Strangeness production has been suggested to be a sensitive probe to the early-time dynamics of the nuclear matter created in heavy-ion collisions. Transverse momentum distributions and yields of ...strange hadrons provide important information on their production mechanisms and can help us probe the properties of the created medium and its evolution. Thanks to the high statistics data taken during the STAR BES-II program in 2018-2021, a series of measurements on the properties of strangeness production at low energies are carried out. In these proceedings, the production of
K
−
, K
S
0
,
ϕ
,
Λ
, and Ξ
−
in Au+Au collisions at √S
NN
= 3 GeV are presented. The strange hadron transverse momentum spectra, rapidity density distributions, and particle ratios are shown. These results are compared with UrQMD model calculations, and the extracted kinetic freeze-out parameters are discussed and compared with the ones from higher collision energies.
In this proceedings, we present our first measurements of
\phi
ϕ
meson and
\Xi^-
Ξ
−
hyperon production in Au+Au collisions at
\sqrt{s_{NN}}
s
N
N
= 3 GeV. Various models including thermal and ...transport model
calculations are compared to data, these results imply that the matter
produced in the 3 GeV Au+Au collisions is considerably different from
that at higher energies.
Technological innovation is considered an important source of national economic development, but existing studies have found that there are few independent research and development (R&D) activities ...in Chinese enterprises, and the achievement transformation of R&D investment is still facing great difficulties. As a new technical means, Internetization is regarded as an important driving force for promoting enterprise innovation in the information technology era. However, few empirical studies have conducted detailed analyses of the relationship between Internetization and enterprise innovation, ignoring the fact that Internetization can quickly transfer information. Therefore, based on the invention patent data of listed enterprises in the computer, communication, and other electronic equipment manufacturing industries in Guangdong Province from 2012 to 2020, and dividing Internetization into two types: Information Internetization and Application Internetization, this study analyzes the basic characteristics o
Temperature-dependent sex determination is a notable model of phenotypic plasticity. In many reptiles, including the red-eared slider turtle
(
), the individual's sex is determined by the ambient ...temperature during egg incubation. In this study, we show that the histone H3 lysine 27 (H3K27) demethylase KDM6B exhibits temperature-dependent sexually dimorphic expression in early
embryos before the gonad is distinct. Knockdown of
at 26°C (a temperature at which all offspring develop into males) triggers male-to-female sex reversal in >80% of surviving embryos. KDM6B directly promotes the transcription of the male sex-determining gene
by eliminating the trimethylation of H3K27 near its promoter. Additionally, overexpression of
is sufficient to rescue the sex reversal induced by disruption of
This study establishes causality and a direct genetic link between epigenetic mechanisms and temperature-dependent sex determination in a turtle species.
The thermal energy storage properties of a working fluid can be modified by the exothermic and endothermic adsorption and desorption of fluid molecules in the micro/nanoporous materials. In this ...study, thermogravimetric (TG) analysis experiments and molecular simulations (molecular dynamics, MD, and grand canonical Monte Carlo, GCMC) were employed to examine the thermal energy storage properties of the UIO-66 metal organic framework material, UIO-66/H2O nanofluids and pure water. Our results showed that the molecular simulation calculations were, in principle, consistent with the obtained experimental data. The thermal energy storage performance of UIO-66/H2O nanofluids was enhanced with the increase in the UIO-66 mass fraction. In addition, the differences between the simulation calculations and experimental results could be mainly ascribed to the different structures of UIO-66 and the evaporation of fluid samples. Furthermore, this work indicated that molecular simulations contributed to developing novel working pairs of metal organic heat carriers (MOHCs).
