Infrastructure Support Research Articles

Enlightening Stakeholders on the COVID-19 Pandemic Impacts and Preparation for Minimizing Future Pandemics’ Negative Effects on Occupational Therapists

The COVID-19 pandemic has affected all aspects of professional disciplines including occupational therapy; however, little is known about how much of an impact the COVID-19 pandemic affected occupational therapy practice in Ghana. This study examined the impacts, coping strategies, and COVID-19 pandemic lessons for occupational therapy practices in the future. A descriptive qualitative design was employed with a purposive and convenience sampling methods to recruit occupational therapists from four practice settings in Ghana. Semi-structured interviews were conducted with seven participants. Interviews were audio-recorded, transcribed, and analyzed using thematic analysis. Four major themes were identified from the analysis enlightening stakeholders on the impact and preparation for minimizing the impact of future pandemics on the workloads of an occupational therapist. The major themes are (1) impacts of the COVID-19 on occupational therapy practice and practitioners; (2) aspects or domains of work significantly affected by the pandemic; (3) the existing strategies employed to handle the challenges; and (4) strategies to minimize these challenges in the future. The current study has enlightened stakeholders on the need to make alternate preparations including telehealth, continuous support for telehealth infrastructures, training of practitioners, and research to adapt intervention strategies effectively.

SME FINANCING THROUGH FINTECH: AN ANALYTICAL STUDY OF TRENDS IN NIGERIA AND THE USA

In this comprehensive review, we examine the burgeoning influence of Financial Technology (FinTech) on Small and Medium Enterprises' (SMEs) financing, with a focus on comparative trends between Nigeria and the USA. The paper aims to dissect how FinTech innovations have redefined the landscape of SME financing, facilitating enhanced accessibility and efficiency in financial services. Through an extensive literature review that spans academic journals, industry reports, and case studies, this study synthesizes current knowledge on the subject, offering a panoramic view of the FinTech ecosystem and its implications for SMEs in both developed and developing economies. Our analysis reveals that in the USA, FinTech has dramatically transformed SME financing by introducing alternative lending platforms, which provide more agile and less cumbersome financing options than traditional banks. This shift has not only improved the speed of funding but also expanded the availability of capital to a broader range of businesses. Conversely, in Nigeria, FinTech's impact is seen in the democratization of financial services, where mobile money and digital banking platforms have significantly increased SMEs' access to financial resources, overcoming historical barriers such as lack of collateral and banking infrastructure. The paper identifies key factors driving FinTech adoption in SME financing, including regulatory environments, technological advancements, and SMEs' growing demand for flexible financial solutions. It also highlights the challenges and opportunities inherent in leveraging FinTech for economic development and SME growth in both countries.
 Conclusively, the study underscores the transformative potential of FinTech in bridging the financing gap faced by SMEs, while also pointing out the necessity for supportive policies, digital literacy, and infrastructure development to fully harness FinTech's benefits. This review contributes to the ongoing dialogue on FinTech's role in economic empowerment, offering insights that could inform policymakers, practitioners, and researchers interested in the nexus between technology and small business financing.
 Keywords: Internet of Things (IoT), oil industry, efficiency, innovation, sustainability, challenges, strategies, emerging trends, cross-country collaboration, USA, Nigeria..

Remote Work Evolution: Contrasting Realities in China and US

The COVID-19 pandemic has posed significant challenges to industries, increasing the uncertainty and dynamics of operations. In this context, digital transformation becomes a core approach for organizations to address challenges. The purpose of this article is to investigate how the COVID-19 pandemic has affected remote work in China and the United States, compare the disparities in telework between the two nations, and evaluate the implementation of remote work during and after the pandemic. Digital transformation has become the cornerstone of long-term organizational competitiveness and sustainability, increasing an organization's agility, innovation potential, and internal collaboration efficiency. There are cultural, regulatory, and technological infrastructure differences between China and the United States when it comes to remote work practices. In the early days of the epidemic, companies in both countries quickly promoted remote working due to policy support, industry culture, and digital infrastructure. After the epidemic, Chinese companies resumed traditional offline office models, while the United States was more inclined to support remote work. In the future, China's office model may develop towards a hybrid work model, emphasizing digital transformation to support remote work. This article recommends that companies adopt flexible working systems, strengthen employee skills training, and build on a culture of trust. In terms of outlook, hybrid working models will attract high-quality employees and require the exploration of new management methods to adapt to remote working models.

