Methods to solve the equations of motion

"Series title: Springerbriefs in applied sciences and technology, ISSN 2191-530X"

Integration methods in dynamic analysis

"Series title: Springerbriefs in applied sciences and technology, ISSN 2191-530X"

A critical evaluation of methods for the reconstruction of tissue-specific models

Under the framework of constraint based modeling, genome-scale metabolic models (GSMMs) have been used for several tasks, such as metabolic engineering and phenotype prediction. More recently, their application in health related research has spanned drug discovery, biomarker identification and host-pathogen interactions, targeting diseases such as cancer, Alzheimer, obesity or diabetes. In the last years, the development of novel techniques for genome sequencing and other high-throughput methods, together with advances in Bioinformatics, allowed the reconstruction of GSMMs for human cells. Considering the diversity of cell types and tissues present in the human body, it is imperative to develop tissue-specific metabolic models. Methods to automatically generate these models, based on generic human metabolic models and a plethora of omics data, have been proposed. However, their results have not yet been adequately and critically evaluated and compared. This work presents a survey of the most important tissue or cell type specific metabolic model reconstruction methods, which use literature, transcriptomics, proteomics and metabolomics data, together with a global template model. As a case study, we analyzed the consistency between several omics data sources and reconstructed distinct metabolic models of hepatocytes using different methods and data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are even contradictory. Additionally, the hepatocyte metabolic models generated are in many cases not able to perform metabolic functions known to be present in the liver tissue. We conclude that reliable methods for a priori omics data integration are required to support the reconstruction of complex models of human cells.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Numerical methods in multibody system dynamics

"Series: Solid mechanics and its applications, vol. 226"

Factors associated with the donation and non-donation of embryos for research: a systematic review

Background: Systematic knowledge on the factors that influence the decisions of IVF users regarding embryo donation for research is a core need for patient-centred policies and ethics in clinical practice. However, no systematic review has been provided on the motivations of patients who must decide embryo disposition. This paper fills this gap, presenting a systematic review of quantitative and qualitative studies, which synthesizes the current body of knowledge on the factors and reasons associated with IVF patients’ decisions to donate or not to donate embryos for research. Methods: A systematic search of studies indexed in PubMed, ISIWoK and PsycINFO, published before November 2013, was conducted. Only empirical, peer-reviewed, full-length, original studies reporting data on factors and reasons associated with the decision concerning donation or non-donation of embryos for research were included. Eligibility and data extraction were performed by two independent researchers and disagreements were resolved by discussion or a third reviewer, if required. The main quantitative findings were extracted and synthesized and qualitative data were assessed by thematic content analysis. Results: A total of 39 studies met the inclusion criteria and were included in the review. More than half of the studies (n ¼ 21) used a quantitative methodology, and the remaining were qualitative (n ¼ 15) or mixed-methods (n ¼ 3) studies. The studies were derived mainly from European countries (n ¼ 18) and the USA(n ¼ 11). The proportion of IVF users who donated embryos for research varied from 7% in a study in France to 73% in a Swiss study. Those who donate embryos for research reported feelings of reciprocity towards science and medicine, positive views of research and high levels of trust in the medical system. They described their decision as better than the destruction of embryos and as an opportunity to help others or to improve health and IVF treatments. The perception of risks, the lack of information concerning research projects and the medical system and the conceptualization of embryos in terms of personhood were the most relevant motives for not donating embryos for research. Results relating to the influence of sociodemographic characteristics and reproductive and gynaecological history were mostly inconclusive. Conclusions: Three iterative and dynamic dimensions of the IVF patients’ decision to donate or not to donate embryos for research emerged from this review: the hierarquization of the possible options regarding embryo disposition, according to the moral, social and instrumental status attributed to embryos; patients’ understanding of expectations and risks of the research on human embryos; and patients’ experiences of information exchange and levels of trust in the medical-scientific institutions.

Hierarchical modelling of timber reference properties using probabilistic methods: Maximum Likelihood Method, Bayesian Methods and Probability Networks

In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.