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The average life expectancy of the world’s population is increasing and the healthcare systems sooner than later will be compromised by its reduced capacity and its highly economic cost; in addition, the age distribution of the population is leading towards the older spectrum. This trend will lead to immeasurable and unexpected economic problems and social changes. In order to face up this challenge and complex economic and social problem, it is necessary to rely on the appropriate digital tools and technological infrastructures for ensuring that the elderly are properly cared in their everyday living environments and they can live independently for longer. This article presents ACTIVAGE IoT Ecosystem Suite (AIoTES), a concrete reference architecture and its implementation process that addresses these issues and that was designed within the first European Large Scale Pilot, ACTIVAGE, a H2020 funded project by the European Commission with the objective of creating sustainable ecosystems for Active and Healthy Ageing (AHA) based on Internet of Things and big data technologies. AIoTES offers platform level semantic interoperability, with security and privacy, as well as Big Data and Ecosystem tools. AIoTES enables and promotes the creation, exchange and adoption of cross-platform services and applications for AHA. The number of existing AHA services and solutions are quite large, especially when state-of-the-art technology is introduced, however a concrete architecture such as AIoTES gains more importance and relevance by providing a vision for establishing a complete ecosystem, that looks for supporting a larger variety of AHA services, rather than claiming to be a unique solution for all the AHA domain problems. AIoTES has been successfully validated by testing all of its components, individually, integrated, and in real-world environments with 4345 direct users. Each validation is contextualized in 11 Deployment Sites (DS) with 13 Validation Scenarios covering the heterogeneity of the AHA-IoT needs. These results also show a clear path for improvement, as well as the importance for standardization efforts in the ever-evolving AHA-IoT domain.

The European Space Operations Centre currently operates five Copernicus Sentinel satellites in the framework of Europe’s Copernicus Earth observation programme. The routine operations rely on a daily orbit determination, carried out on-ground, consisting in a least-squares fit of a dynamical model to GPS navigation solutions generated on-board. The purpose of this paper is the estimation of realistic uncertainties on this daily determined state vector. By comparison with the orbit derived by Precise Orbit Determination, we estimate the 1-sigma errors at approximately 0.5m and 0.5mm/s. Non-stationary errors in the navigation solution preclude their characterisation with a constant covariance matrix. Error whitening is achieved by decreasing the signal-to-noise ratio in the errors through the use of underestimated weights on the data. The approach keeps the errors on the derived state vector unchanged and allows the covariance on the state vector to become realistic.

Purpose To report the anatomical and functional response of combined photodynamic therapy and intravitreal injection of bevacizumab in a patient with symptomatic circumscribed choroidal hemangioma. Methods The patient received a single-session full-fluence photodynamic therapy immediately followed by an intravitreal injection of bevacizumab (1.25 mg/0.05 mL). Results One week after combined therapy, an improvement of best-corrected visual acuity from count fingers to 20/60 and a significant decrease in subretinal fluid were noted. One month later, we observed decreased leakage on fluorescein angiography in all phases of the study. Three months after treatment, the best-corrected visual acuity improved to 20/25 and spectral domain optical coherence tomography scans showed return to normal foveal architecture with no subretinal fluid and completely flat tumor. These findings were maintained during 4 years of follow-up. Conclusion Combination therapy was associated with a rapid and persistent resolution of subretinal fluid, improvement of best-corrected visual acuity, and visual stability at 4 years of follow-up.

There is an increasing evidence supporting the existence of coagulopathy in coronavirus disease 2019 (COVID-19) patients. Most of reports are mainly focused on d-dimer. Our objective is to describe coagulation parameters in these patients that could be involved in a hypercoagulate state and to test platelet function to see if there are short closure times. We analyzed coagulation samples from 80 patients admitted with COVID-19 in our hospital. We also tested platelet function by closure times in a small subgroup of patients. Most of samples had increased d-dimer (96.2%) (median of d-dimer: 1158 ng/ml FEU), increased fibrinogen (75.2%) (median: 5.23 g/l), increased factor VIII (86%) (median: 264.8 U/dl), decreased protein S (22.5% of women, 62.5% of men) (median: 62.8 and 68.5 U/dl, respectively), decreased protein C (7.6%) (median: 100 U/dl), decreased factor XII (25.3%) (median: 90.3 U/dl) and decreased antithrombin activity (21%) (median: 86 U/dl). International normalized ratio was higher than normal in 24 patients (30%) (median: 1.13). The activated partial thromboplastin time ratio was below the normal range in nine patients (11.2%) and above normal in three (3.75%) (median: 0.93). The closure times were short in the 20% and 40% of samples of collagen and ADP and collagen and epinephrine, respectively. Twelve of the 80 patients (15%) had a thrombotic event and all had several abnormal coagulation parameters related with increased thrombotic risk. The results of this study support a hypercoagulability state in COVID-19 patients and it may help to explain the microvascular thrombosis caused by the inflammatory response.

To design and develop AI-based cybersecurity systems (e.g., intrusion detection system (IDS)), users can justifiably trust, one needs to evaluate the impact of trust using machine learning and deep learning technologies. To guide the design and implementation of trusted AI-based systems in IDS, this paper provides a comparison among machine learning and deep learning models to investigate the trust impact based on the accuracy of the trusted AI-based systems regarding the malicious data in IDs. The four machine learning techniques are decision tree (DT), K nearest neighbour (KNN), random forest (RF), and naïve Bayes (NB). The four deep learning techniques are LSTM (one and two layers) and GRU (one and two layers). Two datasets are used to classify the IDS attack type, including wireless sensor network detection system (WSN-DS) and KDD Cup network intrusion dataset. A detailed comparison of the eight techniques’ performance using all features and selected features is made by measuring the accuracy, precision, recall, and F1-score. Considering the findings related to the data, methodology, and expert accountability, interpretability for AI-based solutions also becomes demanded to enhance trust in the IDS.

