Neutron Energy Spectrum Measurements with a Compact Liquid Scintillation Detector on EAST

A neutron detector based on EJ301 liquid scintillator has been employed at EAST to measure the neutron energy spectrum for D-D fusion plasma. The detector was carefully characterized in different quasi-monoenergetic neutron fields generated by a 4.5 MV Van de Graaff accelerator. In recent experimental campaigns, due to the low neutron yield at EAST, a new shielding device was designed and located as close as possible to the tokamak to enhance the count rate of the spectrometer. The fluence of neutrons and gamma-rays was measured with the liquid neutron spectrometer and was consistent with 3He proportional counter and NaI (Tl) gamma-ray spectrometer measurements. Plasma ion temperature values were deduced from the neutron spectrum in discharges with lower hybrid wave injection and ion cyclotron resonance heating. Scattered neutron spectra were simulated by the Monte Carlo transport Code, and they were well verified by the pulse height measurements at low energies.Comment: 19 pages,10 figures, 1 tabl

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

Spatiotemporal Variations of Ecosystem Service Indicators and the Driving Factors Under Climate Change in the Qinghai–Tibet Highway Corridor

In recent decades, the influence of climate change and human activities on the ecosystem services (ES) in the Qinghai–Tibet Plateau (QTP) has been extensively investigated. However, few studies focus on linear traffic corridor area, which is heavily affected by human activities. Taking the Golmud–Lhasa national highway corridor as a case, this study investigated the land-use and land-cover change (LUCC) and spatiotemporal variations of ES indicators using ecosystem indices of fractional vegetation cover (FVC), leaf area index (LAI), evapotranspiration (ET), and net primary productivity (NPP) from 2000 to 2020. The results indicated that LUCC was faster in the last decade, mostly characterized by the conversion from grassland to unused land. In buffer within 3000 m, the proportions of productive areas represented the increased trends with distance. In terms of ES variations, the improved areas outweighed the degraded areas in terms of FVC, LAI, and NPP from 2000 to 2020, mostly positioned in the Qinghai Province. In addition, FVC, LAI, and NPP peaked at approximately 6000 m over time. With regard to influencing factors, precipitation (20.54%) and temperature (14.19%) both positively influenced the spatiotemporal variation of FVC. Nearly 60% of the area exhibited an increased NPP over time, especially in the Qinghai Province, which could be attributed to the temperature increase over the last two decades. In addition, the distance effects of climatic factors on ES indicators exhibited that the coincident effects almost showed an opposite trend, while the reverse effects showed a similar trend. The findings of this study could provide a reference for the ecological recovery of traffic corridors in alpine fragile areas

Rethinking the Metric in Few-shot Learning: From an Adaptive Multi-Distance Perspective

Few-shot learning problem focuses on recognizing unseen classes given a few labeled images. In recent effort, more attention is paid to fine-grained feature embedding, ignoring the relationship among different distance metrics. In this paper, for the first time, we investigate the contributions of different distance metrics, and propose an adaptive fusion scheme, bringing significant improvements in few-shot classification. We start from a naive baseline of confidence summation and demonstrate the necessity of exploiting the complementary property of different distance metrics. By finding the competition problem among them, built upon the baseline, we propose an Adaptive Metrics Module (AMM) to decouple metrics fusion into metric-prediction fusion and metric-losses fusion. The former encourages mutual complementary, while the latter alleviates metric competition via multi-task collaborative learning. Based on AMM, we design a few-shot classification framework AMTNet, including the AMM and the Global Adaptive Loss (GAL), to jointly optimize the few-shot task and auxiliary self-supervised task, making the embedding features more robust. In the experiment, the proposed AMM achieves 2% higher performance than the naive metrics fusion module, and our AMTNet outperforms the state-of-the-arts on multiple benchmark datasets

Study on Total Amount Accounting of Pollutants Entering Qinghe River Basin

The calculation of the total amount of pollutants entering the river is the key to the total amount control system. Since non-point source pollution has not been monitored normally and effectively, based on the principle of the balance of input and output of pollutants, the 2009-2013 Qinghe water quality monitoring data, pollution source survey data and monitoring data were used to establish a binary statistics of the total amount of pollutants model. MATLAB software is used to solve the model. The results show that the model has strong data assimilation ability, can accurately calculate the monthly COD inflow into the river, can divide the point source and non-point source pollution load, and can meet the needs of actual research