Retrieval of sizes and total masses of particles in volcanic clouds using AVHRR bands 4 and 5

The advanced very high resolution radiometer (AVHRR) sensor on polar orbiting NOAA satellites can discriminate between volcanic clouds and meteorological clouds using two-band data in the thermal infrared. This paper is aimed at developing a retrieval of the particle sizes, optical depth, and total masses of particles from AVHRR two-band data of volcanic clouds. Radiative transfer calculations are used with a semi-transparent cloud model that is based on assumptions of spherical particle shape, a homogeneous underlying surface, and a simple thin cloud parallel to the surface. The model is applied to observed AVHRR data from a 13-hour old drifting cloud from the August 19, 1992, eruption of Crater Peak/Spurr Volcano, Alaska. The AVHRR data fit in the range of results calculated by the model, which supports its credibility. According to the model results, the average of effective particle radius in the test frame of this cloud is in the range of 2 to 2.5 μm, the optical depth at 12 μm is about 0.60–0.65. The total estimated mass of ash in the air amounts to 0.24–0.31×106 tons, which is about 0.7–0.9% of the mass measured in the ashfall blanket. Sensitivity tests show that the mass estimate is more sensitive to the assumed ash size distribution than it is to the ash composition

How we learn social norms: a three-stage model for social norm learning

As social animals, humans are unique to make the world function well by developing, maintaining, and enforcing social norms. As a prerequisite among these norm-related processes, learning social norms can act as a basis that helps us quickly coordinate with others, which is beneficial to social inclusion when people enter into a new environment or experience certain sociocultural changes. Given the positive effects of learning social norms on social order and sociocultural adaptability in daily life, there is an urgent need to understand the underlying mechanisms of social norm learning. In this article, we review a set of works regarding social norms and highlight the specificity of social norm learning. We then propose an integrated model of social norm learning containing three stages, i.e., pre-learning, reinforcement learning, and internalization, map a potential brain network in processing social norm learning, and further discuss the potential influencing factors that modulate social norm learning. Finally, we outline a couple of future directions along this line, including theoretical (i.e., societal and individual differences in social norm learning), methodological (i.e., longitudinal research, experimental methods, neuroimaging studies), and practical issues

Multi-UAV-Assisted Offloading for Joint Optimization of Energy Consumption and Latency in Mobile Edge Computing

To address the performance limitations caused by the insufficient computing capacity and energy of edge internet of things devices (IoTDs), we proposed a multi-unmanned aerial vehicles (UAV)-assisted mobile edge computing (MEC) application framework in this article. In this framework, UAVs equipped with high-performance computing devices act as aerial servers deployed in the target area to support data offloading and task computing for IoTDs. We formulated an optimization problem to jointly optimize the connection scheduling, computing resource allocation, and UAVs' flying trajectories, considering the device offloading priority, to achieve a joint optimization of energy consumption and latency for all IoTDs during a given time period. Subsequently, to address this problem, we employed deep reinforcement learning for dynamic trajectory planning, supplemented by optimization theory and heuristic algorithm based on matching theory to assist in solving connection scheduling and computing resource allocation. To evaluate the performance of proposed algorithm, we compared it with deep deterministic policy gradient, particle swarm optimization, random moving, and local execution schemes. Simulation results demonstrated that the multi-UAV-assisted MEC significantly reduces the computing cost of IoTDs. Moreover, our proposed solution exhibited effectiveness in terms of convergence and optimization of computing costs compared to other benchmark schemes

Phytochemical components and biological activities of Artemisia argyi

peer reviewe

The parallax and 3D kinematics of water masers in the massive star-forming region G034.43+0.24

We report a trigonometric parallax measurement of 22 GHz water masers in the massive star-forming region G034.43+0.24 as part of the Bar and Spiral Structure Legacy (BeSSeL) Survey using the Very Long Baseline Array. The parallax is 0.330$\pm$50.018 mas, corresponding to a distance of $3.03^{+0.17}_{-0.16}$ kpc. This locates G034.43+0.24 near the inner edge of the Sagittarius spiral arm and at one end of a linear distribution of massive young stars which cross nearly the full width of the arm. The measured 3-dimensional motion of G034.43+0.24 indicates a near-circular Galactic orbit. The water masers display arc-like distributions, possibly bow shocks, associated with winds from one or more massive young stars

SNP-Based Genetic Linkage Map of Soybean Using the SoySNP6K Illumina Infinium BeadChip Genotyping Array

