SciTech Connect Science & Technology Books Community Tue, 14 Apr 2020 09:17:32 +0000 en-US hourly 1 Science & Technology Books Community SciTech Connect Science & Technology Books Community SciTech Connect Ask the Author Advanced Antenna Systems for 5G Network Deployments Thu, 09 Apr 2020 13:51:51 +0000 We chatted with Peter von Butovitsch, one of the authors of Advanced Antenna Systems for 5G Network Deployments about changes in the field and how their book content can help engineers working in 5G deployment.

  • Can you explain why advanced antenna systems are important for 5G deployment?

Advanced antenna systems (AAS) provide increased coverage, capacity and user throughput, and are therefore an intrinsic part of 5G deployments. AAS is already being established as one of the main-stream solutions on mid-band. On mmWave bands, it is expected that all radio products will have AAS implementations. Furthermore, it is expected that AAS solutions will develop continually and become more cost-efficient over time and that the use of AAS will increase in all types of deployments.

  • What is your approach in your book Advanced Antenna Systems for 5G Network Deployments and how is that beneficial to engineers developing and deploying 5G technology and networks?

We have seen that AAS is a field that involves many different technology domains, including several academic disciplines, standardization, hardware and software solutions and network deployments and operation, and that each specific domain has developed a knowledge base and a corresponding vocabulary. The links between these domains, however, are weak and an understanding across domains is very difficult to establish.

So, we have seen a need for making a comprehensive view of the whole field of AAS and how it can be used in 5G deployments. The most important contribution of this book is that it describes all relevant areas that are necessary to build a broad understanding of how AAS works and how it performs in different environments and particularly how all these parts are connected. The book covers each topic to a significant depth and intends to bring the reader to a professional level of knowledge in each area. The descriptions are intended to provide both an intuitive view described in words and illustrations and a stricter academic description that substantiates and formalizes the intuitive picture.

  • For someone new to advanced antenna systems who want a good understanding, what suggestions do you have on how they should approach reading your book?

Someone who is new to the area and wants to learn AAS in depth will benefit from taking the time and effort to understand the background and the basic technology components, e.g. wave propagation, antenna arrays and the OFDM MIMO channel. This will enable a deeper understanding of the core content, e.g. multi-antenna technologies and high band (mmWave) technologies. The latter chapters can then be read selectively with respect to interest, for example 3GPP solutions, architecture and implementation. Those who are more interested in an overview of the background and do not want to delve into too much algebra may limit the reading to the introduction and the summary of chapter 3-5 to be able to move to their topics of their interests.

  • For the engineer who has some knowledge of the area and wanting to deploy the technology, what is the best way to approach reading your book?

The readers who has some knowledge of the basic technology components can browse chapters 3-5 and focus on what is new and interesting to them, e.g. multi-antenna technologies, 3GPP support for AAS, radio requirements, architecture and implementation or network performance. They can upon need look back into chapters 3-5 to get a deeper understanding of technology components described in these chapters and how these are connected to the later chapters.

  • The book is written by an author team. What collective experience do you bring to the book?

By using a larger team of authors, we have been able to bring together cutting edge experience and expertise from a wide area of AAS related topics and build a comprehensive picture of the whole field, ranging from wave propagation, and multi-antenna technologies to 3GPP solutions, architecture, implementation, feature- and network performance and many other areas. The main contribution of the book is to explain what factors affect the performance and use of AAS in 5G deployments and how these are connected. This, we believe, will provide very useful insights to a broader audience.

  • How do you see advanced antenna systems evolving in the future?

AAS started to evolve during 4G and has become an intrinsic part of 5G. Further performance improvements are being developed in later releases of 5G and the AAS development is expected to continue on to 6G where AAS will likely be considered in all types of solutions on essentially all frequency bands and sites, including an expected evolution towards the terahertz frequency range.

AAS will evolve in many ways, including new usage scenarios, improved cost efficiency and energy efficiency. There are several foreseeable ways to do this. Improved building practice and deployment architecture are interesting areas to explore, in particular multi-site coordination in combination with multi-antenna techniques.


