Capacity limits and matching properties of lateral flux integrated capacitors

Theoretical limits for the capacitance density of lateral flux and quasi-fractal capacitors are calculated. These limits are used to investigate the efficiency of various capacitive structures such as lateral flux and quasi-fractal structures. This study leads to two new capacitor structures with high lateral field efficiency. Simulation and experimental results demonstrate higher capacity and superior matching properties compared to the standard horizontal parallel plate and previously reported lateral-field capacitors

Circular-geometry oscillators

5.3GHz 0.18μm CMOS circular-geometry oscillator exploits high Q of slab inductors. The oscillator draws 10mA from 1.4V with a phase noise of -147.3dBc/Hz at 10MHz offset. A second 5.4GHz circular-geometry VCO has a tuning range of 8% with phase noise of -142.2dBc/Hz at 10MHz offset while drawing 12mA from a 1.8V supply

Predicción de la frescura del aceite de oliva virgen extra durante el almacenamiento mediante espectroscopía de fluorescencia

Virgin olive oil quality relates to flavor and unique health benefits. Some of these properties are at the most desirable level when the oil is just extracted, since it is not a product that improves with age. On the contrary, the concentrations of many compounds change during its shelf-life. These changes reveal the aging of the oil but do not necessarily mean decay in sensory properties, so in some cases an aged oil from healthy olives may be better qualified than a fresh one from olives affected by fermentation. The aim of this work is to analyze different methodologies proposed for assessing the quality of virgin olive oil with implications in freshness and aging of the oil, and to highlight the possibilities of rapid spectrofluorimetric techniques for assessing oil freshness by checking the evolution of pigments during storage. The observed change in the selected spectral features and mathematical modelling over time was compared with the accepted model for predicting the amount of pyropheophytin a, which is based on isokinetic studies. The best regression was obtained for 655 nm (adjustedR2 = 0.91) wavelength, which matches the distinctive band of pigments. The two mathematical models described in this study highlight the usefulness of pigments in the prediction of the shelf-life of extra virgin olive oil.La calidad del aceite de oliva virgen está relacionada con su flavor y sus beneficios únicos para la salud. Algunas de estas propiedades se encuentran en el nivel más deseable cuando el aceite está recién extraído, ya que no es un producto que mejore con el tiempo. Por el contrario, las concentraciones de muchos compuestos cambian a lo largo de la vida útil. Estos cambios revelan el envejecimiento del aceite, pero no implican necesariamente la alteración de las propiedades sensoriales, por lo que en algunos casos un aceite envejecido procedente de aceitunas sanas puede presentar mejor calidad que uno fresco procedente de aceitunas afectadas por procesos de fermentación. El objetivo de este trabajo es estudiar diferentes metodologías propuestas para evaluar la calidad del aceite de oliva virgen con implicaciones en la frescura y el envejecimiento del aceite, destacando las posibilidades de las rápidas técnicas espectrofluorométricas para evaluar la frescura del aceite verificando la evolución de los pigmentos durante el almacenamiento. El cambio observado en las características espectrales seleccionadas y su modelado matemático a lo largo del tiempo se comparó con el modelo aceptado para predecir la cantidad de pirofeofitina a, que se basa en estudios isocinéticos. Los dos modelos matemáticos descritos en este estudio pusieron de manifiesto la utilidad de los pigmentos en la predicción de la vida útil del aceite de oliva virgen extra. La mejor regresión se obtuvo para 655 nm (R2 -ajustado = 0,91), longitud de onda que coincide con la banda distintiva de pigmentos.Secretaría de Estado de Investigación, Desarrollo e Innovación de España-AGL2015-69320-

Predicción de la frescura del aceite de oliva virgen extra durante el almacenamiento mediante espectroscopía de fluorescencia

