Bayesian Semiparametric Multi-State Models

Multi-state models provide a unified framework for the description of the evolution of discrete phenomena in continuous time. One particular example are Markov processes which can be characterised by a set of time-constant transition intensities between the states. In this paper, we will extend such parametric approaches to semiparametric models with flexible transition intensities based on Bayesian versions of penalised splines. The transition intensities will be modelled as smooth functions of time and can further be related to parametric as well as nonparametric covariate effects. Covariates with time-varying effects and frailty terms can be included in addition. Inference will be conducted either fully Bayesian using Markov chain Monte Carlo simulation techniques or empirically Bayesian based on a mixed model representation. A counting process representation of semiparametric multi-state models provides the likelihood formula and also forms the basis for model validation via martingale residual processes. As an application, we will consider human sleep data with a discrete set of sleep states such as REM and Non-REM phases. In this case, simple parametric approaches are inappropriate since the dynamics underlying human sleep are strongly varying throughout the night and individual-specific variation has to be accounted for using covariate information and frailty terms

Naturally-occurring stable isotopes as direct measures of larval feeding efficiency, nutrient incorporation and turnover

environmental conditions on stable isotope incorporation will be of broad relevance not only in terms of larval nutrition but can also more broadly inform the design and interpretation of ecological studies

Evolutionary Population Synthesis for Binary Stellar Population at High Spectral Resolution: Integrated Spectral Energy Distributions and Absorption-feature Indices

Using EPS we present high resolution (0.3 \AA, HRes) ISEDs from 3000 to 7000 \AA and Lick/IDS absorption-line indices, for an extensive set of instantaneous burst binary stellar populations (BSPs) with binary interactions. The ages of the BSPs are in the range 1 - 15 Gyr and the metallicities are in the range 0.004 - 0.03. This HRes synthesis results can satisfy the needs of modern spectroscopic galaxy surveys, and are available on request. By comparing the synthetic continuum of BSPs at high and low resolution (LRes) we show that there is a good agreement for Z=0.02 and a tolerable disagreement for non-solar metallicity. The strength of the Balmer lines at HRes is greater than that at LRes for all metallicities. The comparison of Lick/IDS absorption-line indices at LRes and HRes, both of which are obtained by the fitting functions (FFs), shows that the discrepancies in all indices except for TiO_1 and TiO_2 are insignificant for BSPs with Z=0.004 and Z=0.02. The HRes Ca4227, Fe5015 and Mg_b indices are redder than the corresponding LRes one for BSPs with Z=0.01 and Z=0.03, this effect lowers the derived age and metallicity of the BSP. The high resolution Mg_1, Fe5709 and Fe5782 indices are bluer than those at LRes, it raises the age and metallicity. The discrepancy in these six indices is greater for BSPs with Z=0.03 in comparison to Z=0.01. At HRes we compare the Lick/IDS spectral absorption indices obtained by using the FFs with those measured directly from the synthetic spectra, and see that Ca4455, Fe4668, Mg_b and Na D indices obtained by the use of the FFs are redder for all metallicities, Fe5709 is redder at Z=0.03 and becomes to be bluer at Z=0.01 and 0.004, and other indices are bluer for all metallicities than the corresponding values measured directly from the synthetic spectra.Comment: 11 pages, 10 figures, to be published in MNRA

The CaT strength in Seyfert nuclei revisited: analyzing young stars and non-stellar light contributions to the spectra

In a former paper (Garcia-Rissmann et al. 2005; hereafter Paper I), we have presented spectra of 64 active, 9 normal and 5 Starburst galaxies in the region around the near-IR Calcium triplet absorption lines and the [SIII]9069 line. In the present paper we analyze the CaT strength (WCaT), and kinematical products derived in that study, namely stellar and ionized gas velocity dispersions. Our main results may be summarized as follows: (1) Seyfert 2s show no sign of dilution in WCaT with respect to the values spanned by normal galaxies, even when optical absorption lines such as the CaII K band at 3933 A are much weaker than in old, bulge-like stellar populations. (2) The location of Seyfert 2s in the WCaT-WCaK plane is consistent with evolutionary synthesis models. The implication is that the source responsible for the dilution of optical lines in these AGN is a young stellar population, rather than an AGN featureless continuum, confirming the conclusion of the pioneer study of Terlevich, Diaz & Terlevich. (3) In Seyfert 1s, both W[SIII] and WCaT tend to be diluted due to the presence of a non-stellar component, in agreement with the unification paradigm. (4) A comparison of stellar and gas velocity dispersions confirms the existence of a correlation between the typical velocities of stars and clouds of the Narrow Line Region. The strength and scatter around this correlation are similar to those previously obtained from the [OIII]5007 line width.Comment: 14 pages, 15 figures. Paper accepted for publication in MNRA

