Comparison of Computed and Measured Performance of a Pulsed Inductive Thruster Operating on Argon Propellant

Pulsed inductive plasma accelerators are electrodeless space propulsion devices where a capacitor is charged to an initial voltage and then discharged through a coil as a high-current pulse that inductively couples energy into the propellant. The field produced by this pulse ionizes the propellant, producing a plasma near the face of the coil. Once a plasma is formed if can be accelerated and expelled at a high exhaust velocity by the Lorentz force arising from the interaction of an induced plasma current and the magnetic field. A recent review of the developmental history of planar-geometry pulsed inductive thrusters, where the coil take the shape of a flat spiral, can be found in Ref. [1]. Two concepts that have employed this geometry are the Pulsed Inductive Thruster (PIT)[2, 3] and the Faraday Accelerator with Radio-frequency Assisted Discharge (FARAD)[4]. There exists a 1-D pulsed inductive acceleration model that employs a set of circuit equations coupled to a one-dimensional momentum equation. The model was originally developed and used by Lovberg and Dailey[2, 3] and has since been nondimensionalized and used by Polzin et al.[5, 6] to define a set of scaling parameters and gain general insight into their effect on thruster performance. The circuit presented in Fig. 1 provides a description of the electrical coupling between the current flowing in the thruster I1 and the plasma current I2. Recently, the model was upgraded to include an equation governing the deposition of energy into various modes present in a pulsed inductive thruster system (acceleration, magnetic flux generation, resistive heating, etc.)[7]. An MHD description of the plasma energy density evolution was tailored to the thruster geometry by assuming only one-dimensional motion and averaging the plasma properties over the spatial dimensions of the current sheet to obtain an equation for the time-evolution of the total energy. The equation set governing the dynamics of the coupled electrodynamic-current sheet system is composed of first-order, coupled ordinary differential equations that can be easily solved numerically without having to resort to much more complex 2-D finite element plasma simulations

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Identifying Defects in Li-Ion Cells Using Ultrasound Acoustic Measurements

Identification of the state-of-health (SoH) of Li-ion cells is a vital tool to protect operating battery packs against accelerated degradation and failure. This is becoming increasingly important as the energy and power densities demanded by batteries and the economic costs of packs increase. Here, ultrasonic time-of-flight analysis is performed to demonstrate the technique as a tool for the identification of a range of defects and SoH in Li-ion cells. Analysis of large, purpose-built defects across multiple length scales is performed in pouch cells. The technique is then demonstrated to detect a microscale defect in a commercial cell, which is validated by examining the acoustic transmission signal through the cell. The location and scale of the defects are confirmed using X-ray computed tomography, which also provides information pertaining to the layered structure of the cells. The demonstration of this technique as a methodology for obtaining direct, non-destructive, depth-resolved measurements of the condition of electrode layers highlights the potential application of acoustic methods in real-time diagnostics for SoH monitoring and manufacturing processes

Towards a Physiology-Based Measure of Pain: Patterns of Human Brain Activity Distinguish Painful from Non-Painful Thermal Stimulation

Pain often exists in the absence of observable injury; therefore, the gold standard for pain assessment has long been self-report. Because the inability to verbally communicate can prevent effective pain management, research efforts have focused on the development of a tool that accurately assesses pain without depending on self-report. Those previous efforts have not proven successful at substituting self-report with a clinically valid, physiology-based measure of pain. Recent neuroimaging data suggest that functional magnetic resonance imaging (fMRI) and support vector machine (SVM) learning can be jointly used to accurately assess cognitive states. Therefore, we hypothesized that an SVM trained on fMRI data can assess pain in the absence of self-report. In fMRI experiments, 24 individuals were presented painful and nonpainful thermal stimuli. Using eight individuals, we trained a linear SVM to distinguish these stimuli using whole-brain patterns of activity. We assessed the performance of this trained SVM model by testing it on 16 individuals whose data were not used for training. The whole-brain SVM was 81% accurate at distinguishing painful from non-painful stimuli (p<0.0000001). Using distance from the SVM hyperplane as a confidence measure, accuracy was further increased to 84%, albeit at the expense of excluding 15% of the stimuli that were the most difficult to classify. Overall performance of the SVM was primarily affected by activity in pain-processing regions of the brain including the primary somatosensory cortex, secondary somatosensory cortex, insular cortex, primary motor cortex, and cingulate cortex. Region of interest (ROI) analyses revealed that whole-brain patterns of activity led to more accurate classification than localized activity from individual brain regions. Our findings demonstrate that fMRI with SVM learning can assess pain without requiring any communication from the person being tested. We outline tasks that should be completed to advance this approach toward use in clinical settings

