84 research outputs found

    Mixture of Soft Prompts for Controllable Data Generation

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    Large language models (LLMs) effectively generate fluent text when the target output follows natural language patterns. However, structured prediction tasks confine the output format to a limited ontology, causing even very large models to struggle since they were never trained with such restrictions in mind. The difficulty of using LLMs for direct prediction is exacerbated in few-shot learning scenarios, which commonly arise due to domain shift and resource limitations. We flip the problem on its head by leveraging the LLM as a tool for data augmentation rather than direct prediction. Our proposed Mixture of Soft Prompts (MSP) serves as a parameter-efficient procedure for generating data in a controlled manner. Denoising mechanisms are further applied to improve the quality of synthesized data. Automatic metrics show our method is capable of producing diverse and natural text, while preserving label semantics. Moreover, MSP achieves state-of-the-art results on three benchmarks when compared against strong baselines. Our method offers an alternate data-centric approach for applying LLMs to complex prediction tasks.Comment: 19 pages, 13 Tables, 2 Figures. Accepted at EMNLP 202

    Time-Optimal Control for High-Order Chain-of-Integrators Systems with Full State Constraints and Arbitrary Terminal States

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    Time-optimal control for high-order chain-of-integrators systems with full state constraints and arbitrary given terminal states remains a challenging problem in the optimal control theory domain, yet to be resolved. To enhance further comprehension of the problem, this paper establishes a novel notation system and theoretical framework, successfully providing the switching manifold for high-order problems in the form of switching law. Through deriving properties of switching laws on signs and dimension, this paper proposes a definite condition for time-optimal control. Guided by the developed theory, a trajectory planning method named the manifold-intercept method (MIM) is developed. The proposed MIM can plan time-optimal jerk-limited trajectories with full state constraints, and can also plan near-optimal higher-order trajectories with negligible extra motion time. Numerical results indicate that the proposed MIM outperforms all baselines in computational time, computational accuracy, and trajectory quality by a large gap

    Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States

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    Portfolio management (PM) is a fundamental financial planning task that aims to achieve investment goals such as maximal profits or minimal risks. Its decision process involves continuous derivation of valuable information from various data sources and sequential decision optimization, which is a prospective research direction for reinforcement learning (RL). In this paper, we propose SARL, a novel State-Augmented RL framework for PM. Our framework aims to address two unique challenges in financial PM: (1) data heterogeneity -- the collected information for each asset is usually diverse, noisy and imbalanced (e.g., news articles); and (2) environment uncertainty -- the financial market is versatile and non-stationary. To incorporate heterogeneous data and enhance robustness against environment uncertainty, our SARL augments the asset information with their price movement prediction as additional states, where the prediction can be solely based on financial data (e.g., asset prices) or derived from alternative sources such as news. Experiments on two real-world datasets, (i) Bitcoin market and (ii) HighTech stock market with 7-year Reuters news articles, validate the effectiveness of SARL over existing PM approaches, both in terms of accumulated profits and risk-adjusted profits. Moreover, extensive simulations are conducted to demonstrate the importance of our proposed state augmentation, providing new insights and boosting performance significantly over standard RL-based PM method and other baselines.Comment: AAAI 202

    The role of EGFR mutation as a prognostic factor in survival after diagnosis of brain metastasis in non-small cell lung cancer: A systematic review and meta-analysis

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    Abstract Background The brain is a common site for metastasis in non-small-cell lung cancer (NSCLC). This study was designed to evaluate the relationship between the mutational of the epidermal growth factor receptor (EGFR) and overall survival (OS) in NSCLC patients with brain metastases. Methods Searches were performed in PubMed, EmBase, and the Cochrane Library to identify studies evaluating the association of EGFR mutation with OS in NSCLC patients through September 2017. Results 4373 NSCLC patients with brain metastases in 18 studies were involved. Mutated EGFR associated with significantly improved OS compared with wild type. Subgroup analyses suggested that this relationship persisted in studies conducted in Eastern, with retrospective design, with sample size ≥500, mean age of patients ≥65.0 years, percentage male < 50.0%, percentage of patients receiving tyrosine kinase inhibitor ≥30.0%. Finally, although significant publication bias was observed using the Egger test, the results were not changed after adjustment using the trim and fill method. Conclusions This meta-analysis suggests that EGFR mutation is an important predictive factor linked to improved OS for NSCLC patients with brain metastases. It can serve as a useful index in the prognostic assessment of NSCLC patients with brain metastases

    A Qualitative Study on the User Acceptance of a Home-Based Stroke Telerehabilitation System

