Perceptual bias, more than age, impacts on eye movements during face processing

Consistent with the right hemispheric dominance for face processing, a left perceptual bias (LPB) is typically demonstrated by younger adults viewing faces and a left eye movement bias has also been revealed. Hemispheric asymmetry is predicted to reduce with age and older adults have demonstrated a weaker LPB, particularly when viewing time is restricted. What is currently unclear is whether age also weakens the left eye movement bias. Additionally, a right perceptual bias (RPB) for facial judgments has less frequently been demonstrated, but whether this is accompanied by a right eye movement bias has not been investigated. To address these issues older and younger adults’ eye movements and gender judgments of chimeric faces were recorded in two time conditions. Age did not significantly weaken the LPB or eye movement bias; both groups looked initially to the left side of the face and made more fixations when the gender judgment was based on the left side. A positive association was found between LPB and initial saccades in the freeview condition and with all eye movements (initial saccades, number and duration of fixations) when time was restricted. The accompanying eye movement bias revealed by LPB participants contrasted with RPB participants who demonstrated no eye movement bias in either time condition. Consequently, increased age is not clearly associated with weakened perceptual and eye movement biases. Instead an eye movement bias accompanies an LPB (particularly under restricted viewing time conditions) but not an RPB

The SISO CSPI PDG standard for commercial off-the-shelf simulation package interoperability reference models

For many years discrete-event simulation has been used to analyze production and logistics problems in manufactur-ing and defense. Commercial-off-the-shelf Simulation Packages (CSPs), visual interactive modelling environ-ments such as Arena, Anylogic, Flexsim, Simul8, Witness, etc., support the development, experimentation and visua-lization of simulation models. There have been various attempts to create distributed simulations with these CSPs and their tools, some with the High Level Architecture (HLA). These are complex and it is quite difficult to assess how a set of models/CSP are actually interoperating. As the first in a series of standards aimed at standardizing how the HLA is used to support CSP distributed simula-tions, the Simulation Interoperability Standards Organiza-tion’s (SISO) CSP Interoperability Product Development Group (CSPI PDG) has developed and standardized a set of Interoperability Reference Models (IRM) that are in-tended to clearly identify the interoperability capabilities of CSP distributed simulations

The Wide Integral Field Infrared Spectrograph: Commissioning Results and On-sky Performance

We have recently commissioned a novel infrared ($0.9-1.7$ $\mu$m) integral field spectrograph (IFS) called the Wide Integral Field Infrared Spectrograph (WIFIS). WIFIS is a unique instrument that offers a very large field-of-view (50$^{\prime\prime}$ x 20$^{\prime\prime}$) on the 2.3-meter Bok telescope at Kitt Peak, USA for seeing-limited observations at moderate spectral resolving power. The measured spatial sampling scale is $\sim1\times1^{\prime\prime}$ and its spectral resolving power is $R\sim2,500$ and $3,000$ in the $zJ$ ($0.9-1.35$ $\mu$m) and $H_{short}$ ($1.5-1.7$ $\mu$m) modes, respectively. WIFIS's corresponding etendue is larger than existing near-infrared (NIR) IFSes, which are mostly designed to work with adaptive optics systems and therefore have very narrow fields. For this reason, this instrument is specifically suited for studying very extended objects in the near-infrared such as supernovae remnants, galactic star forming regions, and nearby galaxies, which are not easily accessible by other NIR IFSes. This enables scientific programs that were not originally possible, such as detailed surveys of a large number of nearby galaxies or a full accounting of nucleosynthetic yields of Milky Way supernova remnants. WIFIS is also designed to be easily adaptable to be used with larger telescopes. In this paper, we report on the overall performance characteristics of the instrument, which were measured during our commissioning runs in the second half of 2017. We present measurements of spectral resolving power, image quality, instrumental background, and overall efficiency and sensitivity of WIFIS and compare them with our design expectations. Finally, we present a few example observations that demonstrate WIFIS's full capability to carry out infrared imaging spectroscopy of extended objects, which is enabled by our custom data reduction pipeline.Comment: Published in the Proceedings of SPIE Astronomical Telescopes and Instrumentation 2018. 17 pages, 13 figure

Development, Validation, and Limits of Freezing of Gait Detection Using a Single Waist-Worn Device

