Showing papers by "Spanish National Research Council published in 2020"

The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2

Abstract: The present outbreak of a coronavirus-associated acute respiratory disease called coronavirus disease 19 (COVID-19) is the third documented spillover of an animal coronavirus to humans in only two decades that has resulted in a major epidemic. The Coronaviridae Study Group (CSG) of the International Committee on Taxonomy of Viruses, which is responsible for developing the classification of viruses and taxon nomenclature of the family Coronaviridae, has assessed the placement of the human pathogen, tentatively named 2019-nCoV, within the Coronaviridae. Based on phylogeny, taxonomy and established practice, the CSG recognizes this virus as forming a sister clade to the prototype human and bat severe acute respiratory syndrome coronaviruses (SARS-CoVs) of the species Severe acute respiratory syndrome-related coronavirus, and designates it as SARS-CoV-2. In order to facilitate communication, the CSG proposes to use the following naming convention for individual isolates: SARS-CoV-2/host/location/isolate/date. While the full spectrum of clinical manifestations associated with SARS-CoV-2 infections in humans remains to be determined, the independent zoonotic transmission of SARS-CoV and SARS-CoV-2 highlights the need for studying viruses at the species level to complement research focused on individual pathogenic viruses of immediate significance. This will improve our understanding of virus–host interactions in an ever-changing environment and enhance our preparedness for future outbreaks.

Planck 2018 results. VI. Cosmological parameters

Abstract: We present cosmological parameter results from the final full-mission Planck measurements of the cosmic microwave background (CMB) anisotropies, combining information from the temperature and polarization maps and the lensing reconstruction Compared to the 2015 results, improved measurements of large-scale polarization allow the reionization optical depth to be measured with higher precision, leading to significant gains in the precision of other correlated parameters Improved modelling of the small-scale polarization leads to more robust constraints on manyparameters,withresidualmodellinguncertaintiesestimatedtoaffectthemonlyatthe05σlevelWefindgoodconsistencywiththestandard spatially-flat6-parameter ΛCDMcosmologyhavingapower-lawspectrumofadiabaticscalarperturbations(denoted“base ΛCDM”inthispaper), from polarization, temperature, and lensing, separately and in combination A combined analysis gives dark matter density Ωch2 = 0120±0001, baryon density Ωbh2 = 00224±00001, scalar spectral index ns = 0965±0004, and optical depth τ = 0054±0007 (in this abstract we quote 68% confidence regions on measured parameters and 95% on upper limits) The angular acoustic scale is measured to 003% precision, with 100θ∗ = 10411±00003Theseresultsareonlyweaklydependentonthecosmologicalmodelandremainstable,withsomewhatincreasederrors, in many commonly considered extensions Assuming the base-ΛCDM cosmology, the inferred (model-dependent) late-Universe parameters are: HubbleconstantH0 = (674±05)kms−1Mpc−1;matterdensityparameterΩm = 0315±0007;andmatterfluctuationamplitudeσ8 = 0811±0006 We find no compelling evidence for extensions to the base-ΛCDM model Combining with baryon acoustic oscillation (BAO) measurements (and consideringsingle-parameterextensions)weconstraintheeffectiveextrarelativisticdegreesoffreedomtobe Neff = 299±017,inagreementwith the Standard Model prediction Neff = 3046, and find that the neutrino mass is tightly constrained toPmν < 012 eV The CMB spectra continue to prefer higher lensing amplitudesthan predicted in base ΛCDM at over 2σ, which pulls some parameters that affect thelensing amplitude away from the ΛCDM model; however, this is not supported by the lensing reconstruction or (in models that also change the background geometry) BAOdataThejointconstraintwithBAOmeasurementsonspatialcurvatureisconsistentwithaflatuniverse, ΩK = 0001±0002Alsocombining with Type Ia supernovae (SNe), the dark-energy equation of state parameter is measured to be w0 = −103±003, consistent with a cosmological constant We find no evidence for deviations from a purely power-law primordial spectrum, and combining with data from BAO, BICEP2, and Keck Array data, we place a limit on the tensor-to-scalar ratio r0002 < 006 Standard big-bang nucleosynthesis predictions for the helium and deuterium abundances for the base-ΛCDM cosmology are in excellent agreement with observations The Planck base-ΛCDM results are in good agreement with BAO, SNe, and some galaxy lensing observations, but in slight tension with the Dark Energy Survey’s combined-probe results including galaxy clustering (which prefers lower fluctuation amplitudes or matter density parameters), and in significant, 36σ, tension with local measurements of the Hubble constant (which prefer a higher value) Simple model extensions that can partially resolve these tensions are not favoured by the Planck data