Semantic IoT: Theory and Applicationspp 161–192Cite as PerfectO: An Online Toolkit for Improving Quality, Accessibility, andClassification of Domain-Based Ontologies Amélie Gyrard, Ghislain Atemezing& Martin Serrano Chapter First Online:13 April 2021 431Accesses 2Altmetric Part of theStudies in Computational Intelligencebook series (SCI,volume 941) Abstract Sensor-based applications are increasingly present in our everyday life. Due to the enormous quantity of sensor data produced, interpreting data and building interoperable sensor-based applications is needed. There are several problems to address the heterogeneity of (1) data format, (2) languages to describe sensor metadata, (3) models for structuring sensor datasets, (4) reasoning mechanisms and rule languages to interpret sensor datasets, and (5) applications. Semantic Web technologies (a.k.a, knowledge graphs), are immersed in an increasing number of online activities we perform today (e.g., search engines for gathering information). There is a need to find better ways to share data and distribute more meaningful and more accurate information. Innovative methodologies are needed to link and associate the data from different domains to improve knowledge discovery. Semantic knowledge graphs, made of datasets and ontologies, are intended to describe and organize heterogeneous data explicitly. If an ontology is widely used to structure data of a particular domain, the accessibility and the efficiency in sharing and reusing that information will increase. For this reason, we focused on theontology qualityused when building sensor-based applications. We designedPerfectO, aKnowledge Directory Servicestool, focusing on ontology best practices, which: (1) improves knowledge quality, (2) leverages usability, accessibility, and classification of the information, (3) enhances engineering experience, and (4) promotes engineering best practices.PerfectOimplementation is applied to the Internet of Things (IoT) domain because it covers more than 20 application domains (e.g., healthcare, smart building, smart farm) that use sensors.PerfectOenhances knowledge expertise quality implemented within any ontologies as demonstrated with the Linked Open Vocabularies for IoT (LOV4IoT) ontology catalog.

Despite the growing popularity of machine learning models in the cyber-security applications (e.g., an intrusion detection system (IDS)), most of these models are perceived as a black-box. The eXplainable Artificial Intelligence (XAI) has become increasingly important to interpret the machine learning models to enhance trust management by allowing human experts to understand the underlying data evidence and causal reasoning. According to IDS, the critical role of trust management is to understand the impact of the malicious data to detect any intrusion in the system. The previous studies focused more on the accuracy of the various classification algorithms for trust in IDS. They do not often provide insights into their behavior and reasoning provided by the sophisticated algorithm. Therefore, in this paper, we have addressed XAI concept to enhance trust management by exploring the decision tree model in the area of IDS. We use simple decision tree algorithms that can be easily read and even resemble a human approach to decision-making by splitting the choice into many small subchoices for IDS. We experimented with this approach by extracting rules in a widely used KDD benchmark dataset. We also compared the accuracy of the decision tree approach with the other state-of-the-art algorithms.

Background Analysis of cross-reactivity is necessary for prescribing safe cephalosporins for penicillin allergic patients. Amoxicillin (AX) is the betalactam most often involved in immediate hypersensitivity reactions (IHRs), and cefadroxil (CX) the most likely cephalosporin to cross-react with AX, since they share the same R1 side chain, unlike cefuroxime (CO), with a structurally different R1. We aimed to analyse cross-reactivity with CX and CO in patients with confirmed IHRs to AX, including sIgE recognition to AX, CX, CO, and novel synthetic determinants of CX. Methods Fifty-four patients with confirmed IHRs to AX based on skin test (ST) and/or drug provocation test (DPT) were included. Serum sIgE to AX and benzylpenicillin was determined by Radioallergosorbent test (RAST). Two potential determinants of CX, involving intact or modified R1 structure, with open betalactam ring, were synthesised and sIgE evaluated by RAST inhibition assay. Results Tolerance to CX (Group A) was observed in 64.8% cases and cross-reactivity in 35.2% cases (Group B). Cross-reactivity with CO was only found in 1.8% cases from Group B. ST to CX showed a negative predictive value of 94.6%. RAST inhibition assays showed higher recognition to CX as well as to both synthetic determinants (66% of positive cases) in Group B. Conclusions Cross-reactivity with CX in AX allergic patients is 35%, being ST not enough for prediction. R1, although critical for recognition, is not the unique factor. The synthetic determinants of CX, 1-(HOPhG-Ser-Bu) and 2-(pyrazinone) are promising tools for determining in vitro cross-reactivity to CX in AX allergic patients. Background Betalactams (BLs) are the drugs most frequently involved in immediate (IgE-mediated) hypersensitivity reactions (IHRs) [1,2,3], which could be explained by their ability to act as haptens due to their high chemical reactivity against proteins [4, 5]. BL chemical structure is formed by a 4-membered ring (the so-called BL ring) that in penicillins is fused to a 5-membered thiazolidine ring, and in cephalosporins to a 6-membered dihydrothiazine ring (Fig. 1). These drugs have a side chain (R1) bound to the BL ring; besides, cephalosporins have a second side chain (R2) bound to the dihydrothiazine ring, whose chemical structures distinguish the different compounds [6, 7]. Yes

The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and “things” have evolved significantly. “Things” now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of “intelligent things” (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.

Concern for healthy aging is growing, and all studies show that fighting frailty helps to achieve it. It is necessary to detect frailty as soon as possible, since it precedes the development of disability and dependence. Most of studies agree that it is required to screen the population over 70 years of age. There is a great consensus on the preferential use of the short physical performance battery (SPPB), validated and standardized in geriatrics, since they have a good correlation to detect frailty and high reliability in predicting disability, in addition to its feasibility of use in Primary Care services. The SSPB consists of three tests: gait speed test (GST), standing balance test (SBT) and sit-to-stand test (SST). Generally, this test is carried out manually by specialized health staff, being time-consuming. This work introduces a multi-sensory system, with its corresponding software component for intelligent data management and analysis that allows to carry out the SPPB in an automated way, and its subsequent evaluation by the physician. The objective of this proposal is to facilitate the screening of frailty by health staff, both specialized and non-specialized, in a massive way and to minimize interrater and inter-centre deviations.

