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Public procurement represents a large portion of government expenditure, more so in developing economies. Inefficiencies in public expenditures thus place a heavy burden on society. The Water and Sanitation (W&S) sector is especially vulnerable to public procurement inefficiencies due to the capital-intensive and complex nature of large-scale projects such as sewage, pipelines, and general maintenance. Recent studies have found that quality of corporate governance and transparency of water utilities as well as regulatory and supervisory agencies are key drivers of the sectors performance. To support better policies in the W&S sector, this report conducts a sectoral measurement of public procurement integrity using government administrative data and identifies effective interventions for improving the performance of utilities. The following questions are explored: Which types of integrity risk carry the highest economic costs? What are effective policy solutions? Which address the most impactful risks effectively? What are the price savings and project-delay-reducing impacts of such solutions? To this effect, the study analyzes data for six countries in the Latin American & Caribbean region. Several regression models were run to assess which indicators of integrity are good predictors of improved outcomes in terms of price (unit or relative) and quality (delays) of public purchases in the sector.

Aims The left atrium (LA) has a pivotal role in cardiac performance and LA deformation is a well-known prognostic predictor in several clinical conditions including heart failure with reduced ejection fraction. The aim of this study is to investigate the effect of cardiac resynchronization therapy (CRT) on both LA morphology and function and to assess the impact of LA reservoir strain (LARS) on left ventricular (LV) systolic and diastolic remodelling after CRT. Methods and results Two hundred and twenty-one CRT-candidates were prospectively included in the study in four tertiary centres and underwent echocardiography before CRT-implantation and at 6-month follow-up (FU). CRT-response was defined by a 15% reduction in LV end-systolic volume. LV systolic and diastolic remodelling were defined as the percent reduction in LV end-systolic and end-diastolic volume at FU. Indexed LA volume (LAVI) and LV-global longitudinal (GLS) strain were the main parameters correlated with LARS, with LV-GLS being the strongest determinant of LARS (r = −0.59, P < 0.0001). CRT induced a significant improvement in LAVI and LARS in responders (both P < 0.0001). LARS was an independent predictor of both LV systolic and diastolic remodelling at follow-up (r = −0.14, P = 0.049 and r = −0.17, P = 0.002, respectively). Conclusion CRT induces a significant improvement in LAVI and LARS in responders. In CRT candidates, the evaluation of LARS before CRT delivery is an independent predictor of LV systolic and diastolic remodelling at FU.

International audience; In preterm infants, recurrent episodes of apnea, bradycardia and severe intermittent hypoxia are mainly related to cardiorespiratory immaturity. These episodes are associated with major risks during the first weeks of life. Cardiorespiratory data consisting of a continuous 12 hours recording of transthoracic impedance and ECG signals were acquired in 18 preterm neonates. 106 isolated apnea events (>10 sec) were manually annotated from the database, of which 19 apneas with bradycardia. A system-level physiological model of cardio-respiratory interactions in the newborn is proposed and used to reproduce simulations of mixed apneas with and without bradycardia, by modifying the functional residual capacity. A first qualitative comparison between the simulations and the clinical data shows a close match between the experimental and simulated heart rate series during apnea with bradycardia (RMSE 4.96 bpm) and without (RMSE 2.02 bpm). © 2022 Creative Commons.

International audience; Nerve cuff electrodes are commonly used for neural stimulation and recording applications. Usually, these electrodes are composed of a limited set of metal rings, disposed around the nerve. Although widely used, this technology may be insufficient to record and stimulate in a more selective manner. Higher resolution electrodes, usually composed of a matrix of independent contact points, have been proposed in this sense. These electrodes allow for the exploration of a wide variety of bipolar or multipolar setups, for selective recording and stimulation. In this study, we propose a method to optimally select such multipolar setups and to quantitatively evaluate the performance of a multi-contact neural organic electrode (OE) in recording burst discharges from the rat's phrenic nerve. A 16-channel OE was wrapped around the phrenic nerve (studied electrode) and a suction electrode was applied to the cut-end of the same nerve (gold standard electrode). Analysis of all possible combinations of bipoles and tripoles from the OE were carried out to assess the improvement in the recording performance, measured as the signal-to-noise ratio, compared to the gold standard. The results showed that the bipolar and tripolar configuration significantly increased the overall recording performance. Such configurations are therefore essential to improve nerve burst detection.

