Neighboring Molecular Engineering in Diels-Alder Chemistry Enabling Easily Recyclable Carbon Fiber Reinforced Composites.

Although a variety of dynamic covalent bonds have been successfully used in the development of diverse sustainable thermosetting polymers and their composites, solving the trade-off between recovery efficiency and comprehensive properties is still a major challenge. Herein, a "one-stone-two-birds" strategy of lower rotational energy barrier (Er ) phosphate-derived Diels-Alder (DA) cycloadditions was proposed for easily recyclable carbon fiber (CF)-reinforced epoxy resins (EPs) composites. In such a strategy, the phosphate spacer with lower Er accelerated the segmental mobility and dynamic DA exchange reaction for network rearrangement to achieve high-efficiency repairing, reprocessing of the EPs matrix and its composites and rapid nondestructive recycling of CF; meanwhile, incorporating phosphorus-based units especially reduced their fire hazards. The resulting materials simultaneously showed excellent thermal/mechanical properties, superb fire safety and facile recyclability, realizing the concept of recycling for high-performance thermosetting polymers and composites. This strategy is of great significance for understanding and enriching the molecular connotation of DA chemistry, making it potentially applicable to the design and development of a wide range of dynamic covalent adaptable materials toward practical cutting-edge-tech applications.

Decade-low aerosol levels over the Bohai and Yellow Seas amid the COVID-19 lockdown.

Coronavirus disease 2019 (COVID-19) has crucially influenced anthropogenic activities, which in turn impacts upon the environment. In this study, we investigated the variations on aerosol optical depth (AOD) at 550 nm over the Bohai Sea and Yellow Sea during the COVID-19 lockdown (from February to March in 2020) of China mainland based on Moderate-resolution Imaging Spectroradiometer (MODIS) observation by comparing with historical AOD records (2011-2019). Our results show that with the lockdown implementation, the decade-low AOD levels are achieved in February and March 2020 (0.39 ± 0.18 and 0.37 ± 0.19, respectively), which are 22% and 28% (p < 0.01) lower than the average AOD between 2011 and 2019 (0.50 ± 0.08 and 0.52 ± 0.05, respectively). After the lockdown restrictions were relaxed and industrial production gradually resumed, the AOD in April 2020 rebounded to the historical average level. Besides, compared with historical observations (2011-2019), the AOD temporal variability from February to April 2020 showed different pattern, with the decade-high increase from March to April (+0.11) and decade-low increase from February to March (-0.01). Independent observations and simulation, including fine particulate matter (PM2.5) from ground-based measurements, wind field from Cross-Calibrated Multi-Platform, satellite-derived aerosol type, and back trajectories calculation by Hybird Single Paricle Lagrangian Intergrated Trajectory (HYSPLIT) model, indicated that the above abnormal AOD variation can be attributed to reduction of anthropogenic emissions during the COVID-19 lockdown period. The results of this paper, therefore, indicate that aerosols over the Bohai and Yellow Seas are strongly influenced by human activities, and the public health events such as the epidemic may alter the intensity of human activities and thus the spatio-temporal pattern of aerosol over ocean. With the global spread of the epidemic and the corresponding significant changes in human behavior patterns (restrictions on human activities, etc.), more studies should be carried out in the future about the aerosol variability and its potential impact on the marine environment.

Super-resolution optical mapping of floating macroalgae from geostationary orbit.

The spatial resolution of an observation from a geostationary orbiting satellite is usually too coarse to track small scale macroalgae blooms. For macroalgae mapping to benefit from a geostationary orbit's staring monitoring and frequent revisit intervals, we introduced a super-resolution method that reconstructs a high-resolution (HR) image of a region from a sequence of raw geostationary low-resolution images of the same region. We tested our method with GF-4 images at 50 m spatial resolution and demonstrated that the spatial resolution increased to 25 m. In addition, the derived HR image had better image quality characterized by a higher signal-to-noise ratio, clarity, and contrast. The increased spatial resolution and improved image quality improved our ability to distinguish macroalgae patches from the surrounding waters, especially tiny patches of macroalgae, and to precisely delineate the patch boundaries. Lastly, we more accurately estimated the areal coverage of the patches by reducing underestimation of the coverage of tiny patches and overestimation of the coverage of large patches.

