Model-driven interoperability: engineering heterogeneous IoT systems

Interoperability remains a significant burden to the developers of Internet of Things systems. This is because resources and APIs are dynamically composed; they are highly heterogeneous in terms of their underlying communication technologies, protocols and data formats, and interoperability tools remain limited to enforcing standards-based approaches. In this paper, we propose model-based engineering methods to reduce the development effort towards ensuring that complex software systems interoperate with one another. Lightweight interoperability models can be specified in order to monitor and test the execution of running software so that interoperability problems can be quickly identified, and solutions put in place. A graphical model editor and testing tool are also presented to highlight how a visual model improves upon textual specifications. We show using case-studies from the FIWARE Future Internet Service domain that the software framework can support non-expert developers to address interoperability challenges

An incomplete form of childhood Behçet's disease treated with infliximab.

Behçet's disease (BD) is a multi-systemic vasculitis characterized by the possible presence of cutaneous, ocular, articular and neurological manifestations. In this report, we examine the case of a fifteen-year-old boy with an incomplete form of juvenile Behcet's disease which began with joint involvement and developed into a complete form only after several years. The patient showed a rapid response to anti-TNF-alpha (infliximab) with an improvement of mucocutaneous lesions (oral and genital ulcers, pseudofolliculitis) and arthritis

Probabilistic Verification at Runtime for Self-Adaptive Systems

An effective design of effective and efficient self-adaptive systems may rely on several existing approaches. Software models and model checking techniques at run time represent one of them since they support automatic reasoning about such changes, detect harmful configurations, and potentially enable appropriate (self-)reactions. However, traditional model checking techniques and tools may not be applied as they are at run time, since they hardly meet the constraints imposed by on-the-fly analysis, in terms of execution time and memory occupation. For this reason, efficient run-time model checking represents a crucial research challenge. This paper precisely addresses this issue and focuses on probabilistic run-time model checking in which reliability models are given in terms of Discrete Time Markov Chains which are verified at run-time against a set of requirements expressed as logical formulae. In particular, the paper discusses the use of probabilistic model checking at run-time for self-adaptive systems by surveying and comparing the existing approaches divided in two categories: state-elimination algorithms and algebra-based algorithms. The discussion is supported by a realistic example and by empirical experiments

Run Time Models in Adaptive Service Infrastructure

Software in the near ubiquitous future will need to cope with vari- ability, as software systems get deployed on an increasingly large diversity of computing platforms and operates in different execution environments. Heterogeneity of the underlying communication and computing infrastruc- ture, mobility inducing changes to the execution environments and therefore changes to the availability of resources and continuously evolving requirements require software systems to be adaptable according to the context changes. Software systems should also be reliable and meet the user's requirements and needs. Moreover, due to its pervasiveness, software systems must be de- pendable. Supporting the validation of these self-adaptive systems to ensure dependability requires a complete rethinking of the software life cycle. The traditional division among static analysis and dynamic analysis is blurred by the need to validate dynamic systems adaptation. Models play a key role in the validation of dependable systems, dynamic adaptation calls for the use of such models at run time. In this paper we describe the approach we have un- dertaken in recent projects to address the challenge of assessing dependability for adaptive software systems

Immunogenicity of viral vaccines in the italian military

Military personnel of all armed forces receive multiple vaccinations and have been doing so since long ago, but relatively few studies have investigated the possible negative or positive interference of simultaneous vaccinations. As a contribution to fill this gap, we analyzed the response to the live trivalent measles/mumps/rubella (MMR), the inactivated hepatitis A virus (HAV), the inactivated trivalent polio, and the trivalent subunits influenza vaccines in two cohorts of Italian military personnel. The first cohort was represented by 108 students from military schools and the second by 72 soldiers engaged in a nine-month mission abroad. MMR and HAV vaccines had never been administered before, whereas inactivated polio was administered to adults primed at infancy with a live trivalent oral polio vaccine. Accordingly, nearly all subjects had baseline antibodies to polio types 1 and 3, but unexpectedly, anti-measles/-mumps/-rubella antibodies were present in 82%, 82%, and 73.5% of subjects, respectively (43% for all of the antigens). Finally, anti-HAV antibodies were detectable in 14% and anti-influenza (H1/H3/B) in 18% of the study population. At mine months post-vaccination, 92% of subjects had protective antibody levels for all MMR antigens, 96% for HAV, 69% for the three influenza antigens, and 100% for polio types 1 and 3. An inverse relationship between baseline and post-vaccination antibody levels was noticed with all the vaccines. An excellent vaccine immunogenicity, a calculated long antibody persistence, and apparent lack of vaccine interference were observed