Semantics-Enabled Data Federation: Bringing Materials Scientists Closer to FAIR Data

The development and discovery of new materials can be significantly enhanced through the adoption of FAIR (Findable, Accessible, Interoperable, and Reusable) data principles and the establishment of a robust data infrastructure in support of materials informatics. A FAIR data infrastructure and associated best practices empower materials scientists to access and make the most of a wealth of information on materials properties, structures, and behaviors, allowing them to collaborate effectively, and enable data-driven approaches to material discovery. To make data findable, accessible, interoperable, and reusable to materials scientists, we developed and are in the process of expanding a materials data infrastructure to capture, store, and link data to enable a variety of analytics and visualizations. Our infrastructure follows three key architectural design philosophies: (i) capture data across a federated storage layer to minimize the storage footprint and maximize the query performance for each data type, (ii) use a knowledge graph-based data fusion layer to provide a single logical interface above the federated data repositories, and (iii) provide an ensemble of FAIR data access and reuse services atop the knowledge graph to make it easy for materials scientists and other domain experts to explore, use, and derive value from the data. This paper details our architectural approach, open-source technologies used to build the capabilities and services, and describes two applications through which we have successfully demonstrated its use. In the first use case, we created a system to enable additive manufacturing data storage and process parameter optimization with a range of user-friendly visualizations. In the second use case, we created a system for exploring data from cathodic arc deposition experiments to develop a new steam turbine coating material, fusing a combination of materials data with physics-based equations to enable advanced reasoning over the combined knowledge using a natural language chatbot-like user interface.

Using Hyperspectral Images and Lidar Data to Create Models for the Classification and CAVE Visualization of Tree Species

The article describes the use of artificial intelligence methods to create models for detecting and classifying tree species, using hyperspectral images and LiDAR data in the aerial photography of energy line structures. The most important output is a validated model with cloud infrastructure support for detecting and classifying objects of interest at the TRL 5 level, which is also exceptional on a global scale. The outputs of the research are also a geodatabase of reference tree characteristics, a library of spectral curves, a database of simulation of tree growth, but also a cloud infrastructure to support the development of classification models and data storage. An important output will be the visualization of the results of simulations in the "CAVE" environment.

A review of the institutional landscape for dual-career hiring in higher education

Meeting the needs of dual-career academic couples has become an important part of university efforts to foster family-friendly workplaces. Many universities have developed formal or informal approaches to addressing dual-career issues, but variation across institutions has made it difficult to detect wider patterns or probe their implications. In this paper, we analyze the dual-career policies and materials (848 documents total) of all R1 institutions in the United States. As with studies from roughly two decades ago, we find deficiencies in institutional support and transparency. However, given reduced state revenues for institutions of higher education and a rise in precarious employment arrangements over the same time period, conditions for academic couples are arguably worse today. In order for universities to address these concerns and contribute meaningfully to broader forms of inclusion, we argue that there is a need for sustained funding commitments and infrastructural support for dual-career programs.

Human Capital Formation in High-Tech: Features of Government Policy

Purpose: is to reveal the peculiarities of government policy aimed at building human capital in high-tech industries. Methods: this research is based on a systems approach; decomposition of human capital in order to identify systemic gaps in its formation; qualitative (traditional) analysis of government programs and projects; a comparative analysis of the directions of Russian government policy and some leading countries in the field of high technologies aimed at human capital development. Results: the essence and structure of the organization's human capital are considered based on the stages of its reproduction, as well as from the position of its expanded interpretation. Systemic gaps in the formation of human capital of high-tech organizations have been identified, including gaps in the formation of individual and corporate human capital, as well as in the institutional and infrastructural support for its reproduction. The features of Russian government policy aimed at the formation of human capital in the high-tech sector are shown, in comparison with the policies of a number of foreign countries. The role of government programs and projects (“Priority2030”, “Professionalitet” and “Advanced Engineering Schools”) in overcoming systemic gaps in the formation of human capital in high-tech organizations is outlined. Conclusions and Relevance: the performed analysis showed the presence of a wide range of government policy measures of a number of countries that occupy leading positions in the field of high technology, aimed at developing human capital in the high-tech sector. Among them are the development of fundamental science, interdisciplinary and mathematical knowledge, STEM competencies, as well as strengthening the interaction between the academic sector and the high-tech sector. The arsenal of tools of domestic government policy includes a focus on practice-oriented training, the development of digital competencies, advanced training of management personnel, as well as the development of interaction between the academic and high-tech sectors. The federal project “Advanced Engineering Schools” corresponds to the elimination of the largest number of system gaps. At the same time, the systemic gap at the stage of formation of general human capital, which manifests itself in the poor physical and mathematical training of schoolchildren, remains unresolved.