Heritability of the aged glutathione phenotype is dependent on tissue of origin.

Glutathione is a ubiquitous antioxidant that protects cells against reactive oxygen species and other chemical stressors. Despite its functional importance, the impact of genetics on the glutathione system has yet to be fully appreciated. Here, we investigated the heritability of glutathione levels and redox status in a disease-relevant condition: advanced age. We assembled a panel of 18-21-month-old mice representing 19 inbred strains and quantified the levels of reduced and oxidized glutathione, and their sums and ratios, in liver, kidney, heart, pancreas, cerebral cortex, and striatum. Heritability values were calculated for each phenotype and the results varied by tissue of origin. Cardiac glutathione phenotypes exhibited the highest heritabilities (G2 = 0.44-0.67), while striatal glutathione was least heritable (G2 = 0.11-0.29). Statistical relationships between tissues were evaluated, and the emergence of significant correlations suggested that despite tissue-specific heritabilities, at least some shared regulatory mechanisms may exist. Overall, these data highlight another mechanism by which genetic background determines antioxidant protection and stress resistance.

A refined deep-learning-based algorithm for harmful-algal-bloom remote-sensing recognition using Noctiluca scintillans algal bloom as an example.

Harmful algal blooms (HABs) are challenging to recognize because of their striped and uneven biomass distributions. To address this issue, a refined deep-learning algorithm termed HAB-Ne was developed for the recognition of HABs in GF-1 Wide Field of View (WFV) images using Noctiluca scintillans algal bloom as an example. First, a pretrained image super-resolution model was integrated to improve the spatial resolution of the GF-1 WFV images and minimize the impact of mixed pixels caused by the strip distribution. Side-window convolution was also explored to enhance the edge features of HABs and minimize the effects of uneven biomass distribution. In addition, a convolutional encoder-decoder network was constructed for threshold-free HAB recognition to address the dependence on thresholds in existing methods. HAB-Net effectively recognized HABs from GF-1 WFV images, achieving an average precision of 90.1% and an F1-score of 0.86. HAB-Net showed more fine-grained recognition results than those of existing methods, with over 4% improvement in the F1-Score, especially in the marginal areas of HAB distribution. The algorithm demonstrated its effectiveness in recognizing HABs in different marine environments, such as the Yellow Sea, East China Sea, and northern Vietnam. Additionally, the algorithm was proven suitable for detecting the macroalga Sargassum. This study demonstrates the potential of deep-learning-based fine-grained recognition of HABs, which can be extended to the recognition of other fine-scale and strip-distributed objects, such as oil spills and Ulva prolifera.

A new amide from the marine sponge Haliclona baeri.

A new amide, baeriamide (1), along with nine known diketopiperazines (2-10), was isolated from the marine sponge Haliclona baeri. Their structures were identified by the means of UV, IR, MS and NMR. The absolute configuration of 1 was established by Marfey's method and comparing the specific optical rotation with the known compound HCO-Val-Gly methyl ester. Compound 1 was derived from dehydration of formylated L-valine with γ-amino-butanoic acid methyl ester. Compounds 2-10 were isolated from the genus of Haliclona for the first time. The absolute confirmation of 7 was confirmed first by the means of single-crystal X-ray diffraction. The cytotoxic, antibacterial, antiviral and antifouling activities of these compounds were also tested. However, none of them exhibited significant bioactivities.

Ginsenoside Rd Ameliorates High Fat Diet-Induced Obesity by Enhancing Adaptive Thermogenesis in a cAMP-Dependent Manner.

