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In many high-income countries, severe perinatal trauma (SPT), affecting the anal sphincter muscle complex, has been on the rise over the last decade. However, effective strategies to prevent SPT are scarce. In randomized controlled trials, only perineal warm compresses and massage have shown benefit. Other cohort studies have shown that prevention models involving several components can decrease t
Background: The protein C anticoagulant system plays a key role in maintaining the hemostatic balance. Although several studies have identified thrombomodulin gene (THBD) variants among venous thromboembolism (VTE) patients, the role of THBD in relation to VTE in humans remains to be clarified. Objectives: This study aimed to determine the thrombotic risk of rare and common THBD variants in a larg
To mitigate the climate change-induced water shortage and realize the sustainable development of agriculture, drip irrigation, a more efficient water-saving irrigation method, has been intensively implemented in most arid agricultural regions in the world. However, compared to traditional border irrigation, how drip irrigation affects the biophysical conditions in the cropland and how crops physio
OBJECTIVES: To assess whether the triage model Sepsis Alert for Emergency Departments results in improved initial care of patients with severe infections. DESIGN: Interventional study comparing patient care before and after the start of a new triage model, including 90-day follow-up. SETTING: Eight emergency departments in Skåne County, Sweden. SUBJECTS: Patients with suspected severe infection. I
Oscillatory neural activity in the cortico-basal ganglia-thalamocortical (CBGTC) loop is associated with the motor state of a subject, but also with the availability of modulatory neurotransmitters. For example, increased low-frequency oscillations in Parkinson’s disease (PD) are related to decreased levels of dopamine and have been proposed as biomarkers to adapt and optimize therapeutic interven
Several experiments and theoretical models of intermediate energy heavy ion collision physics are presented in this thesis. Statistical and dynamical aspects of nuclear collisions are widely discussed these days, particularly in connection with the multifragmentation phenomenon and the possible link to a liquid-gas phase transition in the spinodal region of nuclear matter phase diagram. Experiment
Recent years have seen the development of new iron-centered N-heterocyclic carbene (NHC) complexes for solar energy applications. Compared to typical ligand systems, the NHC ligands provide Fe complexes with longer-lived metal-to-ligand charge transfer (MLCT) states. This increased lifetime is ascribed to strong ligand field splitting provided by the NHC ligands that raises the energy levels of th
This thesis investigates the use of artificial neural networks for classifying Raman spectra of partially degraded cellulose samples by fungal species. A multilayer perceptron configuration of 4 hidden layers and 128 hidden nodes was able to classify a set of 60 samples with an overall prediction accuracy of 0.55. Results show that data resolution is an important factor when optimizing classifier
We define a mathematical method that, given the form of an interaction network, defines an energy as a function of the state of the network. When combined with a suitable entropy, it yields a free energy that gives rise to the dynamics of the network, allowing solutions and optimal paths to be efficiently found. This is done primarily with the gene regulatory networks governing cell reprogramming
The recently introduced capsule networks have already shown much success on image classification tasks. In this thesis, capsule networks are described and applied to a binary classification task, namely that of classifying hotspots from bone scintigraphy scans. The performance of capsule networks on this task is compared to that of convolutional neural networks. The results indicate that there is
Widespread presence of toxic and persistent pollutants in the environment, even at low concentrations, causes risks of adverse effects to human health and the ecosystem. Biological methods for treatment of water streams and removal of persistent pollutants are of great interest due to their simplicity, low cost, and mild operational conditions without harmful by-products. The purpose of this resea
En proglacial miljö är en integrerad del av ett glacialt landskap, där smältvattensavlagrade landformer är vanligt förekommande. Deras utseende är beroende av ett antal olika faktorer, så som processer aktiva under transport och deposition samt ursprungsmaterialets karaktär. Denna artikel syftar till att undersöka två terrestra smältvattens-successioner från de terminala delarna av glaciären MyrdaProglacial environments are an integrated part of the glacier landscape, housing a variety of landforms fed by glacier meltwater. Their appearance is dependent on a number of factors, such as the variability of source material and processes active during the transportation and deposition. The present work aims to investigate two such terrestrial outwash successions from the terminus region of the
This paper tests the “Square Root Rule” (the SRR), a Basel sanctioned method of scaling 1-day Value At risk to higher time horizons. The SRR has come under serious assault from leading researchers focusing on its week theoretical basis: assuming i.i.d. asset returns. I performed an empirical test of the SRR on the 10-day horizon, the maximum horizon allowed by Basel, comparing SRR performance to d
This paper proposes and investigates a Bayesian relation between optimal L2 regularization strengths and the number of training patterns and hidden nodes used for an artificial neural network. The results support the proposed dependence for number of training patterns, while the dependence on hidden architecture was less clear. Finally, applying different regularization strengths on different laye
Fitting a model to a time-dependent ensemble average is a process repeated frequently throughout biophysics. A selected ensemble-averaged observable (⟨y(t)⟩) for a given system can be predicted through the use of an estimated ensemble average, where the estimated ensemble average is created via simulated or experimental data sets. Fitting a model to this estimated ensemble average allows for estim
In this project, we compare two error functions for the purpose of training artificial neural networks on heavily censored data (data where key information is missing). J. Kalderstam et al. has shown that it is possible to train artificial neural networks directly on Harrell's C index \cite{Harrell} using genetic algorithms. He has also investigated the possibilities of improving the performa
Maintenance of stem cell pluripotency and the differentiation of stem cells into specialised cells has been studied extensively. More recently, the possibility for a specialised cell to be transferred into a state of induced pluripotency has been demonstrated and investigated. Critical components of the gene regulatory networks governing these processes have been identified, but a complete model h
