Class Distribution Monitoring for Concept Drift Detection

We introduce Class Distribution Monitoring (CDM), an effective concept-drift detection scheme that monitors the class-conditional distributions of a datastream. In particular, our solution leverages multiple instances of an online and nonparametric change-detection algorithm based on QuantTree. CDM reports a concept drift after detecting a distribution change in any class, thus identifying which classes are affected by the concept drift. This can be precious information for diagnostics and adaptation. Our experiments on synthetic and real-world datastreams show that when the concept drift affects a few classes, CDM outperforms algorithms monitoring the overall data distribution, while achieving similar detection delays when the drift affects all the classes. Moreover, CDM outperforms comparable approaches that monitor the classification error, particularly when the change is not very apparent. Finally, we demonstrate that CDM inherits the properties of the underlying change detector, yielding an effective control over the expected time before a false alarm, or Average Run Length (ARL0)

Open-Set Recognition: an Inexpensive Strategy to Increase DNN Reliability

Deep Neural Networks (DNNs) are nowadays widely used in low-cost accelerators, characterized by limited computational resources. These models, and in particular DNNs for image classification, are becoming increasingly popular in safety-critical applications, where they are required to be highly reliable. Unfortunately, increasing DNNs reliability without computational overheads, which might not be affordable in low-power devices, is a non-trivial task. Our intuition is to detect network executions affected by faults as outliers with respect to the distribution of normal network's output. To this purpose, we propose to exploit Open-Set Recognition (OSR) techniques to perform Fault Detection in an extremely low-cost manner. In particuar, we analyze the Maximum Logit Score (MLS), which is an established Open-Set Recognition technique, and compare it against other well-known OSR methods, namely OpenMax, energy-based out-of-distribution detection and ODIN. Our experiments, performed on a ResNet-20 classifier trained on CIFAR-10 and SVHN datasets, demonstrate that MLS guarantees satisfactory detection performance while adding a negligible computational overhead. Most remarkably, MLS is extremely convenient to configure and deploy, as it does not require any modification or re-training of the existing network. A discussion of the advantages and limitations of the analysed solutions concludes the paper

Aliskiren affects fatty-acid uptake and lipid-related genes in rodent and human cardiomyocytes

International audienceWe investigated whether the direct renin inhibitor aliskiren can affect metabolism in cardiomyocytes from rat, mouse and human sources. METHODS AND RESULTS: At 10-50μmol/L, aliskiren significantly increased medium-chain-fatty-acid uptake in primary-cultured neonatal-rat and HL-1 adult-mouse-derived cardiomyocytes (BODIPY-induced fluorescence intensity). The fatty-acid transporter CD-36 was correspondingly translocated to, but the glucose transporter Glut-4 away from, the sarcoplasmic reticulum/plasma membrane, in primary-cultured neonatal-rat (CD-36, Glut-4) and adult-human (CD-36) cardiomyocytes (confocal immunocytochemistry). Immunoblotting showed that aliskiren induced phosphorylation of ERK1/2 in cardiomyocytes from all three sources; responses were dose- and time-dependent, unaffected by renin treatment, and did not cause alterations in expression of (P)R or Igf2/M6P receptors. Microarray analysis of the complete genome of aliskiren-treated neonatal-rat cardiomyocytes, with RT-qPCR and immunoblot confirmation assays in rat and human primary cardiomyocytes, showed that aliskiren up-regulated mRNA and increased protein expression of several enzymes important in lipid and glucose metabolism and in cholesterol biosynthesis. Cardiomyocyte cell-cycle and viability were unaffected by aliskiren

Implementation of an improvement plan for project planning through the lean methodology for increase the metalworking SME’ efficiency in the industrial in Lima

Mantener una alta eficiencia es crucial para las empresas actuales, especialmente las pequeñas y medianas. En el sector metalmecánico peruano, este indicador determina la capacidad de mantener una presencia competitiva. Numerosas pymes en este sector han experimentado un crecimiento notable en producción, acompañado de mejoras en eficiencia operativa. Esta tesis se centra en un caso específico: una empresa metalmecánica mediana en Lima, dedicada a proyectos de mejora de maquinaria para el sector pesquero. A pesar de su contribución al sector, enfrenta un déficit de eficiencia significativo en comparación con el promedio del sector, impactando sus ingresos. El objetivo es presentar una propuesta de mejora basada en ingeniería. Se propone utilizar herramientas de Gestión de Procesos Empresariales (BPM), pronósticos Holt-Winter y el modelo de inventario (Q, s) para cerrar la brecha de eficiencia técnica. Se sugiere la metodología DMAIC para supervisar la implementación y revisiones periódicas para fomentar la mejora continua y el crecimiento sostenido. La esencia reside en mejorar la eficiencia de la empresa metalmecánica limeña. Se espera que la implementación eficiente de estas herramientas eleve la eficiencia del 77% a un nuevo pico del 90%, cumpliendo el objetivo de mejora del 13%. La validación de resultados se realizará mediante simulación de sistemas. En resumen, este estudio aborda un desafío clave en el sector metalmecánico peruano, proponiendo soluciones basadas en ingeniería y metodologías probadas. La implementación exitosa debería posicionar a la empresa para competir eficazmente, contribuyendo al crecimiento continuo del sector.Maintaining a high efficiency ratio is a very important problem for any business today, especially if it is a small or medium-sized business. In the specific case of these, it is a determinant of whether or not they remain in the market of which they are part. In Peru, the metalworking sector is made up of many of these SMEs, which have been experiencing a boom in their production levels in recent years. This productive growth has been accompanied by an increase in the average efficiency with which these companies work. The following article takes as a case study a medium-sized metalworking company based in Lima, Peru, which is dedicated to carrying out projects to improve machinery of companies in the fishing sector, and which presents a problem of low efficiency in carrying out these projects., compared to the average efficiency of the sector. This problem is evidenced by a high economic impact on their income. The objective of this study is to present an improvement proposal based on engineering tools that allows the industry under study to equalize the technical efficiency gap that it maintains with the metalworking sector. For this, it is proposed to make use of the BPM tools, Holt-Winter forecasts and the inventory model (Q, s). Taking this into account, it is proposed to use the DMAIC methodology for the correct monitoring of the implementation of the proposal, as well as a periodic review of the proposal that allows reaching a state of continuous improvement and the growth of the company. The problem to be solved will be to improve the efficiency of a metalworking enterprise based in Lima, Peru, and the expected results will be validated by a systems simulation and in turn will indicate that due to a good implementation of the aforementioned tools, an increase from 77% to a new height of 90%, which will meet the goal of improvement by 13%.Trabajo de Suficiencia Profesiona

