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Objective: To identify prognostic factors for patients with advanced persistent, recurrent, or 2nd primary oral cavity squamous cell carcinoma (OCSCC) potentially unsuitable for salvage surgery with free tissue flap (FTF) reconstruction. Materials and methods: A population-based cohort of 83 consecutive patients with advanced OCSCC who underwent salvage surgery with FTF reconstruction at a tertiar

Background: Five workers from an industry manufacturing various articles from carbon fibre reinforced epoxy plastics were referred to our department because of suspected occupational allergic contact dermatitis (OACD). When patch tested, four of them had positive reactions to components of epoxy resin systems (ERSs) that could explain their current skin problems. All of them had been working at th

Vassiliki “Betty” Smocovitis has done a thorough and admirable job in highlighting the complex history the Modern Synthesis (MS) or the Evolutionary Synthesis (ES) as she prefers to call it. Her interesting contribution should hopefully increase awareness that the history of evolutionary biology is important even for researchers today who are mainly interested in solving practical questions of mor

Purpose: To demonstrate the feasibility and accuracy of chemical shift–encoded imaging of the fatty acid composition (FAC) of human bone marrow adipose tissue at 7 T, and to determine suitable image-acquisition parameters using simulations. Methods: The noise performance of FAC estimation was investigated using simulations with a range of inter-echo time, and accuracy was assessed using a phantom

Background: Resuscitative endovascular balloon occlusion of the aorta (REBOA) is an emerging and potentially life-saving procedure, necessitating qualified operators in an increasing number of centres. The procedure shares technical elements with other vascular access procedures using the Seldinger technique, which is mastered by doctors not only in endovascular specialties but also in trauma surg

The present Multi-view stereo (MVS) methods with supervised learning-based networks have an impressive performance comparing with traditional MVS methods. However, the ground-truth depth maps for training are hard to be obtained and are within limited kinds of scenarios. In this paper, we propose a novel unsupervised multi-metric MVS network, named M 3 VSNet, for dense point cloud reconstruction w

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