This study reports a high density genetic linkage map based on the ‘Maryland 96-5722’ by ‘Spencer’ recombinant inbred line (RIL) population of soybean [Glycine max (L.) Merr.] and constructed exclusively with single nucleotide polymorphism (SNP) markers. The Illumina Infinium SoySNP6K BeadChip genotyping array produced 5,376 SNPs in the mapping population, with a 96.75% success rate. Significant level of goodness-of-fit for each locus was tested based on the observed vs. expected ratio (1:1). Out of 5,376 markers, 1,465 SNPs fit the 1:1 segregation rate having ≤20% missing data plus heterozygosity among the RILs. Among this 1,456 just 657 were polymorphic between the parents DNAs tested. These 657 SNPs were mapped using the JoinMap 4.0 software and 550 SNPs were distributed on 16 linkage groups (LGs) among the 20 chromosomes of the soybean genome. The total map length was just 201.57 centiMorgans (cM) with an average marker density of 0.37 cM. This is one of the high density SNP-based genetic linkage maps of soybean that will be used by the scientific community to map quantitative trait loci (QTL) and identify candidate genes for important agronomic traits in soybean

Simultaneous extraction and determination of alkaloids and organic acids in Uncariae Ramulas Cum Unicis by vortex-assisted matrix solid phase dispersion extraction coupled with UHPLC-MS/MS

A simple and efficient vortex-assisted matrix solid phase dispersion with a ultra-high-performance liquid chromatography-triple quadrupole mass spectrometer (VA-MSPD-UHPLC-MS/MS) was applied for simultaneous extraction and determination of seven alkaloids and three organic acids from Uncariae Ramulas Cum Unicis. The optimal extraction conditions of the target components were obtained by Box-Behnken design (BBD) combined with response surface methodology (RSM). The results of the method validation showed that this analytical method displayed good linearity with a correlation coefficient (r) no lower than 0.9990. The recoveries of ten active ingredients from Uncariae Ramulas Cum Unicis ranged from 95.9% to 103% (RSD ≤ 2.77%). The RSDs of intra-day and inter-day precisions were all below 2.97%. The present method exhibited not only lower solvent and sample usage, but also shorter sample processing and analysis time. Consequently, the developed VA-MSPD-UHPLC-MS/MS method could be successfully and effectively used for the extraction and analysis of ten active components from Uncariae Ramulas Cum Unicis

All-Trans-Retinoic Acid Suppresses Neointimal Hyperplasia and Inhibits Vascular Smooth Muscle Cell Proliferation and Migration via Activation of AMPK Signaling Pathway

The proliferation and migration of vascular smooth muscle cells (VSMC) is extensively involved in pathogenesis of neointimal hyperplasia. All-trans-retinoic acid (ATRA) is a natural metabolite of vitamin A. Here, we investigated the involvement of AMP-activated protein kinase (AMPK) in the anti-neointimal hyperplasia effects of ATRA. We found that treatment with ATRA significantly reduced neointimal hyperplasia in the left common carotid artery ligation mouse model. ATRA reduced the proliferation and migration of VSMC, A7r5 and HASMC cell lines. Our results also demonstrated that ATRA altered the expression of proliferation-related proteins, including CyclinD1, CyclinD3, CyclinA2, CDK2, CDK4, and CDK6 in VSMC. ATRA dose-dependently enhanced the phosphorylation level of AMPKα (Thr172) in the left common carotid artery of experimental mice. Also, the phosphorylation level of AMPKα in A7r5 and HASMC was significantly increased. In addition, ATRA dose-dependently reduced the phosphorylation levels of mTOR and mTOR target proteins p70 S6 kinase (p70S6K) and 4E-binding protein 1 (4EBP1) in A7r5 and HASMC. Notably, the inhibition of AMPKα by AMPK inhibitor (compound C) negated the protective effect of ATRA on VSMC proliferation in A7r5. Also, knockdown of AMPKα by siRNA partly abolished the anti-proliferative and anti-migratory effects of ATRA in HASMC. Molecular docking analysis showed that ATRA could dock to the agonist binding site of AMPK, and the binding energy between AMPK and ATRA was -7.91 kcal/mol. Molecular dynamics simulations showed that the binding of AMPK-ATRA was stable. These data demonstrated that ATRA might inhibit neointimal hyperplasia and suppress VSMC proliferation and migration by direct activation of AMPK and inhibition of mTOR signaling