Quantitative analysis of the spontaneous activity and response profiles of odorant receptor neurons in larval Xenopus laevis using the cell-attached patch-clamp technique

The scope of this thesis was to investigate the activity of ORNs in larval Xenopus laevis in the absence and presence of adequate stimuli. Acute nose-brain slice preparations of the olfactory epithelium, the olfactory nerves and the anterior part of the brain including the olfactory bulb were used as an experimental approach. The olfactory receptor neurons were incubated with the calcium dye Fluo-8-AM and following Ca2+-imaging enabled the detection of amino acid-sensitive ORNs. Patching the amino acid-sensitive ORNs in the cell-attached voltage clamp mode allowed the recording of both spontaneous and stimulus induced activities. All ORNs (n = 46) showed activity in the absence of obvious stimulus. Thereby, the SFRs of ORNs were constant during recording time but differed across different neurons, ranging from 0.24 to 5.5 APs per second on average (median 1.64/s). Furthermore, it was shown that in almost all ORNs the spontaneous activity was a Poisson process and the SFRs were a good first estimate of the event rate λ. The application of stimuli revealed diverse tuning of ORNs, 3/46 ORN responding to concentrations in the nanomolar range, all of them responding to stimulus concentrations as high as 50 μM. The calculated virtual EC-50 value is 8.8 μM. The post-stimulatory instantaneous frequencies and number of APs covered a range of 3.19 to 59.17 Hz and 13 APs to 135 APs, respectively. The reported results were comparable with studies in other species regarding spontaneous activity and the calculated EC-50 value for ORNs in larval Xenopus laevis. Future studies could investigate the origin and function of spontaneous activity in ORNs and its contribution to olfactory coding in the neuronal network.2020-07-0

Application of Software Engineering Principles to Synthetic Biology and Emerging Regulatory Concerns

As the science of synthetic biology matures, engineers have begun to deliver real-world applications which are the beginning of what could radically transform our lives. Recent progress indicates synthetic biology will produce transformative breakthroughs. Examples include: 1) synthesizing chemicals for medicines which are expensive and difficult to produce; 2) producing protein alternatives; 3) altering genomes to combat deadly diseases; 4) killing antibiotic-resistant pathogens; and 5) speeding up vaccine production. Although synthetic biology promises great benefits, many stakeholders have expressed concerns over safety and security risks from creating biological behavior never seen before in nature. As with any emerging technology, there is the risk of malicious use known as the dual-use problem. The technology is becoming democratized and de-skilled, and people in do-it-yourself communities can tinker with genetic code, similar to how programming has become prevalent through the ease of using macros in spreadsheets. While easy to program, it may be non-trivial to validate novel biological behavior. Nevertheless, we must be able to certify synthetically engineered organisms behave as expected, and be confident they will not harm natural life or the environment. Synthetic biology is an interdisciplinary engineering domain, and interdisciplinary problems require interdisciplinary solutions. Using an interdisciplinary approach, this dissertation lays foundations for verifying, validating, and certifying safety and security of synthetic biology applications through traditional software engineering concepts about safety, security, and reliability of systems. These techniques can help stakeholders navigate what is currently a confusing regulatory process. The contributions of this dissertation are: 1) creation of domain-specific patterns to help synthetic biologists develop assurance cases using evidence and arguments to validate safety and security of designs; 2) application of software product lines and feature models to the modular DNA parts of synthetic biology commonly known as BioBricks, making it easier to find safety features during design; 3) a technique for analyzing DNA sequence motifs to help characterize proteins as toxins or non-toxins; 4) a legal investigation regarding what makes regulating synthetic biology challenging; and 5) a repeatable workflow for leveraging safety and security artifacts to develop assurance cases for synthetic biology systems. Advisers: Myra B. Cohen and Brittany A. Dunca