The advent of the Internet of Things (IoT) has lead to increased possibilities for novel human-centric services in smart cities. Nevertheless, existing IoT platforms for smart cities do not provide the means for integrating data and services from different IoT deployments, which is a prerequisite for several smart city applications such as holistic urban planning, tracking of city-wide APIs and integration of deployments at the level of neighbourhoods or communities in the cities. Hence, smart city projects tend to be fragmented, leading to disaggregated application silos. In order to alleviate this fragmentation and enable more integrated applications, there is a need to enable city authorities and application developers to see IoT systems as part of an integrated whole, allowing optimal use of existing infrastructure and achieving more than what these independent systems can do in isolation. This article presents the VITAL-OS, an IoT operating system for smart cities that facilitates access and control of the city infrastructure, resources and sensor networks, with abstraction and tools that can additionally be used by developers to create new applications using available data to empower citizens. VITAL-OS facilitates the semantic interoperability of diverse vertical IoT deployments in smart cities and enables integrated management of IoT resources as well as rapid development of cross-platform and cross-context IoT applications for smart cities. In this way, VITAL-OS provides a unique value proposition when compared to conventional IoT platforms for smart cities.

A Connected World/Web of Things is an emerging area that not only requires development of infrastructure but also deployment of new data services capable of supporting multiple, scalable (cloud-based) and interoperable (cross-systems and cross-domain) applications. In the race of designing the Connected World/Web as part of the Future Internet architecture, academia and Information and Communication Technology (ICT) industry communities have realized that a common problem to be tackled is the interoperability of the data and their availability for providing information services. Worldwide there is an increasingly focusing on how to evolve communications technologies to enable a Connected World, thus Semantic-enabled Web of Things systems will need to interact and be interconnected for offering the always-promoted everything-connected interoperability paradigm. The Connected World/Web & Semantic Interoperability workshop provides to developers, scientific researchers, industry experts and general audience interested in the evolution of the Internet of connected things world, the possibility to explore interoperability research challenges and provide a room to expose their research scientific ideas and progress and also explore new trends and opportunities of using semantic web technologies for solving problems and creating new solutions on emerging specialized paradigms like the current Internet of connected Things or simply acknowledge as Internet of Things (IoT).

In this paper we introduce an adaptation to the "driver intent inference algorithm for urban intersections". This algorithm has been proven to detect potential right turns of vehicles by estimating the probability of a driver to turn right, and we propose to use it for reducing the number of cycling deaths at an intersection. We extend this algorithm following the IoT design principles and thus, with this approach, cyclists’ safety no longer depends only on actions taken inside the vehicles, but also can use additional safety solutions based on standards and available information shared about the vehicles and drivers in vehicular networks. Our approach proposes to process the inference algorithm outside the vehicle, considering cloud and edge computing. We use predicting models for identifying driver’s intention of turning right at intersections and the use of edge connected devices running our algorithm for alerting cyclists of possible collisions, thus preventing as many collisions as possible in intersections.

Allergic drug reactions are currently a major public health problem affecting patient health and increasing healthcare costs. They are caused by interactions between a drug and the human immune system and result in symptoms ranging from urticaria or angioedema to those more serious such as anaphylaxis or anaphylactic shock. The most commonly accepted mechanism for immunological activation is based on the hapten hypothesis. Drugs are low molecular weight substances that cannot cause an immune response on their own. However, they can act as haptens and form covalent adducts with proteins. The resulting hapten-carrier (drug-protein) conjugate can induce the production of IgE antibodies or T cells. An epitope, or antigenic determinant, is the part of the drug-protein antigen that is specifically recognized by the immune system. This may involve not only the drug derivative but also part of the carrier protein. Understanding the way in which drugs are metabolized after protein conjugation is vital in order to make progresses in the diagnosis of clinical allergy. In this review, recent advances in the identification of the chemical structures of antigenic determinants involved in immediate allergic reactions to drugs are presented. We have focused on drugs that most commonly elicit these reactions: betalactam and quinolone antibiotics and the non-steroidal anti-inflamatory drug pyrazolone. This will be discussed from a chemical point of view, relating our understanding of drug structure, chemical reactivity and immune recognition.

To describe the natural history of eyes with symptomatic idiopathic vitreomacular traction (VMT).Retrospective multicenter study of 168 eyes with spectral-domain optical coherence tomography (SD-OCT) findings consistent with idiopathic VMT. All eyes were graded according to SD-OCT findings. Grade 1 was defined as incomplete cortical vitreous separation with foveal attachment. Grade 2 was defined as Grade 1 plus intraretinal cysts or clefts. Grade 3 was defined as Grade 2 plus a foveal detachment. All patients were followed for at least 6 months.There were 168 patients (51 men) with a mean age of 68.8 ± 10.7 years. Patients were followed for a mean of 22.7 ± 20.1 months. The mean duration of symptoms before the initial presentation was 3.65 ± 5.42 months. At baseline, 72 eyes had Grade 1, 74 eyes had Grade 2, and 22 eyes had Grade 3 SD-OCT findings. Over the follow-up period, 36 eyes (21.4%) had spontaneous resolution of the VMT with normalization of the foveal anatomy. The mean time to resolution was 12.3 ± 12.6 months. An unfavorable anatomical outcome occurred in 7.7% (13 of 168) of the eyes, with 6 eyes developing a lamellar macular hole and 7 eyes developing a full-thickness macular hole. This occurred at a mean of 10.3 ± 10.7 months after the presentation. Subgroup analysis based on baseline SD-OCT grade showed that 4.1% (3 of 73) of Grade 1 eyes compared with 6.8% (5 of 74) of Grade 2 eyes, and 23.8% (5 of 21) of Grade 3 eyes developed a full-thickness macular hole or lamellar macular hole (P = 0.0109, chi-square test). In the remaining 119 eyes, at the last follow-up, 65 eyes had Grade 1, 42 eyes had Grade 2, and 12 eyes had Grade 3 VMT. On average, the best-corrected visual acuity improved from 0.40 ± 0.35 logarithm of the minimum angle of resolution (Snellen, 20/50) at baseline to 0.35 ± 0.36 logarithm of the minimum angle of resolution (Snellen, 20/45; P = 0.0372), and the mean central macular thickness improved from 350 ± 132 μm to 323 ± 121 μm.Spontaneous resolution of VMT occurred in 21.4% (36 of 168) of eyes after a mean follow-up of 11.4 ± 12.6 months. An unfavorable anatomical outcome occurred in 7.7% (13 of 168) of eyes. The baseline SD-OCT grade may predict the progression to full-thickness macular hole.

