176 research outputs found
Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland
Present study deals with the mean monthly total ozone time series over Arosa,
Switzerland. The study period is 1932-1971. First of all, the total ozone time
series has been identified as a complex system and then Artificial Neural
Networks models in the form of Multilayer Perceptron with back propagation
learning have been developed. The models are Single-hidden-layer and
Two-hidden-layer Perceptrons with sigmoid activation function. After sequential
learning with learning rate 0.9 the peak total ozone period (February-May)
concentrations of mean monthly total ozone have been predicted by the two
neural net models. After training and validation, both of the models are found
skillful. But, Two-hidden-layer Perceptron is found to be more adroit in
predicting the mean monthly total ozone concentrations over the aforesaid
period.Comment: 22 pages, 14 figure
The CLIVAR C20C Project: Which components of the Asian-Australian monsoon circulation variations are forced and reproducible?
A multi-model set of atmospheric simulations forced by historical sea surface
temperature (SST) or SSTs plus Greenhouse gases and aerosol forcing agents for the
period of 1950-1999 is studied to identify and understand which components of the
Asian-Australian monsoon (A-AM) variability are forced and reproducible. The
analysis focuses on the summertime monsoon circulations, comparing model results
against the observations. The priority of different components of the A-AM
circulations in terms of reproducibility is evaluated. Among the subsystems of the
wide A-AM, the South Asian monsoon and the Australian monsoon circulations are
better reproduced than the others, indicating they are forced and well modeled. The
primary driving mechanism comes from the tropical Pacific. The western North
Pacific monsoon circulation is also forced and well modeled except with a slightly
lower reproducibility due to its delayed response to the eastern tropical Pacific
forcing. The simultaneous driving comes from the western Pacific surrounding the
maritime continent region. The Indian monsoon circulation has a moderate
reproducibility, partly due to its weakened connection to June-July-August SSTs in
the equatorial eastern Pacific in recent decades. Among the A-AM subsystems, the
East Asian summer monsoon has the lowest reproducibility and is poorly modeled.
This is mainly due to the failure of specifying historical SST in capturing the zonal
land-sea thermal contrast change across the East Asia. The prescribed tropical
Indian Ocean SST changes partly reproduce the meridional wind change over East
Asia in several models. For all the A-AM subsystem circulation indices, generally
the MME is always the best except for the Indian monsoon and East Asian monsoon
circulation indices
The CLIVAR C20C Project: Which components of the Asian-Australian monsoon circulation variations are forced and reproducible?
A multi-model set of atmospheric simulations forced by historical sea surface
temperature (SST) or SSTs plus Greenhouse gases and aerosol forcing agents for the
period of 1950-1999 is studied to identify and understand which components of the
Asian-Australian monsoon (A-AM) variability are forced and reproducible. The
analysis focuses on the summertime monsoon circulations, comparing model results
against the observations. The priority of different components of the A-AM
circulations in terms of reproducibility is evaluated. Among the subsystems of the
wide A-AM, the South Asian monsoon and the Australian monsoon circulations are
better reproduced than the others, indicating they are forced and well modeled. The
primary driving mechanism comes from the tropical Pacific. The western North
Pacific monsoon circulation is also forced and well modeled except with a slightly
lower reproducibility due to its delayed response to the eastern tropical Pacific
forcing. The simultaneous driving comes from the western Pacific surrounding the
maritime continent region. The Indian monsoon circulation has a moderate
reproducibility, partly due to its weakened connection to June-July-August SSTs in
the equatorial eastern Pacific in recent decades. Among the A-AM subsystems, the
East Asian summer monsoon has the lowest reproducibility and is poorly modeled.
This is mainly due to the failure of specifying historical SST in capturing the zonal
land-sea thermal contrast change across the East Asia. The prescribed tropical
Indian Ocean SST changes partly reproduce the meridional wind change over East
Asia in several models. For all the A-AM subsystem circulation indices, generally
the MME is always the best except for the Indian monsoon and East Asian monsoon
circulation indices.Submitted3.7. Dinamica del clima e dell'oceanoJCR Journalope
The CLIVAR C20C Project: Which components of the Asian-Australian monsoon circulation variations are forced and reproducible?
