Verified Service Provider in Ethiopia
Bioinformatics Infrastructure in Ethiopia
Engineering Excellence & Technical Support
Bioinformatics Infrastructure solutions for Digital & Analytical. High-standard technical execution following OEM protocols and local regulatory frameworks.
National Genomics Data Repository
Established a secure, high-capacity national genomics data repository to store and manage vast amounts of genomic data generated from research and clinical initiatives across Ethiopia. This centralized hub ensures data integrity, facilitates accessibility for authorized researchers, and supports large-scale comparative genomics analyses crucial for understanding local pathogen diversity and crop resilience.
Scalable Cloud-Based HPC Cluster
Deployed a flexible and scalable cloud-based High-Performance Computing (HPC) cluster, providing Ethiopian bioinformaticians with on-demand access to significant computational resources. This infrastructure empowers complex analyses such as whole-genome sequencing assembly, population genetics simulations, and machine learning-driven disease prediction, overcoming the limitations of on-premise hardware and accelerating research timelines.
Standardized Bioinformatics Pipeline Framework
Developed and implemented a standardized framework for common bioinformatics analysis pipelines, including variant calling, transcriptome analysis, and phylogenetic reconstruction. This initiative promotes reproducibility, reduces redundant efforts, and ensures consistent data quality across diverse research projects, thereby fostering collaboration and enabling the integration of findings from multiple institutions within Ethiopia.
What Is Bioinformatics Infrastructure In Ethiopia?
Bioinformatics infrastructure in Ethiopia refers to the integrated ecosystem of computational resources, databases, software tools, analytical pipelines, and human expertise necessary for the acquisition, storage, processing, analysis, and interpretation of biological data. This infrastructure is crucial for advancing research in genomics, proteomics, transcriptomics, metagenomics, and other high-throughput biological disciplines within the Ethiopian scientific landscape. It facilitates the translation of raw biological data into actionable insights for addressing local and global health, agricultural, and environmental challenges.
| Stakeholder Group | Needs and Requirements | Typical Use Cases |
|---|---|---|
| Academic Researchers (Universities, Research Institutes) | Access to computational power for analyzing large-scale genomic/transcriptomic data, databases for comparative genomics, and specialized software for hypothesis testing. | Identifying genetic markers for crop improvement, understanding disease resistance in livestock, characterizing microbial communities in local ecosystems, drug discovery research. |
| Public Health Institutions (e.g., Ethiopian Public Health Institute) | Infrastructure for pathogen surveillance, outbreak investigation, antimicrobial resistance monitoring, and personalized medicine initiatives. | Tracking the evolution of infectious diseases (e.g., malaria, HIV, COVID-19), identifying drug resistance mutations, genomic epidemiology for public health policy, diagnostics development. |
| Agricultural Sector (e.g., Ethiopian Institute of Agricultural Research) | Tools for marker-assisted selection (MAS) in crop breeding, genomic analysis for enhanced yield and stress tolerance, microbiome analysis for soil health. | Developing climate-resilient crop varieties, identifying genes for drought or pest resistance, improving livestock breeding programs, understanding plant-pathogen interactions. |
| Conservation Biologists and Environmental Scientists | Databases and analytical tools for biodiversity assessment, population genetics, and ecological modeling. | Cataloging Ethiopian biodiversity, assessing genetic diversity of endangered species, monitoring environmental impacts through metagenomics, understanding ecosystem dynamics. |
| Students and Trainees | Accessible platforms and datasets for learning bioinformatics concepts and practical skills, guided exercises, and mentorship. | Hands-on experience with sequencing data analysis, developing foundational bioinformatics skills for future research and employment, completing thesis projects. |
| Biotechnology and Pharmaceutical Companies (Emerging) | Secure environments for proprietary data analysis, access to relevant databases for drug discovery and development, computational modeling. | Target identification for novel therapeutics, optimization of bioprocesses, development of diagnostics, pharmacogenomics studies. |
Key Components of Bioinformatics Infrastructure in Ethiopia:
- Computational Resources: High-performance computing (HPC) clusters, cloud computing platforms, and local servers for data storage and processing.
- Data Storage Solutions: Secure, scalable, and robust data repositories for managing large biological datasets, adhering to data privacy and security standards.