Volatile profile of matured Tronchón cheese affected by oxytetracycline in raw goat milk

[EN] The presence of antibiotics in milk destined for cheese production may affect the biological processes responsible for the formation of volatile compounds, leading to alterations in the characteristic cheese flavor expected by consumers. The aim of this study was to evaluate the effect of the presence of oxytetracycline in goat milk on the volatile profile of ripened cheeses. Traditional mature Tronchón cheeses were manufactured from raw goat milk spiked with different concentrations of oxytetracycline (50, 100, and 200 ug/kg). Cheese made from antibiotic-free goat milk was used as control. We analyzed the residual amounts of the antibiotic and the volatile profile of the experimental cheeses on a fortnightly basis during maturation using liquid chromatography tandem mass spectrometry and then solid-phase microextraction followed by gas chromatography-mass spectrometry. Our results suggested that oxytetracycline was widely transferred from milk to cheese: drug concentrations in the cheeses were 3.5 to 4.3 times higher than those in raw milk. Although the residual amounts of oxytetracycline significantly decreased during maturation (88.8 to 96.5%), variable amounts of residues remained in cheese matured for 60 d (<10 to 79 ug/kg). In general, the presence of oxytetracycline in goat milk did not affect the volatile profile of Tronchón cheeses; volatile profile was significantly modified by ripening time. Still, the presence of oxytetracycline residues in cheeses ripened for 60 d could be of great concern for public health.This work is part of the AGL-2013-45147-R funded by the Ministry of Science and Innovation (Madrid. Spain). The authors thank the Research and Development Support Program, "Ayudas para movilidad dentro del Programa para la Formación de Personal Investigador" (2.016) of Universitat Politècnica de València (Spain), allowing Paloma Quintanilla to perform a predoctoral stay at the Food Quality and Design Group, Wageningen University and Research (Wageningen, the Netherlands). The authors state that they have no conflicts of interest.Quintanilla-Vázquez, PG.; Hettinga, K.; Beltrán Martínez, MC.; Escriche Roberto, MI.; Molina Pons, MP. (2020). Volatile profile of matured Tronchón cheese affected by oxytetracycline in raw goat milk. Journal of Dairy Science. 103(7):6015-6021. https://doi.org/10.3168/jds.2019-16510S601560211037Attaie, R., Bsharat, M., Mora-Gutierrez, A., & Woldesenbet, S. (2015). Short communication: Determination of withdrawal time for oxytetracycline in different types of goats for milk consumption. Journal of Dairy Science, 98(7), 4370-4376. doi:10.3168/jds.2014-8616Beltrán, M. C., Althaus, R. L., Molina, A., Berruga, M. I., & Molina, M. P. (2015). Analytical strategy for the detection of antibiotic residues in sheep and goat’s milk. Spanish Journal of Agricultural Research, 13(1), e0501. doi:10.5424/sjar/2015131-6522Cabizza, R., Rubattu, N., Salis, S., Pes, M., Comunian, R., Paba, A., … Urgeghe, P. P. (2017). Transfer of oxytetracycline from ovine spiked milk to whey and cheese. International Dairy Journal, 70, 12-17. doi:10.1016/j.idairyj.2016.12.002Cabizza, R., Rubattu, N., Salis, S., Pes, M., Comunian, R., Paba, A., … Urgeghe, P. P. (2018). Impact of a thermisation treatment on oxytetracycline spiked ovine milk: Fate of the molecule and technological implications. LWT, 96, 236-243. doi:10.1016/j.lwt.2018.05.026Castillo, I., Calvo, M. V., Alonso, L., Juárez, M., & Fontecha, J. (2007). Changes