Sold! : James River islands auctioned

Recreation ; Real estate investment

Asphalt antidote : "living" roofs absorb runoff

Pollution ; Agriculture

Grundy moves on : town relocates to avoid floods

Cities and towns

Viral Reservoirs in Lymph Nodes of FIV-Infected Progressor and Long-Term Non-Progressor Cats during the Asymptomatic Phase.

BackgroundExamination of a cohort of cats experimentally infected with feline immunodeficiency virus (FIV) for 5.75 years revealed detectable proviral DNA in peripheral blood mononuclear cells (PBMCs) harvested during the asymptomatic phase, undetectable plasma viral RNA (FIV gag), and rarely detectable cell-associated viral RNA. Despite apparent viral latency in peripheral CD4+ T cells, circulating CD4+ T cell numbers progressively declined in progressor animals. The aim of this study was to explore this dichotomy of peripheral blood viral latency in the face of progressive immunopathology. The viral replication status, cellular immunophenotypes, and histopathologic features were compared between popliteal lymph nodes (PLNs) and peripheral blood. Also, we identified and further characterized one of the FIV-infected cats identified as a long-term non-progressor (LTNP).ResultsPLN-derived leukocytes from FIV-infected cats during the chronic asymptomatic phase demonstrated active viral gag transcription and FIV protein translation as determined by real-time RT-PCR, Western blot and in situ immunohistochemistry, whereas viral RNA in blood leukocytes was either undetectable or intermittently detectable and viral protein was not detected. Active transcription of viral RNA was detectable in PLN-derived CD4+ and CD21+ leukocytes. Replication competent provirus was reactivated ex vivo from PLN-derived leukocytes from three of four FIV-infected cats. Progressor cats showed a persistent and dramatically decreased proportion and absolute count of CD4+ T cells in blood, and a decreased proportion of CD4+ T cells in PLNs. A single long-term non-progressor (LTNP) cat persistently demonstrated an absolute peripheral blood CD4+ T cell count indistinguishable from uninfected animals, a lower proviral load in unfractionated blood and PLN leukocytes, and very low amounts of viral RNA in the PLN.ConclusionCollectively our data indicates that PLNs harbor important reservoirs of ongoing viral replication during the asymptomatic phase of infection, in spite of undetectable viral activity in peripheral blood. A thorough understanding of tissue-based lentiviral reservoirs is fundamental to medical interventions to eliminate virus or prolong the asymptomatic phase of FIV infection

Machine Learning and Neutron Sensing in Mobile Nuclear Threat Detection

A proof of concept (PoC) neutron/gamma-ray mobile threat detection system was constructed at Oak Ridge National Laboratory. This device, the Dual Detection Localization and Identification (DDLI) system, was designed to detect threat sources at standoff distance using neutron and gamma ray coded aperture imaging. A major research goal of the project was to understand the benefit of neutron sensing in the mobile threat search scenario. To this end, a series of mobile measurements were conducted with the completed DDLI PoC. These measurements indicated that high detection rates would be possible using neutron counting alone in a fully instrumented system. For a 280,000 neutrons per second Cf-252 source placed 15.9 meters away, a 4σ [sigma] detection rate of 99.3% was expected at 5 m/s. These results support the conclusion that neutron sensing enhances the detection capabilities of systems like the DDLI when compared to gamma-only platforms. Advanced algorithms were also investigated to fuse neutron and gamma coded aperture images and suppress background. In a simulated 1-D coded aperture imaging study, machine learning algorithms using both neutron and gamma ray data outperformed gamma-only threshold methods for alarming on weapons grade plutonium. In a separate study, a Random Forest classifier was trained on a source injection dataset from the Large Area Imager, a mobile gamma ray coded aperture system. Geant4 simulations of weapons-grade plutonium (WGPu) were combined with background data measured by the Large Area Imager to create nearly 4000 coded aperture images. At 30 meter standoff and 10 m/s, the Random Forest classifier was able to detect WGPu with error rates as low as 0.65% without spectroscopic information. A background subtracting filter further reduced this error rate to 0.2%. Finally, a background subtraction method based on principal component analysis was shown to improve detection by over 150% in figure of merit

A Comprehensive Rail Rate Index for Grain

There are several annual rail rate indices commonly used to depict changes in the prices paid for rail service. While accurate for general analyses, each of these indices falls short in capturing the three major components of total railroad grain rates – tariff rates, fuel surcharges, and secondary railcar market costs. Grain is a rail commodity whereby bids in the secondary railcar market can affect whether the actual rate paid by shippers is above or below the published tariff rate. The seasonality of rates inherent in grain transportation is captured through the secondary market but is neither contained in other grain rail rate indices nor apparent in annualized data. In addition, most grain rate indices do not include fuel surcharges, which have become a major component of the total rate paid for any rail commodity movement. In this paper, we develop new rail rate indices for unit trains and shuttle trains and compare them against a rail cost index. The new indices are an improvement upon past grain rail rate indices by including information from the secondary rail market, fuel surcharges, and tariff rates into a weekly index between the years 1997 and 2011. The improved indices show a higher level of detail when compared to other annualized indices, allowing for a more thorough analysis of grain rates. These indices show grain rail rates generally higher than do other indices with a notable departure from rail costs at the beginning of the economic recession in 2009. A comparison of the rail indices with rail costs calls into question whether earlier conclusions about rail market power still hold