Optimizing Bacillus circulans Xue-113168 for biofertilizer production and its effects on crops

In this study, Bacillus circulans Xue-113168 biofertilizer was produced through solid state fermentation processes using food waste and feldspar. Results confirmed that solid state fermentation has considerable advantages compared to complex process (solid-state and bio-bleach). The control of pH, temperature, and humidity effectively led to the formation of 2×109 cfu/g spore and dissolution of potassium at a rate of 41.53%. Compound microbial fertilizer (CMF), formulated by humic acid and K2HPO4 with biofertilizer, has a quick and durable effect. CMF increases the yield of rapeseeds by 75 to 89%, provides higher vitamin C and reduces nitrate in leaf. Yields of selenium-enriched jujube and jujube increased, respectively, in the CMF compared to the matrix control; rates of anthracnose and rust diseases also decreased. Furthermore, our results showed that CMF improved soil properties, such as organic matter, NPK content from 8.83 to 16.16 kg hm2, and reduced chemical fertilizer from 25 to 11%, respectively. For convenient medium, robust process and good effect, CMF is suitable for potassium deficiency and undeveloped arable land resources.Keywords: compound microbial fertilizer, Bacillus circulans Xue-113168, solid-state fermentation (SSF), process, optimiz

Prototyping of LAI and FPAR retrievals from MODIS multi-angle implementation of atmospheric correction (MAIAC) data

Leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR) absorbed by vegetation are key variables in many global models of climate, hydrology, biogeochemistry, and ecology. These parameters are being operationally produced from Terra and Aqua MODIS bidirectional reflectance factor (BRF) data. The MODIS science team has developed, and plans to release, a new version of the BRF product using the multi-angle implementation of atmospheric correction (MAIAC) algorithm from Terra and Aqua MODIS observations. This paper presents analyses of LAI and FPAR retrievals generated with the MODIS LAI/FPAR operational algorithm using Terra MAIAC BRF data. Direct application of the operational algorithm to MAIAC BRF resulted in an underestimation of the MODIS Collection 6 (C6) LAI standard product by up to 10%. The difference was attributed to the disagreement between MAIAC and MODIS BRFs over the vegetation by −2% to +8% in the red spectral band, suggesting different accuracies in the BRF products. The operational LAI/FPAR algorithm was adjusted for uncertainties in the MAIAC BRF data. Its performance evaluated on a limited set of MAIAC BRF data from North and South America suggests an increase in spatial coverage of the best quality, high-precision LAI retrievals of up to 10%. Overall MAIAC LAI and FPAR are consistent with the standard C6 MODIS LAI/FPAR. The increase in spatial coverage of the best quality LAI retrievals resulted in a better agreement of MAIAC LAI with field data compared to the C6 LAI product, with the RMSE decreasing from 0.80 LAI units (C6) down to 0.67 (MAIAC) and the R2 increasing from 0.69 to 0.80. The slope (intercept) of the satellite-derived vs. field-measured LAI regression line has changed from 0.89 (0.39) to 0.97 (0.25).This work was funded by NASA Earth Science Division to MODIS (NNX14AI71G) and VIIRS (NNX14AP80A) programs through grants to Boston University (Ranga B. Myneni, PI), and HBO contract # 21205-14-036 to Yuri Knyazikhin. (NNX14AI71G - NASA; NNX14AP80A - NASA; 21205-14-036 - HBO contract)http://www.mdpi.com/2072-4292/9/4/370Published versio

A DenseNet-based method for decoding auditory spatial attention with EEG

Auditory spatial attention detection (ASAD) aims to decode the attended spatial location with EEG in a multiple-speaker setting. ASAD methods are inspired by the brain lateralization of cortical neural responses during the processing of auditory spatial attention, and show promising performance for the task of auditory attention decoding (AAD) with neural recordings. In the previous ASAD methods, the spatial distribution of EEG electrodes is not fully exploited, which may limit the performance of these methods. In the present work, by transforming the original EEG channels into a two-dimensional (2D) spatial topological map, the EEG data is transformed into a three-dimensional (3D) arrangement containing spatial-temporal information. And then a 3D deep convolutional neural network (DenseNet-3D) is used to extract temporal and spatial features of the neural representation for the attended locations. The results show that the proposed method achieves higher decoding accuracy than the state-of-the-art (SOTA) method (94.4% compared to XANet's 90.6%) with 1-second decision window for the widely used KULeuven (KUL) dataset, and the code to implement our work is available on Github: https://github.com/xuxiran/ASAD_DenseNe

Rapid detection of phosphine resistance in the lesser grain borer, Rhyzopertha dominica (Coleoptera: Bostrychidae) from China using ARMS-PCR: Poster

