Critical Intersections Research Articles

Considering traffic characteristics: Roadside unit deployment optimization algorithm based on dynamic division of road network subareas

AbstractGiven that the overall coverage deployment method fails to meet information needs in important areas, there are redundancies and deficiencies in the information provided. To enhance communication stability for roadside units (RSUs), improve information coverage at critical intersections and optimize algorithm efficiency. Here, a method for deploying RSUs is proposed that aims to optimize revenue in road network subareas. The road network is divided into several subareas based on critical intersections, node similarity, road segment correlations, and characteristics of RSU information transmission. Then, a roadway accessibility algorithm is developed that accounts for channel fading. Considering the robustness of wire network deployment, an improved traveling salesman problem (TSP) problem is proposed that includes candidate locations and constructs a model for optimal RSU deployment that maximizes consolidated revenue. Finally, using the Sioux Falls network as an example, the RSU deployment strategy is evaluated for the overall network and the road network after being subdivided. The results indicate that subdividing the road network improves the efficiency of the optimization solution, the information coverage of critical intersections increases by 1.8 times. The deployment optimization scheme of RSUs is directly influenced by various parameters such as bandwidth capacity and cost coefficient. When deploying RSUs in road network subareas, variations in total demand have minimal impact on RSU deployment, ensuring a stable deployment scheme.

Quantifying the vulnerability of road networks to flood-induced closures using traffic simulation

Disruptions in road networks can significantly impact traffic flow, necessitating the identification and mitigation of vulnerable components. This study presents a methodology to assess the vulnerability and robustness of road networks, addressing the research gap in comprehensive approaches that effectively evaluate both controlled intersections and uncontrolled/free-flow highway segments. The proposed framework employs traffic simulation tools to model road closures within designated study areas, focusing on networks in Qatar. Performance measures such as average control delay and volume to capacity ratios are utilized to calculate vulnerability indices for network components. The two-pronged approach quantifies the impact of simulated closures at both the component and network levels, revealing critical intersections and road segments that markedly affect network performance during disruptions. The findings contribute to the field by providing transportation engineers with an effective quantitative tool to detect vulnerabilities in their road network, guiding design plans and actions to mitigate the potential harmful impacts of disruptive events on transportation infrastructure. The methodology's scalability ensures its applicability to various operational contexts, offering significant insights for transportation planning and infrastructure resilience. By establishing a comprehensive vulnerability analysis framework, this study enhances the understanding and management of road network vulnerabilities in complex urban environments. Further research on integrating dynamic traffic assignment and real-time data is recommended to further enhance the predictive accuracy and applicability of the proposed framework, ultimately improving transportation infrastructure resilience.

The Toxic Mix of Multiculturalism and Medicine: The Credentialing and Professional-Entry Experience for Persons of African Descent

This essay is based on a case study of international medical graduates (IMGs) in Canada who migrated from sub-Saharan Africa. The chapter examines how narratives of race are situated and deployed in the field of medicine and can produce some aversive social–psychological landscapes in the credentialing and the professional-entry process as it relates to persons of African descent. It will show that, often without predetermination or intent, professionals of African descent in Canada are highly susceptible to implicit racial associations and implicit racial stereotyping in relation to evaluations of character, credentials, and culture. The article exposes some of the critical intersections of common experience, such as: (a) cultural deficit bias—Whiteness as an institutionalized cultural capital attribute; (b) confirmation bias—reaching a negative conclusion and working backwards to find evidence to support it; (c) repurposed sub-Saharan Blackness stereotypes—binary forms of techno-scamming and fraud; and (d) biased deception judgement—where the accuracy of deception judgements deteriorates when made across cultures. These social psychological phenomena result in significantly disproportionate returns on their foreign education and labour market experience for Black medical professionals that require decisive efforts in changing the narratives.

A Systematic Review of Artificial Intelligence Used to Predict Loneliness, Social Isolation, and Drug Use During the COVID-19 Pandemic.

