Springer Nature (United States)

Numerical Methods with MATLAB provides a highly-practical reference work to assist anyone working with numerical methods. A wide range of techniques are introduced, their merits discussed and fully working MATLAB code samples supplied to demonstrate how they can be coded and applied. Numerical methods have wide applicability across many scientific, mathematical, and engineering disciplines and are most often employed in situations where working out an exact answer to the problem by another method is impractical. Numerical Methods with MATLAB presents each topic in a concise and readable format to help you learn fast and effectively. It is not intended to be a reference work to the conceptual theory that underpins the numerical methods themselves. A wide range of reference works are readily available to supply this information. If, however, you want assistance in applying numerical methods then this is the book for you.

Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. You will: Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers.

Abstract Although the Journal Impact Factor (JIF) is widely acknowledged to be a poor indicator of the quality of individual papers, it is used routinely to evaluate research and researchers. Here, we present a simple method for generating the citation distributions that underlie JIFs. Application of this straightforward protocol reveals the full extent of the skew of these distributions and the variation in citations received by published papers that is characteristic of all scientific journals. Although there are differences among journals across the spectrum of JIFs, the citation distributions overlap extensively, demonstrating that the citation performance of individual papers cannot be inferred from the JIF. We propose that this methodology be adopted by all journals as a move to greater transparency, one that should help to refocus attention on individual pieces of work and counter the inappropriate usage of JIFs during the process of research assessment.

Skillful storytelling helps listeners understand the essence of complex concepts and ideas in meaningful and often personal ways. For this reason, storytelling is being embraced by scientists who not only want to connect more authentically with their audiences, but also want to understand how the brain processes this powerful form of communication. Here we present part of a conversation between a group of scientists actively engaged with the practice and/or the science of storytelling. We highlight the brain networks involved in the telling and hearing of stories and show how storytelling is being used well beyond the realm of public communication to add a deeper dimension to communication with our students and colleagues, as well as helping to make our profession more inclusive.

In this study, we compared human immunodeficiency virus (HIV) type 1-specific proliferative responses with HIV-1-induced intracellular cytokine production in a cohort of clinically nonprogressing patients and individuals with progressive HIV-1 infection. We found strong HIV-1-specific proliferative responses in the clinical nonprogressor cohort that correlated with significant numbers of circulating HIV-1-specific CD4(+) T cells. In contrast, HIV-1-specific proliferative responses were absent in most individuals with progressive HIV-1 infection, even though interferon-gamma-producing HIV-1-specific CD4(+) T cells were detectable by flow cytometry. The implication of these data is that the important dysfunction seen in most HIV-positive patients from very early in disease may be an inability of HIV-1-specific CD4(+) memory T cells to proliferate in response to HIV antigens rather than an absolute loss of circulating virus-specific CD4(+) T cells.

Desktop or DIY 3D printers are devices you can either buy preassembled as a kit, or build from a collection of parts to design and print physical objects including replacement household parts, custom

Transparency in reporting benefits scientific communication on many levels. While specific needs and expectations vary across fields, the effective interpretation and use of research findings relies on the availability of core information about research materials, study design, data, and experimental and analytical methods. For preclinical research, transparency in reporting is a key focus in response to concerns of replication failure. The inconsistent reporting of key elements of experimental and analytical design, alongside ambiguous description of reagents and lack of access to underlying data and code, has been shown to impair replication (1) and raise doubt about the robustness of results (2, 3). In response to early concerns about replication of published results, funders, publishers, and other stakeholders have called for improvements in reporting transparency (4⇓⇓–7). Several initiatives ensued, including journal policies and joint efforts by journals, funders, and other stakeholders (8⇓–10). One of these initiatives, the Transparency and Openness Promotion (TOP) guidelines (11), outlines a policy framework at the journal level that over 1,000 journals and publishers have adopted. The National Academies have focused on reproducibility and replicability* challenges through several recent initiatives leading to consensus reports, including Reproducibility and Replicability in Science (12), Open Science by Design: Realizing a Vision for 21st Century Research (13), and Fostering Integrity in Research (14). Each of these reports concludes that lack of reporting transparency is one factor which contributes to these systemic problems. Building on these findings, the National Academies convened a public workshop in September 2019 titled "Enhancing Scientific Reproducibility in Biomedical Research Through Transparent Reporting." The workshop was designed to discuss the current state of transparency in reporting biomedical research and to explore the possibility of improving the harmonization of guidelines across journals and funding agencies. During this workshop, we provided … [↵][1]1To whom correspondence may be addressed: Email: Malcolm.Macleod{at}ed.ac.uk (correspondence regarding the development and evaluation of the guideline) or mellor.david{at}gmail.com (for further information about implementation and stewardship). [1]: #xref-corresp-1-1

