Imperfect forgiveness The pragmaticality, prudentiality and ethicality of human forgiveness

XXII Jornades de Foment de la Investigació de la Facultat de Ciències Humanes i Socials (Any 2017)The purpose of this paper is to approach the act and process of forgiveness as an imperfect human ability for peace, exploring the pragmaticality, prudentiality and ethicality of human forgiveness before moral wrongs. To conduct my research, firstly I will assume the epistemological turn that has been developed at the UNESCO Chair of Philosophy for Peace from Universitat Jaume I. This epistemological turn means we no longer work with a negative definition of peace but a positive one, that is, we do not define peace as the absence of violence, but as the presence of social justice. Secondly, I will establish a dialogue between the Philosophy for Peace approach and Christian theology as a key element for grasping a deeper understanding of the act and process of forgiveness, since this imperfect human ability of forgiveness has been a core theme of the Christian religion during the last two thousand years. It is argued that imperfect human forgiveness is pragmatically, prudentially and ethically adequate when we need to address different moral wrongs in different contexts of violence. Therefore, fostering forgiveness in those settings may help us to build more peaceful societies, as in the same way that we have learnt to hurt each other, we can learn to forgive one anothe

Independence numbers of some double vertex graphs and pair graphs

The combinatorial properties of double vertex graphs has been widely studied since the 90's. However only very few results are know about the independence number of such graphs. In this paper we obtain the independence numbers of the double vertex graphs of fan graphs and wheel graphs. Also we obtain the independence numbers of the pair graphs, that is a generalization of the double vertex graphs, of some families of graphs.Comment: 17 pages. Minor changes in the proof

The role of the tourism sector in economic development - Lessons from the Spanish experience

Tourism is one of the most important sectors in the world economy, and it is now considered as an efficient tool for promoting economic growth. In this respect, the experience of the Spanish economy is well known, and might be used to illustrate the benefits of the development of the tourism sector in lagging economies. Actually, there is wide consensus in the idea of its role in enhancing the Spanish industrialisation process. The foreign currency receipts from tourism contributed to finance the expansion of manufacturing by financing imports of capital goods. Moreover, the expansion of tourism in the last three decades has been unstoppable and beneficial for the economy in different aspects. The main purpose of this paper is to assess the real role of the tourism sector in the Spanish economy during the last three decades, paying especial attention to its contribution to the industrialisation of some of the less developed regions. Policy issues that are derived from the results for the Spanish experience should be useful for other developing countries in similar situations, and reveal how the tourist activity in those economies can benefit the overall economy, helping growth in other sectors.

Feedstocks development for Metal Injection Moulding

Today, more tan 90% of used feedstock for MIM in Europe, came from BASF (exclusive patent), with low possibility for change compositions or costs (in Japan or USA, the percentage is quite smaller). In our research group (Powder Technology Group) we can develop new feedstocks formulation that can be used directly by the MIM parts manufacturers and fulfilling their composition requirements. Interest in licensing the applied patent or commercial agreement with technical assistance with companies that would like to incorporate this technology

Deep Neural Networks for the Recognition and Classification of Heart Murmurs Using Neuromorphic Auditory Sensors

Auscultation is one of the most used techniques for detecting cardiovascular diseases, which is one of the main causes of death in the world. Heart murmurs are the most common abnormal finding when a patient visits the physician for auscultation. These heart sounds can either be innocent, which are harmless, or abnormal, which may be a sign of a more serious heart condition. However, the accuracy rate of primary care physicians and expert cardiologists when auscultating is not good enough to avoid most of both type-I (healthy patients are sent for echocardiogram) and type-II (pathological patients are sent home without medication or treatment) errors made. In this paper, the authors present a novel convolutional neural network based tool for classifying between healthy people and pathological patients using a neuromorphic auditory sensor for FPGA that is able to decompose the audio into frequency bands in real time. For this purpose, different networks have been trained with the heart murmur information contained in heart sound recordings obtained from nine different heart sound databases sourced from multiple research groups. These samples are segmented and preprocessed using the neuromorphic auditory sensor to decompose their audio information into frequency bands and, after that, sonogram images with the same size are generated. These images have been used to train and test different convolutional neural network architectures. The best results have been obtained with a modified version of the AlexNet model, achieving 97% accuracy (specificity: 95.12%, sensitivity: 93.20%, PhysioNet/CinC Challenge 2016 score: 0.9416). This tool could aid cardiologists and primary care physicians in the auscultation process, improving the decision making task and reducing type-I and type-II errors.Ministerio de Economía y Competitividad TEC2016-77785-