Analyzing color infrared aerial photographs for the delineation of management units in site-specific agricultural management

Non-Peer ReviewedThis poster addresses the potential of a color infrared aerial photograph to provide spatially distributed information for site specific management. In this process digitized color infrared aerial photographs were used to extract vegetation index information. Crop and soil information were obtained through field sampling. Most important factors for affecting crop productivity were determined using principal component analysis. Point information were interpolated using kriging to create grid surface of the study area. Centroid of each grid cell was used to collect crop and soil information, and vegetation index at a regular interval throughout the study area. Fuzzy k-means with extra-grades algorithms were used to delineate potential within-field management units based on soil and crop information and vegetation index separately. Within-zone grain yield variation were calculated and used to evaluate management zones. The methodology is fast, can be easily automated in commercially available GIS software and has considerable advantages when comparing to other methods for delineating within-field management zones

The Quantum Socket: Three-Dimensional Wiring for Extensible Quantum Computing

Quantum computing architectures are on the verge of scalability, a key requirement for the implementation of a universal quantum computer. The next stage in this quest is the realization of quantum error correction codes, which will mitigate the impact of faulty quantum information on a quantum computer. Architectures with ten or more quantum bits (qubits) have been realized using trapped ions and superconducting circuits. While these implementations are potentially scalable, true scalability will require systems engineering to combine quantum and classical hardware. One technology demanding imminent efforts is the realization of a suitable wiring method for the control and measurement of a large number of qubits. In this work, we introduce an interconnect solution for solid-state qubits: The quantum socket. The quantum socket fully exploits the third dimension to connect classical electronics to qubits with higher density and better performance than two-dimensional methods based on wire bonding. The quantum socket is based on spring-mounted micro wires the three-dimensional wires that push directly on a micro-fabricated chip, making electrical contact. A small wire cross section (~1 mmm), nearly non-magnetic components, and functionality at low temperatures make the quantum socket ideal to operate solid-state qubits. The wires have a coaxial geometry and operate over a frequency range from DC to 8 GHz, with a contact resistance of ~150 mohm, an impedance mismatch of ~10 ohm, and minimal crosstalk. As a proof of principle, we fabricated and used a quantum socket to measure superconducting resonators at a temperature of ~10 mK.Comment: Main: 31 pages, 19 figs., 8 tables, 8 apps.; suppl.: 4 pages, 5 figs. (HiRes figs. and movies on request). Submitte

A comparison of methods to quantify greenhouse gas emissions of cropping systems in LCA

Carbon dioxide and nitrous oxide are two important greenhouse gases (GHG) released from cropping systems. Their emissions can vary substantially with climate, soil, and crop management. While different methods are available to account for GHG emissions in life cycle assessments (LCA) of crop production, there are no standard procedures. In this study, the objectives were: (i) to compare several methods of estimating CO2 and N2O emissions for a LCA of cropping systems and (ii) to estimate the relative contribution of soil GHG emissions to the overall global warming potential (GWP) using results from a field experiment located in Manitoba, Canada. The methods were: (A) measurements; (B) Tier I and (C) Tier II IPCC (Intergovernmental panel on Climate Change) methodology, (D) a simple carbon model combined with Intergovernmental Panel for Climate Change (IPCC) Tier II methodology for soil N2O emissions, and (E) the DNDC (DeNitrification DeComposition) agroecosystem model. The estimated GWPs (−7.2–17 Mg CO2eq ha−1 y−1; −80 to 600 kg CO2eq GJ−1 y−1) were similar to previous results in North America and no statistical difference was found between GWP based on methods D and E and GWP based on observations. The five methods gave estimates of soil CO2 emissions that were not statistically different from each other, whereas for N2O emissions only DNDC estimates were similar to observations. Across crop types, all methods gave comparable CO2 and N2O emission estimates for perennial and legume crops, but only DNDC gave similar results with respect to observations for both annual and cereal crops. Whilst the results should be confirmed for other locations, the agroecosystem model and method D can be used, at certainly one selected site, in place of observations for estimating GHGs in agricultural LCA

Employing an orthotopic model to study the role of epithelial-mesenchymal transition in bladder cancer metastasis.

Epithelial-to-mesenchymal transition (EMT) has been implicated in the progression of bladder cancer. To study its contribution to bladder cancer metastasis, we established new xenograft models derived from human bladder cancer cell lines utilizing an orthotopic "recycling" technique that allowed us to isolate and examine the primary tumor and its corresponding circulating tumor cells (CTC's) and metastatic lesions. Using whole genome mRNA expression profiling, we found that a reversible epithelial-to-mesenchymal transition (EMT) characterized by TGFβ pathway activation and SNAIL expression was associated with the accumulation of CTCs. Finally, we observed that conditional silencing of SNAIL completely blocked CTC production and regional/distant metastasis. Using this unique bladder cancer xenograft model, we conclude that metastasis is dependent on a reversible EMT mediated by SNAIL

Development of Crop.LCA, an adaptable screening life cycle assessment tool for agricultural systems: a Canadian scenario assessment

