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API Development Increases Access to Shared Computing Resources at Boston University

Journal of Software Engineering and Applications 2022年第6期15卷 197-207页

作者： George Jones Amanda E. Wakefield Jeff Triplett Kojo Idrissa james goebel Dima Kozakov Sandor Vajda Department of Applied Mathematics and Statistics Stony Brook University Stony Brook USA Department of Chemistry Boston University Boston USA Department of Biomedical Engineering Boston University Boston USA Revolution Systems LLC. Lawrance USA College of Engineering Boston University Boston USA

Within the last few decades, increases in computational resources have contributed enormously to the progress of science and engineering (S & E). To continue making rapid advancements, the S & E community must be able to access computing resources. One way to provide such resources is through High-Performance Computing (HPC) centers. Many academic research institutions offer their own HPC Centers but struggle to make the computing resources easily accessible and user-friendly. Here we present SHABU, a RESTful Web API framework that enables S & E communities to access resources from Boston University’s Shared Computing Center (SCC). The SHABU requirements are derived from the use cases described in this work.

关键词： API Framework Open Source High-Performance Computing Software Architecture Science and Engineering

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Annual Rainfall and Dryland Cotton Lint Yield—Southern High Plains of Texas

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Agricultural Sciences 2022年第2期13卷 177-200页

作者： Robert J. Lascano Paxton Payton james R. Mahan Timothy S. goebel Dennis C. Gitz III Wind Erosion and Water Conservation Research Unit USDA-ARS Lubbock TX USA Plant Stress and Germplasm Development Research Unit USDA-ARS Lubbock TX USA

Agriculture in the Texas High Plains (THP) is in a transition phase of producing crops with a diminishing supply of irrigation-water from the Ogallala aquifer to dryland production systems. This shift is driven by the fact that the depth to the water table of the Ogallala aquifer continues to increase. Dryland cotton production systems are prevalent in the southern counties of the THP and our purpose was to use the long-term dryland cotton lint yields from these counties as precursors of the future cotton production patterns that will emerge in this region. For this purpose, from 1972 to 2018, we calculated the ratio of dryland cotton lint yield per unit of annual rainfall at the county level. This ratio is called crop water productivity (CWP) and has units of mass per unit volume (g/m3). In our analysis, we used cotton lint yield data provided by the National Agricultural Statistics and rainfall data provided by the National Oceanic and Atmospheric Administration. Our results indicated that the three datasets used in our analysis, i.e., cotton lint yield, rainfall and CWP were all normally distributed. In this time period, 1972 to 2018, only one year 2011—a year with a record drought of 179 mm of rain failed to produce a dryland cotton crop in all the counties used in our analysis. The mean cotton lint yield ± standard deviation ranged from a high of 400 ± 175 kg/ha in Lubbock County to a low of 252 ± 144 kg/ha in Andrews County. However, the counties with the largest CWP > 90 g/m3 were Glasscock, Midland and Martin County. The importance of this result is that these counties are in the southern region of the THP and are subject to extreme environmental conditions and yet cotton producers manage to produce a cotton crop in most years. We conclude that management production methods used by these dryland producers represent the future schemes that will need to be adopted in other counties to sustain the emerging dryland cropping systems across the THP.

关键词： Crop Water Productivity Cotton Cropping Systems Crop Management Rainfed Ogallala Aquifer Water Use Efficiency

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Measurement of Cotton Transpiration

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Agricultural Sciences 2018年第10期9卷 1299-1316页

作者： Robert J. Lascano Jeffery T. Baker Paxton Payton Dennis C. Gitz III james R. Mahan Timothy S. goebel Wind Erosion and Water Conservation Research Cropping Systems Research Laboratory USDA-ARS Lubbock TX USA Plant Stress Germplasm Development Research Cropping Systems Research Laboratory USDA-ARS Lubbock TX USA

There are a few field methods available to directly measure water evapotranspiration (ET) along with its two components, evaporation from the soil (E) and from the crop (T). One such technique that measures T, uses sensors to calculate the sap flow (F) of water through the plant stem and is based on the conservation of mass and energy, i.e., the stem heat balance method. This instrument consists of a flexible heater that is wrapped around the plant stem with temperature sensors to measure the difference in temperature of F below and above the heater. This is a null method, where all inputs and outputs are known and the calculated F is a direct measure of T. This method has been used to measure T in a variety of crops, including cotton, grapes, olive trees, soybean, ornamental and horticultural crops. A new version of the EXO-SkinTM is the Stem Gauge Dual Channel Design (SGDCTM), which was commercially introduced and had a radically new design resulting in a different energy balance, compared to the original design, which needed experimental verification. An initial evaluation was done with potted cotton (Gossypium hirsutum, L.) plants in a greenhouse experiment showing that values of cotton-T measured with the new sensor were accurate;however, this comparison was limited to daily T T in the 2 - 7 mm/d range, representative of the semiarid Texas High Plains. For this purpose, cotton was planted on 12 June 2017 on a 1000 m2 plot in a soil classified in the Amarillo series at the facilities of the USDA-ARS, Lubbock, TX. For a period of 15 days, 2 to 16 Sep 2017, we measured hourly cotton-T with the new sensors and with portable growth chambers (0.75 m × 1 m cross-section, and 1 m height) where water vapor flux was measured at a 10 Hz frequency using an infrared gas analyzer. We used three chambers and, in each chamber, the new sensors were installed on four cotton plants. We used linear regression analysis to compare hourly and daily values of cotton-T measured with the sap flow gauges against T measured by the cham

关键词： Stem Flow Gauge Growth Chamber Water Use Irrigation Evaporation Field Test

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