Indicadores de caracterización de sistemas Fotovoltaicos aislados, para la determinación de la tensión de trabajo óptima. Un estudio preliminar

El objetivo de este trabajo es encontrar indicadores de caracterización, que operen como herramientas para determinar la tensión de trabajo más conveniente de un sistema fotovoltaico aislado. El estudio se realizó, tanto desde el punto de vista económico como técnico, buscando una referencia de costos y eficiencia en relación con la capacidad de energía instalada. Se describe el análisis de sistemas, diseñados con el mismo software, en iguales condiciones meteorológicas, variando la carga (700-1400W) y las configuraciones de diseño según las tensiones de alimentación de las cargas (12V-24V-220VCA). No se utilizó la tensión de 48V, ya que en el mercado no hay disponibilidad de cargas eléctricas. Se encontró algunos índices útiles y otros no adecuados para la caracterización pretendida. El índice Costo por Configuración muestra que la configuración 24V-220V es la más económica en el rango de potencias analizado. Es necesario ahondar este análisis con nuevos estudios, incluyendo otras variables con mayor peso e influencia.Fil: Fernández, R.. Universidad Nacional de Santiago del Estero; ArgentinaFil: Cadena, Carlos Alberto. Universidad Nacional de Salta; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Salta. Instituto de Investigaciones en Energía no Convencional; Argentin

Design Principles for Two-Dimensional Molecular Aggregates Using Kasha's Model: Tunable Photophysics in Near and Short-Wave Infrared

Technologies which utilize near-infrared (700 – 1000 nm) and short-wave infrared (1000 – 2000 nm) electromagnetic radiation have applications in deep-tissue imaging, telecommunications and satellite telemetry due to low scattering and decreased background signal in this spectral region. It is therefore necessary to develop materials that absorb light efficiently beyond 1000 nm. Transition dipole moment coupling (e.g. J-aggregation) allows for redshifted excitonic states and provides a pathway to highly absorptive electronic states in the infrared. We present aggregates of two cyanine dyes whose absorption peaks redshift dramatically upon aggregation in water from ~800 nm to 1000 nm and 1050 nm respectively with sheet-like morphologies and high molar absorptivities (e ~ 105 M-1cm-1). We use Frenkel exciton theory to extend Kasha’s model for J and H aggregation and describe the excitonic states of 2-dimensional aggregates whose slip is controlled by steric hindrance in the assembled structure. A consequence of the increased dimensionality is the phenomenon of an intermediate “I-aggregate”, one which redshifts yet displays spectral signatures of band-edge dark states akin to an H-aggregate. We distinguish between H-, I- and J-aggregates by showing the relative position of the bright (absorptive) state within the density of states using temperature dependent spectroscopy. I-aggregates hold potential for applications as charge injection moieties for semiconductors and donors for energy transfer in NIR and SWIR. Our results can be used to better design chromophores with predictable and tunable aggregation with new photophysical properties

RIDI: Robust IMU Double Integration

This paper proposes a novel data-driven approach for inertial navigation, which learns to estimate trajectories of natural human motions just from an inertial measurement unit (IMU) in every smartphone. The key observation is that human motions are repetitive and consist of a few major modes (e.g., standing, walking, or turning). Our algorithm regresses a velocity vector from the history of linear accelerations and angular velocities, then corrects low-frequency bias in the linear accelerations, which are integrated twice to estimate positions. We have acquired training data with ground-truth motions across multiple human subjects and multiple phone placements (e.g., in a bag or a hand). The qualitatively and quantitatively evaluations have demonstrated that our algorithm has surprisingly shown comparable results to full Visual Inertial navigation. To our knowledge, this paper is the first to integrate sophisticated machine learning techniques with inertial navigation, potentially opening up a new line of research in the domain of data-driven inertial navigation. We will publicly share our code and data to facilitate further research

Correlación clínica e inmunohistopatológica de la nefropatía lúpica en un centro de referencia del Caribe colombiano durante los años 2012 a 2013

