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Asymptotic homogenisation offers a way to efficiently analyse the mechanical behaviour of multiscale configurations. But near a multiscale boundary, the homogenisation strategy should be modified, as the underlying periodicity assumption breaks down there. In this article, we introduce a machine‐learning‐based asymptotic homogenisation and localisation scheme to formulate such boundary layer effects. To this end, we define a set of boundary layer cells, where external loading conditions are imposed on one side of the cell, and matching conditions with the interior periodic cells are imposed on the opposite side. The formulation is also extended to cover situations where the multi‐scale structure is not fully periodic, but spatially varying. Implied from the asymptotic results, neural networks can be trained to memorise the interrelationship between key local quantities, such as the magnitude of the local maximum von Mises stress, and the local mechanical and geometric features. Equipped with the trained neural networks, the online calculation for key (boundary‐localised) quantities of interest under arbitrary loading conditions is expected to be accelerated substantially. Numerical examples are further presented to show the reliability of the proposed work for boundary stress prediction. [ABSTRACT FROM AUTHOR]

High‐temperature electrochemical cells have received increasing interest in the past years as important elements in an energy transition scenario. Their employment in power‐to‐gas or gas‐to‐power systems naturally requires an accurate design that takes into account the effect of operating conditions and geometries on both the performance of the cells themselves and their integration with other units. To this end, it is important to develop flexible yet comprehensive models for their description and to identify performance parameters that allow a concise assessment of their efficiency. The aim of the present work is to identify the limitations – in terms of applicability and consistency – of the mathematical models developed to date to describe high‐temperature electrochemical cells, as well as the key characteristics that they should possess. A brief review of literature in this field is then reported, to identify the research areas that still need to be explored. [ABSTRACT FROM AUTHOR]

Automating the creation and calibration of microkinetic models enables researchers to perform detailed analysis of reaction mechanisms as well as multi‐scale modelling of reactors based on ab initio calculations. The example of electrochemical CO2 reduction shows that this requires a structured and standardised representation of concepts across multiple scales. Massive progress has been made in this area through dynamic knowledge graphs, whereby the first partial successes can be reported in the area of mechanism generation, quantum mechanical calculations as well as calibration with experimental data. [ABSTRACT FROM AUTHOR]

In this review paper, a critical assessment of the main degradation processes in three key components of solid oxide fuel cells and electrolysers (negative and positive electrodes and the interconnect) is undertaken, attempting prioritization of respective degradation effects and recommendation of the best approaches in their experimental ascertainment and numerical modeling. Besides different approaches to quantifying the degradation rate of an operating solid oxide cell (SOC), the latest advancements in microstructural representation (3D imaging and reconstruction) of SOC electrodes are reviewed, applied to the quantification of triple‐phase boundary (TPB) lengths and morphology evolution over time. The intrinsic degradation processes in the negative (fuel) electrode and the positive (oxygen) electrode are discussed, covering first the composition and governing mechanisms of the respective electrodes, followed by a comprehensive evaluation of the most important factors of degradation during operation. By this systematic identification of dominant degradation processes, measurement techniques, and modeling approaches, the foundations are laid for the definition of meaningful accelerated stress testing of SOC cells and stacks, which will help the technology achieve the constantly more demanding durability targets in market applications. [ABSTRACT FROM AUTHOR]

As landscape‐scale conservation models grow in prominence, assessments of how wildlife utilise multiple‐use landscapes are required to inform effective conservation and management planning. Such efforts should incorporate multi‐species perspectives to maximise value for conservation, and should account for scale to accurately capture species‐environment relationships.We show that the random forest machine learning algorithm can be used to model large‐scale sign‐based data in a multi‐scale framework. We used this method to investigate scale‐dependent habitat associations for 16 mammal species of high conservation importance across the southern Kavango Zambezi (KAZA) Transfrontier Conservation Area in Botswana and Zimbabwe.Our findings revealed substantial variation in factors shaping habitat use across species, and illustrate that different species often have divergent responses to the same environmental and anthropogenic factors, and differ in the scales at which they respond to them. For all variables across all species, scale optimisation most often selected our largest scale.Precipitation, soil nutrients, and vegetation appeared to be the most important factors determining mammal distributions, likely through their associations with food resources for herbivores and, in turn, prey availability for carnivores.Anthropogenic pressures also had an important influence, with many species selecting against areas with high cattle density. The variety of relationships with human density indicated that species vary in their tolerance of humans. We found a consistent positive relationship with areas under high protection, and negative relationship with unprotected and less‐strictly protected areas.Policy implications. Through a novel application of random forest modelling to spoor data from 16 mammal species, this study highlights the importance of adopting a multi‐scale, multi‐species approach for decision‐making processes that depend on understanding wildlife distributions and habitat associations, such as protected area and corridor prioritisation. The findings identify changing rainfall patterns and increasing livestock numbers as emerging trends that may impact wildlife distributions, both within sub‐Saharan Africa and on a global scale. Wildlife management authorities should use modelling exercises and adaptive management to ensure that protected area networks remain fit for purpose under anticipated changes in rainfall under climate change, and explore initiatives that promote coexistence of wildlife and livestock. [ABSTRACT FROM AUTHOR]

