Phytochemical Profiles and Antioxidant and Antimicrobial Activities of the Leaves of Zanthoxylum bungeanum

The ethanol crude extracts (ECE) and their subfractions from Zanthoxylum bungeanum leaves were prepared and their phytochemical profiles and antioxidant and antimicrobial activities were investigated. Moreover, the effective HPLC procedure for simultaneous quantification of twelve compounds in Z. bungeanum leaves was established. The correlation between the phytochemicals and antioxidant activity was also discussed. The ethyl acetate fraction (EAF) had the highest total phenolic (97.29 mmol GAE/100 g) and flavonoid content (67.93 mmol QE/100 g), while the greatest total alkaloid content (4.39 mmol GAE/100 g) was observed in the chloroform fraction (CF). Twelve compounds were quantified by RP-HPLC assay. EAF exhibited the highest content of quercitrin, kaempferol-3-rhamnoside, quercetin, sesamin, and nitidine chloride (125.21, 54.95, 24.36, 26.24, and 0.20 mg/g); acetone fraction (AF) contained the highest content of chlorogenic acid, rutin, hyperoside, and trifolin (5.87, 29.94, 98.33, and 31.24 mg/g), while kaempferol-3-rhamnoside, xanthyletin, and sesamin were rich in CF. EAF and AF exhibited significant DPPH, ABTS radical scavenging abilities and reducing power (FRAP), whereas CF exhibited significant antifungal activity. Moreover, EAF also showed stronger antibacterial activity. In conclusion, Z. bungeanum leaves have health benefits when consumed and could be served as an accessible source for production of functional food ingredients and medicinal exploration

Elevated visceral adiposity index is associated with increased stroke prevalence and earlier age at first stroke onset: Based on a national cross-sectional study

ObjectiveThe purpose of this study was to examine the association between the VAI (visceral adiposity index) and stroke prevalence and age at stroke in US adults.MethodsWe examined the association between VAI and stroke prevalence and age at stroke using logistic regression, subgroup analysis, and dose-response curves using participants from the National Health and Nutrition Examination Survey (NHANES) database from 2007-2018.ResultsThis study ultimately included 29,337 participants aged >20 years, of whom 1022 self-reported a history of stroke, and after adjusting for all confounders, each unit increase in corrected VAI was associated with a 12% increase in the prevalence of stroke (OR= 1.12, 95% CI: 1.01, 1.24) along with an earlier age at stroke 1.64 years (β= -1.64, 95% CI: -2.84, -0.45), stratified analysis showed that the prevalence of stroke was 20% higher in the female group (OR= 1.20, 95% CI: 1.04, 1.39), black group (OR= 1.22, 95% CI: 1.01, 1.48), age ≤60 years group (OR= 1.25, 95% CI: 1.05, 1.48), hypertensive group (OR=1.15, 95% CI:1.01, 1.31), and diabetic group (OR=1.23, 95% CI:1.02, 1.48) VAI increase was positively correlated with stroke prevalence increase. The dose-response curves showed a positive linear correlation between increased VAI and stroke prevalence, while a negative linear correlation was observed between increased VAI and age at stroke.ConclusionAlthough a causal relationship cannot be proven, higher VAI was positively associated with stroke prevalence and can lead to earlier stroke onset

Massive Star-Forming Galaxies Have Converted Most of Their Halo Gas into Stars

In the local Universe, the efficiency for converting baryonic gas into stars is very low. In dark matter halos where galaxies form and evolve, the average efficiency varies with galaxy stellar mass and has a maximum of about twenty percent for Milky-Way-like galaxies. The low efficiency at higher mass is believed to be produced by some quenching processes, such as the feedback from active galactic nuclei. We perform an analysis of weak lensing and satellite kinematics for SDSS central galaxies. Our results reveal that the efficiency is much higher, more than sixty percent, for a large population of massive star-forming galaxies around $10^{11}M_{\odot}$. This suggests that these galaxies acquired most of the gas in their halos and converted it into stars without being affected significantly by quenching processes. This population of galaxies is not reproduced in current galaxy formation models, indicating that our understanding of galaxy formation is incomplete. The implications of our results on circumgalactic media, star formation quenching and disc galaxy rotation curves are discussed. We also examine systematic uncertainties in halo-mass and stellar-mass measurements that might influence our results.Comment: Accepted for publication in A&A; 15 pages, 13 figure

