Electroosmotic Flow of Viscoelastic Fluid Through a Constriction Microchannel

Electroosmotic flow (EOF) has been widely used in various biochemical microfluidic applications, many of which use viscoelastic non-Newtonian fluid. This study numerically investigates the EOF of viscoelastic fluid through a 10:1 constriction microfluidic channel connecting two reservoirs on either side. The flow is modelled by the Oldroyd-B (OB) model coupled with the Poisson–Boltzmann model. EOF of polyacrylamide (PAA) solution is studied as a function of the PAA concentration and the applied electric field. In contrast to steady EOF of Newtonian fluid, the EOF of PAA solution becomes unstable when the applied electric field (PAA concentration) exceeds a critical value for a fixed PAA concentration (electric field), and vortices form at the upstream of the constriction. EOF velocity of viscoelastic fluid becomes spatially and temporally dependent, and the velocity at the exit of the constriction microchannel is much higher than that at its entrance, which is in qualitative agreement with experimental observation from the literature. Under the same apparent viscosity, the time-averaged velocity of the viscoelastic fluid is lower than that of the Newtonian fluid

Topologically Optimized Electrodes for Electroosmotic Actuation

Electroosmosis is one of the most used actuation mechanisms for the microfluidics in the current active lab-on-chip devices. It is generated on the induced charged microchannel walls in contact with an electrolyte solution. Electrode distribution plays the key role on providing the external electric field for electroosmosis, and determines the performance of electroosmotic microfluidics. Therefore, this paper proposes a topology optimization approach for the electrodes of electroosmotic microfluidics, where the electrode layout on the microchannel wall can be determined to achieve designer desired microfluidic performance. This topology optimization is carried out by implementing the interpolation of electric insulation and electric potential on the specified walls of microchannels. To demonstrate the capability of this approach, one typical electroosmotic device, i.e., electroosmotic micropump, is modeled with several electrode layouts derived. And this approach permits potential applications in chemicals and biochemistry due to its outstanding capability on determining the performance of electrokinetic microfluidics

Evolution of the strange-metal scattering in momentum space of electron-doped La2−xCexCuO4{\rm La}_{2-x}{\rm Ce}_x{\rm CuO}_4

The linear-in-temperature resistivity is one of the important mysteries in the strange metal state of high-temperature cuprate superconductors. To uncover this anomalous property, the energy-momentum-dependent imaginary part of the self-energy Im ${\rm \Sigma}(k, \omega)$ holds the key information. Here we perform systematic doping, momentum, and temperature-dependent angle-resolved photoemission spectroscopy measurements of electron-doped cuprate ${\rm La}_{2-x}{\rm Ce}_x{\rm CuO}_4$ and extract the evolution of the strange metal scattering in momentum space. At low doping levels and low temperatures, Im ${\rm\Sigma} \propto \omega$ dependence dominates the whole momentum space. For high doping levels and high temperatures, Im ${\rm\Sigma} \propto \omega^2$ shows up, starting from the antinodal region. By comparing with the hole-doped cuprates ${\rm La}_{2-x}{\rm Sr}_x{\rm CuO}_4$ and ${\rm Bi}_2{\rm Sr}_2{\rm CaCu}_2{\rm O}_8$, we find a dichotomy of the scattering rate exists along the nodal and antinodal direction, which is ubiquitous in the cuprate family. Our work provides new insight into the strange metal state in cuprates

Dasatinib vs. imatinib in patients with chronic myeloid leukemia in chronic phase (CML-CP) who have not achieved an optimal response to 3 months of imatinib therapy: the DASCERN randomized study

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Coupling effects of Fe(II) and CaCO3 application on cadmium uptake and accumulation in rice (Oryza sativa L.)

Excessive cadmium (Cd) in rice, caused by Cd pollution of farmlands, poses a serious threat to human health. In this study, a pot experiment was conducted to investigate the effects of two doses of CaCO3 (Ca1: 2 g kg-1, Ca2: 10g kg-1), two types of Fe(II) (EDTA-Fe(II) and FeSO4; 0.14 g Fe kg-1), and their combined application on the uptake and accumulation of Cd in rice plants grown in Cd-contaminated acidic soil. The results revealed that FeSO4 significantly increased rice grain biomass, whereas the other treatments had no significant effects. Further, the addition of EDTA-Fe(II) or FeSO4 significantly enhanced iron plaque formation on the root surface and increased the Fe content in the rice plants and porewater. Compared to the control, CaCO3 addition weakened the formation of iron plaque and reduced the Fe concentration in the porewater and root tissue, stems and leaves, whereas the Fe concentration in brown rice and the husks remained unaffected. Combined application of CaCO3 and Fe(II) significantly promoted the formation of iron plaque and increased the Fe concentration in brown rice. However, the Cd concentration in the iron plaque was reduced by CaCO3 addition but increased by Fe(II) treatment. Notably, all treatments reduced the Cd concentration in all rice plant tissues. The application of Ca1, Ca2, EDTA-Fe(II), FeSO4, Ca1+EDTA-Fe(II), Ca1+FeSO4, Ca2+EDTA-Fe(II) and Ca2+FeSO4 significantly reduced the Cd concentration in brown rice by 69%, 63%, 51%, 60%, 46%, 39%, 38%, and 29%, respectively. These results indicate that the application of CaCO3, EDTA-Fe(II)/FeSO4, or their combination can effectively reduce Cd accumulation and translocation in rice plants