About the book

  • Explains how AAS features impact network performance and how AAS can be effectively used in a 5G network, based on either NR and/or LTE
  • Shows what AAS configurations and features to use in different network deployment scenarios, focusing on MBB, but also including fixed wireless access
  • Presents the latest developments in multi-antenna technologies, including Beamforming, MIMO and cell shaping, along with the potential of different technologies in a commercial network context
  • Provides a deep understanding of the differences between mid-band and mmWave solutions


Advanced Antenna Systems for 5G Network Deployments is available to order now via Elsevier, enter code STC320 at the checkout to save up to 30%

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Off-Board diagnostics Fri, 03 Apr 2020 11:38:00 +0000 Off-Board Diagnostics is a term used for the diagnostics of planes, vehicles and other machines. It was created by Nassim Khaled in 2018 and first published in Digital Twin Development and Deployment on the Cloud Due to be published later this year.

Motivated by Max 737 issues and the subsequent crashes of airplanes [2], Nassim and his co-authors wanted to make the process of predicting and detecting failures of vehicles, machines and processes more robust.

Unlike on-board diagnostics [3] where the diagnostic decision takes place in the controller of the machine, Nassim proposes having the decision made in the cloud [1]. The main advantage of Off-BD compared to On-Board Diagnostics (OBD) is the computational power in the cloud. Nassim proposes using physics-based models that can be used as virtual copies of the physical machine. These virtual copies, or digital twins, can then be used as a reference to check if the machine is operating properly.

Figure 1 demonstrates the concept of a turbine asset and its virtual replica (i.e. the model) and how their outputs can be compared to diagnose a deterioration in the performance of the physical asset. Nassim and his co-authors propose a process to streamline Off-BD. Figure 2 shows the general steps involved in designing Off-BD [1].

About the book

Digital Twin Development and Deployment in the Cloud?promotes a physics-based approach to the field of digital twins. Through usage of multiphysics models running on the cloud, significant improvement to the diagnostics and prognostic of systems can be attained. The book draws a clear definition of digital twins. It helps business leaders clearly identify what it is and what value it brings?Digital Twin Development and Deployment in the Cloud?refines the term digital twins. The book outlines the key elements needed to deploy digital twins. This includes the hardware and software tools needed. Special attention is paid to the process of developing and deploying the multi-physics models of the digital twins.

Key Features:

  • Provides a high-level overview of digital twins and its underutilization in the field of asset management and maintenance
  • Proposes a streamline process to create digital twins for a wide variety of applications using Matlab? Simscape?
  • Deploys developed digital twins on Amazon Web Services
  • Includes Matlab and Simulink codes available for free download on Matlab central
  • Popular prototyping hardwares such as Arduino and Raspberry Pi are used for demonstration of the concepts proposed in the book






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The data-driven future of oncology Thu, 02 Apr 2020 09:08:03 +0000 Medical researchers and practitioners are increasingly embracing artificial intelligence, machine learning and other data-driven approaches. Having recognized the incredible potential for diagnostic and treatment decisions, it’s now time to delve deeper into how to efficiently translate technology, data and analytic innovations into clinical practices. The possibilities for cancer treatment have attracted particular attention.

The conversation around data-driven approaches to oncology is an interdisciplinary one. It involves leading researchers, clinicians, informaticians and technologists, each of whom bring their perspective to the topic. Entrepreneurs and representatives of regulatory bodies also have an important stake in this critical area.

For all of these parties, access to both foundational knowledge and the latest research in oncology, big data and artificial intelligence is essential. That’s why Elsevier created the AI and Big Data in Cancer?special collection. This expertly curated set of book chapters, journal articles and other literature stands as an excellent resource for anyone involved in this important area.

For a limited time, all the literature in the?AI and Big Data in Cancer?special collection is freely accessible to read, download and share.



The collection was created in relation to this year’s AI and Big Data in Cancer?symposium, which will take place in Boston in November. It will bring together people from a whole range of backgrounds for keynote talks, lectures, panels and interviews. It is both a networking and learning opportunity.

Making the?AI and Big Data in Cancer?special collection available and freely accessible is part of Elsevier’s commitment to supporting the scientific community and making the symposium a success. Visit the collection today and spread the word about this unique opportunity.


