Timber Felling Time, Costs, and Productivity in Arkansas

Sixteen stands were harvested by either clearcut, shelterwood, group selection, or single-tree selection methods. Harvest productivity was evaluated in four consecutive years (1991 through 1994). Three of the stands had uneven-aged structure, the other 13 were typical, mature, even-aged stands. Harvest intensity (proportion of basal area removed) ranged from 0.27 to 1.00. Logging contractors used one to three sawyers with production chain saws to fell trees on all 16 tracts. There was no statistical difference in production rate between sawyers on the same stand. Harvested sites were similar in slope, average diameter at breast height (DBH) and pre-harvest number of stems by two inch diameter class. Total felling time (including walk, acquire, fell, and limb-top times) was inversely related to harvesting intensity and directly related to stem DBH. Factors affecting total felling time (in decreasing order of importance) were DBH of harvested stems, intertree distance, and harvest intensity. Felling productivity (100 cubic feet/hour) was found to be highest under high intensity harvests oflarge trees and lowest under low intensity harvests of small trees. Productivity was more sensitive to stem diameter than harvest intensity. Felling cost was shown to have an inverse relationship with felling productivity

Groups without cultured representatives dominate eukaryotic picophytoplankton in the oligotrophic South East Pacific Ocean

Background: Photosynthetic picoeukaryotes (PPE) with a cell size less than 3 µm play a critical role in oceanic primary production. In recent years, the composition of marine picoeukaryote communities has been intensively investigated by molecular approaches, but their photosynthetic fraction remains poorly characterized. This is largely because the classical approach that relies on constructing 18S rRNA gene clone libraries from filtered seawater samples using universal eukaryotic primers is heavily biased toward heterotrophs, especially alveolates and stramenopiles, despite the fact that autotrophic cells in general outnumber heterotrophic ones in the euphotic zone. Methodology/Principal Findings: In order to better assess the composition of the eukaryotic picophytoplankton in the South East Pacific Ocean, encompassing the most oligotrophic oceanic regions on earth, we used a novel approach based on flow cytometry sorting followed by construction of 18S rRNA gene clone libraries. This strategy dramatically increased the recovery of sequences from putative autotrophic groups. The composition of the PPE community appeared highly variable both vertically down the water column and horizontally across the South East Pacific Ocean. In the central gyre, uncultivated lineages dominated: a recently discovered clade of Prasinophyceae (IX), clades of marine Chrysophyceae and Haptophyta, the latter division containing a potentially new class besides Prymnesiophyceae and Pavlophyceae. In contrast, on the edge of the gyre and in the coastal Chilean upwelling, groups with cultivated representatives (Prasinophyceae clade VII and Mamiellales) dominated. Conclusions/Significance: Our data demonstrate that a very large fraction of the eukaryotic picophytoplankton still escapes cultivation. The use of flow cytometry sorting should prove very useful to better characterize specific plankton populations by molecular approaches such as gene cloning or metagenomics, and also to obtain into culture strains representative of these novel groups

The spatial resolution of epidemic peaks

The emergence of novel respiratory pathogens can challenge the capacity of key health care resources, such as intensive care units, that are constrained to serve only specific geographical populations. An ability to predict the magnitude and timing of peak incidence at the scale of a single large population would help to accurately assess the value of interventions designed to reduce that peak. However, current disease-dynamic theory does not provide a clear understanding of the relationship between: epidemic trajectories at the scale of interest (e.g. city); population mobility; and higher resolution spatial effects (e.g. transmission within small neighbourhoods). Here, we used a spatially-explicit stochastic meta-population model of arbitrary spatial resolution to determine the effect of resolution on model-derived epidemic trajectories. We simulated an influenza-like pathogen spreading across theoretical and actual population densities and varied our assumptions about mobility using Latin-Hypercube sampling. Even though, by design, cumulative attack rates were the same for all resolutions and mobilities, peak incidences were different. Clear thresholds existed for all tested populations, such that models with resolutions lower than the threshold substantially overestimated population-wide peak incidence. The effect of resolution was most important in populations which were of lower density and lower mobility. With the expectation of accurate spatial incidence datasets in the near future, our objective was to provide a framework for how to use these data correctly in a spatial meta-population model. Our results suggest that there is a fundamental spatial resolution for any pathogen-population pair. If underlying interactions between pathogens and spatially heterogeneous populations are represented at this resolution or higher, accurate predictions of peak incidence for city-scale epidemics are feasible

