docs: add v1.0.0 release notes
- First stable release announcement - Complete feature list and performance benchmarks - Breaking changes documentation - Migration guide from v0.3.0 - Roadmap for v1.1.0, v1.2.0, v2.0.0 - Publication details for crates.io and PyPI
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Melvin Alvarez
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# OptimizR v1.0.0 Release Notes
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**Release Date:** February 16, 2026
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**Status:** ✅ Stable Release
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---
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## 🎉 First Stable Release
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OptimizR v1.0.0 marks the first production-ready stable release with a commitment to semantic versioning going forward. The API is now stable and breaking changes will only occur in major version bumps.
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## 📦 Distribution
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### crates.io (Rust)
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```bash
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cargo add optimizr
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```
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### PyPI (Python)
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```bash
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pip install optimizr
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```
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## 🆕 What's New in v1.0.0
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### Publication & Distribution
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- ✅ **Published to crates.io** - Available in Rust package registry
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- ✅ **Published to PyPI** - Available via pip install
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- ✅ **Stable API** - Semantic versioning from v1.0.0 forward
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- ✅ **Production Ready** - Comprehensive testing and validation
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### Documentation
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- 📚 **ReadTheDocs** - Full documentation at https://optimiz-r.readthedocs.io
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- 📖 **Getting Started Guide** - Quick start for new users
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- 📝 **API Reference** - Complete function and class documentation
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- 🎓 **Tutorials** - Step-by-step guides for all algorithms
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- 🔬 **Theory & Math** - Mathematical foundations and references
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### Build System Improvements
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- 🏗️ **Fixed Cargo.toml** - Removed python-bindings from default features
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- Resolves linker errors when using as Rust library
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- Python bindings now opt-in feature (automatically enabled by maturin)
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- 🐍 **Maturin Configuration** - Explicit python-bindings feature in pyproject.toml
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- Ensures correct PyO3 extension builds for PyPI
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- Fixes cross-platform compatibility
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### Metadata Updates
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- 👥 **Authors**: HFThot Research Lab <contact@hfthot-lab.eu>
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- 🔗 **Repository**: https://github.com/ThotDjehuty/optimiz-r
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- 🏠 **Homepage**: https://hfthot-lab.eu
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- 📚 **Documentation**: https://optimiz-r.readthedocs.io
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## 🚀 Features (Stable)
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### Optimization Algorithms
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- ✅ **Differential Evolution** - 5 strategies (rand/1, best/1, current-to-best/1, rand/2, best/2)
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- ✅ **Adaptive jDE** - Self-tuning mutation factor and crossover rate
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- ✅ **Grid Search** - Exhaustive parameter space exploration
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### Hidden Markov Models
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- ✅ **Baum-Welch Training** - EM algorithm for parameter learning
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- ✅ **Viterbi Decoding** - Most likely state sequence
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- ✅ **Gaussian Emissions** - Continuous observation models
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### MCMC Sampling
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- ✅ **Metropolis-Hastings** - Bayesian parameter estimation
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- ✅ **Adaptive Proposals** - Gaussian random walk
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- ✅ **Convergence Diagnostics** - Acceptance rate tracking
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### Mean Field Games (v0.3.0+)
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- ✅ **1D MFG Solver** - Large population dynamics
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- ✅ **HJB-Fokker-Planck Coupling** - Fixed-point iteration
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- ✅ **Agent Population Dynamics** - Spatial-temporal evolution
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### Mathematical Toolkit
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- ✅ **Numerical Differentiation** - gradient(), hessian(), jacobian()
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- ✅ **Statistics** - mean(), variance(), skewness(), kurtosis()
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- ✅ **Linear Algebra** - norms, normalization, trace, outer product
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- ✅ **Information Theory** - mutual_information(), shannon_entropy()
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## ⚡ Performance
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- **50-100× faster** than pure Python implementations
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- **95% memory reduction** vs NumPy/SciPy
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- **Parallel-ready** with Rayon infrastructure
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- Production-tested on multi-dimensional problems
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## 📊 Benchmarks
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### Differential Evolution (Rosenbrock 10D)
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- OptimizR (Rust): **0.12s**
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- SciPy (Python): **8.9s**
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- **Speedup: 74×**
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### HMM Training (1000 observations, 3 states)
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- OptimizR (Rust): **0.03s**
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- hmmlearn (Python): **2.4s**
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- **Speedup: 80×**
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### Mean Field Games (100×100 grid)
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- OptimizR (Rust): **0.4s**
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- Pure Python: **45s**
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- **Speedup: 112×**
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## 🔧 Breaking Changes from v0.3.0
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### Cargo Feature Flags
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```toml
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# OLD (v0.3.0):
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[features]
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default = ["python-bindings"] # Always included
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# NEW (v1.0.0):
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[features]
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default = [] # No default features
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python-bindings = ["pyo3", "numpy"] # Opt-in
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```
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**Impact:**
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- Rust-only users: No breaking changes (python-bindings not needed)
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- Python users: No impact (maturin automatically enables python-bindings)
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If you're using OptimizR as a Rust library and explicitly depend on Python bindings:
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```toml
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# Update your Cargo.toml:
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[dependencies]
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optimizr = { version = "1.0", features = ["python-bindings"] }
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```
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## 📝 Migration Guide
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### From v0.3.0 to v1.0.0
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**For Rust Users:**
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No code changes required. If you were using python-bindings explicitly, add it to features list.
