Search

BACKGROUND: Interest in modifiable risk factors (MRFs) for dementia is high, given the personal, social, and economic impact of the disorder, especially in ageing societies such as the United Kingdom. Exploring the population attributable fraction (PAF) of dementia attributable to MRFs and how this may have changed over time remains unclear. Unravelling the temporal dynamics of MRFs is crucial for informing the development of evidence-based and effective public health policies. This investigation examined the temporal trajectories of MRFs for dementia in England. METHODS: We used data from the English Longitudinal Study of Ageing, a panel study over eight waves collected between 2004 and 2019 (76,904 interviews in total). We calculated the PAFs for twelve MRFs (including six early- to mid-life factors and six late-life factors), as recommended by the Lancet Commission, and the individual weighted PAFs (IW-PAFs) for each risk factor. Temporal trends were analysed to understand the changes in the overall PAF and IW-PAF over the study period. Subgroup analyses were conducted by sex and socioeconomic status (SES). RESULTS: The overall PAF for dementia MRFs changed from 46.73% in 2004/2005 to 36.79% in 2018/2019, though this trend was not statistically significant. During 2004-2019, hypertension, with an average IW-PAF of 8.21%, was the primary modifiable determinant of dementia, followed by obesity (6.16%), social isolation (5.61%), hearing loss (4.81%), depression (4.72%), low education (4.63%), physical inactivity (3.26%), diabetes mellitus (2.49%), smoking (2.0%), excessive alcohol consumption (1.16%), air pollution (0.42%), and traumatic brain injury (TBI) (0.26%). During 2004-2019, only IW-PAFs of low education, social isolation, and smoking showed significant decreasing trends, while IW-PAFs of other factors either did not change significantly or increased (including TBI, diabetes mellitus, and air pollution). Upon sex-specific disaggregation, a higher overall PAF

Zhihong Cheng,1,* Song Feng,1,2,* Linfeng Yang,1 Jing Huang,3 Xilei Chen,4 Yang Guo,1 Yu Xiang,1 Bin Peng1 1Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China; 2Department of Neurosurgery, Dazhou Third People’s Hospital, Dazhou, Sichuan, People’s Republic of China; 3Innovation Center for Science and Technology, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China; 4Department of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Bin Peng, Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, No. 234 Fujiang Road, Shunqing District, Nanchong, Sichuan, People’s Republic of China, Tel/Fax +86-817-2242781, Email binpeng01@sina.comPurpose: The spinal nerve ligation (SNL) model is a typical peripheral neuropathic pain model. During its construction, the removal of paraspinal muscles and transverse processes typically occurs, resulting in additional trauma that may potentially affect the pathophysiologic process of neuropathic pain. This study aimed to investigate the feasibility of establishing a more reliable SNL model using an oblique lateral approach.Methods: 36 adult male Sprague-Dawley rats were randomly divided into three groups: the traditional SNL (T-SNL) group, the new SNL (N-SNL) group (where the left L5 spinal nerve was ligated with a titanium clip via an oblique lateral approach), and the sham-operated (Sham) group. The operation time, Intraoperative bleeding, the number of rats that died, gait behavior, mechanical and cold pain threshold were recorded and measured. Stereology technology was used to calculate the number of microglia in spinal dorsal horn, and the Enzyme-linked immunosorbent assay (ELISA) technology was used to detect the expression of TNF-α and IL-1β in spinal cord as well a

Despite the enormous developments in the asymmetric transformations of indole imine methides (IIMs), the remote asymmetric induction involving IIMs remains challenging due to the spatial interaction requirement between the substrate and catalyst. Herein we report the first catalytic asymmetric nucleophilic addition to indole imine 5-methide (5-IIM), the only topological isomer of IIMs whose asymmetric addition remains unknown. Despite the challenging remote stereocontrol, high efficiency and respectable enantioselectivity were achieved to provide access to a range of enantioenriched indole-containing triaryl alkanes. © 2024 American Chemical Society.

Jing-Jing Huang,1,* Lin Jia,2,3,* Qiao-Jun Zhang,4 Hao-Hong Li,5 Da-Li Zheng,2 Ming Zheng3 1Second Department of Dental Implant, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350001, People’s Republic of China; 2Fujian Key Laboratory of Oral Diseases, Fujian Biological Materials Engineering and Technology Center of Stomatology, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, Fujian, 350004, People’s Republic of China; 3Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University, Fuzhou, 350001, People’s Republic of China; 4Zhongshan Hospital Affiliated to Xiamen University, Xiamen, 361000, People’s Republic of China; 5College of Chemistry, Fuzhou University, Fuzhou, Fujian, 350116, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ming Zheng, Department of Prosthodontics, School and Hospital of Stomatology, Fujian Medical University, 246 Yangqiao Middle Road, Fuzhou, 350001, People’s Republic of China, Tel +86-591-83736431, Email zmdentist@163.com Da-Li Zheng, Fujian Key Laboratory of Oral Diseases, School and Hospital of Stomatology, Fujian Medical University, 88 Jiaotong Road, Fuzhou, 350004, People’s Republic of China, Tel +86-591-83720599, Email dalizheng@fjmu.edu.cnPurpose: To investigate the inhibition of Streptococcus mutans (S.mutans) and its biofilm by AgBr-nanoparticles (NP) @CTMAB (cetyltrimethyl-ammonium bromide) and evaluate the changes in Polymethyl methacrylate (PMMA)’s surface roughness (Ra), microhardness, and flexural strength during prolonged immersion in AgBr-NP@CTMAB for application in the denture cleaning industry.Patients and Methods: The antibacterial activity of AgBr-NP@CTMAB against S.mutans was measured colony formation assay, OD600 and laser confocal microscopy. Changes in the specimens’ values for surface roughness, microhardness, and flexural strength (MPa) were measured after i

