Phase transitions in a holographic s+p model with backreaction

In a previous paper (arXiv:1309.2204, JHEP 1311 (2013) 087), we present a holographic s+p superconductor model with a scalar triplet charged under an SU(2) gauge field in the bulk. We also study the competition and coexistence of the s-wave and p-wave orders in the probe limit. In this work we continue to study the model by considering the full back-reaction The model shows a rich phase structure and various condensate behaviors such as the "n-type" and "u-type" ones, which are also known as reentrant phase transitions in condensed matter physics. The phase transitions to the p-wave phase or s+p coexisting phase become first order in strong back-reaction cases. In these first order phase transitions, the free energy curve always forms a swallow tail shape, in which the unstable s+p solution can also play an important role. The phase diagrams of this model are given in terms of the dimension of the scalar order and the temperature in the cases of eight different values of the back reaction parameter, which show that the region for the s+p coexisting phase is enlarged with a small or medium back reaction parameter, but is reduced in the strong back-reaction cases.Comment: 15 pages(two-column), 9 figure

Optimization of microstructured hollow fiber design for membrane distillation applications using CFD modeling

This study explores the potential of microstructured hollow fiber designs to enhance process performance in a direct contact membrane distillation (DCMD) system. Hollow fibers with 10 different geometries (wavy- and gear-shaped cross sections) were evaluated. A series of three-dimensional computational fluid dynamic (CFD) simulations were carried out to investigate their capability in terms of depolarizing the buildup of liquid boundary layers, thus improving water productivity. Analyses of heat and mass transfer as well as the flow-field distribution in respective MD modules were obtained. It was found that the enhancement of the heat-transfer coefficients, hf, was up to 4.5-fold for a module with a wavy fiber design 07 and an approximate 5.5-fold hp increase for a gear-shaped fiber design. The average temperature polarization coefficient and mass flux Nm of the gear-shaped fiber module showed an improvement of 57% and 66%, respectively, over the original straight fiber design, followed by the wavy designs 07 and 08. The enhanced module performance was attributed to the improved hydrodynamics through the flow channels of various fiber geometries, which was confirmed by the visualization of flow-field and temperature profiles in CFD. Investigations of the fiber-length effect showed that the gear-shaped fiber modules exhibited the highest flux enhancement of 57–65% with the same length, compared to the modules with original straight and wavy fibers. In addition, the gear-shaped fiber module is very sensitive to feed velocity changes. Therefore, employing a smart microstructured design on the membrane surface would bring in a significant improvement under adverse flow conditions. Moreover, the computed water production and hydraulic energy consumption (HEC) among the modules with various fiber geometries were compared. With 1.9-fold surface area increase per unit volume, the gear-shaped fiber configuration had the highest water production but the lowest HEC, followed by wavy designs 07 and 08

Analysis of the effect of turbulence promoters in hollow fiber membrane distillation modules by computational fluid dynamic (CFD) simulations

As an extended exploration of process enhancing strategies, nine modified hollow fiber modules with various turbulence promoters were designed and modeled using a two dimensional computational fluid dynamic (CFD) heat-transfer model to investigate their potential in improving heat transfer and module performance for a shell-side feed direct contact membrane distillation (DCMD) system. With the aids of turbulence promoters, the feed heat-transfer coefficient hf of the modified modules generally showed much slower decreasing trends along the fiber length compared to the original (unmodified) module. A 6-fold hf enhancement could be achieved by a modified module with annular baffles and floating round spacers. Consistently, the temperature polarization coefficient (TPC) and mass flux distribution curves of these modified modules presented increasing trends and gained an optimal improvement of 57% and 74%, respectively. With the local flow fields and temperature profiles visualized in CFD simulations, it was confirmed that an appropriate selection of turbulence promoters could promote intense secondary flows and radial mixing to improve the shell-side hydrodynamics and enhance heat transfer. Moreover, an increase of flow velocity was used and compared as a conventional approach to improve hydrodynamics. It was found that a well-designed module could bring more significant enhancement for a liquid-boundary layer dominant heat-transfer process. Finally, the hydraulic energy consumption (HEC) caused by the insertion of turbulence promoters or the increase of circulating velocity was compared. Configurations with attached quad spacers or floating round spacers achieved a good compromise between enhanced permeation fluxes and modest HECs. Overall, the TPC decreases with increasing MD coefficient (C) values and operating temperatures; while the thermal efficiency increases dramatically with increasing C and operating temperatures in a MD system

Analysis of heat and mass transfer by CFD for performance enhancement in direct contact membrane distillation

A comprehensive analysis on the dominant effects for heat and mass transfer in the direct contact membrane distillation (DCMD) process has been performed with the aid of computational fluid dynamics (CFD) simulations for hollow fiber modules without and with annular baffles attached to the shell wall. Potential enhancement strategies under different circumstances have been investigated. Numerical simulations were carried out to investigate the effect of the MD intrinsic mass-transfer coefficient of the membrane (C) on the performance enhancement for both non-baffled and baffled modules. It was found that the temperature polarization coefficient (TPC) decreases significantly with increasing C value regardless of the existence of baffles, signifying a loss of overall driving force. However, the higher C compensated for this and the mass flux showed an increasing trend. A membrane with a lower C value was found to be less vulnerable to the TP effect. In this case, the introduction of turbulence aids such as baffles did not show substantial effect to improve system performance. In contrast, introducing baffles into the module can greatly enhance the mass flux and the TPC for a membrane with a high C value, where the main heat-transfer resistance is determined by the fluid side boundary layers. The effect of operating temperature on heat and mass transfer in the MD process was also studied with a membrane of a lower C value (2.0 × 10−7 kg m−2 s−1 Pa−1). Although the TPC generally decreased with increasing operating temperatures, the mass flux Nm increased significantly when operating temperature increased. A baffled module showed a more significant improvement than a non-baffle module at a higher temperature. Moreover, it was confirmed that higher operating temperatures are preferable for a substantial improvement in the heat/mass transfer as well as MD thermal efficiency, even with a relatively small transmembrane temperature difference of 10 K.Accepted versio

Zc(3900)Z_c(3900) as a DDˉ∗D\bar{D}^* molecule from the pole counting rule

A comprehensive study on the nature of the $Z_c(3900)$ resonant structure is carried out in this work. By constructing the pertinent effective Lagrangians and considering the important final-state-interaction effects, we first give a unified description to all the relevant experimental data available, including the $J/\psi\pi$ and $\pi\pi$ invariant mass distributions from the $e^+e^-\to J/\psi\pi\pi$ process, the $h_c\pi$ distribution from $e^+e^-\to h_c\pi\pi$ and also the $D\bar D^{*}$ spectrum in the $e^+e^-\to D\bar D^{*}\pi$ process. After fitting the unknown parameters to the previous data, we search the pole in the complex energy plane and find only one pole in the nearby energy region in different Riemann sheets. Therefore we conclude that $Z_c(3900)$ is of $D\bar D^*$ molecular nature, according to the pole counting rule method~[Nucl.~Phys.~A543, 632 (1992); Phys.~Rev.~D 35,~1633 (1987)]. We emphasize that the conclusion based upon the pole counting method is not trivial, since both the $D\bar D^{*}$ contact interactions and the explicit $Z_c$ exchanges are introduced in our analyses and they lead to the same conclusion.Comment: 21 pages, 9 figures. To match the published version in PRD. Additional discussion on the spectral density function is include

Machine Learning-Based Identification of Contaminated Images in Light Curves Data Preprocessing

Attitude is one of the crucial parameters for space objects and plays a vital role in collision prediction and debris removal. Analyzing light curves to determine attitude is the most commonly used method. In photometric observations, outliers may exist in the obtained light curves due to various reasons. Therefore, preprocessing is required to remove these outliers to obtain high quality light curves. Through statistical analysis, the reasons leading to outliers can be categorized into two main types: first, the brightness of the object significantly increases due to the passage of a star nearby, referred to as "stellar contamination," and second, the brightness markedly decreases due to cloudy cover, referred to as "cloudy contamination." Traditional approach of manually inspecting images for contamination is time-consuming and labor-intensive. However, We propose the utilization of machine learning methods as a substitute. Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) are employed to identify cases of stellar contamination and cloudy contamination, achieving F1 scores of 1.00 and 0.98 on test set, respectively. We also explored other machine learning methods such as Residual Network-18 (ResNet-18) and Light Gradient Boosting Machine (lightGBM), then conducted comparative analyses of the results.Comment: 12 pages, 15 figure

Efficient nano iron particle-labeling and noninvasive MR imaging of mouse bone marrow-derived endothelial progenitor cells

In this study, we sought to label mouse bone marrow-derived endothelial progenitor cells (EPCs) with Resovist® in vitro and to image them using 7.0 Tesla (T) magnetic resonance imaging (MRI). Mouse bone marrow-derived EPCs were cultured in endothelial basal medium with endothelial growth supplement. They were then characterized by immunocytochemistry, flow cytometry, and fluorescence quantitative polymerase chain reaction. Their functions were evaluated by measuring their uptake of 1,1-dioctadecyl-3,3,3,3-tetramethylindocarbocyanine-labeled acetylated low-density lipoprotein (Dil-Ac-LDL), binding of fluorine isothiocyanate (FITC)-labeled Ulex europaeus agglutinin (UEA), and formation of capillary-like networks. EPCs were labeled with superparamagnetic iron oxide (SPIO) and their proliferation was then assessed in a water-soluble tetrazolium (WST-8)-based cell proliferation assay. Spin echo sequence (multislice, multiecho [MSME]) and gradient echo sequence (2D-FLASH) were used to detect differences in the numbers of labeled cells by 7.0 T MRI. The results showed that the cultured cells were of “cobblestone”-like shape and positive for CD133, CD34, CD31, von Willebrand factor, kinase domain receptor, and CD45, but negative for F4/80. They could take up Dil-Ac-LDL, bind FITC-UEA, and form capillary-like networks on Matrigel in vitro. Prussian-blue staining demonstrated that the cells were efficiently labeled with SPIO. The single-cell T2* effect was more obvious in the 2D-FLASH sequence than in the MSME sequence. Further, there were almost no adverse effects on cell vitality and proliferation. In conclusion, mouse bone marrow-derived EPCs can be efficiently labeled with SPIO and imaged with 7.0-T MRI. They may thus be traced by MRI following transplantation for blood vessel disorders and cancer treatment