“Green” Synthesis of Compounds with Biomedical Significance Facilitated by Water-Soluble Dendritic-Palladium Complexes

The Suzuki-Miyaura cross-coupling reaction (Suzuki reaction) is a highly efficient method of Carbon-Carbon bond formation, making it widely used in the synthesis of biaryl intermediates of pharmaceuticals. The coupling is conventionally performed at elevated temperatures and in organic solvents leading to adverse economic and environmental impacts. Previous studies in our group suggest that water soluble dendrimers, able to complex palladium, are viable Suzuki catalysts able to afford quantitative yields of the target compounds in water at close to ambient temperatures. They are, however, not ideal for catalyzing the reaction between hydrophobic reagents due to lack of contact with water-insoluble substrates. The goals of this study are to design and test water-soluble dendritic-palladium complexes containing a hydrophobic core, able to solubilize and selectively bind hydrophobic substances, in an attempt to improve the spatial arrangement of the catalyst and reagents in water. The structure of these novel “green” catalysts consists of calix[n]arene (n= 4,6,8) as the central core with water soluble poly(ester-ether) dendrons attached at the upper rim of the cycle (see figure below). The progress in the synthesis of these unique macromolecules by Williamson ether synthesis and Cu(I)-catalyzed alkyne-azide cycloaddition is reported. Our ability to reproducibly form the depicted compound with chemical and structural purity is confirmed by diverse analyses (NMR, MALDI-TOF, DLS, ICP and TEM). Upon completion, this work aims to achieve unprecedented yields for the Suzuki reaction in water and produce the first Suzuki catalyst to mimic enzymatic character by selectively incorporating reagents

A bibliography on the search for extraterrestrial intelligence

This report presents a uniform compilation of works dealing with the search for extraterrestrial intelligence. Entries are by first author, with cross-reference by topic index and by periodical index. This bibliography updates earlier bibliographies on this general topic while concentrating on research related to listening for signals from extraterrestrial intelligence

Bayesian multiscale deconvolution applied to gamma-ray spectroscopy

A common task in gamma-ray astronomy is to extract spectral information, such as model constraints and incident photon spectrum estimates, given the measured energy deposited in a detector and the detector response. This is the classic problem of spectral “deconvolution” or spectral inversion. The methods of forward folding (i.e., parameter fitting) and maximum entropy “deconvolution” (i.e., estimating independent input photon rates for each individual energy bin) have been used successfully for gamma-ray solar flares (e.g., Rank, 1997; Share and Murphy, 1995). These methods have worked well under certain conditions but there are situations were they don’t apply. These are: 1) when no reasonable model (e.g., fewer parameters than data bins) is yet known, for forward folding; 2) when one expects a mixture of broad and narrow features (e.g., solar flares), for the maximum entropy method; and 3) low count rates and low signal-to-noise, for both. Low count rates are a problem because these methods (as they have been implemented) assume Gaussian statistics but Poisson are applicable. Background subtraction techniques often lead to negative count rates. For Poisson data the Maximum Likelihood Estimator (MLE) with a Poisson likelihood is appropriate. Without a regularization term, trying to estimate the “true” individual input photon rates per bin can be an ill-posed problem, even without including both broad and narrow features in the spectrum (i.e., amultiscale approach). One way to implement this regularization is through the use of a suitable Bayesian prior. Nowak and Kolaczyk (1999) have developed a fast, robust, technique using a Bayesian multiscale framework that addresses these problems with added algorithmic advantages. We outline this new approach and demonstrate its use with time resolved solar flare gamma-ray spectroscopy

COMPTEL measurements of MeV gamma-ray burst spectra

We present results from the on-going spectral analysis of gamma-ray bursts measured by the COMPTEL instrument in its main Compton “Telescope” observing mode (0.75–30 MeV). Thus far, 18 bursts have been analyzed from three years (April 1991–April 1994) of observations. The time-averaged spectra of these events above 1 MeV are all consistent with a simple power law model with spectral index in the range 1.5–3.5. Exponential, thermal bremsstrahlung and thermal synchrotron models are statistically inconsistent with the burst sample, although they can adequately describe some of the individual burst spectra. We find good agreement between burst spectra measured simultaneously by BATSE, COMPTEL and EGRET, which typically show a spectral transition or “break” in the BATSE energy range around a few hundred keV followed by simple power law emission extending to hundreds of MeV. However, the temporal relation between MeV and GeV (e.g., as measured by EGRET) burst emission is still unclear. Measurement of rapid variability at MeV energies in the stronger bursts provides evidence that either the sources are nearby (within the Galaxy) or the gamma-ray emission is relativistically beamed

Energetic proton spectra in the 11 June 1991 solar flare

We have studied a subset of the 11 June 1991 solar flare γ-ray data that we believe arise from soft proton or ion spectra. Using data from the COMPTEL instrument on the Compton Observatory we discuss the gamma-ray intensities at 2.223 MeV, 4–7 MeV, and 8–30 MeV in terms of the parent proton spectrum responsible for the emission

Inter-rater reliability for movement pattern analysis (MPA): measuring patterning of behaviors versus discrete behavior counts as indicators of decision-making style

The unique yield of collecting observational data on human movement has received increasing attention in a number of domains, including the study of decision-making style. As such, interest has grown in the nuances of core methodological issues, including the best ways of assessing inter-rater reliability. In this paper we focus on one key topic – the distinction between establishing reliability for the patterning of behaviors as opposed to the computation of raw counts – and suggest that reliability for each be compared empirically rather than determined a priori. We illustrate by assessing inter-rater reliability for key outcome measures derived from movement pattern analysis (MPA), an observational methodology that records body movements as indicators of decision-making style with demonstrated predictive validity. While reliability ranged from moderate to good for raw counts of behaviors reflecting each of two Overall Factors generated within MPA (Assertion and Perspective), inter-rater reliability for patterning (proportional indicators of each factor) was significantly higher and excellent (ICC = 0.89). Furthermore, patterning, as compared to raw counts, provided better prediction of observable decision-making process assessed in the laboratory. These analyses support the utility of using an empirical approach to inform the consideration of measuring patterning versus discrete behavioral counts of behaviors when determining inter-rater reliability of observable behavior. They also speak to the substantial reliability that may be achieved via application of theoretically grounded observational systems such as MPA that reveal thinking and action motivations via visible movement patterns

Predicting individual differences in decision-making process from signature movement styles: an illustrative study of leaders

There has been a surge of interest in examining the utility of methods for capturing individual differences in decision-making style. We illustrate the potential offered by Movement Pattern Analysis (MPA), an observational methodology that has been used in business and by the US Department of Defense to record body movements that provide predictive insight into individual differences in decision-making motivations and actions. Twelve military officers participated in an intensive 2-h interview that permitted detailed and fine-grained observation and coding of signature movements by trained practitioners using MPA. Three months later, these subjects completed four hypothetical decision-making tasks in which the amount of information sought out before coming to a decision, as well as the time spent on the tasks, were under the partial control of the subject. A composite MPA indicator of how a person allocates decision-making actions and motivations to balance both Assertion (exertion of tangible movement effort on the environment to make something occur) and Perspective (through movements that support shaping in the body to perceive and create a suitable viewpoint for action) was highly correlated with the total number of information draws and total response time—individuals high on Assertion reached for less information and had faster response times than those high on Perspective. Discussion focuses on the utility of using movement-based observational measures to capture individual differences in decision-making style and the implications for application in applied settings geared toward investigations of experienced leaders and world statesmen where individuality rules the day