Design and optimization of selfnanoemulsifying drug delivery systems for enhanced dissolution of gemfibrozil

Self-nanoemulsifying drug delivery systems of gemfibrozil were developed under Quality by Design approach for improvement of dissolution and oral absorption. Preliminary screening was performed to select proper components combination. BoxBehnken experimental design was employed as statistical tool to optimize the formulation variables, X1 (Cremophor® EL), X2 (Capmul® MCM-C8), and X3 (lemon essential oil). Systems were assessed for visual characteristics (emulsification efficacy), turbidity, droplet size, polydispersity index and drug release. Different pH media were also assayed for optimization. Following optimization, the values of formulation components (X1, X2, and X3) were 32.43%, 29.73% and 21.62%, respectively (16.22% of gemfibrozil). Transmission electron microscopy demonstrated spherical droplet morphology. SNEEDS release study was compared to commercial tablets. Optimized SNEDDS formulation of gemfibrozil showed a significant increase in dissolution rate compared to conventional tablets. Both formulations followed Weibull mathematical model release with a significant difference in td parameter in favor of the SNEDDS. Equally amodelistic parameters were calculated being the dissolution efficiency significantly higher for SNEDDS, confirming that the developed SNEDDS formulation was superior to commercial formulation with respect to in vitro dissolution profile. This paper provides an overview of the SNEDDS of the gemfibrozil as a promising alternative to improve oral absorption.

Toward a rational design of combination therapy in cancer.

By merging computational systems modeling and experimental approaches, we have uncovered treatments reprogramming pro-angiogenic monocytes present in breast tumor into immunologically potent cells capable of mediating an anti-tumor immune response. The unraveled pathways and ligands which underlie monocyte pro-angiogenic activity have a strong predictive value for breast cancer patient relapse - free survival.

A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning

Peer-reviewed

Present and future methodology for the implementation of decision support systems for traffic management

Real-time predictions are an indispensable requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. The combination of predicting the state of the network and the evaluation of different traffic management strategies in the short term future allows system managers to anticipate the effects of traffic control strategies ahead of time in order to mitigate the effect of congestion. This paper presents the current framework of decision support systems for traffic management based on short and medium-term predictions and includes some reflections on their likely evolution, based on current scientific research and the evolution of the availability of new types of data and their associated methodologies.

Managing the Front End of Innovation in a Networked Company Environment - Combining Strategy, Processes and Systems of Innovation

The objective of the thesis is to enhance the understanding about the management of the front end phases of the innovation process in a networked environment. The thesis approaches the front end of innovation from three perspectives, including the strategy, processes and systems of innovation. The purpose of the use of different perspectives in the thesis is that of providing an extensive systemic view of the front end, and uncovering the complex nature of innovation management. The context of the research is the networked operating environment of firms. The unit of analysis is the firm itself or its innovation processes, which means that this research approaches the innovation networks from the point of view of a firm. The strategy perspective of the thesis emphasises the importance of purposeful innovation management, the innovation strategy of firms. The role of innovation processes is critical in carrying out innovation strategies in practice, supporting the development of organizational routines for innovation, and driving the strategic renewal of companies. The primary focus of the thesis from systems perspective is on idea management systems, which are defined as a part of innovation management systems, and defined for this thesis as any working combination of methodology and tools (manual or IT-supported) that enhance the management of innovations within their early phases. The main contribution of the thesis are the managerial frameworks developed for managing the front end of innovation, which purposefully “wire” the front end of innovation into the strategy and business processes of a firm. The thesis contributes to modern innovation management by connecting the internal and external collaboration networks as foundational elements for successful management of the early phases of innovation processes in a dynamic environment. The innovation capability of a firm is largely defined by its ability to rely on and make use of internal and external collaboration already during the front end activities, which by definition include opportunity identification and analysis, idea generation, profileration and selection, and concept definition. More specifically, coordination of the interfaces between these activities, and between the internal and external innovation environments of a firm is emphasised. The role of information systems, in particular idea management systems, is to support and delineate the innovation-oriented behaviour and interaction of individuals and organizations during front end activities. The findings and frameworks developed in the thesis can be used by companies for purposeful promotion of their front end processes. The thesis provides a systemic strategy framework for managing the front end of innovation – not as a separate process, but as an elemental bundle ofactivities that is closely linked to the overall innovation process and strategy of a firm in a distributed environment. The theoretical contribution of the thesis relies on the advancement of the open innovation paradigm in the strategic context of a firm within its internal and external innovation environments. This thesis applies the constructive research approach and case study methodology to provide theoretically significant results, which are also practically beneficial.

