This book constitutes the refereed proceedings of the Third Southwest Data Science Conference, on Recent advances in next-generation data science, SDSC 2024, held in Waco, TX, USA, in March 22, 2024. The 15 full papers presented were carefully reviewed and selected from 59 submissions. These papers focus on AI security in next-generation data science and address a range of challenges, from protecting sensitive data to mitigating adversarial threats.

This book constitutes selected papers of the ​Third International Conference on Data Science, Medicine and Bioinformatics, IDMB 2019, held in Nanning, China, in June 2019. The 19 full papers and 1 short paper were carefully reviewed and selected from 93 submissions. The papers are organized according to the following topical sections: business data science: fintech, management, and analytics.- health and biological data science.- novel data science theory and applications.

This book constitutes the refereed proceedings of the First Southwest Data Science Conference, on The Recent Advances in Transdisciplinary Data Science, SDSC 2022, held in Waco, TX, USA, during March 25–26, 2022. The 14 full papers and 2 short papers included in this book were carefully reviewed and selected from 72 submissions. They were organized in topical sections as follows: Business and social data science; Health and biological data science; Applied data science, artificial intelligence, and data engineering.

This book provides a detailed overview of the latest developments and applications in the field of artificial intelligence and data science. AI applications have achieved great accuracy and performance with the help of developments in data processing and storage. It has also gained strength through the amount and quality of data which is the main nucleus of data science. This book aims to provide the latest research findings in the field of artificial intelligence with data science.

The huge volume of multi-modal neuroimaging data across different neuroscience communities has posed a daunting challenge to traditional methods of data sharing, data archiving, data processing and data analysis. Neuroinformatics plays a crucial role in creating advanced methodologies and tools for the handling of varied and heterogeneous datasets in order to better understand the structure and function of the brain. These tools and methodologies not only enhance data collection, analysis, integration, interpretation, modeling, and dissemination of data, but also promote data sharing and collaboration. This Neuroinformatics Research Topic aims to summarize the state-of-art of the current achievements and explores the directions for the future generation of neuroinformatics infrastructure. The publications present solutions for data archiving, data processing and workflow, data mining, and system integration methodologies. Some of the systems presented are large in scale, geographically distributed, and already have a well-established user community. Some discuss opportunities and methodologies that facilitate large-scale parallel data processing tasks under a heterogeneous computational environment. We wish to stimulate on-going discussions at the level of the neuroinformatics infrastructure including the common challenges, new technologies of maximum benefit, key features of next generation infrastructure, etc. We have asked leading research groups from different research areas of neuroscience/neuroimaging to provide their thoughts on the development of a state of the art and highly-efficient neuroinformatics infrastructure. Such discussions will inspire and help guide the development of a state of the art, highly-efficient neuroinformatics infrastructure.

This book effectively summarizes our knowledge of recent advances in prostate cancer. It focuses on our state-of-the-art understanding of risk factors, prevention, detection, prognosis and treatment of prostate cancer and identifies basic science findings that are being translated into clinical practice. In addition, the book singles out key areas of research that have potential for clinical translation. Both basic scientists and clinicians will be invited to provide up-to-date reviews in each area of prostate cancer.During the last decade the pace of clinical discovery and the scientific advances in prostate cancer have been very rapid. For instance, currently there are more than 100 drugs in the pharmaceutical pipeline that have the potential for clinical management of prostate cancer. Therefore, it has been very difficult for clinicians and basic scientists to keep pace with the field as a whole. Recently, some of these discoveries are already having an impact on clinical practice. For example, the discovery of the androgen receptor gene amplification in prostate cancer has led to the development of a “super-antiandrogen”, which is being tested in clinical trials. Also, recent knowledge of androgen synthesis in prostate cancer cells has led to clinical trials with steroid-metabolism inhibitors. Finally, robotic surgery has also dramatically changed clinical practice. Thus, this important book serves to provide readers with a one-stop overview of the field of prostate cancer research and its translation into the clinical arena.

