Self-driving Multimodal Studies at User Facilities

Multimodal characterization is commonly required for understanding materials. User facilities possess the infrastructure to perform these measurements, albeit in serial over days to months. In this paper, we describe a unified multimodal measurement of a single sample library at distant instruments, driven by a concert of distributed agents that use analysis from each modality to inform the direction of the other in real time. Powered by the Bluesky project at the National Synchrotron Light Source II, this experiment is a world's first for beamline science, and provides a blueprint for future approaches to multimodal and multifidelity experiments at user facilities.Comment: 36th Conference on Neural Information Processing Systems (NeurIPS 2022). AI4Mat Worksho

The "Object-as-a-Service" paradigm

International audienceThe increasing interest about the Internet of Things (IoT) is almost as remarkable than its practical absence in our everyday lives. Announced as the new breakthrough in IT industry, the domain is characterized by a large number of architecture propositions that are in charge of providing a structure for applications creation. These architectures are needed because of the heterogeneity of stakeholders involved in IoT Applications. Programming languages, operating systems, hardware specificities, processing power, memory, network organization, characteristics, constraints, the world of IoT is so diverse. Furthermore, these architectures should provide an easy access to users that are not aware of IT technologies involved. The Services Oriented Computing (SOC) has shown in the past its relevance to the decoupling constraints interoperability among stakeholders. The composition of loosely coupled services facilitates the integration of very varied elements and provides agility in the creation of new applications. But unlike the approach inherited from the SOC in pre-existing services are composed to obtain a specific application, we propose a more dynamic notion of service. Our "Object-as-a-Service" point of view is based on the notion of building dynamically the service needed on each Object and then integrate it in the whole composition. This paper focus on the gain of this approach for the IoT by promoting the "Object-as-a-Service" paradigm as a basis for the creation of dynamic and agile user-made applications

Linked data and online classifications to organise mined patterns in patient data

In this paper, we investigate the use of web data resources in medicine, especially through medical classifications made available using the principles of Linked Data, to support the interpretation of patterns mined from patient care trajectories. Interpreting such patterns is naturally a challenge for an analyst, as it requires going through large amounts of results and access to sufficient background knowledge. We employ linked data, especially as exposed through the BioPortal system, to create a navigation structure within the patterns obtained form sequential pattern mining. We show how this approach provides a flexible way to explore data about trajectories of diagnoses and treatments according to different medical classifications

From parasite genomes to one healthy world: Are we having fun yet?

In 1990, the Human Genome Sequencing Project was established. This laid the ground work for an explosion of sequence data that has since followed. As a result of this effort, the first complete genome of an animal, Caenorhabditis elegans was published in 1998. The sequence of Drosophila melanogaster was made available in March, 2000 and in the following year, working drafts of the human genome were generated with the completed sequence (92%) being released in 2003. Recent advancements and next-generation technologies have made sequencing common place and have infiltrated every aspect of biological research, including parasitology. To date, sequencing of 32 apicomplexa and 24 nematode genomes are either in progress or near completion, and over 600k nematode EST and 200k apicomplexa EST submissions fill the databases. However, the winds have shifted and efforts are now refocusing on how best to store, mine and apply these data to problem solving. Herein we tend not to summarize existing X-omics datasets or present new technological advances that promise future benefits. Rather, the information to follow condenses up-to-date-applications of existing technologies to problem solving as it relates to parasite research. Advancements in non-parasite systems are also presented with the proviso that applications to parasite research are in the making

Microservices-based IoT Applications Scheduling in Edge and Fog Computing: A Taxonomy and Future Directions

