Spectroscopic investigations of photon-induced reactions in tin-oxo cage photoresists

Molecular compounds such as tin-oxo cages are promising photoresists for Extreme UltraViolet (EUV) photolithography, which is the latest nano-patterning technology for high-end computer chips. Solubility switching of the resist is the key for pattern transfer to the semiconductor substrate. In this thesis, different spectroscopic techniques were used to gain insight into the photochemistry upon exposure, which is crucial for optimizing the resist performance. In one research line, we developed a laser-based high harmonic generation setup as the exposure source in the soft-X-ray (XUV) region to perform broadband absorption spectroscopy on tin-oxo cage samples. Resist-coated thin films were exposed to light with energies of 21 – 70 eV, and the induced changes in the transmission as a function of exposure dose were used to quantify the photoconversion of the resist. The results were compared with those obtained with EUV (92 eV). The resist properties were further investigated using X-ray photoelectron spectroscopy and Total Electron Yield techniques. A synchrotron beamline was used as the exposure source (5-150 eV) to study the low-energy emitted electrons from the resist. Outgassing measurements (residual gas analysis) and ellipsometry techniques were used to investigate the resist’s photoconversion under 92 eV exposure. Outgassing species from the resist were determined to be mainly organic carbon-containing products. The outgassing rate was measured for a few selected masses and the induced resist’s thickness change at different exposure doses was related to the outgassing rate of the resist. The fundamental insight obtained in our studies can help to design improved EUV photoresists

Ionic Imbalances and Coupling in Synchronization of Responses in Neurons

Most neurodegenerative diseases (NDD) are a result of changes in the chemical composition of neurons. For example, Alzheimer's disease (AD) is the product of A? peptide deposition which results in changes in the ion concentration. These changes in ion concentration affect the responses of the neuron to stimuli and often result in inducing excessive excitation or inhibition. This paper investigates the dynamics of a single neuron as ion changes occur. These changes are incorporated using the Nernst equation. Within the central and peripheral nervous system, signals and hence rhythms, are propagated through the coupling of the neurons. It was found that under certain conditions the coupling strength between two neurons could mitigate changes in ion concentration. By defining the state of perfect synchrony, it was shown that the effect of ion imbalance in coupled neurons was reduced while in uncoupled neurons these changes had a more significant impact on the neuronal behavior

Ontologies, Mental Disorders and Prototypes

As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field do not allow for the representation of concepts in terms of typical traits. However, the need of representing concepts in terms of typical traits concerns almost every domain of real world knowledge, including medical domains. In particular, in this article we take into account the domain of mental disorders, starting from the DSM-5 descriptions of some specific mental disorders. On this respect, we favor a hybrid approach to the representation of psychiatric concepts, in which ontology oriented formalisms are combined to a geometric representation of knowledge based on conceptual spaces

Level Crossing Analysis of Burgers Equation in 1+1 Dimensions

We investigate the average frequency of positive slope $\nu_{\alpha}^{+}$, crossing the velocity field $u(x)- \bar u = \alpha$ in the Burgers equation. The level crossing analysis in the inviscid limit and total number of positive crossing of velocity field before creation of singularities are given. The main goal of this paper is to show that this quantity, $\nu_{\alpha}^{+}$, is a good measure for the fluctuations of velocity fields in the Burgers turbulence.Comment: 5 pages, 3 figure

Dynamic characterization and predictability analysis of wind speed and wind power time series in Spain wind farm

The renewable energy resources such as wind power have recently attracted more researchers’ attention. It is mainly due to the aggressive energy consumption, high pollution and cost of fossil fuels. In this era, the future fluctuations of these time series should be predicted to increase the reliability of the power network. In this paper, the dynamic characteristics and short-term predictability of hourly wind speed and power time series are investigated via nonlinear time series analysis methods such as power spectral density analysis, time series histogram, phase space reconstruction, the slope of integral sums, the   method, the recurrence plot and the recurrence quantification analysis. Moreover, the interactive behavior of the wind speed and wind power time series is studied via the cross correlation, the cross and joint recurrence plots as well as the cross and joint recurrence quantification analyses. The results imply stochastic nature of these time series. Besides, a measure of the short-term mimic predictability of the wind speed and the underlying wind power has been derived for the experimental data of Spain’s wind farm

A high-level and scalable approach for generating scale-free graphs using active objects

The Barabasi-Albert model (BA) is designed to generate scale-free networks using the preferential attachment mechanism. In the preferential attachment (PA) model, new nodes are sequentially introduced to the network and they attach preferentially to existing nodes. PA is a classical model with a natural intuition, great explanatory power and a simple mechanism. Therefore, PA is widely-used for network generation. However the sequential mechanism used in the PA model makes it an inefficient algorithm. The existing parallel approaches, on the other hand, suffer from either changing the original model or explicit complex low-level synchronization mechanisms. In this paper we investigate a high-level Actor-based model of the parallel algorithm of network generation and its scalable multicore implementation in Haskell