Objective: Freezing of Gait (FOG) often described as the sensation of “the feet being glued to the ground” is prevalent in people with Parkinson's disease (PD) and severely disturbs mobility. In addition to tracking disease progression, precise detection of the exact boundaries for each FOG episode may enable new technologies capable of “breaking” FOG in real time. This study investigates the limits of sensitivity and performance for automatic device-based FOG detection. Methods: Eight machine-learning classifiers (including Neural Networks, Ensemble & Support Vector Machine) were developed using (i) accelerometer and (ii) accelerometer and gyroscope data from a waist-worn device. While wearing the device, 107 people with PD completed a walking and mobility task designed to elicit FOG. Two clinicians independently annotated the precise FOG episodes using synchronized video according to international guidelines, which were incorporated into a flowchart algorithm developed for this study. Device-detected FOG episodes were compared to the annotated FOG episodes using 10-fold cross-validation to determine accuracy and with Interclass Correlation Coefficients (ICC) to assess level of agreement. Results: Development used 50,962 windows of data representing over 10 hours of data and annotated activities. Very strong agreement between clinicians for precise FOG episodes was observed (90% sensitivity, 92% specificity and ICC 1,1 = 0.97 for total FOG duration). Device-based performance varied by method, complexity and cost matrix. The Neural Network that used only 67 accelerometer features provided a good balance between high sensitivity to FOG (89% sensitivity, 81% specificity and ICC 1,1 = 0.83) and solution stability (validation loss ≤ 5%). Conclusion: The waist-worn device consistently reported accurate detection of precise FOG episodes and compared well to more complex systems. The superior agreement between clinicians indicates there is room to improve future device-based FOG detection by using larger and more varied data sets. Significance: This study has clinical implications with regard to improving PD care by reducing reliance on clinical FOG assessments and time-consuming visual inspection. It shows high sensitivity to automatically detect FOG is possible

Development, Validation, and Limits of Freezing of Gait Detection Using a Single Waist-Worn Device

Objective: Freezing of Gait (FOG) often described as the sensation of “the feet being glued to the ground” is prevalent in people with Parkinson's disease (PD) and severely disturbs mobility. In addition to tracking disease progression, precise detection of the exact boundaries for each FOG episode may enable new technologies capable of “breaking” FOG in real time. This study investigates the limits of sensitivity and performance for automatic device-based FOG detection. Methods: Eight machine-learning classifiers (including Neural Networks, Ensemble & Support Vector Machine) were developed using (i) accelerometer and (ii) accelerometer and gyroscope data from a waist-worn device. While wearing the device, 107 people with PD completed a walking and mobility task designed to elicit FOG. Two clinicians independently annotated the precise FOG episodes using synchronized video according to international guidelines, which were incorporated into a flowchart algorithm developed for this study. Device-detected FOG episodes were compared to the annotated FOG episodes using 10-fold cross-validation to determine accuracy and with Interclass Correlation Coefficients (ICC) to assess level of agreement. Results: Development used 50,962 windows of data representing over 10 hours of data and annotated activities. Very strong agreement between clinicians for precise FOG episodes was observed (90% sensitivity, 92% specificity and ICC 1,1 = 0.97 for total FOG duration). Device-based performance varied by method, complexity and cost matrix. The Neural Network that used only 67 accelerometer features provided a good balance between high sensitivity to FOG (89% sensitivity, 81% specificity and ICC 1,1 = 0.83) and solution stability (validation loss ≤ 5%). Conclusion: The waist-worn device consistently reported accurate detection of precise FOG episodes and compared well to more complex systems. The superior agreement between clinicians indicates there is room to improve future device-based FOG detection by using larger and more varied data sets. Significance: This study has clinical implications with regard to improving PD care by reducing reliance on clinical FOG assessments and time-consuming visual inspection. It shows high sensitivity to automatically detect FOG is possible

Stratospheric emissions effects database development

This report describes the development of a stratospheric emissions effects database (SEED) of aircraft fuel burn and emissions from projected Year 2015 subsonic aircraft fleets and from projected fleets of high-speed civil transports (HSCT's). This report also describes the development of a similar database of emissions from Year 1990 scheduled commercial passenger airline and air cargo traffic. The objective of this work was to initiate, develop, and maintain an engineering database for use by atmospheric scientists conducting the Atmospheric Effects of Stratospheric Aircraft (AESA) modeling studies. Fuel burn and emissions of nitrogen oxides (NO(x) as NO2), carbon monoxide, and hydrocarbons (as CH4) have been calculated on a 1-degree latitude x 1-degree longitude x 1-kilometer altitude grid and delivered to NASA as electronic files. This report describes the assumptions and methodology for the calculations and summarizes the results of these calculations