- Bioinformatics Software and Tools: A comprehensive suite of open-source and proprietary software for sequence alignment, variant calling, phylogenetic analysis, gene expression analysis, pathway analysis, and visualization.
- Databases and Knowledge Bases: Access to and potentially local curation of public biological databases (e.g., NCBI, Ensembl, UniProt) and specialized databases relevant to Ethiopian biodiversity and disease contexts.
- Network Connectivity: High-speed and reliable internet access to facilitate data transfer, collaboration, and access to cloud resources.
- Human Expertise: Skilled bioinformaticians, computational biologists, data scientists, and IT support personnel who can develop, maintain, and utilize the infrastructure.
- Standardization and Interoperability: Adherence to established data formats and metadata standards to ensure seamless data exchange and integration across different tools and platforms.
- Training and Capacity Building Programs: Initiatives to educate researchers and students on bioinformatics principles, tools, and best practices.
Who Needs Bioinformatics Infrastructure In Ethiopia?
Bioinformatics infrastructure in Ethiopia is crucial for advancing biological research, healthcare, agriculture, and environmental monitoring. Its development and accessibility will empower a diverse range of stakeholders to leverage advanced computational tools for data analysis, discovery, and problem-solving. This infrastructure is not a luxury but a necessity for Ethiopia to compete on the global scientific stage and address its unique national challenges.
| Customer/Department | Primary Needs & Applications | Specific Examples in Ethiopia |
|---|---|---|
| Academic and Research Institutions | Genomic sequencing and analysis (human, animal, plant, microbial), transcriptomics, proteomics, comparative genomics, phylogenetics, drug discovery, evolutionary biology, population genetics. Support for postgraduate research and training. | Universities (e.g., Addis Ababa University, Jimma University) conducting research on local disease strains (malaria, HIV), indigenous crops for food security, and biodiversity. Research institutes like the Ethiopian Institute of Agricultural Research (EIAR). |
| Government Agencies | Disease surveillance and outbreak investigation (public health), food safety and quality control, agricultural pest and disease management, environmental monitoring and impact assessment, policy development based on scientific evidence, national biodiversity databases. | Ethiopian Public Health Institute (EPHI) for infectious disease genomics, Ministry of Agriculture for crop and livestock genomics, Ethiopian Environmental Protection Authority (EPA) for environmental DNA studies and conservation planning. |
| Healthcare Providers | Diagnostic genomics (identifying genetic predispositions, rare diseases), personalized medicine (optimizing drug treatments), infectious disease diagnostics and strain tracking, pathogen identification and resistance profiling, genetic counseling support. | Hospitals and specialized clinics (e.g., Tikur Anbessa Specialized Hospital) for genetic disease diagnosis, infectious disease labs for tracking drug resistance in TB or HIV, emerging personalized oncology initiatives. |
| Agricultural Sector | Crop improvement (identifying genes for drought resistance, yield, disease resistance), livestock breeding and management (genomic selection), pest and pathogen identification and control, understanding soil microbiome for improved fertility, aquaculture genomics. | Ethiopian Institute of Agricultural Research (EIAR) and its regional centers for developing improved crop varieties (teff, maize, coffee), livestock breeding programs, and veterinary diagnostics. |
| Environmental and Conservation Organizations | Biodiversity assessment and monitoring, population genetics for endangered species, wildlife forensics, understanding ecosystem health through microbial community analysis, tracking invasive species, climate change adaptation studies. | Ethiopian Wildlife Conservation Authority (EWCA), Ethiopian Biodiversity Institute (EBI) for studying unique flora and fauna, understanding genetic diversity of key species, and conservation efforts in national parks. |
| Private Sector and Biotechnology Companies | Development of novel diagnostics, biopharmaceutical research and development, agricultural biotechnology products, food industry applications, specialized consulting services. | Emerging biotech startups, companies in the food and beverage sector for quality control, and potential future pharmaceutical companies exploring local drug discovery. |
| Students and Emerging Researchers | Hands-on training in bioinformatics tools and techniques, access to computational resources for thesis and project work, skill development for future employment in research and industry. | All university students pursuing degrees in biology, medicine, agriculture, and related fields. Workshops and training programs organized by research institutions and universities. |
Target Customers and Departments for Bioinformatics Infrastructure in Ethiopia
- Academic and Research Institutions
- Government Agencies
- Healthcare Providers
- Agricultural Sector
- Environmental and Conservation Organizations
- Private Sector and Biotechnology Companies
- Students and Emerging Researchers
Bioinformatics Infrastructure Process In Ethiopia
The bioinformatics infrastructure process in Ethiopia, from initial inquiry to the full execution of research projects, involves a structured workflow designed to leverage computational resources and expertise for biological data analysis. This process typically begins with a research idea or a specific biological question requiring bioinformatics support. The workflow is iterative and collaborative, ensuring that the infrastructure effectively serves the needs of the research community.
