Understanding fluid flow in granular materials is essential for many engineering applications, including petroleum recovery, groundwater movement and embankment stability. This study investigates the ...influence of particle angularity on permeability and fluid-particle interaction forces. A random shape generator based on spherical harmonics is used to create irregular-shaped particles with different levels of angularity. Granular packings of uniformly sized (monodisperse) particles are then constructed with the discrete element method (DEM), and pore-scale computational fluid dynamics (CFD) simulations are used to determine the flow fields and the resulted fluid-particle interaction. The more angular particle assemblies thus generated are less permeable, and their fluid-particle interaction forces are higher. However, angularity has limited influence on flow rate distribution and flow tortuosity. The influence of angularity is localized. An increase in angularity generates a larger variance of the pressure distribution on the particle surfaces, thus increasing the pressure component of the fluid-particle interaction force.
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•A framework to generate dense packings of angular particles is proposed.•Flow in packings of uniform angular particles is simulated with pore-scale CFD.•Influence of particle angularity on permeability is quantified.•Detailed statistical analysis is performed on fluid-particle interactions.•Particle-to-particle variance of fluid-particle interactions is analyzed.
As a result of rapid economic development, China is consuming roughly 500 million tons of oil. At present, it is the second-largest consumer of oil worldwide. Furthermore, the increase in its oil ...consumption has been the highest in the world for 13 consecutive years. The total mileage of domestic oil–gas transportation pipelines in China is 102,000 km, and these pipelines are hazardous. On November 22, 2013, an oil pipeline exploded in Qingdao City in Shandong Province, thus resulting in great personnel and property losses. This short communication briefly introduces this catastrophe, its causes, and some of the related emergency responses.
This study employs a numerical model to investigate the dispersion characteristics of human exhaled droplets in ventilation rooms. The numerical model is validated by two different experiments prior ...to the application for the studied cases. Some typical questions on studying dispersion of human exhaled droplets indoors are reviewed and numerical study using the normalized evaporation time and normalized gravitational sedimentation time was performed to obtain the answers. It was found that modeling the transient process from a droplet to a droplet nucleus due to evaporation can be neglected when the normalized evaporation time is <0.051. When the normalized gravitational sedimentation time is <0.005, the influence of ventilation rate could be neglected. However, the influence of ventilation pattern and initial exhaled velocity on the exhaled droplets dispersion is dominant as the airflow decides the droplets dispersion significantly. Besides, the influence of temperature and relative humidity on the dispersion of droplets can be neglected for the droplet with initial diameter <200 μm; while droplet nuclei size plays an important role only for the droplets with initial diameter within the range of 10 μm–100 μm.
Practical Implications
Dispersion of human exhaled droplets indoor is a key issue when evaluating human exposure to infectious droplets. Results from detailed numerical studies in this study reveal how the evaporation of droplets, ventilation rate, airflow pattern, initial exhaled velocity, and particle component decide the droplet dispersion indoor. The detailed analysis of these main influencing factors on droplet dispersion in ventilation rooms may help to guide (1) the selection of numerical approach, e.g., if the transient process from a droplet to a droplet nucleus due to evaporation should be incorporated to study droplet dispersion, and (2) the selection of ventilation system to minimize the spread of pathogen‐laden droplets in an indoor environment.
The non-receptor protein tyrosine phosphatase SHP2, encoded by PTPN11, has an important role in signal transduction downstream of growth factor receptor signalling and was the first reported ...oncogenic tyrosine phosphatase. Activating mutations of SHP2 have been associated with developmental pathologies such as Noonan syndrome and are found in multiple cancer types, including leukaemia, lung and breast cancer and neuroblastoma. SHP2 is ubiquitously expressed and regulates cell survival and proliferation primarily through activation of the RAS–ERK signalling pathway. It is also a key mediator of the programmed cell death 1 (PD-1) and B- and T-lymphocyte attenuator (BTLA) immune checkpoint pathways. Reduction of SHP2 activity suppresses tumour cell growth and is a potential target of cancer therapy. Here we report the discovery of a highly potent (IC50 = 0.071 μM), selective and orally bioavailable small-molecule SHP2 inhibitor, SHP099, that stabilizes SHP2 in an auto-inhibited conformation. SHP099 concurrently binds to the interface of the N-terminal SH2, C-terminal SH2, and protein tyrosine phosphatase domains, thus inhibiting SHP2 activity through an allosteric mechanism. SHP099 suppresses RAS–ERK signalling to inhibit the proliferation of receptor-tyrosine-kinase-driven human cancer cells in vitro and is efficacious in mouse tumour xenograft models. Together, these data demonstrate that pharmacological inhibition of SHP2 is a valid therapeutic approach for the treatment of cancers.
