Showing papers by "Chalmers University of Technology published in 2015"

Tissue-based map of the human proteome

Abstract: Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body.

Science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems

Abstract: We present the science and technology roadmap for graphene, related two-dimensional crystals, and hybrid systems, targeting an evolution in technology, that might lead to impacts and benefits reaching into most areas of society. This roadmap was developed within the framework of the European Graphene Flagship and outlines the main targets and research areas as best understood at the start of this ambitious project. We provide an overview of the key aspects of graphene and related materials (GRMs), ranging from fundamental research challenges to a variety of applications in a large number of sectors, highlighting the steps necessary to take GRMs from a state of raw potential to a point where they might revolutionize multiple industries. We also define an extensive list of acronyms in an effort to standardize the nomenclature in this emerging field.

The FEniCS Project Version 1.5

Abstract: The FEniCS Project is a collaborative project for the development of innovative concepts and tools for automated scientific computing, with a particular focus on the solution of differential equations by finite element methods. The FEniCS Projects software consists of a collection of interoperable software components, including DOLFIN, FFC, FIAT, Instant, UFC, UFL, and mshr. This note describes the new features and changes introduced in the release of FEniCS version 1.5.

A Promising New Class of High-Temperature Alloys: Eutectic High-Entropy Alloys

Abstract: High-entropy alloys (HEAs) can have either high strength or high ductility, and a simultaneous achievement of both still constitutes a tough challenge. The inferior castability and compositional segregation of HEAs are also obstacles for their technological applications. To tackle these problems, here we proposed a novel strategy to design HEAs using the eutectic alloy concept, i.e. to achieve a microstructure composed of alternating soft fcc and hard bcc phases. As a manifestation of this concept, an AlCoCrFeNi 2.1 (atomic portion) eutectic high-entropy alloy (EHEA) was designed. The as-cast EHEA possessed a fine lamellar fcc/B2 microstructure, and showed an unprecedented combination of high tensile ductility and high fracture strength at room temperature. The excellent mechanical properties could be kept up to 700°C. This new alloy design strategy can be readily adapted to large-scale industrial production of HEAs with simultaneous high fracture strength and high ductility.

A standardised static in vitro digestion method suitable for food – an international consensus

Abstract: Simulated gastro-intestinal digestion is widely employed in many fields of food and nutritional sciences, as conducting human trials are often costly, resource intensive, and ethically disputable. As a consequence, in vitro alternatives that determine endpoints such as the bioaccessibility of nutrients and non-nutrients or the digestibility of macronutrients (e.g. lipids, proteins and carbohydrates) are used for screening and building new hypotheses. Various digestion models have been proposed, often impeding the possibility to compare results across research teams. For example, a large variety of enzymes from different sources such as of porcine, rabbit or human origin have been used, differing in their activity and characterization. Differences in pH, mineral type, ionic strength and digestion time, which alter enzyme activity and other phenomena, may also considerably alter results. Other parameters such as the presence of phospholipids, individual enzymes such as gastric lipase and digestive emulsifiers vs. their mixtures (e.g. pancreatin and bile salts), and the ratio of food bolus to digestive fluids, have also been discussed at length. In the present consensus paper, within the COST Infogest network, we propose a general standardised and practical static digestion method based on physiologically relevant conditions that can be applied for various endpoints, which may be amended to accommodate further specific requirements. A frameset of parameters including the oral, gastric and small intestinal digestion are outlined and their relevance discussed in relation to available in vivo data and enzymes. This consensus paper will give a detailed protocol and a line-by-line, guidance, recommendations and justifications but also limitation of the proposed model. This harmonised static, in vitro digestion method for food should aid the production of more comparable data in the future.

Minimum Information about a Biosynthetic Gene cluster.

