Showing papers by "Instituto Superior Técnico published in 2018"

Development of a primary human Small Intestine-on-a-Chip using biopsy-derived organoids

Abstract: Here we describe a method for fabricating a primary human Small Intestine-on-a-Chip (Intestine Chip) containing epithelial cells isolated from healthy regions of intestinal biopsies. The primary epithelial cells are expanded as 3D organoids, dissociated, and cultured on a porous membrane within a microfluidic device with human intestinal microvascular endothelium cultured in a parallel microchannel under flow and cyclic deformation. In the Intestine Chip, the epithelium forms villi-like projections lined by polarized epithelial cells that undergo multi-lineage differentiation similar to that of intestinal organoids, however, these cells expose their apical surfaces to an open lumen and interface with endothelium. Transcriptomic analysis also indicates that the Intestine Chip more closely mimics whole human duodenum in vivo when compared to the duodenal organoids used to create the chips. Because fluids flowing through the lumen of the Intestine Chip can be collected continuously, sequential analysis of fluid samples can be used to quantify nutrient digestion, mucus secretion and establishment of intestinal barrier function over a period of multiple days in vitro. The Intestine Chip therefore may be useful as a research tool for applications where normal intestinal function is crucial, including studies of metabolism, nutrition, infection, and drug pharmacokinetics, as well as personalized medicine.

GrapeTree : visualization of core genomic relationships among 100,000 bacterial pathogens

Abstract: Current methods struggle to reconstruct and visualize the genomic relationships of large numbers of bacterial genomes. GrapeTree facilitates the analyses of large numbers of allelic profiles by a static "GrapeTree Layout" algorithm that supports interactive visualizations of large trees within a web browser window. GrapeTree also implements a novel minimum spanning tree algorithm (MSTree V2) to reconstruct genetic relationships despite high levels of missing data. GrapeTree is a stand-alone package for investigating phylogenetic trees plus associated metadata and is also integrated into EnteroBase to facilitate cutting edge navigation of genomic relationships among bacterial pathogens.

Microfluidic Organ-on-a-Chip Models of Human Intestine.

Abstract: Microfluidic organ-on-a-chip models of human intestine have been developed and used to study intestinal physiology and pathophysiology. In this article, we review this field and describe how microfluidic Intestine Chips offer new capabilities not possible with conventional culture systems or organoid cultures, including the ability to analyze contributions of individual cellular, chemical, and physical control parameters one-at-a-time; to coculture human intestinal cells with commensal microbiome for extended times; and to create human-relevant disease models. We also discuss potential future applications of human Intestine Chips, including how they might be used for drug development and personalized medicine.

Fusing Hyperspectral and Multispectral Images via Coupled Sparse Tensor Factorization

Abstract: Fusing a low spatial resolution hyperspectral image (LR-HSI) with a high spatial resolution multispectral image (HR-MSI) to obtain a high spatial resolution hyperspectral image (HR-HSI) has attracted increasing interest in recent years. In this paper, we propose a coupled sparse tensor factorization (CSTF)-based approach for fusing such images. In the proposed CSTF method, we consider an HR-HSI as a 3D tensor and redefine the fusion problem as the estimation of a core tensor and dictionaries of the three modes. The high spatial-spectral correlations in the HR-HSI are modeled by incorporating a regularizer, which promotes sparse core tensors. The estimation of the dictionaries and the core tensor are formulated as a coupled tensor factorization of the LR-HSI and of the HR-MSI. Experiments on two remotely sensed HSIs demonstrate the superiority of the proposed CSTF algorithm over the current state-of-the-art HSI-MSI fusion approaches.

Candida Biofilms: Threats, Challenges, and Promising Strategies.

Abstract: Candida species are fungal pathogens known for their ability to cause superficial and systemic infections in the human host. These pathogens are able to persist inside the host due to the development of pathogenicity and multidrug resistance traits, often leading to the failure of therapeutic strategies. One specific feature of Candida species pathogenicity is their ability to form biofilms, which protects them from external factors such as host immune system defenses and antifungal drugs. This review focuses on the current threats and challenges when dealing with biofilms formed by Candida albicans, Candida glabrata, Candida tropicalis, and Candida parapsilosis, highlighting the differences between the four species. Biofilm characteristics depend on the ability of each species to produce extracellular polymeric substances (EPS) and display dimorphic growth, but also on the biofilm substratum, carbon source availability and other factors. Additionally, the transcriptional control over processes like adhesion, biofilm formation, filamentation, and EPS production displays great complexity and diversity within pathogenic yeasts of the Candida genus. These differences not only have implications in the persistence of colonization and infections but also on antifungal resistance typically found in Candida biofilm cells, potentiated by EPS, that functions as a barrier to drug diffusion, and by the overexpression of drug resistance transporters. The ability to interact with different species in in vivo Candida biofilms is also a key factor to consider when dealing with this problem. Despite many challenges, the most promising strategies that are currently available or under development to limit biofilm formation or to eradicate mature biofilms are discussed.

