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The Plasmodium falciparum drugome and its polypharmacological implications [article]

Yinliang Zhang, Li Xie, Lei Xie, Philip Bourne
2016 bioRxiv   pre-print
Xie et al. previously reported that the false-positive rate is approximately 5% when the SMAP p-value is close to 1.0e-5 14b .  ...  The copyright holder for this preprint (which . http://dx.doi.org/10.1101/042481 doi: bioRxiv preprint first posted online Mar. 5, 2016; Xie et al. developed SMAP 14 for the comparison of potential protein  ... 
doi:10.1101/042481 fatcat:qpplychdyngwnjf3mog76pkexe

Information-Coupled Turbo Codes for LTE Systems [article]

Lei Yang, Yixuan Xie, Xiaowei Wu, Jinhong Yuan, Xingqing Cheng, Lei Wan
2017 arXiv   pre-print
We propose a new class of information-coupled (IC) Turbo codes to improve the transport block (TB) error rate performance for long-term evolution (LTE) systems, while keeping the hybrid automatic repeat request protocol and the Turbo decoder for each code block (CB) unchanged. In the proposed codes, every two consecutive CBs in a TB are coupled together by sharing a few common information bits. We propose a feed-forward and feed-back decoding scheme and a windowed (WD) decoding scheme for
more » ... ng the whole TB by exploiting the coupled information between CBs. Both decoding schemes achieve a considerable signal-to-noise-ratio (SNR) gain compared to the LTE Turbo codes. We construct the extrinsic information transfer (EXIT) functions for the LTE Turbo codes and our proposed IC Turbo codes from the EXIT functions of underlying convolutional codes. An SNR gain upper bound of our proposed codes over the LTE Turbo codes is derived and calculated by the constructed EXIT charts. Numerical results show that the proposed codes achieve an SNR gain of 0.25 dB to 0.72 dB for various code parameters at a TB error rate level of 10^-2, which complies with the derived SNR gain upper bound.
arXiv:1709.06774v1 fatcat:tcfegw7merbhfdaxojk6mhphcq

A New GAN-based End-to-End TTS Training Algorithm [article]

Haohan Guo, Frank K. Soong, Lei He, Lei Xie
2019 arXiv   pre-print
End-to-end, autoregressive model-based TTS has shown significant performance improvements over the conventional one. However, the autoregressive module training is affected by the exposure bias, or the mismatch between the different distributions of real and predicted data. While real data is available in training, but in testing, only predicted data is available to feed the autoregressive module. By introducing both real and generated data sequences in training, we can alleviate the effects of
more » ... the exposure bias. We propose to use Generative Adversarial Network (GAN) along with the key idea of Professor Forcing in training. A discriminator in GAN is jointly trained to equalize the difference between real and predicted data. In AB subjective listening test, the results show that the new approach is preferred over the standard transfer learning with a CMOS improvement of 0.1. Sentence level intelligibility tests show significant improvement in a pathological test set. The GAN-trained new model is also more stable than the baseline to produce better alignments for the Tacotron output.
arXiv:1904.04775v1 fatcat:cuf4g2xwcza7jjof5r2k7ehkh4

Fine-grained Emotion Strength Transfer, Control and Prediction for Emotional Speech Synthesis [article]

Yi Lei, Shan Yang, Lei Xie
2020 arXiv   pre-print
This paper proposes a unified model to conduct emotion transfer, control and prediction for sequence-to-sequence based fine-grained emotional speech synthesis. Conventional emotional speech synthesis often needs manual labels or reference audio to determine the emotional expressions of synthesized speech. Such coarse labels cannot control the details of speech emotion, often resulting in an averaged emotion expression delivery, and it is also hard to choose suitable reference audio during
more » ... nce. To conduct fine-grained emotion expression generation, we introduce phoneme-level emotion strength representations through a learned ranking function to describe the local emotion details, and the sentence-level emotion category is adopted to render the global emotions of synthesized speech. With the global render and local descriptors of emotions, we can obtain fine-grained emotion expressions from reference audio via its emotion descriptors (for transfer) or directly from phoneme-level manual labels (for control). As for the emotional speech synthesis with arbitrary text inputs, the proposed model can also predict phoneme-level emotion expressions from texts, which does not require any reference audio or manual label.
arXiv:2011.08477v1 fatcat:pldzha6vczf6hmt3dyttex7giy

MsEmoTTS: Multi-scale emotion transfer, prediction, and control for emotional speech synthesis [article]

