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  • Near Future Perspective of ESBL-Producing Klebsiella pneumoniae Strains Using Mathematical Modeling
  • Abstract While antibiotic resistance is becoming increasingly serious today, there is almost no doubt that more challenging times await us in the future. Resistant microorganisms have increased in the past decades leading to limited treatment options, along with higher morbidity and mortality. Klebsiella pneumoniae is one of the significant microorganisms causing major public health problems by acquiring resistance to antibiotics and acting as an opportunistic pathogen of healthcare-associated infections. The production of extended spectrum beta-lactamases (ESBL) is one of the resistance mechanisms of K. pneumoniae against antibiotics. In this study, the future clinical situation of ESBL-producing K. pneumoniae was investigated in…
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  • Estimation of Aleatory Randomness by Sa(T1)-Based Intensity Measures in Fragility Analysis of Reinforced Concrete Frame Structures
  • Abstract Based on the multiple stripes analysis method, an investigation of the estimation of aleatory randomness by Sa(T1)-based intensity measures (IMs) in the fragility analysis is carried out for two typical low- and medium-rise reinforced concrete (RC) frame structures with 4 and 8 stories, respectively. The sensitivity of the aleatory randomness estimated in fragility curves to various Sa(T1)-based IMs is analyzed at three damage limit states, i.e., immediate occupancy, life safety, and collapse prevention. In addition, the effect of characterization methods of bidirectional ground motion intensity on the record-to-record variability is investigated. It is found that the damage limit state of…
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  • Ripple+: An Improved Scheme of Ripple Consensus Protocol in Deployability, Liveness and Timing Assumption
  • Abstract Ripple acts as a real-time settlement and payment system to connect banks and payment providers. As the consensus support of the Ripple network to ensure network consistency, Ripple consensus protocol has been widely concerned in recent years. Compared with those Byzantine fault tolerant protocols, Ripple has a significant difference that the system can reach an agreement under decentralized trust model. However, Ripple has many problems both in theory and practice, which are mentioned in the previous researches. This paper presents Ripple+, an improved scheme of Ripple consensus protocol, which improves Ripple from three aspects: (1) Ripple+ employs a specific trust…
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  • Traffic Accident Detection Based on Deformable Frustum Proposal and Adaptive Space Segmentation
  • Abstract Road accident detection plays an important role in abnormal scene reconstruction for Intelligent Transportation Systems and abnormal events warning for autonomous driving. This paper presents a novel 3D object detector and adaptive space partitioning algorithm to infer traffic accidents quantitatively. Using 2D region proposals in an RGB image, this method generates deformable frustums based on point cloud for each 2D region proposal and then frustum-wisely extracts features based on the farthest point sampling network (FPS-Net) and feature extraction network (FE-Net). Subsequently, the encoder-decoder network (ED-Net) implements 3D-oriented bounding box (OBB) regression. Meanwhile, the adaptive least square regression (ALSR) method is…
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  • Sustainable Investment Forecasting of Power Grids Based on the Deep Restricted Boltzmann Machine Optimized by the Lion Algorithm
  • Abstract This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine (DRBM) optimized by the Lion algorithm (LA). Firstly, two factors including transmission and distribution price reform (TDPR) and 5G station construction were comprehensively incorporated into the consideration of influencing factors, and the fuzzy threshold method was used to screen out critical influencing factors. Then, the LA was used to optimize the parameters of the DRBM model to improve the model's prediction accuracy, and the model was trained with the selected influencing factors and investment. Finally, the LA-DRBM model was used to predict the…
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  • Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study
  • Abstract Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms were applied in VS imaging. In this paper, we proposed an adjustable generalized coherence factor (aGCF) for the synthetic aperture sequential beamforming (SASB) of VS imaging to improve image quality. The value of aGCF is adjusted by a sequence intensity factor (SIF) that is defined as the ratio between the effective low resolution scan lines (LRLs) intensity and total…
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  • Analysis of Water Pollution Causes and Control Countermeasures in Liaohe Estuary via Support Vector Machine Particle Swarm Optimization under Deep Learning
  • Abstract This study explores the loss or degradation of the ecosystem and its service function in the Liaohe estuary coastal zone due to the deterioration of water quality. A prediction system based on support vector machine (SVM)-particle swarm optimization (PSO) (SVM-PSO) algorithm is proposed under the background of deep learning. SVM-PSO algorithm is employed to analyze the pollution status of the Liaohe estuary, so is the difference in water pollution of different sea consuming types. Based on the analysis results for causes of pollution, the control countermeasures of water pollution in Liaohe estuary are put forward. The results suggest that the…
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  • Optimization of the Drag Forces of Shell Janus Micromotor: A Study Based on Hydrodynamical Analysis and Numerical Simulation
  • Abstract Micromotors are widely used in cell operation, drug delivery and environmental decontamination due to their small size, low energy consumption and large propelling power. Compared to traditional Janus micromotor, the shell Janus micromotor has better motion performance. However, the structural optimization of its motion performance is still unclear. The main factor restricting the motion performance of shell Janus micromotors is the drag forces. In the current work, theoretical analysis and numerical simulation were applied to analyze the drag forces of shell Janus micromotors. This study aims to design the optimum structure of shell Janus micromotors with minimum drag forces and…
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