Abstract: A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.

van der Waals forces in density functional theory: a review of the vdW-DF method

Abstract: A density functional theory (DFT) that accounts for van der Waals (vdW) interactions in condensed matter, materials physics, chemistry, and biology is reviewed. The insights that led to the construction of the Rutgers–Chalmers van der Waals density functional (vdW-DF) are presented with the aim of giving a historical perspective, while also emphasizing more recent efforts which have sought to improve its accuracy. In addition to technical details, we discuss a range of recent applications that illustrate the necessity of including dispersion interactions in DFT. This review highlights the value of the vdW-DF method as a general-purpose method, not only for dispersion bound systems, but also in densely packed systems where these types of interactions are traditionally thought to be negligible.

Co-occurrence of resistance genes to antibiotics, biocides and metals reveals novel insights into their co-selection potential

Abstract: Antibacterial biocides and metals can co-select for antibiotic resistance when bacteria harbour resistance or tolerance genes towards both types of compounds. Despite numerous case studies, systematic and quantitative data on co-occurrence of such genes on plasmids and chromosomes is lacking, as is knowledge on environments and bacterial taxa that tend to carry resistance genes to such compounds. This effectively prevents identification of risk scenarios. Therefore, we aimed to identify general patterns for which biocide/metal resistance genes (BMRGs) and antibiotic resistance genes (ARGs) that tend to occur together. We also aimed to quantify co-occurrence of resistance genes in different environments and taxa, and investigate to what extent plasmids carrying both types of genes are conjugative and/or are carrying toxin-antitoxin systems. Co-occurrence patterns of resistance genes were derived from publicly available, fully sequenced bacterial genomes (n = 2522) and plasmids (n = 4582). The only BMRGs commonly co-occurring with ARGs on plasmids were mercury resistance genes and the qacE∆1 gene that provides low-level resistance to quaternary ammonium compounds. Novel connections between cadmium/zinc and macrolide/aminoglycoside resistance genes were also uncovered. Several clinically important bacterial taxa were particularly prone to carry both BMRGs and ARGs. Bacteria carrying BMRGs more often carried ARGs compared to bacteria without (p < 0.0001). BMRGs were found in 86 % of bacterial genomes, and co-occurred with ARGs in 17 % of the cases. In contrast, co-occurrences of BMRGs and ARGs were rare on plasmids from all external environments (<0.7 %) but more common on those of human and domestic animal origin (5 % and 7 %, respectively). Finally, plasmids with both BMRGs and ARGs were more likely to be conjugative (p < 0.0001) and carry toxin-antitoxin systems (p < 0.0001) than plasmids without resistance genes. This is the first large-scale identification of compounds, taxa and environments of particular concern for co-selection of resistance against antibiotics, biocides and metals. Genetic co-occurrences suggest that plasmids provide limited opportunities for biocides and metals to promote horizontal transfer of antibiotic resistance through co-selection, whereas ample possibilities exist for indirect selection via chromosomal BMRGs. Taken together, the derived patterns improve our understanding of co-selection potential between biocides, metals and antibiotics, and thereby provide guidance for risk-reducing actions.

Bioenergy and climate change mitigation: an assessment.

Abstract: Bioenergy deployment offers significant potential for climate change mitigation, but also carries considerable risks. In this review, we bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land-use and energy experts, land-use and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life-cycle assessment experts. We summarize technological options, outline the state-of-the-art knowledge on various climate effects, provide an update on estimates of technical resource potential and comprehensively identify sustainability effects. Cellulosic feedstocks, increased end-use efficiency, improved land carbon-stock management and residue use, and, when fully developed, BECCS appear as the most promising options, depending on development costs, implementation, learning, and risk management. Combined heat and power, efficient biomass cookstoves and small-scale power generation for rural areas can help to promote energy access and sustainable development, along with reduced emissions. We estimate the sustainable technical potential as up to 100EJ: high agreement; 100-300EJ: medium agreement; above 300EJ: low agreement. Stabilization scenarios indicate that bioenergy may supply from 10 to 245EJyr(-1) to global primary energy supply by 2050. Models indicate that, if technological and governance preconditions are met, large-scale deployment (>200EJ), together with BECCS, could help to keep global warming below 2 degrees degrees of preindustrial levels; but such high deployment of land-intensive bioenergy feedstocks could also lead to detrimental climate effects, negatively impact ecosystems, biodiversity and livelihoods. The integration of bioenergy systems into agriculture and forest landscapes can improve land and water use efficiency and help address concerns about environmental impacts. We conclude that the high variability in pathways, uncertainties in technological development and ambiguity in political decision render forecasts on deployment levels and climate effects very difficult. However, uncertainty about projections should not preclude pursuing beneficial bioenergy options.

