Pseudonocardians A–C, New Diazaanthraquinone Derivatives from a Deap-Sea Actinomycete Pseudonocardia sp. SCSIO 01299

Pseudonocardians A–C (2–4), three new diazaanthraquinone derivatives, along with a previously synthesized compound deoxynyboquinone (1), were produced by the strain SCSIO 01299, a marine actinomycete member of the genus Pseudonocardia, isolated from deep-sea sediment of the South China Sea. The structures of compounds 1–4 were determined by mass spectrometry and NMR experiments (1H, 13C, HSQC, and HMBC). The structure of compound 1, which was obtained for the first time from a natural source, was confirmed by X-ray analysis. Compounds 1–3 exhibited potent cytotoxic activities against three tumor cell lines of SF-268, MCF-7 and NCI-H460 with IC50 values between 0.01 and 0.21 μm, and also showed antibacterial activities on Staphylococcus aureus ATCC 29213, Enterococcus faecalis ATCC 29212 and Bacillus thuringensis SCSIO BT01, with MIC values of 1–4 μg mL−1

A radiative cooling structural material.

Reducing human reliance on energy-inefficient cooling methods such as air conditioning would have a large impact on the global energy landscape. By a process of complete delignification and densification of wood, we developed a structural material with a mechanical strength of 404.3 megapascals, more than eight times that of natural wood. The cellulose nanofibers in our engineered material backscatter solar radiation and emit strongly in mid-infrared wavelengths, resulting in continuous subambient cooling during both day and night. We model the potential impact of our cooling wood and find energy savings between 20 and 60%, which is most pronounced in hot and dry climates

Evolution of satellite derived chlorophyll-a trends in the Bohai and Yellow Seas during 2002-2018: Comparison between linear and nonlinear trends

The trends of sea surface chlorophyll-a (Chl-a) concentrations in the Bohai and Yellow Seas of China (BYS) were analysed based on the satellite-derived Chl-a dataset from August 2002 to December 2018. The result of linear trend analysis based on the seasonal Mann-Kendall test indicates a significant positive Chl-a trend during this period, with an average trend of similar to 1.15% year 1 (Slope: similar to 0.011 mg year 1). However, the linear trends of Chl-a varied seasonally, with strong and significant increases in spring and summer (about 2% year(-1)), and weak and non-significant increases in winter (lower than 1% year(-1)). The results of the ensemble empirical mode decomposition (EEMD) analysis revealed highly nonlinear and time-varying trends of Chl-a in the BYS, with gradually increased Chl-a during 2002-2011 and decreased Chl-a from 2012 to 2018. The instantaneous rate of Chl-a change was continuously reduced from 2002 to 2018, from a positive value of -2.0% year 1 around the beginning year (2002) to a negative value of approximately 2.0% year 1 around the recent year (2018). The temporal evolution of the Chl-a trend was well in accordance with the changes in nutrient enrichment, suggesting that the status of eutrophication might be the primary driver of the long-term trends in Chl-a. The increase (decrease) in nutrient levels could alleviate (aggravate) the nutrient limitation for phytoplankton growth in spring and summer, thus regulating the changes in Chl-a. In contrast, the Chl-a trend seems to be unrelated to the trend of light intensity in this area. This is the first study aimed to discern and compare the linear and evolutionary nonlinear Chl-a trends in the BYS and provides a baseline against which future changes can be monitored

Spatiotemporal characteristics and influencing factors of grain yield at the county level in Shandong Province, China

China's food security has always been a high priority issue on the political agenda with rapid urbanization affecting agricultural land, and it is challenged by several factors, such as human activities, social politics and policy. Shandong is an important grain-producing province and the second most populous province in China. In this paper, the spatiotemporal characteristics of grain yield and their potential influencing factors were explored at the county level in Shandong by using panel data over a 19-year period. The location Gini coefficient (L-Gini) and exploratory spatial data analysis (ESDA) were used to study the spatial agglomeration characteristics of grain yield, and spatial regression methods (SRMs) were used to analyse the influencing factors. The results indicated that grain yield increased from 38.3 million metric tons to 53.2 million metric tons in 2000-2018, with a growth rate of approximately 28.0%. The increase in grain yield in Shandong was due to the driving effect of radiation from high-yield counties to surrounding moderate-yield counties. This revealed an upward trend of spatial polarization in Shandong's grain yield. In 2000-2018, the L-Gini and global Moran's I increased from 0.330 to 0.479 and from 0.369 to 0.528, respectively. The number of counties in high-high (HH) and low-low (LL) agglomeration areas increased, and the spatial polarization effect was significant. SRMs analysis showed that irrigation investment and non-grain attention have significant positive and negative effects on grain production, respectively. The spatial relationship between grain yield and its influencing factors was explored to provide a reference for formulating scientific and rational agricultural policies

