2,364 research outputs found
The Weibull-Geometric distribution
In this paper we introduce, for the first time, the Weibull-Geometric
distribution which generalizes the exponential-geometric distribution proposed
by Adamidis and Loukas (1998). The hazard function of the last distribution is
monotone decreasing but the hazard function of the new distribution can take
more general forms. Unlike the Weibull distribution, the proposed distribution
is useful for modeling unimodal failure rates. We derive the cumulative
distribution and hazard functions, the density of the order statistics and
calculate expressions for its moments and for the moments of the order
statistics. We give expressions for the R\'enyi and Shannon entropies. The
maximum likelihood estimation procedure is discussed and an algorithm EM
(Dempster et al., 1977; McLachlan and Krishnan, 1997) is provided for
estimating the parameters. We obtain the information matrix and discuss
inference. Applications to real data sets are given to show the flexibility and
potentiality of the proposed distribution
Small-sample corrections for score tests in Birnbaum-Saunders regressions
In this paper we deal with the issue of performing accurate small-sample
inference in the Birnbaum-Saunders regression model, which can be useful for
modeling lifetime or reliability data. We derive a Bartlett-type correction for
the score test and numerically compare the corrected test with the usual score
test, the likelihood ratio test and its Bartlett-corrected version. Our
simulation results suggest that the corrected test we propose is more reliable
than the other tests.Comment: To appear in the Communications in Statistics - Theory and Methods,
http://www.informaworld.com/smpp/title~content=t71359723
Braquiária na agropecuária brasileira: uma história de sucesso.
bitstream/item/99413/1/cap1.pd
Molecular genotyping of sugarcane clones with microsatellite DNA markers
Molecular genotypes of 27 sugarcane clones (Saccharum hybrids) were produced with nine sugarcane microsatellites. A total of 52 alleles were identified using a capillary electrophoresis system with 41 alleles displaying varying degrees of polymorphism and the remaining 11 being monomorphic. There were eight alleles for sugarcane microsatellite SMC286CS, five for SMC334BS, eight for SMC336BS, four for SMC713BS, five for mSSCIR5, five for mSSCIR33, five for MCSA042E08, four for MCSA053C10, and eight for MCSA068G08. Presence or absence of these 52 alleles from a clone allowed the assignment of its arbitrary microsatellite genotype. The genetic relatedness among these clones was assessed using the CLUSTAL W algorithm with DNAMAN(R) software based on their arbitrary genotypes. With the exception of four clones, CP 70-321, HoCP 91-555, L 97-137 and Q124, six groups of clones were identified that shared at least 76% homology between their microsatellite genotypes. The software program also produced a bootstrapped phylogenetic tree with branch patterns that in general coincided with the putative pedigrees of these clones. The derivation of molecular genotypes such as these has enable sugarcane geneticists and breeders to verify the genetic pedigrees and purity of their sugarcane populations. These microsatellite genotypes can also aid in progeny selection and facilitate studies on allele transmission in this aneu-polyploidy crop
Power of microsatellite markers for fingerprinting and parentage analysis in Eucalyptus grandis breeding populations.
Technological evolution and production arrangements of crop-livestock-forestry integration systems in Brazil.