Heart failure (HF) is framed in one of the types of cardiovascular diseases; it consists of an acute and chronic form. The disease can evolve slowly from asymptomatic left ventricular dysfunction, to a state of severe disability, presenting a wide prevalence in the population around 10% in people over 70 years old. More than three-quarters of the deaths from this pathology normally occur in low or middle-income countries. Angola is not exempt from this health problem be observed in a relatively young people, bringing disability and death at an early stage of life. Scientific advances and innovative treatments for the control and prevention of the disease continue to be insufficient. The ozone for it’s antioxidant, hemorheologic properties, oxygenation enhancers and blood circulation is an alternative treatment for these patients. We have performed a study where 45 patients who were diagnosed with a chronic stage of II-III HF due to the functional classification of the New York Heart Association (NYHA) and American Cardiology College / American Heart Association (ACC / AHA), previous echocardiogram with a Fracture of Left Ventricular Ejection (LVEF) less than 45%. We administered a Major Autohemotherapy with a protocol of 15 sessions, maintenance every 15 days and cycles every 6 months at 50?g of concentration, an initial dose of 4,000 ?g / ml up to 12,000?g / ml during the 3 years of treatment. Patients after the first treatment cycle improve their functional physical capacity and LVEF increased to normal levels (55%). It was proved that Autohemotherapy is an adjuvant, viable and beneficial treatment in chronic HF. Key words: Heart failure (HF), Major Autohemotherapy, Ozone therapy, Fracture of Left Ventricular Ejection

The Hepatitis B (HVB) is one of the most common infectious diseases in the world, it’s wide geographical distribution is a health problem, especially on the African continent, with prevalence rate of 6.1% in the adult population. Current treatment requires prolonged therapy (most cases for the rest of life) with the aim of stopping viral replication, maintaining immunological stability, preventing progression of liver disease and the most feared complications such as cirrhosis and hepatic cancer There are multiple references that point to ozone therapy as an alternative in the treatment of Hepatitis B, because of the known and demonstrated antimicrobial and immunomodulatory properties. With these premises, we performed the present clinical study that included 28 patients with positive diagnosis of chronic Hepatitis B, surface antigen (HVBs Ag) positive, antibodies against surface antigen (HVBs) negative, viral load (HVB DNA ) and transaminaseselevated. These patients with 1 year of evolution and antiviral treatment were treated with Major Autohemotherapy with protocol of 15 sessions and maintenance every 15 days to 50 mcg of concentration, initial dose of 4,000 mcg / ml up to 12,000 mcg /ml We indicate Ag HVBs, Ac HVBs, HVB Viral Loading and transaminases before starting treatment at 15 days of completion and quarterly until the year. The results showed negativization of the surface antigen, antibody positivity against the surface antigen, significant decrease of viral load to undetectable values and normal values of the transaminases demonstrating the functional recovery of the disease associated with favorable immunological response providing a better quality of patients' lives. Key words: Hepatitis B, Transaminases, Ozone therapy, Major Autohemotherapy, Surface antigen, Surface Antigen Antibody.

The Internet of Things (IoT) is a fast-emerging technology which aims to address the societal challenges faced by the modern cities. IoT can be underpinned in a wide range of Smart City applications including (but not limited to) holistic urban planning, tracking of city wide services, enhancing public transportation, while reducing traffic congestion, keeping citizens safe, enabling sustainable economic growth, and improving quality of life of citizens. IoT has been growing rapidly in different domains, which led to the development of numerous IoT platforms, standards, and protocols, etc. Today, within a Smart City, different types of IoT systems and applications are deployed which operate independently. There is a need to enable city authorities and application developers to see IoT systems as part of an integrated whole, allowing optimal use of existing infrastructure and achieving more than what these independent systems can do in isolation. Furthermore, with the arrival of European Union’s General Data Protection Regulation (GDPR), the governance of diverse IoT resources has become a critical requirement. This paper presents a smart governance methodology designed for managing heterogeneous IoT systems. The proposed approach facilitates the semantic interoperability of IoT infrastructure deployed across various domains in Smart Cities and enables integrated governance (and management) of IoT systems and their resources.

In this paper we look at describing the ways on how Artificial Intelligence and IoT are related for the future of multi-domain applications and integrated services, a paper discussing the convergence of Artificial Intelligence and IoT technology in the form of real-world applications but also describing how Semantics and Analytics can leverage the next generation of AI IoT-enabled applications like Intelligent Assistant Robots IoT-enabled. We look at the work in progress investigation and also demonstration in a particular scenario for human-centred assistance living in elderly people and how AI IoT-enabled can provide better user experience and how by using IoT data, life improves.

The centralization of Internet of Things (IoT) services (data and applications) running in the cloud has been a tendency since the introduction of the concept-design that the IoT enables the orchestration/management of a huge amount of Internet connected objects. However, the adoption of this conceptual design imposes deployment limitations as high latency and high bandwidth demands. This paper presents an approach to the need of executing load balancing for the Fog of Things Platforms via programmability for distributed Internet of Things environments through the use of Software-Defined Networks (SDN). In this approach each IoT Gateway is responsible for optimally managing a set of sensors through IoT managment Services by reducing the number of failures or overload network link(s) associated with an IoT Gateway. Failure on the IoT Gateway itself due to processing overhead may result in temporary or even permanent unavailability in IoT applications (Web, Mobile, and Desktop) that demand information provided by those devices. We address these problems using Fog of Things load balancing approach and here we present our findings, deployed and implemented progress and experiments results.