Objectives: To determine the behavior of lupus nephropathy (LN) in a population group of a reference center in the Colombian Caribbean during 2012 and 2013, analyzing the most prevalent clinical and laboratory findings and its relation to the immunohistotopathological findings, define the class of Lupus nephritis with greater prevalence and the clinical or paraclinic data more correlated with this one. Methods: Descriptive, retrospective, cross-sectional study conducted from January 1st of 2012 to December 31st 2013, which included 53 patients with systemic lupus erythematosus according to diagnostic critearia of the Colegio Americano de Reumatologia, with manifestations of renal impairment. Results: In our study population in the Colombian Caribbean, LN predominates more in women and class IV represents 66.03% of the total cases analyzed, in which there was more hematuria present, hypertension and proteinuria with nephrotic pattern, as well as higher levels of serum creatinine. Despite the lack of data, none of the clinical or paraclinical variables was specific for a certain class of LN and in relation to the immunostaining, lambda chains were positive in 100% of the cases and only C4 and fibrinogen were specific to LN class IV. Conclusions: Class IV LN is the most prevalent and with a higher percentage of predominance of the variables hematuria, proteinuria, hypertension, elevated serum creatinine and bun levels. At the same time they are not specific for some class of LN in our population.Objetivos: Determinar el comportamiento de la nefropatía lúpica (NL) en un grupo poblacional de un centro de referencia del Caribe colombiano, durante los años 2012 y 2013, analizando los hallazgos clínicos  de laboratorio más prevalentes y su relación con los hallazgos inmunohistopatológicos, definir la clase de NL con mayor prevalencia y el dato clínico o paraclínico más correlacionado con esta.Métodos: Estudio descriptivo, retrospectivo, transversal, realizado desde el 1 de enero de 2012 al 31 de diciembre de 2013, que incluyó a 53 pacientes con lupus eritematoso sistémico (LES), según los criterios diagnósticos del Colegio Americano de Reumatología, con manifestaciones de compromiso renal.Resultados: En nuestra población de estudio del Caribe colombiano, la NL predomina más en mujeres y la clase IV representa el 66,03% del total de casos analizados, en los cuales hubo más presentación de hematuria, hipertensión y proteinuria con patrón nefrótico, al igual que mayores niveles de creatinina sérica. A pesar de la falta de datos, ninguna de las variables clínicas o paraclínicas fue específica para cierta clase de NL y con relación a la inmunomarcación, las cadenas lambda se presentaron positivas en el 100% de los casos y tan solo el C4 y el fibrinógeno fueron específicos de la NL clase IV.Conclusiones: La NL clase IV es la más prevalente y con mayor porcentaje de predominio de las variables como hematuria, proteinuria, hipertensión, niveles de creatinina y BUN séricos elevados y, a su vez, no son específicos para cierta clase de NL en nuestra población

3D multi-robot patrolling with a two-level coordination strategy

Teams of UGVs patrolling harsh and complex 3D environments can experience interference and spatial conflicts with one another. Neglecting the occurrence of these events crucially hinders both soundness and reliability of a patrolling process. This work presents a distributed multi-robot patrolling technique, which uses a two-level coordination strategy to minimize and explicitly manage the occurrence of conflicts and interference. The first level guides the agents to single out exclusive target nodes on a topological map. This target selection relies on a shared idleness representation and a coordination mechanism preventing topological conflicts. The second level hosts coordination strategies based on a metric representation of space and is supported by a 3D SLAM system. Here, each robot path planner negotiates spatial conflicts by applying a multi-robot traversability function. Continuous interactions between these two levels ensure coordination and conflicts resolution. Both simulations and real-world experiments are presented to validate the performances of the proposed patrolling strategy in 3D environments. Results show this is a promising solution for managing spatial conflicts and preventing deadlocks

System analysis of the bio-based economy in Colombia: A bottom-up energy system model and scenario analysis

The transition to a sustainable bio‐based economy is perceived as a valid path towards low‐carbon development for emerging economies that have rich biomass resources. In the case of Colombia, the role of biomass has been tackled through qualitative roadmaps and regional climate policy assessments. However, neither of these approaches has addressed the complexity of the bio‐based economy systematically in the wider context of emission mitigation and energy and chemicals supply. In response to this limitation, we extended a bottom‐up energy system optimization model by adding a comprehensive database of novel bio‐based value chains. We included advanced road and aviation biofuels, (bio)chemicals, bioenergy with carbon capture and storage (BECCS), and integrated biorefinery configurations. A scenario analysis was conducted for the period 2015–2050, which reflected uncertainties in the capacity for technological learning, climate policy ambitions, and land availability for energy crops. Our results indicate that biomass can play an important, even if variable, role in supplying 315–760 PJ/y of modern bio‐based products. In pursuit of a deep decarbonization trajectory, the large‐scale mobilization of biomass resources can reduce the cost of the energy system by up to 11 billion $/year, the marginal abatement cost by 62%, and the potential reliance on imports of oil and chemicals in the future. The mitigation potential of BECCS can reach 24–29% of the cumulative avoided emissions between 2015 and 2050. The proposed system analysis framework can provide detailed quantitative information on the role of biomass in low carbon development of emerging economies