Yujian Shao,1,2 Yonglu Chen,2 Mingyue Zhu,3 Yuanyuan Liu,2 Chen Fang,3 Minjun Wang,2 Peng Sun,3 Weiling Fu,2 Jing Huang,3 Shimei Sheng,2 Yanshan Huang2 1Zhejiang University School of Medicine, Zhejiang University, Hangzhou, Zhejiang, People’s Republic of China; 2Department of Innovative Drug Discovery and Development, Zhejiang Doer Biologics Co., Ltd, Hangzhou, Zhejiang, People’s Republic of China; 3First Research Institute, Zhejiang Heze Pharmaceutical Technology Co., Ltd, Hangzhou, Zhejiang, People’s Republic of ChinaCorrespondence: Yanshan Huang, Department of Innovative Drug Discovery and Development, Zhejiang Doer Biologics Co., Ltd, Hangzhou, Zhejiang, People’s Republic of China, Email yanshanhuang@doerbio.comIntroduction: Diabetes and obesity are momentous risk factors threatening people’s lives and health. Currently available incretin analogue glucagon-like peptide 1 (GLP-1) possesses huge hypoglycemic effect with the unsatisfactory effect of weight loss. Co-agonists targeting GLP-1R plus glucagon receptor (GCGR) or gastric inhibitory polypeptide receptor (GIPR) show synergistic benefits in glycaemic control and weight loss. Here, we describe a novel dual GIP and GLP-1 receptor agonist, DR10627, and performed a preclinical assessment of it.Methods: The agonistic ability of DR10627 was indirectly assessed by inducing cAMP accumulation in Chinese hamster ovary (CHO) cells transfected with GLP-1R or GIPR in vitro. The plasma pharmacokinetics of DR10627 were analysed in cynomolgus monkeys. The OGTTs were performed in Sprague‑Dawley (SD) rats. The glucose lowering effects were evaluated by repeated administration of DR10627 in diabetic (db/db) mice for 4 weeks. The effects of anti-obesity and improving metabolism of DR10627 were evaluated by repeated administration of DR10627 in diet-induced obesity (DIO) mice for 57 days.Results: DR10627 had the capacity to activate both GLP-1R and GIPR in vitro. The terminal half-life of DR10627 was found to be appr

Jing Huang,1 Hongxia Sun,2 Bei Tian2 1Department of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People’s Republic of China; 2Department of Nursing, Shanghai Pudong New Area Zhoupu Hospital (Shanghai Health Medical College Affiliated Zhoupu Hospital), Shanghai, 201318, People’s Republic of ChinaCorrespondence: Bei Tian, Department of Nursing, Shanghai Pudong New Area Zhoupu Hospital (Shanghai Health Medical College Affiliated Zhoupu Hospital), No. 1500 Zhou yuan Road, Pudong New District, Shanghai, 201318, People’s Republic of China, Tel +86-18121216302, Email 18121216302@163.comIntroduction: This study aims to explore the thought, feelings and perceptions of male nursing students and male nursing professionals in the nursing profession.Methods: This present study used a qualitative research design to explore the feelings, thoughts, and opinions of male nursing students (first to fourth years) and male nursing professionals about their perception of the nursing profession. The study recruited 11 male nursing students and 11 male nursing professionals using a purposive sampling method. Data were collected via semi-structured individual interviews using qualitative open-ended inquiries consisting of seven questions. The data were analysed using thematic perspectives.Results: The analysis revealed three themes: (a) perceiving gender varieties, (b) taking apparent advantage of masculine characteristics, and (c) taking an equal perspective. Male students’ replies to their professional gender attitudes were that there was no distinct line among the gender-related advantages and disadvantages according to whether they were first to fourth-year students.Conclusion: Male nursing students and professionals believe that nursing is equally appropriate for both men and women, and they could employ masculine characteristics to thrive in their professional development.Keywords: male nurses, professional development, interventional nursing

Jing-Bin Huang, Yun-Tian Tang Department of Cardiothoracic Surgery, The People’s Hospital of Guangxi Zhuang Autonomous Region, and Guangxi Academy of Medical Sciences, Nanning, Guangxi, People’s Republic of ChinaCorrespondence: Jing-Bin Huang; Yun-Tian Tang, Tel +86-771-2188205, Fax +86-771-2188214, Email hjb010222@163.com; liangdaxin2023@163.comAim: We aim to access the effect of pericardiectomy for constrictive pericarditis with or without cardiopulmonary bypass.Methods: This was a review of pericardiectomy for constrictive pericarditis.Results: Cardiopulmonary bypass is actually an important maneuver to attain complete relief of the constriction. The short additional time of cardiopulmonary bypass during the procedure has very little effect on the risk of morbidity of the main operation.Conclusion: Incomplete pericardiectomy perhaps was the cause of postoperative remnant constriction and high diastolic filling pressure leading to multiorgan failure. Complete pericardiectomy (removal of phrenic-to-phrenic and the postero-lateral and inferior wall pericardial thickening) using cardiopulmonary bypass should be the routine for total relief of the constriction of the heart.Keywords: pericardiectomy, constrictive pericarditis, cardiopulmonary bypass

2D semiconducting transition metal dichalcogenides (TMDs) are emerging as promising candidates in the pursuit of advancing semiconductor technology. One major challenge for integrating 2D TMD materials into practical applications is developing an epitaxial technique with robust reproducibility for single-oriented growth and thus single-crystal growth. Here, the growth of single-orientated MoS2 on c-plane sapphire with atomically thin Fe2O3 decoration layers under various growth conditions is demonstrated. The statistical data highlight robust reproducibility, achieving a single orientation ratio of up to 99%. Density functional theory calculations suggest that MoS2 favors a 0° alignment ((Formula presented.)) on the Fe2O3 (0001) surface. This preference ensures single-oriented growth, even on mirror-reflected exposed surfaces which typically lead to antiparallel domains. Subsequent optical and electrical analyses confirm the uniformity and undoped nature of MoS2 on Fe2O3-decorated sapphire, showing its quality is comparable to MoS2 grown on bared sapphires. The results underscore the potential of Fe2O3-decorated sapphire as an effective substrate for the consistent and high-quality epitaxial growth of 2D TMDs, illuminating the pathway to epitaxial control of 2D TMD orientation through strategic modulation of crystalline atomic surfaces. © 2023 The Authors. Advanced Functional Materials published by Wiley-VCH GmbH.

Multivariate matching algorithms "pair" similar study units in an observational study to remove potential bias and confounding effects caused by the absence of randomizations. In one-to-one multivariate matching algorithms, a large number of "pairs" to be matched could mean both the information from a large sample and a large number of tasks, and therefore, to best match the pairs, such a matching algorithm with efficiency and comparatively limited auxiliary matching knowledge provided through a "training" set of paired units by domain experts, is practically intriguing. We proposed a novel one-to-one matching algorithm based on a quadratic score function $S_{\beta}(x_i,x_j)= \beta^T (x_i-x_j)(x_i-x_j)^T \beta$. The weights $\beta$, which can be interpreted as a variable importance measure, are designed to minimize the score difference between paired training units while maximizing the score difference between unpaired training units. Further, in the typical but intricate case where the training set is much smaller than the unpaired set, we propose a \underline{s}emisupervised \underline{c}ompanion \underline{o}ne-\underline{t}o-\underline{o}ne \underline{m}atching \underline{a}lgorithm (SCOTOMA) that makes the best use of the unpaired units. The proposed weight estimator is proved to be consistent when the truth matching criterion is indeed the quadratic score function. When the model assumptions are violated, we demonstrate that the proposed algorithm still outperforms some popular competing matching algorithms through a series of simulations. We applied the proposed algorithm to a real-world study to investigate the effect of in-person schooling on community Covid-19 transmission rate for policy making purpose.

