“…Fármacos broncodilatadores y antiinfl amatorios en el asma y la enfermedad pulmonar obstructiva crónica I. SANGRE 44. Fármacos antianémicos. Factores de crecimiento hemopoyético. 45. …”

Tabla de Contenidos: “…2.6 Continuous-time ΣΔ Modulators: Architecture and Basic Concepts 64 -- 2.6.1 An Intuitive Analysis of CT-ΣΔMs 66 -- 2.6.2 Some Words about Alias Rejection in CT-ΣΔMs 69 -- 2.7 DT-CT Transformation of ΣΔMs 70 -- 2.7.1 The Impulse-invariant Transformation 70 -- 2.7.2 DT-CT Transformation of a Second-order ΣΔM 72 -- 2.8 Direct Synthesis of CT-ΣΔMs 74 -- 2.9 Summary 76 -- References 76 -- 3 Circuit Errors in Switched-capacitor 𝚺𝚫 Modulators 83 -- 3.1 Overview of Nonidealities in Switched-capacitor ΣΔ Modulators 84 -- 3.2 Finite Amplifier Gain in SC-ΣΔMs 86 -- 3.3 Capacitor Mismatch in SC-ΣΔMs 90 -- 3.4 Integrator Settling Error in SC-ΣΔMs 91 -- 3.4.1 Behavioral Model for the Integrator Settling 91 -- 3.4.2 Linear Effect of Finite Amplifier Gain-Bandwidth Product 95 -- 3.4.3 Nonlinear Effect of Finite Amplifier Slew Rate 98 -- 3.4.4 Effect of Finite Switch On-resistance 100 -- 3.5 Circuit Noise in SC-ΣΔMs 101 -- 3.6 Clock Jitter in SC-ΣΔMs 105 -- 3.7 Sources of Distortion in SC-ΣΔMs 107 -- 3.7.1 Nonlinear Amplifier Gain 107 -- 3.7.2 Nonlinear Switch On-Resistance 109 -- 3.8 Case Study: High-level Sizing of a ΣΔM 111 -- 3.8.1 Ideal Modulator Performance 111 -- 3.8.2 Noise Leakages 112 -- 3.8.3 Circuit Noise 115 -- 3.8.4 Settling Error 116 -- 3.8.5 Overall High-Level Sizing and Noise Budget 117 -- 3.9 Summary 119 -- References 119 -- 4 Circuit Errors and Compensation Techniques in Continuous-time 𝚺𝚫 Modulators 123 -- 4.1 Overview of Nonidealities in Continuous-time ΣΔ Modulators 123 -- 4.2 CT Integrators and Resonators 124 -- 4.3 Finite Amplifier Gain in CT-ΣΔMs 126 -- 4.4 Time-constant Error in CT-ΣΔMs 128 -- 4.5 Finite Integrator Dynamics in CT-ΣΔMs 130 -- 4.5.1 Effect of Finite Gain-Bandwidth Product on CT-ΣΔMs 131.…”

“…An estimated 5.7 percent (95% CI 4.4 to 7.1) of all ED visits had at least one diagnostic error. …”

