This thesis investigates how the assessment of circular economy (CE) at the macro-economic level can be facilitated and promoted. First, a study on the socio-economic environmental impacts of... Show moreThis thesis investigates how the assessment of circular economy (CE) at the macro-economic level can be facilitated and promoted. First, a study on the socio-economic environmental impacts of international agricultural supply chain is presented to better exemplify how Multi-Regional Environmental Extended Input-Output (MR EEIO) data can be used to support policy making. Then, a Python software package (pycirk) and methods for standardized and replicable CE scenarios are presented with a case study on the global environmental and socio-economic impacts CE strategies. The thesis also presents an easy to use and open-source web-based tool for CE scenario construction and analysis (RaMa-Scene). Through these studies, MR EEIO appears to be an adequate tool to assess CE scenarios. However, the implementation of CE interventions will require a variety of micro-level changes across the current international production and consumption system and in many cases more detailed data is required than what is currently available in existing MR EEIO databases. Data availability for CE assessment could be increased through the use of Computer-Aided Technologies and Artificial Intelligence methods in combination with Life Cycle Inventory modelling and MR EEIO databases, but this is only one potential way forward. In fact, the industrial ecology and circular economy communities have many opportunities ahead to improve data collection practices by leveraging digital technologies and artificial intelligence methods. However, coordination in these scientific communities is needed to ensure that the full potential of these technological developments is harvested for the benefit of a sustainable circular economy and society. Show less
When two treatment alternatives (say A and B) are available for some problem, one may be interested in qualitative treatment-subgroup interactions. Such interactions imply the existence of... Show moreWhen two treatment alternatives (say A and B) are available for some problem, one may be interested in qualitative treatment-subgroup interactions. Such interactions imply the existence of subgroups of persons (patients) which are such that in one subgroup Treatment A outperforms Treatment B, whereas the reverse holds in another subgroup. Obviously, this type of interactions is crucial for optimal treatment assignment of future patients. Given baseline characteristics and outcome data from a two-arm Randomized Controlled Trial (RCT), QUalitative INteraction Trees (QUINT) is a tool to identify subgroups that are involved in meaningful qualitative treatment-subgroup interactions. The result of QUINT is a tree that partitions the total group of participants (patients) on the basis of their baseline characteristics into three subgroups (i.e., partition classes): Subgroup 1: Those for whom Treatment A is better than Treatment B (P1), Subgroup 2: Those for whom Treatment B is better than Treatment A (P2), and Subgroup 3: Those for whom it does not make any difference (P3). This mehod was implemented in the R-package "quint". Show less
A circular economy is an industrial system that is restorative or regenerative by intention or design. During the last decade, the circular economy became an attractive paradigm to increase global... Show moreA circular economy is an industrial system that is restorative or regenerative by intention or design. During the last decade, the circular economy became an attractive paradigm to increase global welfare while minimizing the environmental impacts of economic activities. Although several studies concerning the potential benefits and drawbacks of policies that implement the new paradigm have been performed, there is currently no standardized theoretical model or software to execute such assessment. In order to fill this gap, in the present paper we show how to perform these analyses using Environmentally Extended Input-Output Analysis. We also describe a python package (pycirk) for modeling Circular Economy scenarios in the context of the Environmentally Extended Multi-Regional Input-Output database EXIOBASE V3.3, for the year 2011. We exemplify the methods and software through a what-if zero-cost case study on two circular economy strategies (Resource Efficiency and Product Lifetime Extension), four environmental pressures and two socio-economic factors. Show less