Interventions on model-internal states are fundamental operations in many areas of AI, including model editing, steering, robustness, and interpretability. To facilitate such research, we introduce $\textbf{pyvene}$, an open-source Python library that supports customizable interventions on a range of different PyTorch modules. $\textbf{pyvene}$ supports complex intervention schemes with an intuitive configuration format, and its interventions can be static or include trainable parameters. We show how $\textbf{pyvene}$ provides a unified and extensible framework for performing interventions on neural models and sharing the intervened upon models with others. We illustrate the power of the library via interpretability analyses using causal abstraction and knowledge localization. We publish our library through Python Package Index (PyPI) and provide code, documentation, and tutorials at https://github.com/stanfordnlp/pyvene., Comment: 8 pages, 3 figures

We present SimXR, a method for controlling a simulated avatar from information (headset pose and cameras) obtained from AR / VR headsets. Due to the challenging viewpoint of head-mounted cameras, the human body is often clipped out of view, making traditional image-based egocentric pose estimation challenging. On the other hand, headset poses provide valuable information about overall body motion, but lack fine-grained details about the hands and feet. To synergize headset poses with cameras, we control a humanoid to track headset movement while analyzing input images to decide body movement. When body parts are seen, the movements of hands and feet will be guided by the images; when unseen, the laws of physics guide the controller to generate plausible motion. We design an end-to-end method that does not rely on any intermediate representations and learns to directly map from images and headset poses to humanoid control signals. To train our method, we also propose a large-scale synthetic dataset created using camera configurations compatible with a commercially available VR headset (Quest 2) and show promising results on real-world captures. To demonstrate the applicability of our framework, we also test it on an AR headset with a forward-facing camera., Comment: CVPR 2024 Hightlight. Website: https://www.zhengyiluo.com/SimXR

Compared with well-developed construction of C-sp2-C-sp2 atropisomers, the synthesis of C-sp2-N atropisomers remains in its infancy, which is recognized as both appealing and challenging. Herein, we achieved the first organocatalyzed asymmetric synthesis of C-sp2-N atropisomers by formal C-sp2-O amination. With the aid of a suitable acid, 3-alkynyl-3-hydroxyisoindolinones reacted smoothly with 1-methylnaphthalen-2-ols to afford a wide range of atropisomers by selective formation of the C-sp2-N axis. Particularly, both the kinetic (Z)-products and the thermodynamic (E)-products could be selectively formed. Furthermore, the rarely used combination of two chiral Br & oslash;nsted acid catalysts achieved excellent enantiocontrol, which is intriguing and unusual in organocatalysis. Based on control experiments and DFT calculations, a cascade dehydration/addition/rearrangement process was proposed. More importantly, this work provided a new plat-form for direct atroposelective construction of the chiral C-sp2-N axis.

Individual neurons participate in the representation of multiple high-level concepts. To what extent can different interpretability methods successfully disentangle these roles? To help address this question, we introduce RAVEL (Resolving Attribute-Value Entanglements in Language Models), a dataset that enables tightly controlled, quantitative comparisons between a variety of existing interpretability methods. We use the resulting conceptual framework to define the new method of Multi-task Distributed Alignment Search (MDAS), which allows us to find distributed representations satisfying multiple causal criteria. With Llama2-7B as the target language model, MDAS achieves state-of-the-art results on RAVEL, demonstrating the importance of going beyond neuron-level analyses to identify features distributed across activations. We release our benchmark at https://github.com/explanare/ravel.

In robotic deformable object manipulation (DOM) applications, constraints arise commonly from environments and task-specific requirements. Enabling DOM with constraints is therefore crucial for its deployment in practice. However, dealing with constraints turns out to be challenging due to many inherent factors such as inaccessible deformation models of deformable objects (DOs) and varying environmental setups. This article presents a systematic manipulation framework for DOM subject to constraints by proposing a novel path set planning and tracking scheme. First, constrained DOM tasks are formulated into a versatile optimization formalism which enables dynamic constraint imposition. Because of the lack of the local optimization objective and high state dimensionality, the formulated problem is not analytically solvable. To address this, planning of the path set, which collects paths of DO feedback points, is proposed subsequently to offer feasible path and motion references for DO in constrained setups. Both theoretical analyses and computationally efficient algorithmic implementation of path set planning are discussed. Lastly, a control architecture combining path set tracking and constraint handling is designed for task execution. The effectiveness of our methods is validated in a variety of DOM tasks with constrained experimental settings., Comment: 20 pages, 25 figures, journal

We respond to the recent paper by Makelov et al. (2023), which reviews subspace interchange intervention methods like distributed alignment search (DAS; Geiger et al. 2023) and claims that these methods potentially cause "interpretability illusions". We first review Makelov et al. (2023)'s technical notion of what an "interpretability illusion" is, and then we show that even intuitive and desirable explanations can qualify as illusions in this sense. As a result, their method of discovering "illusions" can reject explanations they consider "non-illusory". We then argue that the illusions Makelov et al. (2023) see in practice are artifacts of their training and evaluation paradigms. We close by emphasizing that, though we disagree with their core characterization, Makelov et al. (2023)'s examples and discussion have undoubtedly pushed the field of interpretability forward., Comment: 20 pages, 14 figures

This paper addresses path set planning that yields important applications in robot manipulation and navigation such as path generation for deformable object keypoints and swarms. A path set refers to the collection of finite agent paths to represent the overall spatial path of a group of keypoints or a swarm, whose collective properties meet spatial and topological constraints. As opposed to planning a single path, simultaneously planning multiple paths with constraints poses nontrivial challenges in complex environments. This paper presents a systematic planning pipeline for homotopic path sets, a widely applicable path set class in robotics. An extended visibility check condition is first proposed to attain a sparse passage distribution amidst dense obstacles. Passage-aware optimal path planning compatible with sampling-based planners is then designed for single path planning with adjustable costs. Large accessible free space for path set accommodation can be achieved by the planned path while having a sufficiently short path length. After specifying the homotopic properties of path sets, path set generation based on deformable path transfer is proposed in an efficient centralized manner. The effectiveness of these methods is validated by extensive simulated and experimental results., Comment: 16 pages, 19 figures, 2 tables, conference

This thesis presents the design and implementation of a hardware language, Pyrope. It first describes Pyrope’s distinct language features with their design rationales and compares Pyrope with the mainstream language, SystemVerilog. It then shows the implementation of the Pyrope compilation flow that translates the language specification into low-level intermediate representation in a compiler framework, LiveHD. Several improvements to LiveHD as part of this work are also presented. Finally, the thesis shows the result of compiling an example design written in Pyrope.