Polymer composites can offer a striking combination of properties when a gradient in electrical and thermal properties is generated. Functionally graded composites have shown great promise in ...electromagnetic interference (EMI) shielding, energy storage materials and sensors. This work presents a simple manufacturing route to develop graded microcellular structures, and thereby graded functionality, within polymer composite foams containing graphene nanoplatelets. The polymer/graphene composite foams were fabricated via supercritical fluid treatment in an injection molding machine followed by foaming through rapid depressurization in the mold cavity. The microstructural gradient developed within the composite foams, ranged from shear-induced elongated cells to more isotropic cellular structures over the length of the molded composites. This distinct microstructure offered graded electrical and thermal properties in the composites. The electrical conductivity, permittivity and thermal conductivity of the nanocomposite foams increased, respectively, up to 7 orders of magnitude, 1340% and 143% over the length of the composites. The specific EMI shielding raised up to 45% over the length of the nanocomposite foams. This study shows that foaming can pave the way for manufacture of functionally graded polymer composites for existing and emerging applications such as electromagnetic shielding, energy storage materials and sensors.
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A regional synthesis of organic carbon (OC) burial was conducted using a comprehensive data set to reveal some of the key drivers and human multi‐stressors controlling OC burial and transport in the ...Eastern China Marginal Seas (ECMS). Both OC and Δ14C values of suspended particulate matter (SPM) in the Changjiang River, were significantly higher than estuarine mobile‐muds, suggesting selective decay of more labile younger OC from both marine and terrestrial sources and the accumulation of more recalcitrant older OC. Some of this decay is likely to be associated with iron‐redox cycling in mobile‐muds. In contrast, OC, δ13C, and Δ14C values increased along the Yellow River sediment dispersal pathway, indicating adding of young marine OC and less decay of terrestrial OC. OC burial efficiency in mud areas in the Bohai Sea (∼43%) was significantly higher than those in the Yellow (∼11%) and East China Seas (∼16%), owing to rapid deposition. Burial flux of biospheric OC in mud areas of the ECMS is 7.00 ± 0.79 Mt yr−1, corresponding to atmospheric CO2 drawdown by silicate weathering in major river drainage basins of mainland China. The burial flux of petrogenic OC was estimated to be 0.81 ± 0.25 Mt yr−1, accounting for >1.9% of total burial in the global ocean. While the ECMS is an important OC sink, river damming has greatly reduced OC burial. Thus, the overall impact on anthropogenically altered river‐dominated marginal seas remains an important and rapidly changing component of the coastal ocean carbon budget.
Plain Language Summary
A comprehensive regional synthesis of organic carbon (OC) burial and its drivers, were investigated across the Eastern China Marginal Seas (ECMS). Variation of OC content and carbon isotopic composition from suspended particulate matter to mobile muds, in Changjiang sediment dispersal pathways, indicated selective decomposition of younger more labile marine and terrestrial OC, which resulted in the accumulation of older more recalcitrant OC. However, continuous adding of young marine OC, with little loss of terrestrial OC, in Yellow River sediment dispersal pathway, resulted in more recalcitrant terrestrial OC buried in this relatively more quiescent sedimentary regime. Burial efficiencies of OC from different sources in the ECMS were mainly controlled by OC reactivity and sediment mixing dynamics. The ECMS is an important sink of both petrogenic and biospheric OC over a timescale of ∼100 years. However, dam building in river basins has reduced sediment loads of the Changjiang and Yellow Rivers, which will continually decrease OC burial in the ECMS for decades to come. The changing residence time and redox pathways in these sedimentary regimes, partly controlled by increasing human stressors in the ECMS, are expected to have an important impact on rates of OC turnover and burial in marginal seas.
