Size-dependent aerosol deposition velocities during BEARPEX'07

Aerosol concentrations and 3-D winds were measured from 9 to 25 September 2007, above a pine forest in California. The measurements were combined using the eddy covariance (EC) technique to determine aerosol eddy fluxes as a function of particle diameter within the accumulation mode size range (0.25 μm≤D[subscript]p≤1 μm here). Measured heat and water vapor fluxes were utilized to correct the aerosol eddy fluxes for aerosol hygroscopic growth. The hygroscopic growth correction was necessary despite the low RH and relatively hygrophobic nature of the particles. Uncertainties associated with particle counting also were evaluated from the data. Aerosol deposition velocities (V[subscript]d = EC turbulent flux/mean particle concentration) during daytime were shown to vary from −0.2 to −1.0 cm s⁻¹; the magnitude of particle V[subscript]d increases with friction velocity and particle diameter

Early corn stand count of different cropping systems using UAV-imagery and deep learning

Optimum plant stand density and uniformity is vital in order to maximize corn (Zea mays L.) yield potential. Assessment of stand density can occur shortly after seedlings begin to emerge, allowing for timely replant decisions. The conventional methods for evaluating an early plant stand rely on manual measurement and visual observation, which are time consuming, subjective because of the small sampling areas used, and unable to capture field-scale spatial variability. This study aimed to evaluate the feasibility of an unmanned aerial vehicle (UAV)-based imaging system for estimating early corn stand count in three cropping systems (CS) with different tillage and crop rotation practices. A UAV equipped with an on-board RGB camera was used to collect imagery of corn seedlings (~14 days after planting) of CS, i.e., minimum-till corn-soybean rotation (MTCS), no-till corn-soybean rotation (NTCS), and no-till corn-corn rotation with cover crop implementation (NTCC). An image processing workflow based on a deep learning (DL) model, U-Net, was developed for plant segmentation and stand count estimation. Results showed that the DL model performed best in segmenting seedlings in MTCS, followed by NTCS and NTCC. Similarly, accuracy for stand count estimation was highest in MTCS (R2 = 0.95), followed by NTCS (0.94) and NTCC (0.92). Differences by CS were related to amount and distribution of soil surface residue cover, with increasing residue generally reducing the performance of the proposed method in stand count estimation. Thus, the feasibility of using UAV imagery and DL modeling for estimating early corn stand count is qualified influenced by soil and crop management practices

Estimating corn emergence date using UAV-based imagery

Assessing corn (Zea Mays L.) emergence uniformity soon after planting is important for relating to grain production and for making replanting decisions. Unmanned aerial vehicle (UAV) imagery has been used for determining corn densities at vegetative growth stage 2 (V2) and later, but not as a tool for detecting emergence date. The objective of this study was to estimate days after corn emergence (DAE) using UAV imagery. A field experiment was designed with four planting depths to obtain a range of corn emergence dates. UAV imagery was collected during the first, second and third weeks after emergence. Acquisition height was approximately 5m above ground level resulted in a ground sampling distance 1.5 mm pixel-1. Seedling size and shape features derived from UAV imagery were used for DAE classification based on the Random Forest machine learning model. Results showed image features were distinguishable for different DAE (single day) within the first week after initial corn emergence with a moderate overall classification accuracy of 0.49. However, for the second week and beyond the overall classification accuracy diminished (0.20 to 0.35). When estimating DAE within a three-day window (± 1 DAE), overall 3-day classification accuracies ranged from 0.54 to 0.88. Diameter, area, and major axis length/area were important image features to predict corn DAE. Findings demonstrated that UAV imagery can detect newly-emerged corn plants and estimate their emergence date to assist in establishing emergence uniformity. Additional studies are needed for fine-tuning image collection procedures and image feature identification in order to improve accuracy

The twistorial structure of loop-gravity transition amplitudes

The spin foam formalism provides transition amplitudes for loop quantum gravity. Important aspects of the dynamics are understood, but many open questions are pressing on. In this paper we address some of them using a twistorial description, which brings new light on both classical and quantum aspects of the theory. At the classical level, we clarify the covariant properties of the discrete geometries involved, and the role of the simplicity constraints in leading to SU(2) Ashtekar-Barbero variables. We identify areas and Lorentzian dihedral angles in twistor space, and show that they form a canonical pair. The primary simplicity constraints are solved by simple twistors, parametrized by SU(2) spinors and the dihedral angles. We construct an SU(2) holonomy and prove it to correspond to the (lattice version of the) Ashtekar-Barbero connection. We argue that the role of secondary constraints is to provide a non trivial embedding of the cotangent bundle of SU(2) in the space of simple twistors. At the quantum level, a Schroedinger representation leads to a spinorial version of simple projected spin networks, where the argument of the wave functions is a spinor instead of a group element. We rewrite the Liouville measure on the cotangent bundle of SL(2,C) as an integral in twistor space. Using these tools, we show that the Engle-Pereira-Rovelli-Livine transition amplitudes can be derived from a path integral in twistor space. We construct a curvature tensor, show that it carries torsion off-shell, and that its Riemann part is of Petrov type D. Finally, we make contact between the semiclassical asymptotic behaviour of the model and our construction, clarifying the relation of the Regge geometries with the original phase space.Comment: 40 pages, 3 figures. v2: minor improvements, references adde