in lipolysis and volatile fraction of a goat cheese manufactured employing a hygienized rennet paste and a defined strain starter. Food Chemistry, 100(2), 590-598. doi:10.1016/j.foodchem.2005.09.081Curioni, P. M. G., & Bosset, J. O. (2002). Key odorants in various cheese types as determined by gas chromatography-olfactometry. International Dairy Journal, 12(12), 959-984. doi:10.1016/s0958-6946(02)00124-3Delgado, F. J., González-Crespo, J., Cava, R., García-Parra, J., & Ramírez, R. (2010). Characterisation by SPME–GC–MS of the volatile profile of a Spanish soft cheese P.D.O. Torta del Casar during ripening. Food Chemistry, 118(1), 182-189. doi:10.1016/j.foodchem.2009.04.081Delgado, F. J., González-Crespo, J., Cava, R., & Ramírez, R. (2011). Formation of the aroma of a raw goat milk cheese during maturation analysed by SPME–GC–MS. Food Chemistry, 129(3), 1156-1163. doi:10.1016/j.foodchem.2011.05.096Gajda, A., Nowacka - Kozak, E., Gbylik - Sikorska, M., & Posyniak, A. (2017). Tetracycline antibiotics transfer from contaminated milk to dairy products and the effect of the skimming step and pasteurisation process on residue concentrations. Food Additives & Contaminants: Part A, 35(1), 66-76. doi:10.1080/19440049.2017.1397773Halling-Sørensen, B., Lykkeberg, A., Ingerslev, F., Blackwell, P., & Tjørnelund, J. (2003). Characterisation of the abiotic degradation pathways of oxytetracyclines in soil interstitial water using LC–MS–MS. Chemosphere, 50(10), 1331-1342. doi:10.1016/s0045-6535(02)00766-xHettinga, K. A., van Valenberg, H. J. F., & van Hooijdonk, A. C. M. (2008). Quality control of raw cows’ milk by headspace analysis. International Dairy Journal, 18(5), 506-513. doi:10.1016/j.idairyj.2007.10.005Katla, A.-K., Kruse, H., Johnsen, G., & Herikstad, H. (2001). Antimicrobial susceptibility of starter culture bacteria used in Norwegian dairy products. International Journal of Food Microbiology, 67(1-2), 147-152. doi:10.1016/s0168-1605(00)00522-5Loftin, K. A., Adams, C. D., Meyer, M. T., & Surampalli, R. (2008). Effects of Ionic Strength, Temperature, and pH on Degradation of Selected Antibiotics. Journal of Environmental Quality, 37(2), 378-386. doi:10.2134/jeq2007.0230McSweeney, P. L. H., & Sousa, M. J. (2000). Biochemical pathways for the production of flavour compounds in cheeses during ripening: A review. Le Lait, 80(3), 293-324. doi:10.1051/lait:2000127Padilla, B., Belloch, C., López-Díez, J. J., Flores, M., & Manzanares, P. (2014). Potential impact of dairy yeasts on the typical flavour of traditional ewes’ and goats’ cheeses. International Dairy Journal, 35(2), 122-129. doi:10.1016/j.idairyj.2013.11.002Quintanilla, P., Beltrán, M. C., Molina, A., Escriche, I., & Molina, M. P. (2019). Characteristics of ripened Tronchón cheese from raw goat milk containing legally admissible amounts of antibiotics. Journal of Dairy Science, 102(4), 2941-2953. doi:10.3168/jds.2018-15532Sierra, D., Contreras, A., Sánchez, A., Luengo, C., Corrales, J. C., Morales, C. T., … Gonzalo, C. (2009). Short communication: Detection limits of non-β-lactam antibiotics in goat’s milk by microbiological residues screening tests. Journal of Dairy Science, 92(9), 4200-4206. doi:10.3168/jds.2009-2101Souza, C. F. V. de, Dalla  Rosa, T., & Ayub, M. A. Z. (2003). Changes in the microbiological and physicochemical characteristics of Serrano cheese during manufacture and ripening. Brazilian Journal of Microbiology, 34(3). doi:10.1590/s1517-8382200300030001