The objective of this study was to establish the relationship between the perception of family coping strategies and the perception of family and child well-being in families in vulnerable conditions. The research is quantitative with a cross-sectional analytical design. 113 families were evaluated through questionnaires on family coping and well-being; the children also completed a child welfare inventory. Results showed that children report the highest moderate average score in family well-being, followed by fathers and finally mothers. For family coping, mothers demonstrated higher average coping levels, followed by fathers and children. Bivariate correlations indicated significant relationships between child well-being (IBI), family coping coping (Family Coping Index -FAMCI), and perceived general well-being. The discussion focuses on the mother as a promoter of well-being within the family, the stressors that families suffer and the relationship with experiences of displacement in the past that influence the selected coping strategies.

International audience; We hypothesized that a multiparametric evaluation, based on the combination of electrocardiographic and echocardiographic parameters, could enhance the appraisal of the likelihood of reverse remodeling and prognosis of favorable clinical evolution to improve the response of cardiac resynchronization therapy (CRT). Three hundred and twenty-three heart failure patients were retrospectively included in this multicenter study. 221 patients (68%) were responders, defined by a decrease in left ventricle end-systolic volume ≥15% at the 6-month follow-up. In addition, strain data coming from echocardiography were analyzed with custom-made signal processing methods. Integrals of regional longitudinal strain signals from the beginning of the cardiac cycle to strain peak and to the instant of aortic valve closure were analyzed. QRS duration, septal flash and different other features manually extracted were also included in the analysis. The random forest (RF) method was applied to analyze the relative feature importance, to select the most significant features and to build an ensemble classifier with the objective of predicting response to CRT. The set of most significant features was composed of Septal Flash, E, E/A, E/EA, QRS, left ventricular end-diastolic volume and eight features extracted from strain curves. A Monte Carlo cross-validation method with 100 runs was applied, using, in each run, different random sets of 80% of patients for training and 20% for testing. Results show a mean area under the curve (AUC) of 0.809 with a standard deviation of 0.05. A multiparametric approach using a combination of echo-based parameters of left ventricular dyssynchrony and QRS duration helped to improve the prediction of the response to cardiac resynchronization therapy.

Funding Acknowledgements Type of funding sources: None. Background Speckle tracking based myocardial work calculation is an attractive method to assess left ventricular (LV) myocardial function. In case of aortic stenosis (AS), assessment of work indices is challenging because it requires an accurate evaluation of LV-pressure curves. Therefore, we sought to evaluate the performances of two distinct methods for the estimation of myocardial work indices and to provide a quantitative comparison with invasively measured data. Methods Model-based and template-based methods were defined and applied for the evaluation of LV pressures on 67 AS patients. Global Constructive (GCW), Wasted (GWW), Positive (GPW), Negative (GNW) myocardial work and Global Work Efficiency (GWE) and Index (GWI) parameters were calculated using the available software computing the indices using brachial blood pressure and trans-aortic mean pressure gradient for estimating the LV pressures versus using a model-based and homemade software. A complete comparison was performed with invasive measurements. Results Patients were characterized by mean pressure gradient of 49.8 ± 14.8 mmHg, LV ejection fraction of 59 ± 8%, the global longitudinal strain was -15.0 ± 4.04%, GCW was 2107 ± 800mmHg.% (model-based method) and 2483 ± 1068mmHg.% (template-based method). The root mean square error (RMSE) and correlation were calculated for each patient and for each pressure estimation methods. The mean RMSE are 33.9mmHg and 40.4mmHg and the mean correlation coefficients are 0.81 and 0.72 for the model-based and template-based methods respectively. Correlation coefficient and Bland-Altman analysis were performed for the six work indices. The two methods present correlation coefficient r2 > 0.75 for almost all the indices. Conclusion The two non-invasive methods of LV pressure estimation and the work indices computation correlate with invasive measurements and computations for AS patients. Although the model-based approach requires less information and is associated with slightly better performances, the implementation of template-based method is easier and seems more appropriate in a clinical practice. Abstract Figure. SUMMARY