The progress towards proving full deployable Internet of Things solutions for cross-domain data exchange is moving slowly and in todays IoT's challenges the need for integrating data across different software platforms and its use over heterogeneous technology remains open. The use of Cloud computing for data sharing as part of the IoT solution(s) design is provided on the basis that sharing data is enabled by the cloud. The emerging of Fog computing is generating that new scenarios are being re-defined, and in particular cases the need for combining both technologies enabling interoperability is explored/studied. This paper presents an approach of the Data Interplay for the Fog of Things. The need for a more structured way to exchange data seamlessly between edge applications and the cloud is required. The data interplay between Fog and Cloud infrastructures addresses the need for big volume generation and storage of data and the way on how to transfer the data from the edge to the cloud and viceversa.

The Internet of Things (IoT) is perceived as a key enabler for addressing the challenges that modern cities face today. IoT has the power to transform cities into Smart Cities. As a consequence, we have been witnessing the proliferation of IoT deployments in Smart Cities that aim to improve processes in various domains such as, energy, transport, health, mobility, etc. Environmental noise is one of the major issues affecting the health and well-being of residents in an urban environment. A major contribution in noise pollution comes from road traffic. This work presents an innovative IoT-based approach to monitor and manage road traffic noise in Smart Cities. Our approach uses an IoT platform for collecting and integrating data streams stemming from multifarious sensing devices. The data are then analyzed in order to identify traffic noise events; if the noise level on a particular road exceeds a specified threshold, the traffic flow is controlled by taking certain measures. In addition to research methodology, we discuss a prototype implementation of the system.

FIESTA-IoT project provides a blueprint experimental infrastructure, software tools, semantic techniques, certification processes and best practices enabling IoT testbed/platforms to interconnect their facility's resources in an interoperable semantic way. FIESTA-IoT project enables the integration of IoT platform's resources, testbeds infrastructure and their associated applications. FIESTA-IoT opens up new opportunities in the development and deployment of experiments using data from IoT testbeds. The FIESTA-IoT infrastructure enables experimenters to use a single EaaS API (i.e. the FIESTA-IoT EaaS API) for executing experiments over multiple IoT federated testbeds in a testbed agnostic way i.e. like accessing a single large scale virtualized testbed. The main goal of the FIESTA-IoT project is to open new horizons in the development and deployment of IoT applications and experiments at a EU (and global) scale, based on the interconnection and interoperability of diverse IoT platforms and testbeds. FIESTA-IoT project's experimental infrastructure provides to the European experimenters in the IoT domain with the unique capability for accessing and sharing IoT semantically annotated datasets in a testbed-agnostic way. FIESTA-IoT enables execution of experiments across multiple IoT testbeds, based on a single API for submitting the experiment and a single set of credentials for the researcher and the portability of IoT experiments across different testbeds and the provision of interoperable standards-based IoT/cloud interfaces over diverse IoT experimental facilities.

PurposeTo compare the functional and anatomical outcomes of eyes with chronic central serous chorioretinopathy treated with yellow micropulse (MP) laser versus half-dose verteporfin photodynamic therapy (PDT).MethodsThis is a multicentre, retrospective comparative study of 92 eyes treated with yellow MP laser (duty cycle of 5%, zero spacing between spots, spot size varied from 100 to 200 µm, power varied from 320 to 660 mW, and the pulse burst duration was 200 ms) and 67 eyes treated with PDT (half-dose verteporfin (3 mg/m2) infused over 10 min), followed by laser activation for 83 s. Spot sizes varied from 400 to 2000 µm.ResultsIn the MP group, at 12 months of follow-up, the mean best corrected visual acuity (BCVA) improved from the logarithm of the minimum angle of resolution (logMAR) of 0.41±0.27 at baseline to 0.21±0.26 (PConclusionsBoth PDT and MP are effective in restoring the macular anatomy. In places where PDT is not available, yellow MP laser may be an adequate treatment alternative.

Data models and semantics are a key aspect for the valorization of data in cross-domain applications and to obtain knowledge/insights beyond the original applications (vertical use cases). An important role of Big Data and a key fundament of its success is this capacity to discover and extract new knowledge beyond the original use of data, in order to learn, optimize processes and understand the hidden rules of our world. This works presents the different data models from standardization bodies such as IEEE PAR2530, ITU-T FG DPM, ETSI ISG CIM and oneM2M, W3C SSN, OMA LwM2M etc. An analysis and comparative among all of them and also the opportunities to link them in order to guarantee that we can obtain the major value through co-operation among cities and different departments. This work is contextualized in the principles from the Open and Agile Smart Cites (OASC) and linked initiatives focused on data management cross-cities and large scale pilots.

HIV continues to be one of the biggest problems for the global public health. The African region is one of the most affected, accounting for almost two thirds of the new infections. Many of them are retroviral medications and multi-therapies aiming to stop the viral replication and maintaining immunological stability, which fail to guarantee the quality of life or enhance the patient's immunity Ozone has biological properties, among which the antimicrobial and modulatory effect on the immune response is highlighted, which makes it possible to use it in a complementary way for the treatment of these patients. We conducted the present study in which the effect of the ozone therapy administered systemically (blood route) is analyzed. We have studied 32 patients to whom we applied Major Autohemotherapy with a protocol of 15 sessions and maintenance every 15 days at 50 µg/ml of concentration; the initial dose was 4,000 µg/mlup to 12,000 µg/ml We indicated viral load, CD4 and CD8 counts before and at the end of therapy. The results showed a significant decrease in viral load to undetectable values and an increase of CD4 and CD8 at the end of the 15 sessions, being maintained at 2 years of treatment, thus achieving a permanent activation of the immune system and improving the quality of life of these patients. Key words: Ozone therapy, HIV-AIDS, Immune Response, Major Autohemotherapy

The emergence of Internet of Things (IoT) promises to solve a wide range of issues that are related to the management of existing resources and delivery of new human-centric services in urban environments. IoT is being harnessed to benefit a wide range of Smart City applications including (but not limited to) holistic urban planning, tracking of city wide services, enhancing public transportation, while reducing traffic congestion, keeping citizens safe, enabling sustainable economic growth, and improving quality of life of citizens. Existing, IoT-enabled, Smart City systems tend to be developed and deployed independently, which leads to disaggregated applications silos. In order to take a practical step towards the realization of a global IoT ecosystem and alleviate this fragmentation, there is a need to enable city authorities and application developers to see IoT systems as part of an integrated whole, allowing optimal use of existing infrastructure and achieving more than what these independent systems can do in isolation. This paper presents a service oriented, QoS-aware, integrated management methodology tailored for Smart City IoT systems. This approach facilitates the semantic interoperability of diverse vertical IoT deployments in Smart Cities and enables integrated management of IoT systems and their resources.

