OR-Gate: A Noisy Label Filtering Method for Speaker Verification

The deep learning models used for speaker verification are heavily dependent on large-scale data and correct labels. However, noisy (wrong) labels often occur, which deteriorates the system's performance. Unfortunately, there are relatively few studies in this area. In this paper, we propose a method to gradually filter noisy labels out at the training stage. We compare the network predictions at different training epochs with ground-truth labels, and select reliable (considered correct) labels by using the OR gate mechanism like that in logic circuits. Therefore, our proposed method is named as OR-Gate. We experimentally demonstrated that the OR-Gate can effectively filter noisy labels out and has excellent performance.Comment: Submitted to 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023

Assessing hydrological sensitivity to future climate change in the Canadian southern boreal forest

Global Water Future

EZH2 RIP-seq Identifies Tissue-specific Long Non-coding RNAs.

BackgroundPolycomb Repressive Complex 2 (PRC2) catalyzes histone methylation at H3 Lys27, and plays crucial roles during development and diseases in numerous systems. Its catalytic subunit EZH2 represents a key nuclear target for long non-coding RNAs (lncRNAs) that emerging to be a novel class of epigenetic regulator and participate in diverse cellular processes. LncRNAs are characterized by high tissue-specificity; however, little is known about the tissue profile of the EZH2- interacting lncRNAs.ObjectiveHere we performed a global screening for EZH2-binding lncRNAs in tissues including brain, lung, heart, liver, kidney, intestine, spleen, testis, muscle and blood by combining RNA immuno- precipitation and RNA sequencing. We identified 1328 EZH2-binding lncRNAs, among which 470 were shared in at least two tissues while 858 were only detected in single tissue. An RNA motif with specific secondary structure was identified in a number of lncRNAs, albeit not in all EZH2-binding lncRNAs. The EZH2-binding lncRNAs fell into four categories including intergenic lncRNA, antisense lncRNA, intron-related lncRNA and promoter-related lncRNA, suggesting diverse regulations of both cis and trans-mechanisms. A promoter-related lncRNA Hnf1aos1 bound to EZH2 specifically in the liver, a feature same as its paired coding gene Hnf1a, further confirming the validity of our study. In addition to the well known EZH2-binding lncRNAs like Kcnq1ot1, Gas5, Meg3, Hotair and Malat1, majority of the lncRNAs were firstly reported to be associated with EZH2.ConclusionOur findings provide a profiling view of the EZH2-interacting lncRNAs across different tissues, and suggest critical roles of lncRNAs during cell differentiation and maturation

A missing link in the estuarine nitrogen cycle?: coupled nitrification-denitrification mediated by suspended particulate matter

In estuarine and coastal ecosystems, the majority of previous studies have considered coupled nitrification-denitrification (CND) processes to be exclusively sediment based, with little focus onsuspended particulate matter (SPM) in the water column. Here, we present evidence of CND processes in the water column of Hangzhou Bay, one of the largest macrotidal embayments in the world

RecycleGPT: An Autoregressive Language Model with Recyclable Module

Existing large language models have to run K times to generate a sequence of K tokens. In this paper, we present RecycleGPT, a generative language model with fast decoding speed by recycling pre-generated model states without running the whole model in multiple steps. Our approach relies on the observation that adjacent tokens in a sequence usually have strong correlations and the next token in a sequence can be reasonably guessed or inferred based on the preceding ones. Experiments and analysis demonstrate the effectiveness of our approach in lowering inference latency, achieving up to 1.4x speedup while preserving high performance.Comment: Technical Repor

ERCC2, ERCC1 polymorphisms and haplotypes, cooking oil fume and lung adenocarcinoma risk in Chinese non-smoking females