In this work, silicon carbide (SiC) coatings were successfully grown by pulsed chemical vapor deposition (CVD). The precursors silicon tetrachloride (SiCl4) and ethylene (C2H4) were not supplied in a continuous flow but were pulsed alternately into the growth chamber with H-2 as a carrier and a purge gas. A typical pulsed CVD cycle was SiCl4 pulse-H-2 purge-C2H4 pulse-H-2 purge. This led to growth of superconformal SiC coatings, which could not be obtained under similar process conditions using a constant flow CVD process. We propose a two-step framework for SiC growth via pulsed CVD. During the SiCl4 pulse, a layer of Si is deposited. In the following C2H4 pulse, this Si layer is carburized, and SiC is formed. The high chlorine surface coverage after the SiCl4 pulse is believed to enable superconformal growth via a growth inhibition effect., Funding Agencies|SGL CARBON GmbH

Feima Wu, Guangchao Li, Huijuan Shen, Jing Huang, Zhi Liu, Yangmin Zhu, Qi Zhong, Ruiming Ou, Qing Zhang, Shuang Liu Department of Hematology, Guangdong Second Provincial General Hospital, Guangzhou, Guangdong, People’s Republic of ChinaCorrespondence: Shuang Liu, Department of Hematology, Guangdong Second Provincial General Hospital, XinGangZhong Road 466#, Haizhu Distict, Guangzhou, Guangdong Province, 510317, People’s Republic of China, Tel +86-20-89169214, Email liush@gd2h.org.cnBackground: Centromere protein I (CENPI) has been shown to affect the tumorigenesis of breast and colorectal cancers. However, its biological role and prognostic value in other kinds of cancer, especially adrenocortical carcinoma (ACC), remained to be further investigated.Methods: Various bioinformatics tools were adopted for exploring the significance of differential expression of CENPI in several malignant tumors from databases such as Depmap portal, GTEx, and TCGA. ACC was selected for further analyzed, and information such as clinicopathological features, the prognostic outcome of diverse subgroups, differentially expressed genes (DEGs), co-expression genes, as well as levels of tumor-infiltrating immune cells (TIIC), was extracted from multiple databases. To verify the possibility of CENPI as a therapeutic target in ACC, drug sensitivity assay and si-RNA mediate knockdown of CENPI were carried out.Results: The pan-cancer analyses showed that the CENPI mRNA expression levels differed significantly among most cancer types. Additionally, a high precision in cancer prediction and close relation with cancer survival indicated that CENPI could be a potential candidate biomarker to diagnose and predict cancer prognosis. In ACC, CENPI was closely related to multiple clinical characteristics, such as pathological stage and primary therapy outcome. High CENPI levels predicted poor overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS) of ACC pa

Jing Huang,1,* Kaiyu Wang,1,* Xizi Fu,1,* Manfang Zhu,2 Xiaohua Chen,1 Yan Gao,1 Pingchuan Ma,3 Xingmei Duan,2 Ke Men1 1State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China; 2Department of Pharmacy, Personalized Drug Therapy Key Laboratory of Sichuan Province Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610072, People’s Republic of China; 3State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases & Department of Head and Neck Oncology, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, 610041, People’s Republic of China*These authors contributed equally to this workCorrespondence: Ke Men, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China, Email mendingbob@hotmail.com Xingmei Duan, Department of Pharmacy, Personalized Drug Therapy Key Laboratory of Sichuan Province Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610072, People’s Republic of China, Email duanxingmei2003@163.comBackground: Messenger ribonucleic acid (mRNA)-based gene therapy has great potential in cancer treatment. However, the application of mRNA-based cancer treatment could be further developed. Elevated delivery ability and enhanced immune response are advantages for expanding the application of mRNA-based cancer therapy. It is crucial that the prepared carrier can cause an immune reaction based on the efficient delivery of mRNA.Methods: We reported DMP nanoparticle previously, which was obtained by the self-assembly of 1,2-dioleoyl-3-trimethyla

Cloth manipulation is common in domestic and service tasks, and most studies use fixed-base manipulators to manipulate objects whose sizes are relatively small with respect to the manipulators' workspace, such as towels, shirts, and rags. In contrast, manipulation of large-scale cloth, such as bed making and tablecloth spreading, poses additional challenges of reachability and manipulation control. To address them, this paper presents a novel framework to spread large-scale cloth, with a single-arm mobile manipulator that can solve the reachability issue, for an initial feasibility study. On the manipulation control side, without modeling highly deformable cloth, a vision-based manipulation control scheme is applied and based on an online-update Jacobian matrix mapping from selected feature points to the end-effector motion. To coordinate the control of the manipulator and mobile platform, Behavior Trees (BTs) are used because of their modularity. Finally, experiments are conducted, including validation of the model-free manipulation control for cloth spreading in different conditions and the large-scale cloth spreading framework. The experimental results demonstrate the large-scale cloth spreading task feasibility with a single-arm mobile manipulator and the model-free deformation controller. © 2023 IEEE.

Lead halide perovskites have been considered promising semicon-ducting materials for next-generation optoelectronic devices due to their solution processability and excellent optoelectronic proper-ties. Device performance of perovskite light-emitting diodes (PeLEDs) and perovskite solar cells (PSCs) has been rapidly devel-oped during the past decade. Very recently, organic molecules containing phosphine oxide groups have emerged as promising ad-ditives and passivators to improve the device performance and sta-bility of both PeLEDs and PSCs. In this perspective, we summarize recent progress in the development of new phosphine-oxide-based additives for PeLEDs and PSCs. The passivation mechanism, molecule design principle, and structure-property relationship of phosphine oxide molecules for PeLEDs and PSCs are systematically discussed and analyzed. Finally, we provide an outlook on the mo-lecular design of novel phosphine oxide compounds for efficient and stable PeLEDs and PSCs in the future., Funding Agencies|National Natural Science Foundation of China [22279059]; Fundamental Research Funds for the Central Universities [30921011106]; Nanjing University of Science and Technol- ogy; Research Innovation Program of Nanjing Overseas Returnees [AD411025]