“…Lessons Covered Include: 1.0 Introduction to the AWS Certified Data Analytics (DAS-C01) - Specialty-2023 1.1 technology prerequisite 1.2 sagemaker studio lab 1.3 learn aws cloudshell 1.4 cloud developer workspace advantage 1.5 prototyping ai apis aws cloudshell bash 1.6 cloud9 with codewhisperer Learning Objectives Domain 1: Collection Determine the operational characteristics of the collection system Select a collection system that handles the frequency, volume, and source of data Select a collection system that addresses the key properties of data, such as order, format, and compression 1.0 Introduction to the AWS Certified Data Analytics (DAS-C01) - Specialty-2023 1.1 technology prerequisite 1.2 sagemaker studio lab 1.3 learn aws cloudshell 1.4 cloud developer workspace advantage 1.5 prototyping ai apis aws cloudshell bash 1.6 cloud9 with codewhisperer 1.7 operationalizing collection system 1.11 job styles batch vs streaming 1.12 data ingestion pipelines 1.13 aws batch demo 1.14 step function demo 1.15 transform data in transit 1.16 handle ml specific map reduce 1.17 install rust cloud9 1.18 build aws rust s3 size calculator Domain 2: Storage and Data Management Determine the operational characteristics of the storage solution for analytics Determine data access and retrieval patterns Select the appropriate data layout, schema, structure, and format Define data lifecycle based on usage patterns and business requirements Determine the appropriate system for cataloging data and managing metadata 2.0 domain intro 2.2 one size database 2.3 serverless data engineering 2.4 provisioning ebs 2.5 retrain models 2.6 use s3 storage 2.7 big data challenges 2.8 build systems tools with rust deduplication Domain 3: Processing Determine appropriate data processing solution requirements Design a solution for transforming and preparing data for analysis Automate and operationalize data processing solutions 3.0 domain intro 3.1 kubernetes key concepts 3.2 kubernetes clust 3.3 kubernetes pods nodes 3.4 services deployments 3.5 running minikube 3.6 minikube fastapi kubernetes 3.7 building tiny container 3.8 aws api app runner 3.9 pytorch fastapi deploy app runner 3.10 aws app runner csharp 3.11 options container orchestration 3.12 AWS ECS Fargate Dotnet Microservice 3.1* 3 load testing locust 3.14 sre mindset mlops 3.15 compute choices 3.16 provisioning ec2 Domain 4: Analysis and Visualization Determine the operational characteristics of the analysis and visualization solution Select the appropriate data analysis solution for a given scenario Select the appropriate data visualization solution for a given scenario 4.0 domain intro 4.1 cleanup data 4.2 scaling data 4.3 labeling data 4.4 mechanical turk labeling 4.5 identify extract features 4.6 feature engineering concepts 4.7 graphing data 4.9 clustering 4.11 kaggle nba quicksight 4.12 sagemaker canvas demo 4.13 train test split Domain 5: Security Select appropriate authentication and authorization mechanisms Apply data protection and encryption techniques Apply data governance and compliance controls 5.0 intro domain 5.1 security access strategy 5.2 firewall 5.5 aws trusted advisor demo 5.6 shared security model 5.7 encryption in transit rest 5.8 data protection aws 5.9 audit network 5.10 integrated security 5.11 plp lambda 5.12 analyze logs aws 5.13-conclusion Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ-900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! …”