Increasing efforts points to the understanding of how to maximize the capabilities of the adaptive immune system to fight against the development of immune and inflammatory disorders. Here we focus on the role of T cells as immune cells which subtype imbalance may lead to disease onset. Specifically, we propose that autoimmune disorders may develop as a consequence of a metabolic imbalance that modulates switching between T cell phenotypes. We highlight a Systems Biology strategy that integrates computational metabolic modelling with experimental data to investigate the metabolic requirements of T cell phenotypes, and to predict metabolic genes that may be targeted in autoimmune inflammatory diseases. Thus, we propose a new perspective of targeting T cell metabolism to modulate the immune response and prevent T cell phenotype imbalance, which may help to repurpose already existing drugs targeting metabolism for therapeutic treatment. [ABSTRACT FROM AUTHOR]

Catalytic dry reforming under industrially relevant conditions of high pressures and high temperatures poses severe challenges towards catalyst materials and process engineering. The demanding conditions under which the reaction is performed lead to a coupling of reactions occurring in the gas phase and reactions which are catalyzed by the material employed as catalyst. A profound analysis of the mechanisms occurring in gas phase and resulting products from gas phase reactions is key to understanding part of the challenges that any catalyst material, irrespective of its nature, will have to cope with. The deposition of coke on an active catalyst is as well one of the most limiting factors for catalyst lifetime and catalyst activity in dry reforming. Therefore, an understanding of the thermodynamics behind coke formation and an intricate description of the mechanisms driving the evolution of coke is a vital piece of the picture. Acid‐base properties of the catalyst material and the role and nature of the active metal do also need to be considered. A large part of the review deals with mechanisms which are relevant for coke gasification and insights into materials properties, which are relevant to allow for reaction pathways along these lines. The review article focusses on research results which have been achieved using model systems – typically the analysis of model systems is a more rewarding exercise compared to fully formulated industrial catalyst systems, as here more elucidating structure‐property relationships can be drawn. Additionally the article discusses dry methane reforming in the context of alternative syngas generation technologies and attempts to create an application perspective for the reader in the context of a sustainable approach towards carbon capture and storage. [ABSTRACT FROM AUTHOR]

Aim: Deforestation is rapidly altering Southeast Asian landscapes, resulting in some of the highest rates of habitat loss worldwide. Among the many species facing declines in this region, clouded leopards rank notably for their ambassadorial potential and capacity to act as powerful levers for broader forest conservation programmes. Thus, identifying core habitat and conservation opportunities are critical for curbing further Neofelis declines and extending umbrella protection for diverse forest biota similarly threatened by widespread habitat loss. Furthermore, a recent comprehensive habitat assessment of Sunda clouded leopards (N. diardi) highlights the lack of such information for the mainland species (N. nebulosa) and facilitates a comparative assessment. Location: Southeast Asia. Methods: Species–habitat relationships are scale‐dependent, yet <5% of all recent habitat modelling papers apply robust approaches to optimize multivariate scale relationships. Using one of the largest camera trap datasets ever collected, we developed scale‐optimized species distribution models for two con‐generic carnivores, and quantitatively compared their habitat niches. Results: We identified core habitat, connectivity corridors, and ranked remaining habitat patches for conservation prioritization. Closed‐canopy forest was the strongest predictor, with ~25% lower Neofelis detections when forest cover declined from 100 to 65%. A strong, positive association with increasing precipitation suggests ongoing climate change as a growing threat along drier edges of the species' range. While deforestation and land use conversion were deleterious for both species, N. nebulosa was uniquely associated with shrublands and grasslands. We identified 800 km2 as a minimum patch size for supporting clouded leopard conservation. Main conclusions: We illustrate the utility of multi‐scale modelling for identifying key habitat requirements, optimal scales of use and critical targets for guiding conservation prioritization. Curbing deforestation and development within remaining core habitat and dispersal corridors, particularly in Myanmar, Laos and Malaysia, is critical for supporting evolutionary potential of clouded leopards and conservation of associated forest biodiversity. [ABSTRACT FROM AUTHOR]