Panning for gold: unearthing reliable variables for electronic medical data research

Abstract of a poster presentation at the 2015 PHC Research Conference, Adelaide, 29-31 July, 2015

The G-protein-coupled receptor CLR is upregulated in an autocrine loop with adrenomedullin in clear cell renal cell carcinoma and associated with poor prognosis

Purpose: The G-protein-coupled receptor (GPCR) calcitonin receptor-like receptor (CLR) and its ligand peptide adrenomedullin (encoded by ADM gene) are implicated in tumor angiogenesis in mouse models but poorly defined in human cancers. We therefore investigated the diagnostic/prognostic use for CLR in human tumor types that may rely on adrenomedullin signaling and in clear cell renal cell carcinoma (RCC), a highly vascular tumor, in particular. Experimental Design: In silico gene expression mRNA profiling microarray study (n = 168 tumors) and cancer profiling cDNA array hybridization (n=241 pairs of patient-matched tumor/normal tissue samples) were carried out to analyze ADM mRNA expression in 13 tumor types. Immunohistochemistry on tissue microarrays containing patient-matched renal tumor/normal tissues (n = 87 pairs) was conducted to study CLR expression and its association with clinicopathologic parameters and disease outcome. Results: ADM expression was significantly upregulated only in RCC and endometrial adenocarcinoma compared with normal tissue counterparts (P < 0.01). CLR was localized in tumor cells and vessels in RCC and upregulated as compared with patient-matched normal control kidney (P < 0.001). Higher CLR expression was found in advanced stages (P < 0.05), correlated with high tumor grade (P < 0.01) and conferred shorter overall survival (P < 0.01). Conclusions: In human tissues ADM expression is upregulated in cancer type-specific manner, implicating potential role for adrenomedullin signaling in particular in RCC, where CLR localization suggests autocrine/paracrine mode for adrenomedullin action within the tumor microenvironment. Our findings reveal previously unrecognized CLR upregulation in an autocrine loop with adrenomedullin in RCCwith potential application for this GPCR as a target for future functional studies and drug development. © 2013 AACR

Singing fin whale swimming behavior in the Central North Pacific

This research was supported by Commander, U.S. Pacific Fleet (Code N465JR, Award Number N0007020WR0EP8F), the Office of Naval Research (Code 322, Award Number N0001421WX00156), and tool development necessary for this analysis was supported by the U.S. Navy's Living Marine Resources Program (Award Number N0002520WR0141R).Male fin whales sing using 20 Hz pulses produced in regular patterns of inter-note intervals, but little is known about fin whale swimming behavior while they are singing. Even less is known about fin whales in Hawaiian waters because they have rarely been sighted during surveys and passive acoustic monitoring has been limited to sparse hydrophone systems that do not have localization capabilities. We hypothesized that fin whale kinematics may be related to their singing behavior, or external variables such as time and sea state. To investigate this hypothesis, we analyzed 115 tracks containing 50,034 unique notes generated from passive acoustic recordings on an array of 14 hydrophones from 2011 to 2017 at the U.S. Navy Pacific Missile Range Facility off Kauai, Hawaii. Fin whales swam at an average speed of 1.1 m/s over relatively direct paths. We incorporated the whales' speed and turning angle into hidden Markov models to identify different behavioral states based on the whales' movements. We found that fin whale kinematic behavioral state was related to the vocalization rate (also known as cue rate) and time of day. When cue rate was higher, fin whales were more likely to swim slower and turn more than when cue rate was lower. During the night, fin whales were also more likely to swim slower and turn more than during the day. In addition, we examined whether the presence of singing fin whales was related to time and sea state using generalized additive models. Fin whale track presence was affected by day of the year and song season, and possibly also wind speed and wave height. Although the track kinematics from the fin whale tracks presented here are limited to a subset of whales that are acoustically active, they provide some of the only detailed movements of fin whales in the region and can be compared against fin whale swim speeds in other regions. Understanding how fin whale swimming behavior varies based on their vocalization patterns, time, and environmental factors will help us to contextualize potential changes in whale behavior during Navy training and testing on the range.Publisher PDFPeer reviewe