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BACKGROUND: In healthcare, an increasing collaboration can be noticed between different caregivers, especially considering the shift to homecare. To provide optimal patient care, efficient coordination of data and workflows between these different stakeholders is required. To achieve this, data should be exposed in a machine-interpretable, reusable manner. In addition, there is a need for smart, dynamic, personalized and performant services provided on top of this data. Flexible workflows should be defined that realize their desired functionality, adhere to use case specific quality constraints and improve coordination across stakeholders. User interfaces should allow configuring all of this in an easy, user-friendly way. METHODS: A distributed, generic, cascading reasoning reference architecture can solve the presented challenges. It can be instantiated with existing tools built upon Semantic Web technologies that provide data-driven semantic services and constructing cross-organizational workflows. These tools include RMLStreamer to generate Linked Data, DIVIDE to adaptively manage contextually relevant local queries, Streaming MASSIF to deploy reusable services, AMADEUS to compose semantic workflows, and RMLEditor and Matey to configure rules to generate Linked Data. RESULTS: A use case demonstrator is built on a scenario that focuses on personalized smart monitoring and cross-organizational treatment planning. The performance and usability of the demonstrator's implementation is evaluated. The former shows that the monitoring pipeline efficiently processes a stream of 14 observations per second: RMLStreamer maps JSON observations to RDF in 13.5 ms, a C-SPARQL query to generate fever alarms is executed on a window of 5 s in 26.4 ms, and Streaming MASSIF generates a smart notification for fever alarms based on severity and urgency in 1539.5 ms. DIVIDE derives the C-SPARQL queries in 7249.5 ms, while AMADEUS constructs a colon cancer treatment plan and performs conflict detection with it in 190.8 ms and 1335.7 ms, respectively. CONCLUSIONS: Existing tools built upon Semantic Web technologies can be leveraged to optimize continuous care provisioning. The evaluation of the building blocks on a realistic homecare monitoring use case demonstrates their applicability, usability and good performance. Further extending the available user interfaces for some tools is required to increase their adoption.

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A healthy and safe indoor environment is an important part of containing the coronavirus disease 2019 (COVID-19) pandemic. Therefore, this work presents a real-time Internet of things (IoT) software architecture to automatically calculate and visualize a COVID-19 aerosol transmission risk estimation. This risk estimation is based on indoor climate sensor data, such as carbon dioxide (CO2) and temperature, which is fed into Streaming MASSIF, a semantic stream processing platform, to perform the computations. The results are visualized on a dynamic dashboard that automatically suggests appropriate visualizations based on the semantics of the data. To evaluate the complete architecture, the indoor climate during the student examination periods of January 2020 (pre-COVID) and January 2021 (mid-COVID) was analyzed. When compared to each other, we observe that the COVID-19 measures in 2021 resulted in a safer indoor environment.

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In today's data landscape, data streams are well represented. This is mainly due to the rise of data-intensive domains such as the Internet of Things (IoT), Smart Industries, Pervasive Health, and Social Media. To extract meaningful insights from these streams, they should be processed in real time, while solving an integration problem as these streams need to be combined with more static data and their domain knowledge. Ontologies are ideal for modeling this domain knowledge and facilitate the integration of heterogeneous data within data-intensive domains such as the IoT. Expressive reasoning techniques, such as OWL2 DL reasoning, are needed to completely interpret the domain knowledge and for the extraction of meaningful decisions. Expressive reasoning techniques have mainly focused on static data environments, as it tends to become slow with growing datasets. There is thus a mismatch between expressive reasoning and the real-time requirements of data-intensive domains. In this paper, we take a first step towards bridging the gap between expressivity and efficiency while reasoning over high-velocity IoT data streams for the task of event enrichment. We present a structural caching technique that eliminates reoccurring reasoning steps by exploiting the characteristics of most IoT streams, i.e., streams typically produce events that are similar in structure and size. Our caching technique speeds up reasoning time up to thousands of times for fully fledged OWL2 DL reasoners and even tenths and hundreds of times for less expressive OWL2 RL and OWL2 EL reasoners.

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In the Internet of Things (IoT), multiple sensors and devices are generating heterogeneous streams of data. To perform meaningful analysis over multiple of these streams, stream processing needs to support expressive reasoning capabilities to infer implicit facts and temporal reasoning to capture temporal dependencies. However, current approaches cannot perform the required reasoning expressivity while detecting time dependencies over high frequency data streams. There is still a mismatch between the complexity of processing and the rate data is produced in volatile domains. Therefore, we introduce Streaming MASSIF, a Cascading Reasoning approach performing expressive reasoning and complex event processing over high velocity streams. Cascading Reasoning is a vision that solves the problem of expressive reasoning over high frequency streams by introducing a hierarchical approach consisting of multiple layers. Each layer minimizes the processed data and increases the complexity of the data processing. Cascading Reasoning is a vision that has not been fully realized. Streaming MASSIF is a layered approach allowing IoT service to subscribe to high-level and temporal dependent concepts in volatile data streams. We show that Streaming MASSIF is able to handle high velocity streams up to hundreds of events per second, in combination with expressive reasoning and complex event processing. Streaming MASSIF realizes the Cascading Reasoning vision and is able to combine high expressive reasoning with high throughput of processing. Furthermore, we formalize semantically how the different layers in our Cascading Reasoning Approach collaborate.

