108 research outputs found
Memory and Decision Processes on Lineup Identifications Following Mugshot Exposure
The present study manipulated mugshot search task instructions to reveal when witnesses make commitment or familiarity based lineup errors. Additionally we examined the memory and decision making processes underlying these lineup choices using a computational model. In order to examine these processes, an extension of Clark's (2003) WITNESS model was developed - WITNESS-ME (ME for Mugshot Exposure). In support of previous research, we found a robust commitment effect. Commitment is due to strong encoding of the committed foil and the differentiation of that choice to the other lineup members. When participants were required to choose several foils that resembled the perpetrator from the mugbook (rather than searching for a single perpetrator), no differences in correct identification between the mugbook and no-mugbook control were found. We also found evidence for errors to due to conscious inference and source monitoring in all mugbook conditions. Modeling these data supported the hypothesis that witnesses are influenced by the number of plausible choices in the lineup and subsequently may adopt different strategies because of this. Theoretical and practical implications are discussed
A computational analysis of Turkish makam music based on a probabilistic characterization of segmented phrases
This study targets automatic analysis of Turkish makam music pieces on the phrase level. While makam is most simply defined as an organization of melodic phrases, there has been very little effort to computationally study melodic structure in makam music pieces. In this work, we propose an automatic analysis algorithm that takes as input symbolic data in the form of machine-readable scores that are segmented into phrases. Using a measure of makam membership for phrases, our method outputs for each phrase the most likely makam the phrase comes from. The proposed makam membership definition is based on Bayesian classification and the algorithm is specifically designed to process the data with overlapping classes. The proposed analysis system is trained and tested on a large data set of phrases obtained by transferring phrase boundaries manually written by experts of makam music on printed scores, to machine-readable data. For the task of classifying all phrases, or only the beginning phrases to come from the main makam of the piece, the corresponding F-measures are.52 and.60 respectively.Scientific and Technological Research Council of Turkey, TUBITAK (112E162
A Chemical Genomics Approach to Drug Reprofiling in Oncology: Antipsychotic Drug Risperidone as a Potential Adenocarcinoma Treatment
Drug reprofiling is emerging as an effective paradigm for discovery of cancer treatments. Herein, an antipsychotic drug is immobilised using the Magic Tag® chemical genomics tool and screened against a T7 bacteriophage displayed library of polypeptides from Drosophila melanogaster, as a whole genome model, to uncover an interaction with a section of 17-β-HSD10, a proposed prostate cancer target. A computational study and enzyme inhibition assay with full length human 17-β-HSD10 identifies risperidone as a drug reprofiling candidate. When formulated with rumenic acid, risperidone slows proliferation of PC3 prostate cancer cells in vitro and retards PC3 prostate cancer tumour growth in vivo in xenografts in mice, presenting an opportunity to reprofile risperidone as a cancer treatment
Towards the development of novel Trypanosoma brucei RNA editing ligase 1 inhibitors
Abstract Background Trypanosoma brucei (T. brucei) is an infectious agent for which drug development has been largely neglected. We here use a recently developed computer program called AutoGrow to add interacting molecular fragments to S5, a known inhibitor of the validated T. brucei drug target RNA editing ligase 1, in order to improve its predicted binding affinity. Results The proposed binding modes of the resulting compounds mimic that of ATP, the native substrate, and provide insights into novel protein-ligand interactions that may be exploited in future drug-discovery projects. Conclusions We are hopeful that these new predicted inhibitors will aid medicinal chemists in developing novel therapeutics to fight human African trypanosomiasis
Moltemplate: A Tool for Coarse-Grained Modeling of Complex Biological Matter and Soft Condensed Matter Physics
Coarse-grained models have long been considered indispensable tools in the investigation of biomolecular dynamics and assembly. However, the process of simulating such models is arduous because unconventional force fields and particle attributes are often needed, and some systems are not in thermal equilibrium. Although modern molecular dynamics programs are highly adaptable, software designed for preparing all-atom simulations typically makes restrictive assumptions about the nature of the particles and the forces acting on them. Consequently, the use of coarse-grained models has remained challenging. Moltemplate is a file format for storing coarse-grained molecular models and the forces that act on them, as well as a program that converts moltemplate files into input files for LAMMPS, a popular molecular dynamics engine. Moltemplate has broad scope and an emphasis on generality. It accommodates new kinds of forces as they are developed for LAMMPS, making moltemplate a popular tool with thousands of users in computational chemistry, materials science, and structural biology. To demonstrate its wide functionality, we provide examples of using moltemplate to prepare simulations of fluids using many-body forces, coarse-grained organic semiconductors, and the motor-driven supercoiling and condensation of an entire bacterial chromosome
Performance of the Gemini Planet Imager Non-Redundant Mask and spectroscopy of two close-separation binaries HR 2690 and HD 142527
The Gemini Planet Imager (GPI) contains a 10-hole non-redundant mask (NRM),
enabling interferometric resolution in complement to its coronagraphic
capabilities. The NRM operates both in spectroscopic (integral field
spectrograph, henceforth IFS) and polarimetric configurations. NRM observations
were taken between 2013 and 2016 to characterize its performance. Most
observations were taken in spectroscopic mode with the goal of obtaining
precise astrometry and spectroscopy of faint companions to bright stars. We
find a clear correlation between residual wavefront error measured by the AO
system and the contrast sensitivity by comparing phase errors in observations
of the same source, taken on different dates. We find a typical 5-
contrast sensitivity of at . We explore the
accuracy of spectral extraction of secondary components of binary systems by
recovering the signal from a simulated source injected into several datasets.
