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This practical guide to the use of radiotherapy for the treatment of sarcomas and skin cancers covers a wide range of disease scenarios, identifying which treatment techniques are applicable in particular clinical circumstances. Among the conditions considered are extremity soft tissue sarcomas, retroperitoneal soft tissue sarcomas, bone sarcomas, uterine sarcomas, chordomas, pediatric sarcomas, squamous cell carcinomas, basal cell carcinomas, melanomas, Merkel cell carcinomas, and cutaneous lymphomas. Detailed attention is devoted to the issues and considerations of relevance in everyday practice when treating these diseases. The use of multiple radiotherapy techniques and procedures, including IMRT, brachytherapy, radiosurgery, and particle therapy, is fully explained, and the role of radiotherapy in combination with chemotherapy and emerging therapeutics such as immunotherapy and biologic anticancer agents is also addressed. The book will be of high value for practicing radiationoncologists, medical and surgical oncologists, medical physicists, medical dosimetrists, trainees, and other medical professionals.

This classroom-tested textbook is an innovative, comprehensive, and forward-looking introductory undergraduate physics course. While it clearly explains physical principles and equips the student with a full range of quantitative tools and methods, the material is firmly grounded in biological relevance and is brought to life with plenty of biological examples throughout.It is designed to be a self-contained text for a two-semester sequence of introductory physics for biology and premedical students, covering kinematics and Newton¿s laws, energy, probability, diffusion, rates of change, statistical mechanics, fluids, vibrations, waves, electromagnetism, and optics. Each chapter begins with learning goals, and concludes with a summary of core competencies, allowing for seamless incorporation into the classroom. In addition, each chapter is replete with a wide selection of creative and often surprising examples, activities, computational tasks, and exercises, many of which are inspired by current research topics, making cutting-edge biological physics accessible to the student.

This book provides a detailed technical overview of the use and applications of artificial intelligence (AI), machine learning and big data in cardiology. Recent technological advancements in these fields mean that there is significant gain to be had in applying these methodologies into day-to-day clinical practice. Chapters feature detailed technical reviews and highlight key current challenges and limitations, along with the available techniques to address them for each topic covered. Sample data sets are also included to provide hands-on tutorials for readers using Python-based Jupyter notebooks, and are based upon real-world examples to ensure the reader can develop their confidence in applying these techniques to solve everyday clinical problems.Artificial Intelligence and Big Data in Cardiology systematically describes and technically reviews the latest applications of AI and big data within cardiology. It is ideal for use by the trainee and practicing cardiologist and informatician seeking an up-to-date resource on the topic with which to aid them in developing a thorough understanding of both basic concepts and recent advances in the field.

This work is a textbook on Mathematical Analysis written by expert lecturers in the field. This textbook, other than the classical differentiation and integration tools for functions of several real variables, metric spaces, ordinary differential equations, implicit function and so on, also provides opportunities to go deeper into certain topics: among them, the Ascoli-Arzelà theorem, the regularity of convex functions in R^n, L^p spaces and absolutely continuous functions, all topics that are paramount in modern Mathematical Analysis. Other instances include the Weierstrass theorem on polynomial approximation of continuous functions or Peano's existence theorem (typically only existence, without uniqueness) for nonlinear ODEs and systems under general assumptions.The content is discussed in an elementary way and, at a successive stage, some topics are examined from several, more penetrating, angles. The agile organization of the subject matter helps instructors to effortlesslydetermine which parts to present during lectures and where to stop. The authors believe that any textbook can contribute to the success of a lecture course only to a point, and the choices made by lecturers are decisive in this respect.The book is addressed to graduate or undergraduate honors students in Mathematics, Physics, Astronomy, Computer Science, Statistics and Probability, attending Mathematical Analysis courses at the Faculties of Science, Engineering, Economics and Architecture.

This definitive guide to Machine Learning projects answers the problems an aspiring or experienced data scientist frequently has: Confused on what technology to use for your ML development? Should I use GOFAI, ANN/DNN or Transfer Learning? Can I rely on AutoML for model development? What if the client provides me Gig and Terabytes of data for developing analytic models? How do I handle high-frequency dynamic datasets? This book provides the practitioner with a consolidation of the entire data science process in a single ¿Cheat Sheet¿.The challenge for a data scientist is to extract meaningful information from huge datasets that will help to create better strategies for businesses. Many Machine Learning algorithms and Neural Networks are designed to do analytics on such datasets. For a data scientist, it is a daunting decision as to which algorithm to use for a given dataset. Although there is no single answer to this question, a systematic approach to problem solving is necessary. This book describes the various ML algorithms conceptually and defines/discusses a process in the selection of ML/DL models. The consolidation of available algorithms and techniques for designing efficient ML models is the key aspect of this book. Thinking Data Science will help practising data scientists, academicians, researchers, and students who want to build ML models using the appropriate algorithms and architectures, whether the data be small or big.

This book also provides high-level summaries of several related learning problems such as one-class classification, anomaly detection, and noisy learning and their relation to PU learning.

