Family values and social policy in member and applicant countries of the European Union

Paper read at the ESPRN Conference "Social Values, Social Policies" Tilburg University. 29-31 August 2002.This paper explores the relation between family values and options for social policies of representative citizens from thirty European societies, constituting member and applicant countries of the European Union. It seeks to understand the values and value orientations supporting specific family structures and options for social policies of distinct groups of nations, corresponding to the various waves of accession or application for membership to the European Union. These include European Union (EU) members identified for an IPROSEC (Improving Policy Responses and Outcomes to Socio-Economic Challenges: changing family structures, policy and practice) project according to their welfare system and wave ofEU accession as Continental (France, Germany, Italy [joined in 1951]), Universal (United Kingdom, Ireland [1973]), Latin Rim (Greece [1981], Spain [1986]) and Nordic (Sweden [1995]) countries; post-communist (Hungary [applied in 1994], Poland [ 1994], Estonia [ 1995]) and Mediterranean (Malta [ 1990]) applicant countries (Hantrais 2001); and the remaining countries taken together: members, applicant and non-applicant countries of the European Union.peer-reviewe

Catholicism : the end of a 'world'?

Anthony M. Abela' s observation about the book Catholicisme, lafin d'un monde by Daniele Harvieu-Leger and a revised edition of a renowned book on Catholicism, on the social aspects of dogma, written about 60 years ago by the late Cardinal Henri de Lubac.peer-reviewe

Experimental analysis and transient numerical simulation of a large diameter pulsating heat pipe in microgravity conditions

A multi-parametric transient numerical simulation of the start-up of a large diameter Pulsating Heat Pipe (PHP) specially designed for future experiments on the International Space Station (ISS) are compared to the results obtained during a parabolic flight campaign supported by the European Space Agency. Since the channel diameter is larger than the capillary limit in normal gravity, such a device behaves as a loop thermosyphon on ground and as a PHP in weightless conditions; therefore, the microgravity environment is mandatory for pulsating mode. Because of a short duration of microgravity during a parabolic flight, the data concerns only the transient start-up behavior of the device. One of the most comprehensive models in the literature, namely the in-house 1-D transient code CASCO (French acronym for Code Avancé de Simulation du Caloduc Oscillant: Advanced PHP Simulation Code in English), has been configured in terms of geometry, topology, material properties and thermal boundary conditions to model the experimental device. The comparison between numerical and experimental results is performed simultaneously on the temporal evolution of multiple parameters: tube wall temperature, pressure and, wherever possible, velocity of liquid plugs, their length and temperature distribution within them. The simulation results agree with the experiment for different input powers. Temperatures are predicted with a maximum deviation of 7%. Pressure variation trend is qualitatively captured as well as the liquid plug velocity, length and temperature distribution. The model also shows the ability of capturing the instant when the fluid pressure begins to oscillate after the heat load is supplied, which is a fundamental information for the correct design of the engineering model that will be tested on the ISS. We also reveal the existence of strong liquid temperature gradients near the ends of liquid plugs both experimentally and by simulation. Finally, a theoretical prediction of the stable functioning of a large diameter PHP in microgravity is given. Results show that the system provided with an input power of 185W should be able to reach the steady state after 1min and maintain a stable operation from then on

Predicting Drug-Drug Interactions Using Knowledge Graphs

In the last decades, people have been consuming and combining more drugs than before, increasing the number of Drug-Drug Interactions (DDIs). To predict unknown DDIs, recently, studies started incorporating Knowledge Graphs (KGs) since they are able to capture the relationships among entities providing better drug representations than using a single drug property. In this paper, we propose the medicX end-to-end framework that integrates several drug features from public drug repositories into a KG and embeds the nodes in the graph using various translation, factorisation and Neural Network (NN) based KG Embedding (KGE) methods. Ultimately, we use a Machine Learning (ML) algorithm that predicts unknown DDIs. Among the different translation and factorisation-based KGE models, we found that the best performing combination was the ComplEx embedding method with a Long Short-Term Memory (LSTM) network, which obtained an F1-score of 95.19% on a dataset based on the DDIs found in DrugBank version 5.1.8. This score is 5.61% better than the state-of-the-art model DeepDDI. Additionally, we also developed a graph auto-encoder model that uses a Graph Neural Network (GNN), which achieved an F1-score of 91.94%. Consequently, GNNs have demonstrated a stronger ability to mine the underlying semantics of the KG than the ComplEx model, and thus using higher dimension embeddings within the GNN can lead to state-of-the-art performance

Estimation of brain network ictogenicity predicts outcome from epilepsy surgery

Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal brain lesions or the presence of epileptiform rhythms, do not necessarily predict the best resection strategy. We validate our framework by analysing electrocorticogram (ECoG) recordings from patients who have undergone epilepsy surgery. We find that when post-operative outcome is good, model predictions for optimal strategies align better with the actual surgery undertaken than when post-operative outcome is poor. Crucially, this allows the prediction of optimal surgical strategies and the provision of quantitative prognoses for patients undergoing epilepsy surgery.MG, MPR and JRT gratefully acknowledge the financial support of the EPSRC via grant EP/N014391/1. They further acknowledge funding from Epilepsy Research UK via grant number A1007 and the Medical Research Council via grant MR/K013998/1. The contribution of MG and JRT was generously supported by a Wellcome Trust Institutional Strategic Support Award (WT105618MA). MPR is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust. CR and AE were supported by the Swiss National Science Foundation (grant SPUM 140332). KS is grateful for support from the Swiss National Science Foundation (grants 122010 and 155950)

