Research topics to scale up cover crop use: Reflections from innovative Iowa farmers

Cover crops as a conservation practice continue to receive attention from farmers, researchers, media, and policy makers, given their ability to effectively reduce water pollution and improve soil quality. Recent estimates of cover crop use across the midwestern Corn Belt, as well as the United States, demonstrate large acreage increases over the last number of years. The annual Sustainable Agriculture Research and Education–Conservation Technology Information Center (SARE– CTIC) survey found that nationally cover crop acreage doubled from 2011 to 2016, based on farmers self-reporting cover crop planting (CTIC 2016). However, the total cover crop acreage based on 2012 Census of Agriculture data only represents 3.2% of harvested cropland nationally and just 2.3% of the total cropland in the US Corn Belt (USDA NASS 2014a, 2014b)

Tea: A High-level Language and Runtime System for Automating Statistical Analysis

Though statistical analyses are centered on research questions and hypotheses, current statistical analysis tools are not. Users must first translate their hypotheses into specific statistical tests and then perform API calls with functions and parameters. To do so accurately requires that users have statistical expertise. To lower this barrier to valid, replicable statistical analysis, we introduce Tea, a high-level declarative language and runtime system. In Tea, users express their study design, any parametric assumptions, and their hypotheses. Tea compiles these high-level specifications into a constraint satisfaction problem that determines the set of valid statistical tests, and then executes them to test the hypothesis. We evaluate Tea using a suite of statistical analyses drawn from popular tutorials. We show that Tea generally matches the choices of experts while automatically switching to non-parametric tests when parametric assumptions are not met. We simulate the effect of mistakes made by non-expert users and show that Tea automatically avoids both false negatives and false positives that could be produced by the application of incorrect statistical tests.Comment: 11 page

Collaborative Freight Transportation to Improve Efficiency and Sustainability

Collaborative distribution offers the potential for substantial improvements in freight transportation. As collaboration increases, more loads are available for sharing among transportation service providers, leading to more fully loaded trailers that travel fewer miles and reduce the cost per load on average. In this study, we develop approaches to analyze improvements in key performance measures as collaboration increases in freight transportation. For the data sets analyzed, improvements include a 34% increase in trailer fullness, a 29% reduction in average costs per load, and a 25% decrease in average miles per load. Based on this analysis, collaboration provides substantial improvements for transportation service providers and opportunities for increased driver retention. Drivers would benefit from a better quality of life, more local routes, and more time home with their families. In addition to the economic and social benefit, the environmental benefit include reducing the miles driven and the resulting CO2 emissions

Approaching ‘kit-type’ labelling with 68Ga: the DATA chelators

The DATA chelators are a novel class of tri-anionic ligands based on 6-amino-1,4-diazepine-triacetic acid, which have been introduced recently for the chelation of 68Ga. Compared with macrocyclic chelators based on the cyclen scaffold (i.e., DOTA, DO3A, and DO2A derivatives), DATA chelators undergo quantitative radiolabelling more rapidly and under milder conditions. In this study, a systematic evaluation of the labelling of four DATA chelators—DATAM, DATAP, DATAPh, and DATAPPh—with 68Ga is presented. The results highlight the extraordinary potential of this new class of chelators for application in molecular imaging using 68Ga positron emission tomography (PET)

Advanced modulation technology development for earth station demodulator applications

The purpose of this contract was to develop a high rate (200 Mbps), bandwidth efficient, modulation format using low cost hardware, in 1990's technology. The modulation format chosen is 16-ary continuous phase frequency shift keying (CPFSK). The implementation of the modulation format uses a unique combination of a limiter/discriminator followed by an accumulator to determine transmitted phase. An important feature of the modulation scheme is the way coding is applied to efficiently gain back the performance lost by the close spacing of the phase points

Climate change challenges require collaborative research to drive agrifood system transformation

The recent Climate Science Special Report released as part of the Fourth National Climate Assessment confirms that we are living through the warmest period in modern civilization and that human activities are the primary driver of this warming (Wuebbles et al., 2017). These climatic changes have and will continue to impact global agricultural production, with food security and production consequences that will be felt unequally across the planet. Agricultural activities contribute to global warming emissions, while also offering opportunities for greenhouse gas mitigation. It is clear that the agrifood system will have to adapt to a changing climate. To better assess climate influences on agricultural systems in this themed issue of Renewable Agriculture and Food Systems, we challenged authors to submit interdisciplinary research that examines climate change adaptation and mitigation in agriculture and subsequent interconnected impacts to the food system. Indeed, agrifood systems provide a fertile context for examining climate change from multiple disciplines