We outline data reduction procedures unique to GPI's IFS and describe a newly
public data pipeline used for the presented analyses. We demonstrate recovery
of astrometry and spectroscopy of two known companions to HR 2690 and HD
142527. NRM+polarimetry observations achieve differential visibility precision
of in the best case. We discuss its limitations on
Gemini-S/GPI for resolving inner regions of protoplanetary disks and prospects
for future upgrades. We summarize lessons learned in observing with NRM in
spectroscopic and polarimetric modes.Comment: Accepted to AJ, 22 pages, 14 figure
GPI spectra of HR 8799 c, d, and e from 1.5 to 2.4m with KLIP Forward Modeling
We explore KLIP forward modeling spectral extraction on Gemini Planet Imager
coronagraphic data of HR 8799, using PyKLIP and show algorithm stability with
varying KLIP parameters. We report new and re-reduced spectrophotometry of HR
8799 c, d, and e in H & K bands. We discuss a strategy for choosing optimal
KLIP PSF subtraction parameters by injecting simulated sources and recovering
them over a range of parameters. The K1/K2 spectra for HR 8799 c and d are
similar to previously published results from the same dataset. We also present
a K band spectrum of HR 8799 e for the first time and show that our H-band
spectra agree well with previously published spectra from the VLT/SPHERE
instrument. We show that HR 8799 c and d show significant differences in their
H & K spectra, but do not find any conclusive differences between d and e or c
and e, likely due to large error bars in the recovered spectrum of e. Compared
to M, L, and T-type field brown dwarfs, all three planets are most consistent
with mid and late L spectral types. All objects are consistent with low gravity
but a lack of standard spectra for low gravity limit the ability to fit the
best spectral type. We discuss how dedicated modeling efforts can better fit HR
8799 planets' near-IR flux and discuss how differences between the properties
of these planets can be further explored.Comment: Accepted to AJ, 25 pages, 16 Figure
Multilevel Parallelization of AutoDock 4.2
<p>Abstract</p> <p>Background</p> <p>Virtual (computational) screening is an increasingly important tool for drug discovery. AutoDock is a popular open-source application for performing molecular docking, the prediction of ligand-receptor interactions. AutoDock is a serial application, though several previous efforts have parallelized various aspects of the program. In this paper, we report on a multi-level parallelization of AutoDock 4.2 (mpAD4).</p> <p>Results</p> <p>Using MPI and OpenMP, AutoDock 4.2 was parallelized for use on MPI-enabled systems and to multithread the execution of individual docking jobs. In addition, code was implemented to reduce input/output (I/O) traffic by reusing grid maps at each node from docking to docking. Performance of mpAD4 was examined on two multiprocessor computers.</p> <p>Conclusions</p> <p>Using MPI with OpenMP multithreading, mpAD4 scales with near linearity on the multiprocessor systems tested. In situations where I/O is limiting, reuse of grid maps reduces both system I/O and overall screening time. Multithreading of AutoDock's Lamarkian Genetic Algorithm with OpenMP increases the speed of execution of individual docking jobs, and when combined with MPI parallelization can significantly reduce the execution time of virtual screens. This work is significant in that mpAD4 speeds the execution of certain molecular docking workloads and allows the user to optimize the degree of system-level (MPI) and node-level (OpenMP) parallelization to best fit both workloads and computational resources.</p
Performance of the Gemini Planet Imager Non-Redundant Mask and Spectroscopy of Two Close-Separation Binaries: HR 2690 and HD 142527
The Gemini Planet Imager (GPI) contains a 10-hole non-redundant mask (NRM), enabling interferometric resolution in complement to its coronagraphic capabilities. The NRM operates both in spectroscopic (integral field spectrograph, henceforth IFS) and polarimetric configurations. NRM observations were taken between 2013 and 2016 to characterize its performance. Most observations were taken in spectroscopic mode, with the goal of obtaining precise astrometry and spectroscopy of faint companions to bright stars. We find a clear correlation between residual wavefront error measured by the adaptive optic system and the contrast sensitivity by comparing phase errors in observations of the same source, taken on different dates. We find a typical 5σ contrast sensitivity of (2-3) × 10-3 at ∼λ/D. We explore the accuracy of spectral extraction of secondary components of binary systems by recovering the signal from a simulated source injected into several data sets. We outline data reduction procedures unique to GPI\u27s IFS and describe a newly public data pipeline used for the presented analyses. We demonstrate recovery of astrometry and spectroscopy of two known companions to HR 2690 and HD 142527. NRM+polarimetry observations achieve differential visibility precision of σ ∼ 0.4% in the best case. We discuss its limitations on Gemini-S/GPI for resolving inner regions of protoplanetary disks and prospects for future upgrades. We summarize lessons learned in observing with NRM in spectroscopic and polarimetric modes
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