The ATLAS Experiment at the CERN Large Hadron Collider

Abstract: The ATLAS detector as installed in its experimental cavern at point 1 at CERN is described in this paper. A brief overview of the expected performance of the detector when the Large Hadron Collider begins operation is also presented.

Planck 2018 results: XI. Polarized dust foregrounds

Abstract: The study of polarized dust emission has become entwined with the analysis of the cosmic microwave background (CMB) polarization. We use new Planck maps to characterize Galactic dust emission as a foreground to the CMB polarization. We present Planck EE, BB, and TE power spectra of dust polarization at 353 GHz for six nested sky regions covering from 24 to 71 % of the sky. We present power-law fits to the angular power spectra, yielding evidence for statistically significant variations of the exponents over sky regions and a difference between the values for the EE and BB spectra. The TE correlation and E/B power asymmetry extend to low multipoles that were not included in earlier Planck polarization papers. We also report evidence for a positive TB dust signal. Combining data from Planck and WMAP, we determine the amplitudes and spectral energy distributions (SEDs) of polarized foregrounds, including the correlation between dust and synchrotron polarized emission, for the six sky regions as a function of multipole. This quantifies the challenge of the component separation procedure required for detecting the reionization and recombination peaks of primordial CMB B modes. The SED of polarized dust emission is fit well by a single-temperature modified blackbody emission law from 353 GHz to below 70 GHz. For a dust temperature of 19.6 K, the mean spectral index for dust polarization is $\beta_{\rm d}^{P} = 1.53\pm0.02 $. By fitting multi-frequency cross-spectra, we examine the correlation of the dust polarization maps across frequency. We find no evidence for decorrelation. If the Planck limit for the largest sky region applies to the smaller sky regions observed by sub-orbital experiments, then decorrelation might not be a problem for CMB experiments aiming at a primordial B-mode detection limit on the tensor-to-scalar ratio $r\simeq0.01$ at the recombination peak.

Severe acute respiratory syndrome-related coronavirus: The species and its viruses – a statement of the Coronavirus Study Group

Abstract: The present outbreak of lower respiratory tract infections, including respiratory distress syndrome, is the third spillover, in only two decades, of an animal coronavirus to humans resulting in a major epidemic. Here, the Coronavirus Study Group (CSG) of the International Committee on Taxonomy of Viruses, which is responsible for developing the official classification of viruses and taxa naming (taxonomy) of the Coronaviridae family, assessed the novelty of the human pathogen tentatively named 2019-nCoV. Based on phylogeny, taxonomy and established practice, the CSG formally recognizes this virus as a sister to severe acute respiratory syndrome coronaviruses (SARS-CoVs) of the species Severe acute respiratory syndrome-related coronavirus and designates it as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To facilitate communication, the CSG further proposes to use the following naming convention for individual isolates: SARS-CoV-2/Isolate/Host/Date/Location. The spectrum of clinical manifestations associated with SARS-CoV-2 infections in humans remains to be determined. The independent zoonotic transmission of SARS-CoV and SARS-CoV-2 highlights the need for studying the entire (virus) species to complement research focused on individual pathogenic viruses of immediate significance. This research will improve our understanding of virus-host interactions in an ever-changing environment and enhance our preparedness for future outbreaks.

