A eficácia terapêutica da fisioterapia no linfedema pós cirurgia de cancro da mama

Projeto de Graduação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Licenciada em Fisioterapia

Ciclos económicos, capital bancario y nuevas opciones de política económica

El objetivo de este trabajo es utilizar algunos hechos estilizados de la "Gran recesión", específicamente la drástica caída en el nivel de capitalización bancario, para analizar la relación entre los ciclos financieros y los ciclos reales, así como la efectividad de la política monetaria no convencional y las políticas macroprudenciales. Para esto, en el primer capítulo se desarrolla una microfundamentación de la banca a partir de un modelo de Costly State Verification, que es incluido posteriomente en distintas especificaciones de modelos DSGE. Los resultados muestran que: (i) los ciclos financieros y los ciclos económicos pueden relacionarse a partir del deterioro del capital bancario; (ii) Las políticas macroprudenciales y no convencionales son efectivas para moderar los ciclos económicos, pero son costosas en términos de recursos e inflación.

Credit spreads and monetary policy in a small open economy: an analysis of the colombian economy

This paper estimates Bejarano and Charry (2014)’s small open economy with financial frictions model for the Colombian economy using Bayesian estimation techniques. Additionally, I compute the welfare gains of implementing an optimal response to credit spreads into an augmented Taylor rule. The main result is that a reaction to credit spreads does not imply significant welfare gains unless the economic disturbances increases its volatility, like the disruption implied by a financial crisis. Otherwise its impact over the macroeconomic variables is null.

Avaliação do efeito do corte horizontal da copa, com máquina de podar de discos, em pomares de pera “Rocha

Current pear pruning making use of pneumatic shears still is a very labour intensive operation. The Proder project “Avaliação da poda mecânica em pomares de pera” was designed to contribute to solutions that would reduce the present dependence in labour and therefore to promote a reduction in pruning costs. This paper shows the results of a trial made to evaluate the influence of mechanical topping in manual pruning complement field work and pear yield. Topping was performed using a Reynolds 6DT 3.0m cutting bar with six hydraulic-driven circular disc-saws mounted in the three point tractor linkage system. The field trial was performed in a commercial orchard with 20 years, planted in an array of 4m x 2m with tree lines oriented in North-South direction. Trees were trained as the central leader system. In this trial, in a randomised complete block design with four replications, two treatments are being compared leading to 8 plots with one line of 14 trees per plot. The treatments tests were: T1 - manual pruning performed by workers using pneumatic shears, in each year; T2 - Topping the canopy parallel to the ground, using a discs-saw pruning machine mounted in a front loader of an agricultural tractor, followed by manual pruning complement performed by workers with pneumatic shears. Tree height and width was measured, before and after pruning. Work was timed and pear yields evaluated. Mechanical topping seems to be effective in the control of tree height, which can contribute to increase 14% of work rates on manual pruning complement. No significant differences in pear yield were found between treatments.

Flexible Computing Systems For AI Acceleration At The Extreme Edge Of The IoT

Embedding intelligence in extreme edge devices allows distilling raw data acquired from sensors into actionable information, directly on IoT end-nodes. This computing paradigm, in which end-nodes no longer depend entirely on the Cloud, offers undeniable benefits, driving a large research area (TinyML) to deploy leading Machine Learning (ML) algorithms on micro-controller class of devices. To fit the limited memory storage capability of these tiny platforms, full-precision Deep Neural Networks (DNNs) are compressed by representing their data down to byte and sub-byte formats, in the integer domain. However, the current generation of micro-controller systems can barely cope with the computing requirements of QNNs. This thesis tackles the challenge from many perspectives, presenting solutions both at software and hardware levels, exploiting parallelism, heterogeneity and software programmability to guarantee high flexibility and high energy-performance proportionality. The first contribution, PULP-NN, is an optimized software computing library for QNN inference on parallel ultra-low-power (PULP) clusters of RISC-V processors, showing one order of magnitude improvements in performance and energy efficiency, compared to current State-of-the-Art (SoA) STM32 micro-controller systems (MCUs) based on ARM Cortex-M cores. The second contribution is XpulpNN, a set of RISC-V domain specific instruction set architecture (ISA) extensions to deal with sub-byte integer arithmetic computation. The solution, including the ISA extensions and the micro-architecture to support them, achieves energy efficiency comparable with dedicated DNN accelerators and surpasses the efficiency of SoA ARM Cortex-M based MCUs, such as the low-end STM32M4 and the high-end STM32H7 devices, by up to three orders of magnitude. To overcome the Von Neumann bottleneck while guaranteeing the highest flexibility, the final contribution integrates an Analog In-Memory Computing accelerator into the PULP cluster, creating a fully programmable heterogeneous fabric that demonstrates end-to-end inference capabilities of SoA MobileNetV2 models, showing two orders of magnitude performance improvements over current SoA analog/digital solutions.

Diffusive models and chaos indicators for non-linear betatron motion in circular hadron accelerators

Understanding the complex dynamics of beam-halo formation and evolution in circular particle accelerators is crucial for the design of current and future rings, particularly those utilizing superconducting magnets such as the CERN Large Hadron Collider (LHC), its luminosity upgrade HL-LHC, and the proposed Future Circular Hadron Collider (FCC-hh). A recent diffusive framework, which describes the evolution of the beam distribution by means of a Fokker-Planck equation, with diffusion coefficient derived from the Nekhoroshev theorem, has been proposed to describe the long-term behaviour of beam dynamics and particle losses. In this thesis, we discuss the theoretical foundations of this framework, and propose the implementation of an original measurement protocol based on collimator scans in view of measuring the Nekhoroshev-like diffusive coefficient by means of beam loss data. The available LHC collimator scan data, unfortunately collected without the proposed measurement protocol, have been successfully analysed using the proposed framework. This approach is also applied to datasets from detailed measurements of the impact on the beam losses of so-called long-range beam-beam compensators also at the LHC. Furthermore, dynamic indicators have been studied as a tool for exploring the phase-space properties of realistic accelerator lattices in single-particle tracking simulations. By first examining the classification performance of known and new indicators in detecting the chaotic character of initial conditions for a modulated Hénon map and then applying this knowledge to study the properties of realistic accelerator lattices, we tried to identify a connection between the presence of chaotic regions in the phase space and Nekhoroshev-like diffusive behaviour, providing new tools to the accelerator physics community.

