221 research outputs found

    Curve Your Attention: Mixed-Curvature Transformers for Graph Representation Learning

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    Real-world graphs naturally exhibit hierarchical or cyclical structures that are unfit for the typical Euclidean space. While there exist graph neural networks that leverage hyperbolic or spherical spaces to learn representations that embed such structures more accurately, these methods are confined under the message-passing paradigm, making the models vulnerable against side-effects such as oversmoothing and oversquashing. More recent work have proposed global attention-based graph Transformers that can easily model long-range interactions, but their extensions towards non-Euclidean geometry are yet unexplored. To bridge this gap, we propose Fully Product-Stereographic Transformer, a generalization of Transformers towards operating entirely on the product of constant curvature spaces. When combined with tokenized graph Transformers, our model can learn the curvature appropriate for the input graph in an end-to-end fashion, without the need of additional tuning on different curvature initializations. We also provide a kernelized approach to non-Euclidean attention, which enables our model to run in time and memory cost linear to the number of nodes and edges while respecting the underlying geometry. Experiments on graph reconstruction and node classification demonstrate the benefits of generalizing Transformers to the non-Euclidean domain.Comment: 19 pages, 7 figure

    Deep Collective Knowledge Distillation

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    Many existing studies on knowledge distillation have focused on methods in which a student model mimics a teacher model well. Simply imitating the teacher's knowledge, however, is not sufficient for the student to surpass that of the teacher. We explore a method to harness the knowledge of other students to complement the knowledge of the teacher. We propose deep collective knowledge distillation for model compression, called DCKD, which is a method for training student models with rich information to acquire knowledge from not only their teacher model but also other student models. The knowledge collected from several student models consists of a wealth of information about the correlation between classes. Our DCKD considers how to increase the correlation knowledge of classes during training. Our novel method enables us to create better performing student models for collecting knowledge. This simple yet powerful method achieves state-of-the-art performances in many experiments. For example, for ImageNet, ResNet18 trained with DCKD achieves 72.27\%, which outperforms the pretrained ResNet18 by 2.52\%. For CIFAR-100, the student model of ShuffleNetV1 with DCKD achieves 6.55\% higher top-1 accuracy than the pretrained ShuffleNetV1

    Effect of rapid influenza diagnostic tests on patient management in an emergency department

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    Objective We evaluated the effect of rapid influenza diagnostic tests (RIDTs) on patient management in an emergency department for 3 years after 2009, and also identified factors associated with the choice of treatment for patients with influenza-like illnesses. Methods The study period consisted of three influenza epidemic seasons. Patients older than 15 years who underwent RIDTs in the emergency department and were then discharged without admission were included. Results A total of 453 patients were enrolled, 114 of whom had positive RIDT results and 339 had negative results. Antiviral medication was prescribed to 103 patients (90.4%) who had positive RIDT results, while 1 patient (0.3%) who tested negative was treated with antivirals (P<0.001). Conservative care was administered to 11 RIDT-positive patients (9.6%) and 244 RIDT-negative patients (72.0%) (P<0.001). Symptom onset in less than 48 hours, being older than 65 years, and the presence of comorbidities were not associated with the administration of antiviral therapy. Conclusion RIDT results had a critical effect on physician decision-making regarding antiviral treatment for patients with influenza-like illnesses in the emergency department. However, symptom onset in less than 48 hours, old age, and comorbidities, which are all indications for antiviral therapy, were not found to influence the administration of antiviral treatment

    Effect of transported hospital resources on neurologic outcome after out-of-hospital cardiac arrest

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    Objective. Appropriate regional transport protocol for out-of-hospital cardiac arrest (OHCA) patients is important for achieving favorable outcomes in a certain community. This study aimed to investigate the effect of transported hospital resources on the neurologic outcome after OHCA. Methods. We categorized cardiac receiving centers (CRC) in our community into two levels (primary [P-CRC] and definite CRC [D-CRC]) according to the hospital resources that were identified by the Hospital Assessment Survey in 2015. OHCA patients with presumed cardiac etiology resuscitated by emergency medical service providers between 2012 and 2014, were enrolled in the study. The main exposure was the level of CRC. The primary endpoint was discharge with good neurologic outcomes. We compared outcomes between CRCs after adjusting for potential confounders. Results. Among the 9,912 patients, 5,876 were transported to P-CRC and 4,036 to D-CRC from 2012 to 2014. Patients admitted to D-CRC showed better neurologic outcome than those admitted to P-CRC (6.2% vs 1.5%, p<0.001). With regard to patients who survived to admission, the neurologic outcome of patients in D-CRC was better than those in P-CRC (11.3% vs 3.3%, p<0.001). In the multivariable logistic model, the adjusted odds ratio for all OHCA patients was 2.10 (95% confidence interval, 1.51–2.95). Conclusion. Transportation of OHCA patients to the D-CRC resulted in significantly good neurologic outcome than those transported to P-CRC. Further research is needed to establish a regional OHCA transport protocol

