Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

Stable-isotope techniques to investigate sources of plant water

Stable isotopologues of water (mainly 1H216O, HD16O and 1H218O) have been used for decades as tracers of the Earth's water cycle. In this chapter, we briefly describe the theoretical background and state-of-the-art techniques of the use of water stable isotopes to investigate the sources of plant water. We aim to provide the basic understanding of stable isotope fractionation within the Earth's critical zone that is relevant for studies of plant water sources. We then present a practical guide of their most common applications in field studies and the most common and up-to-date laboratory procedures. We finally introduce the existing statistical approaches for estimating the relative contributions of water sources to plant transpiration. By acknowledging the advantages and limitations of each approach, we aim to provide an overview of the current techniques to researchers in the fields of plant ecophysiology, ecohydrology and forest ecology, so that they can make informed decisions when designing their experiments

The interstitium in cardiac repair: role of the immune-stromal cell interplay

Cardiac regeneration, that is, restoration of the original structure and function in a damaged heart, differs from tissue repair, in which collagen deposition and scar formation often lead to functional impairment. In both scenarios, the early-onset inflammatory response is essential to clear damaged cardiac cells and initiate organ repair, but the quality and extent of the immune response vary. Immune cells embedded in the damaged heart tissue sense and modulate inflammation through a dynamic interplay with stromal cells in the cardiac interstitium, which either leads to recapitulation of cardiac morphology by rebuilding functional scaffolds to support muscle regrowth in regenerative organisms or fails to resolve the inflammatory response and produces fibrotic scar tissue in adult mammals. Current investigation into the mechanistic basis of homeostasis and restoration of cardiac function has increasingly shifted focus away from stem cell-mediated cardiac repair towards a dynamic interplay of cells composing the less-studied interstitial compartment of the heart, offering unexpected insights into the immunoregulatory functions of cardiac interstitial components and the complex network of cell interactions that must be considered for clinical intervention in heart diseases

COST-EFFECTIVE BANDWIDTH PROVISIONING IN MICROWAVE WIRELESS NETWORKS UNDER UNRELIABLE CHANNEL CONDITIONS

International audienceCost-effective planning and dimensioning of backhaul microwave networks under unreliable channel conditions remains a relatively under explored area in the literature. In particular, bandwidth assignment requires special attention as the transport capacity of microwave links is prone to variations due to, e.g., weather conditions. In this paper, we formulate an optimization model that determines the minimum cost bandwidth assignment of the links in the network for which traffic requirements can be fulfilled with high probability. This model also aims to increase network reliability by adjusting dynamically traffic routes in response to variations of link capacities induced by channel conditions. Experimental results show that 45% of the bandwidth cost can be saved compared to the case where a bandwidth over-provisioning policy is uniformly applied to all links in the network planning. Comparisons with previous work also show that our solution approach, based on column generation technique, is able to solve much larger instances in significantly shorter computing times (i.e., few minutes for medium-size networks, and up to 2 hours for very large networks, unsolved so far by previous models/algorithms), with a comparable level of reliability