Guidelines and definitions for research on epithelial–mesenchymal transition

Abstract: Epithelial-mesenchymal transition (EMT) encompasses dynamic changes in cellular organization from epithelial to mesenchymal phenotypes, which leads to functional changes in cell migration and invasion. EMT occurs in a diverse range of physiological and pathological conditions and is driven by a conserved set of inducing signals, transcriptional regulators and downstream effectors. With over 5,700 publications indexed by Web of Science in 2019 alone, research on EMT is expanding rapidly. This growing interest warrants the need for a consensus among researchers when referring to and undertaking research on EMT. This Consensus Statement, mediated by 'the EMT International Association' (TEMTIA), is the outcome of a 2-year-long discussion among EMT researchers and aims to both clarify the nomenclature and provide definitions and guidelines for EMT research in future publications. We trust that these guidelines will help to reduce misunderstanding and misinterpretation of research data generated in various experimental models and to promote cross-disciplinary collaboration to identify and address key open questions in this research field. While recognizing the importance of maintaining diversity in experimental approaches and conceptual frameworks, we emphasize that lasting contributions of EMT research to increasing our understanding of developmental processes and combatting cancer and other diseases depend on the adoption of a unified terminology to describe EMT.

TRY plant trait database : Enhanced coverage and open access

Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Planck 2018 results. I. Overview and the cosmological legacy of Planck

Abstract: The European Space Agency’s Planck satellite, which was dedicated to studying the early Universe and its subsequent evolution, was launched on 14 May 2009. It scanned the microwave and submillimetre sky continuously between 12 August 2009 and 23 October 2013, producing deep, high-resolution, all-sky maps in nine frequency bands from 30 to 857 GHz. This paper presents the cosmological legacy of Planck, which currently provides our strongest constraints on the parameters of the standard cosmological model and some of the tightest limits available on deviations from that model. The 6-parameter ΛCDM model continues to provide an excellent fit to the cosmic microwave background data at high and low redshift, describing the cosmological information in over a billion map pixels with just six parameters. With 18 peaks in the temperature and polarization angular power spectra constrained well, Planck measures five of the six parameters to better than 1% (simultaneously), with the best-determined parameter (θ*) now known to 0.03%. We describe the multi-component sky as seen by Planck, the success of the ΛCDM model, and the connection to lower-redshift probes of structure formation. We also give a comprehensive summary of the major changes introduced in this 2018 release. The Planck data, alone and in combination with other probes, provide stringent constraints on our models of the early Universe and the large-scale structure within which all astrophysical objects form and evolve. We discuss some lessons learned from the Planck mission, and highlight areas ripe for further experimental advances.

The 16th Data Release of the Sloan Digital Sky Surveys: First Release from the APOGEE-2 Southern Survey and Full Release of eBOSS Spectra

Abstract: This paper documents the sixteenth data release (DR16) from the Sloan Digital Sky Surveys; the fourth and penultimate from the fourth phase (SDSS-IV). This is the first release of data from the southern hemisphere survey of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2); new data from APOGEE-2 North are also included. DR16 is also notable as the final data release for the main cosmological program of the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), and all raw and reduced spectra from that project are released here. DR16 also includes all the data from the Time Domain Spectroscopic Survey (TDSS) and new data from the SPectroscopic IDentification of ERosita Survey (SPIDERS) programs, both of which were co-observed on eBOSS plates. DR16 has no new data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey (or the MaNGA Stellar Library "MaStar"). We also preview future SDSS-V operations (due to start in 2020), and summarize plans for the final SDSS-IV data release (DR17).

The physiology of plant responses to drought

Abstract: Drought alone causes more annual loss in crop yield than all pathogens combined. To adapt to moisture gradients in soil, plants alter their physiology, modify root growth and architecture, and close stomata on their aboveground segments. These tissue-specific responses modify the flux of cellular signals, resulting in early flowering or stunted growth and, often, reduced yield. Physiological and molecular analyses of the model plant Arabidopsis thaliana have identified phytohormone signaling as key for regulating the response to drought or water insufficiency. Here we discuss how engineering hormone signaling in specific cells and cellular domains can facilitate improved plant responses to drought. We explore current knowledge and future questions central to the quest to produce high-yield, drought-resistant crops.

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Abstract: The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Scientists' warning on invasive alien species.