Infobiotics : computer-aided synthetic systems biology

Until very recently Systems Biology has, despite its stated goals, been too reductive in terms of the models being constructed and the methods used have been, on the one hand, unsuited for large scale adoption or integration of knowledge across scales, and on the other hand, too fragmented. The thesis of this dissertation is that better computational languages and seamlessly integrated tools are required by systems and synthetic biologists to enable them to meet the significant challenges involved in understanding life as it is, and by designing, modelling and manufacturing novel organisms, to understand life as it could be. We call this goal, where everything necessary to conduct model-driven investigations of cellular circuitry and emergent effects in populations of cells is available without significant context-switching, “one-pot” in silico synthetic systems biology in analogy to “one-pot” chemistry and “one-pot” biology. Our strategy is to increase the understandability and reusability of models and experiments, thereby avoiding unnecessary duplication of effort, with practical gains in the efficiency of delivering usable prototype models and systems. Key to this endeavour are graphical interfaces that assists novice users by hiding complexity of the underlying tools and limiting choices to only what is appropriate and useful, thus ensuring that the results of in silico experiments are consistent, comparable and reproducible. This dissertation describes the conception, software engineering and use of two novel software platforms for systems and synthetic biology: the Infobiotics Workbench for modelling, in silico experimentation and analysis of multi-cellular biological systems; and DNA Library Designer with the DNALD language for the compact programmatic specification of combinatorial DNA libraries, as the first stage of a DNA synthesis pipeline, enabling methodical exploration biological problem spaces. Infobiotics models are formalised as Lattice Population P systems, a novel framework for the specification of spatially-discrete and multi-compartmental rule-based models, imbued with a stochastic execution semantics. This framework was developed to meet the needs of real systems biology problems: hormone transport and signalling in the root of Arabidopsis thaliana, and quorum sensing in the pathogenic bacterium Pseudomonas aeruginosa. Our tools have also been used to prototype a novel synthetic biological system for pattern formation, that has been successfully implemented in vitro. Taken together these novel software platforms provide a complete toolchain, from design to wet-lab implementation, of synthetic biological circuits, enabling a step change in the scale of biological investigations that is orders of magnitude greater than could previously be performed in one in silico “pot”

Infobiotics : computer-aided synthetic systems biology

Until very recently Systems Biology has, despite its stated goals, been too reductive in terms of the models being constructed and the methods used have been, on the one hand, unsuited for large scale adoption or integration of knowledge across scales, and on the other hand, too fragmented. The thesis of this dissertation is that better computational languages and seamlessly integrated tools are required by systems and synthetic biologists to enable them to meet the significant challenges involved in understanding life as it is, and by designing, modelling and manufacturing novel organisms, to understand life as it could be. We call this goal, where everything necessary to conduct model-driven investigations of cellular circuitry and emergent effects in populations of cells is available without significant context-switching, “one-pot” in silico synthetic systems biology in analogy to “one-pot” chemistry and “one-pot” biology. Our strategy is to increase the understandability and reusability of models and experiments, thereby avoiding unnecessary duplication of effort, with practical gains in the efficiency of delivering usable prototype models and systems. Key to this endeavour are graphical interfaces that assists novice users by hiding complexity of the underlying tools and limiting choices to only what is appropriate and useful, thus ensuring that the results of in silico experiments are consistent, comparable and reproducible. This dissertation describes the conception, software engineering and use of two novel software platforms for systems and synthetic biology: the Infobiotics Workbench for modelling, in silico experimentation and analysis of multi-cellular biological systems; and DNA Library Designer with the DNALD language for the compact programmatic specification of combinatorial DNA libraries, as the first stage of a DNA synthesis pipeline, enabling methodical exploration biological problem spaces. Infobiotics models are formalised as Lattice Population P systems, a novel framework for the specification of spatially-discrete and multi-compartmental rule-based models, imbued with a stochastic execution semantics. This framework was developed to meet the needs of real systems biology problems: hormone transport and signalling in the root of Arabidopsis thaliana, and quorum sensing in the pathogenic bacterium Pseudomonas aeruginosa. Our tools have also been used to prototype a novel synthetic biological system for pattern formation, that has been successfully implemented in vitro. Taken together these novel software platforms provide a complete toolchain, from design to wet-lab implementation, of synthetic biological circuits, enabling a step change in the scale of biological investigations that is orders of magnitude greater than could previously be performed in one in silico “pot”

The 8th International Conference on Time Series and Forecasting

The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields

Electromobility in Public Transport: Scheduling of Electric Vehicles and Location Planning of the Charging Infrastructure