Objectives Sepsis is a life-threatening condition which is responsible for a high proportion of intra-hospital deaths and related healthcare costs each year. Early detection and treatment of sepsis episodes is critical, since an early treatment may highly improve prognosis. This study proposed an original method to increase the interpretability of a set of machine learning models for the early detection of sepsis onset. Material and methods Open data from the electronic medical records of 40,336 patients monitored in intensive care units (ICU), provided by the PhysioNet/Computing in Cardiology Challenge 2019 is used in this paper. We proposed a method including data preprocessing, feature engineering, model construction and tuning, as well as an original interpretability analysis method for the final stage. Results A total of 24 models were developed and analyzed. The best model, based on 142 features achieved a 0.4274 utility score. The best compact model integrates only 20 selected features, and provided a utility score of 0.3862. Meanwhile, the proposed sensitivity analysis method allows for the identification of the most relevant markers to early detect the onset of sepsis, as well as their interdependence and relative importance on the final decision. Conclusion A set of optimized machine-learning models were proposed for predicting sepsis early in a real-time way with high performance, and interpretable information including the most significant biomarkers were analyzed through novel interpretability method.

To compare the fracture resistance of five different groups of chairside CAD/CAM molar crowns fabricated from various lithium disilicate ceramic materials (LDC): one conventional precrystallized CAD/CAM LDC, two novel precrystallized LDCs, and one fully crystallized LDC tested both with and without optional sintering.A total of 60 chairside CAD/CAM lithium disilicate molar crowns (n = 12 per group) with 1.5-mm occlusal thickness and a 1.0-mm chamfer finish were designed and fabricated with a chairside CAD/CAM system (CEREC, Dentsply Sirona). The restorations were divided into five groups: (1) IPS e.max CAD; (2) Amber Mill; (3) Straumann n!ce; (4) Straumann n!ce with optional sintering; and (5) Supreme CAD. Restorations were cemented using conventional resin luting cement and primer system to 3D-printed resin dies. Bonded restorations were loaded for 100,000 cycles with 275-N force, and the load at break (LB) and peak load (PL) until fracture were measured. SEM images of fracture surfaces on the printed dies were obtained.Fracture resistance was significantly different depending on the material. Supreme CAD showed the highest fracture resistance (LB: 1,557.2 N; PL: 1,785.8 N), followed by Amber Mill (LB: 1,393.0 N; PL: 1,604.2 N) and IPS e.max CAD (LB: 1,315.7 N; PL: 1,461.9 N). Straumann n!ce without (LB: 862.4 N; PL: 942.9 N) and with the optional sintering (LB: 490.4 N; PL: 541.0 N) showed significantly lower fracture resistance than the others.The fracture resistance of chairside CAD/CAM lithium disilicate molar crowns varied depending on the material, and the novel materials did not perform as well as the conventional equivalents. Fully crystallized lithium disilicate ceramic block materials showed lower fracture resistance than precrystallized counterparts and should be used with caution in the clinic, especially with optional sintering.

International audience; This paper proposes an integrated model of cardio-respiratory interactions in preterm newborns, focused on the study of the patent ductus arteriosus (PDA). A formal model parameter sensitivity analysis on blood flow through the PDA is performed. Results show that the proposed model is capable of simulating hemodynamics in right-to-left and left-to-right shunts. For both configurations, the most significant parameters are associated with mechanical ventricular properties and circulatory parameters related to left ventricle loading conditions. These results highlight important physiological mechanisms involved in PDA and provide key information towards the definition of patient-specific parameters. © 2021 IEEE.

