Programming Toolkit Research Articles

Meeting Report for the Phenoscape TraitFest 2023 with Comments on Organising Interdisciplinary Meetings

The Phenoscape project has developed ontology-based tools and a knowledge base that enables the integration and discovery of phenotypes across species from the scientific literature. The Phenoscape TraitFest 2023 event aimed to promote innovative applications that adopt the capabilities supported by the data in the Phenoscape Knowledgebase and its corresponding semantics-enabled tools, algorithms and infrastructure. The event brought together 26 participants, including domain experts in biodiversity informatics, taxonomy and phylogenetics and software developers from various life-sciences programming toolkits and phylogenetic software projects, for an intense four-day collaborative software coding event. The event was designed as a hands-on workshop, based on the Open Space Technology methodology, in which participants self-organise into subgroups to collaboratively plan and work on their shared research interests. We describe how the workshop was organised, the projects developed and outcomes resulting from the workshop, as well as the challenges in bringing together a diverse group of participants to engage productively in a collaborative environment.

Application of the Double Approximation Method for Constructing Stiffness Matrices of Volumetric Finite Elements

Introduction. When numerically solving problems of elasticity theory in a three-dimensional formulation by the finite element method, finite elements (FE) in the form of parallelepipeds, prisms and tetrahedra are used. Regularly, the construction of stiffness matrices of volumetric FE is based on the principle of isoparametricity, which involves the Lagrange polynomials to approximate the geometry and displacements. In computational practice, the most widespread FE are the so-called multilinear isoparametric FE with a linear law of approximation of displacements. The main disadvantage of these elements lies in the “locking” effect when modulating bending deformations. Moreover, the error of the numerical solution increases drastically in the case when the structure, in comparison to conventional deformations, undergoes significant displacements as a rigid whole. Long-term experience in solving problems of deformable solid mechanics by the finite element method has shown that existing volumetric FE have slow convergence, specifically, when modeling bending deformations of plates and shells. This study aims at constructing stiffness matrices of multilinear volumetric FE of increased accuracy allowing for rigid displacements based on the double approximation method.Materials and Methods. The mathematical apparatus of the double approximation method based on the principle of a separate representation of the distribution functions of displacements and deformations inside the element, was used to construct the stiffness matrices of volumetric FE. The storage and processing of the resulting system of equations was implemented in algorithmic terms of sparse matrices. Software development and computational experiments were carried out using the Microsoft Visual Studio 2013 64-bit computing platform and the Intel ® Parallel Studio XE 2019 compiler with the integrated Intel ® Visual Fortran Composer XE 2019 text editor. Visualization of the calculation results was performed using the descriptor graphics of the MATLAB computer mathematics package. A large eight-node SOLID185 CE of the ANSYS Mechanical software complex was used as a test sample.Results. Mathematical tool and software were developed to study the stress-strain state of massive structures under various types of external actions. The authorized application software package was verified on test examples with known analytical solutions. It has been shown that the constructed FE accurately satisfy the basic requirements for finite element modeling of spatial problems of elasticity theory.Discussion and Conclusion. The performed testing of the developed mathematical and program toolkit has shown that the finite elements constructed on the basis of the double approximation method can successfully compete with similar SOLID185 volumetric elements of the ANSYS Mechanical software complex. The proposed elements can be integrated into domestic import-substituting software systems that implement the finite element method in the form of the displacement method.

Cheminformatics Microservice: unifying access to open cheminformatics toolkits

In recent years, cheminformatics has experienced significant advancements through the development of new open-source software tools based on various cheminformatics programming toolkits. However, adopting these toolkits presents challenges, including proper installation, setup, deployment, and compatibility management. In this work, we present the Cheminformatics Microservice. This open-source solution provides a unified interface for accessing commonly used functionalities of multiple cheminformatics toolkits, namely RDKit, Chemistry Development Kit (CDK), and Open Babel. In addition, more advanced functionalities like structure generation and Optical Chemical Structure Recognition (OCSR) are made available through the Cheminformatics Microservice based on pre-existing tools. The software service also enables developers to extend the functionalities easily and to seamlessly integrate them with existing workflows and applications. It is built on FastAPI and containerized using Docker, making it highly scalable. An instance of the microservice is publicly available at https://api.naturalproducts.net. The source code is publicly accessible on GitHub, accompanied by comprehensive documentation, version control, and continuous integration and deployment workflows. All resources can be found at the following link: https://github.com/Steinbeck-Lab/cheminformatics-microservice.Graphical

