RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation

Large Language Models (LLMs) have demonstrated remarkable capabilities and have been extensively deployed across various domains, including recommender systems. Prior research has employed specialized \textit{prompts} to leverage the in-context learning capabilities of LLMs for recommendation purposes. More recent studies have utilized instruction tuning techniques to align LLMs with human preferences, promising more effective recommendations. However, existing methods suffer from several limitations. The full potential of LLMs is not fully elicited due to low-quality tuning data and the overlooked integration of conventional recommender signals. Furthermore, LLMs may generate inconsistent responses for different ranking tasks in the recommendation, potentially leading to unreliable results. In this paper, we introduce \textbf{RecRanker}, tailored for instruction tuning LLMs to serve as the \textbf{Ranker} for top-\textit{k} \textbf{Rec}ommendations. Specifically, we introduce an adaptive sampling module for sampling high-quality, representative, and diverse training data. To enhance the prompt, we introduce a position shifting strategy to mitigate position bias and augment the prompt with auxiliary information from conventional recommendation models, thereby enriching the contextual understanding of the LLM. Subsequently, we utilize the sampled data to assemble an instruction-tuning dataset with the augmented prompts comprising three distinct ranking tasks: pointwise, pairwise, and listwise rankings. We further propose a hybrid ranking method to enhance the model performance by ensembling these ranking tasks. Our empirical evaluations demonstrate the effectiveness of our proposed RecRanker in both direct and sequential recommendation scenarios

Does high-speed rail stimulate university technology transfer? evidence from China.

Prior studies ignore the impact of infrastructure on university technology transfer. High-speed rail, China's most significant infrastructure, has played an essential role in the economy and society. Using high-speed railway construction as a quasi-experiment and a large sample of Chinese universities for the 2007-2017 period, we investigate the impact of high-speed rail on university technology transfer. We provide extensive evidence that high-speed rail has a positive effect on university technology transfer. The finding remains valid after a battery of robustness tests. Mechanism tests find that high-speed rail can improve university technology transfer by promoting the interaction between universities and enterprises and improving enterprises' technology demand for universities. Further analysis shows that better intellectual property protection strengthens the effect of high-speed rail on university technology transfer, and the relationship between high-speed rail and university technology transfer is more prominent in the regions with underdevelopment technology trading markets. Our study suggests that high-speed rail is an important variable that affects university technology transfer

Underrepresentation of the Linkage between the Barents–Kara Sea Ice and East Asian Rainfall in Early Summer by CMIP6 Models

Our previous study revealed the link between Barents–Kara sea ice and rainfall in eastern China. This study continues evaluating the performance of multiple models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating this linkage. Most CMIP6 models can simulate Arctic sea ice coverage in the present climate system, although the sea ice extent in the edge areas show some biases. Only a few models can roughly reproduce the observed rainfall dipole pattern associated with Arctic sea ice variability. The linkage between Arctic sea ice variability in winter and eastern China rainfall in early summer is performed through a long memory of the sea ice, the stratospheric variability as the mediator, and downward propagation of stratospheric signals. Very few CMIP6 models can exhibit a realistic interannual relationship between the Arctic sea ice and China rainfall. The selected high-skill models with a more realistic linkage between sea ice and China rainfall present a clear downward impact of the stratospheric circulation anomalies associated with sea ice variability. The reversal of the Northern Hemisphere Annular Mode (NAM) from the negative phase in early winter to the positive phase in spring in the high-skill models and observations denotes the important role of the stratosphere as a mediator to bridge the Arctic sea ice and China rainfall. The long memory of the Arctic sea ice with the stratosphere as the mediator has a deep implication on the seasonal forecasts of East Asian countries

Can LLM Substitute Human Labeling? A Case Study of Fine-grained Chinese Address Entity Recognition Dataset for UAV Delivery

We present CNER-UAV, a fine-grained \textbf{C}hinese \textbf{N}ame \textbf{E}ntity \textbf{R}ecognition dataset specifically designed for the task of address resolution in \textbf{U}nmanned \textbf{A}erial \textbf{V}ehicle delivery systems. The dataset encompasses a diverse range of five categories, enabling comprehensive training and evaluation of NER models. To construct this dataset, we sourced the data from a real-world UAV delivery system and conducted a rigorous data cleaning and desensitization process to ensure privacy and data integrity. The resulting dataset, consisting of around 12,000 annotated samples, underwent human experts and \textbf{L}arge \textbf{L}anguage \textbf{M}odel annotation. We evaluated classical NER models on our dataset and provided in-depth analysis. The dataset and models are publicly available at \url{https://github.com/zhhvvv/CNER-UAV}.Comment: Accepted by TheWebConf'24 (WWW'24) as a Resource Pape

