This article examines to what extent and how cannabis users in different countries, with different cannabis legislation and policies practice normalization and self-regulation of cannabis use in everyday life. Data were collected in a survey among a convenience sample of 1,225 last-year cannabis users aged 18–40 from seven European countries, with cannabis policies ranging from relatively liberal to more punitive. Participants were recruited in or in the vicinity of Dutch coffeeshops. We assessed whether cannabis users experience and interpret formal control and informal social norms differently across countries with different cannabis policies. The findings suggest that many cannabis users set boundaries to control their use. Irrespective of national cannabis policy, using cannabis in private settings and setting risk avoidance rules were equally predominant in all countries. This illustrates that many cannabis users are concerned with responsible use, demonstrating the importance that they attach to discretion. Overall, self-regulation was highest in the most liberal country (the Netherlands). This indicates that liberalization does not automatically lead to chaotic or otherwise problematic use as critics of the policy have predicted, as the diminishing of formal control (law enforcement) is accompanied by increased importance of informal norms and stronger self-regulation. In understanding risk-management, societal tolerance of cannabis use seems more important than cross-national differences in cannabis policy. The setting of cannabis use and self-regulation rules were strongly associated with frequency of use. Daily users were less selective in choosing settings of use and less strict in self-regulation rules. Further differences in age, gender, and household status underline the relevance of a differentiated, more nuanced understanding of cannabis normalization.
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Analyzing historical decision-related data can help support actual operational decision-making processes. Decision mining can be employed for such analysis. This paper proposes the Decision Discovery Framework (DDF) designed to develop, adapt, or select a decision discovery algorithm by outlining specific guidelines for input data usage, classifier handling, and decision model representation. This framework incorporates the use of Decision Model and Notation (DMN) for enhanced comprehensibility and normalization to simplify decision tables. The framework’s efficacy was tested by adapting the C4.5 algorithm to the DM45 algorithm. The proposed adaptations include (1) the utilization of a decision log, (2) ensure an unpruned decision tree, (3) the generation DMN, and (4) normalize decision table. Future research can focus on supporting on practitioners in modeling decisions, ensuring their decision-making is compliant, and suggesting improvements to the modeled decisions. Another future research direction is to explore the ability to process unstructured data as input for the discovery of decisions.
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Plant photosynthesis and biomass production are associated with the amount of intercepted light, especially the light distribution inside the canopy. Three virtual canopies (n = 80, 3.25 plants/m2) were constructed based on average leaf size of the digitized plant structures: ‘small leaf’ (98.1 cm2), ‘medium leaf’ (163.0 cm2) and ‘big leaf’ (241.6 cm2). The ratios of diffuse light were set in three gradients (27.8%, 48.7%, 89.6%). The simulations of light interception were conducted under different ratios of diffuse light, before and after the normalization of incident radiation. With 226.1% more diffuse light, the result of light interception could increase by 34.4%. However, the 56.8% of reduced radiation caused by the increased proportion of diffuse light inhibited the advantage of diffuse light in terms of a 26.8% reduction in light interception. The big-leaf canopy had more mutual shading effects, but its larger leaf area intercepted 56.2% more light than the small-leaf canopy under the same light conditions. The small-leaf canopy showed higher efficiency in light penetration and higher light interception per unit of leaf area. The study implied the 3D structural model, an effective tool for quantitative analysis of the interaction between light and plant canopy structure.
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Achtergrond Steeds meer technologie is beschikbaar om zelfmanagement en kwaliteit van leven van ouderen te bevorderen. Zorgorganisatie Livio maakt gefragmenteerd gebruik van die technologie en zoekt naar een manier om technologie duurzaam te implementeren en in te bedden in reguliere werkprocessen, steeds in samenwerking met de cliënt. De Normalization Process Theory (NPT) biedt concrete aanwijzingen om inbedding van innovaties in werkprocessen te ondersteunen. Daarbij is de focus op het concrete wat en hoe het werk gedaan wordt. De NPT onderscheidt daarbij vier mechanismen: samenhang, betrokkenheid, samen doen en reflectie. Met het op NPT gebaseerde NoMAD-instrument kan innovatiebereidheid en implementatievoortgang op die vier mechanismen gemonitord worden. Doelstelling Met deze aanvraag wordt een breed implementatieproject voorbereid gericht op inbedden van technologie in verpleeghuis, thuiszorg en woonzorgcentra (VVT) in Oost-Nederland, met (inter)nationale opschalingsmogelijkheden. In dit project werken hogeschool Saxion, zorgorganisatie Livio en Roessingh Research & Development samen om dit te realiseren. De doelen van deze voorbereidende aanvraag zijn: a) Het aanpassen van het NoMAD instrument voor de implementatie van technologie, voor de context van verpleeghuis, thuiszorg en woonzorgcentra, b) het uitwerken van een werkwijze om cliënten te betrekken in de implementatie van technologie. Daarnaast is het doel van deze aanvraag om een consortium te vormen van zorgorganisaties, netwerk-, onderwijs-, MKB- en kennisinstellingen ten behoeve van het brede implementatieproject om daarmee een subsidieaanvraag voor RAAK Publiek te schrijven, gericht op implementatie van technologie in Oost-Nederland. Resultaten - Aangepaste versie van NoMAD geschikt voor het monitoren van de implementatie van technologie in de VVT; - Een werkwijze voor cliëntparticipatie tijdens het implementatieproject; - Consortium met partners van zorgorganisaties, netwerkorganisaties, MKB, onderwijs, kennisinstellingen en cliëntenorganisaties, ten behoeve van - RAAK Publiek subsidieaanvraag gericht op implementatie van technologie in VVT in regio Oost-Nederland.
