1. |
- Gustafsson, Berit M., 1966-
(författare)
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Identifying Patterns of Emotional and Behavioural Problems in Preschool children : Facilitating Early Detection
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Mental health problems often debut in early childhood and may last throughout adulthood, thereby making early detection and intervention especially important. The overarching aim of the present thesis was to identify patterns of emotional and behavioural problems indicating mental health problems in preschool children. To facilitate the detection of such problems early on, one available screening instrument Strengths and Difficulties Questionnaire (SDQ), was validated. The development and interaction of externalising problems in preschool children were studied over time. Functioning and behaviour and their relations to protective and risk indicators in both environmental and personal characteristics were explored. The long-term goal was to increase knowledge about early identification of emotional and behavioural problems in preschool children in order to facilitate early intervention.In Study I (n=690), the subscales Hyperactivity and Conduct Problems were shown to be valid for children in the age group 1–3 years. A reasonable level of validity was found for the age group 4–5 years when using the original SDQ four-factor solution. The preschool teachers considered most of the SDQ items relevant and possible to rate. Based on the results of Study II (n=815), a score of ≥12 on the SDQ Total Problems Scale is recommended as a cut-off for Swedish preschool children. There were significant differences between boys and girls on all subscales except for the Emotional subscale. The Swedish norms for SDQ are to a large extent similar to findings from other European countries. Study III (n=195) showed that preschool children’s conduct problems decrease over time. Children exhibiting more initial hyperactivity (at year 1) have less reduction in conduct problems over time, i.e. the more hyperactivity early in life, the more conduct problems at year 3. In Study IV (n=197), children high in engagement and social interaction function well over time, even in the presence of hyperactivity, while children with low engagement and interaction alone or in combination with hyperactivity and conduct problems continue to have problems. Stability was related to the existence of a larger number of protective or risk indicators respectively.Taken together, this thesis has shown that the SDQ can be used to identify preschool children at risk of developing mental health problems later in life.
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2. |
- Abenius, Erik, 1971-
(författare)
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Direct and Inverse Methods for Waveguides and Scattering Problems in the Time Domain
- 2005
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Numerical simulation is an important tool in understanding the electromagnetic field and how it interacts with the environment. Different topics for time-domain finite-difference (FDTD) and finite-element (FETD) methods for Maxwell's equations are treated in this thesis. Subcell models are of vital importance for the efficient modeling of small objects that are not resolved by the grid. A novel model for thin sheets using shell elements is proposed. This approach has the advantage of taking into account discontinuities in the normal component of the electric field, unlike previous models based on impedance boundary conditions (IBCs). Several results are presented to illustrate the capabilities of the shell element approach. Waveguides are of fundamental importance in many microwave applications, for example in antenna feeds. The key issues of excitation and truncation of waveguides are addressed. A complex frequency shifted form of the uniaxial perfectly matched layer (UPML) absorbing boundary condition (ABC) in FETD is developed. Prism elements are used to promote automatic grid generation and enhance the performance. Results are presented where reflection errors below -70dB are obtained for different types of waveguides, including inhomogeneous cases. Excitation and analysis via the scattering parameters are achieved using waveguide modes computed by a general frequency-domain mode solver for the vector Helmholtz equation. Huygens surfaces are used in both FDTD and FETD for excitation in waveguide ports. Inverse problems have received an increased interest due to the availability of powerful computers. An important application is non-destructive evaluation of material. A time-domain, minimization approach is presented where exact gradients are computed using the adjoint problem. The approach is applied to a general form of Maxwell's equations including dispersive media and UPML. Successful reconstruction examples are presented both using synthetic and experimental measurement data. Parameter reduction of complex geometries using simplified models is an interesting topic that leads to an inverse problem. Gradients for subcell parameters are derived and a successful reconstruction example is presented for a combined dielectric sheet and slot geometry.
