Magnetic field dependence of the internal quality factor and noise performance of lumped-element kinetic inductance detectors

We present a technique for increasing the internal quality factor of kinetic inductance detectors (KIDs) by nulling ambient magnetic fields with a properly applied magnetic field. The KIDs used in this study are made from thin-film aluminum, they are mounted inside a light-tight package made from bulk aluminum, and they are operated near $150 \, \mathrm{mK}$. Since the thin-film aluminum has a slightly elevated critical temperature ($T_\mathrm{c} = 1.4 \, \mathrm{K}$), it therefore transitions before the package ($T_\mathrm{c} = 1.2 \, \mathrm{K}$), which also serves as a magnetic shield. On cooldown, ambient magnetic fields as small as approximately $30 \, \mathrm{\mu T}$ can produce vortices in the thin-film aluminum as it transitions because the bulk aluminum package has not yet transitioned and therefore is not yet shielding. These vortices become trapped inside the aluminum package below $1.2 \, \mathrm{K}$ and ultimately produce low internal quality factors in the thin-film superconducting resonators. We show that by controlling the strength of the magnetic field present when the thin film transitions, we can control the internal quality factor of the resonators. We also compare the noise performance with and without vortices present, and find no evidence for excess noise beyond the increase in amplifier noise, which is expected with increasing loss.Comment: 5 pages, 4 figure

Public Price Reporting, Marketing Channel Selection, and Price Discovery: The Perspective of Cow/Calf Producers in the Dakotas

Cow/calf producers operating in the Dakotas were surveyed on their price discovery strategies, marketing channel preferences, and their perceptions of how regime change in the public price reporting system for fed cattle affected the beef industry in general and the cow/calf industry in particular. Survey results indicate cow/calf producers consider local institutions (auction barns, etc.) to be more reliable for price discovery than regional or national institutions (futures market, USDA public price reports, satellite auctions, etc.). The auction barn marketing channel is the preferred channel for marketing cattle and is considered the most reliable source of market information by producers. Dakota cow/calf producers perceive livestock mandatory price reporting as benefiting the beef industry in general, but consider public price reports to be less reliable than local sources of market information.beef supply chain, cow-calf marketing, marketing channel, price discovery, public price reporting, Livestock Production/Industries,

The Effect of Early vs. Normal Calf Weaning on Feedlot Performance and Herd Management: A Cross-Discipline Case Study

A study of early vs. normal weaning of calves concludes that early weaning improves feedlot production efficiency, reducing per day and per pound feedlot production costs. Early weaned steers finished higher thus feedlot profitability was not affected. Early weaning has a positive affect on cow health and pasture utilization rates.Livestock Production/Industries,

Access to and Use of Technology for Health: Comparisons Between Appalachian Kentuckians and the General U.S. Population

Introduction: Technology may increase the availability of health information and enable health promoting behaviors. However, lack of access to and use of technology may also exacerbate disparities, particularly in rural communities with limited Internet access. Purpose: The purpose of this study was to compare Internet access, device ownership, and use of technology for health between Appalachian Kentuckians and the general U.S. population. Methods: Findings from the 2017 Assessing the Health Status of Kentucky (ASK) survey were compared to national estimates from the Health Information National Trends Survey (HINTS) 5, Cycle 1 (2017), with a particular focus on degree of rurality. ASK and HINTS respondent sociodemographics, Internet access, and use of technology for health were assessed using weighted percentages; chi-square P-values were calculated based on weighted counts. Results: Over 80% of both populations reported accessing the Internet. However, Appalachian Kentuckians across all geographic strata were significantly less likely to access the Internet through broadband, cellular networks, and Wi-Fi. The U.S. population reported greater electronic device ownership rates. Appalachian Kentuckians were significantly more likely to search for cancer information online compared to national estimates. The majority of both populations reported not having health apps on their smartphones or tablets. Appalachian Kentuckians reported significantly lower rates of using electronic media to exchange information with health professionals. Implications: Ensuring high-speed Internet access among Appalachian Kentuckians could help this population leverage available technology to overcome barriers to care and reduce health disparities – for example, by enabling the use of health-related apps or electronic means to remotely communicate with providers. Such technologies have the potential to improve the health of medically underserved populations and deserve further attention

The ASAC Air Carrier Investment Model (Second Generation)

