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At least 55 records · Page 3

Atmospheric pressure loading effects on Global Positioning System coordinate determinations

Earth deformation signals caused by atmospheric pressure loading are detected in vertical position estimates at Global Positioning System (GPS) stations. Surface displacements due to changes in atmospheric pressure account for up to 24% of the total variance in the GPS height estimates. The detected loading signals are larger at higher latitudes where pressure variations are greatest; the largest effect is observed at Fairbanks, Alaska (latitude 65 deg), with a signal root mean square (RMS) of 5 mm. Out of 19 continuously operating GPS sites (with a mean of 281 daily solutions per site), 18 show a positive correlation between the GPS vertical estimates and the modeled loading displacements. Accounting for loading reduces the variance of the vertical station positions on 12 of the 19 sites investigated. Removing the modeled pressure loading from GPS determinations of baseline length for baselines longer than 6000 km reduces the variance on 73 of the 117 baselines investigated. The slight increase in variance for some of the sites and baselines is consistent with expected statistical fluctuations. The results from most stations are consistent with approximately 65% of the modeled pressure load being found in the GPS vertical position measurements. Removing an annual signal from both the measured heights and the modeled load time series leaves this value unchanged. The source of the remaining discrepancy between the modeled and observed loading signal may be the result of (1) anisotropic effects in the Earth's loading response, (2) errors in GPS estimates of tropospheric delay, (3) errors in the surface pressure data, or (4) annual signals in the time series of loading and station heights. In addition, we find that using site dependent coefficients, determined by fitting local pressure to the modeled radial displacements, reduces the variance of the measured station heights as well as or better than using the global convolution sum.

Vandam, Tonie M.↗

Interannual and Decadal Variability of Summer Rainfall over South America

Using the CPC (Climate Prediction Center) Merged Analysis of Precipitation product along with the Goddard Earth Observing System reanalysis and the Climate Analysis Center sea surface temperature (SST) data, we conduct a diagnostic study of the interannual and decadal scale variability of summer rainfall over South America. Results show three leading modes of rainfall variation identified with interannual, decadal, and long-term trend variability. Together, these modes explain more than half the total variance. The first mode is highly correlated with El Nino/southern oscillation (ENSO), showing severe drought over Northeast Brazil and copious rainfall over the Ecuador coast and the area of Uruguay-Southern Brazil in El Nino years. This pattern is attributed to the large scale zonal shift of the Walker circulation and local Hadley cell anomaly induced by positive (negative) SST anomaly over the eastern (western) equatorial Pacific. In El Nino years, two convective belts indicated by upper tropospheric velocity potential trough and mid-tropospheric rising motion, which are somewhat symmetric about the equator, extend toward the northeast and the southeast into the tropical North and South Atlantic respectively. Sandwiched between the ascent is a region of descending motion over Northeast Brazil. The southern branch of the anomalous Hadley cell is dynamically linked to the increase of rainfall over Uruguay-Southern Brazil. The regional response of anomalous circulation shows a stronger South American summer monsoon and an enhanced (weakened) subtropical high over the South Atlantic (South Pacific) Ocean. The decadal variation displays a meridional shift of the Intertropical Convergence Zone (ITCZ), which is tie to the anomalous cross-equatorial SST gradient over the Atlantic and the eastern Pacific. In conjunction with this mode is a large scale mass swing between the polar regions and midlatitudes in both hemispheres. Over the South Atlantic and the South Pacific, the changes of the strength of the subtropical high and the associated surface wind are dynamically consistent with the distribution of local SST anomalies, suggesting the importance of the atmospheric forcing in the decadal time scale. The decadal mode also presents a weak summer monsoon in its positive phase, which reduces the moisture supply from the equatorial Atlantic and the Amazon Basin and results in negative rainfall anomalies over the central Andes and Gran Chaco. The long-term trend shows decrease of rainfall from the northwest coast to the southeast subtropical region and a southward shift of Atlantic ITCZ that leads to increased rainfall over northern and eastern Brazil. Our result shows a close link of this mode to the observed SST warming trend over the subtropical South Atlantic and a remote connection to the interdecadal SST variation over the extratropical North Atlantic found in previous studies.