Microbial community succession on developing lesions on human enamel

Dental caries is one of the most common diseases in the world. However, our understanding of how the microbial community composition changes in vivo as caries develops is lacking.An in vivo model was used in a longitudinal cohort study to investigate shifts in the microbial community composition associated with the development of enamel caries.White spot lesions were generated in vivo on human teeth predetermined to be extracted for orthodontic reasons. The bacterial microbiota on sound enamel and on developing carious lesions were identified using the Human Oral Microbe Identification Microarray (HOMIM), which permits the detection of about 300 of the approximate 600 predominant bacterial species in the oral cavity.After only seven weeks, 75% of targeted teeth developed white spot lesions (8 individuals, 16 teeth). The microbial community composition of the plaque over white spot lesions differed significantly as compared to sound enamel. Twenty-five bacterial taxa, including Streptococcus mutans, Atopobium parvulum, Dialister invisus, and species of Prevotella and Scardovia, were significantly associated with initial enamel lesions. In contrast, 14 bacterial taxa, including species of Fusobacterium, Campylobacter, Kingella, and Capnocytophaga, were significantly associated with sound enamel.The bacterial community composition associated with the progression of enamel lesions is specific and much more complex than previously believed. This investigation represents one of the first longitudinally-derived studies for caries progression and supports microbial data from previous cross-sectional studies on the development of the disease. Thus, the in vivo experiments of generating lesions on teeth destined for extraction in conjunction with HOMIM analyses represent a valid model to study succession of supragingival microbial communities associated with caries development and to study efficacy of prophylactic and restorative treatments

Using a real-world network to model localized COVID-19 control strategies

Case isolation and contact tracing can contribute to the control of COVID-19 outbreaks1,2. However, it remains unclear how real-world social networks could influence the effectiveness and efficiency of such approaches. To address this issue, we simulated control strategies for SARS-CoV-2 transmission in a real-world social network generated from high-resolution GPS data that were gathered in the course of a citizen-science experiment3,4. We found that tracing the contacts of contacts reduced the size of simulated outbreaks more than tracing of only contacts, but this strategy also resulted in almost half of the local population being quarantined at a single point in time. Testing and releasing non-infectious individuals from quarantine led to increases in outbreak size, suggesting that contact tracing and quarantine might be most effective as a ‘local lockdown’ strategy when contact rates are high. Finally, we estimated that combining physical distancing with contact tracing could enable epidemic control while reducing the number of quarantined individuals. Our findings suggest that targeted tracing and quarantine strategies would be most efficient when combined with other control measures such as physical distancing

How can the public health impact of vaccination be estimated?

BACKGROUND: Deaths due to vaccine preventable diseases cause a notable proportion of mortality worldwide. To quantify the importance of vaccination, it is necessary to estimate the burden averted through vaccination. The Vaccine Impact Modelling Consortium (VIMC) was established to estimate the health impact of vaccination. METHODS: We describe the methods implemented by the VIMC to estimate impact by calendar year, birth year and year of vaccination (YoV). The calendar and birth year methods estimate impact in a particular year and over the lifetime of a particular birth cohort, respectively. The YoV method estimates the impact of a particular year's vaccination activities through the use of impact ratios which have no stratification and stratification by activity type and/or birth cohort. Furthermore, we detail an impact extrapolation (IE) method for use between coverage scenarios. We compare the methods, focusing on YoV for hepatitis B, measles and yellow fever. RESULTS: We find that the YoV methods estimate similar impact with routine vaccinations but have greater yearly variation when campaigns occur with the birth cohort stratification. The IE performs well for the YoV methods, providing a time-efficient mechanism for updates to impact estimates. CONCLUSIONS: These methods provide a robust set of approaches to quantify vaccination impact; however it is vital that the area of impact estimation continues to develop in order to capture the full effect of immunisation