Purpose: To report the incidence and clinical features of patients that experienced un-explained visual loss following silicone oil (SO) removal. Methods: Multicenter retrospective study of patients that underwent SO removal during 2000-2012. Visual loss of ≥2 lines was considered significant. Results: A total of 324 eyes of 324 patients underwent SO removal during the study period. Forty two (13%) eyes suffered a significant visual loss following SO removal. Twenty three (7.1%) of these eyes lost vision secondary to known causes. In the remaining 19 (5.9%) eyes, the loss of vision was not explained by any other pathology. Eleven of these 19 patients (57.9%) were male. The mean age of this group was 49.2 ± 16.4 years. Eyes that had an un-explained visual loss had a mean IOP while the eye was filled with SO of 19.6 ± 6.9 mm Hg. The length of time that the eye was filled with SO was 14.8 ± 4.4 months. In comparison, eyes that did not experience visual loss had a mean IOP of 14 ± 7.3 mm Hg (p < 0.0002) and a mean tamponade duration of 9.3 ± 10.9 months (p < 0.0001). Conclusions: An un-explained visual loss after SO removal was observed in 5.9% of eyes. Factors associated with this phenomenon included a higher IOP and longer SO tamponade duration. © The Author(s) 2017.

Anaphylaxis is an acute, life-threatening, multisystem syndrome resulting from the sudden release of mediators by mast cells and basophils. Although anaphylaxis is often under-communicated and thus underestimated, its incidence appears to have risen over recent decades. Drugs are among the most common triggers in adults, being analgesics and antibiotics the most common causal agents. Anaphylaxis can be caused by immunologic or non-immunologic mechanisms. Immunologic anaphylaxis can be mediated by IgE-dependent or -independent pathways. The former involves activation of Th2 cells and the cross-linking of two or more specific IgE (sIgE) antibodies on the surface of mast cells or basophils. The IgE-independent mechanism can be mediated by IgG, involving the release of platelet-activating factor, and/or complement activation. Non-immunological anaphylaxis can occur through the direct stimulation of mast cell degranulation by some drugs, inducing histamine release and leading to anaphylactic symptoms. Work-up of a suspected drug-induced anaphylaxis should include clinical history; however, this can be unreliable, and skin tests should also be used if available and validated. Drug provocation testing is not recommended due to the risk of inducing a harmful reaction. In vitro testing can help to confirm anaphylaxis by analyzing the release of mediators such as tryptase or histamine by mast cells. When immunologic mechanisms are suspected, serum-sIgE quantification or the use of the basophil activation test can help confirm the culprit drug. In this review, we will discuss multiple aspects of drug-induced anaphylaxis, including epidemiology, mechanisms, and diagnosis.

International audience; This paper introduces an automated rule discovery approach for IoT device data (S-LOR: Sensor-based Linked Open Rules) and its use in smart cities. S-LOR is built following Linked Open Data (LOD) Standards and provides support for semantics-based mechanisms to share, reuse and execute logical rules for interpreting data produced by IoT systems. S-LOR follows LOD principles for data re-usability, semantics-based reasoning and interoperability. In this paper, S-LOR main capability is demonstrated in the context of enabling semantics-based reasoning mechanisms and tools according to application-demand and user requirements. S-LOR (i) supports an automated interpretation of IoT data by executing rules, and (ii) allows an automated rule discovery interface. The implemented S-LOR mechanism can automatically process and interpret data from IoT devices by using rule-based discovery paradigm. Its extension called Linked Open Reasoning (LOR) enables and encourages re-usability of reasoning mechanisms and tools for different IoT smart city applications. The use cases described in this paper fits in the domain of smart city applications within Internet of Things deployed systems.

PurposeTo report the long-term anatomical and visual outcomes of intravitreal bevacizumab (IVB) monotherapy in naive choroidal neovascularisation (CNV) caused by myopia.MethodsRetrospective analysis of naive CNV secondary to myopia that underwent antivascular endothelial growth factor monotherapy was performed. Collected data included demographic details, clinical examination details including visual acuity at presentation and follow-up with imaging and treatment details. Main outcome measures were resolution of CNV activity at the last visit. Secondary outcomes included change in visual acuity, number of injections and adverse events.ResultsThirty-three eyes of 31 subjects with a mean age of 51.48±16.4 years were included. The mean follow-up was 66.47 months. 27 eyes had type 2 CNV and the rest seven eyes had type 1 CNV. The mean number of IVB injections per eye was 4.9. Mean visual acuity at baseline reduced from 0.65±0.33 logMAR units (Snellen equivalent=20/89) to 0.73±0.50 logMAR units (20/107) at final follow-up (p=0.003). The mean central macular thickness decreased from 309.31±86 µm at baseline to 267.5±70.89 µm at the last visit (p=0.03). However, visual acuity was maintained (±1 line of baseline) in 13 eyes (39.4%), ≥2 line improvement in nine (27.3%) eyes and more than two lines worsening in 11 eyes (33.3%). Foveal atrophy was observed at baseline and last visit in 6 (12.5%) and 14 (29.1%), respectively (p=0.007). No systemic adverse events were observed.ConclusionIVB monotherapy is safe and effective for long-term treatment of CNV secondary to myopia in real life.