Black-Hole-to-Halo Mass Relation From UNIONS Weak Lensing

This letter presents, for the first time, direct constraints on the black-hole-to-halo-mass relation using weak gravitational lensing measurements. We construct type I and type II Active Galactic Nuclei (AGNs) samples from the Sloan Digital Sky Survey (SDSS), with a mean redshift of 0.4 0.1 for type I (type II) AGNs. This sample is cross-correlated with weak lensing shear from the Ultraviolet Near Infrared Northern Survey (UNIONS). We compute the excess surface mass density of the halos associated with $36,181$ AGNs from $94,308,561$ lensed galaxies and fit the halo mass in bins of black-hole mass. We find that more massive AGNs reside in more massive halos. We see no evidence of dependence on AGN type or redshift in the black-hole-to-halo-mass relationship when systematic errors in the measured black-hole masses are included. Our results are consistent with previous measurements for non-AGN galaxies. At a fixed black-hole mass, our weak-lensing halo masses are consistent with galaxy rotation curves, but significantly lower than galaxy clustering measurements. Finally, our results are broadly consistent with state-of-the-art hydro-dynamical cosmological simulations, providing a new constraint for black-hole masses in simulations.Comment: 14 pages, 5 figures. Submitted to ApJ

A Lens Antenna with Reconfigurable Beams for mmWave Wind Profile Radar

Wind profile radar systems require antennas with multiple radiation beams for detecting wind velocity, as well as with a low sidelobe and dual polarization for enhancing the sensitivity for the weak signal reflected from the turbulence. This paper proposes a lens antenna operating at 24 GHz with four reconfigurable beams for wind profile radars. This lens antenna includes 2 × 2 corrugated horn antennas for radiating 24 GHz waves in two polarizations, and the dielectric lens for modulating four radiation beams with a high gain and low sidelobe. Experiments demonstrate that this lens antenna can realize reconfigurable beams with deflections of ±15° in dual polarizations, meanwhile with the gain of 30.58 dBi and the sidelobe of −20 dB. This proposed lens antenna can be applied to mmWave wind profile radars of wind turbines for enhancing wind power efficiency

Short Text Aspect-Based Sentiment Analysis Based on CNN + BiGRU

This paper describes the construction a short-text aspect-based sentiment analysis method based on Convolutional Neural Network (CNN) and Bidirectional Gating Recurrent Unit (BiGRU). The hybrid model can fully extract text features, solve the problem of long-distance dependence on the sequence, and improve the reliability of training. This article reports empirical research conducted on the basis of literature research. The first step was to obtain the dataset and perform preprocessing, after which scikit-learn was used to perform TF-IDF calculations to obtain the feature word vector weight, obtain the aspect-level feature ontology words of the evaluated text, and manually mark the ontology of the reviewed text and the corresponding sentiment analysis polarity. In the sentiment analysis section, a hybrid model based on CNN and BiGRU (CNN + BiGRU) was constructed, which uses corpus sentences and feature words as the vector input and predicts the emotional polarity. The experimental results prove that the classification accuracy of the improved CNN + BiGRU model was improved by 12.12%, 8.37%, and 4.46% compared with the Convolutional Neural Network model (CNN), Long-Short Term Memory model (LSTM), and Convolutional Neural Network (C-LSTM) model

Short Text Aspect-Based Sentiment Analysis Based on CNN + BiGRU

This paper describes the construction a short-text aspect-based sentiment analysis method based on Convolutional Neural Network (CNN) and Bidirectional Gating Recurrent Unit (BiGRU). The hybrid model can fully extract text features, solve the problem of long-distance dependence on the sequence, and improve the reliability of training. This article reports empirical research conducted on the basis of literature research. The first step was to obtain the dataset and perform preprocessing, after which scikit-learn was used to perform TF-IDF calculations to obtain the feature word vector weight, obtain the aspect-level feature ontology words of the evaluated text, and manually mark the ontology of the reviewed text and the corresponding sentiment analysis polarity. In the sentiment analysis section, a hybrid model based on CNN and BiGRU (CNN + BiGRU) was constructed, which uses corpus sentences and feature words as the vector input and predicts the emotional polarity. The experimental results prove that the classification accuracy of the improved CNN + BiGRU model was improved by 12.12%, 8.37%, and 4.46% compared with the Convolutional Neural Network model (CNN), Long-Short Term Memory model (LSTM), and Convolutional Neural Network (C-LSTM) model

Seeing is not Believing: Narrative Characteristics and Governance Strategies on the Short Video Rumors of Health Care

With the continuous updating of technology, the media form carrying rumors is constantly upgrading. Especially in the era of mobile social interaction, the boom of mobile short video makes the soil of rumors continue to expand. As a result, the visual impact and mosaic editing of these video rumors make what the eyes see not necessarily true. In such an environment, audiences are likely to be exposed to various short video rumors of health care. It is critical that some analysis be conducted to analyze the impact of these short videos on the society and offer some measures to prevent them from affecting the general public