ARMINES

The purpose of this report is to provide support to the design decisions-makers during the design process. For each of the defined design step decision the important topics to consider were identified, the key stakeholders are declared and the purpose of LCA at the selected design step is defined. The report covers: The definition of the design steps, the definition of the tasks in each design step and an overview of the relevant milestones for performing LCA; An overview of the systematic building decomposition methods and the appropriate levels at each design step; An overview of the tools that can be used for LCA and a selection process for choosing the right LCA tool. A special emphasize is given to the topic of Building Information Modelling (BIM), how the BIM tools can facilitate the LCA assessment and what information should be implemented in the BIM model; Strategies on how to reduce the design-related uncertainties; An overview of the visualization of the LCA results and which are appropriate in the selected design steps.

The INTAROS project develops an integrated Arctic Observation System (iAOS) by extending, improving and unifying existing systems in the different regions of the Arctic. Within INTAROS, WP5 (Data integration and management) is tasked with designing and implementing evolutions of the cloud platform with geo statistical tools for services as part of the iAOS. The work effort in Task 5.4 has been to design, develop and distribute a Geostatistical Library to be used as a scientific toolbox in some different data analysis workflows (e.g. for the iAOS showcase applications). <br> The first version of the Geostatistical Library (v1) was considering CTD data provided by IMR for estimating ocean temperature maps in the Barents Sea (D5.6). <br> This document describes the new version of the Geostatistical Library (v2) where some additional capabilities have been developed. A set of new functions deals with weather stations and AROME Arctic model in order to estimate snow depth maps in Isfjorden (Svalbard). Another set supports the combination of ICES CTD dataset, GINR trawls dataset and GEBCO bathymetry for estimating bottom ocean temperature maps along the West Greenland coast.

The INTAROS project develops an integrated Arctic Observation System (iAOS) by extending, improving and unifying existing systems in the different regions of the Arctic. Within INTAROS, WP5 (Data integration and management) develops the iAOS Portal, which provides access to selected datasets and services offered by INTAROS partners and by other Arctic data providers and service providers. This document describes the major functionality and features of this portal and how it has been implemented. Required functionality has been identified through dialogue with users and stakeholders. The approach has been to use agile development techniques to quickly refine user needs and implement new features iteratively. Two main categories of users of the portal were identified: (1) data/service providers and (2) data/services consumers. Providers make their data or services available through the portal, and update the descriptions of these if changes are made. Consumers search for and access data or services, with sufficient descriptions (metadata) for both data and services to whether to use them in their work. The population and promotion of the iAOS Portal equally depends on data providers and consumers including service providers. The iAOS Portal has been implemented using a leading data management system framework named CKAN (Comprehensive Knowledge Archive Network). CKAN offers a broad range of the needed features out of the box and has an active community that develops additional features (plugins) that can be added to the iAOS Portal as needed. Using the CKAN core components and mature plugins, we have implemented the following main components of the iAOS Portal: <strong>INTAROS Data Catalogue</strong>, holding descriptions (metadata) of datasets collected or generated with support from INTAROS. <strong>iAOS Portal Data Catalogue</strong>, holding metadata harvested from other catalogues offering relevant dataset for the applications under development in WP 6 of INTAROS. <strong>Services and Applications</strong>, describing services and applications developed in INTAROS and by other service providers offering products or functionality that can be exploited in WP 6. <strong>Tools and Resources</strong>, providing links to software libraries and tools, computer platforms, data systems, infrastructures and projects that offer data, information and/or software tools that can be useful for scientists and stakeholders in Arctic sciences and for local communities in the region. The <strong>ARCMAP</strong> web application for mapping and assessing Arctic in situ observing systems is available through the portal. ARCMAP that was developed in a spin-off project is also part of the iAOS Portal. The iAOS Portal will be extended with more features, data and services during the course of the INTAROS project as well as in future projects following up INTAROS and the recommendations from the INTAROS Roadmap. These projects will use the iAOS Portal as a mechanism to make their data and services known to the large network of Arctic scientists and local communities established within INTAROS. In this way, the iAOS Portal will become an important element in a Sustained integrated Arctic Observing System. The IAOS Portal is available at https://portal-intaros.nersc.no/.

- Les objectifs du programme « Mine du Futur, Automatisation de la mine et mutualisation des moyens » sont d’explorer les voies possibles d’automatisation par intégration de technologies innovantes dans le processus minier, et d’étudier les possibilités de mutualisation de moyens entre les compagnies minières opérant en Nouvelle-Calédonie. Le terme d’automatisation doit s’entendre dans un sens très large comme une approche technologique permettant un meilleur contrôle des opérations minières.- Dans ce cadre, il a semblé utile et nécessaire de mieux connaitre les compétences numériques des personnels travaillant dans les différentes mines de Nouvelle-Calédonie pour, d’une part savoir quelle est leur maîtrise de certains outils numériques, avoir leur perception sur leur capacité à les utiliser, etd’autre part identifier les attentes et les craintes légitimes des personnels vis-à-vis du développement d’outils numériques dans leur corps d’emploi. - Ce portrait des compétences numériques des employés représente une étape incontournable pour bien choisir les formations à offrir et les outils adaptés àdéployer en réponse aux attentes et aux besoins.