Bridging Model and Observed Stellar Spectra

Accurate model stellar fluxes are key for the analysis of observations of individual stars or stellar populations. Model spectra differ from real stellar spectra due to limitations of the input physical data and adopted simplifications, but can be empirically calibrated to maximise their resemblance to actual stellar spectra. I describe a least-squares procedure of general use and test it on the MILES library.Comment: 7 pages, 6 figures, accepted for publication in MNRA

Genomics of perivascular space burden unravels early mechanisms of cerebral small vessel disease

Genomics; Perivascular spaceGenòmica; Espai perivascularGenómica; Espacio perivascularPerivascular space (PVS) burden is an emerging, poorly understood, magnetic resonance imaging marker of cerebral small vessel disease, a leading cause of stroke and dementia. Genome-wide association studies in up to 40,095 participants (18 population-based cohorts, 66.3 ± 8.6 yr, 96.9% European ancestry) revealed 24 genome-wide significant PVS risk loci, mainly in the white matter. These were associated with white matter PVS already in young adults (N = 1,748; 22.1 ± 2.3 yr) and were enriched in early-onset leukodystrophy genes and genes expressed in fetal brain endothelial cells, suggesting early-life mechanisms. In total, 53% of white matter PVS risk loci showed nominally significant associations (27% after multiple-testing correction) in a Japanese population-based cohort (N = 2,862; 68.3 ± 5.3 yr). Mendelian randomization supported causal associations of high blood pressure with basal ganglia and hippocampal PVS, and of basal ganglia PVS and hippocampal PVS with stroke, accounting for blood pressure. Our findings provide insight into the biology of PVS and cerebral small vessel disease, pointing to pathways involving extracellular matrix, membrane transport and developmental processes, and the potential for genetically informed prioritization of drug targets.Austrian Stroke Prevention Study (ASPS)/Austrian Stroke Prevention Family Study (ASPS-Fam) (E.H., P.G.G., H.S. and R.S.): We thank the staff and the participants for their valuable contributions. We thank B. Reinhart for her long-term administrative commitment, E. Hofer for the technical assistance in creating the DNA bank, J. Semmler and A. Harb for DNA sequencing and DNA analyses by TaqMan assays, and I. Poelzl for supervising the quality management processes after ISO9001 in the biobanking and DNA analyses. The Medical University of Graz and the Steiermärkische Krankenanstaltengesellschaft support the databank of the ASPS/ASPS-Fam. The research reported in this article was funded by the Austrian Science Fund (FWF) (grant nos. PI904, P20545-P05 and P13180) and supported by the Austrian National Bank Anniversary Fund (grant no. P15435) and the Austrian Ministry of Science under the aegis of the EU Joint Programme–Neurodegenerative Disease Research (JPND): www.jpnd.eu. Epidemiology of Dementia in Singapore (EDIS) (S.H., C.Chen, C.-Y.C., T.Y.W. and W.Z.): The EDIS study is supported by the National Medical Research Council (NMRC), Singapore (NMRC/CG/NUHS/2010 (grant no. R-184-006-184-511), NMRC/CSA/038/2013) and a Ministry of Education Tier 1 grant (no. A-0006106-00-00). Framingham Heart Study (FHS) (J.R.R., A.B., J.J.H., S.L., P.P., C.L.S., Q.Y. and S.Seshadri): This work was supported by the National Heart, Lung and Blood Institute’s FHS Contract (no. N01-HC-25195, no. HHSN268201500001I and no. 75N92019D00031). This study was also supported by grants from the National Institute of Aging (R01 grant nos. AG031287, AG054076, AG049607, AG059421, AG059725; U01 grant nos. AG049505, AG052409) and the National Institute of Neurological Disorders and Stroke (R01 grant no. NS017950). Funding for SHARe Affymetrix genotyping was provided by NHLBI Contract no. N02-HL64278. The computational work reported in this paper was performed on the Shared Computing Cluster which is administered by Boston University’s Research Computing Services. We also thank all the FHS study participants. Internet-based Students’ Health Research Enterprise (i-Share) study (C.B., J.Z., M.M., Q.LG., S. Schilling, Y.-C.Z., A.Tsuchida, M.-G.D., B.M., S.D. and C.T.): The i-Share study is conducted by the Universities of Bordeaux and Versailles Saint-Quentin-en-Yvelines (France). The i-Share study has received funding by the French National Agency (Agence Nationale de la Recherche, ANR), via the Investment for the Future program (grant nos. ANR-10-COHO-05 and ANR-18-RHUS-0002) and from the University of Bordeaux Initiative of Exellence (IdEX). This project has also received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program under grant agreement no. 640643 and from the Fondation pour la Recherche Médicale (grant no. DIC202161236446). Q.L.G. was supported by the Digital Public Health Graduate Program (DPH), a PhD program supported by the French Investment for the Future Program (grant no. 17-EURE-0019). Investigating Silent Strokes in Hypertensives: a Magnetic Resonance Imaging Study (ISSYS) (P.D., C.C. and I.F.