High-field superconducting nested coil magnet

Superconducting magnet, employed in conjunction with five types of superconducting cables in a nested solenoid configuration, produces total, central magnetic field strengths approaching 70 kG. The multiple coils permit maximum information on cable characteristics to be gathered from one test

Rectangular configuration improves superconducting cable

Superconducting cable for a cryogenic electromagnet with improved mechanical and thermal properties consists of a rectangular cross-sectioned combination of superconductor and normal conductor. The conductor cable has superconductors embedded in a metallic coating with high electrical and mechanical conductivity at liquid helium temperatures

Stranded superconducting cable of improved design

High-current cable developed in liquid helium cooled magnets uses aluminum wire interspersed with the superconductor strands. The aluminum maintains higher electrical conductivity, is light in weight, and has low thermal capacity

Biases in estimates of air pollution impacts: the role of omitted variables and measurement errors

Observational studies often use linear regression to assess the effect of ambient air pollution on outcomes of interest, such as human health outcomes or crop yields. Yet pollution datasets are typically noisy and include only a subset of potentially relevant pollutants, giving rise to both measurement error bias (MEB) and omitted variable bias (OVB). While it is well understood that these biases exist, less is understood about whether these biases tend to be positive or negative, even though it is sometimes falsely claimed that measurement error simply biases regression coefficient estimates towards zero. In this paper, we show that more can be said about the direction of these biases under the realistic assumptions that the concentrations of different types of air pollutants are positively correlated with each other and that each type of pollutant has a nonpositive association with the outcome variable. In particular, we demonstrate both theoretically and using simulations that under these two assumptions, the OVB will typically be negative and that more often than not the MEB for null pollutants or for pollutants that are perfectly measured will be negative. We also provide precise conditions, which are consistent with the assumptions, under which we prove that the biases are guaranteed to be negative. While the discussion in this paper is motivated by studies assessing the effect of air pollutants on crop yields, the findings are also relevant to regression-based studies assessing the effect of air pollutants on human health outcomes

Fast Plasma Investigation for MMS: Simulation of the Burst Triggering System

The Magnetospheric Multiscale (MMS) mission will study small-scale reconnection structures and their rapid motions from closely spaced platforms using instruments capable of high angular, energy, and time resolution measurements. To meet these requirements, the Fast Plasma Instrument (FPI) consists of eight (8) identical half top-hat electron sensors and eight (8) identical ion sensors and an Instrument Data Processing Unit (IDPU). The sensors (electron or ion) are grouped into pairs whose 6 degree x 180 degree fields-of-view (FOV) are set 90 degrees apart. Each sensor is equipped with electrostatic aperture steering to allow the sensor to scan a 45 degree x 180 degree fan about the its nominal viewing (0 deflection) direction. Each pair of sensors, known as the Dual Electron Spectrometer (DES) and the Dual Ion Spectrometer (DIS), occupies a quadrant on the MMS spacecraft and the combination of the eight electron/ion sensors, employing aperture steering, image the full-sky every 30-ms (electrons) and 150-ms (ions), respectively. To probe the diffusion regions of reconnection, the highest temporal/spatial resolution mode of FPI results in the DES complement of a given spacecraft generating 6.5-Mb (raised dot) per second of electron data while the DIS generates 1.1-Mb (raised dot) per second of ion data yielding an FPI total data rate of 6.6-Mb (raised dot) per second. The FPI electron/ion data is collected by the IDPU then transmitted to the Central Data Instrument Processor (CIDP) on the spacecraft for science interest ranking. Only data sequences that contain the greatest amount of temporal/spatial structure will be intelligently down-linked by the spacecraft. This requires a data ranking process known as the burst trigger system. The burst trigger system uses pseudo physical quantities to approximate the local plasma environments. As each pseudo quantity will have a different value, a set of two scaling factors is employed for each pseudo term. These pseudo quantities are then combined at the instrument, spacecraft, and observatory level leading to a final ranking of data based on expected scientific interest. Here, we present simulations of the fixed point burst trigger system for the FPI. A variety of data sets based on previous mission data as well as analytical formulations are tested. Comparisons of floating point calculations versus the fixed point hardware simulation are shown. Analysis of the potential sources of error from overflows, quantization, etc. are examined and mitigation methods are presented. Finally a series of calibration curves are presented, showing the expected error in pseudo quantities based solely on the scale parameters chosen and the expected data range. We conclude with a presentation of the current base-lined FPI burst trigger approach

The environmental impact of climate change adaptation on land use and water quality

