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Mathematical modeling of cocoa bean fermentation
No full textIn this thesis, a series of mathematical models are presented to bring a quantitative exploration of the mechanistic features of the cocoa bean fermentation process with the use of Ordinary Differential Equation Systems. In this sense, several sources of data have been used in order to fit these mathematical conceptualizations by a Bayesian framework to solve the parameter estimation problem. A baseline model is proposed, assessed and discussed in terms of its biological plausibility, and an interpretation of its got parameter estimates is introduced as an indirect indicative of differences between trials’ features.
Therefore, I present a deeper analysis of model iterations based on the baseline with the purpose of accomplishing a wider exploration of five hypothesized mechanisms, e.g., over-oxidation of acetic acid and consumption of fructose by lactic acid bacteria. In that way, their likeliness of occurrence is determined by their overall success on fitting several data gathered from 23 different fermentation trials. Also, an analysis of obtained parameter estimates as classifying fermentation features is discussed.
Finally, the effect of temperature on kinetic modeling of cocoa bean fermentation is addressed by the use of Arrhenius terms and discussed in terms of gains in interpretation and biological plausibility of the parameter estimates and its effect on model accuracy.
The findings in this thesis provide new insights into the understanding of the complex process of cocoa bean fermentation by assessing candidate mechanisms, and interpreting parameter estimates from a biological point of view towards their use as an addition to chemical fingerprinting methods for classifying features
Interdisciplinary Assessment of Deep-Sea Mining Impacts: From Science to Policy and Implications for Sustainable Development
No full textMarine mineral resources contain significant amounts of metals, which could, in the future, serve as raw materials for producing various goods. Proponents of deep-sea mining (DSM) point out that DSM may be preferable to terrestrial mining, as it would neither require the removal of vegetation or overburden nor the relocation of local communities. Opponents raise concerns about the industry’s expected environmental and social impacts. To close some knowledge gaps and to contribute to the holistic and interdisciplinary assessment of DSM, this thesis, firstly, investigates the environmental, social, economic, and legal impacts of DSM. It finds that DSM is a highly complex topic and that minimizing its adverse impacts requires intense interdisciplinary and integrated research. Secondly, this thesis quantified the fuel consumption and subsequent release of greenhouse gas (GHG) emissions and air pollutants associated with a hypothetical manganese nodule mining operation. The assessment shows that the emissions may range between 82,600 - 482,000t CO2-equivalent (-eq.), 1,880 - 11,197t SO2-eq., and 1,390–8,734 t NOx-eq., respectively. The exact magnitude of emissions depends on factors such as engine loads, specific fuel oil consumption, and transport speed. The thesis also demonstrates that GHG emissions resulting from DSM in areas beyond national jurisdiction are not adequately regulated. Based on a criteria-based assessment, it recommends that the International Seabed Authority takes the lead in regulating and mitigating these emissions. Lastly, this thesis discussed to what extent deep-sea mining can contribute to reaching the UN’s Sustainable Development Goals (SDGs). It finds that DSM is incompatible with SDGs 12 and 14 but may be compatible with SDGs 2, 3, 10, 7, 13, provided that the minerals obtained are used to produce green technology and that strict regulations and a good governance strategy are in place to minimize the industry’s adverse impacts
The Virgin Lands Campaign in Kazakhstan: A Social History, 1954 - 1964
