Magnetic Nanoparticle Supported Catalyst for Atom Transfer Radical Polymerization

Magnetic nanoparticles were used to support an ATRP catalyst for the polymerization of methyl methacrylate (MMA) for minimized adverse effect of catalyst support and easy catalyst separation. the nanoparticle-supported catalyst mediated a living/controlled radical polymerization of MMA as effectively as unsupported catalysts. with the addition of 22 mol % of CuBr 2, the polymer molecular weights were well-controlled with an initiator efficiency of 0.85 and polydispersity lower than 1.2. the supported catalysts could be easily separated/isolated using an external magnetic field and reused with slightly decreased activity but further improved control. the activity of the recycled catalyst was regenerated by copper metal or in-situ regeneration using reducing agents such as alkylamine or tin (II) compounds. Block copolymerization using PEG macroinitiator and chain extension were conducted to confirm the livingness. Block copolymers with controlled molecular weights and low polydispersity were obtained using the fresh or reused supported catalysts. It was concluded that nanosized supports had reduced adverse effects on catalysis. © 2006 American Chemical Society

Game equilibrium based control analysis on the sustainable market structure of rare metal mineral resources – evidence from China

In rare metal mineral market, as a complex system, multiple decision-making among the stakeholders increases the complexity in its market structure and dynamic process. The unreasonable compensation pricing mechanism for the development of the rare metal mineral resources in China requires to be studied. Drawing on the methods of game theory model and chaos control analysis, this paper builds theoretical model of rare metal mineral market structure, corporating related parameters of rare metal in the game theory model, to conduct the chaotic nature and path analysis, expecting to solve the bottleneck problems that restrict the rare metal pricing and resource security and enhance the waste valorization for the sustainability. Specificly, a Cournot-Nash Equilibrium model is built to analyze the Cournot-equilibrium point, the stability of the Cournot Equilibrium point, the chaotic status, as well as the pattern to chaos of the game system in the rare metal mineral resource market, numerical simulation is used to verify the model. The conclusions facilitate the formulation of industrial economic policies and further improvement of managerial strategies to solve market problems

Graph-Based Radio Resource Management for Vehicular Networks

This paper investigates the resource allocation problem in device-to-device (D2D)-based vehicular communications, based on slow fading statistics of channel state information (CSI), to alleviate signaling overhead for reporting rapidly varying accurate CSI of mobile links. We consider the case when each vehicle-to-infrastructure (V2I) link shares spectrum with multiple vehicle-to-vehicle (V2V) links. Leveraging the slow fading statistical CSI of mobile links, we maximize the sum V2I capacity while guaranteeing the reliability of all V2V links. We propose a graph-based algorithm that uses graph partitioning tools to divide highly interfering V2V links into different clusters before formulating the spectrum sharing problem as a weighted 3-dimensional matching problem, which is then solved through adapting a high-performance approximation algorithm.Comment: 7 pages; 5 figures; accepted by IEEE ICC 201

Clinicopathological and prognostic value of epithelial cell adhesion molecule in solid tumours: a meta-analysis

BackgroundMalignant tumors, mainly solid tumors, are a significant obstacle to the improvement of life expectancy at present. Epithelial cell adhesion molecule (EpCAM), a cancer stem cell biomarker, showed widespread expression in most normal epithelial cells and most cancers. Although the clinical significance of EpCAM in various malignant solid tumors has been studied extensively, the latent relationships between EpCAM and pathological and clinical characteristics in solid tumors and differences in the roles of EpCAM among tumors have not been clearly determined. The destination point of this study was to analyze the value of EpCAM in solid tumors in clinicopathological and prognostic dimension using a meta-analysis approach.Method and materialsA comprehensive and systematic search of the researches published up to March 7th, 2022, in PubMed, EMBASE, Web of Science, Cochrane library and PMC databases was performed. The relationships between EpCAM overexpression, clinicopathological characteristics, and survival outcomes were analyzed. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) and odds ratios (ORs) were estimated as indicators of the degree of correlation. This research was registered on PROSPERO (International prospective register of systematic reviews), ID: CRD42022315070.ResultsIn total, 57 articles and 14184 cases were included in this study. High EpCAM expression had a significant coherence with a poorer overall survival (OS) (HR: 1.30, 95% CI: 1.08–1.58, P < 0.01) and a worse disease-free survival (DFS) (HR: 1.58, 95% CI: 1.28–1.95, P < 0.01), especially of gastrointestinal tumors’ OS (HR: 1.50, 95% CI: 1.15–1.95, P < 0.01), and DFS (HR: 1.84, 95% CI: 1.52–2.33, P < 0.01). The DFS of head and neck tumors (HR: 2.33, 95% CI: 1.51–3.61, P < 0.01) was also associated with the overexpression of EpCAM. There were no positive relationships between the overexpression of EpCAM and sex (RR: 1.03, 95% CI: 0.99–1.07, P = 0.141), T classification (RR: 0.93, 95% CI: 0.82–1.06, P = 0.293), lymph node metastasis (RR: 0.85, 95% CI: 0.54–1.32, P = 0.461), distant metastasis (RR: 0.97, 95% CI: 0.84–1.10, P = 0.606), vascular infiltration (RR: 1.05, 95% CI: 0.85–1.29, P = 0.611), and TNM stage (RR: 0.93, 95% CI: 0.83–1.04, P = 0.187). However, the overexpression of EpCAM exhibited a significant association with the histological grades (RR: 0.88, 95% CI: 0.80–0.97, P < 0.01).ConclusionBased on pooled HRs, the positive expression of EpCAM was totally correlated to a worse OS and DFS in solid tumors. The expression of EpCAM was related to a worse OS in gastrointestinal tumors and a worse DFS in gastrointestinal tumors and head and neck tumors. Moreover, EpCAM expression was correlated with the histological grade. The results presented pointed out that EpCAM could serve as a prognostic biomarker for gastrointestinal and head and neck tumors.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, identifier CRD42022315070