A multi-model set of atmospheric simulations forced by historical sea surface temperature (SST) or SSTs plus Greenhouse gases and aerosol forcing agents for the period of 1950–1999 is studied to identify and understand which components of the Asian–Australian monsoon (A–AM) variability are forced and reproducible. The analysis focuses on the summertime monsoon circulations, comparing model results against the observations. The priority of different components of the A–AM circulations in terms of reproducibility is evaluated. Among the subsystems of the wide A–AM, the South Asian monsoon and the Australian monsoon circulations are better reproduced than the others, indicating they are forced and well modeled. The primary driving mechanism comes from the tropical Pacific. The western North Pacific monsoon circulation is also forced and well modeled except with a slightly lower reproducibility due to its delayed response to the eastern tropical Pacific forcing. The simultaneous driving comes from the western Pacific surrounding the maritime continent region. The Indian monsoon circulation has a moderate reproducibility, partly due to its weakened connection to June–July–August SSTs in the equatorial eastern Pacific in recent decades. Among the A–AM subsystems, the East Asian summer monsoon has the lowest reproducibility and is poorly modeled. This is mainly due to the failure of specifying historical SST in capturing the zonal land-sea thermal contrast change across the East Asia. The prescribed tropical Indian Ocean SST changes partly reproduce the meridional wind change over East Asia in several models. For all the A–AM subsystem circulation indices, generally the MME is always the best except for the Indian monsoon and East Asian monsoon circulation indices
A Framework to Support Interdisciplinary Engagement with Learning Analytics
Learning analytics can provide an excellent opportunity for instructors to get an in-depth understanding of students’ learning experiences in a course. However, certain technological challenges, namely limited availability of learning analytics data because of learning management system restrictions, can make accessing this data seem impossible at some institutions. Furthermore, even in cases where instructors have access to a range of student data, there may not be organized efforts to support students across various courses and university experiences. In the current chapter, the authors discuss the issue of learning analytics access and ways to leverage learning analytics data between instructors, and in some cases administrators, to create interdisciplinary opportunities for comprehensive student support. The authors consider the implications of these interactions for students, instructors, and administrators. Additionally, the authors focus on some of the technological infrastructure issues involved with accessing learning analytics and discuss the opportunities available for faculty and staff to take a multi-pronged approach to addressing overall student success.https://scholarworks.wm.edu/educationbookchapters/1045/thumbnail.jp
Sarilumab in patients admitted to hospital with severe or critical COVID-19: a randomised, double-blind, placebo-controlled, phase 3 trial
Background: Elevated proinflammatory cytokines are associated with greater COVID-19 severity. We aimed to assess safety and efficacy of sarilumab, an interleukin-6 receptor inhibitor, in patients with severe (requiring supplemental oxygen by nasal cannula or face mask) or critical (requiring greater supplemental oxygen, mechanical ventilation, or extracorporeal support) COVID-19. Methods: We did a 60-day, randomised, double-blind, placebo-controlled, multinational phase 3 trial at 45 hospitals in Argentina, Brazil, Canada, Chile, France, Germany, Israel, Italy, Japan, Russia, and Spain. We included adults (≥18 years) admitted to hospital with laboratory-confirmed SARS-CoV-2 infection and pneumonia, who required oxygen supplementation or intensive care. Patients were randomly assigned (2:2:1 with permuted blocks of five) to receive intravenous sarilumab 400 mg, sarilumab 200 mg, or placebo. Patients, care providers, outcome assessors, and investigators remained masked to assigned intervention throughout the course of the study. The primary endpoint was time to clinical improvement of two or more points (seven point