RELIGION IN GLOBAL POLITICS: EXPLAINING DEPRIVATIZATION

Examples of religion’s recent political impact abound in states at varying levels of economic and political development. The paper examines the relationship between religion and politics over the last quarter century in a variety of countries; in effect, a global survey. What was new and became ‘news’ in the 1980s was the widespread and simultaneous refusal of the so-called ‘world religions’ - Islam, Christianity, Hinduism and Buddhism - to restrict them selves to the private sphere. Religious organizations of various kinds seem openly to be rejecting the secular ideals dominating most national policies, appearing as champions of alternative, confessional options. In keeping faith with what they interpret as divine decree, increasingly they refuse to render to nonreligious power either material or moral tribute. They are also refusing to restrict themselves to the pastoral care of individual souls, instead raising questions about, inter alia, the interconnections of private and public morality and the claims of states and markets to be exempt from extrinsic normative considerations

A Predictive Model for Secondary RNA Structure Using Graph Theory and a Neural Network

Background: Determining the secondary structure of RNA from the primary structure is a challenging computational problem. A number of algorithms have been developed to predict the secondary structure from the primary structure. It is agreed that there is still room for improvement in each of these approaches. In this work we build a predictive model for secondary RNA structure using a graph-theoretic tree representation of secondary RNA structure. We model the bonding of two RNA secondary structures to form a larger secondary structure with a graph operation we call merge. We consider all combinatorial possibilities using all possible tree inputs, both those that are RNA-like in structure and those that are not. The resulting data from each tree merge operation is represented by a vector. We use these vectors as input values for a neural network and train the network to recognize a tree as RNA-like or not, based on the merge data vector. The network estimates the probability of a tree being RNA-like.Results: The network correctly assigned a high probability of RNA-likeness to trees previously identified as RNA-like and a low probability of RNA-likeness to those classified as not RNA-like. We then used the neural network to predict the RNA-likeness of the unclassified trees.Conclusions: There are a number of secondary RNA structure prediction algorithms available online. These programs are based on finding the secondary structure with the lowest total free energy. In this work, we create a predictive tool for secondary RNA structures using graph-theoretic values as input for a neural network. The use of a graph operation to theoretically describe the bonding of secondary RNA is novel and is an entirely different approach to the prediction of secondary RNA structures. Our method correctly predicted trees to be RNA-like or not RNA-like for all known cases. In addition, our results convey a measure of likelihood that a tree is RNA-like or not RNA-like. Given that the majority of secondary RNA folding algorithms return more than one possible outcome, our method provides a means of determining the best or most likely structures among all of the possible outcomes

Correspondence

Presents letters to the editor to comment on articles in previous issues. Robert Wright's article "Faux Pas," in the October 11, 1993 issue which castigates Economic Policy Institute President Jeff Faux for his criticism of the North American Free Trade Agreement (NAFTA); Robert Wright's reply; Simon Seba Montefiore's article "Mother Dolores" in the October 4, 1993 issue; Michael Kinsley's "Trading Places" in the October 4 issue in which he criticizes the Republicans who may desert the NAFTA cause; Praise for Jacob Weisberg for finding the unpublished "Blythe Spirit," by William Faulkner, in Weisberg's September 6, 1993 article

Identification of key structural elements for neuronal calcium sensor-1 function in the regulation of the temperature-dependency of locomotion in C. elegans

BACKGROUND: Intracellular Ca(2+) regulates many aspects of neuronal function through Ca(2+) binding to EF hand-containing Ca(2+) sensors that in turn bind target proteins to regulate their function. Amongst the sensors are the neuronal calcium sensor (NCS) family of proteins that are involved in multiple neuronal signalling pathways. Each NCS protein has specific and overlapping targets and physiological functions and specificity is likely to be determined by structural features within the proteins. Common to the NCS proteins is the exposure of a hydrophobic groove, allowing target binding in the Ca(2+)-loaded form. Structural analysis of NCS protein complexes with target peptides has indicated common and distinct aspects of target protein interaction. Two key differences between NCS proteins are the size of the hydrophobic groove that is exposed for interaction and the role of their non-conserved C-terminal tails. RESULTS: We characterised the role of NCS-1 in a temperature-dependent locomotion assay in C. elegans and identified a distinct phenotype in the ncs-1 null in which the worms do not show reduced locomotion at actually elevated temperature. Using rescue of this phenotype we showed that NCS-1 functions in AIY neurons. Structure/function analysis introducing single or double mutations within the hydrophobic groove based on information from characterised target complexes established that both N- and C-terminal pockets of the groove are functionally important and that deletion of the C-terminal tail of NCS-1 did not impair its ability to rescue. CONCLUSIONS: The current work has allowed physiological assessment of suggestions from structural studies on the key structural features that underlie the interaction of NCS-1 with its target proteins. The results are consistent with the notion that full length of the hydrophobic groove is required for the regulatory interactions underlying NCS-1 function whereas the C-terminal tail of NCS-1 is not essential. This has allowed discrimination between two potential modes of interaction of NCS-1 with its targets

Identification of key structural elements for neuronal calcium sensor-1 function in the regulation of the temperature-dependency of locomotion in C. elegans