This book covers a domain that is significantly impacted by the growth of soft computing. Internet of Things (IoT)-related applications are gaining much attention with more and more devices which are getting connected, and they become the potential components of some smart applications. Thus, a global enthusiasm has sparked over various domains such as health, agriculture, energy, security, and retail. So, in this book, the main objective is to capture this multifaceted nature of IoT and machine learning in one single place. According to the contribution of each chapter, the book also provides a future direction for IoT and machine learning research. The objectives of this book are to identify different issues, suggest feasible solutions to those identified issues, and enable researchers and practitioners from both academia and industry to interact with each other regarding emerging technologies related to IoT and machine learning. In this book, we look for novel chapters that recommend new methodologies, recent advancement, system architectures, and other solutions to prevail over the limitations of IoT and machine learning.

This book provides insights on blockchain technology and its applications in real-world business, supply chain, health care, education, HRM, retail, logistics and transport industries. This book grants a comprehensive understanding of how this technology is functioning within modern real-world applications and how it can influence the future of the real-world applications in industry. The chapters cover the case study, applications of blockchain, benefits and challenges, disruptive innovations in real-world applications, privacy and security concerns, and the recent trends of blockchain in real-world applications. It is ideally intended for marketers, advertisers, brand managers, executives, managers, IT specialists and consultants, researchers, businesses, practitioners, stakeholders, academicians, and students interested in blockchain technology and its role in supply chain, health care, education, HRM, retail, logistics and transport industries.

Big data is revolutionizing our ability to measure and study the human brain. New technology increases the resolution of images that are being study as well as enables researchers to study the brain as it functions. These technological advances are combined with efforts to collect neuroimaging data on large numbers of subjects, in some cases longitudinally. This combination of advances in measurement and scope of studies requires novel development in the statistical analysis. Fast, scalable, robust and accurate models and approaches need to be developed to make headway on these problems. This volume represents a unique collection of researchers providing deep insights on the statistical analysis of big neuroimaging data.

Since the first postulation of auxin function by the Darwins, many other plant hormones have been identified and most of them have been found to be synthesized at different sites from their places of action. Hormone transport and thus the responsible hormone transporters are therefore essential for a precise regulation of plant hormone action, which has been repeatedly supported by severe developmental and physiological phenotypes reported for hormone transporter loss-of-function mutants. Plant transporters have been shown to be involved in short and long-distance transport of hormones. Short-distance transport between cells seems to be sufficient for a local hormone action in some tissues (such as seeds), which seem to require exporter and importer proteins in adjacent cells as shown for example for abscisic acid. During long distance transport with the transpiration stream or in the phloem, demonstrated for many (but not all) plant hormones (including auxins, abscisic acid, cytokinins, gibberelins, strigolactones, and salicylic acid), transporters are thought to function in loading and unloading processes. Similarly, in cases where long-distance transport is achieved by cell-to-cell transport (such as for auxins), the highly coordinated action of import and export transporters at the contact surfaces of neighboring cells is apparently needed, however, all these processes are far from being understood on the molecular level. Currently, it appears that many hormones are transported by members of distinct transporter classes, ranging from primary active pumps (that couple hormone translocation to direct ATP hydrolysis), antiporters and symporters (that use the proton motive force to create hormone concentration gradients), and to facilitators. Among those, the ATP-binding cassette (ABC) family and the Nitrate transport1/ Peptide transporter family (NPF) seem to be dominant but currently it is unclear how individual transporters cooperate to achieve a systemic level of transport. Furthermore, in most cases several pairs of importers and exporters are required but how these are correct allocated in order to guarantee the function of a complex hormonal network is unknown. While remarkable progress has been made on hormone transporter regulation on the transcription and post-transcriptional level for transporters involved in long-distance transport (such as auxin), regulation of transporter trafficking, stability and activity is less understood for other hormones.