Mercados emergentes e Infraestructura : análisis de infraestructura en desarrollo y en futuro de India

El papel de las infraestructuras en el desarrollo económico de los países emergentes es un tema clave que ha sido puesto de relieve en muchos estudios y es uno de los elementos que más ha influido en las políticas de desarrollo y cooperación de los diferentes países e instituciones. El objetivo de este TFG es analizar esta relación entre Infraestructuras y países emergentes, y aplicarlo al caso de la India, uno de los países más poblados del mundo, con un gran tamaño, y una economía que en las últimas décadas está experimentando una profunda transformació

Complementary Skyrmion Racetrack Memory with Voltage Manipulation

Magnetic skyrmion holds promise as information carriers in the next-generation memory and logic devices, owing to the topological stability, small size and extremely low current needed to drive it. One of the most potential applications of skyrmion is to design racetrack memory (RM), named Sk-RM, instead of utilizing domain wall (DW). However, current studies face some key design challenges, e.g., skyrmion manipulation, data representation and synchronization etc. To address these challenges, we propose here a complementary Sk-RM structure with voltage manipulation. Functionality and performance of the proposed design are investigated with micromagnetic simulations.Comment: 3 pages, 4 figure

PFAS and their substitutes in groundwater: Occurrence, transformation and remediation

Poly- and perfluoroalkyl substances (PFAS) are increasingly investigated due to their global occurrence and potential human health risk. The ban on PFOA and PFOS has led to the use of novel substitutes such as GenX, F-53B and OBS. This paper reviews the studies on the occurrence, transformation and remediation of major PFAS i.e. PFOA, PFNA, PFBA, PFOS, PFHxS, PFBS and the three substitutes in groundwater. The data indicated that PFOA, PFBA, PFOS and PFBS were present at high concentrations up to 21,200 ng L−1 while GenX and F-53B were found up to 30,000 ng L−1 and 0.18–0.59 ng L−1, respectively. PFAS in groundwater are from direct sources e.g. surface water and soil. PFAS remediation methods based on membrane, redox, sorption, electrochemical and photocatalysis are analyzed. Overall, photocatalysis is considered to be an ideal technology with low cost and high degradation efficacy for PFAS removal. Photocatalysis could be combined with electrochemical or membrane filtration to become more advantageous. GenX, F-53B and OBS in groundwater treatment by UV/sulfite system and electrochemical oxidation proved effective. The review identified gaps such as the immobilization and recycling of materials in groundwater treatment, and recommended visible light photocatalysis for future studies

OnionNet-2: A Convolutional Neural Network Model for Predicting Protein-Ligand Binding Affinity based on Residue-Atom Contacting Shells

One key task in virtual screening is to accurately predict the binding affinity ($\triangle$$G$) of protein-ligand complexes. Recently, deep learning (DL) has significantly increased the predicting accuracy of scoring functions due to the extraordinary ability of DL to extract useful features from raw data. Nevertheless, more efforts still need to be paid in many aspects, for the aim of increasing prediction accuracy and decreasing computational cost. In this study, we proposed a simple scoring function (called OnionNet-2) based on convolutional neural network to predict $\triangle$$G$. The protein-ligand interactions are characterized by the number of contacts between protein residues and ligand atoms in multiple distance shells. Compared to published models, the efficacy of OnionNet-2 is demonstrated to be the best for two widely used datasets CASF-2016 and CASF-2013 benchmarks. The OnionNet-2 model was further verified by non-experimental decoy structures from docking program and the CSAR NRC-HiQ data set (a high-quality data set provided by CSAR), which showed great success. Thus, our study provides a simple but efficient scoring function for predicting protein-ligand binding free energy.Comment: 7 pages, 4 figures, 1 tabl