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3. |
- Aftab, Obaid, 1984-
(författare)
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Towards High-Throughput Phenotypic and Systemic Profiling of in vitro Growing Cell Populations using Label-Free Microscopy and Spectroscopy : Applications in Cancer Pharmacology
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Modern techniques like automated microscopy and spectroscopy now make it possible to study quantitatively, across multiple phenotypic and molecular parameters, how cell populations are affected by different treatments and/or environmental disturbances. As the technology development at the instrument level often is ahead of the data analytical tools and the scientific questions, there is a large and growing need for computational algorithms enabling desired data analysis. These algorithms must have capacity to extract and process quantitative dynamic information about how the cell population is affected by different stimuli with the final goal to transform this information into development of new powerful therapeutic strategies. In particular, there is a great need for automated systems that can facilitate the analysis of massive data streams for label-free methods such as phase contrast microscopy (PCM) imaging and spectroscopy (NMR). Therefore, in this thesis, algorithms for quantitative high-throughput phenotypic and systemic profiling of in vitro growing cell populations via label-free microscopy and spectroscopy are developed and evaluated. First a two-dimensional filter approach for high-throughput screening for drugs inducing autophagy and apoptosis from phase contrast time-lapse microscopy images is studied. Then new methods and applications are presented for label-free extraction and comparison of time-evolving morphological features in phase-contrast time-lapse microscopy images recorded from in vitro growing cell populations. Finally, the use of dynamic morphology and NMR/MS spectra for implementation of a reference database of drug induced changes, analogous to the outstanding mRNA gene expression based Connectivity Map database, is explored. In conclusion, relatively simple computational methods are useful for extraction of very valuable biological and pharmacological information from time-lapse microscopy images and NMR spectroscopy data offering great potential for biomedical applications in general and cancer pharmacology in particular.
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4. |
- Andersson, Claes, 1978-
(författare)
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Fusing Domain Knowledge with Data : Applications in Bioinformatics
- 2008
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Massively parallel measurement techniques can be used for generating hypotheses about the molecular underpinnings of a biological systems. This thesis investigates how domain knowledge can be fused to data from different sources in order to generate more sophisticated hypotheses and improved analyses. We find our applications in the related fields of cell cycle regulation and cancer chemotherapy. In our cell cycle studies we design a detector of periodic expression and use it to generate hypotheses about transcriptional regulation during the course of the cell cycle in synchronized yeast cultures as well as investigate if domain knowledge about gene function can explain whether a gene is periodically expressed or not. We then generate hypotheses that suggest how periodic expression that depends on how the cells were perturbed into synchrony are regulated. The hypotheses suggest where and which transcription factors bind upstreams of genes that are regulated by the cell cycle. In our cancer chemotherapy investigations we first study how a method for identifiyng co-regulated genes associated with chemoresponse to drugs in cell lines is affected by domain knowledge about the genetic relationships between the cell lines. We then turn our attention to problems that arise in microarray based predictive medicine, were there typically are few samples available for learning the predictor and study two different means of alleviating the inherent trade-off betweeen allocation of design and test samples. First we investigate whether independent tests on the design data can be used for improving estimates of a predictors performance without inflicting a bias in the estimate. Then, motivated by recent developments in microarray based predictive medicine, we propose an algorithm that can use unlabeled data for selecting features and consequently improve predictor performance without wasting valuable labeled data.
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5. |
- Andersson, Karl, 1972-
(författare)
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Characterization of Biomolecular Interactions Using a Multivariate Approach
- 2004
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis presents a novel bioinformatic methodology denoted the bio-chemometric approach. The methodology is designed for generation of detailed descriptions and predictions of biomolecular interactions. It is based on multivariate analysis of the sensitivity of a biomolecular interaction to multiple minor changes in the experimental conditions. In this work, either the chemical environment where the interaction takes place, or the molecular structure of one of the interacting molecules, was varied. The sensitivity of the interaction to the performed variations was presented as a vector called the sensitivity fingerprint. The bio-chemometric approach was tested on several biomolecular interactions. Useful descriptions of the interactions were obtained by measuring binding kinetics for each interaction in 12-20 different buffers and correlating buffer composition to binding kinetics. The obtained chemical sensitivity fingerprints were reproducible, significantly different and showed a weak correlation to binding site properties for the tested interactions. The results indicate that the fingerprints contained useful information about the binding site. The predictive ability of the bio-chemometric approach was tested on two different biomolecular interactions where one of the binding partners was slightly modified into multiple analogues by amino acid exchanges. In one example, interactions of 18 peptide analogues with an antibody gave data that could be used for accurate prediction of the dissociation rates of novel analogues. Reliable predictions of binding kinetics and affinity were also obtained for single domain camel antibody analogues binding to a protein antigen. By using the three-dimensional structure of camel antibodies and data obtained using the bio-chemometric approach, even the importance of non-exchanged amino acids for the binding could be estimated. The bio-chemometric approach can potentially improve the development of peptides and proteins for therapeutic and diagnostic use. It is suggested to be valid for general use in biochemistry.
