Insights into Atmospheric Nucleation

Atmospheric aerosol particles have a strong impact on the global climate. A deep understanding of the physical and chemical processes affecting the atmospheric aerosol climate system is crucial in order to describe those processes properly in global climate models. Besides the climatic effects, aerosol particles can deteriorate e.g. visibility and human health. Nucleation is a fundamental step in atmospheric new particle formation. However, details of the atmospheric nucleation mechanisms have remained unresolved. The main reason for that has been the non-existence of instruments capable of measuring neutral newly formed particles in the size range below 3 nm in diameter. This thesis aims to extend the detectable particle size range towards close-to-molecular sizes (~1nm) of freshly nucleated clusters, and by direct measurement obtain the concentrations of sub-3 nm particles in atmospheric environment and in well defined laboratory conditions. In the work presented in this thesis, new methods and instruments for the sub-3 nm particle detection were developed and tested. The selected approach comprises four different condensation based techniques and one electrical detection scheme. All of them are capable to detect particles with diameters well below 3 nm, some even down to ~1 nm. The developed techniques and instruments were deployed in the field measurements as well as in laboratory nucleation experiments. Ambient air studies showed that in a boreal forest environment a persistent population of 1-2 nm particles or clusters exists. The observation was done using 4 different instruments showing a consistent capability for the direct measurement of the atmospheric nucleation. The results from the laboratory experiments showed that sulphuric acid is a key species in the atmospheric nucleation. The mismatch between the earlier laboratory data and ambient observations on the dependency of nucleation rate on sulphuric acid concentration was explained. The reason was shown to be associated in the inefficient growth of the nucleated clusters and in the insufficient detection efficiency of particle counters used in the previous experiments. Even though the exact molecular steps of nucleation still remain an open question, the instrumental techniques developed in this work as well as their application in laboratory and ambient studies opened a new view into atmospheric nucleation and prepared the way for investigating the nucleation processes with more suitable tools.

Space-Vector-Based Hybrid Pulsewidth Modulation Techniques for Reduced Harmonic Distortion and Switching Loss

Novel switching sequences can be employed in spacevector-based pulsewidth modulation (PWM) of voltage source inverters. Differentswitching sequences are evaluated and compared in terms of inverter switching loss. A hybrid PWM technique named minimum switching loss PWM is proposed, which reduces the inverter switching loss compared to conventional space vector PWM (CSVPWM) and discontinuous PWM techniques at a given average switching frequency. Further, four space-vector-based hybrid PWM techniques are proposed that reduce line current distortion as well as switching loss in motor drives, compared to CSVPWM. Theoretical and experimental results are presented.

Spectroscopy of tissue triglyceride composition : In vitro and in vivo studies

Lipid analysis is commonly performed by gas chromatography (GC) in laboratory conditions. Spectroscopic techniques, however, are non-destructive and can be implemented noninvasively in vivo. Excess fat (triglycerides) in visceral adipose tissue and liver is known predispose to metabolic abnormalities, collectively known as the metabolic syndrome. Insulin resistance is the likely cause with diets high in saturated fat known to impair insulin sensitivity. Tissue triglyceride composition has been used as marker of dietary intake but it can also be influenced by tissue specific handling of fatty acids. Recent studies have shown that adipocyte insulin sensitivity correlates positively with their saturated fat content, contradicting the common view of dietary effects. A better understanding of factors affecting tissue triglyceride composition is needed to provide further insights into tissue function in lipid metabolism. In this thesis two spectroscopic techniques were developed for in vitro and in vivo analysis of tissue triglyceride composition. In vitro studies (Study I) used infrared spectroscopy (FTIR), a fast and cost effective analytical technique well suited for multivariate analysis. Infrared spectra are characterized by peak overlap leading to poorly resolved absorbances and limited analytical performance. In vivo studies (Studies II, III and IV) used proton magnetic resonance spectroscopy (1H-MRS), an established non-invasive clinical method for measuring metabolites in vivo. 1H-MRS has been limited in its ability to analyze triglyceride composition due to poorly resolved resonances. Using an attenuated total reflection accessory, we were able to obtain pure triglyceride infrared spectra from adipose tissue biopsies. Using multivariate curve resolution (MCR), we were able to resolve the overlapping double bond absorbances of monounsaturated fat and polyunsaturated fat. MCR also resolved the isolated trans double bond and conjugated linoleic acids from an overlapping background absorbance. Using oil phantoms to study the effects of different fatty acid compositions on the echo time behaviour of triglycerides, it was concluded that the use of long echo times improved peak separation with T2 weighting having a negligible impact. It was also discovered that the echo time behaviour of the methyl resonance of omega-3 fats differed from other fats due to characteristic J-coupling. This novel insight could be used to detect omega-3 fats in human adipose tissue in vivo at very long echo times (TE = 470 and 540 ms). A comparison of 1H-MRS of adipose tissue in vivo and GC of adipose tissue biopsies in humans showed that long TE spectra resulted in improved peak fitting and better correlations with GC data. The study also showed that calculation of fatty acid fractions from 1H-MRS data is unreliable and should not be used. Omega-3 fatty acid content derived from long TE in vivo spectra (TE = 540 ms) correlated with total omega-3 fatty acid concentration measured by GC. The long TE protocol used for adipose tissue studies was subsequently extended to the analysis of liver fat composition. Respiratory triggering and long TE resulted in spectra with the olefinic and tissue water resonances resolved. Conversion of the derived unsaturation to double bond content per fatty acid showed that the results were in accordance with previously published gas chromatography data on liver fat composition. In patients with metabolic syndrome, liver fat was found to be more saturated than subcutaneous or visceral adipose tissue. The higher saturation observed in liver fat may be a result of a higher rate of de-novo-lipogenesis in liver than in adipose tissue. This thesis has introduced the first non-invasive method for determining adipose tissue omega-3 fatty acid content in humans in vivo. The methods introduced here have also shown that liver fat is more saturated than adipose tissue fat.