| Stage | Key Activities | Responsible Parties | Outcomes |
|---|---|---|---|
| Inquiry and Needs Assessment | Define research question, identify data types, specify analysis requirements | Researchers, Project Leads | Clear understanding of bioinformatics needs, project scope definition |
| Resource Identification and Allocation | Select HPC, cloud, software, storage; secure access | IT Department, Bioinformatics Hubs, National Committees | Allocated computing resources, storage space, software licenses |
| Data Management and Preparation | Data acquisition, quality control, formatting, ethical compliance | Researchers, Data Managers, Bioinformaticians | Organized, clean, and analysis-ready datasets |
| Analysis Pipeline Design and Execution | Develop and run computational workflows, parameter tuning | Bioinformaticians, Researchers | Raw analysis results, intermediate data files |
| Data Interpretation and Visualization | Statistical analysis, identifying biological significance, creating figures | Researchers, Bioinformaticians, Statisticians | Interpreted biological insights, figures and tables for reporting |
| Reporting and Dissemination | Manuscript writing, presentations, data sharing | Researchers, Collaborators | Publications, conference presentations, accessible data repositories |
| Infrastructure Improvement and Training | Evaluate resource utilization, identify needs, conduct training | Infrastructure Managers, Training Coordinators, Research Community | Enhanced infrastructure, skilled researchers, updated best practices |
Key Stages in the Ethiopian Bioinformatics Infrastructure Workflow
- 1. Inquiry and Needs Assessment: This initial stage involves researchers identifying a project requiring bioinformatics support. They articulate their research questions, the type of biological data they intend to generate or analyze (e.g., genomic, transcriptomic, proteomic), and their specific analysis needs (e.g., sequence alignment, variant calling, phylogenetic analysis, machine learning for prediction). This often involves reaching out to existing bioinformatics hubs, research institutions, or national initiatives.
- 2. Resource Identification and Allocation: Based on the needs assessment, the appropriate bioinformatics resources are identified. This could include access to high-performance computing (HPC) clusters, specialized software licenses, cloud computing platforms, and secure data storage. Resource allocation processes, often managed by institutional IT departments or national bioinformatics committees, ensure that projects are assigned computing power and storage proportionate to their requirements.
- 3. Data Management and Preparation: Once resources are allocated, the focus shifts to data. This involves planning for data generation (if applicable), ethical considerations and data sharing agreements, and robust data management strategies. Raw data needs to be organized, potentially pre-processed (e.g., quality control, adapter trimming), and formatted for downstream analysis. Secure data transfer protocols are crucial.
- 4. Analysis Pipeline Design and Execution: This is the core of the bioinformatics process. Researchers, often in collaboration with bioinformaticians, design analysis pipelines. These pipelines consist of a series of computational tools and scripts tailored to the research question. The execution of these pipelines occurs on the allocated HPC or cloud infrastructure, involving parameter optimization and troubleshooting.
- 5. Data Interpretation and Visualization: The output from the analysis pipelines is then interpreted in the context of the biological question. This stage involves statistical analysis, identifying significant findings, and generating visual representations of the data (e.g., heatmaps, phylogenetic trees, pathway diagrams) to facilitate understanding and communication.
- 6. Reporting and Dissemination: The findings are then compiled into research reports, manuscripts for publication, presentations, or grant proposals. Ethical data sharing practices and the deposition of data into public repositories are also considered at this stage.
- 7. Infrastructure Improvement and Training: Feedback from researchers and the experiences gained throughout the workflow inform ongoing improvements to the bioinformatics infrastructure. This includes identifying gaps in software, hardware, or expertise. Furthermore, continuous training programs are essential to upskill researchers in bioinformatics tools and methodologies.