Lagged Linkage between the Kara–Barents Sea Ice and Early Summer Rainfall in Eastern China in Chinese CMIP6 Models

The lagged relationship between Kara–Barents sea ice and summer precipitation in eastern China is evaluated for Chinese models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). A previous study revealed a dipole rainfall structure in eastern China related to winter Arctic sea ice variability. Almost all Chinese CMIP6 models reproduce the variability and climatology of the sea ice in most of the Arctic well except the transition regions with evident biases. Further, all Chinese CMIP6 models successfully simulate the decreasing trend for the Kara–Barents sea ice. The dipole centers located in the Yangtze–Huai River Valley (YHRV) and South China (SC) related to Kara–Barents sea ice variability are simulated with different degrees of success. The anomalous dipole rainfall structure related to the winter Kara–Barents sea ice variability can roughly be reproduced by two models, while other models reproduce a shifted rainfall anomaly pattern or with the sign reversed. The possible delayed influence of sea ice forcing on early summer precipitation in China is established via three possible processes: the long memory of ice, the long-lasting stratospheric anomalies triggered by winter sea ice forcing, and the downward impact of the stratosphere as the mediator. Most Chinese models can simulate the negative Northern Hemisphere Annular Mode (NAM) phase in early winter but fail to reproduce the reversal of the stratospheric anomalies to a positive NAM pattern in spring and early summer. Most models underestimate the downward impact from the stratosphere to the troposphere. This implies that the stratospheric pathway is essential to mediate the winter sea ice forcing and rainfall in early summer over China for CMIP6 models

Dark tourism spectrum : visual expression of dark experience

Dark-light spectrum was used to express the depth of dark experience in dark tourism. Based on embodied cognition theory, this paper examined the visual expression of tourists' dark tourism experience. Five consecutive studies were conducted including analysis of tourists' photos in online reviews of 53 dark tourism destinations worldwide, charcoal pencil painting tasks of selected dark tourism sites in lab experiments, and field experiment. Results showed that tourists with darker experience tend to use deeper visual darkness to express their feelings, in the forms of painting and photographs, even when the cognitive process (i.e., expression in the form of words) is omitted. This psychological mechanism explains the scientific principle behind dark tourism spectrum. Our research suggests a new way of interpretation of tourist image data (e.g., photos) and sheds light for effective management of tourist experience

Effects of <i>Clostridium tyrobutyricum</i> on Lipid Metabolism, Intestinal Barrier Function, and Gut Microbiota in Obese Mice Induced by High-Fat Diet

Obesity and its complications constitute a main threat to global human health. The purpose of this investigation was to explore the influences of Clostridium tyrobutyricum (Ct) on lipid metabolism, intestinal barrier function, and intestinal microbiome in obese mice induced by a high-fat diet (HFD). After establishing the obesity model, 107 CFU/mL and 108 CFU/mL C. tyrobutyricum were used to intervene in HFD-fed mice by gavage for six weeks, and indexes related to obesity were measured. In the liver of HFD-fed mice, the results revealed that C. tyrobutyricum reduced liver weight and the levels of triglyceride (TG), total cholesterol (TC), and nonesterified fatty acid (NEFA), along with decreasing red lipid droplets and fat vacuoles. After C. tyrobutyricum intervention, the mRNA expression of peroxisome proliferator-activated receptor-γ (PPARγ) was downregulated, and AMP-activated protein kinase (AMPK), peroxisome proliferator-activated receptor-α (PPARα), adipose triglyceride lipase (ATGL), and hormone-sensitive lipase (HSL) were upregulated in the liver. Additionally, C. tyrobutyricum alleviated intestinal morphology injury caused by HFD, decreased the expression of tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), and IL-1β in the colon, and upregulated tight junction protein expression. In addition, 16S rRNA sequencing revealed that C. tyrobutyricum increases the diversity of intestinal microbiota. Overall, C. tyrobutyricum improved HFD-induced lipid metabolism disorders, preserved the intestinal barrier’s integrity, and modulated the structure of the intestinal microbiome. These findings provide a novel insight into the role of C. tyrobutyricum as a probiotic in regulating lipid metabolism

