The role of earthworms in nitrogen release from herbage residues : a thesis presented in partial fulfilment of the requirements for the degree of Master of Agricultural Science in Soil Science at Massey University

Decomposition and nutrient release from pasture litter were examined in two biotic systems; either with or without large organisms ("macrobes"). Earthworms were the test macrobe and nitrogen (N) the test nutrient. This experiment addressed the hypothesis that consumption of herbage residues by macrobes, as opposed to microbes, should result in more of the contained N becoming available for uptake by plants or for loss processes, because macrobes oxidise a greater proportion of the contained carbon (C) by energetics. Earthworms influenced both soil metabolism and mineral N availability, irrespective of litter type (ryegrass or clover) and temperature (15 or 22.5 C). Carbon dioxide evolution and oxygen consumption increased by 26% and 39%, respectively, in the presence of earthworms. After an 11-week incubation about 50% more mineral N was recorded in the soils containing earthworms. Moreover, less microbial biomass was recorded in the presence of worms. This influence of macrobes carried over into a subsequent, exhaustive cropping experiment, using ryegrass as the test plant. Where soils had been previously influenced by earthworms, there was a significant increase in plant growth and N uptake. Carbon dioxide evolved during incubation was highly correlated with soil mineral N (r= 0.84** ) present at the conclusion of incubation, and also with subsequent plant dry matter yield (r= 0.75** ) and plant N yield (r=0.85** ). The link between elaborated C and contained N has long been recognised as providing stability to organic residues in soils. In the design of this experiment, other influences of macrobes (e.g. mixing or structural influences) were largely obviated, so one can conclude that nitrogen availability was increased primarily through carbon respiration by the macrobial population. These results offer a fresh perspective on the balance between mineralisation and immobilisation in the soil-plant complex and, hence, on the dynamics of nutrients contained in organic matter. Better understanding of these relationships may allow improved management of the dynamics of soil organic matter in temperate grassland ecosystems

OPTIMAL FISCAL POLICY IN A BUSINESS CYCLE MODEL: ALTERNATIVE IDENTIFICATIONS OF THE OPTIMAL EXPOST CAPITAL INCOME TAX RATES

This paper deals with the indeterminacy of optimal fiscal policy treated by Zhu (1992) and Chari, Christiano and Kehoe (1994). These authors identify the optimal fiscal policy restricting the debt return to be uncontingent to the state of nature. In this paper we use other kind of restrictions in order to identify the optimal fiscal policy. Using the solution method proposed by Sims (1998), we can select an equilibrium by enforcing a stable path for the bonds allocation, to identify all the fiscal policy variables contingent to the state of nature. We also use a decomposition of the expectational terms that allow us to obtain the ex-ante capital income tax rate in order to be compared with the ex-post (contingent) tax rate. We can demonstrate that the risk aversion changes the relationship between the expectational errors of the private agents and the sources of fluctuations. The numerical simulation provides some different results: the optimal tax rate on capital incom e is constant, instead of the very volatile tax rate obtained by Chari, Christiano and Kehoe (1994). This property remains unaltered when we use alternative restrictions (exogenous debt path and exogenous expectational errors) to identify the contingent optimal fiscal policy.

Estudi i optimització de l'oferta al Mercat Ibèric d'Electricitat (MIBEL)

Estudi de les ofertes reals de les companyies productores d'energia elèctrica a MIBEL i comparació de dos models alternatius de optimització de l'oferta.La nostra feina durant aquest PFC ha estat entendre el funcionament del mercat ibèric d'electricitat i fer un estudi complet de la seva oferta. Posteriorment, hem utilitzat dos models diferents d'optimització per trobar l'oferta òptima i a la vegada, veure quin d'aquests dos models és més eficient

History of a Letter

What follows is the epilogue to the book Fuego de puro amor: mensajes desde la Resistencia (Santiago: Cinco Ases, 2021) reproduced with the generous permission of its editor, Axel Pickett Lazo, and the author, Camila Krauss Ruz. It is dedicated to all the executed political prisoners of Chile’s civil-military dictatorship. —TH & G

Descubriendo Patrones Craneofaciales Usando Datos Cefalométricos Multivariados para la Toma de Decisiones en Ortodoncia