-C.): This research was funded by the Instituto de Salud Carlos III (grant nos. PI10/0705, PI14/01535, PI17/02222), cofinanced by the European Regional Development Fund. Lothian Birth Cohort 1936 (LBC1936) (M.L., M.E.B., I.J.D., Z.M., S.M.M., M.C.V.H. and J.M.W.): We thank the LBC1936 cohort members and research staff involved in data collection, processing and preparation. The LBC1936 is supported by Age UK (Disconnected Mind program grant). The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (grant no. MR/K026992/1). The brain imaging was performed in the Brain Research Imaging Centre (www.bric.ed.ac.uk), a center in the SINAPSE Collaboration (www.sinapse.ac.uk) supported by the Scottish Funding Council and Chief Scientist Office. Funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC), the UK Medical Research Council (MRC), the Row Fogo Charitable Trust (M.C.V.H.) and the UK Dementia Research Institute, which receives its funding from the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK (J.M.W.), is gratefully acknowledged. Genotyping was supported by a grant from the BBSRC (no. BB/F019394/1). The Nagahama Study (T.K., S.M., M.O., K.S., Y.T., K.Y., A.Tsuchida, P.B., B.M., M.J., M.-G.D. and F.M.): We are grateful to the Nagahama City Office and nonprofit organization Zeroji Club for their help in conducting the study. This project is supported by operational funds of Kyoto University and the Top Global University Project of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan. We also received a Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science, research grants from the Japan Agency for Medical Research and Development for the Practical Research Project for Rare/Intractable Diseases, and the Comprehensive Research on Aging and Health Science for Dementia R&D. We thank C. Galmiche for rating PVS in the validation dataset for the artificial intelligence-based method. The Northern Manhattan Study (NOMAS) (N.D.D., T.J. and R.L.S.): We gratefully acknowledge and thank the NOMAS participants. Funding was awarded through grants from the National Institute of Neurological Disorders and Stroke (R01 grant no. NS 29993) and the Evelyn F. McKnight Brain Institute. Rotterdam Study (M.J.K., F.D., M.W.V., M.A.I. and H.H.H.A.): The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, the Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study (RS I, RS II, RS III) were executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands. The GWAS datasets are supported by the Netherlands Organisation for Scientific Research (NWO) Investments (no. 175.010.2005.011, 911-03-012), the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, the Research Institute for Diseases in the Elderly (grant no. 014-93-015; RIDE2), the Netherlands Genomics Initiative/NWO, the Netherlands Consortium for Healthy Aging, project no. 050-060-810. We thank P. Arp, M. Jhamai, M. Verkerk, L. Herrera, M. Peters and C. Medina-Gomez for their help in creating the GWAS database; and K. Estrada, Y. Aulchenko and C. Medina-Gomez for the creation and analysis of imputed data. H.H.H.A. is supported by ZonMW grant no. 916.19.151. Study of Health in Pomerania (SHIP) (S.F., R.B., A.T., K.W., H.J.G. and U.V.): SHIP is part of the Community Medicine Research net (CMR) (http://www.medizin.uni-greifswald.de/icm) of the University Medicine Greifswald, which is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant no. 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. This study was further supported by the EU-JPND Funding for BRIDGET (grant no. FKZ:01ED1615). H.J.G. has received travel grants and speakers’ honoraria from Fresenius Medical Care, Servier, Neuraxpharm and Janssen Cilag, as well as research funding from Fresenius Medical Care. Sydney Memory and Ageing Study (MAS) & Older Australian Twins Study (OATS) (R.M.T., N.J.A., H.B., J.J., M.P., A.T., J.N.T., P.S.S., W.W., K.A.M. and M.J.W.): Sydney MAS: The Sydney MAS has been funded by three National Health & Medical Research Council (NHMRC) Program Grants (grant nos. ID350833, ID568969 and APP1093083). Collection of WGS data was supported by the NHMRC National Institute for Dementia Research Grants no. APP1115575 and no. APP1115462. MRI scans were processed with the support of NHMRC Project Grants (grant nos. 510175 and 1025243) and an Australian Research