Verification of {\Gamma}7_{7} symmetry assignment for the top valence band of ZnO by magneto-optical studies of the free A exciton state

The circularly-polarized and angular-resolved magneto-photoluminescence spectroscopy was carried out to study the free A exciton 1S state in wurtzite ZnO at 5 K.Comment: 4 figures, 16 pages. arXiv admin note: substantial text overlap with arXiv:0706.396

Wheat Rhizosphere Metagenome Reveals Newfound Potential Soil Zn-Mobilizing Bacteria Contributing to Cultivars’ Variation in Grain Zn Concentration

An effective solution to global human zinc (Zn) deficiency is Zn biofortification of staple food crops, which has been hindered by the low available Zn in calcareous soils worldwide. Many culturable soil microbes have been reported to increase Zn availability in the laboratory, while the status of these microbes in fields and whether there are unculturable Zn-mobilizing microbes remain unexplored. Here, we use the culture-independent metagenomic sequencing to investigate the rhizosphere microbiome of three high-Zn (HZn) and three low-Zn (LZn) wheat cultivars in a field experiment with calcareous soils. The average grain Zn concentration of HZn was higher than the Zn biofortification target 40 mg kg–1, while that of LZn was lower than 40 mg kg–1. Metagenomic sequencing and analysis showed large microbiome difference between wheat rhizosphere and bulk soil but small difference between HZn and LZn. Most of the rhizosphere-enriched microbes in HZn and LZn were in common, including many of the previously reported soil Zn-mobilizing microbes. Notably, 30 of the 32 rhizosphere-enriched species exhibiting different abundances between HZn and LZn possess the functional genes involved in soil Zn mobilization, especially the synthesis and exudation of organic acids and siderophores. Most of the abundant potential Zn-mobilizing species were positively correlated with grain Zn concentration and formed a module with strong interspecies relations in the co-occurrence network of abundant rhizosphere-enriched microbes. The potential Zn-mobilizing species, especially Massilia and Pseudomonas, may contribute to the cultivars’ variation in grain Zn concentration, and they deserve further investigation in future studies on Zn biofortification

A Survey of Large Language Models

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach, language modeling has been widely studied for language understanding and generation in the past two decades, evolving from statistical language models to neural language models. Recently, pre-trained language models (PLMs) have been proposed by pre-training Transformer models over large-scale corpora, showing strong capabilities in solving various NLP tasks. Since researchers have found that model scaling can lead to performance improvement, they further study the scaling effect by increasing the model size to an even larger size. Interestingly, when the parameter scale exceeds a certain level, these enlarged language models not only achieve a significant performance improvement but also show some special abilities that are not present in small-scale language models. To discriminate the difference in parameter scale, the research community has coined the term large language models (LLM) for the PLMs of significant size. Recently, the research on LLMs has been largely advanced by both academia and industry, and a remarkable progress is the launch of ChatGPT, which has attracted widespread attention from society. The technical evolution of LLMs has been making an important impact on the entire AI community, which would revolutionize the way how we develop and use AI algorithms. In this survey, we review the recent advances of LLMs by introducing the background, key findings, and mainstream techniques. In particular, we focus on four major aspects of LLMs, namely pre-training, adaptation tuning, utilization, and capacity evaluation. Besides, we also summarize the available resources for developing LLMs and discuss the remaining issues for future directions.Comment: ongoing work; 51 page

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

Chlorogenic acid prevents alcohol-induced brain damage in neonatal rat

The present investigation evaluates the neuroprotective effect of chlorogenic acid (CA) in alcohol-induced brain damage in neonatal rats. Ethanol (12 % v/v, 5 g/kg) was administered orally in the wistar rat pups on postnatal days (PD) 7-9. Chlorogenic acid (100 and 200 mg/kg, p.o.) was administered continuously from PD 6 to 28. Cognitive function was estimated by Morris water maze (MWM) test. However, activity of acetylcholinesterase, inflammatory mediators, parameters of oxidative stress and activity of caspase-3 enzyme was estimated in the tissue homogenate of cerebral cortex and hippocampus of ethanol-exposed pups. It has been observed that treatment with CA attenuates the altered cognitive function in ethanol-exposed pups. There was a significant decrease in the activity of acetylcholinesterase in the CA treated group compared to the negative control group. However, treatment with CA significantly ameliorates the increased oxidative stress and concentration of inflammatory mediators in the brain tissues of ethanol-exposed pups. Activity of caspase-3 enzyme was also found significantly decreased in the CA treated group compared to the negative control group. The present study concludes that CA attenuates the neuronal damage induced in alcohol exposed neonatal rat by decreasing the apoptosis of neuronal cells

Existence of Solutions of a Class of Boundary Value Problems for n-Dimensional Equations System

Abstract:In this paper, we give theorems about existence of one and multiple solutions in some conditions to the boundary value problem for the following system of -dimensional equation

Synthesis and magnetic characterizations of uniform iron oxide nanoparticles

Uniform iron oxide nanoparticles with a cubic shape were prepared by the decomposition of homemade iron oleate in 1-octadecene with the presence of oleic acid. The particle shape and size uniformity are sensitive to the quantity of oleic acid. XRD, HRTEM and SAED results indicated that the main phase content of as-prepared iron oxide nanoparticles is Fe3O4 with an inverse spinet structure. Magnetic measurements revealed that the as-prepared iron oxide nanoparticles display a ferromagnetic behavior with a blocking temperature of 295 K. At low temperatures the magnetic anisotropy of the aligned nanoparticles caused the appearance of a hysteresis loop. (c) 2014 Elsevier By. All rights reserved

Performance Optimization of High Specific Speed Centrifugal Pump Based on Orthogonal Experiment Design Method

A high specific speed centrifugal pump is used in the situation of large flow and low head. Centrifugal pump parameters need to be optimized in order to raise its head and efficiency under off-design conditions. In this study, the orthogonal experiment design method is adopted to optimize the performance of centrifugal pump basing on three parameters, namely, blade outlet width b2, blade outlet angle β2 and blade wrap angle φ. First, the three-dimensional model of the centrifugal pump is established by CFturbo and SolidWorks. Then nine different schemes are designed by using orthogonal table, and numerical simulation is carried out in CFX15.0. The final optimized combination of parameters is b2 = 24 mm, β2 = 24°, φ = 112°. Under the design condition, the head and efficiency of the optimized centrifugal pump are appropriately improved, the increments of which are 0.74 m and 0.48%, respectively. However, the efficiency considerably increases at high flow rates, with an increase of 6.9% at 1.5 Qd. The anti-cavitation performance of the optimized centrifugal pump is also better than the original pump. The results in this paper can provide references for parameter selection (b2, β2, φ) in the centrifugal pump design