Assessment of the degradation of Aspirin by Differential Scanning Calorimetry (DSC)

Purpose. To study thermal stability of Aspirin and define thermal events that are associated with the thermal degradation of aspirin. Methods. Experiments were performed using a DSC 823e (Mettler Toledo, Swiss). Aspirin is prone to thermal degradation upon exposure to high temperatures. The melting point of aspirin is 140.1±0.4ºC (DSC). Aspirin has been examined by heating samples to 120ºC, 155ºC and 185ºC with subsequent cooling to -55ºC and a final heating to 155ºC. Although different heating and cooling ranges have been used, only results obtained at a rate of 10ºC/min will be presented. All runs where conducted in hermetically sealed pans. Results. Upon heating the sample to 120ºC no significant thermal event can be detected. After cooling the sample and reheating a glass transition can be observed at ~-8ºC, followed by the melting of aspirin at ~139ºC. By heating the sample to 155ºC melting of aspirin has been detected at ~139ºC. On cooling and subsequent heating a glass transition occurs at ~-32ºC, together with a broad crystallisation (onset at ~38ºC and peak maximum at ~57ºC) followed by a broad melting with an onset at 94ºC and peak maximum at ~112ºC. Finally, by heating the sample to 185ºC melting at ~ 139ºC was observed, and upon cooling and reheating a glass transition was detected at ~-26ºC and no further events could be recorded. Conclusions. This research demonstrates that the degradation steps of Aspirin depend on the thermal treatment. The main degradation products of different thermal treatments are currently unknown it is clear that acetic acid, which is one of the degradation products, acts as an antiplasticiser by lowering the glass transition temperature. In addition, due to the presence of the degradation products in liquid form (observed by hot stage microscopy), Aspirin is still present in the sample and recrystallises during the second heating step and melts at much lower temperatures.

The role of space charge formation in the generation of thermally stimulated current (TSC) spectroscopy data for a model amorphous drug system

Thermally stimulated current (TSC) spectroscopy is attracting increasing attention as a means of materials characterization, particularly in terms of measuring slow relaxation processes in solid samples. However, wider use of the technique within the pharmaceutical field has been inhibited by difficulties associated with the interpretation of TSC data, particularly in terms of deconvoluting dipolar relaxation processes from charge distribution phenomena. Here, we present evidence that space charge and electrode contact effects may play a significant role in the generation of peaks that have thus far proved difficult to interpret. We also introduce the use of a stabilization temperature in order to control the space charge magnitude. We have studied amorphous indometacin as a model drug compound and have varied the measurement parameters (stabilization and polarization temperatures), interpreting the changes in spectral composition in terms of charge redistribution processes. More specifically, we suggested that charge drift and diffusion processes, charge injection from the electrodes and high activation energy charge redistribution processes may all contribute to the appearance of shoulders and 'spurious' peaks. We present recommendations for eliminating or reducing these effects that may allow more confident interpretation of TSC data.

Trade credit linkages along the supply chain: evidence for the Italian textile sector

We examine the trade credit linkages among firms within a supply chain to reckon the effect of such linkages on the propagation of liquidity shocks from downstream to upstream firms. We choose a sample appropriate for this task, consisting of a large data set of Italian firms from the textile industry, a well known example of a comprehensive manufacturing cluster featuring a large number of small and specialized firms at each level of the supply chain. The results of the analysis indicate that the level of trade credit that firms provide to their suppliers is positively related to the level of trade credit granted to their clients: when the level of trade credit granted to clients divided by sales goes up by 1, the level of trade credit provided to suppliers divided by cost-of goods-sold goes up by an amount that varies between 0,22 and 0,52. Since all firms along the chain are linked by trade credit relationships, an increase in the level of trade credit granted by wholesalers generates a liquidity cascade throughout the chain. We designate the overall increase in the level of trade credit among all firms in the chain as a result of a unitary impulse in the level of trade credit granted by wholesalers as the multiplier effect of trade credit for the industry chain. We estimate such multiplier to vary between 1.28 and 2.04. We also investigate the effect of final demand on the level of trade credit sourced by firms at various levels of the chain and, in particular, whether such effect is amplified for firms further up in the chain as a result of liquidity propagation via trade credit linkages. We uncover evidence of such amplification when the links of liquidity transmission along the chain are individually modeled and estimated. An unitary increase in wholesalers’ sales is found to produce an effect on trade payables among firms at the top of the chain (i.e., Preparers and Spinners) that is more than twice as big as the corresponding effect among firms at the bottom of the chain (i.e., Wholesalers).