Zhou, Jiayu↗

Maximum Likelihood Factor Analysis of the Effects of Chronic Centrifugation on the Structural Development of the Musculoskeletal System of the Rat

At the age of 30 days female Sprague-Dawley rats were placed on a 3.66 m radius centrifuge and subsequently exposed almost continuously for 810 days to either 2.76 or 4.15 G. An age-matched control group of rats was raised near the centrifuge facility at earth gravity. Three further control groups of rats were obtained from the animal colony and sacrificed at the age of 34, 72 and 102 days. A total of 16 variables were simultaneously factor analyzed by maximum-likelihood extraction routine and the factor loadings presented after-rotation to simple structure by a varimax rotation routine. The variables include the G-load, age, body mass, femoral length and cross-sectional area, inner and outer radii, density and strength at the mid-length of the femur, dry weight of gluteus medius, semimenbranosus and triceps surae muscles. Factor analyses on A) all controls, B) all controls and the 2.76 G group, and C) all controls and centrifuged animals, produced highly similar loading structures of three common factors which accounted for 74%, 68% and 68%. respectively, of the total variance. The 3 factors were interpreted as: 1. An age and size factor which stimulates the growth in length and diameter and increases the density and strength of the femur. This factor is positively correlated with G-load but is also active in the control animals living at earth gravity. 2. A growth inhibition factor which acts on body size, femoral length and on both the outer and inner radius at mid-length of the femur. This factor is intensified by centrifugation.

Amtmann, E.↗

An Analysis of Simulated and Observed Global Mean Near-Surface Air Temperature Anomalies from 1979 to 1999: Trends and Attribution of Causes

The 1979 - 1999 response of the climate system to variations in solar spectral irradiance is estimated by comparing the global averaged surface temperature anomalies simulated by a 2D (two dimensional) energy balance climate model to observed temperature anomalies. We perform a multiple regression of southern oscillation index and the individual model responses to solar irradiance variations, stratospheric and tropospheric aerosol loading, stratospheric ozone trends, and greenhouse gases onto each of five near-surface temperature anomaly data sets. We estimate the observed difference in global mean near surface air temperature attributable to the solar irradiance difference between solar maximum and solar minimum to be between 0.06 and 0.11 K, and that 1.1 - 3.8% of the total variance in monthly mean near-surface air temperature data is attributable to nations in solar spectral irradiance. For the five temperature data sets used in our analysis, the trends in raw monthly mean temperature anomaly data have a large range, spanning a factor of 3 from 0.06 to 0.17 K/decade. However. our analysis suggests that trends in monthly temperature anomalies attributable to the combination of greenhouse gas, stratospheric ozone, and tropospheric sulfate aerosol variations are much more consistent among data sets, ranging from 0.16 to 0.24 K/decade. Our model results suggest that roughly half of the warming from greenhouse gases is cancelled by the cooling from changes in stratospheric ozone. Tropospheric sulfate aerosol loading in the present day atmospheric contributes significantly to the net radiative forcing of the present day climate system. However, because the change in magnitude and latitudinal distribution of tropospheric sulfate aerosol has been small over the past 20 years, the change in the direct radiative forcing attributable to changes in aerosol loading over this time is also small.

MacKay, R. M.↗

Validity of VO(2 max) in predicting blood volume: implications for the effect of fitness on aging

A multiple regression model was constructed to investigate the premise that blood volume (BV) could be predicted using several anthropometric variables, age, and maximal oxygen uptake (VO(2 max)). To test this hypothesis, age, calculated body surface area (height/weight composite), percent body fat (hydrostatic weight), and VO(2 max) were regressed on to BV using data obtained from 66 normal healthy men. Results from the evaluation of the full model indicated that the most parsimonious result was obtained when age and VO(2 max) were regressed on BV expressed per kilogram body weight. The full model accounted for 52% of the total variance in BV per kilogram body weight. Both age and VO(2 max) were related to BV in the positive direction. Percent body fat contributed <1% to the explained variance in BV when expressed in absolute BV (ml) or as BV per kilogram body weight. When the model was cross validated on 41 new subjects and BV per kilogram body weight was reexpressed as raw BV, the results indicated that the statistical model would be stable under cross validation (e.g., predictive applications) with an accuracy of +/- 1,200 ml at 95% confidence. Our results support the hypothesis that BV is an increasing function of aerobic fitness and to a lesser extent the age of the subject. The results may have implication as to a mechanism by which aerobic fitness and activity may be protective against reduced BV associated with aging.

