SnO2 nanocrystals synthesized by microwave-assisted hydrothermal method: towards a relationship between structural and optical properties

The exploration of novel synthetic methodologies that control both size and shape of functional nanostructure opens new avenues for the functional application of nanomaterials. Here, we report a new and versatile approach to synthesize SnO2 nanocrystals (rutile-type structure) using microwave-assisted hydrothermal method. Broad peaks in the X-ray diffraction spectra indicate the nanosized nature of the samples which were indexed as a pure cassiterite tetragonal phase. Chemically and physically adsorbed water was estimated by TGA data and FT-Raman spectra to account for a new broad peak around 560 cm(-1) which is related to defective surface modes. In addition, the spherical-like morphology and low dispersed distribution size around 3-5 nm were investigated by HR-TEM and FE-SEM microscopies. Room temperature PL emission presents two broad bands at 438 and 764 nm, indicating the existence of different recombination centers. When the size of the nanospheres decreases, the relative intensity of 513 nm emission increases and the 393 nm one decreases. UV-Visible spectra show substantial changes in the optical absorbance of crystalline SnO2 nanoparticles while the existence of a small tail points out the presence of localized levels inside the forbidden band gap and supplies the necessary condition for the PL emission.

Morphogenetic and structural characteristics of guinea grass tillers at different ages under intermittent stocking

The objective of this research was to assess morphogenetic and structural characteristics of tillers of guinea grass cv. Tanzania at different ages. The pastures of guinea grass were managed in six pasture conditions related to the combination of three frequencies (90, 95, and 99% light interception) and two post-grazing heights (25 and 50 cm). In these six pastures conditions, three tiller ages were evaluated (young, mature, and old). The design was of completely randomized block with three replications. Young tillers exhibited higher leaf appearance rate and leaf elongation rate and, consequently, higher final leaf length and number of live leaves than mature and old tillers, regardless of the pasture condition. On pastures managed with 90 or 95% light interception associated with a post-grazing height of 25 cm, old tillers presented longer leaf lifespan than young and mature ones. There is a progressive reduction in the vigor of growth of pastures of guinea grass cv. Tanzania with advancing tiller age.

The Effect of Preservative Interventions on the Chemical- Physical and Structural Characteristics of Panel Painting

This work studies the impact of two traditional Romanian treatments, Red Petroleum and Propolis, in terms of real efficiency and consequence on the wooden artifacts. The application of these solutions is still a widely adopted and popular technique in preservative conservation but the impact of these solutions is not well known. It is important to know the effect of treatments on chemical-physical and structural characteristics of the artifacts, not only for understanding the influence on present conditions but also for foreseeing the future behavior. These treatments with Romanian traditional products are compared with a commercial antifungal product, Biotin R, which is utilized as reference to control the effectiveness of Red Petroleum and Propolis. Red Petroleum and Propolis are not active against mould while Biotin R is very active. Mould attack is mostly concentrated in the painted layer, where the tempera, containing glue and egg, enhance nutrition availability for moulds. Biotin R, even if is not a real insecticide but a fungicide, was the most active product against insect attack of the three products, followed by Red Petroleum, Propolis and untreated reference. As for colour, it did not change so much after the application of Red Petroleum and Biotin R and the colour difference was almost not perceptible. On the contrary, Propolis affected the colour a lot. During the exposure at different RH, the colour changes significantly at 100% RH at equilibrium and this is mainly due to the mould attack. Red Petroleum penetrates deeply into wood, while Propolis does not penetrate and remains only on the surface. However, Red Petroleum does not interact chemically with wood substance and it is easy volatilized in oven-dry condition. On the contrary Propolis interacts chemically with wood substance and hardly volatilized, even in oven-dry condition and consequently Propolis remains where it penetrated, mostly on the surface. Treatment by immersion has impact on wood physical parameters while treatment by brushing does not have significant impact. Especially Red Petroleum has an apparent impact on moisture content (MC) due to the penetration of solution, while Propolis does not penetrate so much and remains only on surface therefore Propolis does not have so much impact as Red Petroleum. However, if the weight of the solution penetrated in wood is eliminated, there is not significant difference in MC between treated and untreated samples. Considering physical parameters, dimensional stability is an important parameter. The variation of wood moisture content causes shrinkages/swelling of the wood that polychrome layer can only partially follow. The dimension of wooden supports varied under different moisture conditioning; the painted layer cannot completely follow this deformation, and consequently a degradation and deterioration caused by detachment, occurs. That detachment affects the polychrome stratification of the panel painting and eventually the connections between the different layer compositions of the panel painting.