Yi Lei, Shan Yang, Xinsheng Wang, Lei Xie
2022 arXiv   pre-print
Expressive synthetic speech is essential for many human-computer interaction and audio broadcast scenarios, and thus synthesizing expressive speech has attracted much attention in recent years. Previous methods performed the expressive speech synthesis either with explicit labels or with a fixed-length style embedding extracted from reference audio, both of which can only learn an average style and thus ignores the multi-scale nature of speech prosody. In this paper, we propose MsEmoTTS, a
more » ... -scale emotional speech synthesis framework, to model the emotion from different levels. Specifically, the proposed method is a typical attention-based sequence-to-sequence model and with proposed three modules, including global-level emotion presenting module (GM), utterance-level emotion presenting module (UM), and local-level emotion presenting module (LM), to model the global emotion category, utterance-level emotion variation, and syllable-level emotion strength, respectively. In addition to modeling the emotion from different levels, the proposed method also allows us to synthesize emotional speech in different ways, i.e., transferring the emotion from reference audio, predicting the emotion from input text, and controlling the emotion strength manually. Extensive experiments conducted on a Chinese emotional speech corpus demonstrate that the proposed method outperforms the compared reference audio-based and text-based emotional speech synthesis methods on the emotion transfer speech synthesis and text-based emotion prediction speech synthesis respectively. Besides, the experiments also show that the proposed method can control the emotion expressions flexibly. Detailed analysis shows the effectiveness of each module and the good design of the proposed method.
arXiv:2201.06460v1 fatcat:jzjhbd6f5req3d2bk4zk24lf5a

Hardware/Software Co-monitoring [article]

Li Lei, Kai Cong, Zhenkun Yang, Bo Chen, Fei Xie
2019 arXiv   pre-print
Hardware/Software (HW/SW) interfaces, mostly implemented as devices and device drivers, are pervasive in various computer systems. Nowadays HW/SW interfaces typically undergo intensive testing and validation before release, but they are still unreliable and insecure when deployed together with computer systems to end users. Escaped logic bugs, hardware transient failures, and malicious exploits are prevalent in HW/SW interactions, making the entire system vulnerable and unstable. We present
more » ... W co-monitoring, a runtime co-verification approach to detecting failures and malicious exploits in device/driver interactions. Our approach utilizes a formal device model (FDM), a transaction-level model derived from the device specification, to shadow the real device execution. Based on the co-execution of the device and FDM, HW/SW co-monitoring carries out two-tier runtime checking: (1) device checking checks if the device behaviors conform to the FDM behaviors; (2) property checking detects invalid driver commands issued to the device by verifying system properties against driver/device interactions. We have applied HW/SW co-monitoring to five widely-used devices and their Linux drivers, discovering 9 real bugs and vulnerabilities while introducing modest runtime overhead. The results demonstrate the major potential of HW/SW co-monitoring in improving system reliability and security.
arXiv:1905.03915v1 fatcat:auadrvububhmzdp5ttqykcdgau

Harnessing Big Data for Systems Pharmacology [article]

Lei Xie, Eli Draizen, Philip Bourne
2016 bioRxiv   pre-print
Systems pharmacology aims to holistically understand genetic, molecular, cellular, organismal, and environmental mechanisms of drug actions through developing mechanistic or predictive models. Data-driven modeling plays a central role in systems pharmacology, and has already enabled biologists to generate novel hypotheses. However, more is needed. The drug response is associated with genetic/epigenetic variants and environmental factors, is coupled with molecular conformational dynamics, is
more » ... cted by possible off-targets, is modulated by the complex interplay of biological networks, and is dependent on pharmacokinetics. Thus, in order to gain a comprehensive understanding of drug actions, systems pharmacology requires integration of models across data modalities, methodologies, organismal hierarchies, and species. This imposes a great challenge on model management, integration, and translation. Here, we discuss several upcoming issues in systems pharmacology and potential solutions to them using big data technology. It will allow systems pharmacology modeling to be findable, accessible, interoperable, reusable, reliable, interpretable, and actionable.
doi:10.1101/077115 fatcat:owkyissq65agrdovh2vdgux24m

