Canela, M.A. (Miguel A.)
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- A comparison of models for the forecast of daily concentration thresholds of airborne fungal spores(MDPI, 2023-06-13) Canela, M.A. (Miguel A.); Belmonte, J. (Jordina); Vélez-Pereira, A.M. (Andrés M.); Linares, C. (Concepción) deAerobiological predictive model development is of increasing interest, despite the distribution and variability of data and the limitations of statistical methods making it highly challenging. The use of concentration thresholds and models, where a binary response allows one to establish the occurrence or non-occurrence of the threshold, have been proposed to reduce difficulties. In this paper, we use logistic regression (logit) and regression trees to predict the daily concentration thresholds (low, medium, high, and very high) of six airborne fungal spore taxa (Alternaria, Cladosporium, Agaricus, Ganoderma, Leptosphaeria, and Pleospora) in eight localities in Catalonia (NE Spain) using data from 1995 to 2014. The predictive potential of these models was analyzed through sensitivity and specificity. The models showed similar results regarding the relationship and influence of the meteorological parameters and fungal spores. Ascospores showed a strong relationship with precipitation and basidiospores with minimum temperature, while conidiospores did not indicate any preferences. Sensitivity (true-positive) and specificity (false-positive) presented highly satisfactory validation results for both models in all thresholds, with an average of 73%. However, seeing as logit offers greater precision when attempting to establish the exceedance of a concentration threshold and is easier to apply, it is proposed as the best predictive model.
- Recent updates and developments to plant genome size databases(Oxford University Press, 2013-11-27) Mas-de-Xaxars, G. (Gemma); Pellicer, J. (Jaume); Canela, M.A. (Miguel A.); Johnston, E. (Emmeline); Vallès, J. (Joan); Anadon-Rosell, A. (Alba); Garcia, S. (Sònia); Hidalgo, O. (Oriane); Leitch, I.J. (Ilia J.); Bennett, M.D. (Michael D.); Garnatje, T. (Teresa); Vitales, D. (Daniel); Gálvez, F. (Francisco); Siljak-Yakovlev, S. (Sonja); Gras, A. (Airy)Two plant genome size databases have been recently updated and/or extended: the Plant DNA C-values database (http://data.kew.org/cvalues), and GSAD, the Genome Size in Asteraceae database (http://www.asteraceaegenomesize.com). While the first provides information on nuclear DNA contents across land plants and some algal groups, the second is focused on one of the largest and most economically important angiosperm families, Asteraceae. Genome size data have numerous applications: they can be used in comparative studies on genome evolution, or as a tool to appraise the cost of whole-genome sequencing programs. The growing interest in genome size and increasing rate of data accumulation has necessitated the continued update of these databases. Currently, the Plant DNA C-values database (Release 6.0, Dec. 2012) contains data for 8510 species, while GSAD has 1219 species (Release 2.0, June 2013), representing increases of 17 and 51%, respectively, in the number of species with genome size data, compared with previous releases. Here we provide overviews of the most recent releases of each database, and outline new features of GSAD. The latter include (i) a tool to visually compare genome size data between species, (ii) the option to export data and (iii) a webpage containing information about flow cytometry protocols.
- Improvement of weight and body composition in a group of women through a weight management program using food supplements with or without a hypocaloric diet(Set Publisher, 2014-08-05) Canela, M.A. (Miguel A.); DIECA Group; Rafecas, M. (Magdalena); Arranz, L.I. (Laura Isabel); García, M. (Mireia)Overweight is an increasing health problem characterised as a higher than normal body weight due to an abnormal increase in body fat. Body weight adequacy is categorized by using body mass index (BMI), however other parameters such as fat mass (FM), waist circumference (Wci) or waist to hip ratio, are relevant. Ideally, body composition should be calculated initially to evaluate changes during a dietary intervention of weight loss. Hunger experience is another parameter to take into account. The aim of this study was to assess the improvement of weight and body composition through the use of food supplements to control hunger, with and without a hypocaloric diet prescription. 252 women who wanted to lose weight were recruited in the program and splitted into two groups and were monitored for 8 weeks. Anthropometric measures (weight, height, body mass index, fat mass, waist and hip circumference) were taken. The mean age was of 36.84±7.29 and most of them were within overweight or obesity values for BMI, FM, Wci and hip circumference. After 8 weeks, both groups got significant results, achieving not only weight loss but also reduction in body mass index, fat mass, and waist and hip circumferences. However, as expected, improvements were better in FS+diet than in FS group. There is a need to tackle overweight and obesity individually, taking into account the personal characteristics of the patient. Food supplements may be useful to manage hunger and professional individualised assessment is critical to succeed.
