Interoperable services based on activity monitoring in ambient assisted living environments

Ambient Assisted Living (AAL) is considered as the main technological solution that will enable the aged and people in recovery to maintain their independence and a consequent high quality of life for a longer period of time than would otherwise be the case. This goal is achieved by monitoring human’s activities and deploying the appropriate collection of services to set environmental features and satisfy user preferences in a given context. However, both human monitoring and services deployment are particularly hard to accomplish due to the uncertainty and ambiguity characterising human actions, and heterogeneity of hardware devices composed in an AAL system. This research addresses both the aforementioned challenges by introducing 1) an innovative system, based on Self Organising Feature Map (SOFM), for automatically classifying the resting location of a moving object in an indoor environment and 2) a strategy able to generate context-aware based Fuzzy Markup Language (FML) services in order to maximize the users’ comfort and hardware interoperability level. The overall system runs on a distributed embedded platform with a specialised ceiling- mounted video sensor for intelligent activity monitoring. The system has the ability to learn resting locations, to measure overall activity levels, to detect specific events such as potential falls and to deploy the right sequence of fuzzy services modelled through FML for supporting people in that particular context. Experimental results show less than 20% classification error in monitoring human activities and providing the right set of services, showing the robustness of our approach over others in literature with minimal power consumption

Effect of moisture on cadmium sulfide solar cells

Moisture effect on thin-film cadmium-sulfide solar cell

Fuzzy logic as-a-service for Ambient Intelligence Environments

Fuzzy Logic Systems (FLSs) are normally associated with dedicated hardware/software systems. However, the distributed and pervasive architecture of many modern hardware/software systems is driving increasing interest in pervasive, distributed FLSs. Achieving this vision will require the design of FLS implementations which support client-server models and more specifically, cloud-computing and service-oriented solutions. Here, FLSs become a globally accessible service that enables openness, device independence, load balancing, resource sharing and ultimately cost effectiveness. In this paper, the recently standardised fuzzy mark-up language (IEEE-1855) and proposed extensions are used for designing Web Services for FLS computations. The novelty of this approach is in integrating different FLS components (input collection, processing and output) into a single web service platform which uses a well specified language for communication over the Web via HTTP request/responses. The utility of this approach is shown in the context of implementing FLSs in Ambient Intelligent Environments

Magnetic control of DTT alternative plasma configurations

One of the main challenges concerning next generation tokamaks (such as DEMO) will be the development of a heat and power exhaust system able to withstand the large loads expected in the divertor region. A dedicated Divertor Tokamak Test (DTT) facility has been proposed in the EUROfusion Roadmap, with the aim of testing unconventional solutions, such as advanced magnetic configurations and liquid metal divertors. Magnetic control of alternative plasma configurations, such as the X-Divertor, will play a key role in the solution of the heat exhaust and yet can be a challenging point, due to increased sensitivity introduced by secondary x-points. To overcome the complications introduced by secondary x-points in advanced plasma shapes, magnetic control in DTT is achieved by resolving to the eXtreme Shape Controller, in order to control both the plasma shape and the secondary x-point position

Controller Synthesis for Timeline-based Games

In the timeline-based approach to planning, originally born in the space sector, the evolution over time of a set of state variables (the timelines) is governed by a set of temporal constraints. Traditional timeline-based planning systems excel at the integration of planning with execution by handling temporal uncertainty. In order to handle general nondeterminism as well, the concept of timeline-based games has been recently introduced. It has been proved that finding whether a winning strategy exists for such games is 2EXPTIME-complete. However, a concrete approach to synthesize controllers implementing such strategies is missing. This paper fills this gap, outlining an approach to controller synthesis for timeline-based games

Mechanized recovery of olive pruning residues: ash contamination and harvesting losses

Agricultural residues represent an important source of biomass for energy. Among the available biomass suitable for energy and available in Italy, pruning represents about the 20% of the total. About 1.184 million of hectares are planted with olive trees; the pruning residues coming from these plantations represent a wide source of biomass at National level. The authors tested six commercial pruning harvesters to determine harvesting losses and product contamination when recovering pruning residues. All harvesters used a mechanical pick-up to collect the residues and a shredder to reduce them into chips. Three different pick-up settings were tested and namely: 1 cm above ground level, manufacturer’s specification and 3 cm above ground level. Ash content in the shredded material was taken as a measure of contamination: the uncontaminated branch material collected directly from the trees had a value of 3.5%, whereas in shredded residues varied between 4.5% and over 5.5%, for the shortest and the longest distance between the pick-up and the soil surface, respectively. Harvesting losses were slightly, but significantly, related to pick-up setting, and mainly depended on machine type. Both machines have shown a good quality of the work performed and the results obtained indicates that the work phases could be simplified in order to reduce both the time of use and the harvesting costs

Solid-phase microextraction-gas chromatography-mass spectrometry method validation for the determination of endogenous substances: urinary hexanal and heptanal as lung tumor biomarkers

