Assessing the Synergistic Effect of Caffeine and Sugar on Cognitive Performance in Undergraduate Students

Working independently, both caffeine and sugar provide benefits to attention and memory. However, there is sparse literature on the synergistic effects on improved cognitive performance between caffeine and sugar when taken together. This study explored the dynamics between caffeine and sugar when consumed under ordinary conditions – as a cup of coffee. Twenty-four undergraduate students (15 women and 9 men) were asked to complete a baseline cognitive test, and one of the three variables was given at random in the form of a cup of coffee: decaffeinated with sugar, caffeinated with no sugar, and caffeinated with sugar. The remaining two variables were administered at random over the next two sessions. Results were compared within subjects and between subjects to assess effects on short-term memory and cognitive performance. We hypothesized that there would be a significant improvement on short-term memory as measured by correct responses on n-back tests when caffeine and sugar were consumed simultaneously, as opposed to consuming the caffeine or sugar independently. Additionally, we anticipated that participants’ caffeine consumption habits would influence the effects of different treatments on cognitive performance. The results did not show a synergistic effect on cognitive performance by caffeine and sugar when taken together, although there was a trend supporting this hypothesis in non-regular coffee drinkers as opposed to habitual coffee drinkers. Additionally, there was evidence supporting our hypothesis that caffeine habits influence the cognitive benefits of caffeine and sugar consumption. Non-coffee drinkers saw a higher increase in cognitive performance after consuming caffeinated beverages with sugar, while coffee drinkers received greater benefits from drinking caffeinated beverages without sugar

Methane hydrate: shifting the coexistence temperature to higher temperatures with an external electric field

In the present work, we used molecular dynamic simulations of the equilibrium NPT ensemble to examine the effect of an external electric field on the three-phase coexistence temperature of methane gas, liquid water and methane hydrate. For these simulations, we used the TIP4P/Ice rigid water model and a single-site model for methane. The simulations were implemented at two pressures, 400 and 250bar, over temperatures ranging from 285 to 320K and from 280 to 315K, respectively. The application of an external electric field in the range of 0.1-0.9caused the effect of the thermal vibrations of the water molecules to become attenuated. This resulted in a shift of the three-phase coexistence temperature to higher temperatures. Electric fields below this range did not cause a difference in the coexistence temperature, and electric fields above this range enhanced the thermal effect. The shift had a magnitude of 22.5K on average.Peer ReviewedPostprint (author's final draft

Approximate solutions of one dimensional systems with fractional derivative

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Mechanical recycling of plastic wastes. Case of study: high impact polystyrene for manufacturing TV components shelf

En este trabajo se presenta una introducción sobre la situación actual del reciclaje de los materiales plásticos a nivel mundial, con un especial interés en la situación en la que se encuentra el estado Europeo. A pesar de que existen numerosas técnicas de reciclado de plásticos, el método de reciclado mecánico ha llamado mucho la atención por parte de las industrias transformadoras del plástico debido a la capacidad de producción que puede llevarse a cabo mediante el uso de técnicas como la extrusión y la inyección de plásticos. La parte final de este trabajo se enfoca en un caso práctico que se llevó a cabo en el Centre Català del Plàstic (CCP) y la empresa SONY para la obtención de materiales plásticos reciclables para manufacturar carcasas de televisiones. El trabajo realizado en el CCP fue el estudio de la viabilidad de la sustitución de materiales vírgenes por materiales reciclados procedentes de residuos industriales. El estudio consistió en analizar la viabilidad de sustituir un poliestireno antichoque (HIPS) virgen por el mismo material de origen pero reciclado. De esta manera, se compararon las propiedades de cuatro materiales HIPS reciclados (HIPS-RA, -RB, -RC y -RD) así como un estudio de su morfología. Se observó que el índice de fluidez del HIPS aumentó con la proporción de material reciclado y con el número de procesos de transformación. La propiedad mecánica más afectada resultó ser la resistencia al impacto, y se observaron dos tipos de morfologías claramente diferentes. El material reciclado que mostró mejores propiedades fue el HIPS-RB, y fue escogido para sustituir al HIPS virgen en la producción de componentes de electrónica de consumo. Finalmente, el estudio realizado permitió analizar los factores que intervienen en el estudio de materiales reciclados, conocer las posibilidades de su aplicación en el caso concreto de componentes de electrónica de consumo y crear las bases para poder establecer una metodología para realizar futuros estudios de introducción de materiales reciclados en otras aplicaciones tecnológicas. Por lo anterior, el trabajo presenta una completa introducción en el área del reciclaje mecánico y las tendencias del mercado así como la viabilidad del reaprovechamiento de materiales de residuo para el desarrollo de componentes no estructurales y de elevada producción industrial.Postprint (published version