This systematic literature review evaluates the role of machine learning, artificial intelligence (AI), and social determinants of health (SDOH) in identifying loneliness during the COVID-19 pandemic. By examining various studies and articles through a comprehensive search of databases EBSCOhost, Medline Complete, Academic Search Complete, Directory of Open Access Journals, and Complementary Index, the research team sought to discern consistent themes and patterns. We identified four constructs central to understanding the impact of the pandemic on societal well-being: (1) the prediction of compliance with COVID-19 measures, (2) the prediction of loneliness and its effects, (3) the prediction of well-being and social inclusion, and (4) the prediction of drug use. Within these constructs, prevalent themes related to opioid overdose, stress levels, mental health, well-being, and cognitive decline emerged. The adherence to the PRISMA 2020 checklist has resulted in a PRISMA flow diagram that categorizes the selected literature. The findings of this review, including the proportion of studies predicting various attributes related to loneliness, demonstrate the critical intersections between machine learning, AI, SDOH, and the psychosocial phenomenon of loneliness amidst a global health crisis. The review results provide a summary of the occurrences and predictive percentages of each construct as determined by the literature, contributing to a nuanced understanding of the pandemic's multifaceted impact on loneliness, social isolation, and drug use. Using AI to predict these constructs has remarkable capabilities in identifying individuals at risk and facilitating timely interventions to mitigate adverse outcomes and promote mental health resilience in the face of challenges such as the COVID-19 pandemic. Moving forward, future research is warranted to refine AI algorithms, validate predictive models and utilize AI-based interventions in healthcare and mental health services while ensuring data security, and individuals' privacy.

Bi-Directional Exploitation of Human Trafficking Victims: Both Targets and Perpetrators in Cybercrime

ABSTRACT The article investigates cyber-trafficking, scrutinizing the utilization of cyberspace in generating victims of trafficking. Concurrently, it delves into the methods employed to induce trafficked individuals to participate in cyber-scams and underscores how the gains from these scams are subsequently used to fund and orchestrate sophisticated transnational organized crimes. Consequently, the article discusses the emerging bidirectional relationship between cybercrime and human trafficking, representing a significant trend within organized crime by illustrating a dynamic interaction where cybercrimes are committed to facilitate human trafficking, and conversely, the trafficking of individuals becomes a means to execute cybercriminal activities. The discussion further explores the critical intersections between cybercrime and human trafficking, contributing to a substantial increase in the number of victims of both cybercrime and trafficking. A notable aspect emphasized is the shift in human trafficking targets, expanding beyond traditional demographics to include individuals, especially men with technical education. This departure from the historical focus on women and children underscores the adaptability of traffickers in leveraging the skills of a new demographic. Furthermore, it evaluates the actions taken by international governmental bodies and policymakers to address this ongoing issue and discusses additional measures that could be implemented. The article aims to offer valuable insights for policymakers, law enforcement professionals, and researchers grappling with the intricacies of this evolving nexus and, therefore, advocates for an intensified focus on research in this field and urges collaborative efforts to proactively address the issue before it surpasses current capabilities.

A Holistic Approach to Early Relational Health: Cultivating Culture, Diversity, and Equity.

Early Relational Health (ERH) is the foundation for infant and child emotional and social wellbeing. ERH is a quality of relationships co-created by infants, caregivers, and other members of their families and communities from pregnancy through childhood. Relationships themselves are not ERH; rather, ERH can be a feature of relationships. Those that are characterized by positive, shared emotionality become contexts within which members co-develop mutual capacities that enable them to prevail and flourish. This essay offers a synthesis of current knowledge about ERH in the US and begins to integrate Indigenous and non-Indigenous research and knowledge about ERH in the hope that readers will embrace "Etuaptmumk"-"Two-Eyed Seeing". The authors maintain that systems of care for infants, families, and their communities must first and foremost attend to revitalization, cultural context, diversity, equity, and inclusion. Authors discuss key concepts in ERH; Indigenous and non-Indigenous research that inform ERH; structural and systemic factors in the US that affect ERH ecosystems; the critical intersections of culture, diversity, equity; the broader concept of village support for fostering ERH; and efforts to revitalize ERH discourse, practices, and policies. The authors advocate for a holistic approach to ERH and suggest future directions for research and advocacy.

