Instituto Politécnico de Lisboa

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

This paper proposes an unsupervised algorithm for learning a finite mixture model from multivariate data. The adjective "unsupervised" is justified by two properties of the algorithm: 1) it is capable of selecting the number of components and 2) unlike the standard expectation-maximization (EM) algorithm, it does not require careful initialization. The proposed method also avoids another drawback of EM for mixture fitting: the possibility of convergence toward a singular estimate at the boundary of the parameter space. The novelty of our approach is that we do not use a model selection criterion to choose one among a set of preestimated candidate models; instead, we seamlessly integrate estimation and model selection in a single algorithm. Our technique can be applied to any type of parametric mixture model for which it is possible to write an EM algorithm; in this paper, we illustrate it with experiments involving Gaussian mixtures. These experiments testify for the good performance of our approach.

A large number of clustering approaches have been proposed for the analysis of gene expression data obtained from microarray experiments. However, the results from the application of standard clustering methods to genes are limited. This limitation is imposed by the existence of a number of experimental conditions where the activity of genes is uncorrelated. A similar limitation exists when clustering of conditions is performed. For this reason, a number of algorithms that perform simultaneous clustering on the row and column dimensions of the data matrix has been proposed. The goal is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this paper, we refer to this class of algorithms as biclustering. Biclustering is also referred in the literature as coclustering and direct clustering, among others names, and has also been used in fields such as information retrieval and data mining. In this comprehensive survey, we analyze a large number of existing approaches to biclustering, and classify them in accordance with the type of biclusters they can find, the patterns of biclusters that are discovered, the methods used to perform the search, the approaches used to evaluate the solution, and the target applications.

We consider the scenario emerging from the dynamics of a generalized Born-Infeld theory. The equation of state describing this system is given in terms of the energy density $\ensuremath{\rho}$ and pressure p by the relationship $p=\ensuremath{-}A/{\ensuremath{\rho}}^{\ensuremath{\alpha}},$ where A is a positive constant and $0<\ensuremath{\alpha}<~1.$ We discuss the conditions under which homogeneity arises and show that this equation of state describes the evolution of a universe evolving from a phase dominated by nonrelativistic matter to a phase dominated by a cosmological constant via an intermediate period where the effective equation of state is given by $p=\ensuremath{\alpha}\ensuremath{\rho}.$

In this chapter we provide a comprehensive and unified treatment of the physical concepts and quantities relevant to phase transitions and critical phenomena. Some of these concepts and quantities have already been discussed in the particular contexts of magnetism (Chapter 7), or liquid crystals (Chapter 9, We conclude the chapter with a brief reference to the application of renormalisation group ideas to critical phenomena. The resulting reconciliation of the predictions of classical theories with experiments and exact or quasi-exact solutions of model systems is a major triumph of twentieth-century physics.

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.

Abstract Terrestrial ecosystems sequester 2.1 Pg of atmospheric carbon annually. A large amount of the terrestrial sink is realized by forests. However, considerable uncertainties remain regarding the fate of this carbon over both short and long timescales. Relevant data to address these uncertainties are being collected at many sites around the world, but syntheses of these data are still sparse. To facilitate future synthesis activities, we have assembled a comprehensive global database for forest ecosystems, which includes carbon budget variables (fluxes and stocks), ecosystem traits (e.g. leaf area index, age), as well as ancillary site information such as management regime, climate, and soil characteristics. This publicly available database can be used to quantify global, regional or biome‐specific carbon budgets; to re‐examine established relationships; to test emerging hypotheses about ecosystem functioning [e.g. a constant net ecosystem production (NEP) to gross primary production (GPP) ratio]; and as benchmarks for model evaluations. In this paper, we present the first analysis of this database. We discuss the climatic influences on GPP, net primary production (NPP) and NEP and present the CO 2 balances for boreal, temperate, and tropical forest biomes based on micrometeorological, ecophysiological, and biometric flux and inventory estimates. Globally, GPP of forests benefited from higher temperatures and precipitation whereas NPP saturated above either a threshold of 1500 mm precipitation or a mean annual temperature of 10 °C. The global pattern in NEP was insensitive to climate and is hypothesized to be mainly determined by nonclimatic conditions such as successional stage, management, site history, and site disturbance. In all biomes, closing the CO 2 balance required the introduction of substantial biome‐specific closure terms. Nonclosure was taken as an indication that respiratory processes, advection, and non‐CO 2 carbon fluxes are not presently being adequately accounted for.

