Long-term antagonistic effect of increased precipitation and nitrogen addition on soil respiration in a semiarid steppe

Changes in water and nitrogen (N) availability due to climate change and atmospheric N deposition could have significant effects on soil respiration, a major pathway of carbon (C) loss from terrestrial ecosystems. A manipulative experiment simulating increased precipitation and atmospheric N deposition has been conducted for 9 years (2005–2013) in a semiarid grassland in Mongolian Plateau, China. Increased precipitation and N addition interactively affect soil respiration through the 9 years. The interactions demonstrated that N addition weakened the precipitation-induced stimulation of soil respiration, whereas increased precipitation exacerbated the negative impacts of N addition. The main effects of increased precipitation and N addition treatment on soil respiration were 15.8% stimulated and 14.2% suppressed, respectively. Moreover, a declining pattern and 2-year oscillation were observed for soil respiration response to N addition under increased precipitation. The dependence of soil respiration upon gross primary productivity and soil moisture, but not soil temperature, suggests that resources C substrate supply and water availability are more important than temperature in regulating interannual variations of soil C release in semiarid grassland ecosystems. The findings indicate that atmospheric N deposition may have the potential to mitigate soil C loss induced by increased precipitation, and highlight that long-term and multi-factor global change studies are critical for predicting the general patterns of terrestrial C cycling in response to global change in the future

Learning Word Embeddings: Unsupervised Methods for Fixed-size Representations of Variable-length Speech Segments

International audienceFixed-length embeddings of words are very useful for a variety of tasks in speech and language processing. Here we systematically explore two methods of computing fixed-length embeddings for variable-length sequences. We evaluate their susceptibility to phonetic and speaker-specific variability on English, a high resource language and Xitsonga, a low resource language, using two evaluation metrics: ABX word discrimination and ROC-AUC on same-different phoneme n-grams. We show that a simple downsampling method supplemented with length information can outperform the variable-length input feature representation on both evaluations. Recurrent autoencoders, trained without supervision, can yield even better results at the expense of increased computational complexity

A method to monitor IGBT module bond wire failure using on-state voltage separation strategy

On-state voltage is an important thermal parameter for insulated gate bipolar transistor (IGBT) modules. It is employed widely to predict failure in IGBT module bond wires. However, due to restrictions in work environments and measurement methods, it is difficult to ensure the measurement accuracy for the on-state voltage under practical working conditions. To address this problem, an on-state voltage separation strategy is proposed for the IGBT modules with respect to the influence of collector current (Ic) and junction temperature (Tj). This method involves the separation of the on-state voltage into a dependent part and two independent parts during the IGBT module bond wire prediction. Based on the proposed separation strategy, the independent parts in the failure prediction can be removed, making it possible to directly monitor the voltage variations caused by bond wire failure. The experimental results demonstrate that the proposed diagnosis strategy can accurately predict the bond wire failure stage in an IGBT module under different conditions

Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the "Speaking Rosetta" JSALT 2017 Workshop

We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and words) in a language without orthography. We study the replacement of orthographic transcriptions by images and/or translated text in a well-resourced language to help unsupervised discovery from raw speech.Comment: Accepted to ICASSP 201

Study on the law of residual deformation in mining subsidence area and its influence on the safety of ground buildings

After the mining subsidence area reaches the stable state of surface movement, due to the continuous existence of the mutual extrusion and activation state between rock strata, the movement of particles, rock creep, and soil compression will affect the surface movement in the long-term stability, thereby threatening the safety and stability of the above ground buildings. In order to study the deformation law of rock strata movement and surface displacement after the mining subsidence area is stabilized, establish a ground deformation model caused by mining, explore the characteristics of ground movement and deformation under the action of building loads, design a similar material simulation experiment, record the ground movement changes within 378 days after the mining is completed, after the settlement is stabilized, apply equivalent loads of 10–30 floors to the model at different locations, and study various surface deformation data, Analyze the change rule. In order to quantitatively analyze the impact of residual deformation of goaf on buildings under building load, the D5 gate area of Tangshan World Horticultural Exposition in mining subsidence area is taken as an example to calculate the ground settlement value and other deformation data using probability analysis method, and the Kelvin model in rock mechanics is introduced in terms of the duration of residual deformation. The calculation results are close to the actual measured values, and the impact of residual deformation on the proposed building is analyzed

Genetic diversity, tissue-specific expression, and functional analysis of the ATP7A gene in sheep

In humans, variation of the ATP7A gene may cause cranial exostosis, which is similar to “human horn,” but the function of the ATP7A gene in sheep is still unknown. Tissue expression patterns and potential functional loci analysis of the ATP7A gene could help understand its function in sheep horn. In this study, we first identified tissue, sex, breed, and species-specific expression of the ATP7A gene in sheep based on the RNA-sequencing (RNA-seq) data. Second, the potential functional sites of the ATP7A gene were analyzed by using the whole genome sequencing (WGS) data of 99 sheep from 10 breeds. Last, the allele-specific expression of the ATP7A gene was explored. Our result showed the ATP7A gene has significantly higher expression in the big horn than in the small horn, and the ATP7A gene has high expression in the horn and skin, suggesting that this gene may be related to the horn. The PCA results show that the region around the ATP7A can distinguish horned and hornless groups to some extent, further indicating that the ATP7A may be related to horns. When compared with other species, we find seven ruminate specific amino acid sites of the ATP7A protein, which can be important to the ruminate horn. By analyzing WGS, we found 6 SNP sites with significant differences in frequency in horned and hornless populations, and most of these variants are present in the intron. But we still find some potential functional sites, including three missenses, three synonymous mutations, and four Indels. Finally, by combining the RNA-seq and WGS functional loci results, we find three mutations that showed allele-specific expression between big and small horns. This study shows that the ATP7A gene in sheep may be related to horn size, and several potential functional sites we identified here can be useful molecular markers for sheep horn breeding

Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the “Speaking rosetta” JSALT 2017 workshop

International audienceWe summarize the accomplishments of a multidisciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and words) in a language without orthography. We study the replacement of orthographic transcriptions by images and/or translated text in a well-resourced language to help unsuper-vised discovery from raw speech