Constraints on Dematerialisation and Allocation of Natural Capital along a Sustainable Growth Path

This paper extends the neoclassical growth model with natural capital by introducing two new concepts: allocation of natural capital and materialization. We consider that anthropogenic environmental impact is correlated with the throughput of the economy (materialisation). Materialisation is the material throughput per unit of economic activity. We capture the effect of the reduction of this throughput dematerialisation in the elasticities of materialisation and aggregate environmental impact. In our framework the fraction of natural capital devoted to production does not provide direct environmental services nor does it contribute to ecosystem functioning namely affecting the carrying capacity of natural capital.We analyse an optimal sustainable growth path, in the context of exogenous technological change. Our main conclusion is that the ratio of dematerialisation elasticities must equal the inverse of the share of natural capital in order to assure unbounded economic growth with constant natural capital

Using Open Remote Sensing and Geographic Data for SMART Monitoring of Nature-based TOURISM in the Azores Islands Natural Parks : towards (more) Sustainability

Proceedings of the 11th International Symposium on Digital Earth (ISDE 11), Florence (Italy), September 24-27, 2019.A remote sensing-based operational tool using Sentinel-2 and Landsat-8 free and open access satellite multispectral data, and based on the Google Earth Engine (GEE) platform, is under development for monitoring land-cover/land-use changes in the Azores Islands Natural Park.info:eu-repo/semantics/publishedVersio

Degenerescência aneurismática na doença de Von Recklinghausen

ResumoA doença de Von Recklinghausen é uma facomatose de transmissão autossómica dominante. Apesar da heterogeneidade da expressão clínica, os estigmas cutâneos clássicos como manchas café au lait são frequentes. A arteriopatia é incomum, sendo a degenerescência aneurismática extremamente rara.Os autores apresentam o caso clínico de um homem de 63 anos com doença de Von Recklinghausen e degenerescência multianeurismática aorto‐ilíaca, femoral e poplítea, submetido com sucesso a tratamento cirúrgico convencional.A degenerescência aneurismática na doença de Von Recklinghausen encontra‐se associada a displasia muscular lisa e a invasão neurofibromatosa da parede vascular. Esta fragilidade arterial implica dissecção laboriosa e técnica cirúrgica meticulosa para limitar a hemorragia e a deiscência anastomótica.AbstractThe Von Recklinghausen's disease is a facomatosis with autosomal dominant transmission. Despite the heterogeneity of clinical expression, the classic cutaneous stigmata such as café au lait spots are common. The arteriopathy is unusual, with rare aneurysmal degeneration.The authors disclose the clinical case of a 63 years old man with Von Recklinghausen's disease and multi‐aneurysmal degeneration of the aorto‐iliac, femoral and popliteal sectors, who successfully underwent open surgery.The aneurysmal degeneration in Von Recklinghausen's disease is associated with smooth muscle dysplasia and neurofibromatosis invasion of the vascular wall. This arterial fragility implies laborious and meticulous surgical dissection to limit the bleeding and anastomotic dehiscence

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.CT - Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013 and PTDC/EEI - SII/1302/2012 (INTCare II

uTango: an open-source TEE for IoT devices

Security is one of the main challenges of the Internet of Things (IoT). IoT devices are mainly powered by low-cost microcontrollers (MCUs) that typically lack basic hardware security mechanisms to separate security-critical applications from less critical components. Recently, Arm has started to release Cortex-M MCUs enhanced with TrustZone technology (i.e., TrustZone-M), a system-wide security solution aiming at providing robust protection for IoT devices. Trusted Execution Environments (TEEs) relying on TrustZone hardware have been perceived as safe havens for securing mobile devices. However, for the past few years, considerable effort has gone into unveiling hundreds of vulnerabilities and proposing a collection of relevant defense techniques to address several issues. While new TEE solutions built on TrustZone-M start flourishing, the lessons gathered from the research community appear to be falling short, as these new systems are trapping into the same pitfalls of the past. In this paper, we present UTANGO, the first multi-world TEE for modern IoT devices. UTANGO proposes a novel architecture aiming at tackling the major architectural deficiencies currently affecting TrustZone(-M)-assisted TEEs. In particular, we leverage the very same TrustZone hardware primitives used by dual-world implementations to create multiple and equally secure execution environments within the normal world. We demonstrate the benefits of UTANGO by conducting an extensive evaluation on a real TrustZone-M hardware platform, i.e., Arm Musca-B1. UTANGO will be open-sourced and freely available on GitHub in hopes of engaging academia and industry on securing the foreseeable trillion IoT devices.This work was supported in part by the Fundacao para a Ciencia e Tecnologia (FCT) within the Research and Development Units under Grant UIDB/00319/2020, and in part by FCT within the Ph.D. Scholarship under Grant 2020.04585.BD

