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Hollow carbon nanocages (HCNCs) consisting of sp2 carbon shells featured by a hollow interior cavity with defective microchannels (or customized mesopores) across the carbon shells, high specific surface area, and tunable electronic structure, are quilt different from the other nanocarbons such as carbon nanotubes and graphene. These structural and morphological characteristics make HCNCs a new platform for advanced electrochemical energy storage and conversion. This review focuses on the controllable preparation, structural regulation, and modification of HCNCs, as well as their electrochemical functions and applications as energy storage materials and electrocatalytic conversion materials. The metal single atoms‐functionalized structures and electrochemical properties of HCNCs are summarized systematically and deeply. The research challenges and trends are also envisaged for deepening and extending the study and application of this hollow carbon material. The development of multifunctional carbon‐based composite nanocages provides a new idea and method for improving the energy density, power density, and volume performance of electrochemical energy storage and conversion devices. In this review, a clear and comprehensive definition of hollow carbon nanocages (HCNCs) is provided. The latest research progress (including preparation, regulation, and modification) of HCNCs in the field of electrochemical energy storages and conversions is detailly reviewed and discussed. The challenges and some insights into new trends and directions for HCNCs are also provided.

Background Coronavirus disease 2019 (COVID-19) is associated with a high mortality rate, especially in patients with severe illness. We conducted a systematic review and meta-analysis to assess the potential predictors of mortality in patients with COVID-19. Methods PubMed, EMBASE, the Cochrane Library, and three electronic Chinese databases were searched from December 1, 2019 to April 29, 2020. Eligible studies reporting potential predictors of mortality in patients with COVID-19 were identified. Unadjusted prognostic effect estimates were pooled using the random-effects model if data from at least two studies were available. Adjusted prognostic effect estimates were presented by qualitative analysis. Results Thirty-six observational studies were identified, of which 27 were included in the meta-analysis. A total of 106 potential risk factors were tested, and the following important predictors were associated with mortality: advanced age, male sex, current smoking status, preexisting comorbidities (especially chronic kidney, respiratory, and cardio-cerebrovascular diseases), symptoms of dyspnea, complications during hospitalization, corticosteroid therapy and a severe condition. Additionally, a series of abnormal laboratory biomarkers of hematologic parameters, hepatorenal function, inflammation, coagulation, and cardiovascular injury were also associated with fatal outcome. Conclusion We identified predictors of mortality in patients with COVID-19. These findings could help healthcare providers take appropriate measures and improve clinical outcomes in such patients.

The remote sensing based mapping of land cover at extensive scales, e.g., of whole continents, is still a challenging task because of the need for sophisticated pipelines that combine every step from data acquisition to land cover classification. Utilizing the Google Earth Engine (GEE), which provides a catalog of multi-source data and a cloud-based environment, this research generates a land cover map of the whole African continent at 10 m resolution. This land cover map could provide a large-scale base layer for a more detailed local climate zone mapping of urban areas, which lie in the focus of interest of many studies. In this regard, we provide a free download link for our land cover maps of African cities at the end of this paper. It is shown that our product has achieved an overall accuracy of 81% for five classes, which is superior to the existing 10 m land cover product FROM-GLC10 in detecting urban class in city areas and identifying the boundaries between trees and low plants in rural areas. The best data input configurations are carefully selected based on a comparison of results from different input sources, which include Sentinel-2, Landsat-8, Global Human Settlement Layer (GHSL), Night Time Light (NTL) Data, Shuttle Radar Topography Mission (SRTM), and MODIS Land Surface Temperature (LST). We provide a further investigation of the importance of individual features derived from a Random Forest (RF) classifier. In order to study the influence of sampling strategies on the land cover mapping performance, we have designed a transferability analysis experiment, which has not been adequately addressed in the current literature. In this experiment, we test whether trained models from several cities contain valuable information to classify a different city. It was found that samples of the urban class have better reusability than those of other natural land cover classes, i.e., trees, low plants, bare soil or sand, and water. After experimental evaluation of different land cover classes across different cities, we conclude that continental land cover mapping results can be considerably improved when training samples of natural land cover classes are collected and combined from areas covering each Köppen climate zone.

