Arming NK cells with chimeric antigen receptors (CARs) for treatment of refractory and/or relapsed hematological cancers: preclinical study to determine the best cell source.

Las páginas 111 a 115 están sujetas a confidencialidad por la autora. 142 p.Acute Lymphoblastic Leukemia (ALL) and Chronic Lymphocytic Leukemia (CLL) are the most prevalent hematological cancers in children and elder patients respectively. Sometimes, standard treatments are not enough for curing these patients and new approaches, like immunotherapy need to be explored. In the last years, Chimeric Antigen Receptors (CARs) have arisen as one of the most promising immunotherapies. Usually these CARs are used along with T cells, developing CAR-T cells. Although autologous CAR-T cells have given very good results, their secondary side effects, like cytokine storm and neurotoxicity, are quite severe; and the CAR-T product manufacturing takes 5 weeks minimum. Because of that, we suggest NK cells as a vehicle for allogeneic CAR based treatments, as they do not cause secondary side effects or graft versus host disease. In this thesis, we look for the best cell source inorder to obtain the perfect NK cells for CAR based treatments

Using a Planar Array of MEMS Microphones to Obtain Acoustic Images of a Fan Matrix

This paper proposes the use of a signal acquisition and processing system based on an 8×8 planar array of MEMS (Microelectromechanical Systems) microphones to obtain acoustic images of a fan matrix. A 3×3 matrix of PC fans has been implemented to perform the study. Some tests to obtain the acoustic images of the individual fans and of the whole matrix have been defined and have been carried out inside an anechoic chamber. The nonstationary signals received by each MEMS microphone and their corresponding spectra have been analyzed, as well as the corresponding acoustic images. The analysis of the acoustic signals spectra reveals the resonance frequency of the individual fans. The obtained results reveal the feasibility of the proposed system to obtained acoustic images of a fan matrix and of its individual fans, in this last case, in order to estimate the real position of the fan inside the matrix

A Configurable Sensor Network Applied to Ambient Assisted Living

The rising older people population has increased the interest in Ambient Assisted Living systems. This article presents a system for monitoring the disabled or older persons developed from an existing surveillance system. The modularity and adaptability characteristics of the system allow an easy adaptation for a different purpose. The proposed system uses a network of sensors capable of motion detection that includes fall warning, identification of persons and a configurable control system which allows its use in different scenarios

Design and Evaluation of a Scalable and Reconfigurable Multi-Platform System for Acoustic Imaging

This paper proposes a scalable and multi-platform framework for signal acquisition and processing, which allows for the generation of acoustic images using planar arrays of MEMS (Micro-Electro-Mechanical Systems) microphones with low development and deployment costs. Acoustic characterization of MEMS sensors was performed, and the beam pattern of a module, based on an 8 × 8 planar array and of several clusters of modules, was obtained. A flexible framework, formed by an FPGA, an embedded processor, a computer desktop, and a graphic processing unit, was defined. The processing times of the algorithms used to obtain the acoustic images, including signal processing and wideband beamforming via FFT, were evaluated in each subsystem of the framework. Based on this analysis, three frameworks are proposed, defined by the specific subsystems used and the algorithms shared. Finally, a set of acoustic images obtained from sound reflected from a person are presented as a case study in the field of biometric identification. These results reveal the feasibility of the proposed systemSpanish research project SAM: TEC 2015-68170-R (MINECO/FEDER, UE

Acoustic biometric system based on preprocessing techniques and linear support vector machines

Producción CientíficaDrawing on the results of an acoustic biometric system based on a MSE classifier, a new biometric system has been implemented. This new system preprocesses acoustic images, extracts several parameters and finally classifies them, based on Support Vector Machine (SVM). The preprocessing techniques used are spatial filtering, segmentation—based on a Gaussian Mixture Model (GMM) to separate the person from the background, masking—to reduce the dimensions of images—and binarization—to reduce the size of each image. An analysis of classification error and a study of the sensitivity of the error versus the computational burden of each implemented algorithm are presented. This allows the selection of the most relevant algorithms, according to the benefits required by the system. A significant improvement of the biometric system has been achieved by reducing the classification error, the computational burden and the storage requirements

International Conference on Sensors Engineering and Electronics Instrumental Advances (SEIA 2016)

Producción CientíficaThis paper presents the characterization of each of the MEMS microphones which form a uniform planar array used for acoustical imaging. These microphones show an esentialy flat frequency response, with a ±2dB variation between all sensors. This paper also shows the design and the acoustic characterization of the planar array of MEMS microphones. Analyzing the acoustic array characterization it was observed that as the variations of the measured beampattern, with respect to the theoretical one, are limited, it is not necessary to apply calibration techniques to the array.MINECO/FEDER, UE TEC 2015-68170-

Measurement of acceleration response functions with scalable low-cost devices. An application to the experimental modal analysis

Producción CientíficaOne of the most popular options in the Structural Health Monitoring field is the tracking of the modal parameters, which are estimated through the frequency response functions of the structure, usually in the form of accelerances, which are computed as the ratio between the measured accelerations and the applied forces. This requires the use of devices capable of synchronously recording accelerations at several points of the structure at high sampling rates and the subsequent computational analysis using the recorded data. To this end, this work presents and validates a new scalable acquisition system based on multiple myRIO devices and digital MEMS (Micro-Electro-Mechanical System) accelerometers, intended for modal analysis of large structures. A simple form of this system was presented by the authors in a previous work, showing that a single board with some accelerometers connected to it got to obtain high quality measurements in both time and frequency domains. Now, a larger system composed by several slave boards connected and synchronized to a master one is presented. Delays lower than 100 ns are found between the synchronised channels of the proposed system. For validation purposes, a case study is presented where the devices are deployed on a timber platform to estimate its modal properties, which are compared with the ones provided by a commercial system, based on analog accelerometers, to show that similar results are obtained at a significantly lower cost.Junta de Castilla y León - FEDER (VA095P17 y VA228P20)Ministerio de Ciencia e Innovación y Ministerio de Universidades - FEDER (RTI2018-098425