“…Again, putting these figures in perspective, each birth cohort in these age groups consists of around 44 000 women. If all are invited to yearly screening when they are 40 years old, ca. 572 will be diagnosed with cancer over 13 years. …”

“…Pearson Test Prep online system requirements: Browsers: Chrome version 73 and above, Safari version 12 and above, Microsoft Edge 44 and above. Devices: Desktop and laptop computers, tablets running on Android v8.0 and above and iOS v13 and above, smartphones with a minimum screen size of 4.7. …”

“…This official study guide helps you master all the topics on the CCNP and CCIE Security Core SCOR 350-701 exam, including Network security Cloud security Content security Endpoint protection and detection Secure network access Visibility and enforcement Companion Website: The companion website contains more than 200 unique practice exam questions, practice exercises, and a study planner Pearson Test Prep online system requirements: Browsers: Chrome version 73 and above, Safari version 12 and above, Microsoft Edge 44 and above. Devices: Desktop and laptop computers, tablets running Android v8.0 and above or iPadOS v13 and above, smartphones running Android v8.0 and above or iOS v13 and above with a minimum screen size of 4.7. …”

“…Le Vatican est tout à la fois récent (il n'apparaît qu'en 1870 et n'est reconnu comme Etat souverain qu'en 1929) et séculaire (il est fondé, au sens propre comme au sens figuré, sur le tombeau de l'apôtre Pierre, compagnon du Christ) ; petit (44 ha) et immense (son rayonnement est planétaire) ; réservé à quelques privilégiés (seulement 3 000 personnes y travaillent) et la patrie spirituelle de foules innombrables (plus d'un milliard de fidèles) ; solennel (les cérémonies les plus grandioses y sont célébrées) et prosaïque (on y fait la cuisine, on y entretient plusieurs dizaines de voitures, on y regarde le Calcio) ; un foyer d'héroïsme (la plupart des papes qui y ont résidé ont été béatifiés) et un nid d'intrigues dont certaines, impliquant les officines italiennes les plus douteuses, ont défrayé la chronique. …”

Tabla de Contenidos: “…DEL AJUSTE POR INFLACIÓN 44. Determinación del ajuste por inflación 45. Concepto de créditos 46. …”

Tabla de Contenidos: “…Martínez y Nuria Calavia. UAM. -- 4.4.Radiografía psicológica de un campeón de Judo. …”

Tabla de Contenidos: “…La España de las autonomías. 2 vols. (2007). -- t. 44. Atlas de historia de España (2007)…”

“…De un lado, el análisis del entramado jurídico que hay en su entorno, comenzando con una exhaustiva referencia al panorama legislativo español con el R.D. 1309/2005, de 4 de noviembre, por el que se aprueba el Reglamento de la Ley de Instituciones de Inversión Colectiva (IICs) y las previsiones de sus artículos 43 (sobre las IICs de Inversión Libre) y 44 (sobre las IICs de IICs de Inversión Libre), así como la Orden MEyH 1199/2006, de 25 de abril y la Circular 1/2006, de 3 de Mayo, de la CNMV, ambas normas de desarrollo, menores en su jerarquía técnica, pero de gran calado en su contenido como piezas claves para conocer su funcionamiento, estructura y limitaciones. …”
Acceso al texto completo en Aranzadi

“…The inadequacy of the national climate change regulatory framework in relation to indigenous peoples’ lands: A human rights framework as a regional response Introduction Legal basis for the application of a regional human rights framework Assessing national regulatory frameworks in the context of a regional human rights framework 3.1 Incompatibility of national climate regulatory framework with obligations of states 3.2 Threat to a range of rights The regional climate change regulatory framework and potential for human rights 4.1 Committee of African Heads of State and Government on Climate Change 4.2 African Ministerial Conference on the Environment 4.3 Climate for Development in Africa (ClimDev-Africa) Programme 4.4 African Union Commission 4.5 New Partnership for African Development 4.6 Pan-African Parliament 4.7 Peace and Security Council Potentials in regional human rights mechanisms with focus on the Commission 5.1 Promotional functions 5.2 Protective mandate 5.3 Interpretive functions 5.4 Assembly-entrusted tasks Conclusion 7. …”

