scientific fields
Recently Published Documents





2022 ◽  
Vol 14 (1) ◽  
pp. 1-27
Khalid Belhajjame

Workflows have been adopted in several scientific fields as a tool for the specification and execution of scientific experiments. In addition to automating the execution of experiments, workflow systems often include capabilities to record provenance information, which contains, among other things, data records used and generated by the workflow as a whole but also by its component modules. It is widely recognized that provenance information can be useful for the interpretation, verification, and re-use of workflow results, justifying its sharing and publication among scientists. However, workflow execution in some branches of science can manipulate sensitive datasets that contain information about individuals. To address this problem, we investigate, in this article, the problem of anonymizing the provenance of workflows. In doing so, we consider a popular class of workflows in which component modules use and generate collections of data records as a result of their invocation, as opposed to a single data record. The solution we propose offers guarantees of confidentiality without compromising lineage information, which provides transparency as to the relationships between the data records used and generated by the workflow modules. We provide algorithmic solutions that show how the provenance of a single module and an entire workflow can be anonymized and present the results of experiments that we conducted for their evaluation.

2022 ◽  
Vol 70 ◽  
pp. 55-63
Alexander V. Graham ◽  
John McLevey ◽  
Pierson Browne ◽  
Tyler Crick

2022 ◽  
Vol 12 (2) ◽  
pp. 870
George Tsinarakis ◽  
Nikolaos Sarantinoudis ◽  
George Arampatzis

A generic well-defined methodology for the construction and operation of dynamic process models of discrete industrial systems following a number of well-defined steps is introduced. The sequence of steps for the application of the method as well as the necessary inputs, conditions, constraints and the results obtained are defined. The proposed methodology covers the classical offline modelling and simulation applications as well as their online counterpart, which use the physical system in the context of digital twins, with extensive data exchange and interaction with sensors, actuators and tools from other scientific fields as analytics and optimisation. The implemented process models can be used for what-if analysis, comparative evaluation of alternative scenarios and for the calculation of key performance indicators describing the behaviour of the physical systems under given conditions as well as for online monitoring, management and adjustment of the physical industrial system operations with respect to given rules and targets. An application of the proposed methodology in a discrete industrial system is presented, and interesting conclusions arise and are discussed. Finally, the open issues, limitations and future extensions of the research are considered.

Kai Diethelm ◽  
Virginia Kiryakova ◽  
Yuri Luchko ◽  
J. A. Tenreiro Machado ◽  
Vasily E. Tarasov

AbstractThe area of fractional calculus (FC) has been fast developing and is presently being applied in all scientific fields. Therefore, it is of key relevance to assess the present state of development and to foresee, if possible, the future evolution, or, at least, the challenges identified in the scope of advanced research works. This paper gives a vision about the directions for further research as well as some open problems of FC. A number of topics in mathematics, numerical algorithms and physics are analyzed, giving a systematic perspective for future research.

David Sabando-Vera ◽  
Marcela Yonfa-Medranda ◽  
Néstor Montalván-Burbano ◽  
Jose Albors-Garrigos ◽  
Katherine Parrales-Guerrero

Research on open innovation (OI) has increased in recent years, showing its potential in various areas of knowledge. Its relation to small and medium-sized enterprises has attracted the attention of academics. This article aims to evaluate the intellectual structure of the scientific study of OI, and its close relationship with various scientific fields, through a bibliometric analysis of this academic field using the Scopus database and the application of the VOSviewer software. The methodology comprises a rigorous systematic and transparent process divided into four phases: (i) the establishment of search criteria for the research field, through a literature review for its selection; (ii) the selection of the database, the establishment of the search equation and extraction of information; (iii) the application of inclusion and exclusion criteria for the selected documents and an explanation of the usefulness of the software; and (iv) the analysis of the results through the approaches of scientific output performance and bibliometric mapping. The results show an increasing trend of IO publications in SMEs, consolidated in 396 articles with contributions from 65 countries and 947 authors. The intellectual structure shows seven themes related to firm performance, R&D networks, business management, business models, capabilities and knowledge transfer. This study contributes to the field by providing an overview of IO in SME contexts. It also provides insightful information to policymakers for developing policies for firm economic growth.

