Search this site
Skip to main content
Skip to navigation
ChemicalQDevice
Home
About
Recent Results
Drug Discovery GenAI, De Novo Proteins
Drug Discovery Generative AI: GPT, BERT
Explainability: Tensor Network, Neural Network
How to Code LLMs with Tensor Networks
LLM Explainability with Tensor Networks
Tensor Networks vs. PCA and PLS
Tensor Network, Neural Network, or Hybrid
Tensor Network Developer Revolution
Tensor Network Controllability Studies
FDA GMLP Guidelines; and Practical QiML 2.0
QiML 2.0 Speed-Ups, Scalability, Performance, New Era
The Practical Era of QiML 2.0 for Healthcare
Surpassing the Competition with 3 QiML Frameworks
Appreciably Better Quantum-inspired Processing vs. Field
Medical Quantum-inspired ML Software Migration
Medical Quantum-inspired ML Software Migration Seminar
Innovation by ChemicalQDevice
Quantum Algorithm Time Complexity Analysis
Effective QML Algorithms for Medical R&D
Quantum ML Algorithms for Medical School Research
Efficiency Metrics: Single vs. Parallel QML Algorithms
QML Parameters for Breakthrough Parallel Algorithms
Quantum Algorithms & Parallel Architectures New Results
How to Conduct Medical R&D with QiML Algorithms
Parallel Quantum Algorithms Innovation PyTorch, Keras
Advanced PyTorch, Keras Deep Learning with QML/QiML
NIH Developer Seminar: PennyLane, GPUs, and QiML
QML/QiML for Medical Regulatory Agency Review
Advanced Benchmarking/Efficiency; PennyLane QML/QiML
38 Qiskit, PennyLane QML/QiML Demos
Deep Learning with Quantum and Classical Parameters
100 Coding Tips for Qiskit, Cirq, or PennyLane, a Special Event
100 Resources for Medical QML Software Developers
FDA AI/ML Medical Device Guidelines; Potential QML
QiML Algorithm Architecture R&D; New Utilities
The Shift Towards a Healthy QML Industry
New 2023 FDA Annual Approvals; QiML Applications
Data-Reuploading, Quantum Universal Classifier R&D
How to Select the Correct QML Loss Function and Optimizer
All IBM Qiskit Machine Learning Tutorials Seminar
All PennyLane Python Quantum Machine Learning Demos Seminar
Kernel Based Training of Quantum Models
Specific QiML Algorithms for Medical R&D Applications
Quantum Parameter Study for Quantum Inspired Machine Learning
Huynh, L., et al. 2023 Quantum-Inspired Machine Learning a Survey
Benchmarking Quantum Machine Learning Devices
Quantum ML Algorithms Historical Perspective
Advanced Discussion: Potential Quantum Radiomics ML Workflows
Quantum Inspired ML, Potential New FDA Submissions
Python PyTorch Quantum ML Ports/Models for Potential Medical Use
How to Succeed in PennyLane Library: For Medical Developers
Time, Cost, Efficiency: ResNet Quantum TL, TL Models
Quantum ML Algorithms Prototyping for Neuroradiology
Quantum ML Developer Updates
Quantum Algorithms Prototyping for Neuroradiology
44 Class Classification Quantum TL vs. TL Transformer vs. 2 Classical TL
Startup Tables Research & Development
Embedding Medical Data into Quantum Computing Algorithms
ChemicalQDevice Quantum Medical Image Analysis Platform
ChemicalQDevice June 2023 R&D Update
Quantum Computing Developments for Healthcare
Medical Industry Quantum Algorithms Forecast
ChemicalQDevice May 2023 R&D Update
ChemicalQDevice April 2023 R&D 135,000+ Impressions
Minimum Viable Product Iteration Ten
QML Platform Benefits: Qiskit QML, Pennylane..
Quantum Computers and Simulators for Healthcare
QML Advantages for Medical: Qiskit, Pennylane..