NASA Discipline Cardiopulmonary↗

Heritability of markers of bone metabolism

Several classic twin studies show genetic effects on markers of bone health, including bone mineral density and parathyroid hormone (PTH). This study was performed to assess the relative contribution of genetics to biochemical markers of bone metabolism. Fifteen sets of identical twins (8 male, 7 female) were housed in a clinical research center where diet was controlled (15% protein, 55% carbohydrate, 30% fat) for 3 consecutive days. Each day, 24-h urine pools were collected and N-telopeptide (NTX), deoxypyridinoline (DPD), calcium, and serum PTH were measured. The broad-sense heritability factor (H2) is an estimation of the portion of the total variance of a given phenotype that is attributable to genetic variance. H2 was estimated from the correlation coefficient of the phenotype data. H2 for NTX was 94% for males and 80% for females, DPD was 88% for males and 97% for females, urinary calcium excretion was 97% for males and 90% for females, and PTH was 92% for males and 79% for females. Since environmental variability was minimized for the 3 days of data collection, these heritability factors are likely overestimated. Nonetheless, the data support the concept that PTH is a predominantly heritable trait, and suggest that NTX, DPD, and calcium excretion are as well. These biochemical data support the previously documented heritability of bone health.

Smith, Scott M.↗

The El Nino/Southern Oscillation and Future Soybean Prices

Recently, it was shown that the application of a method combining singular spectrum analysis (SSA) and the maximum entropy method to univariate indicators of the coupled ocean-atmosphere El Nino/Southern Oscillation (ENSO) phenomenon can be helpful in determining whether an El Nino (EN) or La Nina (LN) event will occur. SSA - a variant of principal component analysis applied in the time domain - filters out variability unrelated to ENSO and separates the quasi-biennial (QB), two-to-three year variability, from a lower-frequency (LF) four-to-six year EN-LN cycle; the total variance associated with ENSO combines the QB and LF modes. ENSO has been known to affect weather conditions over much of the globe. For example, EN events have been connected with unusually rainy weather over the Central and Western US, while the opposite phases of the oscillation (LN) have been plausibly associated with extreme dry conditions over much of the same geographical area...

Keppenne, C.↗

Interannual Variability and Trends of Extratropical Ozone, Part II: Southern Hemisphere: Southern Hemisphere - Part 2

A principal component analysis (PCA) is applied to the Southern Hemisphere (SH) total column ozone following the method established for analyzing the data in the Northern Hemisphere (NH) in a companion paper. The interannual variability (IAV) of extratropical O-3 in the SH is characterized by four main modes, which account for 75% of the total variance. The first two leading modes are approximately zonally symmetric and relate to the Southern Hemisphere annular mode and the quasi-biennial oscillation. The third and fourth modes exhibit wavenumber-1 structures. Contrary to the Northern Hemisphere, the third and fourth are nor related to stationary waves. Similar results obtained for the 30 100-hPa geopotential thickness.The decreasing O3 trend in the SH is captured in the first mode. The largest trend is at the South Pole, with value similar to-2 Dobson Units (DU)/yr. Both the spatial pattern and trends in the column ozone are captured by the Goddard Earth Observation System chemistry-climate model (GEOS-CCM) in the SH.

