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The Amazon Rainforest suffers from unsustainable exploitation and encroachment on native peoples' territories, leading to poverty and environmental destruction. This inquiry aims to understand the impact of deforestation on the economic development of communities and peoples and the relationships between persistent poverty and social pathologies. The research project employed empirical and conceptual methods, collecting data through interviews and constructing a systemic model concerning pathological dynamics within the Amazon region. The study found traps involving innovation, biodiversity, capacity building, access to economic assets, social development, cultural identity, access to knowledge, savannization, and forest appropriation. A systemic approach that reconnects with nature is essential to establish a sustainable economy in the Amazon rainforest. Proposed solutions include an ecological economy, stopping deforestation, encouraging entrepreneurship, valuing tradition, safe environment, building skills and competencies, increasing information and communication effectiveness, and fostering cooperation. This research seeks fundamentally new solutions that reach beyond the existing regime and contributes to establishing a new paradigm for the Amazon Forest. [ABSTRACT FROM AUTHOR]

Security is one of the most imperative requirements for the success of systems that deal with highly sensitive data, such as medical information. However, many existing mobile health solutions focused on collecting patients’ data at their homes that do not include security among their main requirements. Aiming to tackle this issue, this paper presents SecourHealth, a lightweight security framework focused on highly sensitive data collection applications. SecourHealth provides many security services for both stored and in-transit data, displaying interesting features such as tolerance to lack of connectivity (a common issue when promoting health in remote locations) and the ability to protect data even if the device is lost/stolen or shared by different data collection agents. Together with the system's description and analysis, we also show how SecourHealth can be integrated into a real data collection solution currently deployed in the city of Sao Paulo, Brazil. [ABSTRACT FROM PUBLISHER]

The continuous growth of peer-to-peer networks has made them responsible for a considerable portion of the current Internet traffic. For this reason, improvements in P2P network resources usage are of central importance. One effective approach for addressing this issue is the deployment of locality algorithms, which allow the system to optimize the peers selection policy for different network situations and, thus, maximize performance. To date, several locality algorithms have been proposed for use in P2P networks. However, they usually adopt heterogeneous criteria for measuring the proximity between peers, which hinders a coherent comparison between the different solutions. In this paper, we develop a thoroughly review of popular locality algorithms, based on three main characteristics: the adopted network architecture, distance metric, and resulting peer selection algorithm. As result of this study, we propose a novel and generic taxonomy for locality algorithms in peer-to-peer networks, aiming to enable a better and more coherent evaluation of any individual locality algorithm. [ABSTRACT FROM PUBLISHER]

Network function virtualization opens a new era for security, allowing on-demand instantiation of defense appliances via technologies such as SDN (Software Defined Networking) and Service Function Chaining (SFC). Taking full advantage of such capabilities, however, requires collaboration among Security Service Functions (SSFs) distributed throughout the network. Indeed, collaboration among SSFs is expected to become as essential to SECaaS (SECurity as a Service) as elasticity is to IaaS (Infrastructure as a Service), enabling the efficient allocation of resources for handling large scale attacks. In this paper, we propose a framework leveraging SDN and SFC to improve collaboration among SSFs, allowing SSFs from different domains to negotiate and dynamically control the amount of resources dedicated to collaboration (called a “best-effort” mode). The feasibility, efficiency and scalability of the solution is experimentally assessed, showing that it incurs low overhead, increases the amount of traffic treated by SSFs before packets start being dropped. [ABSTRACT FROM AUTHOR]

Objective: To identify newborns with congenital Zika infection (CZI) at a maternity hospital in Salvador, Brazil, during the 2016 microcephaly outbreak., Methods: A prospective study enrolled microcephalic and normocephalic newborns with suspected CZI between January and December 2016. Serology (immunoglobulins IgM and IgG) and quantitative reverse transcriptase polymerase chain reaction (RT-qPCR) for the Zika virus were performed. Demographic and clinical characteristics of newborns with and without microcephaly were compared., Results: Of the 151 newborns enrolled, 32 (21.2%) were classified as microcephalic. The majority of these cases were born between January and May 2016. IgM and IgG Zika virus antibodies were detected in 5 (23.8%) and 17 (80.9%) microcephalic newborn blood samples, respectively. Six (24%) microcephalic newborns tested positive for Zika virus by RT-qPCR in urine or placenta samples. Thirteen (11.8%) normocephalic newborns also tested positive for Zika virus by PCR in urine, plasma, or placenta samples, while IgM antibodies against Zika were detected in 4 (4.2%) others., Conclusions: Identification of 17 normocephalic CZI cases, confirmed by IgM serology or RT-qPCR for Zika virus, provides evidence that CZI can present asymptomatically at birth. This finding highlights the need for prenatal and neonatal screening for Zika virus in endemic regions., (© 2020 World Health Organization; licensed by John Wiley & Sons Ltd on behalf of International Federation of Gynecology and Obstetrics.)

Introduction: Mobile health consists in applying mobile devices and communication capabilities for expanding the coverage and improving the effectiveness of health care programs. The technology is particularly promising for developing countries, in which health authorities can take advantage of the flourishing mobile market to provide adequate health care to underprivileged communities, especially primary care. In Brazil, the Primary Care Information System (SIAB) receives primary health care data from all regions of the country, creating a rich database for health-related action planning. Family Health Teams (FHTs) collect this data in periodic visits to families enrolled in governmental programs, following an acquisition procedure that involves filling in paper forms. This procedure compromises the quality of the data provided to health care authorities and slows down the decision-making process., Objectives: To develop a mobile system (GeoHealth) that should address and overcome the aforementioned problems and deploy the proposed solution in a wide underprivileged metropolitan area of a major city in Brazil., Methods: The proposed solution comprises three main components: (a) an Application Server, with a database containing family health conditions; and two clients, (b) a Web Browser running visualization tools for management tasks, and (c) a data-gathering device (smartphone) to register and to georeference the family health data. A data security framework was designed to ensure the security of data, which was stored locally and transmitted over public networks., Results: The system was successfully deployed at six primary care units in the city of Sao Paulo, where a total of 28,324 families/96,061 inhabitants are regularly followed up by government health policies. The health conditions observed from the population covered were: diabetes in 3.40%, hypertension (age >40) in 23.87% and tuberculosis in 0.06%. This estimated prevalence has enabled FHTs to set clinical appointments proactively, with the aim of confirming or detecting cases of non-communicable diseases more efficiently, based on real-time information., Conclusion: The proposed system has the potential to improve the efficiency of primary care data collection and analysis. In terms of direct costs, it can be considered a low-cost solution, with an estimated additional monthly cost of U$ 0.040 per inhabitant of the region covered, or approximately U$ 0.106 per person, considering only those currently enrolled in the system., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)