A set of force field parameters is proposed for the molecular simulation of ionic liquids containing the anions trifluoromethylsufate and bis(trifluoromethylsulfonyl)imide, also known as triflate and bistriflylimide, respectively. The new set can be combined with existing force fields for cations in order to simulate common room-temperature ionic liquids, such as those of the dialkylimidazolium family, and can be integrated with the OPLS-AA or similar force fields. Ab initio quantum chemical calculations were employed to obtain molecular geometry, torsional energy profiles, and partial charge distribution in the triflate and bistriflylimide anions. One of the torsions in bistriflylimide, corresponding to the dihedral angle S−N−S−C, has a complex energy profile which is precisely reproduced by the present parameter set. A new set of partial electrostatic charges is also proposed for the pyrrolidinium and tri- and tetra-alkylammonium cations. Again, these parameters can be combined with the OPLS-AA specification for amines in order to simulate alkylammonium salts. The force-field models were validated against crystal structures and liquid-state densities.

The regulatory mechanisms by which hydrogen peroxide (H2O2) modulates the activity of transcription factors in bacteria (OxyR and PerR), lower eukaryotes (Yap1, Maf1, Hsf1 and Msn2/4) and mammalian cells (AP-1, NRF2, CREB, HSF1, HIF-1, TP53, NF-κB, NOTCH, SP1 and SCREB-1) are reviewed. The complexity of regulatory networks increases throughout the phylogenetic tree, reaching a high level of complexity in mammalians. Multiple H2O2 sensors and pathways are triggered converging in the regulation of transcription factors at several levels: (1) synthesis of the transcription factor by upregulating transcription or increasing both mRNA stability and translation; (ii) stability of the transcription factor by decreasing its association with the ubiquitin E3 ligase complex or by inhibiting this complex; (iii) cytoplasm-nuclear traffic by exposing/masking nuclear localization signals, or by releasing the transcription factor from partners or from membrane anchors; and (iv) DNA binding and nuclear transactivation by modulating transcription factor affinity towards DNA, co-activators or repressors, and by targeting specific regions of chromatin to activate individual genes. We also discuss how H2O2 biological specificity results from diverse thiol protein sensors, with different reactivity of their sulfhydryl groups towards H2O2, being activated by different concentrations and times of exposure to H2O2. The specific regulation of local H2O2 concentrations is also crucial and results from H2O2 localized production and removal controlled by signals. Finally, we formulate equations to extract from typical experiments quantitative data concerning H2O2 reactivity with sensor molecules. Rate constants of 140 M(-1) s(-1) and ≥1.3 × 10(3) M(-1) s(-1) were estimated, respectively, for the reaction of H2O2 with KEAP1 and with an unknown target that mediates NRF2 protein synthesis. In conclusion, the multitude of H2O2 targets and mechanisms provides an opportunity for highly specific effects on gene regulation that depend on the cell type and on signals received from the cellular microenvironment.

Abstract Strategies toward ambitious climate targets usually rely on the concept of ‘decoupling’; that is, they aim at promoting economic growth while reducing the use of natural resources and GHG emissions. GDP growth coinciding with absolute reductions in emissions or resource use is denoted as ‘absolute decoupling’, as opposed to ‘relative decoupling’, where resource use or emissions increase less so than does GDP. Based on the bibliometric mapping in part I (Wiedenhofer et al , 2020 Environ. Res. Lett. 15 063002 ), we synthesize the evidence emerging from the selected 835 peer-reviewed articles. We evaluate empirical studies of decoupling related to final/useful energy, exergy, use of material resources, as well as CO 2 and total GHG emissions. We find that relative decoupling is frequent for material use as well as GHG and CO 2 emissions but not for useful exergy, a quality-based measure of energy use. Primary energy can be decoupled from GDP largely to the extent to which the conversion of primary energy to useful exergy is improved. Examples of absolute long-term decoupling are rare, but recently some industrialized countries have decoupled GDP from both production- and, weaklier, consumption-based CO 2 emissions. We analyze policies or strategies in the decoupling literature by classifying them into three groups: (1) Green growth, if sufficient reductions of resource use or emissions were deemed possible without altering the growth trajectory. (2) Degrowth, if reductions of resource use or emissions were given priority over GDP growth. (3) Others, e.g. if the role of energy for GDP growth was analyzed without reference to climate change mitigation. We conclude that large rapid absolute reductions of resource use and GHG emissions cannot be achieved through observed decoupling rates, hence decoupling needs to be complemented by sufficiency-oriented strategies and strict enforcement of absolute reduction targets. More research is needed on interdependencies between wellbeing, resources and emissions.