Residential demand response is vital for the efficiency of power system. It has attracted much attention from both academic and industry in recent years. Accurate short-term load forecasting is a ...fundamental task for demand response. While short-term forecasting for aggregated load data has been extensively studied, load forecasting for individual residential users is still challenging due to the dynamic and stochastic characteristic of single users' electricity consumption behaviors, i.e., the variability of the residential activities. To address this challenge, this paper presents a short-term residential load forecasting framework, which makes use of the spatio-temporal correlation existing in appliances' load data through deep learning. Multiple time series are conducted in the framework to describe electricity consumption behaviors and their internal spatio-temporal relationship. And a method based on deep neural network and iterative ResBlock is proposed to learn the correlation among different electricity consumption behaviors for short-term load forecasting. Experiments based on real world measurements have been conducted to evaluate the performance of the proposed forecasting approach. The results show that both the appliances' load data and iterative ResBlocks can help to improve the forecasting performance. Compared with existing methods, measurements on Root Mean Squared Error, Mean Absolute Error and Mean Absolute Percentage Error for the proposed approach are reduced by 3.89%-20.00%, 2.18%-22.58% and 0.69%-32.78%. In addition, further experiments are conducted to evaluate the impact of using appliances' load data, iterative ResBlocks as well as other factors for the proposed approach.
This study is aimed to reconstruct displacements from measured accelerations based on a low-frequency attenuation (LFA) algorithm. The integration of acceleration is conducted directly in frequency ...domain and the integral accuracy is governed by an accuracy control factor (ACF). A finite element simulation is conducted to compare the integral accuracy of this algorithm with those of several other conventional integration algorithms and then the superiority of the LFA algorithm is verified. At the same time, a numerical study and a vibration test rig with limit positions of impact are designed to investigate the influence of the ACF on integration accuracy for the LFA algorithm. Besides, three error evaluation indices are proposed to evaluate the integration accuracy. The investigations indicate that the determination of the value of the ACF should fully consider the level of low frequency noise, and it is better to select a relatively large value to ensure a good effect of eliminating the trend error and/or drift error. According to this research, the value of the ACF is suggested to be selected in the range from 0.90 to 0.98 so that integral results with high accuracy can be obtained in engineering applications.
•An improved low-frequency attenuation (LFA) algorithm is presented.•Integral accuracy of the LFA algorithm is governed by an accuracy control factor (ACF).•The superiority of the LFA algorithm against several conventional algorithms is verified by a FE simulation example.•A numerical study and a vibration test are designed to investigate influence of ACF on integration accuracy.•An optimal ACF value is given to get good integral result in engineering applications.
Despite great progress in the development of nonprecious metal catalysts (NPMCs) over the past several decades, the performance and stability of these promising catalysts have not yet achieved ...commercial readiness for proton exchange membrane fuel cells (PEMFCs). Through rational design of the cathode catalyst layer (CCL), we demonstrate the highest reported performance for an NPMC-based membrane electrode assembly (MEA), achieving a peak power of 570 mW/cm
under air. This record performance is achieved using a precommercial catalyst for which nearly all pores are <3 nm in diameter, challenging previous beliefs regarding the need for larger catalyst pores to achieve high current densities. This advance is achieved at industrially relevant scales (50 cm
MEA) using a precommercial NPMC. In situ electrochemical analysis of the CCLs is also used to help gain insight into the degradation mechanism observed during galvanostatic testing. Overall, the performance of this NPMC-based MEA has achieved commercial readiness and will be introduced into an NPMC-based product for portable power applications.
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•The self-assembly of NG and SAN/Si composite microspheres via spray-drying.•Hierarchical structure with carbon coating and voids buffers the volume change of Si.•The Si/C@NGs ...composites deliver high capacity and high first Coulombic efficiency.
Si/C@NGs composite containing flake-shaped sub-micron sized silicon (Si) enwrapped by pyrolyzed carbon and natural graphite (NG) was successfully prepared by spray-drying-assisted self-assembly method and was systematically studied as an anode material for lithium-ion batteries. The as-prepared Si/C@NGs composite material has a loading amount of sub-micron sized silicon as low as 6.7wt%. The Si/C@NGs composite has a hierarchical structure with Si/C embedded into natural graphite which further assembles into larger secondary particles of ∼20–50μm. Compared with pure silicon, the as-synthesized Si/C@NGs composite has multi-layer carbon coating as well as voids to alleviate the structural changes of Si during charging/discharging, exhibits an initial efficiency of 82.8% and a capacity retention of 428.1mAhg−1 (1524.0mAhg−1vs. Si) after 100 cycles at 0.1Ag−1. The remarkable cycling performances, high initial cycle efficiency together with low-cost manufacturing process make Si/C@NGs composite appealing for commercial applications.
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