MEG3 long noncoding RNA regulates the TGF-β pathway genes through formation of RNA–DNA triplex structures

Abstract: Long noncoding RNAs (lncRNAs) regulate gene expression by association with chromatin, but how they target chromatin remains poorly understood. We have used chromatin RNA immunoprecipitation-coupled high-throughput sequencing to identify 276 lncRNAs enriched in repressive chromatin from breast cancer cells. Using one of the chromatin-interacting lncRNAs, MEG3, we explore the mechanisms by which lncRNAs target chromatin. Here we show that MEG3 and EZH2 share common target genes, including the TGF-β pathway genes. Genome-wide mapping of MEG3 binding sites reveals that MEG3 modulates the activity of TGF-β genes by binding to distal regulatory elements. MEG3 binding sites have GA-rich sequences, which guide MEG3 to the chromatin through RNA–DNA triplex formation. We have found that RNA–DNA triplex structures are widespread and are present over the MEG3 binding sites associated with the TGF-β pathway genes. Our findings suggest that RNA–DNA triplex formation could be a general characteristic of target gene recognition by the chromatin-interacting lncRNAs.

Meso/Macroporous Nitrogen‐Doped Carbon Architectures with Iron Carbide Encapsulated in Graphitic Layers as an Efficient and Robust Catalyst for the Oxygen Reduction Reaction in Both Acidic and Alkaline Solutions

Abstract: Meso-/macroporous nitrogen-doped carbon architectures with iron carbide encapsulated in graphitic layers are fabricated by a facile approach. This efficient and robust material exhibits superior catalytic performance toward the oxygen reduction reaction in both acidic and alkaline solutions and is the most promising alternative to a Pt catalyst for use in electrochemical energy devices.

Nanoplasmonic waveguides: towards applications in integrated nanophotonic circuits

Abstract: The properties of propagating surface plasmon polaritons (SPPs) along one-dimensional metal structures have been investigated for more than 10 years and are now well understood. Because of the high confinement of electromagnetic energy, propagating SPPs have been considered to represent one of the best potential ways to construct next-generation circuits that use light to overcome the speed limit of electronics. Many basic plasmonic components have already been developed. In this review, researches on plasmonic waveguides are reviewed from the perspective of plasmonic circuits. Several circuit components are constructed to demonstrate the basic function of an optical digital circuit. In the end of this review, a prototype for an SPP-based nanochip is proposed, and the problems associated with building such plasmonic circuits are discussed. A plasmonic chip that can be practically applied is expected to become available in the near future.

Non-aqueous electrolytes for sodium-ion batteries

Abstract: The first review of the various electrolytes currently used and developed for sodium-ion batteries (SIBs), both in terms of materials and concepts, is presented. In contrast to the Li-ion battery (LIB), which is a mature technology for which a more or less unanimously accepted “standard electrolyte” exists: 1 M LiPF6 in EC/DMC, the electrolyte of choice for SIBs has not yet fully conformed to a standard. This is true for both materials: salts, solvents, or additives, and concept, using the main track of organic solvents or aiming for other concepts. SIB research currently prospers, benefitting from using know-how gained from 30 years of LIB R&D. Here the currently employed electrolytes are emphasized and their effects on practical SIB performance are outlined, scrutinizing the rationale for specific choices made, salts, solvents, additives, concentrations, etc. for each specific cell set-up and usage conditions.

