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How to efficiently solve the discrete-memory-accessing problem of unstructed-grid is one of the hot-spot issues in the field of parallel algorithms and application in scientific and engineering computing.The distributed block reconnection optimization algorithm,which is designed on the basis of domestic Sunway heterogeneous many-core architecture,can maintain high computing performance when solving the problem of unstructured sparsity in applications.After deeply analyzing the on-chip communication mechanism of the many-core architecture,an efficient message grouping strategy is designed to improve the bandwidth utilization of on-chip array on the slave core.At the same time,a barrier-free data distribution algorithm is combined to give full play to the network perfor-mance of the domestic heterogeneous many-core architecture.Through the establishment of perfor-mance models and experimental analysis,the average memory bandwidth of the proposed algorithm can reach more than 70% of the theoretical value under different memory access situations.Compared with the serial algorithm on the master core,it has an ave-rage of 10 times and a maximum of 45 times performance acceleration.At the same time,the universal applicability of the algorithm is proved by application tests in different fields.

Developing effective and stable catalytic interfaces in the medium temperature region is a practical route to replace the existing water gas shift (WGS) process. Here the authors designed a composite Ni-Y2O3 catalyst achieving the highest WGS activity for Ni based catalysts.

BackgroundCancer has become a leading cause of death for Chinese children, imposing a great economic burden on society and families. Therefore, it is extremely important to understand the epidemicsizes and trends of childhood malignancies.ObjectiveTo analyze the epidemiological characteristics of childhood cancer in China from 2005 to 2015, so as to provide evidence for the formulation of prevention and control strategies and rational allocation of health resources concerning childhood cancer in China.MethodsData regarding cancer incidence and mortality in Chinese 0-14 years old children during 2008 to 2018 were collected from the Chinese Cancer Registry Annual Report. Age-standardized incidence and mortality rates were computed by dividing the number of child deaths caused by cancer by the fifth national population census (2010) and multiplying by 100 000. Joinpoint Regression Program was used to compute the annual percentage change (APC) to analyze the temporal trends of annual child cancer incidence and mortality rates.Results(1) During the period of 2005 to 2015, the median crude incidence rate and median crude mortality rate of cancer in 0-14 years old were 9.35/100 000, and 3.91/100 000, respectively. The median crude incidence and median crude mortality rate of 0-4 years old group were higher than those of 5-9 years old group and 10-14 years old group (P

Gasoline/hydrogenated catalytic biodiesel blending fuel has been proposed to improve gasoline ignitability and combustion stability in gasoline compression ignition (GCI) engines. Comprehensive numerical simulation in GCI engine models provides useful information that can be used for efficient utilization of this promising fuel. However, the use of detailed chemical kinetic mechanisms is unfeasible. In this work, a reduced mechanism was developed for a blended fuel of gasoline/hydrogenated catalytic biodiesel (HCB). Based on the fuel composition and physicochemical properties, n-hexadecane was proposed as a surrogate fuel for HCB. Three reduction methods with error propagation extension to directed relation graph, full species sensitivity analysis and quasi steady state approximation were utilized to reduce the detailed mechanism of n-hexadecane. The reduced mechanism was coupled with a gasoline surrogate mechanism to construct gasoline/HCB surrogate mechanism. Reaction path analysis and sensitivity analyses were performed to optimize the reaction kinetic constants of several reactions. The final reduced mechanism included 82 species and 370 reactions, and was able to accurately predict various combustion characteristics such as ignition delay times, laminar flame speed and species concentrations. The reduced mechanism is also applied to 3D computational fluid dynamics to validate the prediction ability of the direct injection compression ignition engine, and the predicted results show good agreement with experimental data. The overall results suggest that the current reduced mechanism could be applied for predicting gasoline/HCB mixture in practical engine simulations. [ABSTRACT FROM AUTHOR]

The electrochemical removal of abundant and toxic H2S from highly sour reservoirs has emerged as a promising method for hydrogen production and desulfurization. Nevertheless, the ineffectiveness and instability of current electrocatalysts have impeded further utilization of H2S. In this communication, we introduce a robust array of Fe2NiSe4 nanowires synthesized in situ on a FeNi3 foam (Fe2NiSe4/FeNi3) via hydrothermal treatment. This array acts as an active electrocatalyst for ambient H2S splitting. It offers numerous exposed active sites and a rapid electron transport channel, significantly enhancing charge transport rates. As an electrode material, Fe2NiSe4/FeNi3 displays remarkable electrocatalytic efficiency for both sulfide oxidation and hydrogen evolution reactions. This bifunctional electrode achieves efficient electrochemical H2S splitting at a low potential of 440 mV to reach a current density of 100 mA∙cm−2, with a faradaic efficiency for hydrogen production of approximately 98%. These findings highlight its significant potential for desulfurization and energy-efficient hydrogen generation. [ABSTRACT FROM AUTHOR]

