Large Language Models are Effective Table-to-Text Generators, Evaluators, and Feedback Providers

Large language models (LLMs) have shown remarkable ability on controllable text generation. However, the potential of LLMs in generating text from structured tables remains largely under-explored. In this paper, we study the capabilities of LLMs for table-to-text generation tasks, particularly aiming to investigate their performance in generating natural language statements that can be logically entailed by a provided table. First, we investigate how LLMs compare to state-of-the-art table-to-text fine-tuned models, and demonstrate that LLMs can generate statements with higher faithfulness compared with previous state-of-the-art fine-tuned models. Given this finding, we next explore whether LLMs can serve as faithfulness-level automated evaluation metrics. Through human evaluation, we show that evaluation metrics adopted from LLMs correlates better with human judgments compared with existing faithfulness-level metrics. Finally, we demonstrate that LLMs using chain-of-thought prompting can generate high-fidelity natural language feedback for other table-to-text models' generations, provide insights for future work regarding the distillation of text generation capabilities from LLMs to smaller models.Comment: work in progres

Critical role of the gut microbiota in immune responses and cancer immunotherapy

The gut microbiota plays a critical role in the progression of human diseases, especially cancer. In recent decades, there has been accumulating evidence of the connections between the gut microbiota and cancer immunotherapy. Therefore, understanding the functional role of the gut microbiota in regulating immune responses to cancer immunotherapy is crucial for developing precision medicine. In this review, we extract insights from state-of-the-art research to decipher the complicated crosstalk among the gut microbiota, the systemic immune system, and immunotherapy in the context of cancer. Additionally, as the gut microbiota can account for immune-related adverse events, we discuss potential interventions to minimize these adverse effects and discuss the clinical application of five microbiota-targeted strategies that precisely increase the efficacy of cancer immunotherapy. Finally, as the gut microbiota holds promising potential as a target for precision cancer immunotherapeutics, we summarize current challenges and provide a general outlook on future directions in this field

Humic acid production from the degradation of Yima coal by Cunninghamella elegans combined with Bacillus sp.

Biodegradation is one of the important ways for the clean and efficient utilization of coal. However, the effectiveness of degradation by the combination of fungi and bacteria has not been well understood. In the present study, the combined degradation of the Yima coal was tested. The coal samples were firstly oxidized with nitric acid, followed by cultured in the media of Cunninghamella elegans and Bacillus sp.. The absorbance of A450, pH and metallic element (Cr, As, Mn, Pb, Co, Ni, Cu, Zn, Mo) contents of the degradation solution were determined by UV-visible spectrophotometry, pH meter and inductively coupled plasma mass spectrometry, respectively. The humic acid was analyzed by element analyzer, Fourier transform infrared spectroscopy and gas chromatog-raphy-mass spectrometry. The results showed that the humic acid yields of C. elegans, Bacillus sp. and their mixture were 58.17%, 61.00% and 67.17%, respectively. The pH of the degradation solution of mixed strains was similar to that of the bacteria. The characteristic products of the bacteria degradation were detected in the humic acid samples derived from mixed strains, while the opposite was true for the fungi. It was suggested that the combination of the two strains enhanced the alkaline environment and improved the degradation rate of nitric acid-treated coal. The bacteria played a leading role in the degradation process. Metallic elements (Cr, As, Mn, Pb, Co, Ni, Cu, Zn, Mo) were transferred from coal to the degradation solution during the degradation process, and the contents of Cr, As, Pb, Ni, Cu and Mo were fitted with A450, the coefficient of determination (R2) were greater than 0.6. It indicated that the contents of these six metal elements in the degradation solution could represent the degradation rate. Chemically extracted humic acid and biologically extracted humic acid were rich in the active functional groups such as carboxyl, hydroxyl, carbonyl, long-chain fatty acids (C16, C18) and four pyrrole derivatives. The biologically extracted humic acid also contained fatty acids (C3, C4, C5, C13, C14, C15), of smaller molecular weight, as well as nitrogen-containing compounds such as two pyrrole derivatives and a furan. The contents of C and H elements in the biologically extracted humic acid were higher than that in the chemically extracted humic acid

Performance Enhancement of Functional Delay and Sum Beamforming for Spherical Microphone Arrays

Functional delay and sum (FDAS) beamforming for spherical microphone arrays can achieve 360° panoramic acoustic source identification, thus having broad application prospects for identifying interior noise sources. However, its acoustic imaging suffers from severe sidelobe contamination under a low signal-to-noise ratio (SNR), which deteriorates the sound source identification performance. In order to overcome this issue, the cross-spectral matrix (CSM) of the measured sound pressure signal is reconstructed with diagonal reconstruction (DRec), robust principal component analysis (RPCA), and probabilistic factor analysis (PFA). Correspondingly, three enhanced FDAS methods, namely EFDAS-DRec, EFDAS-RPCA, and EFDAS-PFA, are established. Simulations show that the three methods can significantly enhance the sound source identification performance of FDAS under low SNRs. Compared with FDAS at SNR = 0 dB and the number of snapshots = 1000, the average maximum sidelobe levels of EFDAS-DRec, EFDAS-RPCA, and EFDAS-PFA are reduced by 6.4 dB, 21.6 dB, and 53.1 dB, respectively, and the mainlobes of sound sources are shrunk by 43.5%, 69.0%, and 80.0%, respectively. Moreover, when the number of snapshots is sufficient, the three EFDAS methods can improve both the quantification accuracy and the weak source localization capability. Among the three EFDAS methods, EFDAS-DRec has the highest quantification accuracy, and EFDAS-PFA has the best localization ability for weak sources. The effectiveness of the established methods and the correctness of the simulation conclusions are verified by the acoustic source identification experiment in an ordinary room, and the findings provide a more advanced test and analysis tool for noise source identification in low-SNR cabin environments

