Publikationen

This Research to Practice Full Paper is driven by the question: In workshops to develop deep-learning API-features, how can trainer be effectively supported in specifying and formative assessing of individual tasks (i.e. the API-features) for each student? In formative assessment, the trainer’s main difficulty in specifying the tasks is to ensure that the challenges in a task are calibrated to the particular needs of a student at a particular time (i.e. the student’s available skills). While goals that are very high challenging lead to a student’s anxiety, goals that are too easy generate student’s disengagement and boredom. This paper presents a specification tool designed to support the trainers in practicing Hattie’s Visible Learning [1] pedagogy in dialogues for tasks specification and formative assessments. Its design enables two support functions in visualization; 1) a function to declare visually a task specification to make its mastery goals clear and progressively challenging, and 2) a function to refactor a task specification for visualizing formative assessment feedback in dialogues for reflection. Besides the two functions, its innovative design enables the flow model based analysis to understand student engagement. The analysis is according to Csikszentmihalyi’s flow model to diagnose, in dialogues for formative assessments, one of student's eight emotional states (i.e. boredom, apathy, worry, anxiety, control, arousal, and flow) in terms of challenge level and skill level. To verify the tool effectiveness in trainer-student Freirean dialogues, we conducted our experimental tests in workshops where students with different culture backgrounds, and different levels of prior skills have tasks to develop API-features based on deep-learning principles and algorithms. The algorithms selected in the test cases are for automatic classification of images or of text documents. The test results show the effective use of the tool to create conditions to overcome student’s negative emotions (e.g. worry or anxiety), and help him/her experience positive emotions (e.g. control or flow) in learning and mastering the algorithms; to put it differently, to create situations in initial specification and co-specification of tasks, where student’s skills are engaged by progressively higher challenges to understand the deep-learning based classifier algorithms.

Remote laboratories play an important role in modern education. Because of this, a multitude of different protocols and systems for building and integrating remote laboratories have been developed over the last years. This Paper analyses these different protocols and systems (SCORM / xAPI, IMS-LTI, IEEE 1876-2019, IVI / VISA, OPC-UA, Weblab-Deusto / LabsLand, GOLDi-Labs) and sorts them into different layers to build a protocol stack for implementing remote laboratories, accompanied by some examples of what is currently possible to implement. A gap in the protocol stack was identified between Controller and the whole Laboratory where no standardised protocol exists. Suggestions for the requirements of such a protocol are laid out. The new possibilities with such a protocol are presented by showing examples of new types of remote laboratories, followed by a short discussion of problems not yet solved by such a new protocol.

Die transkranielle Gleichstromstimulation mit schwachen Strömen (≤ 2 mA) ist ein etabliertes Verfahren zur Untersuchung des menschlichen Nervensystems und zur Behandlung psychologisch-neurologischer Erkrankungen. In den letzten Jahren hat die Stimulation des visuellen Systems, speziell der Retina, an Aufmerksamkeit gewonnen, da Hinweise auf positive Einflüsse einer transokularen Stromstimulation zur Behandlung neurodegenerativer retinaler Erkrankungen gefunden wurden. Bis heute fehlt jedoch ein Wirkungskonzept, das den Einfluss der Stromstimulation auf die verschiedenen retinalen Neuronen beschreibt. Aus Studien ist bekannt, dass ein visuell evoziertes Potential durch eine transkranielle Gleichstromstimulation des visuellen Cortex in den charakteristischen Amplituden beeinflusst werden kann. Daraus ergab sich das methodische Verfahren ein evoziertes Potential retinaler Herkunft, welches durch das Elektroretinogramm erfasst wird, in Kombination mit einer transokularen Stromstimulation zu nutzen, um den Einfluss der Stromstimulation auf die retinalen Zellen zu untersuchen. Durch Variation der visuellen Stimulationsparameter zur Generierung des Elektroretinogramms, ist es möglich, unterschiedliche retinale Neuronen in den Fokus zu nehmen. Im ersten Teil der Dissertation wurde ein grundlegendes Studienkonzept auf Basis des Verfahrens der experimentellen Prozessanalyse entwickelt. Aus diesem wurden Anforderungen an einen Mess- und Stimulationsplatz abgeleitet, um eine simultane transokulare Gleichstromstimulation und Aufnahme eines Elektroretinogramms zu ermöglichen. Des Weiteren wurden Anforderungen an das Studiendesign abgeleitet. Im zweiten Teil der Dissertation wurden insgesamt vier aufeinander aufbauende Probandenstudien durchgeführt, analysiert und interpretiert. In diesen wurden sowohl unterschiedliche retinale Neuronen als auch der Einfluss der Position der Stromstimulationselektroden untersucht. Aus den Ergebnissen wurde ein Wirkungskonzept für die transokulare Gleichstromstimulation auf die retinalen Neuronen abgeleitet. Dieses besagt, dass primär die retinalen Ganglienzellen während einer transokularen Gleichstromstimulation in ihrer elektrophysiologischen Aktivität beeinflusst werden. Die Ergebnisse der Dissertation lassen sich weiterführend für die Entwicklung und die Optimierung von Therapieverfahren zur Behandlung neurodegenerativer retinaler Erkrankungen sowie zur Entwicklung objektiver Messmethoden zum Nachweis einer transokularen Stromwirkung verwenden.

