The Economic Value of Residential Land in Historical Areas: An Application of the Residual Method to the Secondary Market

Land value bears significant weight in house prices in historical town centers. An essential aim for regulating the mortgage market, particularly in the financial and property crisis that countries such as Spain are undergoing, is to have at hand objective procedures for its valuation, whatever the conditions (location, construction, planning). Of all the factors contributing to house price make-up, the land is the only one whose value does not depend on acquisition cost, but rather on the location-time binomial. That is to say, the specific circumstances at that point and at the exact moment of valuation. For this reason, the most commonly applied procedure for land valuation in town centers is the use of the residual method: once the selling price of new housing in a district is known, the other necessary costs and expenses of development are deducted, including those of building and the developer’s profit. The value left is that of the land. To apply these procedures it is vital to have figures such as building costs, technical fees, tax costs, etc. But, above all, it is essential to obtain the selling price of the new housing. This is not always feasible, on account of the lack of newbuild development in this location. This shortage of information occurs in historical town cities, where urban renewal is slight due to the heritage-protection policies, and where, nevertheless there is substantial activity in the secondary market. In these circumstances, as an alternative for land valuation in consolidated urban areas, we have the adaptation of the residual method to the particular characteristics of the secondary market. To these ends, there is the proposal for the appreciation of the dwelling which follows, in a backwards direction, the application of traditional depreciation methods proposed by the various valuation manuals and guidelines. The reliability of the results obtained is analyzed by contrasting it with published figures for newly-built properties, according to different rules applied in administrative appraisals in Spain and the incidence of an eventual correction due to conservation state.

An application of the SMS method for imaging designs.

The Simultaneous Multiple Surface (SMS) method in planar geometry (2D) is applied to imaging designs, generating lenses that compare well with aplanatic designs. When the merit function utilizes image quality over the entire field (not just paraxial), the SMS strategy is superior. In fact, the traditional aplanatic approach is actually a particular case of the SMS strategy

Overal reaction rate and stoichiometry for thermal decomposition of hydrazine

An asymptotic analysîs of the Eberstein-Glassman kinetic mechanlsm for the thermal décomposition of hydrazine is carried out. It is shown that at températures near 800°K and near 1000°K,and for hydrazine molar fractions of the order of unity, 10-2 the entire kinetics reduces to a single, overall reaction. Characteristic times for the chemical relaxation of ail active, intermediate species produced in the décomposition, and for the overall reaction, are obtained. Explicit expressions for the overall reaction rate and stoichiometry are given as functions of température, total molar concentration (or pressure)and hydrazine molar fraction. Approximate, patched expressions can then be obtained for values of température and hydrazine molar fraction between 750 and 1000°K, and 1 and 10-3 respectively.

El paralelo. Bosquejo de un método gráfico = The parallel. Sketch of a graphical method

El paralelo gráfico ha sido -y continúa siendo- un excepcional método para conocer, aprender, investigar y difundir la forma arquitectónica y urbana. Aquí intentamos esbozar los principios que rigen su elaboración y echar un leve vistazo a alguno de los jalones de su intensa historia, que merecería una atención más pausada.

Fast modularisation and aomic decomposition of ontologies using axiom dependency hypergraphs

In this paper we define the notion of an axiom dependency hypergraph, which explicitly represents how axioms are included into a module by the algorithm for computing locality-based modules. A locality-based module of an ontology corresponds to a set of connected nodes in the hypergraph, and atoms of an ontology to strongly connected components. Collapsing the strongly connected components into single nodes yields a condensed hypergraph that comprises a representation of the atomic decomposition of the ontology. To speed up the condensation of the hypergraph, we first reduce its size by collapsing the strongly connected components of its graph fragment employing a linear time graph algorithm. This approach helps to significantly reduce the time needed for computing the atomic decomposition of an ontology. We provide an experimental evaluation for computing the atomic decomposition of large biomedical ontologies. We also demonstrate a significant improvement in the time needed to extract locality-based modules from an axiom dependency hypergraph and its condensed version.