Full instability behavior of N-dimensional dynamical systems with a one-directional nonlinear vector field

We show how certain N-dimensional dynamical systems are able to exploit the full instability capabilities of their fixed points to do Hopf bifurcations and how such a behavior produces complex time evolutions based on the nonlinear combination of the oscillation modes that emerged from these bifurcations. For really different oscillation frequencies, the evolutions describe robust wave form structures, usually periodic, in which selfsimilarity with respect to both the time scale and system dimension is clearly appreciated. For closer frequencies, the evolution signals usually appear irregular but are still based on the repetition of complex wave form structures. The study is developed by considering vector fields with a scalar-valued nonlinear function of a single variable that is a linear combination of the N dynamical variables. In this case, the linear stability analysis can be used to design N-dimensional systems in which the fixed points of a saddle-node pair experience up to N21 Hopf bifurcations with preselected oscillation frequencies. The secondary processes occurring in the phase region where the variety of limit cycles appear may be rather complex and difficult to characterize, but they produce the nonlinear mixing of oscillation modes with relatively generic features

Rigid Rod Polymer Fillers in Acrylic Denture and Dental Adhesive Resin Systems

Polymeric materials have been used in dental applications for decades. Adhesion of polymeric materials to each other and to the tooth substrate is essential to their successful use. The aim of this series of studies was two-folded. First, to improve adhesion of poly(paraphenylene) based rigid rod polymer (RRP) to other dental polymers, and secondly, to evaluate the usability of a new dentin primer system based on RRP fillers. Poly(paraphenylene) based RRP would be a tempting material for dental applications because of its good mechanical properties. To be used in dental applications, reliable adhesion between RRP and other dental polymers is required. In this series of studies, the adhesion of RRP to denture base polymer and the mechanical properties of RRP-denture base polymer-material combination were evaluated. Also adhesion of BisGMA-TEGDMA-resin to RRP was determined. Different surface treatments were tested to improve the adhesion of BisGMA-TEGDMA-resin to RRP. Results were based on three-point bending testing, Vickers surface hardness test and scanning electron microscope analysis (SEM), which showed that no reliable adhesion between RRP and denture base polymer was formed. Addition of RRP filler to denture base polymer increased surface hardness and flexural modulus but flexural strength decreased. Results from the shear bond strength test and SEM revealed that adhesion between resin and RRP was possible to improve by surface treatment with dichloromethane (DCM) based primer and a new kind of adhesive surface can be designed. The current dentin bonding agents have good immediate bond strength, but in long term the bond strength may decrease due to the detrimental effect of water and perhaps by matrix metalloproteinases. This leads to problems in longevity of restorations. Current bonding agents use organic monomers. In this series of studies, RRP filled dentin primer was tested in order to decrease the water sorption of the monomer system of the primers. The properties of new dentin primer system were evaluated in vitro by comparing it to commercial etch and rinse adhesive system. The results from the contact angle measurements and SEM showed that experimental primer with RRP reinforcement provided similar resin infiltration to dentin collagen and formed the resin-dentin interface as the control primer. Microtensile bond strength test and SEM revealed that in short term water storing, RRP increased bond strength and primer with BMEP-monomer (bis[2-(methacryloyloxy)-ethyl]phosphate) and high solvent concentration provided comparable bonding properties to the commercial control primers. In long term water storing, the high solvent-monomer concentration of the experimental primers decreased bond strength. However, in low solvent-monomer concentration groups, the long-term water storing did not decrease the bond strength despite the existence of hydrophilic monomers which were used in the system. These studies demonstrated that new dentin primer system reached the mechanical properties of current traditional etch and rinse adhesive system in short time water storing. Improved properties can be achieved by further modifications of the monomer system. Studies of the adhesion of RRP to other polymers suggest that adhesion between RRP and other dental polymers is possible to obtain by certain surface treatments.

