BlockChain Platforms in Financial Services: Current Perspective

Background: BlockChain technology was invented to support bitcoin, currently the most popular virtual currency. Objectives: The purpose of this paper is to investigate contemporary BlockChain platforms in financial services. Methods/Approach: An unstructured literature review has been used. Results: BlockChain in financial services is mostly associated with bitcoin exchange. However, this is a partial view of both BlockChain technology and its possible adoption for financial services: in fact, many BlockChain platforms are now available and many different financial services can be effectively supported by BlockChain platforms, even though they are not based on virtual-money exchange. Furthermore, people are attracted by the concept of smart contract, i.e., a contract that is automatically executed by computer technology, without human intervention. Conclusions: The contribution of this paper is twofold: first of all, we introduce the four BlockChain platforms that are now most popular, discussing how they support the smart contract concept; second, we identify some typical categories of financial services, matching each of them with the platform that provides the best support for each category

Efficient Object Detection in Autonomous Driving using Spiking Neural Networks: Performance, Energy Consumption Analysis, and Insights into Open-set Object Discovery

Besides performance, efficiency is a key design driver of technologies supporting vehicular perception. Indeed, a well-balanced trade-off between performance and energy consumption is crucial for the sustainability of autonomous vehicles. In this context, the diversity of real-world contexts in which autonomous vehicles can operate motivates the need for empowering perception models with the capability to detect, characterize and identify newly appearing objects by themselves. In this manuscript we elaborate on this threefold conundrum (performance, efficiency and open-world learning) for object detection modeling tasks over image data collected from vehicular scenarios. Specifically, we show that well-performing and efficient models can be realized by virtue of Spiking Neural Networks (SNNs), reaching competitive levels of detection performance when compared to their non-spiking counterparts at dramatic energy consumption savings (up to 85%) and a slightly improved robustness against image noise. Our experiments herein offered also expose qualitatively the complexity of detecting new objects based on the preliminary results of a simple approach to discriminate potential object proposals in the captured image.Comment: 8 pages, 5 figures, presented at ITSC202

Defects in Tracheoesophageal and Lung Morphogenesis inNkx2.1(−/−) Mouse Embryos

AbstractNKX2.1 is a homeodomain transcriptional factor expressed in thyroid, lung, and parts of the brain. We demonstrate that septation of the anterior foregut along the dorsoventral axis, into distinct tracheal and esophageal structures, is blocked in mouse embryos carrying a homozygous targeted disruption of theNkx2.1locus. This is consistent with the loss ofNkx2.1expression, which defines the dorsoventral boundary within the anterior foregut in wild-type E9 embryos. Failure in septation between the trachea and the esophagus inNkx2.1(−/−) mice leads to the formation of a common lumen that connects the pharynx to the stomach, serving both as trachea and as esophagus, similar in phenotype to a human pathologic condition termed tracheoesophageal fistula. The main-stem bronchi bifurcate from this common structure and connect to profoundly hypoplastic lungs. The mutant lungs fail to undergo normal branching embryogenesis, consist of highly dilated sacs that are not capable of sustaining normal gas exchange functions, and lead to immediate postnatal death.In situhybridization suggests reducedBmp-4expression in the mutant lung epithelium, providing a possible mechanistic clue for impaired branching. Functional deletion ofNkx2.1blocks pulmonary-specific epithelial cell differentiation marked by the absence of pulmonary surfactant protein gene expression. Altered expression of temporally regulated genes such asVegfdemonstrates that the lung inNkx2.1(−/−) mutant embryos is arrested at early pseudoglandular (E11–E15) stage. These results demonstrate a critical role forNkx2.1in morphogenesis of the anterior foregut and the lung as well as in differentiation of pulmonary epithelial cells

Managing the unknown: a survey on Open Set Recognition and tangential areas

In real-world scenarios classification models are often required to perform robustly when predicting samples belonging to classes that have not appeared during its training stage. Open Set Recognition addresses this issue by devising models capable of detecting unknown classes from samples arriving during the testing phase, while maintaining a good level of performance in the classification of samples belonging to known classes. This review comprehensively overviews the recent literature related to Open Set Recognition, identifying common practices, limitations, and connections of this field with other machine learning research areas, such as continual learning, out-of-distribution detection, novelty detection, and uncertainty estimation. Our work also uncovers open problems and suggests several research directions that may motivate and articulate future efforts towards more safe Artificial Intelligence methods.Comment: 35 pages, 1 figure, 1 tabl

Smad4-Shh-Nfic Signaling Cascade–Mediated Epithelial-Mesenchymal Interaction Is Crucial in Regulating Tooth Root Development

