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Estimating carbon stocks in wooded systems is crucial to quantify national greenhouse gas balance estimates. However, inaccurate estimates are likely due to the divergent architecture of many species. The monkey puzzle tree Araucaria araucana, with its umbrella-like architecture is a vivid example. This species, often found in monodominant stands at high elevations, is the greatest carbon reservoir in the landscape, hence estimating its carbon storage is crucial. To provide the necessary basis for these estimations, we documented the variation in basic density and moisture content along the stem profile, identified the most suitable biomass estimation models, and quantified biomass allocation for three age ranges. We measured, felled, weighed, and separated trees into three categories: stem wood, stem bark, and foliage (branches + scaly leaves). The log-linear form of the simple allometric equation Y = aXb, based on diameter at breast height as the explanatory variable, covered a large part of the variation and showed good cross-validation performance (>0.96). Models using more covariates achieved lower absolute errors, but the estimation of the additional model parameters was associated with greater uncertainty. A multi-objective model comparison revealed that the best additional covariate to further improve biomass estimation was total tree height. The mean absolute percentage error was 9.8% for the total aboveground biomass, 8% for stem wood, 12% for stem bark and 24% for foliage. Changes in biomass distribution among tree components were related to age. For older trees, there was a relative increase in stem wood, a decreased proportion of foliage, but no change in stem bark. The proportion of stem bark biomass is similar to that of Araucaria angustifolia, but higher than in other conifers and most trees in general. Our results provide key properties for A. araucana and general guidance for the selection of easily-measurable variables allowing for excellent predictive power for local biomass estimation.

We prove the exact multiplicity of flat and compact support stable solutions of an autonomous non-Lipschitz semilinear elliptic equation of eigenvalue type according to the dimension N and the two exponents, 0 < α < β < 1, of the involved nonlinearites. Suitable assumptions are made on the spatial domain Ω where the problem is formulated in order to avoid a possible continuum of those solutions and, on the contrary, to ensure the exact number of solutions according to the nature of the domain Ω. Our results also clarify some previous works in the literature. The main techniques of proof are a Pohozhaev’s type identity and some fibering type arguments in the variational approach.

There is a general trend in WLCG towards the federation of resources, aiming for increased simplicity, efficiency, flexibility, and availability. Although general VO-agnostic federation of resources between two independent and autonomous resource centres may prove arduous, a considerable amount of flexibility in resource sharing can be achieved in the context of a single WLCG VO, with a relatively simple approach. We have demonstrated this for PIC and CIEMAT, the Spanish Tier-1 and Tier-2 sites for CMS, by making use of the existing CMS xrootd federation infrastructure and profiting from the common CE/batch technology used by the two centres. This work describes how compute slots are shared between the two sites, so that the capacity of one site can be dynamically increased with idle execution slots from the remote site, and how data can be efficiently accessed irrespective of its location. Our contribution includes measurements for diverse CMS workflows comparing performances between local and remote execution, and can also be regarded as a benchmark to explore future potential scenarios, where storage resources would be concentrated in a reduced number of sites.

Abstract: Introduction: Various viruses affect the central nervous system (CNS) causing encephalitis, mainly in pediatric patients. Objective: To determine the involvement of viral agents for central nervous system (CNS) infections in children in the State of Zulia, Venezuela during the year 2007. Patients and Methods: 109 samples of cerebrospinal fluid (CSF) and serum were collected from patients between 1 day and 14 years of age, who presented clinical symptoms suggestive of CNS involvement and whose conventional CSF bacteriological study proved negative. The CSF Albumin /serum relationship was determined in order to rule out contamination, resulting in 24 optimal pairs for determining the IgM and IgG antibodies specific for herpes simplex virus (HSV), Epstein Barr (EBV), Dengue fever, rubella, measles and Venezuelan Equine Encephalitis (VEE) using the ELISA technique. Results: Of the 24 cases examined, 15 (62.5%) were positive. The causative agents for encephalitis were 11 cases of Dengue (45.8%) (p

Abstract: Exanthematic diseases are a group of pathologies caused by viral agents, which appear frequently during the first years of life and respond in greater proportion to infections caused by viruses, such as measles, varicella (chickenpox), rubella (German measles) and dengue, among others. The objective of this study is to evaluate immunity to measles and chickenpox viruses in children and adolescents residing in the Páez municipality, state of Zulia, Venezuela. Without regard to sex, 174 samples from apparently healthy adolescents and children between 8 and 17 years old were studied and analyzed using the ELISA technique. A frequency of 59.7% was detected for the measles virus and 44.8% for varicella. Seroprevalence for measles and varicella was distributed homogeneously in all age groups. For both diseases, greater frequency was observed in males, without significant differences. The study demonstrated low immunity to these viruses and suggests increasing vaccination programs in this municipality to eliminate circulation of these infectious agents in the population. Resumen: Las enfermedades exantemáticas son un grupo de patologías causadas por agentes virales, que se presentan frecuentemente sobre todo durante los primeros años de vida y responden en su mayor proporción a infecciones causadas por virus como sarampión, varicela, rubéola y dengue, entre otros. El objetivo de este estudio fue evaluar la inmunidad a los virus de sarampión y varicela en niños y adolescentes, residentes del municipio Páez del estado Zulia, Venezuela. Se estudiaron 174 muestras provenientes de escolares y adolescentes aparentemente sanos, sin distingo de sexo y en un rango de edad comprendido entre 8 a 17 años, las cuales fueron analizadas mediante la técnica de ELISA. Se detectó una frecuencia de 59,7% para el virus del sarampión y un 44,8% para varicela. La seroprevalencia para sarampión y varicela estuvo homogéneamente distribuida en todos los grupos etarios. En ambas enfermedades se observó una mayor frecuencia en el sexo masculino, no encontrándose diferencias significativas. Se evidencia una baja inmunidad a estos virus, se sugiere incrementar los programas de vacunación en este municipio para eliminar la circulación de estos agentes infecciosos en la población.

Stop-level ridership data serve as a basis for various studies toward increasing bus patronage and promoting sustainable land use planning. To address limitations found in previous studies, this study proposes a novel approach based on Geographically Weighted Principal Component Analysis (GWPCA) and Ordinary Kriging to predict the stop-level boarding or alighting data along bus lines in São Paulo (Brazil), considering four different sampling methods. The main contributions are as follows: by accounting for the spatial heterogeneity of the predictor dataset, the GWPCA can identify the most important factor affecting transit ridership even in bus stops with no information on boarding and alighting; the spatial modeling of stop-level ridership data using GWPCA components as explanatory variables allows visualizing the spatially varying effects from predictors on ridership, supporting the land use planning at a local level; GWPCA coupled with kriging simultaneously addresses the multicollinearity of predictor data, its spatial heterogeneity, and the spatial dependence of the stop-level ridership variable, thus enhancing the goodness-of-fit measures of the transit ridership prediction in unsampled stops; and a balanced sample on predictor data and well-spread in the geographic space might be preferred to accurately estimate missing stop-level ridership data. In addition to solve the lack of stop-level ridership data, supporting a reliable bus system planning, the proposed method indicates what predictors should be addressed by policymakers to stimulate a transit-oriented development. The method can be successfully applied to other travel demand variables facing a lack of data such as traffic volume in road segments and mode choice at the household level., Author(s): Samuel de França Marques (corresponding author) [1]; Cira Souza Pitombo [1]; J. Jaime Gómez-Hernández [2] 1. Introduction Stop-level boarding and alighting data are important pieces of information for decisions [...]