Yung, Y. L.↗

Attributing Tropical Cyclogenesis to Equatorial Waves in the Western North Pacific

The direct influences of equatorial waves on the genesis of tropical cyclones are evaluated. Tropical cyclogenesis is attributed to an equatorial wave when the filtered rainfall anomaly exceeds a threshold value at the genesis location. For an attribution threshold of 3 mm/day, 51% of warm season western North Pacific tropical cyclones are attributed to tropical depression (TD)-type disturbances, 29% to equatorial Rossby waves, 26% to mixed Rossby-Gravity waves, 23% to Kelvin waves, 13% to the Madden-Julian oscillation (MJO), and 19% are not attributed to any equatorial wave. The fraction of tropical cyclones attributed to TD-type disturbances is consistent with previous findings. Past studies have also demonstrated that the MJO significantly modulates tropical cyclogenesis, but fewer storms are attributed to the MJO than any other wave type. This disparity arises from the difference between attribution and modulation. The MJO produces broad regions of favorable conditions for cyclogenesis, but the MJO alone might not determine when and where a storm will develop within these regions. Tropical cyclones contribute less than 17% of the power in any portion of the equatorial wave spectrum because tropical cyclones are relatively uncommon equatorward of 15deg latitude. In regions where they are active, however, tropical cyclones can contribute more than 20% of the warm season rainfall and up to 50% of the total variance. Tropical cyclone-related anomalies can significantly contaminate wave-filtered precipitation at the location of genesis. To mitigate this effect, the tropical cyclone-related rainfall anomalies were removed before filtering in this study.

Schreck, Carl J., III↗

Assessing the Urban Heat Island Effect Across Biomes in the Continental USA Using Landsat and MODIS

Impervious surface area (ISA) from the Landsat TM and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined across urban gradients and used to stratify sampling of LST and NDVI. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban - rural temperature difference) with the largest 8 C (average) for cities built in mixed forest biomes. For all cities ISA is the primary driver for increase in temperature explaining 70% of the total variance. Annually, urban areas are warmer than the non-urban fringe by 2.9 C, except in biomes with arid and semiarid climates. The average amplitude of the UHI is asymmetric with a 4.3 C difference in summer and 1.3 C in winter. In desert environments, UHI's point to a possible heat sink effect. Results show that the urban heat island amplitude increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.

Imhoff, Marc L.↗

Remote Sensing of the Urban Heat Island Effect Across Biomes in the Continental USA

Impervious surface area (ISA) from the Landsat TM-based NLCD 2001 dataset and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined for each urban area emanating outward from the urban core to the nonurban rural areas nearby and used to stratify sampling for land surface temperatures and NDVI. Sampling is further constrained by biome and elevation to insure objective intercomparisons between zones and between cities in different biomes permitting the definition of hierarchically ordered zones that are consistent across urban areas in different ecological setting and across scales. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban-rural temperature difference) the largest (8 C average) observed for cities built in biomes dominated by temperate broadleaf and mixed forest. For all cities combined, ISA is the primary driver for increase in temperature explaining 70% of the total variance in LST. On a yearly average, urban areas are substantially warmer than the non-urban fringe by 2.9 C, except for urban areas in biomes with arid and semiarid climates. The average amplitude of the UHI is remarkably asymmetric with a 4.3 C temperature difference in summer and only 1.3 C in winter. In desert environments, the LST's response to ISA presents an uncharacteristic "U-shaped" horizontal gradient decreasing from the urban core to the outskirts of the city and then increasing again in the suburban to the rural zones. UHI's calculated for these cities point to a possible heat sink effect. These observational results show that the urban heat island amplitude both increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.

Imhoff, Marc L.↗

Check-Standard Testing Across Multiple Transonic Wind Tunnels with the Modern Design of Experiments

This paper reports the result of an analysis of wind tunnel data acquired in support of the Facility Analysis Verification & Operational Reliability (FAVOR) project. The analysis uses methods referred to collectively at Langley Research Center as the Modern Design of Experiments (MDOE). These methods quantify the total variance in a sample of wind tunnel data and partition it into explained and unexplained components. The unexplained component is further partitioned in random and systematic components. This analysis was performed on data acquired in similar wind tunnel tests executed in four different U.S. transonic facilities. The measurement environment of each facility was quantified and compared.

Deloach, Richard↗

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Roberts, Yolanda↗

Extension and Statistical Analysis of the GACP Aerosol Optical Thickness Record.

