262 research outputs found

    Few-shot Domain Adaptation for IMU Denoising

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    Different application scenarios will cause IMU to exhibit different error characteristics which will cause trouble to robot application. However, most data processing methods need to be designed for specific scenario. To solve this problem, we propose a few-shot domain adaptation method. In this work, a domain adaptation framework is considered for denoising the IMU, a reconstitution loss is designed to improve domain adaptability. In addition, in order to further improve the adaptability in the case of limited data, a few-shot training strategy is adopted. In the experiment, we quantify our method on two datasets (EuRoC and TUM-VI) and two real robots (car and quadruped robot) with three different precision IMUs. According to the experimental results, the adaptability of our framework is verified by t-SNE. In orientation results, our proposed method shows the great denoising performance

    Glucose Sensing Optionally in Optical and Optoelectrical Modes Based on Au-TiO2 Schottky Nanojunctions

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    Abstract: In recent years, metallic nanostructures have been extensively researched in the field of plasmonic for optical and optoelectronic applications such as biochemical sensing. However, an additional optoelectronic converter or spectrometer is usually required for the sensing application. Herein, the orderly-patterned Au-TiO2 Schottky junction with an Al film that we coupled, which simultaneously works as an optical reflector and conducting layer, can achieve optical sensing of glucose by exciting surface plasmon resonance associated with the environment, and meanwhile can realize glucose detection with direct electrical-signal readout by collecting the photogenerated carriers inside the Au nanostructures and TiO2 film. When used in optical mode, the designed sensor shows a sensing sensitivity of up to 1200.0 nmRIU-1 in numerical calculation, and the measured value is 346.1 nmRIU-1. When used in optoelectrical mode, the glucose sensor under one-sun illumination obtains a sensitivity of 70.0 µAM-1cm-2 in the concentration range of 0–10 mM, with a detection limit of 0.05 µM (Signal/Noise=3). Simulation and experimental results demonstrated that the Al-film-coupled Au-TiO2 Schottky nanojunction can monitor glucose concentration optionally in optical and optoelectrical modes, which presents an alternative route to the miniaturized, portable, and multi-functioned sensors

    Approximate surface-current distributions of rectangular dipole antennas

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    Abstract An approximate surface-current distribution of the rectangular dipole antennas, composed of two linear-currents along the antenna edges and a uniform surface-current within the antenna bodies, is proposed. It presents some new insights to planar dipole antennas, and could also be used for fast, explicit and Ultra-wideband predictions of their radiation patterns. The averaged errors between the calculated results based on the proposed distributions and the fullwave results are respectively 0.075 dB on the H-plane and 2.95º on the E-plane. From the explicit results, some design considerations for stable radiation patterns are presented

    A Tightly Coupled Bi-Level Coordination Framework for CAVs at Road Intersections

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    Since the traffic administration at road intersections determines the capacity bottleneck of modern transportation systems, intelligent cooperative coordination for connected autonomous vehicles (CAVs) has shown to be an effective solution. In this paper, we try to formulate a Bi-Level CAV intersection coordination framework, where coordinators from High and Low levels are tightly coupled. In the High-Level coordinator where vehicles from multiple roads are involved, we take various metrics including throughput, safety, fairness and comfort into consideration. Motivated by the time consuming space-time resource allocation framework in [1], we try to give a low complexity solution by transforming the complicated original problem into a sequential linear programming one. Based on the "feasible tunnels" (FT) generated from the High-Level coordinator, we then propose a rapid gradient-based trajectory optimization strategy in the Low-Level planner, to effectively avoid collisions beyond High-level considerations, such as the pedestrian or bicycles. Simulation results and laboratory experiments show that our proposed method outperforms existing strategies. Moreover, the most impressive advantage is that the proposed strategy can plan vehicle trajectory in milliseconds, which is promising in realworld deployments. A detailed description include the coordination framework and experiment demo could be found at the supplement materials, or online at https://youtu.be/MuhjhKfNIOg

