Aromatase is the enzyme that catalysis the conversion of androgens into estrogens. It´s a member of P450 cytochrome family and is encoded by the CYP19-gene. The enzyme aromatase has an important role in regulating physiological and behavioral sexual mechanisms. This includes for instance activation, motivation and maintenance of the reproductive behaviors. The sexual behavior is affected by a complex series of events that requires the connection of endogenous hormonal and neurochemical changes with social interactions, especially between the opposite sexes. The aim of the present study was to examine how social interactions effect the aromatase expression and activity in the guppy brain. Guppy males were introduced into four different social conditions: Isolated, all male conditions, heterospecific (with zebrafish females) and conspecific female guppies. The focal males were kept under these conditions for two respectively four days. The sexual behavior, of each of the focal males was recorded daily during 10 minutes. The males with the guppy females showed, in contrast to the males in the other groups, a high frequency of reproductive behaviors. The brains of the focal males were collected and the brain aromatase activity was measured using tritiated water assay. I have also tried to analyze the gene-expression of aromatase with RT-PCR. However I was unable to analyze the results with the RT-PCR, because of possible primer-dimerization. Due to the limited time schedule, we were not able to solve the problem. ANOVA performed on the aromatase activity, revealed no significant difference between the different treatment groups. The variance was highest in the zebrafish category and lowest in the isolated males. There was no significant correlation between the mean number of reproductive behaviors and the aromatase activity in males that were together with guppy females. The results do not support the hypothesis that social interactions can affect the brain aromatase activity in guppy males.

A problem when testing timeliness of event-triggered real-time systems is that response times depend on the execution order of concurrent tasks. Conventional testing methods ignore task interleaving and timing and thus do not help determine which execution orders need to be exercised to gain confidence in temporal correctness. This thesis presents and evaluates a framework for testing of timeliness that is based on mutation testing theory. The framework includes two complementary approaches for mutation-based test case generation, testing criteria for timeliness, and tools for automating the test case generation process. A scheme for automated test case execution is also defined. The testing framework assumes that a structured notation is used to model the real-time applications and their execution environment. This real-time system model is subsequently mutated by operators that mimic potential errors that may lead to timeliness failures. Each mutated model is automatically analyzed to generate test cases that target execution orders that are likely to lead to timeliness failures. The validation of the theory and methods in the proposed testing framework is done iteratively through case-studies, experiments and proof-of-concept implementations. This research indicates that an adapted form of mutation-based testing can be used for effective and automated testing of timeliness and, thus, for increasing the confidence level in real-time systems that are designed according to the event-triggered paradigm.

This dissertation concerns testability of event-triggered real-time systems. Real-time systems are known to be hard to test because they are required to function correct both with respect to what the system does and when it does it. An event-triggered real-time system is directly controlled by the events that occur in the environment, as opposed to a time-triggered system, which behavior with respect to when the system does something is constrained, and therefore more predictable. The focus in this dissertation is the behavior in the time domain and it is shown how testability is affected by some factors when the system is tested for timeliness. This dissertation presents a survey of research that focuses on software testability and testability of real-time systems. The survey motivates both the view of testability taken in this dissertation and the metric that is chosen to measure testability in an experiment. We define a method to generate sets of traces from a model by using a meta algorithm on top of a model checker. Defining such a method is a necessary step to perform the experiment. However, the trace sets generated by this method can also be used by test strategies that are based on orderings, for example execution orders. An experimental study is presented in detail. The experiment investigates how testability of an event-triggered real-time system is affected by some constraining properties of the execution environment. The experiment investigates the effect on testability from three different constraints regarding preemptions, observations and process instances. All of these constraints were claimed in previous work to be significant factors for the level of testability. Our results support the claim for the first two of the constraints while the third constraint shows no impact on the level of testability. Finally, this dissertation discusses the effect on the event-triggered semantics when the constraints are applied on the execution environment. The result from this discussion is that the first two constraints do not change the semantics while the third one does. This result indicates that a constraint on the number of process instances might be less useful for some event-triggered real-time systems.

