Pulmonary surfactant coating of multi-walled carbon nanotubes (MWCNTs) influences their oxidative and pro-inflammatory potential in vitro

Background Increasing concern has been expressed regarding the potential adverse health effects that may be associated with human exposure to inhaled multi-walled carbon nanotubes (MWCNTs). Thus it is imperative that an understanding as to the underlying mechanisms and the identification of the key factors involved in adverse effects are gained. In the alveoli, MWCNTs first interact with the pulmonary surfactant. At this interface, proteins and lipids of the pulmonary surfactant bind to MWCNTs, affecting their surface characteristics. Aim of the present study was to investigate if the pre-coating of MWCNTs with pulmonary surfactant has an influence on potential adverse effects, upon both (i) human monocyte derived macrophages (MDM) monocultures, and (ii) a sophisticated in vitro model of the human epithelial airway barrier. Both in vitro systems were exposed to MWCNTs either pre-coated with a porcine pulmonary surfactant (Curosurf) or not. The effect of MWCNTs surface charge was also investigated in terms of amino (−NH2) and carboxyl (−COOH) surface modifications. Results Pre-coating of MWCNTs with Curosurf affects their oxidative potential by increasing the reactive oxygen species levels and decreasing intracellular glutathione depletion in MDM as well as decreases the release of Tumour necrosis factor alpha (TNF-α). In addition, an induction of apoptosis was observed after exposure to Curosurf pre-coated MWCNTs. In triple cell-co cultures the release of Interleukin-8 (IL-8) was increased after exposure to Curosurf pre-coated MWCNTs. Effects of the MWCNTs functionalizations were minor in both MDM and triple cell co-cultures. Conclusions The present study clearly indicates that the pre-coating of MWCNTs with pulmonary surfactant more than the functionalization of the tubes is a key factor in determining their ability to cause oxidative stress, cytokine/chemokine release and apoptosis. Thus the coating of nano-objects with pulmonary surfactant should be considered for future lung in vitro risk assessment studies. Keywords: Multi-walled carbon nanotubes (MWCNTs); Pulmonary surfactant (Curosurf); Macrophages; Epithelial cells; Dendritic cells; Triple cell co-culture; Pro-inflammatory and oxidative reactions

ICOMF: Towards a Multi-cloud Ecosystem for Dynamic Resource Composition and Scaling

Modern cloud-based applications and infrastructures may include resources and services (components) from multiple cloud providers, are heterogeneous by nature and require adjustment, composition and integration. The specific application requirements can be met with difficulty by the current static predefined cloud integration architectures and models. In this paper, we propose the Intercloud Operations and Management Framework (ICOMF) as part of the more general Intercloud Architecture Framework (ICAF) that provides a basis for building and operating a dynamically manageable multi-provider cloud ecosystem. The proposed ICOMF enables dynamic resource composition and decomposition, with a main focus on translating business models and objectives to cloud services ensembles. Our model is user-centric and focuses on the specific application execution requirements, by leveraging incubating virtualization techniques. From a cloud provider perspective, the ecosystem provides more insight into how to best customize the offerings of virtualized resources.

Dynamic SLA management with forecasting using multi-objective optimization

Cost-efficient operation while satisfying performance and availability guarantees in Service Level Agreements (SLAs) is a challenge for Cloud Computing, as these are potentially conflicting objectives. We present a framework for SLA management based on multi-objective optimization. The framework features a forecasting model for determining the best virtual machine-to-host allocation given the need to minimize SLA violations, energy consumption and resource wasting. A comprehensive SLA management solution is proposed that uses event processing for monitoring and enables dynamic provisioning of virtual machines onto the physical infrastructure. We validated our implementation against serveral standard heuristics and were able to show that our approach is significantly better.