Sociodemographic Characteristics Associated with Higher Numbers of COVID-19 Cases: A Neighbourhood Level Study in Ottawa, Ontario

INTRODUCATION: The complex interplay of the social conditions that one lives in and functions greatly influences the exposure to a certain health condition and the ability to recover from it. Reports on COVID-19 diagnosis, hospitalization and fatality reveal a clear sociodemographic divide with the marginalized communities bearing a disproportionately higher burden of the outcomes. The objectives of this study was to explore the neighbourhoods characteristics associated with higher COVID-19 rates in Ottawa by employing a social determinants of health framework that identifies critical intersections that impact of multi-level determinants of health. METHODOLOGY: This study is based on data on 98 neighbourhoods in Ottawa that were collected from the Ottawa Neighbourhood study (ONS). The outcome variable was COVID-19 rate between March 09, 2020 - January 31, 2021. The independent variables were potentially vulnerable groups, Socioeconomic, neighbourhood, and demographic factors. We used descriptive and logistic regression methods to analyse the data. RESULTS: The neighbourhoods that had relatively high number of rates COVID-19 cases were Hunt Club Park (909), Manor Park (831), Greenboro East (739), Overbrook McArthur (641), and Hunt Club Upper-Blossom Park (619); and the ones with lowest rates were Laurentian (44), Old Ottawa South (31), Richmond (22), Riverside South Leitrim (19), Wateridge Village (5), and Westboro (3). Multivariate regression analysis showed that neighborhood characteristics such as percentage of community health center within a 50m walk, higher population density, higher percentage of people taking public transportation to work, higher percentage of people with no high school diploma, perceived walkability score, low income prevalence, higher percentage of unsuitable housing,  households with multiple family,  refugee population, new comer during 2011-16, single parent family, and higher percentage of living alone were associated higher odds of above average COVID-19 rates. CONCLUSION: These findings reflect a greater likelihood of COVID-19 infection in the neighbourhoods with poorer socioeconomic and living conditions such as low income, unhealthy housing, and higher population density. Addressing the challenges among the disadvantaged communities may help reduce the higher vulnerability and promote health conditions.

Assessment of Traffic Characteristic at Major Urban Road Intersection of Kathmandu Valley: A Case Study of Khanivivag, Kesarmahal, and Narayanhiti Intersections

This study addresses the prevalent issue of traffic congestion at critical intersections in urban areas, leading to slowed traffic and increased queue lengths. The centralization of the Kathmandu Valley has contributed to a gradual rise in population thus impacting the efficiency of the traffic management system. This study focuses on three of the busiest intersections of the valley i.e. Kesharmahal, Narayanhiti, and Khanibhivag intersections and aims to provide insights into current traffic conditions and propose measures for enhancing traffic flow. Data collected is analyzed to determine current traffic flow, saturation flow, existing capacity, Level of Service (LOS), and intersection delay using the HCM Manual. The analysis involves assessing present conditions and making comparisons with standardized data. Three days of traffic volume data during peak hours and geometric features of the intersection were gathered. Results indicate that the intersections are experiencing over-saturation, exceeding their capacity based on existing geometry and signalization. Additionally, the vehicle replacement strategy showed limited effectiveness in reducing saturation flow, with the flow persisting at an over-saturated level. These findings highlight the need for targeted measures to address the challenges posed by congestion and enhance the efficiency of traffic management at these intersections for smooth traffic flow.