    On Sparse Modern Hopfield Model

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    We introduce the sparse modern Hopfield model as a sparse extension of the modern Hopfield model. Like its dense counterpart, the sparse modern Hopfield model equips a memory-retrieval dynamics whose one-step approximation corresponds to the sparse attention mechanism. Theoretically, our key contribution is a principled derivation of a closed-form sparse Hopfield energy using the convex conjugate of the sparse entropic regularizer. Building upon this, we derive the sparse memory retrieval dynamics from the sparse energy function and show its one-step approximation is equivalent to the sparse-structured attention. Importantly, we provide a sparsity-dependent memory retrieval error bound which is provably tighter than its dense analog. The conditions for the benefits of sparsity to arise are therefore identified and discussed. In addition, we show that the sparse modern Hopfield model maintains the robust theoretical properties of its dense counterpart, including rapid fixed point convergence and exponential memory capacity. Empirically, we use both synthetic and real-world datasets to demonstrate that the sparse Hopfield model outperforms its dense counterpart in many situations.Comment: 37 pages, accepted to NeurIPS 202

    Sex differences in patients with COVID-19: a retrospective cohort study and meta-analysis

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    BACKGROUND: Accumulated evidence revealed that male was much more likely to higher severity and fatality by SARS-CoV-2 infection than female patients, but few studies and meta-analyses have evaluated the sex differences of the infection and progression of COVID-19 patients. AIM: We aimed to compare the sex differences of the epidemiological and clinical characteristics in COVID-19 patients; and to perform a meta-analysis evaluating the severe rate, fatality rate, and the sex differences of the infection and disease progression in COVID-19 patients. METHODS: We analyzed clinical data of patients in Changchun Infectious Hospital and Center, Changchun, Northeast China; and searched PubMed, Embase, Web of Science, and Cochrane Library without any language restrictions for published articles that reported the data of sex-disaggregated, number of severe, and death patients on the confirmed diagnosis of adult COVID-19 patients. RESULTS: The pooled severe rate and fatality rate of COVID-19 were 22.7% and 10.7%. Male incidence in the retrospective study was 58.1%, and the pooled incidence in male was 54.7%. CONCLUSION: The pooled severe rate in male and female of COVID-19 was 28.2% and 18.8%, the risky of severe and death was about 1.6folds higher in male compared with female, especially for older patients (> 50 y)

    MRI-based radiomics features uncover the micro-change of dorsal root ganglia lesion for patients with post-herpetic neuralgia

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    ObjectiveTo create and authenticate MRI-based radiomic signatures to identify dorsal root ganglia (DRG) lesions in post-herpetic neuralgia (PHN) patients generalizable and interpretable.MethodThis prospective diagnostic study was conducted between January 2021 and February 2022. Lesioned DRG in patients with PHN and normal DRG in age-, sex-, height-, and weight-matched healthy controls were selected for assessment and divided into two groups (8:2) randomly: training and testing sets. The least absolute shrinkage and selection operator algorithm was employed to generate feature signatures and construct a model, followed by the assessment of model efficacy using the area under the curve (AUC) of the receiver operating characteristic (ROC), as well as sensitivity and specificity metrics.ResultsThe present investigation involved 30 patients diagnosed with postherpetic neuralgia (PHN), consisting of 18 males and 12 females (mean age 60.70 ± 10.18 years), as well as 30 healthy controls, comprising 18 males and 12 females (mean age 58.13 ± 10.54 years). A total of 98 DRG were randomly divided into two groups (8:2), namely a training set (n = 78) and a testing set (n = 20). Five radiomic features were chosen to construct the models. In the training dataset, the area under the curve (AUC) was 0.847, while the sensitivity and specificity were 71.79 and 97.44%, respectively. In the test dataset, the AUC was 0.87, and the sensitivity and specificity were 80.00 and 100.00%, respectively.ConclusionAn MRI-based radiomic signatures model has the capacity to uncover the micro-change of damaged DRG in individuals afflicted with postherpetic neuralgia

    Identification of hub genes associated with hepatitis B virus-related hepatocellular cancer using weighted gene co-expression network analysis and protein-protein interaction network analysis

