An implantable centrifugal blood pump has been developed with original features for a left ventricular assist device. This pump is part of a multicenter and international study with the objective to offer simple, affordable, and reliable devices to developing countries. Previous computational fluid dynamics investigations and wear evaluation in bearing system were performed followed by prototyping and in vitro tests. In addition, previous blood tests for assessment of normalized index of hemolysis show results of 0.0054±2.46 × 10⁻³ mg/100 L. An electromechanical actuator was tested in order to define the best motor topology and controller configuration. Three different topologies of brushless direct current motor (BLDCM) were analyzed. An electronic driver was tested in different situations, and the BLDCM had its mechanical properties tested in a dynamometer. Prior to evaluation of performance during in vivo animal studies, anatomical studies were necessary to achieve the best configuration and cannulation for left ventricular assistance. The results were considered satisfactory, and the next step is to test the performance of the device in vivo.
One of the most important recent improvements in cardiology is the use of ventricular assist devices (VADs) to help patients with severe heart diseases, especially when they are indicated to heart transplantation. The Institute Dante Pazzanese of Cardiology has been developing an implantable centrifugal blood pump that will be able to help a sick human heart to keep blood flow and pressure at physiological levels. This device will be used as a totally or partially implantable VAD. Therefore, an improvement on device performance is important for the betterment of the level of interaction with patient's behavior or conditions. But some failures may occur if the device's pumping control does not follow the changes in patient's behavior or conditions. The VAD control system must consider tolerance to faults and have a dynamic adaptation according to patient's cardiovascular system changes, and also must attend to changes in patient conditions, behavior, or comportments. This work proposes an application of the mechatronic approach to this class of devices based on advanced techniques for control, instrumentation, and automation to define a method for developing a hierarchical supervisory control system that is able to perform VAD control dynamically, automatically, and securely. For this methodology, we used concepts based on Bayesian network for patients' diagnoses, Petri nets to generate a VAD control algorithm, and Safety Instrumented Systems to ensure VAD system security. Applying these concepts, a VAD control system is being built for method effectiveness confirmation.
Europe was hit hard by the COVID-19 pandemic and Portugal was severely affected, having suffered three waves in the first twelve months. Approximately between Jan 19th and Feb 5th 2021 Portugal was the country in the world with the largest incidence rate, with 14-days incidence rates per 100,000 inhabitants in excess of 1000. Despite its importance, accurate prediction of the geospatial evolution of COVID-19 remains a challenge, since existing analytical methods fail to capture the complex dynamics that result from the contagion within a region and the spreading of the infection from infected neighboring regions. We use a previously developed methodology and official municipality level data from the Portuguese Directorate-General for Health (DGS), relative to the first twelve months of the pandemic, to compute an estimate of the incidence rate in each location of mainland Portugal. The resulting sequence of incidence rate maps was then used as a gold standard to test the effectiveness of different approaches in the prediction of the spatial-temporal evolution of the incidence rate. Four different methods were tested: a simple cell level autoregressive moving average (ARMA) model, a cell level vector autoregressive (VAR) model, a municipality-by-municipality compartmental SIRD model followed by direct block sequential simulation and a new convolutional sequence-to-sequence neural network model based on the STConvS2S architecture. We conclude that the modified convolutional sequence-to-sequence neural network is the best performing method in this task, when compared with the ARMA, VAR, and SIRD models, as well as with the baseline ConvLSTM model.
This thesis briefly introduces the role of the supervisory control platform of unified time system of survey vessels, and studies thoroughly the design and composition of the supervisory control platform, and then finds out the existing defects for which the cause is that to avoid the interplay between two threads: buffer and packet transmission, when the protection lock for Trap message queue is null, the abnormal access of the pointer occurs, leading to the shutdown of Trap message transmission thread and the SNMP thread, and the monitoring module's failure to respond to the requests from software. This paper elaborates the optimized and improved design for the supervisory control platform. By changing signal variable, the optimization of the system platform, especially the revising of the defects could be accomplished. And, by actual use, the feasibility of optimization and improvement is verified, therefore, the reliability of supervisory control platform of unified time system is enhanced, and it could provide reliable monitoring guarantee for the stable operation of the system. This design has high application value, and could be widely used.
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