Butyrate Glycerides Protect against Intestinal Inflammation and Barrier Dysfunction in Mice

This study investigates the attenuating effects of butyrate glycerides (BG) on intestinal inflammatory responses and barrier dysfunction induced by LPS stimulation. An initial dose-response test was carried out to identify the optimal dose of BG for further testing. The mice were given intragastric administration of BG at different doses followed by lipopolysaccharide (LPS) intraperitoneal injection. The small intestinal morphology and cytokine mRNA expression were measured. With 1.5 g/kg BW BG administration, it was possible to alleviate the injury of duodenal morphology, attenuate ileum villus height reduction and promote IL-10 mRNA expression. Therefore, the optimal dosage of 1.5 g/kg BW BG was selected for the main experiment. The ultrastructure image of jejunum and ileum epithelial cells, mRNA expression, the level of cytokine and immunofluorescence in the ileum were analyzed. The results showed that BG maintain the ileac brush border, tight junction structures and protein expression. BG attenuated the increased inflammatory cytokines, TLR4 and JNK mRNA expression. Taken together, 1.5 g/kg BW BG administration maintained intestinal barrier function and reduced intestinal and body inflammation responses induced by LPS in mice. The mechanism by which BG alleviated intestinal inflammatory response and maintained intestinal barrier function may be related to the JNK signaling pathway

DataSheet_1_Identification of ipsilateral supraclavicular lymph node metastasis in breast cancer based on LASSO regression with a high penalty factor.pdf

Aiming at the problems of small sample size and large feature dimension in the identification of ipsilateral supraclavicular lymph node metastasis status in breast cancer using ultrasound radiomics, an optimized feature combination search algorithm is proposed to construct linear classification models with high interpretability. The genetic algorithm (GA) is used to search for feature combinations within the feature subspace using least absolute shrinkage and selection operator (LASSO) regression. The search is optimized by applying a high penalty to the L1 norm of LASSO to retain excellent features in the crossover operation of the GA. The experimental results show that the linear model constructed using this method outperforms those using the conventional LASSO regression and standard GA. Therefore, this method can be used to build linear models with higher classification performance and more robustness.</p

Effect of denosumab on glucose metabolism in postmenopausal osteoporotic women with prediabetes: a study protocol for a 12-month multicenter, open-label, randomized controlled trial

Abstract Background Participants with prediabetes are at a high risk of developing type 2 diabetes (T2D). Recent studies have suggested that blocking the receptor activator of nuclear factor-κB ligand (RANKL) may improve glucose metabolism and delay the development of T2D. However, the effect of denosumab, a fully human monoclonal antibody that inhibits RANKL, on glycemic parameters in the prediabetes population is uncertain. We aim to examine the effect of denosumab on glucose metabolism in postmenopausal women with osteoporosis and prediabetes. Methods This is a 12-month multicenter, open-label, randomized controlled trial involving postmenopausal women who have been diagnosed with both osteoporosis and prediabetes. Osteoporosis is defined by the World Health Organization (WHO) as a bone mineral density T score of ≤ − 2.5, as measured by dual-energy X-ray absorptiometry (DXA). Prediabetes is defined as (i) a fasting plasma glucose level of 100–125 mg/dL, (ii) a 2-hour plasma glucose level of 140–199 mg/dL, or (iii) a glycosylated hemoglobin A1c (HbA1c) level of 5.7–6.4%. A total of 346 eligible subjects will be randomly assigned in a 1:1 ratio to receive either subcutaneous denosumab 60 mg every 6 months or oral alendronate 70 mg every week for 12 months. The primary outcome is the change in HbA1c levels from baseline to 12 months. Secondary outcomes include changes in fasting and 2-hour blood glucose levels, serum insulin levels, C-peptide levels, and insulin sensitivity from baseline to 12 months, and the incidence of T2D at the end of the study. Follow-up visits will be scheduled at 3, 6, 9, and 12 months. Discussion This study aims to provide evidence on the efficacy of denosumab on glucose metabolism in postmenopausal women with osteoporosis and prediabetes. The results derived from this clinical trial may provide insight into the potential of denosumab in preventing T2D in high-risk populations. Trial registration This study had been registered in the Chinese Clinical Trials Registry. Registration number: ChiCTR2300070789 on April 23, 2023. https://www.chictr.org.cn