Essays in structural heuristics

This dissertation introduces and develops a new method of rational reconstruction called structural heuristics. Structural heuristics takes assignment of structure to any given object of investigation as the starting point for its rational reconstruction. This means to look at any given object as a system of relations and of transformation laws for those relations. The operational content of this heuristics can be summarized as follows: when facing any given system the best way to approach it is to explicitly look for a possible structure of it. The utilization of structural heuristics allows structural awareness, which is considered a fundamental epistemic disposition, as well as a fundamental condition for the rational reconstruction of systems of knowledge. In this dissertation, structural heuristics is applied to reconstructing the domain of economic knowledge. This is done by exploring four distinct areas of economic research: (i) economic axiomatics; (ii) realism in economics; (iii) production theory; (iv) economic psychology. The application of structural heuristics to these fields of economic inquiry shows the flexibility and potential of structural heuristics as epistemic tool for theoretical exploration and reconstruction.

Boundary condition identification of a bridge pier using experimental data and FEM modal updating

Over the past twenty years, new technologies have required an increasing use of mathematical models in order to understand better the structural behavior: finite element method is the one mostly used. However, the reliability of this method applied to different situations has to be tried each time. Since it is not possible to completely model the reality, different hypothesis must be done: these are the main problems of FE modeling. The following work deals with this problem and tries to figure out a way to identify some of the unknown main parameters of a structure. This main research focuses on a particular path of study and development, but the same concepts can be applied to other objects of research. The main purpose of this work is the identification of unknown boundary conditions of a bridge pier using the data acquired experimentally with field tests and a FEM modal updating process. This work doesn’t want to be new, neither innovative. A lot of work has been done during the past years on this main problem and many solutions have been shown and published. This thesis just want to rework some of the main aspects of the structural optimization process, using a real structure as fitting model.

Dissecting Carotenoid from Structural Components of Carotenoid-Based Coloration: A Field Experiment with Great Tits (Parus major)

Carotenoid-based yellowish to red plumage colors are widespread visual signals used in sexual and social communication. To understand their ultimate signaling functions, it is important to identify the proximate mechanism promoting variation in coloration. Carotenoid-based colors combine structural and pigmentary components, but the importance of the contribution of structural components to variation in pigment-based colors (i.e., carotenoid-based colors) has been undervalued. In a field experiment with great tits (Parus major), we combined a brood size manipulation with a simultaneous carotenoid supplementation in order to disentangle the effects of carotenoid availability and early growth condition on different components of the yellow breast feathers. By defining independent measures of feather carotenoid content (absolute carotenoid chroma) and background structure (background reflectance), we demonstrate that environmental factors experienced during the nestling period, namely, early growth conditions and carotenoid availability, contribute independently to variation in yellow plumage coloration. While early growth conditions affected the background reflectance of the plumage, the availability of carotenoids affected the absolute carotenoid chroma, the peak of maximum ultraviolet reflectance, and the overall shape, that is, chromatic information of the reflectance curves. These findings demonstrate that environment-induced variation in background structure contributes significantly to intraspecific variation in yellow carotenoid-based plumage coloration.

Deregulation and Structural Change in the U.S. Commercial Banking Industry

Regulatory change not seen since the Great Depression swept the U.S. banking industry beginning in the early 1980s and culminated with the Interstate Banking and Branching Efficiency Act of 1994. Banking analysts anticipated dramatic consolidation with large numbers of mergers and acquisitions. Some expressed concern about the long-term health of the smaller community banks. This paper describes and discusses the actual evolution of the U.S. banking industry over the past two decades, using the 1976 to 1998 Report of Condition and Income (Call Report) and merger data recently posted on the web site of the Federal Reserve Bank of Chicago. Among several results, more permissive interstate banking and branching regulation significantly associates with higher merger rates, with lower net entry rates, and with higher concentration within states. Interestingly, more permissive intrastate banking and branching regulation only associates with higher concentration.