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Supporting students attending classes online Thu, 26 Mar 2020 10:31:20 +0000 In response to the COVID-19 pandemic, educational institutions worldwide have closed campuses and moved this semester’s classes online. Whether it is due to regional lockdowns or institutional decisions, we commend and fully support their decisions. They’re playing their part in promoting social distancing and they’re protecting?their students, faculty members and other staff.?

To support all the students who are studying remotely, we’re making all Elsevier textbooks freely available online for the next three months. This means that anyone who normally relies on institutional ScienceDirect access to their textbooks can find the full content online at Whether you’re?self-isolating while preparing for exams, attending classes online, preparing for the next semester, or looking for foundational knowledge while preparing your thesis, you’ll be able to read the same textbooks from the safety of your home.

We also hope that this will help faculty members by making it easier for them to set readings for their students and reduce the requests going to librarians for remote access to library collections.

Elsevier is committed to supporting educational institutions maintain this semester’s courses despite the exceptional current circumstances. See the list of textbooks.

Note that remote access is not needed to read the textbook collection as this is freely accessible online. Working from home? No need for VPN. Here’s a guide on setting up RemoteAccess to ScienceDirect so research and study can continue when you’re not on campus or in the office.?

We’d also like to remind librarians, researchers and students that Elsevier offers three options for remote access. These options enable you to use research solutions like ScienceDirect, Scopus, Reaxys and Embase as if you were in your campus office or library. You can find more details about the best option for you here.

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Five Elsevier Titles Win 2020 Textbook Excellence Awards from the Textbook & Academic Authors Association Thu, 12 Mar 2020 15:33:25 +0000 We are delighted to announce that five Elsevier titles have been selected as winners of the Textbook Excellence Award, presented yearly by the Textbook & Academic Authors Association (TAA). We extend our hearty congratulations to all of the authors and editorial teams behind these stunning works of scholarly excellence.

Twenty-nine books were honored this year, across three categories and two age levels. Elsevier titles comprised nearly half of the 12 Textbook Excellence Awards at the College level. These five titles represent the breadth and depth of Elsevier publishing, with topics ranging from ecology to statistics and user experience design.

The 2020 Textbook Excellence Award winners are as follows:

The UX Book: Agile UX Design for a Quality User Experience, 2nd Edition by Rex Hartson and Pardha Pyla. Nominally a second edition, there is so much new material in this release that it might equally fairly be called a sequel. With comprehensive coverage of this rapidly maturing field, The UX Book is tried and tested in university classrooms. You can read Chapter 1: What Are UX and UX Design? for a limited time on ScienceDirect.

Introduction to Probability Models, 12th Edition by Sheldon Ross. Introducing the reader to probability modeling and demonstrating its applicability to a variety of fields, Ross’s classic bestseller has been a staple university textbook since 1972.

The Dissection of Vertebrates, 3rd Edition by Gerardo De Iuliis and Dino Pulerà. Filled with stunning illustrations and photographs, The Dissection of Vertebrates offers detailed and concise instructions to today’s university student. De Iuliis and Pulerà provide the most comprehensive resource on the market today, one that will be relevant to students in biology, zoology, and related majors. Read Chapter 3 The Shark on ScienceDirect

Molecular Biology, 3rd Edition by David Clark, Nanette Pazdernik and Michelle McGehee. This invaluable resource is fully updated and revised to present the most current research, including coverage on epigenetics, CRISPR, and excerpts of cutting-edge research on experimental topics. An accompanying online study guide ties the textbook to current case studies. Read Chapter 2 Basic Genetics now on ScienceDirect

Freshwater Ecology: Concepts and Environmental Applications of Limnology, 3rd Edition by Walter Dodds and Matt Whiles. The third edition of this excellent resource, Dodds and Whiles’s text covers freshwater ecology from an expansive point of view. Including relevant information for students planning to enter the field, such as how to balance human and ecological needs, GMOs, fracking, and more, Freshwater Ecology is an excellent addition to the classroom. You can read Chapter 2?–?Properties of Water on ScienceDirect

The TAA Awards will be presented this June during TAA’s annual conference. We are happy to be able to recognize these excellent titles.

The UX Book: Agile UX Design for a Quality User Experience, 2nd Edition, Introduction to Probability Models, 12th Edition, The Dissection of Vertebrates, 3rd Edition, Molecular Biology, 3rd Edition, Freshwater Ecology: Concepts and Environmental Applications of Limnology, 3rd Edition are available now on ScienceDirect. Want your own copy? Enter STC320 when you order on and save up to 30%.

