using primers for the human cytokines IL-2, IL-4, IL-6, IL-10, Tumor Necrosis Factor, and Interferon gamma. Only IL-4, IL-6, and IL-10 messages were obtained, inferring similar nucleotide homology to the human primer sequences. The PCR products were sequenced. Sixteen IL-4 sequences, twelve IL-6 sequences and seven IL-10 sequences were obtained and analyzed. Each cytokine exhibited the same nucleotide sequence in all dolphins examined. There was no difference in the cytokine profile in response to the various stimuli. The derived amino acid composition for each of the dolphin cytokines was used for molecular modeling, which showed that dolphin IL-4, IL-6, and IL-10 were structurally similar to the corresponding proteins of Perissodactyla. ^

Bioinformatic analysis for exploring relationships between genes and gene products

To carry out their specific roles in the cell, genes and gene products often work together in groups, forming many relationships among themselves and with other molecules. Such relationships include physical protein-protein interaction relationships, regulatory relationships, metabolic relationships, genetic relationships, and much more. With advances in science and technology, some high throughput technologies have been developed to simultaneously detect tens of thousands of pairwise protein-protein interactions and protein-DNA interactions. However, the data generated by high throughput methods are prone to noise. Furthermore, the technology itself has its limitations, and cannot detect all kinds of relationships between genes and their products. Thus there is a pressing need to investigate all kinds of relationships and their roles in a living system using bioinformatic approaches, and is a central challenge in Computational Biology and Systems Biology. This dissertation focuses on exploring relationships between genes and gene products using bioinformatic approaches. Specifically, we consider problems related to regulatory relationships, protein-protein interactions, and semantic relationships between genes. A regulatory element is an important pattern or "signal", often located in the promoter of a gene, which is used in the process of turning a gene "on" or "off". Predicting regulatory elements is a key step in exploring the regulatory relationships between genes and gene products. In this dissertation, we consider the problem of improving the prediction of regulatory elements by using comparative genomics data. With regard to protein-protein interactions, we have developed bioinformatics techniques to estimate support for the data on these interactions. While protein-protein interactions and regulatory relationships can be detected by high throughput biological techniques, there is another type of relationship called semantic relationship that cannot be detected by a single technique, but can be inferred using multiple sources of biological data. The contributions of this thesis involved the development and application of a set of bioinformatic approaches that address the challenges mentioned above. These included (i) an EM-based algorithm that improves the prediction of regulatory elements using comparative genomics data, (ii) an approach for estimating the support of protein-protein interaction data, with application to functional annotation of genes, (iii) a novel method for inferring functional network of genes, and (iv) techniques for clustering genes using multi-source data.

Phylogenetics, conservation, and historical biogeography of the West Indian members of the Adelieae (Euphorbiaceae)

The Caribbean Island Biodiversity Hotspot is the largest insular system of the New World and a priority for biodiversity conservation worldwide. The tribe Adeliae (Euphorbiaceae) has over 35 species endemic to this hotspot, representing one of the most extraordinary cases of speciation in the West Indies, involving taxa from Cuba, Hispaniola, Jamaica, and the Bahamas. These species form a monophyletic group and traditionally have been accommodated in two endemic genera: Lasiocroton and Leucocroton. A study based on: (1) scanning electron microscopy of pollen and trichomes, (2) macromorphology, and (3) molecular data, was conducted to reveal generic relationships within this group. Phylogenies were based on parsimony and Bayesian analyses of nucleotide sequences of the ITS regions of the nuclear ribosomal DNA and the non-coding chloroplast DNA spacers psbM-trnD and ycf6-pcbM. One species, Lasiocroton trelawniensis, was transferred from the tribe into the genus Bernardia. Of the remaining species, three major monophyletic assemblages were revealed, one was restricted to limestone ares of Hispaniola and was sister to a clade with two monophyletic genera, Lasiocroton and Leucocroton. Morphological, biogeographical, and ecological data provided additional support for each of these three monophyletic assemblages. The Hispaniolan taxa were accommodated in a new genus with four species: Garciadelia. Leucocroton includes the nickel hyperaccumulating species from serpentine soils of Cuba, while the rest of the species were placed in Lasiocroton, a genus restricted to limestone areas. The geographic history of the islands as well as the phylogenetic placement of the Leucocroton-alliance, allows the research to include the historical biogeography of the alliance across the islands of the Caribbean based on a dispersal-vicariance analysis. The alliance arose on Eastern Cuba and Hispaniola, with Lasiocroton and Leucocroton diverging on Eastern Cuba according to soil type. Within Leucocroton, the analysis shows two migrations across the serpentine soils of Cuba. Additional morphological, ecological, and phylogenetic analyses support four new species in Cuba (Lasiocroton gutierrezii) and Hispaniola ( Garciadelia abbottii, G. castilloae, and G. mejiae). ^

Drosophila Flight Stabilization Depends on Apparent Distances in Optic Flow Field

