Assessment of the performance of commonly used DFT functionals vs. MP2 in the study of IL-Water, IL-Ethanol and IL-(H2O)3 clusters

We present a comparative study of the accuracy of different DFT approaches vs. MP2 for evaluating ionic liquids (ILs) + cosolvent. Namely, we are interested in [XBmim] + cosolvent (X being Cl−, BF4−, PF6−, and CH3SO3− anions and cosolvent being water or ethanol) and [XBmim] + (H2O)3 clusters. In this study the B3LYP, B3LYP-D3, M06, M06-2X and M06-HF functionals with Pople and Dunning basis sets are considered. We find that the influence of the basis sets is a factor to take into consideration. As already seen for weakly bonded systems when the basis set quality is low the uncorrected counterpoise (unCP) or averaging counterpoise (averCP) energies must be used due to cancellation errors. Besides, the inclusion of extra diffuse functions and polarization is also required specially in the case of ILs interacting with water clusters. The B3LYP functional does not reproduce either the structure or the interaction energies for ILs + H2O and ILs + EtOH aggregates, the energetic discrepancies being more significant than the structural ones. Among the dispersive corrected functionals, M06-2X results resemble to a great extent the reference data when the unCP interaction energies are considered for both water and ethanol. In turn, M06 and B3LYP-D3 functionals are the best option for ILs containing polar and non-polar anions, respectively, whether the averCP interactions energies are taking into consideration. From the structural point of view, B3LYP and M06 functionals describe more open structures whereas B3LYP-D3, M06-2X and M06-HF structures resemble quite well MP2 results. When the number of water molecules increases the H bonding motif gains importance and the effect depends on the underlying functional. Only M06-2X and M06-HF behaviour is similar to that observed for one water molecule. This is important because to describe ILs-cosolvent solutions is not only necessary to take into account the ILs-cosolvent interactions but also the cosolvent-cosolvent ones in the ensemble of the system.Junta de Andalucía FQM282Ministerio de Ciencia e Innovación CTQ2011-2593

Faster ASV decomposition for orthogonal polyhedra using the Extreme Vertices Model (EVM)

The alternating sum of volumes (ASV) decomposition is a widely used technique for converting a B-Rep into a CSG model. The obtained CSG tree has convex primitives at its leaf nodes, while the contents of its internal nodes alternate between the set union and difference operators. This work first shows that the obtained CSG tree T can also be expressed as the regularized Exclusive-OR operation among all the convex primitives at the leaf nodes of T, regardless the structure and internal nodes of T. This is an important result in the case in which EVM represented orthogonal polyhedra are used because in this model the Exclusive-OR operation runs much faster than set union and difference operations. Therefore this work applies this result to EVM represented orthogonal polyhedra. It also presents experimental results that corroborate the theoretical results and includes some practical uses for the ASV decomposition of orthogonal polyhedra.Postprint (published version

Juventud entre la ruralidad y la rurbanidad. San Isidro Libertador y su proceso de transformación física-cultural

Como objetivo central se planteó el analizar el cambio en la cultura de los jóvenes que habitan el contexto en rurbanización de la comarca San Isidro Libertador, ubicada en el distrito III del municipio de Managua. Se emplearon métodos cuantitativos y cualitativos, para la recopilación e interpretación de los datos. Como la Etnografía, la estadística descriptiva y la etnohistoria, levantando entrevistas y encuestas a 20 jóvenes y adultos de la comarca, durante el periodo de 2015 a 2016 para obtener datos demográficos y conocer la percepción de los jóvenes sobre el modo de vida rural. Como principal resultado se obtuvo que la percepción de los jóvenes ha sufrido cambios, que pueden ser interpretados como una consecuencia de la expansión urbana de la ciudad de Managua hacia la comarca, alterando el paisaje y composición de la comarca ya que se trata de un proceso de rurbanización. A pesar de los cambios ocasionados por la rurbanización existen sectores dentro de la comarca que resisten a estos cambios, fortaleciendo sus identidades territoriales. Esto tiene un efecto sobre los jóvenes, puesto que conviven con estos sectores y conocimientos sobre los modos de vida rural tradicionales de la comarca

Elongation factor 2-diphthamide is critical for translation of two IRES-dependent protein targets, XIAP and FGF2, under oxidative stress conditions

