Mechanics and Viscoelastic Properties of Graphene Reinforced Polymer Nanocomposites Through Coarse-Grained Molecular Dynamics Simulations

Graphene possesses remarkable electrical, thermal, and mechanical properties and has been utilized in many advanced applications in either independent form or nanocomposites as nanofillers. In particular, multilayer graphene nanosheets (MLGSs) have been applied as nano-reinforcements in different types of matrices. One of the most promising material systems is graphene reinforced polymer nanocomposites. Many experimental, computational, and analytical studies have been conducted to investigate the physical and functional properties of such nanocomposites. It has been shown that molecular-, nano-, and micro-structures all play significant roles in nanocomposites’ final properties.The thesis focuses on the mechanics and viscoelastic properties of graphene reinforced polymer nanocomposites depending on two specific structural features that have been largely overlooked in recent studies. The first is the wrinkles formed in MLGSs within polymer nanocomposites. The second is the polymer chain structure, particularly the side group’s size in polymer chains. Building upon previously developed coarse-grained models of both MLGSs and polymethyl methacrylate coupled with molecular dynamics (MD) simulations, I have systematically investigated nanocomposites depending on wrinkle configurations of MLGSs and polymer chain structures. I find that both factors significantly impact the mechanical and viscoelastic properties of nanocomposites through non-equilibrium MD simulations by applying different mechanical tests on representative nanocomposite systems. Interlayer sliding within MLGSs happen in specific wrinkle configurations of MLGSs under global shear deformation, which significantly influences the viscoelastic properties of nanocomposites. In addition, the size of the side group in polymer chains affects the interfacial interactions between polymer chains and graphene sheets. With these interactions being altered, the reinforcement effect of MLGSs and the dynamic moduli of the nanocomposite systems are subsequently changed. As a result, both wrinkles formed in MLGSs and side group size of polymer chains have a non-trivial effect on the mechanics and viscoelastic properties of studied nanocomposites. The studies presented in the thesis illustrate the critical dependence of graphene reinforced polymer nanocomposites on graphene configuration and polymer chain structures and provide essential insights into experimental characterization and optimized design of such composites for structural applications

Recent advances in nanoparticle formulation of oleanolic acid

Oleanolic acid (OA) is a natural triterpenoid possessing anti-inflammatory, antitumor, antiviral, hepatoprotective and antihyperlipidemic effects. Research on the pharmacological activities and clinical applications of OA has made significant progress in the past decade, particularly in the areas such as isolation and purification, chemical modifications, pharmacological research, toxicity studies and clinical use of OA. However, due to its poor aqueous solubility, instability and low bioavailability, OA's clinical applications are still rather limited. Recently, nanoparticulate drug delivery as the biological dimension of nanotechnology has been developed, which may help generate useful formulations of OA for clinical applications. Nanoparticulate drug delivery system enhances the dissolution rate and bioavailability of OA, providing a feasible formulation method for clinical applications

Vid2Act: Activate Offline Videos for Visual RL

Pretraining RL models on offline video datasets is a promising way to improve their training efficiency in online tasks, but challenging due to the inherent mismatch in tasks, dynamics, and behaviors across domains. A recent model, APV, sidesteps the accompanied action records in offline datasets and instead focuses on pretraining a task-irrelevant, action-free world model within the source domains. We present Vid2Act, a model-based RL method that learns to transfer valuable action-conditioned dynamics and potentially useful action demonstrations from offline to online settings. The main idea is to use the world models not only as simulators for behavior learning but also as tools to measure the domain relevance for both dynamics representation transfer and policy transfer. Specifically, we train the world models to generate a set of time-varying task similarities using a domain-selective knowledge distillation loss. These similarities serve two purposes: (i) adaptively transferring the most useful source knowledge to facilitate dynamics learning, and (ii) learning to replay the most relevant source actions to guide the target policy. We demonstrate the advantages of Vid2Act over the action-free visual RL pretraining method in both Meta-World and DeepMind Control Suite

