A Few-shot Learning Model based on a Triplet Network for the Prediction of Energy Coincident Peak Days

In an electricity system, a coincident peak (CP) is defined as the highest daily power demand in a year, which plays an important role in keeping the balance between power supply and its demand. Advanced information about the time of coincident peaks would be helpful for both utility companies and their customers. This work addresses the prediction of the five coincident peak days (5CP) in a year. We present a few-shot learning model to classify a day as a 5CP day or a non-5CP day 24-hours ahead. A triplet network is implemented for the 2-way-5-shot classifications on six different historical datasets. The prediction results have an average (across the six datasets) mean recall of 0.933, mean precision of 0.603, and mean F1 score of 0.733

A facile route to encapsulate ultrasmall Ni clusters within the pore channels of AlPO-5

A simple one-step method to encapsulate Ni (II) into the pore channels of AlPO-5 molecule sieve was developed by using nickel-amine complexes as templating agent for synthesis of Ni(deta)2-AlPO-5. The Ni (II) occluded in the pores can be directly reduced by reducing gases in situ generated from the decomposition of nickel-amine complexes in AlPO-5 during heat treatment. The resulted catalyst has ultra-small Ni clusters highly dispersed into the pore channels, showing a high selectivity for 1,2-propanediol in the hydrogenolysis of glycerol

Annotation-free Audio-Visual Segmentation

The objective of Audio-Visual Segmentation (AVS) is to locate sounding objects within visual scenes by accurately predicting pixelwise segmentation masks. In this paper, we present the following contributions: (i), we propose a scalable and annotation-free pipeline for generating artificial data for the AVS task. We leverage existing image segmentation and audio datasets to draw links between category labels, image-mask pairs, and audio samples, which allows us to easily compose (image, audio, mask) triplets for training AVS models; (ii), we introduce a novel Audio-Aware Transformer (AuTR) architecture that features an audio-aware query-based transformer decoder. This architecture enables the model to search for sounding objects with the guidance of audio signals, resulting in more accurate segmentation; (iii), we present extensive experiments conducted on both synthetic and real datasets, which demonstrate the effectiveness of training AVS models with synthetic data generated by our proposed pipeline. Additionally, our proposed AuTR architecture exhibits superior performance and strong generalization ability on public benchmarks. The project page is https://jinxiang-liu.github.io/anno-free-AVS/.Comment: Under Revie

Audio-aware Query-enhanced Transformer for Audio-Visual Segmentation

The goal of the audio-visual segmentation (AVS) task is to segment the sounding objects in the video frames using audio cues. However, current fusion-based methods have the performance limitations due to the small receptive field of convolution and inadequate fusion of audio-visual features. To overcome these issues, we propose a novel \textbf{Au}dio-aware query-enhanced \textbf{TR}ansformer (AuTR) to tackle the task. Unlike existing methods, our approach introduces a multimodal transformer architecture that enables deep fusion and aggregation of audio-visual features. Furthermore, we devise an audio-aware query-enhanced transformer decoder that explicitly helps the model focus on the segmentation of the pinpointed sounding objects based on audio signals, while disregarding silent yet salient objects. Experimental results show that our method outperforms previous methods and demonstrates better generalization ability in multi-sound and open-set scenarios.Comment: arXiv admin note: text overlap with arXiv:2305.1101

Transcriptome Profiling Insights the Feature of Sex Reversal Induced by High Temperature in Tongue Sole Cynoglossus semilaevis

Sex reversal induced by temperature change is a common feature in fish. Usually, the sex ratio shift occurs when temperature deviates too much from normal during embryogenesis or sex differentiation stages. Despite decades of work, the mechanism of how temperature functions during early development and sex reversal remains mysterious. In this study, we used Chinese tongue sole as a model to identify features from gonad transcriptomic and epigenetic mechanisms involved in temperature induced masculinization. Some of genetic females reversed to pseudomales after high temperature treatment which caused the sex ratio imbalance. RNA-seq data showed that the expression profiles of females and males were significantly different, and set of genes showed sexually dimorphic expression. The general transcriptomic feature of pesudomales was similar with males, but the genes involved in spermatogenesis and energy metabolism were differentially expressed. In gonads, the methylation level of cyp19a1a promoter was higher in females than in males and pseudomales. Furthermore, high-temperature treatment increased the cyp19a1a promoter methylation levels of females. We observed a significant negative correlation between methylation levels and expression of cyp19ala. In vitro study showed that CpG within the cAMP response element (CRE) of the cyp19a1a promoter was hypermethylated, and DNA methylation decreased the basal and forskolin-induced activities of cyp19a1a promoter. These results suggested that epigenetic change, i.e., DNA methylation, which regulate the expression of cyp19a1a might be the mechanism for the temperature induced masculinization in tongue sole. It may be a common mechanism in teleost that can be induced sex reversal by temperature

Molecular Insights into Cage Occupancy of Hydrogen Hydrate: A Computational Study

Density functional theory calculations and molecular dynamics simulations were performed to investigate the hydrogen storage capacity in the sII hydrate. Calculation results show that the optimum hydrogen storage capacity is ~5.6 wt%, with the double occupancy in the small cage and quintuple occupancy in the large cage. Molecular dynamics simulations indicate that these multiple occupied hydrogen hydrates can occur at mild conditions, and their stability will be further enhanced by increasing the pressure or decreasing the temperature. Our work highlights that the hydrate is a promising material for storing hydrogen