Interactive Graph Convolutional Filtering

Interactive Recommender Systems (IRS) have been increasingly used in various domains, including personalized article recommendation, social media, and online advertising. However, IRS faces significant challenges in providing accurate recommendations under limited observations, especially in the context of interactive collaborative filtering. These problems are exacerbated by the cold start problem and data sparsity problem. Existing Multi-Armed Bandit methods, despite their carefully designed exploration strategies, often struggle to provide satisfactory results in the early stages due to the lack of interaction data. Furthermore, these methods are computationally intractable when applied to non-linear models, limiting their applicability. To address these challenges, we propose a novel method, the Interactive Graph Convolutional Filtering model. Our proposed method extends interactive collaborative filtering into the graph model to enhance the performance of collaborative filtering between users and items. We incorporate variational inference techniques to overcome the computational hurdles posed by non-linear models. Furthermore, we employ Bayesian meta-learning methods to effectively address the cold-start problem and derive theoretical regret bounds for our proposed method, ensuring a robust performance guarantee. Extensive experimental results on three real-world datasets validate our method and demonstrate its superiority over existing baselines

Orientation-Shared Convolution Representation for CT Metal Artifact Learning

During X-ray computed tomography (CT) scanning, metallic implants carrying with patients often lead to adverse artifacts in the captured CT images and then impair the clinical treatment. Against this metal artifact reduction (MAR) task, the existing deep-learning-based methods have gained promising reconstruction performance. Nevertheless, there is still some room for further improvement of MAR performance and generalization ability, since some important prior knowledge underlying this specific task has not been fully exploited. Hereby, in this paper, we carefully analyze the characteristics of metal artifacts and propose an orientation-shared convolution representation strategy to adapt the physical prior structures of artifacts, i.e., rotationally symmetrical streaking patterns. The proposed method rationally adopts Fourier-series-expansion-based filter parametrization in artifact modeling, which can better separate artifacts from anatomical tissues and boost the model generalizability. Comprehensive experiments executed on synthesized and clinical datasets show the superiority of our method in detail preservation beyond the current representative MAR methods. Code will be available at \url{https://github.com/hongwang01/OSCNet

Graphene oxide mediated self-sacrificial synthesis of LaCO 3 OH-Ni(OH) 2 @graphene hierarchical composite for photocatalytic H 2 evolution and supercapacitor

Abstract(#br)Herein, we designed a one-step lattice-confined etching perovskite nanoparticles and self-sacrificing graphene oxide (GO) induced self-assembly strategy to synthesize novel 3D nest-like LaCO 3 OH and flower-like Ni(OH) 2 @graphene (RGO) hierarchical composite as a high performance photocatalyst and electrode material. The lattice-confined effect regulates the concentration and distribution of nickel ions migrating from perovskite to GO and thus constructs a homogeneous Ni(OH) 2 @RGO nanostructure. La(OH) 3 formed by residual lattice frames react with CO 3 2− from self-sacrificing of GO self-assembly to form nest-like LaCO 3 OH, which is embedded in the Ni(OH) 2 @RGO nanosheets. GO was utilized as both morphology control reagent and self-sacrificed carbon source. Benefit from the extremely rapid transfer of electron on the homogeneous Ni(OH) 2 @RGO nanosheets and high light-harvesting capacity of 3D nest and flower-like composite of LaCO 3 OH-Ni(OH) 2 @RGO, the properties of photocatalysis and supercapacitor are greatly enhanced. The H 2 production rate of 1.3807 mmol h −1 g −1 has been achieved which is 13 times higher than pure LaCO 3 OH. Electrochemical studies showed that a specific capacitance of 572.47 F g −1 was obtained at a scan rate of 10 mv/s with 80% capacitance retention even after 20,000 cycles. This composite synthesized from GO mediated etching solid phase perovskite surface ion migration under lattice-confined action provides a novel technical route for the direct self-assembly of solid nanoparticles and GO to synthesize new functional materials

Bibliometric and visual analysis of intraoperative hypotension from 2004 to 2022

BackgroundIntraoperative hypotension (IOH) is a common complication occurring in surgical practice. This study aims to comprehensively review the collaboration and impact of countries, institutions, authors, journals, keywords, and critical papers on intraoperative hypotension from the perspective of bibliometric, and to evaluate the evolution of knowledge structure clustering and identify research hotspots and emerging topics.MethodsArticles and reviews related to IOH published from 2004 to 2022 were retrieved from the Web of Science Core Collection. Bibliometric analyses and visualization were conducted on Excel, CiteSpace, VOSviewer, and Bibliometrix (R-Tool of R-Studio).ResultsA total of 1,784 articles and reviews were included from 2004 to 2022. The number of articles on IOH gradually increased in the past few years, and peaked in 2021. These publications were chiefly from 1,938 institutions in 40 countries, led by America and China in publications. Sessler Daniel I published the most papers and enjoyed the highest number of citations. Analysis of the journals with the most outputs showed that most journals concentrated on perioperative medicine and clinical anesthesiology. Delirium, acute kidney injury and vasoconstrictor agents are the current and developing research hotspots. The keywords “Acute kidney injury”, “postoperative complication”, “machine learning”, “risk factors” and “hemodynamic instability” may also become new trends and focuses of the near future research.ConclusionThis study uses bibliometrics and visualization methods to comprehensively review the research on intraoperative hypotension, which is helpful for scholars to better understand the dynamic evolution of IOH and provide directions for future research