Towards liminal balance: Unpacking the UK's urban canal space

AbstractThis paper critically examines the liminal geographies of the United Kingdom's 7,000‐mile canal and river network, embodying a thread of complex intersections and interactions between water and land. Drawing on a study involving stakeholder interviews, group discussion with canal users, and observational walks in Manchester and London, the paper explores the concepts of liminal flux, scalar intersections, and deliminalisation. We first outline how the UK's urban canals are characterised by liminal flux over time and space, reflecting their dynamic geographies. Revealing the presence of critical intersections between liminality and scale, we then focus on the ongoing and everyday spatial and territorial entanglements between different canal and towpath users. Finally, we consider the challenge of deliminalisation, and an associated shift from liminality and in‐betweenness towards greater spatial fixity via neoliberal intervention and development. Our findings highlight the importance of preserving the unique characteristics of urban canals as liminal spaces, arguing that they provide recreational opportunities and contribute to urban wellbeing by providing opportunities for ‘transitory dwelling places’. Maintaining a liminal balance within urban canal environments is therefore crucial and requires careful curation. In turn, this notion of curating liminal balance has implications for other potential waterfront developments that offer a similar positive potential for hydrocitizenship and its fluid ambiguities of in‐betweenness. Moreover, it demonstrates the importance of a ‘lighter touch’ of redevelopment and governance in some parts of the urban environment to help preserve, or even enhance, citizen wellbeing.

Investigation on geometric and surface finish quality of 3D concrete printed walls with hollow section

3D concrete printed walls with hollow sections are now widely adopted in 3D concrete printing applications across the construction industry. One of the significant challenges in the printing process is achieving superior surface finishes. Previous research has predominantly focused on the overall geometry of these walls, often neglecting surface finish quality at the intersections of formwork and supporting filaments. This study is dedicated to optimizing the geometric arrangement of supporting filaments and enhancing print quality at these critical intersections. Firstly, two arrangement strategies, the standard approach and the average approach, are introduced to establish high-quality geometric section configurations, with practical demonstrations on both rectangular and arc-shaped walls. Subsequently, the width of concrete filaments is considered to enhance surface finish quality at the intersections. Two print quality control methods, namely the e- Δ control rule and the r- Δ control rule, are then developed. To assess the effectiveness of these arrangement strategies and control methods, configurations of walls with specific dimensions are compared, and printing experiments are conducted. Finally, recommendations for practical application are provided, aimed at improving both the geometric and surface finish quality of 3D concrete printed walls with hollow sections.

Claiming ecological grief: Why are we not mourning (more and more publicly) for ecological destruction?

Eco-anxiety, grief and despair are increasing, yet these emotions tend to remain private, rarely expressed in public. Why is it important and necessary to grieve for ecological loss? Why are we not—as individuals and societies—coming together to express and share our grief for ecological destruction? I address these questions from three angles. Firstly, I draw on recent literature on ecological grief and prior work on grief for human lives, to argue for the importance and urgency of grieving publicly for ecological loss. Building on this, I identify perceptual, cognitive, affective, ritual and political obstacles to ecological mourning; these obstacles point at critical intersections between emotions, practices, disciplines, public and private realms, which can turn into fruitful venues for further research, debate and action on ecological grief (and its absence). In closing, I propose a set of ‘ecological skills’ that might help us overcome these obstacles, and lead us to embrace ecological grief and mourning as acts of ethical responsibility and care for the planet.

Critical intersections in popular culture

In this editorial, the editors introduce the 12.2 volume of The Australasian Journal of Popular Culture. The dynamic and interdisciplinary nature of the field is discussed with reference to the collection of articles within the volume, highlighting the malleability of popular culture in all its transdisciplinary forms. The editors provide a summary of the seven articles included in the volume, which collectively represent diverse critical discussions of the field across sociopolitical, socioeconomic and sociocultural artistic realms. The articles examine the evolving realms of the monstrous, the mythic, the heroic and the historical through various mediums like television, film, characters and historical moments. The editors then conclude by offering a summary of the three book reviews included in the volume.