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Investigating gender disparity and bias in STEM: How to learn more. Thu, 12 Mar 2020 13:59:29 +0000 While the overall representation of women in research has increased, gender disparity and bias in STEM remain significant topics for discussion. They negatively affect both career paths and the breadth and impact of research. While the gains in equal opportunity and representation should be acknowledged, it is more important to recognize the areas where effort is still needed.

How to learn more about gender inequality in STEM

The lack of equality for women in research can be seen in evidence-based analyses of publication output, citations, awarded grants and collaboration opportunities. Such an approach was applied in Elsevier’s 2020 report The researcher journey through a gender lens: An examination of research participation, career progression and perceptions across the globe.

This is the third annual gender-focused report from Elsevier. Building on the approaches of previous years, it has expanded its scope to cover more countries and offer new elements, including career progression and collaboration network analyses.

Download your copy of the report

Key findings of this year’s report

  • In all the countries studied and in the 28 countries of the EU, there is a trend toward parity in the number of female to male authors.
  • In every country, the percentage of women who continue to publish is lower than the percentage of men who continue to publish.
  • In an analysis of first authors, the average citation impact for men was found to be higher than that for women, suggesting a gender bias in citation practice.
  • Researcher attitudes toward gender diversity and equity vary widely among men and women. The differences in viewpoints arise from the individual’s perception of fairness and gender balance in the academic system.

How to learn more from women in STEM

Selected chapters from four recent professional and career development books are available to read now, for a limited time on ScienceDirect. These titles, all authored and/or edited by leading women in STEM, were chosen for their relationship to the findings of The researcher journey through a gender lens.

Inspiring Conversations with Women Professors: The Many Routes to Career Success by Anna Garry features interviews with a diverse group of women in faculty and leadership positions, and from a broad range of STEM disciplines. It provides stories behind the many paths to professorship taken by these featured women, including the obstacles they encountered and how they overcame them.
Read the Introduction now on ScienceDirect

Communicating as Women in STEM by Charlotte Brammer teaches constructive communication strategies for interaction with mentees, mentors, faculty, managers, colleagues and other professionals. The intention is to provide women and other underrepresented groups, faculty and administrators with the tools they need to break barriers raised by different communication styles within the STEM fields.
Read Chapter 2 – Stereotypes and Stacked Decks: Can Females Really Be Scientists and Engineers? on ScienceDirect

Success Strategies from Women in STEM, edited by Peggy A. Pritchard and Christine Grant is a comprehensive and accessible manual containing career advice, mentoring support, and professional development strategies for female scientists in the STEM fields. Chapter topics include leadership and negotiation, important coverage of career management, networking, social media, communication skills, and more.
Read Chapter 3 – Mentoring: Empowering Your Success on ScienceDirect

Equitable Solutions for Retaining a Robust STEM Workforce: Beyond Best Practices by Donna J. Dean and Janet B. Koster presents best practices and internationally transportable policies to support and accommodate STEM work/life satisfaction. It discusses universal issues such as dual careers and strategic decision making, childcare/dependent care in professional  contexts, promoting family-friendly policies, as well as mentoring and networking.
Read Chapter 1 – Envisioning the STEM Workplace of the Future: The Need for Work/Life Programs and Family-Friendly Practices on ScienceDirect

Further recommended reading

Other titles in our current professional and career development publishing initiative focused on women in STEM include:

These books are all available now on ScienceDirect. Want your own copy? Enter code STC320 when you order via the Elsevier store and save up to 30%

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AI and Big Data in Cancer: How to effectively translate technology, data and analytic innovations into clinical practices and patient benefits Fri, 06 Mar 2020 10:37:05 +0000

The future of medicine is data-driven and AI-enabled, which will impact diagnosis, treatment decisions and patient care. AI and Big Data in Cancer 2020, hosted by Elsevier, is taking place March 29-31st in Boston, and is bringing together leading experts from cancer centers, start-ups, technology, private equity, innovation centers, pharma and government. The aim of the conference is for attendees to learn from others along the digital medicine value-chain to understand how to effectively translate technology, data and analytic innovations into clinical practices and patient benefits. Attendees can network and find partners to move innovations forward. In advance of the conference, we asked some of the key speakers their thoughts on the future of the implementation of AI in oncology care and the barriers that must be overcome in order to succeed.