Selecting Negative Samples for PPI Prediction Using Hierarchical Clustering Methodology

Protein-protein interactions (PPIs) play a crucial role in cellular processes. In the present work, a new approach is proposed to construct a PPI predictor training a support vector machine model through a mutual information filter-wrapper parallel feature selection algorithm and an iterative and hierarchical clustering to select a relevance negative training set. By means of a selected suboptimum set of features, the constructed support vector machine model is able to classify PPIs with high accuracy in any positive and negative datasets

Folding Elastic Thermal Surface - FETS

The FETS is a light and compact thermal surface (sun shade, IR thermal shield, cover, and/or deployable radiator) that is mounted on a set of offset tape-spring hinges. The thermal surface is constrained during launch and activated in space by a thermomechanical latch such as a wax actuator. An application-specific embodiment of this technology developed for the MATMOS (Mars Atmospheric Trace Molecule Occultation Spectrometer) project serves as a deployable cover and thermal shield for its passive cooler. The FETS fits compactly against the instrument within the constrained launch envelope, and then unfolds into a larger area once in space. In this application, the FETS protects the passive cooler from thermal damage and contamination during ground operations, launch, and during orbit insertion. Once unfolded or deployed, the FETS serves as a heat shield, intercepting parasitic heat loads by blocking the passive cooler s view of the warm spacecraft. The technology significantly enhances the capabilities of instruments requiring either active or passive cooling of optical detectors. This can be particularly important for instruments where performance is limited by the available radiator area. Examples would be IR optical instruments on CubeSATs or those launched as hosted payloads because radiator area is limited and views are often undesirable. As a deployable radiator, the panels making up the FETS are linked thermally by thermal straps and heat pipes; the structural support and deployment energy is provided using tape-spring hinges. The FETS is a novel combination of existing technologies. Prior art for deployable heat shields uses rotating hinges that typically must be lubricated to avoid cold welding or static friction. By using tape-spring hinges, the FETS avoids the need for lubricants by avoiding friction altogether. This also eliminates the potential for contamination of nearby cooled optics by outgassing lubricants. Furthermore, the tape-spring design of the FETS is also self-locking so the panels stay in a rigid and extended configuration after deployment. This unexpected benefit makes the tape-spring hinge design of the FETS a light, simple, reliable, compact, non-outgassing hinge, spring, and latch. While tape-spring hinges are not novel, they have never been used to deploy passive unfolding thermal surfaces (radiator panels, covers, sun shades, or IR thermal shields). Furthermore, because this technology is compact, it has minimal impact on the launch envelope and mass specifications. FETS enhances the performance of hosted payload instruments where the science data is limited by dark noise. Incorporating FETS into a thermal control system increases radiator area, which lowers the optical detector temperature. This results in higher SNR (signal-to-noise ratio) and improved science data

Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques

Multiple sequence alignments (MSAs) have become one of the most studied approaches in bioinformatics to perform other outstanding tasks such as structure prediction, biological function analysis or next-generation sequencing. However, current MSA algorithms do not always provide consistent solutions, since alignments become increasingly difficult when dealing with low similarity sequences. As widely known, these algorithms directly depend on specific features of the sequences, causing relevant influence on the alignment accuracy. Many MSA tools have been recently designed but it is not possible to know in advance which one is the most suitable for a particular set of sequences. In this work, we analyze some of the most used algorithms presented in the bibliography and their dependences on several features. A novel intelligent algorithm based on least square support vector machine is then developed to predict how accurate each alignment could be, depending on its analyzed features. This algorithm is performed with a dataset of 2180 MSAs. The proposed system first estimates the accuracy of possible alignments. The most promising methodologies are then selected in order to align each set of sequences. Since only one selected algorithm is run, the computational time is not excessively increased