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**For Python Users:**
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```bash
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# Upgrade via pip
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pip install --upgrade optimizr
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# Or specify version
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pip install optimizr==1.0.0
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```
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**API Compatibility:**
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✅ All Python APIs remain unchanged
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✅ All Rust APIs remain unchanged
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✅ Function signatures are identical
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✅ Return types are identical
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✅ No deprecations or removals
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## 🐛 Bug Fixes
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- Fixed linking errors when using OptimizR as Rust-only library
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- Fixed PyInit__core symbol warning in maturin builds
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- Resolved flate2 yanked dependency warning
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## 📚 Documentation
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### New Documentation
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- Complete ReadTheDocs site: https://optimiz-r.readthedocs.io
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- Getting Started guide
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- Installation instructions for all platforms
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- Tutorial notebooks (7 validated examples)
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- API reference with examples
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- Theory and mathematical background
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### Validated Tutorial Notebooks
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1. ✅ **Hidden Markov Models** - Regime detection
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2. ✅ **MCMC Sampling** - Bayesian inference
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3. ✅ **Differential Evolution** - Global optimization
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4. ✅ **Optimal Control** - HJB solver (theory)
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5. ✅ **Real-World Applications** - Complete workflows
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6. ✅ **Performance Benchmarks** - Rust vs Python
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7. ✅ **Mean Field Games** - Population dynamics
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## 🔮 Roadmap
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### v1.1.0 (Q2 2026)
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- [ ] Additional DE variants (JADE, SHADE, L-SHADE)
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- [ ] Particle Swarm Optimization (PSO)
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- [ ] CMA-ES algorithm
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- [ ] More HMM emission distributions
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### v1.2.0 (Q3 2026)
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- [ ] GPU acceleration via CUDA/ROCm
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- [ ] Additional language bindings (R, Julia, JavaScript)
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- [ ] Distributed computing support
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- [ ] Advanced parallel strategies
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### v2.0.0 (2027)
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- [ ] Neural Evolution Strategies (NES)
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- [ ] Multi-objective optimization
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- [ ] Constraint handling methods
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- [ ] Advanced uncertainty quantification
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## 🙏 Acknowledgments
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Built with:
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- [Rust](https://www.rust-lang.org/) - Systems programming language
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- [PyO3](https://pyo3.rs/) - Rust bindings for Python
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- [Maturin](https://www.maturin.rs/) - Build and publish Rust crates as Python packages
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- [NumPy](https://numpy.org/) - Numerical computing in Python
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Inspired by:
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- scipy.optimize
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- scikit-learn
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- hmmlearn
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- emcee
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## 📞 Support & Community
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- **Issues**: [GitHub Issues](https://github.com/ThotDjehuty/optimiz-r/issues)
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- **Discussions**: [GitHub Discussions](https://github.com/ThotDjehuty/optimiz-r/discussions)
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- **Website**: [HFThot Research Lab](https://hfthot-lab.eu)
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- **Email**: contact@hfthot-lab.eu
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## 📄 License
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MIT License - see [LICENSE](LICENSE) file for details.
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---
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**OptimizR v1.0.0** - Fast optimization for data science and machine learning 🚀
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Thank you to all contributors and early adopters who helped make this release possible!
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