Hexanal and heptanal are endogenous aldehydes coming from membrane lipid oxidation, found in lung cancer patients’ blood, and suggested as lung tumor biomarkers. Here the urinary matrix was investigated instead of blood and the difficulties related to the determination of endogenous substances in biological matrices were faced by developing an external calibration HS-SPME/GC/MS method. The methodology was validated according to international validation procedures and it was verified analyzing unknown biological samples from cancer patients and healthy subjects. Percentage accuracy and precision, ranging from −11.25 to 10.85% and from 0.45 to 4.46%, respectively, were obtained, together with limits of detection (LODs) and lower limits of quantification (LLOQs) of 0.11 and 0.23 pg L−1 for hexanal and of 0.10 and 0.21 pg L−1 for heptanal. Analytes percentage recoveries (66.3%, hexanal and 70.5%, heptanal) and stability were evaluated. No analytes degradation was found at room temperature, while the remarkable analytes loss found after 1 month storage suggests analyzing biological samples within a week from storage. Results coming from the analysis of unknown biological samples showed no evident differences of heptanal urinary excretion between lung cancer patients and healthy subjects (0.22–0.95 and 0.21–0.69 pg L−1, respectively), while hexanal urinary concentrations in cancer patients (0.24–4.36 pg L−1) were slightly higher than those found in control group ones (0.23–1.26 pg L−1). The obtained results highly suggest to do further investigations in order to collect statistically significant biological data to discriminate between the pathological state of lung cancer patients and physiological conditions of healthy subjects, using the simple, rapid and cheap method here reported for the quantification of urinary aldehydes

Analytical and pharmacological aspects of therapeutic drug monitoring of mTOR inhibitors

Mammalian Target Of Rapamycin (mTOR) inhibitors represent a new class of immunosuppressant drugs extensively used for the prevention and the treatment of graft rejection in organ transplant recipients. Their current use is due to referred low nephrotoxic effects, particularly important in kidney transplanted and/or patients with renal failure. The most representative drugs of such class are Sirolimus (Siro) and Everolimus (Rad). Both drugs show a narrow therapeutic window, therefore, monitoring of whole-blood drug levels is recommended in order to optimize the therapy. Among the available assays, Liquid Chromatography coupled with UltraViolet or Electrospray Tandem Mass Spectrometry methods (LC/UV or LC/ESI-MSMS) are the most accurate and specific ones. A reliable alternative is represented by immunoassays, which offer the opportunity to minimize sample pre-treatment, thus reducing the time between drawing blood sample and measuring the drug concentration, an important aspect in high-throughput analyses. Despite this, a limitation in the use of immunoassays for therapeutic drug monitoring is the lower specifity compared with the chromatographic methods when analysing structurally-related drugs. New insights to optimize mTOR inhibitors regimens seem to be offered by the evaluation of CYP450 3A activity by using the probe drug approach. To such purpose, there are a number of major probe drugs used for in vivo studies including: midazolam, cortisol, lidocaine, nifedipine, dextromethorphan, erythromycin, dapsone and alfentanil. The aim of the present paper is to report the most recent knowledge concerning this issue, supplying a critical and comprehensive review for whom are involved both in the clinical and analytical areas

Core Competencies in Cancer Genomics for Healthcare Professionals: Results From a Systematic Literature Review and a Delphi Process

The continuous development and use of genomic sequencing requires healthcare professionals to constantly integrate these advancements into their clinical practice. There is a documented lack of cancer genomics contents in the teaching and learning programs. We aimed to identify the core competencies in cancer genomics for non-genetic healthcare professionals. We performed a literature review in PubMed, SCOPUS, and Web of Science databases to retrieve articles published from 2000 to 2018, in English or Italian language. We included articles that reported the competencies for non-genetic healthcare professionals in cancer genomics. A web-based modified Delphi survey was conducted, aiming to define, through consensus, a set of core competencies that should be covered in the curricula. The international expert panel included specialists in genetics, genomics, oncology, and medical specialists. In the literature review, we retrieved nine articles, from which we identified core competencies for general physicians and nurses. The competencies were organized in three main domains: knowledge, attitudes, and practical abilities. In the second round of Delphi survey, consensus of 83.3% was reached for the definition of the core competencies. Thirty-seven items were defined as the competencies required for physicians and forty-two items for nurses. Through a consensus-based approach, a set of core competencies in cancer genomics for non-genetic healthcare professionals has been identified. Our findings could benchmark standards for curriculum development and future educational strategies

Fuzzy logic on quantum annealers

Quantum computation is going to revolutionize the world of computing by enabling the design of massive parallel algorithms that solve hard problems in an efficient way, thanks to the exploitation of quantum mechanics effects, such as superposition, entanglement and interference. These computational improvements could strongly influence the way how fuzzy systems are designed and used in contexts, such as big data, where computational efficiency represents a non-negligible constraint to be taken into account. In order to pave the way towards this innovative scenario, this paper introduces a novel representation of fuzzy sets and operators based on Quadratic Unconstrained Binary Optimization (QUBO) problems, so as to enable the implementation of fuzzy inference engines on a type of quantum computers known as quantum annealers