The goal of this research project was to contribute to the understanding of CuGaSe2/CdS photovoltaic devices, and to improve the performance of these devices. The initial part of the research dealt with the optimization of a Sequential Deposition process for CuIn(Ga)Se2 absorber formation. As an extension of this, a recipe (Type I Process) for CuGaSe2 absorber layer fabrication was developed, and the deposition parameters were optimized. Electrical characterization of the thin films and completed devices was carried out using techniques such as Two-Probe and Three-Probe Current-Voltage, Capacitance-Frequency, Capacitance-Voltage, and Spectral Response measurements. Structural/chemical characterization was done using XRD and EDS analysis. Current densities of up to 15.2 mA/cm2, and Fill Factors of up to 58% were obtained using the Type I CuGaSe2 Process. VOC's, however, were limited to less than 700 mV. Several process variations, such as changes in the rate/order/temperature of depositions and changes in the thickness of layers, resulted in little improvement. With the aim of breaking through this VOC performance ceiling, a new absorber recipe (Type II Process) was developed. VOC's of up to 735 mV without annealing, and those of up to 775 mV after annealing, were observed. Fill Factors were comparable to those obtained with Type I Process, whereas the Current Densities were found to be reduced (typically, 10-12 mA/cm2, with the best value of 12.6 mA/cm2). This performance of Type II devices was correlated to a better intermixing of the elements during the absorber formation. To gain an understanding of the performance limitations, two simulation techniques, viz. SCAPS and AMPS, were used to model our devices. Several processing experiments and SCAPS modeling indicate that a defective interface between CuGaSe2 and CdS, and perhaps a defective absorber layer, are the cause of the VOC limitation. AMPS simulation studies, on the other hand, suggest that the back contact is limiting the performance. Attempts to change the physical back contact, by changes in the absorber processing, were unsuccessful. Processing experiments and simulations also suggest that the CuGaSe2/CdS solar cell involves a true heterojunction between these two layers.

<p>Hämning (Behavior Inhibition) tycks utgöra en riskfaktor för olika typer av ångestsyndrom. Child Inhibition Scale (CIS) är ett föräldraformulär som mäter hämning hos barn. Syftet med studien är att normera samt att psykometriskt utpröva den svenska versionen av CIS mot ett föräldraformulär som mäter generell ångest hos barn och ungdomar Multidimensional Anxiety Scale for Children – Parent version (MASC-P). I studien ingår skolor från fem områden i Storstockholm. Deltagarna är 430 föräldrar/vårdnadshavare till barn i årskurs 2-9. Faktoranalys, Cronbachs alfa och korrelationer genomfördes. I resultatet framkom fyra faktorer samt en god reliabilitet och validitet för CIS. Signifikanta skillnader fanns avseende kön och geografiska områden. Flickorna hade högre medelvärde på delskalorna Räddhågsenhet och Fysiska symtom. Pojkarna hade högre på skalan Socialt undvikande vilket det skulle vara intressant att göra vidare studier på. Sammanfattningsvis visar utprövningen att CIS kan användas i kliniska sammanhang och forskning på en svensk population.</p>

Near IR (NIR) sensitive Au-Au₂S nanoparticles were prepared by mixing HAuCl₄ and Na₂S in aqueous solutions. An anti-tumor drug, cis-platin, was adsorbed onto Au-Au₂S nanoparticle surface via the 11-mercaptoundecanoic acid layers. The results showed that the degree of adsorption of cis-platin onto Au-Au₂S nanoparticles was controlled by the pH value of solution, and the drug release was sensitive to NIR irradiation. The cis-platin loaded Au-Au₂S nanoparticles can be potentially applied as NIR activated drug delivery carrier. / Singapore-MIT Alliance (SMA)

