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Optimizing the operation and maintenance (O&M) schedule of offshore wind farms is an effective approach to controlling O&M costs. This paper takes the perspective of appropriately increasing O&M costs to enhance environmental protection around the wind farm and improve the safety of the O&M process. Firstly, the minimization of total O&M cost, carbon emissions from O&M vessels, and the standard deviation of vessel sailing duration are set as optimization objectives. Constraints are determined, including vessel flow conservation, O&M personnel and spare parts, O&M time, external factors, and decision variable types. A new O&M scheduling model for offshore wind farms, namely the CCB-O&MS model, is constructed. A new algorithm, called the chaotic quantum Harris hawks optimization (CQMHHO), is also proposed. Additionally, the CCB-O&MS model's encoding rules (CRD) are designed, a feasible integerization algorithm (FIA) is developed, and a method for determining the number of wind turbines to be accessed (M-DNTA) is formulated. Consequently, a new optimization method for offshore wind farm O&M scheduling, namely CQMHHO-CCB-O&MS, has been established. Subsequently, the feasibility and superiority of the proposed scheduling model is tested using data from offshore wind farms in southern China. Experiment results demonstrate that, compared to other alternative models, the proposed model can achieve a comprehensive optimal scheduling plan. The improved algorithm is more effective than other benchmark algorithms in solving the CCB-O&MS model. • A new chaotic quantum Harris hawk optimization named CQMHHO is proposed to address the issues of premature convergence. • The proposed algorithm introduces a fast search strategy based on quantum computing. • Experimental results demonstrate that CQMHHO outperforms other benchmarked algorithms when applied to solve CCB-O&MS. • A novel offshore wind farm operation and maintenance scheduling method, namely CQMHHO-CCB-O&MS, is established. • The proposed CQMHHO-CCB-O&MS model can reduce the carbon emissions of vessels and balance the duration of vessel sailing. [ABSTRACT FROM AUTHOR]

Previous studies demonstrated that insulin resistance is associated with hypertension. The present study was undertaken to investigate effects of lacidipine on blood pressure and insulin resistance. Methods and Results: Thirty eight hypertensive patients (62±3 years old) were underwent double-blind trial. Normal people at same age were used as normal control. These hypertensive patients had normal level of blood sugar, abnormal oral glucose tolerance test (OGTT), higher level of insulin, higher insulin/blood sugar ratio and lower sensitivity to insulin than normal control. Eighteen hypertensive patients received conventional therapy for 28 days, and 20 hypertensive patients received oral lacidipine (4 rag/day) for 28 days. Compared with the baseline before treatment (pre-treatment), lacidipine decreased (post-treatment vs pre-treatment, *P<0.05) the blood pressure (systolic pressure: 140±13* vs 170±10 mmHg, diastolic pressure: 88±9* vs 107±8 mmHg). Lacidipine reduced the level of insulin (0.5h post-treatment 57.05±12.24* vs pre-treatment 77.26±14.19 mIU/L; 1h post-treatment 68.55±13.79* vs pre-treatment 90.09±15.25 mIU/L) in OGTT and improved the sensitivity to insulin (insulin/blood sugar ratio: 0.11±0.03* vs 0.14±0.06, post-treatment vs pre-treatment), but did not affected the level of blood sugar. The levels of insulin and sugar were unaffected in conventional therapy group, indicating that the insulin resistance were not improved by conventional therapy. Conclusion: Lacidipine can decrease the blood pressure obviously and improve the insulin resistance in hypertensive patients. [ABSTRACT FROM AUTHOR]