Intrinsic homogeneous linewidth and broadening mechanisms of excitons in monolayer transition metal dichalcogenides

Abstract: The band-edge optical response of transition metal dichalcogenides, an emerging class of atomically thin semiconductors, is dominated by tightly bound excitons localized at the corners of the Brillouin zone (valley excitons). A fundamental yet unknown property of valley excitons in these materials is the intrinsic homogeneous linewidth, which reflects irreversible quantum dissipation arising from system (exciton) and bath (vacuum and other quasiparticles) interactions and determines the timescale during which excitons can be coherently manipulated. Here we use optical two-dimensional Fourier transform spectroscopy to measure the exciton homogeneous linewidth in monolayer tungsten diselenide (WSe2). The homogeneous linewidth is found to be nearly two orders of magnitude narrower than the inhomogeneous width at low temperatures. We evaluate quantitatively the role of exciton-exciton and exciton-phonon interactions and population relaxation as linewidth broadening mechanisms. The key insights reported here—strong many-body effects and intrinsically rapid radiative recombination—are expected to be ubiquitous in atomically thin semiconductors.

Realizing Strong Light-Matter Interactions between Single-Nanoparticle Plasmons and Molecular Excitons at Ambient Conditions.

Abstract: Realizing strong light-matter interactions between individual two-level systems and resonating cavities in atomic and solid state systems opens up possibilities to study optical nonlinearities on a single-photon level, which can be useful for future quantum information processing networks. However, these efforts have been hampered by unfavorable experimental conditions, such as cryogenic temperatures and ultrahigh vacuum, required to study such systems and phenomena. Although several attempts to realize strong light-matter interactions at room temperature using plasmon resonances have been made, successful realizations on the single-nanoparticle level are still lacking. Here, we demonstrate the strong coupling between plasmons confined within a single silver nanoprism and excitons in molecular J aggregates at ambient conditions. Our findings show that deep subwavelength mode volumes V together with quality factors Q that are reasonably high for plasmonic nanostructures result in a strong-coupling figure of merit-Q/root V as high as similar to 6 x 10(3) mu m(-3/2), a value comparable to state-of-the-art photonic crystal and microring resonator cavities. This suggests that plasmonic nanocavities, and specifically silver nanoprisms, can be used for room temperature quantum optics.

Lithium salts for advanced lithium batteries: Li–metal, Li–O2, and Li–S

Abstract: Presently lithium hexafluorophosphate (LiPF6) is the dominant Li-salt used in commercial rechargeable lithium-ion batteries (LIBs) based on a graphite anode and a 3-4 V cathode material. While LiPF6 is not the ideal Li-salt for every important electrolyte property, it has a uniquely suitable combination of properties (temperature range, passivation, conductivity, etc.) rendering it the overall best Li-salt for LIBs. However, this may not necessarily be true for other types of Li-based batteries. Indeed, next generation batteries, for example lithium-metal (Li-metal), lithium-oxygen (Li-O2), and lithium-sulfur (Li-S), require a re-evaluation of Li-salts due to the different electrochemical and chemical reactions and conditions within such cells. This review explores the critical role Li-salts play in ensuring in these batteries viability.

Technological innovation systems in contexts: conceptualizing contextual structures and interaction dynamics

Abstract: This paper addresses interactions between technological innovation systems (TIS) and wider "context structures". While TIS studies have always considered various kinds of contextual influences, we suggest that the TIS framework can be further strengthened by a more elaborated conceptualization of TIS context structures and TIS-context interactions. For that purpose, we identify and discuss four especially important types of context structures: technological, sectorial, geographical and political. For each of these, we provide examples of different ways in which context structures can interact with a focal TIS and how our understanding of TIS dynamics is enhanced by considering them explicitly. Lessons for analysts are given and a research agenda is outlined.