Severe ice accretion on transmission lines can disrupt electrical grids and compromise the stability of power systems. Consequently, precise prediction of ice coating on transmission lines is vital for guiding their operation and maintenance. Traditional single-model icing prediction methods often exhibit limited accuracy under varying environmental conditions and fail to yield highly accurate predictions. We propose a multi-scenario, two-stage adaptive ensemble strategy (MTAES) for ice coating prediction to address this issue. A combined clustering approach is employed to refine the division of ice weather scenarios, segmenting historical samples into multiple scenarios. Within each scenario, the bagging approach generates multiple training subsets, with the extreme learning machine (ELM) used to build diverse models. Subsequently, a two-stage adaptive weight allocation mechanism is introduced. This mechanism calculates the distance from the scenario cluster centers and the prediction error of similar samples in the validation set for each test sample. Weights are dynamically allocated based on these data, leading to the final output results through an adaptive ensemble from the base model repository. The experimental results show that the model is significantly better than traditional models in predicting ice thickness. Key indicators of RMSE, MAE, and  R 2  reach 0.675, 0.522, and 83.2%, respectively, verifying the effectiveness of multi-scene partitioning and adaptive weighting methods in improving the accuracy of ice cover prediction. [ABSTRACT FROM AUTHOR]

Background and Objective: Although growing evidence indicates that non-alcoholic fatty liver disease is related to diabetic retinopathy (DR), research results significantly vary. Therefore, we conducted a meta-analysis to assess the association between the progression of non-alcoholic fatty liver disease and the onset of DR.Methods: PubMed, Embase, and Cochrane databases were searched until 7 November 2021. Combined odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association.Results: We identified 18 studies involving 12,757 patients. The pooled effect assessment showed that liver fibrosis was positively correlated with DR (OR = 1.69, 95%CI 1.30–2.20; p < 0.0001); non-alcoholic fatty liver disease was not associated with the risk of DR (OR = 1.15, 95%CI 0.75-1.76; p = 0.51); non-alcoholic fatty liver disease was positively correlated with DR in patients with type 1 diabetes (OR = 2.96, 95%CI 1.48–5.94; p = 0.002). In patients with type 2 diabetes, there was no association between non-alcoholic fatty liver disease and DR (OR = 0.92, 95%CI 0.59–1.43; p = 0.70). Subgroup analysis showed no correlation in both Asian and Caucasian races.Conclusion: There is a significant correlation between liver fibrosis and DR. This suggests that the ocular examination of DR could be helpful in predicting whether patients with non-alcoholic fatty liver disease would progress to liver fibrosis.

IntroductionDiabetes mellitus (DM) and diabetic retinopathy (DR) increase the global burden. Since their pathogenesis is complex, it is necessary to use the biopsychosocial model to discover the most effective strategies. The study is aimed to investigate the psycho-behavioral factors of DR and confirm the discrepancies from previous studies.Research design and methodsThe study comprised seven cycles of cross-sectional data of the National Health and Nutrition Examination Survey (NHANES) from 2005–2006 to 2017–2018. Samples of DM were selected from this complex multi-stage probability sample and divided into the non-DR and DR groups, where 4,426 samples represented 18,990,825 individuals after weighting. This study comprehensively explored the biological, social, and psychological risk factors of DR, among which the biological factors included blood pressure, blood routine, HbA1c%, blood glucose, the duration of DM, family history, comorbidities, and treatment methods. Social aspects include gender, education, income, insurance, smoking, drinking, sleep habits, and recreational activities. The Patient Health Questionnaire-9 (PHQ-9) was used to assess the psychological state. Taylor series regression was used to examine the connection between factors and DR.ResultsMen accounted for 55.5% of the DR group (P = 0.0174). Lymphocyte count, insulin treatment, heart failure, stroke, liver condition, and renal failure showed significant differences in DR (P < 0.05). The incidence of depression in DR was 40.5%. Mild to moderate depression [odds ratio was associated with DR [(OR) = 1.37, 95% confidence interval (CI): 1.06–1.79], but there was no statistical difference in severe depression (OR = 1.34, 95% CI: 0.83–2.17). Although ≤ 6 h of sleep was associated with DR (OR = 1.38, 95% CI: 1.01–1.88), we found no statistical differences in alcohol consumption, recreational activities, or sedentary time between the two groups in our current study (P > 0.05).ConclusionsThe biological risk factors of DR are significant. It showed that stroke is associated with DR, and retinal exams have the potential value as a screening tool for the brain. Besides, psycho-behavioral risk factors of DR should also be paid attention. Our study highlights that mild and moderate depression and ≤6 h of sleep are distinguishably associated with DM complicated with DR. It indicates that psycho-behavioral risk factors confer a vital influence on diabetic health care and DR.