Detection of the Vulnerable Atherosclerotic Plaque. Pre-Clinical Evaluation of Novel PET Imaging Probes With Experimental Models

Atherosclerosis is a life-long vascular inflammatory disease and the leading cause of death in Finland and in other western societies. The development of atherosclerotic plaques is progressive and they form when lipids begin to accumulate in the vessel wall. This accumulation triggers the migration of inflammatory cells that is a hallmark of vascular inflammation. Often, this plaque will become unstable and form vulnerable plaque which may rupture causing thrombosis and in the worst case, causing myocardial infarction or stroke. Identification of these vulnerable plaques before they rupture could save lives. At present, in the clinic, there exists no appropriated, non-invasive method for their identification. The aim of this thesis was to evaluate novel positron emission tomography (PET) probes for the detection of vulnerable atherosclerotic plaques and to characterize, two mouse models of atherosclerosis. These studies were performed by using ex vivo and in vivo imaging modalities. The vulnerability of atherosclerotic plaques was evaluated as expression of active inflammatory cells, namely macrophages. Age and the duration of high-fat diet had a drastic impact on the development of atherosclerotic plaques in mice. In imaging of atherosclerosis, 6-month-old mice, kept on high-fat diet for 4 months, showed matured, metabolically active, atherosclerotic plaques. [18F]FDG and 68Ga were accumulated in the areas representative of vulnerable plaques. However, the slow clearance of 68Ga limits its use for the plaque imaging. The novel synthesized [68Ga]DOTA-RGD and [18F]EF5 tracers demonstrated efficient uptake in plaques as compared to the healthy vessel wall, but the pharmacokinetic properties of these tracers were not optimal in used models. In conclusion, these studies resulted in the identification of new strategies for the assessment of plaque stability and mouse models of atherosclerosis which could be used for plaque imaging. In the used probe panel, [18F]FDG was the best tracer for plaque imaging. However, further studies are warranted to clarify the applicability of [18F]EF5 and [68Ga]DOTA-RGD for imaging of atherosclerosis with other experimental models.

Maritime safety in the Gulf of Finland. Evaluation of the regulatory system

Growing traffic is believed to increase the risk of an accident in the Gulf of Finland. As the consequences of a large oil accident would be devastating in the vulnerable sea area, accident prevention is performed at the international, regional and national levels. Activities of shipping companies are governed with maritime safety policy instruments, which can be categorised into regulatory, economic and information instruments. The maritime regulatory system has been criticised for being inefficient because it has not been able to eliminate the violations that enable accidents. This report aims to discover how maritime governance systems or maritime safety policy instruments could be made more efficient in the future, in order to improve the maritime safety level. The results of the research are based on a literature review and nine expert interviews, with participants from shipping companies, interest groups and authorities. Based on the literature and the interviews, a suggestion can be made that in the future, instead of implementing new policy instruments, maritime safety risks should be eliminated by making the existing system more efficient and by influencing shipping companies��� safety culture and seafarers��� safety related attitudes. Based on this research, it can be stated that the development of maritime safety policy instruments should concentrate on harmonisation, automation and increasing national and cross-border cooperation. These three tasks could be primarily accomplished by developing the existing technology. Human error plays a role in a significant number of maritime accidents. Because of this, improving companies��� safety culture and voluntary activities that go beyond laws are acknowledged as potential ways of improving maritime safety. In the future, maritime regulatory system should be developed into a direction where the private sector has better possibilities to take part in decision-making.