Multimodal integration of functional and structural brain connectivity. An application to the characterization of Mild Cognitive Impairment

La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

Application of PZT and FBG impedance sensors for structural health monitoring of reinforced concrete beams strengthened with FRP composite materials

Esta Tesis tiene como objetivo principal el desarrollo de métodos de identificación del daño que sean robustos y fiables, enfocados a sistemas estructurales experimentales, fundamentalmente a las estructuras de hormigón armado reforzadas externamente con bandas fibras de polímeros reforzados (FRP). El modo de fallo de este tipo de sistema estructural es crítico, pues generalmente es debido a un despegue repentino y frágil de la banda del refuerzo FRP originado en grietas intermedias causadas por la flexión. La detección de este despegue en su fase inicial es fundamental para prevenir fallos futuros, que pueden ser catastróficos. Inicialmente, se lleva a cabo una revisión del método de la Impedancia Electro-Mecánica (EMI), de cara a exponer sus capacidades para la detección de daño. Una vez la tecnología apropiada es seleccionada, lo que incluye un analizador de impedancias así como novedosos sensores PZT para monitorización inteligente, se ha diseñado un procedimiento automático basado en los registros de impedancias de distintas estructuras de laboratorio. Basándonos en el hecho de que las mediciones de impedancias son posibles gracias a una colocación adecuada de una red de sensores PZT, la estimación de la presencia de daño se realiza analizando los resultados de distintos indicadores de daño obtenidos de la literatura. Para que este proceso sea automático y que no sean necesarios conocimientos previos sobre el método EMI para realizar un experimento, se ha diseñado e implementado un Interfaz Gráfico de Usuario, transformando la medición de impedancias en un proceso fácil e intuitivo. Se evalúa entonces el daño a través de los correspondientes índices de daño, intentando estimar no sólo su severidad, sino también su localización aproximada. El desarrollo de estos experimentos en cualquier estructura genera grandes cantidades de datos que han de ser procesados, y algunas veces los índices de daño no son suficientes para una evaluación completa de la integridad de una estructura. En la mayoría de los casos se pueden encontrar patrones de daño en los datos, pero no se tiene información a priori del estado de la estructura. En este punto, se ha hecho una importante investigación en técnicas de reconocimiento de patrones particularmente en aprendizaje no supervisado, encontrando aplicaciones interesantes en el campo de la medicina. De ahí surge una idea creativa e innovadora: detectar y seguir la evolución del daño en distintas estructuras como si se tratase de un cáncer propagándose por el cuerpo humano. En ese sentido, las lecturas de impedancias se emplean como información intrínseca de la salud de la propia estructura, de forma que se pueden aplicar las mismas técnicas que las empleadas en la investigación del cáncer. En este caso, se ha aplicado un algoritmo de clasificación jerárquica dado que ilustra además la clasificación de los datos de forma gráfica, incluyendo información cualitativa y cuantitativa sobre el daño. Se ha investigado la efectividad de este procedimiento a través de tres estructuras de laboratorio, como son una viga de aluminio, una unión atornillada de aluminio y un bloque de hormigón reforzado con FRP. La primera ayuda a mostrar la efectividad del método en sencillos escenarios de daño simple y múltiple, de forma que las conclusiones extraídas se aplican sobre los otros dos, diseñados para simular condiciones de despegue en distintas estructuras. Demostrada la efectividad del método de clasificación jerárquica de lecturas de impedancias, se aplica el procedimiento sobre las estructuras de hormigón armado reforzadas con bandas de FRP objeto de esta tesis, detectando y clasificando cada estado de daño. Finalmente, y como alternativa al anterior procedimiento, se propone un método para la monitorización continua de la interfase FRP-Hormigón, a través de una red de sensores FBG permanentemente instalados en dicha interfase. De esta forma, se obtienen medidas de deformación de la interfase en condiciones de carga continua, para ser implementadas en un modelo de optimización multiobjetivo, cuya solución se haya por medio de una expansión multiobjetivo del método Particle Swarm Optimization (PSO). La fiabilidad de este último método de detección se investiga a través de sendos ejemplos tanto numéricos como experimentales. ABSTRACT This thesis aims to develop robust and reliable damage identification methods focused on experimental structural systems, in particular Reinforced Concrete (RC) structures externally strengthened with Fiber Reinforced Polymers (FRP) strips. The failure mode of this type of structural system is critical, since it is usually due to sudden and brittle debonding of the FRP reinforcement originating from intermediate flexural cracks. Detection of the debonding in its initial stage is essential thus to prevent future failure, which might be catastrophic. Initially, a revision of the Electro-Mechanical Impedance (EMI) method is carried out, in order to expose its capabilities for local damage detection. Once the appropriate technology is selected, which includes impedance analyzer as well as novel PZT sensors for smart monitoring, an automated procedure has been design based on the impedance signatures of several lab-scale structures. On the basis that capturing impedance measurements is possible thanks to an adequately deployed PZT sensor network, the estimation of damage presence is done by analyzing the results of different damage indices obtained from the literature. In order to make this process automatic so that it is not necessary a priori knowledge of the EMI method to carry out an experimental test, a Graphical User Interface has been designed, turning the impedance measurements into an easy and intuitive procedure. Damage is then assessed through the analysis of the corresponding damage indices, trying to estimate not only the damage severity, but also its approximate location. The development of these tests on any kind of structure generates large amounts of data to be processed, and sometimes the information provided by damage indices is not enough to achieve a complete analysis of the structural health condition. In most of the cases, some damage patterns can be found in the data, but none a priori knowledge of the health condition is given for any structure. At this point, an important research on pattern recognition techniques has been carried out, particularly on unsupervised learning techniques, finding interesting applications in the medicine field. From this investigation, a creative and innovative idea arose: to detect and track the evolution of damage in different structures, as if it were a cancer propagating through a human body. In that sense, the impedance signatures are used to give intrinsic information of the health condition of the structure, so that the same clustering algorithms applied in the cancer research can be applied to the problem addressed in this dissertation. Hierarchical clustering is then applied since it also provides a graphical display of the clustered data, including quantitative and qualitative information about damage. The performance of this approach is firstly investigated using three lab-scale structures, such as a simple aluminium beam, a bolt-jointed aluminium beam and an FRP-strengthened concrete specimen. The first one shows the performance of the method on simple single and multiple damage scenarios, so that the first conclusions can be extracted and applied to the other two experimental tests, which are designed to simulate a debonding condition on different structures. Once the performance of the impedance-based hierarchical clustering method is proven to be successful, it is then applied to the structural system studied in this dissertation, the RC structures externally strengthened with FRP strips, where the debonding failure in the interface between the FRP and the concrete is successfully detected and classified, proving thus the feasibility of this method. Finally, as an alternative to the previous approach, a continuous monitoring procedure of the FRP-Concrete interface is proposed, based on an FBGsensors Network permanently deployed within that interface. In this way, strain measurements can be obtained under controlled loading conditions, and then they are used in order to implement a multi-objective model updating method solved by a multi-objective expansion of the Particle Swarm Optimization (PSO) method. The feasibility of this last proposal is investigated and successfully proven on both numerical and experimental RC beams strengthened with FRP.