During the past decade, ionic-liquid-based Aqueous Biphasic Systems (ABS) have been the focus of a significant amount of research. Based on a compilation and analysis of the data hitherto reported, this critical review provides a judicious assessment of the available literature on the subject. We evaluate the quality of the data and establish the main drawbacks found in the literature. We discuss the main issues which govern the phase behaviour of ionic-liquid-based ABS, and we highlight future challenges to the field. In particular, the effect of the ionic liquid structure and the various types of salting-out agents (inorganic or organic salts, amino acids and carbohydrates) on the phase equilibria of ABS is discussed, as well as the influence of secondary parameters such as temperature and pH. More recent approaches using ionic liquids as additives or as replacements for common salts in polymer-based ABS are also presented and discussed to emphasize the expanding number of aqueous two-phase systems that can actually be obtained. Finally, we address two of the main applications of ionic liquid-based ABS: extraction of biomolecules and other added-value compounds, and their use as alternative approaches for removing and recovering ionic liquids from aqueous media.

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

The histologic examination of endoscopic biopsies or resection specimens remains a key step in the work-up of affected inflammatory bowel disease (IBD) patients and can be used for diagnosis and differential diagnosis, particularly in the differentiation of UC from CD and other non-IBD related colitides. The introduction of new treatment strategies in inflammatory bowel disease (IBD) interfering with the patients' immune system may result in mucosal healing, making the pathologists aware of the impact of treatment upon diagnostic features. The European Crohn's and Colitis Organisation (ECCO) and the European Society of Pathology (ESP) jointly elaborated a consensus to establish standards for histopathology diagnosis in IBD. The consensus endeavors to address: (i) procedures required for a proper diagnosis, (ii) features which can be used for the analysis of endoscopic biopsies, (iii) features which can be used for the analysis of surgical samples, (iv) criteria for diagnosis and differential diagnosis, and (v) special situations including those inherent to therapy. Questions that were addressed include: how many features should be present for a firm diagnosis? What is the role of histology in patient management, including search for dysplasia? Which features if any, can be used for assessment of disease activity? The statements and general recommendations of this consensus are based on the highest level of evidence available, but significant gaps remain in certain areas.

A 1.2 V 10-bit 100 MS/s Successive Approximation (SA) ADC is presented. The scheme achieves high-speed and low-power operation thanks to the reference-free technique that avoids the static power dissipation of an on-chip reference generator. Moreover, the use of a common-mode based charge recovery switching method reduces the switching energy and improves the conversion linearity. A variable self-timed loop optimizes the reset time of the preamplifier to improve the conversion speed. Measurement results on a 90 nm CMOS prototype operated at 1.2 V supply show 3 mW total power consumption with a peak SNDR of 56.6 dB and a FOM of 77 fJ/conv-step.

For millennia, mankind has shaped landscapes, particularly through agriculture. In Europe, the age-old interaction between humans and ecosystems strongly influenced the cultural heritage. Yet European farmland is now being abandoned, especially in remote areas. The loss of the traditional agricultural landscapes and its consequences for biodiversity and ecosystem services is generating concerns in both the scientific community and the public. Here we ask to what extent farmland abandonment can be considered as an opportunity for rewilding ecosystems. We analyze the perceptions of traditional agriculture in Europe and their influence in land management policies. We argue that, contrary to the common perception, traditional agriculture practices were not environmentally friendly and that the standards of living of rural populations were low. We suggest that current policies to maintain extensive farming landscapes underestimate the human labor needed to sustain these landscapes and the recent and future dynamics of the socio-economic drivers behind abandonment. We examine the potential benefits for ecosystems and people from rewilding. We identify species that could benefit from land abandonment and forest regeneration and the ecosystem services that could be provided such as carbon sequestration and recreation. Finally, we discuss the challenges associated with rewilding, including the need to maintain open areas, the fire risks, and the conflicts between people and wildlife. Despite these challenges, we argue that rewilding should be recognized by policy-makers as one of the possible land management options in Europe, particularly on marginal areas.

