An energy-based model for neuro-symbolic reasoning on knowledge graphs

Machine learning on graph-structured data has recently become a major topic in industry and research, finding many exciting applications such as recommender systems and automated theorem proving. We propose an energy-based graph embedding algorithm to characterize industrial automation systems, integrating knowledge from different domains like industrial automation, communications and cybersecurity. By combining knowledge from multiple domains, the learned model is capable of making context-aware predictions regarding novel system events and can be used to evaluate the severity of anomalies that might be indicative of, e.g., cybersecurity breaches. The presented model is mappable to a biologically-inspired neural architecture, serving as a first bridge between graph embedding methods and neuromorphic computing - uncovering a promising edge application for this upcoming technology.Comment: Accepted for publication at the 20th IEEE International Conference on Machine Learning and Applications (ICMLA 2021

SpikE: spike-based embeddings for multi-relational graph data

Despite the recent success of reconciling spike-based coding with the error backpropagation algorithm, spiking neural networks are still mostly applied to tasks stemming from sensory processing, operating on traditional data structures like visual or auditory data. A rich data representation that finds wide application in industry and research is the so-called knowledge graph - a graph-based structure where entities are depicted as nodes and relations between them as edges. Complex systems like molecules, social networks and industrial factory systems can be described using the common language of knowledge graphs, allowing the usage of graph embedding algorithms to make context-aware predictions in these information-packed environments. We propose a spike-based algorithm where nodes in a graph are represented by single spike times of neuron populations and relations as spike time differences between populations. Learning such spike-based embeddings only requires knowledge about spike times and spike time differences, compatible with recently proposed frameworks for training spiking neural networks. The presented model is easily mapped to current neuromorphic hardware systems and thereby moves inference on knowledge graphs into a domain where these architectures thrive, unlocking a promising industrial application area for this technology.Comment: Accepted for publication at IJCNN 202

Machine learning on knowledge graphs for context-aware security monitoring

Machine learning techniques are gaining attention in the context of intrusion detection due to the increasing amounts of data generated by monitoring tools, as well as the sophistication displayed by attackers in hiding their activity. However, existing methods often exhibit important limitations in terms of the quantity and relevance of the generated alerts. Recently, knowledge graphs are finding application in the cybersecurity domain, showing the potential to alleviate some of these drawbacks thanks to their ability to seamlessly integrate data from multiple domains using human-understandable vocabularies. We discuss the application of machine learning on knowledge graphs for intrusion detection and experimentally evaluate a link-prediction method for scoring anomalous activity in industrial systems. After initial unsupervised training, the proposed method is shown to produce intuitively well-calibrated and interpretable alerts in a diverse range of scenarios, hinting at the potential benefits of relational machine learning on knowledge graphs for intrusion detection purposes.Comment: Accepted for publication at IEEE-CSR 2021. Data is available on https://github.com/dodo47/cyberM

Neuro-symbolic computing with spiking neural networks

Knowledge graphs are an expressive and widely used data structure due to their ability to integrate data from different domains in a sensible and machine-readable way. Thus, they can be used to model a variety of systems such as molecules and social networks. However, it still remains an open question how symbolic reasoning could be realized in spiking systems and, therefore, how spiking neural networks could be applied to such graph data. Here, we extend previous work on spike-based graph algorithms by demonstrating how symbolic and multi-relational information can be encoded using spiking neurons, allowing reasoning over symbolic structures like knowledge graphs with spiking neural networks. The introduced framework is enabled by combining the graph embedding paradigm and the recent progress in training spiking neural networks using error backpropagation. The presented methods are applicable to a variety of spiking neuron models and can be trained end-to-end in combination with other differentiable network architectures, which we demonstrate by implementing a spiking relational graph neural network.Comment: Accepted for publication at the International Conference on Neuromorphic Systems (ICONS) 202

El sistema de gestión de la calidad en la Facultad de Química de la Universitat de Barcelona

El Real Decreto 1393/2007 obliga a que todos los estudios de grado tengan un sistema de garantía de la calidad. En esta línea, la Facultad de Química de la Universitat de Barcelona ha creado su Sistema de Gestión de la Calidad (SGC). Este SGC empieza con la definición de la Política de Calidad, Medio Ambiente y Seguridad, continúa con el mapa de procesos de la docencia, sigue con la redacción de todos los procedimientos necesarios para documentar cómo llevar a cabo cada uno de los procesos y finaliza con la preparación de las herramientas de análisis y mejora como indicadores, auditorías, etc. Está previsto que su implementación se lleve a cabo a lo largo del año 2012