This thesis addresses the issues of data management in embedded systems' software. The complexity of developing and maintaining software has increased over the years due to increased availability of resources, e.g., more powerful CPUs and larger memories, as more functionality can be accommodated using these resources. In this thesis, it is proposed that part of the increasing complexity can be addressed by using a real-time database since data management is one constituent of software in embedded systems. This thesis investigates which functionality a real-time database should have in order to be suitable for embedded software that control an external environment. We use an engine control software as a case study of an embedded system. The findings are that a real-time database should have support for keeping data items up-todate, providing snapshots of values, i.e., the values are derived from the same system state, and overload handling. Algorithms are developed for each one of these functionalities and implemented in a real-time database for embedded systems. Performance evaluations are conducted using the database implementation. The evaluations show that the real-time performance is improved by utilizing the added functionality. Moreover, two algorithms for examining whether the system may become overloaded are also outlined; one algorithm for off-line use and the second algorithm for on-line use. Evaluations show the algorithms are accurate and fast and can be used for embedded systems.

The growing amount and diversity of functions to be implemented by the current and future embedded applications (like, for example, in automotive electronics) have shown that, in many cases, time-triggered and event-triggered functions have to coexist on the computing nodes and to interact over the communication infrastructure. When time-triggered and event-triggered activities have to share the same processing node, a natural way for the execution support can be provided through a hierarchical scheduler. Similarly, when such heterogeneous applications are mapped over a distributed architecture, the communication infrastructure should allow for message exchange in both time-triggered and event-triggered manner in order to ensure a straightforward interconnection of heterogeneous components. This thesis studies aspects related to the analysis and design optimisation for safety-critical hard real-time applications running on hierarchically scheduled distributed embedded systems. It first provides the basis for the timing analysis of the activities in such a system, by carefully taking into consideration all the interferences that appear at run-time between the processes executed according to different scheduling policies. Moreover, due to the distributed nature of the architecture, message delays are also taken into consideration during the timing analysis. Once the schedulability analysis has been provided, the entire system can be optimised by adjusting its configuration parameters. In our work, the entire optimisation process is directed by the results from the timing analysis, with the goal that in the end the timing constraints of the application are satisfied. The analysis and design methodology proposed in the first part of the thesis is applied next on the particular category of distributed systems that use FlexRay as a communication protocol. We start by providing a schedulability analysis for messages transmitted over a FlexRay bus, and then by proposing a bus access optimisation algorithm that aims at improving the timing properties of the entire system. For all the problems that we investigated, we have carried out extensive experiments in order to measure the efficiency of the proposed solutions. The results have confirmed both the importance of the addressed aspects during system-level design, and the applicability of our techniques for analysing and optimising the studied systems.

All-electric ship power systems have limited generation capacity and finite rotating inertia compared with large power systems. Moreover, all-electric ship power systems include large portions of nonlinear loads and dynamic loads relative to the total power capacity, which may significantly reduce the stability margin. Pulse loads and other high-energy weapon loads in the system draw a large amount of power intermittently, which may cause significant frequency and voltage oscillations in the system. Thus, an effective real-time load management technique is needed to dynamically balance the load and generation to operate the system normally. Multi-agent systems, inspired by biological phenomena, aim to cooperatively achieve system objectives that are difficult to reach by a single agent or centralized controller. Since power systems include various electrical components with different dynamical systems, conventional homogeneous multi-agent system cooperative controllers have difficulties solving the real-time load management problem with heterogeneous agents. In this dissertation, a novel heterogeneous multi-agent system cooperative control methodology is presented based on artificial potential functions and reduced-order agent models to cooperatively achieve real-time load management for all-electric ship power systems. The technique integrates high-order system dynamics and various kinds of operational constraints into the multi-agent system, which improves the accuracy of the cooperative controller. The multi-agent system includes a MVAC multiagent system and a DC zone multi-agent, which are coordinated by an AC-DC communication agent. The developed multi-agent system framework and the notional all-electric ship power system model were simulated in PSCAD software. Case studies and performance analysis of the MVAC multi-agent system and the DC zone multi-agent system were performed. The simulation results indicated that propulsion loads and pulse loads can be successfully coordinated to reduce the impact of pulse loads on the power quality of all-electric ship power systems. Further, the switch status or power set-point of loads in DC zones can be optimally determined to dynamically balance the generation and load while satisfying the operational constraints of the system and considering load priorities. The method has great potential to be extended to other isolated power systems, such as microgrids.