Artificial Intelligence (AI) applications and usage among the LIS professionals of Pakistan

Artificial intelligence (AI) is an important and emerging sub-discipline in information technology that is progressively being implemented in every field. It is gradually being introduced to support new forms of research, discovery, and reuse of library contents in advanced and interesting ways. University libraries have the potential to substantially improve their library services through the implementation of sophisticated AI tools. This study explored the application of AI tools in the university libraries of Pakistan, as well as draw a comparison in the usage of AI tools between public and private sector universities. This is a quantitative study and data is collected through survey methodology. We used purposive sampling to collect the data from 175 university libraries. The collected data was analyzed using a statistical package for social sciences (SPSS-version 22). Findings indicate that while AI-based services are starting to be introduced into university libraries in Pakistan, no university library has implemented the full suite of AI-based tools. Natural language processing, voice searching, and chatbots are the most familiar and popular tools currently used in libraries. However, robotics technology is rarely used with a mean value of (1.62) because of the financial investment and high level of IT skills required. We found that private university libraries are using AI tools more as compared with public sector university libraries. The study concludes with several key recommendations, including closer collaboration between the library and the respective university IT department for technical support and assistance; improved financial support and ICT infrastructure to establish AI technology-based library services; and training development plans for library staff. Insights gained from this study should contribute to the capacity of Pakistani University librarians and their staff to maximize the full potential of AI within their institutions. The research implications are helpful to library leaders and policymakers in building a policy for AI-based technology in their respective university libraries.

Empowering Nurses for High-Value Healthcare: A Call for Legislative and Systemic Change.

Recognizing the positive impact of clinical data outcomes and patient care experiences, coupled with the growing preference for advanced practice RNs among patients, it is imperative that nurse leaders propel legislative reforms and infrastructure support from health systems. This strategic approach is crucial for maximizing the potential of nurses in improving patient care experience and outcomes, as well as increasing accessibility to healthcare in every community.

The case for a climate bonus: waste pickers’ perceptions of climate change in Minas Gerais

While the work of waste pickers advances urban sustainability, there has been little focus on how climate change impacts affect them. This paper reports on a pilot study with 61 waste pickers in Minas Gerais, Brazil to understand their perspectives on climate change impacts and actions. It explores how waste pickers experience climate change impacts at home and at work, their adaptive strategies and the specific actions and actors needed to address these impacts. Waste pickers have practical knowledge and experience of climate events. But due to precarious employment and lack of access to services, infrastructure and social support, their responses are improvised and inefficient. They require better institutional support and their proposals must be incorporated into a negotiated approach to urban resilience. Proposals such as the climate bonus – similar to the existing recycling bonus – may help address the structural drivers of vulnerability for waste pickers in Minas Gerais.

The Pancreatic Cancer Early Detection (PRECEDE) Study is a Global Effort to Drive Early Detection: Baseline Imaging Findings in High-Risk Individuals.

