Four Legged Parallel Manipulator for Autonomous Delivery Robot

The COVID-19 outbreak has been designated a pandemic and is spreading quickly around the world. The industries most impacted by COVID-19, which has proved a barrier to every major business, were the e-commerce businesses that use door-to-door delivery methods. It's critical to have an unmanned strategy that can be applied to diverse sites during this key time. Although the driverless vehicle is not a novel idea, problems can occur when these systems run into the uneven pavement or unexpected obstacles. The methods for ensuring the stability of the commodities delivered by autonomous robots are discussed in this research. This mechanism guards against product damage. Additionally, a motor that stabilizes a robot's product compartment uses a gyroscope sensor to detect angular rotation and axial movement and preserve the orientation of a quadrupedal leg. In order to conduct trials that mimic problems in the real world, rectify errors, and offer solutions, a prototype model of a robot's stability platform has been created. This type of technological advancement will aid us in future efforts to combat global catastrophes. © 2023 IEEE.

Seeing rainbows through the storms of a health condition: Making space for LGBTQ+ young people to have their identity acknowledged.

LGBTQ+ youth accessing healthcare settings manage the 'storms' of health conditions (e.g. pain, fatigue, social isolation, etc.) while navigating emerging identity exploration and understandings in settings which may have historically overlooked or disaffirmed these identities. The launch of National Health Service Rainbow Badges across the paediatric division of an inner-city hospital provided a context for staff to begin thinking about their practice, development needs and dilemmas in working with LGBTQ+ youth. Through a programme of activity that included staff training, surveys, focus groups and youth engagement, we gained insight into current practice in supporting LGBTQ+ youth and families. This paper presents our findings, ideas for responding to challenges, and areas for future development, including implications in light of the coronavirus pandemic.

Recommender System for Government Service in Smart Cities

significant recommender systems (RS) development has occurred along with the Internet of Things (IoT) development in recent years. Recommender systems have been widely spread across diverse fields, including environmental preservation, e-commerce, healthcare, social and governance systems. There has been a growing focus on e-government as part of smart city initiatives in today's world of connected devices and infrastructure, especially after the COVID-19 pandemic. With the use of information and communication technologies (ICTs), the government can enhance the delivery of public services, increase transparency, accountability, and credibility, as well as engage citizens in the decision-making process. To facilitate 'smart' governance, one of a smart city initiative's objectives is integrating e-government into the city's governance framework. The lack of personalized services for particular stakeholders is one of the most significant limitations of e-governance. There are a number of open challenges coupled with interesting opportunities, making this a very promising and exciting area for research to shape recommendation systems for urban environments. Considering the overwhelming amount of information, services, and tasks available through smart government applications, it is a greater chance of providing personalized recommendations for different stakeholders and tasks within multi-faceted and multi-dimension. There is still a lot of research to be done on recommendation systems in the context of smart cities or smart government. This paper survey the existing studies on recommendation systems for smart governance. The study aims to address smart city challenges to considered when designing and implementing recommendations for e-governance and the target stakeholder's interests. © 2022 IEEE.

Domestic and Family Violence for Culturally and Linguistically Diverse Communities in Australia during COVID-19 Pandemic

Women are disproportionately impacted by the COVID-19 pandemic worldwide. Based on the Australian context, we highlight how women from Culturally and Linguistically Diverse (CALD) communities are vulnerable to Domestic and Family Violence (DFV). During the pandemic, CALD women experienced inequality in relation to DFV support and services. In this paper, our methodology is based on a case study from a rapid review of academic and grey literature that privileged the lived experience of CALD women affected by the pandemic. From a critical social work perspective, we explored the newly emerging literature highlighting DFV for CALD communities during the pandemic. Our research highlights an increase in DFV incidents, frequency and severity of incidents against CALD women, limited access to DFV services, and that women on Temporary and Humanitarian Visas (THV) were more likely to be subjected to DFV. We support the urgent need to include women's services in developing appropriate policy responses to address the specific issues facing women, particularly those on THV. Critical social work perspectives can be utilised to build on and support the response of services during the COVID pandemic to promote social and policy change, and increased access to services. This support can be implemented by workforce initiatives, dedicated resources and community engagement.

