Scientific Programming Research Articles

PyCO2SYS v1.8: marine carbonate system calculations in Python

Abstract. Oceanic dissolved inorganic carbon (TC) is the largest pool of carbon that substantially interacts with the atmosphere on human timescales. Oceanic TC is increasing through uptake of anthropogenic carbon dioxide (CO2), and seawater pH is decreasing as a consequence. Both the exchange of CO2 between the ocean and atmosphere and the pH response are governed by a set of parameters that interact through chemical equilibria, collectively known as the marine carbonate system. To investigate these processes, at least two of the marine carbonate system's parameters are typically measured – most commonly, two from TC, total alkalinity (AT), pH, and seawater CO2 fugacity (fCO2; or its partial pressure, pCO2, or its dry-air mole fraction, xCO2) – from which the remaining parameters can be calculated and the equilibrium state of seawater solved. Several software tools exist to carry out these calculations, but no fully functional and rigorously validated tool written in Python, a popular scientific programming language, was previously available. Here, we present PyCO2SYS, a Python package intended to fill this capability gap. We describe the elements of PyCO2SYS that have been inherited from the existing CO2SYS family of software and explain subsequent adjustments and improvements. For example, PyCO2SYS uses automatic differentiation to solve the marine carbonate system and calculate chemical buffer factors, ensuring that the effect of every modelled solute and reaction is accurately included in all its results. We validate PyCO2SYS with internal consistency tests and comparisons against other software, showing that PyCO2SYS produces results that are either virtually identical or different for known reasons, with the differences negligible for all practical purposes. We discuss insights that guided the development of PyCO2SYS: for example, the fact that the marine carbonate system cannot be unambiguously solved from certain pairs of parameters. Finally, we consider potential future developments to PyCO2SYS and discuss the outlook for this and other software for solving the marine carbonate system. The code for PyCO2SYS is distributed via GitHub (https://github.com/mvdh7/PyCO2SYS, last access: 23 December 2021) under the GNU General Public License v3, archived on Zenodo (Humphreys et al., 2021), and documented online (https://pyco2sys.readthedocs.io/en/latest/, last access: 23 December 2021).

4-H Water Wizards: Lessons Learned for Effective Afterschool Science Programming

The University of California 4-H Youth Development Program created the 4-H Water Wizards project in response to two related issues: the need for high-quality science education programming in afterschool settings, and the desire to foster a citizenry that understands and can make informed decisions about water. In collaboration with afterschool program staff, Sacramento County 4-H implemented the 12-week water education project for children in grades four through six. We evaluated the program over four years (2012–2016) utilizing a pretest-posttest study design and evaluation surveys from participants and program staff. Our findings indicate positive outcomes both for program staff who delivered the project and for the children who participated in the program. Afterschool program staff gained competence in delivering hands-on and inquiry-based science programming. Fourth- and fifth-grade students demonstrated small but significant knowledge gain about water. Students also demonstrated increased awareness about water issues and water conservation behavior. We discuss our findings for both groups and share our insights for promising practices when collaborating with afterschool providers, especially relating to the importance and challenge of science education in afterschool settings.

Content queries and in-depth analysis on version-controlled software

Writing scientific code usually implies the need to coordinate and conflate the contributions of several scientific programmers. Using Git hosting services eases this process, because the hosting services offer many features, which assist in collaborated work on code. The well-established hosting service GitHub has seen continuous growth in terms of number of users, repositories and commits over the last few years; therefore it offers a large data source of scientific codes as well as social interaction of associated scientific programmers.We present a tool, which allows to easily search through relevant GitHub repositories and perform more advanced analyses, which cannot be conducted solely with the GitHub API. Our tool combines benefits from online as well as offline approaches to retrieve and analyse data to optimise time of execution and consumption of storage.We discuss possible use cases and demonstrate the tool's capabilities by investigating the popularity of OpenMP directives in the scientific community.