Abstract: Biological invasions are a global consequence of an increasingly connected world and the rise in human population size The numbers of invasive alien species – the subset of alien species that spread widely in areas where they are not native, affecting the environment or human livelihoods – are increasing Synergies with other global changes are exacerbating current invasions and facilitating new ones, thereby escalating the extent and impacts of invaders Invasions have complex and often immense long‐term direct and indirect impacts In many cases, such impacts become apparent or problematic only when invaders are well established and have large ranges Invasive alien species break down biogeographic realms, affect native species richness and abundance, increase the risk of native species extinction, affect the genetic composition of native populations, change native animal behaviour, alter phylogenetic diversity across communities, and modify trophic networks Many invasive alien species also change ecosystem functioning and the delivery of ecosystem services by altering nutrient and contaminant cycling, hydrology, habitat structure, and disturbance regimes These biodiversity and ecosystem impacts are accelerating and will increase further in the future Scientific evidence has identified policy strategies to reduce future invasions, but these strategies are often insufficiently implemented For some nations, notably Australia and New Zealand, biosecurity has become a national priority There have been long‐term successes, such as eradication of rats and cats on increasingly large islands and biological control of weeds across continental areas However, in many countries, invasions receive little attention Improved international cooperation is crucial to reduce the impacts of invasive alien species on biodiversity, ecosystem services, and human livelihoods Countries can strengthen their biosecurity regulations to implement and enforce more effective management strategies that should also address other global changes that interact with invasions

Gaia Early Data Release 3: Photometric content and validation

Abstract: Gaia Early Data Release 3 contains astrometry and photometry results for about 1.8 billion sources based on observations collected by the ESA Gaia satellite during the first 34 months of operations. This paper focuses on the photometric content, describing the input data, the algorithms, the processing, and the validation of the results. Particular attention is given to the quality of the data and to a number of features that users may need to take into account to make the best use of the EDR3 catalogue. The treatment of the BP and RP background has been updated to include a better estimation of the local background, and the detection of crowding effects has been used to exclude affected data from the calibrations. The photometric calibration models have also been updated to account for flux loss over the whole magnitude range. Significant improvements in the modelling and calibration of the point and line spread functions have also helped to reduce a number of instrumental effects that were still present in DR2. EDR3 contains 1.806 billion sources with G-band photometry and 1.540 billion sources with BP and RP photometry. The median uncertainty in the G-band photometry, as measured from the standard deviation of the internally calibrated mean photometry for a given source, is 0.2 mmag at magnitude G=10 to 14, 0.8 mmag at G=17, and 2.6 mmag at G=19. The significant magnitude term found in the Gaia DR2 photometry is no longer visible, and overall there are no trends larger than 1 mmag/mag. Using one passband over the whole colour and magnitude range leaves no systematics above the 1% level in magnitude in any of the bands, and a larger systematic is present for a very small sample of bright and blue sources. A detailed description of the residual systematic effects is provided. Overall the quality of the calibrated mean photometry in EDR3 is superior with respect to DR2 for all bands.

Variability in the analysis of a single neuroimaging dataset by many teams

Abstract: Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

Planck 2018 results: V. CMB power spectra and likelihoods

Abstract: We describe the legacy Planck cosmic microwave background (CMB) likelihoods derived from the 2018 data release. The overall approach is similar in spirit to the one retained for the 2013 and 2015 data release, with a hybrid method using different approximations at low (l ≥ 30) multipoles, implementing several methodological and data-analysis refinements compared to previous releases. With more realistic simulations, and better correction and modelling of systematic effects, we can now make full use of the CMB polarization observed in the High Frequency Instrument (HFI) channels. The low-multipole EE cross-spectra from the 100 GHz and 143 GHz data give a constraint on the ΛCDM reionization optical-depth parameter τ to better than 15% (in combination with the TT low-l data and the high-l temperature and polarization data), tightening constraints on all parameters with posterior distributions correlated with τ . We also update the weaker constraint on τ from the joint TEB likelihood using the Low Frequency Instrument (LFI) channels, which was used in 2015 as part of our baseline analysis. At higher multipoles, the CMB temperature spectrum and likelihood are very similar to previous releases. A better model of the temperature-to-polarization leakage and corrections for the effective calibrations of the polarization channels (i.e., the polarization efficiencies) allow us to make full use of polarization spectra, improving the ΛCDM constraints on the parameters θ MC , ω c , ω b , and H 0 by more than 30%, and ns by more than 20% compared to TT-only constraints. Extensive tests on the robustness of the modelling of the polarization data demonstrate good consistency, with some residual modelling uncertainties. At high multipoles, we are now limited mainly by the accuracy of the polarization efficiency modelling. Using our various tests, simulations, and comparison between different high-multipole likelihood implementations, we estimate the consistency of the results to be better than the 0.5 σ level on the ΛCDM parameters, as well as classical single-parameter extensions for the joint likelihood (to be compared to the 0.3 σ levels we achieved in 2015 for the temperature data alone on ΛCDM only). Minor curiosities already present in the previous releases remain, such as the differences between the best-fit ΛCDM parameters for the l > 800 ranges of the power spectrum, or the preference for more smoothing of the power-spectrum peaks than predicted in ΛCDM fits. These are shown to be driven by the temperature power spectrum and are not significantly modified by the inclusion of the polarization data. Overall, the legacy Planck CMB likelihoods provide a robust tool for constraining the cosmological model and represent a reference for future CMB observations.

