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Objective: To analyze the epidemiological and clinical characteristics of sporotrichosis, and provide evidences for the diagnosis and treatment of sporotrichosis. Methods: A retrospective analysis was performed on 655 patients with cutaneous sporotrichosis from June 2016 to June 2018. The demographic characteristics, clinical and epidemiological characteristics, and the data of previous diagnosis and treatment were analyzed. Results: Among the 655 patients, there were 253 males and 402 females. The male to female ratio was 1∶1.59. The age ranged for 3 months old to 81 years old, and the common patients′age was between 36 and 65 years old (67.79%). The disease course was more common in 2~4 months of 399 cases (60.92%). The shortest course was 4 days and the longest course was 8 years. Clinically, both the fixed type (77.25%) and the lymphatic type (21.83%) were the main types, and the papular nodule lesions were mostly distributed on face (51.45%) and limbs (43.82%). 133 cases had a clear history of trauma. 499 cases (76.18%) had a history of previous consultations with the disease, and the misdiagnosis rate was 58.72%. Skin infections and dermatitis are the most commonly misdiagnosed diseases. Conclusions: Sporotomycosis has various clinical manifestations, and the common types are fixed and lymphatic types which impact the face and trunk.

Bare-bones differentia1 evo1ution（BBDE）can e1egant1y so1ve the se1ection prob1em of contro1 parameters and mutation strategy in differentia1 evo1ution（DE）.MGBDE is a c1assica1 BBDE based on bi-mutation strategy.However，it random1y assigns a mutation strategy to each individua1，not considering their differences during evo1ution process，meanwhi1e it may suffer from premature convergence.To overcome these drawbacks，a modified a1gorithm based on MGBDE was proposed.A mutation strategy choice factor that guided the individua1 to choose a preferab1e mutation strategy at each mutation operation was introduced，avoiding the evo1ution b1indness brought by the random se1ection of mutation strategy.To retain the a1most parameter-free characteristic of bare-bones a1gorithm，the tuning of choice factor to be adapted was invo1ved in the individua1 evo1ution，inspired by the concept of se1f-adaptive DE.The a1gorithm a1so inc1uded a we11-designed stagnation perturbation mechanism to reduce the risk of trapping into the 1oca1 optima1.Experimenta1 resu1ts on 18 benchmark functions show that the proposed a1gorithm genera11y achieves better performance than state-of-the-art BBDE variants and severa1 we11-known DE a1gorithms in terms of convergence and robustness.