Posterpresentatie gegeven tijdens bezoek SBE (Samenwerkende Bedrijven Eemsdelta) aan de Hanzehogeschool
In the BBI-JU project LIBBIO, institutions across Europe researched the opportunities around the Andean Lupin. The business case of the Andean Lupin can be compared to that of the soybean. Using green processing technologies, we can use it for the production of consumer products, food and feed. Learn more about how this can be achieved in this video.
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PURPOSE: The purpose of this review article is to describe characteristics of auditory processing disorders (APD) by evaluating the literature in which children with suspected or diagnosed APD were compared with typically developing children and to determine whether APD must be regarded as a deficit specific to the auditory modality or as a multimodal deficit.METHOD: Six electronic databases were searched for peer-reviewed studies investigating children with (suspected) APD in comparison with typically developing peers. Relevant studies were independently reviewed and appraised by 2 reviewers. Methodological quality was quantified using the American Speech-Language-Hearing Association's levels of evidence.RESULTS: Fifty-three relevant studies were identified. Five studies were excluded because of weak internal validity. In total, 48 studies were included, of which only 1 was classified as having strong methodological quality. Significant dissimilarities were found between children referred with listening difficulties and controls. These differences relate to auditory and visual functioning, cognition, language, reading, and physiological and neuroimaging measures.CONCLUSIONS: Methodological quality of most of the incorporated studies was rated moderate due to the heterogeneous groups of participants, inadequate descriptions of participants, and the omission of valid and reliable measurements. The listening difficulties of children with APD may be a consequence of cognitive, language, and attention issues rather than bottom-up auditory processing.
Currently, many novel innovative materials and manufacturing methods are developed in order to help businesses for improving their performance, developing new products, and also implement more sustainability into their current processes. For this purpose, additive manufacturing (AM) technology has been very successful in the fabrication of complex shape products, that cannot be manufactured by conventional approaches, and also using novel high-performance materials with more sustainable aspects. The application of bioplastics and biopolymers is growing fast in the 3D printing industry. Since they are good alternatives to petrochemical products that have negative impacts on environments, therefore, many research studies have been exploring and developing new biopolymers and 3D printing techniques for the fabrication of fully biobased products. In particular, 3D printing of smart biopolymers has attracted much attention due to the specific functionalities of the fabricated products. They have a unique ability to recover their original shape from a significant plastic deformation when a particular stimulus, like temperature, is applied. Therefore, the application of smart biopolymers in the 3D printing process gives an additional dimension (time) to this technology, called four-dimensional (4D) printing, and it highlights the promise for further development of 4D printing in the design and fabrication of smart structures and products. This performance in combination with specific complex designs, such as sandwich structures, allows the production of for example impact-resistant, stress-absorber panels, lightweight products for sporting goods, automotive, or many other applications. In this study, an experimental approach will be applied to fabricate a suitable biopolymer with a shape memory behavior and also investigate the impact of design and operational parameters on the functionality of 4D printed sandwich structures, especially, stress absorption rate and shape recovery behavior.
Electrohydrodynamic Atomization (EHDA), also known as Electrospray (ES), is a technology which uses strong electric fields to manipulate liquid atomization. Among many other areas, electrospray is currently used as an important tool for biomedical applications (droplet encapsulation), water technology (thermal desalination and metal recovery) and material sciences (nanofibers and nano spheres fabrication, metal recovery, selective membranes and batteries). A complete review about the particularities of this technology and its applications was recently published in a special edition of the Journal of Aerosol Sciences [1]. Even though EHDA is already applied in many different industrial processes, there are not many controlling tools commercially available which can be used to remotely operate the system as well as identify some spray characteristics, e.g. droplet size, operational mode, droplet production ratio. The AECTion project proposes the development of an innovative controlling system based on the electrospray current, signal processing & control and artificial intelligence to build a non-visual tool to control and characterize EHDA processes.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