scale ranging from 1 [death] to 7 [discharged from hospital]) in the modified intention-to-treat population. The key secondary endpoint was proportion of patients alive at day 29. Safety outcomes included adverse events and laboratory assessments. This study is registered with ClinicalTrials.gov, NCT04327388; EudraCT, 2020-001162-12; and WHO, U1111-1249-6021. Findings: Between March 28 and July 3, 2020, of 431 patients who were screened, 420 patients were randomly assigned and 416 received placebo (n=84 [20%]), sarilumab 200 mg (n=159 [38%]), or sarilumab 400 mg (n=173 [42%]). At day 29, no significant differences were seen in median time to an improvement of two or more points between placebo (12·0 days [95% CI 9·0 to 15·0]) and sarilumab 200 mg (10·0 days [9·0 to 12·0]; hazard ratio [HR] 1·03 [95% CI 0·75 to 1·40]; log-rank p=0·96) or sarilumab 400 mg (10·0 days [9·0 to 13·0]; HR 1·14 [95% CI 0·84 to 1·54]; log-rank p=0·34), or in proportions of patients alive (77 [92%] of 84 patients in the placebo group; 143 [90%] of 159 patients in the sarilumab 200 mg group; difference −1·7 [−9·3 to 5·8]; p=0·63 vs placebo; and 159 [92%] of 173 patients in the sarilumab 400 mg group; difference 0·2 [−6·9 to 7·4]; p=0·85 vs placebo). At day 29, there were numerical, non-significant survival differences between sarilumab 400 mg (88%) and placebo (79%; difference +8·9% [95% CI −7·7 to 25·5]; p=0·25) for patients who had critical disease. No unexpected safety signals were seen. The rates of treatment-emergent adverse events were 65% (55 of 84) in the placebo group, 65% (103 of 159) in the sarilumab 200 mg group, and 70% (121 of 173) in the sarilumab 400 mg group, and of those leading to death 11% (nine of 84) were in the placebo group, 11% (17 of 159) were in the sarilumab 200 mg group, and 10% (18 of 173) were in the sarilumab 400 mg group. Interpretation: This trial did not show efficacy of sarilumab in patients admitted to hospital with COVID-19 and receiving supplemental oxygen. Adequately powered trials of targeted immunomodulatory therapies assessing survival as a primary endpoint are suggested in patients with critical COVID-19. Funding: Sanofi and Regeneron Pharmaceuticals
Towards an integrated set of surface meteorological observations for climate science and applications
Observations are the foundation for understanding the climate system. Yet, currently available land meteorological data are highly fractured into various global, regional and national holdings for different variables and timescales, from a variety of sources, and in a mixture of formats. Added to this, many data are still inaccessible for analysis and usage. To meet modern scientific and societal demands as well as emerging needs such as the provision of climate services, it is essential that we improve the management and curation of available land-based meteorological holdings. We need a comprehensive global set of data holdings, of known provenance, that is truly integrated both across Essential Climate Variables (ECVs) and across timescales to meet the broad range of stakeholder needs. These holdings must be easily discoverable, made available in accessible formats, and backed up by multi-tiered user support. The present paper provides a high level overview, based upon broad community input, of the steps that are required to bring about this integration. The significant challenge is to find a sustained means to realize this vision. This requires a long-term international program. The database that results will transform our collective ability to provide societally relevant research, analysis and predictions in many weather and climate related application areas across much of the globe
Development of knowledge about Septoria nodorum Berk. with regard to breeding wheat for tolerance or resistance. [German]
This review of work on S. nodorum [Leptosphaeria nodorum] is presented under the following headings: (1) history, (2) epidemiology, (3) symptomatology and damage, (4) selection methods and variety testing, (5) genetic basis of tolerance, (6) breeding methods and (7) the assessment of the current state of Septoria prevention and of the prospects for further advances. The contribution of the late W. Feekes to this subject is emphasized. (Abstract retrieved from CAB Abstracts by CABI’s permission
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