MR image reconstruction from under-sampled measurements using local and global sparse representations

This work presented a new model by enforcing both local and global sparsity, which captures both the patch-level and global sparse structures of the anatomical images. Using a model split approach, the image reconstruction quality can be iteratively further improved. Our simulation results demonstrate that, the proposed method outperform those existing methods using only the patch-level or global sparse structure

Analysis on Alighting and Boarding Movement Laws in Subway Using Modified Social Force Model

This paper presents a multi-agent simulator based on social force model to simulate each passenger’s boarding and alighting behavior both in a train and on a platform seamlessly. Passengers can be divided into three types: to board, alight and stay in train. They have different individual attributes and follow different walking rules. Due to the characteristics of subway environment and passengers' behavior in boarding and alighting, some adjustment and improvement were made to the basic social force model: (1) In some cases during the process of boarding and alighting, the driving force targeting to destination needs to be doubled, and the repulsion force between two agents needs to be reduced. (2) Passengers who stay in the train show quite different movement from the usual pedestrian. They usually want to remain still, unless they are in front of the door. To describe their behaviors, we introduced a tangent detour force. The scope of the interaction between agents is extended and some passengers out of the visual field also should be counted. (3) Divide the repulsive force between an agent and an obstacle into the frontal force and convex corner force. These two forces have different spheres of influence and calculation methods. The agents could exhibit reasonable intelligence and diversity during alighting and boarding

A New Acquisition Algorithm with Elimination Side Peak for All BOC Signals

A new inhibition side peak acquisition (ISPA) algorithm is proposed for binary offset carrier (BOC) modulated signals, which will be utilized in global navigation satellite systems (GNSS). We eliminate all side peaks of the BOC correlation function (CF) by structuring special sequences composed of PRN code and cycle rectangular sequences. The new algorithm can be applied to both generic sine- and cosine-phased BOC signals, as well as to all modulation orders. Theoretical and simulation results demonstrate that the new algorithm can completely eliminate the ambiguity threat in the acquisition process, and it can adapt to lower SNR. In addition, this algorithm is better than the traditional algorithms in acquisition performance and inhibition side peak ability

A New Acquisition Algorithm with Elimination Side Peak for All BOC Signals

A new inhibition side peak acquisition (ISPA) algorithm is proposed for binary offset carrier (BOC) modulated signals, which will be utilized in global navigation satellite systems (GNSS). We eliminate all side peaks of the BOC correlation function (CF) by structuring special sequences composed of PRN code and cycle rectangular sequences. The new algorithm can be applied to both generic sine-and cosine-phased BOC signals, as well as to all modulation orders. Theoretical and simulation results demonstrate that the new algorithm can completely eliminate the ambiguity threat in the acquisition process, and it can adapt to lower SNR. In addition, this algorithm is better than the traditional algorithms in acquisition performance and inhibition side peak ability

Gutzwiller Hybrid Quantum-Classical Computing Approach for Correlated Materials

Rapid progress in noisy intermediate-scale quantum (NISQ) computing technology has led to the development of novel resource-efficient hybrid quantum-classical algorithms, such as the variational quantum eigensolver (VQE), that can address open challenges in quantum chemistry, physics and material science. Proof-of-principle quantum chemistry simulations for small molecules have been demonstrated on NISQ devices. While several approaches have been theoretically proposed for correlated materials, NISQ simulations of interacting periodic models on current quantum devices have not yet been demonstrated. Here, we develop a hybrid quantum-classical simulation framework for correlated electron systems based on the Gutzwiller variational embedding approach. We implement this framework on Rigetti quantum processing units (QPUs) and apply it to the periodic Anderson model, which describes a correlated heavy electron band hybridizing with non-interacting conduction electrons. Our simulation results quantitatively reproduce the known ground state quantum phase diagram including metallic, Kondo and Mott insulating phases. This is the first fully self-consistent hybrid quantum-classical simulation of an infinite correlated lattice model executed on QPUs, demonstrating that the Gutzwiller hybrid quantum-classical embedding framework is a powerful approach to simulate correlated materials on NISQ hardware. This benchmark study also puts forth a concrete pathway towards practical quantum advantage on NISQ devices.Comment: 14 pages, 5 figure

Deep Domain Adaptation for Pavement Crack Detection

Deep learning-based pavement cracks detection methods often require large-scale labels with detailed crack location information to learn accurate predictions. In practice, however, crack locations are very difficult to be manually annotated due to various visual patterns of pavement crack. In this paper, we propose a Deep Domain Adaptation-based Crack Detection Network (DDACDN), which learns to take advantage of the source domain knowledge to predict the multi-category crack location information in the target domain, where only image-level labels are available. Specifically, DDACDN first extracts crack features from both the source and target domain by a two-branch weights-shared backbone network. And in an effort to achieve the cross-domain adaptation, an intermediate domain is constructed by aggregating the three-scale features from the feature space of each domain to adapt the crack features from the source domain to the target domain. Finally, the network involves the knowledge of both domains and is trained to recognize and localize pavement cracks. To facilitate accurate training and validation for domain adaptation, we use two challenging pavement crack datasets CQU-BPDD and RDD2020. Furthermore, we construct a new large-scale Bituminous Pavement Multi-label Disease Dataset named CQU-BPMDD, which contains 38994 high-resolution pavement disease images to further evaluate the robustness of our model. Extensive experiments demonstrate that DDACDN outperforms state-of-the-art pavement crack detection methods in predicting the crack location on the target domain.Comment: 12 pages, 10 figure

