Developing an Unstructured Grid, Coupled Storm Surge, Wind Wave and Inundation Model for Super-regional Applications

During extreme weather conditions such as hurricanes and nor\u27easters, both the currents and wind waves generated by the atmospheric forces are important. Although they may act and dominate on different temporal and spatial scales, their interactions and combined effects are without doubt significant. In this dissertation, a major effort has been made to couple an unstructured grid circulation model SELFE (semi-implicit, Eulerian-Lagrangian finite element model) and the WWM II (Wind Wave model II). Moreover, this new coupled model system can be executed in a parallel computational environment. After the coupled model was successfully built, the model was verified with ideal test cases, either through comparisons with analytic solutions or with laboratory experiments. It was further validated by field-measured data during two hurricane events. The SELFE-WWM II model framework described above was used to participate in a SURA testbed project that was recently funded by the NOAA IOOS program. The purpose was to improve the storm surge and inundation modeling skill throughout the Gulf of Mexico as well as along the U.S. East Coast. The coupled tide, surge, and wind wave models in two and three dimensions were tested and compared systematically. Two well-known cases were investigated in detail. One was the event of Hurricane Ike of 2008 in the Gulf of Mexico and the other was the April Nor\u27easter of 2007 in the Gulf of Maine. For the Gulf of Mexico study, the key scientific issue is the origin of the forerunner. It has long been recognized that the forerunner plays an important role in generating large hurricane-induced storm surge in the Gulf of Mexico. The forerunner is a phenomenon whereby water level throughout the vast coastal region was elevated days before the hurricane makes landfall. The forerunner can contribute significantly to the total water level that results subsequently during the primary surge when the hurricane makes landfall. The 2008 Hurricane Ike, which devastated the Galveston Bay along the Texas Coast, is a good example: 1.4 m out of 4.5 m maximum surge was contributed by the forerunner in the Gulf of Mexico. The consensus from initial results of multiple models indicates that the forerunner occurred as a result of Ekman set-up along the broad Louisiana-Texas (LATEX) shelf by the shore-parallel wind field. By contrast, the primary surge was dominated by the low pressure and the maximum wind along a path perpendicular to the shore as the hurricane made landfall. It was found that the cross-shore Ekman set-up is highly sensitive to the bottom boundary layer (BBL) dynamics, especially to the drag coefficient. Given the fact that the Gulf of Mexico is known to be rich in fluid mud, and near-bed flows generally are very weak under fair-weather conditions, one plausible hypothesis is that, during the stormy condition, the suspended sediment-induced density stratification is likely to be ubiquitously present at the bottom boundary layer. A sediment-transport model and wave-current bottom boundary layer sub-model including the sediment-induced stratification effect were coupled to the unstructured grid circulation and wind wave model (SELFE-WWM II) for simulating the forerunner during Hurricane Ike. The model results demonstrate that the bottom boundary layer dynamics have a significant effect on the velocity veering as well as the Ekman set-up across the shelf. In the Gulf of Maine study, the high-resolution coupled SELFE-WWM II model was applied in the Scituate Harbor, a small, shallow coastal embayment, south of Boston. The key issue for the study was the recurring inundation related to the role played by wind waves during nor\u27easter events. With limited observation data in the Scituate, the model result from SELFE was compared with that from FVCOM. The major findings are summarized as follows: (1) wind waves generated by the nor\u27easter can profoundly affect the coastal current by increasing the magnitude and altering its direction, (2) while the mean water level inside the Harbor stays the same, the total transport across the harbor mouth increases when wind waves are included, and (3) the total inundation area, primarily in the northern and southern basins within the Harbor, does increase when wind waves are included. There is a question as to why the inclusion of the wind waves did not cause the mean water level to change inside the Harbor while the inundation area was increased. The plausible explanation is that this lack of impact could be that the Stokes transport was small and the increase of water level by the wave set-up was compensated by the expansion of the inundation area in the shallow region