There is an increasing demand for sustainable agricultural production as part of the transition towards a globally sustainable economy. To quantify impacts of agricultural systems on the environment, life cycle assessment (LCA) is ideal because of its holistic approach. Many tools have been developed to conduct LCAs in agriculture, but they are not publicly available, not open-source, and have a limited scope. Here, a new adaptable open-source tool (Crop.LCA) for carrying out LCA of cropping systems is presented and tested in an evaluation study with a scenario assessment of 4 cropping systems using an agroecosystem model (DNDC) to predict soil GHG emissions. The functional units used are hectares (ha) of land and gigajoules (GJ) of harvested energy output, and 4 impact categories were evaluated: cumulative energy demand (CED), 100-year global warming potential (GWP), eutrophication and acidification potential. DNDC was used to simulate 28 years of cropping system dynamics, and the results were used as input in Crop.LCA. Data were aggregated for each 4-year rotation and statistically analyzed. Introduction of legumes into the cropping system reduced CED by 6%, GWP by 23%, and acidification by 19% per ha. These results highlight the ability of Crop.LCA to capture cropping system characteristics in LCA, and the tool constitutes a step forward in increasing the accuracy of LCA of cropping systems as required for bio-economy system assessments. Furthermore, the tool is open-source, highly transparent and has the necessary flexibility to assess agricultural systems

Development of Crop.LCA, an adaptable screening life cycle assessment tool for agricultural systems: a Canadian scenario assessment

There is an increasing demand for sustainable agricultural production as part of the transition towards a globally sustainable economy. To quantify impacts of agricultural systems on the environment, life cycle assessment (LCA) is ideal because of its holistic approach. Many tools have been developed to conduct LCAs in agriculture, but they are not publicly available, not open-source, and have a limited scope. Here, a new adaptable open-source tool (Crop.LCA) for carrying out LCA of cropping systems is presented and tested in an evaluation study with a scenario assessment of 4 cropping systems using an agroecosystem model (DNDC) to predict soil GHG emissions. The functional units used are hectares (ha) of land and gigajoules (GJ) of harvested energy output, and 4 impact categories were evaluated: cumulative energy demand (CED), 100-year global warming potential (GWP), eutrophication and acidification potential. DNDC was used to simulate 28 years of cropping system dynamics, and the results were used as input in Crop.LCA. Data were aggregated for each 4-year rotation and statistically analyzed. Introduction of legumes into the cropping system reduced CED by 6%, GWP by 23%, and acidification by 19% per ha. These results highlight the ability of Crop.LCA to capture cropping system characteristics in LCA, and the tool constitutes a step forward in increasing the accuracy of LCA of cropping systems as required for bio-economy system assessments. Furthermore, the tool is open-source, highly transparent and has the necessary flexibility to assess agricultural systems

DNA methylation epi-signature is associated with two molecularly and phenotypically distinct clinical subtypes of Phelan-McDermid syndrome

Background: Phelan-McDermid syndrome is characterized by a range of neurodevelopmental phenotypes with incomplete penetrance and variable expressivity. It is caused by a variable size and breakpoint microdeletions in the distal long arm of chromosome 22, referred to as 22q13.3 deletion syndrome, including the SHANK3 gene. Genetic defects in a growing number of neurodevelopmental genes have been shown to cause genome-wide disruptions in epigenomic profiles referred to as epi-signatures in affected individuals. Results: In this study we assessed genome-wide DNA methylation profiles in a cohort of 22 individuals with Phelan-McDermid syndrome, including 11 individuals with large (2 to 5.8 Mb) 22q13.3 deletions, 10 with small deletions (\u3c 1 Mb) or intragenic variants in SHANK3 and one mosaic case. We describe a novel genome-wide DNA methylation epi-signature in a subset of individuals with Phelan-McDermid syndrome. Conclusion: We identified the critical region including the BRD1 gene as responsible for the Phelan-McDermid syndrome epi-signature. Metabolomic profiles of individuals with the DNA methylation epi-signature showed significantly different metabolomic profiles indicating evidence of two molecularly and phenotypically distinct clinical subtypes of Phelan-McDermid syndrome

A Proposal for a Three Detector Short-Baseline Neutrino Oscillation Program in the Fermilab Booster Neutrino Beam

A Short-Baseline Neutrino (SBN) physics program of three LAr-TPC detectors located along the Booster Neutrino Beam (BNB) at Fermilab is presented. This new SBN Program will deliver a rich and compelling physics opportunity, including the ability to resolve a class of experimental anomalies in neutrino physics and to perform the most sensitive search to date for sterile neutrinos at the eV mass-scale through both appearance and disappearance oscillation channels. Using data sets of 6.6e20 protons on target (P.O.T.) in the LAr1-ND and ICARUS T600 detectors plus 13.2e20 P.O.T. in the MicroBooNE detector, we estimate that a search for muon neutrino to electron neutrino appearance can be performed with ~5 sigma sensitivity for the LSND allowed (99% C.L.) parameter region. In this proposal for the SBN Program, we describe the physics analysis, the conceptual design of the LAr1-ND detector, the design and refurbishment of the T600 detector, the necessary infrastructure required to execute the program, and a possible reconfiguration of the BNB target and horn system to improve its performance for oscillation searches.Comment: 209 pages, 129 figure