The spectrum of an algebra of weakly continuous holomorphic mappings

AbstractLet U be an arbitrary absolutely convex open subset of a complex Banach space E and let F be a Banach algebra with identity. The spectrum of the algebra Hb(U, F) of the holomorphic mappings from U and F which are bounded on the U-bonded subsets of U is studied in case E′ has the approximation properly

Levantamento sôbre a composição química bromatológica de 39 variedades forrageiras de cana-de-açúcar

This paper deals with a survey on chemical compositions of 39 forage sugar cane varieties carried out at the Bromatology Laboratory of the E.S.A. "Luiz de Queiroz" (5th chair). Samples were taken at Sugar Cane Experimental Station "Jose Viziolli", Piracicaba, SP, and the material was analised by standard methods. The main conclusions can be summarised as follows: 1. All varieties showed low protein and mineral contents, but were high in crude fiber and nitrogen free extract fractions. 2. A small, but positive correlation was observed between crude fiber and protein content. 3. The amount of observed variation concerning the various nutrient fractions could be used to select better forage sugar cane varieties

Impact of methodological approaches in the agreement between subjective and objective methods for assessing screen time and sedentary behavior in pediatric population: a systematic review

Introduction: sedentary behavior is an important target for health promotion. In this systematic review, we aimed to provide evidence to support decisions about measurement approach choices for subjectively assessing sedentary behavior in pediatric population, adopting objective methods as the reference. Methods: in this systematic review with meta-analysis, published studies were retrieved from electronic databases: Medline (PubMed), Web of Science, Embase, SPORTDiscus, BioMed Central and SCOPUS. We considered studies evaluating sedentary behavior agreement through questionnaire and/or diary in comparison with an objective measure. A total of six inclusion criteria v, rere used. We synthesized the data using correlation coefficients (r) as an indicator of agreement estimates. The review protocol is registered in the PROSPERO database (CRD42014015138). Results: a total of 14 studies met the inclusion criteria with ages ranging from 3 to 17.5 years and provided 17 agreement analyses. Thirteen of these agreement analyses (76.5%) reported correlation coefficients. We found two major groups of sedentary activities: screen time (47.1%) and sedentary behaviors (52.9%). The pooled agreement between questionnaires and accelerometers for assessing self-reported screen time was negative (r =-0.15; Cl 95%:-0.17 to-0.13). Conversely, when the sedentary behavior was assessed by questionnaires and accelerometers, the pooled agreement, vas positive for parent-reporting (r = 0.09; Cl 95%; 0.04 to 0.13) and self-reporting (r = 0.43; CI 95%: 0.40 to 0.47) in children and adolescents, respectively. Conclusion: questionnaires have positive agreement with accelerometers for assessing sedentary behavior, whereas the agreement is negative for assessing screen time. Self-reported questionnaires are recommended methods to measure sedentary behavior in adolescents

Prevalence of cardiovascular risk factors, the association with socioeconomic variables in adolescents from Low-Income region

Objectives: To estimate the prevalence of obesity, overweight, abdominal obesity and high blood pressure in a sample of adolescents from a low-income city in Brazil and to estimate the relationship with the socioeconomic status of the family, the education level of the family provider and the type of school. Methods: This cross-sectional study randomly sampled 1,014 adolescents (54.8% girls), between 14-19 years of age, attending high school from Imperatriz (MA). The outcomes of this study were: obesity and overweight, abdominal obesity and high blood pressure (systolic and/ or diastolic). The independent variables were: socioeconomic status (SES) of the family, education level of the family provider (ELFP) and type of school. The confounding variables were: gender, age and physical activity level. Prevalence was estimated, and the association between the endpoints and the independent variables was analyzed using a prevalence ratio (PR), with a 95% confidence interval, estimated by Poisson regression. Results: The overall prevalence of obesity was 3.8%, overweight, 13.1%, abdominal obesity, 22.7% and high blood pressure, 21.3%. The adjusted analysis indicated that girls with high SES showed an increased likelihood to be overweight (PR=1.71 [95% IC: 1.13-2.87]), while private school boys had an increased likelihood of obesity (PR=1.79 [95% CI: 1.04-3.08]) and abdominal obesity (PR =1.64 [95% CI: 1.06-2.54]). Conclusion: The prevalence of CVDR is high in adolescents from this low-income region. Boys from private schools are more likely to have obesity and abdominal obesity, and girls with high SES are more likely to be overweight

Height-based equations as screening tools for elevated blood pressure in the SAYCARE study

This study evaluated the accuracy of four height-based equations: blood pressure to height ratio (BPHR), modified BPHR (MBPHR), new modified BPHR (NMBPHR), and height-based equations (HBE) for screening elevated BP in children and adolescents in the SAYCARE study. We measured height and BP of 829 children and adolescents from seven South American cities. Receiving operating curves were used to assess formula performance to diagnose elevated BP in comparison to the 2017 clinical guideline. Sensitivity, specificity, and positive and negative predictive values (PPV, NPV) were calculated for the four screening formulas. The diagnostic agreement was evaluated with the kappa coefficient. The HBE equation showed the maximum sensitivity (100%) in children, both for boys and girls, and showed the best performance results, with a very high NPV (>99%) and high PPV (>60%) except for female children (53.8%). In adolescents, the highest sensitivity (100%) was achieved with the NMBPHR for both sexes. Kappa coefficients indicated that HBE had the highest agreement with the gold standard diagnostic method (between 0.70 and 0.75), except for female children (0.57). Simplified methods are friendlier than the percentile gold standard tables. The HBE equation showed better performance than the other formulas in this Latin American pediatric population

Reliability and validity of body weight and body image perception in children and adolescents from the South American Youth/Child Cardiovascular and Environmental (SAYCARE) Study

Objective: To assess the reliability and validity of body weight (BW) and body image (BI) perception reported by parents (in children) and by adolescents in a South American population. Design: Cross-sectional study. BW perception was evaluated by the question, "Do you think you/your child are/is: severely wasted, wasted, normal weight, overweight, obese?" BI perception was evaluated using the Gardner scale. To evaluate reliability, BW and BI perceptions were reported twice, two weeks apart. To evaluate validity, the BW and BI perceptions were compared with WHO BMI Z-scores. Kappa and Kendall's tau-c coefficients were obtained. Setting: Public and private schools and high schools from six countries of South America (Argentina, Peru, Colombia, Uruguay, Chile, Brazil). Participants: Children aged 3-10 years (n 635) and adolescents aged 11-17 years (n 400). Results: Reliability of BW perception was fair in children's parents (k=0·337) and substantial in adolescents (k=0·709). Validity of BW perception was slight in children's parents (k=0·176) and fair in adolescents (k=0·268). When evaluating BI, most children were perceived by parents as having lower weight. Reliability of BI perception was slight in children's parents (k=0·124) and moderate in adolescents (k=0·599). Validity of BI perception was poor in children's parents (k=-0·018) and slight in adolescents (k=0·023). Conclusions: Reliability of BW and BI perceptions was higher in adolescents than in children's parents. Validity of BW perception was good among the parents of the children and adolescents with underweight and normal weight

Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy

Methane (CH) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH. To address this limitation, we developed novel CH prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH production (g CH/animal·d, ANIM-B models) and CH yield (g CH/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin’s concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH emissions from sheep, providing valuable insights for future research and mitigation strategies.Te authors gratefully acknowledge funding for this project from the USDA National Institute of Food and Agriculture (Award number: 2014-67003-21979). Te animal and microbial data originated from a study funded by the Pastoral Greenhouse Gas Research Consortium (www.pggrc.co.nz)