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6. |
- Asraf, Daniel
(författare)
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Optimal Detectors for Transient Signal Families and Nonlinear Sensors : Derivations and Applications
- 2003
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis is concerned with detection of transient signal families and detectors in nonlinear static sensor systems. The detection problems are treated within the framework of likelihood ratio based binary hypothesis testing.An analytical solution to the noncoherent detection problem is derived, which in contrast to the classical noncoherent detector, is optimal for wideband signals. An optimal detector for multiple transient signals with unknown arrival times is also derived and shown to yield higher detection performance compared to the classical approach based on the generalized likelihood ratio test.An application that is treated in some detail is that of ultrasonic nondestructive testing, particularly pulse-echo detection of defects in elastic solids. The defect detection problem is cast as a composite hypothesis test and a methodology, based on physical models, for designing statistically optimal detectors for cracks in elastic solids is presented. Detectors for defects with low computational complexity are also formulated based on a simple phenomenological model of the defect echoes. The performance of these detectors are compared with the physical model-based optimal detector and is shown to yield moderate performance degradation.Various aspects of optimal detection in static nonlinear sensor systems are also treated, in particular the stochastic resonance (SR) phenomenon which, in this context, implies noise enhanced detectability. Traditionally, SR has been quantified by means of the signal-to-noise ratio (SNR) and interpreted as an increase of a system's information processing capability. Instead of the SNR, rigorous information theoretic distance measures, which truly can support the claim of noise enhanced information processing capability, are proposed as quantifiers for SR. Optimal detectors are formulated for two static nonlinear sensor systems and shown to exhibit noise enhanced detectability.
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7. |
- Bäcklin, Christofer, 1983-
(författare)
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Machine Learning Based Analysis of DNA Methylation Patterns in Pediatric Acute Leukemia
- 2015
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer in the Nordic countries. Recent evidence indicate that DNA methylation (DNAm) play a central role in the development and progression of the disease.DNAm profiles of a collection of ALL patient samples and a panel of non-leukemic reference samples were analyzed using the Infinium 450k methylation assay. State-of-the-art machine learning algorithms were used to search the large amounts of data produced for patterns predictive of future relapses, in vitro drug resistance, and cytogenetic subtypes, aiming at improving our understanding of the disease and ultimately improving treatment.In paper I, the predictive modeling framework developed to perform the analyses of DNAm dataset was presented. It focused on uncompromising statistical rigor and computational efficiency, while allowing a high level of modeling flexibility and usability. In paper II, the DNAm landscape of ALL was comprehensively characterized, discovering widespread aberrant methylation at diagnosis strongly influenced by cytogenetic subtype. The aberrantly methylated regions were enriched for genes repressed by polycomb group proteins, repressively marked histones in healthy cells, and genes associated with embryonic development. A consistent trend of hypermethylation at relapse was also discovered. In paper III, a tool for DNAm-based subtyping was presented, validated using blinded samples and used to re-classify samples with incomplete phenotypic information. Using RNA-sequencing, previously undetected non-canonical aberrations were found in many re-classified samples. In paper IV, the relationship between DNAm and in vitro drug resistance was investigated and predictive signatures were obtained for seven of the eight therapeutic drugs studied. Interpretation was challenging due to poor correlation between DNAm and gene expression, further complicated by the discovery that random subsets of the array can yield comparable classification accuracy. Paper V presents a novel Bayesian method for multivariate density estimation with variable bandwidths. Simulations showed comparable performance to the current state-of-the-art methods and an advantage on skewed distributions.In conclusion, the studies characterize the information contained in the aberrant DNAm patterns of ALL and assess its predictive capabilities for future relapses, in vitro drug sensitivity and subtyping. They also present three publicly available tools for the scientific community to use.