Process Decoupling of Plasma Enhanced Synthesis of Chlorinated Polyvinyl Chloride (CPVC) Particles in a Circulating Fluidized Bed

Plasma enhanced synthesis of CPVC particles in a gas-solid plasma circulating fluidized bed reactor (PCFBR) is proposed as a novel CPVC synthesizing method. The chlorination process is decoupled into a fast initiation step in a plasma riser and a slow chlorination process in the accompanying bed. The CPVC product has good properties in terms of chlorine content and microstructure

Multi-Metric AutoRec for High Dimensional and Sparse User Behavior Data Prediction

User behavior data produced during interaction with massive items in the significant data era are generally heterogeneous and sparse, leaving the recommender system (RS) a large diversity of underlying patterns to excavate. Deep neural network-based models have reached the state-of-the-art benchmark of the RS owing to their fitting capabilities. However, prior works mainly focus on designing an intricate architecture with fixed loss function and regulation. These single-metric models provide limited performance when facing heterogeneous and sparse user behavior data. Motivated by this finding, we propose a multi-metric AutoRec (MMA) based on the representative AutoRec. The idea of the proposed MMA is mainly two-fold: 1) apply different $L_p$-norm on loss function and regularization to form different variant models in different metric spaces, and 2) aggregate these variant models. Thus, the proposed MMA enjoys the multi-metric orientation from a set of dispersed metric spaces, achieving a comprehensive representation of user data. Theoretical studies proved that the proposed MMA could attain performance improvement. The extensive experiment on five real-world datasets proves that MMA can outperform seven other state-of-the-art models in predicting unobserved user behavior data.Comment: 6 pages, 4 Table

苏州市三甲医院医患关系现状及其影响因素分析*

Objective: To investigate the relationship between doctors and patients in Suzhou, we focused on exploring the factors of doctor-patient communication, and strived to deepen the doctor-patient communication skills and knowledge. Method: Questionnaire survey was carried out in comprehensive tertiary-class hospitals in Suzhou , adopting the method of random sampling, respectively on patients and doctors. Results: 593 valid questionnaires were from both doctors and patients. The doctors thought that the current doctor-patient relationship  "good" and above accounted for 32% (31/98).At the meanwhile, in the patients, this proportion was 45% (223/495).There was statistically significance between the difference(P ＜0.05).Only 6% doctors thought that the communication between doctors and patients is not important; in the patients, the ratio was 10%. Among the doctors, the top three factors of doctor-patient communication were: lack of communication skills, too much tasks and not enough time and energy, not good attitude. Among patients, the top three factors were: incomprehension and distrust of the doctors, the poor understanding for medical knowledge and the low cultural level. Conclusion: In the first-class hospitals of Suzhou, the relationship between doctors and patients had a relatively good development trend. There were some problems in the communication between doctors and patients. We should enhance the doctor-patient communication, and build a harmonious doctor-patient relationship.目的  了解苏州市三甲医院的医患关系现状，探寻医患沟通的影响因素，以增进医患沟通的知识及技能。方法  在苏州市综合性“三甲”医院进行问卷调查，采用单纯随机抽样方法，分别就患方和医方进行调研。结果  收回医患双方有效问卷593份，有效率为94.6%。医方认为当前医患关系“比较好”及以上者占32%(31/98)，患方认为当前医患关系“比较好”及以上者占45%(223/495)，两者比较差异有统计学意义（P＜0.05）。医方有6%的人认为医患沟通不重要；在患方，这一比率为10%。就医方责任方面来说，影响医患沟通的前三位因素依次为：缺乏沟通技巧、工作任务繁重没有时间和精力、服务态度不好；就患者方面责任来说，影响医患沟通的前三位因素依次为：不理解不信任医护人员、对医疗知识不了解、文化层次相对较低。结论  苏州市3家三甲医院医患关系总体较好，医患沟通方面存在一定不足，应当切实增进医患沟通，构建和谐医患关系

Sorafenib for hepatocellular carcinoma patients beyond Milan criteria after orthotopic liver transplantation: a case control study