Craig Mermel, MD, Ph.D., Product Lead for Pathology at Google Health, believes that first we need to overcome the fear that AI will replace doctors and researchers. “AI-drive medicine won’t be the complete replacement of doctors and specialists. That’s what most people fear and while I think it is inevitable that AI is going to make its way into the delivery of care, but that it is largely going to be an augmentation and efficiency tool for physicians to practice in a way that is much more personalized, accurate and scalable. The reason for this is that the recent advances in AI are still very narrow forms of intelligence. We can train AI systems to do very narrow specific tasks, but it isn’t likely that we’ll just replace doctors by training systems like thousands of consisting of thousands of narrow AI- tools; so we simply don’t yet have the technology to replace the general intelligence and synthetic abilities of doctors. It is a uniquely human characteristic. Also, from a human perspective, we want the information these systems to provide to have the backstop and the values of a human decision-maker, and we’ll still need doctors for that. We need to find out how to be sure that AI-Driven medicine augments what people are doing, not replaces it.”

Manoj Saxena, MBA, Executive Chairman, CognitiveScale and Founding Board Member, AI Global, believes AI and Big Data will be as transformational to medicine as the stethoscope was 200 years ago. “All aspects of medicine are going to be impacted, specifically the four major groups of end customers, care providers, the clinician and research community, and healthcare delivery business models…In ten years, I think AI is going to show business efficiency through agility. These are taking boring backoffice processes and cycle management and claims processing and enrollment and really driving efficiencies through it to make these processes more agile. The second is innovation. This is being able to take work that companies like looking at genetic evidence and how you treat and diagnose and prevent diseases and building a whole new type of healthcare platform for disease lifecycle management. There is innovation that is going to happen around member/patient engagement, there is innovation that is going to happen around disease prediction and diagnosis and treatment, there is innovation that is going to happen around business models around how you connect up different participants in an ecosystem, reimagining the existing processes and coming up with a whole new set of innovative engagement models. The ability to completely reimagine and transform a claims process using a combination of AI and big data and block chain is an example of a moonshot. Many will fail but those that succeed will completely revolutionize the industry.”

Ned Sharpless, MD, Director of the National Cancer Institute agrees. “There are a tremendous range of applications for AI. AI/ML is already having a significant impact on clinical medicine as practiced today, by doing things that humans can already do pretty well, but by doing these things in a manner that is cheaper, highly reproduceable and at scale. These approaches are here at this very moment and their use is considerably more prevalent already than has been commonly realized. In the future, though, we believe AI/ML algorithms will be developed for widespread use to do things that no human can do, but that the technology will make possible. There are many places where we expect to see such advances, but I will give one example of interest to the NCI: the development of algorithms that can predict future cancer risk using standard radiographic imaging data. That is, to predict future cancer risk in a way that no radiologist can discern using standard training. The idea is that an algorithm can be trained on large sets of annotated radiographic imaging to predict future cancer risk from so-called “normal” scans. For example, we expect an algorithm could be trained on chest CT scans from large clinical trials like the National Lung Screening Trial (NLST), and based on that training, then identify subsets of patients with a significantly increased risk of developing lung cancer over the next few years, even though these chest CTs would be considered unremarkable by standard radiologic interpretation. That is going to happen. We’re going to see better readings of pancreatic scans, and chest CTs, and other imaging modalities; and in some instances, these algorithms will make accurate predictions about future cancer risk in a way that radiologists just can’t do. If we train these AI imaging analysis algorithms on large enough datasets, they can start to see things that are too subtle for traditional radiologists. This sort of capability will be very important to us for many reasons. Patients with an increased risk of cancer might be followed by their doctors in a different manner, or would be more likely to benefit from a clinical trial of some sort of cancer prevention. Such a technology has immediate application for the NCI.”

There are quite a few barriers that must be overcome for the successful implementation of AI in oncology care and suggestions on how to surmount them will be discussed during the conference. These barriers include access to expertise, a recalcitrant culture, the availability and quality of data, the maturation of the technology, processes like integration into the workflow, reimbursement model, and administrative requirements, and finally external barriers like regulatory requirement, data privacy & governance, and business models. These will be discussed in detail at the conference with suggestions on how to turn them into opportunities from different perspectives including clinical, research and investing.?