The primary product of the Global Aerosol Climatology Project (GACP) is a continuous record of the aerosol optical thickness (AOT) over the oceans. It is based on channel-1 and -2 radiance data from the Advanced Very High Resolution Radiometer (AVHRR) instruments flown on successive National Oceanic and Atmospheric Administration (NOAA) platforms. We extend the previous GACP dataset by four years through the end of 2009 using NOAA-17 and -18 AVHRR radiances recalibrated against MODerate resolution Imaging Spectroradiometer (MODIS) radiance data, thereby making the GACP record almost three decades long. The temporal overlap of over three years of the new NOAA-17 and the previous NOAA-16 record reveals an excellent agreement of the corresponding global monthly mean AOT values, thereby confirming the robustness of the vicarious radiance calibration used in the original GACP product. The temporal overlap of the NOAA-17 and -18 instruments is used to introduce a small additive adjustment to the channel-2 calibration of the latter resulting in a consistent record with increased data density. The Principal Component Analysis (PCA) of the newly extended GACP record shows that most of the volcanic AOT variability can be isolated into one mode responsible for ~12% of the total variance. This conclusion is confirmed by a combined PCA analysis of the GACP, MODIS, andMulti-angle Imaging SpectroRadiometer (MISR) AOTs during the volcano-free period fromFebruary 2000 to December 2009.We show that the modes responsible for the tropospheric AOT variability in the three datasets agree well in terms of correlation and spatial patterns. A previously identified negative AOT trend which started in the late 1980s and continued into the early 2000s is confirmed. Its magnitude and duration indicate that it was caused by changes in tropospheric aerosols. The latest multi-satellite segment of the GACP record shows that this trend tapered off, with no noticeable AOT change after 2002. This result is consistent with the MODIS andMISR AOT records as well as with the recent gradual reversal frombrightening to dimming revealed by surface flux measurements in many aerosol producing regions. Thus the robustness of the GACP record is confirmed, increasing our confidence in the validity of the negative trend. Although the nominal negative GACP AOT trend could partially be an artifact of increasing aerosol absorption, we argue that the time dependence of the GACP record, including the latest flat period, is more consistent with the actual decrease in the tropospheric AOT.

aerosols↗

How Universal is the Relationship Between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment

Leaf Area Index (LAI) is a key variable that bridges remote sensing observations to the quantification of agroecosystem processes. In this study, we assessed the universality of the relationships between crop LAI and remotely sensed Vegetation Indices (VIs). We first compiled a global dataset of 1459 in situ quality-controlled crop LAI measurements and collected Landsat satellite images to derive five different VIs including Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), two versions of the Enhanced Vegetation Index (EVI and EVI2), and Green Chlorophyll Index (CI(sub Green)). Based on this dataset, we developed global LAI-VI relationships for each crop type and VI using symbolic regression and Theil-Sen (TS) robust estimator. Results suggest that the global LAI-VI relationships are statistically significant, crop-specific, and mostly non-linear. These relationships explain more than half of the total variance in ground LAI observations (R2 greater than 0.5), and provide LAI estimates with RMSE below 1.2 m2/m2. Among the five VIs, EVI/EVI2 are the most effective, and the crop-specific LAI-EVI and LAI-EVI2 relationships constructed by TS, are robust when tested by three independent validation datasets of varied spatial scales. While the heterogeneity of agricultural landscapes leads to a diverse set of local LAI-VI relationships, the relationships provided here represent global universality on an average basis, allowing the generation of large-scale spatial-explicit LAI maps. This study contributes to the operationalization of large-area crop modeling and, by extension, has relevance to both fundamental and applied agroecosystem research.

Vegetation Index↗

Reduced ENSO Variability at the LGM Revealed by an Isotope-Enabled Earth System Model

Studying the El Nino Southern Oscillation (ENSO) in the past can help us better understand its dynamics and improve its future projections. However, both paleoclimate reconstructions and model simulations of ENSO strength at the Last Glacial Maximum (LGM; 21 ka B.P.) have led to contradicting results. Here we perform model simulations using the recently developed water isotope-enabled Community Earth System Model (iCESM). For the first time, model-simulated oxygen isotopes are directly compared with those from ENSO reconstructions using the individual foraminifera analysis (IFA). We find that the LGM ENSO is most likely weaker comparing with the preindustrial. The iCESM suggests that total variance of the IFA records may only reflect changes in the annual cycle instead of ENSO variability as previously assumed. Furthermore, the interpretation of subsurface IFA records can be substantially complicated by the habitat depth of thermocline-dwelling foraminifera and their vertical migration with a temporally varying thermocline.

