Flexible programmable networking: A reflective, component-based approach

The need for programmability and adaptability in networking systems is becoming increasingly important. More specifically, the challenge is in the ability to add services rapidly, and be able to deploy, configure and reconfigure them as easily as possible. Such demand is creating a considerable shift in the way networks are expected to operate in the future. This is the main aim of programmable networking research community, and in our project we are investigating a component-based approach to the structuring of programmable networking software. Our intention is to apply the notion of components, component frameworks and reflection ubiquitously, thus accommodating all the different elements that comprise a programmable networking system

Exploiting the Use of Convolutional Neural Networks for Localization in Indoor Environments

Indoor localization has been an active research area for the last two decades. A great number of sensors have been applied in the task of localization—some with high computational and energy demands (e.g. laser beams), or with issues related to the coverage area, for example, by making use of images obtained by a network of cameras. A different approach, which presents less energy demands and a wide area of coverage, can be created by means of the signal strength of wireless networks. The open issue with signal strength is its high instability due to interferences, attenuation and fading, which, in general, makes the localization systems to present less than desired accuracy. In this article, we exploit the use of Convolutional Neural Networks (ConvNets) in the task of localization. The main motivation behind the employment of ConvNets is its inherent ability of feature extraction, which we believe can deal better with the noise without a filtering step. We evaluate how ConvNets can be employed and identify the best topologies that lead to the lowest errors

ENLACE: A Combination of Layer-Based Architecture and Wireless Communication for Emotion Monitoring in Healthcare

Owing to the increase in the number of people with disabilities, as a result of either accidents or old age, there has been an increase in research studies in the area of ubiquitous computing and the Internet of Things. They are aimed at monitoring health, in an efficient and easily accessible way, as a means of managing and improving the quality of life of this section of the public. It also involves adopting a Health Homes policy based on the Internet of Things and applied in smart home environments. This is aimed at providing connectivity between the patients and their surroundings and includes mechanisms for helping the diagnosis and prevention of accidents and/or diseases. Monitoring gives rise to an opportunity to exploit the way computational systems can help to determine the real-time emotional state of patients. This is necessary because there are some limitations to traditional methods of health monitoring, for example, establishing the behavior of the user’s routine and issuing alerts and warnings to family members and/or medical staff about any abnormal event or signs of the onset of depression. This article discusses how a layer-based architecture can be used to detect emotional factors to assist in healthcare and the prevention of accidents within the context of Smart Home Health. The results show that this process-based architecture allows a load distribution with a better service that takes into account the complexity of each algorithm and the processing power of each layer of the architecture to provide a prompt response when there is a need for some intervention in the emotional state of the user

A service-oriented middleware for integrated management of crowdsourced and sensor data streams in disaster management

The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. As traditional sensor networks are error-prone and difficult to maintain, the study highlights the emerging role of “citizens as sensors” as a complementary data source to increase public awareness. To this end, an interoperable, reusable middleware for managing spatial, temporal, and thematic data using Sensor Web Enablement initiative services and a processing engine was designed, implemented, and deployed. The study found that its approach provided effective sensor data-stream access, publication, and filtering in dynamic scenarios such as disaster management, as well as it enables batch and stream management integration. Also, an interoperability analytics testing of a flood citizen observatory highlighted even variable data such as those provided by the crowd can be integrated with sensor data stream. Our approach, thus, offers a mean to improve near-real-time applications

Implementation of earlier antibiotic administration in patients with severe sepsis and septic shock in Japan: a descriptive analysis of a prospective observational study.

BACKGROUND: Time to antibiotic administration is a key element in sepsis care; however, it is difficult to implement sepsis care bundles. Additionally, sepsis is different from other emergent conditions including acute coronary syndrome, stroke, or trauma. We aimed to describe the association between time to antibiotic administration and outcomes in patients with severe sepsis and septic shock in Japan. METHODS: This prospective observational study enrolled 1184 adult patients diagnosed with severe sepsis based on the Sepsis-2 criteria and admitted to 59 intensive care units (ICUs) in Japan between January 1, 2016, and March 31, 2017, as the sepsis cohort of the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis and Trauma (FORECAST) study. We compared the characteristics and in-hospital mortality of patients administered with antibiotics at varying durations after sepsis recognition, i.e., 0-60, 61-120, 121-180, 181-240, 241-360, and 361-1440 min, and estimated the impact of antibiotic timing on risk-adjusted in-hospital mortality using the generalized estimating equation model (GEE) with an exchangeable, within-group correlation matrix, with "hospital" as the grouping variable. RESULTS: Data from 1124 patients in 54 hospitals were used for analyses. Of these, 30.5% and 73.9% received antibiotics within 1 h and 3 h, respectively. Overall, the median time to antibiotic administration was 102 min [interquartile range (IQR), 55-189]. Compared with patients diagnosed in the emergency department [90 min (IQR, 48-164 min)], time to antibiotic administration was shortest in patients diagnosed in ICUs [60 min (39-180 min)] and longest in patients transferred from wards [120 min (62-226)]. Overall crude mortality was 23.4%, where patients in the 0-60 min group had the highest mortality (28.0%) and a risk-adjusted mortality rate [28.7% (95% CI 23.3-34.1%)], whereas those in the 61-120 min group had the lowest mortality (20.2%) and risk-adjusted mortality rates [21.6% (95% CI 16.5-26.6%)]. Differences in mortality were noted only between the 0-60 min and 61-120 min groups. CONCLUSIONS: We could not find any association between earlier antibiotic administration and reduction in in-hospital mortality in patients with severe sepsis

Effects of hydroxyapatite and PDGF concentrations on osteoblast growth in a nanohydroxyapatite-polylactic acid composite for guided tissue regeneration

The technique of guided tissue regeneration (GTR) has evolved over recent years in an attempt to achieve periodontal tissue regeneration by the use of a barrier membrane. However, there are significant limitations in the currently available membranes and overall outcomes may be limited. A degradable composite material was investigated as a potential GTR membrane material. Polylactic acid (PLA) and nanohydroxyapatite (nHA) composite was analysed, its bioactive potential and suitability as a carrier system for growth factors were assessed. The effect of nHA concentrations and the addition of platelet derived growth factor (PDGF) on osteoblast proliferation and differentiation was investigated. The bioactivity was dependent on the nHA concentration in the films, with more apatite deposited on films containing higher nHA content. Osteoblasts proliferated well on samples containing low nHA content and differentiated on films with higher nHA content. The composite films were able to deliver PDGF and cell proliferation increased on samples that were pre absorbed with the growth factor. nHA–PLA composite films are able to deliver active PDGF. In addition the bioactivity and cell differentiation was higher on films containing more nHA. The use of a nHA–PLA composite material containing a high concentration of nHA may be a useful material for GTR membrane as it will not only act as a barrier, but may also be able to enhance bone regeneration by delivery of biologically active molecules

Effect of Oral Sebacic Acid on Postprandial Glycemia, Insulinemia, and Glucose Rate of Appearance in Type 2 Diabetes

Dicarboxylic acids are natural products with the potential of being an alternate dietary source of energy. We aimed to evaluate the effect of sebacic acid (a 10-carbon dicarboxylic acid; C10) ingestion on postprandial glycemia and glucose rate of appearance (Ra) in healthy and type 2 diabetic subjects. Furthermore, the effect of C10 on insulin-mediated glucose uptake and on GLUT4 expression was assessed in L6 muscle cells in vitro