Systematic calibration of epitranscriptomic maps using a synthetic modification-free RNA library.

Recent years have witnessed rapid progress in the field of epitranscriptomics. Functional interpretation of the epitranscriptome relies on sequencing technologies that determine the location and stoichiometry of various RNA modifications. However, contradictory results have been reported among studies, bringing the biological impacts of certain RNA modifications into doubt.

RNA demethylation increases the yield and biomass of rice and potato plants in field trials.

RNA N-methyladenosine (mA) modifications are essential in plants. Here, we show that transgenic expression of the human RNA demethylase FTO in rice caused a more than threefold increase in grain yield under greenhouse conditions. In field trials, transgenic expression of FTO in rice and potato caused ~50% increases in yield and biomass.

A Multi-Clustering Algorithm to Solve Driving Cycle Prediction Problems Based on Unbalanced Data Sets: A Chinese Case Study.

Vehicle evaluation parameters, which are increasingly of concern for governments and consumers, quantify performance indicators, such as vehicle performance, emissions, and driving experience to help guide consumers in purchasing cars. While past approaches for driving cycle prediction have been proven effective and used in many countries, these algorithms are difficult to use in China with its complex traffic environment and increasingly high frequency of traffic jams. Meanwhile, we found that the vehicle dataset used by the driving cycle prediction problem is usually unbalanced in real cases, which means that there are more medium and high speed samples and very few samples at low and ultra-high speeds.

A new characterization methodology for starch gelatinization.

A gelatinization degree control system, with a combination of Artificial Neural Networks (ANNs) and computer vision, was successfully developed. An intelligent measurement framework was purposely designed to achieve a precise investigation on phase transition and morphology change of starch in real time, as well as a process control during gelatinization. Base on a variation of birefringence number, the degree of gelatinization (DG) control system provided a direct and fast methodology without subjective uncertainty in studying starch gelatinization.