Spatial and behavioral ecology of human-elephant conflict, The

Includes bibliographical references.2022 Fall.To view the abstract, please see the full text of the document

Adding Small Differences can Increase Similarity and Choice

Similarity plays a critical role in many judgments and choices. Traditional models of similarity posit that increasing the number of differences between objects cannot increase judged similarity between them. In contrast to these previous models, the present research shows that introducing a small difference in an attribute that previously was identical across objects can increase perceived similarity between those objects. We propose an explanation based on the idea that small differences draw more attention than identical attributes do and that people’s perceptions of similarity involve averaging attributes that are salient. We provide evidence that introducing small differences between objects increases perceived similarity. We also show that an increase in similarity decreases the difficulty of choice and the likelihood that a choice will be deferred. </jats:p

An agent-based modeling template for a cohort of veterans with diabetic retinopathy

BACKGROUNDAgent-based models are valuable for examining systems where large numbers of discrete individuals interact with each other, or with some environment. Diabetic Veterans seeking eye care at a Veterans Administration hospital represent one such cohort.OBJECTIVEThe objective of this study was to develop an agent-based template to be used as a model for a patient with diabetic retinopathy (DR). This template may be replicated arbitrarily many times in order to generate a large cohort which is representative of a real-world population, upon which in-silico experimentation may be conducted.METHODSAgent-based template development was performed in java-based computer simulation suite AnyLogic Professional 6.6. The model was informed by medical data abstracted from 535 patient records representing a retrospective cohort of current patients of the VA St. Louis Healthcare System Eye clinic. Logistic regression was performed to determine the predictors associated with advancing stages of DR. Predicted probabilities obtained from logistic regression were used to generate the stage of DR in the simulated cohort.RESULTSThe simulated cohort of DR patients exhibited no significant deviation from the test population of real-world patients in proportion of stage of DR, duration of diabetes mellitus (DM), or the other abstracted predictors. Simulated patients after 10 years were significantly more likely to exhibit proliferative DR (PCONCLUSIONSAgent-based modeling is an emerging platform, capable of simulating large cohorts of individuals based on manageable data abstraction efforts. The modeling method described may be useful in simulating many different conditions where course of disease is described in categorical stages

A MultiWavelength Study of the Symbiotic Mira HM Sge with SOFIA and HST

We have targeted the dusty symbiotic mira system HM Sge with four instruments from the IR to the UV. We have used these observations along with archival observations to study how the system has been evolving after its 1975 nova-like outburst. We have detected ro-vibrational water emission in a symbiotic system for the first time using new EXES high spectral resolution infrared spectroscopy. The features, detected in emission, have velocities consistent with the systemic velocity but do not show any clear evidence of high velocity outflows. Mid-infrared photometry and grism spectroscopy show that the oxygen-rich Asymptotic Giant Branch (AGB) dust and dust output has shown little to no change over the past 39 years. In the optical/UV, we detect three main [NII] nebular features that were detected 22 years ago. Two of these features show a small amount of movement corresponding to average outflows speeds of 38 kms and 78 kms since they were previously observed; some previously detected [NII] features are no longer visible. New UV spectroscopy has shown that the nebular environment continues to steadily relax after the system's 1975 outburst. The data suggest however, that the hot component has increased in temperature from 200,000 K in 1989 to now greater than 250,000 K. Our new and archival observations suggest that the evolution of the system after its outburst is swift with little to no major changes after a period of a couple years.Comment: Accepted in Ap

A Knock-In Mouse Model for the R120G Mutation of αB-Crystallin Recapitulates Human Hereditary Myopathy and Cataracts

An autosomal dominant missense mutation in αB-crystallin (αB-R120G) causes cataracts and desmin-related myopathy, but the underlying mechanisms are unknown. Here, we report the development of an αB-R120G crystallin knock-in mouse model of these disorders. Knock-in αB-R120G mice were generated and analyzed with slit lamp imaging, gel permeation chromatography, immunofluorescence, immunoprecipitation, histology, and muscle strength assays. Wild-type, age-matched mice were used as controls for all studies. Both heterozygous and homozygous mutant mice developed myopathy. Moreover, homozygous mutant mice were significantly weaker than wild-type control littermates at 6 months of age. Cataract severity increased with age and mutant gene dosage. The total mass, precipitation, and interaction with the intermediate filament protein vimentin, as well as light scattering of αB-crystallin, also increased in mutant lenses. In skeletal muscle, αB-R120G co-aggregated with desmin, became detergent insoluble, and was ubiquitinated in heterozygous and homozygous mutant mice. These data suggest that the cataract and myopathy pathologies in αB-R120G knock-in mice share common mechanisms, including increased insolubility of αB-crystallin and co-aggregation of αB-crystallin with intermediate filament proteins. These knock-in αB-R120G mice are a valuable model of the developmental and molecular biological mechanisms that underlie the pathophysiology of human hereditary cataracts and myopathy

Nanotechnology for Cell–Substrate Interactions

In the pursuit to understand the interaction between cells and their underlying substrates, the life sciences are beginning to incorporate micro- and nanotechnology-based tools to probe and measure cells. The development of these tools portends endless possibilities for new insights into the fundamental relationships between cells and their surrounding microenvironment that underlie the physiology of human tissue. Here, we review techniques and tools that have been used to study how a cell responds to the physical factors in its environment. We also discuss unanswered questions that could be addressed by these approaches to better elucidate the molecular processes and mechanical forces that dominate the interactions between cells and their physical scaffolds

Zero noise extrapolation on logical qubits by scaling the error correction code distance

In this work, we migrate the quantum error mitigation technique of Zero-Noise Extrapolation (ZNE) to fault-tolerant quantum computing. We employ ZNE on \emph{logically encoded} qubits rather than \emph{physical} qubits. This approach will be useful in a regime where quantum error correction (QEC) is implementable but the number of qubits available for QEC is limited. Apart from illustrating the utility of a traditional ZNE approach (circuit-level unitary folding) for the QEC regime, we propose a novel noise scaling ZNE method specifically tailored to QEC: \emph{distance scaled ZNE (DS-ZNE)}. DS-ZNE scales the distance of the error correction code, and thereby the resulting logical error rate, and utilizes this code distance as the scaling `knob' for ZNE. Logical qubit error rates are scaled until the maximum achievable code distance for a fixed number of physical qubits, and lower error rates (i.e., effectively higher code distances) are achieved via extrapolation techniques migrated from traditional ZNE. Furthermore, to maximize physical qubit utilization over the ZNE experiments, logical executions at code distances lower than the maximum allowed by the physical qubits on the quantum device are parallelized to optimize device utilization. We validate our proposal with numerical simulation and confirm that ZNE lowers the logical error rates and increases the effective code distance beyond the physical capability of the quantum device. For instance, at a physical code distance of 11, the DS-ZNE effective code distance is 17, and at a physical code distance of 13, the DS-ZNE effective code distance is 21. When the proposed technique is compared against unitary folding ZNE under the constraint of a fixed number of executions of the quantum device, DS-ZNE outperforms unitary folding by up to 92\% in terms of the post-ZNE logical error rate.Comment: 8 pages, 5 figure