For Christoph Lengauer, Ph.D., Partner, Third Rock Ventures, the biggest barrier is the data. “It needs to be purposeful data. The second thing is, I think we need to have an application. We do a lot of things because they are cool but very self-fulfilling. From an investor perspective it is so important. We are forgetting in all of this that it has to have some purpose and be value-creating. Just because we can do something faster or quicker; it doesn’t get us anywhere.” David Shaywitz, MD, Ph.D., Founder of Astounding HealthTech advisory services, further adds to this point, “The quality of the data and the need for focus are the biggest barriers for me. When people talk about digital transformation, some folks have the idea that we’ll get lots of data together, stir these up in a big vat, and then magically they will start to speak to us. That seems unlikely. I prefer a use-case drive approach; to define what are the actual problems that you need to solve and then go through the process of trying to solve these specific problems.? In the course of doing that, you really learn what the issues are with the data, and you figure out what are the right technologies. Ideally, you would start from the ground up and collect data in a fashion that is amenable to AI – you’d start by structuring it right from the beginning.”

Ned Sharpless, MD, agrees that a big barrier is having suitable datasets. “From the NCI’s point of view, the biggest barrier is having the appropriate datasets and having the appropriate people to work with that data. Both of those are things that I think we can make a lot of progress on with accurate funding. Data that’s better in the sense that it is clean and well-annotated. So, it has features like clinical outcomes matched to radiology that they want to use to train their algorithms. The argument has been made that retrofitting old datasets is not often possible. In some instances, we will need new collections of data that are designed for machine-learning from the get-go. It’s certainly a big investment for us to use AI on existing datasets, but we’ve also heard the message loud and clear that we need to fund new datasets that have AI in mind from the get-go. Another desperate need is the people to work on it. The machine-learning people who are interested in biology – there are so few of them and we really need to train up more.”

Andrew W. Lo, Ph.D., Professor and Director of the Laboratory for Financial Engineering at MIT Sloan School of Management, believes the biggest barrier, from an investor perspective, are new business models. “That, to me, is the one thing that we can be thinking about differently that we aren’t right now. People are already focused on scientific collaborations, new types of biological mechanisms and targets, genomics, transcriptomics, proteomics, and all the other -omics. But the one omics they haven’t focused on is economics, new ways of structuring biopharma businesses and financing them. This challenge also offers tremendous opportunities for applying the tools of modern financial engineering to biomedicine and getting investors to think differently…. By adopting a portfolio approach to biomedical R&D, we can lower the cost of capital, increase the amount of funding, and get new and better therapies to patients faster and cheaper.”

Kathy Giusti, MBA, Founder and Chief Mission Officer of the Multiple Myeloma Research Foundation and Faculty Co-Chair of the Harvard Business School-Kraft Precision Medicine Accelerator, states, “With an intense focus on generating high-quality data, the MMRF has seen firsthand the challenges of using that data to answer clinical questions that the community deals with on a consistent basis. In addition, new business models must be developed that involve the full ecosystem of academia, health systems, industry and patient groups. Those business models should include having AI at the table much earlier helping to frame the data requirements in advance. Furthermore, incentives must be aligned to prioritize use cases that can improve patient outcomes.”

Craig Mermel, MD, Ph.D., believes the biggest barrier is in the process and externalities. “Until we really understand how to fully integrate AI into the existing workflows and build sustainable reimbursement models around it; that’s a barrier that is slowing it progress down and potentially preventing it the technology from reaching the maximum number of patients. Much of the near-term attention needs to go to process and workflow integration. If we can improve on quality and that this technology is safe, and integrates into actual workflows, and improves overall quality of care, I think many of the regulatory externality issues will move forward as well.”

Help figure out how to turn these barriers into opportunities at the AI and Big Data in Cancer in Boston. ?It is time to shift the conversation from what AI and Big Data can do to what medicine needs. Be sure to attend to hear more from the above great speakers and other leading experts to translate artificial intelligence and data-driven innovations into new clinical care practices for patients.