Transforming growth factor β (TGF-β)/bone morphogenetic protein (BMP) signaling is crucial for regulating epithelial-mesenchymal interaction during organogenesis, and the canonical Smad pathway–mediated TGF-β/BMP signaling plays important roles during development and disease. During tooth development, dental epithelial cells, known as Hertwig's epithelial root sheath (HERS), participate in root formation following crown development. However, the functional significance of HERS in regulating root development remains unknown. In this study we investigated the signaling mechanism of Smad4, the common Smad for TGF-β/BMP signaling, in HERS in regulating root development. Tissue-specific inactivation of Smad4 in HERS results in abnormal enamel and dentin formation in K14-Cre;Smad4fl/fl mice. HERS enlarges but cannot elongate to guide root development without Smad4. At the molecular level, Smad4-mediated TGF-β/BMP signaling is required for Shh expression in HERS and Nfic (nuclear factor Ic) expression in the cranial neural crest (CNC)-derived dental mesenchyme. Nfic is crucial for root development, and loss of Nfic results in a CNC-derived dentin defect similar to the one of K14-Cre;Smad4fl/fl mice. Significantly, we show that ectopic Shh induces Nfic expression in dental mesenchyme and partially rescues root development in K14-Cre;Smad4fl/fl mice. Taken together, our study has revealed an important signaling mechanism in which TGF-β/BMP signaling relies on a Smad-dependent mechanism in regulating Nfic expression via Shh signaling to control root development. The interaction between HERS and the CNC-derived dental mesenchyme may guide the size, shape, and number of tooth roots. © 2010 American Society for Bone and Mineral Research

Atrapamiento nefroesplénico en équidos: revisión bibliográfica y estudio retrospectivo en el HVUZ

El atrapamiento nefroesplénico (ANE) es un tipo de cólico que se da con relativa frecuencia en la clínica equina y que es de especial interés puesto que existen diferentes posibilidades de tratamiento médico (rolling, fenilefrina (FE), ejercicio y/o fluidoterapia) y/o quirúrgico a la hora de hacer frente al caballo con posible ANE. Asimismo, también existe la posibilidad de cerrar el espacio nefroesplénico, con el objetivo de evitar recidivas.Por todo ello, este Trabajo de Fin de Grado tiene como objetivos la realización de una revisión bibliográfica exhaustiva sobre el ANE y las diferentes técnicas que existen para su resolución y un estudio retrospectivo de los casos de ANE tratados en el Hospital Veterinario de la Universidad de Zaragoza (HVUZ).Para la revisión bibliográfica se seleccionaron 35 trabajos y 4 libros, obteniendo los siguientes porcentajes de éxito de cada tratamiento: rolling 74% (91/123), FE + rolling 91,2% (103/113), FE + ejercicio 87,4% (111/127), tratamiento médico 84,6% (357/422) y tratamiento quirúrgico 98,4% (418/425). Asimismo, para el retrospectivo de un total de 419 casos de cólico revisados,20 fueron ANE, obteniendo los siguientes resultados: tratamiento médico 82,3% (14/17) de éxito, quirúrgico 100% (6/6), rolling 83,3% (10/12) y FE + ejercicio 50% (3/6).Para la mayoría de variables, no se encontraron diferencias destacadas entre nuestros resultados y los de la bibliografía. La preferencia fue el tratamiento médico, siempre que el estado del animal lo permita, obteniendo buenos resultado con el rolling. La FE se usó en menos ocasiones (en parte por consideraciones normativas) y con menos eficacia. Asimismo, la tasa de supervivencia fue similar o incluso superior a los datos obtenidos en la bibliografía.Por lo tanto, el ANE puede ser tratado con buenos resultados mediante rolling, sin necesidad de prescripción excepcional de FE, y la cirugía puede reservarse solo para situaciones concretas.<br /

Optimal Maintenance Thresholds to Perform Preventive Actions by Using Multi-Objective Evolutionary Algorithms

Maintenance has always been a key activity in the manufacturing industry because of its economic consequences. Nowadays, its importance is increasing thanks to the Industry 4.0 or fourth industrial revolution. There are more and more complex systems to maintain, and maintenance management must gain efficiency and effectiveness in order to keep all these devices in proper conditions. Within maintenance, Condition-Based Maintenance (CBM) programs can provide significant advantages, even though often these programs are complex to manage and understand. For this reason, several research papers propose approaches that are as simple as possible and can be understood by users and modified by experts. In this context, this paper focuses on CBM optimization in an industrial environment, with the objective of determining the optimal values of preventive intervention limits for equipment under corrective and preventive maintenance cost criteria. In this work, a cost-benefit mathematical model is developed. It considers the evolution in quality and production speed, along with condition based, corrective and preventive maintenance. The cost-benefit optimization is performed using a Multi-Objective Evolutionary Algorithm. Both the model and the optimization approach are applied to an industrial case.This research was funded by the HAZITEK call of the Basque Government, project acronym HORDAGO