PRCA: Fitting Black-Box Large Language Models for Retrieval Question Answering via Pluggable Reward-Driven Contextual Adapter

The Retrieval Question Answering (ReQA) task employs the retrieval-augmented framework, composed of a retriever and generator. The generator formulates the answer based on the documents retrieved by the retriever. Incorporating Large Language Models (LLMs) as generators is beneficial due to their advanced QA capabilities, but they are typically too large to be fine-tuned with budget constraints while some of them are only accessible via APIs. To tackle this issue and further improve ReQA performance, we propose a trainable Pluggable Reward-Driven Contextual Adapter (PRCA), keeping the generator as a black box. Positioned between the retriever and generator in a Pluggable manner, PRCA refines the retrieved information by operating in a token-autoregressive strategy via maximizing rewards of the reinforcement learning phase. Our experiments validate PRCA's effectiveness in enhancing ReQA performance on three datasets by up to 20% improvement to fit black-box LLMs into existing frameworks, demonstrating its considerable potential in the LLMs era.Comment: Accepted by the Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. (EMNLP2023

Numerical study on the evolution law and correction method of turbine characteristics of the gas turbine under alternative fuel conditions

Reducing carbon emissions is an urgent need in the field of marine power. Gas turbines are of great importance in the marine industry. The use of clean or industrial-associated fuels can increase the fuel adaptability of designed, manufactured, or in-service gas turbines to realize the goal of expanding fuel sources, reducing fuel waste, lowering energy demand, and remitting environmental pressure. By changing from fossil fuel to alternative energy, the change in the physical properties of the combustion products will lead to changes in the working medium of the turbines, which result in a profound effect on the performance. In this study, based on the actual law of working medium property change, the evolution mechanism of turbine characteristics is lucubrated in depth, focusing on the key parameters of the influence of working medium properties on turbine characteristics under alternative fuel conditions, and a correction method is proposed to predict the evolution law of the turbine characteristics as working medium varies

From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning

In the realm of Large Language Models, the balance between instruction data quality and quantity has become a focal point. Recognizing this, we introduce a self-guided methodology for LLMs to autonomously discern and select cherry samples from vast open-source datasets, effectively minimizing manual curation and potential cost for instruction tuning an LLM. Our key innovation, the Instruction-Following Difficulty (IFD) metric, emerges as a pivotal tool to identify discrepancies between a model's expected responses and its autonomous generation prowess. Through the adept application of IFD, cherry samples are pinpointed, leading to a marked uptick in model training efficiency. Empirical validations on renowned datasets like Alpaca and WizardLM underpin our findings; with a mere 10% of conventional data input, our strategy showcases improved results. This synthesis of self-guided cherry-picking and the IFD metric signifies a transformative leap in the optimization of LLMs, promising both efficiency and resource-conscious advancements. Codes, data, and models are available: https://github.com/MingLiiii/Cherry_LL

A linear cellular automation technique for predicting dynamic failure mode of a single-layer shell

This paper presents a linear cellular automation (LCA) method for predicting the dynamic failure (DF) mode of both single-layer latticed shell and single-layer cylindrical latticed shell subjected to ground motions. The LCA model of the shell obtains the state values of cells/nodes including the nodal displacements state value and the nodal domain logarithmic strain energy density (NDLSED) state value through its finite element analysis (FEA). Meanwhile, the concepts of nodal domain and nodal domain similarity are derived based on the qualitative analysis of shells. Then, similar nodal domains between two shells are matched through the proposed criterion. Finally, the DF mode of an object shell is mapped using the criterion for projecting the formative values of a base shell to similar nodal domains in the object shell. Case studies show that the LCA method could be used for predicting the DF mode of an object shell. Consequently, the LCA method would explore an LCA application in analyzing shells, which costs much less time than the FEA method for calculating the DF shell mode

GeneWeld: a method for efficient targeted integration directed by short homology

Choices for genome engineering and integration involve high efficiency with little or no target specificity or high specificity with low activity. Here, we describe a targeted integration strategy, called GeneWeld, and a vector series for gene tagging, pGTag (plasmids for Gene Tagging), which promote highly efficient and precise targeted integration in zebrafish embryos, pig fibroblasts, and human cells utilizing the CRISPR/Cas9 system. Our work demonstrates that in vivo targeting of a genomic locus of interest with CRISPR/Cas9 and a donor vector containing as little as 24 to 48 base pairs of homology directs precise and efficient knock-in when the homology arms are exposed with a double strand break in vivo. Given our results targeting multiple loci in different species, we expect the accompanying protocols, vectors, and web interface for homology arm design to help streamline gene targeting and applications in CRISPR compatible systems

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Product-service supplier pre-evaluation with modified fuzzy ANP reducing decision information distortion

The main challenge of new product-service supplier (PSS) selection is the lack of historical performance information of the suppliers. As one of the most popular techniques in supplier evaluation, the analytic network process (ANP) has an advantage in organising and analysing PSS pre-evaluation problems. However, the decision information distortion caused by matrix revision is a major factor affecting the wide application of the ANP when the consistency of the comparison matrix is unqualified. In this paper, a modified fuzzy ANP (F-ANP) with six criteria and 20 sub-criteria is suggested for PSS pre-evaluation. With the purpose of reducing decision information distortion in the pre-evaluation, the geometric scale is employed to improve the consistency of the judgment matrices and a linear approach is proposed for the unqualified judgment matrix revision. It is the first time that the decision information in the comparison matrix can be evaluated and retained as much as possible in generating and selecting the substitute using the proposed linear approach. The improved F-ANP model is verified in a real-life case study. Compared with the approaches in the literature, the linear approach shows advantages in retaining original decision information and the improved F-ANP outperforms the ANP and analytic hierarchy process models in terms of obtaining a stable rank of suppliers and distinguishing the importance of the criteria. 1 2015 Informa UK Limited, trading as Taylor & Francis Group.The research was supported by the Shanghai Research Centre for Industrial Informatics and Shanghai Key Lab of Advanced Manufacturing Environment.Scopu

Analysis and Extension of Safety Mechanisms for Standardized Control Networks in Smart Grid

In smart grid, standardized control networks are typical safety critical components which are under the environments with strong noise and interferences. This paper focuses on the safety mechanisms of standardized control networks in smart grid. The underlying safety mechanisms of standardized wired control networks are analyzed deeply. More importantly, there are very few works considering the safety extensions for wireless control networks. To address this, we propose a combined cyclic redundancy check (CRC) based safety extension mechanism. In addition, key points and open issues of safety-related mechanisms are discussed. To evaluate the safety of the proposed combined CRC mechanism for wireless control networks, error correction capability simulation is performed, which validates the effectiveness of the proposed scheme under the typical noisy background in smart grid. The result supports the usefulness and feasibility of our scheme. To the best of our knowledge, this work is the first to focus deeply on the safety mechanisms for standardized control network in smart grid, especially for the safety extension scheme for wireless control networks

Stress Analysis of KDP Single Crystals Caused by Thermal Expansion Mismatch during Traditional Growth

To further elucidate the relationship between the growth stress and cracking of KDP (KH2PO4, potassium dihydrogen phosphate) crystals of different sizes, a three-dimensional finite element calculation was conducted to analyze the growth stress of KDP single crystals grown from Z-plate seeds with varying cooling rates. The mismatch in the coefficient of thermal expansion (CTE), between the cap region and its close vicinity, and among the transparent region, was taken into account. The results indicate that when the cap region is a solid region (when the seed was regenerated with a cooling rate of 0.1 °C/day), the difference in material properties between the cap region and its close vicinity, especially the CTE mismatch along the a-axis, is the main reason of the high stresses. When the cap region is a box-like structure filled with solution (when the seed was regenerated with a cooling rate of 0.3 °C/day), the calculated stress is in proportion to the CTE gradient of the transparent region. Under both models, the stresses induced from an incremental CTE value (from the cap region to the growth front) are greater than those calculated from a diminishing CTE value, implying that the impurities reduce the CTE of KDP crystals, causing the crystals to crack more easily. Despite the maximum stresses inside the crystals changing slightly with an increase in crystal size, the decreased fracture stress of large brittle crystals leads to a higher cracking risk in a large-sized crystal