275 research outputs found
Learning Segmentation Masks with the Independence Prior
An instance with a bad mask might make a composite image that uses it look
fake. This encourages us to learn segmentation by generating realistic
composite images. To achieve this, we propose a novel framework that exploits a
new proposed prior called the independence prior based on Generative
Adversarial Networks (GANs). The generator produces an image with multiple
category-specific instance providers, a layout module and a composition module.
Firstly, each provider independently outputs a category-specific instance image
with a soft mask. Then the provided instances' poses are corrected by the
layout module. Lastly, the composition module combines these instances into a
final image. Training with adversarial loss and penalty for mask area, each
provider learns a mask that is as small as possible but enough to cover a
complete category-specific instance. Weakly supervised semantic segmentation
methods widely use grouping cues modeling the association between image parts,
which are either artificially designed or learned with costly segmentation
labels or only modeled on local pairs. Unlike them, our method automatically
models the dependence between any parts and learns instance segmentation. We
apply our framework in two cases: (1) Foreground segmentation on
category-specific images with box-level annotation. (2) Unsupervised learning
of instance appearances and masks with only one image of homogeneous object
cluster (HOC). We get appealing results in both tasks, which shows the
independence prior is useful for instance segmentation and it is possible to
unsupervisedly learn instance masks with only one image.Comment: 7+5 pages, 13 figures, Accepted to AAAI 201
EVMP: enhancing machine learning models for synthetic promoter strength prediction by Extended Vision Mutant Priority framework
IntroductionIn metabolic engineering and synthetic biology applications, promoters with appropriate strengths are critical. However, it is time-consuming and laborious to annotate promoter strength by experiments. Nowadays, constructing mutation-based synthetic promoter libraries that span multiple orders of magnitude of promoter strength is receiving increasing attention. A number of machine learning (ML) methods are applied to synthetic promoter strength prediction, but existing models are limited by the excessive proximity between synthetic promoters.MethodsIn order to enhance ML models to better predict the synthetic promoter strength, we propose EVMP(Extended Vision Mutant Priority), a universal framework which utilize mutation information more effectively. In EVMP, synthetic promoters are equivalently transformed into base promoter and corresponding k-mer mutations, which are input into BaseEncoder and VarEncoder, respectively. EVMP also provides optional data augmentation, which generates multiple copies of the data by selecting different base promoters for the same synthetic promoter.ResultsIn Trc synthetic promoter library, EVMP was applied to multiple ML models and the model effect was enhanced to varying extents, up to 61.30% (MAE), while the SOTA(state-of-the-art) record was improved by 15.25% (MAE) and 4.03% (R2). Data augmentation based on multiple base promoters further improved the model performance by 17.95% (MAE) and 7.25% (R2) compared with non-EVMP SOTA record.DiscussionIn further study, extended vision (or k-mer) is shown to be essential for EVMP. We also found that EVMP can alleviate the over-smoothing phenomenon, which may contributes to its effectiveness. Our work suggests that EVMP can highlight the mutation information of synthetic promoters and significantly improve the prediction accuracy of strength. The source code is publicly available on GitHub: https://github.com/Tiny-Snow/EVMP
Diaqua(2,6-dihydroxybenzoato-κ2 O 1 ,O 1′)bis(2,6-dihydroxybenzoato-κO 1)bis(1,10-phenanthroline-κ2 N,N′)lanthanum(III)–1,10-phenanthroline (1/1)
In the title compound, [La(C7H5O4)3(C12H8N2)3(H2O)2]·C12H8N2, the LaIII atom is coordinated by four N atoms from two chelating 1,10-phenanthroline (phen) ligands, four O atoms from three 2,6-dihydroxybenzoate (DHB) anions (one monodentate, the other bidentate) and two water O atoms, completing a distorted LaN4O6 bicapped square-antiprismatic geometry. Within the mononuclear complex molecule, intramolecular π–π stacking interactions are observed, the first between a coordinated phen molecule and a DHB ligand [centroid–centroid distance = 3.7291 (16) Å], and the second between a coordinated phen molecule and an uncoordinated phen ligand [centroid–centroid distance = 3.933 (2) Å]. Intermolecular π–π stacking is observed between adjacent complexes [interplanar distance = 3.461 (3) Å]. Intra- and intermolecular O—H⋯O hydrogen bonds are observed in the DHB ligands and between a water molecule and DHB ligands, respectively. O—H⋯N hydrogen bonds are also observed in the DHB ligands and between uncoordinated phen molecules and aqua ligands
Towards Spontaneous Style Modeling with Semi-supervised Pre-training for Conversational Text-to-Speech Synthesis
The spontaneous behavior that often occurs in conversations makes speech more
human-like compared to reading-style. However, synthesizing spontaneous-style
speech is challenging due to the lack of high-quality spontaneous datasets and
the high cost of labeling spontaneous behavior. In this paper, we propose a
semi-supervised pre-training method to increase the amount of spontaneous-style
speech and spontaneous behavioral labels. In the process of semi-supervised
learning, both text and speech information are considered for detecting
spontaneous behaviors labels in speech. Moreover, a linguistic-aware encoder is
used to model the relationship between each sentence in the conversation.
