Towards Equipping Transformer with the Ability of Systematic Compositionality

One of the key factors in language productivity and human cognition is the ability of systematic compositionality, which refers to understanding composed unseen examples of seen primitives. However, recent evidence reveals that the Transformers have difficulty generalizing the composed context based on the seen primitives. To this end, we take the first step to propose a compositionality-aware Transformer called CAT and two novel pre-training tasks to facilitate systematic compositionality. We tentatively provide a successful implementation of a multi-layer CAT on the basis of the especially popular BERT. The experimental results demonstrate that CAT outperforms baselines on compositionality-aware tasks with minimal impact on the effectiveness on standardized language understanding tasks.Comment: Accepted to AAAI 2024. Paper with appendi

Concept -- An Evaluation Protocol on Conversational Recommender Systems with System-centric and User-centric Factors

The conversational recommendation system (CRS) has been criticized regarding its user experience in real-world scenarios, despite recent significant progress achieved in academia. Existing evaluation protocols for CRS may prioritize system-centric factors such as effectiveness and fluency in conversation while neglecting user-centric aspects. Thus, we propose a new and inclusive evaluation protocol, Concept, which integrates both system- and user-centric factors. We conceptualise three key characteristics in representing such factors and further divide them into six primary abilities. To implement Concept, we adopt a LLM-based user simulator and evaluator with scoring rubrics that are tailored for each primary ability. Our protocol, Concept, serves a dual purpose. First, it provides an overview of the pros and cons in current CRS models. Second, it pinpoints the problem of low usability in the "omnipotent" ChatGPT and offers a comprehensive reference guide for evaluating CRS, thereby setting the foundation for CRS improvement.Comment: 33 pages, 18 tables, and 10 figures. Our code is available at https://github.com/huangzichun/Concept4CR

A Bibliometric Analysis of Literatures on Uterine Leiomyosarcoma in the Last 20 Years

Background: Uterine leiomyosarcoma(uLMS) is a rare malignant tumor with low clinical specificity and poor prognosis.There are many studies related to uLMS, however, there is still a lack of metrological analyses with generalization. This study provides a bibliometric study of uLMS. Methods and materials: We chose the Web of Science (WoS) as our main database due to its extensive interdisciplinary coverage. We specifically focused on the literature from the last 20 years to ensure relevance and practicality. By utilizing the WOS core dataset and leveraging the R package bibliometric version 4.1.0 and Citespace, we performed a comprehensive bibliometric analysis. This allowed us to pinpoint research hotspots and create visual representations, resulting in the retrieval of 2489 pertinent articles. Results: This literature review covers 2489 articles on uterine leiomyosarcoma (uLMS) from the past 20 years. Key findings include an average annual publication rate of 8.75, with a 6.07% yearly growth rate and an average citation count of 17.22. Core+Zone 2 sources contributed 1079 articles and 207 reviews, displaying a 4.98% annual growth rate. The analysis identified top journals, influential authors, and core sources, such as the prevalence of publications from the United States and the dominance of GYNECOLOGIC ONCOLOGY and HENSLEY ML. Bradford\u27s Law and Lotka\u27s Law highlighted core sources and author productivity, respectively. Thematic mapping and factorial analysis revealed research clusters, including etiology, diagnosis, treatment advancements, and surgical approaches, with prominent themes such as gemcitabine and docetaxel. Overall, this comprehensive analysis provides insights into uLMS literature trends and influential factors. Conclusion: This thorough bibliometric analysis, in its whole, illuminates the field\u27s guiding principles while also revealing the subtle patterns within the uLMS literature. The knowledge gained here contributes to the current discussion in uLMS and related scientific fields and provides a solid basis for future research paths

Administration of alpha klotho reduces liver and adipose lipid accumulation in obese mice

α-Klotho, a known anti-aging protein, exerts diverse physiological effects including: maintenance of phosphate and calcium homeostasis, modulation of cell proliferation, and enhanced buffering of reactive oxygen species. However, the role of α-Klotho in the regulation of energy metabolism is complex and poorly understood. Here we investigated the effects of 5 weeks peripheral administration of α-Klotho in high fat diet induced obese mice. Food intake, blood glucose, and body weight were measured daily. Energy expenditure was determined with indirect calorimetry and body composition with magnetic resonance imaging. Liver and adipose tissue were collected for lipid content measurements and gene expression analysis. α-Klotho-treated mice experienced reduced adiposity, increased lean mass, and elevated energy expenditure, despite no changes in food intake, body weight, or fed blood glucose levels. Lipid accumulation in liver and adipose tissue was also reduced compared to controls. Furthermore, Real-time quantitative PCR showed reduced expression of key lipogenic genes in α-Klotho treated mice in these organs. Taken together, these data suggest encouraging therapeutic potential of α-Klotho and highlight a need for further research into the specific mechanisms explaining improved body composition, elevated energy expenditure, and reduced lipid content in both liver and adipose tissue in α-Klotho-treated mice

Biomass-derived carbons for sodium-ion batteries and sodium-ion capacitors

In the past decade, the rapid development of portable electronic devices, electric vehicles, and electrical devices has stimulated extensive interest in fundamental research and the commercialization of electrochemical energy-storage systems. Biomass-derived carbon has garnered significant research attention as an efficient, inexpensive, and eco-friendly active material for energy-storage systems. Therefore, high-performance carbonaceous materials, derived from renewable sources, have been utilized as electrode materials in sodium-ion batteries and sodium-ion capacitors. Herein, the charge-storage mechanism and utilization of biomass-derived carbon for sodium storage in batteries and capacitors are summarized. In particular, the structure–performance relationship of biomass-derived carbon for sodium storage in the form of batteries and capacitors is discussed. Despite the fact that further research is required to optimize the process and application of biomass-derived carbon in energy-storage devices, the current review demonstrates the potential of carbonaceous materials for next-generation sodium-related energy-storage applications.</p

Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph

We study the problem of safe and intention-aware robot navigation in dense and interactive crowds. Most previous reinforcement learning (RL) based methods fail to consider different types of interactions among all agents or ignore the intentions of people, which results in performance degradation. In this paper, we propose a novel recurrent graph neural network with attention mechanisms to capture heterogeneous interactions among agents through space and time. To encourage longsighted robot behaviors, we infer the intentions of dynamic agents by predicting their future trajectories for several timesteps. The predictions are incorporated into a model-free RL framework to prevent the robot from intruding into the intended paths of other agents. We demonstrate that our method enables the robot to achieve good navigation performance and non-invasiveness in challenging crowd navigation scenarios. We successfully transfer the policy learned in simulation to a real-world TurtleBot 2i

Developing a class of dual atom materials for multifunctional catalytic reactions

Dual atom catalysts, bridging single atom and metal/alloy nanoparticle catalysts, offer more opportunities to enhance the kinetics and multifunctional performance of oxygen reduction/evolution and hydrogen evolution reactions. However, the rational design of efficient multifunctional dual atom catalysts remains a blind area and is challenging. In this study, we achieved controllable regulation from Co nanoparticles to CoN4 single atoms to Co2N5 dual atoms using an atomization and sintering strategy via an N-stripping and thermal-migrating process. More importantly, this strategy could be extended to the fabrication of 22 distinct dual atom catalysts. In particular, the Co2N5 dual atom with tailored spin states could achieve ideally balanced adsorption/desorption of intermediates, thus realizing superior multifunctional activity. In addition, it endows Zn-air batteries with long-term stability for 800 h, allows water splitting to continuously operate for 1000 h, and can enable solar-powered water splitting systems with uninterrupted large-scale hydrogen production throughout day and night. This universal and scalable strategy provides opportunities for the controlled design of efficient multifunctional dual atom catalysts in energy conversion technologies

AgRP/NPY Neuron Excitability Is Modulated by Metabotropic Glutamate Receptor 1 During Fasting

The potential to control feeding behavior via hypothalamic AgRP/NPY neurons has led to many approaches to modulate their excitability—particularly by glutamatergic input. In the present study using NPY-hrGFP reporter mice, we visualize AgRP/NPY neuronal metabotropic glutamate receptor 1 (mGluR1) expression and test the effect of fasting on mGluR1 function. Using the pharmacological agonist dihydroxyphenylglycine (DHPG), we demonstrate the enhanced capacity of mGluR1 to drive firing of AgRP/NPY neurons after overnight fasting, while antagonist 3-MATIDA reduces firing. Further, under synaptic blockade we demonstrate that DHPG acts directly on AgRP/NPY neurons to create a slow inward current. Using an in vitro approach, we show that emulation of intracellular signals associated with fasting by forskolin enhances DHPG induced phosphorylation of extracellularly regulated-signal kinase (1/2) in GT1-7 cell culture. We show in vivo that blocking mGluR1 by antagonist 3-MATIDA lowers fasting induced refeeding. In summary, this study identifies a novel layer of regulation on AgRP/NPY neurons integrated with whole body energy balance

FXR Acts as a Metastasis Suppressor in Intrahepatic Cholangiocarcinoma by Inhibiting IL-6-Induced Epithelial-Mesenchymal Transition

Background/Aims: Intrahepatic cholangiocarcinoma (ICC) is a complicated condition, with difficult diagnosis and poor prognosis. The expression and clinical significance of the farnesoid X receptor (FXR), an endogenous receptor of bile acids, in ICC is not well understood. Methods: Western blotting and immunochemical analyses were used to determine the levels of FXR in 4 cholangiocarcinoma cell lines, a human intrahepatic biliary epithelial cell line (HIBEpic) and 322 ICC specimens, respectively, while quantitative reverse transcription polymerase chain reaction was used to detect the mRNA levels of FXR in cholangiocarcinoma cell lines. We evaluated the prognostic value of FXR expression and its association with clinical parameters. We determined the biological significance of FXR in ICC cell lines by agonist-mediated activation and lentivirus-mediated silence. IL-6 expression was tested by an enzyme-linked immunosorbent assay and flow cytometry. In vitro, cell proliferation was examined by Cell Counting Kit-8, migration and invasion were examined by wound healing and transwell assays; in vivo, tumor migration and invasion were explored in NOD-SCID mice. Results: FXR was downregulated in ICC cell lines and clinical ICC specimens. Loss of FXR was markedly correlated with aggressive tumor phenotypes and poor prognosis in patients with ICC. Moreover, FXR expression also had significant prognostic value in carbohydrate antigen 19-9 (CA19-9) negative patients. The expression of FXR was negatively correlated with IL-6 levels in clinical ICC tissues. FXR inhibited the proliferation, migration, invasion and epithelial mesenchymal transition (EMT) of ICC cells via suppression of IL-6 in vitro. Obeticholic acid, an agonist of FXR, inhibited IL-6 production, tumor growth and lung metastasis of ICC in vivo. Conclusions: FXR could be a promising ICC prognostic biomarker, especially in CA19-9 negative patients with ICC. FXR inhibits the tumor growth and metastasis of ICC via IL-6 suppression