IoT Programming Toolkits and Frameworks: Building a Foundation for Smart Connectivity at Home

The Internet of Things (IoT) has ushered in a new era of smart connectivity, where devices and systems interact seamlessly to enhance our daily lives. However, the complexity of IoT development necessitates robust toolkits and frameworks to empower developers in building efficient and secure IoT applications. An overview of IoT programming toolkits and frameworks, highlighting their significance in simplifying IoT development is provided. IoT toolkits, such as Arduino and Raspberry Pi, offer a rich ecosystem of hardware and software resources. PlatformIO extends further, providing a unified development environment for various microcontroller platforms, enhancing productivity and collaboration. On the other hand, IoT programming frameworks like Node-RED, AWS IoT Core, Google Cloud IoT, and Microsoft Azure IoT focus on simplifying the creation, deployment, and management of IoT applications. These IoT programming toolkits and frameworks empower developers with the resources and abstractions necessary to navigate the intricacies of IoT development. The choice of toolkit or framework depends on specific project requirements, hardware compatibility, and the desired level of abstraction. Ultimately, the advent of these invaluable resources paves the way for innovative and impactful IoT applications, propelling us further into the era of interconnected devices and smart environments.

Index-based tools for livelihood security and resilience assessment (LiSeRA) in lower Mekong Basin

This paper presents a framework and toolkit for assessment of multi-hazard livelihood security and resilience in the Lower Mekong Basin (LMB) communities. The LMB is a subsidiary region of the Mekong region in South East Asia, and is frequently exposed to hydrometeorological hazards and anthropogenic stressors that expose and directly affect the livelihoods of more than sixty-five million people living in the region. The main purpose of the study is to support decision-making and risk management planning through integration of the concepts of livelihood security and resilience into a holistic framework, and subsequently developing an index-based toolkit for conducting assessments. Firstly, dimensions, sub-dimensions and indicators for measurement of livelihood security and resilience in the LMB were identified through comprehensive literature review and expert consultation. Then, several local workshops were conducted with various stakeholders (researchers, government officials, community people) in the LMB region to validate the indicators and generate weightages. The indicators were then arranged in a matriculated form, and the weightages were used to generate the algorithm for computing the quantitative outputs of livelihood security and resilience in study area. An Excel toolkit and a ‘R’ programming package were developed using the algorithm for visualization of the assessment outcomes. The proposed framework and toolkit are expected to assist researchers, government officials and development professionals in generating robust resilience assessment indices for risk informed decision-making and planning.Brief outline of the method•Livelihood security and resilience concepts were integrated to generate a holistic assessment framework and an indicator library.•Weightages for indicators were generated using the Analytical Hierarchical Process (AHP) through consultation with relevant stakeholders.•The indicator library was developed into an algorithm-based Excel and ‘R’ programming toolkit that provides quantitative assessment outputs.

Prototype Sistem Monitoring Intensitas Cahaya pada Budidaya Tanaman Cabai Rawit dengan Konsep Smart Farming Berbasis Internet Of Things (IOT)

Light intensity is an important factor to consider as best as possible to support plant fertility and health, especially in cayenne pepper plants. One of the innovations that can be applied to assist the management and maintenance of plants in Greenouse is agricultural technology based on the Internet of Things (IoT) or called smart sarming. In the use of Smart farming technology, the process of Monitoring crop needs is carried out by sensors and microcontrollers so that farmers can monitor all data in real time. This final project aims to describe the implementation of a light intensity Monitoring system in an IoT-based Greenhouse and produce a light intensity Monitoring tool in a Greenhouse using an LDR sensor so that farmers can know that the plants are getting an adequate supply of light. The smart farming system is designed using the MQTT (Message Queue Telemetry Transport) protocol as the center for transferring and receiving data from sensors to Monitoring applications. The stages of implementing system into the Greenhouse include: (1) installation of sensors and microcontrollers on the Prototype Greenhouse for cayenne pepper cultivation; (2) design and decision-making to be carried out by the system; (3) create web and android applications as a place for Monitoring data by end users. The results show that the light intensity Monitoring system in cayenne pepper cultivation is based on the Internet Of Things (IoT), include: first, the manufacture of a system Monitoring tool whose light intensity is carried out in 4 steps, namely determining the components, assembling of components into a series of Monitoring systems, programming toolkits and application software, and packaging step. And the second, the implementation of the light intensity Monitoring system in cayenne pepper cultivation includes the system trial stage which produces an average value of 2676 LUX or 62.43% on sensor readings 12 times over a period of 3 minutes it is still at the optimal level for the growth of cayenne pepper plants with a minimum intensity value of 2528 or 50%. The output value calibration results on the Monitoring application with the LUX Meter application show the same and accurate value. So, it can be concluded that the IoT-based light intensity Monitoring system can run well and can be implemented for Greenhouse farming of cayenne pepper.