Personalized approaches for the management of glaucoma
Introduction: Personalized medicine is the future goal across all specialties. Accurate prediction of optimal treatment beneficial and adverse effects could transform patient management. This is of particular importance in chronic conditions, where a ‘trial and error’ approach over months and years can contribute to significant morbidity. Glaucoma is a chronic irreversible progressive optic neuropathy, a leading cause of blindness worldwide. An ideal personalized approach in glaucoma clinic would be to answer the inevitable question in a patient’s first visit: ‘Which treatment option will work best for me so that I won’t go blind?’ / Areas covered: This review will give an overview of the knowledge we have acquired to achieve this goal, particularly discussing using patient’s individual risk factors, their genetic profile, and different treatment modalities, including therapy compliance, to personalize care. / Expert opinion: Pharmacogenomics and genetic profiling are the most tangible ways in which glaucoma management can be personalized. Future challenges will include developing realistic animal models to reflect the underlying genetic patterns in glaucoma to investigate their interaction with different treatments
Fructo-oligosaccharides separation and purification by simulated moving bed chromatography
The interest on oligosaccharides such as fructo-oligosaccharides (FOS) has strongly increased in recent years for food and pharmaceutical applications, mainly due to their improved technological and functional properties. FOS can be produced by fermentative processes from sucrose, and can be found in mixture with other mono- and di-saccharides and salts, at the end of the process [1]. Unlike FOS, the small saccharides (SGF), namely fructose, glucose and sucrose in the mixture, are known to be cariogenic, caloric and do not present prebiotic activity. The purification of FOS from the other sugars can represent and important increment on the economic value of the final product, which can be further used in diabetic and dietetic food [2]. Different strategies have been developed for this purpose, including microbial treatment [3], ultra and nano-filtration, activated charcoal systems [4], or ion-exchange chromatography [5]. Ion exchange resins may be then used in batch or continuous chromatographic processes, as Simulated Moving Bed (SMB) chromatography, to purify sugars.
A screening of different commercial resins was previously done in order to select the most suitable to separate the oligosaccharides [5]. The resin Diaion 535Ca showed an increased recovery yield and purity of FOS (92 and 90%, respectively). In the present work, the separation process was implemented in the SMB, using the selected resin, namely. Equilibrium adsorption isotherms were determined by the Retention Time Method (RTM), for each single sugar. The resin was afterwards packed in eight SMB columns, and tested in the pilot plant. Different operation parameters, including switching time, extra time, internal flow-rates and operating pump flow-rates for feed, raffinate, desorbent, eluent and recycling streams, were tested in the plant.
The separation of fructose from glucose and FOS from the SGF was evaluated. Firstly, the separation of a binary sugar mixture of fructose/sucrose (~ 50/50%) was performed followed by the separation of FOS from a fermentative broth. Fructose was purified from 53 to 76% and sucrose from 47 to 77%. FOS and SGF were purified from 50 to 67%. The implementation of UV detectors between the SMB columns allowed following the sugar concentration profile online during the separation process. The accurate selection of the operating parameters was made using the concentration signal obtained and showed to be a crucial step for an improved separation
Evaluation of Xgboost and Lgbm Performance in Tree Species Classification with Sentinel-2 Data
Los, H., Mendes, G. S., Cordeiro, D., Grosso, N., Costa, H., Benevides, P., & Caetano, M. (2021). Evaluation of Xgboost and Lgbm Performance in Tree Species Classification with Sentinel-2 Data. In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium: Proceedings (pp. 5803-5806). IEEE. https://doi.org/10.1109/IGARSS47720.2021.9553031Tree species classification with satellite data has become more and more popular since Sentinel-2 launch. We compared efficacy and effectiveness of Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LGBM) with widely used in remote sensing Random Forest (RF), Support Vector Machine (SVM) and K-Nearest Neighbour (KNN) algorithms. Analyses were performed over an area in Portugal with multi-temporal Sentinel-2 data registered in April, June, August and October 2018. The selected classes were: cork oak, holm oak, eucalyptus, other broadleaved, maritime pine, stone pine and other coniferous. Algorithm efficacy was measured through F1-score and accuracy while efficiency was measured through the median time needed for each fit. XGBoost and LGBM outperformed efficacy of other algorithms, which was already high (above 90% for the best variant of each algorithm). In terms of efficacy, LGBM overcame all algorithms, including XGBoost.authorsversionpublishe
Foreword
[Excerpt] This book is the forth book of the series of publications entitled “Occupational Safety and Hygiene”. The main contributions for this book were once more from the works that were previously submitted and approved to be presented at the annual symposium of the Portuguese Society of Occupational Safety and Hygiene (SPOSHO), which is celebrating its 12th edition in 2016. The SHO2016—International Symposium on Occupational Safety and Hygiene, similarly to the past eight years, was held in the School of Engineering at University of Minho in Guimarães, Portugal. [...](undefined
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