Pancreatic adenocarcinoma (PC) is a highly lethal malignancy with a survival rate of only 12%. Surveillance is recommended for high-risk individuals (HRIs), but it is not widely adopted. To address this unmet clinical need and drive early diagnosis research, we established the Pancreatic Cancer Early Detection (PRECEDE) Consortium. PRECEDE is a multi-institutional international collaboration that has undertaken an observational prospective cohort study. Individuals (aged 18-90 years) are enrolled into 1 of 7 cohorts based on family history and pathogenic germline variant (PGV) status. From April 1, 2020, to November 21, 2022, a total of 3,402 participants were enrolled in 1 of 7 study cohorts, with 1,759 (51.7%) meeting criteria for the highest-risk cohort (Cohort 1). Cohort 1 HRIs underwent germline testing and pancreas imaging by MRI/MR-cholangiopancreatography or endoscopic ultrasound. A total of 1,400 participants in Cohort 1 (79.6%) had completed baseline imaging and were subclassified into 3 groups based on familial PC (FPC; n=670), a PGV and FPC (PGV+/FPC+; n=115), and a PGV with a pedigree that does not meet FPC criteria (PGV+/FPC-; n=615). One HRI was diagnosed with stage IIB PC on study entry, and 35.1% of HRIs harbored pancreatic cysts. Increasing age (odds ratio, 1.05; P<.001) and FPC group assignment (odds ratio, 1.57; P<.001; relative to PGV+/FPC-) were independent predictors of harboring a pancreatic cyst. PRECEDE provides infrastructure support to increase access to clinical surveillance for HRIs worldwide, while aiming to drive early PC detection advancements through longitudinal standardized clinical data, imaging, and biospecimen captures. Increased cyst prevalence in HRIs with FPC suggests that FPC may infer distinct biological processes. To enable the development of PC surveillance approaches better tailored to risk category, we recommend adoption of subclassification of HRIs into FPC, PGV+/FPC+, and PGV+/FPC- risk groups by surveillance protocols.

Education for children and youth living in Canadian military families: Lessons from the past and future considerations

LAY SUMMARY Infrastructure to support the educational experiences of children and youth living in Canadian military families has ebbed and flowed over time. With the launch of initiatives, such as Seamless Canada, in recent years and the recent restructuring of support infrastructure in the Department of National Defence, it appears that the educational experiences of military-connected children and youth are once again becoming a priority. However, without knowledge and awareness of past efforts to support the educational experiences of these children and youth, present-day challenges faced by the Canadian Armed Forces may make forward progress more difficult. Using the Second World War Canadian military, particularly the Royal Canadian Air Force (RCAF), as a historical example, this article provides lessons learned and future considerations for supporting the educational experiences of children and youth from Canadian military families.

Literature Study on Problems of Office Management Vocational School Teachers in Implementing Learning Technology

This systematic literature review investigates the challenges faced by vocational school teachers in implementing educational technology. Adopting the PICOC framework, it synthesizes findings from 10 articles published between 2014-2024, selected from Scopus, Web of Science, EBSCOhost, and ProQuest databases. The review explores factors influencing teachers' readiness and effectiveness in integrating technology, such as digital competence, infrastructure, and leadership support. Key challenges identified include time constraints, inadequate training, and limited technical support. Strategies to enhance readiness involve continuous professional development, ICT expert support, diverse training programs, and collaborative learning communities. The findings contribute to developing effective policies and initiatives to support vocational teachers in successfully leveraging technology, ultimately improving education quality and preparing students for the digital era.

Healthcare institution efficiency: Meta-analysis and case study

The article analyses the factors that influence the efficiency of a medical institution. The VOSviewer bibliometric analysis allowed to identify four main clusters that determine the dominant areas of scientific research related to the topic of the medical institution efficiency. The largest cluster was the one describing the relationships between factors that directly determine the healthcare facility efficiency (decision-making, use of information technologies (artificial intelligence, blockchain, Internet of Things, etc.), effectiveness of solving medical problems of patients, etc.) The second largest cluster combines research areas related to the organisation, management, standardisation, audit, professional development, quality and productivity in healthcare facilities. The third and fourth clusters are related to the service and resource components in ensuring the efficiency of a medical institution, respectively. The article presents various approaches to classifying performance indicators of a medical institution: by type of performance, by form, by costs, by measurement of results, by scope of work, by stages. The national approaches to the medical industry development in the UK, Ukraine and Germany are analysed. The mechanisms for decentralising the management of medical institutions, increasing their autonomy, productivity and quality of medical services are described on the example of Ukraine. Using the pattern of a typical medical institution in a small city of Ukraine, the mechanisms for increasing efficiency are analysed: in terms of staffing, patient care, financing, corporate culture, patient-centeredness, and control over financial flows separately for each level of medical care. Priority steps to improve the infrastructure support of the subject of analysis, possible measures to improve the quality of medical services, the preferred resources for financing the planned measures, the implementation period and the expected results of proposed measures are identified. From the theoretical point of view, this article deepens knowledge about the nature of the medical institution efficiency. From a practical point of view, recommendations and ways to improve the medical institution efficiency make it possible to form a roadmap for promising changes. Their implementation will increase the primary healthcare facility efficiency and ensure a vivid rise in the medical provision efficiency at the secondary level in the short and medium term.