Design and evaluation of web interface signs to improve web usability : a semiotic framework

Technological innovations, the development of the internet, and globalization have increased the number and complexity of web applications. As a result, keeping web user interfaces understandable and usable (in terms of ease-of-use, effectiveness, and satisfaction) is a challenge. As part of this, designing userintuitive interface signs (i.e., the small elements of web user interface, e.g., navigational link, command buttons, icons, small images, thumbnails, etc.) is an issue for designers. Interface signs are key elements of web user interfaces because ���interface signs��� act as a communication artefact to convey web content and system functionality, and because users interact with systems by means of interface signs. In the light of the above, applying semiotic (i.e., the study of signs) concepts on web interface signs will contribute to discover new and important perspectives on web user interface design and evaluation. The thesis mainly focuses on web interface signs and uses the theory of semiotic as a background theory. The underlying aim of this thesis is to provide valuable insights to design and evaluate web user interfaces from a semiotic perspective in order to improve overall web usability. The fundamental research question is formulated as What do practitioners and researchers need to be aware of from a semiotic perspective when designing or evaluating web user interfaces to improve web usability? From a methodological perspective, the thesis follows a design science research (DSR) approach. A systematic literature review and six empirical studies are carried out in this thesis. The empirical studies are carried out with a total of 74 participants in Finland. The steps of a design science research process are followed while the studies were designed and conducted; that includes (a) problem identification and motivation, (b) definition of objectives of a solution, (c) design and development, (d) demonstration, (e) evaluation, and (f) communication. The data is collected using observations in a usability testing lab, by analytical (expert) inspection, with questionnaires, and in structured and semi-structured interviews. User behaviour analysis, qualitative analysis and statistics are used to analyze the study data. The results are summarized as follows and have lead to the following contributions. Firstly, the results present the current status of semiotic research in UI design and evaluation and highlight the importance of considering semiotic concepts in UI design and evaluation. Secondly, the thesis explores interface sign ontologies (i.e., sets of concepts and skills that a user should know to interpret the meaning of interface signs) by providing a set of ontologies used to interpret the meaning of interface signs, and by providing a set of features related to ontology mapping in interpreting the meaning of interface signs. Thirdly, the thesis explores the value of integrating semiotic concepts in usability testing. Fourthly, the thesis proposes a semiotic framework (Semiotic Interface sign Design and Evaluation ��� SIDE) for interface sign design and evaluation in order to make them intuitive for end users and to improve web usability. The SIDE framework includes a set of determinants and attributes of user-intuitive interface signs, and a set of semiotic heuristics to design and evaluate interface signs. Finally, the thesis assesses (a) the quality of the SIDE framework in terms of performance metrics (e.g., thoroughness, validity, effectiveness, reliability, etc.) and (b) the contributions of the SIDE framework from the evaluators��� perspective.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here ��� formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty���s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes ��� particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Advanced epithelial ovarian cancer ��� studies on preoperative [18F] FDG PET/CT and HE4 profile during primary chemotherapy

Epithelial ovarian cancer (EOC) is usually diagnosed in an advanced stage. The prognosis depends highly on the amount of the residual tumor in surgery. In patients with extensive disease, neoadjuvant chemotherapy (NACT) is used to diminish the tumor load before debulking surgery. New non-invasive methods are needed to preoperatively evaluate the disease dissemination and operability. [18F] FDG PET/CT (Positron emission tomography/computed tomography) is a promising method for cancer diagnostics and staging. The biomarker profiles during treatment can predict patient���s outcome. This prospective study included 41 EOC patients, 21 treated with primary surgery and 20 with NACT and interval surgery. The performances of preoperative contrast enhanced PET/CT (PET/ceCT) and diagnostic CT (ceCT) were compared. Perioperative visual estimation of tumor spread was studied in primary and interval surgery. The profile of the serum marker HE4 (Human epididymis 4) during primary chemotherapy was evaluated. In primary surgery, surgical findings were found to form an adequate reference standard for imaging studies. After NACT, the sensitivity for visual estimation of cancer dissemination was significantly worse. Preoperative PET/ceCT was more effective than ceCT alone in detecting extra-abdominal disease spread. The high number of supradiaphragmatic lymph node metastases detected by PET/ceCT at the time of diagnosis brings new insight in EOC spread patterns. The sensitivity of both PET/CT and ceCT remained modest in intra-abdominal areas important to operability. The HE4 profile was in concordance with the CA125 profile during primary chemotherapy. Its role in the evaluation of EOC chemotherapy response will be clarified in further studies.