Hole-transporting materials (HTMs) play critical roles in the device performance and stability of perovskite quantum dot light-emitting diodes (Pe-QLEDs). However, the development of small-molecule HTMs for achieving high-performance Pe-QLEDs has proven to be very challenging because of their low hole mobility and poor solvent resistance. Herein, we tailor-made a multifunc-tional small-molecule HTM, termed X10, with methoxy as the substituents, for application in Pe-QLEDs. X10 features high hole mobility, good film-forming ability, and strong solvent resistance ability as well as defect passivation effect. Subsequently, Pe-QLEDs employing X10 as HTM presented a promising external quantum efficiency (EQE) of 20.18%, which is 7-fold higher than that of the reference HTM-TCTA-based ones (EQE approximate to 2.88%). To the best of our knowledge, this is the first case in which a small-molecule HTM displays a high EQE over 20% in Pe-QLEDs. Our work provides important guidance for the rational design of multifunctional small-molecule HTMs for high-performance Pe-QLEDs., Funding Agencies|National Natural Science Foundation of China [22279059, 52131304]; Fundamental Research Funds for the Central Universities [30921011106]; National Key Research and Development Program of China [2022YFB3606502]; Iran National Science Foundation (INSF) [98016555]; University of Isfahan; Nanjing University of Science and Technology; Research Innovation Program of Nanjing Overseas Returnees [AD411025]; NJUST Large Instrument Equipment Open Fund, and Vacuum Interconnect Nano X Research Facility (NANO -X) of Suzhou Institute of Nano -Tech and Nano -Bionics, CAS; Swedish Research Council [2018-05973]; Swedish National Infrastructure for Computing (SNIC) [2022-5-103]; SMART-ER Seed Project

One of the great challenges in perovskite quantum dot light-emitting diodes (Pe-QLEDs) is the unbalanced charge injection that significantly hinders the device performance and stability. Herein, we tailor-made a high mobility electron-transporting material (ETM), named B2, to balance the carrier injection in blue Pe-QLEDs. B2 with a tailored asymmetric anthracenyl structure exhibits a promising electron mobility of 2.7 x 10(-4) cm(2)center dot V-1 center dot s(-1), which is almost 20 times higher than the commonly used ETM-TPBi (1.1 x 10(-5) cm(2)center dot V-1 center dot s(-1)). Subsequently, sky blue (490 nm) Pe-QLED with B2 as the ETM presented a remarkably high external quantum efficiency (EQE) of 13.17% and a low turn-on voltage of 2.2 V, which is much better than that of the TPBi-based device (EQE of 8.31% and Vturn-on of 3.2 V). In addition, B2 also demonstrated a universal application in green and deep blue Pe-QLEDs. This work provides an important guidance to rational design of high electron mobility ETMs for high-performance LEDs., Funding Agencies|National Natural Science Foundation of China [22279059, 52131304]; Fundamental Research Funds for the Central Universities [30921011106]; Nanjing University of Science and Technology (NJUST); Research Innovation Program of Nanjing Overseas Returnees [AD411025]; NJUST Large Instrument Equipment Open Fund, and Vacuum Interconnect Nano X Research Facility (NANO-X) of Suzhou Institute of Nano-Tech and Nano-Bionics, CAS; Swedish Research Council [2018-05973]; Swedish National Infrastructure for Computing - Swedish Research Council [2018-05973, SNIC 20225-103]; program SMART-ER Seed Project

Reducing noises and enhancing signal-to-noise ratios (SNRs) have become critical for designing third-generation gravitational-wave (GW) detectors with a GW strain of less than $10^{-23}$/$\rm \sqrt{Hz}$. In this paper, we propose a potential third-generation GW detector based on autocorrelative weak-value amplification (AWVA) for GW detection with a strain of $h_g =$ $4 \times 10^{-25}$/$\rm \sqrt{Hz}$. In our scheme, a GW event induces a phase difference $\Delta \phi$ by passing through an 11-bounce delay line, 10-km arm-length, zero-area Sagnac interferometer illuminated with a 1064-nm laser. Subsequently, $\Delta \phi$ is amplified as the parameter of post-selection by choosing the appropriate pre-selected state and coupling strength in AWVA. In particular, we theoretically investigate the AWVA measurements for GW detection within the frequency band of 200 Hz $\leq$ $f_g$ $\leq$ 800 Hz, considering Gaussian noises with negative-decibel SNRs. The peak response of the AWVA sensitivity $\kappa(f_g)$ occurs at frequency $f_{g, max}$ = 500 Hz, which falls within the frequency band of interest of the current third-generation GW detectors. Our simulation results indicate that AWVA can demonstrate a measurable sensitivity of $\Theta(f_g)$ within the frequency band of interest. Moreover, the robustness of WVA shows promising potential in mitigating the effects of Gaussian noises., Comment: 21 pages, 6 figures

Jing Huang,1,* Mengmeng Dai,1,* Mingxia He,1,* Weicheng Bu,1 Liwen Cao,1 Jing Jing,1 Run Cao,1 Hailong Zhang,1 Ke Men2 1Joint National Laboratory for Antibody Drug Engineering, The First Affiliated Hospital, Henan University, Kaifeng, Henan Province, 475004, People’s Republic of China; 2State Key Laboratory of Biotherapy and Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610044, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hailong Zhang, Joint National Laboratory for Antibody Drug Engineering, The First Affiliated Hospital, Henan University, Kaifeng, Henan Province, 475004, People’s Republic of China, Email hailong6891@163.com Ke Men, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan Province, 610044, People’s Republic of China, Email mendingbob@hotmail.comPurpose: The abnormal activation of NLRP3 inflammasome is related to the occurrence and development of ulcerative colitis (UC). However, the ideal drug and delivery system remain important factors limiting the targeting of NLRP3 inflammasome in UC therapy. Gene therapy by delivering siRNA is effective in treating various diseases. Therefore, delivering siNLRP3 using an ideal vector for UC treatment is necessary.Materials and Methods: Nanoparticles delivering siNLRP3 were developed based on cationic liposome (CLP/siNLRP3). Their ability to inhibit NLRP3 inflammasome activation was monitored using Western blot (WB) and Enzyme-linked Immunosorbent Assay (ELISA). The ASC oligomerization in LPS-primed peritoneal macrophages (PMs) was detected by WB and immunofluorescence. Moreover, we assessed the role of CLP/siNLRP3 on dextran sodium sulfate (DSS)-induced UC by examining NLRP3 levels, pro-inflammatory cytokines expression, and disease-associated index (DAI). Flow cytometry (FCM) was used to detect the contents of macrophages and T cell

