This research conducts a meticulous examination of the determinants influencing dividend payout dynamics among firms listed on the Korean Stock Exchange (KSE) from 1995 to 2021, a period characterized by profound economic fluctuations. By leveraging a dynamic panel data model and the Generalized Method of Moments (GMM) for estimation, the study addresses endogeneity concerns while exploring the effects of firm-specific and macroeconomic variables on dividend yields. The investigation delineates three distinct economic phases: normal conditions, financial crises, and the aggregate study period, facilitating a granular understanding of firms’ dividend payout adaptability under varying economic landscapes. Empirical findings underscore the persistence of dividend payments, revealing a variable adjustment speed toward target dividend yields contingent upon the economic context, with an expedited adjustment observed during crises. Crucially, firm profitability emerges as a consistent determinant of dividend yields across all examined periods, whereas the influence of macroeconomic variables is notably more pronounced during periods of economic normalcy. This research elucidates the complex interplay between internal corporate strategies and external economic pressures in shaping dividend policies, thereby enriching the discourse on dividend payout behavior in the context of Korea’s economic evolution from an emerging to a developed market.
Enhancing sweetness of vegetables by addition of sucrose or sweeteners can increase acceptance but is not necessarily desirable. An alternative strategy could be to combine vegetables with other vegetables. By offering combinations of vegetables it might be possible to suppress bitterness, enhance sweetness and provide texture variety leading to increased acceptance. The aim of this study was to determine the influence of combining vegetables with other vegetables on sensory properties and acceptance. Carrot (sweet), cucumber (neutral), green bell pepper (bitter) and red bell pepper (sour) were assessed individually and in combination with the other three vegetables in two mixing ratios (1:2 and 2:1). Additionally, four combinations of three vegetables (mixing ratio 1:1:1) were assessed. A trained panel (n = 24) evaluated taste, flavour and texture and a consumer panel (n = 83) evaluated acceptance of all vegetables and combinations. Combining green bell pepper with carrot (1:2 and 2:1) increased sweetness and decreased bitterness. Combining cucumber, carrot or red bell pepper with green bell pepper (1:2) increased bitterness. Mainly sweetness and bitterness were associated with acceptance whereas texture (crunchiness, firmness and juiciness) did not strongly influence acceptance. Cucumber was the most accepted vegetable followed by carrot, red bell pepper and green bell pepper. Acceptance of vegetable combinations can differ from acceptance of individual vegetables depending on vegetable type and mixing ratio. Only 3 of 16 vegetable combinations had higher acceptance compared to the least accepted vegetable in the combination and similar acceptance as the more accepted vegetable in the combination. For 13 of 16 vegetable combinations acceptance did not increase compared to acceptance of individual vegetables. These findings suggest that strategies aimed at increasing vegetable consumption can be devised using specific combinations of vegetables.
This study provides an in-depth understanding of the perceptions of patients with T2DM before use (acceptability) and after use (acceptance) regarding 4 different mobile health apps for diabetes control and self-management. This study was part of the TOPFIT Citizenlab project. TOPFIT Citizenlab is a 3-year research and innovation program in the eastern part of the Netherlands. Citizens, health care professionals (HCPs), and companies have joined forces with researchers to develop and implement technology for health and well-being.
MULTIFILE
Coastal nourishments, where sand from offshore is placed near or at the beach, are nowadays a key coastal protection method for narrow beaches and hinterlands worldwide. Recent sea level rise projections and the increasing involvement of multiple stakeholders in adaptation strategies have resulted in a desire for nourishment solutions that fit a larger geographical scale (O 10 km) and a longer time horizon (O decades). Dutch frontrunner pilot experiments such as the Sandmotor and Ameland inlet nourishment, as well as the Hondsbossche Dunes coastal reinforcement project have all been implemented from this perspective, with the specific aim to encompass solutions that fit in a renewed climate-resilient coastal protection strategy. By capitalizing on recent large-scale nourishments, the proposed Coastal landSCAPE project C-SCAPE will employ and advance the newly developed Dynamic Adaptive Policy Pathways (DAPP) approach to construct a sustainable long-term nourishment strategy in the face of an uncertain future, linking climate and landscape scales to benefits for nature and society. Novel long-term sandy solutions will be examined using this pathways method, identifying tipping points that may exist if distinct strategies are being continued. Crucial elements for the construction of adaptive pathways are 1) a clear view on the long-term feasibility of different nourishment alternatives, and 2) solid, science-based quantification methods for integral evaluation of the social, economic, morphological and ecological outcomes of various pathways. As currently both elements are lacking, we propose to erect a Living Lab for Climate Adaptation within the C-SCAPE project. In this Living Lab, specific attention is paid to the socio-economic implications of the nourished landscape, as we examine how morphological and ecological development of the large-scale nourishment strategies and their design choices (e.g. concentrated vs alongshore uniform, subaqueous vs subaerial, geomorphological features like artificial lagoons) translate to social acceptance.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
CRISPR/Cas genome engineering unleashed a scientific revolution, but entails socio-ethical dilemmas as genetic changes might affect evolution and objections exist against genetically modified organisms. CRISPR-mediated epigenetic editing offers an alternative to reprogram gene functioning long-term, without changing the genetic sequence. Although preclinical studies indicate effective gene expression modulation, long-term effects are unpredictable. This limited understanding of epigenetics and transcription dynamics hampers straightforward applications and prevents full exploitation of epigenetic editing in biotechnological and health/medical applications.Epi-Guide-Edit will analyse existing and newly-generated screening data to predict long-term responsiveness to epigenetic editing (cancer cells, plant protoplasts). Robust rules to achieve long-term epigenetic reprogramming will be distilled based on i) responsiveness to various epigenetic effector domains targeting selected genes, ii) (epi)genetic/chromatin composition before/after editing, and iii) transcription dynamics. Sustained reprogramming will be examined in complex systems (2/3D fibroblast/immune/cancer co-cultures; tomato plants), providing insights for improving tumor/immune responses, skin care or crop breeding. The iterative optimisations of Epi-Guide-Edit rules to non-genetically reprogram eventually any gene of interest will enable exploitation of gene regulation in diverse biological models addressing major societal challenges.The optimally balanced consortium of (applied) universities, ethical and industrial experts facilitates timely socioeconomic impact. Specifically, the developed knowledge/tools will be shared with a wide-spectrum of students/teachers ensuring training of next-generation professionals. Epi-Guide-Edit will thus result in widely applicable effective epigenetic editing tools, whilst training next-generation scientists, and guiding public acceptance.