<p>Abstract</p> <p>Background</p> <p>Excision repair cross-complementing group 1 (ERCC1) and group 2 (ERCC2) proteins play important roles in the repair of DNA damage and adducts. Single nucleotide polymorphisms (SNPs) of DNA repair genes are suspected to influence the risk of lung cancer. This study aimed to investigate the association between the <it>ERCC2 </it>751, 312 and <it>ERCC1 </it>118 polymorphisms and the risk of lung adenocarcinoma in Chinese non-smoking females.</p> <p>Methods</p> <p>A hospital-based case-control study of 285 patients and 285 matched controls was conducted. Information concerning demographic and risk factors was obtained for each case and control by a trained interviewer. After informed consent was obtained, each person donated 10 ml blood for biomarker testing. Three polymorphisms were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method.</p> <p>Results</p> <p>This study showed that the individuals with the combined <it>ERCC2 </it>751AC/CC genotypes were at an increased risk for lung adenocarcinoma compared with those carrying the AA genotype [adjusted odds ratios (OR) 1.64, 95% confidence interval (CI) 1.06-2.52]. The stratified analysis suggested that increased risk associated with <it>ERCC2 </it>751 variant genotypes (AC/CC) was more pronounced in individuals without exposure to cooking oil fume (OR 1.98, 95%CI 1.18-3.32) and those without exposure to fuel smoke (OR 2.47, 95%CI 1.46-4.18). Haplotype analysis showed that the A-G-T and C-G-C haplotypes were associated with increased risk of lung adenocarcinoma among non-smoking females (ORs were 1.43 and 2.28, 95%CIs were 1.07-1.91 and 1.34-3.89, respectively).</p> <p>Conclusion</p> <p><it>ERCC2 </it>751 polymorphism may be a genetic risk modifier for lung adenocarcinoma in non-smoking females in China.</p

Agriculture intensifies soil moisture decline in Northern China

Northern China is one of the most densely populated regions in the world. Agricultural activities have intensified since the 1980s to provide food security to the country. However, this intensification has likely contributed to an increasing scarcity in water resources, which may in turn be endangering food security. Based on in-situ measurements of soil moisture collected in agricultural plots during 1983–2012, we find that topsoil (0–50cm) volumetric water content during the growing season has declined significantly (p < 0.01), with a trend of −0.011 to −0.015 m3 m−3 per decade. Observed discharge declines for the three large river basins are consistent with the effects of agricultural intensification, although other factors (e.g. dam constructions) likely have contributed to these trends. Practices like fertilizer application have favoured biomass growth and increased transpiration rates, thus reducing available soil water. In addition, the rapid proliferation of water-expensive crops (e.g., maize) and the expansion of the area dedicated to food production have also contributed to soil drying. Adoption of alternative agricultural practices that can meet the immediate food demand without compromising future water resources seem critical for the sustainability of the food production system

Analysis of high-position landslide characteristics based on multi-source remote sensing data：A case study of the Yanwo Village landslide in Rongshan Town, Lizhou District, Guangyuan City

On October 6, 2021, a high-position landslide disaster occurred in Yanwo Village，Rongshan Town, Lizhou District, Guangyuan City,Sichuan Province, around 13: 00. The landslide resulted in the destruction of 4 houses, 3 power lines, the burial of a 170-meter-long rural road, and the blockage of a 350-meter-long river channel. By utilizing a variety of remote sensing information sources, including multi-period satellite data before and after landslide, high-precision UAV aerial images, and airborne LiDAR data, the characteristics of high landslide and its sliding mode are studied by using a four-dimensional analysis approach combining three-dimensional space with time. Starting from the development background of high landslide, the deformation and failure characteristics and sliding mode of high landslide are summarized by analyzing the deformation characteristics before sliding and the dynamic procession of the high landslide. Based on the deduced landslide progression and the stability evaluation of the residual landslide at the rear, three sliding modes for future high-position landslide events are predicted and analyzed: Firstly, the back edge of landslide continues to be disjointed and move, causing a direct shear failure of the front part of the landslide by squeezing. Secondly, the trailing edge of the landslide continues to be disjointed and move, resulting in the sliding landslide occurs along the existing landslide channel. Thirdly, the initiation of the front part of the landslide trigger a tractional landslide in the middle and rear parts of the landslide. High-position landslides are common in the southwest mountainous areas, and during early geological hazard investigations, they should be effectively identified, and disaster prevention and mitigation measures should be strengthened