Hands-on Tutorials Research Articles

On the elements of an excellent research paper

Journal publications play a key role in the dissemination of research findings in the biomedical acoustics community. However, authors are often unsure of how to write a paper that will be considered as excellent by their peers, because the notion of excellence is arguably subjective and ill-defined. To demystify such an issue, this presentation will discuss four major elements (novelty, significance, rigor, writing quality) that are often found in excellent journal papers in biomedical ultrasound. Since 2022, these four elements have been adopted as the peer review criteria by the flagship ultrasonics journal of the IEEE press. Multi-day writing workshops with interactive, hands-on tutorials have been designed to engage prospective authors on how to plan and prepare journal manuscripts with the four elements of excellence. Reviewer training workshops have also been offered to inform journal reviewers about these evaluation criteria and expectations. Through these initiatives, we aim to establish a quality-driven publishing emphasis within the biomedical acoustics community. Achieving so will have long-term benefits on the reputation and growth of this research field.

Teaching advanced statistical methods to postgraduate novices: a case example

Higher degree research students in education are largely underprepared for understanding or employing statistical data analysis methods. This is despite their need to read literature in their field which will indubitably include such research. This weakness may result in students choosing to use qualitative or interpretivist methodologies, even though education data are highly complex requiring sophisticated analysis techniques to properly evaluate the impact of nested data, multi-collinear factors, missing data, and changes over time. This paper describes a research methods course at a research-intensive university designed for students in a thesis-only degree program. The course emphasizes the logic and conceptual function of statistical methods and exposes students to hands-on tutorials in which students are required to conduct analyses with open-access data. The first half of the 12-week course focuses on core knowledge, normally taught in first-year probability and statistics courses. The second half focuses on introducing and modeling advanced statistical methods needed to handle complex problems and data. The course outline is provided along with descriptions of teaching and assessments. This exemplar functions as a potential model of how relative novices in statistical methods can be introduced to a conceptual use of statistical methods to raise the credibility of research.

Assessment of knowledge and utilization of electrocardiogram by primary health care physicians and nurses in Qassim Region, Saudi Arabia

Objective: This study aimed to assess primary care physicians' and nurses' knowledge and utilization of electrocardiograms (ECG) in primary health care centers (PHCCs) in Qassim, Saudi Arabia. Methods: A cross-sectional study was conducted among PHCC physicians and nurses in Qassim Region, Saudia Arabia. An online self-administered questionnaire was used to obtain information about the knowledge and use of ECG. Results: A total of 320 physicians, family medicine residents, and nurses participated in the survey. Out of the participants, 174 (54.4%) were females. The majority (n=130, 40.6%) were aged between 31 and 40 years. In terms of the number of ECGs requested per week, approximately half of the participants, 158 (49.4%), requested ECGs two to five times per week. The most common reason for ECG requests was angina at 279 (87.2%), followed by arrhythmia at 139 (66.3%) and hypertension at 80 (25.0%). A majority of the doctors (56.3%) reported receiving ECG interpretation from senior colleagues. The most common ECG diagnosis reported was normal ECG among 296 (92.5%). Furthermore, 114 (35.6%) of the participants stated that they believed bedside teaching was the most effective way to improve ECG knowledge and its practical use. Conclusion: This study revealed that primary care physicians and nurses in Qassim, Saudi Arabia, had a limited understanding of and limited use for ECGs. It is strongly recommended to provide bedside training, hands-on tutorials during clinical rotations, and workshops/continuous medical education (CMEs) to enhance ECG knowledge, attitude, and utilization.

