This paper proposes a linear eddy-current feature to determine the radius of a metallic ball in a non-contact manner. An electromagnetic eddy-current sensor with two coils is placed co-axially to the metal ball during measurement. It is well known that the distance between the sensor and test piece (i.e. lift-off) affects eddy-current signals. In this paper, it is found that the peak frequency feature of inductance spectrum is linear to the lift-off spacing between the centre of coil and ball. Besides, the slope of peak frequencies versus lift-offs is linked to the radius of ball. The radius of metallic balls is retrieved from the experimental and embedded analytical result of the slope. Measurements have been carried out on 6 metallic balls with different radii. The radius of the metallic ball can be retrieved with an error of less than 2 %.

Jellyfish search (JS) algorithm impersonates the foraging behavior of jellyfish in the ocean. It is a new developed meta-heuristic algorithm that solves complex and real world optimization problems. The global explore capability and robustness of JS are strong, but JS still has great development space in solving complex optimization problems with high dimensions and multiple local optima. Therefore, an enhanced jellyfish search (EJS) algorithm is developed in this study, and three improvements are made: (i) By adding sine and cosine learning factors, the jellyfish can learn from both random individual and best individual during Type B motion in swarm to enhance the optimization capability and convergence speed; (ii) Adding local escape operator can skip local optimal trap and boost the exploitation ability of JS; (iii) Opposition-based learning operator and quasi-opposition learning operator can increase and strengthen the population distribution more diversified, and better individuals are selected from present and new opposition-solution to participates in the next iteration, which can boost the solution’s quality, meanwhile convergence speed is fasted and its precision is increased. In addition, the performance contrast of the developed EJS and some previous outstanding and advanced methods are evaluated on CEC2017, CEC2019 test suite and six real engineering example of case. It is demonstrated that EJS algorithm escaped the trap of local optimum, enhanced the solution’s quality and the calculation speed. What’s more, the practical engineering applications of EJS algorithm also verify its superiority and effectiveness in solving both constrained and unconstrained optimization problems, and it stretched one’s mind for solving such optimization problems.

. Colchicine (C22H25NO6) is a substance used for inducing mutations in order to regulate important agronomic traits. The objective of this study was to investigate the effect of different concentrations (0.0, 0.04, 0.06, 0.08 and 0.1%) and treatment time (6, 12 and 24 h) of colchicine on agronomic traits of proso millet (Panicum miliaceum L.) and to assess the genetic diversity of M2 generations using inter simple sequence repeat markers (ISSR). The experiment was conducted in 2021 for the M1-generation and in 2022 for the M2-generation, from May to September. The percentage of the field germination was decreased with the increasing colchicine concentration and exposure duration. The chlorophyll-defective M1-M2 plants were obtained using various concentrations and exposure periods of colchicine. The highest amount of mutational modifications was attained at 0.08-0.1% concentrations colchicine. A total of 248 plant families with chlorophyll-defective mutations based on the research results were selected from 2214 families. The growing season of M1- and M2 plants were diminished under higher colchicine concentration (0.08-0.1%) combined with soaking time. Thus, the highest indicator of growing season (84 days) was observed at six h treatment time for PI 289324, while the fewest (78 days) was recorded at 12 and 24 h. The possibility of obtaining morphological mutations using colchicine has been confirmed. The ISSR primers amplified a total of 1333 fragments, 1281 bands were found to be polymorphic and 52 bands monomorphic. The percentage of polymorphism varied from 80 to 100 % with an average of 96.11%. Our results showed that most of the bands were found at 0.08% colchicine concentration. These positive variations are a great opportunity to use colchicine as a tool for improving agronomic traits in plant breeding.