The European project FLOMIX-R: Fluid mixing and flow distribution inthe reactor circuit - Final summary report

The project was aimed at describing the mixing phenomena relevant for both safety analysis, particularly in steam line break and boron dilution scenarios, and mixing phenomena of interest for economical operation and the structural integrity. Measurement data from a set of mixing experiments, gained by using advanced measurement techniques with enhanced resolution in time and space help to improve the basic understanding of turbulent mixing and to provide data for Computational Fluid Dynamics (CFD) code validation. Slug mixing tests simulating the start-up of the first main circulation pump are performed with two 1:5 scaled facilities: The Rossendorf coolant mixing model ROCOM and the VATTENFALL test facility, modelling a German Konvoi type and a Westinghouse type three-loop PWR, respectively. Additional data on slug mixing in a VVER-1000 type reactor gained at a 1:5 scaled metal mock-up at EDO Gidropress are provided. Experimental results on mixing of fluids with density differences obtained at ROCOM and the FORTUM PTS test facility are made available. Concerning mixing phenomena of interest for operational issues and thermal fatigue, flow distribution data available from commissioning tests (Sizewell-B for PWRs, Loviisa and Paks for VVERs) are used together with the data from the ROCOM facility as a basis for the flow distribution studies. The test matrix on flow distribution and steady state mixing performed at ROCOM comprises experiments with various combinations of running pumps and various mass flow rates in the working loops. Computational fluid dynamics calculations are accomplished for selected experiments with two different CFD codes (CFX-5, FLUENT). Best practice guidelines (BPG) are applied in all CFD work when choosing computational grid, time step, turbulence models, modelling of internal geometry, boundary conditions, numerical schemes and convergence criteria. The BPG contain a set of systematic procedures for quantifying and reducing numerical errors. The knowledge of these numerical errors is a prerequisite for the proper judgement of model errors. The strategy of code validation based on the BPG and a matrix of CFD code validation calculations have been elaborated. Besides of the benchmark cases, additional experiments were calculated by new partners and observers, joining the project later. Based on the "best practice solutions", conclusions on the applicability of CFD for turbulent mixing problems in PWR were drawn and recommendations on CFD modelling were given. The high importance of proper grid generation was outlined. In general, second order discretization schemes should be used to minimise numerical diffusion. First order schemes can provide physically wrong results. With optimised "production meshes" reasonable results were obtained, but due to the complex geometry of the flow domains, no fully grid independent solutions were achieved. Therefore, with respect to turbulence models, no final conclusions can be given. However, first order turbulence models like K-e or SST K-w are suitable for momentum driven slug mixing. For buoyancy driven mixing (PTS scenarios), Reynolds stress models provide better results

Modeling infectious disease dynamics in the complex landscape of global health.

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health

Matrix models and sensitivity analysis of populations classified by age and stage : a vec-permutation matrix approach

© The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Theoretical Ecology 5 (2012): 403-417, doi:10.1007/s12080-011-0132-2.Matrix population models in which individuals are classified by both age and stage can be constructed using the vec-permutation matrix. The resulting age-stage models can be used to derive the age-specific consequences of a stage-specific life history or to describe populations in which the vital rates respond to both age and stage. I derive a general formula for the sensitivity of any output (scalar, vector, or matrix-valued) of the model, to any vector of parameters, using matrix calculus. The matrices describing age-stage dynamics are almost always reducible; I present results giving conditions under which population growth is ergodic from any initial condition. As an example, I analyze a published stage-specific model of Scotch broom (Cytisus scoparius), an invasive perennial shrub. Sensitivity analysis of the population growth rate finds that the selection gradients on adult survival do not always decrease with age but may increase over a range of ages. This may have implications for the evolution of senescence in stage-classified populations. I also derive and analyze the joint distribution of age and stage at death and present a sensitivity analysis of this distribution and of the marginal distribution of age at death.This research was supported by National Science Foundation Grant DEB-0816514 and by a Research Award from the Alexander von Humboldt Foundation