Hämning (Behavior Inhibition) tycks utgöra en riskfaktor för olika typer av ångestsyndrom. Child Inhibition Scale (CIS) är ett föräldraformulär som mäter hämning hos barn. Syftet med studien är att normera samt att psykometriskt utpröva den svenska versionen av CIS mot ett föräldraformulär som mäter generell ångest hos barn och ungdomar Multidimensional Anxiety Scale for Children – Parent version (MASC-P). I studien ingår skolor från fem områden i Storstockholm. Deltagarna är 430 föräldrar/vårdnadshavare till barn i årskurs 2-9. Faktoranalys, Cronbachs alfa och korrelationer genomfördes. I resultatet framkom fyra faktorer samt en god reliabilitet och validitet för CIS. Signifikanta skillnader fanns avseende kön och geografiska områden. Flickorna hade högre medelvärde på delskalorna Räddhågsenhet och Fysiska symtom. Pojkarna hade högre på skalan Socialt undvikande vilket det skulle vara intressant att göra vidare studier på. Sammanfattningsvis visar utprövningen att CIS kan användas i kliniska sammanhang och forskning på en svensk population.

In the past decade, fast advancements have been made in the sequencing, digitalization and collection of the biological data. However the bottleneck remains at the point of analysis and extraction of patterns from the data. We have developed a method that is aimed at widening this bottleneck by automating the knowledge extraction from the biological data. Our approach is aimed at discovering patterns in a set of DNA sequences based on the location of transcription factor binding sites or any other biological markers with the emphasis of discovering relationships. A variety of statistical and computational methods exists to analyze such data. However, they either require an initial hypothesis, which is later tested, or classify the data based on its attributes. Our approach does not require an initial hypothesis and the classification it produces is based on the relationships between attributes. The value of such approach is that is is able to uncover new knowledge about the data by inducing a general theory based on basic known rules. The core of our approach lies in an inductive logic programming engine, which, based on positive and negative examples as well as background knowledge, is able to induce a descriptive, human-readable theory, describing the data. An application provides an end-to-end analysis of DNA sequences. A simple to use Web interface accepts a set of related sequences to be analyzed, set of negative example sequences to contrast the main set (optional), and a set of possible genetic markers as position-specific scoring matrices. A Java-based backend formats the sequences, determines the location of the genetic markers inside them and passes the information to the ILP engine, which induces the theory. The model, assumed in our background knowledge, is a set of basic interactions between biological markers in any DNA sequence. This makes our approach applicable to analyze a wide variety of biological problems, including detection of cis-regulatory modules and analysis of ChIP-Sequencing experiments. We have evaluated our method in the context of such applications on two real world datasets as well as a number of specially designed synthetic datasets. The approach has shown to have merit even in situations when no significant classification could be determined.

The expansion of repetitive sequences leads to more than 40 neurological, neurodegenerative and neuromuscular diseases. These diseases are frequently characterized by ongoing DNA repeat instability upon transmission, worsening of disease severity and decreasing age of onset with each successive generation. The mechanism of repeat instability and contribution of repeat instability to disease pathogenesis are unknown. My thesis examines the contribution of cis-elements – sequences around and within repeats as well as surrounding epigenetic environments – to repeat instability, and discusses their possible contribution to repeat diseases. Here I identify the first cis-element regulating repeat instability, a DNA binding site for a trans factor protein, CTCF. Loss of CTCF binding at the spinocerebellar ataxia type 7 disease locus induces somatic and germline instability in an age- and tissue-specific manner in mice. CTCF protects against instability in an epigenetic manner, and may function at other disease loci also possessing CTCF binding sites near the repeat. Given that CTCF flanks many repeat loci and is often situated between a replication origin and disease-associated repeat, I assess the role of CTCF on replication and instability at the myotonic dystrophy repeat locus. Templates with CTCF binding sites reduce overall replication efficiency in primate cells that may be partly due to replication fork stalling. Mutating CTCF binding sites can alter the stability of the repeat depending on the distance from the origin of replication to the repeat. Finally I examine chromatinization of (ATTCT)n repeats from the spinocerebellar ataxia type 10 locus. These repeats induce very strong nucleosome formation, and at physiological conditions form even more strongly on (ATTCT)n repeats with interruptions that are also found in some patients. These data contribute to the understanding of repeat instability in the causation of many diseases, and suggest that the presence of cis-elements at repeat-associated disease loci alter the behaviour of repeats.

