The semantic web, social media and the amount of user-generated content continues to grow at a staggering rate. Social Media significantly contributed to the information flow during the Arab Spring, the Occupy and Wall Street movement continue to maintain a global online presence using social media technology. But is the social media information explosion really a unique event in media history? How did story telling evolve into social media? In order to place social media in its historical context and anticipate digital native expectations, we explore the origins of narrative and storytelling from the perspective of a documentary producer. How did past media technologies prepare the way for social media? How do digital natives perceive the world via social media and what do they expect from today's documentary producer? What are the viewing habits of digital natives? What do previous 'information explosions' have in common with social and digital media? These are essential questions for media and documentary producers navigating their way through the vast maze of social media technology and the semantic web, in addition to traditional media.
This study explores how journalists in highspeed newsrooms gather information, how gathering activities are temporally structured and how reliability manifests itself in information-gathering activities.
Turkey has received consistent criticism from international media for having many naturalized athletes in its national squad, both in the Olympic Games and other major international sporting events. Similar criticisms have also been a feature of debates for a long time in domestic media, varying in views toward these athletes. This research focuses on media representations of naturalized athletes in Turkey between 2008 and 2020. We investigated the sentiments of news items from four major Turkish newspapers (Milliyet, Cumhuriyet, Sabah and Fanatik) on their stances toward naturalized athletes over the timespan of 2008–2020. Beside analyzing the sentiment of the media content both cumulatively and fragmentedly, we also identified the yearly trends and most featured sports in this context, combining qualitative and quantitative techniques. Our findings showed that sentiments in Turkish media toward naturalized athletes are mostly neutral and negative as well as with differences varying on the basis of the newspapers and news item types. The most criticism underlined pursuing “shortcut” success with naturalized athletes representing Turkey in the international arena. Among the featured sports, basketball, football, and track and field have been the most discussed ones in the naturalization context.
“Empowering learners to create a sustainable future” This is the mission of Centre of Expertise Mission-Zero at The Hague University of Applied Sciences (THUAS). The postdoc candidate will expand the existing knowledge on biomimicry, which she teaches and researches, as a strategy to fulfil the mission of Mission-Zero. We know when tackling a design challenge, teams have difficulties sifting through the mass of information they encounter. The candidate aims to recognize the value of systematic biomimicry, leading the way towards the ecosystems services we need tomorrow (Pedersen Zari, 2017). Globally, biomimicry demonstrates strategies contributing to solving global challenges such as Urban Heat Islands (UHI) and human interferences, rethinking how climate and circular challenges are approached. Examples like Eastgate building (Pearce, 2016) have demonstrated successes in the field. While biomimicry offers guidelines and methodology, there is insufficient research on complex problem solving that systems-thinking requires. Our research question: Which factors are needed to help (novice) professionals initiate systems-thinking methods as part of their strategy? A solution should enable them to approach challenges in a systems-thinking manner just like nature does, to regenerate and resume projects. Our focus lies with challenges in two industries with many unsustainable practices and where a sizeable impact is possible: the built environment (Circularity Gap, 2021) and fashion (Joung, 2014). Mission Zero has identified a high demand for Biomimicry in these industries. This critical approach: 1) studies existing biomimetic tools, testing and defining gaps; 2) identifies needs of educators and professionals during and after an inter-disciplinary minor at The Hague University; and, 3) translates findings into shareable best practices through publications of results. Findings will be implemented into tangible engaging tools for educational and professional settings. Knowledge will be inclusive and disseminated to large audiences by focusing on communication through social media and intervention conferences.
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
Hoogwaardig afvalhout van bewoners, bouwbedrijven en meubelmakers blijft momenteel ongebruikt omdat het te arbeidsintensief is om grote hoeveelheden ongelijke stukken hout van verschillende afmetingen en soorten te verwerken. Waardevol hout wordt waardeloos afval, tegen de principes van de circulaire economie in. In CW.Code werken Powerhouse Company, Bureau HUNC en Vrijpaleis samen met de HvA om te onderzoeken hoe een toegankelijke ontwerptool te ontwikkelen om upcycling en waardecreatie van afvalhout te faciliteren. In andere projecten hebben HvA en partners verschillende objecten gemaakt van afvalhout: een stoel, een receptiebalie, kleine meubels en objecten voor de openbare ruimte, vervaardigd met industriële robots. Deze objecten zijn 3D gemodelleerd met behulp van specifieke algoritmen, in de algemeen gebruikte ontwerpsoftware Rhino en Grasshopper. De projectpartners willen nu onderzoeken hoe deze algoritmen via een toegankelijke tool bruikbaar te maken voor creatieve praktijken. Deze tool integreert generatieve ontwerpalgoritmen en regelsets die rekening houden met beschikbaar afvalhout, en de ecologische, financiële en sociale impact van resulterende ontwerpen evalueren. De belangrijkste ontwerpparameters kunnen worden gemanipuleerd door ontwerpers en/of eindgebruikers, waardoor het een waardevol hulpmiddel wordt voor het co-creëren van circulaire toepassingen voor afvalhout. Dit onderzoek wordt uitgevoerd door HvA Digital Production Research Group, met bovengenoemde partners. HUNC heeft ervaring met stadsontwikkeling waarbij gebruik wordt gemaakt van lokaal gekapt afvalhout. Vrijpaleis biedt toegang tot een actieve, lokale community van makers met een sterke band met buurtbewoners. Powerhouse Company heeft ervaring in het ontwerpen met hout in de bouw. Alle drie kunnen profiteren van slimmere circulaire ontwerptools, waarbij beschikbaar materiaal, productiebeperkingen en impactevaluatie worden geïntegreerd. De tool wordt ontwikkeld en getest voor twee designcases: een binnenmeubelobject en een buitengevelelement. Bevindingen hiervan zullen leidend zijn bij de ontwikkeling van de tool. Na afronding van het project is een bètaversie gereed voor validatie door ontwerpers, bewonerscollectieven en onderzoek/onderwijs van de HvA.