Experimental results indicate that our proposed method achieves superior
expressive speech synthesis performance with the ability to model spontaneous
behavior in spontaneous-style speech and predict reasonable spontaneous
behavior from text.Comment: Accepted by INTERSPEECH 202
Determination of Chlormequat and Mepiquat Residues in Tomato Plants Using Accelerated Solvent Extraction-Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry
An Accelerated-Solvent Extraction-Ultra performance Liquid Chromatography-Tandem Mass Spectrometry (ASE-UPLC-MS/MS) method using purified water as extraction solvent for quantitative analysis of chromequat (CQ) and mepiquat (MQ) in samples of tomato plants with higher sensibility and shorter extraction time was developed. The CQ and MQ residues and their dissipation rate were both covered in this paper. The limits of detection (S/N>3) and limits of quantitation (S/N>10) for CQ and MQ were 0.02 μg/kg and 0.1 μg/kg respectively. The linear range was 0.2~10 μg/kg and the correlation coefficients (r2) was no less than 0.9990, The average recoveries of CQ and MQ from tomato root, stem and leaf in the three spiked range of 1.0, 2.0 and 5.0 μg/kg were in the range of 100.0%~118.8% and 93.2%~110.7% respectively. The dissipation experiment showed that, on average, 98.8% of CQ residues and 99.7% of MQ residues had dissipated after 33 days, with a half-life of 3.67d and 3.66d, which can provide with guideline for using CQ and MQ on tomato in safe range.Key words: Tomato plants; Accelerated solvent extraction; Ultra-performance liquid chromatography-tandem mass spectrometry; Chlormequat; Mepiqua
Successful treatment of a pure red-cell aplasia patient with γδT cells and clonal TCR gene rearrangement: A case report
Pure red-cell aplasia (PRCA) is a syndrome associated with reduced erythroid precursors. This report presents the case of an elderly PRCA patient with significantly proliferated γδT cells and clonal T-cell receptor (TCR) gene rearrangement. The cause of this patient’s PRCA was confirmed to be an autoimmune disorder rather than malignancy on the basis of flow cytometry, TCR gene rearrangement, and positron emission tomography/computed tomography (PET/CT) findings. Moreover, the γδT cell group identified in this case was captured for the first time under the microscope; this CD4+/CD8− (extremely high CD4/CD8 ratio) population is rare in PRCA patients. Our patient with a monoclonal and polyclonal hybrid of TCR gene rearrangement was sensitive to cyclosporin A (CsA), despite previous reports suggesting that patients with TCR clonal rearrangement may respond poorly to this drug. Overall, this case presents valuable clinical findings for the future diagnosis and management of PRCA caused by autoimmune conditions and further research on γδT cells’ autoimmune pathophysiology and gene rearrangement
Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech
Modelling prosody variation is critical for synthesizing natural and expressive speech in end-to-end text-to-speech (TTS) systems. In this paper, a cross-utterance conditional VAE (CUC-VAE) is proposed to estimate a posterior probability distribution of the latent prosody features for each phoneme by conditioning on acoustic features, speaker information, and text features obtained from both past and future sentences. At inference time, instead of the standard Gaussian distribution used by VAE, CUC-VAE allows sampling from an utterance-specific prior distribution conditioned on cross-utterance information, which allows the prosody features generated by the TTS system to be related to the context and is more similar to how humans naturally produce prosody. The performance of CUC-VAE is evaluated via a qualitative listening test for naturalness, intelligibility and quantitative measurements, including word error rates and the standard deviation of prosody attributes. Experimental results on LJ-Speech and LibriTTS data show that the proposed CUC-VAE TTS system improves naturalness and prosody diversity with clear margins
Recommended from our members
Circulating Lysophosphatidylcholines in Early Pregnancy and Risk of Gestational Diabetes in Chinese Women.