Encouraging adaptation is an essential aspect of the policy response to climate change1. Adaptation seeks to reduce the harmful consequences and harness any beneficial opportunities arising from the changing climate. However, given that human activities are the main cause of environmental transformations worldwide2, it follows that adaptation itself also has the potential to generate further pressures, creating new threats for both local and global ecosystems. From this perspective, policies designed to encourage adaptation may conflict with regulation aimed at preserving or enhancing environmental quality. This aspect of adaptation has received relatively little consideration in either policy design or academic debate. To highlight this issue, we analyse the trade-offs between two fundamental ecosystem services that will be impacted by climate change: provisioning services derived from agriculture and regulating services in the form of freshwater quality. Results indicate that climate adaptation in the farming sector will generate fundamental changes in river water quality. In some areas, policies that encourage adaptation are expected to be in conflict with existing regulations aimed at improving freshwater ecosystems. These findings illustrate the importance of anticipating the wider impacts of human adaptation to climate change when designing environmental policies

Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve

Seasonal cycles enhance disparities between low- and high-income countries in exposure to monthly temperature emergence with future warming

A common proxy for the adaptive capacity of a community to the impacts of future climate change is the range of climate variability which they have experienced in the recent past. This study presents an interpretation of such a framework for monthly temperatures. Our results demonstrate that emergence into genuinely 'unfamiliar' climates will occur across nearly all months of the year for low-income nations by the second half of the 21st century under an RCP8.5 warming scenario. However, high income countries commonly experience a large seasonal cycle, owing to their position in the middle latitudes: as a consequence, temperature emergence for transitional months translates only to more-frequent occurrences of heat historically associated with the summertime. Projections beyond 2050 also show low-income countries will experience 2–10 months per year warmer than the hottest month experienced in recent memory, while high-income countries will witness between 1–4 months per year hotter than any month previously experienced. While both results represent significant departures that may bring substantive societal impacts if greenhouse gas emissions continue unabated, they also demonstrate that spatial patterns of emergence will compound existing differences between high and low income populations, in terms of their capacity to adapt to unprecedented future temperatures

The adaptive capacity of maize-based conservation agriculture systems to climate stress in tropical and subtropical environments: A meta-regression of yields

Conservation agriculture is widely promoted across sub-Saharan Africa as a sustainable farming practice that enhances adaptive capacity to climate change. The interactions between climate stress, management, and soil are critical to understanding the adaptive capacity of conservation agriculture. Yet conservation agriculture syntheses to date have largely neglected climate, especially the effects of extreme heat. For the sub-tropics and tropics, we use meta-regression, in combination with global soil and climate datasets, to test four hypotheses: (1) that relative yield performance of conservation agriculture improves with increasing drought and temperature stress; (2) that the effects of moisture and temperature stress exposure interact; (3) that the effects of moisture and temperature stress are modified by soil texture; and (4) that crop diversification, fertilizer application rate, or the time since no-till implementation will enhance conservation agriculture performance under climate stress. Our results support the hypothesis that the relative maize yield performance of conservation agriculture improves with increasing drought severity or exposure to high temperatures. Further, there is an interaction of moisture and heat stress on conservation agriculture performance and their combined effect is both non-additive and modified by soil clay content, supporting our second and third hypotheses. Finally, we found only limited support for our fourth hypothesis as (1) increasing nitrogen application rates did not improve the relative performance of conservation agriculture under high heat stress; (2) crop diversification did not notably improve conservation agriculture performance, but did increase its stability with heat stress; and (3) a statistically robust effect of the time since no-till implementation was not evident. Our meta-regression supports the narrative that conservation agriculture enhances the adaptive capacity of maize production in sub-Saharan Africa under drought and/or heat stress. However, in very wet seasons and on clay-rich soils, conservation agriculture yields less compared to conventional practices

Chemical combinations elucidate pathway interactions and regulation relevant to Hepatitis C replication

SREBP-2, oxidosqualene cyclase (OSC) or lanosterol demethylase were identified as novel sterol pathway-associated targets that, when probed with chemical agents, can inhibit hepatitis C virus (HCV) replication.Using a combination chemical genetics approach, combinations of chemicals targeting sterol pathway enzymes downstream of and including OSC or protein geranylgeranyl transferase I (PGGT) produce robust and selective synergistic inhibition of HCV replication. Inhibition of enzymes upstream of OSC elicit proviral responses that are dominant to the effects of inhibiting all downstream targets.Inhibition of the sterol pathway without inhibition of regulatory feedback mechanisms ultimately results in an increase in HCV replication because of a compensatory upregulation of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) expression. Increases in HMGCR expression without inhibition of HMGCR enzymatic activity ultimately stimulate HCV replication through increasing the cellular pool of geranylgeranyl pyrophosphate (GGPP).Chemical inhibitors that ultimately prevent SREBP-2 activation, inhibit PGGT or encourage the production of polar sterols have great potential as HCV therapeutics if associated toxicities can be reduced