Berberine hydrochloride: anticancer activity and nanoparticulate delivery system

Wen Tan, Yingbo Li, Meiwan Chen, Yitao WangState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao Special Administrative Region, ChinaBackground: Berberine hydrochloride is a conventional component in Chinese medicine, and is characterized by a diversity of pharmacological effects. However, due to its hydrophobic properties, along with poor stability and bioavailability, the application of berberine hydrochloride was hampered for a long time. In recent years, the pharmaceutical preparation of berberine hydrochloride has improved to achieve good prospects for clinical application, especially for novel nanoparticulate delivery systems. Moreover, anticancer activity and novel mechanisms have been explored, the chance of regulating glucose and lipid metabolism in cancer cells showing more potential than ever. Therefore, it is expected that appropriate pharmaceutical procedures could be applied to the enormous potential for anticancer efficacy, to give some new insights into anticancer drug preparation in Chinese medicine.Methods and results: We accessed conventional databases, such as PubMed, Scope, and Web of Science, using “berberine hydrochloride”, “anti-cancer mechanism”, and “nanoparticulate delivery system” as search words, then summarized the progress in research, illustrating the need to explore reprogramming of cancer cell metabolism using nanoparticulate drug delivery systems.Conclusion: With increasing research on regulation of cancer cell metabolism by berberine hydrochloride and troubleshooting of issues concerning nanoparticulate delivery preparation, berberine hydrochloride is likely to become a natural component of the nanoparticulate delivery systems used for cancer therapy. Meanwhile, the known mechanisms of berberine hydrochloride, such as decreased multidrug resistance and enhanced sensitivity of chemotherapeutic drugs, along with improvement in patient quality of life, could also provide new insights into cancer cell metabolism and nanoparticulate delivery preparation.Keywords: berberine hydrochloride, anticancer mechanisms, nanoparticulate drug progres

Provision and Usage of Medical Services by Community Pharmacy: A Comparative Study of New York, Macao and Zhuhai (China)

Community pharmacies around the world are redefining their roles by experimenting to provide medical services directly to consumers. The aim of this study was to investigate the medical services provided by community pharmacies and consumers’ usage of these medical services. This study was carried out through semi-structured interviews with both community pharmacists and their consumers in New York, Macao and Zhuhai. Community pharmacists reported information about provision of medical services, and consumers provided information about their usage of medical services at community pharmacies accordingly. Through analysis of interview materials it showed that community pharmacies mainly provided free medical examination, reference books and booklet of drug information. Some community pharmacies provided health care lecture and founded own website for medicine information. But touch-screen computer querying system and telephone health care service had not been provided. Additionally the consumers’ usage of medical services at community pharmacy is obviously lower than provision by community pharmacy. The provision level of medical services by community pharmacy was relatively low and the types of medical services were relatively narrow. There was an obvious gap between provision of medical services by community pharmacies and usage of such services by consumers. The position of community pharmacy in national health system and capability of community pharmacy have impact on the medical services of community pharmacies.Key words: Community pharmacy; Medical services; Comparative study; New York; Macao; Zhuhai (China

Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction

We study the problem of learning goal-conditioned policies in Minecraft, a popular, widely accessible yet challenging open-ended environment for developing human-level multi-task agents. We first identify two main challenges of learning such policies: 1) the indistinguishability of tasks from the state distribution, due to the vast scene diversity, and 2) the non-stationary nature of environment dynamics caused by partial observability. To tackle the first challenge, we propose Goal-Sensitive Backbone (GSB) for the policy to encourage the emergence of goal-relevant visual state representations. To tackle the second challenge, the policy is further fueled by an adaptive horizon prediction module that helps alleviate the learning uncertainty brought by the non-stationary dynamics. Experiments on 20 Minecraft tasks show that our method significantly outperforms the best baseline so far; in many of them, we double the performance. Our ablation and exploratory studies then explain how our approach beat the counterparts and also unveil the surprising bonus of zero-shot generalization to new scenes (biomes). We hope our agent could help shed some light on learning goal-conditioned, multi-task agents in challenging, open-ended environments like Minecraft.Comment: This paper is accepted by CVPR202

N,N′-{[Bis(trifluoro­meth­yl)methyl­ene]di-p-phenyl­ene}diphthalimide

The molecule of the title compound, C31H16F6N2O4, consists of two phthalimide units linked by a [bis­(trifluoro­meth­yl)methyl­ene]di-p-phenyl­ene bridge, with the two halves of the mol­ecule related to each other by a twofold rotation axis. The dihedral angle between the planes of the two central benzene rings is 70.5 (3)°. The terminal isoindole groups are approximately planar, with a maximum r.m.s. deviation of 0.006 Å from the mean plane, and they form dihedral angles of 46.03 (3)° to the attached benzene rings. Inter­molecular C—H⋯O hydrogen bonds link neighboring mol­ecules into chains along the c axis

DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task

The recent progress of large language models (LLMs), including ChatGPT and GPT-4, in comprehending and responding to human instructions has been remarkable. Nevertheless, these models typically perform better in English and have not been explicitly trained for the medical domain, resulting in suboptimal precision in diagnoses, drug recommendations, and other medical advice. Additionally, training and deploying a dialogue model is still believed to be impossible for hospitals, hindering the promotion of LLMs. To tackle these challenges, we have collected databases of medical dialogues in Chinese with ChatGPT's help and adopted several techniques to train an easy-deploy LLM. Remarkably, we were able to fine-tune the ChatGLM-6B on a single A100 80G in 13 hours, which means having a healthcare-purpose LLM can be very affordable. DoctorGLM is currently an early-stage engineering attempt and contain various mistakes. We are sharing it with the broader community to invite feedback and suggestions to improve its healthcare-focused capabilities: https://github.com/xionghonglin/DoctorGLM