Virgin olive oil quality relates to flavor and unique health benefits. Some of these properties are at the most desirable level when the oil is just extracted, since it is not a product that improves with age. On the contrary, the concentrations of many compounds change during its shelf-life. These changes reveal the aging of the oil but do not necessarily mean decay in sensory properties, so in some cases an aged oil from healthy olives may be better qualified than a fresh one from olives affected by fermentation. The aim of this work is to analyze different methodologies proposed for assessing the quality of virgin olive oil with implications in freshness and aging of the oil, and to highlight the possibilities of rapid spectrofluorimetric techniques for assessing oil freshness by checking the evolution of pigments during storage. The observed change in the selected spectral features and mathematical modelling over time was compared with the accepted model for predicting the amount of pyropheophytin a, which is based on isokinetic studies. The best regression was obtained for 655 nm (adjustedR2 = 0.91) wavelength, which matches the distinctive band of pigments. The two mathematical models described in this study highlight the usefulness of pigments in the prediction of the shelf-life of extra virgin olive oil.La calidad del aceite de oliva virgen está relacionada con su flavor y sus beneficios únicos para la salud. Algunas de estas propiedades se encuentran en el nivel más deseable cuando el aceite está recién extraído, ya que no es un producto que mejore con el tiempo. Por el contrario, las concentraciones de muchos compuestos cambian a lo largo de la vida útil. Estos cambios revelan el envejecimiento del aceite, pero no implican necesariamente la alteración de las propiedades sensoriales, por lo que en algunos casos un aceite envejecido procedente de aceitunas sanas puede presentar mejor calidad que uno fresco procedente de aceitunas afectadas por procesos de fermentación. El objetivo de este trabajo es estudiar diferentes metodologías propuestas para evaluar la calidad del aceite de oliva virgen con implicaciones en la frescura y el envejecimiento del aceite, destacando las posibilidades de las rápidas técnicas espectrofluorométricas para evaluar la frescura del aceite verificando la evolución de los pigmentos durante el almacenamiento. El cambio observado en las características espectrales seleccionadas y su modelado matemático a lo largo del tiempo se comparó con el modelo aceptado para predecir la cantidad de pirofeofitina a, que se basa en estudios isocinéticos. Los dos modelos matemáticos descritos en este estudio pusieron de manifiesto la utilidad de los pigmentos en la predicción de la vida útil del aceite de oliva virgen extra. La mejor regresión se obtuvo para 655 nm (R2 -ajustado = 0,91), longitud de onda que coincide con la banda distintiva de pigmentos.Secretaría de Estado de Investigación, Desarrollo e Innovación de España-AGL2015-69320-

On Multiculturalism and Privilege: A Latina Perspective

Also PCMA Working Paper #41.http://deepblue.lib.umich.edu/bitstream/2027.42/51267/1/501.pd

The Turn to Aesthetics in Latinx Literary and Cultural Studies

Latinx Literature Unbound: Undoing Ethnic Expectations by Ralph E. Rodríquez. New York: Fordham University Press, 2018. Paper $30.00, hardcover$105.00. Abject Performances: Aesthetic Strategies in Latino Cultural Production by Leticia Alvarado. Durham, NC: Duke University Press, 2018. Paper $25.95, Cloth$99.95

Detection of advanced persistent threat using machine-learning correlation analysis

As one of the most serious types of cyber attack, Advanced Persistent Threats (APT) have caused major concerns on a global scale. APT refers to a persistent, multi-stage attack with the intention to compromise the system and gain information from the targeted system, which has the potential to cause significant damage and substantial financial loss. The accurate detection and prediction of APT is an ongoing challenge. This work proposes a novel machine learning-based system entitled MLAPT, which can accurately and rapidly detect and predict APT attacks in a systematic way. The MLAPT runs through three main phases: (1) Threat detection, in which eight methods have been developed to detect different techniques used during the various APT steps. The implementation and validation of these methods with real traffic is a significant contribution to the current body of research; (2) Alert correlation, in which a correlation framework is designed to link the outputs of the detection methods, aims to identify alerts that could be related and belong to a single APT scenario; and (3) Attack prediction, in which a machine learning-based prediction module is proposed based on the correlation framework output, to be used by the network security team to determine the probability of the early alerts to develop a complete APT attack. MLAPT is experimentally evaluated and the presented sy