Manin triples associated to nn-Lie bialgebras

In this paper, we study the Manin triples associated to $n$-Lie bialgebras. We develop the method of double constructions as well as operad matrices to make $n$-Lie bialgebras into Manin triples. Then, the related Manin triples lead to a natural construction of metric $n$-Lie algebras. Moreover, a one-to-one correspondence between the double of $n$-Lie bialgebras and Manin triples of $n$-Lie algebras be established

The Developing Blueberry Industry in China

The present situation of blueberry industry in China was summarized. The six main blueberry cultivation areas in China were reviewed and practical suggestions were made. Reference and guidance for water management of rabbiteye blueberry in Yangtze river basin was provided, and water physiological characteristics and water requirement of blueberry were also clarified so as to provide scientific management of blueberry. Effects of vinegar residue on soil physical and chemical properties, enzymatic activities, growth of blueberry, nutrient uptake, and fruit quality were studied. The effect of vinegar residue on the growth of blueberry and the mechanism revealed from the perspective of soil amelioration were also discussed from the results

CIR at the NTCIR-17 ULTRE-2 Task

The Chinese academy of sciences Information Retrieval team (CIR) has participated in the NTCIR-17 ULTRE-2 task. This paper describes our approaches and reports our results on the ULTRE-2 task. We recognize the issue of false negatives in the Baidu search data in this competition is very severe, much more severe than position bias. Hence, we adopt the Dual Learning Algorithm (DLA) to address the position bias and use it as an auxiliary model to study how to alleviate the false negative issue. We approach the problem from two perspectives: 1) correcting the labels for non-clicked items by a relevance judgment model trained from DLA, and learn a new ranker that is initialized from DLA; 2) including random documents as true negatives and documents that have partial matching as hard negatives. Both methods can enhance the model performance and our best method has achieved nDCG@10 of 0.5355, which is 2.66% better than the best score from the organizer.Comment: 5 pages, 1 figure, NTCIR-1

Feature-Enhanced Network with Hybrid Debiasing Strategies for Unbiased Learning to Rank

Unbiased learning to rank (ULTR) aims to mitigate various biases existing in user clicks, such as position bias, trust bias, presentation bias, and learn an effective ranker. In this paper, we introduce our winning approach for the "Unbiased Learning to Rank" task in WSDM Cup 2023. We find that the provided data is severely biased so neural models trained directly with the top 10 results with click information are unsatisfactory. So we extract multiple heuristic-based features for multi-fields of the results, adjust the click labels, add true negatives, and re-weight the samples during model training. Since the propensities learned by existing ULTR methods are not decreasing w.r.t. positions, we also calibrate the propensities according to the click ratios and ensemble the models trained in two different ways. Our method won the 3rd prize with a DCG@10 score of 9.80, which is 1.1% worse than the 2nd and 25.3% higher than the 4th.Comment: 5 pages, 1 figure, WSDM Cup 202

On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective

Recently, we have witnessed generative retrieval increasingly gaining attention in the information retrieval (IR) field, which retrieves documents by directly generating their identifiers. So far, much effort has been devoted to developing effective generative retrieval models. There has been less attention paid to the robustness perspective. When a new retrieval paradigm enters into the real-world application, it is also critical to measure the out-of-distribution (OOD) generalization, i.e., how would generative retrieval models generalize to new distributions. To answer this question, firstly, we define OOD robustness from three perspectives in retrieval problems: 1) The query variations; 2) The unforeseen query types; and 3) The unforeseen tasks. Based on this taxonomy, we conduct empirical studies to analyze the OOD robustness of several representative generative retrieval models against dense retrieval models. The empirical results indicate that the OOD robustness of generative retrieval models requires enhancement. We hope studying the OOD robustness of generative retrieval models would be advantageous to the IR community.Comment: 4 pages, submit to GenIR2

Neurometabolic and structural alterations of medial septum and hippocampal CA1 in a model of post-operative sleep fragmentation in aged mice: a study combining 1H-MRS and DTI

Post-operative sleep disturbance is a common feature of elderly surgical patients, and sleep fragmentation (SF) is closely related to post-operative cognitive dysfunction (POCD). SF is characterized by sleep interruption, increased number of awakenings and sleep structure destruction, similar to obstructive sleep apnea (OSA). Research shows that sleep interruption can change neurotransmitter metabolism and structural connectivity in sleep and cognitive brain regions, of which the medial septum and hippocampal CA1 are key brain regions connecting sleep and cognitive processes. Proton magnetic resonance spectroscopy (1H-MRS) is a non-invasive method for the evaluation of neurometabolic abnormalities. Diffusion tensor imaging (DTI) realizes the observation of structural integrity and connectivity of brain regions of interest in vivo. However, it is unclear whether post-operative SF induces harmful changes in neurotransmitters and structures of the key brain regions and their contribution to POCD. In this study, we evaluated the effects of post-operative SF on neurotransmitter metabolism and structural integrity of medial septum and hippocampal CA1 in aged C57BL/6J male mice. The animals received a 24-h SF procedure after isoflurane anesthesia and right carotid artery exposure surgery. 1H-MRS results showed after post-operative SF, the glutamate (Glu)/creatine (Cr) and glutamate + glutamine (Glx)/Cr ratios increased in the medial septum and hippocampal CA1, while the NAA/Cr ratio decreased in the hippocampal CA1. DTI results showed post-operative SF decreased the fractional anisotropy (FA) of white matter fibers in the hippocampal CA1, while the medial septum was not affected. Moreover, post-operative SF aggravated subsequent Y-maze and novel object recognition performances accompanied by abnormal enhancement of glutamatergic metabolism signal. This study suggests that 24-h SF induces hyperglutamate metabolism level and microstructural connectivity damage in sleep and cognitive brain regions in aged mice, which may be involved in the pathophysiological process of POCD

Inhibition of PPARγ by BZ26, a GW9662 derivate, attenuated obesity-related breast cancer progression by inhibiting the reprogramming of mature adipocytes into to cancer associate adipocyte-like cells

Obesity has been associated with the development of 13 different types of cancers, including breast cancer. Evidence has indicated that cancer-associated adipocytes promote the proliferation, invasion, and metastasis of cancer. However, the mechanisms that link CAAs to the progression of obesity-related cancer are still unknown. Here, we found the mature adipocytes in the visceral fat of HFD-fed mice have a CAAs phenotype but the stromal vascular fraction of the visceral fat has not. Importantly, we found the derivate of the potent PPARγ antagonist GW9662, BZ26 inhibited the reprogramming of mature adipocytes in the visceral fat of HFD-fed mice into CAA-like cells and inhibited the proliferation and invasion of obesity-related breast cancer. Further study found that it mediated the browning of visceral, subcutaneous and perirenal fat and attenuated inflammation of adipose tissue and metabolic disorders. For the mechanism, we found that BZ26 bound and inhibited PPARγ by acting as a new modulator. Therefore, BZ26 serves as a novel modulator of PPARγ activity, that is, capable of inhibiting obesity-related breast cancer progression by inhibiting of CAA-like cell formation, suggesting that inhibiting the reprogramming of mature adipocytes into CAAs or CAA-like cells may be a potential therapeutic strategy for obesity-related cancer treatment

Synthetic engineering of a new biocatalyst encapsulating [NiFe]-hydrogenases for enhanced hydrogen production

Hydrogenases are microbial metalloenzymes capable of catalyzing the reversible interconversion between molecular hydrogen and protons with high efficiency, and have great potential in the development of new electrocatalysts for renewable...</jats:p