Study of the tracking performance of a liquid Argon detector based on a novel optical imaging concept

The Deep Underground Neutrino Experiment (DUNE) is a long-baseline accelerator experiment designed to make a significant contribution to the study of neutrino oscillations with unprecedented sensitivity. The main goal of DUNE is the determination of the neutrino mass ordering and the leptonic CP violation phase, key parameters of the three-neutrino flavor mixing that have yet to be determined. An important component of the DUNE Near Detector complex is the System for on-Axis Neutrino Detection (SAND) apparatus, which will include GRAIN (GRanular Argon for Interactions of Neutrinos), a novel liquid Argon detector aimed at imaging neutrino interactions using only scintillation light. For this purpose, an innovative optical readout system based on Coded Aperture Masks is investigated. This dissertation aims to demonstrate the feasibility of reconstructing particle tracks and the topology of CCQE (Charged Current Quasi Elastic) neutrino events in GRAIN with such a technique. To this end, the development and implementation of a reconstruction algorithm based on Maximum Likelihood Expectation Maximization was carried out to directly obtain a three-dimensional distribution proportional to the energy deposited by charged particles crossing the LAr volume. This study includes the evaluation of the design of several camera configurations and the simulation of a multi-camera optical system in GRAIN.

Design of a wearable platform for PPG analysis with multicore low-power processor

Photoplethysmography (PPG) sensors allow for noninvasive and comfortable heart-rate (HR) monitoring, suitable for compact wearable devices. However, PPG signals collected from such devices often suffer from corruption caused by motion artifacts. This is typically addressed by combining the PPG signal with acceleration measurements from an inertial sensor. Recently, different energy-efficient deep learning approaches for heart rate estimation have been proposed. To test these new solutions, in this work, we developed a highly wearable platform (42mm x 48 mm x 1.2mm) for PPG signal acquisition and processing, based on GAP9, a parallel ultra low power system-on-chip featuring nine cores RISC-V compute cluster with neural network accelerator and 1 core RISC-V controller. The hardware platform also integrates a commercial complete Optical Biosensing Module and an ARM-Cortex M4 microcontroller unit (MCU) with Bluetooth low-energy connectivity. To demonstrate the capabilities of the system, a deep learning-based approach for PPG-based HR estimation has been deployed. Thanks to the reduced power consumption of the digital computational platform, the total power budget is just 2.67 mW providing up to 5 days of operation (105 mAh battery).

GEANT4 Radioprotection studies of the ERHA system for protontherapy treatment

This work is focused on the radiation protection for a protontherapy facility. The aim is to simulate with the best accuracy the prompt radiation field of the proton accelerator situed in Ruvo di Puglia, owned by Linearbeam s.r.l. company. In order to simulate it, is used Geant4, a software for interaction simulations of particles with matter. Thanks to internship work, thesis speaks about cancer therapy with a new method for particle acceleration, a linear beam. For a complete overview of the therapy, this work starts with a crush course on interactions of particle with matter, goes specifically to biological matter, then is shown a brief introduction to shielding studies for a particle acceleration facility, and then a presentation of Geant4. At the end, the main aspects of the proton accelerator are simulated, from proton hitting material of beam-pipe to detectors used to measure dose.

Utilizzo di sistemi bioreattori per l’ingegnerizzazione di sostituti del tessuto cartilagineo

La mancanza di vascolarizzazione dei costrutti tissutali cartilaginei ingegnerizzati rende opportuno e necessario l’impiego di bioreattori che permettano di indurre un flusso nel terreno di coltura favorendo il trasporto di massa e quindi lo sviluppo del metabolismo e del differenziamento cellulare. I bioreattori intendono replicare gli stimoli fisici fisiologici, nello specifico condrogenici, e a regolare la formazione della matrice extracellulare tramite meccanotrasduzione, il fenomeno biologico che traduce le sollecitazioni meccaniche applicate alle cellule in segnali biochimici che suscitano risposte adattative. In questo elaborato sono riportati i risultati di un recente lavoro - pubblicato da J. Hallas, A. J. Janvier, K. F. Hoettges & J. R. Henstock e intitolato “Pneumatic piston hydrostatic bioreactor for cartilage tissue engineering – che propone la realizzazione di un bioreattore idrostatico a pistone pneumatico, realizzato con componenti facilmente acquisibili a basso costo in commercio. Il bioreattore è collegato a una camera di coltura tramite un connettore pneumatico e un tubo per l’aria in polipropilene. La camera di coltura è realizzata in acido polilattico (PLA) tramite stampante 3D. Il dispositivo è in grado di applicare a una coltura cellulare tridimensionale una pressione idrostatica intermittente con ampiezza compresa tra 0 e 400 kPa e frequenza massima di 3,5 Hz. Condrociti provenienti dalla cartilagine di un’articolazione di ginocchio sono stati coltivati all’interno della camera di coltura del bioreattore dove sono stati sottoposti a una pressione di picco di 300 kPa per 3 ore al giorno per un totale di 5 giorni. Al termine della coltura si è ottenuto un aumento dell’attività metabolica cellulare del 21% e un aumento significativo del contenuto di glicosamminoglicani nell’ECM.