Ordinal patterns in epileptic brains: Analysis of intracranial EEG and simultaneous EEG-fMRI

Epileptic seizures are associated with high behavioral stereotypy of the patients. In the EEG of epilepsy patients characteristic signal patterns can be found during and between seizures. Here we use ordinal patterns to analyze EEGs of epilepsy patients and quantify the degree of signal determinism. Besides relative signal redundancy and the fraction of forbidden patterns we introduce the fraction of under-represented patterns as a new measure. Using the logistic map, parameter scans are performed to explore the sensitivity of the measures to signal determinism. Thereafter, application is made to two types of EEGs recorded in two epilepsy patients. Intracranial EEG shows pronounced determinism peaks during seizures. Finally, we demonstrate that ordinal patterns may be useful for improving analysis of non-invasive simultaneous EEG-fMR

Assessing the impact of intervention strategies against Taenia solium cysticercosis using the EPICYST transmission model

Background The pork tapeworm, Taenia solium, and associated human infections, taeniasis, cysticercosis and neurocysticercosis, are serious public health problems, especially in developing countries. The World Health Organization (WHO) has set goals for having a validated strategy for control and elimination of T. solium taeniasis/cysticercosis by 2015 and interventions scaled-up in selected countries by 2020. Timely achievement of these internationally-endorsed targets requires that the relative benefits and effectiveness of potential interventions be explored rigorously within a quantitative framework. Methods A deterministic, compartmental transmission model (EPICYST) was developed to capture the dynamics of the taeniasis/cysticercosis disease system in the human and pig hosts. Cysticercosis prevalence in humans, an outcome of high epidemiological and clinical importance, was explicitly modelled. A next generation matrix approach was used to derive an expression for the basic reproduction number, R 0. A full sensitivity analysis was performed using a methodology based on Latin-hypercube sampling partial rank correlation coefficient index. Results EPICYST outputs indicate that chemotherapeutic intervention targeted at humans or pigs would be highly effective at reducing taeniasis and cysticercosis prevalence when applied singly, with annual chemotherapy of humans and pigs resulting, respectively, in 94 and 74% of human cysticercosis cases averted. Improved sanitation, meat inspection and animal husbandry are less effective but are still able to reduce prevalence singly or in combination. The value of R 0 for taeniasis was estimated at 1.4 (95% Credible Interval: 0.5–3.6). Conclusions Human- and pig-targeted drug-focussed interventions appear to be the most efficacious approach from the options currently available. The model presented is a forward step towards developing an informed control and elimination strategy for cysticercosis. Together with its validation against field data, EPICYST will be a valuable tool to help reach the WHO goals and to conduct economic evaluations of interventions in varying epidemiological settings

Primary care in Malta : the patients’s expectations in 2009

Given the strong literature base to support the positioning of Primary Care at the core of a sustainable National Health Service, this study examines what the Maltese general public prefer, and expect, from their family doctor, and explores their preferred systems of care changes.peer-reviewe

Computer models to inform epilepsy surgery strategies: prediction of postoperative outcome

This is the final version of the article. Available from OUP via the DOI in this record.M.G., M.P.R. and J.R.T. gratefully acknowledge the financial support of the EPSRC via grant EP/N014391/1. They further acknowledge funding from Epilepsy Research UK via grant number A1007 and the Medical Research Council via grant MR/K013998/1. The contribution of M.G. and J.R.T. was generously supported by a Wellcome Trust Institutional Strategic Support Award (WT105618MA). M.P.R. is supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust. C.R. and A.E. were supported by the Swiss National Science Foundation (grant SPUM 140332). K.S. is grateful for support from the Swiss National Science Foundation (grants 122010 and 155950)

Elevated ictal brain network ictogenicity enables prediction of optimal seizure control

This is the final version of the article. Available from Frontiers Media via the DOI in this record.Recent studies have shown that mathematical models can be used to analyze brain networks by quantifying how likely they are to generate seizures. In particular, we have introduced the quantity termed brain network ictogenicity (BNI), which was demonstrated to have the capability of differentiating between functional connectivity (FC) of healthy individuals and those with epilepsy. Furthermore, BNI has also been used to quantify and predict the outcome of epilepsy surgery based on FC extracted from pre-operative ictal intracranial electroencephalography (iEEG). This modeling framework is based on the assumption that the inferred FC provides an appropriate representation of an ictogenic network, i.e., a brain network responsible for the generation of seizures. However, FC networks have been shown to change their topology depending on the state of the brain. For example, topologies during seizure are different to those pre- and post-seizure. We therefore sought to understand how these changes affect BNI. We studied peri-ictal iEEG recordings from a cohort of 16 epilepsy patients who underwent surgery and found that, on average, ictal FC yield higher BNI relative to pre- and post-ictal FC. However, elevated ictal BNI was not observed in every individual, rather it was typically observed in those who had good post-operative seizure control. We therefore hypothesize that elevated ictal BNI is indicative of an ictogenic network being appropriately represented in the FC. We evidence this by demonstrating superior model predictions for post-operative seizure control in patients with elevated ictal BNI.ML, MG, MR, and JT gratefully acknowledge funding from the Medical Research Council via grant MR/K013998/1. MG, MR, and JT further acknowledge the financial support of the EPSRC via grant EP/N014391/1. The contribution of MG and JT was further generously supported by a Wellcome Trust Institutional Strategic Support Award (WT105618MA). MR and EA are supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust. KS gratefully acknowledges support by the Swiss National Science Foundation (SNF 32003B_155950)