Revista de Vertebrados de la Estación Biológica de Doñana

Página 298 con error de impresiónEstudio cariológico en dos especies de Serránidos del Mediterráneo (Peces: PerciformesRelaciones morfométricas de Atherina boyeri Risso (Pisces: Atherinidae) de la laguna de Zoñar (Córdoba, España)Contribución al conocimiento de la biometríay osteología de Barbus barbus bocagei, Steindachner, 1866 (Pisces: CyprinidaeLa actividad de la salamandra, Salamandra salamandra (L.), en Galicia.Estudios sobre el sapo corredor (Bufo calamita) en el Sur de España.1. BiometríaEstudios sobre el sapo corredor (Bufo calamita) en el Sur de España. II. AlimentaciónBiología de la reproducción de Rana iberica Boulenger 1879 en zonas simpátridas con Rana temporaria Linneo, 1758Nuevos datos sobre la distribución geográfica de Lacerta monticola cantabrica Mertens, 1929. (Sauria, lacertidae).Datos sobre Lacerta monticola Boulenger, 1905 (Saurio: lacertidae)en el oeste del Sistema Central.Nueva especie de Anolis (lacertilia, Iguanidae) para CubaEtograma cuantificado del cortejo en Falco naumannOntogénesis del comportamiento predador en Falco naumanniContaminación xenobiótica del Parque Nacional de Doñana. 1. Residuos de insecticidas organoclorados, bifenilos policlorados y mercurio en anseriformes y gruiformesReproducción del críalo (Clamator glandarius) en Sierra Morena CentraNidificación de Picus viridis en taludes de arcilla en Ramblas de Guadix (Granada)Comportamiento del calamón Porphyrio porphyrio (Linnaeus, 1758) en Doñana, Marismas del GuadalquiviBiología y ecología de la malvasía (Oxyura leucocephala) en Andalucía.On the differential diet of Carnivora in islands:a method for analysing it and a particular case.Notas sobre la distribución pasada y actual del meloncillo Herpestes ichneumon (L.) en la Península IbéricaEstructuración de las interacciones en una camada de lobos (Canís lupus)Nuevos datos sobre la distribución del Cottus gobio L. (pisces, cottidae) en EspañaSobre la alimentación de Callopistes maculatus (Reptilia,teiidaeObservación de Lacerta lepida depredando un nido de Alectoris rufaNueva cita del galápago leproso Mauremys leprosa (Scheigger, 1812) en los pirineosPrimera cita de Psammodromus hispanicus (Fitzinger) para GaliciaSobre la presencia de Gallotia (=Lacerta) atlantica (Peters y Doria, 1882) en Gran CanariaNota sobre las Lacerta monticola Boulenger, 1905 de las zonas del norte de GaliciaPrimeras notas herpetológicas de la provincia de Soria.Datos sobre selección de hábitat y ecología alimenticia del porrón pardo (Aythya nyroca)Probable nueva área de cría del pechiazul (Luscinia svecica cyanecula) en el sistema central. PerisPredación de Falco peregrinus y Falco subbuteo sobre quirópterosResultados de la producción de Oxyura leucocephala en el año 1981 en las lagunas de Zóñar y el rincónAnálisis de la dieta de Tyto alba en un medio árido antropógeno de los alrededores de Almería¿Son Eudocimus ruber y E. albus distintas especies?EL Estornino pinto (Sturnus vulgaris) en Canarias: nueva especie nidifiante en el archipiélagoDatos sobre la alimentación otoñal del cárabo (Strix aluco) en la sierra de CádizObservación primaveral de rapaces y otras aves en el páramo del estado de Mérida (Venezuela).Murciélago hematófago (Desmodus rotundus) parasitando a un chigüire (Hidrochoerus hydrochaeris)Observaciones sobre la reproducción del zacatuche o teporinho Romerolagus diazi (Mammalia: lagomorpha)Estudio electroforético de hemoglobinas y esterasas sanguíneas en Rhinolophus ferrumequinum (Chiroptera: rhinolophidae) y de hemoglobinas en Tadaria taeniotis (chiroptera: molossidae)Peer reviewe

Discourse Analysis and Terminology in Languages for Specific Purposes

Aquest importantíssim recull conté estudis i reflexions sobre temes rellevants en la recerca sobre LSP: anglès mèdic, el llenguatge de la publicitat i periodístic, telecomunicacions i terminologia informàtica, llenguatge comercial i jurídic... Malgrat que gran part dels treballs aplegats es refereixen a l'anglès, també hi ha que tracten l'alemany, francès i altres llengües. Conté textos en anglès, francés, portuguès i castellà

Association of Candidate Gene Polymorphisms With Chronic Kidney Disease: Results of a Case-Control Analysis in the Nefrona Cohort

Chronic kidney disease (CKD) is a major risk factor for end-stage renal disease, cardiovascular disease and premature death. Despite classical clinical risk factors for CKD and some genetic risk factors have been identified, the residual risk observed in prediction models is still high. Therefore, new risk factors need to be identified in order to better predict the risk of CKD in the population. Here, we analyzed the genetic association of 79 SNPs of proteins associated with mineral metabolism disturbances with CKD in a cohort that includes 2, 445 CKD cases and 559 controls. Genotyping was performed with matrix assisted laser desorption ionizationtime of flight mass spectrometry. We used logistic regression models considering different genetic inheritance models to assess the association of the SNPs with the prevalence of CKD, adjusting for known risk factors. Eight SNPs (rs1126616, rs35068180, rs2238135, rs1800247, rs385564, rs4236, rs2248359, and rs1564858) were associated with CKD even after adjusting by sex, age and race. A model containing five of these SNPs (rs1126616, rs35068180, rs1800247, rs4236, and rs2248359), diabetes and hypertension showed better performance than models considering only clinical risk factors, significantly increasing the area under the curve of the model without polymorphisms. Furthermore, one of the SNPs (the rs2248359) showed an interaction with hypertension, being the risk genotype affecting only hypertensive patients. We conclude that 5 SNPs related to proteins implicated in mineral metabolism disturbances (Osteopontin, osteocalcin, matrix gla protein, matrix metalloprotease 3 and 24 hydroxylase) are associated to an increased risk of suffering CKD

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe