Statistical Methodology for Evaluating Process-Based Climate Models

In climatology, there are mainly two types of models used, that is, global circulation/climate models (GCMs) and regional climate models (RCMs). GCMs can be run for the whole globe, while RCMs can be run only for a part of the globe. In this chapter, we provided a general statistical methodology for evaluating process-based (GCM or RCM) climate models. To bridge observed and simulated data sets, statistical bias correction was implemented. A meta-analysis technique is used for selecting a model or scenarios, which have good performance compared to others. For model selection and ensemble projection, Bayesian model averaging (BMA) is used. Posterior inclusion probability (PIP) is used as model selection criterion. Our analysis concluded with a list of best models for maximum, minimum temperature, and precipitation where the rank of the selected models is not the same for the listed three variables. The outputs of BMA closely followed the pattern of observed data; however, it underestimated the variability. To overcome this issue, 90% prediction interval was calculated, and it showed that almost all the observed data are within these intervals. The results of Taylor diagram show that the BMA projected data are better than the individual GCMs’ outputs

A User-Guided Bayesian Framework for Ensemble Feature Selection in Life Science Applications (UBayFS)

Feature selection represents a measure to reduce the complexity of high-dimensional datasets and gain insights into the systematic variation in the data. This aspect is of specific importance in domains that rely on model interpretability, such as life sciences. We propose UBayFS, an ensemble feature selection technique embedded in a Bayesian statistical framework. Our approach considers two sources of information: data and domain knowledge. We build a meta-model from an ensemble of elementary feature selectors and aggregate this information in a multinomial likelihood. The user guides UBayFS by weighting features and penalizing specific feature blocks or combinations, implemented via a Dirichlet-type prior distribution and a regularization term. In a quantitative evaluation, we demonstrate that our framework (a) allows for a balanced trade-off between user knowledge and data observations, and (b) achieves competitive performance with state-of-the-art methods

Functionalization of Ti-40Nb implant material with strontium by reactive sputtering

Background: Surface functionalization of orthopedic implants with pharmaceutically active agents is a modern approach to enhance osseointegration in systemically altered bone. A local release of strontium, a verified bone building therapeutic agent, at the fracture site would diminish side effects, which could occur otherwise by oral administration. Strontium surface functionalization of specially designed titanium-niobium (Ti-40Nb) implant alloy would provide an advanced implant system that is mechanically adapted to altered bone with the ability to stimulate bone formation. Methods: Strontium-containing coatings were prepared by reactive sputtering of strontium chloride (SrCl2) in a self-constructed capacitively coupled radio frequency (RF) plasma reactor. Film morphology, structure and composition were investigated by scanning electron microscopy (SEM), time of flight secondary ion mass spectrometry (ToF-SIMS) and X-ray photoelectron spectroscopy (XPS). High-resolution transmission electron microscopy (HR-TEM) was used for the investigation of thickness and growth direction of the product layer. TEM lamellae were prepared using the focused ion beam (FIB) technique. Bioactivity of the surface coatings was tested by cultivation of primary human osteoblasts and subsequent analysis of cell morphology, viability, proliferation and differentiation. The results are correlated with the amount of strontium that is released from the coating in biomedical buffer solution, quantified by inductively coupled plasma mass spectrometry (ICP-MS). Results: Dense coatings, consisting of SrOxCly, of more than 100 nm thickness and columnar structure, were prepared. TEM images of cross sections clearly show an incoherent but well-structured interface between coating and substrate without any cracks. Sr2+ is released from the SrOxCly coating into physiological solution as proven by ICP-MS analysis. Cell culture studies showed excellent biocompatibility of the functionalized alloy. Conclusions: Ti-40Nb alloy, a potential orthopedic implant material for osteoporosis patients, could be successfully plasma coated with a dense SrOxCly film. The material performed well in in vitro tests. Nevertheless, the Sr2+ release must be optimized in future work to meet the requirements of an effective drug delivery system

ARBOLES DE SOMBRA E INTENSIDAD DEL CULTIVO AFECTAN EL RENDIMIENTO DE CAFÉ (Coffea arabica L.) Y LA VALORACIÓN ECOLÓGICA EN MASATEPE, NICARAGUA

