Power of adjoint of `CuSparseMatrix` does not work anymore

Describe the bug

The power of the adjoint of a CuSparseMatrix does not work anymore. It is only related to Julia v1.10 and not to previous versions.

To reproduce

The Minimal Working Example (MWE) for this bug:

using CUDA
using CUDA.CUSPARSE
CUDA.allowscalar(false)
using LinearAlgebra
using SparseArrays

A = sprand(ComplexF64, 100, 100, 0.1)
A_gpu = cu(A)

julia> A_gpu'^2
ERROR: MethodError: no method matching CuSparseMatrixCSC{ComplexF64, Int32}(::Adjoint{ComplexF64, CuSparseMatrixCSC{ComplexF64, Int32}})

Closest candidates are:
  CuSparseMatrixCSC{Tv, Ti}(::CuArray{<:Integer, 1}, ::CuArray{<:Integer, 1}, ::CuArray{T, 1} where T, ::Tuple{var"#s1271", var"#s1271"} where var"#s1271"<:Integer) where {Tv, Ti<:Integer}
   @ CUDA ~/.julia/packages/CUDA/rXson/lib/cusparse/array.jl:43
  CuSparseMatrixCSC{Tv, Ti}(::Diagonal) where {Tv, Ti}
   @ CUDA ~/.julia/packages/CUDA/rXson/lib/cusparse/conversions.jl:241

Stacktrace:
 [1] convert(T::Type{CuSparseMatrixCSC{ComplexF64, Int32}}, m::Adjoint{ComplexF64, CuSparseMatrixCSC{ComplexF64, Int32}})
   @ CUDA.CUSPARSE ~/.julia/packages/CUDA/rXson/lib/cusparse/array.jl:16
 [2] to_power_type(x::Adjoint{ComplexF64, CuSparseMatrixCSC{ComplexF64, Int32}})
   @ Base ./intfuncs.jl:261
 [3] power_by_squaring(x_::Adjoint{ComplexF64, CuSparseMatrixCSC{ComplexF64, Int32}}, p::Int64)
   @ Base ./intfuncs.jl:276
 [4] ^(A::Adjoint{ComplexF64, CuSparseMatrixCSC{ComplexF64, Int32}}, p::Int64)
   @ LinearAlgebra ~/.julia/juliaup/julia-1.10.0+0.x64.linux.gnu/share/julia/stdlib/v1.10/LinearAlgebra/src/dense.jl:479
 [5] literal_pow(f::typeof(^), x::Adjoint{ComplexF64, CuSparseMatrixCSC{ComplexF64, Int32}}, ::Val{2})
   @ Base ./intfuncs.jl:351
 [6] top-level scope
   @ REPL[8]:1
 [7] top-level scope
   @ ~/.julia/packages/CUDA/rXson/src/initialization.jl:208

Version info

Details on Julia:

Julia Version 1.10.0
Commit 3120989f39b (2023-12-25 18:01 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 32 × 13th Gen Intel(R) Core(TM) i9-13900KF
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, goldmont)
  Threads: 24 on 32 virtual cores
Environment:
  JULIA_NUM_THREADS = 16

Details on CUDA:

CUDA runtime 12.3, artifact installation
CUDA driver 12.3
NVIDIA driver 546.9.0

CUDA libraries:
- CUBLAS: 12.3.4
- CURAND: 10.3.4
- CUFFT: 11.0.12
- CUSOLVER: 11.5.4
- CUSPARSE: 12.2.0
- CUPTI: 21.0.0
- NVML: 12.0.0+545.30

Julia packages:
- CUDA: 5.1.2
- CUDA_Driver_jll: 0.7.0+1
- CUDA_Runtime_jll: 0.10.1+0

Toolchain:
- Julia: 1.10.0
- LLVM: 15.0.7

1 device:
  0: NVIDIA GeForce RTX 4090 (sm_89, 20.981 GiB / 23.988 GiB available)