International audience; Identification of asymptomatic patients at higher risk for suffering cardiac events remains controversial and challenging in Brugada syndrome (BS). In this work, we proposed an ECG-based classifier to predict BS-related symptoms, by merging the most predictive electrophysiological features derived from the ventricular depolarization and repolarization periods, along with autonomic-related markers. The initial feature space included local and dynamic ECG markers, assessed during a physical exercise test performed in 110 BS patients (25 symptomatic). Morphological, temporal and spatial properties quantifying the ECG dynamic response to exercise and recovery were considered. Our model was obtained by proposing a two-stage feature selection process that combined a resampled-based regularization approach with a wrapper model assessment for balancing, simplicity and performance. For the classification step, an ensemble was constructed by several logistic regression base classifiers, whose outputs were fused using a performance-based weighted average. The most relevant predictors corresponded to the repolarization interval, followed by two autonomic markers and two other makers of depolarization dynamics. Our classifier allowed for the identification of novel symptom-related markers from autonomic and dynamic ECG responses during exercise testing, suggesting the need for multifactorial risk stratification approaches in order to predict future cardiac events in asymptomatic BS patients. Graphical abstract Pipeline for feature selection and predictive modeling of symptoms in Brugada syndrome.

International audience; OBJECTIVE: The physiological mechanisms involved in cardio-respiratory responses to sleep apnea events are not yet fully elucidated. A model-based approach is proposed to analyse the acute desaturation response to obstructive apneas. METHODS: An integrated model of cardio-respiratory interactions was proposed and parameters were identified, using an evolutionary algorithm, on a database composed of 107 obstructive apneas acquired from 10 patients (HYPNOS clinical study). Unsupervised clustering was applied to the identified parameters in order to characterize the phenotype of each response to obstructive apneas. RESULTS: A close match was observed between simulated oxygen saturation (SaO2) and experimental SaO2 in all identifications (median RMSE = 1.3892%). Two clusters of parameters, associated with different dynamics related to sleep apnea and periodic breathing were obtained. CONCLUSION AND SIGNIFICANCE: The proposed patient and event-specific model-based analysis provides understanding on specific desaturation patterns, consequent to apnea events, with potential applications for personalized diagnosis and treatment.

International audience; The objective of this study is to propose a model-based method, adapted to patients with severe aortic stenosis (AS), in order to reproduce left ventricle (LV) pressure and volume from patient specific data. A formal sensitivity analysis is proposed, focused on left ventricle volume and pressure. The most influent parameters of this analysis are then selected to be identified in a parameter identification strategy and provide a patient specific pressure curve. This was implemented on 3 AS patients and a close match was observed between experimental and simulated pressure and volume curves. The global root mean square error (RMSE) for pressure and volume curves are respectively 21.8 (pm 1.8) mmHg and 14.8 (pm 9.4)ml,. The model-based approach proposed shows promising results to generate accurate LV pressure and volume in AS case. © 2021 Creative Commons.

International audience; An original integrated model of cardio-respiratory interactions is presented in this paper with the objective of studying the acute physiological responses evoked by obstructive sleep apnea events in adults. A comprehensive sensitivity analysis of the model is proposed during the simulation of a 20 s obstructive apnea episode using the Morris' screening method and local sensitivity analysis. The more relevant parameters are related to the following mechanisms of the physiology: (i) the fraction of oxygen in inspired air, (ii) metabolic rates (oxygen consumption rate, CO2 production rate); (iii) chemoreflex (gains and time constants) (iv) respiratory mechanics (lung compliance and unstressed volume of air in the alveoli). These results highlight significant physiological variables that may be particularly useful for the development of novel diagnostic and therapeutic strategies, integrating a virtual patient approach.