Cloud-based RFID authentication

Wei Xie, Lei Xie, Chen Zhang, Quan Zhang, Chaojing Tang
2013 2013 IEEE International Conference on RFID (RFID)  
Along with the development of cloud computing, cloud-based RFID is receiving more and more attentions of researchers and engineers. However, there is no research in which cloud computing is applied to RFID authentication schemes. Most current works lay emphasis on functionalities, lacking considerations about security and privacy. Classical RFID authentication schemes fail to meet the special security and privacy requirements of cloud-based RFID. The basic postulates of traditional
more » ... -based RFID authentication, i.e. secure backend channel and entirely trustworthy database, are no longer natively tenable in cloud-based RFID scenarios. In this paper, a virtual private network agency is suggested to build secure backend channels and to provide readers with anonymous access to the cloud. The cloud database is structured as an encrypted hash table. The first cloud-based RFID authentication protocol preserving tag/reader privacy to database keepers is proposed. Comparing with classical schemes, the proposed scheme has advantages in deployment cost saving, pervasiveness of authentication, scalability of O(1) complexity to verify a tag, mobile reader holders' privacy preserving, and database security.
doi:10.1109/rfid.2013.6548151 fatcat:sjitqb7cqjdyllz3wcllikdoeq

Learn2Sing: Target Speaker Singing Voice Synthesis by learning from a Singing Teacher [article]

Heyang Xue, Shan Yang, Yi Lei, Lei Xie, Xiulin Li
2020 arXiv   pre-print
Singing voice synthesis has been paid rising attention with the rapid development of speech synthesis area. In general, a studio-level singing corpus is usually necessary to produce a natural singing voice from lyrics and music-related transcription. However, such a corpus is difficult to collect since it's hard for many of us to sing like a professional singer. In this paper, we propose an approach -- Learn2Sing that only needs a singing teacher to generate the target speakers' singing voice
more » ... thout their singing voice data. In our approach, a teacher's singing corpus and speech from multiple target speakers are trained in a frame-level auto-regressive acoustic model where singing and speaking share the common speaker embedding and style tag embedding. Meanwhile, since there is no music-related transcription for the target speaker, we use log-scale fundamental frequency (LF0) as an auxiliary feature as the inputs of the acoustic model for building a unified input representation. In order to enable the target speaker to sing without singing reference audio in the inference stage, a duration model and an LF0 prediction model are also trained. Particularly, we employ domain adversarial training (DAT) in the acoustic model, which aims to enhance the singing performance of target speakers by disentangling style from acoustic features of singing and speaking data. Our experiments indicate that the proposed approach is capable of synthesizing singing voice for target speaker given only their speech samples.
arXiv:2011.08467v1 fatcat:lb75zqy7gjd7dek3nboajbmpbi

Restructuring China's Water Environment Management System: A Social Network Perspective

Lei Cheng, Lei Shi, Yuxi Xie, Weihua Zeng
2020 Sustainability  
Despite restructuring in institutions related to environmental protection, the multi-sectorial decentralized water management system of China continued to be widely criticized. To identify the problems in China's water management system and the direction of future reform, this article implemented social network analysis. From multiple perspectives (covering efficiency analysis, condensation analysis, and network centrality analysis), we quantitatively analyzed the structural change of the
more » ... ministry reform of water environment management in China. We found that the 2018 super ministry reform of the system made the aggregation and central enhancement of China's water management network, hence the power of water environmental management is more concentrated in the core department. However, the function overlap still exists after the reform. Some key issues of water resources management are absent from the responsibility of the core management department. Therefore, the cohesion and management effectiveness of the overall management network need to be further improved. Finally, we summarized several practical implications for future water management system reform, and the kernel is to achieve integrated management of water resource and water environment.
doi:10.3390/su12208422 fatcat:3e5jf56qazej7iio2yvvua42dy

Automatic Image Segmentation With Superpixels and Image-Level Labels

Xinlin Xie, Gang Xie, Xinying Xu, Lei Cui, Jinchang Ren
2019 IEEE Access  
LEI CUI received the B.S. degree from the College of Electrical and Power Engineering, Taiyuan University of Technology, Shanxi, China, in 2010, where he is currently pursuing the Ph.D. degree.  ...  XINLIN XIE received the B.S. degree from the Polytechnic Institute, Taiyuan University of Technology, Shanxi, China, in 2012, where he is currently pursuing the Ph.D. degree.  ... 
doi:10.1109/access.2019.2891941 fatcat:ejyihmbppngcblj3vpaeglrol4

Hepatocyte-like cells from directed differentiation of mouse bone marrow cells in vitro1