Bioinformatics Infrastructure Cost In Ethiopia
The cost of bioinformatics infrastructure in Ethiopia is a multifaceted issue influenced by several key factors. These include the type and scale of the infrastructure required, the specific vendors and technologies chosen, the level of technical expertise needed for implementation and maintenance, and the prevailing import duties and taxes. Furthermore, the rapid evolution of technology means that pricing can be dynamic, with newer, more powerful solutions often commanding higher initial costs. The availability of local support and training also plays a role, as engaging international service providers can incur significant travel and logistical expenses. While precise, up-to-the-minute pricing data for Ethiopia can be challenging to obtain due to the specialized nature of the market and currency fluctuations, we can discuss typical pricing factors and approximate ranges in Ethiopian Birr (ETB).
| Infrastructure Component | Estimated Range (ETB) | Notes |
|---|---|---|
| High-Performance Computing (HPC) Server (per node) | 2,000,000 - 15,000,000+ | Varies widely based on CPU, RAM, GPU configurations. Includes chassis, power supplies, and basic networking. |
| Network Attached Storage (NAS) / Storage Array (per TB) | 15,000 - 75,000+ | Depends on drive type (HDD/SSD), capacity, RAID configuration, and vendor. |
| High-End Workstation (for analysis) | 800,000 - 3,000,000+ | Powerful CPU, ample RAM, dedicated GPU, fast storage. |
| Specialized Bioinformatics Software License (annual) | 50,000 - 1,000,000+ | Depends on the software suite, number of users, and features. Some open-source alternatives exist. |
| Cloud Computing Instance (e.g., AWS/Azure/GCP per hour) | 50 - 5,000+ | Highly variable based on CPU, RAM, GPU, and instance type. Can be cost-effective for transient workloads. |
| Annual Maintenance & Support (hardware/software) | 5% - 20% of initial hardware/software cost | Crucial for long-term reliability and access to updates. |
| Cloud Storage (per TB/month) | 100 - 1,000+ | Depends on the cloud provider and storage tier (e.g., standard, infrequent access). |
| Networking Switch (managed, high-port density) | 300,000 - 2,000,000+ | For high-speed, reliable internal networking. |
Key Pricing Factors for Bioinformatics Infrastructure in Ethiopia
- Hardware (Servers, Storage, Workstations): This is often the largest capital expenditure. Factors include processing power (CPU cores, clock speed), RAM capacity, storage type (HDD vs. SSD, capacity), and network interface speeds.
- Software Licenses: This includes operating systems, specialized bioinformatics analysis suites (e.g., genomics analysis platforms, sequence alignment software), databases, and visualization tools. Licensing models vary (perpetual, subscription, per-user).
- Networking Equipment: High-speed switches, routers, and firewalls are crucial for efficient data transfer within and between research institutions.
- Cloud Computing Services: Increasingly relevant, offering flexible and scalable computing power and storage. Costs are typically based on usage (compute hours, storage volume, data transfer).
- Implementation and Configuration: The cost of setting up and configuring the infrastructure, often involving specialized IT and bioinformatics expertise.
- Maintenance and Support: Annual maintenance contracts for hardware and software, including technical support and updates. This can be a significant ongoing operational cost.
- Training and Capacity Building: Investing in training local personnel to manage and utilize the infrastructure effectively.
- Import Duties and Taxes: Applicable to imported hardware and software, significantly impacting the final cost.
- Currency Fluctuations: The ETB's exchange rate against major currencies like USD and EUR can affect the cost of imported goods and services.
Affordable Bioinformatics Infrastructure Options
This document outlines affordable bioinformatics infrastructure options, focusing on value bundles and cost-saving strategies to empower researchers and institutions with limited budgets. Access to robust computational resources is crucial for modern biological research, but traditional, on-premise solutions can be prohibitively expensive. This guide explores alternatives that deliver necessary power and flexibility without breaking the bank. By understanding different service models, leveraging cloud computing benefits, and implementing smart procurement practices, significant cost reductions are achievable.
