CSSI-PRO: a method for secondary structure type editing, assignment and estimation in proteins using linear combination of backbone chemical shifts

Estimation of secondary structure in polypeptides is important for studying their structure, folding and dynamics. In NMR spectroscopy, such information is generally obtained after sequence specific resonance assignments are completed. We present here a new methodology for assignment of secondary structure type to spin systems in proteins directly from NMR spectra, without prior knowledge of resonance assignments. The methodology, named Combination of Shifts for Secondary Structure Identification in Proteins (CSSI-PRO), involves detection of specific linear combination of backbone H-1(alpha) and C-13' chemical shifts in a two-dimensional (2D) NMR experiment based on G-matrix Fourier transform (GFT) NMR spectroscopy. Such linear combinations of shifts facilitate editing of residues belonging to alpha-helical/beta-strand regions into distinct spectral regions nearly independent of the amino acid type, thereby allowing the estimation of overall secondary structure content of the protein. Comparison of the predicted secondary structure content with those estimated based on their respective 3D structures and/or the method of Chemical Shift Index for 237 proteins gives a correlation of more than 90% and an overall rmsd of 7.0%, which is comparable to other biophysical techniques used for structural characterization of proteins. Taken together, this methodology has a wide range of applications in NMR spectroscopy such as rapid protein structure determination, monitoring conformational changes in protein-folding/ligand-binding studies and automated resonance assignment.

Human papillomavirus infection and vaccination: Awareness and knowledge of HPV and acceptability of HPV vaccine among mothers of teenage daughters in Weihai, Shandong, China

In preparation for the introduction of human papillomavirus (HPV) vaccine, we investigated awareness and knowledge of HPV/HPV vaccine and potential acceptability to HPV vaccine among mothers with a teenage daughter in Weihai, Shandong, China. A cross-sectional survey was conducted in 2013 with a sample of 1850 mothers who had a daughter (aged 9–17 years) attending primary, junior and senior high schools. In the final sample (N = 1578, response rate 85.30%), awareness of HPV was reported by 305 (19.32%) mothers. Awareness varied significantly by daughter’s age (P<0.01), mother’s education level (P<0.01), mother’s occupation (P<0.01), household income (P<0.01) and residence type (P<0.01). Knowledge about HPV/HPV vaccine was poor with a mean total score of 3.56 (SD = 2.40) out of a possible score of 13. Mothers with a higher education level reported higher levels of knowledge (P = 0.02). Slightly more than one-fourth (26.49%) of mothers expressed their potential acceptability of HPV vaccine for their daughters. Acceptability increased along with increased daughters’ age (P<0.01), household income (P<0.01) and knowledge level (P<0.01). House wives and unemployed mothers had the highest acceptability (P<0.01). The most common reasons for not accepting HPV vaccination were “My daughter is too young to have risk of cervical cancer (30.95%)”, “The vaccine has not been widely used, and the decision will be made after it is widely used (24.91%)”, “Worry about the safety of the vaccine (22.85%)”. Awareness and knowledge of HPV/HPV vaccines are poor and HPV vaccine acceptability is low among these Chinese mothers. These results may help inform appropriate health education programs in this population.

Visualization of enantiomers using natural abundant 13C-filtered single and double quantum selective refocusing experiments: Application to small chiral molecules

The routine use of proton NMR for the visualization of enantiomers, aligned in the chiral liquid crystal solvent poly-γ-benzyl-l-glutamate (PBLG), is restricted due to severe loss of resolution arising from large number of pair wise interaction of nuclear spins. In the present study, we have designed two experimental techniques for their visualization utilizing the natural abundance 13C edited selective refocusing of single quantum (CH-SERF) and double quantum (CH-DQSERF) coherences. The methods achieve chiral discrimination and aid in the simultaneous determination of homonuclear couplings between active and passive spins and heteronuclear couplings between the excited protons and the participating 13C spin. The CH-SERF also overcomes the problem of overlap of central transitions of the methyl selective refocusing (SERF) experiment resulting in better chiral discrimination. Theoretical description of the evolution of magnetization in both the sequences has been discussed using polarization operator formalism.

Knowledge discovery from tree databases using balanced optimal search

This research is a step forward in discovering knowledge from databases of complex structure like tree or graph. Several data mining algorithms are developed based on a novel representation called Balanced Optimal Search for extracting implicit, unknown and potentially useful information like patterns, similarities and various relationships from tree data, which are also proved to be advantageous in analysing big data. This thesis focuses on analysing unordered tree data, which is robust to data inconsistency, irregularity and swift information changes, hence, in the era of big data it becomes a popular and widely used data model.