This research investigates the application of competition law to abuse of dominant position in the software industry. The software industry is known as an innovation-driven market. It differs... Show moreThis research investigates the application of competition law to abuse of dominant position in the software industry. The software industry is known as an innovation-driven market. It differs substantially from traditional industries, which feature competition using low-priced products. Established competition law was formed in markets which featured price competition; applying it to an industry in which market players compete with innovative products challenges competition law enforcement. This research shows that when applying competition law to the software industry, although some traditional rules and criteria still apply, many are adjusted due to the different industrial characteristics. It shows that despite being widely applied, competition law assessment criteria and analysis approaches are subject to controversy. Show less
Hoogenboom, J.; Gaag, K.J. van der; Leeuw, R.H. de; Sijen, T.; Knijff, P. de; Laros, J.F.J. 2017
MultiLevel Simultaneous Component Analysis (MLSCA) is a data-analytical technique for multivariate two-level data. MLSCA sheds light on the associations between the variables at both levels by... Show moreMultiLevel Simultaneous Component Analysis (MLSCA) is a data-analytical technique for multivariate two-level data. MLSCA sheds light on the associations between the variables at both levels by specifying separate submodels for each level. Each submodel consists of a component model. Although MLSCA has already been successfully applied in diverse areas within and outside the behavioral sciences, its use is hampered by two issues. First, as MLSCA solutions are fitted by means of iterative algorithms, analyzing large data sets (i.e., data sets with many level one units) may take a lot of computation time. Second, easily accessible software for estimating MLSCA models is lacking so far. In this paper, we address both issues. Specifically, we discuss a computational shortcut for MLSCA fitting. Moreover, we present the MLSCA package, which was built in MATLAB, but is also available in a version that can be used on any Windows computer, without having MATLAB installed. Show less
Bleichrodt, F.; Leeuwen, T. van; Palenstijn, W.J.; Aarle, W. van; Sijbers, J.; Batenburg, K.J. 2016
Mathematical scripting languages are commonly used to develop new tomographic reconstruction algorithms. For large experimental datasets, high performance parallel (GPU) implementations are... Show moreMathematical scripting languages are commonly used to develop new tomographic reconstruction algorithms. For large experimental datasets, high performance parallel (GPU) implementations are essential, requiring a re-implementation of the algorithm using a language that is closer to the computing hardware. In this paper, we introduce a new MATLAB interface to the ASTRA toolbox, a high performance toolbox for building tomographic reconstruction algorithms. By exposing the ASTRA linear tomography operators through a standard MATLAB matrix syntax, existing and new reconstruction algorithms implemented in MATLAB can now be applied directly to large experimental datasets. This is achieved by using the Spot toolbox, which wraps external code for linear operations into MATLAB objects that can be used as matrices. We provide a series of examples that demonstrate how this Spot operator can be used in combination with existing algorithms implemented in MATLAB and how it can be used for rapid development of new algorithms, resulting in direct applicability to large-scale experimental datasets. Show less
Mestdagh, M.; Verdonck, S.; Duisters, K.L.W.; Tuerlinckx, F. 2015
Centraal in dit proefschrift staat het begrip interactie - wederzijds beinvloedend gedrag. In hedendaagse computersystemen speelt interactie een steeds belangrijker rol. Software wordt meer en meer... Show moreCentraal in dit proefschrift staat het begrip interactie - wederzijds beinvloedend gedrag. In hedendaagse computersystemen speelt interactie een steeds belangrijker rol. Software wordt meer en meer ontwikkeld als een verzameling zelfstandig werkende componenten die services aanbieden aan andere componenten. Iedere component kent een eigen "levenscyclus" - hij wordt ontwikkeld, doorontwikkeld, uitgebreid, gesplitst, samengevoegd, en weer weggegooid. Concrete toepassingen ontstaan doordat componenten worden samengesteld tot een groter geheel. Zulke toepassingen zijn alleen bruikbaar als er sprake is van zinvolle interactie tussen de componenten.De modelleertaal Paradigm, ontwikkeld aan het Leiden Institute of Advanced Computer Science (LIACS), is een taal die speciaal geschikt is voor het modelleren en analyseren van interactie. Een Paradigm-model beschrijft op een abstract niveau het gedrag van individuele componenten, de rollen die de componenten kunnen spelen in interactie met andere componenten, en de manier waarop die interactie tussen de rollen plaatsvindt. De taal heeft een aantal interessante eigenschappen, niet in de laatste plaats het feit dat het een executeerbare taal is: Paradigm-modellen kunnen door een computer worden uitgevoerd. Als bijzondere bijkomstigheid kunnen Paradigm-modellen zo worden ingericht dat ze zichzelf veranderen terwijl ze worden uitgevoerd - zo kunnen we ook de levenscyclus van componenten modelleren. Show less