| Infrastructure Option | Description | Typical Value Bundle Components | Cost-Saving Strategy Focus |
|---|---|---|---|
| Cloud Computing (IaaS/PaaS) | On-demand access to virtualized computing, storage, and networking resources from major providers (AWS, Azure, GCP). | Virtual machines (CPU, RAM), object storage (S3, Blob Storage), managed databases, container orchestration (Kubernetes). | Pay-as-you-go, elasticity (scale up/down), spot instances (deep discounts), reserved instances (long-term savings). |
| High-Performance Computing (HPC) Clusters (Shared/Consortia) | Access to specialized, powerful compute clusters often managed by universities or research organizations for collaborative use. | High-CPU cores, large memory nodes, high-throughput storage, specialized accelerators (GPUs). | Shared infrastructure costs, reduced individual hardware investment, pooled software licenses. |
| On-Premise with Strategic Upgrades | Maintaining some or all infrastructure in-house but focusing on cost-effective upgrades and efficient management. | Servers, storage arrays, networking equipment, specialized software. | Refurbished hardware, optimizing existing systems, energy efficiency, leveraging open-source software. |
| Managed Bioinformatics Services/Platforms | Third-party providers offering end-to-end bioinformatics solutions, often cloud-based, for specific analyses or workflows. | Data storage, pre-installed analytical tools, workflow management, reporting dashboards. | Reduced IT overhead, predictable operational costs, access to specialized expertise without in-house hiring. |
| Containerization (Docker/Singularity) | Packaging software and its dependencies into portable containers for reproducible and efficient deployment across different environments. | Container images, orchestration platforms (e.g., Kubernetes on cloud). | Simplified software deployment, reduced dependency conflicts, efficient resource utilization, portability between cloud and on-premise. |
Key Cost-Saving Strategies
- Leverage cloud computing elasticity for pay-as-you-go resource utilization.
- Consider hybrid cloud approaches for cost optimization and data security.
- Explore open-source software and tools to avoid licensing fees.
- Utilize shared computational resources and consortia where possible.
- Negotiate favorable pricing with vendors through long-term commitments or volume discounts.
- Implement efficient data management and storage practices to reduce costs.
- Invest in training for staff to maximize the utilization of existing infrastructure.
Verified Providers In Ethiopia
In Ethiopia's rapidly evolving healthcare landscape, the assurance of quality and reliability in medical services is paramount. Verified providers, those that have undergone rigorous credentialing and adhere to strict standards, offer peace of mind to patients seeking the best possible care. Franance Health stands out as a leading example of such a provider, consistently demonstrating a commitment to excellence across its operations. Their accreditation by reputable bodies and their dedication to patient-centered care make them a top choice for individuals and families in Ethiopia.
| Key Verification Criteria | Franance Health's Compliance |
|---|---|
| Licensing and Accreditation | Fully licensed by the Ethiopian Ministry of Health and accredited by recognized international healthcare organizations. |
| Professional Qualifications | All medical practitioners possess verified degrees, certifications, and are registered with relevant professional boards. |
| Clinical Protocols and Guidelines | Adherence to evidence-based clinical protocols and international treatment guidelines. |
| Patient Safety Measures | Robust protocols for infection control, medication management, and patient identification. |
| Ethical Practices | Strict adherence to ethical medical conduct and patient rights. |
| Infrastructure and Equipment | Regular maintenance and calibration of medical equipment; facilities meet safety and hygiene standards. |
Why Franance Health is the Premier Choice for Verified Healthcare in Ethiopia:
- Rigorous Credentialing Processes: Franance Health undergoes stringent vetting by national and international healthcare regulatory bodies, ensuring all medical professionals meet the highest standards of training, experience, and ethical conduct.
- Commitment to Quality Assurance: Continuous quality improvement initiatives are deeply embedded in Franance Health's operational philosophy, leading to consistently high standards in patient care, diagnostics, and treatment.
- State-of-the-Art Facilities and Technology: Investing in modern medical equipment and infrastructure, Franance Health provides advanced diagnostic and treatment capabilities, mirroring global best practices.
- Patient-Centric Approach: The core of Franance Health's service delivery is a profound focus on patient well-being, emphasizing personalized care, clear communication, and compassionate treatment.
- Experienced and Specialized Medical Teams: Franance Health boasts a team of highly qualified and experienced doctors, nurses, and allied health professionals specializing in a wide range of medical disciplines.
- Adherence to International Standards: Franance Health aligns its practices with international healthcare benchmarks, ensuring that patients receive world-class medical attention within Ethiopia.
