Sea Level Rise and Public Perceptions of Climate Change at Otter Point Creek Estuarine Reserve, MD

Freshwater tidal marshes are essential stopover points for migratory birds traveling up and down the east coast of North America. Given the importance of these habitats, we examined the effects of sea level rise on vegetation health and vegetation migration at Otter Point Creek Estuarine Reserve. We aimed to test three predictions: 1) vegetation health will decline over time during vegetation growth periods, 2) vegetation migration of less water-tolerant species will occur with movement into higher elevation plots, 3) people will be aware that there are impacts of climate change on species around them and themselves. We used a combination of Google Earth Engine, ArcGIS, field-collected vegetation data analyzed in R, and a survey of visitor perceptions to test these predictions. Our results demonstrate that 1) vegetation health has increased in some areas but decreased in others over time; it is unclear which vegetation has grown over time, 2) there is a slow vegetation migration in low- to mid-marsh transects, 3) people are aware that climate change impacts plants, animals, and people, but fewer recognize that it will impact them personally. Our results also show that, with a 10ft increase in sea level, this system would disappear completely. Overall, this vital wildlife habitat will continue to change with increased extreme weather events that will negatively cause significant shifts within the marsh

PickCells: A Physically Reconfigurable Cell-composed Touchscreen

Touchscreens are the predominant medium for interactions with digital services; however, their current fixed form factor narrows the scope for rich physical interactions by limiting interaction possibilities to a single, planar surface. In this paper we introduce the concept of PickCells, a fully reconfigurable device concept composed of cells, that breaks the mould of rigid screens and explores a modular system that affords rich sets of tangible interactions and novel acrossdevice relationships. Through a series of co-design activities – involving HCI experts and potential end-users of such systems – we synthesised a design space aimed at inspiring future research, giving researchers and designers a framework in which to explore modular screen interactions. The design space we propose unifies existing works on modular touch surfaces under a general framework and broadens horizons by opening up unexplored spaces providing new interaction possibilities. In this paper, we present the PickCells concept, a design space of modular touch surfaces, and propose a toolkit for quick scenario prototyping

Computing prime factors with a Josephson phase qubit quantum processor

A quantum processor (QuP) can be used to exploit quantum mechanics to find the prime factors of composite numbers[1]. Compiled versions of Shor's algorithm have been demonstrated on ensemble quantum systems[2] and photonic systems[3-5], however this has yet to be shown using solid state quantum bits (qubits). Two advantages of superconducting qubit architectures are the use of conventional microfabrication techniques, which allow straightforward scaling to large numbers of qubits, and a toolkit of circuit elements that can be used to engineer a variety of qubit types and interactions[6, 7]. Using a number of recent qubit control and hardware advances [7-13], here we demonstrate a nine-quantum-element solid-state QuP and show three experiments to highlight its capabilities. We begin by characterizing the device with spectroscopy. Next, we produces coherent interactions between five qubits and verify bi- and tripartite entanglement via quantum state tomography (QST) [8, 12, 14, 15]. In the final experiment, we run a three-qubit compiled version of Shor's algorithm to factor the number 15, and successfully find the prime factors 48% of the time. Improvements in the superconducting qubit coherence times and more complex circuits should provide the resources necessary to factor larger composite numbers and run more intricate quantum algorithms.Comment: 5 pages, 3 figure

Generation of Three-Qubit Entangled States using Superconducting Phase Qubits

Entanglement is one of the key resources required for quantum computation, so experimentally creating and measuring entangled states is of crucial importance in the various physical implementations of a quantum computer. In superconducting qubits, two-qubit entangled states have been demonstrated and used to show violations of Bell's Inequality and to implement simple quantum algorithms. Unlike the two-qubit case, however, where all maximally-entangled two-qubit states are equivalent up to local changes of basis, three qubits can be entangled in two fundamentally different ways, typified by the states $|\mathrm{GHZ}> = (|000> + |111>)/\sqrt{2}$ and $|\mathrm{W}> = (|001> + |010> + |100>)/\sqrt{3}$. Here we demonstrate the operation of three coupled superconducting phase qubits and use them to create and measure $|\mathrm{GHZ}>$ and $|\mathrm{W}>$ states. The states are fully characterized using quantum state tomography and are shown to satisfy entanglement witnesses, confirming that they are indeed examples of three-qubit entanglement and are not separable into mixtures of two-qubit entanglement.Comment: 9 pages, 5 figures. Version 2: added supplementary information and fixed image distortion in Figure 2

Planar Superconducting Resonators with Internal Quality Factors above One Million

We describe the fabrication and measurement of microwave coplanar waveguide resonators with internal quality factors above 10 million at high microwave powers and over 1 million at low powers, with the best low power results approaching 2 million, corresponding to ~1 photon in the resonator. These quality factors are achieved by controllably producing very smooth and clean interfaces between the resonators' aluminum metallization and the underlying single crystal sapphire substrate. Additionally, we describe a method for analyzing the resonator microwave response, with which we can directly determine the internal quality factor and frequency of a resonator embedded in an imperfect measurement circuit.Comment: 4 pages, 3 figures, 1 tabl

