ABSTRACT
Understanding the architecture of a processor can be uninteresting and deterring for Computer Science students, since low level details of computer architecture are often perceived to lack real-world impact. These courses typically have a strong practical component where students learn the fundamentals of the computer architecture and the handling of I/O operations through the development of simple programs in a low-level assembly programming language. Since these practical sessions require a strong involvement, student attendance and withdrawal rates are poor, what lowers academic results and introduces a negative feedback loop that preconditions students to dislike them. This paper introduces a new methodology for the practical sessions of Computer Organization and Design courses. This methodology disavows the use of simulators and focuses on actual hardware to promote a feeling of proximity to the execution and outcome of the programs. The proposed setup uses Raspberry Pi devices to encourage students to work autonomously, due to their low cost, capability of running an OS, and rich ecosystem of simple hardware devices. The setup is completed with RISC OS, which combines a simple window-based graphical interface with a low-level management of the hardware without requiring software ion layers. The work presents the methodology and the UCDebug tool, developed to help students debug their codes in RISC OS. After the introduction of the new setup at the University of Cantabria, academic results and student satisfaction have improved. The setup has also allowed to sustain a similar organization of the courses throughout the COVID-19 pandemic. IEEE
ABSTRACT
Recent studies suggest that thrombotic complications are a common phenomenon in the novel SARS-CoV-2 infection. The main objective of our study is to assess cumulative incidence of pulmonary embolism (PE) in non critically ill COVID-19 patients and to identify its predicting factors associated to the diagnosis of pulmonary embolism. We retrospectevely reviewed 452 electronic medical records of patients admitted to Internal Medicine Department of a secondary hospital in Madrid during Covid 19 pandemic outbreak. We included 91 patients who underwent a multidetector Computed Tomography pulmonary angiography(CTPA) during conventional hospitalization. The cumulative incidence of PE was assessed ant the clinical, analytical and radiological characteristics were compared between patients with and without PE. PE incidence was 6.4% (29/452 patients). Most patients with a confirmed diagnosed with PE recieved low molecular weight heparin (LMWH): 79.3% (23/29). D-dimer peak was significatly elevated in PE vs non PE patients (14,480 vs 7230 mcg/dL, p = 0.03). In multivariate analysis of patients who underwent a CTPA we found that plasma D-dimer peak was an independen predictor of PE with a best cut off point of > 5000 µg/dl (OR 3.77; IC95% (1.18-12.16), p = 0.03). We found ninefold increased risk of PE patients not suffering from dyslipidemia (OR 9.06; IC95% (1.88-43.60). Predictive value of AUC for ROC is 75.5%. We found a high incidence of PE in non critically ill hospitalized COVID 19 patients despite standard thromboprophylaxis. An increase in D-dimer levels is an independent predictor for PE, with a best cut-off point of > 5000 µg/ dl.