Accurate nuclear radii and binding energies from a chiral interaction

Abstract: With the goal of developing predictive ab initio capability for light and medium-mass nuclei, two-nucleon and three-nucleon forces from chiral effective field theory are optimized simultaneously to low-energy nucleon-nucleon scattering data, as well as binding energies and radii of few-nucleon systems and selected isotopes of carbon and oxygen. Coupled-cluster calculations based on this interaction, named NNLOsat, yield accurate binding energies and radii of nuclei up to Ca-40, and are consistent with the empirical saturation point of symmetric nuclear matter. In addition, the low-lying collective J(pi) = 3(-) states in O-16 and 40Ca are described accurately, while spectra for selected p- and sd-shell nuclei are in reasonable agreement with experiment.

Orchestra: Robust Mesh Networks Through Autonomously Scheduled TSCH

Abstract: Time slotted operation is a well-proven approach to achieve highly reliable low-power networking through scheduling and channel hopping. It is, however, difficult to apply time slotting to dynamic networks as envisioned in the Internet of Things. Commonly, these applications do not have pre-defined periodic traffic patterns and nodes can be added or removed dynamically.This paper addresses the challenge of bringing TSCH (Time Slotted Channel Hopping MAC) to such dynamic networks. We focus on low-power IPv6 and RPL networks, and introduce Orchestra. In Orchestra, nodes autonomously compute their own, local schedules. They maintain multiple schedules, each allocated to a particular traffic plane (application, routing, MAC), and updated automatically as the topology evolves. Orchestra (re)computes local schedules without signaling overhead, and does not require any central or distributed scheduler. Instead, it relies on the existing network stack information to maintain the schedules. This scheme allows Orchestra to build non-deterministic networks while exploiting the robustness of TSCH.We demonstrate the practicality of Orchestra and quantify its benefits through extensive evaluation in two testbeds, on two hardware platforms. Orchestra reduces, or even eliminates, network contention. In long running experiments of up to 72~h we show that Orchestra achieves end-to-end delivery ratios of over 99.99%. Compared to RPL in asynchronous low-power listening networks, Orchestra improves reliability by two orders of magnitude, while achieving a similar latency-energy balance.

A dusty, normal galaxy in the epoch of reionization

Abstract: Candidates for the modest galaxies that formed most of the stars in the early Universe, at redshifts z> 7, have been found in large numbers with extremely deep restframe-ultraviolet imaging. But it has proved difficult for existing spectrographs to characterize them using their ultraviolet light. The detailed properties of these galaxies could be measured from dust and cool gas emission at far-infrared wavelengths if the galaxies have become sufficiently enriched in dust and metals. So far, however, the most distant galaxy discovered via its ultraviolet emission and subsequently detected in dust emission is only at z = 3.2, and recent results have cast doubt on whether dust and molecules can be found in typical galaxies at z >= 7. Here we report thermal dust emission from an archetypal early Universe star-forming galaxy, A1689-zDI. We detect its stellar continuum in spectroscopy and determine its redshift to be z = 7.5 +/- 0.2 from a spectroscopic detection of the Lyman-a break. A1689-zD1 is representative of the star-forming population during the epoch of reionization, with a total star-formation rate of about 12 solar masses per year. The galaxy is highly evolved: it has a large stellar mass and is heavily enriched in dust, with a dust-to-gas ratio close to that of the Milky Way. Dusty, evolved galaxies are thus present among the fainter star-forming population at z> 7.

METAXA2: improved identification and taxonomic classification of small and large subunit rRNA in metagenomic data.