In recent years, considerable efforts have been made to make public transport more environmentally friendly. This should primarily be achieved by reducing greenhouse gas emissions. Electromobility is considered to be a key technology as electric vehicles create a variety of benefits. However, the use of electric vehicles involves a number of challenges. Modern battery electric vehicles have only a fractional part of the ranges of combustion engine vehicles. Thus, a major challenge is charging the vehicles at specific charging stations to compensate for this disadvantage. Technological aspects of electric vehicles are also of importance and have to be considered. Planning tasks of public transport companies are affected by these challanges, especially vehicle scheduling. Vehicle scheduling is a well-studied optimization problem. The objective is to cover a given set of timetabled service trips by a set of vehicles at minimum costs. An issue strongly related to vehicle scheduling is location planning of the charging infrastructure. For an effcient use of electric vehicles, charging stations must be located at suitable locations in order to minimize operational costs. Location planning of charging stations is a long-term planning task whereas vehicle scheduling is a more short-term planning task in public transport. This thesis examines optimization methods for scheduling electric vehicles in public transport and location planning of the charging infrastructure. Electric vehicles' technological aspects are particularly considered. Case studies based on real-world data are used for evaluation of the artifacts developed. An exact optimization method addresses scheduling of mixed vehicles fleets consisting of electric vehicles and vehicles without range limitations. It is examined whether traditional solution methods for vehicle scheduling are able to cope with the challenges imposed by electric vehicles. The results show, that solution methods for vehicle scheduling are able to deal with the additional challenges to a certain degree. However, novel methods are required to fully deal with the requirements of electric vehicles. A heuristic solution method for scheduling electric vehicles and models for the charging process of batteries are developed. The impact of the detail level of electric vehicles' technological aspects on resulting solutions is analyzed. A computational study reveales major discrepancies between model assumptions and real charging behaviours. A metaheuristic solution method for the simultaneous optimization of location planning of charging stations and scheduling electric vehicles is designed to connect the optimization problems and to open up synergy effects. In comparison to a sequential planning, the simultaneous problem solving is necessary because a sequential planning generally leads to either infeasible solutions or to significant increases in costs.In den letzten Jahren wurden erhebliche Anstrengungen unternommen, um den öffentlichen Personennahverkehr (ÖPNV) umweltfreundlicher zu gestalten. Dabei sollen insbesondere Treibhausgasemissionen reduziert werden. Elektromobilität wird dabei auf Grund der zahlreichen Vorteile von Elektrofahrzeugen als Schlüsseltechnologie angesehen. Der Einsatz von Elektrofahrzeugen ist jedoch mit Herausforderungen verbunden, da diese über weitaus geringere Reichweiten im Vergleich zu Fahrzeugen mit Verbrennungsmotoren verfügen, weshalb ein Nachladen der Fahrzeugbatterien während des Betriebs notwendig ist. Zudem müssen technische Aspekte von Elektrofahrzeugen, wie beispielsweise Batteriealterungsprozesse, berücksichtigt werden. Die Fahrzeugeinsatzplanung als Teil des Planungsprozesses von Verkehrsunternehmen im ÖPNV ist besonders von diesen Herausforderungen betroffen. Diese legt den Fahrzeugeinsatz für die Bedienung der angebotenen Fahrplanfahrten bei Minimierung der Gesamtkosten fest. Die Standortplanung der Ladeinfrastruktur ist eng mit dieser Aufgabe verbunden, da für einen effizienten Einsatz der Fahrzeuge Ladestationen an geeigneten Orten errichtet werden müssen, um Betriebskosten zu minimieren. Die Planung der Ladeinfrastruktur ist ein langfristiges Planungsproblem, wohingegen die Fahrzeugeinsatzplanung eine eher kurzfristige Planungsaufgabe darstellt. Diese Dissertation befasst sich mit Optimierungsmethoden für die Fahrzeugeinsatzplanung mit Elektrofahrzeugen und mit der Standortplanung der Ladeinfrastruktur. Technische Aspekte von Elektrofahrzeugen werden dabei berücksichtigt. Die entwickelten Artefakte werden mit Hilfe von realen Datensätzen evaluiert. Durch eine exakte Optimierungsmethode für die Fahrzeugeinsatzplanung mit gemischten Fahrzeugflotten bestehend aus Fahrzeugen mit und ohne Reichweiterestriktionen wird die Anwendbarkeit von Optimierungsmethoden ohne Berücksichtigung von Reichweitebeschränkungen auf die Herausforderungen von Elektrofahrzeugen untersucht. Die Ergebnisse zeigen, dass herkömmliche Optimierungsmethoden für die neuen Herausforderungen bis zu einem gewissen Grad geeignet sind, es jedoch neuartige Lösungsmethoden erfordert, um den Anforderungen von Elektrofahrzeugen vollständig gerecht zu werden. Mit Hilfe einer heuristischen Lösungsmethode für die Fahrzeugeinsatzplanung mit Elektrofahrzeugen und Modellen für den Ladeprozess von Batterien wird untersucht, inwiefern sich der Detailgrad bei der Abbildung von Ladeprozessen auf resultierende Lösungen auswirkt. Erhebliche Unterschiede zwischen Modellannahmen und realen Gegebenheiten von Ladeprozessen werden herausgearbeitet. Durch ein metaheuristisches Lösungsverfahren für die simultane Optimierung der Standortplanung der Ladeinfrastruktur und der Fahrzeugeinsatzplanung werden beide Problemstellungen miteinander verbunden, um Synergieeffekte offenzulegen. Im Vergleich zu einer sequentiellen Planung ist ein simultanes Lösen notwendig, da ein sequentielles Lösen entweder zu unzulässigen Ergebnissen oder zu erheblichen Kostensteigerungen führt

Advanced Information Systems and Technologies

This book comprises the proceedings of the V International Scientific Conference "Advanced Information Systems and Technologies, AIST-2017". The proceeding papers cover issues related to system analysis and modeling, project management, information system engineering, intelligent data processing computer networking and telecomunications. They will be useful for students, graduate students, researchers who interested in computer science