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In hospitals and smart nursing homes, ambient-intelligent care rooms are equipped with many sensors. They can monitor environmental and body parameters, and detect wearable devices of patients and nurses. Hence, they continuously produce data streams. This offers the opportunity to collect, integrate and interpret this data in a context-aware manner, with a focus on reactivity and autonomy. However, doing this in real time on huge data streams is a challenging task. In this context, cascading reasoning is an emerging research approach that exploits the trade-off between reasoning complexity and data velocity by constructing a processing hierarchy of reasoners. Therefore, a cascading reasoning framework is proposed in this paper. A generic architecture is presented allowing to create a pipeline of reasoning components hosted locally, in the edge of the network, and in the cloud. The architecture is implemented on a pervasive health use case, where medically diagnosed patients are constantly monitored, and alarming situations can be detected and reacted upon in a context-aware manner. A performance evaluation shows that the total system latency is mostly lower than 5 s, allowing for responsive intervention by a nurse in alarming situations. Using the evaluation results, the benefits of cascading reasoning for healthcare are analyzed.

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In 2013, the Flemish Government launched the Vitalink platform. This initiative focuses on the sharing of health and welfare data to support primary healthcare. In this paper, the objectives and mission of the Vitalink initiative are discussed. Security and privacy measures are reviewed, and the technical implementation of the Vitalink platform is presented. Through a case study, the possibility of interaction with cloud solutions for healthcare is also investigated upon; this was initially not the focus of Vitalink. The Vitalink initiative provides support for secure data sharing in primary healthcare, which in the long term will improve the efficiency of care and will decrease costs. Based on the results of the case study, Vitalink allowed cloud solutions or applications not providing end-to-end security to use their system. The most important lesson learned during this research was the need for firm regulations and stipulations for cloud solutions to interact with the Vitalink platform. However, these are currently still vague.

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Doping scandals can reveal unresolved tensions between the meritocratic values of equal opportunity + reward for effort and the "talentocratic" love of hereditary privilege. Whence this special reverence for talent? We analyze the following arguments: (1) talent is a unique indicator of greater potential, whereas doping enables only temporary boosts (the fluke critique); (2) developing a talent is an authentic endeavor of "becoming who you are," whereas reforming the fundamentals of your birth suit via artifice is an act of alienation (the phony critique); (3) your (lack of) talent informs you of your proper place and purpose in life, whereas doping frustrates such an amor fati self-understanding (the fateless critique). We conclude that these arguments fail to justify a categorical preference for natural talent over integrated artifice. Instead, they illustrate the extent to which unsavory beliefs about "nature's aristocracy" may still be at play in the moral theatre of sports.

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BACKGROUND: The preventative paradigm of preconception care is receiving increasing attention, yet its boundaries remain vague in three respects: temporally; agentially; and instrumentally. Crucially, it remains unclear just who is to be considered a 'potential parent', how soon they should take up preconception responsibilities, and how weighty their responsibilities should be. DISCUSSION: In this paper, we argue that a normal potential parent of reasonable prudence has a moral duty to adequately optimize the conditions under which she or his reproductive partner will conceive, though a proportionality calculus calls for toleration of several forms of preconception behaviour that are non-ideal from the perspective of reproductive risk. We distinguish between five categories of potential parents to which different duties of preconception care should be ascribed. This framework is advanced to assign preconception care responsibilities with more precision than is often done in the current debate on preconception care. We conclude by applying our theoretical framework to three types of preconception care interventions: consumption of folic acid; keeping one's weight under control; and engaging in preconception genetic screening. Our analysis shows that the literature on preconception care often glosses over crucial distinctions between different types of potential parents and uses a notion of preconception beneficence that may be overly demanding. Nevertheless, preconception moral duties will often be weighty and reluctance to accept such duties on account of the burden they impose do not warrant preconception insouciance. SUMMARY: To avoid misplaced responsibility ascriptions in the growing field of preconception care, distinctions must be made between different types of potential parents to whom different degrees of preconception responsibility apply. We present such a preliminary framework and bring it to bear on the cases of folic acid consumption, obesity and genetic testing.

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In several jurisdictions, sex offenders may be offered chemical castration as an alternative to further incarceration. In some, agreement to chemical castration may be made a formal condition of parole or release. In others, refusal to undergo chemical castration can increase the likelihood of further incarceration though no formal link is made between the two. Offering chemical castration as an alternative to further incarceration is often said to be partially coercive, thus rendering the offender's consent invalid. The dominant response to this objection has been to argue that any coercion present in such cases is compatible with valid consent. In this article, we take a different tack, arguing that, even if consent would not be valid, offering chemical castration will often be supported by the very considerations that underpin concerns about consent: considerations of autonomy. This is because offering chemical castration will often increase the offender's autonomy, both at the time the offer is made and in the future.

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