Semantic unification during sentence comprehension has been associated with amplitude change of the N400 in event-related potential (ERP) studies, and activation in the left inferior frontal gyrus (IFG) in functional magnetic resonance imaging (fMRI) studies. However, the specificity of this activation to semantic unification remains unknown. To more closely examine the brain processes involved in semantic unification, we employed simultaneous EEG-fMRI to time-lock the semantic unification related N400 change, and integrated trial-by-trial variation in both N400 and BOLD change beyond the condition-level BOLD change difference measured in traditional fMRI analyses. Participants read sentences in which semantic unification load was parametrically manipulated by varying cloze probability. Separately, ERP and fMRI results replicated previous findings, in that semantic unification load parametrically modulated the amplitude of N400 and cortical activation. Integrated EEG-fMRI analyses revealed a different pattern in which functional activity in the left IFG and bilateral supramarginal gyrus (SMG) was associated with N400 amplitude, with the left IFG activation and bilateral SMG activation being selective to the condition-level and trial-level of semantic unification load, respectively. By employing the EEG-fMRI integrated analyses, this study among the first sheds light on how to integrate trial-level variation in language comprehension.
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This paper describes the concept of a new algorithm to control an Unmanned Aerial System (UAS) for accurate autonomous indoor flight. Inside a greenhouse, Global Positioning System (GPS) signals are not reliable and not accurate enough. As an alternative, Ultra Wide Band (UWB) is used for localization. The noise is compensated by combining the UWB with the delta position signal from a novel optical flow algorithm through a Kalman Filter (KF). The end result is an accurate and stable position signal with low noise and low drift.
from the article: The demand for a wireless CO2 solution is ever increasing. One of the biggest problems with the majority of commercial available CO2 sensors is the high energy consumption which makes them unsuitable for battery operation. Possible candidates for CO2 sensing in a low power wireless application are very limited and show a problematic calibration process. This study focuses on one of those EMF candidates, which is a Ag4RbI5 based sensor. This EMF sensor is based on the potentiometric principle and consumes no energy. The EMF cell was studied in a chamber where humidity, temperature and CO2 level could be controlled. This study gives an detailed insight in the different drift properties of the potentiometric CO2 sensor and a method to amplify the sensors signal. Furthermore, a method to minimize the several types of drift is given. With this method the temperature drift can be decreased by a factor 10, making the sensor a possible candidate for a wireless CO2 sensor network.
In het project werken onderzoekers van het Lectoraat samen met publieke organisaties toe naar een tool waarmee onderstromen in het publieke debat rondom issues eerder kunnen worden opgemerkt. We exploreren met welk algoritme we patronen in geruchtvorming en mobilisatie kunnen opsporen, en tevens hoe we de interactie tussen newsroom-analisten en de output van een monitoring tool het beste kunnen vormgeven.Doel Het doel van dit project is een brede en structureel toepasbare aanpak van het issuemanagement: Hoe kunnen de communicatieprofessionals van publieke organisaties potentiële issues op sociale media vroegtijdig opmerken? Resultaten We willen dit bereiken door enerzijds kennis en inzicht te vergaren en anderzijds de uitkomsten daarvan voor publieke organisaties te vertalen in praktische handgrepen: tools, handleiding, training. Looptijd 01 oktober 2022 - 30 september 2024 Aanpak Via cases ingebracht door de praktijkpartners en focusgroepen staan we in nauw contact met het consortium. In de eerste werkpakketten onderzoeken we de verschillende cases aan de hand van discoursanalyse. De inzichten die we hierbij opdoen, gebruiken we vervolgens om te bekijken hoe we de interactie tussen mens en machine het beste kunnen vormgeven en wel zo dat er ten behoeve van de communicatie en het management van issues via interactieve visualisaties steeds weer triggers afgegeven worden. Op basis van de opgedane inzichten richten we een interface in. Deze maakt het analisten en communicatieprofessionals mogelijk om vroegtijdig issues te signaleren.
In het project werken onderzoekers van het Lectoraat samen met publieke organisaties toe naar een tool waarmee onderstromen in het publieke debat rondom issues eerder kunnen worden opgemerkt. We exploreren met welk algoritme we patronen in geruchtvorming en mobilisatie kunnen opsporen, en tevens hoe we de interactie tussen newsroom-analisten en de output van een monitoring tool het beste kunnen vormgeven.
Carboxylated cellulose is an important product on the market, and one of the most well-known examples is carboxymethylcellulose (CMC). However, CMC is prepared by modification of cellulose with the extremely hazardous compound monochloracetic acid. In this project, we want to make a carboxylated cellulose that is a functional equivalent for CMC using a greener process with renewable raw materials derived from levulinic acid. Processes to achieve cellulose with a low and a high carboxylation degree will be designed.
