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Additional file 7: Table S4. Clinical features of CAH patients without pathologic biallelic variants.

Additional file 5: Table S2. PGS of CAH patients.

Additional file 4: Table S1. PCR primers for CYP21A2 amplification.

Additional file 7: Table S4. Clinical features of CAH patients without pathologic biallelic variants.

Additional file 1: Fig. S1. Diagnostic algorithm for PAI patients. For a patient with primary adrenal insufficiency, a high serum level of 17-OHP suggests CAH, and he or she was subjected to CYP21A2 sequencing and MLPA. Children with normal or lower 17-OHP levels accompanied by developmental delay, intellectual disability or congenital anomalies underwent Array-GCH examination. WES was performed for the remaining patients.

Additional file 5: Table S2. PGS of CAH patients.

Additional file 4: Table S1. PCR primers for CYP21A2 amplification.

Additional file 6: Table S3. Variants in CYP21A2 gene.

Additional file 6: Table S3. Variants in CYP21A2 gene.

To detect demagnetization faults in real time based on an adaptive sliding mode observer, we used a permanent-magnet synchronous motor (PMSM). Demagnetization faults are first modeled for the PMSM using coordinates oriented to the magnetic field. To solve demagnetization faults problems as multiple parameters change, we used adaptive and sliding mode variable structure control and designed an adaptive sliding mode observer. The adaptive estimation algorithm of the permanent magnet flux is given and the observer’s stability is proven by Lyapunov stability theory. Simulation and experimental results demonstrate the feasibility and effectiveness of our proposal.

For a class of nonlinear system with multi-dimensional actuator faults and multi-dimensional unknown input disturbances, the twice-linear coordinate transformation is made and the sliding mode observer is designed to obtain two dynamic deviation equations. One equation only deals with the faults and the other deals with both the faults and the disturbances. By means of the principle of equivalence of sliding mode observer and sliding mode variable structure, both the actuator faults and the unknown input disturbances can be reconstructed. The effectiveness of such method can be verified by the simulation example.

In view of variable time-delay cellular neural networks with activation function bounded and meeting the conditions of Lippschitz, the result of the global exponential stability is obtained by constructing a special Lyapunov function equality and using Lyapunov function technology and matrix inequality. The global exponential stability of variable time-delay cellular neural networks whose activation function is likewise linear function is discussed. An example and its computer simulation is given to prove the effectiveness of the obtained result. Finally the result of this paper is discussed by comparing existing achievements, and it is with advantage of low dimension validated matrix, simple calculation and easy computer implementation.