School Age Programs and Services Committee: Learning Beyond: Twenty-First-Century Summer and Out of School Time Toolkit

This fall, library staff serving school-age children have a new ALSC toolkit with a supportive framework that applies year round: Learning Beyond, available online at https://bit.ly/3FR5BUT. Here are a couple key tools from the work that I think especially apply to programs and services during this school year.Firstly, the case studies in each section show how libraries of different sizes and structures put these tools into practice. This grounded approach ties together the breadth of ALSC membership and illuminates the structure and topics with examples. These examples are from the task force members’ own experiences leading this work and many center on STEAM as a tool for building equity and access. Case studies are handy for demonstrating proven relevant results of investing in scientific and makerspace equipment and programming partnerships to funders in your community and your boss or board.

MFAST: A MATLAB toolbox for ocean bottom seismometer refraction first-arrival traveltime tomography

First-arrival seismic traveltime tomography (FAST) is a well-established technique to estimate subsurface velocity structures. Although several existing open-source packages are available for first-arrival traveltime tomography, most were written in compiled languages and lack sufficient extendibility for new algorithms and functionalities. In this work, we develop an open-source, self-contained FAST package based on MATLAB, one of the most popular interpreted scientific programming languages, with a focus on ocean bottom seismometer refraction traveltime tomography. Our package contains a complete traveltime tomography workflow, including ray-tracing-based first-arrival traveltime computation, linearized inversion, quality control, and high-quality visualization. We design the package as a modular toolbox, making it convenient to integrate new algorithms and functionalities as needed. At the current stage, our package is most efficient for performing FAST for two-dimensional ocean bottom seismometer surveys. We demonstrate the efficacy and accuracy of our package by using a synthetic data example based on a modified Marmousi model.

Using Machine Learning to Identify At-risk Students in an Introductory Programming Course at a Two-year Public College

In the United States, more than one-third of students enrolling in introductory computer science programming courses (CS101) do not succeed. To improve student success rates, this research team used supervised machine learning to identify students who are “at risk” of not succeeding in CS101 at a two-year public college. The resultant predictive model accurately identifies ≈99% of at-risk students in an out-of-sample test dataset. The programming instructor piloted the use of the model’s predictive factors as early alert triggers to intervene with individualized outreach and support across three course sections of CS101 in fall 2020. The outcome of this pilot study was a 23% increase in student success and a 7.3 percentage point decrease in the DFW rate. More importantly, this study identified academic, early alert triggers for CS101. The first two graded programs are of paramount importance for student success in the course.

Using 4-H Animal Science Programming to Improve One Health

Zoonoses, or diseases that can be transferred between humans and animals, such as variant swine influenza, avian influenza A viruses, and coronaviruses, comprise a large percentage of all newly identified and existing infectious diseases (Centers for Disease Control and Prevention, 2017). As a result, there is an ever-growing need for a One Health approach towards preventing and controlling zoonotic diseases. To better manage these public health risks at the human-animal-environment interface, Maryland 4-H and Maryland Department of Health initiated a statewide, multi-agency collaborative partnership. Through steps taken to collectively develop and implement long-term strategies to prevent future variant influenza outbreaks in Maryland, a valuable One Health partnership was developed. As a result, the Healthy Animals | Healthy YOUth program, novel influenza, and other zoonotic disease subject matter content was delivered using multiple approaches, including 1) the addition of new content to an already existing online 4-H Animal Husbandry and Quality Assurance program, 2) distribution of 120 resource kits across two states containing a collection of 24 hands-on lessons, resource documents, and supplemental teaching materials, 3) in-person and virtual train-the-trainer sessions, 4) youth workshops, 5) educational and hands-on activity videos, and 6) standardized fair signage for use at animal exhibits.

Healthcare Big Data Management and Analytics in Scientific Programming

Healthcare Big Data Management and Analytics in Scientific Programming

Type stability in Julia: avoiding performance pathologies in JIT compilation

As a scientific programming language, Julia strives for performance but also provides high-level productivity features. To avoid performance pathologies, Julia users are expected to adhere to a coding discipline that enables so-called type stability. Informally, a function is type stable if the type of the output depends only on the types of the inputs, not their values. This paper provides a formal definition of type stability as well as a stronger property of type groundedness, shows that groundedness enables compiler optimizations, and proves the compiler correct. We also perform a corpus analysis to uncover how these type-related properties manifest in practice.