In this thesis a replication protocol - PRiDe - is presented, which supports optimistic replication in distributed real-time databases with deterministic detection and forward resolution of transaction conflicts. The protocol is designed to emphasize node autonomy, allowing individual applications to proceed without being affected by distributed operation. For conflict management, PRiDe groups distributed operations into generations of logically concurrent and potentially conflicting operations. Conflicts between operations in a generation can be resolved with no need for coordination among nodes, and it is shown that nodes eventually converge to mutually consistent states. A generic framework for conflict resolution is presented that allows semantics-based conflict resolution policies and application-specific compensation procedures to be plugged in by the database designer and application developer. It is explained how transaction semantics are supported by the protocol, and how applications can tolerate exposure to temporary database inconsistencies. Transactions can detect inconsistent reads and compensate for inconsistencies through callbacks to application-specific compensation procedures. A tool - VADer - has been constructed, which allows database designers and application programmers to quickly construct prototype applications, conflict resolution policies and compensation procedures. VADer can be used to simulate application and database behavior, and supports run-time visualization of relationships between concurrent transactions. Thus, VADer assists the application programmer in conquering the complexity inherent in optimistic replication and forward conflict resolution.

This thesis addresses several issues related to the design and optimization of embedded systems. In particular, in the context of time-constrained embedded systems, the thesis investigates two problems: the minimization of the energy consumption and the implementation of predictable applications on multiprocessor system-on-chip platforms. Power consumption is one of the most limiting factors in electronic systems today. Two techniques that have been shown to reduce the power consumption effectively are dynamic voltage selection and adaptive body biasing. The reduction is achieved by dynamically adjusting the voltage and performance settings according to the application needs. Energy minimization is addressed using both offline and online optimization approaches. Offline, we solve optimally the combined supply voltage and body bias selection problem for multiprocessor systems with imposed time constraints, explicitly taking into account the transition overheads implied by changing voltage levels. The voltage selection technique is applied not only to processors, but also to buses with repeaters and fat wires. We investigate the continuous voltage selection as well as its discrete counterpart. While the above mentioned methods minimize the active energy, we propose an approach that combines voltage selection and processor shutdown in order to optimize the total energy. In order to take full advantage of slack that arises from variations in the execution time, it is important to recalculate the voltage and performance settings during run-time, i.e., online. However, voltage scaling is computationally expensive, and, thus, performed at runtime, significantly hampers the possible energy savings. To overcome the online complexity, we propose a quasi-static voltage scaling scheme, with a constant online time complexity O(1). This allows to increase the exploitable slack as well as to avoid the energy dissipated due to online recalculation of the voltage settings. Worst-case execution time (WCET) analysis and, in general, the predictability of real-time applications implemented on multiprocessor systems has been addressed only in very restrictive and particular contexts. One important aspect that makes the analysis difficult is the estimation of the system’s communication behavior. The traffic on the bus does not solely originate from data transfers due to data dependencies between tasks, but is also affected by memory transfers as result of cache misses. As opposed to the analysis performed for a single processor system, where the cache miss penalty is constant, in a multiprocessor system each cache miss has a variable penalty, depending on the bus contention. This affects the tasks’ WCET which, however, is needed in order to perform system scheduling. At the same time, the WCET depends on the system schedule due to the bus interference. In this context, we propose, an approach to worst-case execution time analysis and system scheduling for real-time applications implemented on multiprocessor SoC architectures.

