Equal Weight Quadrature on Infinite Intervals

1971 ◽  
Vol 8 (1) ◽  
pp. 75-79 ◽  
Author(s):  
David Kahaner ◽  
J. L. Ullman
Keyword(s):  
Equal Weight ◽  
Infinite Intervals ◽  
Weight Quadrature

Effects of compression during formation on the microstructure of composite hydroxylapatite/plaster implants for bone reconstruction

1988 ◽  
Vol 46 ◽  
pp. 750-751
Author(s):  
J. Hanker ◽  
K. Cowden ◽  
R. Noecker ◽  
P. Yates ◽  
N. Georgiade ◽  
...  
Keyword(s):  
Cosmetic Surgery ◽  
Glass Plate ◽  
Surgical Reconstruction ◽  
Equal Weight ◽  
Sintered Ceramic ◽  
Setting Times ◽  
Excess Water ◽  
Mixture Prior ◽  
Mechanical Strengths ◽  
Calcium Sulfate Hemihydrate

Composites of plaster of Paris (PP) and hydroxylapatite (HA) particles are being applied for the surgical reconstruction of craniofacial bone defects and for cosmetic surgery. Two types of HA particles are being employed, the dense sintered ceramic (DHA) and the porous, coralline hydroxylapatite (PHA) particles. Excess water is expressed out of the moistened HA/PP mixture prior to implantation and setting by pressing it in a non-tapered syringe against a glass plate. This results in implants with faster setting times and greater mechanical strengths. It was therefore of interest to compare samples of the compressed versus noncompressed mixtures to see whether or not any changes in their microstructure after setting could be related to these different properties.USG Medical Grade Calcium Sulfate Hemihydrate (which has the lowest mortar consistency of any known plaster) was mixed with an equal weight of Interpore 200 particles (a commercial form of PHA). After moistening with a minimum amount of water, disc-shaped noncompressed samples were made by filling small holes (0.339 in. diameter x 0.053 in. deep) in polypropylene molds with a microspatula.

CHASSIS DESIGN & PERFORMANCE ANALYSIS FOR THE EUROPEAN EXOMARS ROVER

2005 ◽  
Vol 29 (4) ◽  
pp. 507-517
Author(s):  
Alex Ellery ◽  
Lutz Richter ◽  
Reinhold Bertrand
Keyword(s):  
Performance Analysis ◽  
Weight Distribution ◽  
High Performance ◽  
High Mobility ◽  
Scientific Instrument ◽  
Equal Weight ◽  
Scientific Instruments ◽  
Design Issues ◽  
Martian Surface ◽  
Considerable Size

The European Space Agency’s (ESA) ExoMars rover has recently been subject to a Phase A study led by EADS Astrium, UK. This rover mission represents a highly ambitious venture in that the rover is of considerable size ~200+kg with high mobility carrying a highly complex scientific instrument suite (Pasteur) of up to 40 kg in mass devoted to exobiological investigation of the Martian surface and sub-surface. The chassis design has been a particular challenge given the inhospitable terrain on Mars and the need to traverse such terrain robustly in order to deliver the scientific instruments to science targets of exobiological interest, We present some of the results and design issues encountered during the Phase A study related to the chassis. In particular, we have focussed on the overall tractive performance of a number of candidate chassis designs and selected the RCL (Science & Technology Rover Company Ltd in Russian) concept C design as the baseline option in terms of high performance with minimal mechanical complexity overhead. This design is a six-wheeled double-rocker bogie design to provide springless suspension and maintain approximately equal weight distribution across each wheel.

scholarly journals A susceptibility-based rainfall threshold approach for landslide occurrence

2019 ◽  
Vol 19 (4) ◽  
pp. 775-789 ◽  
Author(s):  
Elise Monsieurs ◽  
Olivier Dewitte ◽  
Alain Demoulin
Keyword(s):  
Landslide Susceptibility ◽  
Rainfall Threshold ◽  
Exceedance Probability ◽  
Equal Weight ◽  
Antecedent Rainfall ◽  
Rainfall Thresholds ◽  
Landslide Occurrence ◽  
Continental Scale ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Abstract. Rainfall threshold determination is a pressing issue in the landslide scientific community. While major improvements have been made towards more reproducible techniques for the identification of triggering conditions for landsliding, the now well-established rainfall intensity or event-duration thresholds for landsliding suffer from several limitations. Here, we propose a new approach of the frequentist method for threshold definition based on satellite-derived antecedent rainfall estimates directly coupled with landslide susceptibility data. Adopting a bootstrap statistical technique for the identification of threshold uncertainties at different exceedance probability levels, it results in thresholds expressed as AR = (α±Δα)⋅S(β±Δβ), where AR is antecedent rainfall (mm), S is landslide susceptibility, α and β are scaling parameters, and Δα and Δβ are their uncertainties. The main improvements of this approach consist in (1) using spatially continuous satellite rainfall data, (2) giving equal weight to rainfall characteristics and ground susceptibility factors in the definition of spatially varying rainfall thresholds, (3) proposing an exponential antecedent rainfall function that involves past daily rainfall in the exponent to account for the different lasting effect of large versus small rainfall, (4) quantitatively exploiting the lower parts of the cloud of data points, most meaningful for threshold estimation, and (5) merging the uncertainty on landslide date with the fit uncertainty in a single error estimation. We apply our approach in the western branch of the East African Rift based on landslides that occurred between 2001 and 2018, satellite rainfall estimates from the Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis (TMPA 3B42 RT), and the continental-scale map of landslide susceptibility of Broeckx et al. (2018) and provide the first regional rainfall thresholds for landsliding in tropical Africa.