The study was carried out in the community of Masatepe, department of Masaya, Nicaragua where in 2000 a longterm coffee experiment was established with two repetitions in the Centro de Capacitación y Servicios Regionales del Café del Pacífico Sur (Jardín Botánico) part of the Unión Nicaragüense de Cafetaleros (UNICAFE) and a third repetition in the Centro Experimental de Campos Azules (CECA) of the INTA. The purpose of the research was to study the production, yield and quality of green coffee under the influence from different shade types and levels of fertilization and their correlation. Another purpose was to investigate the effect of the different agro ecosystems on the environmental conditions. Predominantly the production is less with cultivation under shade but it offers better conversion from cherries to green coffee and quality compared to cropping systems with full sun. Also the different shade tree species affect both production and environmental services. Coffee cultivation with regulated shade cover and adequate tree species combined with organic fertilization can achieve the same production level as cultivation at full sun with synthetic fertilizers. The combination of Simarouba glauca/Tabebuia rosea (SGTR) and the intensive organic fertilization results as the best treatment regarding the principal variables with an average production of 2674 kg oro ha-1 in the fifth crop (higher even than the full sun with a high level of synthetic fertilization). Furthermore, this kind of agroforestry system with regulated shade improves the quality and the conditions of the ecosystems and creates additional value from the shade trees (wood, firewood, fruits) and payments for environmental services. The shade SGTR offered the best conditions for the environment and the conservation of the soil, but with respect to the capture of carbon dioxide, with shade from Simanea saman + Inga laurina surpasses the other treatments containing 92.4 t C ha-1 against only 24.4 t C ha-1 in SGTR, or 4.7 t C ha-1 in full sun coffee. Further investigations should focus on effect, benefit and ecological value of different shade tree species and their influence in the cup quality, also considering different altitudes. In addition greater awareness of the ecological issues needs to be developed from the farmer up to the consumer. DOI: http://dx.doi.org/10.5377/calera.v11i17.776 La Calera Vol.11 No.17, p.41-47En el año 2000 se establecieron dos repeticiones de un ensayo de café, en el Centro de Capacitación y Servicios Regionales del Café del Pacífico Sur – UNICAFE; una tercera repetición fue establecida en el año 2001 en el Centro Experimental Campos Azules (CECA) del INTA, en el Municipio de Masatepe, departamento de Masaya, Nicaragua. El propósito general del ensayo fue evaluar la influencia de diferentes tipos de sombra: Simaruba glauca + Tabebuia rosea (SGTR), Simaruba glauca + Inga laurina (SGIL), Samanea Saman + Tabebuia Rosea (SSTR), Inga laurina + Samanea saman (ILSG) y un cafetal a Pleno sol (PS), con dos niveles de insumo Convencional intensivo (CI) y Convencional moderado (CM), sobre la producción y rendimiento de café oro y la valoraron de los servicios ambientales como Biodiversidad, Captura de carbono, Conservación de suelo y de agua. Además, se incluyeron los tratamientos orgánico intensivo (OI) y Orgánico moderado (OM). Se determinó que la sombra afectó la producción de café oro, pero mejoró el rendimiento en comparación al cultivo a pleno sol. La combinación de sombra de SGTR interactuando con las aplicaciones de insumos orgánicos intensivos, registró mejor producción promedio (2674 kg oro ha-1) de la cosecha 5, superando al tratamiento a pleno sol con uso de insumos convencionales intensivo. Cafetales bajo especies arbóreas y nivel de sombra adecuada con un manejo orgánico intensivo pueden llegar a la misma producción que el cultivo a pleno sol con un tratamiento intensivo convencional. Adicional a esto, los sistemas con sombra mejoran la calidad y las condiciones ecológicas, también agregan valor por la madera, leña y frutos producidos y/o el pago por los servicios ambientales. El tratamiento SGTR brindó las mejores condiciones de hábitat y conservación de suelo, sin embargo, respecto a la fijación de carbono la combinación SSIL fue superior (24.41 SGTR vs 92.64 SSIL). Futuras investigaciones deberán evaluar más detalles sobre el efecto, uso y valor ecológico de especies de sombra y su influencia particular en la calidad en taza a diversas altitudes. DOI: http://dx.doi.org/10.5377/calera.v11i17.776 La Calera Vol.11 No.17, p.41-4

Geo-additive modelling of malaria in Burundi

Abstract Background Malaria is a major public health issue in Burundi in terms of both morbidity and mortality, with around 2.5 million clinical cases and more than 15,000 deaths each year. It is still the single main cause of mortality in pregnant women and children below five years of age. Because of the severe health and economic burden of malaria, there is still a growing need for methods that will help to understand the influencing factors. Several studies/researches have been done on the subject yielding different results as which factors are most responsible for the increase in malaria transmission. This paper considers the modelling of the dependence of malaria cases on spatial determinants and climatic covariates including rainfall, temperature and humidity in Burundi. Methods The analysis carried out in this work exploits real monthly data collected in the area of Burundi over 12 years (1996-2007). Semi-parametric regression models are used. The spatial analysis is based on a geo-additive model using provinces as the geographic units of study. The spatial effect is split into structured (correlated) and unstructured (uncorrelated) components. Inference is fully Bayesian and uses Markov chain Monte Carlo techniques. The effects of the continuous covariates are modelled by cubic p-splines with 20 equidistant knots and second order random walk penalty. For the spatially correlated effect, Markov random field prior is chosen. The spatially uncorrelated effects are assumed to be i.i.d. Gaussian. The effects of climatic covariates and the effects of other spatial determinants are estimated simultaneously in a unified regression framework. Results The results obtained from the proposed model suggest that although malaria incidence in a given month is strongly positively associated with the minimum temperature of the previous months, regional patterns of malaria that are related to factors other than climatic variables have been identified, without being able to explain them. Conclusions In this paper, semiparametric models are used to model the effects of both climatic covariates and spatial effects on malaria distribution in Burundi. The results obtained from the proposed models suggest a strong positive association between malaria incidence in a given month and the minimum temperature of the previous month. From the spatial effects, important spatial patterns of malaria that are related to factors other than climatic variables are identified. Potential explanations (factors) could be related to socio-economic conditions, food shortage, limited access to health care service, precarious housing, promiscuity, poor hygienic conditions, limited access to drinking water, land use (rice paddies for example), displacement of the population (due to armed conflicts).</p