Abstract. The effect of aerosols on lightning has been noted in many case studies, but much less is known about the long-term impact, relative importance of dynamics–thermodynamics versus aerosol, and any difference by different types of aerosols. Attempts are made to tackle all these factors, whose distinct roles are discovered by analyzing 11-year datasets of lightning, aerosol loading and composition, and dynamic–thermodynamic data from satellite and model reanalysis. Variations in the lightning rate are analyzed with respect to changes in dynamic–thermodynamic variables and indices such as the convective available potential energy (CAPE) and vertical wind shear. In general, lightning has strong diurnal and seasonal variations, peaking in the afternoon and during the summer. The lightning flash rate is much higher in moist central Africa than in dry northern Africa presumably because of the combined influences of surface heating, CAPE, relative humidity (RH), and aerosol type. In both regions, the lightning flash rate changes with aerosol optical depth (AOD) in a boomerang shape: first increasing with AOD, tailing off around AOD = 0.3, and then behaving differently, i.e., decreasing for dust and flattening for smoke aerosols. The deviation is arguably caused by the tangled influences of different thermodynamics (in particular humidity and CAPE) and aerosol type between the two regions. In northern Africa, the two branches of the opposite trends seem to echo the different dominant influences of the aerosol microphysical effect and the aerosol radiative effect that are more pronounced under low and high aerosol loading conditions, respectively. Under low-AOD conditions, the aerosol microphysical effect more likely invigorates deep convection. This may gradually yield to the suppression effect as AOD increases, leading to more and smaller cloud droplets that are highly susceptible to evaporation under the dry conditions of northern Africa. For smoke aerosols in moist central Africa, the aerosol invigoration effect can be sustained across the entire range of AOD by the high humidity and CAPE. This, plus a potential heating effect of the smoke layer, jointly offsets the suppression of convection due to the radiative cooling at the surface by smoke aerosols. Various analyses were done that tend to support this hypothesis.
Lithium reactivity with electrolytes leads to their continuous consumption and dendrite growth, which constitute major obstacles to harnessing the tremendous energy of lithium-metal anode in a reversible manner. Considerable attention has been focused on inhibiting dendrite via interface and electrolyte engineering, while admitting electrolyte-lithium metal reactivity as a thermodynamic inevitability. Here, we report the effective suppression of such reactivity through a nano-porous separator. Calculation assisted by diversified characterizations reveals that the separator partially desolvates Li+ in confinement created by its uniform nanopores, and deactivates solvents for electrochemical reduction before Li0-deposition occurs. The consequence of such deactivation is realizing dendrite-free lithium-metal electrode, which even retaining its metallic lustre after long-term cycling in both Li-symmetric cell and high-voltage Li-metal battery with LiNi0.6Mn0.2Co0.2O2 as cathode. The discovery that a nano-structured separator alters both bulk and interfacial behaviors of electrolytes points us toward a new direction to harness lithium-metal as the most promising anode.
This paper introduces a new algorithm to detect aerosols and clouds based on micropulse lidar measurements. A semidiscretization processing technique is first used to inhibit the impact of increasing noise with distance. The value distribution equalization method which reduces the magnitude of signal variations with distance is then introduced. Combined with empirical threshold values, we determine if the signal waves indicate clouds or aerosols. This method can separate clouds and aerosols with high accuracy, although differentiation between aerosols and clouds are subject to more uncertainties depending on the thresholds selected. Compared with the existing Atmospheric Radiation Measurement program lidar-based cloud product, the new method appears more reliable and detects more clouds with high bases. The algorithm is applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu sites. At the SGP site, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring and shows bimodal vertical distributions with maximum occurrences at around 3-6 km and 8-12 km. The annual averaged cloud frequency is about 50%. The dominant clouds are stratiform in winter and convective in summer. By contrast, the cloud frequency at the Taihu site shows no clear seasonal variation and the maximum occurrence is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at the SGP site. A seasonal analysis of cloud base occurrence frequency suggests that stratiform clouds dominate at the Taihu site.
Objective:
Recently, ribosome binding protein 1 (RRBP1) is reported to be involved in tumorigenesis. However, the expression and clinical significance of RRBP1 in prostate cancer (PCa) remains unknown. This study is aimed to investigate the expression and clinical significance of RRBP1 in PCa.
Materials and methods:
RRBP1 expression was firstly detected in 6 cases of PCa and matched adjacent non-cancerous prostate tissues by reverse transcription-quantitative PCR (RT-qPCR) and Western blot. Then, RRBP1 expression was further detected in 127 cases of PCa and 40 cases of non-cancerous prostate tissues by immunohistochemistry (IHC). The relationship of RRBP1 with clinical-pathological characters and patients’ prognosis was analyzed in PCa.
Results:
RT-qPCR and Western blot analysis showed that RRBP1 expression levels in PCa tissues were significantly higher compared with those in matched adjacent non-cancerous prostate tissues. IHC results shown that the high-expression rate of RRBP1 in PCa was 69.3%, which was significantly greater than those in non-cancerous prostate tissues (15.0%,
P
<0.001). RRBP1 expression was significantly associated with T stage, lymph node metastasis, PSA and Gleason score in PCa. Survival analysis indicated that patients with RRBP1 low-expression presented longer survival time compared with those with RRBP1 high-expression. Moreover, RRBP1 as well as T stage, lymph node metastasis and Gleason score could serve as independent prognostic factors in PCa.
Conclusion:
RRBP1 is highly expressed in PCa and correlates with prognosis, which may serve as a potential biomarker in PCa.
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