Controlling the Amount of Verbatim Copying in Abstractive Summarization

An abstract must not change the meaning of the original text. A single most effective way to achieve that is to increase the amount of copying while still allowing for text abstraction. Human editors can usually exercise control over copying, resulting in summaries that are more extractive than abstractive, or vice versa. However, it remains poorly understood whether modern neural abstractive summarizers can provide the same flexibility, i.e., learning from single reference summaries to generate multiple summary hypotheses with varying degrees of copying. In this paper, we present a neural summarization model that, by learning from single human abstracts, can produce a broad spectrum of summaries ranging from purely extractive to highly generative ones. We frame the task of summarization as language modeling and exploit alternative mechanisms to generate summary hypotheses. Our method allows for control over copying during both training and decoding stages of a neural summarization model. Through extensive experiments we illustrate the significance of our proposed method on controlling the amount of verbatim copying and achieve competitive results over strong baselines. Our analysis further reveals interesting and unobvious facts.Comment: AAAI 2020 (Main Technical Track

CL-MVSNet:Unsupervised Multi-view Stereo with Dual-level Contrastive Learning

Unsupervised Multi-View Stereo (MVS) methods have achieved promising progress recently. However, previous methods primarily depend on the photometric consistency assumption, which may suffer from two limitations: indistinguishable regions and view-dependent effects, e.g., low-textured areas and reflections. To address these issues, in this paper, we propose a new dual-level contrastive learning approach, named CL-MVSNet. Specifically, our model integrates two contrastive branches into an unsupervised MVS framework to construct additional supervisory signals. On the one hand, we present an image-level contrastive branch to guide the model to acquire more context awareness, thus leading to more complete depth estimation in indistinguishable regions. On the other hand, we exploit a scene-level contrastive branch to boost the representation ability, improving robustness to view-dependent effects. Moreover, to recover more accurate 3D geometry, we introduce an ℒ0.5 photometric consistency loss, which encourages the model to focus more on accurate points while mitigating the gradient penalty of undesirable ones. Extensive experiments on DTU and Tanks&Temples benchmarks demonstrate that our approach achieves state-of-the-art performance among all end-to-end unsupervised MVS frameworks and outperforms its supervised counterpart by a considerable margin without fine-tuning

Uneven warming likely contributed to declining near-surface wind speeds in Northern China between 1961 and 2016

A decline in mean near-surface (10 m) wind speed has been widely reported for many land regions over recent decades, yet the underlying cause(s) remains uncertain. This study investigates changes in near-surface wind speed over northern China from 1961 to 2016, and analyzes the associated physical mechanisms using station observations, reanalysis products and model simulations from the Community Atmosphere Model version 5.1 (CAM5). The homogenized near-surface wind speed shows a significantly (p 50°N) in recent decades, which has weakened the annual and seasonal meridional air temperature gradient (−0.33°C to −0.12°C dec−1, p < 0.05, except autumn) between these regions (50°–60°N, 75°–135°E) and the northern China zone (35°–45°N, 75°–135°E). This caused a significant (p < 0.05) decrease in annual and seasonal pressure gradient (−0.43 to −0.20 hPa dec−1) between the two zones, which contributed to the slowdown of winds. CAM5 simulations demonstrate that spatially uneven air temperature increases and near-surface wind speed decreases over northern China can be realistically reproduced using the so-called “all forcing” simulation, while the “natural only forcing” simulation fails to realistically simulate the uneven warming patterns and declines in near-surface wind speed over most of northern China, except for summer.This study was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP, Grant No. 2019QZKK0606), the National Natural Science Foundation of China (Grant No. 41621061), and by the National Key Research and Development Program—Global Change and Mitigation Project (Grant No. 2016YFA0602404). This work was also supported by a Swedish Research Council (2017-03780) and a Swedish Research Council for Sustainable Development (2019-00509) grant, and by the IBER-STILLING project, funded by the Spanish Ministry of Science, Innovation and Universities (RTI2018-095749-A-I00; MCIU/AEI/FEDER, UE)

Rapid urbanization induced daily maximum wind speed decline in metropolitan areas: A case study in the Yangtze River Delta (China)

Wind extremes cause many environmental and natural hazard related problems globally, particularly in heavily populated metropolitan areas. However, the underlying causes of maximum wind speed variability in urbanized regions remain largely unknown. Here, we investigated how rapid urbanization in the Yangtze River Delta (YRD), China, impacted daily maximum wind speed (DMWS) between 1990 and 2015, based on near-surface (10 m height) DMWS observations, reanalysis datasets, and night-time lighting data (a proxy for urbanization). The station observation shows that annual DMWS in the YRD significantly (p 0.1) positive trends were found in NCEP-NCAR1 (+0.048 m s−1 decade−1) and ERA5 (+0.027 m s−1 decade−1). An increasing divergence between the reanalysis output and the station observation since 2005 was found, and those stations located in areas with high rates of urbanization show the strongest negative annual DMWS trend, implying the key role of urbanization in weakening DMWS. This finding is supported by sensitivity experiments conducted using a regional climate model (RegCM4) forced with both 1990 and 2015 land-use and land-cover (LULC) data, where the simulated DMWS using the 2015 LULC data was lower than that simulated using the 1990 LULC data.This study was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP, Grant No. 2019QZKK0606), the National Natural Science Foundation of China (Grant No. 42101027 and No.41621061). This work was also supported by a Swedish Research Council (2017-03780) and a Swedish Research Council for Sustainable Development (2019-00509) grant, and by the IBER-STILLING project, funded by the Spanish Ministry of Science, Innovation and Universities (RTI2018-095749-A-I00; MCIU/AEI/FEDER, UE). C.A.M. was supported by a Ramon y Cajal fellowship (RYC-2017-22830). L.M. was founded by the International Postdoc grant from the Swedish Research Council (2021-00444)

ceRNA crosstalk mediated by ncRNAs is a novel regulatory mechanism in fish sex determination and differentiation

