Das leuchten der gase und dämpfe, mit besonderer berücksichtigung der gesetzmässigkeiten in spektren,

Mode of access: Internet.

Uber die Absorption der Rontgenstrahlen durch Metallbleche verschiedener Dicke, gemessen durch die von den Rontgenstrahlen bewirkte Ionisation der Gase.

Thesis (doctoral)--Universitat Basel.

Untersuchungen uber die Explosionsgrenzen brennbarer Gase und Dampfe.

Thesis (doctoral)--Universitat Basel.

Ueber die Abhangigkeit der Warmeleitung einiger Gase und Dampfe von der Temperatur.

Thesis (doctoral)--Universitat Jena.

Kristallografische en molekulaire symmetrie van plaatsings-isom...

Thesis (doctoral)--

Uber das Verhaltnis der spezifischen Warmen der Gase und seine Abhangigkeit von der Temperatur.

Thesis (doctoral)--Hessische Ludwigs-Universitat, Giessen.

Experimentaluntersuchung uber die Dielektrizitatskonstante einiger Gase und Dampfe in ihrer Abhangigkeit von der Temperatur.

Thesis (doctoral)--Georg-Augusts-Universitat, Gottingen.

Uber die Einwirkung des Druckes auf die Absorption ultraroter Strahlung durch Gase.

Thesis (doctoral)--Uppsala.

Uber den wesentlichen Einfluss von Spuren nitroser Gase auf die Wasserdampf.

Thesis (doctoral)--Universitat Marburg.

Uber die verdichtung der gase auf glasoberflachen.

Thesis (doctoral)--

ROR alpha regulates the expression of genes involved in lipid homeostasis in skeletal muscle cells - Caveolin-3 and CPT-1 are direct targets of ROR

The staggerer mice carry a deletion in the RORalpha gene and have a prolonged humoral response, overproduce inflammatory cytokines, and are immunodeficient. Furthermore, the staggerer mice display lowered plasma apoA-I/-II, decreased plasma high density lipoprotein cholesterol and triglycerides, and develop hypo-alpha-lipoproteinemia and atherosclerosis. However, relatively little is known about RORalpha in the context of target tissues, target genes, and lipid homeostasis. For example, RORalpha is abundantly expressed in skeletal muscle, a major mass peripheral tissue that accounts for similar to40% of total body weight and 50% of energy expenditure. This lean tissue is a primary site of glucose disposal and fatty acid oxidation. Consequently, muscle has a significant role in insulin sensitivity, obesity, and the blood-lipid profile. In particular, the role of RORalpha in skeletal muscle metabolism has not been investigated, and the contribution of skeletal muscle to the ROR-/- phenotype has not been resolved. We utilize ectopic dominant negative RORalpha expression in skeletal muscle cells to understand the regulatory role of RORs in this major mass peripheral tissue. Exogenous dominant negative RORalpha expression in skeletal muscle cells represses the endogenous levels of RORalpha and -gamma mRNAs and ROR-dependent gene expression. Moreover, we observed attenuated expression of many genes involved in lipid homeostasis. Furthermore, we show that the muscle carnitine palmitoyltransferase-1 and caveolin-3 promoters are directly regulated by ROR and coactivated by p300 and PGC-1. This study implicates RORs in the control of lipid homeostasis in skeletal muscle. In conclusion, we speculate that ROR agonists would increase fatty acid catabolism in muscle and suggest selective activators of ROR may have therapeutic utility in the treatment of obesity and atherosclerosis.

SAMPLING BIAS IN EVALUATING THE PROBABILITY OF SEISMICALLY INDUCED SOIL LIQUEFACTION WITH SPT & CPT CASE HISTORIES

Several deterministic and probabilistic methods are used to evaluate the probability of seismically induced liquefaction of a soil. The probabilistic models usually possess some uncertainty in that model and uncertainties in the parameters used to develop that model. These model uncertainties vary from one statistical model to another. Most of the model uncertainties are epistemic, and can be addressed through appropriate knowledge of the statistical model. One such epistemic model uncertainty in evaluating liquefaction potential using a probabilistic model such as logistic regression is sampling bias. Sampling bias is the difference between the class distribution in the sample used for developing the statistical model and the true population distribution of liquefaction and non-liquefaction instances. Recent studies have shown that sampling bias can significantly affect the predicted probability using a statistical model. To address this epistemic uncertainty, a new approach was developed for evaluating the probability of seismically-induced soil liquefaction, in which a logistic regression model in combination with Hosmer-Lemeshow statistic was used. This approach was used to estimate the population (true) distribution of liquefaction to non-liquefaction instances of standard penetration test (SPT) and cone penetration test (CPT) based most updated case histories. Apart from this, other model uncertainties such as distribution of explanatory variables and significance of explanatory variables were also addressed using KS test and Wald statistic respectively. Moreover, based on estimated population distribution, logistic regression equations were proposed to calculate the probability of liquefaction for both SPT and CPT based case history. Additionally, the proposed probability curves were compared with existing probability curves based on SPT and CPT case histories.

Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay

Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.