This book discusses the natural classification and biosystematics of Triticeae and presents the most significant findings of comprehensive studies on the Triticeae, an important tribe in the grass family (Poaceae) that includes major crops such as wheat, barley, rye, and triticale, as well as various forage crops found in different genera. The five-volume Chinese version of Biosystematics of Triticeae was published in 1998, 2004, 2006, 2011, and 2013, and included the 30 genera, two subgenera, 464 species, nine subspecies, and 186 varieties of Triticeae identified to date. This is their English edition.

"Machine Learning for Cybersecurity: Threat Detection and Mitigation" delves into the transformative role of machine learning in addressing contemporary cybersecurity challenges. This reprint provides an in-depth exploration of how advanced techniques such as deep learning, natural language processing, and explainable AI are revolutionizing intrusion detection, anomaly detection, and threat intelligence. With a focus on practical applications, it covers critical topics such as malware analysis, IoT and cloud security, blockchain security, adversarial attacks, and secure data sharing. Through this reprint, readers will gain insights into cutting-edge approaches for vulnerability assessments, authentication, and privacy preservation while exploring frameworks for implementing security-aware AI systems.

Cet essai analyse la baisse récente – et préoccupante – de la fécondité en France, et traite des voies et moyens pour y remédier. Il propose une évaluation des politiques familiales à l’aune de ce qu’Emmanuel Macron a baptisé le « réarmement démographique ».

The Book contains 17 in total articles that are accepted and published in the Special Issue “Computational Methods and Application in Machine Learning, 2023” of the MDPI Mathematics journal. The articles cover a wide range of topics with respect to the theory and applications of the computational method in machine learning. These keywords include artificial intelligence big data and analysis, machine learning, deep learning, natural language understanding, pattern recognition, computer vision, information retrieval, data mining, bioinformatics and biomedical applications, reinforcement learning, multimedia analysis and retrieval, multimodal representation learning, feature selection, clustering, etc.

Spectatrice assidue depuis ses dix ans, Constance Vilanova n’a jamais décroché de ces programmes. Devenue journaliste, elle s’est interrogée : pourquoi avons-nous collectivement méprisé ce phénomène ? Dans cette enquête, elle nous entraîne au coeur de cette industrie : culte de l’individu, aspiration à la célébrité, banalisation de la chirurgie esthétique, apologie du clash et du harcèlement, romantisation des violences sexistes et sexuelles… Pendant que nous détournions le regard, la téléréalité s’est exportée sur les réseaux sociaux, ne cessant d’exploiter et de creuser les failles de notre société.

In a world where uncertainty and complexity dominate decision-making processes, Advances in Neural Networks and Fuzzy Logic presents groundbreaking studies exploring the potential of these Artificial Intelligence approaches to solve real-world problems. The chapters cover applications across various fields, such as robust galaxy classification, simulations in weighted finite automata, stock price prediction, large-scale water purification selection, speech deficiency detection in children, and supply chain management. Advanced techniques such as deep neural networks, fuzzy clustering, SHAP, LIME, and Hesitant Fuzzy Linguistic Term Sets are explored. This reprint is helpful for researchers, engineers, and students who wish to understand the latest advancements in and practical applications of neural networks and fuzzy logic. Within these pages, you will discover how these technologies solve complex problems and foster more transparent and reliable decision-support systems, as well as the state of the art in Artificial Intelligence, where neural networks and fuzzy logic converge to tackle modern challenges with innovation and precision.

The aim of this Bookis to delve into the intricate world of railway vehicle dynamics, exploring the cutting-edge techniques and advanced methodologies that have revolutionized the field. From the fundamental principles of wheel–rail interaction to the complex modeling of suspension systems, we aim to unravel the mysteries behind the smooth and efficient motion of trains. This reprint brings together the expertise of renowned researchers and practitioners, offering a wealth of knowledge and insights into the dynamic behavior of rail vehicles. Through detailed case studies, mathematical models, and experimental analyses, we shed light on the critical factors that influence the stability, safety, and performance of trains. From high-speed passenger trains to heavy-haul freight locomotives, we cover a wide spectrum of railway applications, addressing the unique challenges and opportunities associated with each. We also explore the latest advancements in computer simulation, sensor technology, and data analytics, which have transformed the way we analyze and optimize the dynamics of rail vehicles. As we embark on this journey, we seek to bridge the gap between theory and practice, providing a valuable resource for engineers, researchers, and decision-makers in the railway industry. By understanding the intricacies of vehicle dynamics, we can design safer, more efficient, and environmentally friendly rail transportation systems that meet the growing demands of modern society. Together, let us unlock the full potential of railway vehicle dynamics, paving the way for a future where trains continue to play a vital role in connecting people, goods, and ideas across vast distances, while minimizing their impact on our planet's precious resources.

The present book contains 11 articles accepted and published in the second edition of the Special Issue “Analytical Methods and Convergence in Probability with Applications” of the MDPI journal Mathematics, which cover a wide range of topics from the theory of distributions and analytical methods in probability to limit theorems, convergence rate estimates, and statistical estimation.

This book explores the various functions of butterfly and moth wings. Lepidoptera wings are covered with variously colored scales and exhibit a wide variety of color patterns, with some functioning as significant signals in behavior. They are also the flight organs, as the wings of the other insects are. Although research on Lepidopteran wings has predominantly focused on the color patterns and flight performance, they have many other functions that contribute to their lives.

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