Modeling of non-isothermalvapor membrane separation with thermodynamic models and generalized mass transfer equations

A rigorous unit operation model is developed for vapor membrane separation. The new model is able to describe temperature, pressure, and concentration dependent permeation as wellreal fluid effects in vapor and gas separation with hydrocarbon selective rubbery polymeric membranes. The permeation through the membrane is described by a separate treatment of sorption and diffusion within the membrane. The chemical engineering thermodynamics is used to describe the equilibrium sorption of vapors and gases in rubbery membranes with equation of state models for polymeric systems. Also a new modification of the UNIFAC model is proposed for this purpose. Various thermodynamic models are extensively compared in order to verify the models' ability to predict and correlate experimental vapor-liquid equilibrium data. The penetrant transport through the selective layer of the membrane is described with the generalized Maxwell-Stefan equations, which are able to account for thebulk flux contribution as well as the diffusive coupling effect. A method is described to compute and correlate binary penetrant¿membrane diffusion coefficients from the experimental permeability coefficients at different temperatures and pressures. A fluid flow model for spiral-wound modules is derived from the conservation equation of mass, momentum, and energy. The conservation equations are presented in a discretized form by using the control volume approach. A combination of the permeation model and the fluid flow model yields the desired rigorous model for vapor membrane separation. The model is implemented into an inhouse process simulator and so vapor membrane separation may be evaluated as an integralpart of a process flowsheet.

A generalized 1D particle transport method for convection diffusion reaction model

This work is devoted to the development of numerical method to deal with convection diffusion dominated problem with reaction term, non - stiff chemical reaction and stiff chemical reaction. The technique is based on the unifying Eulerian - Lagrangian schemes (particle transport method) under the framework of operator splitting method. In the computational domain, the particle set is assigned to solve the convection reaction subproblem along the characteristic curves created by convective velocity. At each time step, convection, diffusion and reaction terms are solved separately by assuming that, each phenomenon occurs separately in a sequential fashion. Moreover, adaptivities and projection techniques are used to add particles in the regions of high gradients (steep fronts) and discontinuities and transfer a solution from particle set onto grid point respectively. The numerical results show that, the particle transport method has improved the solutions of CDR problems. Nevertheless, the method is time consumer when compared with other classical technique e.g., method of lines. Apart from this advantage, the particle transport method can be used to simulate problems that involve movingsteep/smooth fronts such as separation of two or more elements in the system.

Generalized Differential Evolution for Global Multi-Objective Optimization with Constraints

The objective of this thesis work is to develop and study the Differential Evolution Algorithm for multi-objective optimization with constraints. Differential Evolution is an evolutionary algorithm that has gained in popularity because of its simplicity and good observed performance. Multi-objective evolutionary algorithms have become popular since they are able to produce a set of compromise solutions during the search process to approximate the Pareto-optimal front. The starting point for this thesis was an idea how Differential Evolution, with simple changes, could be extended for optimization with multiple constraints and objectives. This approach is implemented, experimentally studied, and further developed in the work. Development and study concentrates on the multi-objective optimization aspect. The main outcomes of the work are versions of a method called Generalized Differential Evolution. The versions aim to improve the performance of the method in multi-objective optimization. A diversity preservation technique that is effective and efficient compared to previous diversity preservation techniques is developed. The thesis also studies the influence of control parameters of Differential Evolution in multi-objective optimization. Proposals for initial control parameter value selection are given. Overall, the work contributes to the diversity preservation of solutions in multi-objective optimization.