Edge and Fog computing paradigms utilise distributed, heterogeneous and resource-constrained devices at the edge of the network for efficient deployment of latency-critical and bandwidth-hungry IoT application services. Moreover, MicroService Architecture (MSA) is increasingly adopted to keep up with the rapid development and deployment needs of the fast-evolving IoT applications. Due to the fine-grained modularity of the microservices along with their independently deployable and scalable nature, MSA exhibits great potential in harnessing both Fog and Cloud resources to meet diverse QoS requirements of the IoT application services, thus giving rise to novel paradigms like Osmotic computing. However, efficient and scalable scheduling algorithms are required to utilise the said characteristics of the MSA while overcoming novel challenges introduced by the architecture. To this end, we present a comprehensive taxonomy of recent literature on microservices-based IoT applications scheduling in Edge and Fog computing environments. Furthermore, we organise multiple taxonomies to capture the main aspects of the scheduling problem, analyse and classify related works, identify research gaps within each category, and discuss future research directions.Comment: 35 pages, 10 figures, submitted to ACM Computing Survey

Combining Pharmacokinetics and Vibrational Spectroscopy: MCR-ALS Hard-and-Soft Modelling of Drug Uptake In Vitro Using Tailored Kinetic Constraints

Raman microspectroscopy is a label-free technique which is very suited for the investigation of pharmacokinetics of cellular uptake, mechanisms of interaction, and efficacies of drugs in vitro. However, the complexity of the spectra makes the identification of spectral patterns associated with the drug and subsequent cellular responses difficult. Indeed, multivariate methods that relate spectral features to the inoculation time do not normally take into account the kinetics involved, and important theoretical information which could assist in the elucidation of the relevant spectral signatures is excluded. Here, we propose the integration of kinetic equations in the modelling of drug uptake and subsequent cellular responses using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and tailored kinetic constraints, based on a system of ordinary differential equations. Advantages of and challenges to the methodology were evaluated using simulated Raman spectral data sets and real Raman spectra acquired from A549 and Calu-1 human lung cells inoculated with doxorubicin, in vitro. The results suggest a dependency of the outcome on the system of equations used, and the importance of the temporal resolution of the data set to enable the use of complex equations. Nevertheless, the use of tailored kinetic constraints during MCR-ALS allowed a more comprehensive modelling of the system, enabling the elucidation of not only the time-dependent concentration profiles and spectral features of the drug binding and cellular responses, but also an accurate computation of the kinetic constants

Improving Semantic Web Services Discovery Using SPARQL-Based Repository Filtering

Semantic Web Services discovery is commonly a heavyweight task, which has scalability issues when the number of services or the ontology complexity increase, because most approaches are based on Description Logics reasoning. As a higher number of services becomes available, there is a need for solutions that improve discovery performance. Our proposal tackles this scalability problem by adding a preprocessing stage based on two SPARQL queries that filter service repositories, discarding service descriptions that do not refer to any functionality or non-functional aspect requested by the user before the actual discovery takes place. This approach fairly reduces the search space for discovery mechanisms, consequently improving the overall performance of this task. Furthermore, this particular solution does not provide yet another discovery mechanism, but it is easily applicable to any of the existing ones, as our prototype evaluation shows. Moreover, proposed queries are automatically generated from service requests, transparently to the user. In order to validate our proposal, this article showcases an application to the OWL-S ontology, in addition to a comprehensive performance analysis that we carried out in order to test and compare the results obtained from proposed filters and current discovery approaches, discussing the benefits of our proposal

Engineering Pervasive Service Ecosystems: The SAPERE approach

Emerging pervasive computing services will typically involve a large number of devices and service components cooperating together in an open and dynamic environment. This calls for suitable models and infrastructures promoting spontaneous, situated, and self-adaptive interactions between components. SAPERE (Self-Aware Pervasive Service Ecosystems) is a general coordination framework aimed at facilitating the decentralized and situated execution of self-organizing and self-adaptive pervasive computing services. SAPERE adopts a nature-inspired approach, in which pervasive services are modeled and deployed as autonomous individuals in an ecosystem of other services and devices, all of which interact in accord to a limited set of coordination laws, or eco-laws. In this article, we present the overall rationale underlying SAPERE and its reference architecture. We introduce the eco-laws--based coordination model and show how it can be used to express and easily enforce general-purpose self-organizing coordination patterns. The middleware infrastructure supporting the SAPERE model is presented and evaluated, and the overall advantages of SAPERE are discussed in the context of exemplary use cases