Indexación: Web of Science; Scielo.The aim was to find craniofacial morphology patterns in a multivariate cephalometric database using a clustering technique. Cephalometric analysis was performed in a sample of 100 teleradiographs collected from Chilean orthodontic patients. Thirty cephalometric measurements were taken from commonly used analysis. The computed variables were used to perform a clustering analysis with the k-means algorithm to identify patterns of craniofacial morphology. The J48 decision tree was used to analyze each cluster, and the ANOVA test to determine the statistical differences between the clusters. Four clusters were found that had significant differences (P<0.001) in 24 of the 30 variables studied, suggesting that they represent different patterns of craniofacial form. Using the decision tree, 8 of the 30 variables appeared to be relevant for describing the clusters. The clustering analysis is effective in identifying different craniofacial patterns based on a multivariate database. The distinct clusters appear to be caused by differences in the compensation process of the facial structure responding to a genetically determined cranial and mandible form. The proposed method can be applied to several databases, creating specific classifications for each one of them. KEY WORDS: Craniofacial patterns; Morphological patterns; Clustering technique; Orthodontics.RESUMEN: El objetivo fue encontrar patrones morfológicos craneofaciales, a partir de una base de datos cefalométricos multivariada, utilizando una técnica de clustering. Se realizó un análisis cefalométrico a una muestra de 100 telerradiografías pertenecientes a pacientes chilenos de ortodoncia. Treinta medidas cefalométricas obtenidas de los análisis más utilizados fueron registradas. Las variables computadas se utilizaron para realizar un análisis de clustering con el algoritmo k-medias, para identificar patrones de morfología craneofacial. El árbol de decisión J48 se utilizó para analizar cada cluster, y test de ANOVA para determinar diferencias estadísticamente significativas entre los clusters. Se encontraron cuatro clusters con diferencia estadísticamente significativas (p<0,001) en 24 de las 30 variables estudiadas, lo que sugiere que efectivamente corresponden a diferentes patrones craneofaciales. Utilizando el árbol de decisión, se pudo determinar que 8 de las 30 variables resultaron ser relevantes en la definición de los clusters. El análisis de clustering es efectivo en identificar patrones morfológicos craneofaciales usando una base de datos multivariada. Los distintos cluster encontrados, aparentemente se formarían a partir de diferencias en el proceso de compensación de la estructura facial, en respuesta a la forma mandibular genéticamente determinada. El método propuesto puede ser aplicado a múltiples bases de datos, creando clasificaciones específicas para cada una de ellas. PALABRAS CLAVE: Patrones craneofaciales; Patrones morfológicos; Técnica de clustering; Ortodoncia.http://ref.scielo.org/qdkkz

How a General-Purpose Commonsense Ontology can Improve Performance of Learning-Based Image Retrieval

The knowledge representation community has built general-purpose ontologies which contain large amounts of commonsense knowledge over relevant aspects of the world, including useful visual information, e.g.: "a ball is used by a football player", "a tennis player is located at a tennis court". Current state-of-the-art approaches for visual recognition do not exploit these rule-based knowledge sources. Instead, they learn recognition models directly from training examples. In this paper, we study how general-purpose ontologies---specifically, MIT's ConceptNet ontology---can improve the performance of state-of-the-art vision systems. As a testbed, we tackle the problem of sentence-based image retrieval. Our retrieval approach incorporates knowledge from ConceptNet on top of a large pool of object detectors derived from a deep learning technique. In our experiments, we show that ConceptNet can improve performance on a common benchmark dataset. Key to our performance is the use of the ESPGAME dataset to select visually relevant relations from ConceptNet. Consequently, a main conclusion of this work is that general-purpose commonsense ontologies improve performance on visual reasoning tasks when properly filtered to select meaningful visual relations.Comment: Accepted in IJCAI-1

History of cosmic evolution with modified Gauss-Bonnet-dilatonic coupled term

Gauss-Bonnet-dilatonic coupling in four dimension plays an important role to explain late time cosmic evolution. However, this term is an outcome of low energy string effective action and thus ought to be important in the early universe too. Unfortunately, phase-space formulation of such a theory does not exist in the literature due to branching. We therefore consider a modified theory of gravity, which contains a nonminimally coupled scalar-tensor sector in addition to higher order scalar curvature invariant term with Gauss-Bonnet-dilatonic coupling. Such an action unifies early inflation with late-time cosmic acceleration. Quantum version of the theory is also well-behaved.Comment: 13 pages, 5 figures, To appear in EPJC (2017