Dispersed two-phase flows are abundant in nature and play an important role in a large number of engineering and environmental applications. In a Lagrangian--Eulerian modeling approach, the motion of ...particles in a carrier fluid is accounted for through force laws. In this thesis, our focus is to extend the current capability in predicting drag and lift forces on a particle, primarily when located near wall vicinity, and to gain a better understanding of the interactions between a particle and wall turbulence around a single particle in the context of finite particle Reynolds number. The investigations are performed through direct numerical simulation (DNS) using a highly accurate spectral element method. Firstly, we study a finite-sized particle translating parallel to a wall in an otherwise stagnant fluid. This analysis addresses mainly the pure wall effect on the particle motion. The particle location is systematically varied from fairly close to the wall to sufficiently far away from the wall. The results show that lift coefficient follows a down-and-up behavior in contrast to the anticipated monotonically decreasing trend. Secondly, we investigate a finite-sized particle in a wall-bounded linear shear flow. In addition to varying the particle location as in the previous part, we also present results for the case of a particle nearly sitting on the wall. Correlations for the lift and drag coefficients are proposed. Thirdly, we investigate the interaction of a finite-sized particle embedded in a turbulent channel flow. Particles of various sizes have been located at two specific wall-normal locations, the buffer region and the channel center. Near-wall region mechanisms are observed consisting of such different events as bursting, sweep, and ejection, whereas channel center can be considered as nearly isotropic turbulence. We compare the computed forces with the standard force formulations and analyze possible mechanisms for their deviations. Further, we analyze the back effects that the particle imposes on the turbulence field—in particular, the wake responses to the ambient turbulence and the turbulence modulation by the particle for the energy and wall shear stress.
There is a mutual influence between COVID-19, diabetes ketoacidosis, and acute pancreatitis, with clinical manifestations overlapping each other, which can lead to misdiagnosis and delayed treatment ...that could aggravate the condition and affect the prognosis. COVID-19-induced diabetes ketoacidosis and acute pancreatitis are extremely rare, with only four case reports in adults and no cases yet reported in children.
We reported a case of acute pancreatitis associated with diabetic ketoacidosis in a 12-year-old female child post novel coronavirus infection. The patient presented with vomiting, abdominal pain, shortness of breath, and confusion. Laboratory findings showed elevated levels of inflammatory markers, hypertriglyceridemia, and high blood glucose. The patient was treated with fluid resuscitation, insulin, anti-infection treatments, somatostatin, omeprazole, low-molecular-weight heparin, and nutritional support. Blood purification was administered to remove inflammatory mediators. The patient's symptoms improved, and blood glucose levels stabilized after 20 days of admission.
The case highlights the need for greater awareness and understanding of the interrelated and mutually promoting conditions of COVID-19, diabetes ketoacidosis, and acute pancreatitis among clinicians, to reduce misdiagnosis and missed diagnoses.
Southern China is a major grain-producing area, but has been suffering from increasingly serious droughts caused by global warming. As a result, crop losses have become serious. To provide insights ...into these losses, we obtained data to support a systematic and comprehensive analysis of how agricultural drought has caused crop losses from 1961 to 2011 and of the relationship between these changes and the climatic factors responsible for the losses. We found an obvious increase in the loss of crops due to agricultural drought in southern China, with the greatest increase in crop loss in the southwest and smaller increases in the south and southeast. Moreover, because each crop growth stage is affected differently by climatic factors and because the values of these factors show an uneven seasonal distribution, the losses were greatest when changes in various climatic factors occurred during key crop developmental periods. The fittings of the relationship between crop loss and various climatic factors was often strongest based on data from key developmental periods rather than based on data for the whole year. In addition, we found improved prediction of losses using multiple regression, and developed a model for assessing crop losses. Our results provide a scientific reference for developing methods to evaluate the losses caused by agricultural drought in southern China.
The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) causes severe acute respiratory failure and considerable extrapumonary organ dysfuction with substantial high mortality. For the limited ...number of autopsy reports, small animal models are urgently needed to study the mechanisms of MERS-CoV infection and pathogenesis of the disease and to evaluate the efficacy of therapeutics against MERS-CoV infection. In this study, we developed a transgenic mouse model globally expressing codon-optimized human dipeptidyl peptidase 4 (hDPP4), the receptor for MERS-CoV. After intranasal inoculation with MERS-CoV, the mice rapidly developed severe pneumonia and multi-organ damage, with viral replication being detected in the lungs on day 5 and in the lungs, kidneys and brains on day 9 post-infection. In addition, the mice exhibited systemic inflammation with mild to severe pneumonia accompanied by the injury of liver, kidney and spleen with neutrophil and macrophage infiltration. Importantly, the mice exhibited symptoms of paralysis with high viral burden and viral positive neurons on day 9. Taken together, this study characterizes the tropism of MERS-CoV upon infection. Importantly, this hDPP4-expressing transgenic mouse model will be applicable for studying the pathogenesis of MERS-CoV infection and investigating the efficacy of vaccines and antiviral agents designed to combat MERS-CoV infection.
Under the guidance of the new policy of urban renewal, the concept of community garden is gaining popularity in theory and practice in today's increasingly tense urban environment. This paper is a ...review of the research on community gardens. Based on the visualization system of CiteSpace software, it focuses on the analysis of 42 important studies In China and abroad, covering their keywords, research methodology and main findings. Through analysis, this study mainly studies the current knowledge structure, hot topics and research trends in the field of community garden, so as to provide reference for the theoretical research and design practice applied to the field of community garden, and inspire the design of community gardens according to different sites, audiences, scenarios and needs. This study shows that designers and researchers are realizing the importance of promoting civic participation to achieve design optimization and promoting community support for urban landscape systems. Public participation can help designers consider regional culture, religion, history and human needs in a comprehensive manner. At the same time, public participation and gatherings can also promote community identity and sustainable development.
The environment for acquiring microseismic signals is always filled with complex noise, leading to the presence of abundant invalid signals in the collected data and greatly disturbing effective ...microseismic signals. Regarding the identification of effective microseismic signals with a low signal-to-noise ratio, a method for identifying effective microseismic signals in a strong-noise environment by using the variational mode decomposition (VMD) and genetic algorithm (GA)-based optimized support vector machine (SVM) model is proposed. Microseismic signals with a low signal-to-noise ratio are adaptively decomposed into several intrinsic mode functions (IMFs) by using VMD. The characteristics of such IMFs are extracted and used as a basis for the determination of signal validity. The SVM model is optimized by utilizing GA to obtain the optimal penalty factor c and the kernel function parameter g. The availability of IMF components is judged by the optimized SVM model, based on which the effectiveness of microseismic signals is further identified. By applying the algorithm to the microseismic signals with artificially added noise, the effective microseismic signals and ineffective noise are discriminated, verifying the feasibility of the algorithm. After processing the microseismic records collected in the field, we effectively judge the effectiveness of microseismic signals, suppress the interfering noise in the data and greatly improve the signal-to-noise ratio of the seismic records. The results show that the method for identifying effective microseismic signals based on VMD and GA-SVM can well discriminate between effective and ineffective microseismic signals, which is very significant and provides technical support for microseismic monitoring in a strong-noise environment.
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