A juvenile mouse model of anti-N-methyl-D-aspartate receptor encephalitis by active immunization

IntroductionAnti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a common autoimmune encephalitis, and it is associated with psychosis, dyskinesia, and seizures. Anti-NMDAR encephalitis (NMDARE) in juveniles and adults presents different clinical charactreistics. However, the pathogenesis of juvenile anti-NMDAR encephalitis remains unclear, partly because of a lack of suitable animal models.MethodsWe developed a model of juvenile anti-NMDAR encephalitis using active immunization with an amino terminal domain peptide from the GluN1 subunit (GluN1356 − 385) against NMDARs in 3-week-old female C57BL/6J mice.ResultsImmunofluorescence staining suggested that autoantibody levels in the hippocampus increased, and HEK-293T cells staining identified the target of the autoantibodies as GluN1, suggesting that GluN1-specific immunoglobulin G was successfully induced. Behavior assessment showed that the mice suffered significant cognition impairment and sociability reduction, which is similar to what is observed in patients affected by anti-NMDAR encephalitis. The mice also exhibited impaired long-term potentiation in hippocampal CA1. Pilocarpine-induced epilepsy was more severe and had a longer duration, while no spontaneous seizures were observed.ConclusionThe juvenile mouse model for anti-NMDAR encephalitis is of great importance to investigate the pathological mechanism and therapeutic strategies for the disease, and could accelerate the study of autoimmune encephalitis

Search for the decay J/ψ→γ+invisibleJ/\psi\to\gamma + \rm {invisible}

We search for $J/\psi$ radiative decays into a weakly interacting neutral particle, namely an invisible particle, using the $J/\psi$ produced through the process $\psi(3686)\to\pi^+\pi^-J/\psi$ in a data sample of $(448.1\pm2.9)\times 10^6$ $\psi(3686)$ decays collected by the BESIII detector at BEPCII. No significant signal is observed. Using a modified frequentist method, upper limits on the branching fractions are set under different assumptions of invisible particle masses up to 1.2 $\mathrm{\ Ge\kern -0.1em V}/c^2$. The upper limit corresponding to an invisible particle with zero mass is 7.0$\times 10^{-7}$ at the 90\% confidence level

Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models

Deep learning recommendation models (DLRMs) are used across many business-critical services at Facebook and are the single largest AI application in terms of infrastructure demand in its data-centers. In this paper we discuss the SW/HW co-designed solution for high-performance distributed training of large-scale DLRMs. We introduce a high-performance scalable software stack based on PyTorch and pair it with the new evolution of Zion platform, namely ZionEX. We demonstrate the capability to train very large DLRMs with up to 12 Trillion parameters and show that we can attain 40X speedup in terms of time to solution over previous systems. We achieve this by (i) designing the ZionEX platform with dedicated scale-out network, provisioned with high bandwidth, optimal topology and efficient transport (ii) implementing an optimized PyTorch-based training stack supporting both model and data parallelism (iii) developing sharding algorithms capable of hierarchical partitioning of the embedding tables along row, column dimensions and load balancing them across multiple workers; (iv) adding high-performance core operators while retaining flexibility to support optimizers with fully deterministic updates (v) leveraging reduced precision communications, multi-level memory hierarchy (HBM+DDR+SSD) and pipelining. Furthermore, we develop and briefly comment on distributed data ingestion and other supporting services that are required for the robust and efficient end-to-end training in production environments

Search for the reaction e+e−→χcJπ+π− and a charmoniumlike structure decaying to χcJπ± between 4.18 and 4.60 GeV

We search for the process e+e-→χcJπ+π- (J=0, 1, 2) and for a charged charmoniumlike state in the χcJπ± subsystem. The search uses datasets collected with the BESIII detector at the BEPCII storage ring at center-of-mass energies between 4.18 GeV and 4.60 GeV. No significant χcJπ+π- signals are observed at any center-of-mass energy, and thus upper limits are provided which also serve as limits for a possible charmoniumlike structure in the invariant χcJπ± mass