Stratified Rule-Aware Network for Abstract Visual Reasoning

Abstract reasoning refers to the ability to analyze information, discover rules at an intangible level, and solve problems in innovative ways. Raven's Progressive Matrices (RPM) test is typically used to examine the capability of abstract reasoning. The subject is asked to identify the correct choice from the answer set to fill the missing panel at the bottom right of RPM (e.g., a 3$\times$3 matrix), following the underlying rules inside the matrix. Recent studies, taking advantage of Convolutional Neural Networks (CNNs), have achieved encouraging progress to accomplish the RPM test. However, they partly ignore necessary inductive biases of RPM solver, such as order sensitivity within each row/column and incremental rule induction. To address this problem, in this paper we propose a Stratified Rule-Aware Network (SRAN) to generate the rule embeddings for two input sequences. Our SRAN learns multiple granularity rule embeddings at different levels, and incrementally integrates the stratified embedding flows through a gated fusion module. With the help of embeddings, a rule similarity metric is applied to guarantee that SRAN can not only be trained using a tuplet loss but also infer the best answer efficiently. We further point out the severe defects existing in the popular RAVEN dataset for RPM test, which prevent from the fair evaluation of the abstract reasoning ability. To fix the defects, we propose an answer set generation algorithm called Attribute Bisection Tree (ABT), forming an improved dataset named Impartial-RAVEN (I-RAVEN for short). Extensive experiments are conducted on both PGM and I-RAVEN datasets, showing that our SRAN outperforms the state-of-the-art models by a considerable margin.Comment: AAAI 2021 paper. Code: https://github.com/husheng12345/SRA

Genomic and Proteomic Analyses of the Fungus Arthrobotrys oligospora Provide Insights into Nematode-Trap Formation

Nematode-trapping fungi are “carnivorous” and attack their hosts using specialized trapping devices. The morphological development of these traps is the key indicator of their switch from saprophytic to predacious lifestyles. Here, the genome of the nematode-trapping fungus Arthrobotrys oligospora Fres. (ATCC24927) was reported. The genome contains 40.07 Mb assembled sequence with 11,479 predicted genes. Comparative analysis showed that A. oligospora shared many more genes with pathogenic fungi than with non-pathogenic fungi. Specifically, compared to several sequenced ascomycete fungi, the A. oligospora genome has a larger number of pathogenicity-related genes in the subtilisin, cellulase, cellobiohydrolase, and pectinesterase gene families. Searching against the pathogen-host interaction gene database identified 398 homologous genes involved in pathogenicity in other fungi. The analysis of repetitive sequences provided evidence for repeat-induced point mutations in A. oligospora. Proteomic and quantitative PCR (qPCR) analyses revealed that 90 genes were significantly up-regulated at the early stage of trap-formation by nematode extracts and most of these genes were involved in translation, amino acid metabolism, carbohydrate metabolism, cell wall and membrane biogenesis. Based on the combined genomic, proteomic and qPCR data, a model for the formation of nematode trapping device in this fungus was proposed. In this model, multiple fungal signal transduction pathways are activated by its nematode prey to further regulate downstream genes associated with diverse cellular processes such as energy metabolism, biosynthesis of the cell wall and adhesive proteins, cell division, glycerol accumulation and peroxisome biogenesis. This study will facilitate the identification of pathogenicity-related genes and provide a broad foundation for understanding the molecular and evolutionary mechanisms underlying fungi-nematodes interactions

Estimation of the Underlying F0 Range of a Speaker from the Spectral Features of a Brief Speech Input

From a very brief speech, human listeners can estimate the pitch range of the speaker and normalize pitch perception. Spectral features which inherently involve both articulatory and phonatory characteristics were speculated to play roles in this process, but few were reported to directly correlate with speaker’s F0 range. To mimic this human auditory capability and validate the speculation, in a preliminary study we proposed an LSTM-based method to estimate speaker’s F0 range from a 300 ms-long speech input, which turned out to outperform the conventional method. By two more experiments, this study further improved the method and verified its validity in estimating the speaker-specific underlying F0 range. After incorporating a novel measurement of F0 range and a multi-task training approach, Experiment 1 showed that the refined model gave more accurate estimates than the initial model. Based on a Japanese-Chinese bilingual parallel speech corpus, Experiment 2 found that the F0 ranges estimated with the model from the Chinese speech and the model from the Japanese speech produced by the same set of speakers had no significant difference, whereas the conventional method showed significant difference. The results indicate that the proposed spectrum-based method captures the speaker-specific underlying F0 range which is independent of the linguistic content

Numerical Simulation and Experimental Research on Multi-Channel Laser Directional Energy Deposition of IN718

In this paper, the deposition layer calculation model is proposed for laser-directed energy deposition (DED) with coaxial powder feeding by combining the powder feeding equation with the volume of fluid (VOF) method, and the single-channel IN718 forming process is simulated in real-time with moving boundary conditions in a fixed coordinate system and experimentally validated. Under single-layer single-channel deposition processing, the deposition height and width decreased by 57.1% and 21.6%, respectively, as the scanning speed increased from 8 mm/s to 14 mm/s. The calculated deposition height, width, and melt pool depth were in good agreement with the experimental results. Calculating the temperature field distribution of the single-layer double-channel deposition at an overlapping-rate of 30% yielded the temperature fluctuation pattern of the deposition at various lap moments. Under the influence of the thermal accumulation of the first deposition channel, the latent heat effect of the melt pool will cause the maximum surface temperature during overlap processing to be slightly lower than the maximum surface temperature during single channel processing; at the same time, under the influence of the high-temperature state of the overlap deposition channel during the scanning process, the first deposition channel will exhibit rewarming during the overlap scanning process. The deposition layer and temperature field of single-layer multi-channel laser deposition are modelled using this information. It has been proved that the model may be used to forecast deposition and temperature fields for intricate processing procedures. The study findings are significant for understanding the process mechanism of coaxial powder feeding laser-directed energy deposition in detail and optimizing the process

Numerical Simulation and Experimental Research on Multi-Channel Laser Directional Energy Deposition of IN718

In this paper, the deposition layer calculation model is proposed for laser-directed energy deposition (DED) with coaxial powder feeding by combining the powder feeding equation with the volume of fluid (VOF) method, and the single-channel IN718 forming process is simulated in real-time with moving boundary conditions in a fixed coordinate system and experimentally validated. Under single-layer single-channel deposition processing, the deposition height and width decreased by 57.1% and 21.6%, respectively, as the scanning speed increased from 8 mm/s to 14 mm/s. The calculated deposition height, width, and melt pool depth were in good agreement with the experimental results. Calculating the temperature field distribution of the single-layer double-channel deposition at an overlapping-rate of 30% yielded the temperature fluctuation pattern of the deposition at various lap moments. Under the influence of the thermal accumulation of the first deposition channel, the latent heat effect of the melt pool will cause the maximum surface temperature during overlap processing to be slightly lower than the maximum surface temperature during single channel processing; at the same time, under the influence of the high-temperature state of the overlap deposition channel during the scanning process, the first deposition channel will exhibit rewarming during the overlap scanning process. The deposition layer and temperature field of single-layer multi-channel laser deposition are modelled using this information. It has been proved that the model may be used to forecast deposition and temperature fields for intricate processing procedures. The study findings are significant for understanding the process mechanism of coaxial powder feeding laser-directed energy deposition in detail and optimizing the process