Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH) is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional), 10 CEC2005 benchmark functions (30-dimensional), and a real-world problem (multilevel image segmentation problems). Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests

Composition, antibiotic resistance, and virulence analysis of microbiota in dormitory drain pipes

IntroductionDormitory washbasins can breed microorganisms that produce odorous gases, polluting the indoor environment.MethodsWe utilized metagenome sequencing to analyze the microbiota of 40 samples from the drain pipes of dormitory washbasins. Our study aimed to investigate the microbial community structure, antibiotic resistance genes, and virulence factors, and to identify potential influencing factors such as gender, hometown, frequency of hand sanitizer usage, and number of dormitory residents.ResultsThe analysis revealed 12 phyla and 147 genera, with Proteobacteria and Actinobacteria being the dominant phyla, and Mycobacterium and Nakamurella being the dominant genera. We found that the factors influencing the microbial community structure of the dormitory washbasin drain pipe are complex. The investigated factors have a slight influence on the drain pipe microbial community, with gender exerting a discernible influence. The annotation results revealed the presence of various virulence factors, pathogenic toxins and antibiotic resistance genes, including 246 different toxin types and 30 different types of antibiotic resistance genes. In contrast to the observed differences in microbial composition among samples, the distribution of resistance genes shows relatively small changes among samples. Antibiotics should be a contributing factor in the overall increase of antibiotic resistance genes in drain pipes.DiscussionOverall, our study provides important insights into the community structure and function of microorganisms in dormitory drainage systems, and can guide efforts to prevent and control microbial pollution

CMRxRecon: An open cardiac MRI dataset for the competition of accelerated image reconstruction

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a limitation of CMR is its slow imaging speed, which causes patient discomfort and introduces artifacts in the images. There has been growing interest in deep learning-based CMR imaging algorithms that can reconstruct high-quality images from highly under-sampled k-space data. However, the development of deep learning methods requires large training datasets, which have not been publicly available for CMR. To address this gap, we released a dataset that includes multi-contrast, multi-view, multi-slice and multi-coil CMR imaging data from 300 subjects. Imaging studies include cardiac cine and mapping sequences. Manual segmentations of the myocardium and chambers of all the subjects are also provided within the dataset. Scripts of state-of-the-art reconstruction algorithms were also provided as a point of reference. Our aim is to facilitate the advancement of state-of-the-art CMR image reconstruction by introducing standardized evaluation criteria and making the dataset freely accessible to the research community. Researchers can access the dataset at https://www.synapse.org/#!Synapse:syn51471091/wiki/.Comment: 14 pages, 8 figure

Electronic Ratchet Nanodiodes

Using a two-dimensional ensemble Monte Carlo (EMC) method, electronic nanometer devices with different parameters are studied in detail. Calculation results show that at nanoscale the electric properties of interface inside the devices play an important role in determining the working properties of the devices. By properly arranging device structures, surface charges originated from device fabrication can be exploited to produce a predetermined electric potential in the devices. Based on this fact, two structures that can lead to an asym-metric potential along their nanochannel are proposed for designing strong nonlinear devices. Further studies indicate that Ratchet effect brought by the asymmetric potential results in diode-like current-voltage charac-teristics of the devices. Through optimizing device parameters, zero threshold voltage can be achieved, which is desired for detecting applications. Moreover, since the devices are at nanoscale, simulation results reveal that used as rectifiers the working frequencies can be up to a few THz

Urban Mobility Dynamics Based on Flexible Discrete Region Partition

Understanding the urban mobility patterns is essential for the planning and management of public infrastructure and transportation services. In this paper we focus on taxicab moving trajectory records and present a new approach to modeling and analyzing urban mobility dynamics. The proposed method comprises two phases. First, discrete space partition based on flexible grid is developed to divide urban environment into finite nonoverlapping subregions. By integrating mobility origin-destination points with covered region, the partitioned discrete subregions have better spatial semantics scalability. Then, we study mobility activity and its distribution randomness during given time periods among discrete subregions. Moreover, we also carry out the analysis of mobility linkage of mobility trips between different regions by O-D matrix. We present a case study with real dataset of taxicab mobility logs in Shenzhen, China, to demonstrate and evaluate the methodology. The experimental results show that the proposed method outperforms the clustering partition and regular partition methods

Physics-driven Synthetic Data Learning for Biomedical Magnetic Resonance

Deep learning has innovated the field of computational imaging. One of its bottlenecks is unavailable or insufficient training data. This article reviews an emerging paradigm, imaging physics-based data synthesis (IPADS), that can provide huge training data in biomedical magnetic resonance without or with few real data. Following the physical law of magnetic resonance, IPADS generates signals from differential equations or analytical solution models, making the learning more scalable, explainable, and better protecting privacy. Key components of IPADS learning, including signal generation models, basic deep learning network structures, enhanced data generation, and learning methods are discussed. Great potentials of IPADS have been demonstrated by representative applications in fast imaging, ultrafast signal reconstruction and accurate parameter quantification. Finally, open questions and future work have been discussed

Study on the Performance of Ball Mill with Liner Structure based on DEM

This study used the discrete element method (DEM), which is effective and popular for solving the problem of granular systems simulating the motion of particles in a ball mill in different structural forms and at different rotational speeds. Firstly, simulations of five kinds of lifters (triangular, trapezoidal, rectangular, ladder and hemispherical) were set up. The results were as follows: when the rectangular lifter was selected as mill liner, the ball mill efficiency was significantly high. The breaking performance of the hemispherical lifter and the ladder lifter was poor, because the main pattern of motion was grinding rather than impact breakage. Secondly, the effects of the height"“width ratio of the rectangular lifter, the height of the lifter and the number of lifters on the working efficiency of the ball mill were studied. It was found that a number of rectangular lifters of 12 and a height-width ratio of 3:1 produced the best results. The best height of the rectangular lifter was about 13 mm. Lastly, displacement, stress and deformation were analyzed using DEM coupled with a finite element method (FEM). The purpose was to design the geometrical lifter structure and to improve the performance of the ball mill

Numerical and Experimental Investigation on Nosebleed Air Jet Control for Hypersonic Vehicle

A new idea of nosebleed air jets with strong coupled internal and external flow is put forward using the lateral jet control principle to improve the maneuverability and fast reaction capabilities of hypersonic vehicles. The hypersonic vehicle’s nose stagnant high-pressure and high-temperature gas is utilized as the drive source for long-term jet control. The significant coupled jet interaction of the internal and external flow changes the aerodynamic characteristics. As a result, the structure is basic and does not rely on any external source to achieve flight attitude control. The complicated flow characteristics of the nosebleed jet in supersonic crossflow surrounding the vehicle were numerically and experimentally investigated. The jet interaction characteristics and the aerodynamic characteristic changes generated by the nosebleed air jet are verified by comparing the flow field with and without the jet. Results indicate that the nosebleed air jet alters the center-of-pressure coefficient, which is subsequently coupled with the interference aerodynamic force. This results in a variation in pitch moment. The jet decreases the pitching moment coefficient when compared with the case without a jet. It is probable that combining nosebleed air jets with model centroid adjustment yields an optimal trim angle of attack