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A commentary on Four conceptual fallacies in mapping the time course of recognition by VanRullen, R. (2011). Front. Psychol. 2:365. doi: 10.3389/fpsyg.2011.00365 Does filtering preclude us from studying ERP time-courses? by Rousselet, G. A. (2012). Front. Psychol. 3:131. doi: 10.3389/fpsyg.2012.00131

Syfte: Att ta reda på hur lång livslängd en bildplatta har avseende slitage och bildkvalité.Material och metod: Tre fabriksnya bildplattor användes för att undersöka hur en enskild faktor i arbetsgången för bildgenerering påverkar bildkvalitén. Den första plattan exponerades och skannades 300 gånger. Platta nummer två användes för att undersöka effekten av totalt 300 av- och påtagningar i en frigolithållare, och platta tre användes för motsvarande test av en plasthållare. Exponering skedde utan patient och mot en neutral bakgrund. För samtliga plattor togs i initialskedet en referensbild, och resulterande bilder från testerna granskades i Planmeca Romexis 3.8 och bedömdes enligt en skala 0-3. Plattorna i sig granskades även okulärt, och test av uniformitet gjordes av referensbild och bild 300 i serie 1 med hjälp av ImageJ. Resultat: Samtliga bilder från samtliga plattor bedömdes vara likvärdiga med referensbild. Vid okulär granskning var reporna klart mer uttalade hos den platta som skannats 300 gånger, men reporna återfanns endast på den sida som ej är avsedd att exponeras. Test av uniformitet fann ingen skillnad mellan referensbild och bild nr 300 i serie 1. Slutsats: Studien visar att varken röntgenexponering, skanning eller av- och påtagning i hållare av två olika slag har någon inverkan på bildkvalité efter 300 upprepningar då momenten gjordes var för sig. Vi konkluderar att plattan sannolikt är som mest sårbar då den placeras intraoralt, och föreslår att alla moment gjorda i följd delvis kan svara för den reduktion av bildkvalité som observerats i andra studier. / Aim: To determine the longevity of photostimulable storage phosphor plates (PSPs) with respect to wear and image quality. Method: Three brand new PSPs were used to assess how a solitary factor in the picture generation process affects the picture quality. The first plate was exposed and scanned 300 times. Plate number two was used to assess the effect of mounting and demounting the plate 300 times onto a holder made of styrofoam, and the third plate was used for a corresponding test with a plastic holder. A flat surface was exposed and no patients were involved. A reference picture was taken initially for each plate, and the resulting pictures from the tests were viewed using Planmeca Romexis 3.8 and were evaluated on a scale from 0-3. The individual plates also underwent ocular inspection, and a uniformity test was performed on the first and last picture taken with plate 1, using ImageJ. Results: Each picture from each plate was deemed equivalent to the reference picture. The ocular inspection revealed a more distinct band of scratches on the plate that was scanned the most, although the scratches were only found on the side not meant to receive exposure. No difference in uniformity was found between the first and last picture taken using plate 1. Conclusion: X-ray exposure, scanning and mounting and demounting of PSPs onto holders of two different kinds do not affect the picture quality after 300 repetitions when done separately. We conclude that the plate is likely most susceptible to wear when placed intraorally, and suggest that all the steps made in succession can partly account for the reduction in picture quality observed in other studies.

Laser speckle contrast imaging (LSCI) is a non-invasive method for assessment of microcirculatory blood flow. The technique is based on analysis of speckle patterns to build 2D maps of perfusion with high spatial and temporal resolution. A drawback of the method is that it is highly sensitive to motion artifacts since the perfusion estimates are based on quantification of the motion blurring in the images. The camera is today limited to a bulky stand for good measurements, but even as it is fixed, it does not ensure that the patient is completely still. In many clinical settings, it would be advantageous to have a more flexible camera and to be able to detect if an image is influenced by external motion. Multi-exposure laser speckle contrast imaging (MELSCI) is an extension to LSCI that utilizes the contrast from multiple exposure times. The gain in information has paved way for more accurate perfusion estimates. The technique has been limited due to its computational complexity, but recently a real time system has been developed. The goals of this thesis was twofold, firstly find a quantifiable measure of motion artifacts to be able to evaluate and compare LSCI and MELSCI. Secondly, propose an algorithm that detects movements in LSCI recordings. Motion artifacts in LSCI and MELSCI were investigated by developing a setup where repeatable movements could be made. Measurements of a hand influenced by motions of different speeds and directions were acquired and the relative difference between motion and static states were calculated and compared for the two systems. The relative difference of the MELSCI measurements were lower for all speeds above 0.57 mm/s, indicating more robustness to motion artifacts. A detection algorithm using image registration to calculate the instantaneous speed in each frame of the recording was developed. The method successfully detects movements perpendicular to the camera and shows that the intensity images of an LSCI recording can be used to give a direct indication of when movement has occurred.