Council (ARC) Discovery Project Grant (no. DP0774213) and the John Holden Family Foundation. We also thank the MRI Facility at NeuRA. We thank the participants and their informants for their time and generosity in contributing to this research. We also acknowledge the MAS research team: https://cheba.unsw.edu.au/research-projects/sydney-memory-and-ageing-study. OATS: The OATS study has been funded by an NHMRC and ARC Strategic Award Grant of the Ageing Well, Ageing Productively Program (grant no. 401162); NHMRC Project (seed) Grants (grant nos. 1024224 and 1025243); NHMRC Project Grants (grant nos. 1045325 and 1085606); and NHMRC Program Grants (grant nos. 568969 and 1093083). Collection of WGS data was supported by the NHMRC National Institute for Dementia Research Grants no. APP1115575 and no. APP1115462. This research was facilitated through access to Twins Research Australia, a national resource supported by a Centre of Research Excellence Grant (no. 1079102) from the National Health and Medical Research Council. We thank the participants for their time and generosity in contributing to this research. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/project/older-australian-twins-study) to this study. Three-City Dijon Study (3C-Dijon) (S.D., M.-G.D., S. Schilling, C.T., B.M. and A.M.): This project is supported by a grant overseen by the French National Research Agency (ANR) as part of the ‘Investment for the Future Program’ no. ANR-18-RHUS-0002. It is also supported by a JPND project through the following funding organizations under the aegis of JPND: www.jpnd.eu: Australia, National Health and Medical Research Council; Austria, Federal Ministry of Science, Research and Economy; Canada, Canadian Institutes of Health Research; France, French National Research Agency; Germany, Federal Ministry of Education and Research; the Netherlands, the Netherlands Organisation for Health Research and Development; United Kingdom, Medical Research Council. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement nos. 643417, 640643, 667375 and 754517. The project also received funding from the French National Research Agency (ANR) through the VASCOGENE and SHIVA projects, and from the Initiative of Excellence of the University of Bordeaux (C-SMART project). Computations were performed on the Bordeaux Bioinformatics Center (CBiB) computer resources, University of Bordeaux. Funding support for additional computer resources at the CREDIM (Centre de Recherche et Développement en Informatique Médicale, University of Bordeaux) has been provided to S.D. by the Fondation Claude Pompidou. The Three-City (3C) Study: The 3C Study is conducted under a partnership agreement among the Institut National de la Santé et de la Recherche Médicale (INSERM), the University of Bordeaux and Sanofi-Aventis. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study is also supported by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, Mutuelle Générale de l’Education Nationale (MGEN), Institut de la Longévité, Conseils Régionaux of Aquitaine and Bourgogne, Fondation de France and Ministry of Research–INSERM program ‘Cohortes et collections de données biologiques.’ C.T. and S.D. have received investigator-initiated research funding from the French National Research Agency (ANR) and from the Fondation Leducq. M.-G.D. received a grant from the ‘Fondation Bettencourt Schueller’. We thank P. Amouyel, U1167 Institut Pasteur de Lille - University of Lille - Inserm, for supporting funding of genome-wide genotyping of the 3C Study. This work was supported by the National Foundation for Alzheimer’s disease and related disorders, the Institut Pasteur de Lille, the labex DISTALZ and the Centre National de Génotypage. We thank A. Boland (CNG) for her technical help in preparing the DNA samples for analyses. UK Biobank (UKB) (M.J.K., F.D., M.W.V., M.A.I., H.H.H.A., A.M. and T.E.): This research has been conducted using the UK Resource under application no. 23509. McGill Genome Center (M.B., P.M., G.B. and M.Lathrop): Work done at the Canadian Center for Computational Genomics was supported by Genome Canada. Data analyses were enabled by computing and storage resources provided by Compute Canada and Calcul Québec. G.B. is supported by the Fonds de Recherche Santé Québec and the Canada Research Chair program. We thank all the participating cohorts for contributing to this study. We thank H. Jacqmin-Gadda, Bordeaux Population Health research center, University of Bordeaux/Inserm U1219 for statistical advice. We thank J. Thomas-Crusells, Bordeaux Population Health Research Center, University of Bordeaux/Inserm U1219, for editorial assistance. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript

