Primate vocalizations during social separation and aggression: effects of alcohol and benzodiazepines

The most common group of squirrel monkey vocalizations, peeps, are emitted during different social situations including social separation, affiliative interactions, feeding and aggressive confrontations. The present experiments investigated whether peeps and other vocalizations emitted during different social contexts are pharmacologically altered in a similar manner. First, vocalizations were characterized during (1) social separation in juveniles, and (2) "resident-intruder" aggressive confrontations between dominant monkeys from different social groups. Then, the effects of alcohol (EtOH) and the benzodiazepine chlordiazepoxide (CDP) on vocalizations during social separation and during aggression were examined. Isolated juveniles emitted only one type of call, the isolation peep. Resident monkeys primarily emitted peeps, but also emitted cackles, chucks, noisy calls and pulsed calls. Aggressive peeps were similar in structure and frequency (kHz) to isolation peeps, but were shorter in duration. At the same doses, both CDP (0.3-3 mg/kg) and EtOH (0.1-1.0 g/kg) reduced explosive motor behaviors and isolation peeps in juvenile monkeys during social separation and increased threat displays and aggression peeps in resident monkeys during confrontations with an intruder monkey from a different social group. Thus, similarly structured vocalizations that were emitted during social separation and aggression were very sensitive to EtOH and CDP, but the social context determined the direction and magnitude of effects.     

Upper limit ofTc for the copper oxides

The value of the critical temperature of the cuprates correlates with the doping level and is affected by the interplay of two competing factors: (1) the increase in carrier concentration, and (2) the pair-breaking effect of magnetic impurities. An analysis of the temperature dependence of the critical field leads to the conclusion that magnetic impurities are present even in a sample with the maximum observed value ofT _c.A new parameter, intrinsicT _c (T _cintr), which is its value in the absence of magnetic impurities, is introduced. The maximum value ofT _cintr, which corresponds to the maximum doping level, appears to be similar for different cuprates and to be equal to 160–170 K. This is the upper limit ofT _c in the cuprates.     

Animal and plant cell lysates share a conserved chaperone system that assembles the glucocorticoid receptor into a functional heterocomplex with hsp90

The hormone-binding domain of the glucocorticoid receptor must be bound to heat shock protein (hsp) 90 for it to have a high-affinity steroid-binding conformation. Cell-free assembly of a glucocorticoid receptor-hsp90 heterocomplex is brought about in reticulocyte lysate by a preformed protein-folding complex containing hsp90, hsp70, and other proteins [Hutchison, K.A., Dittmar, K. D., & Pratt, W.B. (1994) J. Biol. Chem. 269, 27894-27899]. In this "foldosome" system, hsp70 is required for assembly of the receptor-hsp90 complex and concomitant activation of steroid-binding activity [Hutchison, K.A., Dittmar, K.D., Czar, M.J., & Pratt, W.B. (1994) J. Biol. Chem. 269, 22157-22161]. All previous experiments involving cell-free assembly of both receptor-hsp90 and protein kinase-hsp90 heterocomplexes have been carried out with the protein-folding system in rabbit reticulocyte lysate. In this work, we show that concentrated lysates of receptor-free mouse (L cells) and insect (Sf9) cells and also a plant (wheat germ) lysate fold the immunopurified glucocorticoid receptor into a functional (i.e., steroid binding) heterocomplex with hsp90. Receptor heterocomplex formation in animal lysates and in the plant lysate are not identical in that the dynamics of complex assembly are different, but both systems produce a functional complex that binds steroid. Also, in contrast to animal and insect complexes, receptor-plant hsp90 complexes are not stabilized by molybdate. When added to the other lysate, purified plant and animal hsp90s show partial complementarity, in that a receptor-hsp90 complex is formed but the receptor is not converted to the steroid-binding conformation. When added to rabbit reticulocyte lysate that has been depleted of endogenous hsp70, purified wheat germ and mouse hsp70's are equally active in promoting both assembly of receptor-hsp90 heterocomplexes and conversion of receptor to the steroid-binding conformation. Thus, hsp70 from the plant kingdom has conserved the ability to interact functionally with chaperone proteins of the animal kingdom to cooperate in protein folding as evidenced by formation of a functional receptor-hsp90 heterocomplex.     

A rapid computational filter for predicting the rate of human renal clearance

In silico models that predict the rate of human renal clearance for a diverse set of drugs, that exhibit both active secretion and net re-absorption, have been produced using three statistical approaches. Partial Least Squares (PLS) and Random Forests (RF) have been used to produce continuous models whereas Classification And Regression Trees (CART) has only been used for a classification model. The best models generated from either PLS or RF produce significant models that can predict acids/zwitterions, bases and neutrals with approximate average fold errors of 3, 3 and 4, respectively, for an independent test set that covers oral drug-like property space. These models contain additional information on top of any influence arising from plasma protein binding on the rate of renal clearance. Classification And Regression Trees (CART) has been used to generate a classification tree leading to a simple set of Renal Clearance Rules (RCR) that can be applied to man. The rules are influenced by lipophilicity and ion class and can correctly predict 60% of an independent test set. These percentages increase to 71% and 79% for drugs with renal clearances of < 0.1 ml/min/kg and > 1 ml/min/kg, respectively. As far as the authors are aware these are the first set of models to appear in the literature that predict the rate of human renal clearance and can be used to manipulate molecular properties leading to new drugs that are less likely to fail due to renal clearance.     