MicroRNAs (miRNAs) are a member of the family of non-coding RNA molecules, and consist of small conserved sequences between 19-25 nucleotides in length that are responsible for regulating many cellular functions by affecting a wide range of messenger RNAs in a sequence specific manner.

This book introduces complex analysis and is appropriate for a first course in the subject at typically the third-year University level. Throughout the text an emphasis is placed on geometric properties of complex numbers and visualization of complex mappings.

Transfer learning (TL), and in particular domain adaptation (DA), has emerged as an effective solution to overcome the burden of annotation, exploiting the unlabeled data available from the target domain together with labeled data or pre-trained models from similar, yet different source domains.

Spatio-temporal Characteristics of Land-cover Changes in China During 2000-2019.- Analyzing Geospatial Key Factors and Predicting Bike Activity in Hamburg.- Evaluation and Pattern Optimization of Ecological Space of Chongqing with Remote Sensing Data.- Research on Calculation Model of National Fragile State Based on Climate Vulnerability.- Daily Rainfall Analysis in Indonesia using ARIMA, Neural Network and LSTM.- Development of A Geoinformation Monitoring Module for The Khankalsky Geothermal Deposit in The Chechen Republic.- Mapping Fences in Xilingol Grassland Using High Spatiotemporal Resolution Remote Sensing Data.- Comparative Study on Remote Sensing Image Classifier of Jiulong River Basin.- OSM-GAN: Using Generative Adversarial Networks for Detecting Change in High-Resolution Spatial Images.- Analysis of Urban Sprawl and Growth Pattern Using Geospatial Technologies in Megacity, Bangkok, Thailand.- WEB-GIS for Transportation System of Oran City.- Construction Method of City-level Geographic Knowledge Graph Based on Geographic Entity.- Development of Remote Sensing Software Using a Boosted Tree Machine Learning Model Architecture for Professional and Citizen Science Applications.- Fast Construction of Vegetation Polygons Based on Object-oriented Method.- A/B Testing via Continuous Integration and Continuous Delivery.- An Automated Approach for Mapping between Software Requirements and Design Items: An Industrial Case from Turkey.- Code Comprehension for Read-Copy-Update Synchronization Contexts in C Code.

This volume constitutes the proceedings of the 9th International Work-Conference on IWBBIO 2020, held in Maspalomas, Gran Canaria, Spain, in June 2022.

This volume constitutes the proceedings of the 9th International Work-Conference on IWBBIO 2020, held in Maspalomas, Gran Canaria, Spain, in June 2022.

This three-volume set LNCS 13338-13340 constitutes the thoroughly refereed proceedings of the 8th International Conference on Artificial Intelligence and Security, ICAIS 2022, which was held in Qinghai, China, in July 2022. The total of 166 papers included in the 3 volumes were carefully reviewed and selected from 1124 submissions.

This three-volume set LNCS 13338-13340 constitutes the thoroughly refereed proceedings of the 8th International Conference on Artificial Intelligence and Security, ICAIS 2022, which was held in Qinghai, China, in July 2022. The total of 166 papers included in the 3 volumes were carefully reviewed and selected from 1124 submissions.

This three-volume set LNCS 13338-13340 constitutes the thoroughly refereed proceedings of the 8th International Conference on Artificial Intelligence and Security, ICAIS 2022, which was held in Qinghai, China, in July 2022. The total of 166 papers included in the 3 volumes were carefully reviewed and selected from 1124 submissions.

Chapter "Swedish Recreational Businesses Coping with COVID-19 Using Technologies" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book constitutes the refereed post-conference proceedings of the 10th International Conference on Mobile Communication and Healthcare, MobiHealth 2021, held in November 2021. Due to Covid-19 pandemic the conference was held virtually.

This book constitutes revised selected papers from the workshops held at the 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021, which took place in Portugal, in August 2021.

Papers include a varied set of digital marketing and eCommerce-related topics such as user psychology and behavior in social commerce, influencer marketing in social commerce, social media monetization strategies and social commerce characteristics.

This book presents the fundamental aspects, recent developments in fabrication and characterization techniques, structure, properties, and emerging applications of MXenes. An overview of all the latest developments in energy storage and conversion applications, catalysis, environmental remediation, and radiation shielding, etc is reported.

By extending the technique of Plonka sums from algebras to logical matrices, the authors investigate the different classes of models for logics of variable inclusion and they shed new light into their formal properties.The book opens with the historical origins of logics of variable inclusion and on their philosophical motivations.

Social stress has emerged as a research front in the neurosciences, and this volume highlights recent insights in brain mechanisms and methodological advances. The parallel presentation of work with animal models and human subjects is bound to be useful to a broad research community.

Agricultural automation is the emerging technologies which heavily rely on computer-integrated management and advanced control systems.

Providing a shared memory abstraction in distributed systems is a powerful tool that can simplify the design and implementation of software systems for networked platforms. Emulations of shared atomic memory in distributed systems is an active area of research and development.