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    Objective: This paper reports a qualitative study of a home-based stroke telerehabilitation system. The telerehabilitation system delivers treatment sessions in the form of daily guided rehabilitation games, exercises, and stroke education in the patient’s home. The aims of the current report are to investigate patient perceived benefits of and barriers to using the telerehabilitation system at home. Methods: We used a qualitative study design that involved in-depth semi-structured interviews with 13 participants who were patients in the subacute phase after stroke and had completed a six-week intervention using the home-based telerehabilitation system. Thematic analysis was conducted to analyze the data. Results: Participants mostly reported positive experiences with the telerehabilitation system. Benefits included observed improvements in limb functions, cognitive abilities, and emotional well-being. They also perceived the system easy to use due to the engaging experience and the convenience of conducting sessions at home. Meanwhile, participants pointed out the importance of considering technical support and physical environment at home. Further, family members’ support helped them sustain in their rehabilitation. Finally, adjusting difficulty levels and visualizing patients’ rehabilitation progress might help them in continued use of the telerehabilitation system. Conclusion: Telerehabilitation systems can be used as an efficient and user-friendly tool to deliver home-based stroke rehabilitation that enhance patients’ physical recovery and mental and social-emotional wellbeing. Such systems need to be designed to offer engaging experience, display of recovery progress, and flexibility of schedule and location, with consideration of facilitating and social factors

    Electrochemical reforming of ethanol with acetate Co-Production on nickel cobalt selenide nanoparticles

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    The energy efficiency of water electrolysis is limited by the sluggish reaction kinetics of the anodic oxygen evolution reaction (OER). To overcome this limitation, OER can be replaced by a less demanding oxidation reaction, which in the ideal scenario could be even used to generate additional valuable chemicals. Herein, we focus on the electrochemical reforming of ethanol in alkaline media to generate hydrogen at a Pt cathode and acetate as a co-product at a NiCoSe anode. We first detail the solution synthesis of a series of NiCoSe electrocatalysts. By adjusting the Ni/Co ratio, the electrocatalytic activity and selectivity for the production of acetate from ethanol are optimized. Best performances are obtained at low substitutions of Ni by Co in the cubic NiSe phase. Density function theory reveals that the Co substitution can effectively enhance the ethanol adsorption and decrease the energy barrier for its first step dehydrogenation during its conversion to acetate. However, we experimentally observe that too large amounts of Co decrease the ethanol-to-acetate Faradaic efficiency from values above 90% to just 50 %. At the optimized composition, the NiCoSe electrode delivers a stable chronoamperometry current density of up to 45 mA cm, corresponding to 1.2 A g, in a 1 M KOH + 1 M ethanol solution, with a high ethanol-to-acetate Faradaic efficiency of 82.2% at a relatively low potential, 1.50 V vs. RHE, and with an acetate production rate of 0.34 mmol cm h.This work was supported by the start-up funding at Chengdu University. It was also supported by the European Regional Development Funds and by the Spanish Ministerio de Economía y Competitividad through the project SEHTOP (ENE2016-77798-C4-3-R), MCIN/ AEI/10.13039/501100011033/ project, and NANOGEN (PID2020-116093RB-C43). X. Wang, C. Xing, X. Han, R. He, Z. Liang, and Y. Zhang are grateful for the scholarship from China Scholarship Council (CSC). X. Han and J. Arbiol acknowledge funding from Generalitat de Catalunya 2017 SGR 327. ICN2 acknowledges support from the Severo Ochoa Programme (MINECO, Grant no. SEV-2013-0295). IREC and ICN2 are funded by the CERCA Programme / Generalitat de Catalunya

    Mechanism of homocysteine-mediated endothelial injury and its consequences for atherosclerosis

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    Homocysteine (Hcy) is an intermediate amino acid formed during the conversion from methionine to cysteine. When the fasting plasma Hcy level is higher than 15 μmol/L, it is considered as hyperhomocysteinemia (HHcy). The vascular endothelium is an important barrier to vascular homeostasis, and its impairment is the initiation of atherosclerosis (AS). HHcy is an important risk factor for AS, which can promote the development of AS and the occurrence of cardiovascular events, and Hcy damage to the endothelium is considered to play a very important role. However, the mechanism by which Hcy damages the endothelium is still not fully understood. This review summarizes the mechanism of Hcy-induced endothelial injury and the treatment methods to alleviate the Hcy induced endothelial dysfunction, in order to provide new thoughts for the diagnosis and treatment of Hcy-induced endothelial injury and subsequent AS-related diseases
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