Key Points
Aging of terrestrial organic carbon in the Changjiang sedimentary system is more intense than that in the Yellow River sedimentary system
More efficient burial of organic carbon in the quiescent Bohai and Yellow Seas mud areas compared to East China Sea mobile muds
The Eastern China Marginal Seas are important OC sinks in terms of both petrogenic and biospheric OC burial fluxes
Abstract
The time-resolved magneto-optical (MO) Voigt effect can be utilized to study the Néel order dynamics in antiferromagnetic (AFM) materials, but it has been limited for collinear AFM spin ...configuration. Here, we have demonstrated that in Mn
3
Sn with an inverse triangular spin structure, the quench of AFM order by ultrafast laser pulses can result in a large Voigt effect modulation. The modulated Voigt angle is significantly larger than the polarization rotation due to the crystal-structure related linear dichroism effect and the modulated MO Kerr angle arising from the ferroic ordering of cluster magnetic octupole. The AFM order quench time shows negligible change with increasing temperature approaching the Néel temperature (
T
N
), in markedly contrast with the pronounced slowing-down demagnetization typically observed in conventional magnetic materials. This atypical behavior can be explained by the influence of weakened Dzyaloshinskii–Moriya interaction rather than the smaller exchange splitting on the diminished AFM order near
T
N
. The temperature-insensitive ultrafast spin manipulation can pave the way for high-speed spintronic devices either working at a wide range of temperature or demanding spin switching near
T
N
.
The Loess Plateau of China is the most concentrated and largest loess area on Earth. Shanxi Province lies in the eastern margin of the Loess Plateau and is one of the regions with the worst serious ...soil erosion and most fragile ecological environment in the world. On March 15, 2019, a landslide hit Xiangning County in Shanxi Province in northern China and resulted in heavy casualties. This paper mainly gives an introduction about the catastrophe, causes, and related emergency response.
From the nano-scale to the macro-scale, biological tissue is spatially heterogeneous. Even when tissue behavior is well understood, the exact subject specific spatial distribution of material ...properties is often unknown. And, when developing computational models of biological tissue, it is usually prohibitively computationally expensive to simulate every plausible spatial distribution of material properties for each problem of interest. Therefore, one of the major challenges in developing accurate computational models of biological tissue is capturing the potential effects of this spatial heterogeneity. Recently, machine learning based metamodels have gained popularity as a computationally tractable way to overcome this problem because they can make predictions based on a limited number of direct simulation runs. These metamodels are promising, but they often still require a high number of direct simulations to achieve an acceptable performance. Here we show that transfer learning, a strategy where knowledge gained while solving one problem is transferred to solving a different but related problem, can help overcome this limitation. Critically, transfer learning can be used to leverage both low-fidelity simulation data and simulation data that is the outcome of solving a different but related mechanical problem. In this paper, we extend Mechanical MNIST, our open source benchmark dataset of heterogeneous material undergoing large deformation, to include a selection of low-fidelity simulation results that require ≈ 2 − 4 orders of magnitude less CPU time to run. Then, we show that transferring the knowledge stored in metamodels trained on these low-fidelity simulation results can vastly improve the performance of metamodels used to predict the results of high-fidelity simulations. In the most dramatic examples, metamodels trained on 100 high fidelity simulations but pre-trained on 60,000 low-fidelity simulations achieves nearly the same test error as metamodels trained on 60,000 high-fidelity simulations (1 − 1.5% mean absolute percent error). In addition, we show that transfer learning is an effective method for leveraging data from different load cases, and for leveraging low-fidelity two-dimensional simulations to predict the outcomes of high-fidelity three-dimensional simulations. Looking forward, we anticipate that transfer learning will enable us to better capture the influence of tissue spatial heterogeneity on the mechanical behavior of biological materials across multiple different domains.