The DrrAB proteins of Streptomyces peucetius belong to the ABC family of ubiquitous membrane transporters. The DrrA and DrrB proteins together form a drug efflux pump that carries out the transport of the anticancer drug doxorubicin by carrying out ATP hydrolysis. The present study is the first where the intrinsic factors involved in the assembly of the DrrAB functional complex have been elucidated. The drrA and drrB genes in the wild type operon have overlapping stop and start codons (ATGA) which indicates translational coupling between the two genes. On insertion of a fortuitous stop codon in DrrA it was shown that the expression of DrrB is coupled to that of the upstream gene drrA. Furthermore, it was observed that a functional complex could be achieved only when the genes were maintained in cis in a translationally coupled manner. Translational regulation in DrrA was found to be involved in the control of optimal levels of DrrB. Inhibitory interactions within drrA sequence were speculated to cause translational arrest at the C terminus of DrrA. A novel assembly domain that forms the interface between DrrA containing the Nucleotide Binding Domain (NBD) and DrrB comprising the TransMembrane Domain (TMD) was found. Based on the data presented in this study a model is proposed for the biogenesis of the DrrAB drug pump. The model suggests that translational coupling between DrrA and DrrB is crucial for functional complex formation. Further, there is evidence of regulation of translation by attenuation in the intergenic region of drrA and drrB. The regulation seems to involve the last 30 nucleotides of the mRNA of drrA and some upstream sequences within drrA that cause translational arrest within the C terminus of DrrA. Since DrrB is translationally coupled to drrA, this translational arrest in conjunction with coupling causes lowering in the levels of DrrB. Finally, since the DrrA-DrrB interaction domain lies in the C terminus of DrrA, only the fully translated DrrA product will be competent to form a complex with DrrB. This interaction between the C terminus of DrrA and the N terminus of DrrB may be crucial for initial targeting of the complex to the membrane. The model is expected to serve as primer and open up an interesting yet insufficiently understood subject of membrane protein biogenesis.

The expansion of repetitive sequences leads to more than 40 neurological, neurodegenerative and neuromuscular diseases. These diseases are frequently characterized by ongoing DNA repeat instability upon transmission, worsening of disease severity and decreasing age of onset with each successive generation. The mechanism of repeat instability and contribution of repeat instability to disease pathogenesis are unknown. My thesis examines the contribution of cis-elements – sequences around and within repeats as well as surrounding epigenetic environments – to repeat instability, and discusses their possible contribution to repeat diseases. Here I identify the first cis-element regulating repeat instability, a DNA binding site for a trans factor protein, CTCF. Loss of CTCF binding at the spinocerebellar ataxia type 7 disease locus induces somatic and germline instability in an age- and tissue-specific manner in mice. CTCF protects against instability in an epigenetic manner, and may function at other disease loci also possessing CTCF binding sites near the repeat. Given that CTCF flanks many repeat loci and is often situated between a replication origin and disease-associated repeat, I assess the role of CTCF on replication and instability at the myotonic dystrophy repeat locus. Templates with CTCF binding sites reduce overall replication efficiency in primate cells that may be partly due to replication fork stalling. Mutating CTCF binding sites can alter the stability of the repeat depending on the distance from the origin of replication to the repeat. Finally I examine chromatinization of (ATTCT)n repeats from the spinocerebellar ataxia type 10 locus. These repeats induce very strong nucleosome formation, and at physiological conditions form even more strongly on (ATTCT)n repeats with interruptions that are also found in some patients. These data contribute to the understanding of repeat instability in the causation of many diseases, and suggest that the presence of cis-elements at repeat-associated disease loci alter the behaviour of repeats.