The Web of Things (WoT) is rapidly growing in popularity getting the interest of not only technologist and scientific communities but industrial, system integrators and solution providers. The key aspect of the WoT to succeed is the relatively, easy-to-build ecosystems nature inherited from the web and the capacity for building end-to-end solutions. At the WoT connecting physical devices such as sensors, RFID tags or any devices that can send data through the Internet using the Web is almost automatic. The WoT shared data can be used to build smarter solutions that offer business services in the form of IoT applications. In this chapter, we review the main WoT challenges, with particular interest on highlighting those that rely on combining heterogeneous IoT data for the design of smarter services and applications and that benefit from data interoperability. Semantic web technologies help for overcoming with such challenges by addressing, among other ones the following objectives: 1) semantically annotating and unifying heterogeneous data, 2) enriching semantic WoT datasets with external knowledge graphs, and 3) providing an analysis of data by means of reasoning mechanisms to infer meaningful information. To overcome the challenge of building interoperable semantics-based IoT applications, the Machine-to-Machine Measurement (M3) semantic engine has been designed to semantically annotate WoT data, build the logic of smarter services and deduce meaningful knowledge by linking it to the external knowledge graphs available on the web. M3 assists application and business developers in designing interoperable Semantic Web of Things applications. Contributions in the context of European semantic-based WoT projects are discussed and a particular use case within FIESTA-IoT project is presented., 22 pages

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things ( ...

The Internet as we know it today is a critical infrastructure composed by communication services and end-user applications transforming all aspects of our lives. Recent advances in technology and the inexorable shift towards everything connected are creating a data-driven society where productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex networked systems. The challenge for the Next Generation Internet (NGI) is to design and build enabling technologies, implement and deploy systems, to create opportunities considering increasing uncertainties and emergent systemic behaviours where humans and machines seamlessly cooperate.

Ontology-based applications are becoming more and more popular and are usually domain-specific (e.g., eHealth or domotic). Designing ontologies and semantic-based applications manually is tedious and cumbersome for non-technical expert or semantic web beginners. Internet of Things (IoT) is a new field aiming to connect the physical world surrounded by devices such as sensors to the web to automatically interact with them and build innovative applications. The main challenges are to automate as much as possible the tasks of: (1) reusing the background knowledge previously designed by domain experts, (2) facilitating the tasks of IoT developers willing to integrate semantic web technologies into their applications, and (3) designing interoperable semantic-based IoT applications. Stemming from Linked Open Data and Linked Open Vocabularies, we designed Linked Open Vocabularies for Internet of Things (LOV4IoT), a catalogue of ontologies/datasets/rules relevant for IoT available online. LOV4IoT has been extended with more domains and ontology-based projects, a semantic-based dataset and a bot to enhance automation, and web services. Moreover, we demonstrate several use cases of the LOV4IoT dataset: (1) building Semantic Web of Things applications, (2) extracting frequent terms used in existing ontologies, and (3) stakeholders who can exploit, reuse and combine domain ontologies. Finally, we evaluated this dataset with users who exploit this dataset for their own purposes.

Semantic Web of Things is a new field combining Semantic Web and Internet of Things technologies to be surrounded by smart objects and applications connected to the Web. On one hand, one of the Linked Open Data applications, called DataHub aims at referencing datasets, on the other hand, the Linked Open Vocabularies (LOV) references more than 400 ontologies. However, we discovered that more than 200 ontology-based projects relevant for IoT are not referenced on such tools since domain experts are not aware of them nor of the semantic web best practices. We propose the Machine-to-Machine Measurement (M3) framework, available online, to rapidly design and develop semantic-based cross-domain IoT applications by reusing as much as possible the domain knowledge (ontologies, datasets and rules). To achieve this goal, there are challenging steps: (1) referencing and classifying semantic-based projects relevant for IoT, (2) re-engineering a dataset of interoperable domain rules to deduce high-level abstractions from sensor data, (3) re-engineering an interoperable cross-domain knowledge to combine domains, and (4) assisting developers in designing IoT applications by designing pre-defined templates. In this article, we are focused on referencing and classifying semantic-based projects relevant for IoT by designing the Linked Open Vocabularies for Internet of Things (LOV4IoT) dataset. We also design a dataset of interoperable domain rules to deduce high-level abstractions from sensor data by designing the Sensor-based Linked Open Rules (S-LOR). This work has been applied to two uses cases: (1) redesigning a security and cross-domain knowledge base to assist users in suggesting security mechanisms to secure their applications, and (2) designing semantic-based IoT applications embedded in Android-powered devices.

The Internet of Things (IoT) is driving the technology and advances of the Internet and every day it is becoming more popular to talk about IoT systems in multiple domains: Smart Cities, Agriculture, and Industrial Internet, etc. Increasingly, IoT systems will need to interact and be interconnected for offering the always-promoted everything-connected paradigm. Current IoT systems rely on semantic web technologies for integrating data and ensure web services interoperability. However there are yet a gap to ensure semantic interoperability among IoT systems. Most of the existing proposed (open) approaches and solutions lack on formal methodologies for interoperability in technology and standard format of the data. We studied and analyzed most available semantic-based IoT approaches to identify the main requirements hindering IoT semantic interoperability. In this paper, we present SEG 3.0 a methodology to federate, unify and provide semantic interoperability. SEG 3.0 emerges from methodologies for ontology engineering and the idea of unification and federated systems. We propose SEG 3.0 and apply it to Internet of Things (IoT) and particularly on use cases for smart cities as proof of concept. Firstly, we define characteristics required for the methodology. Secondly, we describe the processes and the different formal steps. Thirdly, we provide a proof of concept framework and architecture applying this methodology, thus the benefits of using SEG 3.0 methodology in IoT domains are described. Finally, we demonstrate that the SEG 3.0 methodology is applied to three use cases: (1) the M3 framework to assist developers in designing semantic-based IoT applications, (2) the VITAL EU project for smart cities, and (3) the FIESTA-IoT EU project for IoT semantic interoperability. SEG 3.0 is a formal methodology generic enough to be applied to other domains than IoT and smart cities, since the main benefit of the SEG 3.0 is integrating heterogeneous data and adding value to it to build innovative applications.