View the full program and register here: Follow the conversation on Twitter:

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Series Editor awarded highest scientific honor in China Tue, 03 Mar 2020 15:15:00 +0000 ?We are delighted to share the news that renowned Elsevier editor and author Prof. Atta-ur-Rahman has been awarded the highest scientific honor of China, the International Science and Technology Cooperation Award, presented by President Xi Jinping in Beijing on January 10, 2020. The award is granted to foreign scientists, engineers or organizations that have made important contributions to China’s bilateral or multilateral scientific and technological cooperation. He is the Editor-in-Chief of eight European Chemistry journals and is editor of the world’s leading encyclopedic series of volumes on natural products Studies in Natural Product Chemistry. 62 volumes have been published under his editorship during the last two decades with more volumes in planning stages.

In October 2019, The Hunan University of Chinese Medicine (HUCM) established a major research center in Prof. Atta-ur-Rahman’s name. ?The “Academician Professor Atta-ur-Rahman One Belt and One Road TCM Research Center” at its main campus in Changsha, capital of China’s Hunan province.

Prof. Atta-ur-Rahman obtained his Ph.D. in organic chemistry from Cambridge University (1968). He has 1250 publications in several fields of organic chemistry including 775 research publications, 45 international patents, 69 chapters in books and 341 books published, including 70 books with Elsevier.

Studies in Natural Product Chemistry is available now on ScienceDirect.

Want your own copy? Order via the Elsevier store and enter code STC320 at the checkout to save up to 30%

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Two Elsevier Books Named Subject Category Winners in AAP’s 2020 PROSE Awards Fri, 28 Feb 2020 13:20:17 +0000 Elsevier is delighted to announce that two titles have been named Subject Category Winners in the 2020 PROSE Awards, sponsored by the Association of American Publishers (AAP). Chemical, Gas, and Biosensors for Internet of Things and Related Applications by Kohji Mitsubayashi and Osamu Niwa and Yuko Ueno was honored in the Chemistry and Physics category and Handbook of Sleep Disorders in Medical Conditions by Josée Savard and Marie-Christine Ouellet was honored in the Textbook/Medicine and Clinical Science category.

These two titles both represent some of the best scholarship to come out of their respective fields in recent years.

Chemical, Gas, and Biosensors for Internet of Things and Related Applications features an interdisciplinary examination of sensors and analytical chemistry, devices and machines, and network and information technology. As Internet of Things (IoT)-equipped devices become more and more commonplace, more advanced technologies open up new opportunities to integrate IoT devices into fields such as healthcare, biomedicine, and food and environmental safety monitoring. Chemical, Gas, and Biosensors for Internet of Things explores this rapidly changing landscape and offers researchers and engineers in relevant fields a fantastic overview of the field.

For a limited time you can read Chapter 2?–?Design, application, and integration of paper-based sensors with the Internet of Things on ScienceDirect

In the healthcare field, Savard and Ouellet’s Handbook of Sleep Disorders in Medical Conditions is a comprehensive review of sleep disorders and how they present and affect common medical conditions, such as epilepsy, dementia, and traumatic brain injury. As sleep (or its lack) can greatly affect one’s ability to recover from injury or manage an ongoing condition, its consideration is a vital element of a treatment plan. Handbook of Sleep Disorders in Medical Conditions is ideal for neurologists, physicians, nurses, and other healthcare professionals looking to expand their knowledge on this important topic.

You can access Chapter Chapter 2?–?Treatment of Insomnia on ScienceDirect now.

AAP selected 49 category winners out of a total of 157 finalists, spanning diverse topics from the humanities to the sciences. The Subject Category Winners will go on to compete against each other for five PROSE Awards for Excellence. Chemical, Gas, and Biosensors for Internet of Things and Related Applications is in the running for the 2020 PROSE Award for Excellence in Physical Science and Mathematics. Handbook of Sleep Disorders in Medical Conditions is under consideration for the 2020 PROSE Award for Excellence in Reference Works. The PROSE Awards for Excellence will be announced within the coming weeks.

Chemical, Gas, and Biosensors for Internet of Things and Related Applications and Handbook of Sleep Disorders in Medical Conditions is ideal for neurologists are available now on ScienceDirect. Want your own copy? Enter STC320 when you order on and save up to 30%

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