Onderzoeksplatform ‘Connected Learning: ’Al ruim vijftien jaar houdt De Haagse Hogeschool zich bezig met onderzoek als deel van haar missie. Terwijl onderwijs vaak geworteld is in monodisciplinaire vakgebieden, kan met onderzoek wat makkelijker gekeken worden naar domeinen in de samenleving (zorg, veiligheid, ondernemen, etc.) waarin complexe problematiek steeds vaker wél dan niet een multidisciplinaire aanpak vereist. Bijna niemand werkt nog alleen of met alleen vakgenoten aan problemen of uitdagingen. En die veranderende beroepspraktijk is bij uitstek het domein van het hoger beroepsonderwijs. Daar leiden we voor op. Het onderzoeken van en experimenteren met nieuwe uitdagingen in de praktijk verbindt ons sterker met de samenleving, het stelt ons in staat om ons beroepsonderwijs te vernieuwen en geeft docenten, onderzoekers en studenten de kans om zich te ontwikkelen door samen te werken aan vragen en uitdagingen die de toekomst van de beroepspraktijk vorm geven. Veel onderzoek wordt uitgevoerd onder begeleiding van lectoren die samenwerken met docent-onderzoekers, studenten, en professionals in het werkveld aan veelal meerjarige onderzoeksagenda’s die lijn aanbrengen in verschillende deelactiviteiten. Een van de manieren waarop De Haagse Hogeschool onderzoek organiseert is in de vorm van onderzoeksplatforms die zich richten op verschillende domeinen van de samenleving. Wij zijn ‘Connected Learning’, een onderzoeksplatform dat zich richt op leren in de netwerksamenleving - in de samenleving zelf, maar ook in de beroepspraktijk en in ons onderwijs. Aangenaam. Wat wij doen? Daar gaat dit boek over, dus daar verklappen we hier nog niets over. Wat verwacht u als u nadenkt over onze naam? Enig idee? Geen idee? Benieuwd? Lees verder om te ontdekken wat ons inspireert, uitdaagt en nieuwsgierig maakt. Sommige van onze ideeën zijn doordacht en doorleefd omdat we er al jaren onderzoek naar doen, andere zijn nieuw en dagen ons uit om er grip op te krijgen. Wij geven met dit boek een beeld van waar we staan in 2018. Zie het als een eerste kennismaking, met de nadruk op ‘eerste’: we werken graag met veel en verschillende partners. Zie het als visitekaartje van onze onderzoeksagenda. We hopen van harte dat u zich als lezer uitgenodigd voelt om met ons samen op zoek te gaan—misschien wel naar een gezamenlijke toekomst. ‘Connected Learning’ Research Platform: For over fifteen years, The Hague University of Applied Sciences has been carrying out research as part of its mission. While education is often rooted in monodisciplinary subject areas, research allows for a broader look at areas of society (care, security, entrepreneurship etc.), where complex problems more often than not require a multidisciplinary approach. Today, barely anyone works on problems or challenges alone or solely with colleagues from within the same subject area. Universities of applied sciences are uniquely placed to deal with these changes in professional practices; after all, we train the professionals who will one day enter that field. Researching and experimenting with new challenges in professional practice allows us to connect more strongly with society, enables us to be innovative in our professional training and gives lecturers, researchers and students the opportunity to develop themselves by cooperating on the challenges and issues that will shape the future of that professional practice. Most research is carried out under the guidance of professors who cooperate with lecturers/researchers, students and the professional field, mainly on long-term research agendas that provide an outline for various sub-activities. One of the ways in which research is organised at The Hague University of Applied Sciences is in the form of research platforms that focus on various areas of society. We are ‘Connected Learning’, a research platform focusing on learning in the network society — in that society as such, but also in professional practice and our education. Nice to meet you! So, what do we do? That’s what this book is about, so we’re not going to give anything away just yet. Just thinking about our name, what do you expect we do? Any ideas? Or not a clue at all? If you’d like to find out, keep reading to find out what inspires us, what challenges we face and what drives our curiosity. Some of our ideas are well-established because we’ve been researching them for years, while other, newer ideas are more challenging to grasp. This book provides an overview of where we stand in 2018. You could see it as an initial introduction, with the emphasis on “initial”; we work with many different partners, and we enjoy doing so. Alternatively, you could see it as a calling card for our research agenda. We sincerely hope that, as a reader, you feel encouraged to join us in our quest — possibly towards a joint future.