This work presents the application of droplet-based microfluidics for the cultivation of microspores from Brassica napus using the doubled haploid technology. Under stress conditions (e.g. heat shock) or by chemical induction a certain fraction of the microspores can be reprogrammed and androgenesis can be induced. This process is an important approach for plant breeding because desired plant properties can be anchored in the germline on a genetic level. However, the reprogramming rate of the microspores is generally very low, increasing it by specific stimulation is, therefore, both a necessary and challenging task. In order to accelerate the optimisation and development process, the application of droplet-based microfluidics can be a promising tool. Here, we used a tube-based microfluidic system for the generation and cultivation of microspores inside nL-droplets. Different factors like cell density, tube material and heat shock conditions were investigated to improve the yield of vital plant organoids. Evaluation and analysis of the stimuli response were done on an image base aided by an artificial intelligence cell detection algorithm. Droplet-based microfluidics allowed us to apply large concentration programs in small test volumes and to screen the best conditions for reprogramming cells by the histone deacetylase inhibitor trichostatin A and for enhancing the yield of vital microspores in droplets. An enhanced reprogramming rate was found under the heat shock conditions at 32 &ring;C for about 3 to 6 days. In addition, the comparative experiment with MTP showed that droplet cultivation with lower cell density (<10 cells per droplet) or adding media after 3 or 6 days significantly positively affects the microspore growth and embryo rate inside 120 nL droplets. Finally, the developed embryos could be removed from the droplets and further grown into mature plants. Overall, we demonstrated that the droplet-based tube system is suitable for implementation in an automated, miniaturized system to achieve the induction of embryogenic development in haploid microspore stem cells of Brassica napus.

As data analytics becomes more crucial to digital systems, so grows the importance of characterizing the database queries that admit a more efficient evaluation. We consider the tractability yardstick of answer enumeration with a polylogarithmic delay after a linear-time preprocessing phase. Such an evaluation is obtained by constructing, in the preprocessing phase, a data structure that supports polylogarithmic-delay enumeration. In this article, we seek a structure that supports the more demanding task of a “random permutation”: polylogarithmic-delay enumeration in truly random order. Enumeration of this kind is required if downstream applications assume that the intermediate results are representative of the whole result set in a statistically meaningful manner. An even more demanding task is that of “random access”: polylogarithmic-time retrieval of an answer whose position is given. We establish that the free-connex acyclic CQs are tractable in all three senses: enumeration, random-order enumeration, and random access; and in the absence of self-joins, it follows from past results that every other CQ is intractable by each of the three (under some fine-grained complexity assumptions). However, the three yardsticks are separated in the case of a union of CQs (UCQ): while a union of free-connex acyclic CQs has a tractable enumeration, it may (provably) admit no random access. We identify a fragment of such UCQs where we can guarantee random access with polylogarithmic access time (and linear-time preprocessing) and a more general fragment where we can guarantee tractable random permutation. For general unions of free-connex acyclic CQs, we devise two algorithms with relaxed guarantees: one has logarithmic delay in expectation, and the other provides a permutation that is almost uniformly distributed. Finally, we present an implementation and an empirical study that show a considerable practical superiority of our random-order enumeration approach over state-of-the-art alternatives.