Subwavelength dielectric waveguide for efficient travelling-wave magnetic resonance imaging.

Magnetic resonance imaging (MRI) has diverse applications in physics, biology, and medicine. Uniform excitation of nuclei spins through circular-polarized transverse magnetic component of electromagnetic field is vital for obtaining unbiased tissue contrasts. However, achieving this in the electrically large human body poses a significant challenge, especially at ultra-high fields (UHF) with increased working frequencies (≥297 MHz). Canonical volume resonators struggle to meet this challenge, while radiative excitation methods like travelling-wave (TW) show promise but often suffer from inadequate excitation efficiency. Here, we introduce a new technique using a subwavelength dielectric waveguide insert that enhances both efficiency and homogeneity at 7 T. Through TE11-to-TM11 mode conversion, power focusing, wave impedance matching, and phase velocity matching, we achieved a 114% improvement in TW efficiency and mitigated the center-brightening effect. This fundamental advancement in TW MRI through effective wave manipulation could promote the electromagnetic design of UHF MRI systems.

An improved gene expression programming algorithm for function mining of map-reduce job execution in catenary monitoring systems.

Gene expression programming (GEP) is one of the most prominent algorithms in function mining. In order to obtain a more accurate function model in configuration parameters-execution efficiency (CP-EE) of map-reduce job in the high-speed railway catenary monitoring system, this paper proposes a novel algorithm, called GEP based on multi-strategy (MS-GEP). Compared to traditional GEP, the proposed algorithm can escape premature convergence and jump out of local optimum. First, an adaptive mutation rate is designed according to the evolutionary generations, population diversity, and individual fitness values. A manual intervention strategy is then proposed to determine whether the algorithm enters the dilemma of local optimum based on the generations of population evolutionary stagnation. Finally, the average quality of the population is changed by randomly replacing individuals, and the ancestral population is traced to change the evolutionary direction. The experimental results on the benchmarks of function mining show that the proposed MS-GEP has better solution quality and higher population diversity than other GEP algorithms. Furthermore, the proposed MS-GEP has higher accuracy on the function model of CP-EE of high-speed railway catenary monitoring system than other commonly used algorithms in the field of function mining.

Pantograph Detection Algorithm with Complex Background and External Disturbances.

As an important equipment for high-speed railway (HSR) to obtain electric power from outside, the state of the pantograph will directly affect the operation safety of HSR. In order to solve the problems that the current pantograph detection method is easily affected by the environment, cannot effectively deal with the interference of external scenes, has a low accuracy rate and can hardly meet the actual operation requirements of HSR, this study proposes a pantograph detection algorithm. The algorithm mainly includes three parts: the first is to use you only look once (YOLO) V4 to detect and locate the pantograph region in real-time; the second is the blur and dirt detection algorithm for the external interference directly affecting the high-speed camera (HSC), which leads to the pantograph not being detected; the last is the complex background detection algorithm for the external complex scene "overlapping" with the pantograph when imaging, which leads to the pantograph not being recognized effectively. The dirt and blur detection algorithm combined with blob detection and improved Brenner method can accurately evaluate the dirt or blur of HSC, and the complex background detection algorithm based on grayscale and vertical projection can greatly reduce the external scene interference during HSR operation. The algorithm proposed in this study was analyzed and studied on a large number of video samples of HSR operation, and the precision on three different test samples reached 99.92%, 99.90% and 99.98%, respectively. Experimental results show that the algorithm proposed in this study has strong environmental adaptability and can effectively overcome the effects of complex background and external interference on pantograph detection, and has high practical application value.

Corrigendum: Dislocation Strengthening without Ductility Trade-off in Metastable Austenitic Steels.

This corrects the article DOI: 10.1038/srep35345.

Dislocation Strengthening without Ductility Trade-off in Metastable Austenitic Steels.

Strength and ductility are mutually exclusive if they are manifested as consequence of the coupling between strengthening and toughening mechanisms. One notable example is dislocation strengthening in metals, which invariably leads to reduced ductility. However, this trend is averted in metastable austenitic steels. A one-step thermal mechanical treatment (TMT), i.e. hot rolling, can effectively enhance the yielding strength of the metastable austenitic steel from 322 ± 18 MPa to 675 ± 15 MPa, while retaining both the formability and hardenability. It is noted that no boundaries are introduced in the optimized TMT process and all strengthening effect originates from dislocations with inherited thermal stability. The success of this method relies on the decoupled strengthening and toughening mechanisms in metastable austenitic steels, in which yield strength is controlled by initial dislocation density while ductility is retained by the capability to nucleate new dislocations to carry plastic deformation. Especially, the simplicity in processing enables scaling and industrial applications to meet the challenging requirements of emissions reduction. On the other hand, the complexity in the underlying mechanism of dislocation strengthening in this case may shed light on a different route of material strengthening by stimulating dislocation activities, rather than impeding motion of dislocations.

Application of stochastic method to optimum design of energy-efficient induction motors with a target of LCC.

For an energy-efficient induction machine, the life-cycle cost (LCC) usually is the most important index to the consumer. With this target, the optimization design of a motor is a complex nonlinear problem with constraints. To solve the problem, the authors introduce a united random algorithm. At first, the problem is divided into two parts, the optimal rotor slots and the optimization of other dimensions. Before optimizing the rotor slots with genetic algorithm (GA), the second part is solved with TABU algorithm to simplify the problem. The numerical results showed that this method is better than the method using a traditional algorithm.