SNAPSHOT USA 2019 : a coordinated national camera trap survey of the United States

This article is protected by copyright. All rights reserved.With the accelerating pace of global change, it is imperative that we obtain rapid inventories of the status and distribution of wildlife for ecological inferences and conservation planning. To address this challenge, we launched the SNAPSHOT USA project, a collaborative survey of terrestrial wildlife populations using camera traps across the United States. For our first annual survey, we compiled data across all 50 states during a 14-week period (17 August - 24 November of 2019). We sampled wildlife at 1509 camera trap sites from 110 camera trap arrays covering 12 different ecoregions across four development zones. This effort resulted in 166,036 unique detections of 83 species of mammals and 17 species of birds. All images were processed through the Smithsonian's eMammal camera trap data repository and included an expert review phase to ensure taxonomic accuracy of data, resulting in each picture being reviewed at least twice. The results represent a timely and standardized camera trap survey of the USA. All of the 2019 survey data are made available herein. We are currently repeating surveys in fall 2020, opening up the opportunity to other institutions and cooperators to expand coverage of all the urban-wild gradients and ecophysiographic regions of the country. Future data will be available as the database is updated at eMammal.si.edu/snapshot-usa, as well as future data paper submissions. These data will be useful for local and macroecological research including the examination of community assembly, effects of environmental and anthropogenic landscape variables, effects of fragmentation and extinction debt dynamics, as well as species-specific population dynamics and conservation action plans. There are no copyright restrictions; please cite this paper when using the data for publication.Publisher PDFPeer reviewe

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Guidelines for the use of chest radiographs in community-acquired pneumonia in children and adolescents

© 2017, The Author(s). National guidance from the United Kingdom and the United States on community-acquired pneumonia in children states that chest radiographs are not recommended routinely in uncomplicated cases. The main reason in the ambulatory setting is that there is no evidence of a substantial impact on clinical outcomes. However clinical practice and adherence to guidance is multifactorial and includes the clinical context (developed vs. developing world), the confidence of the attending physician, the changing incidence of complications (according to the success of immunisation programs), the availability of alternative imaging (and its relationship to perceived risks of radiation) and the reliability of the interpretation of imaging. In practice, chest radiographs are performed frequently for suspected pneumonia in children. Time pressures facing clinicians at the front line, difficulties in distinguishing which children require admission, restricted bed numbers for admissions, imaging-resource limitations, perceptions regarding risk from procedures, novel imaging modalities and the probability of other causes for the child’s presentation all need to be factored into a guideline. Other drivers that often weigh in, depending on the setting, include cost-effectiveness and the fear of litigation. Not all guidelines designed for the developed world can therefore be applied to the developing world, and practice guidelines require regular review in the context of new information. In addition, radiologists must improve radiographic diagnosis of pneumonia, reach consensus on the interpretive terminology that clarifies their confidence regarding the presence of pneumonia and act to replace one imaging technique with another whenever there is proof of improved accuracy or reliability

The Software Architecture and development approach for the ASTRI Mini-Array gamma-ray air-Cherenkov experiment at the Observatorio del Teide

The ASTRI Mini-Array is an international collaboration led by the Italian National Institute for Astrophysics (INAF) and devoted to the imaging of atmospheric Cherenkov light for very-high gamma-ray astronomy. The project is deploying an array of 9 telescopes sensitive above 1 TeV. In this contribution, we present the architecture of the software that covers the entire life cycle of the observatory, from scheduling to remote operations and data dissemination. The high-speed networking connection available between the observatory site, at the Canary Islands, and the Data Center in Rome allows for ready data availability for stereo triggering and data processing