CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-Thought

Unsupervised sentence representation learning aims to transform input sentences into fixed-length vectors enriched with intricate semantic information while obviating the reliance on labeled data. Recent progress within this field, propelled by contrastive learning and prompt engineering, has significantly bridged the gap between unsupervised and supervised strategies. Nonetheless, the potential utilization of Chain-of-Thought, remains largely untapped within this trajectory. To unlock latent capabilities within pre-trained models, such as BERT, we propose a two-stage approach for sentence representation: comprehension and summarization. Subsequently, the output of the latter phase is harnessed as the vectorized representation of the input sentence. For further performance enhancement, we meticulously refine both the contrastive learning loss function and the template denoising technique for prompt engineering. Rigorous experimentation substantiates our method, CoT-BERT, transcending a suite of robust baselines without necessitating other text representation models or external databases

Spatio-temporal Tendency Reasoning for Human Body Pose and Shape Estimation from Videos

In this paper, we present a spatio-temporal tendency reasoning (STR) network for recovering human body pose and shape from videos. Previous approaches have focused on how to extend 3D human datasets and temporal-based learning to promote accuracy and temporal smoothing. Different from them, our STR aims to learn accurate and natural motion sequences in an unconstrained environment through temporal and spatial tendency and to fully excavate the spatio-temporal features of existing video data. To this end, our STR learns the representation of features in the temporal and spatial dimensions respectively, to concentrate on a more robust representation of spatio-temporal features. More specifically, for efficient temporal modeling, we first propose a temporal tendency reasoning (TTR) module. TTR constructs a time-dimensional hierarchical residual connection representation within a video sequence to effectively reason temporal sequences' tendencies and retain effective dissemination of human information. Meanwhile, for enhancing the spatial representation, we design a spatial tendency enhancing (STE) module to further learns to excite spatially time-frequency domain sensitive features in human motion information representations. Finally, we introduce integration strategies to integrate and refine the spatio-temporal feature representations. Extensive experimental findings on large-scale publically available datasets reveal that our STR remains competitive with the state-of-the-art on three datasets. Our code are available at https://github.com/Changboyang/STR.git.Comment: Accepted by BMVC202

Photosynthetic Rate and Root Growth Responses to Ascophyllum nodosum Extract–based Biostimulant in Creeping Bentgrass under Heat and Drought Stress

Creeping bentgrass (Agrostis stolonifera) experiences quality decline during summer in the United States transition zone and warmer regions. Various bioproducts have been used to improve creeping bentgrass performance and to mitigate effects of summer stress in the United States transition zone. This 2-year study was carried out to examine if foliar application of seaweed extract (SWE; Ascophyllum nodosum)-based biostimulant Utilize® could enhance creeping bentgrass nitrate reductase (NaR) activity, and root viability under heat and drought stress conditions. The Utilize® was sprayed biweekly on creeping bentgrass foliage at 0, 29, 58, 87, and 116 µL⋅m−2, with application volume of 815 L⋅ha−2. Two weeks after first application, plants were exposed to heat (35/25 °C, day/night) and drought stress (40% to 50% evapotranspiration replacement) conditions for 42 days in an environment-controlled growth chamber. In general, the abiotic stress caused turf quality reduction. Foliar application of Utilize® at 58, 87, and 116 µL⋅m−2 increased turf quality, leaf color ratings, leaf chlorophyll, carotenoid content, and net photosynthetic rate (Pn). Utilize® at 58, 87, and 116 µL⋅m−2 increased NaR activity by 26.5%, 16.3%, and 16.3%, respectively, when compared with the control. Utilize® at 58, 87, and 116 µL⋅m−2 increased root biomass, root length, surface area (SA), and root volume when compared with the control. Utilize® at 58 and 87 µL⋅m−2 improved root viability by 16.3% and 30.9%, respectively, when compared with the control. Our data indicate that the SWE-based biostimulant Utilize® improves nitrogen (N) metabolism and root viability. Utilize® treatment at 58 µL⋅m−2 biweekly can be considered an effective approach for improving creeping bentgrass performance during summer stress

Biomechanical study of the effect of traction on elbow joint capsule contracture

Dynamic orthoses have a significant effect on the treatment of elbow capsular contracture. Because of the lack of quantitative research on traction forces, determining the appropriate traction force to help stretch soft tissues and maintain the joint's range of motion is a challenge in the rehabilitation process. We developed a human elbow finite element (FE) model incorporating the activity behavior of the muscles and considering different capsular contracture locations, including total, anterior and posterior capsular contractures, to analyze the internal biomechanical responses of different capsular contracture models during flexion (30 to 80 degrees). Traction loads of 10, 20, 30 and 40 N were applied to the ulna and radius at the maximum flexion angle (80 degrees) to explore the appropriate traction loads at week 4 after a joint capsule injury. We observed a significant increase in posterior capsule stress with anterior capsular contracture (ACC), and the maximum peak stress was 1.3 times higher than that in the healthy model. During the fourth week after elbow capsule injury, the appropriate traction forces for total capsule contracture (TCC), ACC and posterior capsule contracture (PCC) were 20, 10 and 20 N, respectively; these forces maintained a stable biomechanical environment for the elbow joint and achieved a soft tissue pulling effect, thus increasing elbow mobility. The results can be used as a quantitative guide for the rehabilitation physicians to determine the traction load for a specific patient

