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To provide several comparisons between linear and nonlinear approaches in denoising applications.

The comparison is based on the peak signal noise ratio (PSNR) image quality measure. Which one of the algorithms gives higher PSNR and then denoises more the original picture is studied.

Nonlinear reconstruction operators can improve the accuracy of the prediction in the vicinity of isolated singularities. A better treatment of the singularities corresponding to the image edges and, therefore, an improvement on the sparsity of the multiresolution representation of images are then expected.

In this paper the point‐value framework is considered. Other frameworks, as the cell‐average discretization, are more suitable for image processing where noise and texture appear. But, the point value schemes can be adapted to the cell‐average discretization using primitive function.

People can use the new denoising algorithm presented in the paper.

In this paper nonlinear schemes in the Harten's multiresolution framework that improve the results of the classical linear schemes are presented.

Multiresolution representations of data are classical tools in image processing applications. The purpose of this paper is to discuss a particular problem, obtaining good reconstructions of noise images.

A nonlinear multiresolution scheme within Harten's framework corresponding to a nonlinear cell‐average technique is used for color image denoising.

This paper finds it is possible, for example, to apply the theoretical framework to case studies in internationally operating companies delivering a mix of goods and services.

The present study provides a starting point for further research in the denoising problems using nonlinear techniques.

Moreover, the proposed framework has proven to be useful in improving the classical linear multiresolution approaches.

The purpose of this paper is to study the case of Chile and identify the internal factors that lead to senior (+55 years old) entrepreneurship, either by necessity or opportunity, compared to that in other age groups.

The analysis is based on the adult population survey of the global entrepreneurship monitor between 2012 and 2016 and uses a logistic regression model that applies different variables to total early-stage entrepreneurial activity by necessity and opportunity.

Education, human and social capital development, gender and prior experience as an entrepreneur are internal factors that affect entrepreneurial activity with different weights and directions for people over 55 years old in Chile, either by necessity or opportunity. Further, certain factors exhibited by other age groups in the country explain entrepreneurship.

This study does not consider external perspectives on how context influences entrepreneurial intentions.

This paper represents a first step to understanding the factors that governments should consider when designing policies to support entrepreneurial activity in the senior demographic sector, considering differences in motivation by necessity or opportunity. In addition, this study contributes to the development of knowledge regarding senior entrepreneurship in Chile and to the identification of best practices that could be used in other regions.

This report is the first to focus on the motivations of senior entrepreneurs in Chile by quantifying the effects of different factors.

The innovation process demands an interaction between environment agents, knowledge generators and policies of incentive for innovation and not only development by companies. Universities have gradually become the core of the knowledge production system and, therefore, their role regarding innovation has become more important and diversified. This study is aimed at identifying the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.

This study is aimed at identifying, based on a systematic literature review, the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.

The analysis of the 72 selected articles enabled identifying 15 mechanisms of U–I collaboration, proposing a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process.

In this paper, the authors screened nearly 1,500 papers and analyzed in detail 86 papers addressing U–I collaboration, mechanisms of U–I collaboration and operationalization steps of the U–I collaboration process. This paper provides a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process. This research contributes to both theory and practice by highlighting managerial aspects and stimulating academic research on such timely topic.