    Cellular direct conversion by cell penetrable OCT4-30Kc19 protein and BMP4 growth factor

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    Background : The number of patients suffering from osteoporosis is increasing as the elderly population increases. The demand for investigating bone regeneration strategies naturally arises. One of the approaches to induce bone regeneration is somatic cell transdifferentiation. Among the transcriptional regulators for transdifferentiation, octamer-binding transcription factor 4 (OCT4) is famous for its role in the regulation of pluripotency of stem cells. Bone morphogenetic protein 4 (BMP4) is another factor that is known to have a significant role in osteogenic differentiation. Previous studies have achieved transdifferentiation of cells into osteoblasts using viral and plasmid deliveries of these factors. Although these methods are efficient, viral and plasmid transfection have safety issues such as permanent gene incorporations and bacterial DNA insertions. Herein, we developed a cell penetrating protein-based strategy to induce transdifferentiation of endothelial cells into osteoblasts via nuclear delivery of OCT4 recombinant protein combined with the BMP4 treatment. For the nuclear delivery of OCT4 protein, we fused the protein with 30Kc19, a cell-penetrating and protein stabilizing protein derived from a silkworm hemolymph of Bombyx mori with low cytotoxic properties. This study proposes a promising cell-based therapy without any safety issues that existing transdifferentiation approaches had. Methods : OCT4-30Kc19 protein with high penetrating activities and stability was synthesized for a protein-based osteogenic transdifferentiation system. Cells were treated with OCT4-30Kc19 and BMP4 to evaluate their cellular penetrating activity, cytotoxicity, osteogenic and angiogenic potentials in vitro. The osteogenic potential of 3D cell spheroids was also analyzed. In addition, in vivo cell delivery into subcutaneous tissue and cranial defect model was performed. Results : OCT4-30Kc19 protein was produced in a soluble and stable form. OCT4-30Kc19 efficiently penetrated cells and were localized in intracellular compartments and the nucleus. Cells delivered with OCT4-30Kc19 protein combined with BMP4 showed increased osteogenesis, both in 2D and 3D culture, and showed increased angiogenesis capacity in vitro. Results from in vivo subcutaneous tissue delivery of cell-seeded scaffolds confirmed enhanced osteogenic properties of transdifferentiated HUVECs via treatment with both OCT4-30Kc19 and BMP4. In addition, in vivo mouse cranial defect experiment demonstrated successful bone regeneration of HUVECs pretreated with both OCT4-30Kc19 and BMP4. Conclusions : Using a protein-based transdifferentiation method allows an alternative approach without utilizing any genetic modification strategies, thus providing a possibility for safer use of cell-based therapies in clinical applications.This work was fnancially supported by the Ministry of Science and ICT (NRF2021R1A2C2008821). The Institute of Engineering Research at Seoul National University provided research facilities for this work

    Evaluating indoor positioning systems in a shopping mall : the lessons learned from the IPIN 2018 competition

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    The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

    Heterogeneous stacking of nanodot monolayers by dry pick-and-place transfer and its applications in quantum dot light-emitting diodes

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    Layered assembly structures composed of nanomaterials, such as nanocrystals, have attracted considerable attention as promising candidates for new functional devices whose optical, electromagnetic and electronic behaviours are determined by the spatial arrangement of component elements. However, difficulties in handling each constituent layer in a materialspecific manner limit the 3D integration of disparate nanomaterials into the appropriate heterogeneous electronics. Here we report a pick-and-place transfer method that enables the transfer of large-area nanodot assemblies. This solvent-free transfer utilizes a lifting layer and allows for the reliable transfer of a quantum dot (QD) monolayer, enabling layer-by-layer design. With the controlled multistacking of different bandgap QD layers, we are able to probe the interlayer energy transfer among different QD monolayers. By controlling the emission spectrum through such designed monolayer stacking, we have achieved white emission with stable optoelectronic properties, the closest to pure white among the QD lightemitting diodes reported so far. (c) 2013 Macmillan Publishers Limited. All rights reserved.402
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