This thesis explores best practices in teaching religious history in public schools using primary sources. Lesson plans on specific sites and themes within the history of religious freedom in Philadelphia contextualize and celebrate the religious diversity that the city has known since its inception. By understanding how this diversity developed over time and through obstacles, students will be more willing and motivated to do their individual part to maintain and protect religious liberty. This goal is emphasized through the use of primary sources, which bring gravity, accessibility, and engagement to a topic that might otherwise be considered controversial, distant, or unnecessary. / History

Rapid technological advances in artificial intelligence (AI), data analytics, big data, the semantic web, the Internet of Things (IoT), and cloud and mobile computing have given rise to a new generation of AI-driven recommendation agents (RAs). These agents continue to evolve and offer potential for use in a variety of application domains. However, extant information systems (IS) research has predominantly focused on user perceptions and evaluations of traditional non-intelligent product-brokering recommendation agents (PRAs), supported by empirical studies on custom-built experimental RAs that heavily rely on explicit user preference elicitations. To address the lack of research in the new generation of intelligent RAs (RAs 2.0), this dissertation aims to study consumer responses to AI-driven RAs using an affordance perspective. Notably, this research is the first in the IS discourse to link RA design artifacts, RA affordances, RA outcomes, and user continuance. It examines how actualized RA affordances influence user engagements with and evaluations of these highly personalized systems, which increasingly focus on user experiences and long-term relationships. This three-essay dissertation, consisting of one theory-building paper and two empirical studies, conceptually defines "RAs 2.0," proposes a comprehensive theoretical framework with testable propositions, and conducts two empirical studies guided by smaller carved-out models to test the validity of the comprehensive framework. The research is expected to enrich the IS literature on RAs and identify potential areas for future research. Moreover, it offers key implications for industry professionals regarding the effective system development of the new generation of intelligent RAs. / Doctor of Philosophy / Rapid technological advances in artificial intelligence (AI), data analytics, big data, the semantic web, the Internet of Things (IoT), and cloud and mobile computing have given rise to a new generation of AI-driven recommendation agents (RAs). These agents continue to evolve and offer potential for use in a variety of application domains. This three-essay dissertation, consisting of one theory-building paper and two empirical studies, conceptually defines "RAs 2.0," proposes a comprehensive theoretical framework with testable propositions, and conducts two empirical studies guided by smaller carved-out models to test the validity of the comprehensive framework. The research is expected to enrich the IS literature on RAs and identify potential areas for future research. Moreover, it offers key implications for industry professionals regarding the effective system development of the new generation of intelligent RAs.

This diploma thesis deals with reduction of metal artifacts in CT data with submicron resolution. The first part of this thesis briefly describes x-ray computed tomography followed by the description of artifacts of tomographic images and existing approaches of the reduction of metal artifacts. In the second part proposed methods of reduction of metal artifacts and their implementation in Matlab programming environment are described. Finally functionality of algorithms is tested on a newly created database and the results are compared, evaluated and discussed.

