A Turbulent Heating Model Combining Diffusion and Advection Effects for Giant Planet Magnetospheres

In recent years, the increasing rate of road crashes involving cyclists with a disproportionate overrepresentation in injury statistics has become a major concern in road safety and public health. However, much remains unknown about factors contributing to cyclists’ high crash rates, especially those related to personal characteristics. This study aims to explore the influence of cyclist personality traits and cycling behaviors on their road safety outcomes using a mediated model combining these constructs. A total of 628 cyclists completed an online questionnaire consisting of questions related to cycling anger, impulsiveness, normlessness, sensation seeking, risky cycling behaviors, and involvement in crash-related conditions in the past year. After the psychometric properties of the employed scales were examined, the relationships among the tested constructs were investigated using structural equation modeling. The results showed that cyclists’ crash risks were directly predicted by risky cycling behaviors and cycling anger, and the effects of cycling anger, impulsiveness, as well as normlessness on crash risks, were mediated by cycling behaviors. The current findings provide insight into the importance of personality traits in impacting cycling safety and could facilitate the development of evidence-based prevention and promotion strategies targeting cyclists in China.

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Giant planet formation with pebble accretion

Icarus ◽

10.1016/j.icarus.2014.01.036 ◽

2014 ◽

Vol 233 ◽

pp. 83-100 ◽

Cited By ~ 40

Author(s):

J.E. Chambers

Keyword(s):

Planet Formation ◽

Giant Planet

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AMBITION – comet nucleus cryogenic sample return

Experimental Astronomy ◽

10.1007/s10686-021-09770-4 ◽

2021 ◽

Author(s):

D. Bockelée-Morvan ◽

Gianrico Filacchione ◽

Kathrin Altwegg ◽

Eleonora Bianchi ◽

Martin Bizzarro ◽

...

Keyword(s):

Giant Planet ◽

Building Blocks ◽

Cometary Nucleus ◽

Comet Nucleus ◽

Surface Layers ◽

International Context ◽

Rosetta Mission ◽

Nucleus Surface ◽

And Storage ◽

Scientific Questions

AbstractWe describe the AMBITION project, a mission to return the first-ever cryogenically-stored sample of a cometary nucleus, that has been proposed for the ESA Science Programme Voyage 2050. Comets are the leftover building blocks of giant planet cores and other planetary bodies, and fingerprints of Solar System’s formation processes. We summarise some of the most important questions still open in cometary science and Solar System formation after the successful Rosetta mission. We show that many of these scientific questions require sample analysis using techniques that are only possible in laboratories on Earth. We summarize measurements, instrumentation and mission scenarios that can address these questions. We emphasize the need for returning a sample collected at depth or, still more challenging, at cryogenic temperatures while preserving the stratigraphy of the comet nucleus surface layers. We provide requirements for the next generation of landers, for cryogenic sample acquisition and storage during the return to Earth. Rendezvous missions to the main belt comets and Centaurs, expanding our knowledge by exploring new classes of comets, are also discussed. The AMBITION project is discussed in the international context of comet and asteroid space exploration.

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Improved Hough Transform and Total Variation Algorithms for Features Extraction of Wood

Forests ◽

10.3390/f12040466 ◽

2021 ◽

Vol 12 (4) ◽

pp. 466

Author(s):

Weiwei Du ◽

Yarui Xi ◽

Kiichi Harada ◽

Yumei Zhang ◽

Keiko Nagashima ◽

...

Keyword(s):

Total Variation ◽

Hough Transform ◽

Annual Ring ◽

Wood Quality ◽

Volume Density ◽

Low Noise ◽

Impact Factors ◽

Annual Rings ◽

New Model ◽

Model Combining

Research shows that the intensity impact factors of wood, such as late timber ratio, volume density and the intensity of itself, correlate with the width of wood annual rings. Therefore, extracting wood annual ring information from wood images is helpful for evaluating wood quality. During the past few years, many researchers have conducted defect detection by studying the information of wood images. However, there are few in-depth studies on the statistics and calculation of wood annual ring information. This study proposes a new model combining the Total Variation (TV) algorithm and the improved Hough transform to accurately measure the wood annual ring information. The TV algorithm is used to suppress image noise, and the Hough transform is for detecting the center of the wood image. Moreover, the edges of wood annual rings are extracted, and the statistical ring information is calculated. The experimental results show that the new model has good denoising capability, clearly extract the edges of wood annual rings and calculate the related parameters from the indoor wood images of the processed logs and the unprocessed low-noise logs.