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8. |
- Chantzi, Efthymia
(författare)
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Algorithmic discovery, development and personalized selection of higher-order drug cocktails : A label-free live-cell imaging & secretomics approach
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- An upward trend in clinical pharmacology is the use of multiple drugs to combat complex and co-occurring diseases due to better efficacy, decreased toxicity and reduced risk of evolving resistance. Despite high late-stage attrition rates and the need for multi drug treatments, most drug discovery and development efforts are still mainly focused on new one-size-fits-all monotherapies. This is unfortunate given the complex, heterogeneous and often only partially understood pathophysiology of many diseases. In this context, polypharmacotherapies hold strong potential, especially when patient tailored. However, as of today, the personalized combination therapy area remains vastly unexplored. A major reason is lack of standardized and robust tools that allow systematic in vitro drug combination sensitivity testing of different disease models and patient derived cells.This thesis fills in this lack by introducing two methodological frameworks, namely COMBImageDL and COMBSecretomics, designed to enable systematic second- and higher-order drug combination studies within and beyond cancer pharmacology. They include advanced quality control procedures, non-parametric resampling statistics to quantify uncertainty and a data driven methodology to evaluate response patterns and discern higher- from lower- and single-drug effects. Both are based on a standardized and reproducible format that could be employed with any experimental platform that provides the required raw data. COMBImageDL searches exhaustively for drug cocktails that induce changes in cell viability and time evolving cell culture morphology by employing conventional endpoint synergy analyses jointly with quantitative label-free live-cell imaging. Deep neural network learning, MapReduce parallel processing and method-specific parameter tuning are key components of the design. The purely phenotypic functionality of COMBImageDL is extended by COMBSecretomics, which searches exhaustively for drug cocktails that can modify, or even reverse malfunctioning secretomic patterns. It processes complex datasets involving drug treated cells observed before and after being stimulated by relevant proteins. Finally, the highest single agent method is generalized for higher-order drug combination analysis and adjusted for secreted protein profiles.The frameworks were used in five pharmacological studies being industrial, academic and clinical collaborations in areas where novel and personalized multi drug regimens are highly needed; oncology (acute myeloid leukemia and glioblastoma multiforme) and osteoarthritis. These studies demonstrate intriguing drug combination findings and in general the great potential of tools like COMBImageDL and COMBSecretomics to accelerate the discovery and development of novel potent polypharmacotherapeutic candidates.
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9. |
- Cullhed, Anna, 1966-
(författare)
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The language of passion : the order of poetics and the construction of a lyric genre 1746-1806
- 2001
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The subject of this dissertation is the construction of a lyric genre in academic poetics between 1746 and 1806, in handbooks and lectures by Ch. Batteux, J. A. Schlegel, J. G. Sulzer, H. Blair, J. J. Eschenburg, J. J. Engel, A. W. Schlegel, F. W. J. Schelling, F. Ast, and F. Bouterwek. The study also aims at a reconsideration of neoclassical versus romantic poetics. The first chapter investigates the relation between tradition and discourse. It argues that poetics as a discipline relies on an ancient legacy and on contemporary legitimising discourses, such as the natural sciences, moral philosophy, or idealist philosophy. The two levels indicate sites of interplay between continuity and change. The second chapter discusses the concept of genre. It is established that the lyric genre is not dependent on a triadic system of genres. All sources provide generic enumerations, even though they represent different approaches to systematic closure. The lyric genre consists of a classical canon paired with a more changeable set of contemporary lyrics. The lyric genre is defined as the language of passion in all sources and is connected with brevity, enthusiasm, metrical freedom, and disorder. In the third chapter lyrical expression is related to concepts such as imitation, authenticity, original poetry, and religious poetry. The lyric genre vacillates between the expression of universal and individual feelings. It is argued that the identification of lyric poetry as expression does not entail that the emotions in question are to be understood as authentic.
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10. |
- Dymek, Mikolaj, 1978-
(författare)
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Industrial Phantasmagoria : Subcultural Interactive Cinema Meets Mass-Cultural Media of Simulation
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The video game industry has in three decades gone from a garage hobby to a global multi-billion euro media industry that challenges the significantly older and established cultural industries. After decades of explosive growth the industry surprisingly finds itself in a crisis – in terms of sales, future trajectories and creative paradigms. The global gaming culture receives substantial attention from society, media and academia – but the industry itself appears in comparison as an enigmatic terra incognita with astonishingly little dedicated research. This thesis aims to amend this situation by presenting a study at the cross-section of the video game industry, game studies, literary theory, cultural industries and business studies. It deals with the following question: how does the global game industry relate to its own product, in terms of communication and media dimensions, and what are the (business) consequences, in terms of production, strategy and commercial/creative innovation, of this relationship? This study’s departure point is constituted by a comprehensive description of the industry’s structure, dynamics and processes, based on extensive interviews with industry professionals. It is followed by an examination and comparison of the game industry with other media/cultural industries in relation to their economy and business dynamics. With inconclusive answers regarding the medium-industry relation, this study proceeds by exploring literary theories from the field of game studies, in order to gain insights into the dynamics of medium and industry. Literary theories from ludology and narratology provide rewarding perspectives on this inquiry, since it is found that the ontological dichotomy of simulation vs. respresentation present in the interpretational realm of the game medium is also reflected in the industry and its dynamics. This has pivotal consequences for the analysis of the game industry. This study concludes by positing the current critical condition of the industry as an extremely decisive moment in its history: will it become a truly universal mass-medium, or will it continue down its subcultural path? Subcultural “interactive cinema” meets mass-cultural media of simulation – how will the industry evolve?
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