ObjectivesThis study aimed to explore associations of lysophosphatidylcholines (LPCs) in early pregnancy with gestational diabetes mellitus (GDM), and whether LPCs mediated the associations of bile acids with GDM risk or had interactive effects with bile acids on GDM risk.DesignWe conducted a 1:1 nested case-control study (n = 486) from a large prospective pregnant women cohort in urban Tianjin, China. Blood samples were collected at their first antenatal care visit (median at 10th gestational week). LPCs were measured by liquid chromatography-tandem mass spectrometry analysis. Conditional binary logistic regression and restricted cubic spline analysis were used to identify cutoff points of these metabolites for GDM risk.ResultsOf the 6 detectable LPCs, LPC14:0 less than 0.24 nmol/mL, LPC15:0 at 0.45 nmol/mL or greater, and LPC18:0 at 18.00 nmol/mL or greater were independently associated with GDM risk. Adjustment for LPC18:0 slightly attenuated odds ratios (ORs) of deoxycholic acid (DCA, ≤ 0.36 nmol/mL) and glycoursodeoxycholic acid (GUDCA, ≤ 0.07 nmol/mL) for GDM, and the correlations of DCA and GUDCA with LPC18:0 were weak. However, the presence of DCA at 0.36 nmol/mL or less greatly amplified the adjusted OR of LPC18:0 at 18.00 nmol/mL or greater alone for GDM from 8.18 (2.51-26.7) up to 17.7 (6.64-47.1), with significant additive interaction. Similarly, the presence of GUDCA at 0.07 nmol/mL or less also greatly amplified the adjusted OR of LPC18:0 at 18.00 nmol/mL or greater alone for GDM from 17.2 (1.77-168) up to 73.8 (12.7-429), with significant additive interaction.ConclusionsLPCs in early pregnancy were associated with GDM risk. Low DCA or GUDCA greatly amplified the effect of high LPC18:0 on GDM, and its molecular mechanism is worth further investigations
Duodenal perforation due to a kink in a nasojejunal feeding tube in a patient with severe acute pancreatitis: a case report
<p>Abstract</p> <p>Introduction</p> <p>Nasojejunal feeding tube placement can be achieved by fluoroscopic or endoscopic techniques. Significant complications due to nasojejunal feeding tube placement, such as hydrothorax, duodenal perforation and retroperitoneal emphysema, are very rare. We present a case of massive retroperitoneal emphysema and abscess because of duodenal perforation caused by a kink in a nasojejunal feeding tube.</p> <p>Case presentation</p> <p>A 34-year-old Chinese woman was admitted to our intensive care unit due to hypertriglyceridemia and severe acute pancreatitis. As she suffered from acute respiratory distress syndrome and required mechanical ventilation, a nasojejunal feeding tube was placed by transnasal endoscopic technique. The procedure took place at her bedside. Half a month later, she had a high fever and abdominal distension. An abdominal radiography was performed and showed that the nasojejunal feeding tube was kinking on the third portion of the duodenum and the tip of the nasojejunal feeding tube was inserted into the right retroperitoneum on the second portion of the duodenum.</p> <p>Conclusion</p> <p>When a nasojejunal feeding tube is placed through the transnasal endoscopic technique, an abdominal radiography should be used to confirm the tube's position and indicate if it is kinking or beyond the ligament of Treitz.</p
- …