QERaman: An open-source program for calculating resonance Raman spectra based on Quantum ESPRESSO

We present an open-source program QERaman that computes first-order resonance Raman spectroscopy of materials using the output data from Quantum ESPRESSO. Complex values of Raman tensors are calculated based on the quantum description of the Raman scattering from calculations of electron-photon and electron-phonon matrix elements, which are obtained by using the modified Quantum ESPRESSO. Our program also calculates the resonant Raman spectra as a function of incident laser energy for linearly- or circularly-polarized light. Hands-on tutorials for graphene and MoS2 are given to show how to run QERaman. All codes, examples, and scripts are available on the GitHub repository. Program summaryProgram Title:QERamanCPC Library link to program files:https://doi.org/10.17632/ddcrrrmxw9.1Developer's repository link:https://github.com/nguyen-group/QERamanLicensing provisions: GNU General Public Licence 3.0Programming language: FortranExternal routines:Quantum ESPRESSO v7.2Nature of problem: Resonance Raman spectra with first-principles calculations.Solution method: The Raman intensity formula is given by the quantum theory, in which the electron-photon and the electron-phonon matrix elements are obtained from the modified Quantum ESPRESSO package.

Theoretical and computational tools to model multistable gene regulatory networks.

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.

Ten Topics to Get Started in Medical Informatics Research.

The vast and heterogeneous data being constantly generated in clinics can provide great wealth for patients and research alike. The quickly evolving field of medical informatics research has contributed numerous concepts, algorithms, and standards to facilitate this development. However, these difficult relationships, complex terminologies, and multiple implementations can present obstacles for people who want to get active in the field. With a particular focus on medical informatics research conducted in Germany, we present in our Viewpoint a set of 10 important topics to improve the overall interdisciplinary communication between different stakeholders (eg, physicians, computational experts, experimentalists, students, patient representatives). This may lower the barriers to entry and offer a starting point for collaborations at different levels. The suggested topics are briefly introduced, then general best practice guidance is given, and further resources for in-depth reading or hands-on tutorials are recommended. In addition, the topics are set to cover current aspects and open research gaps of the medical informatics domain, including data regulations and concepts; data harmonization and processing; and data evaluation, visualization, and dissemination. In addition, we give an example on how these topics can be integrated in a medical informatics curriculum for higher education. By recognizing these topics, readers will be able to (1) set clinical and research data into the context of medical informatics, understanding what is possible to achieve with data or how data should be handled in terms of data privacy and storage; (2) distinguish current interoperability standards and obtain first insights into the processes leading to effective data transfer and analysis; and (3) value the use of newly developed technical approaches to utilize the full potential of clinical data.

ForeTiS: A comprehensive time series forecasting framework in Python

Summary: Time series forecasting is a research area with applications in various domains, nevertheless without yielding a predominant method so far. We present ForeTiS, a comprehensive and open source Python framework that allows rigorous training, comparison, and analysis of state-of-the-art time series forecasting approaches. Our framework includes fully automated yet configurable data preprocessing and feature engineering. In addition, we use advanced Bayesian optimization for automatic hyperparameter search. ForeTiS is easy to use, even for non-programmers, requiring only a single line of code to apply state-of-the-art time series forecasting. Various prediction models, ranging from classical forecasting approaches to machine learning techniques and deep learning architectures, are already integrated. More importantly, as a key benefit for researchers aiming to develop new forecasting models, ForeTiS is designed to allow for rapid integration and fair benchmarking in a reliable framework. Thus, we provide a powerful framework for both end users and forecasting experts.Availability:ForeTiS is available at https://github.com/grimmlab/ForeTiS. We provide a setup using Docker, as well as a Python package at https://pypi.org/project/ForeTiS/. Extensive online documentation with hands-on tutorials and videos can be found at https://foretis.readthedocs.io.

EasyPheno: An easy-to-use and easy-to-extend Python framework for phenotype prediction using Bayesian optimization.