A Weighted Loss Function to Predict Control Parameters for Supercontinuum Generation Via Neural Networks

Supercontinuum light is generated by a train of laser pulses propagating in an optical fiber. The parameters characterizing these pulses influence the spectrum of the light as it exits the fiber. While spectrum generation is a direct process governed by nonlinear equations that can be reproduced through numerical simulation, determining the parameters of the pulse generating a given spectrum is a difficult inverse problem. Solving this inverse problem has a relevant practical implication, as it allows generating beams with desired spectral properties. We solve this multidimensional parameter estimation problem by training a neural network and we introduce, as key technical contribution, a weighted loss function that improves the estimation accuracy. Most remarkably, this loss function is not specific to the considered supercontinuum scenario, but has the potential to improve solutions of similar inverse problems where the forward process can be reproduced via computationally demanding simulations. Our experiments demonstrate the effectiveness of the pursued approach and of our weighted loss function

Derecho Empresarial 1-DE119-200701

El presente curso busca acercar al alumno de manera introductoria al conocimiento de ciertas instituciones jurídicas fundamentales con las cuales será frecuente que se relacione directa o indirectamente en el transcurso de su ejercicio profesional.Al efecto en la primera parte del curso se procurará ubicar conceptualmente al alumno en la estructura funcional y orgánica del Estado peruano. Ello se lograra a través de un enfoque analítico del las principales instituciones estatales según lo dispuesto por el marco constitucional vigente.Una vez que adquiera una visión global del ámbito de actuación el rol y la importancia de las entidades y organismos que intervienen en la creación y aplicación del derecho se le brindaran herramientas que le permiten conocer de modo general los métodos que utiliza el abogado para aplicar los conocimientos jurídicos en la solución de problemas concretos

Cirurgia híbrida na exérese de tumor glômico Shamblin II

Resumo O tumor glômico é uma neoplasia benigna rara originada de células paraganglionares da crista neural que se desenvolve na camada adventícia do vaso. São tumores não encapsulados e altamente vascularizados. Paciente feminina, 64 anos, foi diagnosticada com tumor glômico hipervascularizado com 5 cm posteriormente à bifurcação carotídea esquerda e oclusão de carótida contralateral. Optou-se por realizar embolização através de acesso endovascular seguida de punção percutânea direta, guiada por angiografia, para preenchimento da área remanescente. Após embolização, realizou-se a exérese cirúrgica do tumor com menor sangramento e maior facilidade para encontrar o plano de clivagem das estruturas adjacentes. Em acompanhamento tardio, a paciente apresenta-se sem recidiva tumoral. O tumor foi classificado como pertencente ao grupo Shamblin II, o qual inclui tumores apresentando de 4 a 6 cm com inserção arterial moderada. Através dessa dupla abordagem, foi possível notar uma redução relativa do sangramento intraoperatório e facilitação de identificação do plano de clivagem, colaborando para sua exérese e evitando o pinçamento cirúrgico

Automated radiosynthesis and preclinical evaluation of two new PSMA-617 derivatives radiolabelled via [18F]AlF2+ method

Abstract Background In the last decade the development of new PSMA-ligand based radiopharmaceuticals for the imaging and therapy of prostate cancer has been a highly active and important area of research. The most promising derivative in terms of interaction with the antigen and clinical properties has been found to be “PSMA-617”, and its lutetium-177 radiolabelled version has recently been approved by EU and USA regulatory agencies for therapeutic purposes. For the above reasons, the development of new derivatives of PSMA-617 radiolabelled with fluorine-18 may still be of great interest. This paper proposes the comparison of two different PSMA-617 derivatives functionalized with NODA and RESCA chelators, respectively, radiolabelled via [18F]AlF2+ complexation. Results The organic synthesis of two PSMA-617 derivatives and their radiolabelling via [18F]AlF2+ complexation resulted to proceed efficiently and successfully. Moreover, stability in solution and in plasma has been evaluated. The whole radiosynthesis procedure has been fully automated, and the final products have been obtained with radiochemical yield and purity potentially suitable for clinical studies. The biodistribution of the two derivatives was performed both in prostate cancer and glioma tumour models. Compared with the reference [18F]F-PSMA-1007 and [18F]F-PSMA-617-RESCA, [18F]F-PSMA-617-NODA derivative showed a higher uptake in both tumors, faster clearance in non-target organs, and lower uptake in salivary glands. Conclusion PSMA-617 NODA and RESCA derivatives were radiolabelled successfully via [18F]AlF2+ chelation, the former being more stable in solution and human plasma. Moreover, preclinical biodistribution studies showed that [18F]F-PSMA-617-NODA might be of potential interest for clinical applications