4 research outputs found
The influence of C₃ and C₄ vegetation on soil organic matter dynamics in contrasting semi-natural tropical ecosystems
No full textVariations in the carbon isotopic composition of soil organic matter (SOM) in bulk and fractionated samples were used to assess the influence of C3 and C4 vegetation on SOM dynamics in semi-natural tropical ecosystems sampled along a precipitation gradient in West Africa. Differential patterns in SOM dynamics in C3/C4 mixed ecosystems occurred at various spatial scales. Relative changes in C / N ratios between two contrasting SOM fractions were used to evaluate potential site-scale differences in SOM dynamics between C3- and C4-dominated locations. These differences were strongly controlled by soil texture across the precipitation gradient, with a function driven by bulk δ13C and sand content explaining 0.63 of the observed variability. The variation of δ13C with soil depth indicated a greater accumulation of C3-derived carbon with increasing precipitation, with this trend also being strongly dependant on soil characteristics. The influence of vegetation thickening on SOM dynamics was also assessed in two adjacent, but structurally contrasting, transitional ecosystems occurring on comparable soils to minimise the confounding effects posed by climatic and edaphic factors. Radiocarbon analyses of sand-size aggregates yielded relatively short mean residence times (τ) even in deep soil layers, while the most stable SOM fraction associated with silt and clay exhibited shorter τ in the savanna woodland than in the neighbouring forest stand. These results, together with the vertical variation observed in δ13C values, strongly suggest that both ecosystems are undergoing a rapid transition towards denser closed canopy formations. However, vegetation thickening varied in intensity at each site and exerted contrasting effects on SOM dynamics. This study shows that the interdependence between biotic and abiotic factors ultimately determine whether SOM dynamics of C3- and C4-derived vegetation are at variance in ecosystems where both vegetation types coexist. The results highlight the far-reaching implications that vegetation thickening may have for the stability of deep SOM. Â © Author(s) 2015
Brucellosis in dairy herds: a public health concern in the milk supply chains of West and Central Africa
No full textTen herd-level cross-sectional studies were conducted in peri-urban dairy production areas of seven West and Central African countries (Burkina Faso, Burundi, Cameroon, Mali, Niger, Senegal and Togo). The objectives were to estimate herd level Brucella spp. seroprevalence and identify risk factors for seropositivity.
In each of the ten study areas, herds (between 52 and 142 per area, total = 965) were selected probabilistically and a structured questionnaire was administered to gather information on their structure and management. A bulk milk sample from each herd was tested by indirect ELISA for Brucella spp. For each area, herd seroprevalence estimates were obtained after adjusting for the assumed performance of the diagnostic test. Herd level risk factors for Brucella spp. seropositivity were identified by means of stratified logistic regression, with each peri-urban zone as a stratum. Area-specific models were also explored.
Estimated herd seroprevalences were: Lomé (Togo) 62.0% (95% CI:55.0-69.0), Bamako (Mali) 32.5% (95% CI:28.0-37.0), Bujumbura (Burundi) 14.7% (95%CI:9.4-20.8), Bamenda (Cameroon) 12.6% (95% CI:7.6-21.9), Ouagadougou (Burkina Faso) 3.0% (95% CI:1.0-9.1), Ngaoundere (Cameroon) 2.3% (95% CI:1.0-7.0), Thies (Senegal) 1.3% (95% CI:0.1, 5.3), Niamey (Niger) 1.2% (95% CI:0.08-5.3), Dakar (Senegal) 0.2% (95% CI:0.01-1.7) and Niakhar (Senegal) <0.04%. Logistic regression modelling revealed transhumant herds to be at lower risk of infection (adjusted OR: 0.25, 95% CI: 0.13 - 0.5) and in one of the areas (Bamenda), regular purchase of new animals was found to be strongly associated with Brucella spp. seropositivity (adjusted OR = 5.3, 95% CI: 1.4-25.9). Our findings confirm that Brucella spp. circulates among dairy cattle supplying milk to urban consumers in West and Central Africa, posing a serious public health concern. Control programs are urgently needed in areas such as Lomé or Bamako, where more than 30% of the herds show evidence of infection
Modelado y simulación de sistemas fotovoltaicos bajo condiciones de sombreado parcial
No full textgraficas, tablasThis thesis introduces a methodology for modeling commercial photovoltaic panels at the cell
level operating under partial shading conditions. In the first part, a review of the literature
is presented, focusing on the proper representation of the current-voltage characteristics in
both forward and reverse bias, the mathematical formulation, the circuit model, and the
estimation of parameters for photovoltaic cells.
