Task Relation Distillation and Prototypical Pseudo Label for Incremental Named Entity Recognition

Incremental Named Entity Recognition (INER) involves the sequential learning of new entity types without accessing the training data of previously learned types. However, INER faces the challenge of catastrophic forgetting specific for incremental learning, further aggravated by background shift (i.e., old and future entity types are labeled as the non-entity type in the current task). To address these challenges, we propose a method called task Relation Distillation and Prototypical pseudo label (RDP) for INER. Specifically, to tackle catastrophic forgetting, we introduce a task relation distillation scheme that serves two purposes: 1) ensuring inter-task semantic consistency across different incremental learning tasks by minimizing inter-task relation distillation loss, and 2) enhancing the model's prediction confidence by minimizing intra-task self-entropy loss. Simultaneously, to mitigate background shift, we develop a prototypical pseudo label strategy that distinguishes old entity types from the current non-entity type using the old model. This strategy generates high-quality pseudo labels by measuring the distances between token embeddings and type-wise prototypes. We conducted extensive experiments on ten INER settings of three benchmark datasets (i.e., CoNLL2003, I2B2, and OntoNotes5). The results demonstrate that our method achieves significant improvements over the previous state-of-the-art methods, with an average increase of 6.08% in Micro F1 score and 7.71% in Macro F1 score.Comment: Accepted by CIKM2023 as a long paper with an oral presentatio

Comparison of doxycycline and benzathine penicillin G for the treatment of early syphilis

Doxycycline is the preferred recommended second-line treatment for the treatment of early syphilis. Recent reports showed a declining efficacy trend of doxycycline in treatment of early syphilis. The aim of our study was to assess the serological response to the treatment for early syphilis with doxycycline compared with benzathine penicillin G and evaluate whether doxycycline is still an effective agent for the treatment of early syphilis. A record-based retrospective study was conducted. Patients were diagnosed with early syphilis in an sexually transmitted disease (STD) clinic from January 1, 2008 to December 31, 2014. They were treated with a single dose of benzathine penicillin G 2.4MU or oral doxycycline 100 mg twice daily for 14 days. Pearson’s chi-squared test was used for data analysis. 601 cases were included in the final study sample: 105 (17.5%) patients received a 14-day course of doxycycline (doxycycline group), and 496 (82.5%) patients received single-dose benzathine penicillin G (BPG group). The serological responses at 6 months and 12 months after treatment were compared. No statistically significant differences were found between the two groups at 6 months (69.52% vs. 75.00%, P=0.245), and at 12 months (92.38% vs. 96.17%, P=0.115). Doxycycline is still an effective agent for the treatment of early syphilis. </p

The Development of LLMs for Embodied Navigation

In recent years, the rapid advancement of Large Language Models (LLMs) such as the Generative Pre-trained Transformer (GPT) has attracted increasing attention due to their potential in a variety of practical applications. The application of LLMs with Embodied Intelligence has emerged as a significant area of focus. Among the myriad applications of LLMs, navigation tasks are particularly noteworthy because they demand a deep understanding of the environment and quick, accurate decision-making. LLMs can augment embodied intelligence systems with sophisticated environmental perception and decision-making support, leveraging their robust language and image-processing capabilities. This article offers an exhaustive summary of the symbiosis between LLMs and embodied intelligence with a focus on navigation. It reviews state-of-the-art models, research methodologies, and assesses the advantages and disadvantages of existing embodied navigation models and datasets. Finally, the article elucidates the role of LLMs in embodied intelligence, based on current research, and forecasts future directions in the field. A comprehensive list of studies in this survey is available at https://github.com/Rongtao-Xu/Awesome-LLM-E

Cognition, Aryl Hydrocarbon Receptor Repressor Methylation, and Abstinence Duration-Associated Multimodal Brain Networks in Smoking and Long-Term Smoking Cessation