Second generation Dirac cones and inversion symmetry breaking induced gaps in graphene/hexagonal boron nitride

Graphene/h-BN has emerged as a model van der Waals heterostructure, and the band structure engineering by the superlattice potential has led to various novel quantum phenomena including the self-similar Hofstadter butterfly states. Although newly generated second generation Dirac cones (SDCs) are believed to be crucial for understanding such intriguing phenomena, so far fundamental knowledge of SDCs in such heterostructure, e.g. locations and dispersion of SDCs, the effect of inversion symmetry breaking on the gap opening, still remains highly debated due to the lack of direct experimental results. Here we report first direct experimental results on the dispersion of SDCs in 0$^\circ$ aligned graphene/h-BN heterostructure using angle-resolved photoemission spectroscopy. Our data reveal unambiguously SDCs at the corners of the superlattice Brillouin zone, and at only one of the two superlattice valleys. Moreover, gaps of $\approx$ 100 meV and $\approx$ 160 meV are observed at the SDCs and the original graphene Dirac cone respectively. Our work highlights the important role of a strong inversion symmetry breaking perturbation potential in the physics of graphene/h-BN, and fills critical knowledge gaps in the band structure engineering of Dirac fermions by a superlattice potential.Comment: Nature Physics 2016, In press, Supplementary Information include

Revisiting Multimodal Representation in Contrastive Learning: From Patch and Token Embeddings to Finite Discrete Tokens

Contrastive learning-based vision-language pre-training approaches, such as CLIP, have demonstrated great success in many vision-language tasks. These methods achieve cross-modal alignment by encoding a matched image-text pair with similar feature embeddings, which are generated by aggregating information from visual patches and language tokens. However, direct aligning cross-modal information using such representations is challenging, as visual patches and text tokens differ in semantic levels and granularities. To alleviate this issue, we propose a Finite Discrete Tokens (FDT) based multimodal representation. FDT is a set of learnable tokens representing certain visual-semantic concepts. Both images and texts are embedded using shared FDT by first grounding multimodal inputs to FDT space and then aggregating the activated FDT representations. The matched visual and semantic concepts are enforced to be represented by the same set of discrete tokens by a sparse activation constraint. As a result, the granularity gap between the two modalities is reduced. Through both quantitative and qualitative analyses, we demonstrate that using FDT representations in CLIP-style models improves cross-modal alignment and performance in visual recognition and vision-language downstream tasks. Furthermore, we show that our method can learn more comprehensive representations, and the learned FDT capture meaningful cross-modal correspondence, ranging from objects to actions and attributes.Comment: Accepted to CVPR 202

Redox Regulation in Cancer Stem Cells

Reactive oxygen species (ROS) and ROS-dependent (redox regulation) signaling pathways and transcriptional activities are thought to be critical in stem cell self-renewal and differentiation during growth and organogenesis. Aberrant ROS burst and dysregulation of those ROS-dependent cellular processes are strongly associated with human diseases including many cancers. ROS levels are elevated in cancer cells partially due to their higher metabolism rate. In the past 15 years, the concept of cancer stem cells (CSCs) has been gaining ground as the subpopulation of cancer cells with stem cell-like properties and characteristics have been identified in various cancers. CSCs possess low levels of ROS and are responsible for cancer recurrence after chemotherapy or radiotherapy. Unfortunately, how CSCs control ROS production and scavenging and how ROS-dependent signaling pathways contribute to CSCs function remain poorly understood. This review focuses on the role of redox balance, especially in ROS-dependent cellular processes in cancer stem cells (CSCs). We updated recent advances in our understanding of ROS generation and elimination in CSCs and their effects on CSC self-renewal and differentiation through modulating signaling pathways and transcriptional activities. The review concludes that targeting CSCs by manipulating ROS metabolism/dependent pathways may be an effective approach for improving cancer treatment