Teaching a Robot to Drive - A Skill Learning Inspired Approach

Roboter können unser Leben erleichtern, indem sie für uns unangenehme, oder sogar gefährliche Aufgaben übernehmen. Um sie effizient einsetzen zu können, sollten sie autonom, adaptiv und einfach zu instruieren sein. Traditionelle 'white-box'-Ansätze in der Robotik basieren auf dem Verständnis des Ingenieurs der unterliegenden physikalischen Struktur des gegebenen Problems. Ausgehend von diesem Verständnis kann der Ingenieur eine mögliche Lösung finden und es in dem System implementieren. Dieser Ansatz ist sehr mächtig, aber gleichwohl limitiert. Der wichtigste Nachteil ist, dass derart erstellte Systeme von vordefiniertem Wissen abhängen und deswegen jedes neue Verhalten den gleichen, teuren Entwicklungszyklus benötigt. Im Gegensatz dazu sind Menschen und einige andere Tiere nicht auf ihre angeborene Verhalten beschränkt, sondern können während ihrer Lebenszeit vielzählige weitere Fähigkeiten erwerben. Zusätzlich scheinen sie dazu kein detailliertes Wissen über den (physikalische) Ablauf einer gegebenen Aufgabe zu benötigen. Diese Eigenschaften sind auch für künstliche Systeme wünschenswert. Deswegen untersuchen wir in dieser Dissertation die Hypothese, dass Prinzipien des menschlichen Fähigkeitslernens zu alternativen Methoden für adaptive Systemkontrolle führen können. Wir untersuchen diese Hypothese anhand der Aufgabe des Autonomen Fahrens, welche ein klassiches Problem der Systemkontrolle darstellt und die Möglichkeit für vielfältige Applikationen bietet. Die genaue Aufgabe ist das Erlernen eines grundlegenden, antizipatorischen Fahrverhaltens von einem menschlichem Lehrer. Nachdem wir relevante Aspekte bezüglich des menschlichen Fähigkeitslernen aufgezeigt haben, und die Begriffe 'interne Modelle' und 'chunking' eingeführt haben, beschreiben wir die Anwendung dieser auf die gegebene Aufgabe. Wir realisieren chunking mit Hilfe einer Datenbank in welcher Beispiele menschlichen Fahreverhaltens gespeichert werden und mit Beschreibungen der visuell erfassten Strassentrajektorie verknüpft werden. Dies wird zunächst innerhalb einer Laborumgebung mit Hilfe eines Roboters verwirklicht und später, im Laufe des Europäischen DRIVSCO Projektes, auf ein echtes Auto übertragen. Wir untersuchen ausserdem das Erlernen visueller 'Vorwärtsmodelle', welche zu den internen Modellen gehören, sowie ihren Effekt auf die Kontrollperformanz beim Roboter. Das Hauptresultat dieser interdisziplinären und anwendungsorientierten Arbeit ist ein System, welches in der Lage ist als Antwort auf die visuell wahrgenommene Strassentrajektorie entsprechende Aktionspläne zu generieren, ohne das dazu metrische Informationen benötigt werden. Die vorhergesagten Aktionen in der Laborumgebung sind Lenken und Geschwindigkeit. Für das echte Auto Lenken und Beschleunigung, wobei die prediktive Kapazität des Systems für Letzteres beschränkt ist. D.h. der Roboter lernt autonomes Fahren von einem menschlichen Lehrer und das Auto lernt die Vorhersage menschlichen Fahrverhaltens. Letzteres wurde während der Begutachtung des Projektes duch ein internationales Expertenteam erfolgreich demonstriert. Das Ergebnis dieser Arbeit ist relevant für Anwendungen in der Roboterkontrolle und dabei besonders in dem Bereich intelligenter Fahrerassistenzsysteme

Endothelial cell apoptosis in brown adipose tissue of rats induced by hyperinsulinaemia: the possible role of TNF-α

The aim of the present study was to investigate whether hyperinsulinaemia, which frequently precedes insulin resistance syndrome (obesity, diabetes), induces apoptosis of endothelial cells (ECs) in brown adipose tissue (BAT) and causes BAT atrophy and also, to investigate the possible mechanisms underlying ECs death. In order to induce hyperinsuli-naemia, adult male rats of Wistar strain were treated with high dose of insulin (4 U/kg, intraperitonely) for one or three days. Examinations at ultrastructural level showed apoptotic changes of ECs, allowing us to point out that changes mainly but not exclusively, occur in nuclei. Besides different stages of condensation and alterations of the chromatin, nuclear fragmentation was also observed. Higher number of ECs apoptotic nuclei in the BAT of hyperinsulinaemic rats was also confirmed by propidium iodide staining. Immunohistochemical localization of tumor necrosis factor-alpha (TNF-α) revealed increased expression in ECs of BAT of hyperinsulinaemic animals, indicating its possible role in insulin-induced apoptotic changes. These results suggest that BAT atrophy in hyperinsulinaemia is a result of endothelial and adipocyte apoptosis combined, rather than any of functional components alone

Fractal and stereological analyses of insulin-induced rat exocrine pancreas remodelling

