NA error occured in fitting simulation model using sparsedossa2

An error occurred while fitting the model to the simulated data. Could you help me troubleshoot this issue?
The errors are as follows:
Filtering for all-zero features/samples…
Data appears to be count table. Fitting library size distribution…
Fitting EM algorithm…
EM iteration 1
Error in if ((slope1 <= slopes[2] & slopes[2] <= slope2) | (slope1 >= :
missing value where TRUE/FALSE needed
Calls: system.time … resolve.list → signalConditionsASAP → signalConditions
In addition: Warning messages:
1: UNRELIABLE VALUE: One of the ‘future.apply’ iterations (‘future_vapply-1’) unexpectedly generated random numbers without declaring so. There is a risk that those random numbers are not statistically sound and the overall results might be invalid. To fix this, specify ‘future.seed=TRUE’. This ensures that proper, parallel-safe random numbers are produced via the L’Ecuyer-CMRG method. To disable this check, use ‘future.seed = NULL’, or set option ‘future.rng.onMisuse’ to “ignore”.
2: UNRELIABLE VALUE: One of the ‘future.apply’ iterations (‘future_vapply-2’) unexpectedly generated random numbers without declaring so. There is a risk that those random numbers are not statistically sound and the overall results might be invalid. To fix this, specify ‘future.seed=TRUE’. This ensures that proper, parallel-safe random numbers are produced via the L’Ecuyer-CMRG method. To disable this check, use ‘future.seed = NULL’, or set option ‘future.rng.onMisuse’ to “ignore”.
3: UNRELIABLE VALUE: One of the ‘future.apply’ iterations (‘future_vapply-3’) unexpectedly generated random numbers without declaring so. There is a risk that those random numbers are not statistically sound and the overall results might be invalid. To fix this, specify ‘future.seed=TRUE’. This ensures that proper, parallel-safe random numbers are produced via the L’Ecuyer-CMRG method. To disable this check, use ‘future.seed = NULL’, or set option ‘future.rng.onMisuse’ to “ignore”.
4: UNRELIABLE VALUE: One of the ‘future.apply’ iterations (‘future_vapply-4’) unexpectedly generated random numbers without declaring so. There is a risk that those random numbers are not statistically sound and the overall results might be invalid. To fix this, specify ‘future.seed=TRUE’. This ensures that proper, parallel-safe random numbers are produced via the L’Ecuyer-CMRG method. To disable this check, use ‘future.seed = NULL’, or set option ‘future.rng.onMisuse’ to “ignore”.
5: UNRELIABLE VALUE: One of the ‘future.apply’ iterations (‘future_vapply-5’) unexpectedly generated random numbers without declaring so. There is a risk that those random numbers are not statistically sound and the overall results might be invalid. To fix this, specify ‘future.seed=TRUE’. This ensures that proper, parallel-safe random numbers are produced via the L’Ecuyer-CMRG method. To disable this check, use ‘future.seed = NULL’, or set option ‘future.rng.onMisuse’ to “ignore”.
6: UNRELIABLE VALUE: One of the ‘future.apply’ iterations (‘future_vapply-6’) unexpectedly generated random numbers without declaring so. There is a risk that those random numbers are not statistically sound and the overall results might be invalid. To fix this, specify ‘future.seed=TRUE’. This ensures that proper, parallel-safe random numbers are produced via the L’Ecuyer-CMRG method. To disable this check, use ‘future.seed = NULL’, or set option ‘future.rng.onMisuse’ to “ignore”.