In the past decade, fast advancements have been made in the sequencing, digitalization and collection of the biological data. However the bottleneck remains at the point of analysis and extraction of patterns from the data. We have developed a method that is aimed at widening this bottleneck by automating the knowledge extraction from the biological data. Our approach is aimed at discovering patterns in a set of DNA sequences based on the location of transcription factor binding sites or any other biological markers with the emphasis of discovering relationships. A variety of statistical and computational methods exists to analyze such data. However, they either require an initial hypothesis, which is later tested, or classify the data based on its attributes. Our approach does not require an initial hypothesis and the classification it produces is based on the relationships between attributes. The value of such approach is that is is able to uncover new knowledge about the data by inducing a general theory based on basic known rules. The core of our approach lies in an inductive logic programming engine, which, based on positive and negative examples as well as background knowledge, is able to induce a descriptive, human-readable theory, describing the data. An application provides an end-to-end analysis of DNA sequences. A simple to use Web interface accepts a set of related sequences to be analyzed, set of negative example sequences to contrast the main set (optional), and a set of possible genetic markers as position-specific scoring matrices. A Java-based backend formats the sequences, determines the location of the genetic markers inside them and passes the information to the ILP engine, which induces the theory. The model, assumed in our background knowledge, is a set of basic interactions between biological markers in any DNA sequence. This makes our approach applicable to analyze a wide variety of biological problems, including detection of cis-regulatory modules and analysis of ChIP-Sequencing experiments. We have evaluated our method in the context of such applications on two real world datasets as well as a number of specially designed synthetic datasets. The approach has shown to have merit even in situations when no significant classification could be determined.

Previous studies have suggested that iron PRBs, receiving high concentrations of inorganic constituents in groundwater, may experience passivation because of the accumulation of inorganic precipitates. In an iron PRB containing more highly reactive material, even though the initial contaminant removal rate is faster than for less reactive material, a faster migration of the contaminant removal front may occur due to the greater reactivity loss, caused by faster accumulation of secondary precipitates. In contrast, an iron PRB containing less reactive material may show a slower accumulation of precipitates, and thus will show a slower migration of the contaminant removal front over time. Thus, it is hypothesized that an iron material having moderate initial reactivity may be more advantageous than material having a higher reactivity in terms of long-term performance. The objective of this study was to test this hypothesis by evaluating the changes of the reactivities of different iron materials in the presence of dissolved CaCO₃. <br /><br /> Four different iron materials (Connelly, G-M, Ispat and Peerless) were selected for the column experiments. The changes in reactivities of the iron and formation of secondary precipitates over time were assessed, primarily by the iron corrosion rates, calculated from the hydrogen gas generation rates, by the cis-DCE removal rates and by the alkalinity profiles. The accumulation of precipitates in the four columns caused passivation of the iron. The passivation of the iron in turn resulted in migration of the mineral precipitation fronts as well as profiles of cis-DCE, TCE, VC, alkalinity, Eh, pH, and chloride. Connelly and G-M had longer periods of operation than Ispat and Peerless and thus their performance was the primary test of the hypothesis. G-M iron, which had the higher initial corrosion rate, compared to Connelly, showed a faster accumulation of precipitates near the influent end. The difference in accumulated precipitates resulted in a difference in the leading edge of the organic profiles and a significant difference in the pattern of passivation, indicating a faster passivation in the region near the influent end for G-M. <br /><br /> Model simulations were performed using the same fitting parameters but with different initial corrosion rate constants to further test the hypothesis. The model provided a reasonable representation of changing reactivities of the columns, being consistent with the observed data. In the simulation for long-term prediction, the cases of higher corrosion rates showed earlier breakthroughs and steeper curves than those of lower corrosion rates. Also, the predictions showed greater porosity loss for the case of higher corrosion rate. Thus, long-term predictions support the hypothesis. Accurate determination of model parameters such as cis-DCE degradation rate constants and iron corrosion rates are required for better predictions of long-term performance.