Mastering 3D Printing shows you how to get the most out of your printer, including how to design models, choose materials, work with different printers, and integrate 3D printing with traditional prototyping to make techniques like sand casting more efficient. You've printed key chains. You've printed simple toys. Now you're ready to innovate with your 3D printer to start a business or teach and inspire others. Joan Horvath has been an educator, engineer, author, and startup 3D printing company team member. She shows you all of the technical details you need to know to go beyond simple model printing to make your 3D printer work for you as a prototyping device, a teaching tool, or a business machine.

OBJECTIVE: ) became the first journals to routinely include patients and the public in the peer review process of journal articles. This survey explores the perspectives and early experiences of these reviewers. DESIGN: A cross-sectional survey. SETTING AND PARTICIPANTS: who have been invited to review. RESULTS: The response rate was 69% (157/227) for those who had previously reviewed and 31% (67/217) for those who had not yet reviewed. Reviewers described being motivated to review by the opportunity to include the patient voice in the research process, influence the quality of the biomedical literature and ensure it meets the needs of patients. Of the 157 who had reviewed, 127 (81%) would recommend being a reviewer to other patients and carers. 144 (92%) thought more journals should adopt patient and public review. Few reviewers (16/224, 7%) reported concerns about doing open review. Annual acknowledgement on the journals' websites was welcomed as was free access to journal information. Participants were keen to have access to more online resources and training to improve their reviewing skills. Suggestions on how to improve the reviewing experience included: allowing more time to review; better and more frequent communication; a more user-friendly process; improving guidance on how to review including videos; improving the matching of papers to reviewers' experience; providing more varied sample reviews and brief feedback on the usefulness of reviews; developing a sense of community among reviewers; and publicising of the contribution that patient and public review brings. CONCLUSIONS: Patient and public reviewers shared practical ideas to improve the reviewing experience and these will be reviewed to enhance the guidance and support given to them.

<ns4:p>Software is as integral as a research paper, monograph, or dataset in terms of facilitating the full understanding and dissemination of research. This article provides broadly applicable guidance on software citation for the communities and institutions publishing academic journals and conference proceedings. We expect those communities and institutions to produce versions of this document with software examples and citation styles that are appropriate for their intended audience. This article (and those community-specific versions) are aimed at authors citing software, including software developed by the authors or by others. We also include brief instructions on how software can be made citable, directing readers to more comprehensive guidance published elsewhere. The guidance presented in this article helps to support proper attribution and credit, reproducibility, collaboration and reuse, and encourages building on the work of others to further research.</ns4:p>

Beginning Sensor Networks with Arduino and Raspberry Pi teaches you how to build sensor networks with Arduino, Raspberry Pi, and XBee radio modules, and even shows you how to turn your Raspberry Pi into a MySQL database server to store your sensor data! First you'll learn about the different types of sensors and sensor networks, including how to build a simple XBee network. Then you'll walk through building an Arduino-based temperature sensor and data collector, followed by building a Raspberry Pi-based sensor node. Next you'll learn different ways to store sensor data, including writing to an SD card, sending data to the cloud, and setting up a Raspberry Pi MySQL server to host your data. You even learn how to connect to and interact with a MySQL database server directly from an Arduino! Finally you'll learn how to put it all together by connecting your Arduino sensor node to your new Raspberry Pi database server. If you want to see how well Arduino and Raspberry Pi can get along, especially to create a sensor network, then Beginning Sensor Networks with Arduino and Raspberry Pi is just the book you need.