This paper proposes the integration and analysis of a closed-loop model of the baroreflex and cardiovascular systems, focused on a time-varying estimation of the autonomic modulation of heart rate in Brugada syndrome (BS), during exercise and subsequent recovery. Patient-specific models of 44 BS patients at different levels of risk (symptomatic and asymptomatic) were identified through a recursive evolutionary algorithm. After parameter identification, a close match between experimental and simulated signals (mean error = 0.81%) was observed. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge, enabling to observe the expected autonomic changes induced by exercise testing. In particular, symptomatic patients presented a significantly higher parasympathetic activity during exercise, and an autonomic imbalance was observed in these patients at peak effort and during post-exercise recovery. A higher vagal modulation during exercise, as well as an increasing parasympathetic activity at peak effort and a decreasing vagal contribution during post-exercise recovery could be related with symptoms and, thus, with a worse prognosis in BS. This work proposes the first evaluation of the sympathetic and parasympathetic responses to exercise testing in patients suffering from BS, through the recursive identification of computational models; highlighting important trends of clinical relevance that provide new insights into the underlying autonomic mechanisms regulating the cardiovascular system in BS. The joint analysis of the extracted autonomic parameters and classic electrophysiological markers could improve BS risk stratification. © 2018 Elsevier B.V.

International audience; In prostate cancer radiotherapy, biochemical recurrence has been traditionally predicted using radiomics approaches with however limited performance. The purpose of this work was to use a mechanistic in silico model of tumor growth and response to irradiation to obtain better predictions. A cohort of 76 patients with localized prostate adenocarcinoma having undergone external beam radiotherapy was used. Analogous digital tissues were built from pre-treatment MRI. The prescribed irradiation protocols were simulated using the mechanistic model. Logistic regression was then performed to predict recurrence i) directly from MRI features following a conventional radiomics approach, ii) from intermediate parameters and iii) from the number of tumor cells at t =8 weeks output given by the mechanistic model. Significant improvement in prediction (p-value leq 0.0001) was achieved using the simulation-based marker (AUC =0.85) compared to predictions based on the MRI features without and with oversampling (AUC =0.77 and 0.80, respectively). © 2021 IEEE.

RESUMEN Gradualmente la humanidad tiende a los cambios debido a las circunstancias que se viven. Por ello, la disponibilidad y la creciente demanda de energía es una fuente principal para el desarrollo, pero sin poner en peligro a futuras generaciones. De ahí la importancia del término de sustentabilidad energética. En México como en el mundo se han perfilado gradualmente al concepto de innovación en la industria eléctrica para el desarrollo de nuevos materiales. En el Centro de Investigaciones en Ingeniería y Ciencias Aplicadas (CIICAp), y el Instituto Nacional de Electricidad y Energías Limpias (INEEL), se propuso contribuir en el desarrollo de polímeros electroactivos orgánicos con aplicación a supercapacitores (SC´s) para el almacenamiento de energía. En el presente trabajo se investigaron los componentes principales del SC como electrodos, electrolito y material dieléctrico. En el electrodo se usó el polímero conductor poli(3-hexiltiofeno) (P3HT) sin dopar y dopado con FeCl3, el cual fue sintetizado por el método de metátesis de Grignard (GRIM). Como material dieléctrico se empleó celulosa, nanocristales de celulosa (CNC´s) fueron extraídos del papel mediante la síntesis del método de hidrólisis de ácido sulfúrico (H2SO4), para lograr su estabilidad electrostática y así, aumentar su permeabilidad relativa. En relación al P3HT se analizó el peso molecular y la polidispersidad por la técnica de cromatografía de permeación en gel (GPC), la regioregularidad por resonancia magnética nuclear de protón (1H NMR), estabilidad térmica y temperatura de descomposición por análisis termogravimétrico (TGA), estructura química por espectroscopía de infrarrojo (FTIR), absorción óptica y gap de energía por espectroscopía ultravioleta‑visible (UV-Vis), morfología por microscopía de fuerza atómica (AFM) y microscopio electrónico de barrido (SEM), y finalmente por voltametría cíclica (VC) se determinó la carga almacenada, la estabilidad y los potenciales de oxidación y reducción del polímero, así como el análisis de los SC´s mediante VC, impedancia y Nyquist. Con relación al P3HT-RR se ha reportado que la estabilidad y el aumento de la regioregularidad (RR), favorece a la capacidad específica de los ciclos repetidos de cargas y descargas. ABSTRACT Gradually humanity tends to change due to the circumstances that are being experienced. Therefore, the availability and growing demand of energy is a main source for development, but without endangering future generations. Hence the importance of the term energy sustainability. In Mexico, as in the world, they have gradually outlined the concept in innovation in the electrical industry for the development of new materials. Together with the Center for Research in Engineering and Applied Sciences (CIICAp), and the National Institute of Electricity and Clean Energy (INEEL), it was proposed to contribute to the development of electroactive organic polymers with application to supercapacitors (SC's) for energy storage. In the present work, the main components of SC were investigated, such as electrodes, electrolyte, and dielectric material. The conductive polymer poly (3-hexylthiophene) (P3HT) undoped and doped with FeCl3 was used in the electrode, which was synthesized by the Grignard metathesis method (GRIM). Cellulose was used as dielectric material, cellulose nanocrystals (CNC's) were extracted from the paper by means of the synthesis of the sulfuric acid hydrolysis method (H2SO4), to achieve their electrostatic stability and thus increase their relative permeability. In relation to P3HT, molecular weight and polydispersity were analyzed by gel permeation chromatography (GPC) technique, regioregularity by proton nuclear magnetic resonance (1HNMR), thermal stability and decomposition temperature by thermogravimetric analysis (TGA), chemical structure by infrared spectroscopy (FTIR), optical absorption and energy gap by ultraviolet ‑ visible spectroscopy (UV-Vis), morphology by atomic force microscopy (AFM) and scanning electron microscope (SEM), and finally by voltammetry cyclic (VC) the stored charge, the stability and the oxidation and reduction potentials of the polymer were determined, as well as the analysis of the SC's by means of VC, impedance and Nyquist. Regarding the P3HT-RR, it has been reported that the stability and the increase of the regioregularity (RR), favors the specific capacity of the repeated cycles of charges and discharges.