Open Discussion-Quantum and Medical Imaging Radiology
Existing Quantum Computing Advantages, Neuroimages
Optimizing Quantum Parameters for Better Results
MIT and Google QML Platforms as candidates for Improving Medical
Next Steps in Quantum Computing and Neuroradiology
Fireside Chat April 13th, 2023
Live Demo: Brain Algorithms Design, Hybrid
Demo Quantum Classical Hybrid Code; Neuroradiology
Advancing Quantum Algorithms, Neuroradiology
Quantum Algorithm Advancements for Radiology
Next Generation Neuroradiology Algorithms
Developing New Quantum Neural Networks
Brain Disorders and Quantum Computing
Incorporation of New Quantum Frameworks
FDA AI/ML Approvals, Basis for QNN Neuroimaging
FDA Radiology and Quantum Algorithms
FDA 510(k)/De Novo & QML Neuroimaging for Alzheimer’s
FDA and Regulation factors for upcoming Quantum Machine Learning
Alzheimer's Disease Neuroradiology and Quantum
Ion Trap for Radiology Advancements
Quantum Coding Advantages: Neuroradiology
Washington D.C. Quantum Efforts, Neuroimaging
Quantum Programming for Neuroradiology
Trapped Ion Quantum Computers for Neuroradiology
QML Neuroradiology (QMLN) Product Innovation
2023 President's Quantum Initiative Summary
Quantum Neuroimaging Industry, Alzheimer’s
Quantum Computing and Medical Industry Results
Welcome to ChemicalQDevice - Holidays 2022
Towards a New Quantum Era in Healthcare
Advancements in Apple Healthcare AI, and QML Neuroimaging Opportunities
AI in Imaging, Framework for New Quantum Era
Multimodal Neuroimaging, and QML for Alzheimer’s
Alzheimer’s QML - Neuroimaging & other Biomarkers
ChemicalQDevice Year End Summary - 2022
Explainable Neuroimaging AI ML for FDA; Prospective QML
QML, and Neuroimaging AI ML Alzheimer's Prediction
Classification & QML Neuroimaging for Alzheimer’s Prediction
Quantum Machine Learning Medical Imaging
Image Classification, MRI PET for AD Drug Clinical Trials
QML Product Development for Neuroimaging, Alzheimer’s
Pre-existing Alzheimer's Neuroimages and QML Prediction
Prospective FDA approval factors for Healthcare QML
QML Neuroimaging Clinical Implementation Factors
A New Quantum Era in Healthcare
The Case for Quantum Machine Learning Neuroimaging
Imaging in Alzheimer's disease, with emerging quantum technologies
Organoid Imaging Technology Improvements
Quantum imaging making personalized medicine a reality
Brain Organoids and Quantum Technologies
2022 ChemicalQDevice Annual Update
QML, QGANs, and QFL for Neuroimaging
Transitioning from ML to Hybrid QML in Neuroimaging
Quantum Neuroimage Processing and QML
Quantum Machine Learning Neuroimaging for Alzheimer's Disease
Quantum Machine Learning Neuroimaging
Quantum Machine Learning Neuroimaging
Quantum Neuroimaging Outline
AI neuroimaging and quantum technologies for Alzheimer's Disease
Imaging in Alzheimer's disease, with emerging quantum technologies
AI in Neuroradiology, Stanford, UC San Diego, and Startup Mission Statement
Organoid Imaging Quantum Advancements
Quantum imaging making personalized medicine a reality
Brain Organoids and Quantum Technologies
Nobel Prize Nominations, Potential Startup Investors, and NSF Progress
Neuroscience and Quantum Discussion
Quantum Investments
Quantum Forecasts
Special Speakers
Quantum Timeline 6-30-22
Newsletter #19
Newsletter #20
Newsletter #21
Newsletter #22
Newsletter #23
Newsletter #24
Newsletter #25
Newsletter #26
Newsletter #27
Newsletter #28
Newsletter #29
Newsletter #30
Newsletter #31
Newsletter #32
Newsletter #33
Newsletter #34
Newsletter #35
Newsletter #36
Newsletter #37
Newsletter #38
Newsletter #39
Newsletter #40
Newsletter #41
Newsletter #42
Newsletter #43
Newsletter #44