Multifunctional cement composites strain and damage sensors applied on reinforced concrete (RC) structural elements

In this research, strain-sensing and damage-sensing functional properties of cement composites have been studied on a conventional reinforced concrete (RC) beam. Carbon nanofiber (CNFCC) and fiber (CFCC) cement composites were used as sensors on a 4 m long RC beam. Different casting conditions (in situ or attached), service location (under tension or compression) and electrical contacts (embedded or superficial) were compared. Both CNFCC and CFCC were suitable as strain sensors in reversible (elastic) sensing condition testing. CNFCC showed higher sensitivities (gage factor up to 191.8), while CFCC only reached gage factors values of 178.9 (tension) or 49.5 (compression). Furthermore, damage-sensing tests were run, increasing the applied load progressively up to the RC beam failure. In these conditions, CNFCC sensors were also strain sensitive, but no damage sensing mechanism was detected for the strain levels achieved during the tests. Hence, these cement composites could act as strain sensors, even for severe damaged structures near to their collapse.

Seismic behavior of a masonry chimney with severe cracking condition: preliminary study

This paper presents a structural analysis of a masonry chimney built in the 1940s, which is currently being cataloged as local interest heritage. This structure has not served any industrial purpose for the last thirty years. The chimney is located in the town of Agost (Alicante - Spain) and directly exposed to the prevailing winds from the sea, as it is approximately 12 km away from the waterfront and there are not any significant barriers, which could protect the structure against the wind. There are longitudinal cracks and fissures all along the shaft because of the chimney’s geometrical characteristics, the effect of the masonry creep and especially the lack of maintenance. Moreover, there is also a permanent bending deformation in the upper 1/3 of the height due to the wind pressure. A numerical analysis for the static behavior against gravity and wind loads was performed using the structure’s current conditions after a detailed report of its geometry, its construction system and the cracking pattern. Afterwards, the dynamic behavior was studied, i.e. a seismic analysis using both response spectra and accelerograms in order to examine the structural stability. This work shows the pre-monitoring analysis before any experimental testing. Using the current results the future test conditions will be determined (e.g. number of sensors and monitoring point location, excitation systems, etc) prior to a possible structural reinforcement by applying composite material (fiber reinforced polymers).