Fens, which are among the most biodiverse of wetland types in the USA, typically occur in glacial landscapes characterized by geo-morphologic variability at multiple spatial scales. As a result, the hydrologic systems that sustain fens are complex and not well understood. Traditional approaches for characterizing such systems use simplifying assumptions that cannot adequately capture the impact of variability in geology and topography. In this study, a hierarchical, multi-scale groundwater modelling approach coupled with a geologic model is used to understand the hydrology of a fen in Michigan. This approach uses high-resolution data to simulate the multi-scale topographic and hydrologic framework and lithologic data from more than 8500 boreholes in a statewide water well database to capture the complex geology. A hierarchy of dynamically linked models is developed that simulates groundwater flow at all scales of interest and to delineate the areas that contribute groundwater to the fen. The results show the fen receiving groundwater from multiple sources: an adjacent wetland, local recharge, a nearby lake and a regional groundwater mound. Water from the regional mound flows to an intermediate source before reaching the fen, forming a 'cascading' connection, while other sources provide water through 'direct' connections. The regional mound is also the source of water to other fens, streams and lakes in this area, thus creating a large, interconnected hydrologic system that sustains the entire ecosystem. In order to sustainably manage such systems, conservation efforts must include both site-based protection and management, as well as regional protection and management of groundwater source areas. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY A new framework for estimation of lumped (for instance, Windkessel) model parameters from uncertain clinical measurements is presented. The ultimate aim is to perform patient-specific haemodynamic analysis. This framework is based on sensitivity analysis tools and the sequential estimation approach of the unscented Kalman filter. Sensitivity analysis and parameter estimation are performed in lumped parameter models, which act as reduced order surrogates of the 3D domain for haemodynamic analysis. While the goal of sensitivity analysis is to assess potential identifiability problems, the unscented Kalman filter estimation leads to parameter estimates based on clinical measurements and modelling assumptions. An application of such analysis and parameter estimation methodology is demonstrated for synthetic and real data. Equality constraints on various physiological parameters are enforced. Since the accuracy of the Windkessel parameter estimates depends on the lumped parameter representativeness, the latter is iteratively improved by running few 3D simulations while simultaneously improving the former. Such a method is applied on a patient-specific aortic coarctation case. Less than 3% and 9% errors between the clinically measured quantities and 3D simulation results for rest and stress are obtained, respectively. Knowledge on how these Windkessel parameters change from rest to stress can thus be learned by such an approach. Lastly, it is demonstrated that the proposed approach is capable of dealing with a wide variety of measurements and cases where the pressure and flow clinical measurements are not taken simultaneously. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Blood travels throughout the body in an extensive network of vessels - arteries, veins and capillaries. This vascular network is not static, but instead dynamically remodels in response to stimuli from cells in the nearby tissue. In particular, the smallest vessels - arterioles, venules and capillaries - can be extended, expanded or pruned, in response to exercise, ischaemic events, pharmacological interventions, or other physiological and pathophysiological events. In this review, we describe the multi-step morphogenic process of angiogenesis - the sprouting of new blood vessels - and the stability of vascular networks in vivo. In particular, we review the known interactions between endothelial cells and the various blood cells and plasma components they convey. We describe progress that has been made in applying computational modelling, quantitative biology and high-throughput experimentation to the angiogenesis process. [ABSTRACT FROM AUTHOR]

Biological complexity has forced scientists to develop highly reductive approaches, with an ever-increasing degree of specialization. As a consequence, research projects have become fragmented, and their results strongly dependent on the experimental context. The general research question, that originally motivated these projects, appears to have been forgotten in many highly specialized research programmes. We here investigate the prospects for use of an old regulative ideal from systems theory to describe the organization of cellular systems 'in general' by identifying key concepts, challenges and strategies to pursue the search for organizing principles. We argue that there is no tension between the complexity of biological systems and the search for organizing principles. On the contrary, it is the complexity of organisms and the current level of techniques and knowledge that urge us to renew the search for organizing principles in order to meet the challenges that are arise from reductive approaches in systems medicine. Reductive approaches, as important and inevitable as they are, should be complemented by an integrative strategy that de-contextualizes through abstractions, and thereby generalizes results. [ABSTRACT FROM AUTHOR]

The cellular recognition of viruses evokes the secretion of type‐I interferons (IFNs) that induce an antiviral protective state. By live‐cell imaging, we show that key steps of virus‐induced signal transduction, IFN‐β expression, and induction of IFN‐stimulated genes (ISGs) are stochastic events in individual cells. The heterogeneity in IFN production is of cellular—and not viral—origin, and temporal unpredictability of IFN‐β expression is largely due to cell‐intrinsic noise generated both upstream and downstream of the activation of nuclear factor‐κB and IFN regulatory factor transcription factors. Subsequent ISG induction occurs as a stochastic all‐or‐nothing switch, where the responding cells are protected against virus replication. Mathematical modelling and experimental validation show that reliable antiviral protection in the face of multi‐layered cellular stochasticity is achieved by paracrine response amplification. Achieving coherent responses through intercellular communication is likely to be a more widely used strategy by mammalian cells to cope with pervasive stochasticity in signalling and gene expression. [ABSTRACT FROM AUTHOR]

