El TDAH es uno de los trastornos del comportamiento infantil más controvertidos del momento. Lejos ya de su uso clasificatorio en psicopatología, ha adquirido el poder de nombrar al malestar principal de la infancia y la adolescencia y, por si eso fuera poco, ahora se está extendiendo a la edad adulta. En esta obra, de forma monográfica, se hace un recorrido por todos los estudios llevados a cabo por diferentes autores sobre los factores que pueden dar origen al TDAH, su evaluación e intervención en el entorno clínico, escolar y familiar, y su tratamiento tanto psicológico como con el uso de fármacos. Su objetivo es mostrar una visión global de lo que hoy se sabe o, mejor dicho, no se sabe del TDAH. Se puede decir que la obra es un pequeño tratado con información de gran interés y utilidad para todos aquellos que quieran conocer el inicio y desarrollo de la ciencia en el campo del TDAH.

Illinois 2021 Rules of the Road handbook, drive safe!

Applied Biomechatronics Using Mathematical Models provides an appropriate methodology to detect and measure diseases and injuries relating to human kinematics and kinetics. It features mathematical models that, when applied to engineering principles and techniques in the medical field, can be used in assistive devices that work with bodily signals. The use of data in the kinematics and kinetics analysis of the human body, including musculoskeletal kinetics and joints and their relationship to the central nervous system (CNS) is covered, helping users understand how the complex network of symbiotic systems in the skeletal and muscular system work together to allow movement controlled by the CNS. With the use of appropriate electronic sensors at specific areas connected to bio-instruments, we can obtain enough information to create a mathematical model for assistive devices by analyzing the kinematics and kinetics of the human body. The mathematical models developed in this book can provide more effective devices for use in aiding and improving the function of the body in relation to a variety of injuries and diseases. - Focuses on the mathematical modeling of human kinematics and kinetics - Teaches users how to obtain faster results with these mathematical models - Includes a companion website with additional content that presents MATLAB examples

This book reviews and analyzes what is known about metacognitive processes in relation to language. Each of its seven chapters deals systematically with the relationship between the comprehension and production of the phonetic, syntactic, semantic, pragmatic, and textual aspects of language. This material is then related to the metacognitive principles which govern reflective awareness. A concluding chapter deals with written language and metalinguistics. --From publisher's description.

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system. There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that sends orders from the central nervous system (CNS) through the peripheral nervous systems (PNS) to do tasks using the musculoskeletal system. These actions can be detected by many Bioinstruments (Biomedical Instruments) and cognitive device data, allowing us to apply AI using Machine Learning-Deep Learning-Cognitive Computing models through algorithms to analyze, detect, classify, and forecast the process of various illnesses, diseases, and injuries of the human body. Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models provides readers with the study of injuries, illness, and neurological diseases of the human body through Artificial Intelligence using Machine Learning (ML), Deep Learning (DL) and Cognitive Computing (CC) models based on algorithms developed with MATLAB® and IBM Watson®. Provides an introduction to Cognitive science, cognitive computing and human cognitive relation to help in the solution of AI Biomedical engineering problems Explain different Artificial Intelligence (AI) including evolutionary algorithms to emulate natural evolution, reinforced learning, Artificial Neural Network (ANN) type and cognitive learning and to obtain many AI models for Biomedical Engineering problems Includes coverage of the evolution Artificial Intelligence through Machine Learning (ML), Deep Learning (DL), Cognitive Computing (CC) using MATLAB® as a programming language with many add-on MATLAB® toolboxes, and AI based commercial products cloud services as: IBM (Cognitive Computing, IBM Watson®, IBM Watson Studio®, IBM Watson Studio Visual Recognition®), and others Provides the necessary tools to accelerate obtaining results for the analysis of injuries, illness, and neurologic diseases that can be detected through the static, kinetics and kinematics, and natural body language data and medical imaging techniques applying AI using ML-DL-CC algorithms with the objective of obtaining appropriate conclusions to create solutions that improve the quality of life of patients

This book documents and disseminates experiences from a wide range of universities, across the five continents, which showcase how the principles of sustainable development may be incorporated as part of university programmes, and present transformatory projects and programmes, showing how sustainability can be implemented across disciplines. Sustainability in a higher education context is a fast growing field. Thousands of universities across the world have signed declarations or have committed themselves to integrate the principles of sustainable development in their activities: teaching, research and extension, and many more will follow.