Predicting complex traits from genotypic information is a major challenge in various biological domains. With easyPheno, we present a comprehensive Python framework enabling the rigorous training, comparison and analysis of phenotype predictions for a variety of different models, ranging from common genomic selection approaches over classical machine learning and modern deep learning-based techniques. Our framework is easy-to-use, also for non-programming-experts, and includes an automatic hyperparameter search using state-of-the-art Bayesian optimization. Moreover, easyPheno provides various benefits for bioinformaticians developing new prediction models. easyPheno enables to quickly integrate novel models and functionalities in a reliable framework and to benchmark against various integrated prediction models in a comparable setup. In addition, the framework allows the assessment of newly developed prediction models under pre-defined settings using simulated data. We provide a detailed documentation with various hands-on tutorials and videos explaining the usage of easyPheno to novice users. easyPheno is publicly available at https://github.com/grimmlab/easyPheno and can be easily installed as Python package via https://pypi.org/project/easypheno/ or using Docker. A comprehensive documentation including various tutorials complemented with videos can be found at https://easypheno.readthedocs.io/. Supplementary data are available at Bioinformatics Advances online.

The Bioinformatics Virtual Coordination Network: An Open-Source and Interactive Learning Environment

Lockdowns and “stay-at-home” orders, starting in March 2020, shuttered bench and field dependent research across the world as a consequence of the global COVID-19 pandemic. The pandemic continues to have an impact on research progress and career development, especially for graduate students and early career researchers, as strict social distance limitations stifle ongoing research and impede in-person educational programs. The goal of the Bioinformatics Virtual Coordination Network (BVCN) was to reduce some of these impacts by helping research biologists learn new skills and initiate computational projects as alternative ways to carry out their research. The BVCN was founded in April 2020, at the peak of initial shutdowns, by an international group of early-career microbiology researchers with expertise in bioinformatics and computational biology. The BVCN instructors identified several foundational bioinformatic topics and organized hands-on tutorials through cloud-based platforms that had minimal hardware requirements (in order to maximize accessibility) such as RStudio Cloud and MyBinder. The major topics included the Unix terminal interface, R and Python programming languages, amplicon analysis, metagenomics, functional protein annotation, transcriptome analysis, network science, and population genetics and comparative genomics. The BVCN was structured as an open-access resource with a central hub providing access to all lesson content and hands-on tutorials (https://biovcnet.github.io/). As laboratories reopened and participants returned to previous commitments, the BVCN evolved: while the platform continues to enable “a la carte” lessons for learning computational skills, new and ongoing collaborative projects were initiated among instructors and participants, including a virtual, open-access bioinformatics conference in June 2021. In this manuscript we discuss the history, successes, and challenges of the BVCN initiative, highlighting how the lessons learned and strategies implemented may be applicable to the development and planning of future courses, workshops, and training programs.

SGI: automatic clinical subgroup identification in omics datasets.

SummaryThe ‘Subgroup Identification’ (SGI) toolbox provides an algorithm to automatically detect clinical subgroups of samples in large-scale omics datasets. It is based on hierarchical clustering trees in combination with a specifically designed association testing and visualization framework that can process an arbitrary number of clinical parameters and outcomes in a systematic fashion. A multi-block extension allows for the simultaneous use of multiple omics datasets on the same samples. In this article, we first describe the functionality of the toolbox and then demonstrate its capabilities through application examples on a type 2 diabetes metabolomics study as well as two copy number variation datasets from The Cancer Genome Atlas.Availability and implementationSGI is an open-source package implemented in R. Package source codes and hands-on tutorials are available at https://github.com/krumsieklab/sgi. The QMdiab metabolomics data is included in the package and can be downloaded from https://doi.org/10.6084/m9.figshare.5904022.Supplementary information Supplementary data are available at Bioinformatics online.