I Explain, You Collaborate, He Cheats: An Empirical Study with Social Network Analysis of Study Groups in a Computer Programming Subject

Students interact with each other in order to solve computer science programming assignments. Group work is encouraged because it has been proven to be beneficial to the learning process. However, sometimes, collaboration might be confused with dishonest behaviours. This article aimed to quantitatively discern between both cases. We collected code similarity measures from students over four academic years and analysed them using statistical and social network analyses. Three studies were carried out: an analysis of the knowledge flow to identify dishonest behaviour, an analysis of the structure of the social organisation of study groups and an assessment of the relationship between successful students and social behaviour. Continuous dishonest behaviour in students is not as alarming as many studies suggest, probably due to the strict control, automatic plagiarism detection and high penalties for unethical behaviour. The boundary between both is given by the amount of similar content and regularity along the course. Three types of study groups were identified. We also found that the best performing groups were not made up of the best individual students but of students with different levels of knowledge and stronger relationships. The best students were usually the central nodes of those groups.

Tailoring Our Approach in Response to the SARS-CoV-2 Pandemic and Transcending Science Outreach Modalities for Native American Students in a Cancer Research Education Program.

In response to the SARS-CoV-2 pandemic, a cancer research education program at the University of Nebraska Medical Center designed for Native American middle school, high school and undergraduate students adapted activities to be delivered online. There are considerable challenges to adapting in-person science programming to online delivery that can impact overall effectiveness. These challenges are further exacerbated when the cognate student population also faces significant disparities in health, wealth, and educational outcomes. We encountered both disadvantages and advantages in transitioning programming to online virtual formats. Challenges faced in delivering our programming during the pandemic included varied online accessibility, peripheral stressors, and disconnection to places and people. Despite these challenges, we found several benefits in remote delivery, some of which have alleviated barriers to program participation for Native American students. Some successes achieved by transitioning to fully remote programming included increased program reach, sustainability, and cultural relevancy. In this overview of the implementation of four online programs at the middle school, high school, and undergraduate levels, we highlight the challenges and successes experienced. Through this program description, we aim to provide insight into potential strategies to improve program delivery designed for Native American students during the SARS-CoV-2 pandemic and beyond.

Gauging Informal STEM Youth Program Impact: A Conceptual Framework and a Measurement Instrument

STEM education programs are often formulated with a "hands-on activities" focus across a wide array of topics from robotics to rockets to ecology. Traditionally, the impact of these programs is based on surveys of youth on program-specific experiences or the youths’ interest and impressions of science in general. In this manuscript, we offer a new approach to analyzing science programming design and youth participant impact. The conceptual framework discussed here concentrates on the organization and analysis of common learning activities and instructional strategies. We establish instrument validity and reliability through an analysis of validity threats and pilot study results. We conclude by using this instrument in an example analysis of a STEM education program.

Unimapper: An Online Interactive Analyzer/Visualizer of Optical Mapping Experimental Data.

Time series of spatially-extended two-dimensional recordings are the cornerstone of basic and clinical cardiac electrophysiology. The data source may be either multipolar catheters, multi-electrode arrays, optical mapping with the help of voltage and calcium-sensitive fluorescent dyes, or the output of simulation studies. The resulting data cubes (usually two spatial and one temporal dimension) are shared either as movie files or, after additional processing, various graphs and tables. However, such data products can only convey a limited view of the data. It will be beneficial if the data consumers can interactively process the data, explore different processing options and change its visualization. This paper presents the Unified Electrophysiology Mapping Framework (Unimapper) to facilitate the exchange of electrophysiology data. Its pedigree includes a Java-based optical mapping application. The core of Unimapper is a website and a collection of JavaScript utility functions for data import and visualization (including multi-channel visualization for simultaneous voltage/calcium mapping), basic image processing (e.g., smoothing), basic signal processing (e.g., signal detrending), and advanced processing (e.g., phase calculation using the Hilbert transform). Additionally, Unimapper can optionally use graphics processing units (GPUs) for computationally intensive operations. The Unimapper ecosystem also includes utility libraries for commonly used scientific programming languages (MATLAB, Python, and Julia) that allow the data producers to convert images and recorded signals into a standard format readable by Unimapper. Unimapper can act as a nexus to share electrophysiology data - whether recorded experimentally, clinically or generated by simulation - and enhance communication and collaboration among researchers.