Enhancing Safety of a System-Wide In Situ Simulation Program Using No-Go Considerations.

A large-scale in situ simulation initiative on cardiac arrest in pregnancy was implemented across NYC Health + Hospitals. In situ simulation must be safely balanced with clinical conditions such as through application of no-go considerations or standardized reasons to cancel or postpone the simulation. Our objective is to describe our findings on the application of no-go considerations during this simulation initiative. NYC Health + Hospitals/Simulation Center developed an in situ simulation program focused on cardiac arrest in pregnancy, implemented at 11 acute care facilities. The program's toolkit included no-go considerations for in situ simulation safety: situations prompting a need to cancel, reschedule, or postpone a simulation to ensure patient and/or staff safety. Data were collected from June 2018 through December 2019. The simulation sites reviewed the 13 established no-go considerations before each simulation event to assess if the simulation was safe to "go". After the conclusion of the initiative, all data related to no-go considerations were analyzed.Two hundred seventy-four in situ simulations were scheduled and 223 simulations (81%) were completed. Fifty-one no-go events were reported, with 78% identifying a reason by category. Twenty-two percent did not report a reason or category. Four of the 13 suggested no-go considerations were not reported. The no-go considerations framework promotes standardized and strategic scheduling of in situ simulation. Analysis of no-go consideration application during this system-wide initiative provides a model for the usage of tracking no-go data to enhance safety and inform future simulation planning.

Tair-PMem

In-memory databases (IMDBs) have been the backbone of modern systems that demand high throughput and low latency. Because of the cost and volatility of DRAM, IMDBs become incompetent when dealing with workloads that require large data volume and strict durability. The emergence of non-volatile memory (NVM) brings new opportunities for IMDBs to tackle this situation. However, it is non-trivial to build an NVM-based IMDB, due to performance degradation, NVM programming complexity, and other challenges. In this paper, we present Tair-PMem , an NVM-based enterprise-strength database atop Redis, the most popular IMDB. Tair-PMem adopts a well-controlled data layout and a log-as-user-data design to mitigate NVM overheads. It eases the NVM programming complexity by providing a hybrid memory programming toolkit. To better leverage the enterprise-strength features and implementations from Redis, Tair-PMem retrofits it in a less intrusive way to achieve full compatibility and stability, while retaining its advanced features. With all of the above techniques elaborately implemented, Tair-PMem satisfies full durability, high throughput, and low latency at the same time. Tair-PMem has now been publicly available as a cloud service on Alibaba Cloud. To the best of our knowledge, Tair-PMem is the first cloud service that makes good use of the persistence capability of NVM.

Design of Dual-LiDAR High Precision Natural Navigation System

With the further development of online shopping and the impact of the COVID-19 pandemic, the logistics industry has further increased the demand for unmanned, automated warehousing and logistics handling. To realize intelligent warehousing and logistics handling, reliable positioning navigation technology is indispensable. Therefore, this paper designs a Dual-lidar high-precision natural navigation system based on the ROS (Robot Operating System) platform, which can fulfill the basic warehousing and logistics requirements. The natural navigation system uses the Lidar-SLAM method based on graph optimization to construct the 2D environment map, the PF (Particle Filter) algorithm in MRPT (Mobile Robot Programming Toolkit) is used for system positioning, and the real-time correction algorithm is used for motion control. On the built hardware platform, the navigation system completed the fixed-point cruise navigation task, and finally achieved a navigation accuracy of 4 cm and an average repeatable navigation accuracy of 6 mm. The designed navigation system has reference significance for multi-sensor fusion navigation. In reality, it can be applied to the transportation of warehousing and logistics, and it is expected to be mass-produced in the future.