BACKGROUND: Intracellular Ca2+ regulates many aspects of neuronal function through Ca2+ binding to EF hand-containing Ca2+ sensors that in turn bind target proteins to regulate their function. Amongst the sensors are the neuronal calcium sensor (NCS) family of proteins that are involved in multiple neuronal signalling pathways. Each NCS protein has specific and overlapping targets and physiological functions and specificity is likely to be determined by structural features within the proteins. Common to the NCS proteins is the exposure of a hydrophobic groove, allowing target binding in the Ca2+-loaded form. Structural analysis of NCS protein complexes with target peptides has indicated common and distinct aspects of target protein interaction. Two key differences between NCS proteins are the size of the hydrophobic groove that is exposed for interaction and the role of their non-conserved C-terminal tails. RESULTS: We characterised the role of NCS-1 in a temperature-dependent locomotion assay in C. elegans and identified a distinct phenotype in the ncs-1 null in which the worms do not show reduced locomotion at actually elevated temperature. Using rescue of this phenotype we showed that NCS-1 functions in AIY neurons. Structure/function analysis introducing single or double mutations within the hydrophobic groove based on information from characterised target complexes established that both N- and C-terminal pockets of the groove are functionally important and that deletion of the C-terminal tail of NCS-1 did not impair its ability to rescue. CONCLUSIONS: The current work has allowed physiological assessment of suggestions from structural studies on the key structural features that underlie the interaction of NCS-1 with its target proteins. The results are consistent with the notion that full length of the hydrophobic groove is required for the regulatory interactions underlying NCS-1 function whereas the C-terminal tail of NCS-1 is not essential. This has allowed discrimination between two potential modes of interaction of NCS-1 with its targets

Traffic Aware Planner (TAP) Flight Evaluation

NASA's Traffic Aware Planner (TAP) is a cockpit decision support tool that has the potential to achieve significant fuel and time savings when it is embedded in the data-rich Next Generation Air Transportation System (NextGen) airspace. To address a key step towards the operational deployment of TAP and the NASA concept of Traffic Aware Strategic Aircrew Requests (TASAR), a system evaluation was conducted in a representative flight environment in November, 2013. Numerous challenges were overcome to achieve this goal, including the porting of the foundational Autonomous Operations Planner (AOP) software from its original simulation-based, avionics-embedded environment to an Electronic Flight Bag (EFB) platform. A flight-test aircraft was modified to host the EFB, the TAP application, an Automatic Dependent Surveillance Broadcast (ADS-B) processor, and a satellite broadband datalink. Nine Evaluation Pilots conducted 26 hours of TAP assessments using four route profiles in the complex eastern and north-eastern United States airspace. Extensive avionics and video data were collected, supplemented by comprehensive inflight and post-flight questionnaires. TAP was verified to function properly in the live avionics and ADS-B environment, characterized by recorded data dropouts, latency, and ADS-B message fluctuations. Twelve TAP-generated optimization requests were submitted to ATC, of which nine were approved, and all of which resulted in fuel and/or time savings. Analysis of subjective workload data indicated that pilot interaction with TAP during flight operations did not induce additional cognitive loading. Additionally, analyses of post-flight questionnaire data showed that the pilots perceived TAP to be useful, understandable, intuitive, and easy to use. All program objectives were met, and the next phase of TAP development and evaluations with partner airlines is in planning for 2015

A predictive model for secondary RNA structure using graph theory and a neural network

Background: Determining the secondary structure of RNA from the primary structure is a challenging computational problem. A number of algorithms have been developed to predict the secondary structure from the primary structure. It is agreed that there is still room for improvement in each of these approaches. In this work we build a predictive model for secondary RNA structure using a graph-theoretic tree representation of secondary RNA structure. We model the bonding of two RNA secondary structures to form a larger secondary structure with a graph operation we call merge. We consider all combinatorial possibilities using all possible tree inputs, both those that are RNA-like in structure and those that are not. The resulting data from each tree merge operation is represented by a vector. We use these vectors as input values for a neural network and train the network to recognize a tree as RNA-like or not, based on the merge data vector. The network estimates the probability of a tree being RNA-like.Results: The network correctly assigned a high probability of RNA-likeness to trees previously identified as RNA-like and a low probability of RNA-likeness to those classified as not RNA-like. We then used the neural network to predict the RNA-likeness of the unclassified trees.Conclusions: There are a number of secondary RNA structure prediction algorithms available online. These programs are based on finding the secondary structure with the lowest total free energy. In this work, we create a predictive tool for secondary RNA structures using graph-theoretic values as input for a neural network. The use of a graph operation to theoretically describe the bonding of secondary RNA is novel and is an entirely different approach to the prediction of secondary RNA structures. Our method correctly predicted trees to be RNA-like or not RNA-like for all known cases. In addition, our results convey a measure of likelihood that a tree is RNA-like or not RNA-like. Given that the majority of secondary RNA folding algorithms return more than one possible outcome, our method provides a means of determining the best or most likely structures among all of the possible outcomes

City of Stone Mountain

Students from the Spring 2008 Preservation Planning class compiled and presented these design guidelines to the City of Stone Mountain. The design guidelines were meant to be used as a blueprint for rehabilitation or alteration of historic buildings and new construction. The guidelines present recommended and discouraged courses of action within the historic district. Three character groups are defined, commercial Main Street, a residential area centered on East and West Mountain streets, and Shermantown.https://scholarworks.gsu.edu/history_heritagepreservation/1040/thumbnail.jp

Housworth-Moseley House

Prepared by the Fall 2007 Conservation of Historic Building Materials Class. This historic structure report details the history, current condition, and future treatment and use for the Houseworth-Moseley house located in the Klondike Community of Southern Dekalb County, Georgia. The home was built approximately 1843.https://scholarworks.gsu.edu/history_heritagepreservation/1019/thumbnail.jp