Newsletter #45
Newsletter #46
Newsletter #47
Newsletter #48
Newsletter #49
Newsletter #50
Newsletter #51
Newsletter #52
Newsletter #53
Newsletter #54
Newsletter #55
Newsletter #56
Newsletter #57
Newsletter #58
Newsletter #59
Newsletter #60
Newsletter #61
Newsletter #62
Newsletter #63
Newsletter #64
ChemicalQDevice
Home
About
Recent Results
Drug Discovery GenAI, De Novo Proteins
Drug Discovery Generative AI: GPT, BERT
Explainability: Tensor Network, Neural Network
How to Code LLMs with Tensor Networks
LLM Explainability with Tensor Networks
Tensor Networks vs. PCA and PLS
Tensor Network, Neural Network, or Hybrid
Tensor Network Developer Revolution
Tensor Network Controllability Studies
FDA GMLP Guidelines; and Practical QiML 2.0
QiML 2.0 Speed-Ups, Scalability, Performance, New Era
The Practical Era of QiML 2.0 for Healthcare
Surpassing the Competition with 3 QiML Frameworks
Appreciably Better Quantum-inspired Processing vs. Field
Medical Quantum-inspired ML Software Migration
Medical Quantum-inspired ML Software Migration Seminar
Innovation by ChemicalQDevice
Quantum Algorithm Time Complexity Analysis
Effective QML Algorithms for Medical R&D
Quantum ML Algorithms for Medical School Research
Efficiency Metrics: Single vs. Parallel QML Algorithms
QML Parameters for Breakthrough Parallel Algorithms
Quantum Algorithms & Parallel Architectures New Results
How to Conduct Medical R&D with QiML Algorithms
Parallel Quantum Algorithms Innovation PyTorch, Keras
Advanced PyTorch, Keras Deep Learning with QML/QiML
NIH Developer Seminar: PennyLane, GPUs, and QiML
QML/QiML for Medical Regulatory Agency Review
Advanced Benchmarking/Efficiency; PennyLane QML/QiML
38 Qiskit, PennyLane QML/QiML Demos
Deep Learning with Quantum and Classical Parameters
100 Coding Tips for Qiskit, Cirq, or PennyLane, a Special Event
100 Resources for Medical QML Software Developers
FDA AI/ML Medical Device Guidelines; Potential QML
QiML Algorithm Architecture R&D; New Utilities
The Shift Towards a Healthy QML Industry
New 2023 FDA Annual Approvals; QiML Applications
Data-Reuploading, Quantum Universal Classifier R&D
How to Select the Correct QML Loss Function and Optimizer
All IBM Qiskit Machine Learning Tutorials Seminar
All PennyLane Python Quantum Machine Learning Demos Seminar
Kernel Based Training of Quantum Models
Specific QiML Algorithms for Medical R&D Applications
Quantum Parameter Study for Quantum Inspired Machine Learning
Huynh, L., et al. 2023 Quantum-Inspired Machine Learning a Survey
Benchmarking Quantum Machine Learning Devices
Quantum ML Algorithms Historical Perspective
Advanced Discussion: Potential Quantum Radiomics ML Workflows
Quantum Inspired ML, Potential New FDA Submissions
Python PyTorch Quantum ML Ports/Models for Potential Medical Use
How to Succeed in PennyLane Library: For Medical Developers
Time, Cost, Efficiency: ResNet Quantum TL, TL Models
Quantum ML Algorithms Prototyping for Neuroradiology
Quantum ML Developer Updates
Quantum Algorithms Prototyping for Neuroradiology
44 Class Classification Quantum TL vs. TL Transformer vs. 2 Classical TL
Startup Tables Research & Development
Embedding Medical Data into Quantum Computing Algorithms
ChemicalQDevice Quantum Medical Image Analysis Platform
ChemicalQDevice June 2023 R&D Update
Quantum Computing Developments for Healthcare
Medical Industry Quantum Algorithms Forecast
ChemicalQDevice May 2023 R&D Update
ChemicalQDevice April 2023 R&D 135,000+ Impressions
Minimum Viable Product Iteration Ten
QML Platform Benefits: Qiskit QML, Pennylane..
Quantum Computers and Simulators for Healthcare
QML Advantages for Medical: Qiskit, Pennylane..