ScaFI: A Scala DSL and Toolkit for Aggregate Programming

ScaFI: A Scala DSL and Toolkit for Aggregate Programming

Evaluation of an Arab American AD care intervention program in the United States

AbstractBackgroundThis initiative is part of a program of research designed to maximize the health and quality of life within the large Arab‐American community in Michigan through cultural/linguistic adaptations of the Alzheimer’s Association’s Living with Alzheimer’s education and support strategies program. Further, we aim to break new ground in terms of explicitly focusing on family systems as part of a caregiver support intervention.Methods10 families (two individuals from each, for a total of 20 individuals) signed up to attend the program. The program was offered twice virtually due to COVID‐19, delivered by bi‐lingual Arab American trainers. All participants were sent a link to an evaluation survey after completing the program (1=strongly disagree; 5=strongly agree) on: the usefulness of the program, the tip sheet, the language of delivery, and Alzheimer's Association resources. Descriptive analysis was conducted to ascertain rating frequency.ResultsSession 1 was delivered in English. Results showed that overall, all respondents agreed that the program was useful in that they learned something new and improved their caregiving skills. Half reported they neither agree/disagree about whether the program met their expectations with. Less than half reported they planned to use the Alzheimer’s Association resources available to them. Session 2 was delivered in Arabic. Results showed that overall, all respondents strongly agreed that the program was useful in that they learned something new and improved their caregiving skills. More than half strongly agreed the program met their expectations. More than half reported they planned to use the Alzheimer’s Association resources available to them. When asked “What would you change about this program” replies from both sessions asked to receive more strategies on how to deal with family members with Alzheimer’s. They also reported liking the Q&A time because that alleviated their feelings of the stigmatization of Alzheimer’s. As one said, “I felt at ease talking and sharing my experience with people who know what am I talking about.”ConclusionIdentifying successful and challenging elements of the adapted intervention will enable the creation of a program tool kit, which will set the stage for full‐scale broader implementation in underserved diverse populations.

An open source library to parse and analyze online collaborative knowledge-building portals

With the success of collaborative knowledge-building portals, such as Wikipedia, Stack Overflow, Quora, and GitHub, a class of researchers is driven towards understanding the dynamics of knowledge building on these portals. Even though collaborative knowledge building portals are known to be better than expert-driven knowledge repositories, limited research has been performed to understand the knowledge building dynamics in the former. This is mainly due to two reasons; first, unavailability of the standard data representation format, second, lack of proper tools and libraries to analyze the knowledge building dynamics.We describe Knowledge Data Analysis and Processing Platform (KDAP), a programming toolkit that is easy to use and provides high-level operations for analysis of knowledge data. We propose Knowledge Markup Language (Knol-ML), a generic representation format for the data of collaborative knowledge building portals. KDAP can process the massive data of crowdsourced portals like Wikipedia and Stack Overflow efficiently. As a part of this toolkit, a data-dump of various collaborative knowledge building portals is published in Knol-ML format. The combination of Knol-ML and the proposed open-source library will help the knowledge building community to perform benchmark analysis.Link of the repository: Verma et al. (2020)Video Tutorial: Verma et al. (2020)Supplementary Material: Verma et al. (2020)

Developing New Academic Programs in the Medical/Health Humanities: A Toolkit to Support Continued Growth.

Academic programs in the medical/health humanities have proliferated widely in recent years, and the professional, academic, and cultural drivers of this growth promise sustained new program development. In this article, we present the results of a survey sent to representatives of one hundred twenty-four baccalaureate and ten graduate programs in the medical/health humanities to assess the experiences and needs of existing programs. Survey results confirm the interest in and need for a descriptive toolkit as opposed to a prescriptive manual; indicate what data and materials are most needed to support the successful development of new academic programs in the field; and identify areas for future research. Recognizing a need for program development resources, the Health Humanities Consortium (HHC) has initiated the creation of a comprehensive online toolkit. We discuss survey results and the toolkit in relation to the drivers of new program growth. Finally, we describe resources now available through the HHC’s new online program toolkit, including existing programs; sample syllabi; sample curricula templates; program rationale; proposal templates; and graduation data.