Shadows and strong gravitational lensing: a brief review

Abstract: For ultra compact objects, light rings and fundamental photon orbits (FPOs) play a pivotal role in the theoretical analysis of strong gravitational lensing effects, and of BH shadows in particular. In this short review, specific models are considered to illustrate how FPOs can be useful in order to understand some non-trivial gravitational lensing effects. This paper aims at briefly overviewing the theoretical foundations of these effects, touching also some of the related phenomenology, both in general relativity and alternative theories of gravity, hopefully providing some intuition and new insights for the underlying physics, which might be critical when testing the Kerr black hole hypothesis.

Multifunctional Ln-MOF Luminescent Probe for Efficient Sensing of Fe3+, Ce3+, and Acetone.

Abstract: A new series of five three-dimensional Ln(III) metal-organic frameworks (MOFs) formulated as [Ln4(μ6-L)2(μ-HCOO)(μ3-OH)3(μ3-O)(DMF)2(H2O)4] n {Ln3+ = Tb3+ (1), Eu3+ (2), Gd3+ (3), Dy3+ (4), and Er3+ (5)} was successfully obtained via a solvothermal reaction between the corresponding lanthanide(III) nitrates and 2-(6-carboxypyridin-3-yl)terephthalic acid (H3L). All of the obtained compounds were fully characterized, and their structures were established by single-crystal X-ray diffraction. All products are isostructural and possess porous 3D networks of the fluorite topological type, which are driven by the cubane-like [Ln4(μ3-OH)3(μ3-O)(μ-HCOO)]6+ blocks and μ6-L3- spacers. Luminescent and sensing properties of 1-5 were investigated in detail, revealing a unique capability of Tb-MOF (1) for sensing acetone and metal(III) cations (Fe3+ or Ce3+) with high efficiency and selectivity. Apart from a facile recyclability after sensing experiments, the obtained Tb-MOF material features a remarkable stability in a diversity of environments such as common solvents, aqueous solutions of metal ions, and solutions with a broad pH range from 4 to 11. In addition, compound 1 represents a very rare example of the versatile Ln-MOF probe capable of sensing Ce3+ or Fe3+ cations or acetone molecules.

The Various Roles of Fatty Acids

Abstract: Lipids comprise a large group of chemically heterogeneous compounds. The majority have fatty acids (FA) as part of their structure, making these compounds suitable tools to examine processes raging from cellular to macroscopic levels of organization. Among the multiple roles of FA, they have structural functions as constituents of phospholipids which are the “building blocks” of cell membranes; as part of neutral lipids FA serve as storage materials in cells; and FA derivatives are involved in cell signalling. Studies on FA and their metabolism are important in numerous research fields, including biology, bacteriology, ecology, human nutrition and health. Specific FA and their ratios in cellular membranes may be used as biomarkers to enable the identification of organisms, to study adaptation of bacterial cells to toxic compounds and environmental conditions and to disclose food web connections. In this review, we discuss the various roles of FA in prokaryotes and eukaryotes and highlight the application of FA analysis to elucidate ecological mechanisms. We briefly describe FA synthesis; analyse the role of FA as modulators of cell membrane properties and FA ability to store and supply energy to cells; and inspect the role of polyunsaturated FA (PUFA) and the suitability of using FA as biomarkers of organisms.

Quasinormal modes and Strong Cosmic Censorship

Abstract: The fate of Cauchy horizons, such as those found inside charged black holes, is intrinsically connected to the decay of small perturbations exterior to the event horizon. As such, the validity of the strong cosmic censorship (SCC) conjecture is tied to how effectively the exterior damps fluctuations. Here, we study massless scalar fields in the exterior of Reissner-Nordstrom-de Sitter black holes. Their decay rates are governed by quasinormal modes of the black hole. We identify three families of modes in these spacetimes: one directly linked to the photon sphere, well described by standard WKB-type tools; another family whose existence and time scale is closely related to the de Sitter horizon; finally, a third family which dominates for near-extremally charged black holes and which is also present in asymptotically flat spacetimes. The last two families of modes seem to have gone unnoticed in the literature. We give a detailed description of linear scalar perturbations of such black holes, and conjecture that SCC is violated in the near extremal regime.