COVID-19 infection and vaccination uptake in men and gender-diverse people who have sex with men in the UK: analyses of a large, online community cross-sectional survey (RiiSH-COVID) undertaken November-December 2021.

BACKGROUND: Men and gender-diverse people who have sex with men are disproportionately affected by health conditions associated with increased risk of severe illness due to COVID-19 infection. METHODS: An online cross-sectional survey of men and gender-diverse people who have sex with men in the UK recruited via social networking and dating applications from 22 November-12 December 2021. Eligible participants included self-identifying men, transgender women, or gender-diverse individuals assigned male at birth (AMAB), aged ≥ 16, who were UK residents, and self-reported having had sex with an individual AMAB in the last year. We calculated self-reported COVID-19 test-positivity, proportion reporting long COVID, and COVID-19 vaccination uptake anytime from pandemic start to survey completion (November/December 2021). Logistic regression was used to assess sociodemographic, clinical, and behavioural characteristics associated with SARS-CoV-2 (COVID-19) test positivity and complete vaccination (≥ 2 vaccine doses). RESULTS: Among 1,039 participants (88.1% white, median age 41 years [interquartile range: 31-51]), 18.6% (95% CI: 16.3%-21.1%) reported COVID-19 test positivity, 8.3% (95% CI: 6.7%-10.1%) long COVID, and 94.5% (95% CI: 93.3%-96.1%) complete COVID-19 vaccination through late 2021. In multivariable models, COVID-19 test positivity was associated with UK country of residence (aOR: 2.22 [95% CI: 1.26-3.92], England vs outside England) and employment (aOR: 1.55 [95% CI: 1.01-2.38], current employment vs not employed). Complete COVID-19 vaccination was associated with age (aOR: 1.04 [95% CI: 1.01-1.06], per increasing year), gender (aOR: 0.26 [95% CI: 0.09-0.72], gender minority vs cisgender), education (aOR: 2.11 [95% CI: 1.12-3.98], degree-level or higher vs below degree-level), employment (aOR: 2.07 [95% CI: 1.08-3.94], current employment vs not employed), relationship status (aOR: 0.50 [95% CI: 0.25-1.00], single vs in a relationship), COVID-19 infection history (aOR: 0.47 [95% CI: 0.25-0.88], test positivity or self-perceived infection vs no history), known HPV vaccination (aOR: 3.32 [95% CI: 1.43-7.75]), and low self-worth (aOR: 0.29 [95% CI: 0.15-0.54]). CONCLUSIONS: In this community sample, COVID-19 vaccine uptake was high overall, though lower among younger age-groups, gender minorities, and those with poorer well-being. Efforts are needed to limit COVID-19 related exacerbation of health inequalities in groups who already experience a greater burden of poor health relative to other men who have sex with men.

The Role of Crowdfunding in Delivering Entrepreneurship Within the Hospitality Sector: A Case Study Analysis

Over the last decade, crowdfunding, has emerged as a hugely disruptive force within the financial landscape worldwide. Crowdfunding, the process of raising relatively small sums of money from the crowd, via the internet, enables entrepreneurs, particularly at the innovative and new start-ups stage, to access much needed funding, overcoming a "funding gap”. The growth of crowdfunding has been phenomenal. In 2019, an estimated €14 billion was crowdfunded worldwide (Statistia 2020) and the forecast is for the sector to grow to €30 billion by 2025 (Mordo Intelligence, 2020). Initially, crowdfunding gained prominence through funding creative and artistic projects, but over the last number of years, this appeal has spread across a diverse range of businesses and sectors (Bradford 2012 and Research and Markets 2022). In the wake of the 2007-2008 financial crisis and more recently the COVID-19 pandemic, crowdfunding offers entrepreneurs and businesses access to much needed seed funding, but also non-financial benefits in the form of market and product testing, media exposure and customer feedback. Crowdfunding is a relatively new domain for businesses in the hospitality sector. As noted by Belavin, Marinesi and Tsoukalas (2020), crowdfunding offers huge potential for the sector, who often face funding challenges thereby limiting new innovative start-ups, critical for the sector's long term viability. This case study examined how one entrepreneur in the hospitality sector, successfully crowdfunded an innovative business idea in the midst of the COVID-19 pandemic. The case traces the idea and the factors that shaped the decision to crowdfund. Additionally, the case examines the benefits and challenges involved in successfully crowdfunding the business idea and closes with the entrepreneur reflecting on the key learning from the experience. The contribution of this case study is twofold. Firstly, it serves to highlight the potential of crowdfunding as a funding source of enterprise development, particularly among new, innovative businesses. Secondly, it adds to the current debate, as noted by Belavin, Marinesi and Tsoukalas (2020), of the potential crowdfunding in fostering entrepreneurship and economic development within the hospitality sector. © 2022, Academic Conferences and Publishing International Limited. All right reserved.

"We Can Manage This Corona Disaster”: Psycho-Social Experiences of a Diverse Suburban Middle-Class Community in South Africa: Interview-Based Study

The study concerns psycho-social domains experienced in a diverse suburban middle-class community, reporting the most positive cases and the deepest suffering, and interactions towards adaptation in stressful situations, such as the Coronavirus pandemic. This qualitative investigation used a descriptive design, with a strengths-based perspective directing a two-phased method. Through non-probability convenience sampling, 80 participants completed a web-based qualitative questionnaire (phase one). From those, 20 purposely selected volunteers participated in individual, face-to-face, open-ended, and unstructured interviews (phase 2). Themes, interpreted as one set, show how strengths and resilience appear, despite extreme shock and uncertainty. Transitional processes in psycho-social spheres reveal conscious decisions towards dynamic engagement, embracing change, reflecting on life's value, and regarding novel meaningful priorities in contrast with "before”. Most prominent relational spaces have human connections in the inner (close) and outer (community) circles. Personal, meaningful relationships strengthen social bonds. Appreciative inquiry (AI) assisted in the transitional process to co-construct awareness of the positive core, emotional agility, and pride in embracing and expanding on newly developed strengths. Interpreted inductively, meaning described in ed knowledge can be transferred to and integrated with other contexts, identifying new initiatives and trans-, multi-, and inter-disciplinary debates mitigating psycho-social consequences and fostering resilience during disasters.

Co-design of the Transgender Health Information Resource: Web-Based Participatory Design.

BACKGROUND: There is an urgent and unmet need for accessible and credible health information within the transgender and gender-diverse (TGD) community. Currently, TGD individuals often seek and must find relevant resources by vetting social media posts. A resource that provides accessible and credible health-related resources and content via a mobile phone app may have a positive impact on and support the TGD population. OBJECTIVE: COVID-19 stay-at-home orders forced a shift in the methods used in participatory design. In this paper, we aimed to describe the web-based participatory methods used to develop the Transgender Health Information Resource. We also described and characterized the web-based engagement that occurred during a single session of the overall design process. METHODS: We planned and conducted web-based design sessions to replace the proposed in-person sessions. We used web-based collaborative tools, including Zoom (Zoom Video Communications), Mural (Mural), REDCap (Research Electronic Data Capture; Vanderbilt University), and Justinmind (Justinmind), to engage the participants in the design process. Zoom was used as an integrated platform for design activities. Mural was used to perform exercises, such as free listing, brainstorming, and grouping. REDCap allowed us to collect survey responses. Justinmind was used to create prototypes that were shared and discussed via Zoom. Recruitment was led by one of our community partners, One Colorado, who used private Facebook groups in which web-based flyers were dispersed. The design process took place in several workshops over a period of 10 months. We described and characterized engagement during a single design session by tracking the number of influential interactions among participants. We defined an influential interaction as communication, either verbal or web-based content manipulation, that advanced the design process. RESULTS: We presented data from a single design session that lasted 1 hour and 48 minutes and included 4 participants. During the session, there were 301 influential interactions, consisting of 79 verbal comments and 222 web-based content manipulations. CONCLUSIONS: Web-based participatory design can elicit input and decisions from participants to develop a health information resource, such as a mobile app user interface. Overall, participants were highly engaged. This approach maintained the benefits and fidelity of traditional in-person design sessions, mitigated deficits, and exploited the previously unconsidered benefits of web-based methods, such as enhancing the ability to participate for those who live far from academic institutions. The web-based approach to participatory design was an efficient and feasible methodological design approach.

Acceptability of Telehealth for Gender-Affirming Care in Transgender and Gender Diverse Youth and Their Caregivers.

Gender-affirming care (GAC) is critical to the well-being of transgender and gender diverse youth and was limited by COVID-19 stay-at-home orders. Telehealth created opportunities for youth to continue receiving lifesaving care. We examined the attitudes of patients (n=21) and caregivers (n=38) receiving telehealth-delivered GAC (TGAC) from May to July 2020. Participants completed surveys after telehealth visits. Descriptive statistics compared telehealth with in-person visits across key domains. Overall, 86.5% of patients and 95.4% of caregivers were satisfied with medical TGAC and 94.3% and 93.3% were satisfied with behavioral health TGAC. Future research should determine the effectiveness of TGAC and identify areas for improvement.

Advances and Application of Artificial Intelligence and Machine Learning in the Field of Cardiovascular Diseases and Its Role During the Pandemic Condition

Artificial intelligence (AI) has shown an immense potential to affect diverse domains of healthcare during the COVID-19 pandemic. The applications of AI in the field of cardiovascular disorders during the COVID-19 pandemic were an added advantage to the cardiologists, as it helped in certain aspects of treatments digitally. This technology is constructive for providing sophisticated treatment in the area of cardiovascular medicine based on technology, because it may assist in assessing and measuring the human heart function. Artificial intelligence employs simulated neuronal program for predicting the survival of a COVID-19 patient affected with heart dysfunction. AI entails intricate algorithms for predicting successful evaluation and therefore the treatment protocol. AI utilizes various methods like cognitive computing, deep learning, and machine learning. It is integrated to make an assessment and determine multifaceted challenges. In humans, cardiovascular disease is still one of the major causes of death, and it is escalating for years together and is also very expensive. AI is employed to recognize new drug treatment and advance the efficacy of a clinician. AI is turning into a well-approved attribute of a variety of engineering and healthcare segments and is being expected to provide a feasible treatment stage. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Active Keyword Selection to Track Evolving Topics on Twitter

How can we study social interactions on evolving topics at a mass scale? Over the past decade, researchers from diverse fields such as economics, political science, and public health have often done this by querying Twitter's public API endpoints with hand-picked topical keywords to search or stream discussions. However, despite the API's accessibility, it remains difficult to select and update keywords to collect high-quality data relevant to topics of interest. In this paper, we propose an active learning method for rapidly refining query keywords to increase both the yielded topic relevance and dataset size. We leverage a large open-source COVID-19 Twitter dataset to illustrate the applicability of our method in tracking Tweets around the key sub-topics of Vaccine, Mask, and Lockdown. Our experiments show that our method achieves an average topic-related keyword recall 2x higher than baselines. We open-source our code along with a web interface for keyword selection to make data collection from Twitter more systematic for researchers. © 2022 IEEE.

The Design and Utilisation of PanSim, a Portable Pandemic Simulator

The COVID-19 pandemic has presented a clear and present need for urgent decision making. Set in an environment of uncertain and unreliable data, and a diverse range of possible interventions, there is an obvious need for integrating HPC into workflows that include model calibration, and the exploration of the decision space. In this paper, we present the design of PanSim, a portable, performant, and productive agent-based simulator, which has been extensively used to model and forecast the pandemic in Hungary. We show its performance and scalability on CPUs and GPUs, then we discuss the workflows PanSim integrates into. We describe the heterogeneous, resource-constrained HPC environment available to us, and formulate a scheduling optimisation problem, as well as heuristics to solve them, to either minimise the execution time of a given number of simulations or to maximise the number of simulations executed in a given time frame. © 2022 IEEE.

Concept Drift Aware Analysis of Learning Engagement During COVID-19 Pandemic Using Adaptive Windowing

Change is the only thing in the real world which has been known to last forever. It takes various forms and progressions, ranging from gradual in some cases and abrupt in the others to even constantly incremental in yet other cases like ageing. Machine learning (ML) algorithms, in its simplest definitions, use the statistical analysis of static past data records to make predictions about the future and have reached a fair amount of accuracy on diverse data sets across different application domains. There exists an inherent contradictory friction between real life analysis and machine learning models based on above definitions, and it gets compounded while capturing the ever-changing data from streaming sources. Concept drift is a principle used for description of unpredictable variations in streaming data sourced from the real world through a given time period. The drift phenomenon occurring even in a single feature, if left unaddressed leads to silent decay and can play havoc with the accuracy of a previously accurate ML model. With increasing prevalence and scale of real-world deployments of ML analytics, models cannot remain invariant to instability of data distributions and must adapt to concept drift. We analyse the occurrence and effect of concept drift in the COVID-19 online education data sourced from LearnPlatform edtech Company in this paper. The data set has almost 20 million entries related to engagement index and can be fairly assumed to be big data for processing purposes. A comparative case analysis for the accuracy of concept drift aware modelling using adaptive windowing (ADWIN) vis-a-vis the basic ML counterpart to predict the student engagement based on digital connectivity and education technology has been carried out for the study. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Pacific approaches to fundraising in the digital age: COVID-19, resilience and community relational economic practices

The aim of this paper is to discuss how community relational economic practices in virtual spaces are effective in building resilience because they are borne of and sustained by familiar traditional Fijian values of collective work and social interdependence. The researchers adopted a pandemic-induced methodology, conducting online-based talanoa (fluid conversations between two or more people) with a number of people leading, or involved in, these initiatives. We also engaged with online community groups behind a number of initiatives. Examples are provided of online crowdfunding, livestreaming of concerts to solicit donations, and bartering facilitated by social media sites. To conclude, we stress the enduring nature of communal bonds and traditional systems which Pacific people readily adapt and translate into different forums and forms in the face of challenges such as the restrictions and financial hardships caused by COVID-19. The findings highlight that solesolevaki – a tradition of working together for a common cause – can also occur in the digital era: this demonstrates the deep connection of Fijian peoples and their sense of obligation to one another and to their culture, regardless of where they are in the world. © 2023 The Authors. Asia Pacific Viewpoint published by Victoria University of Wellington and John Wiley & Sons Australia, Ltd.

Principles of inclusive practice in schools: what is COVID-19 teaching us?

In March 2020, schools worldwide closed due to COVID-19 and students were required to continue learning from home. Following a review of principles for inclusive practice in schools, we share related literature focusing on how school systems employed these principles during online delivery. After describing emergent themes, we provide a commentary suggesting that the online learning environment resembled the "building of a plane, while flying”. Although there was disregard of a number of principles globally, positive stories are also shared to disseminate ideas for moving forward. We conclude with some key recommendations for future development of inclusive education in schools. © 2023 Elsevier Ltd. All rights reserved.

Chemoinformatics and bioinformatics by discrete mathematics and numbers: an adventure from small data to the realm of emerging big data

Currently, we are witnessing the emergence of big data in various fields including the biomedical and natural sciences. The size of chemoinformatics and bioinformatics databases is increasing every day. This gives us both challenges and opportunities. This chapter discusses the mathematical methods used in these fields both for the generation and analysis of such data. It is emphasized that proper use of robust statistical and machine learning methods in the analysis of the available big data may facilitate both hypothesis-driven and discovery-oriented research. © 2023 Elsevier Inc. All rights reserved.

Online support for students with diverse learning needs at an inclusive private school in South Africa

Teachers of diverse classes often include different forms of support in their teaching to accommodate the varying learner needs, while some benefit from the services of Learning Support Educators (LSE) who manage the learning needs of students who experience barriers to learning. With the onset of lockdown due to the coronavirus pandemic, the shift to online teaching and learning left students with diverse learning needs feeling adrift and on their own to grapple with the change, without prior preparation. As teachers also had to adapt to the shift to online teaching, the diverse learner needs became a secondary concern to them. The LSE were also unable to offer support in the traditional form due to physical distancing and lockdown rules. This paper explores possible ways in which teachers of diverse classes and LSEs can assist learners with diverse needs to succeed in their online learning. The study followed action research methodology that was conducted by an LSE who case-managed seven learners in a Johannesburg private school with inclusive teaching practices. The qualitative research study explored new ways to support diverse learners in their online learning by finding possible alternatives to the challenges that online learning posed for them. Observations, self-reflections, and information collected from students, their teachers and parents, were analysed using content analysis technique to propose possible workable solutions. Checking in on learners and their parents regularly during lockdown and giving them strategies for coping was found to be helpful. Teachers who had previously incorporated ‘blended' teaching in their practice were found to be generally more collaborative: they varied their teaching, had their students produce better results, were able to include online inclusive activities and groupwork activities in their teaching in order to avoid learner boredom, and they were found to be giving quality feedback to the learners and their parents. © The Author(s) 2023.

Pilot studies of recruitment and feasibility of remote Tai Chi in racially diverse older adults with multisite pain.

BACKGROUND: Multisite musculoskeletal pain is highly prevalent among older adults yet undertreated. Studies support the promise of Tai Chi for managing pain and lowering fall risk. Since the COVID-19 pandemic, effective alternatives to classroom-based exercise programming are warranted. AIMS: To recruit 100 racially diverse older adults with multisite pain and increased fall risk, who are interested in participating in a future Tai Chi clinical trial, and to evaluate the feasibility and acceptability of a short-term, remotely delivered home-based Tai Chi program. METHODS: A random sample of adults aged 65 years or older living in diverse Boston neighborhoods were sent mailed invitations to participate in a telephone screening survey. Eligible adults were invited to join a 4-week Tai Chi program offered online via Zoom. Primary outcomes were class attendance, experience, and program safety. RESULTS: Among 334 survey respondents, 105 were eligible for the intervention. Average age of eligible participants was 74 years, 75% were women, and 62% were Black. We assigned 32 participants to 4 Tai Chi or 2 light exercise groups conducted via Zoom; of these, 24 (75%) completed the program and 79% attended ≥6 of 8 classes. There were no adverse events reported. Two-thirds reported it was very easy to join the online classes and 88%, very easy to see the instructor. CONCLUSION: Mailed invitations were effective for recruiting a racially diverse sample. Remote exercise programming delivered online via live Zoom sessions is safe and feasible for diverse older adults who have multisite pain and risk of falls.

SARS-CoV-2 Infection and Testing Experiences in a Nationwide Sample of Transgender and Gender-Diverse Adults, June-December 2021.

OBJECTIVES: COVID-19 surveillance data are rarely collected or disaggregated by gender identity in the United States. We quantified COVID-19 testing experiences and SARS-CoV-2 infection history among transgender and gender-diverse (TGD) people to inform testing strategies and public health responses. METHODS: From June 14 through December 16, 2021, TGD adults enrolled in a US nationwide online survey with optional SARS-CoV-2 antibody testing. We used multinomial regression analyses to identify correlates of suspected and confirmed SARS-CoV-2 infection (vs no known infection). We identified correlates of inability to access COVID-19 testing when needed using generalized linear models for binomial variables. RESULTS: Participants (N = 2092) reported trans masculine (30.5%), trans feminine (27.3%), and nonbinary (42.2%) gender identities. Ten percent of respondents had a confirmed history of SARS-CoV-2 infection, and 29.8% had a history of suspected SARS-CoV-2 infection. Nonbinary gender (adjusted prevalence ratio [aPR] = 1.68; 95% CI, 1.12-2.53), experiencing homelessness (aPR = 1.65; 95% CI, 1.05-2.60), and food insecurity (aPR = 1.45; 95% CI, 1.03-2.04) were associated with confirmed SARS-CoV-2 infection. Food insecurity (aPR = 1.38; 95% CI, 1.10-1.72), chronic physical health condition (aPR = 1.44; 95% CI, 1.15-1.80), chronic mental health condition (aPR = 3.65; 95% CI, 2.40-5.56), and increased anticipated discrimination scores (aPR = 1.03; 95% CI, 1.01-1.05) were associated with suspected SARS-CoV-2 infection. Thirty-four percent (n = 694 of 2024) of participants reported an inability to access COVID-19 testing when needed, which was associated with Latinx or Hispanic ethnicity, inconsistent telephone access, homelessness, disability, and transportation limitations. The majority (79.4%) reported a complete COVID-19 vaccine course at the time of participation. CONCLUSIONS: Inclusion of TGD people in public health surveillance and tailored public health strategies to address TGD communities' social and structural vulnerabilities may reduce barriers to COVID-19 testing.

Team Science: Advancing Women and Black, Indigenous, and other People of Color on the Pathway of Conducting Clinical Research.

Introduction: Innovative discovery begins with diverse perspectives; research teams should harness this model. Black, Indigenous, and other People of Color (BIPOC) and women are underrepresented as researchers. Team science leverages collaborative and cross-disciplinary approaches to diversify the research workforce, and introduces academic (and non-academic) faculty with limited research exposure/experience to clinical research. Methods: In 2020, two Black women academic physicians implemented an academic collaborative - COVID-19 Characteristics, Readmissions, Outcomes, and Social Determinants of Health (CROSS) - to investigate COVID-19 health inequities, with intentional recruitment of BIPOC and women. The 37 CROSS team members were of diverse races, ethnicities, sex, specialties, and disciplines, and represented eight hospitals. Team members were electronically surveyed to determine their interest, desired activities, and level of participation in research activities; concurrently, self-identified demographics (including race, ethnicity, sex, and language(s) spoken) were obtained. Results: All team members completed the survey: 78.4% (n = 29) were BIPOC and 78.4% (n = 29) were women. Team members spoke 18 languages (including English). Academic medical ranks included Assistant Professor (32.4%; n = 12), Associate Professor (16.2%; n = 6), and Full Professor (2.7%; n = 1). Each member identified desired activities (data collection, data analytics, manuscript development, abstract development/poster presentation, serving as a consultant) and the percentage of time they intended to allocate to each. Between June 2020 and February 2023, the team produced five original peer-reviewed manuscripts (including this article); five members served as first or senior authors. Twenty-one abstracts were presented at local conferences, and 10 at national and regional conferences. Five members achieved academic promotion, and team members were awarded three intramural grants resulting directly from team collaborations. Conclusion: Intentional recruitment and assessment of team members' desired levels of participation in an integrated clinical research team is an effective strategy to engage BIPOC and women. The CROSS Collaborative is a model for diversity and inclusion in team science and clinical research.