Elongation factor-2 (eEF2) catalyzes the movement of the ribosome along the mRNA. A single histidine residue in eEF2 (H715) is modified to form diphthamide. A role for eEF2 in cellular stress responses is highlighted by the fact that eEF2 is sensitive to oxidative stress and that it must be active in order to drive the synthesis of proteins that help cells to mitigate the adverse effects of oxidative stress. Many of the latter proteins are encoded by mRNAs containing a sequence called an “internal ribosomal entry site” (IRES). Under high oxidative stress conditions diphthamide-deficient cells were significantly more sensitive to cell death. These results suggest that diphthamide may play a role in protection against the degradation of eEF2. Its protection is especially important under those situations where it is necessary for the re-programming of translation from global to IRES synthesis. Indeed, we found that the expression of X-linked inhibitor of apoptosis (XIAP) and fibroblast growth factor 2 (FGF2), two proteins synthesized from mRNAs with IRES that promote cell survival are deregulated in diphthamide-deficient cells. Our findings therefore suggest that eEF2/diphthamide controls the selective translation of IRES-dependent protein targets XIAP and FGF2, critical for cell survival under conditions of oxidative stress.España, Ministerio de Ciencia e Innovación BFU 2010-20882

Translational Functional Imaging in Surgery Enabled by Deep Learning

Many clinical applications currently rely on several imaging modalities such as Positron Emission Tomography (PET), Magnetic Resonance Imaging (MRI), Computed Tomography (CT), etc. All such modalities provide valuable patient data to the clinical staff to aid clinical decision-making and patient care. Despite the undeniable success of such modalities, most of them are limited to preoperative scans and focus on morphology analysis, e.g. tumor segmentation, radiation treatment planning, anomaly detection, etc. Even though the assessment of different functional properties such as perfusion is crucial in many surgical procedures, it remains highly challenging via simple visual inspection. Functional imaging techniques such as Spectral Imaging (SI) link the unique optical properties of different tissue types with metabolism changes, blood flow, chemical composition, etc. As such, SI is capable of providing much richer information that can improve patient treatment and care. In particular, perfusion assessment with functional imaging has become more relevant due to its involvement in the treatment and development of several diseases such as cardiovascular diseases. Current clinical practice relies on Indocyanine Green (ICG) injection to assess perfusion. Unfortunately, this method can only be used once per surgery and has been shown to trigger deadly complications in some patients (e.g. anaphylactic shock). This thesis addressed common roadblocks in the path to translating optical functional imaging modalities to clinical practice. The main challenges that were tackled are related to a) the slow recording and processing speed that SI devices suffer from, b) the errors introduced in functional parameter estimations under changing illumination conditions, c) the lack of medical data, and d) the high tissue inter-patient heterogeneity that is commonly overlooked. This framework follows a natural path to translation that starts with hardware optimization. To overcome the limitation that the lack of labeled clinical data and current slow SI devices impose, a domain- and task-specific band selection component was introduced. The implementation of such component resulted in a reduction of the amount of data needed to monitor perfusion. Moreover, this method leverages large amounts of synthetic data, which paired with unlabeled in vivo data is capable of generating highly accurate simulations of a wide range of domains. This approach was validated in vivo in a head and neck rat model, and showed higher oxygenation contrast between normal and cancerous tissue, in comparison to a baseline using all available bands. The need for translation to open surgical procedures was met by the implementation of an automatic light source estimation component. This method extracts specular reflections from low exposure spectral images, and processes them to obtain an estimate of the light source spectrum that generated such reflections. The benefits of light source estimation were demonstrated in silico, in ex vivo pig liver, and in vivo human lips, where the oxygenation estimation error was reduced when utilizing the correct light source estimated with this method. These experiments also showed that the performance of the approach proposed in this thesis surpass the performance of other baseline approaches. Video-rate functional property estimation was achieved by two main components: a regression and an Out-of-Distribution (OoD) component. At the core of both components is a compact SI camera that is paired with state-of-the-art deep learning models to achieve real time functional estimations. The first of such components features a deep learning model based on a Convolutional Neural Network (CNN) architecture that was trained on highly accurate physics-based simulations of light-tissue interactions. By doing this, the challenge of lack of in vivo labeled data was overcome. This approach was validated in the task of perfusion monitoring in pig brain and in a clinical study involving human skin. It was shown that this approach is capable of monitoring subtle perfusion changes in human skin in an arm clamping experiment. Even more, this approach was capable of monitoring Spreading Depolarizations (SDs) (deoxygenation waves) in the surface of a pig brain. Even though this method is well suited for perfusion monitoring in domains that are well represented with the physics-based simulations on which it was trained, its performance cannot be guaranteed for outlier domains. To handle outlier domains, the task of ischemia monitoring was rephrased as an OoD detection task. This new functional estimation component comprises an ensemble of Invertible Neural Networks (INNs) that only requires perfused tissue data from individual patients to detect ischemic tissue as outliers. The first ever clinical study involving a video-rate capable SI camera in laparoscopic partial nephrectomy was designed to validate this approach. Such study revealed particularly high inter-patient tissue heterogeneity under the presence of pathologies (cancer). Moreover, it demonstrated that this personalized approach is now capable of monitoring ischemia at video-rate with SI during laparoscopic surgery. In conclusion, this thesis addressed challenges related to slow image recording and processing during surgery. It also proposed a method for light source estimation to facilitate translation to open surgical procedures. Moreover, the methodology proposed in this thesis was validated in a wide range of domains: in silico, rat head and neck, pig liver and brain, and human skin and kidney. In particular, the first clinical trial with spectral imaging in minimally invasive surgery demonstrated that video-rate ischemia monitoring is now possible with deep learning

