La\u3csub\u3e0.85\u3c/sub\u3eSr\u3csub\u3e0.15\u3c/sub\u3eMnO\u3csub\u3e3−\u3c/sub\u3e Infiltrated Y\u3csub\u3e0.5\u3c/sub\u3eBi\u3csub\u3e1.5\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e Cathodes for Intermediate-Temperature Solid Oxide Fuel Cells

Porous yttria-stabilized bismuth oxides (YSB) were investigated as the backbones for La0.85Sr0.15MnO3−(LSM) infiltrated cathodes in intermediate-temperature solid oxide fuel cells. The cathodes were evaluated using anode-supported single cells with scandia-stabilized zirconia as the electrolytes. With humidified H2 as the fuel, the cell showed peak power density of 0.33, 0.52, and 0.74 W cm−2 at 650, 700, and 750°C, respectively. At 650°C, the cell polarization resistance was only 1.38 Ω cm2, \u3c50% of the lowest value previously reported, indicating that YSB is a promising backbone for the LSM infiltrated cathode

Optimal pricing strategy for green products under salience theory

Environmental pressures and people’s demands for green consumption have prompted manufacturers to engage in the research and development of green products. Manufacturers need to consider the price and greenness of products when making production decisions. This paper analyzes the level of greenness and price competition of duopoly manufacturers in the consumer market in which both green-sensitive consumers (salience to greenness) and price-sensitive consumers (salience to price) exist simultaneously according to salience theory. We find that the regular manufacturer will enter the green market when all consumers’ average degree of price responsiveness is small or in a moderate part of the region. In addition, this paper also discusses the influence of salience on manufacturers’ level of greenness and pricing strategy choice. We find that the degree of salient thinking of consumers influences optimal pricing, optimal greenness and profits under the uniform pricing and price discrimination mechanisms

Singular robust room-temperature spin response from topological Dirac fermions

Topological insulators are a class of solids in which the nontrivial inverted bulk band structure gives rise to metallic surface states that are robust against impurity scattering. In three-dimensional (3D) topological insulators, however, the surface Dirac fermions intermix with the conducting bulk, thereby complicating access to the low energy (Dirac point) charge transport or magnetic response. Here we use differential magnetometry to probe spin rotation in the 3D topological material family (Bi$_2$Se$_3$, Bi$_2$Te$_3$, and Sb$_2$Te$_3$). We report a paramagnetic singularity in the magnetic susceptibility at low magnetic fields which persists up to room temperature, and which we demonstrate to arise from the surfaces of the samples. The singularity is universal to the entire family, largely independent of the bulk carrier density, and consistent with the existence of electronic states near the spin-degenerate Dirac point of the 2D helical metal. The exceptional thermal stability of the signal points to an intrinsic surface cooling process, likely of thermoelectric origin, and establishes a sustainable platform for the singular field-tunable Dirac spin response.Comment: 20 pages, 14 figure

A Dataset of Open-Domain Question Answering with Multiple-Span Answers

Multi-span answer extraction, also known as the task of multi-span question answering (MSQA), is critical for real-world applications, as it requires extracting multiple pieces of information from a text to answer complex questions. Despite the active studies and rapid progress in English MSQA research, there is a notable lack of publicly available MSQA benchmark in Chinese. Previous efforts for constructing MSQA datasets predominantly emphasized entity-centric contextualization, resulting in a bias towards collecting factoid questions and potentially overlooking questions requiring more detailed descriptive responses. To overcome these limitations, we present CLEAN, a comprehensive Chinese multi-span question answering dataset that involves a wide range of open-domain subjects with a substantial number of instances requiring descriptive answers. Additionally, we provide established models from relevant literature as baselines for CLEAN. Experimental results and analysis show the characteristics and challenge of the newly proposed CLEAN dataset for the community. Our dataset, CLEAN, will be publicly released at zhiyiluo.site/misc/clean_v1.0_ sample.json

DiGAN breakthrough: advancing diabetic data analysis with innovative GAN-based imbalance correction techniques

In the rapidly evolving field of medical diagnostics, the challenge of imbalanced datasets, particularly in diabetes classification, calls for innovative solutions. The study introduces DiGAN, a groundbreaking approach that leverages the power of Generative Adversarial Networks (GAN) to revolutionize diabetes data analysis. Marking a significant departure from traditional methods, DiGAN applies GANs, typically seen in image processing, to the realm of diabetes data. This novel application is complemented by integrating the unsupervised Laplacian Score for sophisticated feature selection. The pioneering approach not only surpasses the limitations of existing techniques but also sets a new benchmark in classification accuracy with a 90% weighted F1-score, achieving a remarkable improvement of over 20% compared to conventional methods. Additionally, DiGAN demonstrates superior performance over popular SMOTE-based methods in handling extremely imbalanced datasets. This research, focusing on the integrated use of Laplacian Score, GAN, and Random Forest, stands at the forefront of diabetic classification, offering a uniquely effective and innovative solution to the long-standing data imbalance issue in medical diagnostics

Economic Dispatch of an Integrated Microgrid Based on the Dynamic Process of CCGT Plant

Intra-day economic dispatch of an integrated microgrid is a fundamental requirement to integrate distributed generators. The dynamic energy flows in cogeneration units present challenges to the energy management of the microgrid. In this paper, a novel approximate dynamic programming (ADP) approach is proposed to solve this problem based on value function approximation, which is distinct with the consideration of the dynamic process constraints of the combined-cycle gas turbine (CCGT) plant. First, we mathematically formulate the multi-time periods decision problem as a finite-horizon Markov decision process. To deal with the thermodynamic process, an augmented state vector of CCGT is introduced. Second, the proposed VFA-ADP algorithm is employed to derive the near-optimal real-time operation strategies. In addition, to guarantee the monotonicity of piecewise linear function, we apply the SPAR algorithm in the update process. To validate the effectiveness of the proposed method, we conduct experiments with comparisons to some traditional optimization methods. The results indicate that our proposed ADP method achieves better performance on the economic dispatch of the microgrid.Comment: This paper has won the Zhang Si-Ying (CCDC) Outstanding Youth Paper Award in the 33 rd Chinese Control and Decision Conference (CCDC 2021

Supercontinuum generation and carrier envelope offset frequency measurement in a tapered single-mode fiber

We report supercontinuum generation by launching femtosecond Yb fiber laser pulses into a tapered single-mode fiber of 3 um core diameter. A spectrum of more than one octave, from 550 to 1400 nm, has been obtained with an output power of 1.3 W at a repetition rate of 250 MHz, corresponding to a coupling efficiency of up to 60%. By using a typical f-2f interferometer, the carrier envelope offset frequency was measured and found to have a signal-to-noise ratio of nearly 30 dB.Comment: 10 pages, accepted by Appl Phys