Small hive beetles, Aethina tumida, are vectors of Paenibacillus larvae

The transmission of honeybee pathogens by free-flying pests, such as small hive beetles (=SHB), would be independent of bees and beekeepers and thereby constitute a new challenge for pathogen control measures. Here we show that larval and adult SHB become contaminated with Paenibacillus larvae spores when exposed to honeybee brood combs with clinical American foulbrood (=AFB) symptoms in the laboratory. This contamination persists in pupae and newly emerged adults. After exposure to contaminated adult SHB, honeybee field colonies showed higher numbers of P. larvae spores in worker and honey samples after five weeks. Despite these results, the rather low number of P. larvae spores on adult SHB suggests that clinical AFB outbreaks are not likely. However, even small spore numbers can be sufficient to spread P. larvae. Therefore, our data clearly show that SHB are vectors of P. larvae. We suggest considering the role of SHB in AFB control in areas where both pests are established.

Winter Losses of Honeybee Colonies (Hymenoptera: Apidae): The Role of Infestations With Aethina tumida (Coleoptera: Nitidulidae) and Varroa destructor (Parasitiformes: Varroidae)

Multiple infections of managed honeybee, Apis mellifera, colonies are inevitable due to the ubiquitous ectoparasitic mite Varroa destructor and might be an underlying cause of winter losses. Here we investigated the role of adult small hive beetles, Aethina tumida, alone and in combination with V. destructor for winter losses and for infections with the microsporidian endoparasite Nosema ceranae. We found no significant influence of A. tumida and V destructor alone or in combination on the numbers of N. ceranae spores. Likewise, A. tumida alone had no significant effects on winter losses, which is most likely due to the observed high winter mortality of the adult beetles. Therefore, our data suggest that A. tumida is unlikely to contribute to losses of overwintering honeybee colonies. However, high losses occurred in all groups highly infested with V. destructor, supporting the central role of the mite for colony losses.

Performance of the Halex in Logitudinal Studies of Older Adults

Goal: The Halex is an indicator of health status that combines self-rated health and activity limitations, which has been used by NCHS to predict future years of healthy life. The scores for each health state were developed based on strong assumptions, notably that a person in excellent health with ADL disabilities is as healthy as a person in poor health with no disabilities. Our goal was to examine the performance of the Halex as a longitudinal measure of health for older adults, and to improve the scoring if necessary. Methods: We used data from the Cardiovascular Health Study (CHS) to compare the relationship of baseline health to health 2 years later. Subject ages ranged from 65 to 103 (mean age 75). A total of 40,827 transitions were available for analysis. We examined whether Halex scores at time 0 were related monotonically to scores two years later, and iterated the original scores to improve the fit over time. Findings: The original Halex scores were not consistent over time. Persons in excellent health with ADL limitations were much healthier 2 years later than people in poor health with no limitations, even though they had been assumed to have identical health. People with ADL limitations had higher scores than predicted. The assumptions made in creating the Halex were not upheld in the data. Conclusions: The new iterated scores are specific to older adults, are appropriate for longitudinal data, and are relatively assumption-free. We recommend the use of these new scores for longitudinal studies of older adults that use the Halex health states.

Bioconductor: Open software development for computational biology and bioinformatics

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. We detail some of the design decisions, software paradigms and operational strategies that have allowed a small number of researchers to provide a wide variety of innovative, extensible, software solutions in a relatively short time. The use of an object oriented programming paradigm, the adoption and development of a software package system, designing by contract, distributed development and collaboration with other projects are elements of this project's success. Individually, each of these concepts are useful and important but when combined they have provided a strong basis for rapid development and deployment of innovative and flexible research software for scientific computation. A primary objective of this initiative is achievement of total remote reproducibility of novel algorithmic research results.

Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

PENALIZED FUNCTIONAL REGRESSION

We develop fast fitting methods for generalized functional linear models. An undersmooth of the functional predictor is obtained by projecting on a large number of smooth eigenvectors and the coefficient function is estimated using penalized spline regression. Our method can be applied to many functional data designs including functions measured with and without error, sparsely or densely sampled. The methods also extend to the case of multiple functional predictors or functional predictors with a natural multilevel structure. Our approach can be implemented using standard mixed effects software and is computationally fast. Our methodology is motivated by a diffusion tensor imaging (DTI) study. The aim of this study is to analyze differences between various cerebral white matter tract property measurements of multiple sclerosis (MS) patients and controls. While the statistical developments proposed here were motivated by the DTI study, the methodology is designed and presented in generality and is applicable to many other areas of scientific research. An online appendix provides R implementations of all simulations.