Improving Transportation and Warehousing Efficiency with Simulation-Based Decision Support Systems

Transportation and warehousing are large and growing sectors in the society, and their efficiency is of high importance. Transportation also has a large share of global carbondioxide emissions, which are one the leading causes of anthropogenic climate warming. Various countries have agreed to decrease their carbon emissions according to the Kyoto protocol. Transportation is the only sector where emissions have steadily increased since the 1990s, which highlights the importance of transportation efficiency. The efficiency of transportation and warehousing can be improved with the help of simulations, but models alone are not sufficient. This research concentrates on the use of simulations in decision support systems. Three main simulation approaches are used in logistics: discrete-event simulation, systems dynamics, and agent-based modeling. However, individual simulation approaches have weaknesses of their own. Hybridization (combining two or more approaches) can improve the quality of the models, as it allows using a different method to overcome the weakness of one method. It is important to choose the correct approach (or a combination of approaches) when modeling transportation and warehousing issues. If an inappropriate method is chosen (this can occur if the modeler is proficient in only one approach or the model specification is not conducted thoroughly), the simulation model will have an inaccurate structure, which in turn will lead to misleading results. This issue can further escalate, as the decision-maker may assume that the presented simulation model gives the most useful results available, even though the whole model can be based on a poorly chosen structure. In this research it is argued that simulation- based decision support systems need to take various issues into account to make a functioning decision support system. The actual simulation model can be constructed using any (or multiple) approach, it can be combined with different optimization modules, and there needs to be a proper interface between the model and the user. These issues are presented in a framework, which simulation modelers can use when creating decision support systems. In order for decision-makers to fully benefit from the simulations, the user interface needs to clearly separate the model and the user, but at the same time, the user needs to be able to run the appropriate runs in order to analyze the problems correctly. This study recommends that simulation modelers should start to transfer their tacit knowledge to explicit knowledge. This would greatly benefit the whole simulation community and improve the quality of simulation-based decision support systems as well. More studies should also be conducted by using hybrid models and integrating simulations with Graphical Information Systems.

Structural and operational optimisation : applications in energy systems

In this work mathematical programming models for structural and operational optimisation of energy systems are developed and applied to a selection of energy technology problems. The studied cases are taken from industrial processes and from large regional energy distribution systems. The models are based on Mixed Integer Linear Programming (MILP), Mixed Integer Non-Linear Programming (MINLP) and on a hybrid approach of a combination of Non-Linear Programming (NLP) and Genetic Algorithms (GA). The optimisation of the structure and operation of energy systems in urban regions is treated in the work. Firstly, distributed energy systems (DES) with different energy conversion units and annual variations of consumer heating and electricity demands are considered. Secondly, district cooling systems (DCS) with cooling demands for a large number of consumers are studied, with respect to a long term planning perspective regarding to given predictions of the consumer cooling demand development in a region. The work comprises also the development of applications for heat recovery systems (HRS), where paper machine dryer section HRS is taken as an illustrative example. The heat sources in these systems are moist air streams. Models are developed for different types of equipment price functions. The approach is based on partitioning of the overall temperature range of the system into a number of temperature intervals in order to take into account the strong nonlinearities due to condensation in the heat recovery exchangers. The influence of parameter variations on the solutions of heat recovery systems is analysed firstly by varying cost factors and secondly by varying process parameters. Point-optimal solutions by a fixed parameter approach are compared to robust solutions with given parameter variation ranges. In the work enhanced utilisation of excess heat in heat recovery systems with impingement drying, electricity generation with low grade excess heat and the use of absorption heat transformers to elevate a stream temperature above the excess heat temperature are also studied.