“…: 2.40-what-is-colab.mp4 Using Bard to enhance notebook development: 2.41-using-bard-to-enhance-productivity.mp4 Exploring Life Expectency in a Notebook: 2.42-life-expectancy-eda.mp4 Load a DataFrame with sensitive data: 2.43-Load-a-DataFrame-with-sensitive-information.mp4 Using MLFlow with Databricks Notebooks: 2.44-mlops-mlflow-tracking.mp4 End to End ML with MLFlow and Databricks: 2.45-end-to-end-ml-with-mlflow-and-databricks.mp4 Comparing DataFrame Libraries between Rust and Python: 2.46-comparing-dataframe-libs-rust-python.mp4 Lesson 3: Data Engineering Libraries and Tools with Rust Parquet file writing and reading with Rust: 2.50-parquet-read-write-rust.mp4 Arrow & Parquet in Rust: 2.51-arrow-parquet-rust.mp4 Serverless functions with Rust and AWS Lambda: 2.52-serverless-rust-aws-lambda.mp4 Polars library overview: 2.53-polars-library-overview.mp4 Building RESTful APIs with Rocket: 2.54-building-restful-apis-rocket.mp4 Utilizing Async Rust in Web Development: 2.55-utilizing-async-rust-web-development.mp4 Applying Data Cleaning Techniques with Rust: 2.56-applying-data-cleaning-rust.mp4 Deploying Rust Applications in a Kubernetes Environment: 2.57-deploying-rust-apps-kubernetes.mp4 Section 4: Designing Data Processing Systems in Rust Lesson 1: Getting Started with Rust Data Pipelines (Including ETL) Jack and the Beanstalk Data Pipelines: 4.1-jack-beanstalk-building-data-pipelines.mp4 Open Source Data Engineering - Pros and Cons: 4.2-open-source-de-pro-con.mp4 Core Components of Data Engineering Pipelines: 4.3-core-components-data-engineering-pipelines.mp4 Rust AWS Step Functions Pipeline: 4.4-rust-aws-step-functions.mp4 Rust AWS Lambda Async S3 Size Calculator: 4.5-rust-async-s3-size-calculator-lambda.mp4 What is Distroless: 4.6-what-is-distroless.mp4 Demo Deploying Rust Microservices on GCP: 4.7-demo-build-deploy-rust-microservice-cloud-run.mp4 Lesson 2: Using Rust and Python for LLMs, ONNX, Hugging Face, and PyTorch Pipelines Introduction to Hugging Face Hub: 4.10-intro-hugging-face-hub.mp4 Rust PyTorch Pre-trained Model Ecosystem: 4.11-rust-pytorch-pretrained-models-ecosystem.mp4 Rust GPU Hugging Face Translator: 4.12-rust-gpu-hugging-face-translator.mp4 Rust PyTorch High-Performance Options: 4.13-high-performance-pytorch-rust-demo.mp4 Rust CUDA PyTorch Stress Test: 4.14-building-cuda-enabled-stress-test-with-rust-pytorch.mp4 EFS ONNX Rust Inference with AWS Lambda: 4.15-efs-onnx-lambda-rust-inference-mlops.mp4 Theory behind model fine-tuning: 4.16-intro-fine-tuning-theory.mp4 Doing Fine Tuning: 4.17-doing-fine-tuning.mp4 Lesson 3: Building SQL Solutions with Rust, Generative AI and Cloud Selecting the correct database on GCP: 4.20-gcp-optimize-database-solution.mp4 Rust SQLite Hugging Face Zero Shot Classifier: 4.21-rust-sqlite-hugging-face-zero-shot-classifier-demo.mp4 Prompt Engineering for BigQuery: 4.22-big-query-prompt-engineering-v3.mp4 Big Query to Colab Pipeline: 4.23-bq-colab-pipeline-v2.mp4 Exploring Data with Big Query: 4.24-exploring-data-google-bigquery-v2.mp4 Using Public Datasets for Data Science: 4.25-using-public-datasets.mp4 Querying Log files with BigQuery: 4.26-demo-big-query-log-query.mp4 There is no one size database: 4.27-one-size-database.mp4 Course Conclusion: 4.28-conclusion.mp4 Learning Objectives By the end of this Course, you will be able to: Leverage Rust's robust data structures and collections for efficient data manipulation. …”

“…El caso de Alemania 4.3. El caso de Francia 4.4. El caso de Italia 4.5. El caso de otros países 4.6. …”

“…El caso de Alemania 4.3. El caso de Francia 4.4. El caso de Italia 4.5. El caso de otros países 4.6. …”

“…The complete Certified Cloud Security Professional video course with CCSK extras by Dean Bushmiller Domain 1 Cloud Concepts, Architecture and Design 1.1 Understand cloud computing concepts Cloud computing definitions Cloud computing roles and responsibilities Key cloud computing characteristics Building block technologies 1.2 Describe cloud reference architecture Cloud computing activities Cloud service capabilities Cloud service categories IaaS, PaaS, SaaS Cloud deployment models Cloud shared considerations , auditability, regulatory, outsourcing 1.3 Understand security concepts relevant to cloud computing Cryptography and key management Identity and access control Data and media sanitization Network security Virtualization security Common threats Security hygiene 1.4 Understand design principles of secure cloud computing Cloud secure data lifecycle Cloud-based business continuity and disaster recovery plan Business impact analysis Functional security requirements Security considerations and responsibilities for different cloud categories Cloud design patterns Enterprise Architecture DevOps security 1.5 Evaluate cloud service providers Verification against criteria System/subsystem product certifications Domain 2 Cloud Data Security 2.1 Describe cloud data concepts Cloud data life cycle phases Data dispersion Data flows 2.2 Design and implement cloud data storage architectures Storage types Threats to storage types 2.3 Design and apply data security technologies and strategies Encryption and key management Hashing Data obfuscation Tokenization Data loss prevention Keys, secrets and certificates management 2.4 Implement data discovery Structured data Unstructured data Semi-structured data Data location 2.5 Plan and implement data classification Data classification policies Data mapping Data labeling 2.6 Design and implement Information Rights Management Legal hold 2.7 Design and implement auditability, traceability and accountability of data events Definition of event sources and requirement of event attributes address, geolocation Logging, storage and analysis of data events Chain of custody and non repudiation Domain 3 Cloud Platform and Infrastructure Security 3.1 Comprehend cloud infrastructure and platform components Physical environment Network and communications Compute Virtualization Storage Management plane 3.2 Design a secure data center Logical design Physical design Environmental design Design resilient 3.3 Analyze risks associated with cloud infrastructure and platforms Risk assessment Cloud vulnerabilities, threats and attacks Risk mitigation strategies 3.4 Plan and implementation of security controls Physical and environmental protection System, storage and communication protection Identification, authentication and authorization in cloud environments Audit mechanisms correlation, packet capture 3.5 Plan business continuity and disaster recovery Business continuity and disaster recovery strategies Business requirements , Recovery Point Objective Creation, implementation and testing of plan Domain 4 Cloud Application Security 4.1 Advocate training and awareness for application security Cloud development basics Common pitfalls Common cloud vulnerabilities OWASP Top 10 4.2 Describe the Secure Software Development Life Cycle process Business requirements Phases and methodologies 4.3 Apply the Secure Software Development Life Cycle Cloud specific risks Threat modeling STRIDE and DREAD Avoid common vulnerabilities during development Secure coding Application Security Verification Standard Software configuration management and versioning 4.4 Apply cloud software assurance and validation Functional and non functional testing Security testing methodologies SAST DAST Quality assurance Abuse case testing 4.5 Use verified secure software Securing application programming interfaces Supply chain management Third party software management Validated open source software 4.6 Comprehend the specifics of cloud application architecture Supplemental security components , Database Activity Monitoring, Extensible Markup Language firewalls, application programming interface gateway Cryptography Sandboxing Application virtualization and orchestration 4.7 Design appropriate identity and access management solutions Federated identity Identity providers Single sign on Multi factor authentication Cloud access security broker Secrets management Domain 5 Cloud Security Operations 5.1 Build and implement physical and logical infrastructure for cloud environment Hardware specific security configuration requirements and Trusted Platform Module Installation and configuration of management tools Virtual hardware specific security configuration requirements , Hypervisor types Installation of guest operating system virtualization toolsets 5.2 Operate and maintain physical and logical infrastructure for cloud environment Access controls for local and remote access , secure terminal access, Secure Shell, console based access mechanisms, jumpboxes, virtual client Secure network configuration , Transport Layer Security, Dynamic Host Configuration Protocol, Domain Name System Security Extensions, virtual private network Network security controls , intrusion prevention systems, honeypots, vulnerability assessments, network security groups, bastion host Operating system hardening through the application of baselines, monitoring and remediation Patch management Infrastructure as Code strategy Availability of clustered hosts Availability of guest operating system Performance and capacity monitoring Hardware monitoring Configuration of host and guest operating system backup and restore functions Management plane 5.3 Implement operational controls and standards Change management Continuity management Information security management Continual service improvement management Incident management Problem management Release management Deployment management Configuration management Service level management Availability management Capacity management 5.4 Support digital forensics Forensic data collection methodologies Evidence management Collect, acquire, and preserve digital evidence 5.5 Manage communication with relevant parties Vendors Customers Partners Regulators Other stakeholders 5.6 Manage security operations Security operations center Intelligent monitoring of security controls , intrusion prevention systems, honeypots, network security groups, artificial intelligence Log capture and analysis , log management Incident management Vulnerability assessments Domain 6 Legal, Risk and Compliance 6.1 Articulate legal requirements and unique risks within the cloud environment Conflicting international legislation Evaluation of legal risks specific to cloud computing Legal framework and guidelines eDiscovery Forensics requirements 6.2 Understand privacy issues Difference between contractual and regulated private data , personally identifiable information Country specific legislation related to private data , personally identifiable information Jurisdictional differences in data privacy Standard privacy requirements Privacy Impact Assessments 6.3 Understand audit process, methodologies, and required adaptations for a cloud environment Internal and external audit controls Impact of audit requirements Identify assurance challenges of virtualization and cloud Types of audit reports Restrictions of audit scope statements Gap analysis Audit planning Internal information security management system Internal information security controls system Policies Identification and involvement of relevant stakeholders Specialized compliance requirements for highly regulated industries Impact of distributed information technology model 6.4 Understand implications of cloud to enterprise risk management Assess providers risk management programs Difference between data owner/controller vs. data custodian/processor Regulatory transparency requirements , General Data Protection Regulation Risk treatment Different risk frameworks Metrics for risk management Assessment of risk environment 6.5 Understand outsourcing and cloud contract design Business requirements , master service agreement, statement of work Vendor management Contract management Supply chain management…”

“…Es van estudiar 135 subjectes (78 homes i 57 dones), mitjana d’ edat 44,2 anys (DE=10,3), majoritàriament vivien en ciutats, la meitat eren solters, el 41,5% tenien estudis universitaris i el 60% no treballaven. …”
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Tabla de Contenidos: “….-- En Madrid : en la imprenta de Pedro Marin, 1775. [2], 44 p., [5] h. ; Fol. Certifica la copia Antonio Martinez Salazar. …”

“…En relació amb el grup telefònic, l'estimació crua d'OR per a l'abstinència a les 52 setmanes va ser de 1,44; IC95%, [1,2-2,7] i de 1,39; IC95%, [1,01-2,2] per al grup semipresencial i el presencial respectivament. …”
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