To meet its objective of assisting the U.S. aviation industry with the technological challenges of the future, NASA must identify research areas that have the greatest potential for improving the operation of the air transportation system. To accomplish this, NASA is building an Aviation System Analysis Capability (ASAC). The ASAC differs from previous NASA modeling efforts in that the economic behavior of buyers and sellers in the air transportation and aviation industries is central to its conception. To link the economics of flight with the technology of flight, ASAC requires a parametrically based mode with extensions that link airline operations and investments in aircraft with aircraft characteristics. This model also must provide a mechanism for incorporating air travel demand and profitability factors into the airlines' investment decisions. Finally, the model must be flexible and capable of being incorporated into a wide-ranging suite of economic and technical models that are envisioned for ASAC. We describe a second-generation Air Carrier Investment Model that meets these requirements. The enhanced model incorporates econometric results from the supply and demand curves faced by U.S.-scheduled passenger air carriers. It uses detailed information about their fleets in 1995 to make predictions about future aircraft purchases. It enables analysts with the ability to project revenue passenger-miles flown, airline industry employment, airline operating profit margins, numbers and types of aircraft in the fleet, and changes in aircraft manufacturing employment under various user-defined scenarios

Eeg-Derived Estimators of Present and Future Cognitive Performance

Previous electroencephalography (EEG)-based fatigue-related research primarily focused on the association between concurrent cognitive performance and time-locked physiology. The goal of this study was to investigate the capability of EEG to assess the impact of fatigue on both present and future cognitive performance during a 20-min sustained attention task, the 3-choice active vigilance task (3CVT), that requires subjects to discriminate one primary target from two secondary non-target geometric shapes. The current study demonstrated the ability of EEG to estimate not only present, but also future cognitive performance, utilizing a single, combined reaction time (RT), and accuracy performance metric. The correlations between observed and estimated performance, for both present and future performance, were strong (up to 0.89 and 0.79, respectively). The models were able to consistently estimate “unacceptable” performance throughout the entire 3CVT, i.e., excessively missed responses and/or slow RTs, while acceptable performance was recognized less accurately later in the task. The developed models were trained on a relatively large dataset (n = 50 subjects) to increase stability. Cross-validation results suggested the models were not over-fitted. This study indicates that EEG can be used to predict gross-performance degradations 5–15 min in advance

Developing a Model Framework for Predicting Effects of Woody Expansion and Fire on Ecosystem Carbon and Nitrogen in a Pinyon-Juniper Woodland

Sagebrush-steppe ecosystems are one of the most threatened ecosystems in North America due to woodland expansion, wildfire, and exotic annual grass invasion. Some scientists and policy makers have suggested that woodland expansion will lead to increased carbon (C) storage on the landscape. To assess this potential we used data collected from a Joint Fire Sciences Program demonstration area to develop a Microsoft Excel™ based biomass, carbon, and nitrogen (N) spreadsheet model. The model uses input for tree cover, soil chemistry, soil physical properties, and vegetation chemistry to estimate biomass, carbon, and nitrogen accumulation on the landscape with woodland expansion. The model also estimates C and N losses associated with prescribed burning. On our study plots we estimate in treeless sagebrush-steppe ecosystems, biomass accounts for 4.5 Mg ha−1 C and 0.3 Mg ha−1 N this is \u3c10% of total estimated ecosystem C and N to a soil depth of 53 cm, but as tree cover increases to near closed canopy conditions aboveground biomass may account for 62 Mg ha−1 C and 0.6 Mg ha−1 N which is nearly 53% of total estimated ecosystem C and 13% of total estimated ecosystem N to a soil depth of 53 cm. Prescribed burning removes aboveground biomass, C and N, but may increase soil C at areal tree cover below 26%. The model serves as a tool by which we are able to assess our understanding of the system and identify knowledge gaps which exist for this ecosystem. We believe that further work is necessary to quantify herbaceous biomass, root biomass, woody debris decomposition, and soil C and N with woodland expansion and prescribed fire. It will also be necessary to appropriately scale these estimates from the plot to the landscape

Influence of Prescribed Fire on Ecosystem Biomass, Carbon, and Nitrogen in a Pinyon Juniper Woodland