Chalcogenide perovskites have shown great potential for photovoltaic applications. Most researchers have begun to pay close attention to the crystal synthesis, phase stability, and optoelectronic properties of chalcogenide perovskites AMX3 (A = Ca, Sr, Ba; M = Ti, Zr, Hf, Sn; X = S, Se). At present, the A-site metal cations are mainly limited to alkaline earth metal cations in the literature. The replacement of the alkaline earth metal cations by Yb2+ is proposed as an alternative for chalcogenide perovskites. In this study, the phase stability, and mechanical, electronic, optical, and photovoltaic properties of novel chalcogenides YbMX3 (M = Zr, Hf; X = S, Se) are theoretically evaluated in detail for the first time. It is mentioned that YbZrS3 and YbHfS3 are marginally thermodynamically stable while YbZrSe3 and YbHfSe3 exhibit superior phase stability against decomposition. Good mechanical and dynamical stability of these chalcogenide perovskites are verified, and they are all ductile materials. The accurate electronic structure calculations suggest that the predicted direct bandgap of YbMSe3 (M = Zr, Hf) is within 1.3–1.7 eV. Additionally, the small effective mass and low exciton binding energy of YbMSe3 (M = Zr, Hf) are favorable for their photovoltaic applications. However, YbZrS3 and YbHfS3 show larger direct band gaps with a change from 1.92 to 2.27 eV. The optical and photovoltaic properties of these compounds are thoroughly studied. In accordance with their band gaps, YbZrSe3 and YbHfSe3 are discovered to exhibit high visible-light absorption coefficients. The maximum conversion efficiency analysis shows that YbMSe3 (M = Zr, Hf) can achieve an excellent efficiency, especially for YbZrSe3, whose efficiency can reach ~32% in a film thickness of 1 μm. Overall, our study uncovers that YbZrSe3 is an ideal stable photovoltaic material with a high efficiency comparable to those of lead-based halide perovskites.

Aiming at the problem of distributed state estimation in sensor networks, a novel optimal distributed finite-time fusion filtering method based on dynamic communication weights has been developed. To tackle the fusion errors caused by incomplete node information in distributed sensor networks, the concept of limited iterations of global information aggregation was introduced, namely, fast finite-time convergence techniques. Firstly, a local filtering algorithm architecture was constructed to achieve fusion error convergence within a limited number of iterations. The maximum number of iterations was derived to be the diameter of the communication topology graph in the sensor network. Based on this, the matrix weight fusion was used to combine the local filtering results, thereby achieving optimal estimation in terms of minimum variance. Next, by introducing the generalized information quality (GIQ) calculation method and associating it with the local fusion result bias, the relative communication weights were obtained and embedded in the fusion algorithm. Finally, the effectiveness and feasibility of the proposed algorithm were validated through numerical simulations and experimental tests.

In the late stage of underground brine mining in salt lakes, the method of injecting fresh water is often used to extract the salt from the brine storage medium. This method of freshwater displacement breaks the original water–rock equilibrium and changes the evolution process of the original underground brine. To explore the mechanism of salt release in saline water-bearing media under conditions of relatively fresh lake water dissolution, this paper analyzes the changes in the chemical parameters of brine from 168 sampling points in the Mahai salt lake in the Qaidam Basin at three stages (before exploitation, during exploitation, and late exploitation) by correlation analysis, ion ratio analysis, and other methods and investigate the variations in porosity and the evolution laws of brine. The results show that the changes in the main ion content and brine mineralization during the exploitation process are small. The changes in Ca 2+ content are significant due to the low solubility of calcium minerals, the precipitation of gypsum during the mixing process, and the adsorption of cations by alternating with Ca 2+ . Primary intergranular pore skeletons are easily corroded to form secondary pores, which increase the geological porosity. Na + and Cl - are the dominant ions in the brine in the study area, but the concentration of Ca2 + decreased significantly under the influence of mining, by 41.7% in the middle period and 24.5% in the late period. The correlation between Ca 2+ and salinity changes significantly in different mining stages, and the reason for the decrease of Ca 2+ may be due to the influence of mineral dissolution, mixing, and anion-cation exchange. The porosity of the layer in the study area showed the opposite trend of Ca 2+ , and the porosity increased first and then decreased. The innovation of this paper lies in analyzing the reasons and mechanisms of the disturbance of artificial dissolution mining on stratum structure by comparing the hydrochemical characteristics and porosity of underground brine storage media in three different mining stages. The research in this paper provides a theoretical basis for the calculation of brine resource reserves and the sustainable development of underground brine in salt lake areas.

PRRSV nsp1α, the first viral protein translated in virus-infected cells, is released from viral polyprotein 1a through autocleavage. It plays important roles in viral replication, the suppression of the host innate immune response, and the modulation of cell-mediated immune responses. Nsp1α forms a homodimer in vitro. In this study, we aimed to elucidate the functional significance of nsp1α dimerization. Using the alanine scanning strategy, we identified valine132 and proline134 as critical residues for nsp1α dimerization. Using recombinant viruses expressing an additional FLAG-nsp1α mutant (V132A or P134A), we demonstrated that both the V132A and P134A mutations disrupted nsp1α dimerization in PRRSV-infected cells. When ectopically expressed, the V132A or P134A mutation did not affect the ability of nsp1α to antagonize host type I IFN production or degrade SLA-I molecules. Introducing V132A or P134A mutations into an HP‒PRRSV replicon system significantly interfered with the expression of a Gaussia luciferase reporter and viral proteins, suggesting that nsp1α dimerization is critical for viral replication. Using PRRSV reverse genetics, a recombinant virus carrying the V132A mutation (vV132A) was successfully rescued, while the P134A mutation was lethal. Compared with the wild-type virus, vV132A significantly attenuated growth and reduced the relative expression levels of subgenomic RNAs in MARC-145 cells. In BHK-21 cells transfected with full-length cDNA clones, the P134A mutation nearly completely blocked the synthesis of specific sgRNAs at both the minus- and positive-strand levels while maintaining sgRNA6 accumulation. Thus, nsp1α dimerization is essential for viral RNA synthesis and transcriptional regulation but appears to be dispensable for both the autoproteolytic activity and immune evasion functions of PCPα. This study not only enhances our fundamental knowledge of PRRSV biology but also establishes a foundation for developing targeted antiviral strategies against PRRSV and related arteriviruses.

