Migration and the future of Europe’s demography and economy

This contribution was delivered on the occasion of the EUI State of the Union in Florence on 09 May 2013Together with Chatham House Rule this paralel session was coordinated and organised by EUI professors, with speakers, journalists, academics and EUI researchers leading discussionBy 2050 Europe’s population will have decreased by 11 per cent, while the world population will have increased by 35 per cent. Is demography a threat to Europe’s future weight in world affairs? Demographic aging and shrinking workforces put Europe’s welfare systems at risk. Should immigrants be seen as an additional burden or as an asset under these conditions? Should EU member states apply the principle of European preference or, to promote innovation and competitiveness, promote the selection of highly skilled immigrants from third countries? Would low- or mid-skilled immigration bring a suitable response to the massive outsourcing of labour to low-wage countries, and eventually foster employment in Europe?Transcripts of the recorded single speeches are available in publication ‘The State of the Union 2013 : collected perspectives’, 201

Probabilistic Detection of Short Events, with Application to Critical Care Monitoring

We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular, we consider the arterial-line blood pressure sensor, which is subject to frequent data artifacts that cause false alarms in the ICU and make the raw data almost useless for automated decision making. The problem is complicated by the fact that the sensor data are averaged over fixed intervals whereas the events causing data artifacts may occur at any time and often have durations significantly shorter than the data collection interval. We show that careful modeling of the sensor, combined with a general technique for detecting sub-interval events and estimating their duration, enables detection of artifacts and accurate estimation of the underlying blood pressure values. Our model¿s performance identifying artifacts is superior to two other classifiers¿ and about as good as a physician¿s

Probabilistic Modeling of Sensor Artifacts in Critical Care

We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular, we consider the arterial-line blood pressure sensor, which is subject to frequent data artifacts that cause false alarms in the ICU and make the raw data almost useless for automated decision making. The problem is complicated by the fact that the sensor data are acquired at fixed intervals whereas the events causing data artifacts may occur at any time and have durations that may be significantly shorter than the data collection inter- val. We show that careful modeling of the sensor, combined with a general technique for detecting sub-interval events and estimating their duration, enables effective detection of artifacts and accurate estimation of the underlying blood pressure values

Antibiotic prescribing in nursing homes in an area with low prevalence of antibiotic resistance: Compliance with national guidelines

Objective. To examine antibiotic prescribing in nursing homes and determine to what degree the prescribing was in accordance with the national guidelines for antibiotic prescribing. Design. Retrospective examination of patients’ records who were prescribed antibiotics in the period 1 March 2007 to 28 February 2008. Setting and patients. Patients residing in the nursing homes of Arendal, Norway. Main outcome measures. Choice of antibiotic in respect of the recommendations in the national guidelines for antibiotic prescribing. Results. A total of 714 antibiotic courses were prescribed to 327 patients yielding a prevalence of 6.6%. Compliant prescribing was 77% for urinary tract infections (UTI), 79% for respiratory tract infections (RTI), and 76% for skin and soft tissue infections (SSTI). Ciprofloxacin was responsible for 63% of non-compliant prescribing. On the respite wards there was a higher rate of total prescribing, non-compliant prescribing, and prescribing by physicians employed at the local hospital. Conclusion. Guidelines for antibiotic use must be implemented actively and efforts to improve antibiotic prescribing in nursing homes must be aimed at both nursing home and hospital physicians

Oblivious Dimension Reduction fork-Means:Beyond Subspaces and the Johnson-Lindenstrauss Lemma

We show that fornpoints ind-dimensional Euclidean space, a dataoblivious random projection of the columns ontoO(((logk+log logn)/ε^6)log(1/ε)) dimensions is sufficient to approximate the cost of all k-means clusterings up to a multiplicative (1±ε) factor. The previous-bestupper bounds on O(logn/ε^2) given by a direct application of the Johnson-Lindenstrauss Lemma, and O(k/ε^2)given by [Cohen etal.-STOC’15