Multi-scale micro-structure generation strategy for up-scaling transport in clays

Clays and claystones are used as backfill and barrier materials in the design of waste repositories, because they act as hydraulic barriers and retain contaminants. Transport through such barriers occurs mainly by molecular diffusion. There is thus an interest to relate the diffusion properties of clays to their structural properties. In previous work, we have developed a concept for up-scaling pore-scale molecular diffusion coefficients using a grid-based model for the sample pore structure. Here we present an operational algorithm which can generate such model pore structures of polymineral materials. The obtained pore maps match the rock’s mineralogical components and its macroscopic properties such as porosity, grain and pore size distributions. Representative ensembles of grains in 2D or 3D are created by a lattice Monte Carlo (MC) method, which minimizes the interfacial energy of grains starting from an initial grain distribution. Pores are generated at grain boundaries and/or within grains. The method is general and allows to generate anisotropic structures with grains of approximately predetermined shapes, or with mixtures of different grain types. A specific focus of this study was on the simulation of clay-like materials. The generated clay pore maps were then used to derive upscaled effective diffusion coefficients for non-sorbing tracers using a homogenization technique. The large number of generated maps allowed to check the relations between micro-structural features of clays and their effective transport parameters, as is required to explain and extrapolate experimental diffusion results. As examples, we present a set of 2D and 3D simulations and investigated the effects of nanopores within particles (interlayer pores) and micropores between particles. Archie’s simple power law is followed in systems with only micropores. When nanopores are present, additional parameters are required; the data reveal that effective diffusion coefficients could be described by a sum of two power functions, related to the micro- and nanoporosity. We further used the model to investigate the relationships between particle orientation and effective transport properties of the sample.

Opportunistic Routing for Multi-flow Video Dissemination over Flying Ad-Hoc Networks

A reliable and robust routing service for Flying Ad-Hoc Networks (FANETs) must be able to adapt to topology changes. User experience on watching live video sequences must also be satisfactory even in scenarios with buffer overflow and high packet loss ratio. In this paper, we introduce a Cross-layer Link quality and Geographical-aware beaconless opportunistic routing protocol (XLinGO). It enhances the transmission of simultaneous multiple video flows over FANETs by creating and keeping reliable persistent multi-hop routes. XLinGO considers a set of cross-layer and human-related information for routing decisions, as performance metrics and Quality of Experience (QoE). Performance evaluation shows that XLinGO achieves multimedia dissemination with QoE support and robustness in a multi-hop, multi-flow, and mobile network environments.

Adapting agricultural land management to climate change: a regional multi-objective optimization approach

In several regions of the world, climate change is expected to have severe impacts on agricultural systems. Changes in land management are one way to adapt to future climatic conditions, including land-use changes and local adjustments of agricultural practices. In previous studies, options for adaptation have mostly been explored by testing alternative scenarios. Systematic explorations of land management possibilities using optimization approaches were so far mainly restricted to studies of land and resource management under constant climatic conditions. In this study, we bridge this gap and exploit the benefits of multi-objective regional optimization for identifying optimum land management adaptations to climate change. We design a multi-objective optimization routine that integrates a generic crop model and considers two climate scenarios for 2050 in a meso-scale catchment on the Swiss Central Plateau with already limited water resources. The results indicate that adaptation will be necessary in the study area to cope with a decrease in productivity by 0–10 %, an increase in soil loss by 25–35 %, and an increase in N-leaching by 30–45 %. Adaptation options identified here exhibit conflicts between productivity and environmental goals, but compromises are possible. Necessary management changes include (i) adjustments of crop shares, i.e. increasing the proportion of early harvested winter cereals at the expense of irrigated spring crops, (ii) widespread use of reduced tillage, (iii) allocation of irrigated areas to soils with low water-retention capacity at lower elevations, and (iv) conversion of some pre-alpine grasslands to croplands.