Strong Connectivity in Directed Hypergraphs and its Application to the Atomic Decomposition of Ontologies

Los hipergrafos dirigidos se han empleado en problemas relacionados con lógica proposicional, bases de datos relacionales, linguística computacional y aprendizaje automático. Los hipergrafos dirigidos han sido también utilizados como alternativa a los grafos (bipartitos) dirigidos para facilitar el estudio de las interacciones entre componentes de sistemas complejos que no pueden ser fácilmente modelados usando exclusivamente relaciones binarias. En este contexto, este tipo de representación es conocida como hiper-redes. Un hipergrafo dirigido es una generalización de un grafo dirigido especialmente adecuado para la representación de relaciones de muchos a muchos. Mientras que una arista en un grafo dirigido define una relación entre dos de sus nodos, una hiperarista en un hipergrafo dirigido define una relación entre dos conjuntos de sus nodos. La conexión fuerte es una relación de equivalencia que divide el conjunto de nodos de un hipergrafo dirigido en particiones y cada partición define una clase de equivalencia conocida como componente fuertemente conexo. El estudio de los componentes fuertemente conexos de un hipergrafo dirigido puede ayudar a conseguir una mejor comprensión de la estructura de este tipo de hipergrafos cuando su tamaño es considerable. En el caso de grafo dirigidos, existen algoritmos muy eficientes para el cálculo de los componentes fuertemente conexos en grafos de gran tamaño. Gracias a estos algoritmos, se ha podido averiguar que la estructura de la WWW tiene forma de “pajarita”, donde más del 70% del los nodos están distribuidos en tres grandes conjuntos y uno de ellos es un componente fuertemente conexo. Este tipo de estructura ha sido también observada en redes complejas en otras áreas como la biología. Estudios de naturaleza similar no han podido ser realizados en hipergrafos dirigidos porque no existe algoritmos capaces de calcular los componentes fuertemente conexos de este tipo de hipergrafos. En esta tesis doctoral, hemos investigado como calcular los componentes fuertemente conexos de un hipergrafo dirigido. En concreto, hemos desarrollado dos algoritmos para este problema y hemos determinado que son correctos y cuál es su complejidad computacional. Ambos algoritmos han sido evaluados empíricamente para comparar sus tiempos de ejecución. Para la evaluación, hemos producido una selección de hipergrafos dirigidos generados de forma aleatoria inspirados en modelos muy conocidos de grafos aleatorios como Erdos-Renyi, Newman-Watts-Strogatz and Barabasi-Albert. Varias optimizaciones para ambos algoritmos han sido implementadas y analizadas en la tesis. En concreto, colapsar los componentes fuertemente conexos del grafo dirigido que se puede construir eliminando ciertas hiperaristas complejas del hipergrafo dirigido original, mejora notablemente los tiempos de ejecucion de los algoritmos para varios de los hipergrafos utilizados en la evaluación. Aparte de los ejemplos de aplicación mencionados anteriormente, los hipergrafos dirigidos han sido también empleados en el área de representación de conocimiento. En concreto, este tipo de hipergrafos se han usado para el cálculo de módulos de ontologías. Una ontología puede ser definida como un conjunto de axiomas que especifican formalmente un conjunto de símbolos y sus relaciones, mientras que un modulo puede ser entendido como un subconjunto de axiomas de la ontología que recoge todo el conocimiento que almacena la ontología sobre un conjunto especifico de símbolos y sus relaciones. En la tesis nos hemos centrado solamente en módulos que han sido calculados usando la técnica de localidad sintáctica. Debido a que las ontologías pueden ser muy grandes, el cálculo de módulos puede facilitar las tareas de re-utilización y mantenimiento de dichas ontologías. Sin embargo, analizar todos los posibles módulos de una ontología es, en general, muy costoso porque el numero de módulos crece de forma exponencial con respecto al número de símbolos y de axiomas de la ontología. Afortunadamente, los axiomas de una ontología pueden ser divididos en particiones conocidas como átomos. Cada átomo representa un conjunto máximo de axiomas que siempre aparecen juntos en un modulo. La decomposición atómica de una ontología es definida como un grafo dirigido de tal forma que cada nodo del grafo corresponde con un átomo y cada arista define una dependencia entre una pareja de átomos. En esta tesis introducimos el concepto de“axiom dependency hypergraph” que generaliza el concepto de descomposición atómica de una ontología. Un modulo en una ontología correspondería con un componente conexo en este tipo de hipergrafos y un átomo de una ontología con un componente fuertemente conexo. Hemos adaptado la implementación de nuestros algoritmos para que funcionen también con axiom dependency hypergraphs y poder de esa forma calcular los átomos de una ontología. Para demostrar la viabilidad de esta idea, hemos incorporado nuestros algoritmos en una aplicación que hemos desarrollado para la extracción de módulos y la descomposición atómica de ontologías. A la aplicación la hemos llamado