Modleamiento y predicción de lluvias usando Edge Computing para el entorno colombiano

International audienceNowadays the number of devices connected to internet which offer the possibility to collect data is increasing. The interconnectivity of these new sensors favors the creation of sustainable cities, in which the optimization of resources is based on the collected data. These sensors are also a big source of information for forecasting future values. In this work we present an Edge Computing approach for the analysis and forecasting of rainfall data that is later validated on the CITI Laboratory Youpi Platform. To this end, we built a container image with the necessary tools and libraries to use the time series prediction models SARIMA and Prophet on ARMv7 architectures. A Raspberry Pi 3 node was chosen to evaluate performance on an Edge Computing device. Colombia was chosen due to its tropical location and its variant geography which present a wide range of historical rainfall data. The data we used to train our models consisted on the historical mesures from sensors deployed in Colombia by the "Instituto de Hidrología, Meteorología y es-tudios Ambientales de Colombia-IDEAM". In first place, we selected Bucaramanga to study its data sensors and to define the well-suited parameters for SARIMA and Prophet trend models. The comparison between them presented a high degree of similarity, offering a good prediction of dry and wet seasons. Thereafter, the SARIMA and Prophet model of Bucaramanga were used to observe its adaptability to the cities of Bogotá and Medellín, getting a successful outcome at seasonal predictions. After this estimation of the SARIMA parameters and its analysis offline, a container image was created to simplify and speed up the models implementation in the devices for predicting the two years monthly rainfall for Bucaramanga, Bogotá and Medellín. The container is available for armv7 architectures, that is usually used for IoT nodes on the Youpi platform. The proposed model allows to create a network of sensors, with distributed analysis capacity, that improve the prevention of flood or drought emergencies in Smart Cities on Colombia, helping to manage resources for agriculture or prevent catastrophes

Stellar Content from high resolution galactic spectra via Maximum A Posteriori

This paper describes STECMAP (STEllar Content via Maximum A Posteriori), a flexible, non-parametric inversion method for the interpretation of the integrated light spectra of galaxies, based on synthetic spectra of single stellar populations (SSPs). We focus on the recovery of a galaxy's star formation history and stellar age-metallicity relation. We use the high resolution SSPs produced by PEGASE-HR to quantify the informational content of the wavelength range 4000 - 6800 Angstroms. A detailed investigation of the properties of the corresponding simplified linear problem is performed using singular value decomposition. It turns out to be a powerful tool for explaining and predicting the behaviour of the inversion. We provide means of quantifying the fundamental limitations of the problem considering the intrinsic properties of the SSPs in the spectral range of interest, as well as the noise in these models and in the data. We performed a systematic simulation campaign and found that, when the time elapsed between two bursts of star formation is larger than 0.8 dex, the properties of each episode can be constrained with a precision of 0.04 dex in age and 0.02 dex in metallicity from high quality data (R=10 000, signal-to-noise ratio SNR=100 per pixel), not taking model errors into account. The described methods and error estimates will be useful in the design and in the analysis of extragalactic spectroscopic surveys.Comment: 31 pages, 23 figures, accepted for publication in MNRA