471 research outputs found

    Maximum modulus, maximum term and interpolation error of an entire function

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    No Abstract. SINET: Ethiopian Journal of Science Vol. 29(1) 2006: 81–8

    Big Data analytics to transform agriculture: Experience and progress

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    Prevention of bone mineral changes induced by bed rest: Modification by static compression simulating weight bearing, combined supplementation of oral calcium and phosphate, calcitonin injections, oscillating compression, the oral diophosphonatedisodium etidronate, and lower body negative pressure

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    The phenomenon of calcium loss during bed rest was found to be analogous to the loss of bone material which occurs in the hypogravic environment of space flight. Ways of preventing this occurrence are investigated. A group of healthy adult males underwent 24-30 weeks of continuous bed rest. Some of them were given an exercise program designed to resemble normal ambulatory activity; another subgroup was fed supplemental potassium phosphate. The results from a 12-week period of treatment were compared with those untreated bed rest periods. The potassium phosphate supplements prevented the hypercalciuria of bed rest, but fecal calcium tended to increase. The exercise program did not diminish the negative calcium balance. Neither treatment affected the heavy loss of mineral from the calcaneus. Several additional studies are developed to examine the problem further

    Investigations into free tropospheric new particle formation in the central Canadian arctic during the winter/spring transition as part of TOPSE

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    In this paper, we investigate the role of in situ new particle production in the central Canadian sub-Arctic and Arctic as part of the TOPSE experiment. Airborne measurements conducted primarily in the free troposphere were made from 50° to 90°W longitude and 60° to 85°N latitude during the period from February to May 2000. Data pertinent to this paper include 3–4 nm diameter (Dp) particles, ultrafine condensation nuclei (Dp \u3e 3 nm), fine particles (0.2 \u3c Dp \u3c 3 μm), and the possible nucleation precursor, sulfuric acid, and its precursor, sulfur dioxide. For data averaged over this period, most species showed little evidence for a latitudinal trend. Fine aerosol number concentrations, however, showed a slight increase with latitude. The evolution of various species concentrations over the period of the study show that fine particles also had a consistent temporal trend, increasing at all altitudes from February to May, whereas sulfur dioxide at the surface tended to peak in late March. Ultrafine condensation nuclei and 3–4 nm particles showed no temporal trends. Little evidence for in situ new particle production was observed during the study, except for one atypical event where SO2concentrations were 3.5 ppbv, 2 orders of magnitude higher than typical levels. This paper cannot address the question of whether the observed condensation nuclei were produced in situ by a low particle production rate or transported from lower latitudes

    Python Climate Predictability Tool (PyCPT) training for improved seasonal climate prediction over Ethiopia

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    Training on weather forecasting tools and techniques is a fundamental requirement for meteorological services to improve the accuracy and reliability of weather and climate forecasts. These tools greatly support the generation and packaging of forecasts that are destined for private and public consumption. Ethiopia's National Meteorological Agency (NMA), under the support of the International Research Institute for Climate and Society (IRI), through the project Adapting Agriculture to Climate Today, for Tomorrow (ACToday), is working together with the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) - East Africa (EA) to address the needs and demands of different stakeholders including governmental, non-governmental organizations and other non-state actors by conducting staff training to improve the generation of reliable, timely and accurate weather and seasonal forecasts. With the support of the IRI and CCAFS - EA, training on the Next Generation (NextGen) seasonal forecasting was given from January 11-15, 2021, to 26 participants from the National Metrological Agency of Ethiopia (NMA). Participants were selected from NMA's Regional Meteorological Service Centers (RMSC's) and NMA head office. The Next Generation (NextGen) multi-model approach is a general systematic approach for designing, implementing, producing, and verifying objective climate forecasts. It involves identifying decision-relevant variables by stakeholders and analyzing the physical mechanisms, sources of predictability, and suitable candidate predictors (in models and observations) for key relevant variables. When prediction skill is high enough, NextGen helps select the best dynamic models for the region of interest through a process-based evaluation and automizes the generation and verification of tailored multi-model, statistically calibrated predictions at seasonal and sub-seasonal timescales
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