Asymmetric information distances for automated taxonomy construction

A novel method for automatically constructing taxonomies for specific research domains is presented. The proposed methodology uses term co-occurrence frequencies as an indicator of the semantic closeness between terms. To support the automated creation of taxonomies or subject classifications we present a simple modification to the basic distance measure, and describe a set of procedures by which these measures may be converted into estimates of the desired taxonomy. To demonstrate the viability of this approach, a pilot study on renewable energy technologies is conducted, where the proposed method is used to construct a hierarchy of terms related to alternative energy. These techniques have many potential applications, but one activity in which we are particularly interested is the mapping and subsequent prediction of future developments in the technology and research.     

Accelerating geoscience and engineering system simulations on graphics hardware

Many complex natural systems studied in the geosciences are characterized by simple local-scale interactions that result in complex emergent behavior. Simulations of these systems, often implemented in parallel using standard central processing unit (CPU) clusters, may be better suited to parallel processing environments with large numbers of simple processors. Such an environment is found in graphics processing units (GPUs) on graphics cards.This paper discusses GPU implementations of three example applications from computational fluid dynamics, seismic wave propagation, and rock magnetism. These candidate applications involve important numerical modeling techniques, widely employed in physical system simulations, that are themselves examples of distinct computing classes identified as fundamental to scientific and engineering computing. The presented numerical methods (and respective computing classes they belong to) are: (1) a lattice-Boltzmann code for geofluid dynamics (structured grid class); (2) a spectral-finite-element code for seismic wave propagation simulations (sparse linear algebra class); and (3) a least-squares minimization code for interpreting magnetic force microscopy data (dense linear algebra class). Significant performance increases (between 10× and 30× in most cases) are seen in all three applications, demonstrating the power of GPU implementations for these types of simulations and, more generally, their associated computing classes.     

SimpleGrid toolkit: Enabling geosciences gateways to cyberinfrastructure

Cyberinfrastructure science and engineering gateways have become an important modality to connect science and engineering communities and cyberinfrastructure. The use of cyberinfrastructure through gateways is fundamental to the advancement of science and engineering. However, learning science gateway technologies and developing science gateways remain a significant challenge, given that science gateway technologies are still actively evolving and often include a number of sophisticated components. A geosciences gateway must be designed to accommodate legacy methods that geoscientists use in conventional computational tools. The research described in this paper establishes an open-source toolkit—SimpleGrid for learning and developing science gateways based on a service-oriented architecture using a component-based approach that allows flexible separation and integration of the components between geocomputation applications and cyberinfrastructure. The design and implementation of SimpleGrid is based on the National Science Foundation TeraGrid—a key element of the U.S. and world cyberinfrastructure. This paper illustrates our experience of using SimpleGrid and a spatial interpolation method in a tutorial to teach TeraGrid science gateways.     

Assessing tropical cyclone impacts using object-based moderate spatial resolution image analysis: a case study in Bangladesh

The environmental and societal impacts of tropical cyclones could be reduced using a range of management initiatives. Remote sensing can be a cost effective, accurate, and potential tool for mapping the multiple impacts caused by tropical cyclones using high-to-moderate spatial resolution (5–30 m) satellite imagery to provide data on the following essential parameters – evacuation, relief, and management of natural resources. This study developed and evaluated an approach for assessing the impacts of tropical cyclones through object-based image analysis and moderate spatial resolution imagery. Pre- and post-cyclone maps of artificial and natural features are required for assessing the overall impacts in the landscape that could be acquired by mapping specific land cover types. We used the object-based approach to map land-cover types in pre- and post-cyclone Satellite Pour l’Observation de la Terre (SPOT) 5 image data and the post-classification comparison technique to identify changes in the particular features in the landscape. Cyclone Sidr (2007) was used to test the applicability of this approach in Sarankhola Upazila in Bangladesh. The object-based approach provided accurate results for classifying features from pre- and post-cyclone satellite images with an overall accuracy of 95.43% and 93.27%, respectively. Mapped changes identified the extent, type, and form of cyclone induced impacts. Our results indicate that 63.15% of the study area was significantly affected by cyclone Sidr. The majority of mapped damage was found in vegetation, cropped lands, settlements, and infrastructure. The damage results were verified through the high spatial resolution satellite imagery, reports and pictures that were taken after the cyclone. The methods developed may be used in future to assess the multiple impacts caused by tropical cyclones in Bangladesh and other similar environments for the purposes of tropical cyclone disaster management.     

Racing to the precipice: a model of artificial intelligence development

This paper presents a simple model of an AI (artificial intelligence) arms race, where several development teams race to build the first AI. Under the assumption that the first AI will be very powerful and transformative, each team is incentivised to finish first—by skimping on safety precautions if need be. This paper presents the Nash equilibrium of this process, where each team takes the correct amount of safety precautions in the arms race. Having extra development teams and extra enmity between teams can increase the danger of an AI disaster, especially if risk-taking is more important than skill in developing the AI. Surprisingly, information also increases the risks: the more teams know about each others’ capabilities (and about their own), the more the danger increases. Should these results persist in more realistic models and analysis, it points the way to methods of increasing the chance of the safe development of AI.