diff --git a/Project.toml b/Project.toml
index 3f35539b..5355cb08 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "FMIFlux"
 uuid = "fabad875-0d53-4e47-9446-963b74cae21f"
-version = "0.10.2"
+version = "0.10.3"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
diff --git a/src/layers.jl b/src/layers.jl
index abd3f54d..0ddb8c1b 100644
--- a/src/layers.jl
+++ b/src/layers.jl
@@ -11,18 +11,22 @@ import FMIImport: fmi2Real, fmi2ValueReferenceFormat
 """
 ToDo.
 """
-struct FMUParameterRegistrator
+struct FMUParameterRegistrator{T}
     fmu::FMU2
     p_refs::AbstractArray{<:fmi2ValueReference}
-    p::AbstractArray{<:Real}
+    p::AbstractArray{T}
    
-    function FMUParameterRegistrator(fmu::FMU2, p_refs::fmi2ValueReferenceFormat, p::AbstractArray{<:Real})
+    function FMUParameterRegistrator{T}(fmu::FMU2, p_refs::fmi2ValueReferenceFormat, p::AbstractArray{T}) where {T}
         @assert length(p_refs) == length(p) "`p_refs` and `p` need to be the same length!"
         p_refs = prepareValueReference(fmu, p_refs)
         fmu.optim_p_refs = p_refs 
         fmu.optim_p = p 
         return new(fmu, p_refs, p)
     end
+
+    function FMUParameterRegistrator(fmu::FMU2, p_refs::fmi2ValueReferenceFormat, p::AbstractArray{T}) where {T}
+        return FMUParameterRegistrator{T}(fmu, p_refs, p)
+    end
 end
 export FMUParameterRegistrator
 
diff --git a/src/neural.jl b/src/neural.jl
index a9a5e808..59a69623 100644
--- a/src/neural.jl
+++ b/src/neural.jl
@@ -426,11 +426,11 @@ function affectFMU!(nfmu::ME_NeuralFMU, c::FMU2Component, integrator, idx)
 
         # ToDo: Problem-related parameterization of optimize-call
         #result = optimize(x_seek -> f_optim(x_seek, nfmu, right_x_fmu), left_x, LBFGS(); autodiff = :forward)
-        #result = Optim.optimize(x_seek -> f_optim(x_seek, nfmu, right_x_fmu, idx, sign(indicators[idx])), left_x, NelderMead())
+        #result = Optim.optimize(x_seek -> f_optim(x_seek, nfmu, right_x_fmu, idx, sign(indicators[idx])), left_x, Optim.NelderMead())
         
         # if there is an ANN above the FMU, propaget FMU state through top ANN:
         if nfmu.modifiedState == true
-            result = Optim.optimize(x_seek -> f_optim(x_seek, nfmu, c, right_x_fmu), left_x, NelderMead())
+            result = Optim.optimize(x_seek -> f_optim(x_seek, nfmu, c, right_x_fmu), left_x, Optim.NelderMead())
             right_x = Optim.minimizer(result)
         else # if there is no ANN above, then:
             right_x = right_x_fmu
diff --git a/src/scheduler.jl b/src/scheduler.jl
index c76bd7a7..3acf0d3a 100644
--- a/src/scheduler.jl
+++ b/src/scheduler.jl
@@ -188,7 +188,7 @@ function initialize!(scheduler::BatchScheduler; runkwargs...)
         scheduler.runkwargs = runkwargs
     end
 
-    #scheduler.elementIndex = apply!(scheduler)
+    scheduler.elementIndex = apply!(scheduler)
     
     if scheduler.plotStep > 0
         plot(scheduler, lastIndex)
@@ -201,11 +201,11 @@ function update!(scheduler::BatchScheduler)
 
     scheduler.step += 1
     
-    if scheduler.step % scheduler.applyStep == 0
+    if scheduler.applyStep > 0 && scheduler.step % scheduler.applyStep == 0
         scheduler.elementIndex = apply!(scheduler)
     end
 
-    if scheduler.step % scheduler.plotStep == 0
+    if scheduler.plotStep > 0 && scheduler.step % scheduler.plotStep == 0
         plot(scheduler, lastIndex)
     end
 end