Experimental Studies on Non-Metallic Composite Bone Implants With a Special Reference to Staphylococcal Biofilm Infection

Non-metallic implants made of bioresorbable or biostable synthetic polymers are attractive options in many surgical procedures, ranging from bioresorbable suture anchors of arthroscopic surgery to reconstructive skull implants made of biostable fiber-reinforced composites. Among other benefits, non-metallic implants produce less interference in imaging. Bioresorbable polymer implants may be true multifunctional, serving as osteoconductive scaffolds and as matrices for simultaneous delivery of bone enhancement agents. As a major advantage for loading conditions, mechanical properties of biostable fiber-reinforced composites can be matched with those of the bone. Unsolved problems of these biomaterials are related to the risk of staphylococcal biofilm infections and to the low osteoconductivity of contemporary bioresorbable composite implants. This thesis was focused on the research and development of a multifunctional implant model with enhanced osteoconductivity and low susceptibility to infection. In addition, the experimental models for assessment, diagnostics and prophylaxis of biomaterial-related infections were established. The first experiment (Study I) established an in vitro method for simultaneous evaluation of calcium phosphate and biofilm formation on bisphenol-Aglycidyldimethacrylate and triethylenglycoldimethacrylate (BisGMA-TEGDMA) thermosets with different content of bioactive glass 45S5. The second experiment (Study II) showed no significant difference in osteointegration of nanostructured and microsized polylactide-co-glycolide/��-tricalcium phosphate (PLGA /��-TCP) composites in a minipig model. The third experiment (Study III) demonstrated that positron emission tomography (PET) imaging with the novel 68Ga labelled 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA) CD33 related sialic-acid immunoglobulin like lectins (Siglec-9) tracer was able to detect inflammatory response to S. epidermidis and S. aureus peri-implant infections in an intraosseous polytetrafluoroethylene catheter model. In the fourth experiment (Study IV), BisGMATEGDMA thermosets coated with lactose-modified chitosan (Chitlac) and silver nanoparticles exhibited antibacterial activity against S. aureus and P. aeruginosa strains in an in vitro biofilm model and showed in vivo biocompatibility in a minipig model. In the last experiment (Study V), a selective androgen modulator (SARM) released from a poly(lactide)-co-��-caprolactone (PLCL) polymer matrix failed to produce a dose-dependent enhancement of peri-implant osteogenesis in a bone marrow ablation model.

Tracing Innovation Practices in Seaports: the Ports of Klaipeda and Stockholm as Case Studies

This study explores variegated means through which ports have become increasingly entangled in the planning logic of neoliberal innovation-driven economy. The research topic belongs to the academic disciplines of economics and human geography. The aim of the thesis is to analyse how the notion of innovation, adopted in a variety of supranational and national port policy documents, is deployed in operational port environment in two different ports of the Baltic Sea Region: the port of Stockholm, Sweden, and the port of Klaipeda, Lithuania. This novel innovation agenda is visible in several topics I examine in the study, that is, port governance, environmental issues, and seaport ��� port-city interface. The gathered primary source material on port policy documents, strategies, development planning documents and reports is analysed by utilizing the qualitative content analysis research method. Moreover, the empirical part of the case study, that is, tracing innovation practices in mundane port activities is based on collected qualitative semi-structured interviews with port authorities in Klaipeda and Stockholm, researchers and other port experts. I examine the interview material by employing the theoretical reading research method. In my analysis, I have reframed port-related policy development by tracing and identifying the port transformation from ���functional terminals��� to ���engines for growth���. My results show that this novel innovation-oriented rhetoric imprinted in the narrative ���engines for growth��� is often contested in daily port practices. In other words, my analysis reveals that the port authorities��� and other port actors��� attitudes towards innovations do not necessarily correspond to the new narrative of innovation and do not always ���fit��� within a framework of neoliberal economic thinking that glorifies the ���culture of innovations���. I argue that the ability to develop innovative initiatives in the ports of Klaipeda and Stockholm is strongly predetermined by local conditions, a port���s governance model, the way port actors perceive the importance of innovations per se, demand factors and new regulations.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.