105 research outputs found
Transfer Matrices and Partition-Function Zeros for Antiferromagnetic Potts Models. V. Further Results for the Square-Lattice Chromatic Polynomial
We derive some new structural results for the transfer matrix of
square-lattice Potts models with free and cylindrical boundary conditions. In
particular, we obtain explicit closed-form expressions for the dominant (at
large |q|) diagonal entry in the transfer matrix, for arbitrary widths m, as
the solution of a special one-dimensional polymer model. We also obtain the
large-q expansion of the bulk and surface (resp. corner) free energies for the
zero-temperature antiferromagnet (= chromatic polynomial) through order q^{-47}
(resp. q^{-46}). Finally, we compute chromatic roots for strips of widths 9 <=
m <= 12 with free boundary conditions and locate roughly the limiting curves.Comment: 111 pages (LaTeX2e). Includes tex file, three sty files, and 19
Postscript figures. Also included are Mathematica files data_CYL.m and
data_FREE.m. Many changes from version 1: new material on series expansions
and their analysis, and several proofs of previously conjectured results.
Final version to be published in J. Stat. Phy
Transfer matrices and partition-function zeros for antiferromagnetic Potts models. VI. Square lattice with special boundary conditions
We study, using transfer-matrix methods, the partition-function zeros of the
square-lattice q-state Potts antiferromagnet at zero temperature (=
square-lattice chromatic polynomial) for the special boundary conditions that
are obtained from an m x n grid with free boundary conditions by adjoining one
new vertex adjacent to all the sites in the leftmost column and a second new
vertex adjacent to all the sites in the rightmost column. We provide numerical
evidence that the partition-function zeros are becoming dense everywhere in the
complex q-plane outside the limiting curve B_\infty(sq) for this model with
ordinary (e.g. free or cylindrical) boundary conditions. Despite this, the
infinite-volume free energy is perfectly analytic in this region.Comment: 114 pages (LaTeX2e). Includes tex file, three sty files, and 23
Postscript figures. Also included are Mathematica files data_Eq.m,
data_Neq.m,and data_Diff.m. Many changes from version 1, including several
proofs of previously conjectured results. Final version to be published in J.
Stat. Phy
Unconventional MBE Strategies from Computer Simulations for Optimized Growth Conditions
We investigate the influence of step edge diffusion (SED) and desorption on
Molecular Beam Epitaxy (MBE) using kinetic Monte-Carlo simulations of the
solid-on-solid (SOS) model. Based on these investigations we propose two
strategies to optimize MBE growth. The strategies are applicable in different
growth regimes: During layer-by-layer growth one can exploit the presence of
desorption in order to achieve smooth surfaces. By additional short high flux
pulses of particles one can increase the growth rate and assist layer-by-layer
growth. If, however, mounds are formed (non-layer-by-layer growth) the SED can
be used to control size and shape of the three-dimensional structures. By
controlled reduction of the flux with time we achieve a fast coarsening
together with smooth step edges.Comment: 19 pages, 7 figures, submitted to Phys. Rev.
A nationwide follow-up study of occupational organic dust exposure and risk of chronic obstructive pulmonary disease (COPD)
Objectives To study exposure-response relations
between cumulative organic dust exposure and incident
chronic obstructive pulmonary disease (COPD) among
subjects employed in the Danish farming and wood
industry.
Methods We studied exposure-response relations
between cumulative organic dust exposure and incident
COPD (1997–2013) among individuals born during
1950–1977 in Denmark ever employed in the farming
or wood industry (n=1 75 409). Industry-specific
employment history (1964–2007), combined with
time-dependent farming and wood industry-specific
exposure matrices defined cumulative exposure. We used
logistic regression analysis with discrete survival function
adjusting for age, sex and calendar year. Adjustment for
smoking status was explored in a subgroup of 4023 with
smoking information available.