To perform daily flight tasks, insects rely heavily on their visual perception of a dynamic environment. They must process visual signals quickly and accurately and update their behavior. Flies are vulnerable to environmental disturbances, such as gusts of wind blowing them off course, but they may use the altered visual field to compensate and regain their original course. In studies using Drosophila melanogaster, it has been shown that their corrective responses can be analyzed by measuring changes in their wing beats. By enclosing a tethered fly in a cuboidal visual arena displaying a computerized optic flow field, it is possible to calculate the change in wing beat amplitudes from an infrared shadow of its wings using photodiodes and a custom wing beat analyzer. In this experiment, manipulations ofthe optic flow field are used to create a field where points have varying relative forward speed, to study how the insect performs corrective maneuvers. The results show that Drosophila have a stronger corrective response to the quickly moving, apparently near points compared to the slower moving, apparently distant points. This implies the flies are distinguishing points based on their relative speeds, inferring distance, and adjusting their corrective actions with this information.

Effect of Hydrologic Restoration on the Habitat of The Cape Sable Seaside Sparrow, Annual Report of 2004-2005

The major activities in Year 3 on ‘Effect of hydrologic restoration on the habitat of the Cape Sable seaside sparrow (CSSS)’ included presentations, field work, data analysis, and report preparation. During this period, we made 4 presentations, two at the CSSS – fire planning workshops at Everglades National Park (ENP), one at the Society of Wetland Scientists’ meeting in Charleston, SC, and a fourth at the Marl Prairie/CSSS performance measure workshop at ENP. We started field work in the third week of January and continued till June 3, 2005. Early in the field season, we completed vegetation surveys along two transects, B and C (~15.1 km). During April and May, vegetation sampling was completed at 199 census sites, bringing to 608 the total number of CSSS census sites with quantitative vegetation data. We updated data sets from all three years, 2003-05, and analyzed them using cluster analysis and ordination as in previous two years. However, instead of weighted averaging, we used weighted-averaging partial least square regression (WA-PLS) model, as this method is considered an improvement over WA for inferring values of environmental variables from biological species composition. We also validated the predictive power of the WA-PLS regression model by applying it to a sub-set of 100 census sites for which hydroperiods were “known” from two sources, i.e., from elevations calculated from concurrent water depth measurements onsite and at nearby water level recorders, and from USGS digital elevation data. Additionally, we collected biomass samples at 88 census sites, and determined live and dead aboveground plant biomass. Using vegetation structure and biomass data from those sites, we developed a regression model that we used to predict aboveground biomass at all transects and census sites. Finally, biomass data was analyzed in relation to hydroperiod and fire frequency.

Acurácia dos indicadores clínicos do diagnóstico de enfermagem falta de adesão em pessoas vivendo com AIDS

In the early 1990s, a major milestone in the treatment of Acquired Immune Deficiency Syndrome was the development of highly active combination antiretroviral therapy. The great benefit generated by the use of this therapy was prolonging the survival of the people who got this disease, since it is no longer considered fatal, becoming a chronic condition. Despite improvements generated by this therapy, there are still many difficulties to be overcome. One is the patient adherence to their treatment, bringing challenges to services and health professionals. Hence the need for early identification of nursing diagnosis Lack of Accession so that solutions are sought by the nurse with the patient and his family. With this problem, adds to the difficulty of hospital nurses in inferring that diagnosis, especially in identifying their defining characteristics. In this context, the objective was to evaluate the accuracy of clinical indicators of nursing diagnosis Lack of Adherence to antiretroviral treatment for people living with the Acquired Immunodeficiency Syndrome. The research took place in two stages. The first consists of the evaluation of the diagnostic indicators in the study; and second, the diagnostic inference performed by specialist nurses. The first step took place in a referral hospital in the treatment of infectious diseases in the Northeast of Brazil, and data were collected through an instrument for carrying out history and physical examination and analyzed for the presence or absence of the diagnostic indicators. In the second stage, the data were sent to experts, who judged the presence or absence of the diagnosis in the studied clientele. The project was submitted to the Ethics Committee of the Federal University of Rio Grande do Norte, obtaining approval with the General Certificate for Ethics Assessment (CAAE) No 46206215.3.0000.5537. Data were analyzed using descriptive and inferential statistics. Test were used Fisher's exact, chi-square test of Pearson and logistic regression. Since the accuracy of clinical indicators was measured by sensitivity, specificity, predictive values, likelihood ratios. As a result, we identified the presence of diagnosis Lack of Accession on 69% (n = 78) of the study patients. The defining characteristics that showed statistically significant association with the diagnosis studied were: lack of adherence behavior, complications related to development, missing scheduled appointments, failure to achieve results, and exacerbation of symptoms. The characteristic with greater sensitivity was missing scheduled appointments and the highest specificity behavior of noncompliance. The logistic regression showed as predictors for the diagnosis Lack of Accession: lack of adherence behavior, missing scheduled appointments, failure to achieve results, and exacerbation of symptoms. It was concluded that the identification of clinical indicators accurately enabled a good prediction of the nursing diagnosis Lack of Accession on people living with the Acquired Immune Deficiency Syndrome, helping nurses develop early on strategies for promoting adherence to the use of antiretrovirals.