The Recovery of Valuable Metals from Ocean Polymetallic Nodules Using Solid-State Metalized Reduction Technology

Ocean polymetallic nodules are oxide ores rich in Ni, Co, Cu, and Mn, which are valuable metals found in deep-sea mineral resources. Such non-ferrous metals do not exist in isolation, and producing concentrates using conventional mineral separation techniques is challenging without pre-treatment. We propose an effective, environmentally-friendly recovery technology combined with solid-state metalized reduction treatment and magnetic separation to recycle these metals from ocean polymetallic nodules. We conducted single-factor tests to investigate the effects of additives, anthracite dosage, duration, and reduction temperature on metal recovery and to obtain optimal operating parameters. We found that valuable metals in ocean polymetallic nodules may be selectively reduced to a metallic state. Only a fraction of Mn was reduced to metal. The reduced metals were recovered to concentrates using magnetic separation. More than 80% of these metals were concentrated to magnetic concentrates with mass ratios of 10–15%. The recovery rates of Ni, Co, Cu, Mn, and Fe in concentrates were optimum at 86.48%, 86.74%, 83.91%, 5.63%, and 91.46%, respectively, when using CaF2 4%, anthracite 7%, SiO2 dosage 5%, and FeS 6% at 1100 °C for 2.5 h. This approach to non-ferrous metal extraction using conventional hydrometallurgical processes could be a step toward practical industrial-scale techniques for the recovery of metals from polymetallic nodules

Rewilding the wildlife in Sangjiangyuan National Park, Qinghai-Tibetan Plateau

The targets of China’s national park construction are to protect the authenticity and integrity of the ecosystems, and to achieve the harmonious development between humans and nature. Because of the high intensity of human activities, the authenticity of ecosystems has deviated over the past few decades. It is time to rewild the wildlife and restore the authenticity of these ecosystems. The status of rewilding wildlife in Sanjiangyuan National Park, indicating that the wildlife population, diversity and wildness have increased within the National Park. The wildlife population in the national park has been restored, with about 60,000 Tibetan antelope, 60,000 Tibetan gazelle, 36,000 Tibetan wild ass, 10,000 wild yak, and 10,000 white-lipped deer up to 2017. However, overgrazing existed on the alpine grassland with population increasing both of ungulates and livestock

Research on Recovery of Valuable Metals from Cobalt-Rich Crust Using Carbon as a Reduction Agent during the Acid Baking Process

Cobalt-rich crust is a seabed metal mineral resource that is different from oceanic polymetallic nodules. Based on the higher Co content than polymetallic nodules, the commercial value of cobalt-rich crust may be better than that of polymetallic nodules. Due to the special distribution of valuable metals, commercial implementation is always limited. Herein, a novel process is proposed to efficiently and, in an eco-friendly way, recycle valuable metals from cobalt-rich crust. The results indicate that carbon could promote the decomposition of manganite in the cobalt-rich crust during the acid baking process, and the leaching ratio of Mn could increase by 50% when carbon is added during acid baking. In addition, it can be found that the promotion of carbon for Co is stronger at low sulfuric acid consumption than that at high sulfuric acid consumption; however, there is no promotion of carbon for leaching Ni and Cu during the acid baking process. The leaching ratio of Ni, Co, Cu, Mn, and Fe reached 98.59%, 91.62%, 93.81%, 41.27%, and 26.94%, respectively, when the mass ratio of the sulfuric acid and cobalt-rich crust was 0.567, the mass ratio of the carbon and cobalt-rich crust was 0.1, the temperature was 200 °C and the time was 240 min. This research could provide an alternative economic process for recycling valuable metals from cobalt-rich crusts

Parameters Identification and Adaptive Feedforward Control of Permanent Magnent Linear Synchronous Motor

This paper proposes a novel adaptive feedforward control strategy based on the parameters identification of a permanent magnent linear synchronous motor (PMLSM). The parameters such as the moving mass and viscous coefficient of a PMLSM are identified through an unbiased least square estimation approach with the employment of current and position signals from the built-in sensors. Based on the identified parameters, the accurate state-space model of the PMLSM is established and a robust feedback controller applying H-infinity control method is built. An adaptive feedforward controller based on the nominal model and the online recursion least square method is designed. Simulations and experiments are conducted to verify the control performance of the proposed control system. The results validate that the proposed control approaches are feasible and have better dynamic and tracking performances compared to traditional PID controllers