MThe lesser grain borer, Rhyzopertha dominica is one of the serious cosmopolitan stored grain pests worldwide. High phosphine resistant R. dominica has been reported in several countries. The evolution of strong phosphine resistance is a major challenge for continuous application of the fumigant. Rapid detection of phosphine resistance level is a prime key to implement an appropriate strategy for control the stored-product pests. Dihydrolipoamide dehydrogenase (DLD) is a key metabolic enzyme mediating the phosphine resistance in population of R. dominica, Tribolium castaneum and Caenorhabditis elegans. Analysis of the DLD sequences deposited in GenBank revealed that the P45/49S mutation was the most common one in many PH3-resistant stored-product pest insects. This information now enables direct detection of resistance using molecular diagnosis in field populations. We herein propose a method for rapid detection of phosphine resistance in R. dominica according to P49S point mutation of the DLD gene. Our data provides evidence that the ARMS-PCR method can be used for early warning of phosphine resistance in R. dominica in field conditions.MThe lesser grain borer, Rhyzopertha dominica is one of the serious cosmopolitan stored grain pests worldwide. High phosphine resistant R. dominica has been reported in several countries. The evolution of strong phosphine resistance is a major challenge for continuous application of the fumigant. Rapid detection of phosphine resistance level is a prime key to implement an appropriate strategy for control the stored-product pests. Dihydrolipoamide dehydrogenase (DLD) is a key metabolic enzyme mediating the phosphine resistance in population of R. dominica, Tribolium castaneum and Caenorhabditis elegans. Analysis of the DLD sequences deposited in GenBank revealed that the P45/49S mutation was the most common one in many PH3-resistant stored-product pest insects. This information now enables direct detection of resistance using molecular diagnosis in field populations. We herein propose a method for rapid detection of phosphine resistance in R. dominica according to P49S point mutation of the DLD gene. Our data provides evidence that the ARMS-PCR method can be used for early warning of phosphine resistance in R. dominica in field conditions

Division Gets Better: Learning Brightness-Aware and Detail-Sensitive Representations for Low-Light Image Enhancement

Low-light image enhancement strives to improve the contrast, adjust the visibility, and restore the distortion in color and texture. Existing methods usually pay more attention to improving the visibility and contrast via increasing the lightness of low-light images, while disregarding the significance of color and texture restoration for high-quality images. Against above issue, we propose a novel luminance and chrominance dual branch network, termed LCDBNet, for low-light image enhancement, which divides low-light image enhancement into two sub-tasks, e.g., luminance adjustment and chrominance restoration. Specifically, LCDBNet is composed of two branches, namely luminance adjustment network (LAN) and chrominance restoration network (CRN). LAN takes responsibility for learning brightness-aware features leveraging long-range dependency and local attention correlation. While CRN concentrates on learning detail-sensitive features via multi-level wavelet decomposition. Finally, a fusion network is designed to blend their learned features to produce visually impressive images. Extensive experiments conducted on seven benchmark datasets validate the effectiveness of our proposed LCDBNet, and the results manifest that LCDBNet achieves superior performance in terms of multiple reference/non-reference quality evaluators compared to other state-of-the-art competitors. Our code and pretrained model will be available.Comment: 14 pages, 16 figure

Engineered myocardial tissues constructed in vivo using cardiomyocyte-like cells derived from bone marrow mesenchymal stem cells in rats

<p>Abstract</p> <p>Background</p> <p>To explore the feasibility of constructing engineered myocardial tissues (EMTs) <it>in vivo</it>, using polylactic acid -co-glycolic acid (PLGA) for scaffold and cardiomyocyte-like cells derived from bone marrow mesenchymal stem cells (BMMSCs) for seeded cells.</p> <p>Methods</p> <p>BMMSCs were isolated from femur and tibia of Sprague-Dawley (SD) rats by density-gradient centrifugation. The third passage cells were treated with 10 μmol/L 5-azacytidine (5-aza) and 0.1 μmol/L angiotensin II (Ang II) for 24 h, followed by culturing in complete medium for 3 weeks to differentiated into cardiomyocyte-like cells. The cardiomyocyte-like cells were seeded into PLGA scaffolds to form the grafts. The grafts were cultured in the incubator for three days and then implanted into the peritoneal cavity of SD rats. Four weeks later, routine hematoxylin-eosin (HE) staining, immunohistochemical staining for myocardium-specific cardiac troponin I (cTnI), scanning electron microscopy and transmission electron microscopy were used to analyze the morphology and microconstruction of the EMTs in host rats.</p> <p>Results</p> <p>HE staining showed that the cardiomyocyte-like cells distributed equally in the PLGA scaffold, and the nuclei arranged in the spindle shape. Immunohistochemical staining revealed that majority of engrafted cells in the PLGA -Cardiomyocyte-like cells group were positive for cTnI. Scanning electron microscopy showed that the inoculated cells well attached to PLGA and grew in 3 dimensions in construct. Transmission electron microscopy showed that the EMTs contained well arranged myofilaments paralleled to the longitudinal cell axis, the cells were rich in endoplasmic reticulum and mitochondria, while desmosomes, gap junction and Z line-like substances were also can be observed as well within the engrafted cells.</p> <p>Conclusion</p> <p>We have developed an in vivo method to construct engineered myocardial tissue. The <it>in vivo </it>microenvironment helped engrafted cells/tissue survive and share similarities with the native heart tissue.</p