Southern Ocean sea ice concentration budgets of five ocean-sea ice reanalyses

In this study, sea ice concentration (SIC) budgets were calculated for five ocean-sea ice reanalyses (CFSR, C-GLORSv7, GLORYS12v1, NEMO-EnKF and ORAS5), in the Southern Ocean and compared with observations. Benefiting from the assimilation of SIC, the reanalysis products display a realistic representation of sea ice extent as well as sea ice area. However, when applying the SIC budget diagnostics to decompose the changes in SIC into contributions from advection, divergence, thermodynamics, deformation and data assimilation, we find that both atmospheric and oceanic forcings and model configurations are significant contributors on the budget differences. For the CFSR, the primary source of deviation compared to other reanalyses is the stronger northward component of ice velocity, which results in stronger sea ice advection and divergence. Anomalous surface currents in the CFSR are proposed to be the main cause of the ice velocity anomaly. Furthermore, twice the mean ice thickness in the CFSR compared to other reanalyses makes it more susceptible to wind and oceanic stresses under Coriolis forces, exacerbating the northward drift of sea ice. The C-GLORSv7, GLORYS12v1 and NEMO-EnKF have some underestimation of the contribution of advection and divergence to changes in SIC in autumn, winter and spring compared to observations, but are more reasonable in summer. ORAS5, although using the same coupled model and atmospheric forcing as C-GLORSv7 and GLORYS12v1, has a more significant underestimation of advection and divergence to changes in SIC compared to these two reanalyses. The results of the SIC budgets of five ocean-sea ice reanalyses in the Southern Ocean suggest that future reanalyses should focus on improving the modelling of sea ice velocities, for example through assimilation of sea ice drift observations.Peer reviewe

Impurity band assisted carrier relaxation in Cr doped topological insulator Bi2Se3

Topological insulators (TIs) with unique band structures have wide application prospects in the fields of ultrafast optical and spintronic devices. The dynamics of hot carriers plays a key role in these TI-based devices. In this work, using the time- and angle-resolved photoemission spectroscopy technique, the relaxation process of the hot carriers in Cr-doped Bi2Se3 has been systematically studied since the ferromagnetic TI is one of the key building blocks for next-generation spintronics. It is found that electronic temperature (Te) and chemical potential (μ) decrease faster with the increase in the Cr doping concentration. Similarly, the lifetime (τ) of the excited electrons also decreases with more Cr doped into Bi2Se3. The results suggest a mechanism of impurity band-assisted carrier relaxation, where the impurity band within the bulk bandgap introduced by Cr doping provides significant recombination channels for the excited electrons. This work directly illustrates the dynamic process of the photon-generated carriers in Cr-doped Bi2Se3, which is expected to promote the applications of (Bi1-xCrx)2Se3 in photoelectric devices

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

CIP Method of Characteristics for the Solution of Tide Wave Equations

The CIP-MOC (Constrained Interpolation Profile/Method of Characteristics) is proposed to solve the tide wave equations with large time step size. The bottom topography and bottom friction, which are very important factor for the tidal wave model, are included to the equation of Riemann invariants as the source term. Numerical experiments demonstrate the good performance of the scheme. Compared to traditional semi-implicit (SI) finite difference scheme which is widely used in tidal wave simulation, CIP-MOC has better stability in simulating large gradient water surface change and has the ability to use much longer time step size under the premise of maintaining accuracy. Besides, numerical tests with reflective boundary conditions are carried out by CIP-MOC with large time step size and good results are obtained

Application status of risk assessment models for periodontal disease

Risk assessment models for periodontal disease provide dentists with a precise and consolidated evaluation of the prognosis of periodontitis, enabling the formulation of personalized treatment plans. Periodontal risk assessment systems have been widely applied in clinical practice and research. The application fields of periodontal risk assessment systems vary based on the distinctions between clinical periodontal parameters and risk factors. The assessment models listed below are commonly used in clinical practice, including the periodontal risk calculator (PRC), which is an individual-based periodontal risk assessment tool that collects both periodontal and systemic information for prediction; the periodontal assessment tool (PAT), which allows for quantitative differentiation of stages of periodontal disease; the periodontal risk assessment (PRA) and modified periodontal risk assessment (mPRA), which are easy to use; and the classification and regression trees (CART), which assess the periodontal prognosis based on a single affected tooth. Additionally, there are orthodontic-periodontal combined risk assessment systems and implant periapical risk assessment systems tailored for patients needing multidisciplinary treatment. This review focuses on the current application status of periodontal risk assessment systems

Model and Algorithm for Human Resource-Constrained R&D Program Scheduling Optimization

In resource-constrained project scheduling problems, renewable resources can be expanded into human resources with competency differences. A flexible resource-constrained project scheduling problem with competency differences is proposed, which is a practical extension close to Research and Development (R&D) program management, from the traditional multimode resource-constrained project scheduling problem. A parameter and estimation formula to measure staff competency is presented, and a mixed-integer programming model is established for the problem. The single-objective optimization problems of optimal duration and optimal cost are solved sequentially according to the biobjective importance. To solve the model, according to the assumptions and constraints of the model, the initial network diagram of multiple projects is determined, the enumeration algorithm satisfying constraint conditions provides the feasible solution sets, and the algorithm based on dynamic programming is designed for phased optimization. Experimental results show that the proposed optimization model considering competence differences can solve the problem effectively