Results Cumulative organic dust exposure was inversely
associated with COPD (adjusted rate ratios (RRadj
(95% CIs) of 0.90 (0.82 to 0.99), 0.76 (0.69 to 0.84) and
0.52 (0.47 to 0.58) for intermediate-low, intermediatehigh and high exposure quartiles, respectively, compared
with the lowest exposure quartile). Lagging exposure 10
years was not consistently suggestive of an association
between cumulative exposure and COPD; RRadj (95% CI):
1.05 (0.94 to 1.16), 0
Multiomics analysis of rheumatoid arthritis yields sequence variants that have large effects on risk of the seropositive subset
Funding Information: Funding The study was funded by NORDFORSK (grant agreement no. 90825, project NORA), the Swedish Research Council (2018-02803), the Swedish innovation Agency (Vinnova), Innovationsfonden and The Research Council of Norway, Region Stockholm-Karolinska Institutet and Region Västerbotten (ALF), the Danish Rheumatism Association (R194-A6956), the Swedish Brain Foundation, Nils and Bibbi Jensens Foundation, the Knut and Alice Wallenberg Foundation, Margaretha af Ugglas Foundation, the South-Eastern Heath Region of Norway, the Health Research Fund of Central Denmark Region, Region of Southern Denmark, the A.P. Moller Foundation for the Advancement of Medical Science, the Colitis-Crohn Foreningen, the Novo Nordisk Foundation (NNF15OC0016932), Aase og Ejnar Danielsens Fond, Beckett-Fonden, Augustinus Fonden, Knud and Edith Eriksens Mindefond, Laege Sofus Carl Emil Friis and Hustru Olga Doris Friis’ Legat, the Psoriasis Forskningsfonden, the University of Aarhus, the Danish Rheumatism Association (R194-A6956, A1923, A3037 and A3570 – www. gigtforeningen.dk), Region of Southern Denmark’s PhD Fund, 12/7725 (www.regionsyddanmark.dk) and the Department of Rheumatology, Frederiksberg Hospital (www.frederiksberghospital. dk). MoBa Genetics has been funded by the Research Council of Norway (#229624, #223273), South East and Western Norway Health Authorities, ERC AdG project SELECTionPREDISPOSED, Stiftelsen Kristian Gerhard Jebsen, Trond Mohn Foundation, the Novo Nordisk Foundation and the University of Bergen. KB and SB acknowledge the Novo Nordisk Foundation (grant NNF14CC0001). Funding Information: competing financial interests as employees. OAA is a consultant to HealthLytix. The following coauthors report the following but unrelated to the current report: Karolinska Institutet, with JA as principal investigator, has entered into agreements with the following entities, mainly but not exclusively for safety monitoring of rheumatology immunomodulators: Abbvie, BMS, Eli Lilly, Janssen, MSD, Pfizer, Roche, Samsung Bioepis and Sanofi, unrelated to the present study. SB has ownerships in Intomics A/S, Hoba Therapeutics Aps, Novo Nordisk A/S, Lundbeck A/S and managing board memberships in Proscion A/S and Intomics A/S. BG has received research grants from AbbVie, Bristol Myers-Squibb and Pfizer; OH has received research grants from AbbVie, Novartis and Pfizer, DVJ has received speaker and consultation fees from AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, AGL has received speaking and/or consulting fees from AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB; and CT has received consulting fees from Roche, speaker fees from Abbvie, Bristol Myers-Squibb, Nordic Drugs, Pfizer and Roche, and an unrestricted grant from Bristol Myers-Squibb. Publisher Copyright: © Funding Information: Funding The study was funded by NORDFORSK (grant agreement no. 90825, project NORA), the Swedish Research Council (2018-02803), the Swedish innovation Agency (Vinnova), Innovationsfonden and The Research Council of Norway, Region Stockholm-Karolinska Institutet and Region Västerbotten (ALF), the Danish Rheumatism Association (R194-A6956), the Swedish Brain Foundation, Nils and Bibbi Jensens Foundation, the Knut and Alice Wallenberg Foundation, Margaretha af Ugglas Foundation, the South-Eastern Heath Region of Norway, the Health Research Fund of Central Denmark Region, Region of Southern Denmark, the A.P. Moller Foundation for the Advancement of Medical Science, the Colitis-Crohn Foreningen, the Novo Nordisk Foundation (NNF15OC0016932), Aase og Ejnar Danielsens Fond, Beckett-Fonden, Augustinus Fonden, Knud and Edith Eriksens Mindefond, Laege Sofus Carl Emil Friis and Hustru Olga Doris Friis’ Legat, the Psoriasis Forskningsfonden, the University of Aarhus, the Danish Rheumatism Association (R194-A6956, A1923, A3037 and A3570 – www. gigtforeningen.dk), Region of Southern Denmark’s PhD Fund, 12/7725 (www.regionsyddanmark.dk) and the Department of Rheumatology, Frederiksberg Hospital (www.frederiksberghospital. dk). MoBa Genetics has been funded by the Research Council of Norway (#229624, #223273), South East and Western Norway Health Authorities, ERC AdG project SELECTionPREDISPOSED, Stiftelsen Kristian Gerhard Jebsen, Trond Mohn Foundation, the Novo Nordisk Foundation and the University of Bergen. KB and SB acknowledge the Novo Nordisk Foundation (grant NNF14CC0001). Funding Information: competing financial interests as employees. OAA is a consultant