Abstract: The ribosomal rRNA genes are widely used as genetic markers for taxonomic identification of microbes. Particularly the small subunit (SSU; 16S/18S) rRNA gene is frequently used for species- or genus-level identification, but also the large subunit (LSU; 23S/28S) rRNA gene is employed in taxonomic assignment. The metaxa software tool is a popular utility for extracting partial rRNA sequences from large sequencing data sets and assigning them to an archaeal, bacterial, nuclear eukaryote, mitochondrial or chloroplast origin. This study describes a comprehensive update to metaxa – metaxa2 – that extends the capabilities of the tool, introducing support for the LSU rRNA gene, a greatly improved classifier allowing classification down to genus or species level, as well as enhanced support for short-read (100 bp) and paired-end sequences, among other changes. The performance of metaxa2 was compared to other commonly used taxonomic classifiers, showing that metaxa2 often outperforms previous methods in terms of making correct predictions while maintaining a low misclassification rate. metaxa2 is freely available from http://microbiology.se/software/metaxa2/

Molecules with a sense of logic: a progress report

Abstract: In this tutorial review, the most recent developments in the field of molecular logic and information processing are discussed. Special emphasis is given to the report of progress in the concatenation of molecular logic devices and switches, the design of memory systems working according to the principles of sequential logic, the mimicking of transistors, and the research on photochromic platforms with an unprecedented degree of functional integration. Furthermore, a series of achievements that add up to the conceptual diversity of molecular logic is introduced, such as the realization of highly complex and logically reversible Toffoli and Fredkin gates by the action of DNAzymes or the use of a multifluorophoric platform as a viable approach towards keypad lock functions.

Impacts of European livestock production: nitrogen, sulphur, phosphorus and greenhouse gas emissions, land-use, water eutrophication and biodiversity

Abstract: Livestock production systems currently occupy around 28% of the land surface of the European Union (equivalent to 65% of the agricultural land). In conjunction with other human activities, livestock production systems affect water, air and soil quality, global climate and biodiversity, altering the biogeochemical cycles of nitrogen, phosphorus and carbon. Here, we quantify the contribution of European livestock production to these major impacts. For each environmental effect, the contribution of livestock is expressed as shares of the emitted compounds and land used, as compared to the whole agricultural sector. The results show that the livestock sector contributes significantly to agricultural environmental impacts. This contribution is 78% for terrestrial biodiversity loss, 80% for soil acidification and air pollution (ammonia and nitrogen oxides emissions), 81% for global warming, and 73% for water pollution (both N and P). The agriculture sector itself is one of the major contributors to these environmental impacts, ranging between 12% for global warming and 59% for N water quality impact. Significant progress in mitigating these environmental impacts in Europe will only be possible through a combination of technological measures reducing livestock emissions, improved food choices and reduced food waste of European citizens.

A 71-Gb/s NRZ Modulated 850-nm VCSEL-Based Optical Link

Abstract: We report error free ( $\textrm {BER} ) operation of a directly non-return-to-zero modulated 850-nm vertical cavity surface-emitting laser (VCSEL) link operating to 71 Gb/s. This is the highest error free modulation rate for a directly modulated laser of any type. The optical link consists of a 130-nm BiCMOS driver IC with two-tap feed-forward equalization, a wide bandwidth 850-nm VCSEL, a surface illuminated GaAs PIN photodiode, and a 130-nm BiCMOS receiver IC.

An Artificial Neural Network Approach for Early Fault Detection of Gearbox Bearings

Abstract: Gearbox has proven to be a major contributor toward downtime in wind turbines. The majority of failures in the gearbox originate from the gearbox bearings. An early indication of possible wear and tear in the gearbox bearings may be used for effective predictive maintenance, thereby reducing the overall cost of maintenance. This paper introduces a self-evolving maintenance scheduler framework for maintenance management of wind turbines. Furthermore, an artificial neural network (ANN)-based condition monitoring approach using data from supervisory control and data acquisition system is proposed. The ANN-based condition monitoring approach is applied to gearbox bearings with real data from onshore wind turbines, rated 2 MW, and located in the south of Sweden. The results demonstrate that the proposed ANN-based condition monitoring approach is capable of indicating severe damage in the components being monitored in advance.