NONLINEAR TUBE-FITTING FOR THE ANALYSIS OF ANATOMICAL AND FUNCTIONAL STRUCTURES

We are concerned with the estimation of the exterior surface of tube-shaped anatomical structures. This interest is motivated by two distinct scientific goals, one dealing with the distribution of HIV microbicide in the colon and the other with measuring degradation in white-matter tracts in the brain. Our problem is posed as the estimation of the support of a distribution in three dimensions from a sample from that distribution, possibly measured with error. We propose a novel tube-fitting algorithm to construct such estimators. Further, we conduct a simulation study to aid in the choice of a key parameter of the algorithm, and we test our algorithm with validation study tailored to the motivating data sets. Finally, we apply the tube-fitting algorithm to a colon image produced by single photon emission computed tomography (SPECT)and to a white-matter tract image produced using diffusion tensor `imaging (DTI).

Sound As Artifact

A distinguishing feature of the discipline of archaeology is its reliance upon sensory dependant investigation. As perceived by all of the senses, the felt environment is a unique area of archaeological knowledge. It is generally accepted that the emergence of industrial processes in the recent past has been accompanied by unprecedented sonic extremes. The work of environmental historians has provided ample evidence that the introduction of much of this unwanted sound, or "noise" was an area of contestation. More recent research in the history of sound has called for more nuanced distinctions than the noisy/quiet dichotomy. Acoustic archaeology tends to focus upon a reconstruction of sound producing instruments and spaces with a primary goal of ascertaining intentionality. Most archaeoacoustic research is focused on learning more about the sonic world of people within prehistoric timeframes while some research has been done on historic sites. In this thesis, by way of a meditation on industrial sound and the physical remains of the Quincy Mining Company blacksmith shop (Hancock, MI) in particular, I argue for an acceptance and inclusion of sound as artifact in and of itself. I am introducing the concept of an individual sound-form, or sonifact, as a reproducible, repeatable, representable physical entity, created by tangible, perhaps even visible, host-artifacts. A sonifact is a sound that endures through time, with negligible variability. Through the piecing together of historical and archaeological evidence, in this thesis I present a plausible sonifactual assemblage at the blacksmith shop in April 1916 as it may have been experienced by an individual traversing the vicinity on foot: an 'historic soundwalk.' The sensory apprehension of abandoned industrial sites is multi-faceted. In this thesis I hope to make the case for an acceptance of sound as a primary heritage value when thinking about the industrial past, and also for an increased awareness and acceptance of sound and listening as a primary mode of perception.

Model-Centric, Context-Aware Software Adaptation

Software must be constantly adapted to changing requirements. The time scale, abstraction level and granularity of adaptations may vary from short-term, fine-grained adaptation to long-term, coarse-grained evolution. Fine-grained, dynamic and context-dependent adaptations can be particularly difficult to realize in long-lived, large-scale software systems. We argue that, in order to effectively and efficiently deploy such changes, adaptive applications must be built on an infrastructure that is not just model-driven, but is both model-centric and context-aware. Specifically, this means that high-level, causally-connected models of the application and the software infrastructure itself should be available at run-time, and that changes may need to be scoped to the run-time execution context. We first review the dimensions of software adaptation and evolution, and then we show how model-centric design can address the adaptation needs of a variety of applications that span these dimensions. We demonstrate through concrete examples how model-centric and context-aware designs work at the level of application interface, programming language and runtime. We then propose a research agenda for a model-centric development environment that supports dynamic software adaptation and evolution.

Language Boxes: Bending the Host Language with Modular Language Changes

As domain-specific modeling begins to attract widespread acceptance, pressure is increasing for the development of new domain-specific languages. Unfortunately these DSLs typically conflict with the grammar of the host language, making it difficult to compose hybrid code except at the level of strings; few mechanisms (if any) exist to control the scope of usage of multiple DSLs; and, most seriously, existing host language tools are typically unaware of the DSL extensions, thus hampering the development process. Language boxes address these issues by offering a simple, modular mechanism to encapsulate (i) compositional changes to the host language, (ii) transformations to address various concerns such as compilation and highlighting, and (iii) scoping rules to control visibility of language extensions. We describe the design and implementation of language boxes, and show with the help of several examples how modular extensions can be introduced to a host language and environment.