OBJECTIVE: With the discovery of thermogenic adipocytes in humans, it has been hypothesized that enhancing adaptive thermogenesis may improve obesity. Although many studies have found that ginseng can improve obesity, the beneficial effects of ginsenoside Rd on obesity and its mechanisms have not been studied. METHODS: High-fat diet-induced obese mice were used as the study subjects, with intraperitoneal injection of Rd daily at a dose of 15 mg/kg. Body weight and energy metabolism were observed. The effects of Rd on glucose tolerance, insulin sensitivity, and cold tolerance were tested. The expression of genes associated with thermogenesis was analyzed. Finally, the mechanisms by which Rd regulates adaptive thermogenesis were studied. RESULTS: Rd ameliorated obesity and insulin resistance. Rd increased cold tolerance through enhancing thermogenic gene expression in brown adipose tissue and increased the browning of white adipose tissue induced by cold stress. Rd increased intracellular cyclic adenosine monophosphate (cAMP) content. Decreasing intracellular cAMP levels by an inhibitor of adenylyl cyclase SQ22536 abolished the promoting effects of Rd on the expression of thermogenic genes. CONCLUSIONS: Rd improves obesity and insulin resistance. The upregulation of thermogenesis by Rd is dependent on the cAMP/protein kinase A signaling pathway.

Remote sensing estimation of the biomass of floating Ulva prolifera and analysis of the main factors driving the interannual variability of the biomass in the Yellow Sea.

Since 2007, green tide blooms with Ulva prolifera as the dominant species have occurred every summer in the Yellow Sea. Biomass is a critical parameter used to describe the severity of green tide blooms. In this study, we analyzed the relationships between several indices (normalized difference vegetation index (NDVI), floating algae index (FAI), ratio vegetation index (RVI), enhanced vegetation index (EVI), ocean surface algal bloom index (OSABI), Korea Ocean Satellite Center (KOSC) approach) and the biomass per unit area of Ulva prolifera by using the in situ measurements from a water tank experiment. EVI, NDVI, and FAI showed strong exponential relationships with Ulva prolifera biomass per unit area. In order to apply the relationships to satellite remote sensing data, the impacts of the atmosphere (different aerosol optical depth at 550 nm) and mixed pixels to the relationships were analyzed. The results show that atmosphere has little effect on the relationship between EVI and Ulva prolifera biomass per unit area with R2 = 0.94 and APD (the average percentage deviation) = 19.55% when EVI is calculated from Rrc (Rayleigh-corrected reflectance), and R2 = 0.95 and APD = 17.53% when EVI is calculated from Rtoa (top-of-atmosphere reflectance). Due to the low sensitivity to the atmosphere, the EVI relationship can be directly utilized in the top-of-atmosphere (TOA) reflectance without atmospheric correction. In addition, the EVI was slightly affected by mixed pixels with the APD only increased by ~10%. The EVI relationship was then applied to a long MODIS image time series to obtain the maximal total biomass of floating Ulva prolifera in the Yellow Sea from 2007 to 2016. The results showed that the maximum and minimum total biomass occurred in 2016 (~1.17 million tons) and 2012 (~0.074 million tons), respectively. The main factors that caused the inter-annual biomass variability were analyzed. The total amount of nutrients from Sheyang River which was the largest river on the northern coast of Jiangsu Province, and Porphyra cultivation in the Radial Sand Ridges of Jiangsu Province had both strong correlation with Ulva prolifera total biomass.

Connection-Improved Conductive Network of Carbon Nanotubes in a Rubber Cross-Link Network.

Conductive rubber composites usually suffer a large filler content and relatively low conductivity because the uniform dispersion of conductive nanofillers in rubbers is probably inhibited by the cross-link networks. However, by establishing a double-network model of cross-link and conductive networks, we found the connection of one-dimensional nanofillers could be improved by cross-link networks, which stabilized the conductive network. The percolation value of nanofillers could reduce to 0.06 wt % in experiments, using carbon nanotubes (CNTs) with 9.5 nm diameter and 1.5 µm length as nanofillers and poly(dimethylsiloxane) as the matrix. Moreover, the conductive network owned a critical exponent of 5.63, which was higher than that of conventional conductive networks (ca. 2). This feature proved that the connection between CNTs was improved by the poly(dimethylsiloxane) cross-link network. This work subverted the fundamental conception that cross-link networks in rubbers should make fillers aggregate, and we believed it would conduce to the development of sensors and flexible devices of rubber composites.