Growing Neonatal Advanced Practice Providers via Mentorship Can Fill the Need: Program Description and Tool Kit.

The need for neonatal advanced practice providers (APPs) has been described. Hospital training programs for neonatal physician assistants (PAs) have been developed by physicians. No publications exist about programs administered by neonatal APPs for both new graduate neonatal nurse practitioners (NNPs) and neonatal PAs. The purpose of this work was to mentor, train, and hire neonatal APPs in a program administered by neonatal APPs. We developed a 2-pronged approach to attract PAs and new graduate NNPs. Marketing strategies included receptions, information, and mentorship. A 12-month neonatal PA fellowship program included clinical mentorship and weekly didactics. Case-based presentations were provided by neonatal APPs, neonatologists, and allied professionals. The new graduate NNP program included clinical mentorship and monthly meetings with peer support, lectures, and case presentations. Neonatal APPs were clinical mentors. Team-building activities supported mentorship and collaboration among all care providers. In less than 5 years, 10 PAs and 11 new graduate NNPs have been trained and hired, as well as experienced neonatal APPs hired for this regional neonatology program. For the first time in years, locum tenens neonatal APPs are not required. We have developed a "tool kit" of content, activities, exercises, and evaluations to support successful attainment of expected competencies. Future studies can measure retention, satisfaction, and clinical outcomes. A successful training program has been implemented to meet the growing demand. We support the values of integrity, collaboration, and equity to facilitate this successful paradigm shift among all neonatal professional team members.

NetV.js: A web-based library for high-efficiency visualization of large-scale graphs and networks

Graph visualization plays an important role in several fields, such as social media networks, protein–protein interaction networks, and traffic networks. A number of visualization design tools and programming toolkits have been widely used in graph-related applications. However, a key challenge remains in the high-efficiency visualization of large-scale graph data. In this study, we present NetV.js, an open-source and WebGL-based JavaScript library that supports the fast visualization of large-scale graph data (up to 50 thousand nodes and 1 million edges) at an interactive frame rate with a commodity computer. Experimental results demonstrate that our library outperforms existing toolkits (Sigma.js, D3.js, Cytoscape.js, and Stardust.js) in terms of performance.

Experience of the distance testing system development and operation

The article discusses the original remote testing system of students BonTest, created on the basis of the Department of Safety for Life and Activity of the St. Petersburg State Electrotechnical University ETU “LETI”. As part of the “digital economy” formation, the education system faces new challenges. Electronic and distance learning of students requires the creation of new software products integrated into the digital educational environment of the educational institution. The BonTest testing system provides the ability to automatically generate options and upload test results in MS Office Word, MS Office Excel formats, as well as provide statistical data on student progress by academic semesters, groups, types of classes and course topics. The teacher’s interface allows you to control access to testing, customize the parameters for passing the test and displaying the results, including the errors of each student. The test is available both in the classroom from computers (Microsoft Windows operating system) or smartphones (iOS or Android operating systems), and in a remote format. The program has a two-stage protection against unauthorized access; its database contains more than 3 thousand test questions. Currently, the BonTest system is widely used in the educational process at the department. Its main advantages are simplicity and efficiency of administration when solving technical issues; no failures or reduced response time of the system as a result of increased load on the server, the ability to promptly refine the program toolkit for emerging requests, as well as the ability to store an extensive database of test questions.

Novel hybrid robot and its processes for precision polishing of freeform surfaces

Freeform surfaces have important applications in various industrial fields. However, achieving a high level surface finish on freeform surfaces using polishing is always a challenging task. Hybrid robots are promising alternatives to conventional computer numerical control (CNC) machines and industrial robots for ultra-precision machining. Herein, we present a novel custom-built hybrid robot for freeform polishing. After the laboratory prototype was successfully developed, its automation for a specific freeform surface was a major obstacle preventing its application. This critical issue was addressed by presenting a process to deal with tedious robot programming. Random tool path planning was performed in the task space, and hybrid robot motion planning was conducted in the joint space. By integrating the process flows, a robot programming toolkit was developed to directly output the control program for a specific robot controller. An illustrative example with a freeform surface is provided to verify the functionality of the developed hybrid robot and the proposed control processes, and the corresponding experimental results verify their effectiveness.