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Aims Myocardial work (manually controlled software) and integral-derived longitudinal strain (automatic quantification of strain curves) are two promising tools to quantify dyssynchrony and potentially select the patients that are most likely to have a reverse remodelling due to cardiac resynchronization therapy (CRT). We sought to test and compare the value of these two methods in the prediction of CRT-response. Materials and results Two hundred and forty-three patients undergoing CRT-implantation from three European referral centres were considered. The characteristics from the six-segment of the four-chamber view were computed to obtain regional myocardial work and the automatically generated integrals of strain. The characteristics were studied in mono-parametric and multiparametric evaluations to predict CRT-induced 6-month reverse remodelling. For each characteristic, the performance to estimate the CRT response was determined with the receiver operating characteristic (ROC) curve and the difference between the performances was statistically evaluated. The best area under the curve (AUC) when only one characteristic used was obtained for a myocardial work (AUC = 0.73) and the ROC curve was significantly better than the others. The best AUC for the integrals was 0.63, and the ROC curve was not significantly greater than the others. However, with the best combination of works and integrals, the ROC curves were not significantly different and the AUCs were 0.77 and 0.72. Conclusion Myocardial work used in a mono-parametric estimation of the CRT-response has better performance compared to other methods. However, in a multiparametric application such as what could be done in a machine-learning approach, the two methods provide similar results.

Objective: Purposes of this work were i) to develop an in silico model of tumor response to radiotherapy, ii) to perform an exhaustive sensitivity analysis in order to iii) propose a simplified version and iv) to predict biochemical recurrence with both the comprehensive and the reduced model. Methods: A multiscale computational model of tumor response to radiotherapy was developed. It integrated the following radiobiological mechanisms: oxygenation, including hypoxic death; division of tumor cells; VEGF diffusion driving angiogenesis; division of healthy cells and oxygen-dependent response to irradiation, considering, cycle arrest and mitotic catastrophe. A thorough sensitivity analysis using the Morris screening method was performed on 21 prostate computational tissues. Tumor control probability (TCP) curves of the comprehensive model and 15 reduced versions were compared. Logistic regression was performed to predict biochemical recurrence after radiotherapy on 76 localized prostate cancer patients using an output of the comprehensive and the reduced models. Results: No significant difference was found between the TCP curves of the comprehensive and a simplified version which only considered oxygenation, division of tumor cells and their response to irradiation. Biochemical recurrence predictions using the comprehensive and the reduced models improved those made from pre-treatment imaging parameters (AUC = 0.81 $\pm$ 0.02 and 0.82 $\pm$ 0.02 vs. 0.75 $\pm$ 0.03, respectively). Conclusion: A reduced model of tumor response to radiotherapy able to predict biochemical recurrence in prostate cancer was obtained. Significance: This reduced model may be used in the future to optimize personalized fractionation schedules.