HyS y hemos estudiado sus tiempos de ejecución usando una selección de ontologías muy conocidas del área biomédica, la mayoría disponibles en el portal de Internet NCBO. Los resultados de la evaluación muestran que los tiempos de ejecución de HyS son mucho mejores que las aplicaciones más rápidas conocidas. ABSTRACT Directed hypergraphs are an intuitive modelling formalism that have been used in problems related to propositional logic, relational databases, computational linguistic and machine learning. Directed hypergraphs are also presented as an alternative to directed (bipartite) graphs to facilitate the study of the interactions between components of complex systems that cannot naturally be modelled as binary relations. In this context, they are known as hyper-networks. A directed hypergraph is a generalization of a directed graph suitable for representing many-to-many relationships. While an edge in a directed graph defines a relation between two nodes of the graph, a hyperedge in a directed hypergraph defines a relation between two sets of nodes. Strong-connectivity is an equivalence relation that induces a partition of the set of nodes of a directed hypergraph into strongly-connected components. These components can be collapsed into single nodes. As result, the size of the original hypergraph can significantly be reduced if the strongly-connected components have many nodes. This approach might contribute to better understand how the nodes of a hypergraph are connected, in particular when the hypergraphs are large. In the case of directed graphs, there are efficient algorithms that can be used to compute the strongly-connected components of large graphs. For instance, it has been shown that the macroscopic structure of the World Wide Web can be represented as a “bow-tie” diagram where more than 70% of the nodes are distributed into three large sets and one of these sets is a large strongly-connected component. This particular structure has been also observed in complex networks in other fields such as, e.g., biology. Similar studies cannot be conducted in a directed hypergraph because there does not exist any algorithm for computing the strongly-connected components of the hypergraph. In this thesis, we investigate ways to compute the strongly-connected components of directed hypergraphs. We present two new algorithms and we show their correctness and computational complexity. One of these algorithms is inspired by Tarjan’s algorithm for directed graphs. The second algorithm follows a simple approach to compute the stronglyconnected components. This approach is based on the fact that two nodes of a graph that are strongly-connected can also reach the same nodes. In other words, the connected component of each node is the same. Both algorithms are empirically evaluated to compare their performances. To this end, we have produced a selection of random directed hypergraphs inspired by existent and well-known random graphs models like Erd˝os-Renyi and Newman-Watts-Strogatz. Besides the application examples that we mentioned earlier, directed hypergraphs have also been employed in the field of knowledge representation. In particular, they have been used to compute the modules of an ontology. An ontology is defined as a collection of axioms that provides a formal specification of a set of terms and their relationships; and a module is a subset of an ontology that completely captures the meaning of certain terms as defined in the ontology. In particular, we focus on the modules computed using the notion of syntactic locality. As ontologies can be very large, the computation of modules facilitates the reuse and maintenance of these ontologies. Analysing all modules of an ontology, however, is in general not feasible as the number of modules grows exponentially in the number of terms and axioms of the ontology. Nevertheless, the modules can succinctly be represented using the Atomic Decomposition of an ontology. Using this representation, an ontology can be partitioned into atoms, which are maximal sets of axioms that co-occur in every module. The Atomic Decomposition is then defined as a directed graph such that each node correspond to an atom and each edge represents a dependency relation between two atoms. In this thesis, we introduce the notion of an axiom dependency hypergraph which is a generalization of the atomic decomposition of an ontology. A module in the ontology corresponds to a connected component in the hypergraph, and the atoms of the ontology to the strongly-connected components. We apply our algorithms for directed hypergraphs to axiom dependency hypergraphs and in this manner, we compute the atoms of an ontology. To demonstrate the viability of this approach, we have implemented the algorithms in the application HyS which computes the modules of ontologies and calculate their atomic decomposition. In the thesis, we provide an experimental evaluation of HyS with a selection of large and prominent biomedical ontologies, most of which are available in the NCBO Bioportal. HyS outperforms state-of-the-art implementations in the tasks of extracting modules and computing the atomic decomposition of these ontologies.

