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Dam break caused by natural disasters, such as heavy rainfall, poses a potential threat to the safety of downstream structures. It brings damages to the structures with a strong nonlinearity and complex mechanism. Based on an in-house three-dimensional parallel model, the dynamic response process of the fluid-structure interaction caused by water disasters is investigated. The accelerated computing is achieved by the parallel algorithm, the free surface is captured by the volume of fluid method, and the fluid-structure interaction is dealt with by the immersed boundary method. While a quantitative forecast of the flow velocity and impact load during the dam-break flood is carried out, the reliability of the mathematical models in dealing with the fluid-structure interaction of water disasters is demonstrated by real-life cases and published data comparison. Dam break wave carries a large amount of kinetic and potential energies. The information of the whole flow field describes the disaster-causing flow patterns that change many times in a short period. Water advancing and falling make it easy to form scouring, and the impact load transmitted to the structure is apt to damage the engineering structure. This study of disaster-causing mechanism provides a scientific basis for disaster prevention and mitigation.

To solve the problem of resource shortage of ternary content addressable memory (TCAM) in the data plane of software defined network (SDN), a deep flow table aggregation method was proposed based on content entry trees, and a storage architecture of large-scale SDN flow tables named ADAFT was established. The architecture relaxed the Hamming distance requirement between ag-gregated flow entries, and a content entry tree was constructed to aggregate flow entries with different action sets, for significantly en-hancing the aggregation degree of flow tables. Then a dynamic limitation mechanism was designed for the height of content entry trees based on the awareness of TCAM load ratio, to minimize the lookup overhead of aggregated flow tables. Meanwhile, an adaptive selec-tion strategy of flow entry aggregation was presented in the light of TCAM load ratio, to strike a balance between the aggregation degree and lookup overhead of flow tables. Experimental results indicate that the ADAFT architecture achieves much higher flow table com-pression ratios up to 65.74% than existing methods.

In order to analyze and solve the erosion of the inside of nozzle caused by high - speed abrasive particles for improving the nozzle’s erosion and wear resistances and optimizing the structure design of ultra - high pressure jet nozzle, transient two - phase flow simulation, discrete phase simulation and visualization processing were used to simulate the erosion test. An axisymmetric solid - liquid two - phase flow analysis model was established for the inside of the nozzle, and the motion trajectory and acceleration process of the premixed abrasive water jet particles in the nozzle were simulated. Meanwhile, the maximum erosion rate of the nozzle inner wall was calculated, and the internal structure of the nozzle was optimized. Results showed that the garnet abrasive particles collided with the inner wall of the nozzle in the focusing section of the tungsten carbide nozzle and were reflected back to the axis to cause a focusing effect, the particle movement speed decreased and the inner wall was eroded. Furthermore, the maximum erosion rate was 1.9×10-6kg/(m2·s), which arose at the junction between the contraction section and focusing section of the nozzle. The second peak appeared in the middle and front of the focusing section, 20 mm away from the nozzle outlet, and the erosion rate was 1.7×10-6kg/(m2·s). According to the actual test life and failure criterion of nozzle, the calculated actual erosion rate of the nozzle was 1.078×10-6kg/(m2·s) and the correction coefficient of erosion rate was 0.567 4. Generally, the finite element analysis provided a basis for the optimization of the nozzle shape, which was beneficial for the improvement of the corrosion resistance of the nozzle.

Objective: The deterioration of acute decompensated heart failure (ADHF) is associated with abnormal activation of inflammatory pathways. This study aims to evaluate the impact and predictive value of a novel inflammatory marker, the systemic inflammation response index (SIRI), on short-term adverse outcomes in ADHF patients. Methods: This retrospective cohort study included 1,448 ADHF patients from Jiangxi Provincial People's Hospital between 2019-2022. SIRI was calculated using the formula: (neutrophil count × monocyte count)/lymphocyte count. In the correlation analysis, the study outcome was the 30-day mortality in patients with ADHF. Cox regression analysis and receiver operating characteristic curves were employed to investigate the risk assessment and predictive value of the SIRI for 30-day mortality in ADHF patients. Finally, we also exploratively assessed the mediation effect of nutritional factors (albumin: Alb, total cholesterol: TC, and lymphocyte count) on the association between SIRI and 30-day mortality in ADHF patients. Results: During the 30-day follow-up, 53 deaths were recorded. Mortality rates across SIRI tertiles were 0.62%, 2.07%, and 8.28%, respectively. There was a significant linear positive correlation between SIRI and 30-day mortality in ADHF patients (HR: 1.21; P for non-linearity = 0.113). Additionally, compared to ADHF patients with low SIRI, those with high SIRI had a 685% increased risk of 30-day mortality (HR: 7.85). Furthermore, receiver operating characteristic curve analysis demonstrated that SIRI significantly improved the predictive value for 30-day mortality in ADHF patients compared to neutrophil count, monocyte count, and lymphocyte count alone (AUC: neutrophil count 0.7633, monocyte count 0.6835, lymphocyte count 0.7356, SIRI 0.8237; all DeLong P <0.05). Mediation analyses indicated that, except for lymphocyte count, both Alb and TC had significant indirect effects on the SIRI-related 30-day mortality in ADHF patients; Specifically, Alb accounted for approximately 24.46% of the mediation effect, while TC accounted for approximately 13.35%. Conclusion: This cohort study based on a Southern Chinese population demonstrates a significant linear positive correlation between SIRI and 30-day mortality in ADHF patients, highlighting its substantial predictive value. Incorporating SIRI into the monitoring regimen of ADHF patients may be crucial for preventing further disease progression. [ABSTRACT FROM AUTHOR]

Aims: The value of the systemic immune‐inflammatory index (SII) in assessing adverse outcomes in various cardiovascular diseases has been extensively discussed. This study aims to evaluate the predictive value and risk stratification ability of SII for 30 day mortality in patients with acute decompensated heart failure (ADHF). Methods: This analysis included 1452 patients hospitalized for ADHF, all the participants being part of the China Jiangxi‐acute decompensated heart failure1 project. The risk stratification capability of the SII in patients with ADHF, as well as its correlation with the 30 day mortality risk among ADHF patients, was evaluated utilizing Kaplan–Meier survival analysis and multivariable Cox regression models. A restricted cubic spline was employed to model the dose–response relationship between the two, and the receiver operating characteristic curve was utilized to assess the predictive ability of SII for 30 day mortality. Results: The Kaplan–Meier analysis revealed that the risk of mortality in the high SII group (SII ≥ 980 × 109/L) was significantly greater than that in the low SII group (SII < 980 × 109/L, log‐rank P < 0.001). After adjusting for various confounding factors, a higher SII was associated with an increased risk of 30 day mortality in ADHF patients [hazard ratio (HR) = 2.03, 95% confidence interval (CI): 1.34–3.08]. Further restricted cubic spline analysis revealed a non‐linear dose–response relationship between the two (P for non‐linear = 0.006). Receiver operating characteristic analysis demonstrated that SII had a high accuracy in predicting 30 day mortality events in ADHF patients (AUC = 0.7479), and the optimal predictive threshold was calculated to be 980 × 109/L, a sensitivity of 0.7547 and a specificity of 0.7234. Conclusions: This study found a significant positive association between SII and 30 day all‐cause mortality in ADHF patients. We determined the SII cut‐off point for predicting 30 day all‐cause mortality in patients with ADHF to be 980 × 109/L. [ABSTRACT FROM AUTHOR]