El Niño–Southern Oscillation;isotope-enabled si↗

The Cognition and Fine Motor Skills Test Batteries: Normative Data and Interdependencies

Space mission success and safety relies upon astronaut functional state. Since spaceflight stressors affect cognitive processing and fine motor skills, NASA requires that measures of performance of these things remain within clinically accepted values (NASA STD 3001). NASA is in the process of developing two test batteries for the assessment of crew cognitive and fine motor skills before, during and after spaceflight. Toward that goal, the current project collected normative scores in 91 “astronaut-like” military and civilian pilots. The Cognition Test Battery (CTB) contains ten sub-tests that measure a range of cognitive abilities. For five of the ten CTB sub-tests, we propose scores to improve the battery’s sensitivity. Among the ten sub-tests, response times were more highly correlated than accuracy scores. Principle component analysis of the correlations revealed that the first response time factor could explain over 40% of the total variance and appeared to represent the tendency of observers to try to respond more quickly. The first accuracy factor (explaining only 20%) gave a high weight to the higher level cognitive sub-tests and a negative weight to tasks associated with motor and lower level cognitive processing. The Fine Motor Skills (FMS) test battery contains four sub-tests (Tracking, Pointing, Tracing, Rotating) performed on an Apple iPad tablet computer. Principle component analysis on the sub-test response time correlations revealed that the first two factors accounted for ~80% of the variance in performance. The first component captured overall speed on all four of the sub-tests. The second factor separated the sub-tasks into two groups (Drag-Point vs Trace-Rotate). Previous work found the first group response times correlated with that of a standard peg board task, while those of the other group did not. Correlations were computed between the first FMS factor and the response time and accuracy scores from each CTB sub-task. Performing fine motor behaviors rapidly was significantly correlated with the ability to perform many of the CTB sub-tests rapidly. This ability cannot be simple motor speed since scores on the Psychomotor Vigilance Test (PVT) subtask did not correlate with the ability to perform the other tasks rapidly. Speed on fine motor skills correlated significantly with accuracy on the short-term-memory sub-test. We hypothesize that eye movements, which can be regarded as a fine motor skill, may explain this relationship.

cognition↗

Toward the Neutrino Discovery Platform: An Auditable, Uncertainty-Bearing Toolchain for MINERvA Open-Data Cross-Section Analysis

The Neutrino Discovery Platform (NDP) aims to accelerate DUNE-era science by making the neutrino program's existing datasets analyzable through fast, reproducible, and auditable workflows. We report a working version of two of its layers, data curation and agentic orchestration, built and tested end to end on MINERvA open data. The guiding lesson throughout is that a cross section is a measurement, and not just a plotted shape, only if it carries a defensible systematic-uncertainty budget, a trustworthy unfolding, and a reproducible record. Using a single medium-energy playlist pair from the MINERvA open-data release (about $2.05\times10^{17}$ protons on target of data), we first reproduced the shapes of two published charged-current inclusive $\nu_\mu$ measurements through a complete extraction ladder: selection, background subtraction, D'Agostini unfolding, efficiency correction, and flux normalization. These shape-level reproductions ran and tracked the published results, but they lacked the systematic-uncertainty machinery that defines a MINERvA cross section. To supply it, we vendored and built the MINERvA Analysis Toolkit and developed a many-universe systematic-uncertainty tool that produces a portable covariance artifact, a parallel event-loop runner, and a per-run auditability harness. Validated against a published covariance release, the toolchain reproduces the released statistical, flux, and muon-energy-scale terms and shows that they account for roughly 63\% of the total variance, with the remainder unreleased. Using this same infrastructure, we then performed a measurement of our own design, the hadronic recoil-energy distribution of low-energy ($E_\nu<2.5$~GeV) charged-current inclusive events, and found data/simulation shape agreement of $\chi^2/\mathrm{ndf}=1.26$. Together these results show that the platform supports original physics and not only reproductions.

Breaux, Auto [Tulane U. (main)]↗