• Introduction - Angiogenesis in physiology and pathology - Angiogenesis in current medicine - VEGF ligand and receptor system: where does sVEGFR1 fit? - Ligands: the human VEGF family - Membrane-bound signalling receptors: VEGFRs - Non-signalling co-receptors and matrix proteins: HSPGs and NRPs - Soluble receptors: sVEGFR1, sVEGFR2, sNRP1 • Molecular biology of sVEGFR1 • Physiological and pathophysiological roles of sVEGFR1 • Molecular mechanism of sVEGFR1’s anti-angiogenic potential • sVEGFR1 as a clinical marker for disease • Plasma VEGF and sVEGFR1: non-uniform predictors of angiogenic status across all diseases • Systems biology perspective: unifying interpretation of plasma angiogenic markers - Baseline heterogeneity in clinical measurements of healthy VEGF and sVEGFR1 levels in plasma - Effect of sVEGFR1 on VEGF bioavailability: VEGF-sVEGFR1 complexes - Compartmental analysis: biotransport and biodistribution - Pathogenic phenomenon versus compensatory response • Concluding remarks Angiogenesis is the growth of new capillaries from pre-existent microvasculature. A wide range of pathological conditions, from atherosclerosis to cancer, can be attributed to either excessive or deficient angiogenesis. Central to the physiological regulation of angiogenesis is the vascular endothelial growth factor (VEGF) system – its ligands and receptors (VEGFRs) are thus prime molecular targets of pro-angiogenic and anti-angiogenic therapies. Of growing interest as a prognostic marker and therapeutic target in angiogenesis-dependent diseases is soluble VEGF receptor-1 (sVEGFR1, also known as sFlt-1) – a truncated version of the cell membrane-spanning VEGFR1. For instance, it is known that sVEGFR1 is involved in the endothelial dysfunction characterizing the pregnancy disorder of pre-eclampsia, and sVEGFR1’s therapeutic potential as an anti-angiogenic agent is being evaluated in pre-clinical models of cancer. This mini review begins with an examination of the protein domain structure and biomolecular interactions of sVEGFR1 in relation to the full-length VEGFR1. A synopsis of known and inferred physiological and pathological roles of sVEGFR1 is then given, with emphasis on the utility of computational systems biology models in deciphering the molecular mechanisms by which sVEGFR1’s purported biological functions occur. Finally, we present the need for a systems biology perspective in interpreting circulating VEGF and sVEGFR1 concentrations as surrogate markers of angiogenic status in angiogenesis-dependent diseases. [ABSTRACT FROM AUTHOR]

In this work theoretical investigation of the stability of various defect complexes including vacancies, self-interstitials and their clusters was performed by means of ab initio as well as molecular dynamic calculations. Meta-stable defect configurations similar to those observed earlier experimentally were found. Also the software for the molecular dynamic calculations and for the visualization of calculation results was developed. The results of the first-principles calculations were used for the parametrical fitting of Tersoff potential of silicon. Obtained potential was used to perform molecular dynamic calculations of the various configurations of defects in silicon. This approach allowed us to study the dynamics of the atomic system over time and temperature range. (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [ABSTRACT FROM AUTHOR]

This work deals with flow and transport phenomena in porous media, which occur on different space and time scales. Additionally, the porous medium itself is heterogeneous where the heterogeneities occur on all spatial scales. We consider a large domain with randomly distributed heterogeneities where complex two-phase–two-component processes are relevant only in a small (local) subdomain. This subdomain needs fine resolution as the complex processes are governed by small-scale effects. For a comprehensive fine-scale model taking into account two-phase–two-component processes as well as heterogeneities in the whole (global) model domain, data collection is expensive and computational time is high. Therefore, we developed a multi-scale concept where on the one hand, the global flow field influences the local two-phase–two-component processes on the fine scale. On the other hand, a coarse-scale saturation equation is solved where the effects of the fine-scale two-phase–two-component processes in the subdomain are captured by source/sink terms and the effects of fine-scale heterogeneities by a macrodispersion term. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Keywords: dry reforming; carbon deposits; industrially catalysis; high throughput experimentation; multi-scale modelling EN dry reforming carbon deposits industrially catalysis high throughput experimentation multi-scale modelling 2127 2127 1 04/27/20 20200420 NES 200420 B The Cover Feature b illustrates how dry reforming serves as backbone in paving the path towards sustainable olefins. On the left, the pilot reformer is depicted, which serves as a symbol for Linde's DRYREF© process, while the dry reforming catalyst represents BASF's SYNSPIRE© catalyst technology. Dry reforming, carbon deposits, industrially catalysis, high throughput experimentation, multi-scale modelling. [Extracted from the article]