Intrinsic Fluctuations and Driven Response of Insect Swarms

Animals of all sizes form groups, as acting together can convey advantages over acting alone; thus, collective animal behavior has been identified as a promising template for designing engineered systems. However, models and observations have focused predominantly on characterizing the overall group morphology, and often focus on highly ordered groups such as bird flocks. We instead study a disorganized aggregation (an insect mating swarm), and compare its natural fluctuations with the group-level response to an external stimulus. We quantify the swarm’s frequency-dependent linear response and its spectrum of intrinsic fluctuations, and show that the ratio of these two quantities has a simple scaling with frequency. Our results provide a new way of comparing models of collective behavior with experimental data

Improving Temporal Accuracy of Human Metabolic Chambers for Dynamic Metabolic Studies

Metabolic chambers are powerful tools for assessing human energy expenditure, providing flexibility and comfort for the subjects in a near free-living environment. However, the flexibility offered by the large living room size creates challenges in the assessment of dynamic human metabolic signals—such as those generated during high-intensity interval training and short-term involuntary physical activities—with sufficient temporal accuracy. Therefore, this paper presents methods to improve the temporal accuracy of metabolic chambers. The proposed methods include 1) adopting a shortest possible step size, here one minute, to compute the finite derivative terms for the metabolic rate calculation, and 2) applying a robust noise reduction method—total variation denoising—to minimize the large noise generated by the short derivative term whilst preserving the transient edges of the dynamic metabolic signals. Validated against 24-hour gas infusion tests, the proposed method reconstructs dynamic metabolic signals with the best temporal accuracy among state-of-the-art approaches, achieving a root mean square error of 0.27 kcal/min (18.8 J/s), while maintaining a low cumulative error in 24-hour total energy expenditure of less than 45 kcal/day (188280 J/day). When applied to a human exercise session, the proposed methods also show the best performance in terms of recovering the dynamics of exercise energy expenditure. Overall, the proposed methods improve the temporal resolution of the chamber system, enabling metabolic studies involving dynamic signals such as short interval exercises to carry out the metabolic chambers

Improving Ammonia Emission Modeling and Inventories by Data Mining and Intelligent Interpretation of the National Air Emission Monitoring Study Database

Ammonia emission is one of the greatest environmental concerns in sustainable agriculture development. Several limitations and fundamental problems associated with the current agricultural ammonia emission modeling and emission inventories have been identified. They were associated with a significant disconnection between field monitoring data and knowledge about the data. Comprehensive field measurement datasets have not been fully exploited for scientific research and emission regulations. This situation can be considerably improved if the currently available data are better interpreted and the new knowledge is applied to update ammonia emission modeling techniques. The world’s largest agricultural air quality monitoring database with more than 2.4 billion data points has recently been created by the United States’ National Air Emission Monitoring Study. New approaches of data mining and intelligent interpretation of the database are planned to uncover new knowledge and to answer a series of questions that have been raised. The expected results of this new research idea include enhanced fundamental understanding of ammonia emissions from animal agriculture and improved accuracy and scope in regional and national ammonia emission inventories

Shear-Wave Splitting and Mantle Flow Beneath the Colorado Plateau and its Boundary with the Great Basin

Shear-wave splitting measurements from SKS and SKKS phases show fast polarization azimuths that are subparallel to North American absolute plate motion within the central Rio Grande Rift (RGR) and Colorado Plateau (CP) through to the western rim of the CP, with anisotropy beneath the CP and central RGR showing a remarkably consistent pattern with a mean fast azimuth of 4 degrees +/- degrees 6 E of N. Approaching the rim from the southeast, fast anisotropic directions become north-northeast-south-southwest (NNE-SSW), rotate counter clockwise to north-south in the CP-GB transition, and then to NNW-SSE in the western Great Basin ( GB). This change is coincident with uppermost mantle S-wave velocity perturbations that vary from +4% beneath the western CP and the eastern edge of the Marysvale volcanic field to about -8% beneath the GB. Corresponding delay times average 1.5 sec beneath the central CP, decrease to approximately 0.8 sec near the CP-GB transition, and increase to about 1.2 sec beneath the GB. For the central CP, we suggest anisotropy predominantly controlled by North American plate motion above the asthenosphere. The observed pattern of westward-rotating anisotropy from the western CP through the CP-GB transition may be influenced to asthenospheric flow around a CP lithospheric keel and/or by vertical flow arising from edge-driven small-scale convection. The anisotropic transition from the CP to the GB thus marks a first-order change from absolute plate motion dominated lithosphere-asthenosphere shear to a new regime controlled by regional flow processes. The NNW-SSE anisotropic fast directions of split SKS waves in the eastern GB area are part of a broad circular pattern of seismic anisotropic fast direction in the central GB that has recently been hypothesized to be due to toroidal flow around the sinking Juan de Fuca-Gorda slab.National Science Foundation EAR 9706094, 9707188, 9707190, 0207812Los Alamos National Laboratory Institute of Geophysics and Planetary PhysicsNational Science Foundation Cooperative EAR-000430Department of Energy National Nuclear Security AdministrationGeological Science

Precision Spectroscopy of Polarized Molecules in an Ion Trap

Polar molecules are desirable systems for quantum simulations and cold chemistry. Molecular ions are easily trapped, but a bias electric field applied to polarize them tends to accelerate them out of the trap. We present a general solution to this issue by rotating the bias field slowly enough for the molecular polarization axis to follow but rapidly enough for the ions to stay trapped. We demonstrate Ramsey spectroscopy between Stark-Zeeman sublevels in 180Hf19F+ with a coherence time of 100 ms. Frequency shifts arising from well-controlled topological (Berry) phases are used to determine magnetic g-factors. The rotating-bias-field technique may enable using trapped polar molecules for precision measurement and quantum information science, including the search for an electron electric dipole moment.Comment: Accepted to Scienc

Neurological manifestations of coronavirus disease: a literature review

In December 2019, coronavirus pandemic re-emerged. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been identified as the causation in series of acute pneumonia cases discovered in Wuhan in Hubei Province, China. This disease is officially named COVID-19 by WHO. Symptoms manifestation of COVID-19 range from fever, malaise, myalgia, headache, to respiratory system symptoms of cough, stuffy/runny nose, and difficulty breathing. In severe cases, it may result in ARDS. A case study has reported that COVID-19 may also have cardiovascular manifestation, i.e. life threatening arrhythmia. Although COVID-19 is a respiratory infection and cardiovascular event is the main cause of fatality, medical professionals must understand its neurological complications in order to reduce mortality rate in infected patients. Further researches on specific risk factors or determinant protective factors from the neurological symptoms are needed to reduce risk of complication in COVID-19 infection cases