A New Electrolyte Formulation for Securing High Temperature Cycling and Storage Performances of Na‐Ion Batteries

The Na‐ion battery is recognized as a possible alternative to the Li‐ion battery for applications where power and cost override energy density performance. However, the increasing instability of their electrolyte with temperature is still problematic. Thus, a central question remains how to design Na‐based electrolytes. Here, the discovery of a Na‐based electrolyte formulation is reported which enlists four additives (vinylene carbonate, succinonitrile, 1,3‐propane sultone, and sodium difluoro(oxalate)borate) in proper quantities that synergistically combine their positive attributes to enable a stable solid electrolyte interphase at both negative and positive electrodes surface at 55 °C. Moreover, the role of each additive that consists in producing specific NaF coatings, thin elastomers, sulfate‐based deposits, and so on via combined impedance and X‐ray photoelectron spectroscopy is rationalized. It is demonstrated that empirical electrolyte design rules previously established for Li‐ion technology together with theoretical guidance is vital in the quest for better Na‐based electrolytes that can be extended to other chemistries. Overall, this finding, which is implemented to 18 650 cells, widens the route to the rapid development of the Na‐ion technology based on Na₃V₂(PO₄)₂F₃/C chemistry.     

Solution structure of the N‐terminal domain of DC‐UbP/UBTD2 and its interaction with ubiquitin

DC‐UbP/UBTD2 is a ubiquitin (Ub) domain‐containing protein first identified from dendritic cells, and is implicated in ubiquitination pathway. The solution structure and backbone dynamics of the C‐terminal Ub‐like (UbL) domain were elucidated in our previous work. To further understand the biological function of DC‐UbP, we then solved the solution structure of the N‐terminal domain of DC‐UbP (DC‐UbP_N) and studied its Ub binding properties by NMR techniques. The results show that DC‐UbP_N holds a novel structural fold and acts as a Ub‐binding domain (UBD) but with low affinity. This implies that the DC‐UbP protein, composing of a combination of both UbL and UBD domains, might play an important role in regulating protein ubiquitination and delivery of ubiquitinated substrates in eukaryotic cells.     

Water inputs across a tropical montane landscape in Veracruz,Mexico: synergistic effects of land cover,rain and fog seasonality,and interannual precipitation variability

Land‐cover change can alter the spatiotemporal distribution of water inputs to mountain ecosystems, an important control on land‐surface and land‐atmosphere hydrologic fluxes. In eastern Mexico, we examined the influence of three widespread land‐cover types, montane cloud forest, coffee agroforestry, and cleared areas, on total and net water inputs to soil. Stand structural characteristics, as well as rain, fog, stemflow, and throughfall (water that falls through the canopy) water fluxes were measured across 11 sites during wet and dry seasons from 2005 to 2008. Land‐cover type had a significant effect on annual and seasonal net throughfall (NTF <0=canopy water retention plus canopy evaporation; NTF >0=fog water deposition). Forest canopies retained and/or lost to evaporation (i.e. NTF<0) five‐ to 11‐fold more water than coffee agroforests. Moreover, stemflow was fourfold higher under coffee shade than forest trees. Precipitation seasonality and phenological patterns determined the magnitude of these land‐cover differences, as well as their implications for the hydrologic cycle. Significant negative relationships were found between NTF and tree leaf area index (R²=0.38, P<0.002), NTF and stand basal area (R²=0.664, P<0.002), and stemflow and epiphyte loading (R²=0.414, P<0.001). These findings indicate that leaf and epiphyte surface area reductions associated with forest conversion decrease canopy water retention/evaporation, thereby increasing throughfall and stemflow inputs to soil. Interannual precipitation variability also altered patterns of water redistribution across this landscape. Storms and hurricanes resulted in little difference in forest‐coffee wet season NTF, while El Niño Southern Oscillation was associated with a twofold increase in dry season rain and fog throughfall water deposition. In montane headwater regions, changes in water delivery to canopies and soils may affect infiltration, runoff, and evapotranspiration, with implications for provisioning (e.g. water supply) and regulating (e.g. flood mitigation) ecosystem services.     

Preparation of capacitor’s electrode from sunflower seed shell

Series of nanoporous carbons are prepared from sunflower seed shell (SSS) by two different strategies and used as electrode material for electrochemical double-layer capacitor (EDLC). The surface area and pore-structure of the nanoporous carbons are characterized intensively using N₂ adsorption technique. The results show that the pore-structure of the carbons is closely related to activation temperature and dosage of KOH. Electrochemical measurements show that the carbons made by impregnation-activation process have better capacitive behavior and higher capacitance retention ratio at high drain current than the carbons made by carbonization-activation process, which is due to that there are abundant macroscopic pores and less interior micropore surface in the texture of the former. More importantly, the capacitive performances of these carbons are much better than ordered mesoporous carbons and commercial wood-based active carbon, thus highlighting the success of preparing high performance electrode material for EDLC from SSS.     

A cross-talk between epithelium and endothelium mediates human alveolar–capillary injury during SARS-CoV-2 infection

COVID-19, caused by SARS-CoV-2, is an acute and rapidly developing pandemic, which leads to a global health crisis. SARS-CoV-2 primarily attacks human alveoli and causes severe lung infection and damage. To better understand the molecular basis of this disease, we sought to characterize the responses of alveolar epithelium and its adjacent microvascular endothelium to viral infection under a co-culture system. SARS-CoV-2 infection caused massive virus replication and dramatic organelles remodeling in alveolar epithelial cells, alone. While, viral infection affected endothelial cells in an indirect manner, which was mediated by infected alveolar epithelium. Proteomics analysis and TEM examinations showed viral infection caused global proteomic modulations and marked ultrastructural changes in both epithelial cells and endothelial cells under the co-culture system. In particular, viral infection elicited global protein changes and structural reorganizations across many sub-cellular compartments in epithelial cells. Among the affected organelles, mitochondrion seems to be a primary target organelle. Besides, according to EM and proteomic results, we identified Daurisoline, a potent autophagy inhibitor, could inhibit virus replication effectively in host cells. Collectively, our study revealed an unrecognized cross-talk between epithelium and endothelium, which contributed to alveolar–capillary injury during SARS-CoV-2 infection. These new findings will expand our understanding of COVID-19 and may also be helpful for targeted drug development.Subject terms: Mechanisms of disease, Viral infection     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.