CPPS 101 - A Tutorial Introduction on Cyber-Physical Production Systems

Today we stand at the threshold of a new revolution towards Smart Manufacturing, which is leading us to the 4th Industrial Revolution. In a moment like this, companies need to adapt and go beyond existing industrial systems, into Cyber-Physical Production Systems (CPPS), to achieve added value. With this new revolution comes a new mindset and the need to train people to become aware of the major transformations, processes and concepts surrounding this new paradigm. The primary outcome of the CPPS 101 European project is the CPPS 101 e-learning course, which was designed to provide a clear and integrated view of CPPS. It covers the main essential topics and emergent technologies within Industry 4.0 in 8 different learning modules. Trainees have access to video tutorials, quizzes, and practical hands-on exercises that will help them learn and test their knowledge. Moreover, remote testbeds are available for the deployment and testing of developed applications within the hands-on tutorials. This work describes the CPPS 101 project main goals and results, while discussing the pedagogical approach and main benefits regarding the learning experience of Smart Manufacturing related topics.

Exploring the Feasibility of Comprehensive Uncertainty Assessment in Health Economic Modeling: A Case Study

ObjectivesDecision makers adopt health technologies based on health economic models that are subject to uncertainty. In an ideal world, these models parameterize all uncertainties and reflect them in the cost-effectiveness probability and risk associated with the adoption. In practice, uncertainty assessment is often incomplete, potentially leading to suboptimal reimbursement recommendations and risk management. This study examines the feasibility of comprehensive uncertainty assessment in health economic models. MethodsA state transition model on peripheral arterial disease treatment was used as a case study. Uncertainties were identified and added to the probabilistic sensitivity analysis if possible. Parameter distributions were obtained by expert elicitation, and structural uncertainties were either parameterized or explored in scenario analyses, which were model averaged. ResultsA truly comprehensive uncertainty assessment, parameterizing all uncertainty, could not be achieved. Expert elicitation informed 8 effectiveness, utility, and cost parameters. Uncertainties were parameterized or explored in scenario analyses and with model averaging. Barriers included time and resource constraints, also of clinical experts, and lacking guidance regarding some aspects of expert elicitation, evidence aggregation, and handling of structural uncertainty. The team’s multidisciplinary expertise and existing literature and tools were facilitators. ConclusionsWhile comprehensive uncertainty assessment may not be attainable, improvements in uncertainty assessment in general are no doubt desirable. This requires the development of detailed guidance and hands-on tutorials for methods of uncertainty assessment, in particular aspects of expert elicitation, evidence aggregation, and handling of structural uncertainty. The issue of benefits of uncertainty assessment versus time and resources needed remains unclear.

Investigating the use of hands-on tutorials to teach civic online reasoning

With the rise of misinformation, there is a great need for scalable educational interventions supporting students’ abilities to determine the trustworthiness of digital news. We address this challenge in our study by developing an online intervention tool based on tutorials in civic online reasoning that aims to teach people how to critically assess online information comprising text, videos, and images. Our findings from an online intervention with 209 participants highlight how observational learning and feedback may support students' lateral reading and ability to determine credibility of digital news and social media posts.

Orchestrating a community-developed computational workshop and accompanying training materials.

The importance of bioinformatics, computational biology, and data science in biomedical research continues to grow, driving a need for effective instruction and education. A workshop setting, with lectures and guided hands-on tutorials, is a common approach to teaching practical computational and analytical methods. Here, we detail the process we used to produce high-quality, community-authored educational materials that are available for public consumption and reuse. The coordinated efforts of 17 authors over 10 weeks resulted in 15 workshops available as a website and as a 388-page electronic book. We describe how we utilized cloud infrastructure, GitHub, and a literate programming approach to robustly deliver hands-on tutorials to participants of the annual Bioconductor conference. The scripts, raw and published workshop materials, and cloud machine image are all openly available. Our approach uses free services and software and can be adapted by workshop organizers and authors in other contests with appropriate technical backgrounds.