Fast Hyperspectral Image Denoising and Inpainting Based on Low-Rank and Sparse Representations

Abstract: This paper introduces two very fast and competitive hyperspectral image (HSI) restoration algorithms: fast hyperspectral denoising (FastHyDe), a denoising algorithm able to cope with Gaussian and Poissonian noise, and fast hyperspectral inpainting (FastHyIn), an inpainting algorithm to restore HSIs where some observations from known pixels in some known bands are missing. FastHyDe and FastHyIn fully exploit extremely compact and sparse HSI representations linked with their low-rank and self-similarity characteristics. In a series of experiments with simulated and real data, the newly introduced FastHyDe and FastHyIn compete with the state-of-the-art methods, with much lower computational complexity.

From Phase Change Materials to Green Solvents: Hydrophobic Low Viscous Fatty Acid-based Deep Eutectic Solvents

Abstract: Inspired by the use of fatty acids in development of low temperature latent heat storage materials, novel low viscous and hydrophobic deep eutectic solvents (DESs) based exclusively on fatty acids are herein proposed as sustainable solvents. Three DESs were prepared by exclusively combining fatty acids, namely octanoic acid (C8), nonanoic acid (C9), decanoic acid (C10), and dodecanoic acid (C12), which can simultaneously act as hydrogen bond donors and acceptors. The obtained fatty acid-based DESs were analyzed in order to check their structures, purities, and proportions. Water stability was also carefully evaluated through 1H NMR. Fatty-acid DESs melting point diagrams were determined by visual observation. Good agreement was obtained between the experimental eutectic point and that predicted by considering an ideal system of two individually melting compounds. Important solvent thermophysical properties, such as density and viscosity of the dried and water-saturated DESs, were measured. Finally, the re...

Marian: Fast Neural Machine Translation in C++

Abstract: We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs. Marian is written entirely in C++. We describe the design of the encoder-decoder framework and demonstrate that a research-friendly toolkit can achieve high training and translation speed.

Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network

Abstract: The Sentinel-2 satellite mission delivers multi-spectral imagery with 13 spectral bands, acquired at three different spatial resolutions. The aim of this research is to super-resolve the lower-resolution (20 m and 60 m Ground Sampling Distance – GSD) bands to 10 m GSD, so as to obtain a complete data cube at the maximal sensor resolution. We employ a state-of-the-art convolutional neural network (CNN) to perform end-to-end upsampling, which is trained with data at lower resolution, i.e., from 40 → 20 m, respectively 360 → 60 m GSD. In this way, one has access to a virtually infinite amount of training data, by downsampling real Sentinel-2 images. We use data sampled globally over a wide range of geographical locations, to obtain a network that generalises across different climate zones and land-cover types, and can super-resolve arbitrary Sentinel-2 images without the need of retraining. In quantitative evaluations (at lower scale, where ground truth is available), our network, which we call DSen2, outperforms the best competing approach by almost 50% in RMSE, while better preserving the spectral characteristics. It also delivers visually convincing results at the full 10 m GSD.

Acceleration of electrons in the plasma wakefield of a proton bunch

Abstract: High-energy particle accelerators have been crucial in providing a deeper understanding of fundamental particles and the forces that govern their interactions. To increase the energy or to reduce the size of the accelerator, new acceleration schemes need to be developed. Plasma wakefield acceleration1–5, in which the electrons in a plasma are excited, leading to strong electric fields, is one such promising novel acceleration technique. Pioneering experiments have shown that an intense laser pulse6–9 or electron bunch10,11 traversing a plasma drives electric fields of tens of gigavolts per metre and above. These values are well beyond those achieved in conventional radio-frequency accelerators, which are limited to about 0.1 gigavolt per metre. A limitation of laser pulses and electron bunches is their low stored energy, which motivates the use of multiple stages to reach very high energies5,12. The use of proton bunches is compelling, as they have the potential to drive wakefields and accelerate electrons to high energy in a single accelerating stage13. The long proton bunches currently available can be used, as they undergo a process called self-modulation14–16, a particle–plasma interaction which longitudinally splits the bunch into a series of high-density microbunches, which then act resonantly to create large wakefields. The Advanced Wakefield (AWAKE) experiment at CERN17–19 uses intense bunches of protons, each of energy 400 gigaelectronvolts (GeV), with a total bunch energy of 19 kilojoules, to drive a wakefield in a 10-metre-long plasma. Bunches of electrons are injected into the wakefield formed by the proton microbunches. Here we present measurements of electrons accelerated up to 2 GeV at the AWAKE experiment. This constitutes the first demonstration of proton-driven plasma wakefield acceleration. The potential for this scheme to produce very high-energy electron bunches in a single accelerating stage20 means that the results shown here are a significant step towards the development of future high-energy particle accelerators21,22.