QSPcc reduces bottlenecks in computational model simulations

Mathematical models have grown in size and complexity becoming often computationally intractable. In sensitivity analysis and optimization phases, critical for tuning, validation and qualification, these models may be run thousands of times. Scientific programming languages popular for prototyping, such as MATLAB and R, can be a bottleneck in terms of performance. Here we show a compiler-based approach, designed to be universal at handling engineering and life sciences modeling styles, that automatically translates models into fast C code. At first QSPcc is demonstrated to be crucial in enabling the research on otherwise intractable Quantitative Systems Pharmacology models, such as in rare Lysosomal Storage Disorders. To demonstrate the full value in seamlessly accelerating, or enabling, the R&D efforts in natural sciences, we then benchmark QSPcc against 8 solutions on 24 real-world projects from different scientific fields. With speed-ups of 22000x peak, and 1605x arithmetic mean, our results show consistent superior performances.

The floating point: Tales of the unexpected

Digital computation is central to almost all scientific endeavors and has become integral to university physics education. Students collect experimental data using digital devices, process data using spreadsheets and graphical software, and develop scientific programming skills for modeling, simulation, and computational work. Issues associated with the floating-point representation of numbers are rarely explored. In this article, problems of floating point are divided into three categories: significant-figure limits, propagation of floating-point representation error, and rounding. For each category, examples are presented of unexpected ways, in which the digital representation of floating-point numbers can impact the veracity of scientific results. These examples cover aspects of classical dynamics, numerical integration, cellular automata, statistical analysis, and digital timing. Suggestions are made for curriculum enhancement and project-style investigations that reinforce the issues covered at a level suitable for physics undergraduate students.

The Role Of Family Support In Physical Activity And Motor Development In Adolescents

[Abstract]OBJECTIVE: The aim of this study was to explore the relationship between family background and parental support and physical activity and motor competence in adolescents, and to provide a theoretical basis for the health promotion of children and adolescents in China. METHODS: Select a junior high school in Shanxi Province 12 ~ 14 years old, 140 junior high school students (male 70, female 70) as the research object, the ActiGraph GT3X + model of accelerometer are used to records research object for 7d physical activity, and questionnaire to collect the basic information of the subjects' parents, adopting The Activity Support Scale for Chinese (ACTS - CN) to evaluate the behavior of parents to the child activity support and attitude, The Canadian Agility And Movement Skill Assessment CAMSA was used to evaluate the motor competence development of adolescents. RESULTS: Male students participated in MVPA for 40.57 min every day, while female students participated in MVPA for 31.65 min every day. Male students had higher MVPA than female students. In the motor skill test, the average skill score of male students is 10.8, and the completion time is 17.7 s, while the average skill score of female students is 10.1, and the completion time is 19.1 s. There is no significant difference between the score and completion time of male and female students. Under different family backgrounds, children's sports behaviors are different. Supportive parents are positively correlated with their children's physical activity and motor competence. CONCLUSION: Family environment plays an important role in promoting physical activity and developing motor competence of adolescents, the company of parents and support can significantly affect a child's behavior from several aspects, intervention strategies for adolescent health promotion can include promoting parental activities, through the parents' role models for activity behaviors among adolescents internalizing positive attitude and behavior.[Key words] Family support; Physical activity; Motor competence; Teenagers Supported by Beijing education science programming project(BEAA19045)

Scientific Programming Tools for Water Management

This special issue delivers a platform in which researchers expose intersections between algorithm design, software platforms, and hardware architectures to deal with emerging challenges in the scientific field of management of water and water-dependent resources. Since the call for papers was announced in June 2019, this special issue has received 10 manuscripts. After a rigorous review process, 6 papers have been finally accepted for publication. Published papers deal with groundwater quality monitoring, coastal groundwater-dependent irrigation agriculture, desertification risk, water recovery from tailings, future scenarios of water resources, and vulnerability of coastal aquifers.

Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective

Abstract. Following the rise of R as a scientific programming language, the increasing requirement for more transferable research and the growth of data availability in hydrology, R packages containing hydrological models are becoming more and more available as an open-source resource to hydrologists. Corresponding to the core of the hydrological studies workflow, their value is increasingly meaningful regarding the reliability of methods and results. Despite package and model distinctiveness, no study has ever provided a comparison of R packages for conceptual rainfall–runoff modelling from a user perspective by contrasting their philosophy, model characteristics and ease of use. We have selected eight packages based on our ability to consistently run their models on simple hydrology modelling examples. We have uniformly analysed the exact structure of seven of the hydrological models integrated into these R packages in terms of conceptual storages and fluxes, spatial discretisation, data requirements and output provided. The analysis showed that very different modelling choices are associated with these packages, which emphasises various hydrological concepts. These specificities are not always sufficiently well explained by the package documentation. Therefore a synthesis of the package functionalities was performed from a user perspective. This synthesis helps to inform the selection of which packages could/should be used depending on the problem at hand. In this regard, the technical features, documentation, R implementations and computational times were investigated. Moreover, by providing a framework for package comparison, this study is a step forward towards supporting more transferable and reusable methods and results for hydrological modelling in R.

Consider the following: A pilot study of the effects of an educational television program on viewer perceptions of anthropogenic climate change and ocean acidification

Climate change portends significant harms to humans and biodiversity but public knowledge of relevant scientific information remains limited. As societal changes and investment are essential to addressing anthropogenic climate change, efforts to better promote both civic science literacy and public awareness of climate change impacts are urgently required. Popular scientific television programming provides one avenue for broad climate change communication efforts. Our pilot study seeks to evaluate the effects viewing a popular scientific television program, “Bill Nye Saves the World: The Earth is a hot mess” on both fact recall and personal perceptions. We surveyed undergraduate students enrolled in non-majors courses at two institutions of higher education, one large selective private university, and one community college with open enrollment before and after viewing this program. The survey contained both open-response questions and Likert-like ordinal responses intended to evaluate both fact recall and beliefs related to climate change. After viewing the program, student awareness of climate change impacts was improved, especially for topics emphasized by the program such as sea level rise. Student awareness of ocean acidification was extremely low prior to viewing the program, and improved dramatically, with most respondents aware that ocean acidification is already impacting marine life after viewing. Our pilot study suggests that scientific television programs may successfully promote awareness of climate change impacts and increase perceived personal relevance of climate change, but additional data from a larger and demographically broad population is required to test whether this result is more broadly applicable. Supplemental data for this article is available online at https://doi.org/10.1080/10899995.2021.1949693

School and Community Garden Pollinator Census: A Pilot Project in Georgia

Abstract During 2017 and 2018, gardeners at 36 locations across 21 Georgia counties volunteered to be part of the Georgia Pollinator Census project. The goals of the project were to generate a snapshot of pollinator population data while educating gardeners about the importance of pollinators and other beneficial insects and assisting schools with science, technology, engineering, art, and math programming. Effective insect identification training and on-going support were crucial parts of this citizen science project. Insect counting was conducted in September and October on an aster species and another plant species chosen by the participants. Twenty-eight plant taxa were chosen by participants to be frequently visited by pollinators. Analysis of the data indicates a higher number of sightings of bumble bees, Bombus spp. Latrelle (Hymenoptera: Apidae); honey bees, Apis mellifera L. (Hymenoptera: Apidae), and wasps (Hymenoptera: Vespidae) in rural areas and a higher number of sightings of carpenter bees, Xylocopa spp. Latrelle (Hymenoptera: Apidae); flies (Diptera); and “other insects” (e.g., those that did not fall into any of the other seven categories) in urban areas. We also saw an increase in entomological interest among the participants as well as an increase in insect knowledge. This pilot project was used to refine criteria for a larger state-wide census.