Hunger in the Land of Plenty: Local Responses to Food Insecurity in Iowa

Story County (estimated population 92,406 in 2013) lies in the heart of central Iowa, a state renowned for its remarkable agricultural productivity. Iowa leads all states for production of corn, soybean, and hogs. Revenues from agricultural products in Iowa total more than $30 billion annually according the 2012 Agricultural Census (USDA-NASS 2014). This productivity stems from a favorable natural and political environment. The temperate climate, productive soils, and gentle topography are ideal for our production system of commodity agriculture facilitated by federal policies, which include subsidized crop insurance and commodity payments (Horrigan, Lawrence, and Walker 2002). Despite this productivity and political support for commodity production, a very small amount of acreage in Iowa produces food crops such as fruits and vegetables. Within Story County, the amount of cropland dedicated to fruit, vegetable, and nut production per one thousand residents is 2.4 acres, compared to 3.7 acres statewide, which is much lower than the US average of 32 acres per one thousand residents (ISUEO 2014). Paradoxically, in this land so perfectly suited for agriculture, there is an increasing demand for food assistance. Iowa State University Extension and Outreach (ISUEO) estimates 16,366 people live in poverty in Story County, a 20.1 percent poverty rate, compared to a statewide average of 12.2 percent (2014). ISUEO further estimates that 15.2 percent of Story County residents are food insecure, representing nearly 14,000 individuals. Comparatively, the statewide rate is 12.7 percent (ISUEO 2014). Compounding the problem, 45 percent of people who are food insecure in Story County do not qualify for direct government assistance because their income is above the economic threshold set for federal food assistance, and so they depend on charitable efforts to meet their needs. According to Feeding America’s statistics, Story County is the most food insecure county in Iowa (Gundersen, Engelhard, and Waxman 2015). The juxtaposition of a productive agricultural system with persistent hunger and need for food assistance is widely apparent in Story County and has inspired community-based efforts to address food needs. Through this chapter, we analyze the work of Food at First (FAF), a nonprofit that has emerged in response to the need for food assistance in Story County. Their work addresses the food needs of Story County residents by providing a daily free meal program and market as well as the recent development of a community garden. We illustrate the benefits of the FAF effort dedicated to building community-based solutions to hunger and food insecurity through a form of food democracy. We also explore key challenges associated with doing this work, including pragmatic issues of retaining and engaging volunteers. Further, we examine limitations of this model by exploring the underlying causes of food insecurity and how this organization contests as well as perpetuates a neoliberal model of food assistance. This neoliberal focus emphasizes individual responsibility and corporate charitable donations rather than collective, and/or government-level, responsibility for community food insecurity. We hope to raise important questions about how this community-driven work critically improves food security and a broader sense of community while still falling short of addressing poverty and inequality, the underlying reason for food insecurity in Ames and across the country

Comparison of the oxygen isotope signatures in speleothem records and iHadCM3 model simulations for the last millennium

Improving the understanding of changes in the mean and variability of climate variables as well as their interrelation is crucial for reliable climate change projections. Comparisons between general circulation models and paleoclimate archives using indirect proxies for temperature or precipitation have been used to test and validate the capability of climate models to represent climate changes. The oxygen isotopic ratio δ18O, a proxy for many different climate variables, is routinely measured in speleothem samples at decadal or higher resolution, and single specimens can cover full glacial–interglacial cycles. The calcium carbonate cave deposits are precisely dateable and provide well preserved (semi-)continuous albeit multivariate climate signals in the lower and mid-latitudes, where the measured δ18O in the mineral does not directly represent temperature or precipitation. Therefore, speleothems represent suitable archives to assess climate model abilities to simulate climate variability beyond the timescales covered by meteorological observations (101–102 years). Here, we present three transient isotope-enabled simulations from the Hadley Center Climate Model version 3 (iHadCM3) covering the last millennium (850–1850 CE) and compare them to a large global dataset of speleothem δ18O records from the Speleothem Isotopes Synthesis and AnaLysis (SISAL) database version 2 (Comas-Bru et al., 2020b). We systematically evaluate offsets in mean and variance of simulated δ18O and test for the main climate drivers recorded in δ18O for individual records or regions. The time-mean spatial offsets between the simulated δ18O and the speleothem data are fairly small. However, using robust filters and spectral analysis, we show that the observed archive-based variability of δ18O is lower than simulated by iHadCM3 on decadal and higher on centennial timescales. Most of this difference can likely be attributed to the records' lower temporal resolution and averaging or smoothing processes affecting the δ18O signal, e.g., through soil water residence times. Using cross-correlation analyses at site level and modeled grid-box level, we find evidence for highly variable but generally low signal-to-noise ratios in the proxy data. This points to a high influence of cave-internal processes and regional climate particularities and could suggest low regional representativity of individual sites. Long-range strong positive correlations dominate the speleothem correlation network but are much weaker in the simulation. One reason for this could lie in a lack of long-term internal climate variability in these model simulations, which could be tested by repeating similar comparisons with other isotope-enabled climate models and paleoclimate databases

Electronics and data acquisition demonstrator for a kinetic inductance camera

A prototype of digital frequency multiplexing electronics allowing the real time monitoring of kinetic inductance detector (KIDs) arrays for mm-wave astronomy has been developed. It requires only 2 coaxial cables for instrumenting a large array. For that, an excitation comb of frequencies is generated and fed through the detector. The direct frequency synthesis and the data acquisition relies heavily on a large FPGA using parallelized and pipelined processing. The prototype can instrument 128 resonators (pixels) over a bandwidth of 125 MHz. This paper describes the technical solution chosen, the algorithm used and the results obtained

Predictive Validity of the MAYSI-2 and PAI-A for Suicide-Related Behavior and Nonsuicidal Self-Injury Among Adjudicated Adolescent Offenders on Probation

This prospective study evaluated the ability of the MAYSI-2 and PAI-A to predict suicide-related behavior (SRB) and non-suicidal self-injury (NSSI) among adjudicated adolescent offenders on probation. Predictive validity of the MAYSI-2 for SRB and NSSI has generally been postdictively examined among detained adolescents. In addition, no published studies have examined the predictive validity of the PAI-A for SRB and NSSI among adolescent offenders. Neither the MAYSI-2 nor PAI-A added incremental predictive validity above lifetime SRB or NSSI. However, several MAYSI-2 and PAI-A subscales were predictive of SRB or NSSI. With some exceptions, most recommended instrument cut-off scores differentiated between low-risk and high-risk youth. These findings suggest that the MAYSI-2 and PAI-A hold promise for evaluating SRB and NSSI among justice-involved youth. In addition, these findings contribute to more informed decisions regarding the use of these tools and can be used to inform SRB and NSSI prevention efforts