Giovanni Battista Montano as Architectural Draughtsman: Recording the Past and Designing the Future

Giovanni Battista Montano (1534-1621), who was born in Milan and trained as a woodcarver, relocated permanently to Rome in the early 1570s where his interest in sculpting was replaced by intense study of the city’s antique monuments and ruins. Although Montano carried out several sculptural and architectural projects during his time in Rome, it is his surviving corpus of drawings that testifies to his passion of exploring ancient architecture through the medium of drawing. While Montano was not famous during his lifetime, a large body of his intriguing designs became celebrated and widely circulated after his death thanks to the 1624 publication of Montano’s designs by his loyal pupil, Giovanni Battista Soria. Montano’s lifelong work differs from virtually all of his predecessors and contemporaries in its “fantastical” and ornamental nature. This thesis explores Montano’s artistic training as it relates to his later interest in imaginatively reconstructing antique buildings, along with his disregard for archaeological or historical accuracy. The subject matter upon which Montano focused is discussed, along with his objective in creating a large corpus of half-historical, half-invented drawings. His drawing techniques are explored with specific reference to the largest group of extant Montano drawings, today housed in Sir John Soane’s Museum, London, England, and also in reference to three original Montano drawings in the Centre Canadien d’Architecture/Canadian Centre for Architecture, Montréal. Also explored is the legacy and impact of Montano’s drawings and the later publications of his designs on the works of Roman Baroque architects, specifically Borromini and Bernini. This thesis ultimately attempts to understand the impact of the intellectual and artistic environment surrounding Montano in late sixteenth and early seventeenth century Rome, his drawing techniques, his choice of subject matter, and the reception that his unique works received from contemporary artists and intellectuals, along with those of the following generation.

Una revisión de la Cadena Datos-Información-Conocimiento desde el Pragmatismo de Peirce

La Cadena Datos-Información-Conocimiento (DIC), denominada “Jerarquía de la Información” o “Pirámide del Conocimiento”, es uno de los modelos más importantes en la Gestión de la Información y la Gestión del Conocimiento. Por lo general, la estructuración de la cadena se ha ido definiendo como una arquitectura en la que cada elemento se levanta sobre el elemento inmediatamente inferior; sin embargo no existe un consenso en la definición de los elementos, ni acerca de los procesos que transforman un elemento de un nivel a uno del siguiente nivel. En este artículo se realiza una revisión de la Cadena Datos-Información-Conocimiento examinando las definiciones más relevantes sobre sus elementos y sobre su articulación en la literatura, para sintetizar las acepciones más comunes. Se analizan los elementos de la Cadena DIC desde la semiótica de Peirce; enfoque que nos permite aclarar los significados e identificar las diferencias, las relaciones y los roles que desempeñan en la cadena desde el punto de vista del pragmatismo. Finalmente se propone una definición de la Cadena DIC apoyada en las categorías triádicas de signos y la semiosis ilimitada de Peirce, los niveles de sistemas de signos de Stamper y las metáforas de Zeleny.

Extruder Melt Temperature Control with Fuzzy Logic

In polymer extrusion, the delivery of a melt which is homogenous in composition and temperature is paramount for achieving high quality extruded products. However, advancements in process control are required to reduce temperature variations across the melt flow which can result in poor product quality. The majority of thermal monitoring methods provide only low accuracy point/bulk melt temperature measurements and cause poor controller performance. Furthermore, the most common conventional proportional-integral-derivative controllers seem to be incapable of performing well over the nonlinear operating region. This paper presents a model-based fuzzy control approach to reduce the die melt temperature variations across the melt flow while achieving desired average die melt temperature. Simulation results confirm the efficacy of the proposed controller.

Model Selection in SVMs Using Differential Evolution

To improve the performance of classification using Support Vector Machines (SVMs) while reducing the model selection time, this paper introduces Differential Evolution, a heuristic method for model selection in two-class SVMs with a RBF kernel. The model selection method and related tuning algorithm are both presented. Experimental results from application to a selection of benchmark datasets for SVMs show that this method can produce an optimized classification in less time and with higher accuracy than a classical grid search. Comparison with a Particle Swarm Optimization (PSO) based alternative is also included.