Open Discussion-Quantum and Medical Imaging Radiology
Existing Quantum Computing Advantages, Neuroimages
Optimizing Quantum Parameters for Better Results
MIT and Google QML Platforms as candidates for Improving Medical
Next Steps in Quantum Computing and Neuroradiology
Fireside Chat April 13th, 2023
Live Demo: Brain Algorithms Design, Hybrid
Demo Quantum Classical Hybrid Code; Neuroradiology
Advancing Quantum Algorithms, Neuroradiology
Quantum Algorithm Advancements for Radiology
Next Generation Neuroradiology Algorithms
Developing New Quantum Neural Networks
Brain Disorders and Quantum Computing
Incorporation of New Quantum Frameworks
FDA AI/ML Approvals, Basis for QNN Neuroimaging
FDA Radiology and Quantum Algorithms
FDA 510(k)/De Novo & QML Neuroimaging for Alzheimer’s
FDA and Regulation factors for upcoming Quantum Machine Learning
Alzheimer's Disease Neuroradiology and Quantum
Ion Trap for Radiology Advancements
Quantum Coding Advantages: Neuroradiology
Washington D.C. Quantum Efforts, Neuroimaging
Quantum Programming for Neuroradiology
Trapped Ion Quantum Computers for Neuroradiology
QML Neuroradiology (QMLN) Product Innovation
2023 President's Quantum Initiative Summary
Quantum Neuroimaging Industry, Alzheimer’s
Quantum Computing and Medical Industry Results
Welcome to ChemicalQDevice - Holidays 2022
Towards a New Quantum Era in Healthcare
Advancements in Apple Healthcare AI, and QML Neuroimaging Opportunities
AI in Imaging, Framework for New Quantum Era
Multimodal Neuroimaging, and QML for Alzheimer’s
Alzheimer’s QML - Neuroimaging & other Biomarkers
ChemicalQDevice Year End Summary - 2022
Explainable Neuroimaging AI ML for FDA; Prospective QML
QML, and Neuroimaging AI ML Alzheimer's Prediction
Classification & QML Neuroimaging for Alzheimer’s Prediction
Quantum Machine Learning Medical Imaging
Image Classification, MRI PET for AD Drug Clinical Trials
QML Product Development for Neuroimaging, Alzheimer’s
Pre-existing Alzheimer's Neuroimages and QML Prediction
Prospective FDA approval factors for Healthcare QML
QML Neuroimaging Clinical Implementation Factors
A New Quantum Era in Healthcare
The Case for Quantum Machine Learning Neuroimaging
Imaging in Alzheimer's disease, with emerging quantum technologies
Organoid Imaging Technology Improvements
Quantum imaging making personalized medicine a reality
Brain Organoids and Quantum Technologies
2022 ChemicalQDevice Annual Update
QML, QGANs, and QFL for Neuroimaging
Transitioning from ML to Hybrid QML in Neuroimaging
Quantum Neuroimage Processing and QML
Quantum Machine Learning Neuroimaging for Alzheimer's Disease
Quantum Machine Learning Neuroimaging
Quantum Machine Learning Neuroimaging
Quantum Neuroimaging Outline
AI neuroimaging and quantum technologies for Alzheimer's Disease
Imaging in Alzheimer's disease, with emerging quantum technologies
AI in Neuroradiology, Stanford, UC San Diego, and Startup Mission Statement
Organoid Imaging Quantum Advancements
Quantum imaging making personalized medicine a reality
Brain Organoids and Quantum Technologies
Nobel Prize Nominations, Potential Startup Investors, and NSF Progress
Neuroscience and Quantum Discussion
Quantum Investments
Quantum Forecasts
Special Speakers
Quantum Timeline 6-30-22
Newsletter #19
Newsletter #20
Newsletter #21
Newsletter #22
Newsletter #23
Newsletter #24
Newsletter #25
Newsletter #26
Newsletter #27
Newsletter #28
Newsletter #29
Newsletter #30
Newsletter #31
Newsletter #32
Newsletter #33
Newsletter #34
Newsletter #35
Newsletter #36
Newsletter #37
Newsletter #38
Newsletter #39
Newsletter #40
Newsletter #41
Newsletter #42
Newsletter #43
Newsletter #44