How to Succeed in Knowledge Transfer : Case Study of Scandinavian Alliance in Ukraine

The current study of Scandinavian multinational corporate subsidiaries in the rapidly growing Eastern European market, due to their particular organizational structure, attempts to gain some new insights into processes and potential benefits of knowledge and technology transfer. This study explores how to succeed in knowledge transfer and to become more competitive, driven by the need to improve transfer of systematic knowledge for the manufacture of product and service provisions in newly entered market. The scope of current research is exactly limited to multinational corporations, which are defined as enterprises comprising entities in two or more countries, regardless of legal forms and field of activity of those entities, and which operate under a system of decision-making permitting coherent policies and a common strategy through one or more decision-making centers. The entities are linked, by ownership, and able to exercise influence over the activities of the others; and, in particular, to share the knowledge, resources, and responsibilities with others. The research question is "How and to which extent can knowledge-transfer influence a company's technological competence and economic competitiveness?" and try to find out what particular forces and factors affect the development of subsidiary competencies; what factors influence the corporate integration and use of the subsidiary's competencies; and what may increase competitiveness of MNC pursuing leading position in entered market. The empirical part of the research was based on qualitative analyses of twenty interviews conducted among employees in Scandinavian MNC subsidiary units situated in Ukraine, using structured sequence of questions with open-ended answers. The data was investigated by comparison case analyses to literature framework. Findings indicate that a technological competence developed in one subsidiary will lead to an integration of that competence with other corporate units within the MNC. Success increasingly depends upon people's learning. The local economic area is crucial for understanding competition and industrial performance, as there seems to be a clear link between the performance of subsidiaries and the conditions prevailing in their environment. The linkage between competitive advantage and company's success is mutually dependent. Observation suggests that companies can be characterized as clusters of complementary activities such as R&D, administration, marketing, manufacturing and distribution. Study identifies barriers and obstacles in technology and knowledge transfer that is relevant for the subsidiaries' competence development. The accumulated experience can be implemented in new entered market with simple procedures, and at a low cost under specific circumstances, by cloning. The main goal is focused to support company prosperity, making more profits and sustaining an increased market share by improved product quality and/or reduced production cost of the subsidiaries through cloning approach. Keywords: multinational corporation; technology transfer; knowledge transfer; subsidiary competence; barriers and obstacles; competitive advantage; Eastern European market

Digital access to knowledge in the preschool classroom: Reports from Australia

Australian preschool teachers’ use of Web-searching in their classroom practice was examined (N = 131). Availability of Internet-enabled digital technology and the contribution of teacher demographic characteristics, comfort with digital technologies and beliefs about their use were assessed. Internet-enabled technologies were available in 53% (n = 69) of classrooms. Within these classrooms, teacher age and beliefs predicted Web-searching practice. Although comfortable with digital access of knowledge in their everyday life, teachers reported less comfort with Web-searching in the context of their classroom practice. The findings identify the provision of Internet-enabled technologies and professional development as actions to support effective and confident inclusion of Web-searching in classrooms. Such actions are necessary to align with national policy documents that define acquisition of digital literacies as a goal and assert digital access to knowledge as an issue of equity.

Comprehensive Two-Dimensional Gas Chromatography: Instrumental and Methodological Development

Comprehensive two-dimensional gas chromatography (GC×GC) offers enhanced separation efficiency, reliability in qualitative and quantitative analysis, capability to detect low quantities, and information on the whole sample and its components. These features are essential in the analysis of complex samples, in which the number of compounds may be large or the analytes of interest are present at trace level. This study involved the development of instrumentation, data analysis programs and methodologies for GC×GC and their application in studies on qualitative and quantitative aspects of GC×GC analysis. Environmental samples were used as model samples. Instrumental development comprised the construction of three versions of a semi-rotating cryogenic modulator in which modulation was based on two-step cryogenic trapping with continuously flowing carbon dioxide as coolant. Two-step trapping was achieved by rotating the nozzle spraying the carbon dioxide with a motor. The fastest rotation and highest modulation frequency were achieved with a permanent magnetic motor, and modulation was most accurate when the motor was controlled with a microcontroller containing a quartz crystal. Heated wire resistors were unnecessary for the desorption step when liquid carbon dioxide was used as coolant. With use of the modulators developed in this study, the narrowest peaks were 75 ms at base. Three data analysis programs were developed allowing basic, comparison and identification operations. Basic operations enabled the visualisation of two-dimensional plots and the determination of retention times, peak heights and volumes. The overlaying feature in the comparison program allowed easy comparison of 2D plots. An automated identification procedure based on mass spectra and retention parameters allowed the qualitative analysis of data obtained by GC×GC and time-of-flight mass spectrometry. In the methodological development, sample preparation (extraction and clean-up) and GC×GC methods were developed for the analysis of atmospheric aerosol and sediment samples. Dynamic sonication assisted extraction was well suited for atmospheric aerosols collected on a filter. A clean-up procedure utilising normal phase liquid chromatography with ultra violet detection worked well in the removal of aliphatic hydrocarbons from a sediment extract. GC×GC with flame ionisation detection or quadrupole mass spectrometry provided good reliability in the qualitative analysis of target analytes. However, GC×GC with time-of-flight mass spectrometry was needed in the analysis of unknowns. The automated identification procedure that was developed was efficient in the analysis of large data files, but manual search and analyst knowledge are invaluable as well. Quantitative analysis was examined in terms of calibration procedures and the effect of matrix compounds on GC×GC separation. In addition to calibration in GC×GC with summed peak areas or peak volumes, simplified area calibration based on normal GC signal can be used to quantify compounds in samples analysed by GC×GC so long as certain qualitative and quantitative prerequisites are met. In a study of the effect of matrix compounds on GC×GC separation, it was shown that quality of the separation of PAHs is not significantly disturbed by the amount of matrix and quantitativeness suffers only slightly in the presence of matrix and when the amount of target compounds is low. The benefits of GC×GC in the analysis of complex samples easily overcome some minor drawbacks of the technique. The developed instrumentation and methodologies performed well for environmental samples, but they could also be applied for other complex samples.