PracticalOpenCV is a hands-on project book that shows you how to get the best resultsfrom OpenCV, the open-source computer vision library. Computer vision is key to technologies like object recognition, shapedetection, and depth estimation. OpenCV is an open-source library with over2500 algorithms that you can use to do all of these, as well as trackmoving objects, extract 3D models, and overlay augmented reality. It'sused by major companies like Google (in its autonomous car), Intel, andSony; and it is the backbone of the Robot Operating System’s computer vision capability.In short, if you're working with computer vision at all, you need to knowOpenCV. With Practical OpenCV, you'll be able to: Get OpenCV up and running on Windows or Linux. Use OpenCV to control the camera board and run vision algorithms on Raspberry Pi. Understand what goes on behind the scenes in computer vision applications like object detection, image stitching, filtering, stereo vision, and more. Code complex computer vision projects for your class/hobby/robot/job, many of which can execute in real time on off-the-shelf processors. Combine different modules that you develop to create your own interactive computer vision app.

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Optimization Techniques introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. It begins by introducing the MATLAB environment and the structure of MATLAB programming before moving on to the mathematics of optimization. The central part of the book is dedicated to MATLAB’s Optimization Toolbox, which implements state-of-the-art algorithms for solving multiobjective problems, non-linear minimization with boundary conditions and restrictions, minimax optimization, semi-infinitely constrained minimization and linear and quadratic programming. A wide range of exercises and examples are included, illustrating the most widely used optimization methods.

The increasing availability of structured datasets, from Web tables and open-data portals to enterprise data, opens up opportunities to enrich analytics and improve machine learning models through relational data augmentation. In this paper, we introduce a new class of data augmentation queries: join-correlation queries. Given a column Q and a join column KQ from a query table TQ, retrieve tables TX in a dataset collection such that TX is joinable with TQ on KQ and there is a column C ∈ TX such that Q is correlated with C. A naïve approach to evaluate these queries, which first finds joinable tables and then explicitly joins and computes correlations between Q and all columns of the discovered tables, is prohibitively expensive. To efficiently support correlated column discovery, we 1) propose a sketching method that enables the construction of an index for a large number of tables and that provides accurate estimates for join-correlation queries, and 2) explore different scoring strategies that effectively rank the query results based on how well the columns are correlated with the query. We carry out a detailed experimental evaluation, using both synthetic and real data, which shows that our sketches attain high accuracy and the scoring strategies lead to high-quality rankings.

When you create an app, a website, or a game, how do you attract users, and perhaps more importantly, how do you keep them? Irresistible Apps explains exactly how to do this using a library of 27 moti

The third Human Variome Project (HVP) Meeting "Integration and Implementation" was held under UNESCO Patronage in Paris, France, at the UNESCO Headquarters May 10-14, 2010. The major aims of the HVP are the collection, curation, and distribution of all human genetic variation affecting health. The HVP has drawn together disparate groups, by country, gene of interest, and expertise, who are working for the common good with the shared goal of pushing the boundaries of the human variome and collaborating to avoid unnecessary duplication. The meeting addressed the 12 key areas that form the current framework of HVP activities: Ethics; Nomenclature and Standards; Publication, Credit and Incentives; Data Collection from Clinics; Overall Data Integration and Access-Peripheral Systems/Software; Data Collection from Laboratories; Assessment of Pathogenicity; Country Specific Collection; Translation to Healthcare and Personalized Medicine; Data Transfer, Databasing, and Curation; Overall Data Integration and Access-Central Systems; and Funding Mechanisms and Sustainability. In addition, three societies that support the goals and the mission of HVP also held their own Workshops with the view to advance disease-specific variation data collection and utilization: the International Society for Gastrointestinal Hereditary Tumours, the Micronutrient Genomics Project, and the Neurogenetics Consortium.