Rong Liu,1,* Min Zhu,2,* Jiaojiao Chen,3 Junwei Gai,2 Jing Huang,2 Yingqun Zhou,1 Yakun Wan,2 Chuantao Tu4 1Department of Gastroenterology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, People’s Republic of China; 2Shanghai Novamab Biopharmaceuticals Co., Ltd, Shanghai, 201318, People’s Republic of China; 3Department of Gastroenterology, Shanghai Fourth People’s Hospital, Tongji University School of Medicine, Shanghai, 200434, People’s Republic of China; 4Department of Gastroenterology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chuantao Tu; Yakun Wan, Email tuchuantao@hotmail.com; ykwan@novamab.comBackground: No agents are currently available for the treatment or reversal of liver fibrosis. Novel antifibrotic therapies for chronic liver diseases are thus urgently needed. Connective tissue growth factor (CTGF) has been shown to contributes profoundly to liver fibrogenesis, which makes CTGF as a promising target for developing antifibrotic agents.Methods: In this study, we identified a novel nanobody (Nb) against human CTGF (anti-CTGF Nb) by phage display using an immunized camel, which showed high affinity and specificity in vitro. LX-2 cells, the immortalized human hepatic stellate cells, were induced by transforming growth factor beta1 (TGFβ 1) as an in vitro model of liver fibrosis to verify the antifibrotic activity of the anti-CTGF Nb.Results: Our data demonstrated that anti-CTGF Nb effectively alleviated TGFβ 1-induced LX-2 cell proliferation, activation, and migration, and promoted the apoptosis of activated LX-2 cells in response to TGFβ 1. Moreover, the anti-CTGF Nb remarkably reduced the levels of TGFβ 1, Smad2, and Smad3 expression in LX-2 stellate cells stimulated by TGFβ 1.Conclusion: Taken together, we successfully identified a novel Nb against huma

Image-based multi-person reconstruction in wide-field large scenes is critical for crowd analysis and security alert. However, existing methods cannot deal with large scenes containing hundreds of people, which encounter the challenges of large number of people, large variations in human scale, and complex spatial distribution. In this paper, we propose Crowd3D, the first framework to reconstruct the 3D poses, shapes and locations of hundreds of people with global consistency from a single large-scene image. The core of our approach is to convert the problem of complex crowd localization into pixel localization with the help of our newly defined concept, Human-scene Virtual Interaction Point (HVIP). To reconstruct the crowd with global consistency, we propose a progressive reconstruction network based on HVIP by pre-estimating a scene-level camera and a ground plane. To deal with a large number of persons and various human sizes, we also design an adaptive human-centric cropping scheme. Besides, we contribute a benchmark dataset, LargeCrowd, for crowd reconstruction in a large scene. Experimental results demonstrate the effectiveness of the proposed method. The code and datasets will be made public., Comment: Accepted by CVPR 2023

Jing Huang,1,2,* Hongjiang Pu,3,* Jintao He,4 Xiaohu Tang5 1The First Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, People’s Republic of China; 2Department of Integrated Traditional Chinese and Western Medicine, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Centre, Kunming, People’s Republic of China; 3Department of Oncology, Dazhou Central Hospital, Dazhou, Sichuan, People’s Republic of China; 4Kunming Medical University, Kunming, People’s Republic of China; 5Department of Rheumatology, The First Affiliated Hospital of Yunnan University of Traditional Chinese Medicine, Kunming, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xiaohu Tang, Department of Rheumatology, the First Affiliated Hospital of Yunnan University of Traditional Chinese Medicine, 120 Guanghua Street, Wuhua District, Kunming, 650032, People’s Republic of China, Tel/Fax +86-871-63639262, Email h.tang0718@163.comBackground: Most cancer-related deaths around the globe are caused by lung cancer. The present treatments for metastatic non-small cell lung cancer (mNSCLC) are cytotoxic chemotherapy (CCT), targeted therapy (TT) and immunotherapy, but the benefit of the same regime varies greatly. Hence, it is important to identify biomarkers to predict the efficacy of modalities. Previous literature suggested certain parameters might be predictive factors. Nevertheless, the utility of these parameters is limited due to the types of solid tumors.Purpose: The study aimed to examine whether the lung immune prognostic index (LIPI) was related to outcomes of CCT, immune checkpoint inhibitors (ICIs) and TT for mNSCLC patients.Materials and Methods: A retrospective cohort study between September 2012 and May 2020 was conducted on 350 Chinese mNSCLC patients, including 147 patients receiving ICIs, 103 TT, and 100 CCT. The data were examined to analyze the pro

Jing Huang, Zhijian Lin, Yu Wang, Xueli Ding, Bing Zhang School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, People’s Republic of ChinaCorrespondence: Bing Zhang, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, People’s Republic of China, Email zhangb@bucm.edu.cnBackground: Hyperuricemia (HUA) is a major public health issue with a high prevalence worldwide. Wuling San (WLS) is an effective treatment for HUA. However, the active compounds and the related mechanism are unclear. In this study, we aimed to explore the active compounds and the underlying pharmacological mechanisms of WLS against HUA.Methods: First, a network pharmacology approach was used to detect active compounds of WLS, and potential targets and signaling pathways involved in the treatment of HUA were predicted. Then, a molecular docking strategy was used to predict the affinity between active compounds and key targets. Finally, to verify the prediction, the HUA rat model was established.Results: 49 active compounds with 108 common targets were obtained. Besides, cerevisterol, luteolin, ergosterol peroxide, beta-sitosterol, and sitosterol were identified as key active compounds. In PPI analysis, TNF, IL6, CASP3, PPARG, STAT3, and other 12 core targets were obtained. GO enrichment analysis indicated that WLS was likely to interfere with oxidative stress in the treatment of HUA, and KEGG enrichment analysis indicated multiple inflammation-related signaling pathways possibly involved in the treatment of HUA by WLS, including TNF, and NOD-like receptor, HIF-1, PI3K-Akt, and IL-17 signaling pathways. The results of molecular docking indicated that the active compounds had good binding properties to their key targets. In the validation experiments, WLS significantly reduced the levels of serum uric acid (SUA) and serum malondialdehyde (MDA). Moreover, WLS not only significantly increased the levels of total antioxidant capacity (T-AOC) an