Designing against boredom in automated driving

I draw on four years of experience in mobility and transport research. I was part of a research project with Siemens, for which we identified global trends in urban mobility and explored future business opportunities through scenario planning methods. Some of the proposed solutions for personal and public transport included driverless vehicles. In collaboration with BMW Design I explored the potential of new materials for automotive user interfaces...

Bayesian fisheries stock assessment: integrating and updating knowledge

In this thesis the use of the Bayesian approach to statistical inference in fisheries stock assessment is studied. The work was conducted in collaboration of the Finnish Game and Fisheries Research Institute by using the problem of monitoring and prediction of the juvenile salmon population in the River Tornionjoki as an example application. The River Tornionjoki is the largest salmon river flowing into the Baltic Sea. This thesis tackles the issues of model formulation and model checking as well as computational problems related to Bayesian modelling in the context of fisheries stock assessment. Each article of the thesis provides a novel method either for extracting information from data obtained via a particular type of sampling system or for integrating the information about the fish stock from multiple sources in terms of a population dynamics model. Mark-recapture and removal sampling schemes and a random catch sampling method are covered for the estimation of the population size. In addition, a method for estimating the stock composition of a salmon catch based on DNA samples is also presented. For most of the articles, Markov chain Monte Carlo (MCMC) simulation has been used as a tool to approximate the posterior distribution. Problems arising from the sampling method are also briefly discussed and potential solutions for these problems are proposed. Special emphasis in the discussion is given to the philosophical foundation of the Bayesian approach in the context of fisheries stock assessment. It is argued that the role of subjective prior knowledge needed in practically all parts of a Bayesian model should be recognized and consequently fully utilised in the process of model formulation.

e-Extinction: an illusion of knowledge, the presence of ignorance, or evolutionary fate?

At present, the rate of small firm adoption of the Internet's ubiquitous World Wide Web (the web) far exceeds the actual exploitation its commercial potential. An inability to strategically acquire, comprehend and use external knowledge is proposed as a major barrier to optimal exploitation of the Internet. This paper discusses the limitations of applying market orientation theory to explain and guide small firm exploitation of the web. Absorptive capacity is introduced as an alternative theory that when viewed from an evolutionary perspective provides potentially more insightful discussion. An inability to detect emerging business model dominant designs is suggested to be a mixture of the nature of the technology that supports the Internet and underdeveloped small firm knowledge processing capabilities. We conclude with consideration of the practical and theoretical implications that arise from the paper.

Fine-tuning of unmanned aerial surveillance for ecological systems

Much of our understanding and management of ecological processes requires knowledge of the distribution and abundance of species. Reliable abundance or density estimates are essential for managing both threatened and invasive populations, yet are often challenging to obtain. Recent and emerging technological advances, particularly in unmanned aerial vehicles (UAVs), provide exciting opportunities to overcome these challenges in ecological surveillance. UAVs can provide automated, cost-effective surveillance and offer repeat surveys for pest incursions at an invasion front. They can capitalise on manoeuvrability and advanced imagery options to detect species that are cryptic due to behaviour, life-history or inaccessible habitat. UAVs may also cause less disturbance, in magnitude and duration, for sensitive fauna than other survey methods such as transect counting by humans or sniffer dogs. The surveillance approach depends upon the particular ecological context and the objective. For example, animal, plant and microbial target species differ in their movement, spread and observability. Lag-times may exist between a pest species presence at a site and its detectability, prompting a need for repeat surveys. Operationally, however, the frequency and coverage of UAV surveys may be limited by financial and other constraints, leading to errors in estimating species occurrence or density. We use simulation modelling to investigate how movement ecology should influence fine-scale decisions regarding ecological surveillance using UAVs. Movement and dispersal parameter choices allow contrasts between locally mobile but slow-dispersing populations, and species that are locally more static but invasive at the landscape scale. We find that low and slow UAV flights may offer the best monitoring strategy to predict local population densities in transects, but that the consequent reduction in overall area sampled may sacrifice the ability to reliably predict regional population density. Alternative flight plans may perform better, but this is also dependent on movement ecology and the magnitude of relative detection errors for different flight choices. Simulated investigations such as this will become increasingly useful to reveal how spatio-temporal extent and resolution of UAV monitoring should be adjusted to reduce observation errors and thus provide better population estimates, maximising the efficacy and efficiency of unmanned aerial surveys.

Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.