TECHNIQUE OF C PROGRAM TRANSLATION FOR RECONFIGURABLE AND HYBRID COMPUTER SYSTEMS BASED ON FIELD-PROGRAMMABLE GATE ARRAYS

In this paper, we thoroughly consider the technique of conversion of procedural programs in C to configuration files for field-programmable gate arrays used in the toolkit for programming of reconfigurable and hybrid computer systems. The creation of parallel program in the COLAMO (Common Oriented Language for Architecture of Multi Objects) language using the analysis results of information dependences in the initial procedural program and its further conversion to a parallel and pipeline form are the distinctive characteristics of the technique. We addressed the methods of scalar splitting and array extension by iterations, which are applied for the fulfillment of the single assignment and unique substitution rules in parallel program and the saving of information communications of the initial procedural program. The technique of conversion of automatically created parallel program to the scalable parallel and pipeline form is presented. The “Procrustes” preprocessor adapts the form for different architectures and configurations of reconfigurable and hybrid computer systems. Owing to the described methodology, it is possible to synthesize a resource-independent scalable COLAMO-application, which can adapt to available computational resource by changing of several constants in automatic mode without any considerable modification of the program source code. Then, the scalable COLAMO-applicationis translated by the COLAMO-translator into field-programmable gate arrays configuration files for the specified reconfigurable computer resource.

Impact of the Agency for Healthcare Research and Quality's Safety Program for Perinatal Care

BackgroundThe Safety Program for Perinatal Care (SPPC) seeks to improve safety on labor and delivery (L&D) units through three mutually reinforcing components: (1) fostering a culture of teamwork and communication, (2) applying safety science principles to care processes; and (3) in situ simulation. The objective of this study was to describe the SPPC implementation experience and evaluate the short-term impact on unit patient safety culture, processes, and adverse events. MethodsWe supported SPPC implementation by L&D units with a program toolkit, trainings, and technical assistance. We evaluated the program using a pre-post, mixed-methods design. Implementing units reported uptake of program components, submitted hospital discharge data on maternal and neonatal adverse events, and participated in semi-structured interviews. We measured changes in safety and quality using the Modified Adverse Outcome Index (MAOI) and other perinatal care indicators. ResultsForty-three L&D units submitted data representing 97,740 deliveries over 10 months of follow-up. Twenty-six units implemented all three program components. L&D staff reported improvements in teamwork, communication, and unit safety culture that facilitated applying safety science principles to clinical care. The MAOI decreased from 5.03% to 4.65% (absolute change -0.38% [95% CI, -0.88% to 0.12%]). Statistically significant decreases in indicators for obstetric trauma without instruments and primary cesarean delivery were observed. A statistically significant increase in neonatal birth trauma was observed, but the overall rate of unexpected newborn complications was unchanged. ConclusionsThe SPPC had a favorable impact on unit patient safety culture and processes, but short-term impact on maternal and neonatal adverse events was mixed.

A Heterogeneous Multi-Core Based Biomedical Application Processing System and Programming Toolkit

Due to the growth of biological databases and biomedical instruments, the high performance active (real-time) signal processing becomes a challenge for medical scientists and engineers. The medical applications require a high-performance signal processor which can process the scientific and engineering biomedical applications and is easy to program. In this article, we have suggested a biomedical sensor interface and heterogeneous multi-core processing architecture based biomedical application processing system (BAPS) and biomedical applications toolkit. The biomedical sensor interface supports multiple regular and complex medical signals and provides digital data to the processing system. The BAPS uses heterogeneous multi-core architecture that processes biomedical applications with the performance up to 10 billion operations per sec and accuracy of 1 μ sec. The biomedical application toolkit provides programmability by giving support of hardware-level, scientific and artificial intelligence programming. The BAPS provides a single embedded platform solution to process a wide range of biomedical signal and image processing applications. To prove the importance of the proposed system, we developed the BAPS hardware architecture and tested it with different biomedical applications. When compared the results of BAPS with the baseline system, the results show that BAPS improves active (real-time) applications performance up to 12.8 times and processes passive (non-real-time) application 7.4 times faster and improves the 4.84-time performance of artificial intelligence application. While comparing the power and energy, the BAPS draws 1.56 times less dynamic power and consumes 21.85 times less energy.