A new scintillator-based fast ion loss detector (FILD) has been devised for the HL-2A tokamak, with the objective of discerning the temporal evolution of energy and pitch angle among lost fast ions. A code named FILD ...
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A new scintillator-based fast ion loss detector (FILD) has been devised for the HL-2A tokamak, with the objective of discerning the temporal evolution of energy and pitch angle among lost fast ions. A code named FILD Simulation (FSC) has been developed to assist in the design of the detector head and the interpretation of experimental data. By optimising the geometric design, the resolutions of energy and pitch angle are optimised to 5 keV and 3 degrees, respectively. A branched imaging fiber bundle is used to relay the fluorescence image on the scintillator to two distinct instruments. One of these is a high-speed camera, while the other is a silicon photomultiplier tube (SiPM) array with a sampling rate of up to 1 MSamples/s. This configuration enables the attainment of superior temporal and spatial resolution, as well as high photon sensitivity.
Agile-satellite mission planning is a crucial issue in the construction of satellite constellations. The large scale of remote sensing missions and the high complexity of constraints in agile-satellite mission plannin...
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Agile-satellite mission planning is a crucial issue in the construction of satellite constellations. The large scale of remote sensing missions and the high complexity of constraints in agile-satellite mission planning pose challenges in the search for an optimal solution. To tackle the issue, a dynamic destroy deep-reinforcement learning (D3RL) model is designed to facilitate subsequent optimization operations via adaptive destruction to the existing solutions. Specifically, we first perform a clustering and embedding operation to reconstruct tasks into a clustering graph, thereby improving data utilization. Secondly, the D3RL model is established based on graph attention networks (GATs) to enhance the search efficiency for optimal solutions. Moreover, we present two applications of the D3RL model for intensive scenes: the deep-reinforcement learning (DRL) method and the D3RL-based large-neighborhood search method (DRL-LNS). Experimental simulation results illustrate that the D3RL-based approaches outperform the competition in terms of solutions' quality and computational efficiency, particularly in more challenging large-scale scenarios. DRL-LNS outperforms ALNS with an average scheduling rate improvement of approximately 11% in Area instances. In contrast, the DRL approach performs better in World scenarios, with an average scheduling rate that is around 8% higher than that of ALNS.
Mechanical soil aeration is used for soil remediation at sites contaminated by volatile organic compounds. However, the effectiveness of the method is limited by low soil temperature, high soil moisture, and high soil...
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Mechanical soil aeration is used for soil remediation at sites contaminated by volatile organic compounds. However, the effectiveness of the method is limited by low soil temperature, high soil moisture, and high soil viscosity. Combined with mechanical soil aeration, quicklime has a practical application value related to reinforcement remediation and to its action in the remediation of soil contaminated with volatile organic compounds. In this study, the target pollutant was trichloroethylene, which is a volatile chlorinated hydrocarbon pollutant commonly found in contaminated soils. A restoration experiment was carried out, using a set of mechanical soil-aeration simulation tests, by adding quicklime (mass ratios of 3,10, and 20%) to the contaminated soil. The results clearly indicate that quicklime changed the physical properties of the soil, which affected the environmental behaviour of trichloroethylene in the soil. The addition of CaO increased soil temperature and reduced soil moisture to improve the mass transfer of trichloroethylene. In addition, it improved the macroporous cumulative pore volume and average pore size, which increased soil permeability. As soil pH increased, the clay mineral content in the soils decreased, the cation exchange capacity and the redox potential decreased, and the removal of trichloroethylene from the soil was enhanced to a certain extent. After the addition of quicklime, the functional group COO of soil organic matter could interact with calcium ions, which increased soil polarity and promoted the removal of trichloroethylene.
By imitating the structural characteristics of the lotus leaf, a new excellent energy absorption structure named as the leaf vein branched circular tube (LVBCT) is proposed by referring to lotus leaf vein branched str...
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By imitating the structural characteristics of the lotus leaf, a new excellent energy absorption structure named as the leaf vein branched circular tube (LVBCT) is proposed by referring to lotus leaf vein branched structure. The evolution of its cross-section may be controlled by the number of main veins distributed along the circumference (N) and the ratio of radius of inner circle Rinner to radius of outer circle Router (gamma). To study the crushing behavior of LVBCTs under axial dynamic crushing, the finite element simulation model established by LS-DYNA is first verified by comparing with the experimental results. Following that, a systematic parametric study on geometric parameters N and gamma is carried out with three different wall thicknesses. The mechanical properties of LVBCTs are revealed by analyzing the deformation mechanism and crashworthiness indicators (specific energy absorption per unit mass SEAm and peak crushing force PCF). The numerical results show that the LVBCTs may absorb more impact energy and its energy absorption characteristics are closely related to geometric parameters N, gamma and wall thickness t. The LVBCTs with N = 6 and gamma of 0.5 similar to 0.7 have better crashworthiness. Furthermore, the numerical results show that the thickness matching between main vein and branch vein has influence on the energy absorption ability. The SEAm of LVBCT is improved by 11.3% when the thickness matching between the main vein and the branch vein is 0.92 mm. The results of this study will be helpful to design novel thin-walled structure with better energy absorption ability.
Background: Observational epidemiologic investigations into the link between diabetes mellitus and preeclampsia (PE) have been conducted, but genetic evidence is still lacking. We utilized a two-sample Mendelian rando...
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Background: Observational epidemiologic investigations into the link between diabetes mellitus and preeclampsia (PE) have been conducted, but genetic evidence is still lacking. We utilized a two-sample Mendelian randomization (MR) analysis to shed light on the potential influence of type 2 diabetes mellitus (T2DM) on PE at the genetic prediction level. Methods: We carried out a two-sample bidirectional MR analysis, utilizing genetic variants associated with T2DM (N=461,920) and PE (N=219,817) from the largest available genome-wide association studies. Using inverse variance weighting (IVW) and five validated approaches-MR-Egger, MR-RAPS, ConMix, weighted median, and weighted mode-we derived a potential causal association between T2DM and PE. The relationship between PE and T2DM was explored using reverse MR analysis. Results: The two-sample MR analysis indicated a causal link between T2DM and PE, with an odds ratio of 1.10 (95% CI, 1.02-1.18;P=0.01). The weighted mode method yielded an odds ratio of 1.22 (95% CI, 1.06-1.40;P=0.019), and the weighted median method produced an odds ratio of 1.19 (95% CI, 1.04-1.36;P=0.022). However, no significant association was detected in the MR-Egger analysis. heterogeneity was noted in the analysis of T2DM and PE, but no significant horizontal pleiotropy was observed. The results of the reverse MR analysis indicated no significant causal association between PE and T2DM. Conclusion: For the first time, MR analysis showed a positive causal link from T2DM to PE, but not vice versa. The limited number of SNPs in reverse analysis may affect reliability. Future studies should use more instrumental variables to strengthen findings. Further experiments are also needed to explore underlying mechanisms.
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