Studying newborns in the first days of life prior to experiencing the world provides remarkable insights into the neurocognitive predispositions that humans are endowed with. First, it helps us to improve our current knowledge of the development of a typical brain. Secondly, it potentially opens new pathways for earlier diagnosis of several developmental neurocognitive disorders such as Autism Spectrum Disorder (ASD). While most studies investigating early cognition in the literature are purely behavioural, recently there has been an increasing number of neuroimaging studies in newborns and infants. Electroencephalography (EEG) is one of the most optimal neuroimaging technique to investigate neurocognitive functions in human newborns because it is non-invasive and quick and easy to mount on the head. Since EEG offers a versatile design with custom number of channels/electrodes, an ergonomic wearable solution could help study newborns outside clinical settings such as their homes. Compared to adult EEG, newborn EEG data are different in two main aspects: 1) In experimental designs investigating stimulus-related neural responses, collected data is extremely short in length due to the reduced attentional span of newborns; 2) Data is heavily contaminated with noise due to their uncontrollable movement artifacts. Since EEG processing methods for adults are not adapted to very short data length and usually deal with well-defined, stereotyped artifacts, they are unsuitable for newborn EEG. As a result, researchers manually clean the data, which is a subjective and time-consuming task. This thesis work is specifically dedicated to developing (semi-) automated novel signal processing methods for noise removal and for extracting reliable neural responses specific to this population. The solutions are proposed for both high-density EEG for traditional lab-based research and wearable EEG for clinical applications. To this end, this thesis, first, presents novel signal processing methods applied to newborn EEG: 1) Local Outlier Factor (LOF) for detecting and removing bad/noisy channels; 2) Artifacts Subspace Reconstruction (ASR) for detecting and removing or correcting bad/noisy segments. Then, based on these algorithms and other preprocessing functionalities, a robust preprocessing pipeline, Newborn EEG Artifact Removal (NEAR), is proposed. Notably, this is the first time LOF is explored for EEG bad channel detection, despite being a popular outlier detection technique in other kinds of data such as Electrocardiogram (ECG). Even if ASR is already an established artifact real algorithm originally developed for mobile adult EEG, this thesis explores the possibility of adapting ASR for short newborn EEG data, which is the first of its kind. NEAR is validated on simulated, real newborn, and infant EEG datasets. We used the SEREEGA toolbox to simulate neurologically plausible synthetic data and contaminated a certain number of channels and segments with artifacts commonly manifested in developmental EEG. We used newborn EEG data (n = 10, age range: 1 and 4 days) recorded in our lab based on a frequency-tagging paradigm. The chosen paradigm consists of visual stimuli to investigate the cortical bases of facelike pattern processing, and the results were published in 2019. To test NEAR performance on an older population with an event-related design (ERP) and with data recorded in another lab, we also evaluated NEAR on infant EEG data recorded on 9-months-old infants (n = 14) with an ERP paradigm. The experimental paradigm for these datasets consists of auditory stimulus to investigate the electrophysiological evidence for understanding maternal speech, and the results were published in 2012. Since authors of these independent studies employed manual artifact removal, the obtained neural responses serve as ground truth for validating NEAR’s artifact removal performance. For comparative evaluation, we considered the performance of two state-of-the-art pipelines designed for older infants. Results show that NEAR is successful in recovering the neural responses (specific to the EEG paradigm and the stimuli) compared to the other pipelines. In sum, this thesis presents a set of methods for artifact removal and extraction of stimulus-related neural responses specifically adapted to newborn and infant EEG data that will hopefully contribute to strengthening the reliability and reproducibility of developmental cognitive neuroscience studies, both in research laboratories and in clinical applications.

Computed tomography (CT) is a widely used medical imaging modality. By rotating an x-ray tube and an x-ray detector around the patient, a CT scanner is able to measure the x-ray transmission from all directions and form an image of the patient’s interior. CT scanners in clinical use today all use energy-integrating detectors, which measure the total incident energy for each measurement interval. A photon-counting detector, on the other hand, counts the number of incoming photons and can in addition measure the energy of each photon by comparing it to a number of energy thresholds. Using photon- counting detectors in computed tomography could lead to improved signal-to-noise ratio, higher spatial resolution and improved spectral imaging which allows better visualization of contrast agents and more reliable quantitative measurements. In this Thesis, the feasibility of using a photon-counting silicon-strip detector for CT is investigated. In the first part of the Thesis, the necessary performance requirements on such a detector is investigated in two different areas: the detector element homogeneity and the capability of handling high photon fluence rates. A metric of inhomogeneity is proposed and used in a simulation study to evaluate different inhomogeneity compensation methods. Also, the photon fluence rate incident on the detector in a scanner in clinical use today is investigated for different patient sizes through dose rate measurements together with simulations of transmission through patient im- ages. In the second part, a prototype detector module is used to demonstrate new applications enabled by the energy resolution of the detector. The ability to generate material-specific images of contrast agents with iodine and gadolinium is demonstrated. Furthermore, it is shown theoretically and ex- perimentally that interfaces in the image can be visualized by imaging the so-called nonlinear partial volume effect. The results suggest that the studied silicon-strip detector is a promising candidate for photon-counting CT.