This paper is concerned with the estimation of correlated noise and packet dropout for information fusion in distributed sensing networks. By studying the problem of the correlation of correlated noise in sensor network information fusion, a matrix weight fusion method with a feedback structure is proposed to deal with the interrelationship between multi-sensor measurement noise and estimation noise, and the method can achieve optimal estimation in the sense of linear minimum variance. Based on this, a method is proposed using a predictor with a feedback structure to compensate for the current state quantity to deal with packet dropout that occurs during multi-sensor information fusion, which can reduce the covariance of the fusion results. Simulation results show that the algorithm can solve the problem of information fusion noise correlation and packet dropout in sensor networks, and effectively reduce the fusion covariance with feedback.

HighlightsThe LiNO3-implanted electroactive β phase polyvinylidene fluoride-co-hexafluoropropylene was built as an artificial solid electrolyte interphase layer for dendrite suppression.The electronegatively charged polymer layer can capture Li ion on its surface to form Li-ion charged channels and recompense the ionic flux of electrolytes via continuous supply of Li ion.The modified Li anode achieved a long cycle life over 2000 h under ultrahigh Li utilization of 50% in symmetric cell and worked in full cell for 100 cycles at harsh condition of extremely low N/P of 0.83.The concentration difference in the near-surface region of lithium metal is the main cause of lithium dendrite growth. Resolving this issue will be key to achieving high-performance lithium metal batteries (LMBs). Herein, we construct a lithium nitrate (LiNO3)-implanted electroactive β phase polyvinylidene fluoride-co-hexafluoropropylene (PVDF-HFP) crystalline polymorph layer (PHL). The electronegatively charged polymer chains attain lithium ions on the surface to form lithium-ion charged channels. These channels act as reservoirs to sustainably release Li ions to recompense the ionic flux of electrolytes, decreasing the growth of lithium dendrites. The stretched molecular channels can also accelerate the transport of Li ions. The combined effects enable a high Coulombic efficiency of 97.0% for 250 cycles in lithium (Li)||copper (Cu) cell and a stable symmetric plating/stripping behavior over 2000 h at 3 mA cm−2 with ultrahigh Li utilization of 50%. Furthermore, the full cell coupled with PHL-Cu@Li anode and LiFePO4 cathode exhibits long-term cycle stability with high-capacity retention of 95.9% after 900 cycles. Impressively, the full cell paired with LiNi0.87Co0.1Mn0.03O2 maintains a discharge capacity of 170.0 mAh g−1 with a capacity retention of 84.3% after 100 cycles even under harsh condition of ultralow N/P ratio of 0.83. This facile strategy will widen the potential application of LiNO3 in ester-based electrolyte for practical high-voltage LMBs.

Abscisic acid (ABA) is a key hormone in plant growth and development, playing a central role in responses to various biotic and abiotic stresses as well as in fruit ripening. The present study examined the impact of ABA and nordihydroguaiaretic acid (NDGA) on various postharvest ‘Docteur Jules Guyot’ pear fruit characteristics, including firmness, pectinase activity, pectin content, volatile aromatic substances, and the expression of correlated genes. The results showed that ABA quickly reduced fruit firmness, increasing the activity of pectin degradation-related enzymes. The contents of water-soluble pectin (WSP) and ionic-soluble pectin (ISP) increased, and covalent binding pectin (CBP) decreased under ABA treatment. Among the detected volatile aromatic substances, the highest-level substance of the fruit was ester, and the ABA treatment significantly promoted the amount of ester substances. The cell wall disassembly-related genes PcPME3 , PcPG1 , PcPG2 , PcPL , PcARF2 , and PcGAL1 , as well as ABA biosynthesis-related genes PcNCED1 and PcNCED2 , were also significantly induced by ABA. Conversely, all these genes were repressed in the NDGA treatment group. Therefore, it was speculated that ABA may promote the softening of postharvest European pear fruit by affecting the activity of pectin degradation enzymes in fruit cell walls.