ADLES: Specifying, deploying, and sharing hands-on cyber-exercises

Hands-on tutorials and exercises are recognized as an effective means for gaining much needed cybersecurity and communication and information technology skills. These exercises must be performed in dedicated and virtually isolated computing environments or laboratories, most of which make use of virtualization technology. Building, modifying, and deploying the virtual environments that enable hands-on instruction is currently very time consuming. A new complete exercise instance must be deployed and configured for each course or module, tutorial or exercise, and student. In addition, efficient sharing and reuse of hands-on exercises between organizations is currently extremely difficult, unless the computing resources and virtualization environment are also shared. ADLES is a specification language and associated deployment system created to address these issues up-front. ADLES enables: (1) the formal specification of hands-on virtual computing, networking, and cybersecurity exercises, (2) the automated deployment of specified exercises, and (3) the efficient sharing of such exercises and their computing environment. In this article, we describe in detail the ADLES specification language and deployment system. We also demonstrate ADLES capabilities using two case studies: a pentesting tutorial and a cyber defense competition. The ADLES system is open source and available for all educators to use and improve.

Gene Graphics: a genomic neighborhood data visualization web application.

The examination of gene neighborhood is an integral part of comparative genomics but no tools to produce publication quality graphics of gene clusters are available. Gene Graphics is a straightforward web application for creating such visuals. Supported inputs include National Center for Biotechnology Information gene and protein identifiers with automatic fetching of neighboring information, GenBank files and data extracted from the SEED database. Gene representations can be customized for many parameters including gene and genome names, colors and sizes. Gene attributes can be copied and pasted for rapid and user-friendly customization of homologous genes between species. In addition to Portable Network Graphics and Scalable Vector Graphics, produced representations can be exported as Tagged Image File Format or Encapsulated PostScript, formats that are standard for publication. Hands-on tutorials with real life examples inspired from publications are available for training. Gene Graphics is freely available at https://katlabs.cc/genegraphics/ and source code is hosted at https://github.com/katlabs/genegraphics. katherinejh@ufl.edu or remizallot@ufl.edu. Supplementary data are available at Bioinformatics online.

The eBioKit, a stand-alone educational platform for bioinformatics.

Bioinformatics skills have become essential for many research areas; however, the availability of qualified researchers is usually lower than the demand and training to increase the number of able bioinformaticians is an important task for the bioinformatics community. When conducting training or hands-on tutorials, the lack of control over the analysis tools and repositories often results in undesirable situations during training, as unavailable online tools or version conflicts may delay, complicate, or even prevent the successful completion of a training event. The eBioKit is a stand-alone educational platform that hosts numerous tools and databases for bioinformatics research and allows training to take place in a controlled environment. A key advantage of the eBioKit over other existing teaching solutions is that all the required software and databases are locally installed on the system, significantly reducing the dependence on the internet. Furthermore, the architecture of the eBioKit has demonstrated itself to be an excellent balance between portability and performance, not only making the eBioKit an exceptional educational tool but also providing small research groups with a platform to incorporate bioinformatics analysis in their research. As a result, the eBioKit has formed an integral part of training and research performed by a wide variety of universities and organizations such as the Pan African Bioinformatics Network (H3ABioNet) as part of the initiative Human Heredity and Health in Africa (H3Africa), the Southern Africa Network for Biosciences (SAnBio) initiative, the Biosciences eastern and central Africa (BecA) hub, and the International Glossina Genome Initiative.

Knowledge and utilization of electrocardiogram among resident doctors in family medicine in Nigeria.