Funding Acknowledgements Type of funding sources: None. Background Despite having all a systolic heart failure and broad QRS, patients proposed for cardiac resynchronization therapy (CRT) are highly heterogeneous and it remains extremely complicated to predict the impact of the device on left ventricular (LV) function and outcomes. Objectives We sought to evaluate the relative impact of clinical, electrocardiographic, and echocardiographic data on the left ventricular (LV) remodeling and prognosis of CRT-candidates by the application of machine learning (ML) approaches. Methods 193 patients with systolic heart failure undergoing CRT according to current recommendations were prospectively included in this multicentre study. We used a combination of the Boruta algorithm and random forest methods to identify features predicting both CRT volumetric response and prognosis (Figure 1). The model performance was tested by the area under the receiver operating curve (AUC). We also applied the K-medoid method to identify clusters of phenotypically-similar patients. Results From 28 clinical, electrocardiographic, and echocardiographic-derived variables, 16 features were predictive of CRT-response; 11 features were predictive of prognosis. Among the predictors of CRT-response, 7 variables (44%) pertained to right ventricular (RV) size or function. Tricuspid annular plane systolic excursion was the main feature associated with prognosis. The selected features were associated with a very good prediction of both CRT response (AUC 0.81, 95% CI: 0.74-0.87) and outcomes (AUC 0.84, 95% CI: 0.75-0.93) (Figure 1, Supervised Machine Learning Panel). An unsupervised ML approach allowed the identifications of two phenogroups of patients who differed significantly in clinical and parameters, biventricular size and RV function. The two phenogroups had significant different prognosis (HR 4.70, 95% CI: 2.1-10.0, p Conclusions Machine learning can reliably identify clinical and echocardiographic features associated with CRT-response and prognosis. The evaluation of both RV-size and function parameters has pivotal importance for the risk stratification of CRT-candidates and should be systematically assessed in patients undergoing CRT. Abstract Figure 1

International audience; Background - The mechanisms of improvement of left ventricular (LV) function with cardiac resynchronization therapy (CRT) are not yet elucidated. The aim of this study was to characterize CRT responder profiles through clustering analysis, on the basis of clinical and echocardiographic preimplantation data, integrating automatic quantification of longitudinal strain signals. Methods - This was a multicenter observational study of 250 patients with chronic heart failure evaluated before CRT device implantation and followed up to 4 years. Clinical, electrocardiographic, and echocardiographic data were collected. Regional longitudinal strain signals were also analyzed with custom-made algorithms in addition to existing approaches, including myocardial work indices. Response was defined as a decrease of ≥15% in LV end-systolic volume. Death and hospitalization for heart failure at 4 years were considered adverse events. Seventy features were analyzed using a clustering approach (k-means clustering). Results - Five clusters were identified, with response rates between 50% in cluster 1 and 92.7% in cluster 5. These five clusters differed mainly by the characteristics of LV mechanics, evaluated using strain integrals. There was a significant difference in event-free survival at 4 years between cluster 1 and the other clusters. The quantitative analysis of strain curves, especially in the lateral wall, was more discriminative than apical rocking, septal flash, or myocardial work in most phenogroups. Conclusions - Five clusters are described, defining groups of below-average to excellent responders to CRT. These clusters demonstrate the complexity of LV mechanics and prediction of response to CRT. Automatic quantitative analysis of longitudinal strain curves appears to be a promising tool to improve the understanding of LV mechanics, patient characterization, and selection for CRT.

