Reducing Spurious Correlations for Aspect-Based Sentiment Analysis with Variational Information Bottleneck and Contrastive Learning

Deep learning techniques have dominated the literature on aspect-based sentiment analysis (ABSA), yielding state-of-the-art results. However, these deep models generally suffer from spurious correlation problems between input features and output labels, which creates significant barriers to robustness and generalization capability. In this paper, we propose a novel Contrastive Variational Information Bottleneck framework (called CVIB) to reduce spurious correlations for ABSA. The proposed CVIB framework is composed of an original network and a self-pruned network, and these two networks are optimized simultaneously via contrastive learning. Concretely, we employ the Variational Information Bottleneck (VIB) principle to learn an informative and compressed network (self-pruned network) from the original network, which discards the superfluous patterns or spurious correlations between input features and prediction labels. Then, self-pruning contrastive learning is devised to pull together semantically similar positive pairs and push away dissimilar pairs, where the representations of the anchor learned by the original and self-pruned networks respectively are regarded as a positive pair while the representations of two different sentences within a mini-batch are treated as a negative pair. To verify the effectiveness of our CVIB method, we conduct extensive experiments on five benchmark ABSA datasets and the experimental results show that our approach achieves better performance than the strong competitors in terms of overall prediction performance, robustness, and generalization

Transjugular Intrahepatic Portosystemic Shunt for the Treatment of Portal Hypertension in Noncirrhotic Patients with Portal Cavernoma

Background. The purpose of this study was to evaluate the safety and efficacy of transjugular intrahepatic portosystemic shunt (TIPS) placement in the management of portal hypertension in noncirrhotic patients with portal cavernoma. Methods. We conducted a single institution retrospective analysis of 15 noncirrhotic patients with portal cavernoma treated with TIPS placement. 15 patients (4 women and 11 men) were evaluated via the technical success of TIPS placement, procedural complications, and follow-up shunt patency. Results. TIPS placement was technically successful in 11 out of 15 patients (73.3%). Procedure-related complications were limited to a single instance of hepatic encephalopathy in one patient. In patients with successful shunt placement, the portal pressure gradient decreased from 25.8±5.7 to 9.5±4.2 mmHg (P<0.001). TIPS dysfunction occurred in two patients during a median follow-up time of 45.2 months. Revision was not performed in one patient due to inadequate inflow. The other patient died of massive gastrointestinal bleeding in a local hospital. The remaining nine patients maintained functioning shunts through their last evaluation. Conclusions. TIPS is a safe and effective therapeutic treatment for noncirrhotic patients with symptomatic portal hypertension secondary to portal cavernoma

Geo6D: Geometric Constraints Learning for 6D Pose Estimation

Numerous 6D pose estimation methods have been proposed that employ end-to-end regression to directly estimate the target pose parameters. Since the visible features of objects are implicitly influenced by their poses, the network allows inferring the pose by analyzing the differences in features in the visible region. However, due to the unpredictable and unrestricted range of pose variations, the implicitly learned visible feature-pose constraints are insufficiently covered by the training samples, making the network vulnerable to unseen object poses. To tackle these challenges, we proposed a novel geometric constraints learning approach called Geo6D for direct regression 6D pose estimation methods. It introduces a pose transformation formula expressed in relative offset representation, which is leveraged as geometric constraints to reconstruct the input and output targets of the network. These reconstructed data enable the network to estimate the pose based on explicit geometric constraints and relative offset representation mitigates the issue of the pose distribution gap. Extensive experimental results show that when equipped with Geo6D, the direct 6D methods achieve state-of-the-art performance on multiple datasets and demonstrate significant effectiveness, even with only 10% amount of data

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase&nbsp;chain&nbsp;reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of&nbsp;prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics

Influence of residual stress on stress concentration factor for high strength steel welded joints

In this study, a set of plate-to-plate T and Y joints specimens made from high strength steel plates with yield stress equal to 690 MPa is investigated. The joints are fabricated by SMAW welding procedure. Two groups of specimens with different welding procedures are included: one group is composed by the joints with welding completed at ambient temperature and the other group is composed by the joints with welding completed at a preheating temperature of 100 °C. The residual stress near the weld toe is investigated for both groups. Hole-drilling method is applied to investigate the residual stress distribution and variation in joints. Sequentially coupled thermal-stress analysis is then conducted with finite element package ABAQUS to investigate the residual stress distribution in the joints. Finally, the effects of residual stress on the stress concentration factor distributions of the joints are evaluated. A new parameter is put forward in stress concentration factor evaluation to combine the residual stress effect

Functional analysis of the Nep1-like proteins from Plasmopara viticola

Necrosis and ethylene-inducing peptide 1 (Nep1) -like proteins (NLP) are secreted by multiple taxonomically unrelated plant pathogens (bacteria, fungi, and oomycete) and are best known for inducing cell death and immune responses in dicotyledonous plants. A group of putative NLP genes from obligate biotrophic oomycete Plasmopara viticola were predicted by RNA-Seq in our previous study, but their activity has not been established. Therefore, we analyzed the P. viticola NLP (PvNLP) family and identified seven PvNLP genes. They all belong to type 1 NLP genes and form a P. viticola-specific cluster when compared with other pathogen NLP genes. The expression of PvNLPs was induced during early infection process and the expression patterns could be categorized into two groups. Agrobacterium tumefaciens-mediated transient expression assays revealed that only PvNLP7 was cytotoxic and could induce Phytophthora capsici resistance in Nicotiana benthamiana. Functional analysis showed that PvNLP4, PvNLP5, PvNLP7, and PvNLP10 significantly improved disease resistance of Arabidopsis thaliana to Hyaloperonospora arabidopsidis. Moreover, the four genes caused an inhibition of plant growth which is typically associated with enhanced immunity when over-expressed in Arabidopsis. Further research found that PvNLP7 could activate the expression of defense-related genes and its conserved NPP1 domain was critical for cell death- and immunity-inducing activity. This record of NLP genes from P. viticola showed a functional diversification, laying a foundation for further study on pathogenic mechanism of the devastating pathogen