- Anthropometric characteristics and other dietary aspects of a group of Spanish women looking for weight loss and enrolled in a weight management program(Set Publisher, 2014-06-05) Canela, M.A. (Miguel A.); DIECA Group; Rafecas, M. (Magdalena); Arranz, L.I. (Laura Isabel); García, M. (Mireia)Overweight is a health problem characterised as a higher than normal body weight due to an abnormal increase in body fat. Body weight adequacy is categorised using body mass index (BMI), however other parameters as fat mass (FM), waist circumference or waist to hip ratio, are relevant. Ideally, body composition should be calculated initially to evaluate changes during a dietary intervention for weight loss. Hunger experience is another parameter to take into account in order to succeed. The aim was to investigate and describe the characteristics of women seeking weight loss solutions. We organised an open program for people with body excess who wanted to lose weight. 252 women participated and answered to a dietary interview. Anthropometric measures of weight, height, body mass index, body fat, waist and hip circumference were taken. The mean age was of 36.84±7.29 years, and most of them, about 90%, have followed dietary programs for weight loss throughout their lives. They all wanted to lose weight in a range of 3 to 20 kilograms with a mean value of 11.49±6.01 kilograms. 123 women had a hunger profile of satiating behaviour and 129 a snacking one. The mean BMI was within overweight values, and mean fat mass was within obesity values. Waist and hip circumference were higher than normal in most of the participants and excess body weight perception and attitude were different. There is a need to tackle overweight and obesity individually, taking into account personal consciousness and expectancy, anthropometric measures and hunger experience.
- Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis(Elsevier, 2021) Strobl, C. (Carolin); Canela, M.A. (Miguel A.); Viganola, D. (Domenico); Staub, N. (Nicola); Schaumans, C.B.C. (Catherine B.C.); Murase, T. (Toshio); Snellman, K. (Kaisa); Goldstein, P. (Pavel); Althoff, T. (Tim); Schweinsberg, M. (Martin); Kelchtermans, S. (Stijn); Bernstein, A. (Abraham); Feldman, M. (Michael); Aert, R.C.M. (Robbie C.M.) van; Tierney, W. (Warren); Robinson, E. (Emily); Heer, J. (Jeffrey); Sommer, S.A. (S. Amy); Madan, N. (Nikhil); Prasad, V.V. (Vaishali Venkatesh); Mandl, B. (Benjamin); Liu, Y. (Yang); Kale, A. (Alex); Amireh, H. (Hashem); Robinson, D. (David); Silberzahn, R. (Raphael); Akker, O.R. (Olmo R.) van den; Assen, M.A.L.M (Marcel A.L.M.) van; Otner, S.M.G. (Sarah M.G.); Mohamed, Z. (Zainab)In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
- Dataset on PGA Tour tournament entry(Elsevier, 2022-02-15) Canela, M.A. (Miguel A.); Pastoriza, D. (David); Alegre, I. (Inés)This article describes a dataset that allows to explore the determinants and moderators of athletes’ decision to enter in tournaments endowed with a monetary prize. Specifically, the dataset contains variables that describe athlete's short-term momentum (i.e., performance streak in the tournaments recently entered) and long-term momentum (i.e., performance streak in the same tournament across seasons), which permits an in-depth analysis of how past performance trajectory drives self-selection into tournaments. The dataset consists of 54,915 self-selection decisions that golfers have taken over an eleven-year period (1996–2006) when deciding to participate in PGA Tour tournaments.