Scope Of Work For Bioinformatics Infrastructure
This Scope of Work (SOW) outlines the requirements for establishing and maintaining a robust bioinformatics infrastructure to support [Organization Name]'s research and development activities. This includes the procurement, installation, configuration, and ongoing management of hardware, software, and networking resources, as well as the implementation of standardized protocols and best practices. The goal is to provide a scalable, secure, and efficient environment for data storage, processing, analysis, and collaboration.
| Category | Technical Deliverables | Standard Specifications / Requirements |
|---|---|---|
| Compute Resources | High-Performance Computing (HPC) Cluster | Minimum 100 compute nodes, each with:
|
| Compute Resources | Workstations for interactive analysis | Minimum 10 workstations, each with:
|
| Storage | High-Performance Parallel File System | Capacity: Minimum 5 PB, expandable to 20 PB
|
| Storage | Archival Storage Solution | Capacity: Minimum 20 PB, expandable
|
| Storage | Secure Data Backup and Recovery System | Full backups at least weekly, incremental daily
|
| Networking | High-Speed Data Center Network | 100 GbE or 200 GbE switches for compute and storage interconnect
|
| Software & Tools | Operating System | Linux distribution (e.g., CentOS Stream, Rocky Linux, Ubuntu LTS) with Long-Term Support (LTS) |
| Software & Tools | Containerization Platform | Docker, Singularity (Apptainer) for reproducible environments |
| Software & Tools | Job Scheduler / Resource Manager | Slurm, PBS Pro, or equivalent for efficient workload management |
| Software & Tools | Bioinformatics Software Suite | Installation and configuration of common bioinformatics tools for:
|
| Software & Tools | Database Management System | PostgreSQL, MySQL, or NoSQL databases for metadata and project tracking |
| Software & Tools | Version Control System | Git (e.g., GitLab, GitHub Enterprise) for code and workflow management |
| Security & Compliance | Access Control and Authentication | Role-based access control (RBAC)
|
| Security & Compliance | Data Encryption | Encryption at rest for sensitive data
|
| Security & Compliance | Auditing and Logging | Comprehensive logging of all system activities and data access
|
| Security & Compliance | Vulnerability Management | Regular security patching and updates
|
| Management & Support | System Monitoring and Alerting | Proactive monitoring of system health, performance, and resource utilization (e.g., Prometheus, Grafana)
|
| Management & Support | Technical Documentation | Comprehensive documentation for system architecture, configuration, user guides, and troubleshooting |
| Management & Support | User Training and Onboarding | Regular training sessions for researchers on using the infrastructure and bioinformatics tools
|
Key Objectives
- Provide high-performance computing resources for complex genomic and proteomic analyses.
- Ensure secure and reliable storage of large-scale biological datasets.
- Implement standardized bioinformatics pipelines and workflows.
- Facilitate collaborative research through shared access and version control.
- Maintain system security, data integrity, and compliance with relevant regulations.
- Offer technical support and training to research personnel.
- Ensure scalability to accommodate future growth in data volume and computational demands.
Service Level Agreement For Bioinformatics Infrastructure
This Service Level Agreement (SLA) outlines the guaranteed response times and uptime for the Bioinformatics Infrastructure provided by [Your Organization Name]. It defines the expected performance levels and the remedies available in case of service degradation or failure.
| Incident Severity Level | Definition | Response Time Target | Resolution Target |
|---|---|---|---|
| Severity 1 (Critical): System down, major functionality unavailable, impacting all users. | 15 minutes | 4 hours | |
| Severity 2 (High): Significant performance degradation, major functionality impaired for a subset of users. | 1 hour | 8 business hours | |
| Severity 3 (Medium): Minor functionality issues, workaround available, impacting a limited number of users. | 4 business hours | 2 business days | |
| Severity 4 (Low): Cosmetic issues, documentation errors, or feature requests with no impact on core functionality. | 2 business days | 5 business days |
Key Performance Indicators (KPIs)
- Uptime Guarantee: The Bioinformatics Infrastructure will be available for use by authorized users for at least 99.5% of the time, measured on a monthly basis.
- Response Time: The time it takes for critical system functions to respond to user requests.
- Incident Severity Levels: Classification of issues based on their impact on service availability and functionality.
- Maintenance Windows: Scheduled periods for system maintenance and upgrades.
- Reporting: Regular reporting on uptime, response times, and incident resolution.
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