Evidence for a maximum mass cut-off in the neutron star mass distribution and constraints on the equation of state

Abstract: We infer the mass distribution of neutron stars in binary systems using a flexible Gaussian mixture model and use Bayesian model selection to explore evidence for multi-modality and a sharp cut-off in the mass distribution. We find overwhelming evidence for a bimodal distribution, in agreement with previous literature, and report for the first time positive evidence for a sharp cut-off at a maximum neutron star mass. We measure the maximum mass to be $2.0M_\odot 2M_\odot$ neutron stars, our inference of $m_\mathrm{max}$ is able to distinguish between models at odds ratios of up to $12:1$, whilst under a flexible piecewise polytropic equation of state model our maximum mass measurement improves constraints on the pressure at $3-7\times$ the nuclear saturation density by $\sim 30-50\%$ compared to simply requiring $m_\mathrm{max}> 2M_\odot$. We obtain a lower bound on the maximum sound speed attained inside the neutron star of $c_s^\mathrm{max} > 0.63c$ (99.8\%), ruling out $c_s^\mathrm{max} < c/\sqrt{3}$ at high significance. Our constraints on the maximum neutron star mass strengthen the case for neutron star-neutron star mergers as the primary source of short gamma-ray bursts.

Anatomy of the inert two-Higgs-doublet model in the light of the LHC and non-LHC dark matter searches

Abstract: The inert two-Higgs-doublet model (i2HDM) is a theoretically well-motivated example of a minimal consistent dark matter (DM) model which provides monojet, mono-Z, mono-Higgs, and vector-boson-fusion+ETmiss signatures at the LHC, complemented by signals in direct and indirect DM search experiments. In this paper we have performed a detailed analysis of the constraints in the full five-dimensional parameter space of the i2HDM, coming from perturbativity, unitarity, electroweak precision data, Higgs data from the LHC, DM relic density, direct/indirect DM detection, and LHC monojet analysis, as well as implications of experimental LHC studies on disappearing charged tracks relevant to a high DM mass region. We demonstrate the complementarity of the above constraints and present projections for future LHC data and direct DM detection experiments to probe further i2HDM parameter space. The model is implemented into the CalcHEP and micrOMEGAs packages, which are publicly available at the HEPMDB database, and it is ready for a further exploration in the context of the LHC, relic density, and DM direct detection.

Marine Biofilms: A Successful Microbial Strategy With Economic Implications

Abstract: Bacteria and other microorganisms have evolved an ingenious form of life, where they cooperate and improve their chances of survival when subjected to environmental stress, called biofilms. In these communities of adhered cells, bacteria are protected by a matrix of extracellular polymeric substances that provide protection against e.g. temperature and pH fluctuations, UV exposure, changes in salinity, depletion of nutrients, antimicrobial compounds and predation. Their success in marine environments and the number of bacterial cells in the sea, allow them to colonize nearly all man-made surfaces in contact with seawater. The costs to maritime transport, aquaculture, oil and gas industries, desalination plants and other industries are significant which has led to the development of various strategies to prevent biofilm formation and cleaning of infected surfaces. In this review, the benefits for bacterial cells to live in biofilms and the consequences to human activities are discussed.

