Filetype
Wood is a porous, hygroscopic material that can take up water both within cell walls (cell-wall water) and in the macrovoid structure (capillary water). Therefore, moisture transport in wood occurs through multiple pathways and phases of water, that is, both cell-wall water, liquid water, and water vapor can be transported through the material structure. The amount of water in wood is quantified b
The advent of deep learning has yielded powerful tools to automatically compute gradients of computations. This is because training a neural network equates to iteratively updating its parameters using gradient descent to find the minimum of a loss function. Deep learning is then a subset of a broader paradigm; a workflow with free parameters that is end-to-end optimisable, provided one can keep t
This article extends the optimal covariance steering (CS) problem for discrete time linear stochastic systems modeled using moment-based ambiguity sets. To hedge against the uncertainty in the state distributions while performing covariance steering, distributionally robust risk constraints are employed during the optimal allocation of the risk. Specifically, a distributionally robust iterative ri
Aim: The aim of the study was to explore the work conditions that influence the opportunities for professional development of specialist nurses in surgical care. Design: A qualitative descriptive design was used. Methods: With a purposeful sampling procedure, 14 specialist nurses in surgical care were included. Four focus-group interviews were conducted during November to December 2021 and deducti
We investigate the problem of risk averse robot path planning using the deep reinforcement learning and distributionally robust optimization perspectives. Our problem formulation involves modelling the robot as a stochastic linear dynamical system, assuming that a collection of process noise samples is available. We cast the risk averse motion planning problem as a Markov decision process and prop
An integration of distributionally robust risk allocation into sampling-based motion planning algorithms for robots operating in uncertain environments is proposed. We perform non-uniform risk allocation by decomposing the distributionally robust joint risk constraints defined over the entire planning horizon into individual risk constraints given the total risk budget. Specifically, the determini
Paperboard is a thin and lightweight material made of cellulose fibers and it is an important component in packaging material where it provides stiffness and rigidity. The scope of this work is the development of continuum models, and its numerical treatments, for simulating the processes of converting paperboard into packages. The thesis begins with a general introduction to paperboard and a revi
Objectives: To examine potential sex differences in cognitive and functional progression rates in Alzheimer’s disease (AD) between patients with different concomitant medications. Methods: The Swedish Alzheimer Treatment Study is a prospective, observational, multicentre study in clinical practice undertaken at the initiation of cholinesterase inhibitor therapy in 1,021 patients diagnosed with mil
Global ecosystems are currently buckling under the weight of “plastics turbulence:” the condition of ubiquitous plastic entanglement within all human and non-human natural systems. This chapter argues that “global plastics governance” - the fragmented and variable political and institutional response to the plastics crisis - suffers from strategies that are doomed to fail because they miss what is
COVID-19 is a major public health threat associated with increased disease burden, mortality, and economic loss to countries and communities. Safe and efficacious COVID-19 vaccines are key in halting and reversing the pandemic. Low confidence in vaccines has been one of the factors leading to hesitancy. We aimed to assess the COVID-19 vaccine confidence (safety and effectiveness), associated facto
BACKGROUND: Post-term pregnancy is a health problem of clinical importance and; tends to recur in subsequent pregnancies. Maternal age, height, and male fetal sex are risk factors associated with Post-term pregnancy. The study aimed to determine the recurrence risk of post-term pregnancy and associated factors among women delivered at KCMC referral hospital.METHODOLOGY: This retrospective cohort s
This PhD thesis examines how application of 3D visualization and related digital analytical tools is having a transformative impact on archaeological practice via improvement of visual-spatial thinking and the strengthening of conceptual understanding. However, the deployment of these new digital methods is essentially still at an experimental stage. Therefore, the thesis undertakes a critical eva
In 2005, Pachon et al.1 proposed cardiac vagal denervation to treat neurally mediated syncope. Since then, a metanalysis of observational studies2 and a recent randomized controlled trial (RCT)3 have provided some evidence that cardioneuroablation (CNA) is able to prevent syncope recurrence at least during the first 2 years following the procedure in patients affected by reflex syncope. In brief,
This introductory article conceptualizes the notion of third country influence on European Union (EU) law and policy and proposes an analytical framework theorizing the venues and means through which third countries may gain such impact, under what conditions and with which implications for the EU’s legal and political order. The article first introduces the focus on outside-in influence in the co
Marja-Liisa Öberg unpacks the logic behind EU ‘decision-making autonomy’ – where only member states can participate in making EU decisions – suggesting that treating third countries as outsiders is not a flaw in the system but a fundamental policy choice that is unlikely to change any time soon.
The study of European integration has traditionally focused "inside-in" on the internal development of common laws and policies. With the maturing of the single market and the evolution of EU external relations, attention has shifted beyond the EU to the ways in which the EU intentionally and unintentionally projects its norms beyond its borders - the "inside-out" dynamics of European integration.
Deep learning, the study of multi-layered artificial neural networks, has received tremendous attention over the course of the last few years. Neural networks are now able to outperform humans in a growing variety of tasks and increasingly have an impact on our day-to-day lives. There is a wide range of potential directions to advance deep learning, two of which we investigate in this thesis:(1) O