In the second part, the single diode model (SDM), the direct-reverse model (DRM), and
Bishop’s model are introduced, emphasizing their current-voltage relationship, mathematical
formulation, circuit model, and parameter requirements.
In the third part of the thesis, a procedure to obtain I-V curves in panel terminals without
the need for any physical intervention is detailed. This procedure is necessary to compare
the behavior of the three models analyzed in both quadrants. The procedure requires a panel
without a bypass diode and measurement equipment capable of acquiring current, voltage,
temperature, and irradiation.
After considering the evaluation of some metrics such as root mean square error (RMSE)
and mean absolute percentage error (MAPE), Bishop’s model is selected for use in the
methodology.
In the fourth part, a methodology to estimate the parameters of Bishop’s model is proposed, which formulates the estimation of the parameters as an optimization problem. The metho-
dology uses a genetic algorithm, and it is validated using information from two commercial
panels. The curve reconstructions for each technology are evaluated using metrics such as
RMSE and MAPE to assess the accuracy of the models (Texto tomado de la fuente)Esta tesis presenta una metodología de modelado de paneles fotovoltaicos comerciales a nivel
de celda operando bajo condiciones de sombreado parcial. En la primera parte se realiza
una revisión de la literatura sobre la representación de celdas fotovoltaicas, en la que se
consideran características importantes como la formulación matemática, el modelo circuital,
la representación apropiada del comportamiento en modo directo e inverso y la estimación
de parámetros.
En la segunda parte, se exponen algunos de los modelos m ́as utilizados en la literatura para
el modelado de celdas fotovoltaicas, Modelo de un solo diodo (SDM), Modelo DRM y el
modelo de Bishop, prestando especial atención a la relación corriente-voltaje, la formulación
matemática, el modelo circuital y los parámetros necesarios para su evaluación. Para modelar
los paneles a nivel de celda, la tercera parte se enfoca en detallar un procedimiento para
obtener las curvas I-V en terminales de un panel, sin necesidad de ninguna intervención
física. Para lo se requiere un panel sin diodo de bypass, información del panel obtenida al
sombrear el panel y algunos equipos de medida que permitan adquirir corriente, voltaje,
temperatura e irradiación.
En la tercera parte de la tesis se detalla un procedimiento para obtener curvas I-V en terminales del panel sin necesidad de intervención física alguna. Este procedimiento es necesario
para comparar el comportamiento de los tres modelos analizados en ambos cuadrantes. El
procedimiento requiere un panel sin diodo de derivación y un equipo de medición capaz de
adquirir corriente, voltaje, temperatura e irradiación.
Después de considerar la evaluación de algunas métricas como el error cuadrático medio
(RMSE) y el error porcentual absoluto medio (MAPE), se selecciona el modelo de Bishop
para su uso en la metodología.
En la cuarta parte, se propone una metodología para estimar los parámetros del modelo de
Bishop, formulando el problema de estimación de parámetros como un problema de optimización. La metodología utiliza un algoritmo genético y se valida con información de dos
paneles comerciales. Las reconstrucciones de curvas para cada tecnología se evalúan utilizando métricas como RMSE y MAPE para evaluar la precisión de los modelos.DoctoradoDoctor en IngenieríaEléctrica, Electrónica, Automatización Y Telecomunicaciones.Sede Manizale