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Decoupled Metric Learning Model combining Tag Information for Recommendation

2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI) ◽

10.1109/mlbdbi51377.2020.00093 ◽

2020 ◽

Author(s):

YanJun Wang ◽

Yan Tang ◽

Qiang Chen

Keyword(s):

Metric Learning ◽

Learning Model ◽

Model Combining

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Application of an Innovative Model for the Risk Management of COVID-19 in a Multinational Manufacturing Company

Sustainability ◽

10.3390/su13115771 ◽

2021 ◽

Vol 13 (11) ◽

pp. 5771

Author(s):

Piero Lovreglio ◽

Angela Stufano ◽

Francesco Cagnazzo ◽

Nicola Bartolomeo ◽

Ivo Iavicoli

Keyword(s):

Risk Management ◽

Manufacturing Industry ◽

Incidence Rates ◽

Manufacturing Plants ◽

Model Combining ◽

Innovative Model ◽

Global Prevention ◽

The Relationship ◽

Physician Team ◽

The Eu

The COVID-19 incidence in 61 manufacturing plants in Europe (EU), North America (NA) and Latin-America (LATAM) was compared with the incidence observed in the countries where the plants are located in order to evaluate the application of an innovative model for COVID-19 risk management. Firstly, a network of local and global teams was created, including an external university occupational physician team for scientific support. In July 2020, global prevention guidelines for the homogenous management of the pandemic were applied, replacing different site or regional procedures. A tool for COVID-19 monitoring was implemented to investigate the relationship between the incidence rates inside and outside the plants. In the period of May–November 2020, 565 confirmed cases (EU 330, NA 141, LATAM 94) were observed among 20,646 workers with different jobs and tasks, and in the last two months 85% EU and 70% NA cases were recorded. Only in 10% of cases was a possible internal origin of the contagion not excluded. In the EU and NA, unlike LATAM, the COVID-19 incidence rates inside the sites punctually followed the rising trend outside. In conclusion, the model, combining a global approach with the local application of the measures, maintains the sustainability in the manufacturing industry.

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Developing a Fuzzy TOPSIS Model Combining MACBETH and Fuzzy Shannon Entropy to Select a Gamification App

Mathematics ◽

10.3390/math9091034 ◽

2021 ◽

Vol 9 (9) ◽

pp. 1034

Author(s):

María Carmen Carnero

Keyword(s):

Shannon Entropy ◽

Fuzzy Topsis ◽

Preference Ranking ◽

Promethee Ii ◽

Ciudad Real ◽

Industrial Manufacturing ◽

Model Combining ◽

La Mancha ◽

University Course ◽

The University

Due to the important advantages it offers, gamification is one of the fastest-growing industries in the world, and interest from the market and from users continues to grow. This has led to the development of more and more applications aimed at different fields, and in particular the education sector. Choosing the most suitable application is increasingly difficult, and so to solve this problem, our study designed a model which is an innovative combination of fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) and Shannon entropy theory, to choose the most suitable gamification application for the Industrial Manufacturing and Organisation Systems course in the degree programmes for Electrical Engineering and Industrial and Automatic Electronics at the Higher Technical School of Industrial Engineering of Ciudad Real, part of the University of Castilla-La Mancha. There is no precedent in the literature that combines MACBETH and fuzzy Shannon entropy to simultaneously consider the subjective and objective weights of criteria to achieve a more accurate model. The objective weights computed from fuzzy Shannon entropy were compared with those calculated from De Luca and Termini entropy and exponential entropy. The validity of the proposed method is tested through the Preference Ranking Organisation METHod for Enrichment of Evaluations (PROMETHEE) II, ELimination and Choice Expressing REality (ELECTRE) III, and fuzzy VIKOR method (VIsekriterijumska optimizacija i KOmpromisno Resenje). The results show that Quizizz is the best option for this course, and it was used in two academic years. There are no precedents in the literature using fuzzy multicriteria decision analysis techniques to select the most suitable gamification application for a degree-level university course.

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A predictable smoothing evolution model for computer-controlled polishing

Journal of the European Optical Society Rapid Publications ◽

10.1186/s41476-020-00145-4 ◽

2020 ◽

Vol 16 (1) ◽

Author(s):

Jing Hou ◽

Pengli Lei ◽

Shiwei Liu ◽

Xianhua Chen ◽

Jian Wang ◽

...

Keyword(s):

Evolution Model ◽

Quantitative Prediction ◽

Theoretical Support ◽

Model Combining ◽

Process Guidance ◽

Dependent Model ◽

Computer Controlled Optical Surfacing ◽

Computer Controlled ◽

Time Dependent Model ◽

Selection Of

AbstractQuantitative prediction of the smoothing of mid-spatial frequency errors (MSFE) is urgently needed to realize process guidance for computer controlled optical surfacing (CCOS) rather than a qualitative analysis of the processing results. Consequently, a predictable time-dependent model combining process parameters and an error decreasing factor (EDF) were presented in this paper. The basic smoothing theory, solution method and modification of this model were expounded separately and verified by experiments. The experimental results show that the theoretical predicted curve agrees well with the actual smoothing effect. The smoothing evolution model provides certain theoretical support and guidance for the quantitative prediction and parameter selection of the smoothing of MSFE.

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