Newsletter #45
Newsletter #46
Newsletter #47
Newsletter #48
Newsletter #49
Newsletter #50
Newsletter #51
Newsletter #52
Newsletter #53
Newsletter #54
Newsletter #55
Newsletter #56
Newsletter #57
Newsletter #58
Newsletter #59
Newsletter #60
Newsletter #61
Newsletter #62
Newsletter #63
Newsletter #64
More
Home
About
Recent Results
Drug Discovery GenAI, De Novo Proteins
Drug Discovery Generative AI: GPT, BERT
Explainability: Tensor Network, Neural Network
How to Code LLMs with Tensor Networks
LLM Explainability with Tensor Networks
Tensor Networks vs. PCA and PLS
Tensor Network, Neural Network, or Hybrid
Tensor Network Developer Revolution
Tensor Network Controllability Studies
FDA GMLP Guidelines; and Practical QiML 2.0
QiML 2.0 Speed-Ups, Scalability, Performance, New Era
The Practical Era of QiML 2.0 for Healthcare
Surpassing the Competition with 3 QiML Frameworks
Appreciably Better Quantum-inspired Processing vs. Field
Medical Quantum-inspired ML Software Migration
Medical Quantum-inspired ML Software Migration Seminar
Innovation by ChemicalQDevice
Quantum Algorithm Time Complexity Analysis
Effective QML Algorithms for Medical R&D
Quantum ML Algorithms for Medical School Research
Efficiency Metrics: Single vs. Parallel QML Algorithms
QML Parameters for Breakthrough Parallel Algorithms
Quantum Algorithms & Parallel Architectures New Results
How to Conduct Medical R&D with QiML Algorithms
Parallel Quantum Algorithms Innovation PyTorch, Keras
Advanced PyTorch, Keras Deep Learning with QML/QiML
NIH Developer Seminar: PennyLane, GPUs, and QiML
QML/QiML for Medical Regulatory Agency Review
Advanced Benchmarking/Efficiency; PennyLane QML/QiML
38 Qiskit, PennyLane QML/QiML Demos
Deep Learning with Quantum and Classical Parameters
100 Coding Tips for Qiskit, Cirq, or PennyLane, a Special Event
100 Resources for Medical QML Software Developers
FDA AI/ML Medical Device Guidelines; Potential QML
QiML Algorithm Architecture R&D; New Utilities
The Shift Towards a Healthy QML Industry
New 2023 FDA Annual Approvals; QiML Applications
Data-Reuploading, Quantum Universal Classifier R&D
How to Select the Correct QML Loss Function and Optimizer
All IBM Qiskit Machine Learning Tutorials Seminar
All PennyLane Python Quantum Machine Learning Demos Seminar
Kernel Based Training of Quantum Models
Specific QiML Algorithms for Medical R&D Applications
Quantum Parameter Study for Quantum Inspired Machine Learning
Huynh, L., et al. 2023 Quantum-Inspired Machine Learning a Survey
Benchmarking Quantum Machine Learning Devices
Quantum ML Algorithms Historical Perspective
Advanced Discussion: Potential Quantum Radiomics ML Workflows
Quantum Inspired ML, Potential New FDA Submissions
Python PyTorch Quantum ML Ports/Models for Potential Medical Use
How to Succeed in PennyLane Library: For Medical Developers
Time, Cost, Efficiency: ResNet Quantum TL, TL Models
Quantum ML Algorithms Prototyping for Neuroradiology
Quantum ML Developer Updates
Quantum Algorithms Prototyping for Neuroradiology
44 Class Classification Quantum TL vs. TL Transformer vs. 2 Classical TL
Startup Tables Research & Development
Embedding Medical Data into Quantum Computing Algorithms
ChemicalQDevice Quantum Medical Image Analysis Platform
ChemicalQDevice June 2023 R&D Update
Quantum Computing Developments for Healthcare
Medical Industry Quantum Algorithms Forecast
ChemicalQDevice May 2023 R&D Update
ChemicalQDevice April 2023 R&D 135,000+ Impressions
Minimum Viable Product Iteration Ten
QML Platform Benefits: Qiskit QML, Pennylane..
Quantum Computers and Simulators for Healthcare
QML Advantages for Medical: Qiskit, Pennylane..