The Internet of Things (IoT) has advanced in different directions, including the development of new architectures, platforms and applications. This multidirectional progress has resulted in the creation of several parallel IoT ecosystems called verticals. Therefore, several approaches have proposed solutions for interoperability of these ecosystems through the delivery of services over virtual infrastructure (Cloud Computing). We introduce the paradigm of Fog of Things (FoT) and propose the design and development of a self-organizing platform called SOFT-IoT: Self-Organizing Fog of Things. SOFT-IoT implements the "Fog Computing" concept introduced by CISCO for the Internet of Things, where part of data processing capacity and service delivery operations are processed locally in "small servers", i.e., close to where data is collected. SOFT-IoT deals with protocols to facilitate the local computing processing and rely in more complex operations running in virtual entities avoiding the traditional approach of centralized cloud computing solutions. In this way, SOFT-IoT enables interoperability of local ecosystems in the fog and also at the cloud level, where other data is stored, processed and complex operations are resolved. In other words, in SOFT-IoT the data processing and delivery of services occurs locally in order to overcome with current infrastructure limitations and data processing alleviating those demands for heavy computational resources that can occur in remote servers, i.e., geographically away from where data is generated.

This paper discusses pervasive computing work in the transition from traditional health care programs to personalised health systems (pHealth). A chronological guided transition survey is discussed to highlight trends in medicine describing their most recent developments about health care systems. Future trends in this interdisciplinary techno-medical area are described as research goals. Particularly, research and technological efforts concerning ICT’s and pervasive computing in healthcare and medical applications are presented to identify systems requirements supporting secure and reliable networks and services. The main objectives are to summarise both the pHealth systems requirements providing end-user applications and the necessary pervasive computing support to interconnect device-based health care applications and distributed information data systems in secure and reliable forms, highlighting the role pervasive computing plays in this process. A generic personalised healthcare scheme is introduced to provide guidance in the transition and can be used for multiple medical and health applications. An example is briefly introduced by using the generic scheme proposed.

Internet of Things (IoT) is becoming more and more popular. Increasingly, European projects (CityPulse, IoT.est, IoT-i and IERC), standard development organizations (ETSI M2M, oneM2M and W3C) and developers are involved in integrating Semantic Web technologies to Internet of Things. All of them design IoT application uses cases which are not necessarily interoperable with each other. The main innovative research challenge is providing a unified system to build interoperable semantic-based IoT applications. In this paper, to overcome this challenge, we design the Semantic Web of Things (SWoT) generator to assist IoT projects and developers in: (1) building interoperable Semantic Web of Things (SWoT) applications by providing interoperable semantic-based IoT application templates, (2) easily inferring high-level abstractions from sensor measurements thanks to the rules provided by the template, (3) designing domain-specific or inter-domain IoT applications thanks to the interoperable domain knowledge provided by the template, and (4) encouraging to reuse as much as possible the background knowledge already designed. We demonstrate the usefulness of our contribution though three use cases: (1) cloud-based IoT developers, (2) mobile application developers, and (3) assisting IoT projects. A proof-of concept for providing Semantic Web of Things application templates is available at http://www.sensormeasurement.appspot.com/?p=m3api.

We discuss in this paper, semantic web methodologies, best practices and recommendations beyond the IERC Cluster Semantic Interoperability Best Practices and Recommendations (IERC AC4). The semantic web community designed best practices and methodologies which are unknown from the IoT community. In this paper, we synthesize and highlight the most relevant work regarding ontology methodologies, engineering, best practices and tools that could be applied to Internet of Things (IoT). To the best of our knowledge, this is the first work aiming at bridging such methodologies to the IoT community and go beyond the IERC AC4 cluster. This research is being applied to three uses cases: (1) the M3 framework assisting IoT developers in designing interoperable ontology-based IoT applications, (2) the FIESTA-IoT EU project encouraging semantic interoperability within IoT, and (3) a collaborative publication of legacy ontologies.

To report the long-term anatomical and functional outcomes of patients with choroidal neovascularization secondary to age-related macular degeneration treated with intravitreal bevacizumab (IVB).Retrospective case series. Patients diagnosed with subfoveal choroidal neovascularization secondary to age-related macular degeneration that were treated with at least 1 intravitreal injection of 1.25 mg of IVB and had a minimum follow-up of 60 months. Patients underwent best-corrected Snellen visual acuity testing, optical coherence tomography, and ophthalmoscopic examination at baseline and follow-up visits.Two hundred and forty-seven consecutive patients (292 eyes) were included. The mean number of IVB injections per eye was 10.9 ± 6.4. At 5 years, the BCVA decreased from 20/150 (logMAR 0.9 ± 0.6) at baseline to 20/250 (logMAR 1.1 ± 0.7) (P =0.0001). The mean CMT decreased from 343.1+ 122.3 μm at baseline to 314.7 ± 128.8 μm at 60 months of follow-up (P = 0.009). Geographic atrophy (GA) was observed at baseline in 47 (16%) of 292 eyes. By 5 years, GA developed or progressed in 124 (42.5%) of 292 eyes (P0.0001).The early visual gains obtained from IVB were not maintained at 5 years of follow-up. In addition, IVB may play a role in the development or progression of GA.

Background/aims To report the long-term anatomical and functional outcomes of patients with centre-involved diabetic macular oedema (DME) treated with intravitreal bevacizumab (IVB). Methods Retrospective case series. Patients diagnosed with centre-involved DME that were treated with at least one injection of 1.25 mg IVB and had a minimum follow-up of 60 months. Patients underwent measurement of best-corrected visual acuity (BCVA), ophthalmoscopy, optical coherence tomography and fluorescein angiography at baseline, 6-month, 12-month, 24-month, 36-month, 48-month and 60-month visits. The paired samples t test was used to compare the central macular thickness (CMT) and BCVA with baseline values. Statistical significance was indicated by p Results Two hundred and one consecutive patients (296 eyes) were included. The mean number of IVB injections per eye was 8.4±7.1 (range: 1–47 injections). At 5 years, the BCVA remained stable at 20/100 (logarithm of the minimum angle of resolution=0.7±0.4). Eighty-six (29%) eyes improved ≥2 lines of BCVA, 129 (43.6%) eyes remained stable and 81 (27.4%) eyes lost ≥2 lines of BCVA at 60 months. Mean CMT decreased from 403.5±142.2 μm at baseline to 313.7±117.7 μm over 5 years follow-up (p≤0.0001). Conclusions The early visual gains due to IVB were not maintained 5 years after treatment.