Relationship of body condition score and blood urea and ammonia to pregnancy in Italian Mediterranean buffaloes

The relationship of body condition score ( BCS) and blood urea and ammonia to pregnancy outcome was examined in Italian Mediterranean Buffalo cows mated by AI. The study was conducted on 150 buffaloes at 145 +/- 83 days in milk that were fed a diet comprising 14.8% crude protein, 0.9 milk forage units . kg(-1) dry matter and a non- structural carbohydrate/ crude protein ratio of 2.14. The stage of the oestrous cycle was synchronised by the Ovsynch- TAI programme and blood urea and ammonia levels were assessed on the day of AI. Energy corrected milk ( ECM) production and BCS were recorded bi- weekly. The pregnancy risk was 46.7% and was slightly lower in buffaloes with BCS < 6.0 and BCS > 7.5. There were no significant differences in ECM, urea and ammonia between pregnant and non- pregnant buffaloes. However, pregnancy outcome was higher ( P = 0.02) in buffaloes with blood urea < 6.83 mmol . L-1. The likelihood of pregnancy for buffaloes with low urea blood level was 2.6 greater than for high urea level and exposure to a high urea level lowered the probability of pregnancy by about 0.25. The findings indicate that buffaloes are similar to cattle and increased blood levels of urea are associated with reduced fertility when animals are mated by AI.

Structural evolution in a hydrothermal reaction between Nb2O5 and NaOH solution: From Nb2O5 grains to microporous Na2Nb2O6 center dot(2)/3H2O fibers and NaNbO3 cubes

Niobium pentoxide reacts actively with concentrate NaOH solution under hydrothermal conditions at as low as 120 degrees C. The reaction ruptures the corner-sharing of NbO7 decahedra and NbO6 octahedra in the reactant Nb2O5, yielding various niobates, and the structure and composition of the niobates depend on the reaction temperature and time. The morphological evolution of the solid products in the reaction at 180 degrees C is monitored via SEM: the fine Nb2O5 powder aggregates first to irregular bars, and then niobate fibers with an aspect ratio of hundreds form. The fibers are microporous molecular sieve with a monoclinic lattice, Na2Nb2O6 center dot(2)/3H2O. The fibers are a metastable intermediate of this reaction, and they completely convert to the final product NaNbO3 Cubes in the prolonged reaction of 1 h. This study demonstrates that by carefully optimizing the reaction condition, we can selectively fabricate niobate structures of high purity, including the delicate microporous fibers, through a direct reaction between concentrated NaOH solution and Nb2O5. This synthesis route is simple and suitable for the large-scale production of the fibers. The reaction first yields poorly crystallized niobates consisting of edge-sharing NbO6 octahedra, and then the microporous fibers crystallize and grow by assembling NbO6 octahedra or clusters of NbO6 octahedra and NaO6 units. Thus, the selection of the fibril or cubic product is achieved by control of reaction kinetics. Finally, niobates with different structures exhibit remarkable differences in light absorption and photoluminescence properties. Therefore, this study is of importance for developing new functional materials by the wet-chemistry process.

Using interior point algorithms for the solution of linear programs with special structural features

Linear Programming (LP) is a powerful decision making tool extensively used in various economic and engineering activities. In the early stages the success of LP was mainly due to the efficiency of the simplex method. After the appearance of Karmarkar's paper, the focus of most research was shifted to the field of interior point methods. The present work is concerned with investigating and efficiently implementing the latest techniques in this field taking sparsity into account. The performance of these implementations on different classes of LP problems is reported here. The preconditional conjugate gradient method is one of the most powerful tools for the solution of the least square problem, present in every iteration of all interior point methods. The effect of using different preconditioners on a range of problems with various condition numbers is presented. Decomposition algorithms has been one of the main fields of research in linear programming over the last few years. After reviewing the latest decomposition techniques, three promising methods were chosen the implemented. Sparsity is again a consideration and suggestions have been included to allow improvements when solving problems with these methods. Finally, experimental results on randomly generated data are reported and compared with an interior point method. The efficient implementation of the decomposition methods considered in this study requires the solution of quadratic subproblems. A review of recent work on algorithms for convex quadratic was performed. The most promising algorithms are discussed and implemented taking sparsity into account. The related performance of these algorithms on randomly generated separable and non-separable problems is also reported.