Conceptualizing and measuring human anxiety on the Internet

Since the 1990’s, the Internet has played a central role in our daily lives. The Internet is an integral part of our personal, business, family, research, entertainment, academic and social life. However, there are social implications in using the Internet that are dependent on categories such as gender, age, ethnicity and cultural attributes. This social aspect can play a detrimental role in the expression of human anxiety on the Internet. An anxiety is a complex phenomenon that requires further elaboration. Thus, the aim of this thesis is to investigate human anxiety, or specifically, whether Internet anxiety can be conceptualized and measured. This thesis utilizes literature, qualitative and quantitative research methodologies, and a triangulation validation approach to conceptualize and measure the Internet anxiety phenomenon. In particular, the aim is to explore anxiety levels of Internet participants to develop and validate an Internet anxiety scale based on earlier research on Internet anxiety. The results of the dissertation present a two phase study. In Phase I, a smaller set of studies were conducted with a limited sample size. In Phase II, the research topic was investigated using 385 participants. Based on a number of studies or experiments, the state-of-the-art discovered in this thesis is creation, design, and validation of two scales, the Self-Assessment Scale (SAS) and a Modified Internet Anxiety Scale (MIAS) for measuring users’ anxieties on the Internet. The result of this dissertation is a conceptualization and measurement of various types of Internet anxiety and measurement of affective feelings of users on the Internet. As a proof-of-concept of measuring Internet anxiety, this thesis describes the author’s implementation of three sets of tools: MyAnxiety, introducing Internet anxieties types; Intelligentia, for collecting Internet anxieties types; and MyIAControl tool, implemented as a browser plug-in, for measuring affective feelings of users on the Internet. Conclusions drawn from the results show that these empirically validated scales and tools might be useful for researchers and practitioners in understanding and measuring the Internet anxiety phenomenon further.

JNK regulation of neurogenesis, neuroplasticity and anxiety-related behaviors in mice

I vår moderna värld har förekomsten av ångeststörningar drastiskt ökat, vilket påverkar välfärden i våra samhällen. Eftersom de molekylära mekanismerna bakom ångest är relativt okända, är möjligheterna till behandling av ångeststörningar begränsade. I och med utvecklingen av genetiska manipuleringmetoder och avbildningstekniker har strukturella förändringar associerade med ångeststörningar kunnat konstateras. Neuroanatomiska studier har påvisat störningar i dendritarkitektur, dendrittaggar och i neurogenesen hos vuxna individer. Särskilt neurogenesen i hippocampus anses viktig i detta sammanhang. Neurogenes i hippocampus har föreslagits spela en viktig roll i ångeststörningarnas patofysiologi och för hur vissa antidepressiva läkemedel förmedlar sin effekt. Under senare år har MAP-kinaser (MAPK) föreslagits vara involverade både i uppkomsten av affektiva störningar och i neurogenes i hippocampus. JNK är en grupp kinaser inom MAPK-familjen som aktiveras av olika externa stressfaktorer. I normala celler är aktiviteten hos JNK låg. Cell-stress ökar aktiviteten hos JNK vilket leder till bl.a. apoptos. JNK kinaser anses vara potentiella terapeutiska mål för behandling av neurodegenerativa sjukdomar men deras potential som mål för behandling av affektiva sjukdomar har tillsvidare inte utretts. Den här avhandlingen behandlar betydelsen av JNK för ångestrelaterat beteende hos möss. Med hjälp av Jnk1-knockout möss och farmakologisk inhibering av JNK-signalering, demonstreras att JNK reglerar neurogenes i hippocampus, vilket i sin tur ligger bakom mössens ångestrelaterade beteende. Jnk1-knockout möss var mindre ängsliga och uppvisade ökad neurogenes i hippcampus jämfört med kontrollmöss. Inhibering av JNK-signalering i hjärnan hos möss gjorde dem också mindre ängsliga och ökade neurogenesen i hippocampus på samma sätt som vissa antidepressiva läkemedel. Inhibering av JNK-aktivitet ledde inte bara till ökad neurogenes i hippocampus, utan främjade också mognandet av nybildade nervceller hos vuxna möss. Resultaten visar också att dendritarkitekturen och fördelningen av dendrittaggar hos CA3 neuroner i hippocampus är förändrad hos Jnk1-knockout möss. Genom screening av substratmolekyler för JNK hittades två JNKeffektormolekyler, MARCKSL1 (ett aktin-associerat protein) och MAP2 (ett mikrotubulus-associerat protein), som reglerade neuronernas sttruktur. Det här tyder på att JNK-signalering kan kontrollera ångeststörningsrelaterade förändringar hor dendriter och dendrittaggar. Sammanfattningsvis ger resultaten som presenteras i avhandlingen en ökad insikt i molekylära mekanismer som kan leda till ångeststörningsrelaterade förändringar i neurogenes och dendritstruktur. Därtill föreslås att JNKsignalbanan har potential som terapeutiskt mål för behandling av ångeststörningar.