Two Rings and a Doctorate: Gender and Marital Status in the Pursuit of Ph.D. Success in Moroccan Universities

This study provides a qualitative examination of the intersected impact of gender and marital status on Ph.D. success for both men and women in Morocco. Utilizing semi-structured interviews with 20 married doctoral students from both genders across three Moroccan universities, the research revealed a significant divergence in the lived experiences and Ph.D. success indicators of married men and women. Men were generally encouraged by gender expectations, which often served as a motivator in their academic journey, whereas women faced hurdles due to these expectations, as their academic roles often collided with traditional roles as wives and mothers. Both genders, however, reported struggles in maintaining work-life balance, with women experiencing more challenges due to social expectations and conventional gender roles. This research emphasized the importance of a strong support system and a conducive home environment for academic success. Cultural context significantly influenced the participants’ academic journey, stressing the need for societal change and redefinition of traditional gender roles. The findings suggest the need for institutional and societal efforts to establish a supportive infrastructure for all Ph.D. students, irrespective of their marital status or gender.

Regional ecosystems of socially oriented entrepreneurship in Southern Kazakhstan

Goal – scientific work is based on defining conceptual approaches to the formation of regional ecosystem model of socially oriented entrepreneurship and identifying opportunities for its implementation for sustainable growth of socio-economic development of regions. Methods – bibliographic analysis of scientific articles in this area. The modeling method contributed to justifying the need to form a regional “business ecosystem”. The statistical method allowed to draw conclusions about the state and prospects for expanding social entrepreneurial activity in the Republic of Kazakhstan. Results – a review of literature sources made it possible to identify a direction aimed at solving social problems as the basic form of manifestation of socialization and inclusiveness of modern economy, ensuring its sustainable development by achieving not only the social efficiency of entrepreneurial initiative, but also economic profitability; the importance of various types of social projects is shown, which is based on fundamental principle of entrepreneurial practice, the essence of which is to ensure its self-sufficiency: non-profit organizations (NPO), including socially oriented ones. Conclusions – for effective and efficient use of potential of social startups in the context of sustainable development of society, it is necessary to study their phenomenon and develop ecosystem of corporate social responsibility not only at microeconomic level in individual and collective forms of the enterprise, but also in the macroeconomic format of the institution of regional ecosystem of socially oriented entrepreneurship, which is being formed as a network of interrelations between subjects of commercial, non-profit and public sectors, establishing the interaction of supply and demand for social value created. The main elements of ecosystem should be the state, social capital, market for social services and infrastructural support.

Challenges and Opportunities of Implementing Open Access Policies

Purpose: The aim of the study was to investigate the challenges and opportunities of implementing open access policies in African universities.&#x0D; Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.&#x0D; Findings: The implementation of open access policies in African universities faces significant challenges due to limited infrastructure, funding constraints, and inadequate institutional support. However, these challenges also present opportunities for collaboration, capacity building, and leveraging existing networks to enhance access to scholarly research. By overcoming these barriers through strategic partnerships and targeted investments, African universities can foster greater knowledge dissemination, innovation, and socio-economic development across the continent.&#x0D; Unique Contribution to Theory, Practice and Policy: Institutional theory, diffusion of innovation theory&amp; resource dependency theory may be used to anchor future studies on the challenges and opportunities of implementing open access policies in African universities. Implementing open access policies in African universities encourages innovation in knowledge management practices, including the development of institutional repositories, metadata standards, and digital preservation strategies. African universities' implementation of open access policies can influence national and regional policy frameworks related to scholarly communication, research funding, and copyright reform.