Background: The effect of insulin on the endocrine pancreas has been the subject of extensive study, but quantitative morphometric investigations of the exocrine pancreas are scarce. This study was therefore undertaken to investigate the effect of acute and chronic insulin administration (two doses, 0.4 IU and 4 IU) on the morphology of rat pancreas acini. Materials and methods: Semi-fine sections stained with methylene blue and basic fuchsine or haematoxylin and eosin-stained 5-micrometer thick paraffin sections were used for fractal and stereological analysis of exocrine acini. Acute insulin treatment, independent of applied doses increased fractal dimension in line with decreased lacunarity of pancreas acini. Chronic low dose insulin decreased fractal dimension and increased lacunarity of pancreas acini, but a high dose had the opposite effect. The volume densities (Vv) of cytoplasm, granules and nucleus are affected differently: acute low dose and high chronic dose significantly decreased granules Vv, and in line increased cytoplasmic Vv, whereas other examined structures showed slight changes without statistical significance. Results: The results obtained from this investigation indicate that insulin treatment induced structural remodelling of the exocrine pancreas suggesting a substantial role of insulin in its functioning. Conclusions: Additionally, we showed that fine architectural changes in acini could be detected by fractal analysis, suggesting this method as an alternative or addition to routine stereology

EPS-SJ exopolisaccharide produced by the strain Lactobacillus paracasei subsp. paracasei BGSJ2-8 is involved in adhesion to epithelial intestinal cells and decrease on E. coli association to Caco-2 cells

The aim of this study was to determine the role of an exopolysaccharide produced by natural dairy isolate Lactobacillus paracasei subsp. paracasei BGSJ2-8, in the adhesion to intestinal epithelial cells and a decrease in Escherichia coli's association with Caco-2 cells. Annotation of the BGSJ2-8 genome showed the presence of a gene cluster, epsSJ, which encodes the biosynthesis of the strain-specific exopolysaccharide EPS-SJ, detected as two fractions (P1 and P2) by size exclusion chromatography (SEC) coupled with multi-angle laser light scattering (MALLS) detection. SEC-MALLS analysis revealed that an EPS-SJ- mutant (EPS7, obtained by insertion mutagenesis of the glps_2198 gene encoding primary glycosyltransferase) does not produce the P2 fraction of EPS-SJ. Transmission electron microscopy showed that EPS7 mutant has a thinner cell wall compared to the EPS-SJ strain BGSJ2-83 (a plasmid free-derivative of BGSJ2-8). Interestingly, strain BGSJ2-83 showed higher adhesion to Caco-2 epithelial intestinal cell line than the EPS7 mutant. Accordingly, BGSJ2-83 effectively reduced E. coli ATCC25922's association with Caco-2 cells, while EPS7 did not show statistically significant differences. In addition, the effect of EPS-SJ on the proliferation of lymphocytes in gastrointestinal associated lymphoid tissue (GALT) was tested and the results showed that the reduction of GALT lymphocyte proliferation was higher by BGSJ2-83 than by the mutant. To the best of our knowledge this is the first report indicating that the presence of EPS (EPS-SJ) on the surface of lactobacilli can improve communication between bacteria and intestinal epithelium*Implying its possible role in gut colonization.Peer Reviewe

ESPAD Report 2019: Results From European School Survey Project on Alcohol and Other Drugs

The main purpose of the European School Survey Project on Alcohol and Other Drugs (ESPAD) is to collect comparable data on substance use and other forms of risk behaviour among 15- to 16-year-old students in order to monitor trends within, as well as between, countries. Between 1995 and 2019, seven waves of data collection were conducted across 49 European countries. This report presents selected key results. The full set of data on which the current report is based, including all of the standard tables, is available online (http://www.espad.org). All tables can be downloaded in Excel format and used for further analysi

Anticipatory driving for a robot-car based on supervised learning

Prediction and Planning are essential elements of successful human driving, making them equally important for autonomously driving systems. Many approaches achieve planning based on built-in world-knowledge. However, we show how a learning-based system can be extended to planning, needing little a priori knowledge. A car-like robot is trained by a human driver by constructing a database, where look ahead sensory information is stored together with action sequences. From that we achieve a novel form of velocity control, based only on information in image coordinates. For steering we employ a two-level approach in which database information is combined with an additional reactive controller. The result is a trajectory planning robot running at real-time, issuing steering and velocity control commands in a human mannerInformatikos fakultetasVytauto Didžiojo universiteta

Time scales of memory, learning, and plasticity.

After only about 10 days would the storage capacity of our nervous system be reached if we stored every bit of input. The nervous system relies on at least two mechanisms that counteract this capacity limit: compression and forgetting. But the latter mechanism needs to know how long an entity should be stored: some memories are relevant only for the next few minutes, some are important even after the passage of several years. Psychology and physiology have found and described many different memory mechanisms, and these mechanisms indeed use different time scales. In this prospect we review these mechanisms with respect to their time scale and propose relations between mechanisms in learning and memory and their underlying physiological basis.peerReviewe

Generalizing objects by analyzing language

Generalizing objects in an action-context by a robot, for example addressing the problem: ”Which items can be cut with which tools?”, is an unresolved and difficult problem. Answering such a question defines a complete action class and robots cannot do this so far. We use a bootstrapping mechanism similar to that known from human language acquisition, and combine language- with image-analysis to create action classes built around the verb (action) in an utterance. A human teaches the robot a certain sentence, for example: ”Cut a sausage with a knife”, from where on the machine generalizes the arguments (nouns) that the verb takes and searches for possible alternative nouns. Then, by ways of an internet-based image search and a classification algorithm, image classes for the alternative nouns are extracted, by which a large ”picture book” of the possible objects involved in an action is created. This concludes the generalization step. Using the same classifier, the machine can now also perform a recognition procedure. Without having seen the objects before, it can analyze a visual scene, discovering, for example, a cucumber and a mandolin, which match to the earlier found nouns allowing it to suggest actions like: ”I could cut a cucumber with a mandolin”. The algorithm for generalizing objects by analyzing language (GOAL) presented here, allows, thus, generalization and recognition of objects in an action-context. It can then be combined with methods for action execution (e.g. action generation-based on human demonstration) to execute so far unknown actionsInformatikos fakultetasVytauto Didžiojo universiteta