Complex Ashtekar variables and reality conditions for Holst's action

From the Holst action in terms of complex valued Ashtekar variables additional reality conditions mimicking the linear simplicity constraints of spin foam gravity are found. In quantum theory with the results of You and Rovelli we are able to implement these constraints weakly, that is in the sense of Gupta and Bleuler. The resulting kinematical Hilbert space matches the original one of loop quantum gravity, that is for real valued Ashtekar connection. Our result perfectly fit with recent developments of Rovelli and Speziale concerning Lorentz covariance within spin-form gravity.Comment: 24 pages, 2 picture

Earlier versus later start of antiretroviral therapy in HIV-infected adults with tuberculosis.

Tuberculosis remains an important cause of death among patients infected with the human immunodeficiency virus (HIV). Robust data are lacking with regard to the timing for the initiation of antiretroviral therapy (ART) in relation to the start of antituberculosis therapy

Cell surface and in vivo interaction of dendrimeric N-glycoclusters

© 2015 Springer Science+Business Media New York. While many examples have been reported that glycoclusters interact with target lectins more strongly than single molecules of glycans, through multivalency effects, literature examples to support lectin interactions/modulations on cell surface and in live animals is quite rare. Our N-glycoclusters, which were efficiently prepared by immobilizing 16 molecules of the asparagine-linked glycans (N-glycans) onto a lysine-based dendron template through histidine-mediated Huisgen cycloaddition, were shown to efficiently detect platelet endothelial cell adhesion molecule (PECAM) on human umbilical vein endothelial cells (HUVEC) as a α(2-6)-sialylated oligosaccharides recognizing lectin. Furthermore, the identity of the N-glycans on our N-glycoclusters allowed control over organ-selective accumulation and serum clearance properties when intravenously injected into mice

Cost and disease burden of Dengue in Cambodia

<p>Abstract</p> <p>Background</p> <p>Dengue is endemic in Cambodia (pop. estimates 14.4 million), a country with poor health and economic indicators. Disease burden estimates help decision makers in setting priorities. Using recent estimates of dengue incidence in Cambodia, we estimated the cost of dengue and its burden using disability adjusted life years (DALYs).</p> <p>Methods</p> <p>Recent population-based cohort data were used to calculate direct and productive costs, and DALYs. Health seeking behaviors were taken into account in cost estimates. Specific age group incidence estimates were used in DALYs calculation.</p> <p>Results</p> <p>The mean cost per dengue case varied from US$36 -$75 over 2006-2008 respectively, resulting in an overall annual cost from US$3,327,284 in 2008 to US$14,429,513 during a large epidemic in 2007. Patients sustain the highest share of costs by paying an average of 78% of total costs and 63% of direct medical costs. DALY rates per 100,000 individuals ranged from 24.3 to 100.6 in 2007-2008 with 80% on average due to premature mortality.</p> <p>Conclusion</p> <p>Our analysis confirmed the high societal and individual family burden of dengue. Total costs represented between 0.03 and 0.17% of Gross Domestic Product. Health seeking behavior has a major impact on costs. The more accurate estimate used in this study will better allow decision makers to account for dengue costs particularly among the poor when balancing the benefits of introducing a potentially effective dengue vaccine.</p

Hazard Analysis of Critical Control Points Assessment as a Tool to Respond to Emerging Infectious Disease Outbreaks

Highly pathogenic avian influenza virus (HPAI) strain H5N1 has had direct and indirect economic impacts arising from direct mortality and control programmes in over 50 countries reporting poultry outbreaks. HPAI H5N1 is now reported as the most widespread and expensive zoonotic disease recorded and continues to pose a global health threat. The aim of this research was to assess the potential of utilising Hazard Analysis of Critical Control Points (HACCP) assessments in providing a framework for a rapid response to emerging infectious disease outbreaks. This novel approach applies a scientific process, widely used in food production systems, to assess risks related to a specific emerging health threat within a known zoonotic disease hotspot. We conducted a HACCP assessment for HPAI viruses within Vietnam’s domestic poultry trade and relate our findings to the existing literature. Our HACCP assessment identified poultry flock isolation, transportation, slaughter, preparation and consumption as critical control points for Vietnam’s domestic poultry trade. Introduction of the preventative measures highlighted through this HACCP evaluation would reduce the risks posed by HPAI viruses and pressure on the national economy. We conclude that this HACCP assessment provides compelling evidence for the future potential that HACCP analyses could play in initiating a rapid response to emerging infectious diseases

Up-Regulation of Annexin-A1 and Lipoxin A4 in Individuals with Ulcerative Colitis May Promote Mucosal Homeostasis

PubMed ID: 22723974This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited