Large Collaborative Project Research Articles

Individual differences in information demand have a low dimensional structure predicted by some curiosity traits

To understand human learning and progress, it is crucial to understand curiosity. But how consistent is curiosity's conception and assessment across scientific research disciplines? We present the results of a large collaborative project assessing the correspondence between curiosity measures in personality psychology and cognitive science. A total of 820 participants completed 15 personality trait measures and 9 cognitive tasks that tested multiple aspects of information demand. We show that shared variance across the cognitive tasks was captured by a dimension reflecting directed (uncertainty-driven) versus random (stochasticity-driven) exploration and individual differences along this axis were significantly and consistently predicted by personality traits. However, the personality metrics that best predicted information demand were not the central curiosity traits of openness to experience, deprivation sensitivity, and joyous exploration, but instead included more peripheral curiosity traits (need for cognition, thrill seeking, and stress tolerance) and measures not traditionally associated with curiosity (extraversion and behavioral inhibition). The results suggest that the umbrella term "curiosity" reflects a constellation of cognitive and emotional processes, only some of which are shared between personality measures and cognitive tasks. The results reflect the distinct methods that are used in these fields, indicating a need for caution in comparing results across fields and for future interdisciplinary collaborations to strengthen our emerging understanding of curiosity.

An architecture for model-based and intelligent automation in DevOps

The increasing complexity of modern systems poses numerous challenges at all stages of system development and operation. Continuous software and system engineering processes, e.g., DevOps, are increasingly adopted and spread across organizations. In parallel, many leading companies have begun to apply artificial intelligence (AI) principles and techniques, including Machine Learning (ML), to improve their products. However, there is no holistic approach that can support and enhance the growing challenges of DevOps. In this paper, we propose a software architecture that provides the foundations of a model-based framework for the development of AI-augmented solutions incorporating methods and tools for continuous software and system engineering and validation. The key characteristic of the proposed architecture is that it allows leveraging the advantages of both AI/ML and Model Driven Engineering (MDE) approaches and techniques in a DevOps context. This architecture has been designed, developed and applied in the context of the European large collaborative project named AIDOaRt. In this paper, we also report on the practical evaluation of this architecture. This evaluation is based on a significant set of technical solutions implemented and applied in the context of different real industrial case studies coming from the AIDOaRt project. Moreover, we analyze the collected results and discuss them according to both architectural and technical challenges we intend to tackle with the proposed architecture.

Chasing balloons as scientific practice: On transformative cocreation and epistemic ethics of care in the emerging field of youth citizen social science

How does including youth in research within a citizen social science framework challenge and transform our participatory action research practices and approaches? Through a storying journey we unravel how the training and subsequent conducting of a co-creative research process with young citizen social scientists are evolving from a cacophony of traditions, approaches and disciplines, among them youth participatory action research, action research in organizations, citizen science and social anthropology. The article is based on empirical research with a group of young people in Oslo, Norway, involved in a large collaborative citizen social science project on social inclusion of youth in Europe. We have witnessed closely how an epistemic ethics of care is integral to securing the epistemic justice of youth and argue that citizen social science can promote both epistemic justice and epistemic abundance by including youth in all parts of a rigorous research process that produces new scientific knowledge. Yet, we found that performing an ethics of care is (close to) impossible within the current conditions and structures of social sciences, as our ideals and views on what science is, delimit the practices of relational care necessary for inclusive processes. The implications of our findings call for an ethics of care framework for both citizen social science and action research practices.

‘We fear the repercussions from parents’: primary school parents and teachers’ perspectives on the inclusion of LGBTQ+ issues in the English primary school curriculum

ABSTRACT This paper reports on findings from a survey conducted within a larger collaborative project, working with primary school teachers and parents to normalise conversations about LGBTQ+ issues in four English primary schools. Survey data from 96 teachers and parents highlight different perspectives on the inclusion of LGBTQ+ issues. Existing research shows teachers are often reluctant to address such issues, signalling various concerns, including fear of a negative parental reaction. Using quantitative analysis of Likert items combined with a qualitative analysis of open-ended comments, the study shows differences in perceptions between teachers and parents, and among participating parents. The findings show teachers are willing to address LGBTQ+ issues within the primary school curriculum with support from the majority of parents. Parental opposition to teaching about LGBTQ+ issues appears to be associated with some parents’ religious views and limited engagement with members of the LGBTQ+ community. Parents’ concerns largely focused on notions of childhood innocence and perceptions of age-appropriateness for teaching about/engagement with LGBTQ+ issues.

Abstract IA003: Molecular subtypes and clinical benefit from neoadjuvant chemotherapy: A ten-year update

Abstract Ten years ago TCGA and two private groups reported that muscle-invasive bladder cancers (MIBCs) could be grouped into basal and luminal molecular subtypes that shared features with the corresponding subtypes of breast cancer. These and earlier studies by the group at Lund University demonstrated that molecular subtype membership was prognostic: patients whose tumors were assigned to basal/squamous subtypes had shorter survival than did patients whose tumors were assigned to the luminal subtypes, and these relationships were confirmed in subsequent studies. In addition, one of the studies included tumors from patients treated with neoadjuvant cisplatin-based combination chemotherapy (NAC), where patients whose tumors were infiltrated with smooth muscle cells and fibroblasts (the MD Anderson p53-like subtype) had the lowest response rates. Parallel comparisons of patients who either did or did not receive NAC concluded that patients with basal tumors derived the most clinical benefit in terms of disease-specific or overall survival. Thus, in addition to being prognostic, there was a suggestion that molecular subtypes might also be used to predict resistance to NAC. This work led to the design of two large collaborative projects that were designed to validate these observations and the conclusion that inactivating mutations in several DNA damage and repair (DDR) genes were also associated with response. One leveraged the S1314 Phase-2 “CoXEN” trial that was designed to prospectively validate another gene expression-based biomarker, and the other exploited pretreatment samples from the CALGB/Alliance 90601 Phase-3 trial of gemcitabine/cisplatin with or without bevacizumab in patients with advanced or metastatic disease. Comparisons of response rates as a function of molecular subtype membership in S1314 failed to validate the original link between the MD Anderson p53-like subtype and resistance, and patients with basal/squamous tumors in 90601 did not have better outcomes than did patients with luminal tumors. Thus, while the prognostic value of molecular subtype membership was confirmed, the predictive value was not. Developing biomarkers to predict response to chemotherapy remains a challenge not only for bladder cancer but also for other solid and hematopoietic malignancies. It seems likely that success will require the integration of measurements using multiple platforms, including liquid biopsies and others. The exciting results of the EV-302 clinical trial of enfortumab vedotin plus pembrolizumab have shifted the focus of biomarker work to these and other novel agents. Citation Format: David J McConkey. Molecular subtypes and clinical benefit from neoadjuvant chemotherapy: A ten-year update [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr IA003.

Students-as-partner experience

This article offers a case study of a student-faculty partnership. Focusing on the perspectives of two student research assistants and a faculty member, the authors utilize current literature on student-faculty partnerships to support their perspectives. This case study adds to the body of research suggesting student-faculty partnerships enrich and mutually benefit those involved. This article explores the working partnership of the consultation team and their work as part of a large collaborative project amongst post-secondary institutions and community-based organizations. Over the course of 3 years, success was evidenced by the outcomes of this project. The team has led workshops on the subject matter, and, additionally, contributed to the co-creation of a workbook/e-course on mitigating vicarious trauma for English language learning teachers. The research team published two subject-related articles. This article explores the facets that impacted the quality of the partnership.

The demographic and diagnostic profile of women with intellectual disability and mental health disorder in New South Wales and patterns of service use: A data linkage study

AbstractBackgroundCurrent evidence indicates that intellectual disability and gender are both factors in differential usage of services. However, there are limited data about the demographic and service usage patterns of people with intellectual disability who use mental health services. This is particularly true in relation to women with intellectual disability with mental ill health. Interrogation of large‐scale linked data sets can provide valuable insights into patterns of service usage among marginalised groups.MethodA large collaborative data linkage project was assembled with the overarching aim of providing an epidemiological profile of the health (including mental health), health service use, mortality and other service system contacts of people with intellectual disability in New South Wales (NSW), Australia. These linked data were used to interrogate the demographic, diagnostic and service use profiles of women with intellectual disability who have sought mental health support in NSW.ResultsThe linked data demonstrated important differences in patterns of diagnosis and service use for women with intellectual disability and mental health disorders, when compared to women without intellectual disability and men with and without intellectual disability, with mental health disorders. The diagnostic profile of women with intellectual disability reflected the gendered nature of diagnoses found in the wider population. Women with intellectual disability also experienced higher rates of diagnostic instability than other groups.ConclusionsThe intersection between gender, intellectual disability and mental health has an effect on diagnostic profile and patterns of service use for women with intellectual disability. These differences are important and may impact targeted service delivery and planning for women with intellectual disability who have sought mental health support.

Motivational drivers for health professionals in a large quality improvement collaborative project in Brazil: a qualitative study

BackgroundThe success of collaborative quality improvement (QI) projects in healthcare depends on the context and engagement of health teams; however, the factors that modulate teams’ motivation to participate in these projects are still unclear. The objective of the current study was to explore the barriers to and facilitators of motivation; the perspective was health professionals in a large project aiming to implement evidence-based infection prevention practices in intensive care units of Brazilian hospitals.MethodsThis qualitative study was based on content analysis of semistructured in-depth interviews held with health professionals who participated in a collaborative QI project named “Improving patient safety on a large scale in Brazil”. In accordance with the principle of saturation, we selected a final sample of 12 hospitals located throughout the five regions of Brazil that have implemented QI; then, we conducted videoconference interviews with 28 health professionals from those hospitals. We encoded the interview data with NVivo software, and the interrelations among the data were assessed with the COM-B model.ResultsThe key barriers identified were belief that improvement increases workload, lack of knowledge about quality improvement, resistance to change, minimal involvement of physicians, lack of supplies, lack support from senior managers and work overload. The primary driver of motivation was tangible outcomes, as evidenced by a decrease in infections. Additionally, factors such as the active participation of senior managers, teamwork, learning in practice and understanding the reason for changes played significant roles in fostering motivation.ConclusionThe motivation of health professionals to participate in collaborative QI projects is driven by a variety of barriers and facilitators. The interactions between the senior manager, quality improvement teams, and healthcare professionals generate attitudes that modulate motivation. Thus, these aspects should be considered during the implementation of such projects. Future research could explore the cost-effectiveness of motivational approaches.

An iterative approach for model-based requirements engineering in large collaborative projects: A detailed experience report

In this paper, we report on our 7 years of practical experience designing, developing, deploying, using, and evolving an iterative Model-based Requirements Engineering (MBRE) approach and language in the context of five large European collaborative projects providing complex software-intensive solutions. Based on significant data sets collected both during project execution and via surveys realized afterward, we demonstrate that such a model-based approach can bring interesting benefits in terms of scalability (e.g., a large number of handled requirements), heterogeneity (e.g., partners with different types of RE background), adaptability and extensibility (e.g., to various project's needs), traceability (e.g., from the requirements to the software components), automation (e.g., documentation generation), consistency and quality (e.g., central model), and usefulness or usability (e.g., actual deployment and practical use). Along the way, we illustrate the application of our MBRE approach and language with concrete elements from these several European collaborative projects. More broadly, we discuss the general benefits and current limitations of using such a model-based approach and corresponding language, as well as the related lessons we learned during these past years.

From “Taking Orders” to Being a “Self-starter”: Research Assistants and Postdoctoral Fellows’ Skill Development in Large Collaborative Research Projects

From “Taking Orders” to Being a “Self-starter”: Research Assistants and Postdoctoral Fellows’ Skill Development in Large Collaborative Research Projects

Secondary vectors of Zika Virus, a systematic review of laboratory vector competence studies.

After the unprecedented Zika virus (ZIKV) outbreak in the western hemisphere from 2015-2018, Aedes aegypti and Ae. albopictus are now well established primary and secondary ZIKV vectors, respectively. Consensus about identification and importance of other secondary ZIKV vectors remain. This systematic review aims to provide a list of vector species capable of transmitting ZIKV by reviewing evidence from laboratory vector competence (VC) studies and to identify key knowledge gaps and issues within the ZIKV VC literature. A search was performed until 15th March 2022 on the Cochrane Library, Lilacs, PubMed, Web of Science, WHOLIS and Google Scholar. The search strings included three general categories: [1] "ZIKA"; [2] "vector"; [3] "competence", "transmission", "isolation", or "feeding behavior" and their combinations. Inclusion and exclusion criteria has been predefined and quality of included articles was assessed by STROBE and STROME-ID criteria. From 8,986 articles retrieved, 2,349 non-duplicates were screened by title and abstracts,103 evaluated using the full text, and 45 included in this analysis. Main findings are 1) secondary vectors of interest include Ae. japonicus, Ae. detritus, and Ae. vexans at higher temperature 2) Culex quinquefasciatus was not found to be a competent vector of ZIKV, 3) considerable heterogeneity in VC, depending on the local mosquito strain and virus used in testing was observed. Critical issues or gaps identified included 1) inconsistent definitions of VC parameters across the literature; 2) equivalency of using different mosquito body parts to evaluate VC parameters for infection (mosquito bodies versus midguts), dissemination (heads, legs or wings versus salivary glands), and transmission (detection or virus amplification in saliva, FTA cards, transmission to neonatal mice); 3) articles that fail to use infectious virus assays to confirm the presence of live virus; 4) need for more studies using murine models with immunocompromised mice to infect mosquitoes. Recent, large collaborative multi-country projects to conduct large scale evaluations of specific mosquito species represent the most appropriate approach to establish VC of mosquito species.

BSBM-17 NOVEL VALIDATED PATIENT-DERIVED MODELS OF A RECTAL CANCER BRAIN METASTASIS

Abstract Colorectal adenocarcinomas (CRC) rarely metastasize to the brain, however, survival rates in patients with colorectal brain metastases (CBM) are short, with a median survival of only 4 months from diagnosis. Currently, no evidence-based treatment options against these rare brain metastases are available (PMC). Therefore, characterization of these tumors and development of targeted therapies are imperative. Optimal models for neoplasms heighten the notoriously low success rate of bench-to-bedside translation. Historically, brain cancer metastases models are established cell lines grown on plastic and transplanted as xenografts (Valiente; PMC7572582). Genomic drift, lack of genetic accuracy and heterogeneity, caused by serial passaging on plastic and in high-serum media, are frequent limitations of these models. Growth in defined media without serum and as 3-dimensional (3-D) spheroids or organoids is thought to improve the fidelity of cancer cell lines (Lee; PMID:16697959; Lo; PMC820864). Despite significant efforts of large collaborative projects (https://hcmi-searchable-catalog.nci.nih.gov/), 3-D rectal brain cancer metastasis models have not been reported. To address this unmet medical need, we developed 3-D (suspension, organoid) cultures of a rectal adenocarcinoma brain metastasis with moderate to focally poor differentiation. Next-generation sequencing, expression profiling, and immunohistochemistry were performed to validate our models. Our data confirmed that the PDO model contains tumor cells; pathogenic alterations and expression profiles in the models largely match that of the original tumor. Overall, we detected a significant phenotypic overlap with the original tumor sample. Spatial profiling and PDO-derived xenografts are in progress and will facilitate experimental therapeutics. Taken together, our models retained tumor heterogeneity and fidelity from the primary tumor, making this one of the first studies to establish 3-D patient-derived models for disease progression in rectal cancer brain metastases. Collectively, these models will be valuable translational tools for future exploration of targeted therapy, which remains absent in this disease process.

Improved Management of Issue Dependencies in Issue Trackers of Large Collaborative Projects

Issue trackers, such as Jira, have become the prevalent collaborative tools in software engineering for managing issues, such as requirements, development tasks, and software bugs. However, issue trackers inherently focus on the lifecycle of single issues, although issues have and express dependencies on other issues that constitute issue dependency networks in large complex collaborative projects. The objective of this study is to develop supportive solutions for the improved management of dependent issues in an issue tracker. This study follows the Design Science methodology, consisting of eliciting drawbacks and constructing and evaluating a solution and system. The study was carried out in the context of The Qt Company's Jira, which exemplifies an actively used, almost two-decade-old issue tracker with over 100,000 issues. The drawbacks capture how users operate with issue trackers to handle issue information in large, collaborative, and long-lived projects. The basis of the solution is to keep issues and dependencies as separate objects and automatically construct an issue graph. Dependency detections complement the issue graph by proposing missing dependencies, while consistency checks and diagnoses identify conflicting issue priorities and release assignments. Jira's plugin and service-based system architecture realize the functional and quality concerns of the system implementation. We show how to adopt the intelligent supporting techniques of an issue tracker in a complex use context and a large data-set. The solution considers an integrated and holistic system view, practical applicability and utility, and the practical characteristics of issue data, such as inherent incompleteness.

Influence of external authorities on collaborative frictions

AbstractWhen institutional frictions threaten to disrupt collaborations, an external authority can be brought in to resolve disputes. How effective is such external imposition? What are the institutional circumstances in which it works? Framed by the collaborative governance regime (CGR), which sees established procedures and institutions as a critical collaborative capacity, this research employs a unique concept—collaborative friction—to explore the role of external imposition in collaboration among entities with significant institutional differences. We examined 965 recorded collaborative frictions from four large collaborative infrastructure projects between governments in Hong Kong and mainland China. Our finding suggests a significant, but limited, effect of the central government's imposition on collaborative frictions. We also find a significant role of sociopolitical circumstances in collaboration. Based on the findings, we make several theoretical propositions articulating external imposition's role in collaboration.

Networking to reduce microbial risk in foods

Networking to reduce microbial risk in foods

ADSP Functional Genomics: from gene, to function to mechanisms and targets

AbstractBackgroundGenetic studies have been highly successful in identifying genetic regions associated with Alzheimer’s disease, and we are now at the exciting juncture of applying this knowledge to understanding disease mechanisms. The ability to generate and mine clinical and omicdata is advancing our understanding of neurodegeneration. The Alzheimer’s Disease Sequencing Project (ADSP) Functional Genomics Consortium (FunGen‐AD; https://adsp‐fgc.niagads.org/) aims to apply cutting‐edge genomics technologies, high‐throughput genetic screening and cutting edge disease modeling to understand the functional consequences of genetic susceptibility and resilience to Alzheimer’s Disease, and to identify genetics‐guided targets for the prevention, diagnosis, and treatment of Alzheimer’s disease and related dementias (AD/ADRD).MethodThe investigators of the FunGen‐AD consortium are using multiple approaches, including brain single cell data acquisition, human stem cell modeling and high through put CRISPR‐based screens, to understand how AD variants lead to changes across molecular networks, and understand how specific risk variants affect disease in diverse populations. Multi‐omic data generated in well characterized cohorts are being used to identify systems‐level alterations in and provide insight into the mechanisms underlying genetic variants.ResultThe FunGen‐AD consortium is organizing and facilitating large collaborative projects. Currently we are working on a xQTL project putting together data from multi‐tissue (brain, myeloid cells, CSF and plasma), and multi‐omic layers (transcriptomic in bulk and at single cell level, epigenetic, proteomic, and metabolomic). In order to fully understand the biology of AD we recognize that multiple tissues, and ‐omic layers need to be studied. All the omic data are being processed, harmonized and analyzed using standard pipelines, and mapping on a reference genome and annotation developed by the group. This QTL atlas will be used to perform colocalization and identify the functional genes within AD risk loci, and Mendelian Randomization to identify novel causal genes, proteins and druggable targets. This xQTL project will provide a rich resource of multi‐omics datasets, analysis pipelines, and an xQTL atlas for the research community studying AD/ADRD and other complex neurodegenerative traits.ConclusionsIn summary, the FunGen‐AD consortium is using multidisciplinary and collaborative research approaches to identify genetics‐guided targets for the prevention, diagnosis, and treatment of AD/ADRD.

AIDOaRt: AI-augmented Automation for DevOps, a model-based framework for continuous development in Cyber–Physical Systems

The advent of complex Cyber–Physical Systems (CPSs) creates the need for more efficient engineering processes. Recently, DevOps promoted the idea of considering a closer continuous integration between system development (including its design) and operational deployment. Despite their use being still currently limited, Artificial Intelligence (AI) techniques are suitable candidates for improving such system engineering activities (cf. AIOps). In this context, AIDOaRT is a large European collaborative project that aims at providing AI-augmented automation capabilities to better support the modeling, coding, testing, monitoring, and continuous development of CPSs. The project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable CPSs. The resulting framework will (1) enable the dynamic observation and analysis of system data collected at both runtime and design time and (2) provide dedicated AI-augmented solutions that will then be validated in concrete industrial cases. This paper describes the main research objectives and underlying paradigms of the AIDOaRt project. It also introduces the conceptual architecture and proposed approach of the AIDOaRt overall solution. Finally, it reports on the actual project practices and discusses the current results and future plans.

Fault tolerant multi-sensor data fusion for autonomous navigation in future civil aviation operations

The problem addressed in this paper is that of fault-tolerant multi-sensor data-fusion for flight navigation during approach and landing of a civil jetliner. The work falls within the scope of a large collaborative project on future single pilot operations issues. The proposed methodology is based on a multi-layer hierarchical architecture which can integrate several heterogeneous information sources. The study is restricted to three classical information sources, namely, Inertial Reference System (IRS), Global Positioning System (GPS) and Instrument Landing System (ILS). The system is designed to meet the specified navigation performance requirements in terms of validity, accuracy, continuity and on-board implementation issues. The methodology takes advantage of recently developed set-membership tools, and paves the way toward a new and simple tuning of global merging filter.

More Power in Series

More Power in Series

Creativity in CS1: A Literature Review

Computer science is a fast-growing field in today’s digitized age, and working in this industry often requires creativity and innovative thought. An issue within computer science education, however, is that large introductory programming courses often involve little opportunity for creative thinking within coursework. The undergraduate introductory programming course (CS1) is notorious for its poor student performance and retention rates across multiple institutions. Integrating opportunities for creative thinking may help combat this issue by adding a personal touch to course content, which could allow beginner CS students to better relate to the abstract world of programming. Research on the role of creativity in computer science education (CSE) is an interesting area with a lot of room for exploration due to the complexity of the phenomenon of creativity as well as the CSE research field being fairly new compared to some other education fields where this topic has been more closely explored.To contribute to this area of research, this article provides a literature review exploring the concept of creativity as relevant to computer science education and CS1 in particular. Based on the review of the literature, we conclude creativity is an essential component to computer science, and the type of creativity that computer science requires is in fact, a teachable skill through the use of various tools and strategies. These strategies include the integration of open-ended assignments, large collaborative projects, learning by teaching, multimedia projects, small creative computational exercises, game development projects, digitally produced art, robotics, digital story-telling, music manipulation, and project-based learning. Research on each of these strategies and their effects on student experiences within CS1 is discussed in this review. Last, six main components of creativity-enhancing activities are identified based on the studies about incorporating creativity into CS1. These components are as follows: Collaboration, Relevance, Autonomy, Ownership, Hands-On Learning, and Visual Feedback. The purpose of this article is to contribute to computer science educators’ understanding of how creativity is best understood in the context of computer science education and explore practical applications of creativity theory in CS1 classrooms. This is an important collection of information for restructuring aspects of future introductory programming courses in creative, innovative ways that benefit student learning.