Robert Burns and the Hellish Legion

Folk tales and beliefs are as important a part of cultural history as novels or organised religion. Robert Burns and the Hellish Legion explores some aspects of life in the world in which Burns lived and wrote, the supernatural beliefs which people held, and how they fitted into their everyday lives. Burns himself did not believe that the cloven-hoofed Devil appeared in Ayrshire, but he understood that other people did think that Satan walked the earth and witches were real, and that these were genuine beliefs which stemmed from the need to understand the inconsistent world. This is the world of ordinary men and women who deserve to have their history recorded, whether they are washing clothes in the burn, harvesting corn or sitting at the fireside, telling the story of a witch pursuing a drunken farmer on a grey horse. Devils, witches and evil – this book examines beliefs in these in Burns’s time. Several of his most famous poems deal with the supernatural. In contrast with the insubstantial but terrifying world of the supernatural the book also looks at the lives of country people and the nature of the material world in which they lived. ‘Tam o’Shanter’ brings all of this together and the book ends with a discussion of the poem

RNA interference approaches for treatment of HIV-1 infection.

HIV/AIDS is a chronic and debilitating disease that cannot be cured with current antiretroviral drugs. While combinatorial antiretroviral therapy (cART) can potently suppress HIV-1 replication and delay the onset of AIDS, viral mutagenesis often leads to viral escape from multiple drugs. In addition to the pharmacological agents that comprise cART drug cocktails, new biological therapeutics are reaching the clinic. These include gene-based therapies that utilize RNA interference (RNAi) to silence the expression of viral or host mRNA targets that are required for HIV-1 infection and/or replication. RNAi allows sequence-specific design to compensate for viral mutants and natural variants, thereby drastically expanding the number of therapeutic targets beyond the capabilities of cART. Recent advances in clinical and preclinical studies have demonstrated the promise of RNAi therapeutics, reinforcing the concept that RNAi-based agents might offer a safe, effective, and more durable approach for the treatment of HIV/AIDS. Nevertheless, there are challenges that must be overcome in order for RNAi therapeutics to reach their clinical potential. These include the refinement of strategies for delivery and to reduce the risk of mutational escape. In this review, we provide an overview of RNAi-based therapies for HIV-1, examine a variety of combinatorial RNAi strategies, and discuss approaches for ex vivo delivery and in vivo delivery

U.S. State-Level Carbon Dioxide Emissions: A Spatial-Temporal Econometric Approach of the Environmental Kuznets Curve

One of the major criticisms of past environmental Kuznets curve (EKC) studies is that the spatiotemporal aspects within the data have largely been ignored. By ignoring the spatial aspect of pollution emissions past estimates of the EKC implicitly assume that a region’s emissions are unaffected by events in neighboring regions (i.e., assume there are no transboundary pollution emissions between neighbors). By ignoring the spatial aspects within the data several past estimates of the EKC could have generated biased or inconsistent regression results. By ignoring the temporal aspect within the data several past estimates of the EKC could have generated spurious regression results or misspecified t and F statistics. To address this potential misspecification we estimate the relationship between state-level carbon dioxide emissions and income (GDP) accounting for both the spatiotemporal components within the data. Specifically, we estimate a dynamic spatiotemporal panel model using a newly proposed robust, spatial fixed effects model. This new estimation scheme is appropriate for panels with large N and T. Consistent with the EKC hypothesis we find the inverted-U shaped relationship between CO2 emissions and income. Further, we find adequate evidence that carbon dioxide emissions and state-level GDP are temporally and spatially dependent. These findings offer policy implications for both interstate energy trade and pollution emission regulations. These implications are particularly important for the formulation of national policies related to the 2009 Copenhagen Treaty in which the U.S. has committed to significantly reduce greenhouse gas emissions over the next twenty years.Environmental Kuznets Curve, Carbon Dioxide, Spatial Econometrics, Panel Data Econometrics, Time Series Analysis, Environmental Economics, Pollution Economics, Environmental Economics and Policy, Q50, Q53, Q43, C01, C33,

A Spatiotemporal Fixed Effects Estimation of U.S. State-Level Carbon Dioxide Emissions

One of the major shortcommings of past environmental Kuznets curve (EKC) studies is that the spatiotemporal aspects within the data have largely been ignored. By ignoring the spatial aspect of pollution emissions past estimates of the EKC implicitly assume that a region’s emissions are unaffected by events in neighboring regions (i.e., assume there are no transboundary pollution emissions between neighbors). By ignoring the spatial aspects within the data several past estimates of the EKC could have generated biased or inconsistent regression results. By ignoring the temporal aspect within the data several past estimates of the EKC could have generated spurious regression results or misspecified t and F statistics. To address this potential misspecification we estimate the relationship between state-level carbon dioxide emissions and income (GDP) accounting for both the spatiotemporal components within the data. Specifically, we estimate a dynamic spatiotemporal panel model using a newly proposed robust, spatial fixed effects model. This new estimation scheme is appropriate for panels with large N and T. Consistent with the EKC hypothesis we find the inverted-U shaped relationship between CO2 emissions and income. Further, we find adequate evidence that the underlying economic processes driving carbon dioxide emissions and state-level GDP are temporally and spatially dependent. These findings offer policy implications for both interstate energy trade and pollution emission regulations. These implications are particularly important for the formulation of national policies related to the 2009 Copenhagen Treaty in which the U.S. has committed to significantly reduce greenhouse gas emissions over the next twenty years.Pollution Economics, Environmental Kuznets Curve, Spatial Econometrics, Dynamic Panel Data, Carbon Dioxide Emissions, Global Climate Change, Environmental Economics and Policy, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy, C33, C51, Q43, Q50, Q53, Q58,

Orders: A Wolf in Sheep\u27s Clothing for Environmental and Toxic Tort Litigation

In colorful prose, the author begins the Comment with an excellent hypothetical illustrating the heavy burden a Lone Pine Order places on a plaintiff struggling to keep a toxic torts case in court. Starting with this foundation, the author conducts an in-depth review of the elements and operation of Lone Pine Orders. Next, the author outlines the features of typical torts case, pointing out how the features make compliance with a Lone Pine Order very difficult. The author next discusses and compares the pros and cons of Lone Pine Orders. He thoroughly examines how a Lone Pine Order can be used as a case management tool by the courts to expeditiously dispense with toxic torts cases. In contrast, the author discusses the adequacy of existing procedural safeguards and the inconsistency with which Lone Pine Orders are issued to undermine any case management benefits the orders may serve. The author concludes by arguing that Lone Pine Orders should no longer be used due to both the existence of the procedural safeguards and trends in modern toxic torts cases indicating reliance on such safeguards

Mobile robot localization using a Kalman filter and relative bearing measurements to known landmarks

This paper discusses mobile robot localization using a single, fixed camera that is capable of detecting predefined landmarks in the environment. For each visible landmark, the camera provides a relative bearing but not a relative range. This research represents work toward an inexpensive sensor that could be added to a mobile robot in order to provide more accurate estimates of the robot\u27s location. It uses the Kalman filter as a framework, which is a proven method for incorporating sensor data into navigation problems. In the simulations presented later, it is assumed that the filter can perform accurate feature recognition. In the experimental setup, however, a webcam and an open source library are used to recognize and track bearing to a set of unique markers. Although this research requires that the landmark locations be known, in contrast to research in simultaneous localization and mapping, the results are still useful in an industrial setting where placing known landmarks would be acceptable