Cigarette smoking and smoking cessation are associated with changes in cognition and DNA methylation; however, the neurobiological correlates of these effects have not been fully elucidated, especially in long-term cessation. Cognitive performance, percent methylation of the aryl hydrocarbon receptor repressor (AHRR) gene, and abstinence duration were used as references to supervise a multimodal fusion analysis of functional, structural, and diffusion magnetic resonance imaging (MRI) data, in order to identify associated brain networks in smokers and ex-smokers. Correlations among these networks and with smoking-related measures were performed. Cognition-, methylation-, and abstinence duration-associated networks discriminated between smokers and ex-smokers and correlated with differences in fractional amplitude of low frequency fluctuations (fALFF) values, gray matter volume (GMV), and fractional anisotropy (FA) values. Long-term smoking cessation was associated with more accurate cognitive performance, as well as lower fALFF and more GMV in the hippocampus complex. The methylation- and abstinence duration-associated networks positively correlated with smoking-related measures of abstinence duration and percent methylation, respectively, suggesting they are complementary measures. This analysis revealed structural and functional co-alterations linked to smoking abstinence and cognitive performance in brain regions including the insula, frontal gyri, and lingual gyri. Furthermore, AHRR methylation, a promising epigenetic biomarker of smoking recency, may provide an important complement to self-reported abstinence duration

Cognition, Aryl Hydrocarbon Receptor Repressor Methylation, and Abstinence Duration-Associated Multimodal Brain Networks in Smoking and Long-Term Smoking Cessation

Cigarette smoking and smoking cessation are associated with changes in cognition and DNA methylation; however, the neurobiological correlates of these effects have not been fully elucidated, especially in long-term cessation. Cognitive performance, percent methylation of the aryl hydrocarbon receptor repressor (AHRR) gene, and abstinence duration were used as references to supervise a multimodal fusion analysis of functional, structural, and diffusion magnetic resonance imaging (MRI) data, in order to identify associated brain networks in smokers and ex-smokers. Correlations among these networks and with smoking-related measures were performed. Cognition-, methylation-, and abstinence duration-associated networks discriminated between smokers and ex-smokers and correlated with differences in fractional amplitude of low frequency fluctuations (fALFF) values, gray matter volume (GMV), and fractional anisotropy (FA) values. Long-term smoking cessation was associated with more accurate cognitive performance, as well as lower fALFF and more GMV in the hippocampus complex. The methylation- and abstinence duration-associated networks positively correlated with smoking-related measures of abstinence duration and percent methylation, respectively, suggesting they are complementary measures. This analysis revealed structural and functional co-alterations linked to smoking abstinence and cognitive performance in brain regions including the insula, frontal gyri, and lingual gyri. Furthermore, AHRR methylation, a promising epigenetic biomarker of smoking recency, may provide an important complement to self-reported abstinence duration

Human Influenza A (H5N1) Cases, Urban Areas of People’s Republic of China, 2005–2006

We investigated potential sources of infection for 6 confirmed influenza A (H5N1) patients who resided in urban areas of People’s Republic of China. None had known exposure to sick poultry or poultry that died from illness, but all had visited wet poultry markets before illness

Changes in Soil Bacterial Community and Function in Winter Following Long-Term Nitrogen (N) Deposition in Wetland Soil in Sanjiang Plain, China

N deposition is a key factor affecting the composition and function of soil microbial communities in wetland ecosystems. Previous studies mainly focused on the effects of N deposition in the soil during the growing season (summer and autumn). Here, we focused on the response of the soil microbial community structure and function in winter. Soil from the Sanjiang Plain wetland, China, that had been treated for the past 11 years by using artificial N deposition at three levels (no intervention in N0, N deposition with 4 g N m−2 yr−1 in N1, and with 8 g N m−2 yr−1 in N2). Soil characteristics were determined and the bacterial composition and function was characterized using high-throughput sequence technology. The N deposition significantly reduced the soil bacterial diversity detected in winter compared with the control N0, and it significantly changed the composition of the bacterial community. At the phylum level, the high N deposition (N2) increased the relative abundance of Acidobacteria and decreased that of Myxococcota and Gemmatimonadota compared with N0. In soil from N2, the relative abundance of the general Candidatus_Solibacter and Bryobacter was significantly increased compared with N0. Soil pH, soil organic carbon (SOC), and total nitrogen (TN) were the key factors affecting the soil bacterial diversity and composition in winter. Soil pH was correlated with soil carbon cycling, probably due to its significant correlation with aerobic_chemoheterotrophy. The results show that a long-term N deposition reduces soil nutrients in winter wetlands and decreases soil bacterial diversity, resulting in a negative impact on the Sanjiang plain wetland. This study contributes to a better understanding of the winter responses of soil microbial community composition and function to the N deposition in temperate wetland ecosystems