Xiao-lei SHI, Yu-dong QIU, Qiang LI, Ting XIE, Zhang-hua ZHU, Lei-lei CHEN, Lei LI, Yi-tao DING
2005 Acta Pharmacologica Sinica  
Aim: To design the effective directed differentiation medium to differentiate bone marrow cells into hepatocyte-like cells. Methods: Bone marrow cells were cultured in the directed differentiation media including fibroblast growth factor-4 (FGF-4) and oncostatin M (OSM). Hepatocyte-like cells from directed differentiation of bone marrow cells were identified through cell morphology, RNA expressions by reverse transcriptase-polymerase chain reaction (RT-PCR), protein expressions by Western blot,
more » ... and hepatocellular synthesis and metabolism functions by albumin ELISA, Periodic acid-Shiff staining and urea assay. Results: Some epithelial-like cells or polygonal cells appeared and increased in the course of the cell directed differentiation. Hepatocyte nucleur factor-3β (HNF-3β), albumin (ALB), cytokeratin 18 (CK18), transthyretin (TTR), glucose-6-phosphate (G-6-Pase), and tyrosine aminotransferase (TAT) mRNA were expressed in the course of the directed differentiation. The directed differentiated cells on d 21 expressed HNF-3β, ALB, and CK18 proteins. The directed differentiated cells produced albumin and synthesized urea in a time-dependent manner. They could also synthesize glycogen. Conclusion: Our differentiation media, including FGF-4 and OSM, are effective to differentiate bone marrow cells into hepatocyte-like cells, which could be used for hepatocyte resources for bioartificial liver or hepatocyte transplantation.
doi:10.1111/j.1745-7254.2005.00093.x pmid:15780197 fatcat:gp5uqobi5zffbni5nkvexflbpq

Exploiting Syntactic Features in a Parsed Tree to Improve End-to-End TTS [article]

Haohan Guo, Frank K. Soong, Lei He, Lei Xie
2019 arXiv   pre-print
The end-to-end TTS, which can predict speech directly from a given sequence of graphemes or phonemes, has shown improved performance over the conventional TTS. However, its predicting capability is still limited by the acoustic/phonetic coverage of the training data, usually constrained by the training set size. To further improve the TTS quality in pronunciation, prosody and perceived naturalness, we propose to exploit the information embedded in a syntactically parsed tree where the
more » ... se/word information of a sentence is organized in a multilevel tree structure. Specifically, two key features: phrase structure and relations between adjacent words are investigated. Experimental results in subjective listening, measured on three test sets, show that the proposed approach is effective to improve the pronunciation clarity, prosody and naturalness of the synthesized speech of the baseline system.
arXiv:1904.04764v1 fatcat:odhcejspkngzja5u6fmh5ug6ti

Towards Language-Universal Mandarin-English Speech Recognition

Shiliang Zhang, Yuan Liu, Ming Lei, Bin Ma, Lei Xie
2019 Interspeech 2019  
Multilingual and code-switching speech recognition are two challenging tasks that are studied separately in many previous works. In this work, we jointly study multilingual and codeswitching problems, and present a language-universal bilingual system for Mandarin-English speech recognition. Specifically, we propose a novel bilingual acoustic model, which consists of two monolingual system initialized subnets and a shared output layer corresponding to the Character-Subword acoustic modeling
more » ... . The bilingual acoustic model is trained using a large Mandarin-English corpus with CTC and sMBR criteria. We find that this model, which is not given any information about language identity, can achieve comparable performance in monolingual Mandarin and English test sets compared to the well-trained language-specific Mandarin and English ASR systems, respectively. More importantly, the proposed bilingual model can automatically learn the language switching. Experimental results on a Mandarin-English code-switching test set show that it can achieve 11.8% and 17.9% relative error reduction on Mandarin and English parts, respectively.
doi:10.21437/interspeech.2019-1365 dblp:conf/interspeech/ZhangLLMX19 fatcat:a2jq5aa2arakrcsyh2gqhgjsji

Predicting serious rare adverse reactions of novel chemicals [article]

Aleksandar Poleksic, Lei Xie
2017 bioRxiv   pre-print
Adverse drug reactions (ADRs) are one of the main causes of death and a major financial burden on the world's economy. Due to the limitations of the animal model, computational prediction of serious, rare ADRs is invaluable. However, current state-of-the-art computational methods do not yield significantly better predictions of rare ADRs than random guessing. We present a novel method, based on the theory of "compressed sensing", which can accurately predict serious side-effects of candidate
more » ... market drugs. Not only is our method able to infer new chemical-ADR associations using existing noisy, biased, and incomplete databases, but our data also demonstrates that the accuracy of our approach in predicting a serious adverse reaction (ADR) for a candidate drug increases with increasing knowledge of other ADRs associated with the drug. In practice, this means that as the candidate drug moves up the different stages of clinical trials, the prediction accuracy of our method will increase accordingly. Thus, the compressed sensing based computational method reported here represents a major advance in predicting severe rare ADRs, and may facilitate reducing the time and cost of drug discovery and development.
doi:10.1101/160473 fatcat:psqc7ghfvzgvrjy2v6mi53jjw4
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