No full textFrom today’s perspective, the Virgin Lands Campaign (VLC), an initially agricultural intervention which unfolded in Soviet Kazakhstan in the decade between 1954 and 1964 and turned into a major social reform, appears like a mosaic made of pieces which, although fitting together seemingly well, were of a different nature, scale, importance and clarity. This dissertation is an attempt to deconstruct this phenomenon and, in so doing, to find how the VLC as a sequence of agricultural, social and ideological interventions, interplayed with larger developments associated with Khrushchev’s leadership, in the specific setting of the Kazakh countryside. I seek to answer two questions: How did the social and ideological settings of Soviet Kazakhstan change with the onset of the VLC and what implications did this have for the livelihood patterns and cultural identification of Kazakhs? What kind of development was triggered by the VLC in the Kazakh countryside and beyond, and what was the role of other, larger processes characteristic of the Soviet Union as a whole, in this transformation? I answer these questions in five chapters, which mirror the dimensions of the VLC. Chapter 1 proffers a lens of construction and planning to show how the VLC, on the one hand, laid the foundation for the radical improvement of the standard of rural living in Soviet Kazakhstan and, on the other, contributed to the preservation of customary means of existence in the Kazakh steppe. Chapter 2, which looks into a drive to boost livestock production in the Virgin Lands from 1957 onwards, introduces the earlier obscure players of the VLC, that is, stockbreeders and animals. Chapter 3 explores the Virgin Lands as an arena for social engineering efforts to build the internationalist society. Chapter 4 takes a closer look at one of the cultural identifiers, the Kazakh language. Chapter 5 considers the role of another cultural identifier, Kazakh literature, in legitimizing the VLC in the public eye
Machine Learning Supervised Classification Methodology for Autism Spectrum Disorder based on Resting-State Electroencephalography (EEG) Signals
No full textAutism Spectrum Disorder is a neurological and developmental disorder that starts early in adolescence and lasts throughout a person’s life affecting information flow in the brain leading to secondary problems for the patient. Early detection of ASD is vital in enhancing the efficiency of the treatment. Current diagnostic approaches for autism are time-consuming, to accelerate this process of diagnosing the disease as early as possible with fewer efforts and better accuracy machine learning methods have been proposed recently. This paper presents the diagnosis of ASD based on resting-state eyes-closed EEG signals using machine learning algorithms. The research study population consists of 100 children with ASD (82 male and 18 female) between 5-19 years and 88 healthy developing children in the same range of age with equal proportion of males and female. Power spectrum analysis was used for the analysis of EEG as feature extraction. In addition, feature selection is applied based on principal component analysis for dimensionality reduction. The Logistic Regression, K-Nearest Neighbours, Decision Trees, Random Forest, Extra Trees and Extreme Gradient Boosting classifiers are used for the classification of autistic versus typically developing children. Evaluating the performance of the best classifier among the baseline models results in a classification accuracy of 67.7%, AUC 0.74, 83.3% recall, 61% precision and 54.3% specificity using Extra Trees Additionally, the results revealed that the children with ASD showed convincingly higher power in theta delta and beta bands and low power in alpha than normal group
Translocation of Phosphonic Acid Antibiotics Through Bacterial Outer Membrane Channels
No full textThe outer membrane of Gram-negative bacteria acts as a formidable barrier for the passage of substances from the external environment to the inside of the bacterium. Understanding the permeation of antibiotics through bacterial outer membrane channels is a subject of great interest to overcome the resistance and permeability problems associated with the translocation of antibiotics. The present Ph.D. thesis aims to understand the permeation of phosphonic acid-containing antibiotics through bacterial outer membrane channels.
In the first part, the permeation of fosfomycin through the porin OmpF of Escherichia coli has been investigated using molecular dynamics and Brownian dynamics simulations and is complementary to the electrophysiology experiments. This study aims to understand the permeation of fosfomycin and estimate the free energy barriers involved in the respective permeation process. Two OmpF triple mutants have been investigated to illustrate the effect of OmpF mutations on the translocation properties of fosfomycin. A high rate of fosfomycin diffusion through wild-type OmpF has been observed along with low permeation energy barriers, while higher barriers have been obtained for the studied mutants.