Min-Max Coverage in Multi-interface Networks

International audienceWe consider devices equipped with multiple wired or wireless interfaces. By switching among interfaces or by combining the available interfaces, each device might establish several connections. A connection is established when the devices at its endpoints share at least one active interface. Each interface is assumed to require an activation cost. In this paper, we consider the problem of establishing the connections defined by a network G = (V,E) while keeping as low as possible the maximum cost set of active interfaces at the single nodes. Nodes V represent the devices, edges E represent the connections that must be established. We study the problem of minimizing the maximum cost set of active interfaces among the nodes of the network in order to cover all the edges. We prove that the problem is NP-hard for any fixed Δ ≥ 5 and k ≥ 16, with Δ being the maximum degree, and k being the number of different interfaces among the network. We also show that the problem cannot be approximated within Ω(ln Δ). We then provide a general approximation algorithm which guarantees a factor of O((1 + b)ln (Δ)), with b being a parameter depending on the topology of the input graph. Interestingly, b can be bounded by a constant for many graph classes. Other approximation and exact algorithms for special cases are presented

Bandwidth Constrained Multi-interface Networks

International audienceIn heterogeneous networks, devices can communicate by means of multiple wired or wireless interfaces. By switching among interfaces or by combining the available interfaces, each device might establish several connections. A connection is established when the devices at its endpoints share at least one active interface. Each interface is assumed to require an activation cost, and provides a communication bandwidth. In this paper, we consider the problem of activating the cheapest set of interfaces among a network G = (V,E) in order to guarantee a minimum bandwidth B of communication between two specified nodes. Nodes V represent the devices, edges E represent the connections that can be established. In practical cases, a bounded number k of different interfaces among all the devices can be considered. Despite this assumption, the problem turns out to be NP-hard even for small values of k and Δ, where Δ is the maximum degree of the network. In particular, the problem is NP-hard for any fixed k ≥ 2 and Δ ≥ 3, while it is polynomially solvable when k = 1, or Δ ≤ 2 and k = O(1). Moreover, we show that the problem is not approximable within ηlogB or Ω(loglog|V|) for any fixed k ≥ 3, Δ ≥ 3, and for a certain constant η, unless P=NP. We then provide an approximation algorithm with ratio guarantee of b max , where b max is the maximum communication bandwidth allowed among all the available interfaces. Finally, we focus on particular cases by providing complexity results and polynomial algorithms for Δ ≤ 2

A Feedback-Based Adaptive Service-Oriented Paradigm for the Internet of Things

© Springer International Publishing AG, part of Springer Nature 2018. With integrating physical devices into digital world, Internet of Things (IoT) have presented tremendous potential in various different application domains such as smart cities, intelligent transportation, smart home, healthcare and industrial automation. However, current IoT solutions and usage scenarios are still very limited because of the difficulty in sensing the context in continuously changing environments and adaptation to the changes accordingly. The complex dynamic interactions between system components and physical environments are a bit challenging especially when there are other concerns such as scalability and heterogeneity. To solve this problem, a novel adaptive service-oriented paradigm is proposed to support IoT from a low-level viewpoint. The paradigm can overcome some disadvantages of REST (Representational State Transfer) architecture style in the IoT. Two classical examples are illustrated using the proposed paradigm by adding an extra constraint based on REST to improve system states verification and enhance the functionality in modelling physical processes

Cell-to-Cell Signaling Influences the Fate of Prostate Cancer Stem Cells and Their Potential to Generate More Aggressive Tumors

An increasing number of malignancies has been shown to be initiated and propelled by small subpopulations of cancer stem cells (CSC). However, whether tumor aggressiveness is driven by CSC and by what extent this property may be relevant within the tumor mass is still unsettled. To address this issue, we isolated a rare tumor cell population on the basis of its CD44+CD24− phenotype from the human androgen-independent prostate carcinoma cell line DU145 and established its CSC properties. The behavior of selected CSC was investigated with respect to the bulk DU145 cells. The injection of CSC in nude mice generated highly vascularized tumors infiltrating the adjacent tissues, showing high density of neuroendocrine cells and expressing low levels of E-cadherin and β-catenin as well as high levels of vimentin. On the contrary, when a comparable number of unsorted DU145 cells were injected the resulting tumors were less aggressive. To investigate the different features of tumors in vivo, the influence of differentiated tumor cells on CSC was examined in vitro by growing CSC in the absence or presence of conditioned medium from DU145 cells. CSC grown in permissive conditions differentiated into cell populations with features similar to those of cells held in aggressive tumors generated from CSC injection. Differently, conditioned medium induced CSC to differentiate into a cell phenotype comparable to cells of scarcely aggressive tumors originated from bulk DU145 cell injection. These findings show for the first time that CSC are able to generate differentiated cells expressing either highly or scarcely aggressive phenotype, thus influencing prostate cancer progression. The fate of CSC was determined by signals released from tumor environment. Moreover, using microarray analysis we selected some molecules which could be involved in this cell-to-cell signaling, hypothesizing their potential value for prognostic or therapeutic applications

Structure-Based Virtual Screening for Drug Discovery: a Problem-Centric Review

Structure-based virtual screening (SBVS) has been widely applied in early-stage drug discovery. From a problem-centric perspective, we reviewed the recent advances and applications in SBVS with a special focus on docking-based virtual screening. We emphasized the researchers’ practical efforts in real projects by understanding the ligand-target binding interactions as a premise. We also highlighted the recent progress in developing target-biased scoring functions by optimizing current generic scoring functions toward certain target classes, as well as in developing novel ones by means of machine learning techniques