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    Background. Chronic hepatitis B virus (HBV) infection is the main pathogen of hepatocellular carcinoma. However, the mechanisms of HBV-related hepatocellular carcinoma (HCC) progression are practically unknown. Materials and Methods. The results of RNA-sequence and clinical data for GSE121248 and GSE17548 were accessed from the Gene Expression Omnibus data library. We screened Sangerbox 3.0 for differentially expressed genes (DEGs). The weighted gene co-expression network analysis (WGCNA) was employed to select core modules and hub genes, and protein-protein interaction network module analysis also played a significant part in it. Validation was performed using RNA-sequence data of cancer and normal tissues of HBV-related HCC patients in the cancer genome atlas-liver hepatocellular cancer database (TCGA-LIHC). Results. 787 DEGs were identified from GSE121248 and 772 DEGs were identified from GSE17548. WGCNA analysis indicated that black modules (99 genes) and grey modules (105 genes) were significantly associated with HBV-related HCC. Gene ontology analysis found that there is a direct correlation between DEGs and the regulation of cell movement and adhesion; the internal components and external packaging structure of plasma membrane; signaling receptor binding, calcium ion binding, etc. Kyoto Encyclopedia of Genes and Genomes pathway analysis found out the association between cytokine receptors, cytokine-cytokine receptor interactions, and viral protein interactions with cytokines were important and HBV-related HCC. Finally, we further validated 6 key genes including C7, EGR1, EGR3, FOS, FOSB, and prostaglandin-endoperoxide synthase 2 by using the TCGALIHC. Conclusions. We identified 6 hub genes as candidate biomarkers for HBV-related HCC. These hub genes may act as an essential part of HBV-related HCC progression

    Rodent models of postherpetic neuralgia: How far have we reached?

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    BackgroundInduced by varicella zoster virus (VZV), postherpetic neuralgia (PHN) is one of the common complications of herpes zoster (HZ) with refractory pain. Animal models play pivotal roles in disclosing the pain mechanisms and developing effective treatments. However, only a few rodent models focus on the VZV-associated pain and PHN.ObjectiveTo summarize the establishment and characteristics of popular PHN rodent models, thus offer bases for the selection and improvement of PHN models.DesignIn this review, we retrospect two promising PHN rodent models, VZV-induced PHN model and HSV1-induced PHN model in terms of pain-related evaluations, their contributions to PHN pathogenesis and pharmacology.ResultsSignificant difference of two PHN models is the probability of virus proliferation; 2) Most commonly used pain evaluation of PHN model is mechanical allodynia, but pain-induced anxiety and other behaviours are worth noting; 3) From current PHN models, pain mechanisms involve changes in virus gene and host gene expression, neuroimmune–glia interactions and ion channels; 4) antiviral drugs and classical analgesics serve more on the acute stage of herpetic pain.ConclusionsDifferent PHN models assessed by various pain evaluations combine to fulfil more comprehensive understanding of PHN

    Interictal Abnormalities of Neuromagnetic Gamma Oscillations in Migraine Following Negative Emotional Stimulation

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    Here, we aimed to investigate brain activity in migraineurs in response to emotional stimulation. Magnetoencephalography (MEG) was used to examine 20 patients with episodic migraine (EM group), 15 patients with chronic migraine (CM group), and 35 healthy participants (control group). Neuromagnetic brain activity was elicited by emotional stimulation using photographs of facial expressions. We analyzed the latency and amplitude of M100 and M170 components and used Morlet wavelet and beamformers to analyze the spectral and spatial signatures of MEG signals in gamma band (30–100 Hz). We found that the timing and frequency of MEG activity differed across the three groups in response negative emotional stimuli. First, peak M170 amplitude was significantly lower in the CM group than in the control group. Second, compared with the control group, the average spectral power was significantly lower in the EM group and CM group at M100 and M170. Third, the average spectral powers of the M100 and M170 in the CM group were negatively correlated with either HAM-D scores or migraine attack frequency. No significant differences across groups was found for positive or neutral emotional stimuli. Furthermore, after negative emotional stimuli, the MEG source analysis demonstrated that the CM group showed a significantly higher percentage of amygdala activation than the control group for M100 and M170. Thus, during headache free phases, migraineurs have abnormal brain activity in the gamma band in response to negative emotional stimuli.Trial Registration:ChiCTR-RNC-17012599. Registered 7 September, 2017
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