A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions

A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

Improving algorithm speed in PNL mixture separation and Wiener system inversion

This paper proposes a very simple method for increasing the algorithm speed for separating sources from PNL mixtures or invertingWiener systems. The method is based on a pertinent initialization of the inverse system, whose computational cost is very low. The nonlinear part is roughly approximated by pushing the observations to be Gaussian; this method provides a surprisingly good approximation even when the basic assumption is not fully satisfied. The linear part is initialized so that outputs are decorrelated. Experiments shows the impressive speed improvement.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

New Algorithm for Managing Childhood Illness Using Mobile Technology (ALMANACH): A Controlled Non-Inferiority Study on Clinical Outcome and Antibiotic Use in Tanzania.

INTRODUCTION: The decline of malaria and scale-up of rapid diagnostic tests calls for a revision of IMCI. A new algorithm (ALMANACH) running on mobile technology was developed based on the latest evidence. The objective was to ensure that ALMANACH was safe, while keeping a low rate of antibiotic prescription. METHODS: Consecutive children aged 2-59 months with acute illness were managed using ALMANACH (2 intervention facilities), or standard practice (2 control facilities) in Tanzania. Primary outcomes were proportion of children cured at day 7 and who received antibiotics on day 0. RESULTS: 130/842 (15∙4%) in ALMANACH and 241/623 (38∙7%) in control arm were diagnosed with an infection in need for antibiotic, while 3∙8% and 9∙6% had malaria. 815/838 (97∙3%;96∙1-98.4%) were cured at D7 using ALMANACH versus 573/623 (92∙0%;89∙8-94∙1%) using standard practice (p<0∙001). Of 23 children not cured at D7 using ALMANACH, 44% had skin problems, 30% pneumonia, 26% upper respiratory infection and 13% likely viral infection at D0. Secondary hospitalization occurred for one child using ALMANACH and one who eventually died using standard practice. At D0, antibiotics were prescribed to 15∙4% (12∙9-17∙9%) using ALMANACH versus 84∙3% (81∙4-87∙1%) using standard practice (p<0∙001). 2∙3% (1∙3-3.3) versus 3∙2% (1∙8-4∙6%) received an antibiotic secondarily. CONCLUSION: Management of children using ALMANACH improve clinical outcome and reduce antibiotic prescription by 80%. This was achieved through more accurate diagnoses and hence better identification of children in need of antibiotic treatment or not. The building on mobile technology allows easy access and rapid update of the decision chart. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR201011000262218.

Managing the Sick Child in the Era of Declining Malaria Transmission: Development of ALMANACH, an Electronic Algorithm for Appropriate Use of Antimicrobials.

OBJECTIVE: To review the available knowledge on epidemiology and diagnoses of acute infections in children aged 2 to 59 months in primary care setting and develop an electronic algorithm for the Integrated Management of Childhood Illness to reach optimal clinical outcome and rational use of medicines. METHODS: A structured literature review in Medline, Embase and the Cochrane Database of Systematic Review (CDRS) looked for available estimations of diseases prevalence in outpatients aged 2-59 months, and for available evidence on i) accuracy of clinical predictors, and ii) performance of point-of-care tests for targeted diseases. A new algorithm for the management of childhood illness (ALMANACH) was designed based on evidence retrieved and results of a study on etiologies of fever in Tanzanian children outpatients. FINDINGS: The major changes in ALMANACH compared to IMCI (2008 version) are the following: i) assessment of 10 danger signs, ii) classification of non-severe children into febrile and non-febrile illness, the latter receiving no antibiotics, iii) classification of pneumonia based on a respiratory rate threshold of 50 assessed twice for febrile children 12-59 months; iv) malaria rapid diagnostic test performed for all febrile children. In the absence of identified source of fever at the end of the assessment, v) urine dipstick performed for febrile children <2 years to consider urinary tract infection, vi) classification of 'possible typhoid' for febrile children >2 years with abdominal tenderness; and lastly vii) classification of 'likely viral infection' in case of negative results. CONCLUSION: This smartphone-run algorithm based on new evidence and two point-of-care tests should improve the quality of care of <5 year children and lead to more rational use of antimicrobials.

From Educational Segregation to Transformative Inclusion

Recent studies conducted in Europe using communicative methodology highlight that different ways of grouping students has a direct effect on their academic output. This article analyzes how said research methodology identifies and analyzes those student groupings that provide greater academic success and improve classroom coexistence at Spanish educational centers. Said methodology entails all of the research participants researchers, teachers, families, and students reflecting on the consequences of streaming, mixture, and inclusion for student academic achievement. Following this, our conclusions are compared with the policies and educational practices implemented in Spanish schools, which are not based on scientific knowledge and do not usually lead to academic success. Finally, recommendations are presented for future educational policies with the aim of providing an alternative for teachers and educational managers that would substantially improve student academic success.