AI competitions as infrastructures of power in medical imaging

ABSTRACT This article examines how platform-based AI competitions structure power relations in medical imaging research. It focuses on two leading platforms, Kaggle and Grand Challenge, which provide organisational as well as infrastructural support to run AI competitions. In dialogue with critical AI and platform studies research, we investigate how such competitions are organised – under which infrastructural conditions and by whom – and how this shapes processes of model production and evaluation. To address these concerns, we have collected data from 118 medical image AI competitions on Kaggle and Grand Challenge, organised between January 2017 and May 2022. In addition, a variety of platform boundary resources – platform documentation, competition descriptions, dataset descriptions, and competition leaderboards – have been gathered. The analysis of these materials shows, first, that platforms direct the AI development process by requiring substantial financial resources, defining which institutions can host a competition and under which conditions. Second, competition organisers define dataset diversity and the generalisability of models. As most datasets are constructed with data from hospitals in North America, Western Europe and China, the application of models to different geographical contexts is potentially limited. Finally, competition participants influence model development through the institutional, demographic, and disciplinary contexts in which they operate. Overall, the examination demonstrates the importance of critically interrogating the entire medical AI research pipeline, including the definition of research problems, the construction of datasets as well as model production and evaluation.

Design of Instrumentation and Control Components of Power Distribution Systems

Introduction. In recent years, the development of high-voltage power systems has received a boost due to the need for infrastructural support for priority development areas. Universal models and algorithms are required to implement processes in power components and identify their optimal parameters. However, there are no such solutions. Accordingly, there are no ready-made subsystems with control and optimization algorithms adequate to the tasks under consideration. The objective of the presented research is to develop an optimization subsystem for the design of control and measurement components of power distribution systems.Materials and Methods. Methods for constructing automated design systems, optimization, system analysis, mathematical modeling, and adaptive control were used. When selecting methods, we proceeded from the fact that the components of power distribution systems consisted of a finite number of elements. The synthesis of a power system includes tens or hundreds of sequential operations. This was taken into account in the developed models and algorithms.Results. The possibilities of managing and monitoring manufacturing processes (MP) for the production of components of low-voltage power distribution systems were shown in terms of checking the operability and correct functioning of processing equipment. A modular structure was created to allow the integration of CAD output files into the manufacturing processes of energy distribution system components. A functional diagram of a subsystem for control and monitoring of the manufacturing processes of the production of components of power distribution systems was developed. The proposed schematic diagram of production control showed how the data collection subsystem, management system, and operating mechanisms were involved in the control of operations. The multi-level optimization module model created within the framework of this research sequentially optimized the service intensity of the i-th block, the input flow separation coefficients, and the priorities of the original data flows that form the input flow of the i-th block.Discussion and Conclusion. The combined application of modeling, system analysis, and optimization methods maintains control of the accuracy of the generated power components. The algorithm for controlling electrical loads opens up opportunities for creating a mathematical model of a power supply system that combines management, control, and monitoring, which ultimately leads to an improvement in the quality of electric power. The solution can be in demand in the development of power systems of priority development areas.

Exploring the changes in travel behavior between the first and second waves of the COVID-19 pandemic in Dhaka

The COVID-19 outbreak created immense disruptions in our daily lives. Travel is one of the major areas severely impacted by the pandemic. Bangladesh experienced two waves of COVID-19 between March 2020 and July 2021. Although several studies focused on significant changes in the travel behavior of urban road users before and during the pandemic, hardly any research examined the differences between the two waves. Hence, it was important to study the differences in travel behavior between the two waves of the COVID-19 pandemic to understand how the effects of travel restrictions, health concerns, and the severity of the pandemic on people's travel decisions change over time. This study intends to investigate the changes in travel behavior between the first and second waves of the COVID-19 pandemic in Dhaka and the factors that influence these changes. Data were collected through online questionnaire surveys using the Google form. Voluntary response and convenience sampling techniques were used to collect responses from 447 people in Dhaka. Descriptive statistics and non-parametric tests were conducted to analyze the data. In addition, two multinomial logistic models were developed to identify the factors behind the changes in travel behavior. This study reveals that work and shopping trips increased, whereas work-from-home and online shopping somewhat decreased during the second pandemic wave compared to the first pandemic wave. Most non-car owners who reduced their use of public transportation during the first pandemic increased their use during the second wave. There was no significant increase in the use of active transport modes for work and shopping trips in Dhaka. The perceived risk of COVID-19 infection was relatively lower during the second wave, influencing the respondents to travel more frequently for work and shopping purposes. Ensuring more adaptive public transportation, flexibility to work from home, and creating supportive infrastructures for active transport modes might help to provide a safe, affordable, and efficient transportation system for all during the future waves of the pandemic and other unprecedented events.