Automatic melody-to-lyric generation is a task in which song lyrics are generated to go with a given melody. It is of significant practical interest and more challenging than unconstrained lyric generation as the music imposes additional constraints onto the lyrics. The training data is limited as most songs are copyrighted, resulting in models that underfit the complicated cross-modal relationship between melody and lyrics. In this work, we propose a method for generating high-quality lyrics without training on any aligned melody-lyric data. Specifically, we design a hierarchical lyric generation framework that first generates a song outline and second the complete lyrics. The framework enables disentanglement of training (based purely on text) from inference (melody-guided text generation) to circumvent the shortage of parallel data. We leverage the segmentation and rhythm alignment between melody and lyrics to compile the given melody into decoding constraints as guidance during inference. The two-step hierarchical design also enables content control via the lyric outline, a much-desired feature for democratizing collaborative song creation. Experimental results show that our model can generate high-quality lyrics that are more on-topic, singable, intelligible, and coherent than strong baselines, for example SongMASS, a SOTA model trained on a parallel dataset, with a 24% relative overall quality improvement based on human ratings., Comment: ACL 2023. arXiv admin note: substantial text overlap with arXiv:2305.07760

Conventional task- and modality-specific artificial intelligence (AI) models are inflexible in real-world deployment and maintenance for biomedicine. At the same time, the growing availability of biomedical data, coupled with the advancements in modern multi-modal multi-task AI techniques, has paved the way for the emergence of generalist biomedical AI solutions. These solutions hold the potential to interpret different medical modalities and produce expressive outputs such as free-text reports or disease diagnosis. Here, we propose BiomedGPT, the first open-source and generalist visual language AI for diverse biomedical tasks. BiomedGPT achieved 16 state-of-the-art results across five clinically significant tasks on 26 datasets. Notably, it outperformed OpenAI's GPT-4 with vision (GPT-4V) in radiology human evaluation and surpassed Google's Med-PaLM M (12B) in breast cancer diagnosis and medical visual question answering. Moreover, BiomedGPT facilitates zero-shot transfer learning, greatly enhancing its utility as a biomedical assistant, similar to ChatGPT. Our method demonstrates effective training with diverse datasets can lead to more practical biomedical AI., Comment: under submission

Existing efforts on text synthesis for code-switching mostly require training on code-switched texts in the target language pairs, limiting the deployment of the models to cases lacking code-switched data. In this work, we study the problem of synthesizing code-switched texts for language pairs absent from the training data. We introduce GLOSS, a model built on top of a pre-trained multilingual machine translation model (PMMTM) with an additional code-switching module. This module, either an adapter or extra prefixes, learns code-switching patterns from code-switched data during training, while the primary component of GLOSS, i.e., the PMMTM, is frozen. The design of only adjusting the code-switching module prevents our model from overfitting to the constrained training data for code-switching. Hence, GLOSS exhibits the ability to generalize and synthesize code-switched texts across a broader spectrum of language pairs. Additionally, we develop a self-training algorithm on target language pairs further to enhance the reliability of GLOSS. Automatic evaluations on four language pairs show that GLOSS achieves at least 55% relative BLEU and METEOR scores improvements compared to strong baselines. Human evaluations on two language pairs further validate the success of GLOSS., Comment: Paper accepted by ACL2023 as a Finding paper

As deep learning gains popularity in modelling dynamical systems, we expose an underappreciated misunderstanding relevant to modelling dynamics on networks. Strongly influenced by graph neural networks, latent vertex embeddings are naturally adopted in many neural dynamical network models. However, we show that embeddings tend to induce a model that fits observations well but simultaneously has incorrect dynamical behaviours. Recognising that previous studies narrowly focus on short-term predictions during the transient phase of a flow, we propose three tests for correct long-term behaviour, and illustrate how an embedding-based dynamical model fails these tests, and analyse the causes, particularly through the lens of topological conjugacy. In doing so, we show that the difficulties can be avoided by not using embedding. We propose a simple embedding-free alternative based on parametrising two additive vector-field components. Through extensive experiments, we verify that the proposed model can reliably recover a broad class of dynamics on different network topologies from time series data., Comment: Accepted by IJCAI 2023

Automatic song writing is a topic of significant practical interest. However, its research is largely hindered by the lack of training data due to copyright concerns and challenged by its creative nature. Most noticeably, prior works often fall short of modeling the cross-modal correlation between melody and lyrics due to limited parallel data, hence generating lyrics that are less singable. Existing works also lack effective mechanisms for content control, a much desired feature for democratizing song creation for people with limited music background. In this work, we propose to generate pleasantly listenable lyrics without training on melody-lyric aligned data. Instead, we design a hierarchical lyric generation framework that disentangles training (based purely on text) from inference (melody-guided text generation). At inference time, we leverage the crucial alignments between melody and lyrics and compile the given melody into constraints to guide the generation process. Evaluation results show that our model can generate high-quality lyrics that are more singable, intelligible, coherent, and in rhyme than strong baselines including those supervised on parallel data., Comment: Presented at AAAI23 CreativeAI workshop (Non-Archival). A later version is accepted to ACL23

Strong cocomparability graphs are the reflexive graphs whose adjacency matrix can be rearranged by a simultaneous row and column permutation to avoid the submatrix with rows $01, 10$. Strong cocomparability graphs form a subclass of cocomparability graphs (i.e., the complements of comparability graphs) and can be recognized in polynomial time. In his seminal paper, Gallai characterized cocomparability graphs in terms of a forbidden structure called asteroids. Gallai proved that cocomparability graphs are precisely those reflexive graphs which do not contain asteroids. In this paper, we give a characterization of strong cocomparability graphs which is analogous to Gallai's characterization for cocomparability graphs. We prove that strong cocomparability graphs are precisely those reflexive graphs which do not contain weak edge-asteroids (a weaker version of asteroids). Our characterization also leads to a polynomial time recognition algorithm for strong cocomparability graphs., Comment: 9 pages

Recently, several new solar radio telescopes have been put into operation and provided spectral-imaging observations with much higher resolutions in decimeter (dm) and centimeter (cm) wavelengths. These telescopes include the Mingantu Spectral Radioheliograph (MUSER, at frequencies of 0.4 - 15 GHz), the Expanded Owens Valley Solar Array (EOVSA, at frequencies of 1 - 18 GHz), and the Siberian Radio Heliograph (SRH, at frequencies of 3 - 24 GHz). These observations offer unprecedented opportunities to study solar physics and space weather, especially to diagnose the coronal magnetic fields, reveal the basic nature of solar eruptions and the related non-thermal energy release, particle accelerations and propagation, and the related emission mechanisms. These results might be the important input to the space weather modeling for predicting the occurrence of disastrous powerful space weather events. In order to provide meaningful reference for other solar physicists and space weather researchers, this paper mainly focus on discussing the potential scientific problems of solar radio spectral-imaging observations in dm-cm wavelengths and its possible applications in the field of space weather. These results will provide a helpful reference for colleagues to make full use of the latest and future observation data obtained from the above solar radio telescopes., Comment: 10 pages, 7 figures, accepted by Advance in Space Research, 2022