On the use of OpenEHR in a portable PHR

Quality medical acts rely on patient medical information. With paper records, the responsibility of gathering the disparate information and making it available to the caregivers, falls exclusively upon the patient. This still is, to great extent, the case with electronic health documents. The consensus is that the advantages of patient involvement in his own health are numerous. With the advent of recent technologies and their deployment in healthcare, new ways of involving the patient and making him an active part of his own health are possible. Electronic Health Records (EHR) and specially Personal Health Records (PHR) are important tools for patient empowerment but data population and management through non-intuitive structured forms is time consuming, takes a great amount of effort, and can be deterring specially for people that are not very computer-oriented. PHRs can be simple and scalable applications that the patient uses to get started and afterwards evolve towards complexity. In any case, compliance with standards must be accomplished. In this paper we present a PHR simple to use, implemented on a USB Flash pen for mobility, and compliant with the openEHR specification. Our model builds on openEHR and adds security and privacy features, allows patient data management and can work as an information repository

ClimaWin : an intelligent window for optimal ventilation and minimum thermal loss

In this paper the ClimaWin concept is introduced. The ClimaWin project's main goals are to improve both indoor air quality and the energy efficiency of new and refurbished buildings, through the use of novel green smart windows. Generally, in order to improve windows' energy efficiency better insulation materials are used in windows frames and glasses. However, this approach leads to a severe deterioration of indoor air quality (IAQ) especially in buildings that are not equipped with heating, ventilation and air conditioning (HVAQ) systems. The Climawin windows do not require wires neither for power nor for communications. The window is powered through a battery (for blind operation) and a solar panel, which makes it an ideal solution for retrofitting. In order to achieve the energy efficiency requirements, the Climawin system hardware, the microcontroller software architecture and the radio communication strategy were designed for low power consumption. Furthermore, all the information about the system status can be monitored and actuated using intuitive graphical applications developed for PCs and Android OS smartphones. A remote database keeps all the relevant information about the system, making it easy to detect any anomaly or even to adjust the control algorithm parameters from a remote location. A full-set of web services are also provided in order to simplify the communication with home automation systems.Fundação para a Ciência e a Tecnologia (FCT

Hierarchical temporal memory theory approach to stock market time series forecasting

Over the years, and with the emergence of various technological innovations, the relevance of automatic learning methods has increased exponentially, and they now play a key role in society. More specifically, Deep Learning (DL), with the ability to recognize audio, image, and time series predictions, has helped to solve various types of problems. This paper aims to introduce a new theory, Hierarchical Temporal Memory (HTM), that applies to stock market prediction. HTM is based on the biological functions of the brain as well as its learning mechanism. The results are of significant relevance and show a low percentage of errors in the predictions made over time. It can be noted that the learning curve of the algorithm is fast, identifying trends in the stock market for all seven data universes using the same network. Although the algorithm suffered at the time a pandemic was declared, it was able to adapt and return to good predictions. HTM proved to be a good continuous learning method for predicting time series datasets.This work is funded by “FCT—Fundação para a Ciência e Tecnologia” within the R&D Units Project Scope: UIDB/00319/2020. The grant of R.S. is supported by the European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internalization Programme (COMPETE 2020). [Project n. 039479. Funding Reference: POCI-01-0247- FEDER-039479]