Competing endogenous RNAs (ceRNAs) are vital regulators of gene networks in mammals. The involvement of noncoding RNAs (ncRNAs) as ceRNA in genotypic sex determination (GSD) and environmental sex determination (ESD) in fish is unknown. The Chinese tongue sole, which has both GSD and ESD mechanisms, was used to map the dynamic expression pattern of ncRNAs and mRNA in gonads during sex determination and differentiation. Transcript expression patterns shift during the sex differentiation phase, and ceRNA modulation occurs through crosstalk of differentially expressed long ncRNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and sex-related genes in fish. Of note was the significant up-regulation of a circRNA from the sex-determining gene dmrt1 (circular RNA dmrt1) and a lncRNA, called AMSDT (which stands for associated with male sex differentiation of tongue sole) in Chinese tongue sole testis. These two ncRNAs both share the same miRNA response elements with gsdf, which has an up-regulated expression when they bind to miRNA cse-miR-196 and concurrent down-regulated female sex-related genes to facilitate testis differentiation. This is the first demonstration in fish that ceRNA crosstalk mediated by ncRNAs modulates sexual development and unveils a novel regulatory mechanism for sex determination and differentiation.info:eu-repo/semantics/publishedVersio

The enormous repetitive Antarctic krill genome reveals environmental adaptations and population insights

Antarctic krill (Euphausia superba) is Earth’smost abundant wild animal, and its enormous biomass is vital to the Southern Ocean ecosystem. Here, we report a 48.01-Gb chromosome-level Antarctic krill genome, whose large genome size appears to have resulted from inter-genic transposable element expansions. Our assembly reveals the molecular architecture of the Antarctic krill circadian clock and uncovers expanded gene families associated with molting and energy metabolism, providing insights into adaptations to the cold and highly seasonal Antarctic environment. Population-level genome re-sequencing from four geographical sites around the Antarctic continent reveals no clear population structure but highlights natural selection associated with environmental variables. An apparent drastic reduction in krill population size 10 mya and a subsequent rebound 100 thousand years ago coincides with climate change events. Our findings uncover the genomic basis of Antarctic krill adaptations to the Southern Ocean and provide valuable resources for future Antarctic research

A Transcriptome Reveals the Mechanism of Nitrogen Regulation in Tillering

Nitrogen (N) application significantly increases tiller numbers and is accompanied by changes in endogenous hormone content. We treated seedlings of Festuca kirilowii—a perennial forage grass—with nitrogen, determined the endogenous hormone content in the tiller buds, and performed a transcriptome analysis. The application of N reduced GA3, ABA, and 5-DS content and increased ZT and IAA content. By screening DEGs in the transcriptome results, we obtained DEGs annotated to 25 GO entries and 8 KEGG pathways associated with endogenous hormones. Most of these GO entries and KEGG pathways were associated with IAA, GAS, and ABA. We conducted a validation analysis of hormone-related DEGs using qRT-PCR to demonstrate that nitrogen controls the content of endogenous hormones by regulating the expression of these DEGs, which further affects tillering in F. kirilowii

A Cloud Detection Method Based on Spectral and Gradient Features for SDGSAT-1 Multispectral Images

Due to the limited penetration of visible bands, optical remote sensing images are inevitably contaminated by clouds. Therefore, cloud detection or cloud mask products for optical image processing is a very important step. Compared with conventional optical remote sensing satellites (such as Landsat series and Sentinel-2), sustainable development science Satellite-1 (SDGSAT-1) multi-spectral imager (MII) lacks a short-wave infrared (SWIR) band that can be used to effectively distinguish cloud and snow. To solve the above problems, a cloud detection method based on spectral and gradient features (SGF) for SDGSAT-1 multispectral images is proposed in this paper. According to the differences in spectral features between cloud and other ground objects, the method combines four features, namely, brightness, normalized difference water index (NDWI), normalized difference vegetation index (NDVI), and haze-optimized transformation (HOT) to distinguish cloud and most ground objects. Meanwhile, in order to adapt to different environments, the dynamic threshold using Otsu’s method is adopted. In addition, it is worth mentioning that gradient features are used to distinguish cloud and snow in this paper. With the test of SDGSAT-1 multispectral images and comparison experiments, the results show that SGF has excellent performance. The overall accuracy of images with snow surface can reach 90.80%, and the overall accuracy of images with other surfaces is above 94%

A Novel Rotation Scheme for MEMS IMU Error Mitigation Based on a Missile-Borne Rotation Semi-Strapdown Inertial Navigation System

In previous research, a semi-strapdown inertial navigation system (SSINS), based on micro-electro-mechanical system (MEMS) sensors, was able to realize over-range measurement of the attitude information of high-rotation missiles by constructing a single axis &#8220;spin reduction&#8222; platform. However, the MEMS sensors in SSINS were corrupted by significant sensor errors. In order to further improve SSINS measurement accuracy, a rotational modulation technique has been introduced to compensate for sensor errors. The ideal modulation angular velocity is changed sharply to achieve a constant speed, while in practical applications, the angular rate of the rotating mechanism&#8217;s output needs to go through an acceleration-deceleration process. Furthermore, the stability of the modulation angular rate is difficult to achieve in a high-speed rotation environment. In this paper, a novel rotation scheme is proposed which can effectively suppress the residual error in the navigation coordinate system caused by the modulation angular rate error, including the acceleration-deceleration process and instability of angular rate. The experiment results show that the position and attitude accuracy of the new rotation scheme was increased by more than 56%. In addition, the proposed scheme is applicable to navigation accuracy improvement under various dynamic conditions