In the second part, the translocation mechanism of various anionic solutes, i.e., from simple ions to complex antibiotics through the OprO channel of Pseudomonas aeruginosa has been explored using metadynamics and umbrella sampling methods. Aspects of the free energy convergence and the role of the complexity of the permeating solutes in determining free energy surfaces have been demonstrated. Further, the permeation of fosfomycin and fosmidomycin through the phosphate specific OprP and OprO channels of Pseudomonas aeruginosa has been discussed. The findings presented in this thesis provide the atomistic and functional aspects of permeation processes through the outer membrane channels of Gram-negative bacteria
Modeling, Estimating, and Visualizing Spatial and Temporal Uncertainty for Image-Guided Therapy
No full textWe address different aspects of the problem of uncertainty in image-guided therapies. This is of great interest, because such uncertainty could have a substantial impact on public health. Significant uncertainties can occur in image segmentation and estimating deformations of anatomy. To model the uncertainty in the image segmentation aspect, we propose a novel stationary Gaussian process (GP)-based generative segmentation model. This segmentation model allows us to draw many possible image segmentations, which can be used for estimating and visualizing different aspects of the uncertainty in image-guided therapies. To enable drawing of many image segmentation samples efficiently, we propose a fast method for sampling from stationary GPs. To model the uncertainty in the aspect of estimating deformations of anatomy, we propose a novel spatiotemporal GP model for uncertainty-aware soft-tissue motion estimation using GP regression. The spatiotemporal GP formalism enables the estimation of anatomy displacements at any location, and for any time interval from measured motions that are sparse in space and time. The use of GP regression enables the quantification of uncertainty in the soft-tissue motion estimation result, which allows the amount of uncertainty in some aspects, e.g., registered planning medical images, of image-guided therapies or procedures governing the decisions of medical specialists to be conveyed. To convey the amount of uncertainty in the anatomy motion estimates, we propose novel motion uncertainty visualization methods. To showcase the use of the devised methods, we deploy them in the context of radiotherapy and image-guided soft-tissue intervention navigation. We expect that incorporating estimates of spatial and temporal uncertainty into the processing pipelines of image-guided therapy will eventually enable improved treatments, and thus, improved outcomes
Modelling the ballast water distribution in the Arctic Ocean
No full textBallast water is essential for a ship’s safe navigation and to compensate for weight changes during the load and unload of cargo. However, it is considered one of the main vectors for the transfer of aquatic organisms worldwide. These organisms can survive the voyage and discharge, reproduce, and become invasive to the host environment. With the decrease of sea ice extent in the Arctic seas, shipping has been increasing in the region, and it will keep growing. This study aims to identify areas where the discharge of ballast water represents the risk of contamination of ecosystems along the main Arctic shipping routes. For that, a series of passive tracer experiments are conducted using the regional coupled ocean-sea ice model, NAOSIM. The ballast water tracer (bw-tracer) is discharged in the model at selected ship positions. The model results show that the bw-tracer starts to accumulate at the end of spring, and its concentration increases during summer and autumn. In the west Spitsbergen sector, the bw-tracer is mainly transported by the West Spitsbergen Current and the East Greenland Current. Water recirculation between south Spitsbergen and Bear Island created an area of tracer accumulation. In the Barents Sea sector, the bw-tracer starts to accumulate south of Novaya Zemlya at the end of spring. Tracer concentration increase during summer and autumn. Particle trajectories demonstrated that organisms could be advected by the ocean surface currents to coastal ecosystems while presenting different pathways from the tracer. Tracer mixing is enhanced by the turbulent horizontal flow and vertical convection, being dependent on the mixed-layer seasonality. Eddy kinetic energy is correlated to the mixing of bw-tracer, and the displacement of particles along the trajectory pathways. Areas of tracer accumulation are indicators of high propagule pressure of non-indigenous species. That increases the chances of survival, reproduction, and establishment of invasive species
The temporal and spatial dynamics of the sublittoral fish community of Kongsfjorden, Spitsbergen
No full textThe Arctic is one of the areas that is most affected by global climate change (IPCC 2014). As a result of anthropogenic Arctic warming, the Arctic fish community might change, and species from temperate areas are expected to invade (Cheung et al. 2009). In this context, it is critical that “Arctic marine fishes are indispensable to ecosystem structuring and functioning, but they are still beyond credible assessment due to lack of basic biological data“ (Christiansen et al. 2014). Especially in the shallow-water zones (3 - 12 m) of Arctic fjord systems only qualitative data on fish community composition are available. In other ecosystems, it was shown that the structured shallow-water zone has special ecological functions (Seitz 2014, Pondella et al. 2015). Therefore, the objective of this study is to increase our scientific knowledge on the fish assemblage of this special area by performing a quantitative first-time assessment of its species composition and abundance as well as the size and age structure of selected species.