Decreasing educational differences in mortality over 40 years: evidence from the Turin Longitudinal Study (Italy)

BACKGROUND: Recent studies suggest that inequalities in premature mortality have continued to rise over the last decade in most European countries, but not in southern European countries. METHODS: In this study, we assess long-term trends (1971-2011) in absolute and relative educational inequalities in all-cause and cause-specific mortality in the Turin Longitudinal Study (Turin, Italy), a record-linkage study including all individuals resident in Turin in the 1971, 1981, 1991 and 2001 censuses, and aged 30-99 years (more than 2 million people). We examined mortality for all causes, cardiovascular disease (CVD), all cancers and specific cancers (lung, breast), as well as smoking and alcohol-related mortality. RESULTS: Overall mortality substantially decreased in all educational groups over the study period, although cancer rates only slightly declined. Absolute inequalities decreased for both genders (SII=962/694 in men/women in 1972-1976 and SII=531/259 in 2007-2011, p<0.01). Among men, absolute inequalities for CVD and alcohol-related causes declined (p<0.05), while remaining stable for other causes of death. Among women, declines in absolute inequalities were observed for CVD, smoking and alcohol-related causes and lung cancer (p<0.05). Relative inequalities in all-cause mortality remained stable for men and decreased for women (RII=1.92/2.03 in men/women in 1972-1976 and RII=2.15/1.32 in 2007-2011). Among men, relative inequalities increased for smoking-related causes, while among women they decreased for all cancers, CVD, smoking-related causes and lung cancer (p<0.05). CONCLUSIONS: Absolute inequalities in mortality strongly declined over the study period in both genders. Relative educational inequalities in mortality were generally stable among men; while they tended to narrow among women. In general, this study supports the hypothesis that educational inequalities in mortality have decreased in southern European countries.

Development of phase retrieval algorithm and techniques for optical spectrum analysis

Coherent anti-Stokes Raman scattering is the powerful method of laser spectroscopy in which significant successes are achieved. However, the non-linear nature of CARS complicates the analysis of the received spectra. The objective of this Thesis is to develop a new phase retrieval algorithm for CARS. It utilizes the maximum entropy method and the new wavelet approach for spectroscopic background correction of a phase function. The method was developed to be easily automated and used on a large number of spectra of different substances.. The algorithm was successfully tested on experimental data.

The Dialogic Turn in Educational Psychology

The increasing presence of and claim for dialogue in today"s society has already had an impact on the theory and practice of learning. Whereas in the past individual and cognitive elements were seen as crucial to learning, since about two decades ago, scientific literature indicates that culture, interaction and dialogue are the key factors. In addition, the research project of highest scientific rank and with most resources dedicated to the study of school education in the Framework Program of the European Union: INCLUD-ED shows that the practices of successful schools around Europe are in line with the dialogic approach to learning. This article presents the dialogic turn in educational psychology, consisting of moving from symbolic conceptions of mind and internalist perspectives that focus on mental schemata of previous knowledge, to theories that see intersubjectivity and communication as the primary factors in learning. The paper deepens on the second approach.

Efficient total variation algorithm for fetal MRI reconstruction

Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

Educational resources offered by the European Board of Physical and Rehabilitation Medicine (EBPRM)

Background .- Physical and Rehabilitation Medicine (PRM) is a very demanding medical speciality. To ensure high standard of research and care in PRM all across Europe, it is crucial to attract gifted trainees and offer them high quality education. At undergraduate level, many medical schools in Europe omit to offer teaching on disabled persons and on basic PRM knowledge. Thus PRM is hardly known to medical students. For postgraduate trainees access to evidence-based knowledge as well as teaching of research methodology specific to PRM, rehabilitation methodology, disability management and team building also need to be strengthened to increase the visibility of PRM. Action .- To address these issues the EBPRM proposes presently a specific undergraduate curriculum in PRM including the issues of disability, participation and handicap as a basis for general medical practice and postgraduate rehabilitation training. For PRM trainees many educational documents are now available on the EBPRM website. A growing number of educational sessions for PRM trainees take place during international and national PRM Congresses which can be accessed at low cost. Educational papers published regularly in European rehabilitation journals and European PRM Schools are offered free or at very low cost to trainees.

Question Waves: A multicast query routing algorithm for social search

This paper describes Question Waves, an algorithm that can be applied to social search protocols, such as Asknext or Sixearch. In this model, the queries are propagated through the social network, with faster propagation through more trustable acquaintances. Question Waves uses local information to make decisions and obtain an answer ranking. With Question Waves, the answers that arrive first are the most likely to be relevant, and we computed the correlation of answer relevance with the order of arrival to demonstrate this result. We obtained correlations equivalent to the heuristics that use global knowledge, such as profile similarity among users or the expertise value of an agent. Because Question Waves is compatible with the social search protocol Asknext, it is possible to stop a search when enough relevant answers have been found; additionally, stopping the search early only introduces a minimal risk of not obtaining the best possible answer. Furthermore, Question Waves does not require a re-ranking algorithm because the results arrive sorted