Open Discussion-Quantum and Medical Imaging Radiology
Existing Quantum Computing Advantages, Neuroimages
Optimizing Quantum Parameters for Better Results
MIT and Google QML Platforms as candidates for Improving Medical
Next Steps in Quantum Computing and Neuroradiology
Fireside Chat April 13th, 2023
Live Demo: Brain Algorithms Design, Hybrid
Demo Quantum Classical Hybrid Code; Neuroradiology
Advancing Quantum Algorithms, Neuroradiology
Quantum Algorithm Advancements for Radiology
Next Generation Neuroradiology Algorithms
Developing New Quantum Neural Networks
Brain Disorders and Quantum Computing
Incorporation of New Quantum Frameworks
FDA AI/ML Approvals, Basis for QNN Neuroimaging
FDA Radiology and Quantum Algorithms
FDA 510(k)/De Novo & QML Neuroimaging for Alzheimer’s
FDA and Regulation factors for upcoming Quantum Machine Learning
Alzheimer's Disease Neuroradiology and Quantum
Ion Trap for Radiology Advancements
Quantum Coding Advantages: Neuroradiology
Washington D.C. Quantum Efforts, Neuroimaging
Quantum Programming for Neuroradiology
Trapped Ion Quantum Computers for Neuroradiology
QML Neuroradiology (QMLN) Product Innovation
2023 President's Quantum Initiative Summary
Quantum Neuroimaging Industry, Alzheimer’s
Quantum Computing and Medical Industry Results
Welcome to ChemicalQDevice - Holidays 2022
Towards a New Quantum Era in Healthcare
Advancements in Apple Healthcare AI, and QML Neuroimaging Opportunities
AI in Imaging, Framework for New Quantum Era
Multimodal Neuroimaging, and QML for Alzheimer’s
Alzheimer’s QML - Neuroimaging & other Biomarkers
ChemicalQDevice Year End Summary - 2022
Explainable Neuroimaging AI ML for FDA; Prospective QML
QML, and Neuroimaging AI ML Alzheimer's Prediction
Classification & QML Neuroimaging for Alzheimer’s Prediction
Quantum Machine Learning Medical Imaging
Image Classification, MRI PET for AD Drug Clinical Trials
QML Product Development for Neuroimaging, Alzheimer’s
Pre-existing Alzheimer's Neuroimages and QML Prediction
Prospective FDA approval factors for Healthcare QML
QML Neuroimaging Clinical Implementation Factors
A New Quantum Era in Healthcare
The Case for Quantum Machine Learning Neuroimaging
Imaging in Alzheimer's disease, with emerging quantum technologies
Organoid Imaging Technology Improvements
Quantum imaging making personalized medicine a reality
Brain Organoids and Quantum Technologies
2022 ChemicalQDevice Annual Update
QML, QGANs, and QFL for Neuroimaging
Transitioning from ML to Hybrid QML in Neuroimaging
Quantum Neuroimage Processing and QML
Quantum Machine Learning Neuroimaging for Alzheimer's Disease
Quantum Machine Learning Neuroimaging
Quantum Machine Learning Neuroimaging
Quantum Neuroimaging Outline
AI neuroimaging and quantum technologies for Alzheimer's Disease
Imaging in Alzheimer's disease, with emerging quantum technologies
AI in Neuroradiology, Stanford, UC San Diego, and Startup Mission Statement
Organoid Imaging Quantum Advancements
Quantum imaging making personalized medicine a reality
Brain Organoids and Quantum Technologies
Nobel Prize Nominations, Potential Startup Investors, and NSF Progress
Neuroscience and Quantum Discussion
Quantum Investments
Quantum Forecasts
Special Speakers
Quantum Timeline 6-30-22
Newsletter #19
Newsletter #20
Newsletter #21
Newsletter #22
Newsletter #23
Newsletter #24
Newsletter #25
Newsletter #26
Newsletter #27
Newsletter #28
Newsletter #29
Newsletter #30
Newsletter #31
Newsletter #32
Newsletter #33
Newsletter #34
Newsletter #35
Newsletter #36
Newsletter #37
Newsletter #38
Newsletter #39
Newsletter #40
Newsletter #41
Newsletter #42
Newsletter #43
Newsletter #44
Newsletter #45
Newsletter #46
Newsletter #47
Newsletter #48
Newsletter #49
Newsletter #50
Newsletter #51
Newsletter #52
Newsletter #53
Newsletter #54
Newsletter #55
Newsletter #56
Newsletter #57
Newsletter #58
Newsletter #59
Newsletter #60
Newsletter #61
Newsletter #62
Newsletter #63
Newsletter #64
ChemicalQDevice
ChemicalQDevice Newsletter #
30
Newsletter #30.pdf
Created by Kevin Kawchak
Founder CEO ChemicalQDevice
2022 San Diego, California
Healthcare Innovation
Report abuse
Report abuse
Newsletter #30.pdfNewsletter #30.pdf