Multivariate Techniques for Identifying Diffractive Interactions at the LHC

Close to one half of the LHC events are expected to be due to elastic or inelastic diffractive scattering. Still, predictions based on extrapolations of experimental data at lower energies differ by large factors in estimating the relative rate of diffractive event categories at the LHC energies. By identifying diffractive events, detailed studies on proton structure can be carried out. The combined forward physics objects: rapidity gaps, forward multiplicity and transverse energy flows can be used to efficiently classify proton-proton collisions. Data samples recorded by the forward detectors, with a simple extension, will allow first estimates of the single diffractive (SD), double diffractive (DD), central diffractive (CD), and non-diffractive (ND) cross sections. The approach, which uses the measurement of inelastic activity in forward and central detector systems, is complementary to the detection and measurement of leading beam-like protons. In this investigation, three different multivariate analysis approaches are assessed in classifying forward physics processes at the LHC. It is shown that with gene expression programming, neural networks and support vector machines, diffraction can be efficiently identified within a large sample of simulated proton-proton scattering events. The event characteristics are visualized by using the self-organizing map algorithm.

Future chemistry teachers use of knowledge dimensions and high-order cognitive skills in pre-laboratory concept maps

This poster describes a pilot case study, which aim is to study how future chemistry teachers use knowledge dimensions and high-order cognitive skills (HOCS) in their pre-laboratory concept maps to support chemistry laboratory work. The research data consisted of 168 pre-laboratory concept maps that 29 students constructed as a part of their chemistry laboratory studies. Concept maps were analyzed by using a theory based content analysis through Anderson & Krathwohls' learning taxonomy (2001). This study implicates that novice concept mapper students use all knowledge dimensions and applying, analyzing and evaluating HOCS to support the pre-laboratory work.

Overview on different sterilization techniques for baby food

The nutritional quality of the product as well as other quality attributes like microbiological and sensory quality are essential factors in baby food industry, and therefore different alternative sterilizing methods for conventional heating processes are of great interest in this food sector. This report gives an overview on different sterilization techniques for baby food. The report is a part of the work done in work package 3 ”QACCP Analysis Processing: Quality – driven distribution and processing chain analysis“ in the Core Organic ERANET project called Quality analysis of critical control points within the whole food chain and their impact on food quality, safety and health (QACCP). The overall objective of the project is to optimise organic production and processing in order to improve food safety as well as nutritional quality and increase health promoting aspects in consumer products. The approach will be a chain analysis approach which addresses the link between farm and fork and backwards from fork to farm. The objective is to improve product related quality management in farming (towards testing food authenticity) and processing (towards food authenticity and sustainable processes. The articles in this volume do not necessarily reflect the Core Organic ERANET’s views and in no way anticipate the Core Organic ERANET’s future policy in this area. The contents of the articles in this volume are the sole responsibility of the authors. The information contained here in, including any expression of opinion and any projection or forecast, has been obtained from sources believed by the authors to be reliable but is not guaranteed as to accuracy or completeness. The information is supplied without obligation and on the understanding that any person who acts upon it or otherwise changes his/her position in reliance thereon does so entirely at his/her own risk. The writers gratefully acknowledge the financial support from the Core Organic Funding Body: Ministry of Agriculture and Forestry, Finland, Swiss Federal Office for Agriculture, Switzerland and Federal Ministry of Consumer Protection, Food and Agriculture, Germany.

The reaction of the nuclei of the vegetative cells and zygotes of Saccharomyces carlsbergensis to some staining techniques

Vegetative cells and zygotes of Saccharomyces carlsbergensis fixed in iodine formaldehyde acetic acid solution and stained after acid hydrolysis in hæmatoxylin, Feulgen and Giemsa show a remarkable similarity in the size and orientation of the structures in the nuclear matrix with reference to the nuclear membrane. The nucleolus described by Guilliermond may either be the chromocenter or the nucleolar equivalent.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Strategic Priorities, Company Performance and Attitudes Towards Management Accounting Techniques: an Empirical Study

The study investigates whether there is an association between different combinations of emphasis on generic strategies (product differentiation and cost efficiency) and perceived usefulness of management accounting techniques. Previous research has found that cost leadership is associated with traditional accounting techniques and product differentiation with a variety of modern management accounting approaches. The present study focuses on the possible existence of a strategy that mixes these generic strategies. The empirical results suggest that (a) there is no difference in the attitudes towards the usefulness of traditional management accounting techniques between companies that adhere either to a single strategy or a mixed strategy; (b) there is no difference in the attitudes towards modern and traditional techniques between companies that adhere to a single strategy, whether this is product differentiation or cost efficiency, and c) companies that favour a mixed strategy seem to have a more positive attitude towards modern techniques than companies adhering to a single strategy