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 defences 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 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.

Is concerned with human value management, examines the relationships between organizations’ competitiveness, innovation advancements, and knowledge management and presents a set of considerations regarding how these relationships affect strategic management and the formulation of competitive strategies. By considering how knowledge development is related with personal characteristics and personal development, this article attempts to provide useful insights on the linkages between innovation and competitiveness. These considerations point out the importance of knowledge development and the role of knowledge management in order to assure competitiveness. This work proposes also a conceptual model, with special focus on the relationships between knowledge management, competitiveness, and innovation. The major factors are presented and directions for future research are suggested according to the proposed model.

BACKGROUND: Multilocus Sequence Typing (MLST) is a frequently used typing method for the analysis of the clonal relationships among strains of several clinically relevant microbial species. MLST is based on the sequence of housekeeping genes that result in each strain having a distinct numerical allelic profile, which is abbreviated to a unique identifier: the sequence type (ST). The relatedness between two strains can then be inferred by the differences between allelic profiles. For a more comprehensive analysis of the possible patterns of evolutionary descent, a set of rules were proposed and implemented in the eBURST algorithm. These rules allow the division of a data set into several clusters of related strains, dubbed clonal complexes, by implementing a simple model of clonal expansion and diversification. Within each clonal complex, the rules identify which links between STs correspond to the most probable pattern of descent. However, the eBURST algorithm is not globally optimized, which can result in links, within the clonal complexes, that violate the rules proposed. RESULTS: Here, we present a globally optimized implementation of the eBURST algorithm - goeBURST. The search for a global optimal solution led to the formalization of the problem as a graphic matroid, for which greedy algorithms that provide an optimal solution exist. Several public data sets of MLST data were tested and differences between the two implementations were found and are discussed for five bacterial species: Enterococcus faecium, Streptococcus pneumoniae, Burkholderia pseudomallei, Campylobacter jejuni and Neisseria spp.. A novel feature implemented in goeBURST is the representation of the level of tiebreak rule reached before deciding if a link should be drawn, which can used to visually evaluate the reliability of the represented hypothetical pattern of descent. CONCLUSION: goeBURST is a globally optimized implementation of the eBURST algorithm, that identifies alternative patterns of descent for several bacterial species. Furthermore, the algorithm can be applied to any multilocus typing data based on the number of differences between numeric profiles. A software implementation is available at http://goeBURST.phyloviz.net.

The energy spectrum of cosmic rays above $2.5\ifmmode\times\else\texttimes\fi{}{10}^{18}\text{ }\mathrm{eV}$, derived from 20 000 events recorded at the Pierre Auger Observatory, is described. The spectral index $\ensuremath{\gamma}$ of the particle flux, $J\ensuremath{\propto}{E}^{\ensuremath{-}\ensuremath{\gamma}}$, at energies between $4\ifmmode\times\else\texttimes\fi{}{10}^{18}\text{ }\mathrm{eV}$ and $4\ifmmode\times\else\texttimes\fi{}{10}^{19}\text{ }\mathrm{eV}$ is $2.69\ifmmode\pm\else\textpm\fi{}0.02(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}0.06(\mathrm{syst})$, steepening to $4.2\ifmmode\pm\else\textpm\fi{}0.4(\mathrm{stat})\ifmmode\pm\else\textpm\fi{}0.06(\mathrm{syst})$ at higher energies. The hypothesis of a single power law is rejected with a significance greater than 6 standard deviations. The data are consistent with the prediction by Greisen and by Zatsepin and Kuz'min.

In this paper, direct power control (DPC) of three-phase pulsewidth-modulated rectifiers without line voltage sensors is presented. The new system is based on virtual flux (VF) estimation. Theoretical principles of this method are discussed. The steady-state and dynamic behavior of VF-DPC are presented that illustrate the operation and performance of the proposed system compared to a conventional DPC method. Both strategies are also investigated under unbalance and predistorted grid. It is shown that the VF-DPC exhibits several advantages, particularly providing sinusoidal line current when the supply voltage is not ideal. Test results show the excellent performance of the proposed system.