to HealthLytix. The following coauthors report the following but unrelated to the current report: Karolinska Institutet, with JA as principal investigator, has entered into agreements with the following entities, mainly but not exclusively for safety monitoring of rheumatology immunomodulators: Abbvie, BMS, Eli Lilly, Janssen, MSD, Pfizer, Roche, Samsung Bioepis and Sanofi, unrelated to the present study. SB has ownerships in Intomics A/S, Hoba Therapeutics Aps, Novo Nordisk A/S, Lundbeck A/S and managing board memberships in Proscion A/S and Intomics A/S. BG has received research grants from AbbVie, Bristol Myers-Squibb and Pfizer; OH has received research grants from AbbVie, Novartis and Pfizer, DVJ has received speaker and consultation fees from AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, AGL has received speaking and/or consulting fees from AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB; and CT has received consulting fees from Roche, speaker fees from Abbvie, Bristol Myers-Squibb, Nordic Drugs, Pfizer and Roche, and an unrestricted grant from Bristol Myers-Squibb. Publisher Copyright: ©Objectives To find causal genes for rheumatoid arthritis (RA) and its seropositive (RF and/or ACPA positive) and seronegative subsets. Methods We performed a genome-wide association study (GWAS) of 31 313 RA cases (68% seropositive) and ∼1 million controls from Northwestern Europe. We searched for causal genes outside the HLA-locus through effect on coding, mRNA expression in several tissues and/or levels of plasma proteins (SomaScan) and did network analysis (Qiagen). Results We found 25 sequence variants for RA overall, 33 for seropositive and 2 for seronegative RA, altogether 37 sequence variants at 34 non-HLA loci, of which 15 are novel. Genomic, transcriptomic and proteomic analysis of these yielded 25 causal genes in seropositive RA and additional two overall. Most encode proteins in the network of interferon-Alpha/beta and IL-12/23 that signal through the JAK/STAT-pathway. Highlighting those with largest effect on seropositive RA, a rare missense variant in STAT4 (rs140675301-A) that is independent of reported non-coding STAT4-variants, increases the risk of seropositive RA 2.27-fold (p=2.1×10-9), more than the rs2476601-A missense variant in PTPN22 (OR=1.59, p=1.3×10-160). STAT4 rs140675301-A replaces hydrophilic glutamic acid with hydrophobic valine (Glu128Val) in a conserved, surface-exposed loop. A stop-mutation (rs76428106-C) in FLT3 increases seropositive RA risk (OR=1.35, p=6.6×10-11). Independent missense variants in TYK2 (rs34536443-C, rs12720356-C, rs35018800-A, latter two novel) associate with decreased risk of seropositive RA (ORs=0.63-0.87, p=10-9-10-27) and decreased plasma levels of interferon-Alpha/beta receptor 1 that signals through TYK2/JAK1/STAT4. Conclusion Sequence variants pointing to causal genes in the JAK/STAT pathway have largest effect on seropositive RA, while associations with seronegative RA remain scarce.Peer reviewe
Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019
Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66–2•79) in 2000 to 2•31 (2•17–2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5–137•8) in 2000 to a peak of 139•6 million (133•0–146•9) in 2016. Global livebirths then declined to 135•3 million (127•2–144•1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2•1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27•1% (95% UI 26•4–27•8) of global livebirths. Global life expectancy at birth increased from 67•2 years (95% UI 66•8–67•6) in 2000 to 73•5 years (72•8–74•3) in 2019. The total number of deaths increased from 50•7 million (49•5–51•9) in 2000 to 56•5 million (53•7–59•2) in 2019. Under-5 deaths declined from 9•6 million (9•1–10•3) in 2000 to 5•0 million (4•3–6•0) in 2019. Global population increased by 25•7%, from 6•2 billion (6•0–6•3) in 2000 to 7•7 billion (7•5–8•0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58•6 years (56•1–60•8) in 2000 to 63•5 years (60•8–66•1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens
Global burden of 87 risk factors in 204 countries and territories, 1990�2019: a systematic analysis for the Global Burden of Disease Study 2019
Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk�outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk�outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk�outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95 uncertainty interval UI 9·51�12·1) deaths (19·2% 16·9�21·3 of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12�9·31) deaths (15·4% 14·6�16·2 of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253�350) DALYs (11·6% 10·3�13·1 of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0�9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10�24 years, alcohol use for those aged 25�49 years, and high systolic blood pressure for those aged 50�74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens
Photochromism of metal oxides—I the light sensitivity of MoO3 or WO3 coprecipitated with TiO2
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