Learning Point-wise Abstaining Penalty for Point Cloud Anomaly Detection

LiDAR-based semantic scene understanding is an important module in the modern autonomous driving perception stack. However, identifying Out-Of-Distribution (OOD) points in a LiDAR point cloud is challenging as point clouds lack semantically rich features when compared with RGB images. We revisit this problem from the perspective of selective classification, which introduces a selective function into the standard closed-set classification setup. Our solution is built upon the basic idea of abstaining from choosing any known categories but learns a point-wise abstaining penalty with a marginbased loss. Synthesizing outliers to approximate unlimited OOD samples is also critical to this idea, so we propose a strong synthesis pipeline that generates outliers originated from various factors: unrealistic object categories, sampling patterns and sizes. We demonstrate that learning different abstaining penalties, apart from point-wise penalty, for different types of (synthesized) outliers can further improve the performance. We benchmark our method on SemanticKITTI and nuScenes and achieve state-of-the-art results. Risk-coverage analysis further reveals intrinsic properties of different methods. Codes and models will be publicly available.Comment: codes is available at https://github.com/Daniellli/PAD.gi

Facile template-free synthesis of hierarchically porous NiO hollow architectures with high-efficiency adsorptive removal of Congo red

Hierarchically porous NiO hollow architectures (HPHAs) were synthesized via a one-pot facile chemical bath deposition method and followed by a calcination process. The crystal structure, component and morphology of the products were characterized by various techniques. The results revealed that hierarchical architectures with hollow interior are composed of mesoporous NiO nanoflakes with thickness of about 8 nm. Interestingly, the as-synthesized NiO HPHAs have the unusual three-ordered porous features including a microscale hollow interior and two mesoscale pores which are attributed to the holes on the surface of nanoflakes with an average diameter of about 3.9 nm and the cavities on the wall of microsphere in the range of 20–40 nm in diameter formed by interconnecting nanoflakes. These comprehensive hierarchically porous structures are beneficial for the adsorption performance towards Congo red in water. The absorptive capacity over NiO HPHAs achieved about 1.8 and 4.0 times as high as that of the precursor β-Ni(OH)2 hollow microspheres (HSs) and the commercial activity carbon (AC) under the same conditions. The studies of adsorption kinetics illustrated that the adsorption behavior perfectly obeyed the pseudo-second-order model and the adsorption isotherm fits the Langmuir adsorption assumption well. The maximum adsorption capacities were calculated to be 490.2 mg g−1 according to the Langmuir equation, which is excellent result compared to NiO absorbents. The high-efficiency adsorption capacities for NiO HPHAs are attributed to the large specific surface area, the synergistic effect of micro-mesoporous structure and the electrostatic interaction of NiO with CR molecules. Additionally, NiO HPHAs can be easily renewed and has good chemical stability, indicating a great promising absorbent in the application for the removal of diazo organics in wastewater.Hefei Universit

Thioredoxin reductase was nitrated in the aging heart after myocardial ischemia/reperfusion.

The age-related loss of anti-oxidant defense reduces recovery from myocardial ischemia/reperfusion injury (MI/R) in aged people. Our previous data showed that inactivation of thioredoxin (Trx) was involved in enhanced aging MI/R injury. Thioredoxin reductase (TrxR), the enzyme known to regulate Trx, is less efficient with age. The aim of the current study was to determine why TrxR activity was reduced and whether reduced TrxR activity contributed to enhanced aging MI/R injury. Both Trx and TrxR activity were decreased in the aging heart, and this difference was further amplified after MI/R. However, MI/R injury did not change TrxR expression between young and aging rats. Increased nitrogen oxide (NOx) but decreased nitric oxide (NO) bioavailability (decreased phosphorylated vasodilator-stimulated phosphoprotein) was observed in aging hearts. Peroxynitrite (ONOO⁻) was increased in aging hearts and was further amplified after MI/R. TrxR nitration in young and aging hearts was detected by immunoprecipitation (anti-nitrotyrosine) followed by immunoblotting (anti-TrxR). Compared with young hearts, TrxR nitration was increased in the aging hearts, and this was further intensified after MI/R. The ONOO⁻ decomposition catalyst (FeTMPyp) reduced TrxR nitration and increased TrxR and Trx activity. More importantly, FeTMPyp attenuated the MI/R injury in aging hearts as evidenced by decreased caspase-3 and malondialdehyde (MDA) concentration and increased cardiac function. Increased ONOO⁻ nitrated TrxR in the aging heart as a post-translational modification, which may be related to the enhanced MI/R injury of aging rats. Interventions that inhibit nitration and restore TrxR activity might be a therapy for attenuating enhanced MI/R injury in aging heart

The reporting quality of randomized controlled trials in Chinese herbal medicine (CHM) formulas for diabetes based on the consort statement and its extension for CHM formulas

Background: This study aimed to assess the overall reporting quality of randomized controlled trials (RCTs) in Chinese herbal medicine (CHM) formulas for patients with diabetes, and to identify factors associated with better reporting quality.Methods: Four databases including PubMed, Embase, Cochrane Library and Web of Science were systematically searched from their inception to December 2022. The reporting quality was assessed based on the Consolidated Standards of Reporting Trials (CONSORT) statement and its CHM formula extension. The overall CONSORT and its CHM formula extension scores were calculated and expressed as proportions separately. We also analyzed the pre-specified study characteristics and performed exploratory regressions to determine their associations with the reporting quality.Results: Seventy-two RCTs were included. Overall reporting quality (mean adherence) were 53.56% and 45.71% on the CONSORT statement and its CHM formula extension, respectively. The strongest associations with reporting quality based on the CONSORT statement were multiple centers and larger author numbers. Compliance with the CHM formula extension, particularly regarding the disclosure of the targeted traditional Chinese medicine (TCM) pattern (s), was generally insufficient.Conclusion: The reporting quality of RCTs in CHM formulas for diabetes remains unsatisfactory, and the adherence to the CHM formula extension is even poorer. In order to ensure transparent and standardized reporting of RCTs, it is essential to advocate for or even mandate adherence of the CONSORT statement and its CHM formula extension when reporting trials in CHM formulas for diabetes by both authors and editors