A probabilistic epidemiological model

2021 ◽  
Vol 16 (1) ◽  
pp. 15-23
Author(s):  
Hal M. Switkay
Keyword(s):  
United States ◽  
United Kingdom ◽  
United States Of America ◽  
Compartmental Model ◽  
The United States ◽  
Epidemiological Model ◽  
Probabilistic Methods ◽  
Infinite Intervals ◽  
Best Fit ◽  
Family Of Distributions

We construct a model for the progress of the 2020 coronavirus epidemic in the United States of America, using probabilistic methods rather than the traditional compartmental model. We employ the generalized beta family of distributions, including those supported on bounded intervals and those supported on semi-infinite intervals. We compare the best-fit distributions for daily new cases and daily new deaths in America to the corresponding distributions for United Kingdom, Spain, and Italy. We explore how such a model might be justified theoretically in comparison to the apparently more natural compartmental model. We compare forecasts based on these models to observations, and find the forecasts useful in predicting total pandemic deaths.

scholarly journals Potential health impact of increasing adoption of sustainable dietary practices in Sweden

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Emma Patterson ◽  
Patricia Eustachio Colombo ◽  
James Milner ◽  
Rosemary Green ◽  
Liselotte Schäfer Elinder
Keyword(s):  
Health Impact ◽  
Milk Intake ◽  
Processed Meat ◽  
Years Of Life Lost ◽  
Equal Weight ◽  
Dietary Practices ◽  
Swedish Population ◽  
Potential Health ◽  
The Impact ◽  
Red And Processed Meat

Abstract Background An urgent transition to more sustainable diets is necessary for the improvement of human and planetary health. One way to achieve this is for sustainable practices to become mainstream. We estimated the potential health impact of wider adoption of dietary practices deemed by consumers, researchers and stakeholders in Sweden to be niche, sustainable and with the potential to be scaled up. Methods A life table method was used to estimate the impact - changes in years of life lost (YLL) - over periods of 20 and 30 years in the Swedish population had the practices been adopted in 2010–11, when the last national adult dietary survey was conducted. The practices modelled were reducing red and processed meat (by 25, 50 and 100%), and assuming, for each stage, replacement by an equal weight of poultry/fish and vegetables +/− legumes; reducing milk intake (by 25, 50 and 100%); and reducing sugar-sweetened beverage intake (by 25, 50 and 100%). Using population data together with data on cause-specific mortality and relative risks for diet-disease outcomes, impacts were estimated for each scenario separately and in combination, for the outcomes ischaemic heart disease (IHD), ischaemic stroke, diabetes type 2 and colorectal cancer. Results For a “moderate” combination of scenarios (changes at the 50% level), reductions of 513,200 YLL (lower-upper uncertainty estimate 59,400-797,900) could have been achieved over 20 years and 1,148,500 YLL (135,900-1,786,600) over 30 years. The majority (over 90%) of YLLs prevented were related to IHD, and the majority were in men. The singular practice that had the most impact was reducing the intake of red and processed meat and replacing it with a mixture of vegetables and legumes. Reducing milk intake resulted in an increase in YLL, but this was compensated for by other scenarios. Conclusion If these practices were more widely adopted, they would be expected to lead to improvements in public health in Sweden. Over the long term, this would translate to many premature deaths postponed or prevented from a number of chronic diseases, to the benefit of individuals, society, the climate and the economy.

scholarly journals Improving drug safety predictions by reducing poor analytical practices

2020 ◽  
Vol 4 ◽  
pp. 239784732097863
Author(s):  
Stanley E Lazic ◽  
Dominic P Williams
Keyword(s):  
At Risk ◽  
Drug Discovery ◽  
Drug Safety ◽  
Prediction Models ◽  
Predictive Modelling ◽  
Equal Weight ◽  
Negative Consequences ◽  
Preclinical Data ◽  
Safety Pharmacology ◽  
Patients At Risk

Predicting the safety of a drug from preclinical data is a major challenge in drug discovery, and progressing an unsafe compound into the clinic puts patients at risk and wastes resources. In drug safety pharmacology and related fields, methods and analytical decisions known to provide poor predictions are common and include creating arbitrary thresholds, binning continuous values, giving all assays equal weight, and multiple reuse of information. In addition, the metrics used to evaluate models often omit important criteria and models’ performance on new data are often not assessed rigorously. Prediction models with these problems are unlikely to perform well, and published models suffer from many of these issues. We describe these problems in detail, demonstrate their negative consequences, and propose simple solutions that are standard in other disciplines where predictive modelling is used.

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