Acurácia dos indicadores clínicos do diagnóstico de enfermagem falta de adesão em pessoas vivendo com AIDS

In the early 1990s, a major milestone in the treatment of Acquired Immune Deficiency Syndrome was the development of highly active combination antiretroviral therapy. The great benefit generated by the use of this therapy was prolonging the survival of the people who got this disease, since it is no longer considered fatal, becoming a chronic condition. Despite improvements generated by this therapy, there are still many difficulties to be overcome. One is the patient adherence to their treatment, bringing challenges to services and health professionals. Hence the need for early identification of nursing diagnosis Lack of Accession so that solutions are sought by the nurse with the patient and his family. With this problem, adds to the difficulty of hospital nurses in inferring that diagnosis, especially in identifying their defining characteristics. In this context, the objective was to evaluate the accuracy of clinical indicators of nursing diagnosis Lack of Adherence to antiretroviral treatment for people living with the Acquired Immunodeficiency Syndrome. The research took place in two stages. The first consists of the evaluation of the diagnostic indicators in the study; and second, the diagnostic inference performed by specialist nurses. The first step took place in a referral hospital in the treatment of infectious diseases in the Northeast of Brazil, and data were collected through an instrument for carrying out history and physical examination and analyzed for the presence or absence of the diagnostic indicators. In the second stage, the data were sent to experts, who judged the presence or absence of the diagnosis in the studied clientele. The project was submitted to the Ethics Committee of the Federal University of Rio Grande do Norte, obtaining approval with the General Certificate for Ethics Assessment (CAAE) No 46206215.3.0000.5537. Data were analyzed using descriptive and inferential statistics. Test were used Fisher's exact, chi-square test of Pearson and logistic regression. Since the accuracy of clinical indicators was measured by sensitivity, specificity, predictive values, likelihood ratios. As a result, we identified the presence of diagnosis Lack of Accession on 69% (n = 78) of the study patients. The defining characteristics that showed statistically significant association with the diagnosis studied were: lack of adherence behavior, complications related to development, missing scheduled appointments, failure to achieve results, and exacerbation of symptoms. The characteristic with greater sensitivity was missing scheduled appointments and the highest specificity behavior of noncompliance. The logistic regression showed as predictors for the diagnosis Lack of Accession: lack of adherence behavior, missing scheduled appointments, failure to achieve results, and exacerbation of symptoms. It was concluded that the identification of clinical indicators accurately enabled a good prediction of the nursing diagnosis Lack of Accession on people living with the Acquired Immune Deficiency Syndrome, helping nurses develop early on strategies for promoting adherence to the use of antiretrovirals.

(Table 2) Radiocarbon dates from lakes on Fildes Peninsula, King George Island

Precise relative sea level (RSL) data are important for inferring regional ice sheet histories, as well as helping to validate numerical models of ice sheet evolution and glacial isostatic adjustment. Here we develop a new RSL curve for Fildes Peninsula, South Shetland Islands (SSIs), a sub-Antarctic archipelago peripheral to the northern Antarctic Peninsula ice sheet, by integrating sedimentary evidence from isolation basins with geomorphological evidence from raised beaches. This combined approach yields not only a Holocene RSL curve, but also the spatial pattern of how RSL change varied across the archipelago. The curve shows a mid-Holocene RSL highstand on Fildes Peninsula at 15.5 m above mean sea level between 8000 and 7000 cal a BP. Subsequently RSL gradually fell as a consequence of isostatic uplift in response to regional deglaciation. We propose that isostatic uplift occurred at a non-steady rate, with a temporary pause in ice retreat ca. 7200 cal a BP, leading to a short-lived RSL rise of ~1 m and forming a second peak to the mid-Holocene highstand. Two independent approaches were taken to constrain the long-term tectonic uplift rate of the SSIs at 0.22-0.48 m/ka, placing the tectonic contribution to the reconstructed RSL highstand between 1.4 and 2.9 m. Finally, we make comparisons to predictions from three global sea level models.

RNA Virus Evolution: a Cross-scale, Disease Dynamic Perspective

RNA viruses are an important cause of global morbidity and mortality. The rapid evolutionary rates of RNA virus pathogens, caused by high replication rates and error-prone polymerases, can make the pathogens difficult to control. RNA viruses can undergo immune escape within their hosts and develop resistance to the treatment and vaccines we design to fight them. Understanding the spread and evolution of RNA pathogens is essential for reducing human suffering. In this dissertation, I make use of the rapid evolutionary rate of viral pathogens to answer several questions about how RNA viruses spread and evolve. To address each of the questions, I link mathematical techniques for modeling viral population dynamics with phylogenetic and coalescent techniques for analyzing and modeling viral genetic sequences and evolution. The first project uses multi-scale mechanistic modeling to show that decreases in viral substitution rates over the course of an acute infection, combined with the timing of infectious hosts transmitting new infections to susceptible individuals, can account for discrepancies in viral substitution rates in different host populations. The second project combines coalescent models with within-host mathematical models to identify driving evolutionary forces in chronic hepatitis C virus infection. The third project compares the effects of intrinsic and extrinsic viral transmission rate variation on viral phylogenies.