State sampling dependence of the Hopfield network inference

The fully connected Hopfield network is inferred based on observed magnetizations and pairwise correlations. We present the system in the glassy phase with low temperature and high memory load. We find that the inference error is very sensitive to the form of state sampling. When a single state is sampled to compute magnetizations and correlations, the inference error is almost indistinguishable irrespective of the sampled state. However, the error can be greatly reduced if the data is collected with state transitions. Our result holds for different disorder samples and accounts for the previously observed large fluctuations of inference error at low temperatures.Comment: 4 pages, 1 figure, further discussions added and relevant references adde

Collective perspective on advances in Dyson-Schwinger Equation QCD

We survey contemporary studies of hadrons and strongly interacting quarks using QCD's Dyson-Schwinger equations, addressing: aspects of confinement and dynamical chiral symmetry breaking; the hadron spectrum; hadron elastic and transition form factors, from small- to large-Q^2; parton distribution functions; the physics of hadrons containing one or more heavy quarks; and properties of the quark gluon plasma.Comment: 56 pages. Summary of lectures delivered by the authors at the "Workshop on AdS/CFT and Novel Approaches to Hadron and Heavy Ion Physics," 2010-10-11 to 2010-12-03, hosted by the Kavli Institute for Theoretical Physics, China, at the Chinese Academy of Science

Fungal Planet description sheets: 1042–1111

Novel species of fungi described in this study include those from various countries as follows: Antarctica, Cladosporium arenosum from marine sediment sand. Argentina, Kosmimatamyces alatophylus (incl. Kosmimatamyces gen. nov.) from soil. Australia, Aspergillus banksianus, Aspergillus kumbius, Aspergillus luteorubrus, Aspergillus malvicolor and Aspergillus nanangensis from soil, Erysiphe medicaginis from leaves of Medicago polymorpha, Hymenotorrendiella communis on leaf litter of Eucalyptus bicostata, Lactifluus albopicri and Lactifluus austropiperatus on soil, Macalpinomyces collinsiae on Eriachne benthamii, Marasmius vagus on soil, Microdochium dawsoniorum from leaves of Sporobolus natalensis, Neopestalotiopsis nebuloides from leaves of Sporobolus elongatus, Pestalotiopsis etonensis from leaves of Sporobolus jacquemontii, Phytophthora personensis from soil associated with dying Grevillea mccutcheonii. Brazil, Aspergillus oxumiae from soil, Calvatia baixaverdensis on soil, Geastrum calycicoriaceum on leaf litter, Greeneria kielmeyerae on leaf spots of Kielmeyera coriacea. Chile, Phytophthora aysenensis on collar rot and stem of Aristotelia chilensis. Croatia, Mollisia gibbospora on fallen branch of Fagus sylvatica. Czech Republic, Neosetophoma hnaniceana from Buxus sempervirens. Ecuador, Exophiala frigidotolerans from soil. Estonia, Elaphomyces bucholtzii in soil. France, Venturia paralias from leaves of Euphorbia paralias. India, Cortinarius balteatoindicus and Cortinarius ulkhagarhiensis on leaf litter. Indonesia, Hymenotorrendiella indonesiana on Eucalyptus urophylla leaf litter. Italy, Penicillium taurinense from indoor chestnut mill. Malaysia, Hemileucoglossum kelabitense on soil, Satchmopsis pini on dead needles of Pinus tecunumanii. Poland, Lecanicillium praecognitum on insects' frass. Portugal, Neodevriesia aestuarina from saline water. Republic of Korea, Gongronella namwonensis from freshwater. Russia, Candida pellucida from Exomias pellucidus, Heterocephalacria septentrionalis as endophyte from Cladonia rangiferina, Vishniacozyma phoenicis from dates fruit, Volvariella paludosa from swamp. Slovenia, Mallocybe crassivelata on soil. South Africa, Beltraniella podocarpi, Hamatocanthoscypha podocarpi, Coleophoma podocarpi and Nothoseiridium podocarpi (incl. Nothoseiridium gen. nov.)from leaves of Podocarpus latifolius, Gyrothrix encephalarti from leaves of Encephalartos sp., Paraphyton cutaneum from skin of human patient, Phacidiella alsophilae from leaves of Alsophila capensis, and Satchmopsis metrosideri on leaf litter of Metrosideros excelsa. Spain, Cladophialophora cabanerensis from soil, Cortinarius paezii on soil, Cylindrium magnoliae from leaves of Magnolia grandiflora, Trichophoma cylindrospora (incl. Trichophoma gen. nov.) from plant debris, Tuber alcaracense in calcareus soil, Tuber buendiae in calcareus soil. Thailand, Annulohypoxylon spougei on corticated wood, Poaceascoma filiforme from leaves of unknown Poaceae. UK, Dendrostoma luteum on branch lesions of Castanea sativa, Ypsilina buttingtonensis from heartwood of Quercus sp. Ukraine, Myrmecridium phragmiticola from leaves of Phragmites australis. USA, Absidia pararepens from air, Juncomyces californiensis (incl. Juncomyces gen. nov.) from leaves of Juncus effusus, Montagnula cylindrospora from a human skin sample, Muriphila oklahomaensis (incl. Muriphila gen. nov.)on outside wall of alcohol distillery, Neofabraea eucalyptorum from leaves of Eucalyptus macrandra, Diabolocovidia claustri (incl. Diabolocovidia gen. nov.)from leaves of Serenoa repens, Paecilomyces penicilliformis from air, Pseudopezicula betulae from leaves of leaf spots of Populus tremuloides. Vietnam, Diaporthe durionigena on branches of Durio zibethinus and Roridomyces pseudoirritans on rotten wood. Morphological and culture characteristics are supported by DNA barcodes