Modern Electric, Hybrid Electric, and Fuel Cell Vehicles, Third Edition [Book News]

Abstract: This book explains the dynamic modeling, simulation, and optimization needed for hybrid electric vehicles. It presents a comprehensive overview of technologies and how they are designed, integrated, and controlled. The book begins with environmental issues and transportation history, before continuing to fundamentals of vehicle propulsion and braking, theoretical bases of internal combustion engines, and explanations about vehicle transmission. Next, the authors explain in a wellstructured, clear, and concise manner, information about electric vehicles (EVs), hybrid EVs (HEVs), fuel cell vehicles (FCVs), and propulsion electric motors together with their controllers. The authors analyze design principles of series, parallel, series–parallel, and soft hybrid electric drive trains, and they explain design and control principles for plug-in hybrid electric vehicles, with examples showing simulation results using the overall drive train system, not just the individual components. A good grasp of such principles is essential for understanding the modeling before conducting research on advanced control methods for switching power converters. Storage (batteries, supercapacitors, fuel cells) and regenerative braking, together with off-road vehicles and their requirements, are expansively analyzed and discussed in this third edition. The book’s concluding chapters cover optimization of full-size engine HEVs and power-trains and include a guide for a multiobjective optimization toolbox. The authors are known around the world as specialists in power electronics; motor drives; hybrid vehicles and their control systems; architecture, modeling, and design of electric and hybrid electric drive trains; energy management and power-train control; mechatronic systems; and sustainable energy engineering.

Constraining the mass of dark photons and axion-like particles through black-hole superradiance

Abstract: Ultralight bosons and axion-like particles appear naturally in different scenarios and could solve some long-standing puzzles. Their detection is challenging, and all direct methods hinge on unknown couplings to the Standard Model of particle physics. However, the universal coupling to gravity provides model-independent signatures for these fields. We explore here the superradiant instability of spinning black holes triggered in the presence of such fields. The instability taps angular momentum from and limits the maximum spin of astrophysical black holes. We compute, for the first time, the spectrum of the most unstable modes of a massive vector (Proca) field for generic black-hole spin and Proca mass. The observed stability of the inner disk of stellar-mass black holes can be used to derive direct constraints on the mass of dark photons in the mass range 10−13 eV mV 3 × 10−12 eV. By including also higher azimuthal modes, similar constraints apply to axion-like particles in the mass range 6 × 10−13 eV mALP 10−11 eV. Likewise, mass and spin distributions of supermassive BHs – as measured through continuum fitting, Kα iron line, or with the future space-based gravitational-wave detector LISA – imply indirect bounds in the mass range approximately 10−19 eV mV , mALP 10−13 eV, for both axion-like particles and dark photons. Overall, superradiance allows to explore a region of approximately 8 orders of magnitude in the mass of ultralight bosons.

Social norm complexity and past reputations in the evolution of cooperation.

Abstract: Indirect reciprocity is the most elaborate and cognitively demanding of all known cooperation mechanisms, and is the most specifically human because it involves reputation and status. By helping someone, individuals may increase their reputation, which may change the predisposition of others to help them in future. The revision of an individual's reputation depends on the social norms that establish what characterizes a good or bad action and thus provide a basis for morality. Norms based on indirect reciprocity are often sufficiently complex that an individual's ability to follow subjective rules becomes important, even in models that disregard the past reputations of individuals, and reduce reputations to either 'good' or 'bad' and actions to binary decisions. Here we include past reputations in such a model and identify the key pattern in the associated norms that promotes cooperation. Of the norms that comply with this pattern, the one that leads to maximal cooperation (greater than 90 per cent) with minimum complexity does not discriminate on the basis of past reputation; the relative performance of this norm is particularly evident when we consider a 'complexity cost' in the decision process. This combination of high cooperation and low complexity suggests that simple moral principles can elicit cooperation even in complex environments.

Life cycle assessment of concrete made with high volume of recycled concrete aggregates and fly ash

Abstract: Since concrete is the most widely used construction material in the world, it is important to improve its environmental performance. A possibility is to use supplementary cementitious materials and recycled aggregates. Therefore, the objective of this work is to compare the environmental impacts (EI) of concrete mixes, which contain different incorporation ratios of fly ash (FA) and recycled concrete aggregates (RCA), with and without Superplasticizer (SP). The Life Cycle Assessment methodology was used for environmental assessment, according to ISO 14040 (2006) and EN 15804 (2012). Contrary to most of the previous studies, this one separately obtained the impact for each life cycle stage in detail (e.g. the impact of raw materials production, transportation, and mixing procedure), and explains the reason behind selecting each dataset. Thus, the results of this study can be used for other case studies. The results show that the EI slightly increased when SP was used. Moreover, the incorporation ratio of fine RCA did not change the results for most of the EI categories. Nevertheless, the EI of most of the categories decreased when coarse NA was fully replaced with coarse RCA. Despite the long transportation distance between the coal power plant and the concrete plant considered in the case study, the EI significantly decreased in most categories with increasing amounts of FA.