ABSTRACTCarbon-14 (radiocarbon,14C) is a long-lived radionuclide (5730 yr) of interest regarding the safety for the management of intermediate level wastes (ILW). The present study gives an overview of the release of14C from irradiated Zircaloy cladding in alkaline media.14C is found either in the alloy part of Zircaloy cladding due to the neutron activation of14N impurities by14N(n,p)14C reaction, or in the oxide layer (ZrO2) formed at the metal surface by the neutron activation of17O from UO2or (U-Pu)O2fuel and water from the primary circuit in the reactor by17O(n,α)14C reaction. Various irradiated and unirradiated Zircaloys have been studied. The total14C inventory has been determined both experimentally and by calculations. The results seem to be in good agreement. Leaching experiments were conducted in alkaline media for several time durations.14C was mainly released as carboxylic acids. Further, corrosion measurements were performed by using both hydrogen measurements and electrochemical measurements. The corrosion rate (CR) ranges from a few nm/yr to 100 nm/yr depending on the surface conditions and the method used for measurement. From a safety assessment point of view, the instant release fraction (IRF) was determined on irradiated Zircaloy-2. The results showed that the14C inventory in the oxide was significantly below the 20% commonly used in safety case assessments.

The 4-years European project ATLAS+ project was launched in June 2017. Its main objective is to develop advanced structural assessment tools to address the remaining technology gaps for the safe and long term operation of nuclear reactor pressure coolant boundary systems. The transferability of ductile material properties from small scale fracture mechanics specimens to large scale components is one of the topics of the project. A large programme of experimental work is to be conducted in support of the development and validation of advanced tools for structural integrity assessment within the framework of the work-package 1 (WP 1): Design and execution of simulation oriented experiments to validate models at different scales. The experimental work is based on a full set of fracture mechanics experiments conducted on standard specimens and large scale components (several pipes and one mock-up), including a full materials characterization. Three materials are considered: • a ferritic steel 15NiCuMoNb5 (WB 36) • an aged austenitic stainless steel weld • a VVER (eastern PWR) dissimilar metal weld (DMW) The paper presents the WP 1, the experimental programme and summarizes the first results.

We present a practical, differentially private algorithm for answering a large number of queries on high dimensional datasets. Like all algorithms for this task, ours necessarily has worst-case complexity exponential in the dimension of the data. However, our algorithm packages the computationally hard step into a concisely defined integer program, which can be solved non-privately using standard solvers. We prove accuracy and privacy theorems for our algorithm, and then demonstrate experimentally that our algorithm performs well in practice. For example, our algorithm can efficiently and accurately answer millions of queries on the Netflix dataset, which has over 17,000 attributes; this is an improvement on the state of the art by multiple orders of magnitude.

Conventional flow control systems, such as syringe and peristaltic pumps, are not well adapted to the control of flow in microchannels. They often result in long equilibration times, hysteresis and low stability. Herein, we present a new method to control the flows in microchannels based on a pressure actuation, by pressurization of reservoirs filled with fluids to be injected in the microsystem. The regulated pressure within the reservoirs generates pulse-free and very stable flows through the microchannels, with short settling time. To control the flow-rate with pressure actuation, highly precise flow sensors are implemented in the fluidic system and an algorithm has been developed to adjust automatically the pressure orders to reach the targeted flow-rates. Unlike a conventional PID regulation which is very sensitive to any transient behavior, our algorithm deals with any coupling effect between the different channels, and is designed to deliver the fastest and the most stable flow response. It calculates a matrix image of the microsystem with the relations between each actuated pressure channels and the measured flow-rates. Furthermore, the system can cope with any external disturbances of the system (presence of air bubble, partial clogging, variation of viscosity or temperature, etc…), and continuously re-adjust the applied pressures. The technology is perfectly suited for droplet manipulation experiments (among other applications) where we can generate 2pL water-in-oil droplets with very high monodispersity (1.63% CV) at an up to 12 kHz/s frequency. Only few seconds are needed to stop the droplets flow, reducing costs by a huge factor.