Rochman Achwan ◽  
Meuthia Ganie-Rochman ◽  
Lidya Triana ◽  
Ricardi S. Adnan ◽  
Syora Alya Eka Putri

Mikhail Fominykh ◽  
Joshua Weidlich ◽  
Marco Kalz ◽  
Ingunn Dahler Hybertsen

AbstractThis article contributes to the debate on the growing number of interdisciplinary study programs in learning and technology, and aims to understand the diversity of programs as well as curricula structure in an international landscape. Scientific fields share their knowledge and recruit young researchers by offering discipline-specific study programs. Thus, study programs are a reflection of the fields they represent. As technology-enhanced learning is considered to be particularly interdisciplinary and heterogenous, it is important to better understand the landscape of study programs that represents the field. This article presents an analysis of master programs in technology-enhanced learning. A systematic review and analysis of master programs offered in English has been conducted and further used as input for hierarchical cluster analysis. The study identified general characteristics, curricula structure, and organization of topics of these programs. Hierarchical cluster analysis and qualitative content analysis helped us to identify the major types of curricular structures and typical topics covered by the courses. Results show that most study programs rely on interdisciplinary subjects in technology-enhanced learning with a considerable number of subjects from education, learning and psychology. Subjects related to technology, information and computer science appear in such programs less frequently.

2022 ◽  
pp. 363-388
Zeeshan Ahmad Bhutta ◽  
Ayesha Kanwal ◽  
Ambreen Ashar ◽  
Moazam Ali ◽  
Ashar Mahfooz ◽  

The rapid growth of nanotechnology towards the development of nanomedicines has improved cancer treatment. Nanomedicine provides the opportunity to implement complex and targeted multifunctional strategies. Today, nanoparticles (NPs) have many uses in a number of scientific fields. In recent years, it has been repeatedly reported that NPs hold a significant place in the regulation of modern medicine by implementing a varying number of clinical approaches like drug carrying substances, genetic material delivery to tumors, as well as in radiography as a contrast media agent. Various nanomaterials based on organic, inorganic, lipid or glycan compounds, and synthetic polymers have been used to develop and improve new cancer treatments. In this chapter, the authors discussed the role of NPs in cancer treatment among various anticancer drug delivery methods.

2021 ◽  
Vol 1 (4) ◽  
pp. 1-21
Manuel López-ibáñez ◽  
Juergen Branke ◽  
Luís Paquete

Experimental studies are prevalent in Evolutionary Computation ( EC ), and concerns about the reproducibility and replicability of such studies have increased in recent times, reflecting similar concerns in other scientific fields. In this article, we discuss, within the context of EC, the different types of reproducibility and suggest a classification that refines the badge system of the Association of Computing Machinery ( ACM ) adopted by ACM Transactions on Evolutionary Learning and Optimization ( TELO ). We identify cultural and technical obstacles to reproducibility in the EC field. Finally, we provide guidelines and suggest tools that may help to overcome some of these reproducibility obstacles.

2021 ◽  
Vol 47 (4) ◽  
pp. 1-36
Cécile Daversin-Catty ◽  
Chris N. Richardson ◽  
Ada J. Ellingsrud ◽  
Marie E. Rognes

Mixed dimensional partial differential equations (PDEs) are equations coupling unknown fields defined over domains of differing topological dimension. Such equations naturally arise in a wide range of scientific fields including geology, physiology, biology, and fracture mechanics. Mixed dimensional PDEs are also commonly encountered when imposing non-standard conditions over a subspace of lower dimension, e.g., through a Lagrange multiplier. In this article, we present general abstractions and algorithms for finite element discretizations of mixed domain and mixed dimensional PDEs of codimension up to one (i.e., n D- m D with |n-m| ≤ 1). We introduce high-level mathematical software abstractions together with lower-level algorithms for expressing and efficiently solving such coupled systems. The concepts introduced here have also been implemented in the context of the FEniCS finite element software. We illustrate the new features through a range of examples, including a constrained Poisson problem, a set of Stokes-type flow models, and a model for ionic electrodiffusion.

Sign in / Sign up

Export Citation Format

Share Document