The GenTree Dendroecological Collection: tree-ring and wood density data from seven tree species across Europe

Abstract: The dataset presented here was collected by the GenTree project (EU-Horizon 2020), which aims to improve the use of forest genetic resources across Europe by better understanding how trees adapt to their local environment. This dataset of individual tree-core characteristics including ring-width series and whole-core wood density was collected for seven ecologically and economically important European tree species: silver birch (Betula pendula), European beech (Fagus sylvatica), Norway spruce (Picea abies), European black poplar (Populus nigra), maritime pine (Pinus pinaster), Scots pine (Pinus sylvestris), and sessile oak (Quercus petraea). Tree-ring width measurements were obtained from 3600 trees in 142 populations and whole-core wood density was measured for 3098 trees in 125 populations. This dataset covers most of the geographical and climatic range occupied by the selected species. The potential use of it will be highly valuable for assessing ecological and evolutionary responses to environmental conditions as well as for model development and parameterization, to predict adaptability under climate change scenarios.

Planck 2018 results. VIII. Gravitational lensing

Abstract: We present measurements of the cosmic microwave background (CMB) lensing potential using the final Planck 2018 temperature and polarization data. Using polarization maps filtered to account for the noise anisotropy, we increase the significance of the detection of lensing in the polarization maps from 5σ to 9σ . Combined with temperature, lensing is detected at 40σ . We present an extensive set of tests of the robustness of the lensing-potential power spectrum, and construct a minimum-variance estimator likelihood over lensing multipoles 8 ≤ L ≤ 400 (extending the range to lower L compared to 2015), which we use to constrain cosmological parameters. We find good consistency between lensing constraints and the results from the Planck CMB power spectra within the ΛCDM model. Combined with baryon density and other weak priors, the lensing analysis alone constrains (1σ errors). Also combining with baryon acoustic oscillation data, we find tight individual parameter constraints, σ 8 = 0.811 ± 0.019, , and . Combining with Planck CMB power spectrum data, we measure σ 8 to better than 1% precision, finding σ 8 = 0.811 ± 0.006. CMB lensing reconstruction data are complementary to galaxy lensing data at lower redshift, having a different degeneracy direction in σ 8 − Ωm space; we find consistency with the lensing results from the Dark Energy Survey, and give combined lensing-only parameter constraints that are tighter than joint results using galaxy clustering. Using the Planck cosmic infrared background (CIB) maps as an additional tracer of high-redshift matter, we make a combined Planck -only estimate of the lensing potential over 60% of the sky with considerably more small-scale signal. We additionally demonstrate delensing of the Planck power spectra using the joint and individual lensing potential estimates, detecting a maximum removal of 40% of the lensing-induced power in all spectra. The improvement in the sharpening of the acoustic peaks by including both CIB and the quadratic lensing reconstruction is detected at high significance.