Introduction/ Background In hematology, actual diagnosis of B chronic lymphocyte-leukemia (CLL) is based on the microscopic analysis of cell morphology from patient blood smear. However, new photonic technologies appear promising to facilitate and improve the early diagnosis, prognostic and monitoring of personalized therapy. The development of automated diagnostic approaches could assist clinicians in improving the efficiency and quality of health services, but also reduce medical costs. Aims The M3S project aims at improving the diagnosis and prognosis of the CLL pathology by developing a multimodal microscopy platform, including Raman spectrometry, dedicated to the automatic analysis of lymphocytes. Methods Blood smears were prepared on glass slides commonly used in pathology laboratories for microscopy. Two types of sample per patient were prepared: a conventional blood smear and a deposit of “pure” lymphocyte subtypes (i.e. normal B, CLL B, T and NK), sorted out in flow cytometry by using the negative double labeling technique. The second sample is used for the construction of a database of spectral markers specific of these different cell types. The preparations were analyzed with the multimodal machine which combines i) a Raman micro-spectrometer, equipped with a 532nm diode laser excitation source; ii) a microscope equipped with 40x and 150x lenses and a high precision xyz motorized stage for scanning the blood smear, and localizing x-y coordinates of representative series (~100 for each patient) of lymphocyte cells before registering three Raman spectra; these cells of interest being previously localized by an original method based on the morphology analysis. After the Raman acquisitions, the conventional blood smears were submitted to immunolabelling using specific antibodies. For the establishment of the Raman classifiers, this post-acquisition treatment was used as reference to distinguish the different lymphocyte sub-populations. Raman data were then analyzed using chemometric processing and supervised statistical classifiers in order to construct a spectral library of markers highly specific of the lymphocyte type and status (normal or pathological). Results Currently, a total of 60 patients (CLL and healthy) were included in the study. Various classification methods such as LDA (Linear Discriminant Analysis), PLS-DA (Partial Least Square Discriminant Analysis), RF (Random Forest) and SVM (Support Vector Machine), were tested in the purpose to distinguish tumoral B lymphocytes from other cell types. These classification algorithms were combined with feature selection approaches. The best performances were around 70% of correct identification when a three-class model (B-CLL vs B-normal vs T and NK lymphocytes) was considered, and 80% in case of a two-class model (B-CLL vs B-normal lymphocytes). These encouraging results demonstrate the potential of Raman micro-spectroscopy coupled to supervised classification algorithms for leukemic cell classification. The approach can find interest more generally in the field of cyto-hematology. Further developments will concern the integration of additional modality such as Quantitative Phase Imaging on one hand to speed the exploration process of cells of interest to be probed, and on the other hand to extract additional characteristics likely to be informative for CLL diagnosis. In addition, the identification of prognostic markers will be investigated by confronting the photonic data to clinical patient information.

Introduction/ Background In hematology, actual diagnosis of B chronic lymphocyte-leukemia (CLL) is based on the microscopic analysis of cell morphology from patient blood smear. However, new photonic technologies appear promising to facilitate and improve the early diagnosis, prognostic and monitoring of personalized therapy. The development of automated diagnostic approaches could assist clinicians in improving the efficiency and quality of health services, but also reduce medical costs. Aims The M3S project aims at improving the diagnosis and prognosis of the CLL pathology by developing a multimodal microscopy platform, including Raman spectrometry, dedicated to the automatic analysis of lymphocytes. Methods Blood smears were prepared on glass slides commonly used in pathology laboratories for microscopy. Two types of sample per patient were prepared: a conventional blood smear and a deposit of “pure” lymphocyte subtypes (i.e. normal B, CLL B, T and NK), sorted out in flow cytometry by using the negative double labelling technique. The second sample is used for the construction of a database of spectral markers specific of these different cell types. The preparations were analyzed with the multimodal machine which combines i) a Raman micro-spectrometer, equipped with a 532nm diode laser excitation source; ii) a micro- scope equipped with 40x and 150x lenses and a high precision xyz motorized stage for scanning the blood smear, and localizing x-y coordinates of representative series (~100 for each patient) of lymphocyte cells before registering three Raman spectra; these cells of interest being previously localized by an original method based on the morphology analysis. After the Raman acquisitions, the conventional blood smears were submitted immunolabelling using specific antibodies. For the establishment of the Raman classifiers, this post-acquisition treatment was used as reference to distinguish the different lymphocyte sub-populations. Raman data were then analyzed using chemometric processing and supervised statistical classifiers in order to construct a spectral library of markers highly specific of the lymphocyte type and status (normal or pathological). Results Currently, a total of 60 patients (CLL and healthy) were in- cluded in the study. Various classification methods such as LDA (Linear Discriminant Analysis), PLS-DA (Partial Least Square Discriminant Analysis), RF (RandomForest) and SVM (Support Vector Machine), were tested in the purpose to distinguish tumoral B lymphocytes from other cell types. These classification algorithms were combined with feature selection approaches. The best performances were around 70% of correct identification when a three-class model (B-CLL vs B-normal vs T and NK lymphocytes) was considered, and 80% in case of a two-class model (B-CLL vs B-normal lymphocytes). These encouraging results demonstrate the potential of Raman micro-spectroscopy coupled to supervised classification algorithms for leukemic cell classification. The approach can find interest more generally in the field of cyto-hematology. Further developments will concern the integration of additional modality such as Quantitative Phase Imaging on one hand to speed the exploration process of cells of interest to be probed, and on the other hand to extract additional characteristics likely to be informative for CLL diagnosis. In addition, the identification of prognostic markers will be investigated by confronting the photonic data to clinical patient information.