Image Watermarking Using Dither Modulation in Dual-Transform Domain

Abstract: A new method for inserting invisible watermark into a digital image is described, which uses two layers of orthogonal transforms, pseudorandom data shuffling and a dither modulation technique. Neither the original host image nor the inserted data string is needed in extraction of the watermark. Experiments show that watermark embedded in this way is sufficiently transparent and robust. A desired tradeoff between invisibility, robustness, and embedding capacity can be achieved by appropriately choosing the system parameters and the candidate coefficients for embedding

Retrieval of Aerosol Optical Depth in the Arid or Semiarid Region of Northern Xinjiang, China

Satellite remote sensing has been widely used to retrieve aerosol optical depth (AOD), which is an indicator of air quality as well as radiative forcing. The dark target (DT) algorithm is applied to low reflectance areas, such as dense vegetation, and the deep blue (DB) algorithm is adopted for bright-reflecting regions. However, both DT and DB algorithms ignore the effect of surface bidirectional reflectance. This paper provides a method for AOD retrieval in arid or semiarid areas, in which the key points are the accurate estimation of surface reflectance and reasonable assumptions of the aerosol model. To reduce the uncertainty in surface reflectance, a minimum land surface reflectance database at the spatial resolution of 500 m for each month was constructed based on the moderate-resolution imaging spectroradiometer (MODIS) surface reflectance product. Furthermore, a bidirectional reflectance distribution function (BRDF) correction model was adopted to compensate for the effect of surface reflectance anisotropy. The aerosol parameters, including AOD, single scattering albedo, asymmetric factor, Ångström exponent and complex refractive index, are determined based on the observation of two sunphotometers installed in northern Xinjiang from July to August 2014. The AOD retrieved from the MODIS images was validated with ground-based measurements and the Terra-MODIS aerosol product (MOD04). The 500 m AOD retrieved from the MODIS showed high consistency with ground-based AOD measurements, with an average correlation coefficient of ~0.928, root mean square error (RMSE) of ~0.042, mean absolute error (MAE) of ~0.032, and the percentage falling within the expected error (EE) of the collocations is higher than that for the MOD04 DB product. The results demonstrate that the new AOD algorithm is more suitable to represent aerosol conditions over Xinjiang than the DB standard product

Validation and Comparison of MODIS C6.1 and C6 Aerosol Products over Beijing, China

The operational Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Products (APs) have provided long-term and wide-spatial-coverage aerosol optical properties across the globe, such as aerosol optical depth (AOD). However, the performance of the latest Collection 6.1 (C6.1) of MODIS APs is still unclear over urban areas that feature complex surface characteristics and aerosol models. The aim of this study was to validate and compare the performance of the MODIS C6.1 and C6 APs (MxD04, x = O for Terra, x = Y for Aqua) over Beijing, China. The results of the Dark Target (DT) and Deep Blue (DB) algorithms were validated against Aerosol Robotic Network (AERONET) ground-based observations at local sites. The retrieval uncertainties and accuracies were evaluated using the expected error (EE: ±0.05 + 15%) and the root-mean-square error (RMSE). It was found that the MODIS C6.1 DT products performed better than the C6 DT products, with a greater percentage (by about 13%⁻14%) of the retrievals falling within the EE. However, the DT retrievals collected from two collections were significantly overestimated in the Beijing region, with more than 64% and 48% of the samples falling above the EE for the Terra and Aqua satellites, respectively. The MODIS C6.1 DB products performed similarly to the C6 DB products, with 70%⁻73% of the retrievals matching within the EE and estimation uncertainties. Moreover, the DB algorithm performed much better than DT algorithm over urban areas, especially in winter where abundant missing pixels were found in DT products. To investigate the effects of factors on AOD retrievals, the variability in the assumed surface reflectance and the main optical properties applied in DT and DB algorithms are also analyzed

Identification of Cellulose-Degrading Bacteria and Assessment of Their Potential Value for the Production of Bioethanol from Coconut Oil Cake Waste

Bioconversion of lignocellulosic biomass is a highly promising alternative to rapidly reduce reliance on fossil fuels and greenhouse gas emissions. However, the use of lignocellulosic biomass is limited by the challenges of efficient degradation strategies. Given this need, Bacillus tropicus (B. tropicus) with cellulose degradation ability was isolated and screened from rotten dahlia. The strain efficiently utilized coconut oil cake (COC) to secrete 167.3 U/mL of cellulase activity. Electron microscopy results showed significant changes in the structure and properties of cellulose after treatment with B. tropicus, which increased the surface accessibility and the efficiency of the hydrolysis process. The functional group modification observed by Fourier transform infrared spectroscopy indicated the successful depolymerization of COC. The X-ray diffraction pattern showed that the crystallinity index increased from 44.8% to 48.2% due to the hydrolysis of the amorphous region in COC. The results of colorimetry also reveal an efficient hydrolysis process. A co-culture of B. tropicus and Saccharomyces cerevisiae was used to produce ethanol from COC waste, and the maximum ethanol yield was 4.2 g/L. The results of this work show that B. tropicus can be used to prepare biotechnology value-added products such as biofuels from lignocellulosic biomass, suggesting promising utility in biotechnology applications