Feature Representation Learning with Adaptive Displacement Generation and Transformer Fusion for Micro-Expression Recognition

Micro-expressions are spontaneous, rapid and subtle facial movements that can neither be forged nor suppressed. They are very important nonverbal communication clues, but are transient and of low intensity thus difficult to recognize. Recently deep learning based methods have been developed for micro-expression (ME) recognition using feature extraction and fusion techniques, however, targeted feature learning and efficient feature fusion still lack further study according to the ME characteristics. To address these issues, we propose a novel framework Feature Representation Learning with adaptive Displacement Generation and Transformer fusion (FRL-DGT), in which a convolutional Displacement Generation Module (DGM) with self-supervised learning is used to extract dynamic features from onset/apex frames targeted to the subsequent ME recognition task, and a well-designed Transformer Fusion mechanism composed of three Transformer-based fusion modules (local, global fusions based on AU regions and full-face fusion) is applied to extract the multi-level informative features after DGM for the final ME prediction. The extensive experiments with solid leave-one-subject-out (LOSO) evaluation results have demonstrated the superiority of our proposed FRL-DGT to state-of-the-art methods

The catadromous teleost Anguilla japonica has a complete enzymatic repertoire for the biosynthesis of docosahexaenoic acid from alpha-linolenic acid: Cloning and functional characterization of an Elovl2 elongase

The Japanese eel Anguilla japonica is a catadromous fish species with considerable farming scale. Previous studies showed that dietary α-linolenic acid (18:3n-3) and linoleic acid (18:2n-6) satisfied essential fatty acid requirements in eel, which suggested that Japanese eel should have a complete pathway for the biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFA). However, existing knowledge was insufficient to explain the molecular basis of LC-PUFA biosynthetic capacity in eel. In order to further characterize this pathway in eel, a full-length cDNA of a putative fatty acyl elongase was isolated, with the ORF encoding a protein with 294 amino acids. The putative elongase displayed high homology to Elovl2 of other teleosts. Functional characterization by heterologous expression in yeast showed the protein product of the cDNA had high activity towards C20 and C22 PUFA substrates and low activity towards C18 PUFA substrates, characteristic of Elovl2 elongases. Tissue distribution of the elovl2 mRNA showed highest expression in brain and eyes, which was different from freshwater and anadromous species. This may reflect an important role for this enzyme in the in situ endogenous biosynthesis of docosahexaenoic acid (DHA) in neural tissues in eel. This is the first report of an Elovl2 in a catadromous teleost and demonstrates that Japanese eel has a complete enzyme repertoire required for the endogenous biosynthesis of DHA via the Sprecher pathway. These data have increased our knowledge of the diversity of LC-PUFA biosynthesis in vertebrates, and provided further insight into the regulatory mechanisms of LC-PUFA biosynthesis in teleost fish

Classification and Analysis of Multiple Cattle Unitary Behaviors and Movements Based on Machine Learning Methods.

peer reviewedThe behavior of livestock on farms is the primary representation of animal welfare, health conditions, and social interactions to determine whether they are healthy or not. The objective of this study was to propose a framework based on inertial measurement unit (IMU) data from 10 dairy cows to classify unitary behaviors such as feeding, standing, lying, ruminating-standing, ruminating-lying, and walking, and identify movements during unitary behaviors. Classification performance was investigated for three machine learning algorithms (K-nearest neighbors (KNN), random forest (RF), and extreme boosting algorithm (XGBoost)) in four time windows (5, 10, 30, and 60 s). Furthermore, feed tossing, rolling biting, and chewing in the correctly classified feeding segments were analyzed by the magnitude of the acceleration. The results revealed that the XGBoost had the highest performance in the 60 s time window with an average F1 score of 94% for the six unitary behavior classes. The F1 score of movements is 78% (feed tossing), 87% (rolling biting), and 87% (chewing). This framework offers a possibility to explore more detailed movements based on the unitary behavior classification

Defective Expression of Mitochondrial, Vacuolar H+-ATPase and Histone Genes in a C. elegans Model of SMA

Spinal muscular atrophy (SMA) is a severe motor neuron degenerative disease caused by loss-of-function mutations in the survival motor neuron gene SMN1. It is widely posited that defective gene expression underlies SMA. However, the identities of these affected genes remain to be elucidated. By analyzing the transcriptome of a Caenorhabditis elegans SMA model at the pre-symptomatic stage, we found that the expression of numerous nuclear encoded mitochondrial genes and vacuolar H+-ATPase genes was significantly down-regulated, while that of histone genes was significantly up-regulated. We previously showed that the uaf-1 gene, encoding key splicing factor U2AF large subunit, could affect the behavior and lifespan of smn-1 mutants. Here, we found that smn-1 and uaf-1 interact to affect the recognition of 3′ and 5′ splice sites in a gene-specific manner. Altogether, our results suggest a functional interaction between smn-1 and uaf-1 in affecting RNA splicing and a potential effect of smn-1 on the expression of mitochondrial and histone genes

Ocean internal tides suppress tropical cyclones in the South China Sea

Tropical Cyclones (TCs) are devastating natural disasters. Analyzing four decades of global TC data, here we find that among all global TC-active basins, the South China Sea (SCS) stands out as particularly difficult ocean for TCs to intensify, despite favorable atmosphere and ocean conditions. Over the SCS, TC intensification rate and its probability for a rapid intensification (intensification by ≥ 15.4 m s−1 day−1) are only 1/2 and 1/3, respectively, of those for the rest of the world ocean. Originating from complex interplays between astronomic tides and the SCS topography, gigantic ocean internal tides interact with TC-generated oceanic near-inertial waves and induce a strong ocean cooling effect, suppressing the TC intensification. Inclusion of this interaction between internal tides and TC in operational weather prediction systems is expected to improve forecast of TC intensity in the SCS and in other regions where strong internal tides are present