Electrocardiogram (ECG) is a simple, readily affordable, and noninvasive tool for the evaluation of cardiac disorders. There is a dearth of information on the utility of ECG in general practice in Nigeria. We assessed the knowledge and utilization of ECG among family medicine residents in Nigeria. A cross-sectional evaluation was conducted between November 2011 and May 2012 in four family medicine training centers in Nigeria. A self-administered questionnaire was used to obtain information from the resident doctors regarding their ECG requests, preferred source of interpretation, most common ECG diagnosis, and update of ECG knowledge. Only 61 out of 120 questionnaires (50.8%) were returned. The respondents were mostly between 31 and 40 years (54.7%) and were predominantly males (73.8%) and senior residents (65.6%). Fifty-four (88.3%) respondents made <5 ECG requests/week, and the most common indication was hypertension (50%). ECG interpretation was either self-reported (41%), by a cardiologist (26.5%), or automated reports (21.3%). Self-reporting of ECG was more common among senior residents (P < 0.01). Left ventricular hypertrophy was the most common ECG diagnosis (55.8%). About 69% of respondents did not update their knowledge of ECG. Most respondents (50%) reported basic interpretation as the aspect of ECG for which further learning was desired. Teaching ECG to resident doctors in the update courses of the postgraduate medical colleges and continuing medical education (CME) activities was adjudged the best way to improve knowledge/utility (61.1%). The attitude to and utility of ECG among family medicine residents in Nigeria is poor. Improved knowledge, attitude, and utilization of ECG through curriculum revision, hands-on tutorials, and CMEs are highly recommended.

INTEGRATING A SHORT SIMULATION PROJECT INTO AN INTRODUCTORY TRANSPORT PHENOMENA COURSE

Transport phenomena is an integral part of many engineering curricula. Some programs, particularly in chemical engineering, teach transport phenomena in an integrated manner, but most teach heat, mass and momentum transfer in separate courses. Since powerful computers and software packages are now available to solve transport problems numerically, many current transport phenomena courses incorporate these tools for demonstration purposes. Many institutions also offer advanced level courses focusing on the use of this type of software, but the intuitive nature of modern software packages also permits the integration of these tools directly into introductory courses.This paper summarizes efforts made in the Department of Process Engineering and Applied Science at Dalhousie University to integrate one such tool, COMSOL Multiphysics, directly into the introductory transport phenomena course. In an introductory course, the time available to study software tools is inherently limited, and therefore it is necessary to introduce these topics as efficiently as possible. In our course, several hands-on tutorials are used to introduce students to COMSOL. We avoid focusing too much on numerical methods, error estimation techniques, or even detailed model validation techniques. Instead, these tutorials focus on using commercial software to solve transport problems and demonstrating good modeling practices. Near the end of the course, students are asked to complete a short modeling project. In the latest iteration, students were asked to reproduce a simulation in a recent journal publication, to expand on the results, and comment on the significance of their findings. The main challenges related to implementing such a project include selecting problems that do not have unreasonably high computational requirements, the increased workload for teaching assistants, the required level of expertise among teaching assistants, and the increased workload for students.

Decision tools for coral reef managers: Using participatory decision support to integrate potential climate impacts and informed decision making

The decline in coral reef health presents a complex management issue. While several causes of decline have been identified and are under continued study, it is often difficult to discern management actions necessary to address multiple near- and far-field stressors to these ecosystems. As a result, resource managers seek tools to improve the understanding of ecosystem condition and to develop management responses to reduce local and regional pressures in the wake of larger, global impacts. A research study conducted from 2010 to 2014 in southeast Florida, USA consisted of two objectives: (1) conduct a needs assessment survey with coral reef and marine resource managers to identify data needs and the preferred design and delivery of climate information; and (2) develop and evaluate prototype decision support tools. The needs assessment process was helpful for identifying the types of climate information managers would like to obtain to inform decision making and to specify the preferred format for the delivery of that information. Three prototype tools were evaluated by managers using pre/post surveys that included hands-on tutorials to explore the functionality of each. Manager responses were recorded using a five-point scale with 1 being No or Not Useful to 5 being Absolutely or Very Useful. The median responses rated the usefulness of the tools (4), if they would consider using the tool (4), and if they would recommend using the tool to other managers (4 or 5). The median response for increasing manager’s knowledge about climate impacts after completing a tutorial of each of the climate tools was a 3 (moderately useful). Of the managers surveyed in the pre/post-survey, all but one stated they believed they would use the decision support tools in the future with the single response due to wealth of data availability in their institution.