Fungal Planet description sheets: 1042–1111

Novel species of fungi described in this study include those from various countries as follows: Antarctica, Cladosporium arenosum from marine sediment sand. Argentina, Kosmimatamyces alatophylus (incl. Kosmimatamyces gen. nov.) from soil. Australia, Aspergillus banksianus, Aspergillus kumbius, Aspergillus luteorubrus, Aspergillus malvicolor and Aspergillus nanangensis from soil, Erysiphe medicaginis from leaves of Medicago polymorpha, Hymenotorrendiella communis on leaf litter of Eucalyptus bicostata, Lactifluus albopicri and Lactifluus austropiperatus on soil, Macalpinomyces collinsiae on Eriachne benthamii, Marasmius vagus on soil, Microdochium dawsoniorum from leaves of Sporobolus natalensis, Neopestalotiopsis nebuloides from leaves of Sporobolus elongatus, Pestalotiopsis etonensis from leaves of Sporobolus jacquemontii, Phytophthora personensis from soil associated with dying Grevillea mccutcheonii. Brazil, Aspergillus oxumiae from soil, Calvatia baixaverdensis on soil, Geastrum calycicoriaceum on leaf litter, Greeneria kielmeyerae on leaf spots of Kielmeyera coriacea. Chile, Phytophthora aysenensis on collar rot and stem of Aristotelia chilensis. Croatia, Mollisia gibbospora on fallen branch of Fagus sylvatica. Czech Republic, Neosetophoma hnaniceana from Buxus sempervirens. Ecuador, Exophiala frigidotolerans from soil. Estonia, Elaphomyces bucholtzii in soil. France, Venturia paralias from leaves of Euphorbia paralias. India, Cortinarius balteatoindicus and Cortinarius ulkhagarhiensis on leaf litter. Indonesia, Hymenotorrendiella indonesiana on Eucalyptus urophylla leaf litter. Italy, Penicillium taurinense from indoor chestnut mill. Malaysia, Hemileucoglossum kelabitense on soil, Satchmopsis pini on dead needles of Pinus tecunumanii. Poland, Lecanicillium praecognitum on insects' frass. Portugal, Neodevriesia aestuarina from saline water. Republic of Korea, Gongronella namwonensis from freshwater. Russia, Candida pellucida from Exomias pellucidus, Heterocephalacria septentrionalis as endophyte from Cladonia rangiferina, Vishniacozyma phoenicis from dates fruit, Volvariella paludosa from swamp. Slovenia, Mallocybe crassivelata on soil. South Africa, Beltraniella podocarpi, Hamatocanthoscypha podocarpi, Coleophoma podocarpi and Nothoseiridium podocarpi (incl. Nothoseiridium gen. nov.)from leaves of Podocarpus latifolius, Gyrothrix encephalarti from leaves of Encephalartos sp., Paraphyton cutaneum from skin of human patient, Phacidiella alsophilae from leaves of Alsophila capensis, and Satchmopsis metrosideri on leaf litter of Metrosideros excelsa. Spain, Cladophialophora cabanerensis from soil, Cortinarius paezii on soil, Cylindrium magnoliae from leaves of Magnolia grandiflora, Trichophoma cylindrospora (incl. Trichophoma gen. nov.) from plant debris, Tuber alcaracense in calcareus soil, Tuber buendiae in calcareus soil. Thailand, Annulohypoxylon spougei on corticated wood, Poaceascoma filiforme from leaves of unknown Poaceae. UK, Dendrostoma luteum on branch lesions of Castanea sativa, Ypsilina buttingtonensis from heartwood of Quercus sp. Ukraine, Myrmecridium phragmiticola from leaves of Phragmites australis. USA, Absidia pararepens from air, Juncomyces californiensis (incl. Juncomyces gen. nov.) from leaves of Juncus effusus, Montagnula cylindrospora from a human skin sample, Muriphila oklahomaensis (incl. Muriphila gen. nov.)on outside wall of alcohol distillery, Neofabraea eucalyptorum from leaves of Eucalyptus macrandra, Diabolocovidia claustri (incl. Diabolocovidia gen. nov.)from leaves of Serenoa repens, Paecilomyces penicilliformis from air, Pseudopezicula betulae from leaves of leaf spots of Populus tremuloides. Vietnam, Diaporthe durionigena on branches of Durio zibethinus and Roridomyces pseudoirritans on rotten wood. Morphological and culture characteristics are supported by DNA barcodes

Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17 : analysis for the Global Burden of Disease Study 2017

Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor estimates. Findings The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1–65·8), 17·4% (7·7–28·4), and 59·5% (34·2–86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy coverage. Interpretation By co-analysing geospatial trends in diarrhoeal burden and its key risk factors, we could assess candidate drivers of subnational death reduction. Further, by doing a counterfactual analysis of the remaining disease burden using key risk factors, we identified potential intervention strategies for vulnerable populations. In view of the demands for limited resources in LMICs, accurately quantifying the burden of diarrhoea and its drivers is important for precision public health

Measurement of the cross section of high transverse momentum Z→bb̄ production in proton–proton collisions at √s = 8 TeV with the ATLAS detector

This Letter reports the observation of a high transverse momentum Z→bb̄ signal in proton–proton collisions at √s=8 TeV and the measurement of its production cross section. The data analysed were collected in 2012 with the ATLAS detector at the LHC and correspond to an integrated luminosity of 19.5 fb−¹. The Z→bb̄ decay is reconstructed from a pair of b -tagged jets, clustered with the anti-ktkt jet algorithm with R=0.4R=0.4, that have low angular separation and form a dijet with pT>200 GeVpT>200 GeV. The signal yield is extracted from a fit to the dijet invariant mass distribution, with the dominant, multi-jet background mass shape estimated by employing a fully data-driven technique that reduces the dependence of the analysis on simulation. The fiducial cross section is determined to be σZ→bb¯fid=2.02±0.20 (stat.) ±0.25 (syst.)±0.06 (lumi.) pb=2.02±0.33 pb, in good agreement with next-to-leading-order theoretical predictions

Measurement of the branching ratio Γ(Λb⁰ → ψ(2S)Λ0)/Γ(Λb⁰ → J/ψΛ0) with the ATLAS detector

