An Efficient Two-grid Method for a Two-phase Mixed-domain Model of Polymer Exchange Membrane Fuel Cell

AbstractIn this paper, an efficientandfast numerical methodis studiedand implementedfora simplifiedtwo-phasemixed domain model of polymer exchange membrane fuel cell (PEMFC), which fully incorporates both the anode and cathode sides, including the conservation equations of mass, momentum, water vapor concentration, liquid water saturationandwater content.Theproposed numericalalgorithmisbasedonthetwo-grid discretization technique,the combined finite element-upwind finitevolume method and some other appropriate linearization schemes. The original nonlinear partial differential equations are only solved on the coarse grid while the fine grid approximation solution is obtained linearly. Therefore the computational time can be reduced tremendously compared with the traditional one-grid method. Numerical experiments of the two-grid method and conventional method for a two-phase mixed domain fuel cell model are carried out, showing that the presented method is effective and accurate for the numerical simulation of PEMFC

4,4′-Bipyridine–dimethyl­glyoxime (1/1)

In the title compound, C10H8N2·C4H8N2O2, both the dimethyl­glyoxime and the 4,4′-bipyridine mol­ecules have crystallographic C i symmetry. The mol­ecules stack along the a-axis direction with a dihedral angle of 20.4 (8)° between their planes. In the crystal, the components are linked by O—H⋯N hydrogen bonds into alternating chains along [120] and [10]

La Situación de La Relación de Género China en los Aspectos Sociales, Jurídicos y Políticos

Este estudio pretende analizar la situación de las relaciones de género China en los aspectos sociales, jurídicos y políticos, para comparar los cambios entre tradición y modernidad, presentar las diferencias y destacar las transformaciones de la concepción de género. Al final, se trata de dar algunas recomendaciones para perfeccionar la construcción y la estructura del sistema jurídico

YOLO-FaceV2: A Scale and Occlusion Aware Face Detector

In recent years, face detection algorithms based on deep learning have made great progress. These algorithms can be generally divided into two categories, i.e. two-stage detector like Faster R-CNN and one-stage detector like YOLO. Because of the better balance between accuracy and speed, one-stage detectors have been widely used in many applications. In this paper, we propose a real-time face detector based on the one-stage detector YOLOv5, named YOLO-FaceV2. We design a Receptive Field Enhancement module called RFE to enhance receptive field of small face, and use NWD Loss to make up for the sensitivity of IoU to the location deviation of tiny objects. For face occlusion, we present an attention module named SEAM and introduce Repulsion Loss to solve it. Moreover, we use a weight function Slide to solve the imbalance between easy and hard samples and use the information of the effective receptive field to design the anchor. The experimental results on WiderFace dataset show that our face detector outperforms YOLO and its variants can be find in all easy, medium and hard subsets. Source code in https://github.com/Krasjet-Yu/YOLO-FaceV

An Ensemble Learning Based Framework for Traditional Chinese Medicine Data Analysis with ICD-10 Labels

Objective. This study aims to establish a model to analyze clinical experience of TCM veteran doctors. We propose an ensemble learning based framework to analyze clinical records with ICD-10 labels information for effective diagnosis and acupoints recommendation. Methods. We propose an ensemble learning framework for the analysis task. A set of base learners composed of decision tree (DT) and support vector machine (SVM) are trained by bootstrapping the training dataset. The base learners are sorted by accuracy and diversity through nondominated sort (NDS) algorithm and combined through a deep ensemble learning strategy. Results. We evaluate the proposed method with comparison to two currently successful methods on a clinical diagnosis dataset with manually labeled ICD-10 information. ICD-10 label annotation and acupoints recommendation are evaluated for three methods. The proposed method achieves an accuracy rate of 88.2%  ±  2.8% measured by zero-one loss for the first evaluation session and 79.6%  ±  3.6% measured by Hamming loss, which are superior to the other two methods. Conclusion. The proposed ensemble model can effectively model the implied knowledge and experience in historic clinical data records. The computational cost of training a set of base learners is relatively low