“…El primer estudi analitzà i va comparar la correlació entre la Tsk i les variables cardio-respiratòries en homes corredors de fons amb una alta condició física (HF) (n= 35; VO2peak = 56.62 ± 4.31 ml/kg/min) i amb una condició física moderada (MF) (n = 44; VO2peak = 47.86 ± 5.29 ml/kg/min) durant un test incremental amb períodes de 2 minuts fins l’ esgotament, seguit d’un període de recuperació de 5 minuts. …”
Accés lliure

“…Domain 1: Data Engineering 1.0 course intro 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 domain one intro 1.8 data storage 1.9 determine storage medium 1.10 using s3 demo 1.11 job styles batch vs streaming 1.12 data ingestion pipelines 1.13 aws batch demo 1.14 step function demo Domain 2: Exploratory Data Analysis 2.0 domain intro Sanitize and prepare data for modeling 2.1 cleanup data 2.2 scaling data 2.3 labeling data 2.4 mechanical turk labeling Perform feature engineering 2.5 identify extract features 2.6 feature engineering concepts Analyze and visualize data for machine learning 2.7 graphing data 2.9 clustering Conclusion 2.10 conclusion Domain 3: Modeling 3.0 domain intro Frame business problems as machine learning problems 3.1 when to use ml 3.2 supervised vs unsupervized 3.3 selection right ml solution Select the appropriate model(s) for a given machine learning problem 3.4 select models 3.5 sagemaker canvas demo Train machine learning models 3.6 train test split 3.7 optimization 3.8 compute choice Perform hyperparameter optimization 3.14 neural network architecture Evaluate machine learning models 3.18 overfitting vs underfitting 3.19 selecting metrics 3.22 compare models experiment tracking Conclusion 3.23 Conclusion Domain 4: Machine Learning Implementation and Operations 4.0 course intro Build machine learning solutions for performance, availability, scalability, resiliency, and fault 4.1 logging monitoring 4.2 multiple regions 4.3 reproducible workflow 4.4 aws flavored devops Recommend and implement the appropriate machine learning services and features for a given 4.5 provisioning ec2 4.5 compute choices 4.6 provisioning ebs 4.7 aws ai ml services Apply basic AWS security practices to machine learning solutions. 4.9 plp aws lambda 4.10 integrated security Deploy and operationalize machine learning solutions 4.13 sagemaker workflow 4.14 doing predictions with sagemaker canvas 4.16 retrain models Conclusion 5.0 course conclusion Topics Covered Include: Domain 1: Data Engineering Domain 2: Exploratory Data Analysis Domain 3: Modeling Domain 4: Machine Learning Implementation and Operations 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! …”

“…Els menors que mostraven dificultats en el desenvolupament emocional foren el 14,2% i un 44% els que presentaven retard en l'àrea del llenguatge. …”
Accés lliure

“…Compared with baseline, online PM was associated with a statistically significant decrease in the ZBI score (SE, −3.44; CI, −6.31 to −0.57; P = .002) with no HTE from any of the demographic variables. …”