Gliomas are the most common primary brain tumours, and their capacity to invade surrounding normal brain prevents complete removal of the tumour. Malignant glioma has still a poor prognosis. However, with the rapid development of molecular biology our understanding about glioma has increased dramatically. Among known growth factors, EGF and its receptor are frequently amplified and over expressed in malignant glioma. Therefore, it is of interest to find approaches to hamper the activity of EGF/EGFR. The aim of this thesis was to identify and characterize human analogues to a recently identified gene in Drosophilia, kekkon-1, which negatively regulates the activity of Drosophilia EGF receptor. In the first part, we set up a quantitative real-time RT-PCR assay, which showed good linearity, reproducibility and uniformity. We analyzed the expression of the most commonly used reference genes, and showed that 18S was the most reliable endogenous reference gene in this study. In the second part, we cloned, identified, and sequenced a gene family, which we named leucine-rich repeats and immunoglobulin–like domains family (LRIG). The LRIG gene family had three vertebrate paralogs and one homolog in ascidiacea. The proteins encoded by human LRIG genes shared an overall structure with a signal peptide, 15 tandems leucine-rich repeats with N- and C- terminal flanking regions followed by 3 immunoglobulin-like domains, a transmembrane domain, and a cytoplasmic tail. Northern blot showed the mRNA sizes to be 5.5 kb for LRIG1, 4.8 kb for LRIG2, and 5.1 kb for LRIG3. LRIG1-3 mRNAs were detected in all human and mouse tissues analyzed, however, at various levels. FISH and BLAST analysis showed that LRIG1 was located at 3p14, LRIG2 at 1q13, and LRIG3 at 12q13. LRIG1 was shown to be down-regulated in several cancer cell lines and proposed to be a tumour suppressor gene. In the third part, we analysed the expression of LRIG gene family in human astrocytic tumours. LRIG1-3 mRNAs were detected in all human glioma cell lines, in primary tumour tissues and control-matched normal brain tissues, at various levels. Subcellular localizations of LRIG1-GFP fusion proteins were visualized in nuclear, perinuclear, and cytoplasmic compartment. According to the predicted protein sequences, short peptides were synthesized and used to raise antibodies in rabbits. The antibodies were used for immunohistochemical analysis of LRIG1-3 in 404 human astrocytic tumours in a tissue micro array. The pattern of immunoreactivity of LRIG1-3 was heterogeneous with staining in nuclear, perinuclear and cytoplasmic compartment of positive tumour cells. Perinuclear staining of LRIG1-3 displayed a significant inverse correlation with WHO grade and especially positive LRIG3 perinuclear and cytoplasmic staining correlated with a low proliferation index. The LRIGs correlated with survival, and LRIG3 perinuclear staining was in addition to tumour grade an independent prognostic factor. The results suggest that LRIGs may play a role in normal tissue, and may be of importance in the pathogenesis and prognosis of tumours. The exact function of LRIG1-3 remains to be established.

During recent years there has been a great focus on the climate changes within the media. More or less every day more newspaper articles are presented about the global warming issue and the effect on us human race. Climate models predict higher temperatures and more rain in the northern part of Europe. It is also predicted that the weather will become more extreme e.g. it will rain a lot during longer periods than has been the norm. If these predictions are correct, the amount of water that is going to be transported away in streams and rivers will increase and so also will the subsoil water level. The latter increases the risk for landslides in areas with fine grained soils. An early warning system that is able to alert people before a landslide take place would be of great interest. The purpose of this work is to develop a complete real-time displacement monitoring system based on observations from several GPS-receivers that could be used as an early warning system. Due to the complex correlation structure of the traditionally used double differences, an alternative method based on undifferenced observations is used. Theoretically this approach shows some advantages and simplifies the correlative structure of observables compared to the double differenced method. A complete model for the undifferenced approach is presented in this thesis including its software implementation. A displacement detection system includes not only the positioning algorithms, but also methods to detect if any displacement occurs. There are many methods available to discriminate displacements, which are used in the traditional control of manufacturing processes. Several of these methods are compared in this thesis, such as the Shewhart chart, different Weighted Moving Average (WMA) charts and the CUmulative SUMmation (CUSUM). Practical tests show that it is possible to detect an abrupt shift on sub centimetre level at the same epoch as the shift occurs. Smaller shifts are also detectable with the applied approach but with a slightly longer detection time. / QC 20100624