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Abstract: The typical structure of the healthcare sector involves (specialist) intertwined practices co-occurring in formal or informal networks. These practices must answer to the concerns and needs of all related stakeholders. Multimorbidity and the need to share knowledge for scientific development are among the driving factors for collaboration in healthcare. To establish and keep up a permanent collaborative link, it takes effort and understanding of the network characteristics that must be governed. It is not hard to find practices of Network Governance (NG) in a variety of industries. Still, there is a lack of insight in this subject, including knowledge on how to establish and maintain an effective healthcare network. Consequently, this study's research question is: How is network governance organized in the healthcare sector? A systematic literature study was performed to select 80 NG articles. Based on these publications the characteristics of NG are made explicit. The findings demonstrate that combinations of governance style (relational versus contractual governance) and governance structure (lead versus shared governance) lead to different network dynamics. Furthermore, the results show that in order to comprehend how networks in the healthcare sector emerge and can be regulated, it is vital to understand the current network type. Additionally, it informs us of the governing factors. Zie https://www.hbo-kennisbank.nl/details/sharekit_han:oai:surfsharekit.nl:e4f8fa3a-4af8-42ef-b2dd-c86d77b4cec6
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From the article: Abstract: An overview of neural network architectures is presented. Some of these architectures have been created in recent years, whereas others originate from many decades ago. Apart from providing a practical tool for comparing deep learning models, the Neural Network Zoo also uncovers a taxonomy of network architectures, their chronology, and traces back lineages and inspirations for these neural information processing systems.
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Background: Due to multimorbidity and geriatric problems, older people often require both psychosocial and medical care. Collaboration between medical and social professionals is a prerequisite to deliver high-quality care for community-living older people. Effective, safe, and person-centered care relies on skilled interprofessional collaboration and practice. Little is known about interprofessional education to increase interprofessional collaboration in practice (IPCP) in the context of community care for older people. This study examines the feasibility of the implementation of an IPCP program in three community districts and determines its potential to increase interprofessional collaboration between primary healthcare professionals caring for older people. Method: A feasibility study was conducted to determine the acceptability and feasibility of data collection and analysis regarding interprofessional collaboration in network development. A questionnaire was used to measure the learning experience and the acquisition of knowledge and skills regarding the program. Network development was assessed by distributing a social network survey among professionals attending the program as well as professionals not attending the program at baseline and 5.5 months after. Network development was determined by calculating the number, reciprocity, value, and diversity of contacts between professionals using social network analysis. Results: The IPCP program was found to be instructive and the knowledge and skills gained were applicable in practice. Social network analysis was feasible to conduct and revealed a spill-over effect regarding network development. Program participants, as well as non-program participants, had larger, more reciprocal, and more diverse interprofessional networks than they did before the program. Conclusions: This study showed the feasibility of implementing an IPCP program in terms of acceptability, feasibility of data collection, and social network analysis to measure network development, and indicated potential to increase interprofessional collaboration between primary healthcare professionals. Both program participants and non-program participants developed a larger, more collaborative, and diverse interprofessional network.
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Battery energy storage (BES) can provide many grid services, such as power flow management to reduce distribution grid overloading. It is desirable to minimise BES storage capacities to reduce investment costs. However, it is not always clear how battery sizing is affected by battery siting and power flow simultaneity (PFS). This paper describes a method to compare the battery capacity required to provide grid services for different battery siting configurations and variable PFSs. The method was implemented by modelling a standard test grid with artificial power flow patterns and different battery siting configurations. The storage capacity of each configuration was minimised to determine how these variables affect the minimum storage capacity required to maintain power flows below a given threshold. In this case, a battery located at the transformer required 10–20% more capacity than a battery located centrally on the grid, or several batteries distributed throughout the grid, depending on PFS. The differences in capacity requirements were largely attributed to the ability of a BES configuration to mitigate network losses. The method presented in this paper can be used to compare BES capacity requirements for different battery siting configurations, power flow patterns, grid services, and grid characteristics.