Genome Biology has built a reputation in the community for our strong data deposition policies We require our published methods and software to have their source code deposited on a public software repository, such as Github, and in a DOI-assigning repository, such as zenodo. The source code must also be released under an open source license compliant with OSI, and this must be clearly stated on the repository and in the manuscript. Not only is it essential to have code available for reproducing results, but it enables other researchers to build on the work or find potential pitfalls of a method.

&lt;em&gt;Beginning WebGL for HTML5&lt;/em&gt; gets you rapidly up to speed with WebGL, a powerful new graphics language within the browser. You'll render realistic scenes with advanced lighting models, shadows, blending and textures. You'll also use mathematics to model fractals and particle systems. Going beyond that, &lt;em&gt;Beginning WebGL for HTML5&lt;/em&gt; presents advanced vertex and fragment shader usage for creating stunning, top-end results. &lt;br&gt; &lt;br&gt; You'll benefit from using modern frameworks to rapidly develop complex scenes, and make use of many tools to help improve rendering performance and debugging. &lt;em&gt;Beginning WebGL for HTML5 &lt;/em&gt;builds your critical WebGL development skills while being enjoyable at each step of the way. &lt;br&gt; &lt;ul&gt; &lt;li&gt;Quickly get up to speed with WebGL &lt;/li&gt; &lt;li&gt;Render realistic scenes &lt;/li&gt; &lt;li&gt;Work faster with frameworks &lt;/li&gt; &lt;li&gt;Improve rendering performance &lt;/li&gt; &lt;/ul&gt;

Major advances in fundamental mechanisms underlying (patho)physiology over the past decades have generated a robust therapeutic armamentarium; exemplifi ed by synthetic hormones, multigenerational antibiotics, and recombinant vaccines, off ering eff ective interventions across a range of diseases. Th e exponential ascent of the new biology has transformed the comprehension of human health and disease and revolutionized technology; redefi ning clinical pharmacology in the context of discovery and translation, and the role of the clinical pharmacologist as the bridge between the laboratory and the patient, and thence to the population at large. Th e integration of cross-disciplinary concepts emerging from discovery and driving therapeutic solutions has imposed an evolutionary pressure on clinical pharmacology to focus on the identifi cation and application of tools for prognosis, prediction, cure, and, ultimately, prevention in pursuit of personalized medicine. Th e promise of clinical pharmacology and its impact on the future of therapeutics, in the emerging areas of combinatorial pharmacogenetics, targeted interference with disease, as well as stem cell–based tissue engineering and regeneration (to name a few), extends

Inflammation in response to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection drives severity of coronavirus disease 2019 (COVID-19) and is influenced by host genetics. To understand mechanisms of inflammation, animal models that reflect genetic diversity and clinical outcomes observed in humans are needed. We report a mouse panel comprising the genetically diverse Collaborative Cross (CC) founder strains crossed to human ACE2 transgenic mice (K18-hACE2) that confers susceptibility to SARS-CoV-2. Infection of CC x K18-hACE2 resulted in a spectrum of survival, viral replication kinetics, and immune profiles. Importantly, in contrast to the K18-hACE2 model, early type I interferon (IFN-I) and regulated proinflammatory responses were required for control of SARS-CoV-2 replication in PWK x K18-hACE2 mice that were highly resistant to disease. Thus, virus dynamics and inflammation observed in COVID-19 can be modeled in diverse mouse strains that provide a genetically tractable platform for understanding anti-coronavirus immunity.