Effect of type of fiber, site of fermentation, and method of analysis on digestibility of soluble and insoluble fiber in rabbits

The effect of type of fiber, site of fermetation, method for quantifying insoluble and soluble dietary fiber, and their correction for intestinal mucin on fiber digestibility were examined in rabbits. Three diets differing in soluble fiber were formulated (8.5% soluble fiber, on DM basis, in the low soluble fiber [LSF] diet; 10.2% in the medium soluble fiber [MSF] diet; and 14.5% in the high soluble fiber [HSF] diet). They were obtained by replacing half of the dehydrated alfalfa in the MSF diet with a mixture of beet and apple pulp (HSF diet) or with a mix of oat hulls and soybean protein (LSF diet). Thirty rabbits with ileal T-cannulas were used to determine ileal and fecal digestibility. Cecal digestibility was determined by difference between fecal and ileal digestibility. Insoluble fiber was measured as NDF, insoluble dietary fiber (IDF), and in vitro insoluble fiber, whereas soluble fiber was calculated as the difference between total dietary fiber (TDF) and NDF (TDF_NDF), IDF (TDF-IDF), and in vitro insoluble fiber (TDF-in vitro insoluble fiber). The intestinal mucin content was used to correct the TDF and soluble fiber digestibility. Ileal and fecal concentration of mucin increased from the LSF to the HSF diet group (P < 0.01). Once corrected for intestinal mucin, ileal and fecal digestibility of TDF and soluble fiber increased whereas cecal digestibility decreased (P < 0.01). Ileal digestibility of TDF increased from the LSF to the HSF diet group (12.0 vs. 28.1%; P < 0.01), with no difference in the cecum (26.4%), resulting in a higher fecal digestibility from the LSF to the HSF diet group (P < 0.01). Ileal digestibility of insoluble fiber increased from the LSF to the HSF diet group (11.3 vs. 21.0%; P < 0.01), with no difference in the cecum (13.9%) and no effect of fiber method, resulting in a higher fecal digestibility for rabbits fed the HSF diet compared with the MSF and LSF diets groups (P < 0.01).Fecal digestibility of NDF was higher compared with IDF or in vitro insoluble fiber (P < 0.01). Ileal soluble fiber digestibility was higher for the HSF than for the LSF diet group (43.6 vs. 14.5%; P < 0.01) and fiber method did not affect it. Cecal soluble fiber digestibility decreased from the LSF to the HSF diet group (72.1 vs. 49.2%; P < 0.05). The lowest cecal and fecal soluble fiber digestibility was measured using TDF-NDF (P < 0.01). In conclusion, a correction for intestinal mucin is necessary for ileal TDF and soluble fiber digestibility whereas the selection of the fiber method has a minor relevance. The inclusion of sugar beet and apple pulp increased the amount of TDF fermented in the small intestine.

Application of the Boundary Method to the determination of the properties of the beam cross-sections

Using the 3-D equations of linear elasticity and the asylllptotic expansion methods in terms of powers of the beam cross-section area as small parameter different beam theories can be obtained, according to the last term kept in the expansion. If it is used only the first two terms of the asymptotic expansion the classical beam theories can be recovered without resort to any "a priori" additional hypotheses. Moreover, some small corrections and extensions of the classical beam theories can be found and also there exists the possibility to use the asymptotic general beam theory as a basis procedure for a straightforward derivation of the stiffness matrix and the equivalent nodal forces of the beam. In order to obtain the above results a set of functions and constants only dependent on the cross-section of the beam it has to be computed them as solutions of different 2-D laplacian boundary value problems over the beam cross section domain. In this paper two main numerical procedures to solve these boundary value pf'oblems have been discussed, namely the Boundary Element Method (BEM) and the Finite Element Method (FEM). Results for some regular and geometrically simple cross-sections are presented and compared with ones computed analytically. Extensions to other arbitrary cross-sections are illustrated.