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Humanitarian logistics is regarded as a key area for improved disaster management efficiency and effectiveness. In this study, a multi-objective integrated logistic model is proposed to locate disaster relief centers while taking into account network costs and responsiveness. Because this location problem is NP-hard, we present a genetic approach to solve the proposed model.
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Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
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Objectives Most complex healthcare interventions target a network of healthcare professionals. Social network analysis (SNA) is a powerful technique to study how social relationships within a network are established and evolve. We identified in which phases of complex healthcare intervention research SNA is used and the value of SNA for developing and evaluating complex healthcare interventions. Methods A scoping review was conducted using the Arksey and O’Malley methodological framework. We included complex healthcare intervention studies using SNA to identify the study characteristics,level of complexity of the healthcare interventions, reported strengths and limitations, and reported implications of SNA. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews 2018 was used to guide the reporting. Results Among 2466 identified studies, 40 studies were selected for analysis. At first, the results showed that SNA seems underused in evaluating complex intervention research. Second, SNA was not used in the development phase of the included studies. Third, the reported implications in the evaluation and implementation phase reflect the value of SNA in addressing the implementation and population complexity. Fourth, pathway complexity and contextual complexity of the included interventions were unclear or unable to access. Fifth, the use of a mixed methods approach was reported as a strength, as the combination and integration of a quantitative and qualitative method clearly establishes the results. Conclusion SNA is a widely applicable method that can be used in different phases of complex intervention research. SNA can be of value to disentangle and address the level of complexity of complex healthcare interventions. Furthermore, the routine use of SNA within a mixed method approach could yield actionable insights that would be useful in the transactional context of complex interventions.
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The academic and professional attention to the large synergies hidden in horizontal collaborations is increasing. This study attempts to address the impact of collaborative transport on transportation lead-time and lead-time variability through empirically investigating a group of SMEs involved in a collaborative distribution network. Data was collected for seven pre-cooperation and eight cooperative orders over a period of 14 months. The results of Mann-Whitney U-test show a significant average reduction of 30.8% in the duration of lead times. Lead-time variability was also found to be reduced as the result of changes in the coefficient of variances and the Bartlett’s test for homogeneity of variances. Horizontal collaboration in transport could eventually lead to reduced lead times and lower variability of lead time which results in reduced supply chain costs. This can be achieved by means of direct routing and avoiding multi-transshipment routes which reduces the uncertainty and variability by diminishing the number of stages in the transport chain. Thus, effective lead-time management is considered a source of competitive advantage as it can reduce supply chain costs by lowering inventory levels, but is also capable of improving performance and customer service by offering improved product quality service levels.
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While the Municipality of Amsterdam wants to expand the electric vehicle public charging infrastructure to reach carbon-neutral objectives, the Distribution System Operator cannot allow new charging stations where low-voltage transformers are reaching their maximum capacity. To solve this situation, a smart charging project called Flexpower is being tested in some districts. Charging power is limited during peak times to avoid grid congestion and, therefore, enable the expansion of charging infrastructure while deferring grid investments. This work simulates the implementation of the Flexpower strategy with high penetration of electric vehicles, considering dynamic and local power limits, to assess the impact on both the satisfaction of electric vehicle users and the business model of the Charging Point Operator. A stochastic approach, based on Gaussian Mixture Models, has been used to model different profiles of electric vehicle users using data from the Amsterdam public electric vehicle charging infrastructure. Several key performance indicators have been defined to assess the impact of such charging limitations on the different stakeholders. The results show that, while Amsterdam’s existing public charging infrastructure can host just twice the current electric vehicle demand, the application of Flexpower will enable the growth in charging stations without requiring grid upgrades. Even with 7 times more charging sessions, Flexpower could provide a power peak reduction of 57% while supplying 98% of the total energy required by electric vehicle users.
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