Planck 2018 results. IX. Constraints on primordial non-Gaussianity

Abstract: We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and optimal modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following final results: $f_{NL}^{local}$ = −0.9 ± 5.1; $f_{NL}^{equil}$ = −26 ± 47; and $f_{NL}^{ortho}$ = −38 ± 24 (68% CL, statistical). These results include low-multipole (4 ≤ l < 40) polarization data that are not included in our previous analysis. The results also pass an extensive battery of tests (with additional tests regarding foreground residuals compared to 2015), and they are stable with respect to our 2015 measurements (with small fluctuations, at the level of a fraction of a standard deviation, which is consistent with changes in data processing). Polarization-only bispectra display a significant improvement in robustness; they can now be used independently to set primordial NG constraints with a sensitivity comparable to WMAP temperature-based results and they give excellent agreement. In addition to the analysis of the standard local, equilateral, and orthogonal bispectrum shapes, we consider a large number of additional cases, such as scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is, however, detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5σ. Beyond estimates of individual shape amplitudes, we also present model-independent reconstructions and analyses of the Planck CMB bispectrum. Our final constraint on the local primordial trispectrum shape is $g_{NL}^{local}$ = (−5.8 ± 6.5) × 10$^4$ (68% CL, statistical), while constraints for other trispectrum shapes are also determined. Exploiting the tight limits on various bispectrum and trispectrum shapes, we constrain the parameter space of different early-Universe scenarios that generate primordial NG, including general single-field models of inflation, multi-field models (e.g. curvaton models), models of inflation with axion fields producing parity-violation bispectra in the tensor sector, and inflationary models involving vector-like fields with directionally-dependent bispectra. Our results provide a high-precision test for structure-formation scenarios, showing complete agreement with the basic picture of the ΛCDM cosmology regarding the statistics of the initial conditions, with cosmic structures arising from adiabatic, passive, Gaussian, and primordial seed perturbations.

Toward Nanotechnology-Enabled Approaches against the COVID-19 Pandemic.

Abstract: The COVID-19 outbreak has fueled a global demand for effective diagnosis and treatment as well as mitigation of the spread of infection, all through large-scale approaches such as specific alternative antiviral methods and classical disinfection protocols. Based on an abundance of engineered materials identifiable by their useful physicochemical properties through versatile chemical functionalization, nanotechnology offers a number of approaches to cope with this emergency. Here, through a multidisciplinary Perspective encompassing diverse fields such as virology, biology, medicine, engineering, chemistry, materials science, and computational science, we outline how nanotechnology-based strategies can support the fight against COVID-19, as well as infectious diseases in general, including future pandemics. Considering what we know so far about the life cycle of the virus, we envision key steps where nanotechnology could counter the disease. First, nanoparticles (NPs) can offer alternative methods to classical disinfection protocols used in healthcare settings, thanks to their intrinsic antipathogenic properties and/or their ability to inactivate viruses, bacteria, fungi, or yeasts either photothermally or via photocatalysis-induced reactive oxygen species (ROS) generation. Nanotechnology tools to inactivate SARS-CoV-2 in patients could also be explored. In this case, nanomaterials could be used to deliver drugs to the pulmonary system to inhibit interaction between angiotensin-converting enzyme 2 (ACE2) receptors and viral S protein. Moreover, the concept of "nanoimmunity by design" can help us to design materials for immune modulation, either stimulating or suppressing the immune response, which would find applications in the context of vaccine development for SARS-CoV-2 or in counteracting the cytokine storm, respectively. In addition to disease prevention and therapeutic potential, nanotechnology has important roles in diagnostics, with potential to support the development of simple, fast, and cost-effective nanotechnology-based assays to monitor the presence of SARS-CoV-2 and related biomarkers. In summary, nanotechnology is critical in counteracting COVID-19 and will be vital when preparing for future pandemics.

Bandgap engineering of two-dimensional semiconductor materials

Abstract: Semiconductors are the basis of many vital technologies such as electronics, computing, communications, optoelectronics, and sensing. Modern semiconductor technology can trace its origins to the invention of the point contact transistor in 1947. This demonstration paved the way for the development of discrete and integrated semiconductor devices and circuits that has helped to build a modern society where semiconductors are ubiquitous components of everyday life. A key property that determines the semiconductor electrical and optical properties is the bandgap. Beyond graphene, recently discovered two-dimensional (2D) materials possess semiconducting bandgaps ranging from the terahertz and mid-infrared in bilayer graphene and black phosphorus, visible in transition metal dichalcogenides, to the ultraviolet in hexagonal boron nitride. In particular, these 2D materials were demonstrated to exhibit highly tunable bandgaps, achieved via the control of layers number, heterostructuring, strain engineering, chemical doping, alloying, intercalation, substrate engineering, as well as an external electric field. We provide a review of the basic physical principles of these various techniques on the engineering of quasi-particle and optical bandgaps, their bandgap tunability, potentials and limitations in practical realization in future 2D device technologies.

Opportunities and challenges for spintronics in the microelectronics industry

Abstract: Spintronic devices exploit the spin, as well as the charge, of electrons and could bring new capabilities to the microelectronics industry However, in order for spintronic devices to meet the ever-increasing demands of the industry, innovation in terms of materials, processes and circuits are required Here, we review recent developments in spintronics that could soon have an impact on the microelectronics and information technology industry We highlight and explore four key areas: magnetic memories, magnetic sensors, radio-frequency and microwave devices, and logic and non-Boolean devices We also discuss the challenges—at both the device and the system level—that need be addressed in order to integrate spintronic materials and functionalities into mainstream microelectronic platforms This Review Article examines the potential of spintronics in four key areas of application —memories, sensors, microwave devices, and logic devices — and discusses the challenges that need be addressed in order to integrate spintronic materials and functionalities into mainstream microelectronic platforms

Multiple elements of soil biodiversity drive ecosystem functions across biomes.

Abstract: The role of soil biodiversity in regulating multiple ecosystem functions is poorly understood, limiting our ability to predict how soil biodiversity loss might affect human wellbeing and ecosystem sustainability. Here, combining a global observational study with an experimental microcosm study, we provide evidence that soil biodiversity (bacteria, fungi, protists and invertebrates) is significantly and positively associated with multiple ecosystem functions. These functions include nutrient cycling, decomposition, plant production, and reduced potential for pathogenicity and belowground biological warfare. Our findings also reveal the context dependency of such relationships and the importance of the connectedness, biodiversity and nature of the globally distributed dominant phylotypes within the soil network in maintaining multiple functions. Moreover, our results suggest that the positive association between plant diversity and multifunctionality across biomes is indirectly driven by soil biodiversity. Together, our results provide insights into the importance of soil biodiversity for maintaining soil functionality locally and across biomes, as well as providing strong support for the inclusion of soil biodiversity in conservation and management programmes.

Global ecosystem thresholds driven by aridity

Abstract: Aridity, which is increasing worldwide because of climate change, affects the structure and functioning of dryland ecosystems. Whether aridification leads to gradual (versus abrupt) and systemic (versus specific) ecosystem changes is largely unknown. We investigated how 20 structural and functional ecosystem attributes respond to aridity in global drylands. Aridification led to systemic and abrupt changes in multiple ecosystem attributes. These changes occurred sequentially in three phases characterized by abrupt decays in plant productivity, soil fertility, and plant cover and richness at aridity values of 0.54, 0.7, and 0.8, respectively. More than 20% of the terrestrial surface will cross one or several of these thresholds by 2100, which calls for immediate actions to minimize the negative impacts of aridification on essential ecosystem services for the more than 2 billion people living in drylands.

D-NeRF: Neural Radiance Fields for Dynamic Scenes

Abstract: Neural rendering techniques combining machine learning with geometric reasoning have arisen as one of the most promising approaches for synthesizing novel views of a scene from a sparse set of images. Among these, stands out the Neural radiance fields (NeRF), which trains a deep network to map 5D input coordinates (representing spatial location and viewing direction) into a volume density and view-dependent emitted radiance. However, despite achieving an unprecedented level of photorealism on the generated images, NeRF is only applicable to static scenes, where the same spatial location can be queried from different images. In this paper we introduce D-NeRF, a method that extends neural radiance fields to a dynamic domain, allowing to reconstruct and render novel images of objects under rigid and non-rigid motions from a \emph{single} camera moving around the scene. For this purpose we consider time as an additional input to the system, and split the learning process in two main stages: one that encodes the scene into a canonical space and another that maps this canonical representation into the deformed scene at a particular time. Both mappings are simultaneously learned using fully-connected networks. Once the networks are trained, D-NeRF can render novel images, controlling both the camera view and the time variable, and thus, the object movement. We demonstrate the effectiveness of our approach on scenes with objects under rigid, articulated and non-rigid motions. Code, model weights and the dynamic scenes dataset will be released.