Effect of aging on acute pancreatitis through gut microbiota

BackgroundCompared to younger people, older people have a higher risk and poorer prognosis of acute pancreatitis, but the effect of gut microbiota on acute pancreatitis is still unknown. We aim to investigate the effect of aging gut microbiota on acute pancreatitis and explore the potential mechanism of this phenomenon.MethodsEighteen fecal samples from healthy adult participants, including nine older and nine younger adults were collected. C57BL/6 mice were treated with antibiotics for fecal microbiota transplantation from older and younger participants. Acute pancreatitis was induced by cerulein and lipopolysaccharide in these mice. The effect of the aged gut microbiota was further tested via antibiotic treatment before or after acute pancreatitis induction.ResultsThe gut microbiota of older and younger adults differed greatly. Aged gut microbiota exacerbated acute pancreatitis during both the early and recovery stages. At the same time, the mRNA expression of multiple antimicrobial peptides in the pancreas and ileum declined in the older group. Antibiotic treatment before acute pancreatitis could remove the effect of aging gut microbiota, but antibiotic treatment after acute pancreatitis could not.ConclusionAging can affect acute pancreatitis through gut microbiota which characterizes the deletion of multiple types of non-dominant species. This change in gut microbiota may potentially regulate antimicrobial peptides in the early and recovery stages. The level of antimicrobial peptides has negative correlations with a more severe phenotype

MiR-29a Knockout Aggravates Neurological Damage by Pre-polarizing M1 Microglia in Experimental Rat Models of Acute Stroke

ObjectiveBy exploring the effects of miR-29a-5p knockout on neurological damage after acute ischemic stroke, we aim to deepen understanding of the molecular mechanisms of post-ischemic injury and thus provide new ideas for the treatment of ischemic brain injury.MethodsmiR-29a-5p knockout rats and wild-type SD rats were subjected to transient middle cerebral artery occlusion (MCAO). miR-29a levels in plasma, cortex, and basal ganglia of ischemic rats, and in plasma and neutrophils of ischemic stroke patients, as well as hypoxic glial cells were detected by real-time PCR. The infarct volume was detected by TTC staining and the activation of astrocytes and microglia was detected by western blotting.ResultsThe expression of miR-29a-5p was decreased in parallel in blood and brain tissue of rat MCAO models. Besides, miR-29a-5p levels were reduced in the peripheral blood of acute stroke patients. Knockout of miR-29a enhanced infarct volume of the MCAO rat model, and miR-29a knockout showed M1 polarization of microglia in the MCAO rat brain. miR-29a knockout in rats after MCAO promoted astrocyte proliferation and increased glutamate release.ConclusionKnockout of miR-29a in rats promoted M1 microglial polarization and increased glutamate release, thereby aggravating neurological damage in experimental stroke rat models

Does Serum Uric Acid Mediate Relation between Healthy Lifestyle and Components of Metabolic Syndrome?

A healthy lifestyle is related to metabolic syndrome (MetS), but the mechanism is not fully understood. This study aimed to examine the association of components of MetS with lifestyle in a Chinese population and potential mediation role of serum uric acid (SUA) in the association between lifestyle behaviors and risk of components of MetS. Data were derived from a baseline survey of the Shaanxi urban cohort in the Regional Ethnic Cohort Study in northwest China. The relationship between components of MetS, healthy lifestyle score (HLS), and SUA was investigated by logistic or linear regression. A counterfactual-based mediation analysis was performed to ascertain whether and to what extent SUA mediated the total effect of HLS on components of MetS. Compared to those with 1 or less low-risk lifestyle factors, participants with 4–5 factors had 43.6% lower risk of impaired glucose tolerance (OR = 0.564; 95%CI: 0.408~0.778), 60.8% reduction in risk of high blood pressure (OR = 0.392; 95%CI: 0.321~0.478), 69.4% reduction in risk of hypertriglyceridemia (OR = 0.306; 95%CI: 0.252~0.372), and 47.3% lower risk of low levels of HDL cholesterol (OR = 0.527; 95%CI: 0.434~0.641). SUA mediated 2.95% (95%CI: 1.81~6.16%) of the total effect of HLS on impaired glucose tolerance, 14.68% (95%CI: 12.04~18.85%) on high blood pressure, 17.29% (95%CI: 15.01~20.5%) on hypertriglyceridemia, and 12.83% (95%CI: 10.22~17.48%) on low levels of HDL cholesterol. Increased HLS tends to reduce risk of components of MetS partly by decreasing the SUA level, which could be an important mechanism by which lifestyle influences MetS

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve