Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling.

Multi-fidelity modelling enables accurate inference of quantities of interest by synergistically combining realizations of low-cost/low-fidelity models with a small set of high-fidelity observations. This is particularly effective when the low- and high-fidelity models exhibit strong correlations, and can lead to significant computational gains over approaches that solely rely on high-fidelity models. However, in many cases of practical interest, low-fidelity models can only be well correlated to their high-fidelity counterparts for a specific range of input parameters, and potentially return wrong trends and erroneous predictions if probed outside of their validity regime. Here we put forth a probabilistic framework based on Gaussian process regression and nonlinear autoregressive schemes that is capable of learning complex nonlinear and space-dependent cross-correlations between models of variable fidelity, and can effectively safeguard against low-fidelity models that provide wrong trends. This introduces a new class of multi-fidelity information fusion algorithms that provide a fundamental extension to the existing linear autoregressive methodologies, while still maintaining the same algorithmic complexity and overall computational cost. The performance of the proposed methods is tested in several benchmark problems involving both synthetic and real multi-fidelity datasets from computational fluid dynamics simulations.

Multi-fidelity modelling via recursive co-kriging and Gaussian-Markov random fields.

We propose a new framework for design under uncertainty based on stochastic computer simulations and multi-level recursive co-kriging. The proposed methodology simultaneously takes into account multi-fidelity in models, such as direct numerical simulations versus empirical formulae, as well as multi-fidelity in the probability space (e.g. sparse grids versus tensor product multi-element probabilistic collocation). We are able to construct response surfaces of complex dynamical systems by blending multiple information sources via auto-regressive stochastic modelling. A computationally efficient machine learning framework is developed based on multi-level recursive co-kriging with sparse precision matrices of Gaussian-Markov random fields. The effectiveness of the new algorithms is demonstrated in numerical examples involving a prototype problem in risk-averse design, regression of random functions, as well as uncertainty quantification in fluid mechanics involving the evolution of a Burgers equation from a random initial state, and random laminar wakes behind circular cylinders.

Attitudes of nurse professionals and nursing students towards children with disabilities. Do nurses really overcome children's physical and mental handicaps?

BACKGROUND: Many health professionals and nurses, who are involved in the care of disabled children, do not exhibit the essential sensitivity and appropriate attitudes towards them, resulting in a poor quality of nursing care. AIM: The objective of this study was to investigate the attitudes of nurse professionals (paediatric nurses) and nursing students towards disabled children. PATIENTS AND METHODS: The present study is a comparative study. The sample consisted of 228 first-year nursing students, 90 post-diploma nurses attending MSc degree course and 123 nurse professionals who are employed in paediatric hospitals. After obtaining permission from the hospitals and the educational settings and informing about the subjects of the study, data were collected using the paediatric Attitude Towards Disabled Person Scale (ATDP). RESULTS: Overall nurses' attitudes appeared to be poor (mean ATDP score 61.7 +/- 14.2). However, the post-diploma nurses had significantly higher ATDP scores than first-year students and paediatric nurses (P < 0.001). In addition, first-year students had significantly higher scores than paediatric nurses (P = 0.047). Across the sample, females hold significantly more positive attitudes than males (F = 9.5, P = 0.002), while age did not have any significant effect. CONCLUSIONS: Carefully designed curricula can influence the attitudes of nursing students towards children with disabilities. Special courses for treating disabled children should be integrated to the basic nursing studies. Moreover, continuing hospital education can change paediatric nurses' attitudes towards children with disabilities.

Greek students' knowledge and sources of information regarding sex education.

BACKGROUND: Human sexuality is a complex part of life and is considered a multidimensional phenomenon. Therefore there is an increased need for adequate and comprehensive sex education, especially for teenagers and young adults. AIM: The main aim of the study was to evaluate the level of students' sexual knowledge, as well as to identify their sources of information regarding sexual life and reproduction. POPULATION AND METHOD: A cross-sectional study using a designed self-report questionnaire was performed. The study population consisted of 936 students who were attending 10 high schools and four medical schools in Attica. Data were collected after obtaining permission from the Pedagogic Institute of the Greek Ministry of Education. FINDINGS: The main sources of students' sexual information about reproduction were friends (29.1%) and parents (24.0%), whereas school was reported by 14.3% of them. The preferred sources of information, according to students' perceptions, were sex education specialists (65.6%), followed by school (39.1%), parents (32.2%) and friends (27.7%). CONCLUSIONS: The importance of school, peer and parent support upon adolescents' sexual life was revealed by the results of the study. Students' knowledge level on sex topics is not satisfactory and therefore there is a need for sex education specialists and special courses regarding sex education in Greek schools.

Evaluating depression in a sample of children and adolescents with cancer in Greece.

BACKGROUND: Several studies have found that serious illness increases the risk of depression. One of the most common psychiatric disorders related to the diagnosis and treatment of cancer is depression. AIM: The aim of the present study was to investigate the rate of depression in children with cancer compared with that in healthy children. PATIENTS AND METHODS: The present study is an ongoing prospective study. The research group consisted of 80 children with cancer followed up by an oncology inpatient clinic of a Greek Children's hospital. The control group consisted of 84 healthy children. After parental consent was obtained, data were collected using the Children's Depression Inventory (CDI) and a socio-demographic data form. RESULTS: At the time that this study was carried out, neither the research group nor the control group suffered from depression. In particular, there was no statistically significant difference between the two groups with respect to symptoms of depression (mean = 5.88 for children with cancer vs. mean = 7.23 for healthy children, U = 3013, P = 0.25). CONCLUSIONS: Our findings suggest that the children in this study with malignancies did not have higher depression scores than their healthy peers, although many previous surveys confirm that children with cancer are at high risk for depression.

Changes in children's fatigue during the course of treatment for paediatric cancer.

BACKGROUND: Fatigue is described as one of the most distressing symptoms of cancer therapy; yet it has received limited clinical attention. Children are suffering from a symptom that is under-diagnosed during their treatment. AIM: The aim of this study is: (a) to assess the change in fatigue scores during cancer treatment according to children's perspectives, and (b) to describe the possible causes of fatigue from children's points of view. SAMPLE AND METHODS: The present study is part of an ongoing prospective study. The research group consisted of 40 (n = 40) children aged 7-12 years with cancer who are being followed up in the oncology clinic of a Greek children's hospital. After parental consent was obtained, data were collected using the Child Fatigue Scale and a sociodemographic data form. RESULTS: The children with cancer reported a statistically significant increase in fatigue scores during their treatment (F = 6.846, P = 0.003). Gender was the only demographic factor associated with a significant increase in the fatigue scores (F = 4.857, P = 0.034). CONCLUSIONS: Cancer treatment was found significantly to increase children's fatigue levels. Medical procedures and the hospital environment seemed to be major causative factors of the fatigue experienced by children with cancer during their treatment.