As study site, Kongsfjorden (79°N, 12°E) at the west coast of the Svalbard archipelago was chosen. It is one of the best investigated fjords in the Arctic, and the local AWIPEV research base provides one of few sites where this project could be logistically supported. Despite the local infrastructure, access to the field was restricted due to the challenging climatic regime of Kongsfjorden. A thorough risk assessment resulted in the finding that no fishing from small boats can be performed safely during the polar night. Fish assessments were therefore conducted with two complementary methodologies. The first method was seasonal fyke net fishing in June/July and September of the years 2012 to 2014. The second method was a year-round assessment via a stereo-optic imaging system, which was connected to an underwater observatory
Small but numerous - The spatial distribution of microplastics in the North Sea
No full textMicroplastics (MP) in the marine environment are of global concern. The European Marine Strategy Framework Directive (MSFD), targeting marine pollution, provides a legal framework for MP research in the North Sea. Utilizing state-of-the-art methods, this thesis presents a comprehensive dataset of concentrations, polymer types, size distribution, weathering status, and spatial distribution of MP (11–5000 µm) in sediments and surface waters of the southern North Sea. In surface waters, low-density polymers like polyethylene (PE) and polypropylene (PP) dominated, with the highest MP concentration (245 particles m-3) detected close to the English Channel and the Rhine delta. In sediments, PP was omnipresent but less abundant, accompanied by varnishes and rubbers, and the highest concentration (1189 particles kg-1) found in the central southern North Sea. Weathering status, assessed through carbonyl indices for PE and PP, differed significantly for the compartments and was on average lower for large MP (500–5000 µm) than for small MP (10–500 µm), potentially indicating a weathering dependent fragmentation. Surface water samples were also analyzed for paraffin waxes of 500 to 5000 µm size, which were detected at 14 of 24 stations. Their synthetic origin was confirmed by spectroscopic complemented with thermoanalytical techniques. Sediments of an urban fjord in Norway were analyzed with harmonized methods. The fjord’s MP concentrations ranged from 12×103 to 205×103 particles kg-1, exceeding the highest concentration in the southern North Sea 10 to 100 times. This thesis confirmes the significant influence of regional input processes and highlights that harmonized methods providing comprehensive data are indispensable for inter-study comparisons. It emphasizes that future studies and monitoring efforts should analyze small MP, which showed much higher concentrations and more diverse polymer compositions than large MP, to allow for reliable environmental risk assessment dat
A Query Language for Analytics on Spatio-Temporally Varying Objects
No full textThis report defines a high-level, abstract query language targeted at analytics on multidi-mensional spatio-temporally varying objects. Specifically, the language focuses on ex-traction, processing, and analysis of datacubes representing – among others – spatio-temporal sensor, image, simulation, or statistics data. The conceptual data model is given by coverages as per OGC and ISO standards, in particular grid coverages as defined in OGC Coverage Implementation Schema (CIS) version 1.1.
Except for the space/time and coverage specific elements the language employs the same expression evaluation semantics as the ISO SQL/MDA (Multi-Dimensional Arrays) ex-tension developed by our team in parallel. A mapping of WCPS to the rasdaman array query language, the blueprint for SQL/MDA, has been implemented and evaluated suc-cessfully.
The document is formatted with the purpose of submitting it as a standards proposal to OGC under the name Web Coverage Processing Service (WCPS)