Out-of-distribution (OOD) detection is an important topic for real-world machine learning systems, but settings with limited in-distribution samples have been underexplored. Such few-shot OOD settings are challenging, as models have scarce opportunities to learn the data distribution before being tasked with identifying OOD samples. Indeed, we demonstrate that recent state-of-the-art OOD methods fail to outperform simple baselines in the few-shot setting. We thus propose a hypernetwork framework called HyperMix, using Mixup on the generated classifier parameters, as well as a natural out-of-episode outlier exposure technique that does not require an additional outlier dataset. We conduct experiments on CIFAR-FS and MiniImageNet, significantly outperforming other OOD methods in the few-shot regime.

We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric video of skilled human activities (e.g., sports, music, dance, bike repair). 740 participants from 13 cities worldwide performed these activities in 123 different natural scene contexts, yielding long-form captures from 1 to 42 minutes each and 1,286 hours of video combined. The multimodal nature of the dataset is unprecedented: the video is accompanied by multichannel audio, eye gaze, 3D point clouds, camera poses, IMU, and multiple paired language descriptions -- including a novel "expert commentary" done by coaches and teachers and tailored to the skilled-activity domain. To push the frontier of first-person video understanding of skilled human activity, we also present a suite of benchmark tasks and their annotations, including fine-grained activity understanding, proficiency estimation, cross-view translation, and 3D hand/body pose. All resources are open sourced to fuel new research in the community. Project page: http://ego-exo4d-data.org, Comment: updated baseline results and dataset statistics to match the released v2 data; added table to appendix comparing stats of Ego-Exo4D alongside other datasets

Collection of annotated dialogs for training task-oriented dialog systems have been one of the key bottlenecks in improving current models. While dialog response generation has been widely studied on the agent side, it is not evident if similar generative models can be used to generate a large variety of, and often unexpected, user inputs that real dialog systems encounter in practice. Existing data augmentation techniques such as paraphrase generation do not take the dialog context into consideration. In this paper, we develop a novel dialog augmentation model that generates a user turn, conditioning on full dialog context. Additionally, with a new prompt design for language model, and output re-ranking, the dialogs generated from our model can be directly used to train downstream dialog systems. On common benchmark datasets MultiWoZ and SGD, we show that our dialog augmentation model generates high quality dialogs and improves dialog success rate by as much as $8\%$ over baseline., Comment: ECML-PKDD 2023 Workshop on Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications (COLLM)

We present a universal motion representation that encompasses a comprehensive range of motor skills for physics-based humanoid control. Due to the high dimensionality of humanoids and the inherent difficulties in reinforcement learning, prior methods have focused on learning skill embeddings for a narrow range of movement styles (e.g. locomotion, game characters) from specialized motion datasets. This limited scope hampers their applicability in complex tasks. We close this gap by significantly increasing the coverage of our motion representation space. To achieve this, we first learn a motion imitator that can imitate all of human motion from a large, unstructured motion dataset. We then create our motion representation by distilling skills directly from the imitator. This is achieved by using an encoder-decoder structure with a variational information bottleneck. Additionally, we jointly learn a prior conditioned on proprioception (humanoid's own pose and velocities) to improve model expressiveness and sampling efficiency for downstream tasks. By sampling from the prior, we can generate long, stable, and diverse human motions. Using this latent space for hierarchical RL, we show that our policies solve tasks using human-like behavior. We demonstrate the effectiveness of our motion representation by solving generative tasks (e.g. strike, terrain traversal) and motion tracking using VR controllers., Comment: ICLR 2024 Spotlight. Project page: https://zhengyiluo.github.io/PULSE

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features on simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein (GFP) chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations at only a modest increase in cost., Comment: 16 pages, 5 figures

Natural language is an appealing medium for explaining how large language models process and store information, but evaluating the faithfulness of such explanations is challenging. To help address this, we develop two modes of evaluation for natural language explanations that claim individual neurons represent a concept in a text input. In the observational mode, we evaluate claims that a neuron $a$ activates on all and only input strings that refer to a concept picked out by the proposed explanation $E$. In the intervention mode, we construe $E$ as a claim that the neuron $a$ is a causal mediator of the concept denoted by $E$. We apply our framework to the GPT-4-generated explanations of GPT-2 XL neurons of Bills et al. (2023) and show that even the most confident explanations have high error rates and little to no causal efficacy. We close the paper by critically assessing whether natural language is a good choice for explanations and whether neurons are the best level of analysis.

Recently, there has been significant progress in the development of large models. Following the success of ChatGPT, numerous language models have been introduced, demonstrating remarkable performance. Similar advancements have also been observed in image generation models, such as Google's Imagen model, OpenAI's DALL-E 2, and stable diffusion models, which have exhibited impressive capabilities in generating images. However, similar to large language models, these models still encounter unresolved challenges. Fortunately, the availability of open-source stable diffusion models and their underlying mathematical principles has enabled the academic community to extensively analyze the performance of current image generation models and make improvements based on this stable diffusion framework. This survey aims to examine the existing issues and the current solutions pertaining to image generation models.

Cloth manipulation is common in domestic and service tasks, and most studies use fixed-base manipulators to manipulate objects whose sizes are relatively small with respect to the manipulators' workspace, such as towels, shirts, and rags. In contrast, manipulation of large-scale cloth, such as bed making and tablecloth spreading, poses additional challenges of reachability and manipulation control. To address them, this paper presents a novel framework to spread large-scale cloth, with a single-arm mobile manipulator that can solve the reachability issue, for an initial feasibility study. On the manipulation control side, without modeling highly deformable cloth, a vision-based manipulation control scheme is applied and based on an online-update Jacobian matrix mapping from selected feature points to the end-effector motion. To coordinate the control of the manipulator and mobile platform, Behavior Trees (BTs) are used because of their modularity. Finally, experiments are conducted, including validation of the model-free manipulation control for cloth spreading in different conditions and the large-scale cloth spreading framework. The experimental results demonstrate the large-scale cloth spreading task feasibility with a single-arm mobile manipulator and the model-free deformation controller., Comment: 6 pages, 6 figures, submit to CASE2023