Risk Factors for Ventilator Dependency Following Coronary Artery Bypass Grafting

Background: Ventilator dependency following coronary artery bypass grafting (CABG) is often associated with significant morbidity and mortality. However, few reports have focused on the independent risk factors for ventilator dependency following CABG. This study aimed to evaluate the independent risk factors for ventilator dependency following coronary artery bypass grafting (CABG). Methods: The relevant pre-, intra- and post-operative data of patients without a history of chronic obstructive pulmonary disease undergoing isolated CABG from January 2003 to December 2008 in our center were retrospectively analyzed. Elapsed time between CABG and extubation of more than 48 hours was defined as postoperative ventilator dependency (PVD). Results: The incidence of PVD was 13.8% (81/588). The in-hospital mortality in the PVD group was significantly higher than that in the non-PVD group (8.6% versus 2.4%, p=0.0092). Besides the length of ICU and hospital stay, PVD correlated with negative respiratory outcomes. The independent risk factors for PVD were preoperative congestive heart failure (OR=2.456, 95%CI 1.426-6.879), preoperative hypoalbuminemia (OR=1.353, 95%CI 1.125-3.232), preoperative arterial oxygen partial pressure (PO2) (OR=0.462, 95%CI 0.235-0.783) and postoperative anaemia (OR=1.541, 95%CI 1.231-3.783). Conclusions: Preoperative congestive heart failure, preoperative hypoalbuminemia, low preoperative PO2 and postoperative anaemia were identified as four independent risk factors for ventilator dependency following CABG

Integrated analysis of the functions and clinical implications of exosome circRNAs in colorectal cancer

BackgroundExosome circRNAs (Exo-circRNAs) regulate cancer progression and intercellular crosstalk in the tumor microenvironment. However, their biological functions and potential clinical importance in colorectal cancer (CRC) remain unknown.MethodsWe used exoRBase 2.0 data to identify significant differentially expressed Exo-circRNAs (Exo-DEcircRNAs) in CRC patients and healthy individuals. The least absolute shrinkage and selector operation algorithm, support vector machine-recursive feature elimination, and multivariate Cox regression analyses were used to select candidate Exo-circRNAs and constructed a diagnostic model. Quantitative reverse transcription-polymerase chain reaction analysis was performed to confirm the expression of Exo-circRNAs in the serum samples of patients. Furthermore, we constructed an exosome circRNA-miRNA-mRNA network for CRC. Upregulated target mRNAs in the exosome competing endogenous RNA (Exo-ceRNA) network were used for functional and pathway enrichment analyses. We identified 22 immune cell types in CRC patients using CIBERSORT. Correlation analysis revealed the relationship between Exo-ceRNA networks and immune-infiltrating cells. The relationship between target mRNAs and immunotherapeutic response was also explored. Finally, using the Kaplan–Meier survival curve, a prognostic upregulated target mRNA was screened. We constructed a survival-related Exo-ceRNA subnetwork and explored the correlation between the Exo-ceRNA subnetwork and immune-infiltrating cells.ResultsThe constructed diagnostic model had a high area under the curve (AUC) value in both the training and validation sets (AUC = 0.744 and AUC = 0.741, respectively). qRT-PCR confirmed that the Exo-circRNAs were differentially expressed in CRC serum samples. We constructed Exo-ceRNA networks based on the interactions among seven upregulated Exo-DEcircRNAs, eight differentially expressed miRNAs, and twenty-two differentially expressed mRNAs in CRC. Functional enrichment analysis revealed that the upregulated target mRNAs were significantly enriched in cytoskeletal motor activity and the PI3K-Akt signaling pathway. Co-expression analysis showed a significant correlation between the Exo-ceRNA networks and immune cells. The significant correlation was observed between target mRNAs and the immunotherapeutic response. Additionally, based on the prognostic upregulated target gene (RGS2), we constructed a survival-related Exo-ceRNA subnetwork (Exosome hsa_circ_0050334-hsa_miR_182_5p-RGS2). CIBERSORT results revealed that the Exo-ceRNA subnetwork correlated with M2 macrophages (P = 4.6e-07, R = 0.31).ConclusionsOur study identified an Exo-diagnostic model, established Exo-ceRNA networks, and explored the correlation between Exo-ceRNA networks and immune cell infiltration in CRC. These findings elucidated the biological functions of Exo-circRNAs and their potential clinical implications