On state and parameter estimation in chaotic systems

State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

Importance of considering food waste in the development of sustainable food packaging systems

Meeting the needs of both present and future generations forms the foundation of sustainable development. Concern about food demand is increasing alongside the continuously growing population. In the pursuit of food security preventing food waste is one solution avoiding the negative environmental impacts that result from producing food unnecessarily. Packages offer one answer to preventing food waste, as they 1) preserve and protect food, 2) introduce the user to the correct way to handle and use the food and package and 3) allow the user to consume the food in its entirety. This thesis aims to enhance the sustainability of food packages by giving special emphasis to preventing food waste. The focus of this thesis is to assist the packaging designer in being able to take into account the requirements for the sustainability of food packages and to be able to integrate these requirements into the product development process. In addition, life cycle methods that can be used as a tool in the packaging design process or in assessing the sustainability of finished food-packaging combinations are evaluated. The methods of life cycle costing (LCC) and life cycle working environment (LCWE) are briefly discussed. The method of life cycle assessment (LCA) is examined more thoroughly through the lens of the literature review of food-package LCA case studies published in the 21st century in three relevant journals. Based on this review and on experiences learned from conducting LCAs, recommendations are given as to how the LCA practitioner should conduct a food packaging study to make most of the results. Two case studies are presented in this thesis. The first case study relates the results of a life cycle assessment conducted for three food items (cold cut (ham), sliced dark bread (rye) and Soygurt drink) and the alternative packaging options of each. Results of this study show that the packaging constitutes only 1–12 % of the total environmental impacts of the food-packaging combination. The greatest effect is derived from the food itself and the wasted food. Even just a small percentage of wasted food causes more environmental impacts than does the packaging. The second case study presents the results of LCC and LCWE analysis done for fruit and vegetable transport packages. In this thesis, the specific results of the study itself are not the focus, but rather the study methods and scope are analysed based on how these complement the sustainability assessment of food packages. This thesis presents reasons why prevention of food waste should be more thoroughly taken into account in food packaging design. In addition, the task of the packaging designer is facilitated by the requirements of sustainable food packaging, by the methods and step-by-step guidance on how to integrate sustainability issues into the design process, and by the recommendations on how to assess the sustainability of food packages. The intention of this thesis is to express the issues that are important in the field of the food packaging industry. Having recognised and implemented these issues, businesses can better manage the risks that could follow from neglecting these sustainability aspects.

Combined effects of diethylpropion and alcohol on locomotor activity of mice: participation of the dopaminergic and opioid systems

The widespread consumption of anorectics and combined anorectic + alcohol misuse are problems in Brazil. In order to better understand the interactive effects of ethanol (EtOH) and diethylpropion (DEP) we examined the locomotion-activating effects of these drugs given alone or in combination in mice. We also determined whether this response was affected by dopamine (DA) or opioid receptor antagonists. A total of 160 male Swiss mice weighing approximately 30 g were divided into groups of 8 animals per group. The animals were treated daily for 7 consecutive days with combined EtOH + DEP (1.2 g/kg and 5.0 mg/kg, ip), EtOH (1.2 g/kg, ip), DEP (5.0 mg/kg, ip) or the control solution coadministered with the DA antagonist haloperidol (HAL, 0.075 mg/kg, ip), the opioid antagonist naloxone (NAL, 1.0 mg/kg, ip), or vehicle. On days 1, 7 and 10 after the injections, mice were assessed in activity cages at different times (15, 30, 45 and 60 min) for 5 min. The acute combination of EtOH plus DEP induced a significantly higher increase in locomotor activity (day 1: 369.5 ± 34.41) when compared to either drug alone (day 1: EtOH = 232.5 ± 23.79 and DEP = 276.0 ± 12.85) and to control solution (day 1: 153.12 ± 7.64). However, the repeated administration of EtOH (day 7: 314.63 ± 26.79 and day 10: 257.62 ± 29.91) or DEP (day 7: 309.5 ± 31.65 and day 10: 321.12 ± 39.24) alone or in combination (day 7: 459.75 ± 41.28 and day 10: 427.87 ± 33.0) failed to induce a progressive increase in the locomotor response. These data demonstrate greater locomotion-activating effects of the EtOH + DEP combination, probably involving DA and/or opioid receptor stimulation, since the daily pretreatment with HAL (day 1: EtOH + DEP = 395.62 ± 11.92 and EtOH + DEP + HAL = 371.5 ± 6.76; day 7: EtOH + DEP = 502.5 ± 42.27 and EtOH + DEP + HAL = 281.12 ± 16.08; day 10: EtOH + DEP = 445.75 ± 16.64 and EtOH + DEP + HAL = 376.75 ± 16.4) and NAL (day 1: EtOH + DEP = 553.62 ± 38.15 and EtOH + DEP + NAL = 445.12 ± 55.67; day 7: EtOH + DEP = 617.5 ± 38.89 and EtOH + DEP + NAL = 418.25 ± 61.18; day 10: EtOH + DEP = 541.37 ± 32.86 and EtOH + DEP + NAL = 427.12 ± 51.6) reduced the locomotor response induced by combined administration of EtOH + DEP. These findings also suggest that a major determinant of combined anorectic-alcohol misuse may be the increased stimulating effects produced by the combination.