Out-of-tank evaporator demonstration. Final report

The project reported here was conducted to demonstrate a skid-mounted, subatmospheric evaporator to concentrate liquid low-level waste (LLLW) stored in underground tanks at Oak Ridge National Laboratory (ORNL). This waste is similar to wastes stored at Hanford and Savannah River. A single-stage subatmospheric evaporator rated to produce 90 gallons of distillate per hour was procured from Delta Thermal, Inc., of Pensacola, Florida, and installed in an existing building. During the 8-day demonstration, 22,000 gal of LLLW was concentrated by 25% with the evaporator system. Decontamination factors achieved averaged 5 x 10{sup 6} (i.e., the distillate contained five million times less Cesium 137 than the feed). Evaporator performance substantially exceeded design requirements and expectations based on bench-scale surrogate test data. Out-of tank evaporator demonstration operations successfully addressed the feasibility of hands-on maintenance. Demonstration activities indicate that: (1) skid-mounted, mobile equipment is a viable alternative for the treatment of ORNL LLLW, and (2) hands-on maintenance and decontamination for movement to another site is achievable. Cost analysis show that 10% of the demonstration costs will be immediately recovered by elimination of solidification and disposal costs. The entire cost of the demonstration can be recovered by processing the inventory of Melton Valley Storage Tank waste and/or sluice water prior to solidifications. An additional savings of approximately $200,000 per year can be obtained by processing newly generated waste through the system. The results indicate that this type of evaporator system should be considered for application across the DOE complex. 25 refs., 11 figs., 2 tabs

Holistic Slowdown Driven Scheduling and Resource Management for Malleable Jobs

In job scheduling, the concept of malleability has been explored since many years ago. Research shows that malleability improves system performance, but its utilization in HPC never became widespread. The causes are the difficulty in developing malleable applications, and the lack of support and integration of the different layers of the HPC software stack. However, in the last years, malleability in job scheduling is becoming more critical because of the increasing complexity of hardware and workloads. In this context, using nodes in an exclusive mode is not always the most efficient solution as in traditional HPC jobs, where applications were highly tuned for static allocations, but offering zero flexibility to dynamic executions. This paper proposes a new holistic, dynamic job scheduling policy, Slowdown Driven (SD-Policy), which exploits the malleability of applications as the key technology to reduce the average slowdown and response time of jobs. SD-Policy is based on backfill and node sharing. It applies malleability to running jobs to make room for jobs that will run with a reduced set of resources, only when the estimated slowdown improves over the static approach. We implemented SD-Policy in SLURM and evaluated it in a real production environment, and with a simulator using workloads of up to 198K jobs. Results show better resource utilization with the reduction of makespan, response time, slowdown, and energy consumption, up to respectively 7%, 50%, 70%, and 6%, for the evaluated workloads

Using Microbial Community Interactions within Plant Microbiomes to Advance an Evergreen Agricultural Revolution

Innovative plant breeding and technology transfer fostered the Green Revolution (GR), which transformed agriculture worldwide by increasing grain yields in developing countries. The GR temporarily alleviated world hunger, but also reduced biodiversity, nutrient cycling, and carbon (C) sequestration that agricultural lands can provide. Meanwhile, economic disparity and food insecurity within and among countries continues. Subsequent agricultural advances, focused on objectives such as increasing crop yields or reducing the risk of a specific pest, have failed to meet food demands at the local scale or to restore lost ecosystem services. An increasing human population, climate change, growing per capita food and energy demands, and reduced ecosystem potential to provide agriculturally relevant services have created an unrelenting need for improved crop production practices. Meeting this need in a sustainable fashion will require interdisciplinary approaches that integrate plant and microbial ecology with efforts to advance crop production while mitigating effects of a changing climate. Metagenomic advances are revealing microbial dynamics that can simultaneously improve crop production and soil restoration while enhancing crop resistance to environmental change. Restoring microbial diversity to contemporary agroecosystems could establish ecosystem services while reducing production costs for agricultural producers. Our framework for examining plant-microbial interactions at multiple scales, modeling outcomes to broadly explore potential impacts, and interacting with extension and training networks to transfer microbial based agricultural technologies across socioeconomic scales, offers an integrated strategy for advancing agroecosystem sustainability while minimizing potential for the kind of negative ecological and socioeconomic feedbacks that have resulted from many widely adopted agricultural technologies

Impact of Different Plant Canopy Traits on Sorghum Yields

Studying changes in plant canopy can help to improve plant architecture and increase yields. Specifically, for sorghum (Sorghum bicolor L.), characterizing and identifying relevant canopy traits can be helpful not only to improve its productivity but to better fit this crop in the rotation from a system perspective. With this purpose, morphological characteristics of 20 sorghum hybrids were measured during the 2022 growing season in Wamego, KS, U.S. (United States). The most relevant canopy traits examined were leaf angle and leaf area at leaf- and at canopy-level (leaf area index, LAI), all determined at different points of the crop growth cycle (seventh-leaf, V7, flowering, and physiological maturity). Furthermore, duration of the vegetative and reproductive phases were also recorded as days to flowering, and days to maturity. A conditional decision tree analysis was employed to cluster the hybrids according to their variation in canopy characteristics and impact on yield. In summary, end of season LAI (at physiological maturity) was one of the most relevant plant canopy traits to group the hybrids and it accounted for ~70% of the variation. Hybrids with high LAI at V7 and low LAI at maturity, in addition to their longer time to maturity, presented greater yields. These findings can lead to future investigation using the same traits under different climatic conditions