Efficient spectrum reuse in cellular networks with stochastic optimization

[SPA]Aproximadamente cada diez a~nos, una nueva tecnolog a celular es desarrollada y puesta en el mercado. Sin embargo, lo operadores se ven obligados a mantener sus redes antiguas debido a que no todos los usuarios migran a nuevas redes a la vez. Por tanto, el espectro asociado a esas redes antiguas cada vez est a m as infrautilizado. Usando t ecnicas de radio cognitiva, el operador puede permitir a los usuarios de las redes m as nuevas a reutilizar ese espectro. Se propone un esquema de acceso semi-distribuido donde el operador gu a al usuario secundario difundiendo algunos par ametros operacionales de la estrategia de acceso. Este mecanismo aprende de forma din amica los par ametros optimos por medio del algoritmo Response Surface Methodology (RSM), que requiere muy poca se~nalizaci on. Los resultados muestras un notable aumento de la capacidad comparado con los cl asicos esquemas de uso de oportunidades temporales o espaciales.[ENG]As cellular network technology evolves, the operators deploy new generation networks while maintaining their legacy networks, since not all users upgrade their terminals at the same pace. Therefore, the spectrum associated to these legacy networks becomes gradually underused. By means of cognitive radio techniques, the operator can allow its new generation terminals to reuse this spectrum. We propose a semi-decentralized scheme in which the operator guides the secondary access by broadcasting some operational parameters of the access strategy. The mechanism dynamically learns the optimal parameters by means of a response surface methodology (RSM), implying a very small signaling overhead. Our results show a notable capacity improvement compared to the classical approaches of exploiting spatial or temporal opportunities.Escuela Técnica Superior de Ingeniería de TelecomunicaciónUniversidad Politécnica de CartagenaUniversidad Politécnica de Cartagen

Complexity and Sociocultural Urbanization of Spare Time in Magdalena Mixhuca Sports City

This article derives from my thesis research project “Fragmentation and sociocultural urbanization of spare time. High-significance places in Magdalena Mixhuca Sports City”. Its purpose is to concisely present those considerations that allowed integrating transdisciplinary epistemological and methodological frameworks. An analytical method was designed to integrate epistemological considerations for cultural and deep hermeneutics analysis, and the principles of complex thinking and complex systems theory, with the purpose of explaining the spare time sociocultural urbanization that is taking place in this fragmented public space that is characteristic of Mexico City. We present here some of the results of the implementation of this analytical method based on hologramatic, recursive and dialogic principles, that allowed interpreting Magdalena Mixhuca Sports City (at first sight considered fragmented, disarticulated and chaotic) as a fractal space, integrated by symbolic forms, socially and historically structured in this public space, from its origin, in 1958, up to the 21st century. We can conclude that these symbolic forms, located within a complex system, are condensed in high significance places such as Juan Escutia Sports Palace, Rodríguez Brothers Racetrack, Foro Sol, Gates 3 and 2, and Agustín Melgar Olympic Velodrome Esplanade, all of which have their own cultural dynamics that determine the characteristics, as a whole, of this sport centre

Parientes mayores de Guipúzcoa: señores del palacio casa-fuerte de Murguía en Astigarraga

Genealogía de la casa de Murguía. Se dan las biografías de algunas de las personas que pertenecen a esta familia. Los más antiguos señores de Murguía son los del linaje de SalcedoGenealogy of the house of Murguía. The author provides the biography of some of the persons that belonged to this family. The most ancient Lords of Murguía proceed from the Salcedo lineag