Migrant Background and Higher Education Participation in Europe. The Effect of the Educational Systems

The main aim of this article is to shed light on the extent to which differences in higher education participation between people with and without a migrant background of low/higher social origin can be explained by two macro-level characteristics of national educational institutions: stratification of the secondary school system and provision of alternative access to higher education. General assumptions are that people with a migrant background of low social origin benefit in low-stratified secondary school systems and in systems that provide alternative access to institutions of higher education more than their native peers in the same social stratum, owing to primary and secondary effects of migrant background. Database is a pooled dataset of the five waves of the European Social Survey. Results of logistic multi-level analyses indicate that a low-stratified secondary school system improves the probability of people with a migrant background/low social origin attaining a higher education degree. On the other hand, a stratified secondary school system reduces their chances regarding this educational stage. The provision of alternative access to an institution of higher education improves their likelihood of becoming higher education graduates.

Loyal to the Game? Strategic Policy Representation in Mixed Electoral Systems

In Germany's compensatory mixed electoral system, alternative electoral routes lead into parliament. We study the relationship between candidates' electoral situations across both tiers and policy representation, fully accounting for candidate, party and district preferences in a multi-actor constellation and the exact electoral incentives for candidates to represent either the party or the district. The results (2009 Bundestag election data) yield evidence of an interactive effect of closeness of the district race and list safety on candidates' positioning between their party and constituency.

Pangea: A Workbench for Statically Analyzing Multi-Language Software Corpora

Software corpora facilitate reproducibility of analyses, however, static analysis for an entire corpus still requires considerable effort, often duplicated unnecessarily by multiple users. Moreover, most corpora are designed for single languages increasing the effort for cross-language analysis. To address these aspects we propose Pangea, an infrastructure allowing fast development of static analyses on multi-language corpora. Pangea uses language-independent meta-models stored as object model snapshots that can be directly loaded into memory and queried without any parsing overhead. To reduce the effort of performing static analyses, Pangea provides out-of-the box support for: creating and refining analyses in a dedicated environment, deploying an analysis on an entire corpus, using a runner that supports parallel execution, and exporting results in various formats. In this tool demonstration we introduce Pangea and provide several usage scenarios that illustrate how it reduces the cost of analysis.

Anamorphic pixels for multi-channel superresolution

Superresolution from plenoptic cameras or camera arrays is usually treated similarly to superresolution from video streams. However, the transformation between the low-resolution views can be determined precisely from camera geometry and parallax. Furthermore, as each low-resolution image originates from a unique physical camera, its sampling properties can also be unique. We exploit this option with a custom design of either the optics or the sensor pixels. This design makes sure that the sampling matrix of the complete system is always well-formed, enabling robust and high-resolution image reconstruction. We show that simply changing the pixel aspect ratio from square to anamorphic is sufficient to achieve that goal, as long as each camera has a unique aspect ratio. We support this claim with theoretical analysis and image reconstruction of real images. We derive the optimal aspect ratios for sets of 2 or 4 cameras. Finally, we verify our solution with a camera system using an anamorphic lens.

Galileo Orbit and Clock Quality of the IGS Multi-GNSS Experiment

The Multi-GNSS Experiment (MGEX) of the International GNSS Service (IGS) aims at the data collection and analysis of all available satellite navigation systems. In particular the new global and regional satellite navigation systems are of interest, i.e., the European Galileo, the Chinese BeiDou, the Japanese QZSS as well as satellite based augmentation systems. This article analyzes the orbit and clock quality of the Galileo products of four MGEX analysis centers for a common time period of 20 weeks. Orbit comparisons of the individual analysis centers have a consistency at the 5–30 cm level. Day boundary discontinuities range from 4 to 28 cm whereas 2-day orbit fit RMS values vary between 1 and 7 cm. The accuracy evaluated by satellite laser ranging residuals is on the one decimeter level with a systematic bias of about −5 cm for all analysis centers. In addition, systematic errors on the decimeter level related to solar radiation pressure mismodeling are present in all orbit products. Due to the correlation of radial orbit errors with the clock parameters, these errors are also visible as a bump in the Allan deviation of the Galileo satellite clocks at the orbital frequency.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.