“…Lessons Covered Include: Domain 1: Threat Detection and Incident Response 1.0 Introduction 1.1 Designing and Implementing Incident Response Plans 1.2 Detecting Security Threats and Anomalies with AWS Services 1.3 Responding to Compromised Resources and Workloads 1.4 Automating Incident Response with AWS Lambda 1.5 Conducting Root Cause Analysis with Amazon Detective 1.6 Capturing Forensics Data from Compromised Resources 1.7 Querying Logs to Validate Security Events 1.8 Preserving Forensic Artifacts with S3 Object Lock 1.9 Preparing and Recovering Services After Incidents 1.10 Incident Response Case Study 1.11 Practice Exam - Threat Detection and Response 1.12 Threat Detection and Incident Response Summary Learning Objectives Understand best practices for incident response in the cloud Explore AWS services to detect security threats Learn how to respond to compromised resources Domain 2: Security Logging and Monitoring 2.0 Introduction 2.1 Designing and Implementing Monitoring and Alerting 2.2 Troubleshooting Security Monitoring and Alerting 2.3 Designing and Implementing Logging Solutions 2.4 Troubleshooting Logging Solutions 2.5 Designing Log Analysis Solutions 2.6 Configuring AWS CloudTrail for Logging 2.7 Analyzing Logs with Amazon Athena 2.8 Monitoring Case Study 2.9 Practice Exam - Logging and Monitoring 2.10 Optimizing Log Storage Lifecycles 2.11 Third Party Log Analysis Tools 2.12 Security Logging and Monitoring Summary Learning Objectives Understand how to set up monitoring and alerts for security Learn best practices for logging and log analysis Gain skills in troubleshooting logging and monitoring Domain 3: Infrastructure Security 3.0 Introduction 3.1 Designing and Implementing Edge Service Security 3.2 Designing and Implementing Network Security 3.3 Designing and Securing Compute Workloads 3.4 Troubleshooting Network Security 3.5 Securing EC2 Instances with SSM 3.6 Scanning Images for Vulnerabilities 3.7 Infrastructure Security Case Study 3.8 Practice Exam - Infrastructure Security 3.9 Integrating AWS Firewall Manager 3.10 Applying Security Best Practices to Lambdas 3.11 Hardening AMIs with EC2 Image Builder 3.12 Infrastructure Security Summary Learning Objectives Learn how to secure AWS network infrastructure Understand options for compute and workload security Gain skills in troubleshooting infrastructure issues Domain 4: Identity and Access Management 4.0 Introduction 4.1 Designing Authentication for AWS Resources 4.2 Designing Authorization for AWS Resources 4.3 Troubleshooting with IAM Access Analyzer 4.4 Enforcing Least Privilege Access 4.5 Separating Duties with IAM Roles 4.6 Identity and Access Management Case Study 4.7 Practice Exam - Identity and Access Management 4.8 Securing Root User Credentials 4.9 IAM Policy Simulator for Troubleshooting 4.10 Enabling Federated Access with SSO 4.11 Managing Credentials and Secrets 4.12 Identity and Access Management Summary Learning Objectives Master IAM best practices for authentication and authorization Understand how to apply least privilege and separation of duties Learn to troubleshoot IAM issues Domain 5: Data Protection 5.0 Introduction 5.1 Data in Transit Confidentiality and Integrity 5.2 Data at Rest Confidentiality and Integrity 5.3 Managing Data at Rest Lifecycles 5.4 Protecting Credentials, Secrets, and Keys 5.5 Encrypting Data with AWS KMS 5.6 Data Protection Case Study 5.7 Practice Exam - Data Protection 5.8 Enforcing Data Retention with Glacier 5.9 Preventing Data Deletion with S3 Object Lock 5.10 Rotating RDS Credentials 5.11 Encrypting Data in Transit with SSL/TLS 5.12 Data Protection Summary Learning Objectives Learn techniques to protect data in transit and at rest Understand how to manage data lifecycles Gain skills in managing credentials and secrets Domain 6: Management and Security Governance 6.0 Introduction 6.1 Strategies for Central Account Deployment 6.2 Secure and Consistent Cloud Deployment 6.3 Evaluating Compliance of AWS Resources 6.4 Identifying Security Gaps through Reviews and Cost 6.5 AWS Organizations SCP Best Practices 6.6 Governance Case Study 6.7 Practice Exam - Governance 6.8 Automating Security Deployments 6.9 Tagging Resources for Governance 6.10 AWS Config for Security Assessments 6.11 AWS Well Architected Tool 6.12 Governance and Security Management Summary Learning Objectives Understand best practices for governing accounts and resources Learn how to align security with organizational requirements Gain skills in compliance, auditing, and deployment Additional Popular Resources Assimilate OpenAI 52 Weeks of AWS-The Complete Series Microsoft Azure Fundamentals (AZ-900) Certification AWS Solutions Architect Professional (SAP-C02) 2023 Assimilate Python From Zero…”

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

“…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! …”

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.…”

“…: 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. …”