<p>Abstract</p> <p>Background</p> <p>Orthotopic liver transplantation (OLT) is one of the most effective treatments for patients with hepatocellular carcinoma (HCC) within the Milan criteria. However, for patients beyond these criteria, the recurrence rate is higher and the prognosis is worse. Sorafenib is the only drug showing survival benefits in advanced HCC patients; however, its role in patients beyond the Milan criteria after OLT remains unclear and requires further investigation.</p> <p>Methods</p> <p>As a case-control study, we retrospectively analyzed 17 Chinese patients beyond Milan criteria undergoing OLT for HCC. These patients were stratified into adjuvant (n = 5), palliative (n = 6), and control groups (n = 6).</p> <p>Results</p> <p>Nine of 11 patients who received sorafenib after OLT needed dose reduction due to more than grade 2 side effects. The disease-free survival rates for patients with or without adjuvant sorafenib were 100% versus 37.5% (p = 0.034) at 6 months, 66.7% versus 9.4% (p = 0.026) at 12 months, and 66.7% versus 0.0% (p = 0.011) at 18 months, respectively. The overall survival rates for patients in palliative and control groups were 66.7% versus 40.0% (p = 0.248) at 6 months, 66.7% versus 40.0% (p = 0.248) at 12 months, and 50.0% versus 20.0% (p = 0.17) at 18 months, respectively. Patients in the adjuvant group had better overall survival rates than those in the palliative and control groups (p = 0.031) at 24-month follow-up.</p> <p>Conclusions</p> <p>Adjuvant sorafenib could possibly extend both disease-free and overall survival for HCC patients beyond Milan criteria after OLT.</p

Monitoring a PGD solver for parametric power flow problems with goal-oriented error assessment

This is the peer reviewed version of the following article: [García-Blanco, R., Borzacchiello, D., Chinesta, F., and Diez, P. (2017) Monitoring a PGD solver for parametric power flow problems with goal-oriented error assessment. Int. J. Numer. Meth. Engng, 111: 529–552. doi: 10.1002/nme.5470], which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/nme.5470/full. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.The parametric analysis of electric grids requires carrying out a large number of Power Flow computations. The different parameters describe loading conditions and grid properties. In this framework, the Proper Generalized Decomposition (PGD) provides a numerical solution explicitly accounting for the parametric dependence. Once the PGD solution is available, exploring the multidimensional parametric space is computationally inexpensive. The aim of this paper is to provide tools to monitor the error associated with this significant computational gain and to guarantee the quality of the PGD solution. In this case, the PGD algorithm consists in three nested loops that correspond to 1) iterating algebraic solver, 2) number of terms in the separable greedy expansion and 3) the alternated directions for each term. In the proposed approach, the three loops are controlled by stopping criteria based on residual goal-oriented error estimates. This allows one for using only the computational resources necessary to achieve the accuracy prescribed by the end- user. The paper discusses how to compute the goal-oriented error estimates. This requires linearizing the error equation and the Quantity of Interest to derive an efficient error representation based on an adjoint problem. The efficiency of the proposed approach is demonstrated on benchmark problems.Peer ReviewedPostprint (author's final draft

A fully coupled 3D wave-current interaction model on unstructured grids

We present a new modeling system for wave-current interaction based on unstructured grids and thus suitable for very large-scale high-resolution multiscale studies. The coupling between the 3D current model (SELFE) and the 3rd generation spectral wave model (WWM-II) is done at the source code level and the two models share same sub-domains in the parallel MPI implementation in order to ensure parallel efficiency and avoid interpolation. We demonstrate the accuracy, efficiency, stability and robustness of the coupled SELFE-WWM-II model with a suite of progressively challenging benchmarks with analytical solution, laboratory data, and field data. The coupled model is shown to be able to capture important physics of the wave-current interaction under very different scales and environmental conditions with excellent convergence properties even in complicated test cases. The challenges in simulating the 3D wave-induced effects are highlighted as well, where more research is warranted