Biochar is widely recognized as an efficient tool for carbon sequestration and soil fertility. The understanding of its chemical and physical properties, which are strongly related to the type of the initial material used and pyrolysis conditions, is crucial to identify the most suitable application of biochar in soil. A selection of organic wastes with different characteristics (e.g., rice husk (RH), rice straw (RS), wood chips of apple tree (Malus pumila) (AB), and oak tree (Quercus serrata) (OB)) were pyrolyzed at different temperatures (400, 500, 600, 700, and 800 °C) in order to optimize the physicochemical properties of biochar as a soil amendment. Low-temperature pyrolysis produced high biochar yields; in contrast, high-temperature pyrolysis led to biochars with a high C content, large surface area, and high adsorption characteristics. Biochar obtained at 600 °C leads to a high recalcitrant character, whereas that obtained at 400 °C retains volatile and easily labile compounds. The biochar obtained from rice materials (RH and RS) showed a high yield and unique chemical properties because of the incorporation of silica elements into its chemical structure. The biochar obtained from wood materials (AB and OB) showed high carbon content and a high absorption character.

What is the smallest protein? This is actually not such a simple question to answer, because there is no established consensus among scientists as to the definition of a protein. We describe here a designed molecule consisting of only 10 amino acids. Despite its small size, its essential characteristics, revealed by its crystal structure, solution structure, thermal stability, free energy surface, and folding pathway network, are consistent with the properties of natural proteins. The existence of this kind of molecule deepens our understanding of proteins and impels us to define an “ideal protein” without inquiring whether the molecule actually occurs in nature.

Global carbon cycle research and climate change mitigation measures require a means for large-scale monitoring of forest aboveground biomass (AGB). L-band synthetic aperture radar (SAR) is one of promising means, although its signal is saturated at 75–150 Mg ha−1 of AGB, making it difficult to monitor high biomass forest. The Advanced Land Observing Satellite-2/Phased Array L-band SAR-2 (PALSAR-2) conducts ScanSAR mode observations that cover the whole tropical region about nine times a year. We investigated whether such time-series data is effective in overcoming the signal saturation issue. In Borneo, we adopted a spaceborne Light Detection and Ranging (LiDAR) Ice, Cloud, and Land Elevation/Geoscience Laser Altimeter System (GLAS)-derived AGB data for training and validation data, then developed an AGB estimation model using the Random Forest algorithm. As a result, we improved the saturation issue, and estimated the AGB up to 280 Mg ha−1 with a root mean square error (RMSE) of 62.8 Mg ha−1. Such an AGB range covers 83% of Borneo's forests. The developed model was applied to create an AGB map of Borneo with a 250-m resolution as of 2016. Total AGB of Borneo was calculated at 12.8 Gt with an average of 173.3 Mg ha−1. This article showed the PALSAR-2 time-series data to be highly useful in the AGB mapping of high carbon stock forests. However, we needed to correct the difference in observation years between GLAS and PALSAR-2 using a simple biomass growth model, but the accuracy will be improved by using future LiDAR and SAR sensors.

Background: Evolutionary relations of similar segments shared by different protein folds remain controversial, even though many examples of such segments have been found. To date, several methods such as those based on the results of structure comparisons, sequence-based classifications, and sequence-based profile-profile comparisons have been applied to identify such protein segments that possess local similarities in both sequence and structure across protein folds. However, to capture more precise sequence-structure relations, no method reported to date combines structure-based profiles, and sequence-based profiles based on evolutionary information. The former are generally regarded as representing the amino acid preferences at each position of a specific conformation of protein segment. They might reflect the nature of ancient short peptide ancestors, using the results of structural classifications of protein segments.Results: This report describes the development and use of "Cross Profile Analysis" to compare sequence-based profiles and structure-based profiles based on amino acid occurrences at each position within a protein segment cluster. Using systematic cross profile analysis, we found structural clusters of 9-residue and 15-residue segments showing remarkably strong correlation with particular sequence profiles. These correlations reflect structural similarities among constituent segments of both sequence-based and structure-based profiles. We also report previously undetectable sequence-structure patterns that transcend protein family and fold boundaries, and present results of the conformational analysis of the deduced peptide of a segment cluster. These results suggest the existence of ancient short-peptide ancestors.Conclusions: Cross profile analysis reveals the polyphyletic and convergent evolution of β-hairpin-like structures, which were verified both experimentally and computationally. The results presented here give us new insights into the evolution of short protein segments.