Increases in pinyon and juniper woodland cover associated with land-use history are suggested to provide offsets for carbon emissions in arid regions. However, the largest pools of carbon in arid landscapes are typically found in soils, and aboveground biomass cannot be considered long-term storage in fire-prone ecosystems. Also, the objectives of carbon storage may conflict with management for other ecosystem services and fuels reduction. Before appropriate decisions can be made it is necessary to understand the interactions between woodland expansion, management treatments, and carbon retention. We quantified effects of prescribed fire as a fuels reduction and ecosystem maintenance treatment on fuel loads, ecosystem carbon, and nitrogen in a pinyon–juniper woodland in the central Great Basin. We found that plots containing 30% tree cover averaged nearly 40 000 kg · ha−1 in total aboveground biomass, 80 000 kg · ha−1 in ecosystem carbon (C), and 5 000 kg · ha−1 in ecosystem nitrogen (N). Only 25% of ecosystem C and 5% of ecosystem N resided in aboveground biomass pools. Prescribed burning resulted in a 65% reduction in aboveground biomass, a 68% reduction in aboveground C, and a 78% reduction in aboveground N. No statistically significant change in soil or total ecosystem C or N occurred. Prescribed fire was effective at reducing fuels on the landscape and resulted in losses of C and N from aboveground biomass. However, the immediate and long-term effects of burning on soil and total ecosystem C and N is still unclear

MR446: Profiles of Sixteen Eastern Maine Fishing Communities

In the United States, a number of legal mandates require social impact assessments of proposed federal fisheries management and other actions. However, too often there are insufficient data with which to conduct social impact assessments for fisheries management, in part because these data are expensive and time consuming to collect and social science for SIAs is typically underfunded. To address this lack of data, these authors profiled 16 fish­ing communities in eastern Maine (Vinalhaven, Stonington, Bar Harbor, Northeast Harbor, Southwest Harbor, Bass Harbor, Swan’s Island, Steuben, Winter Harbor, Gouldsboro, Milbridge, Jonesport, Beals, Bucks Harbor, Lubec, and Eastport), focusing on the communities in eastern Maine currently or historically engaged in the New England groundfish fishery. The profiles are based on a rapid assessment to document the current infrastructure and updated with social, economic, and demographic data available from the 2010 U.S. Census and with 2011 state and federal license data.https://digitalcommons.library.umaine.edu/aes_miscreports/1026/thumbnail.jp

Associations between residual feed intake and apparent nutrient digestibility, in vitro methane-producing activity, and volatile fatty acid concentrations in growing beef cattle

The objectives of this study were to examine the relationship between residual feed intake (RFI) and DM and nutrient digestibility, in vitro methane production, and volatile fatty acid (VFA) concentrations in growing beef cattle. Residual feed intake was measured in growing Santa Gertrudis steers (Study 1; n = 57; initial BW = 291.1 ± 33.8 kg) and Brangus heifers (Study 2; n = 468; initial BW = 271.4 ± 26.1 kg) fed a high-roughage-based diet (ME = 2.1 Mcal/kg DM) for 70 d in a Calan-gate feeding barn. Animals were ranked by RFI based on performance and feed intake measured from day 0 to 70 (Study 1) or day 56 (Study 2) of the trial, and 20 animals with the lowest and highest RFI were identified for subsequent collections of fecal and feed refusal samples for DM and nutrient digestibility analysis. In Study 2, rumen fluid and feces were collected for in vitro methane-producing activity (MPA) and VFA analysis in trials 2, 3, and 4. Residual feed intake classification did not affect BW or BW gain (P \u3e 0.05), but low-RFI steers and heifers both consumed 19% less (P \u3c 0.01) DMI compared with high-RFI animals. Steers with low RFI tended (P \u3c 0.1) to have higher DM digestibility (DMD) compared with high-RFI steers (70.3 vs. 66.5 ± 1.6% DM). Heifers with low RFI had 4% higher DMD (76.3 vs. 73.3 ± 1.0% DM) and 4 to 5% higher (P \u3c 0.01) CP, NDF, and ADF digestibility compared with heifers with high RFI. Low-RFI heifers emitted 14% less (P \u3c 0.01) methane (% GE intake; GEI) calculated according to Blaxter and Clapperton (1965) as modified by Wilkerson et al. (1995), and tended (P = 0.09) to have a higher rumen acetate:propionate ratio than heifers with high RFI (GEI = 5.58 vs. 6.51 ± 0.08%; A:P ratio = 5.02 vs. 4.82 ± 0.14%). Stepwise regression analysis revealed that apparent nutrient digestibilities (DMD and NDF digestibility) for Study 1 and Study 2 accounted for an additional 8 and 6%, respectively, of the variation in intake unaccounted for by ADG and mid-test BW0.75. When DMD, NDF digestibility, and total ruminal VFA were added to the base model for Study 2, trials 2, 3, and 4, the R2 increased from 0.33 to 0.47, explaining an additional 15% of the variation in DMI unrelated to growth and body size. On the basis of the results of these studies, differences in observed phenotypic RFI in growing beef animals may be a result of inter-animal variation in apparent nutrient digestibility and ruminal VFA concentrations