Review of water electrolysis technologies and design of renewable hydrogen production systems

An electric system based on renewable energy faces challenges concerning the storage and utilization of energy due to the intermittent and seasonal nature of renewable energy sources. Wind and solar photovoltaic power productions are variable and difficult to predict, and thus electricity storage will be needed in the case of basic power production. Hydrogen’s energetic potential lies in its ability and versatility to store chemical energy, to serve as an energy carrier and as feedstock for various industries. Hydrogen is also used e.g. in the production of biofuels. The amount of energy produced during hydrogen combustion is higher than any other fuel’s on a mass basis with a higher-heating-value of 39.4 kWh/kg. However, even though hydrogen is the most abundant element in the universe, on Earth most hydrogen exists in molecular forms such as water. Therefore, hydrogen must be produced and there are various methods to do so. Today, the majority hydrogen comes from fossil fuels, mainly from steam methane reforming, and only about 4 % of global hydrogen comes from water electrolysis. Combination of electrolytic production of hydrogen from water and supply of renewable energy is attracting more interest due to the sustainability and the increased flexibility of the resulting energy system. The preferred option for intermittent hydrogen storage is pressurization in tanks since at ambient conditions the volumetric energy density of hydrogen is low, and pressurized tanks are efficient and affordable when the cycling rate is high. Pressurized hydrogen enables energy storage in larger capacities compared to battery technologies and additionally the energy can be stored for longer periods of time, on a time scale of months. In this thesis, the thermodynamics and electrochemistry associated with water electrolysis are described. The main water electrolysis technologies are presented with state-of-the-art specifications. Finally, a Power-to-Hydrogen infrastructure design for Lappeenranta University of Technology is presented. Laboratory setup for water electrolysis is specified and factors affecting its commissioning in Finland are presented.

Energy aware software for many-core systems

Many-core systems provide a great potential in application performance with the massively parallel structure. Such systems are currently being integrated into most parts of daily life from high-end server farms to desktop systems, laptops and mobile devices. Yet, these systems are facing increasing challenges such as high temperature causing physical damage, high electrical bills both for servers and individual users, unpleasant noise levels due to active cooling and unrealistic battery drainage in mobile devices; factors caused directly by poor energy efficiency. Power management has traditionally been an area of research providing hardware solutions or runtime power management in the operating system in form of frequency governors. Energy awareness in application software is currently non-existent. This means that applications are not involved in the power management decisions, nor does any interface between the applications and the runtime system to provide such facilities exist. Power management in the operating system is therefore performed purely based on indirect implications of software execution, usually referred to as the workload. It often results in over-allocation of resources, hence power waste. This thesis discusses power management strategies in many-core systems in the form of increasing application software awareness of energy efficiency. The presented approach allows meta-data descriptions in the applications and is manifested in two design recommendations: 1) Energy-aware mapping 2) Energy-aware execution which allow the applications to directly influence the power management decisions. The recommendations eliminate over-allocation of resources and increase the energy efficiency of the computing system. Both recommendations are fully supported in a provided interface in combination with a novel power management runtime system called Bricktop. The work presented in this thesis allows both new- and legacy software to execute with the most energy efficient mapping on a many-core CPU and with the most energy efficient performance level. A set of case study examples demonstrate realworld energy savings in a wide range of applications without performance degradation.

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.