Improving the Accuracy of Length of stay Risk Adjustment Models using Linked Data

ABSTRACT Background Hospital length of stay (LOS) is a widely used measure for assessing cross-jurisdiction health system performance and informs resource allocation decisions. However, the accuracy of existing LOS risk adjustment models are limited, because they are mostly derived from administrative data, which mostly contain clinical/diagnostic information but lack detailed information on relevant demographic, socio-economic (SES), and self-reported health-related quality of life (HRQOL) risk factors, which have been shown to improve the accuracy of LOS risk adjustment models. The study investigates the relative contribution of demographic, socio-economic, and health status risk factors derived through data linkage in improving the accuracy of LOS risk adjustment models. Methods Population-based data on 8000 individuals hospitalized for coronary heart disease were obtained from Alberta Provincial Project on Outcomes Assessment in Coronary Heart Disease (APPROACH) registry and linked to Alberta Discharge Abstract Database (DAD). SES was measured using multi-domain measure of SES derived from area-level census information, while the health-related quality of life outcome was measured using the Seattle Angina Questionnaire. LOS risk adjustment model based on hierarchical logistic regression models was developed to assess relative impact of each SES measure and HRQOL measure improving the predictive accuracy of LOS adjustment models. The relative impact of each predictor was assessed by its adjusted odds ratio (OR) and improvement over the predictive accuracy of a reference model that included patients’ clinical risk factors only.  Result More than 80% of the hospitalized individuals had prolonged LOS more than 10 days. The HRQOL and single-domain measures of SES had significant impact in accurately predicting LOS. But the inclusion of the multi-domain measure SES did not significantly improve the accuracy of LOS risk adjustment models Conclusion Using large population-based Canadian data, our study suggests that the inclusion of patients’ SES and health status information through data linkage can improve the accuracy of LOS risk adjustment models. The development of more accurate risk adjustment models can aid the identification of individuals at risk of prolonged LOS and comparison of health system performance across several cross-jurisdictions

The complete chloroplast genome sequence of Vitis berlandieri

Vitis berlandieri, a species of grape native to the southern North America, is known for good tolerance against soils with a high content of lime and was almost used for rootstock breeding. Here, we report the complete chloroplast genome of V. berlandieri. The chloroplast genome was 161,028 bp in length, harboring a large single-copy region (89,228 bp) and a small single-copy region (19,028 bp) separated by two inverted repeat regions. A total of 130 unique genes were identified from this genome, including 85 protein-coding genes (PCGs), 37 tRNA genes, and 8 rRNA genes. Chloroplast phylogenetic analysis revealed that V. berlandieri is closely related to V. cordifolia

The complete chloroplast genome sequence of Vitis champinii

Vitis champinii is a grapevine rootstock species and widely used in vineyards and in rootstock breeding programs for regions with high nematode populations or saline soils. Here, the complete chloroplast genome of V. champinii was reported. The length of the chloroplast genome was 160,657 bp with a large single copy region of 89,217 bp, a small single copy region of 19,504 bp and two separated inverted regions of 51,936 bp, respectively. In total, 130 unique genes were identified of this genome, including 85 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Phylogenetic analysis indicates that V. champinii is closely related to Vitis acerifolia

Dynamic Damping-Based Terminal Sliding Mode Event-Triggered Fault-Tolerant Pre-Compensation Stochastic Control for Tracked ROV

Due to the unknown disturbance caused by the harsh environment in deep water, the stability of Underwater Tracked Remotely Opreated Vehicle (UTROV) trajectory tracking control is affected; especially the resistance forces of random vibrations caused by non-differentiable random disturbance resistance, which has become one of the main problems in controller design. Considering engineering practice, a stochastic model and new dynamic damping-based terminal sliding mode event-triggered fault-tolerant controller were designed in this paper. Firstly, based on the random resistance pre-compensation theory for the first time, a stochastic model was designed for differential drive UTROV. Meanwhile, a new nonsingular terminal sliding mode and dynamic damping reaching law were designed to achieve global finite-time convergence and reduce chattering with better robust response speed. Furthermore, to deal with the wear and tear caused by actuator failure and fixed sampling rate transmission, a new dynamic event trigger mechanism was designed and the faults analyzed. On this basis, combined with the finite-time adaptive on-line estimation technology, it can not only better reduce the transmission frequency, but also the finite-time dynamic active fault-tolerant compensation. The control scheme has semi-globally finite-time stability in probability and is proved by theory, which is compliant with engineering requirements. Then, according to characteristics of innovation, the three groups of simulation of control methods are designed to compare the methods in this paper. Finally the advantages of the method are verified by simulation to achieve the design expectations