An observation of the $\Lambda_b^0 \rightarrow \psi(2S) \Lambda^0$ decay and a comparison of its branching fraction with that of the $\Lambda_b^0 \rightarrow J/\psi \Lambda^0$ decay has been made with the ATLAS detector in proton--proton collisions at $\sqrt{s}=8\,$TeV at the LHC using an integrated luminosity of $20.6\,$fb$^{-1}$. The $J/\psi$ and $\psi(2S)$ mesons are reconstructed in their decays to a muon pair, while the $\Lambda^0\rightarrow p\pi^-$ decay is exploited for the $\Lambda^0$ baryon reconstruction. The $\Lambda_b^0$ baryons are reconstructed with transverse momentum $p_{\rm T}>10\,$GeV and pseudorapidity $|\eta|<2.1$. The measured branching ratio of the $\Lambda_b^0 \rightarrow \psi(2S) \Lambda^0$ and $\Lambda_b^0 \rightarrow J/\psi \Lambda^0$ decays is $\Gamma(\Lambda_b^0 \rightarrow \psi(2S)\Lambda^0)/\Gamma(\Lambda_b^0 \rightarrow J/\psi\Lambda^0) = 0.501\pm 0.033 ({\rm stat})\pm 0.019({\rm syst})$, lower than the expectation from the covariant quark model.Comment: 12 pages plus author list (28 pages total), 5 figures, 1 table, published on Physics Letters B 751 (2015) 63-80. All figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/BPHY-2013-08

Measurement of the View the tt production cross-section using eμ events with b-tagged jets in pp collisions at √s = 13 TeV with the ATLAS detector

This paper describes a measurement of the inclusive top quark pair production cross-section (σtt¯) with a data sample of 3.2 fb−1 of proton–proton collisions at a centre-of-mass energy of √s = 13 TeV, collected in 2015 by the ATLAS detector at the LHC. This measurement uses events with an opposite-charge electron–muon pair in the final state. Jets containing b-quarks are tagged using an algorithm based on track impact parameters and reconstructed secondary vertices. The numbers of events with exactly one and exactly two b-tagged jets are counted and used to determine simultaneously σtt¯ and the efficiency to reconstruct and b-tag a jet from a top quark decay, thereby minimising the associated systematic uncertainties. The cross-section is measured to be: σtt¯ = 818 ± 8 (stat) ± 27 (syst) ± 19 (lumi) ± 12 (beam) pb, where the four uncertainties arise from data statistics, experimental and theoretical systematic effects, the integrated luminosity and the LHC beam energy, giving a total relative uncertainty of 4.4%. The result is consistent with theoretical QCD calculations at next-to-next-to-leading order. A fiducial measurement corresponding to the experimental acceptance of the leptons is also presented

Search for strong gravity in multijet final states produced in pp collisions at √s=13 TeV using the ATLAS detector at the LHC

A search is conducted for new physics in multijet final states using 3.6 inverse femtobarns of data from proton-proton collisions at √s = 13TeV taken at the CERN Large Hadron Collider with the ATLAS detector. Events are selected containing at least three jets with scalar sum of jet transverse momenta (HT) greater than 1TeV. No excess is seen at large HT and limits are presented on new physics: models which produce final states containing at least three jets and having cross sections larger than 1.6 fb with HT > 5.8 TeV are excluded. Limits are also given in terms of new physics models of strong gravity that hypothesize additional space-time dimensions

Operation and performance of the ATLAS semiconductor tracker

The semiconductor tracker is a silicon microstrip detector forming part of the inner tracking system of the ATLAS experiment at the LHC. The operation and performance of the semiconductor tracker during the first years of LHC running are described. More than 99% of the detector modules were operational during this period, with an average intrinsic hit efficiency of (99.74±0.04)%. The evolution of the noise occupancy is discussed, and measurements of the Lorentz angle, δ-ray production and energy loss presented. The alignment of the detector is found to be stable at the few-micron level over long periods of time. Radiation damage measurements, which include the evolution of detector leakage currents, are found to be consistent with predictions and are used in the verification of radiation background simulations