Plant long noncoding RNAs: Recent progress in understanding their roles in growth, development, and stress responses.

Long noncoding RNA (lncRNA) transcripts are longer than 200 nt and are not translated into proteins. LncRNAs function in a wide variety of processes in plants and animals, but, perhaps because of their lower expression and conservation levels, plant lncRNAs had attracted less attention than protein-coding mRNAs. Now, recent studies have made remarkable progress in identifying lncRNAs and understanding their functions. In this review, we discuss a number of lncRNAs that have important functions in growth, development, reproduction, responses to abiotic stresses, and regulation of disease and insect resistance in plants. Additionally, we describe the known mechanisms of action of plant lncRNAs according to their origins within the genome. This review thus provides a guide for identifying and functionally characterizing new lncRNAs in plants.

A Study on Seizure Detection of EEG Signals Represented in 2D.

A seizure is a neurological disorder caused by abnormal neuronal discharges in the brain, which severely reduces the quality of life of patients and often endangers their lives. Automatic seizure detection is an important research area in the treatment of seizure and is a prerequisite for seizure intervention. Deep learning has been widely used for automatic detection of seizures, and many related research works decomposed the electroencephalogram (EEG) raw signal with a time window to obtain EEG signal slices, then performed feature extraction on the slices, and represented the obtained features as input data for neural networks. There are various methods for EEG signal decomposition, feature extraction, and representation, and most of the studies have been based on fixed hardware resources for the design of the scheme, which reduces the adaptability of the scheme in different application scenarios and makes it difficult to optimize the algorithms in the scheme. To address the above issues, this paper proposes a deep learning-based model for seizure detection, mainly characterized by the two-dimensional representation of EEG features and the scalability of neural networks. The model modularizes the main steps of seizure detection and improves the adaptability of the model to different hardware resource constraints, in order to increase the convenience of the algorithm optimization or the replacement of each module. The proposed model consists of five parts, and the model was tested using two epilepsy datasets separately. The experimental results showed that the proposed model has strong generality and good classification accuracy for seizure detection.

Transcriptome and metabolome analyses reveal the responses of brown planthoppers to RH resistant rice cultivar.

The brown planthopper (BPH) Nilaparvata lugens (Stål) (Hemiptera: Delphacidae) is one of the most destructive rice pests in Asia. The application of insect-resistant rice cultivars is currently one of the principal means of controlling BPH. Understanding the physiological response mechanisms of BPH feeding on insect-resistant rice is the key for maintaining rice yield. Here, we measured the ecological fitness and analyzed the whole-body transcriptome and metabolome of BPH reared on susceptible cultivar Taichung Native 1 (TN1) and resistant cultivar Rathu Heenati (RH). Our results showed that RH significantly decreased the survival rate, female adult weight, honeydew secretion, the number of eggs laid per female and fat content of BPH. We identified 333 upregulated and 486 downregulated genes in BPH feeding on RH. These genes were mainly involved in energy metabolism, amino acid metabolism, hormone synthesis and vitamin metabolism pathways. We also detected 145 differentially accumulated metabolites in BPH reared on RH plants compared to BPH reared on TN1 plants, including multiple carbohydrates, amino acids, lipids, and some nucleosides. Combined analyses of transcriptome and metabolome showed that five pathways, including starch, sucrose, and galactose metabolism, were altered. The network for these pathways was subsequently visualized. Our results provide insights into the mechanisms of metabolite accumulation in BPH feeding on the RH rice variety. The results could help us better understand how insect-resistant rice cultivars combat BPH infestation, which is important for the comprehensive management of BPH.

An optimal selection method of wells for secondary fracturing in a single coal seam and its application.

At present, methods including mathematical modeling, physical or numerical simulation, and in-situ monitoring have been generally adopted to determine evaluation parameters for coalbed methane (CBM) wells for secondary fracturing. These conventional methods either entail many assumptions, or some parameters are difficult to obtain, resulting in a certain deviation between the evaluation results and reality, or the application cost is high, preventing the monitoring of each CBM well. In view of this, an evaluation index system for the gas production potential, effective length of cracks formed by fracturing, and supporting length of proppant in cracks was established based on the system theory. The evaluation indices were characterized through production data, such as logging, fracturing and drainage, which could avoid potential bias in evaluation when only considering a certain parameter and ensured accuracy and practicability of the evaluation parameters for each well. Principal component analysis (PCA) and the entropy weight method (EWM) were used to obtain weights of evaluation parameters, which avoided the contradiction of contributions of various parameters to optimal selection and the rationalized results. In this way, a method for step-wise optimal selection of wells for secondary fracturing integrating construction of evaluation parameters, determination of critical values, and entropy evaluation was proposed. The results of an evaluation of the Shizhuang South Block of Qinshui Basin (Shanxi Province, China) indicate that wells whose three evaluation indices are satisfied are most preferable; wells that only meet the effective length of cracks formed by fracturing or effective supporting length of proppant in cracks can be selected; wells which do not meet the gas production potential or all of the three parameters cannot be selected.