In this paper, a method for apnea bradycardia detection in preterm infants is presented based on coupled hidden semi Markov model (CHSMM). CHSMM is a generalization of hidden Markov models (HMM) used for modeling mutual interactions among different observations of a stochastic process through using finite number of hidden states with corresponding resting time. We introduce a new set of equations for CHSMM to be integrated in a detection algorithm. The detection algorithm was evaluated on a simulated data to detect a specific dynamic and on a clinical dataset of electrocardiogram signals collected from preterm infants for early detection of apnea bradycardia episodes. For simulated data, the proposed algorithm was able to detect the desired dynamic with sensitivity of 96.67% and specificity of 98.98%. Furthermore, the method detected the apnea bradycardia episodes with 94.87% sensitivity and 96.52% specificity with mean time delay of 0.73 s. The results show that the algorithm based on CHSMM is a robust tool for monitoring of preterm infants in detecting apnea bradycardia episodes. Graphical Abstract Apnea Bradycardia detection using Coupled hidden semi Markov Model from electrocardiography. In this model, a sequence of hidden states is assigned to each observation based on the effects of previous states of all observations.

In this chapter we study corruption risks in EU defense procurement. Defense procurement has long been thought to present significant potential for corruption and state capture. Using a large dataset of contracts covering nearly ten years and applying an objective corruption risk indicator, we find strong empirical support for this hypothesis. In nearly all countries our corruption risk indicator is higher for military contracts than for contracts in general. By mapping national markets as complex networks, we find that risks are significantly clustered, suggesting potential islands of state capture. The centralization of corruption risk varies from country to country: in some corruption risk is significantly higher in the periphery, while in others it is significantly higher in the center of the market. We argue that network maps of procurement markets are an effective tool to highlight hotspots of corruption risk, especially in the overall high risk context of defense contracting. We thank the participants of the workshop "Defence procurement in the EU and data" organised at the University of Nottingham, especially Aris Georgopoulos. Acknowledge support from Open Society Foundations under the grant "State capture and the defence procurement in the EU" (grant number: OR2017-34852).

Purpose: Depending on the exposure scenario, different biological and/or physical assays will be required to recover the exposure situation and to obtain reliable dose estimates to aid medical decision making. Inter-laboratory comparisons (ILCs) are a central tool to validate and improve the performance of methods and laboratories. In most cases such ILCs are performed under laboratory conditions where the influence of parameters contributing to uncertainties can be minimized. In a reallife scenario, the situation is much more complicated, and it is therefore crucial to validate methods and laboratories’ abilities to carry out these methods under more realistic conditions. In 2019, EURADOS (The European Radiation Dosimetry Group) Working Group 10 (Retrospective Dosimetry) and RENEB (Running the European Network of Biological and retrospective Physical dosimetry) organized a field exercise in Lund, Sweden, to validate different methods for biological and physical retrospective dosimetry in parallel by simulating real- life exposure scenarios. Materials and methods: For the dicentric chromosome assay (DCA), 18 blood tubes were distributed across 8 thermos flasks filled with heated water and positioned at the hips and shoulders of anthropomorphic phantoms in different geometries. Two irradiations were performed with a 1.36 TBq 192Ir-source, each with two phantoms, to simulate close, distant, lateral or partially shielded exposures. For each of the blood tubes DCA dose estimates were provided by at least one laboratory and for tubes from four thermos flasks by 17 participating RENEB laboratories. In addition, blood from the different thermos flasks on each phantom was mixed to simulate heterogeneous exposures. Three radio-photoluminescence (RPL) glass dosimeters (GD) were placed at each tube to assess reference doses and the inter- and intra-tube variability. Results: The results from the DCA were homogeneous between participants and matched well with RPL GD reference doses (≥95% of estimates within ±0.5 Gy of the reference). For samples close to the source, exposed to doses >1 Gy, systematic underestimation could be corrected by accounting for exposure time. Heterogeneity within and between tubes was detected for RPL GD reference doses as well as for doses estimates from the DCA. The sample simulating a heterogeneous exposure with two different doses was detected by ~50% of the participants. Conclusions: The participants were able to successfully estimate the doses and to provide important information on the exposure scenarios under conditions closely resembling a real-life situation. The reliability of the results emphasizes the value of the DCA for retrospective dosimetry under field conditions.