QuASeR -- Quantum Accelerated De Novo DNA Sequence Reconstruction

In this article, we present QuASeR, a reference-free DNA sequence reconstruction implementation via de novo assembly on both gate-based and quantum annealing platforms. Each one of the four steps of the implementation (TSP, QUBO, Hamiltonians and QAOA) is explained with simple proof-of-concept examples to target both the genomics research community and quantum application developers in a self-contained manner. The details of the implementation are discussed for the various layers of the quantum full-stack accelerator design. We also highlight the limitations of current classical simulation and available quantum hardware systems. The implementation is open-source and can be found on https://github.com/prince-ph0en1x/QuASeR.Comment: 24 page

Automating defects simulation and fault modeling for SRAMs

The continues improvement in manufacturing process density for very deep sub micron technologies constantly leads to new classes of defects in memory devices. Exploring the effect of fabrication defects in future technologies, and identifying new classes of realistic functional fault models with their corresponding test sequences, is a time consuming task up to now mainly performed by hand. This paper proposes a new approach to automate this procedure. The proposed method exploits the capabilities of evolutionary algorithms to automatically identify faulty behaviors into defective memories and to define the corresponding fault models and relevant test sequences. Target defects are modeled at the electrical level in order to optimize the results to the specific technology and memory architecture

I Jornadas científicas CIBM

Las primeras Jornadas del Centro de Investigación Biomédica han sido un éxito. Tenemos que felicitarnos todos, organizadores y participantes, por la gran calidad de las comunicaciones que se han presentado. Tuvimos un intenso día en que todos hemos participado con ilusión para mostrar a los demás nuestro trabajo. Todo buscamos alcanzar un nivel de excelencia en nuestras investigaciones. Espero que estas jornadas nos hayan permitido dar un paso más en este sentido.   La ciencia también es compartir. Compartir lo que hacemos, compartir nuestras técnicas, compartir lo que hemos aprendido aquí o en centros lejanos y punteros. Las fuerzas individuales son limitadas, pero los granos de arena que cada uno aportamos hacen posible la creación del gran edificio de la Ciencia. Ese ha sido el principal objetivo de las jornadas: conocer que estamos haciendo, compartir nuestros conocimientos y ver las posibilidades de colaboración que tenemos con los que están trabajando al lado. Cuando estamos en nuestro laboratorio es muy fácil aislarnos y dedicarnos a resolver los problemas del día a día. Pero muchas veces esos problemas se solucionan con más rapidez consultando y conociendo como otros lo han resuelto antes. Y también tenemos que saber hacia dónde va el conocimiento. Por eso es tan importante asistir a las reuniones científicas y relacionarse con los demás grupos.   Estamos preparando novedades interesantes en las próximas jornadas, pronto las conoceréis. Hasta entonces, trabajemos con ilusión y colaboremos entre todos para obtener los mejores resultados en nuestras investigaciones

Activitat cerebral i cognició: una connexió entre la termodinàmica i la teoria de la informació

El cervell pot ser conceptuat com un sistema termodinàmic i com un processador de la informació; conseqüentment, l'activitat cerebral pot ser modelada en termes termodinàmics i l'activitat cognitiva mitjançant la teoria de la informació. L'objectiu ha estat plantejar una estructura formal que permeti el lligam entre ambdós sistemes (activitat neuronal i cognicions) a partir de les connexions teòriques entre la termodinàmica i la teoria de la informació, disciplines on el concepte d'entropia és clau. El marc teòric proposat obriria les portes a una millor comprensió de la connexió entre mesures termodinàmiques de l'activitat neuronal amb l'activitat cognitiva i la seva corresponent càrrega informativa.The brain can be conceptualized as a thermodynamic system and as an information processor. Consequently, brain activity can be modelled in terms of thermodynamics and cognitive activity in information theoretic terms. The authors proposed a new formal structure that allows to link between both systems (neural and cognitive) from the theoretical connections between thermodynamics and information theory. This leverages the concept of entropy which is key in both disciplines. The theoretical framework proposed would open the doors to a better understanding of the connection between thermodynamic measurements of neural activity and cognitive informational load.El cerebro puede ser conceptuado como un sistema termodinámico y como un procesador de la información; consecuentemente, la actividad cerebral puede ser modelada en términos termodinámicos y la actividad cognitiva mediante la teoría de la información. El objetivo ha sido plantear una estructura formal que permita el vínculo entre ambos sistemas (actividad neuronal y cogniciones) a partir de las conexiones teóricas entre la termodinámica y la teoría de la información, disciplinas donde el concepto de entropía es clave. El marco teórico propuesto abriría las puertas a una mejor comprensión de la conexión entre las medidas termodinámicas de la actividad cerebral con la actividad cognitiva y su correspondiente carga informativa

Future Of Cluster Developments – Lessons From Energy Valley, The Netherlands

The research explored how a Dutch energy cluster embedded within a larger context of European and global developments reflected complex dynamics due to changes in its context. The case study explored Energy Valley of the Netherlands, a peripheral region that meets the challenge of energy transition, regional development and national economic interests. The research engaged complex adaptive systems approach to gain insights into complex cluster dynamics to contribute to cluster study and policy. The research captured insights into increased complexity of an energy cluster due to energy transition and other developments in the cluster context, exacerbated by differences in perceptions and responses of stakeholders to the new challenges. Findings on cluster developments included insights into cluster context, cluster condition, cluster dynamics and cluster transformations, and the interconnectedness of such developments based on Energy Valley and supplementary cases of Karlstad and Silicon Valley. The research findings led to insights into cluster systems developments and a model capturing cluster emergence. The research contributed to cluster theory by developing a CAS approach for cluster study that developed a whole systems approach to understand cluster dynamics, offering to the field of cluster study a qualitative understanding of cluster systems developments. Insights into interconnected developments at the micro, macro and inter-systemic levels, and into energy clusters in the context of energy transition were results of the research. The broad scope and nature of the study meant limitations were inherent and therefore recommendations for future research were included. EU Cluster Policy motivated the research and hence recommendations for policy developments were also part of the research contribution

A geometric view of cryptographic equation solving

This paper considers the geometric properties of the Relinearisation algorithm and of the XL algorithm used in cryptology for equation solving. We give a formal description of each algorithm in terms of projective geometry, making particular use of the Veronese variety. We establish the fundamental geometrical connection between the two algorithms and show how both algorithms can be viewed as being equivalent to the problem of finding a matrix of low rank in the linear span of a collection of matrices, a problem sometimes known as the MinRank problem. Furthermore, we generalise the XL algorithm to a geometrically invariant algorithm, which we term the GeometricXL algorithm. The GeometricXL algorithm is a technique which can solve certain equation systems that are not easily soluble by the XL algorithm or by Groebner basis methods