Down-Regulation of Vascular Endothelial Growth Factor by Tissue Inhibitor of Metalloproteinase-2: Effect on in Vivo Mammary Tumor Growth and Angiogenesis

The tissue inhibitor of metalloproteinases-2 (TIMP-2) has at least two independent functions, i.e., regulation of matrix metalloproteinases and growth promoting activity. We investigated the effects of TIMP-2 overexpression, induced by retroviral mediated gene transfer, on the in vivo development of mammary tumors in syngeneic mice inoculated with EF43.fgf-4 cells. The EF43.fgf-4 cells established by stably infecting the normal mouse mammary EF43 cells with a retroviral expression vector for the fgf-4 oncogene, are highly tumorigenic and overproduce vascular endothelial growth factor (VEGF). Despite a promotion of the in vitro growth rate of EF43.fgf-4 cells overexpressing timp-2, the in vivo tumor growth was delayed. At day 17 post-cell injection, the volume of tumor derived from TIMP-2-overexpressing cells was reduced by 80% as compared with that obtained with control cells. Overexpression of TIMP-2 was associated with a down-regulation of VEGF expression in vitro and in vivo, a reduction of vessel size, density, and blood supply in the induced tumors. In addition, TIMP-2 completely inhibited the angiogenic activity of EF43.fgf-4 cell-conditioned medium in vitro using a rat aortic ring model. Our findings suggest that overexpression of TIMP-2 delays growth and angiogenesis of mammary carcinoma in vivo and that down-regulation of VEGF expression may play an important role in this TIMP-2-mediated antitumoral and antiangiogenic effects. Finally the in vivo delivery of TIMP-2, as assessed by i.v. injection of recombinant adenoviruses vectors, significantly reduced the growth of the EF43.fgf-4-induced tumors. This effect of TIMP-2 was shown to be equally comparable with that of angiostatin, a known potent inhibitor of angiogenesis

Proposal of a Solar-Coal Power Plant on Off-Design Operation

In a solar hybrid system, the intermittent solar radiation seriously effects the solar-toelectricity conversion. In this paper, the energy-level mechanism between the concentrated solar heat and the thermal cycle was discussed. The system analysis was taken on a 200 MW coal-fired power plant hybridized with solar heat at approximately 300 C, where the middle-temperature solar thermal energy was used to preheat the feed water before entering the boiler. With changing solar radiation in typical days, the solar share, the work output and the net solar-to-electricity efficiency of this solar hybrid system were evaluated. The net solar-to-electricity efficiency would be increased by 3-7% points compared to that in a solar-only power plant. An off-design parallel configuration of this hybrid system was proposed, achieving the net annual solar-to-electricity efficiency of 18%. It would expected to be an attractive approach to develop the scale-up mid-temperature solar thermal power technology in the short and midterm

Using Polystyrene-block-poly(acrylic acid)-coated Metal Nanoparticles as Monomers for Their Homo- and Co-polymerization

We present a template-free method for “polymerizing” nanoparticles into long chains without side branches. A variety of nanoparticles are encapsulated in polystyrene-block-poly(acrylic acid) (PSPAA) shells and then used as monomers for their self-assembly. Spherical PSPAA micelles upon acid treatment are known to assemble into cylindrical micelles. Exploiting this tendency, the core-shell nanoparticles are induced to aggregate, coalesce, and then transform into long chains. When more than one type of nanoparticles are used, random and block “copolymers” of nanoparticles can be obtained. Detailed procedures are reported for the PSPAA encapsulation of nanoparticles, homo- and co-polymerization of the core-shell nanoparticles, separation and purification of the resulting nanoparticle chains. Transformations of single-line chains into double- and triple-line chains are also presented. The synergy between the polymer shell and the embedded nanoparticles leads to an unusual chain-growth polymerization mode, giving long nanoparticle chains that are distinct from the products of the traditional step-growth aggregation process.NRF (Natl Research Foundation, S’pore)ASTAR (Agency for Sci., Tech. and Research, S’pore)MOE (Min. of Education, S’pore)Published versio