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The evaluation of novel materials such as the acrylonitrile styrene acrylate (ASA) for tribological and mechanical conditions can provide a structural protection against the environmental and wear effects that results in the long-term integrity of the 3 D printed parts. Results of the experimental stage are intended to identify the influence of the printing conditions on the functional characteristics of ASA parts that results in variations of the friction coefficient, wear rate and tensile response. In addition, this study aims to highlight the relevance of printing parameters to avoid the use of chemical post-processing stages, increasing the performance and sustainability of the process.

In this research, an evaluation of the influence of printing parameters of layer thickness and temperature on the mechanical and tribological response have been carried out for ASA specimens manufactured by fused filament fabrication technology. For this purpose, a range of three different values of thickness of fused layer and three different printing temperatures were combined in the manufacturing process of tests samples. Mechanical behavior of the printed parts was evaluated by standard tensile tests, and friction forces were measured by pin-on-disk tribological tests against steel spheres.

Higher layer thickness of the printed parts shows lower resistance to tribological wear effects; in terms of friction coefficient and wear rate, this type of parts also presents lower tensile strength. It has been detected that mechanical and tribological behavior is highly related to the micro-geometrical characteristics of the printed surfaces, which can be controlled by the manufacturing parameters. Under this consideration, a reduction in the coefficient of friction near to 65% in the average value was obtained through the variation of the layer thickness of printed surfaces.

This research aims to fill a gap in the scientific literature about the use of specific additive manufacturing materials under dynamic contact. This paper is mainly focused on the influence of the manufacturing parameters on the tribological and mechanical behavior of a weather resistant polymer (ASA).

How long does it take to write a book? Authors often get asked this question. There is, of course, no straightforward universal answer; so much depends on the book, on the author concerned, and also on many other circumstances. Some books are generated slowly, some quickly, a few at immense speed. Some may even be the work of very many years, or even a lifetime. The question of the actual time taken over writing is one that always interests readers.

I recently visited the 1994 Poetry Publication Showcase at Poets House in New York City. This is a wonderful annual exhibit of new poetry including both volumes by individual poets and anthologies. This year I was particularly struck by some excellent poetry anthologies. All these anthologies present contemporary poets which should be represented in library collections. Since many libraries do not own individual volumes by all of these writers, the anthologies described in this column will enable libraries to enrich their poetry collection and to introduce new exciting writers to their users.

The purpose of this paper is to analyze the disciplines and thematic study of scientific production in police training over the period 1988-2012.

Introduction and homogenization of keywords and assigning of descriptors to documents, thematic categorization of journals and, analysis of indicators of productivity and relationship of descriptors and thematic areas has been the used methodology.

Totally, 59 different descriptors of a total of 585 assigned to the 182 articles that were published in 95 journals belonging into 20 different subject areas have been identified. The most frequent descriptors are “skills,” “management development” and “violence” and the main thematic areas have been “Criminology and Penology” and “Psychology”. Totally, 47 relationships between 30 descriptors in more than two works, 35 relationships between 20 thematic areas and, 78 relationships between 43 descriptors and eight subject areas in more than two articles have been identified.

Characterize the disciplines and thematic of study of the articles and journals in the scientific production on police training, as well as to identify the relationships between descriptors, subject areas and among these.

Establishing alliances between social economy enterprises (SEEs) is considered to be a solution to the problem of providing enough resources and knowledge to compete in the global market and, at the same time, to maintain identity and ownership. Nevertheless, an important number of alliances breaks up after several years. Therefore, the purpose of this paper is to study the key factors that affect alliances’ development and outcome. In this study, the success factors that have been extensively tested in investor-owned companies are assessed in SEEs, which present important differences in organizational issues and corporate principles and values.

This study defines a scale that includes the most important factors that might be controlled by SEE managers to develop successful alliances. These factors are grouped into three categories: relational capital, relationship governance and the partner selection process. The study also assesses the impact of these factors on alliance performance.

Statistical analysis through structural equation modelling shows that relationship governance and the partner selection process have a significant impact on performance. Therefore, they can be considered success factors in alliances among SEEs.

Taking into account the relevant contribution of the SEEs to the European economy, and having noted the scarce number of studies about alliances success factors in the social economy sector, this study offers a significant contribution to this research field. Moreover, findings will be also interesting for SEE managers and social economy authorities when designing programmes to empower and support alliances.

The purpose of this paper is to understand how Design for Additive manufacturing Knowledge has been developing and its significance to both academia and industry.

In this paper, the authors use a bibliometric approach to analyse publications from January 2010 to December 2020 to explore the subject areas, publication outlets, most active authors, geographical distribution of scholarly outputs, collaboration and co-citations at both institutional and geographical levels and outcomes from keywords analysis.

The findings reveal that most knowledge has been developed in DfAM methods, rules and guidelines. This may suggest that designers are trying to learn new ways of harnessing the freedom offered by AM. Furthermore, more knowledge is needed to understand how to tackle the inherent limitations of AM processes. Moreover, DfAM knowledge has thus far been developed mostly by authors in a small number of institutional and geographical clusters, potentially limiting diverse perspectives and synergies from international collaboration which are essential for global knowledge development, for improvement of the quality of DfAM research and for its wider dissemination.

A concise structure of DfAM knowledge areas upon which the bibliometric analysis was conducted has been developed. Furthermore, areas where research is concentrated and those that require further knowledge development are revealed.

Artificial intelligence (AI) is the most progressive commodity among current information system applications. In-house development and sales of beneficial products are difficult for many software development and service companies (SDSCs). SDSCs have some implicit concerns about implementing AI software development due to the complexity of AI technology; they require an evaluation framework to avoid development failure. To fill the void, this study identified the factors influencing SDSCs when developing AI software development.

Based on complex adaptive systems theory, three aspects were developed as the main factors of hierarchy, namely, employees' capabilities, environmental resources and team capabilities. Fuzzy analytic hierarchy process (FAHP) was used to assess the SDSCs' attitude. Based on SDSCs, attitudes toward implementing AI software projects were collected to calculate the hierarchy of factors.

The outcome of FAHP is used as understanding the key factors of SDSCs for selecting an AI software project, toward the improvement of overall project planning. Employees' stress resistance was considered as a priority for the project, although professional AI skills and resources were also important.

This study suggested three variables developed using complex adaptive systems. This study contributes to a better understanding of the critical aspects of developing AI software projects in SDSCs. The study's findings have practical and academic implications for SDSCs and subsequent academic development, broadening the scope of AI software development research.