Spin Glass Correlation Length: a Caliper for Temperature Chaos

The spin glass correlation length is used as a caliper for the onset of temperature chaos in a Cu$_{0.94}$Mn$_{0.06}$ single crystal sample. From the values of the correlation length at different temperatures, we are able to calibrate the onset of the transition from reversible to chaotic behavior. We find that temperature chaos sets in abruptly as the chaos length scale $L^*$ becomes comparable to the spin glass correlation length $\xi$. We find the chaotic exponent for temperature chaos, $\zeta$, to be the order of unity assuming either fractal or compact glassy domains, in good agreement with previous theoretical analyses and numerical simulations

Long-Term Effects of Activity Status in the Elderly on Cardiorespiratory Capacity, Blood Pressure, Blood Lipids, and Body Composition: A Five-Year Follow-Up Study

It is generally recognized that physical activity levels in the elderly do not remain constant over time, and typically there is a marked reduction in physical activities in the elderly. The long-term benefits of regular physical training programs in the elderly are still not fully understood. This is a study of 55 elderly healthy subjects (over 65 years old) and re-evaluated for the effects of different physical activity patterns (sedentary, moderately active, and highly active) on several physiological parameters (pre- and post-training) after a 5-year period (5.30 ± 1.14 years). Measurements included: body composition, blood lipid profiles, resting systolic and diastolic blood pressure, maximal oxygen uptake, and pulmonary function. Results indicated a larger decrease in maximal oxygen uptake (VO2max) in the group of elderly sedentary individuals (1.5 ± 0.5 l/min) compared to the moderately active (1.7 ± 0.6 l/min) and the highly active groups (1.9 ± 0.4 l/min). An active lifestyle was not sufficient to increase the physiological function of an individual.This study could not clearly demonstrate favorable differences for the physically active groups over the sedentary group with regard to several important physiological factors over the 5-year follow-up and it appears that the recommendation for, and the initiation of, adopting active lifestyles may not be sufficient on their own to significantly increase an individual's physiological functioning

Slowing down of spin glass correlation length growth: Simulations meet experiments

The growth of the spin glass correlation length has been measured as a function of the waiting time tw on a single crystal of CuMn (6 at. %), reaching values ¿~150 nm, larger than any other glassy correlation length measured to date. We find an aging rate dlntw/dln¿ larger than found in previous measurements, which evinces a dynamic slowing down as ¿ grows. Our measured aging rate is compared with simulation results by the Janus Collaboration. After critical effects are taken into account, we find excellent agreement with the Janus data

Monitoring methane emissions from oil and gas operations

The atmospheric concentration of methane has more than doubled since the start of the Industrial Revolution. Methane is the second-most-abundant greenhouse gas created by human activities and a major driver of climate change. This APS-Optica report provides a technical assessment of the current state of monitoring U.S. methane emissions from oil and gas operations, which accounts for roughly 30% of U.S. anthropogenic methane emissions. The report identifies current technological and policy gaps and makes recommendations for the federal government in three key areas: methane emissions detection, reliable and systematized data and models to support mitigation measures, and effective regulation. &nbsp;</p

Multi-Timescale Perceptual History Resolves Visual Ambiguity

When visual input is inconclusive, does previous experience aid the visual system in attaining an accurate perceptual interpretation? Prolonged viewing of a visually ambiguous stimulus causes perception to alternate between conflicting interpretations. When viewed intermittently, however, ambiguous stimuli tend to evoke the same percept on many consecutive presentations. This perceptual stabilization has been suggested to reflect persistence of the most recent percept throughout the blank that separates two presentations. Here we show that the memory trace that causes stabilization reflects not just the latest percept, but perception during a much longer period. That is, the choice between competing percepts at stimulus reappearance is determined by an elaborate history of prior perception. Specifically, we demonstrate a seconds-long influence of the latest percept, as well as a more persistent influence based on the relative proportion of dominance during a preceding period of at least one minute. In case short-term perceptual history and long-term perceptual history are opposed (because perception has recently switched after prolonged stabilization), the long-term influence recovers after the effect of the latest percept has worn off, indicating independence between time scales. We accommodate these results by adding two positive adaptation terms, one with a short time constant and one with a long time constant, to a standard model of perceptual switching

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

© Copyright © 2020 Sandifer, Knapp, Lichtveld, Manley, Abramson, Caffey, Cochran, Collier, Ebi, Engel, Farrington, Finucane, Hale, Halpern, Harville, Hart, Hswen, Kirkpatrick, McEwen, Morris, Orbach, Palinkas, Partyka, Porter, Prather, Rowles, Scott, Seeman, Solo-Gabriele, Svendsen, Tincher, Trtanj, Walker, Yehuda, Yip, Yoskowitz and Singer. The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop

Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

© Copyright © 2020 Sandifer, Knapp, Lichtveld, Manley, Abramson, Caffey, Cochran, Collier, Ebi, Engel, Farrington, Finucane, Hale, Halpern, Harville, Hart, Hswen, Kirkpatrick, McEwen, Morris, Orbach, Palinkas, Partyka, Porter, Prather, Rowles, Scott, Seeman, Solo-Gabriele, Svendsen, Tincher, Trtanj, Walker, Yehuda, Yip, Yoskowitz and Singer. The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop