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Results on the production of 4He and Image 1 nuclei in Pb–Pb collisions at √sNN=2.76TeV in the rapidity range |y|<1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0–10% central events are found to be dN/dyHe4=(0.8±0.4(stat)±0.3(syst))×10−6 and Image 2, respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (Tchem=156MeV) as for light hadrons. The measured ratio of Image 3 is 1.4±0.8(stat)±0.5(syst).
Transverse momentum (pT ) spectra of charged particles at mid-pseudorapidity in Xe–Xe collisions at √sNN=5.44TeV measured with the ALICE apparatus at the Large Hadron Collider are reported. The kinematic range 0.15<pT<50GeV/c and |η|<0.8 is covered. Results are presented in nine classes of collision centrality in the 0–80% range. For comparison, a pp reference at the collision energy of √s=5.44 TeV is obtained by interpolating between existing pp measurements at √s=5.02 and 7 TeV. The nuclear modification factors in central Xe–Xe collisions and Pb–Pb collisions at a similar center-of-mass energy of √sNN=5.02 TeV, and in addition at 2.76 TeV, at analogous ranges of charged particle multiplicity density 〈dNch/dη〉 show a remarkable similarity at pT>10 GeV/c. The centrality dependence of the ratio of the average transverse momentum 〈pT〉 in Xe–Xe collisions over Pb–Pb collision at √s=5.02 TeV is compared to hydrodynamical model calculations.
The elliptic flow (v2) of (anti-)3He is measured in Pb–Pb collisions at √sNN=5.02TeV in the transverse-momentum (pT) range of 2–6 GeV/c for the centrality classes 0–20%, 20–40%, and 40–60% using the event-plane method. This measurement is compared to that of pions, kaons, and protons at the same center-of-mass energy. A clear mass ordering is observed at low pT, as expected from relativistic hydrodynamics. The violation of the scaling of v2 with the number of constituent quarks at low pT, already observed for identified hadrons and deuterons at LHC energies, is confirmed also for (anti-)3He. The elliptic flow of (anti-)3He is underestimated by the Blast-Wave model and overestimated by a simple coalescence approach based on nucleon scaling. The elliptic flow of (anti-)3He measured in the centrality classes 0–20% and 20–40% is well described by a more sophisticated coalescence model where the phase-space distributions of protons and neutrons are generated using the iEBE-VISHNU hybrid model with AMPT initial conditions.
In ultrarelativistic heavy-ion collisions, the event-by-event variation of the elliptic flow v2 reflects fluctuations in the shape of the initial state of the system. This allows to select events with the same centrality but different initial geometry. This selection technique, Event Shape Engineering, has been used in the analysis of charge-dependent two- and three-particle correlations in Pb–Pb collisions at √sNN=2.76 TeV. The two-particle correlator 〈cos(φα−φβ)〉, calculated for different combinations of charges α and β, is almost independent of v2 (for a given centrality), while the three-particle correlator 〈cos(φα+φβ−2Ψ2)〉 scales almost linearly both with the event v2 and charged-particle pseudorapidity density. The charge dependence of the three-particle correlator is often interpreted as evidence for the Chiral Magnetic Effect (CME), a parity violating effect of the strong interaction. However, its measured dependence on v2 points to a large non-CME contribution to the correlator. Comparing the results with Monte Carlo calculations including a magnetic field due to the spectators, the upper limit of the CME signal contribution to the three-particle correlator in the 10–50% centrality interval is found to be 26–33% at 95% confidence level.
The ALICE Collaboration reports the measurement of semi-inclusive distributions of charged-particle jets recoiling from a high-transverse momentum trigger hadron in p–Pb collisions at √sNN=5.02 TeV. Jets are reconstructed from charged-particle tracks using the anti-kT algorithm with resolution parameter R=0.2 and 0.4. A data-driven statistical approach is used to correct the uncorrelated background jet yield. Recoil jet distributions are reported for jet transverse momentum 15<pT,jetch<50GeV/c and are compared in various intervals of p–Pb event activity, based on charged-particle multiplicity and zero-degree neutral energy in the forward (Pb-going) direction. The semi-inclusive observable is self-normalized and such comparisons do not require the interpretation of p–Pb event activity in terms of collision geometry, in contrast to inclusive jet observables. These measurements provide new constraints on the magnitude of jet quenching in small systems at the LHC. In p–Pb collisions with high event activity, the average medium-induced out-of-cone energy transport for jets with R=0.4 and 15<pT,jetch<50GeV/c is measured to be less than 0.4 GeV/c at 90% confidence, which is over an order of magnitude smaller than a similar measurement for central Pb–Pb collisions at √sNN=2.76TeV. Comparison is made to theoretical calculations of jet quenching in small systems, and to inclusive jet measurements in p–Pb collisions selected by event activity at the LHC and in d–Au collisions at RHIC.
The first evidence of spin alignment of vector mesons (K*0 and ϕ) in heavy-ion collisions at the Large Hadron Collider (LHC) is reported. The spin density matrix element ρ00 is measured at midrapidity (|y|< 0.5) in Pb-Pb collisions at a center-of-mass energy (√sNN) of 2.76 TeV
with the ALICE detector. ρ00 values are found to be less than 1/3 (1/3 implies no spin alignment) at low transverse momentum (pT<2 GeV/c) for K*0 and ϕ at a level of 3σ and 2σ, respectively. No significant spin alignment is observed for the K0S meson (spin = 0) in Pb-Pb collisions and for the vector mesons in pp collisions. The measured spin alignment is unexpectedly large but qualitatively consistent with the expectation from models which attribute it to a polarization of quarks in the presence of angular momentum in heavy-ion collisions and a subsequent hadronization by the process of recombination.
The transverse momentum (pT) differential yields of (anti-)3He and (anti-)3H measured in p-Pb collisions at sNN−−−√ = 5.02 TeV with ALICE at the Large Hadron Collider (LHC) are presented. The ratios of the pT-integrated yields of (anti-)3He and (anti-)3H to the proton yields are reported, as well as the pT dependence of the coalescence parameters B3 for (anti-)3He and (anti-)3H. For (anti-)3He, the results obtained in four classes of the mean charged-particle multiplicity density are also discussed. These results are compared to predictions from a canonical statistical hadronization model and coalescence approaches. An upper limit on the total yield of 4He¯ is determined.
The ALICE collaboration at the CERN LHC reports novel measurements of jet substructure in pp collisions at s√= 7 TeV and central Pb-Pb collisions at sNN−−−√ = 2.76 TeV. Jet substructure of track-based jets is explored via iterative declustering and grooming techniques. We present the measurement of the momentum sharing of two-prong substructure exposed via grooming, the zg, and its dependence on the opening angle, in both pp and Pb-Pb collisions. We also present the first measurement of the distribution of the number of branches obtained in the iterative declustering of the jet, which is interpreted as the number of its hard splittings. In Pb-Pb collisions, we observe a suppression of symmetric splittings at large opening angles and an enhancement of splittings at small opening angles relative to pp collisions, with no significant modification of the number of splittings. The results are compared to predictions from various Monte Carlo event generators to test the role of important concepts in the evolution of the jet in the medium such as color coherence.
The ALICE collaboration at the CERN LHC reports novel measurements of jet substructure in pp collisions at s√= 7 TeV and central Pb-Pb collisions at sNN−−−√ = 2.76 TeV. Jet substructure of track-based jets is explored via iterative declustering and grooming techniques. We present the measurement of the momentum sharing of two-prong substructure exposed via grooming, the zg, and its dependence on the opening angle, in both pp and Pb-Pb collisions. We also present the first measurement of the distribution of the number of branches obtained in the iterative declustering of the jet, which is interpreted as the number of its hard splittings. In Pb-Pb collisions, we observe a suppression of symmetric splittings at large opening angles and an enhancement of splittings at small opening angles relative to pp collisions, with no significant modification of the number of splittings. The results are compared to predictions from various Monte Carlo event generators to test the role of important concepts in the evolution of the jet in the medium such as color coherence.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and −10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.
The growth of aerosol due to the aqueous phase oxidation of sulfur dioxide by ozone was measured in laboratory-generated clouds created in the Cosmics Leaving OUtdoor Droplets (CLOUD) chamber at the European Organization for Nuclear Research (CERN). Experiments were performed at 10 and −10 °C, on acidic (sulfuric acid) and on partially to fully neutralised (ammonium sulfate) seed aerosol. Clouds were generated by performing an adiabatic expansion – pressurising the chamber to 220 hPa above atmospheric pressure, and then rapidly releasing the excess pressure, resulting in a cooling, condensation of water on the aerosol and a cloud lifetime of approximately 6 min. A model was developed to compare the observed aerosol growth with that predicted using oxidation rate constants previously measured in bulk solutions. The model captured the measured aerosol growth very well for experiments performed at 10 and −10 °C, indicating that, in contrast to some previous studies, the oxidation rates of SO2 in a dispersed aqueous system can be well represented by using accepted rate constants, based on bulk measurements. To the best of our knowledge, these are the first laboratory-based measurements of aqueous phase oxidation in a dispersed, super-cooled population of droplets. The measurements are therefore important in confirming that the extrapolation of currently accepted reaction rate constants to temperatures below 0 °C is correct.
Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species’ threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project – and avert – future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups – including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems – www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.
About half of present-day cloud condensation nuclei originate from atmospheric nucleation, frequently appearing as a burst of new particles near midday1. Atmospheric observations show that the growth rate of new particles often accelerates when the diameter of the particles is between one and ten nanometres2,3. In this critical size range, new particles are most likely to be lost by coagulation with pre-existing particles4, thereby failing to form new cloud condensation nuclei that are typically 50 to 100 nanometres across. Sulfuric acid vapour is often involved in nucleation but is too scarce to explain most subsequent growth5,6, leaving organic vapours as the most plausible alternative, at least in the planetary boundary layer7,8,9,10. Although recent studies11,12,13 predict that low-volatility organic vapours contribute during initial growth, direct evidence has been lacking. The accelerating growth may result from increased photolytic production of condensable organic species in the afternoon2, and the presence of a possible Kelvin (curvature) effect, which inhibits organic vapour condensation on the smallest particles (the nano-Köhler theory)2,14, has so far remained ambiguous. Here we present experiments performed in a large chamber under atmospheric conditions that investigate the role of organic vapours in the initial growth of nucleated organic particles in the absence of inorganic acids and bases such as sulfuric acid or ammonia and amines, respectively. Using data from the same set of experiments, it has been shown15 that organic vapours alone can drive nucleation. We focus on the growth of nucleated particles and find that the organic vapours that drive initial growth have extremely low volatilities (saturation concentration less than 10−4.5 micrograms per cubic metre). As the particles increase in size and the Kelvin barrier falls, subsequent growth is primarily due to more abundant organic vapours of slightly higher volatility (saturation concentrations of 10−4.5 to 10−0.5 micrograms per cubic metre). We present a particle growth model that quantitatively reproduces our measurements. Furthermore, we implement a parameterization of the first steps of growth in a global aerosol model and find that concentrations of atmospheric cloud concentration nuclei can change substantially in response, that is, by up to 50 per cent in comparison with previously assumed growth rate parameterizations.
The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.
Cloud microphysical processes involving the ice phase in tropospheric clouds are among the major uncertainties in cloud formation, weather and General Circulation Models (GCMs). The simultaneous detection of aerosol particles, liquid droplets, and ice crystals, especially in the small cloud-particle size range below 50 µm, remains challenging in mixed phase, often unstable ice-water phase environments. The Cloud Aerosol Spectrometer with Polarisation (CASPOL) is an airborne instrument that has the ability to detect such small cloud particles and measure their effects on the backscatter polarisation state. Here we operate the versatile Cosmics-Leaving- OUtdoor-Droplets (CLOUD) chamber facility at the European Organisation for Nuclear Research (CERN) to produce controlled mixed phase and other clouds by adiabatic expansions in an ultraclean environment, and use the CASPOL to discriminate between different aerosols, water and ice particles. In this paper, optical property measurements of mixed phase clouds and viscous Secondary Organic Aerosol (SOA) are presented. We report observations of significant liquid – viscous SOA particle polarisation transitions under dry conditions using CASPOL. Cluster analysis techniques were subsequently used to classify different types of particles according to their polarisation ratios during phase transition. A classification map is presented for water droplets, organic aerosol (e.g., SOA and oxalic acid), crystalline substances such as ammonium sulphate, and volcanic ash. Finally, we discuss the benefits and limitations of this classi- fication approach for atmospherically relevant concentration and mixtures with respect to the CLOUD 8–9 campaigns and its potential contribution to Tropical Troposphere Layer (TTL) analysis.
Cloud microphysical processes involving the ice phase in tropospheric clouds are among the major uncertainties in cloud formation, weather, and general circulation models. The detection of aerosol particles, liquid droplets, and ice crystals, especially in the small cloud particle-size range below 50 μm, remains challenging in mixed phase, often unstable environments. The Cloud Aerosol Spectrometer with Polarization (CASPOL) is an airborne instrument that has the ability to detect such small cloud particles and measure the variability in polarization state of their backscattered light. Here we operate the versatile Cosmics Leaving OUtdoor Droplets (CLOUD) chamber facility at the European Organization for Nuclear Research (CERN) to produce controlled mixed phase and other clouds by adiabatic expansions in an ultraclean environment, and use the CASPOL to discriminate between different aerosols, water, and ice particles. In this paper, optical property measurements of mixed-phase clouds and viscous secondary organic aerosol (SOA) are presented. We report observations of significant liquid–viscous SOA particle polarization transitions under dry conditions using CASPOL. Cluster analysis techniques were subsequently used to classify different types of particles according to their polarization ratios during phase transition. A classification map is presented for water droplets, organic aerosol (e.g., SOA and oxalic acid), crystalline substances such as ammonium sulfate, and volcanic ash. Finally, we discuss the benefits and limitations of this classification approach for atmospherically relevant concentrations and mixtures with respect to the CLOUD 8–9 campaigns and its potential contribution to tropical troposphere layer analysis.
Simple Summary: Early and accurate diagnosis of breast cancer that has spread to other organs and tissues is crucial, as therapeutic decisions and outcome expectations might change. Computed tomography (CT) is often used to detect breast cancer’s spread, but this method has its weaknesses. The computer-assisted technique “radiomics” extracts grey-level patterns, so-called radiomic features, from medical images, which may reflect underlying biological processes. Our retrospective study therefore evaluated whether breast cancer spread can be predicted by radiomic features derived from iodine maps, an application on a new generation of CT scanners visualizing tissue blood flow. Based on 77 patients with newly diagnosed breast cancer, we found that this approach might indeed predict cancer spread to other organs/tissues. In the future, radiomics may serve as an additional tool for cancer detection and risk assessment.
Abstract: Dual-energy CT (DECT) iodine maps enable quantification of iodine concentrations as a marker for tissue vascularization. We investigated whether iodine map radiomic features derived from staging DECT enable prediction of breast cancer metastatic status, and whether textural differ- ences exist between primary breast cancers and metastases. Seventy-seven treatment-naïve patients with biopsy-proven breast cancers were included retrospectively (41 non-metastatic, 36 metastatic). Radiomic features including first-, second-, and higher-order metrics as well as shape descriptors were extracted from volumes of interest on iodine maps. Following principal component analysis, a multilayer perceptron artificial neural network (MLP-NN) was used for classification (70% of cases for training, 30% validation). Histopathology served as reference standard. MLP-NN predicted metastatic status with AUCs of up to 0.94, and accuracies of up to 92.6 in the training and 82.6 in the validation datasets. The separation of primary tumor and metastatic tissue yielded AUCs of up to 0.87, with accuracies of up to 82.8 in the training, and 85.7 in the validation dataset. DECT iodine map-based radiomic signatures may therefore predict metastatic status in breast cancer patients. In addition, microstructural differences between primary and metastatic breast cancer tissue may be reflected by differences in DECT radiomic features.
Autophagy is a core molecular pathway for the preservation of cellular and organismal homeostasis. Pharmacological and genetic interventions impairing autophagy responses promote or aggravate disease in a plethora of experimental models. Consistently, mutations in autophagy-related processes cause severe human pathologies. Here, we review and discuss preclinical data linking autophagy dysfunction to the pathogenesis of major human disorders including cancer as well as cardiovascular, neurodegenerative, metabolic, pulmonary, renal, infectious, musculoskeletal, and ocular disorders.
The growth of freshly formed aerosol particles can be the bottleneck in their survival to cloud condensation nuclei. It is therefore crucial to understand how particles grow in the atmosphere. Insufficient experimental data has impeded a profound understanding of nano-particle growth under atmospheric conditions. Here we study nano-particle growth in the CLOUD (Cosmics Leaving OUtdoors Droplets) chamber, starting from the formation of molecular clusters. We present measured growth rates at sub-3 nm sizes with different atmospherically relevant concentrations of sulphuric acid, water, ammonia and dimethylamine. We find that atmospheric ions and small acid-base clusters, which are not generally accounted for in the measurement of sulphuric acid vapour, can participate in the growth process, leading to enhanced growth rates. The availability of compounds capable of stabilizing sulphuric acid clusters governs the magnitude of these effects and thus the exact growth mechanism. We bring these observations into a coherent framework and discuss their significance in the atmosphere.