Passenger flow management is an important issue at many airports around the world. There are high concentrations of passengers arriving and leaving the airport in waves of large volumes in short periods, particularly in big hubs. This might cause congestion in some locations depending on the layout of the terminal building. With a combination of real airport data, as well as synthetic data obtained through an airport simulator, a Long Short-Term Memory Recurrent Neural Network has been implemented to predict the possible trajectories that passengers may travel within the airport depending on user-defined passenger profiles. The aim of this research is to improve passenger flow predictability and situational awareness to make a more efficient use of the airport, that could also positively impact communication with public and private land transport operators.
Passenger flow management is an important issue at many airports around the world. There are high concentrations of passengers arriving and leaving the airport in waves of large volumes in short periods, particularly in big hubs. This might cause congestion in some locations depending on the layout of the terminal building. With a combination of real airport data, as well as synthetic data obtained through an airport simulator, a Long Short-Term Memory Recurrent Neural Network has been implemented to predict the possible trajectories that passengers may travel within the airport depending on user-defined passenger profiles. The aim of this research is to improve passenger flow predictability and situational awareness to make a more efficient use of the airport, that could also positively impact communication with public and private land transport operators.
Already for some decades lateral flow assays (LFAs) are ‘common use’ devices in our daily life. Also, for forensic use LFAs are developed, such as for the analysis of illicit drugs and DNA, but also for the detection of explosives and body fluid identification. Despite their advantages, including ease-of-use, LFAs are not yet frequently applied at a crime scene. This review describes (academic) developments of LFAs for forensic applications, focusing on biological and chemical applications, whereby the main advantages and disadvantages of LFAs for the different forensic applications are summarized. Additionally, a critical review is provided, discussing why LFAs are not frequently applied within the forensic field and highlighting the steps that are needed to bring LFAs to the forensic market.
Hoe kan zorgvernieuwing structureel en efficiënt gerealiseerd worden door inzet van 3D-technieken en welke praktische medische vraagstukken worden hiermee opgelost? Dat was een vraag die voortkwam uit experimenten van MST (afdeling Radiotherapie) voor het KIEM-project ‘Zorgvernieuwing door de inzet van 3D’. Hierin is onderzoek gedaan naar state-of-the-art 3D-technieken in de zorg. Op basis hiervan is een roadmap ontwikkeld waarin de kansen voor MST zijn samengevat. Dit heeft MST-intern geleid tot intensieve discussies over de vraag HOE deze 3D-technieken gerealiseerd kunnen worden in de huidige workflow. Uit de roadmap is een selectie gemaakt waar 3D-technieken een duidelijke meerwaarde kunnen bieden, als deze goed geïntegreerd kunnen worden met de ontwikkelende workflow binnen het in het KIEM-project opgezette Medisch-3D-Printlab bij het MST. De uitdaging is enerzijds om 3D-printen succesvol te introduceren en implementeren in de bestaande workflow van verschillende afdelingen in het ziekenhuis, waardoor innovatie in de zorg plaatsvindt en de kwaliteit van deze zorg verbeterd kan worden. Anderzijds een volgende stap in de mogelijkheden van 3Dprinten te verkennen: combinatie harde-zachte materialen. Het MST, Saxion Lectoraat Industrial Design en FabLab Enschede slaan de handen ineen, samen de met nieuwe partners uit de regio Siemonsma Tandtechniek en LAYaLAY om 3D-technieken daadwerkelijk te implementeren binnen de complexe wereld van het ziekenhuis. Doel van dit project is drieledig: 1) Implementatie van nieuwe 3D-technieken uit de roadmap en deze te optimaliseren aan de hand van praktijkcasussen. 2) Het verkennen van kansen binnen verschillende medische disciplines alsmede nieuwe 3Dscan/ printtechnieken (combinatie van harde-zachte materialen). 3) Het bijeenbrengen van nieuwe kennispartners en andere specialismen om dit thema grootschalig uit te werken in een vervolgproject.
National forestry Commission (SBB) and National Park De Biesbosch. Subcontractor through NRITNational parks with large flows of visitors have to manage these flows carefully. Methods of data collection and analysis can be of help to support decision making. The case of the Biesbosch National Park is used to find innovative ways to figure flows of yachts, being the most important component of water traffic, and to create a model that allows the estimation of changes in yachting patterns resulting from policy measures. Recent policies oriented at building additional waterways, nature development areas and recreational concentrations in the park to manage the demands of recreation and nature conservation offer a good opportunity to apply this model. With a geographical information system (GIS), data obtained from aerial photographs and satellite images can be analyzed. The method of space syntax is used to determine and visualize characteristics of the network of leisure routes in the park and to evaluate impacts resulting from expected changes in the network that accompany the restructuring of waterways.
Chemical preservation is an important process that prevents foods, personal care products, woods and household products, such as paints and coatings, from undesirable change or decomposition by microbial growth. To date, many different chemical preservatives are commercially available, but they are also associated with health threats and severe negative environmental impact. The demand for novel, safe, and green chemical preservatives is growing, and this process is further accelerated by the European Green Deal. It is expected that by the year of 2050 (or even as soon as 2035), all preservatives that do not meet the ‘safe-by-design’ and ‘biodegradability’ criteria are banned from production and use. To meet these European goals, there is a large need for the development of green, circular, and bio-degradable antimicrobial compounds that can serve as alternatives for the currently available biocidals/ preservatives. Anthocyanins, derived from fruits and flowers, meet these sustainability goals. Furthermore, preliminary research at the Hanze University of Applied Science has confirmed the antimicrobial efficacy of rose and tulip anthocyanin extracts against an array of microbial species. Therefore, these molecules have the potential to serve as novel, sustainable chemical preservatives. In the current project we develop a strategy consisting of fractionation and state-of-the-art characterization methods of individual anthocyanins and subsequent in vitro screening to identify anthocyanin-molecules with potent antimicrobial efficacy for application in paints, coatings and other products. To our knowledge this is the first attempt that combines in-depth chemical characterization of individual anthocyanins in relation to their antimicrobial efficacy. Once developed, this strategy will allow us to single out anthocyanin molecules with antimicrobial properties and give us insight in structure-activity relations of individual anthocyanins. Our approach is the first step towards the development of anthocyanin molecules as novel, circular and biodegradable non-toxic plant-based preservatives.