Understanding the Intersections of IPV and HIV and Their Impact on Infant Feeding Practices among Black Women: A Narrative Literature Review

Intimate partner violence (IPV), particularly sexual and emotional violence, against Black mothers who acquire human immunodeficiency virus (HIV) during childbearing age is a significant health and social concern requiring targeted interventions and precautions. IPV against women increases the chances of early mixed feeding, placing infants at high risk of mother-to-child transmission of HIV and increasing infant morbidities. Although violence complicates many Black mothers’ lives, limited research evidence exists about the critical intersections of violence, HIV, and motherhood. Women’s fear associated with IPV makes them less likely to disclose their positive HIV status to their partners, which subsequently prevents them from applying the guidelines for safe infant feeding practices. This review aims to explore the critical intersections between IPV and HIV and their impact on the infant feeding practices of Black mothers living with HIV. Furthermore, the theme of IPV and how it overlaps with other factors such as HIV-positive status and gender dynamics to compromise the motherhood experience is also the focus of this narrative review of existing literature. Understanding the intersection of IPV and other factors influencing infant feeding practices among women living with HIV will help inform programming and policy interventions for HIV-positive Black women who may experience IPV during the perinatal period.

Macroscopic Fundamental Diagram Estimation Considering Traffic Flow Condition of Road Network

A macroscopic fundamental diagram (MFD) is an important basis for road network research. It describes the functional relationship between the average flow and average density of the road network. We proposed an MFD estimation method based on the traffic flow condition. Firstly, according to statistical theories, the road network data are divided into three traffic flow conditions (free flow, chaotic and congested) bounded by a 95% confidence interval of the maximum traffic capacity of each intersection in the road network. Then, in each condition, we combined principal component analysis and the Jolliffe B4 method to reduce dimension for extracting critical intersections. Finally, the full-scale dataset of the road network was reconstructed to estimate the road network MFD. Through numerical simulation and empirical research, it is found that the root mean square error and absolute percentage error between estimated MFD and true MFD considering the traffic flow condition are smaller than those without considering the traffic flow condition. The MFD estimation and the division of the traffic states of the road network were completed at the same time. The proposed method effectively saves the time cost of road network research and is highly accurate.

Arap Şairlerin Osmanlı Hükümdarlarına Övgü Şiirleri

This study aims to examine the rich tradition of panegyric odes composed by Arab poets in honor of Ottoman sovereigns, highlighting the historical, cultural, and political context that gave rise to this distinctive form of literary expression. The paper seeks to explore the reciprocal relationship between Arab poets and the Ottoman Empire, shedding light on how these poets paid tribute to the imperial majesty, conveyed the sultans’ might, and helped to legitimize their rule. By focusing on a diverse range of panegyric odes from the later periods of the Ottoman Empire, the research encompasses the evolving dynamics of power, patronage, and poetic expression that underpinned this unique interaction between Arab poets and the Ottoman court. The primary purpose of the study is to offer a comprehensive analysis of the thematic and stylistic features of these panegyric odes, elucidating the creative strategies employed by Arab poets to extol the virtues of the Ottoman sultans and to articulate their own political, social, and religious allegiances. The paper utilizes historical, literary, and textual analysis, to examine panegyric poetry’s role in fostering cultural exchange and diplomatic communication between the Arab and Ottoman worlds, and its function in bolstering imperial ideology and projecting the Ottoman state’s image. This paper further delves into the critical intersections of politics, religion, and artistic expression within these odes, illuminating how the poets navigated these spheres to construct a nuanced portrait of Ottoman rule. By interpreting the subtexts, allegories, and metaphors employed within these poems, the research uncovers the profound philosophical, spiritual, and cultural paradigms that underscored the political landscapes of the time. Through this lens, the panegyric odes emerge as invaluable literary artifacts that bear testimony to the grandeur of the Ottoman Empire and the intricate socio-political relationships that existed between the Arab poets and the Ottoman court.

Identifying critical urban intersections from a fine-grained spatio-temporal perspective

With the rising travel demand of crowds, urban road networks are under increasing pressure, which makes them progressively more fragile. Accurate identification of critical intersections is essential for urban management, resource allocation and traffic supervision. However, existing intersection evaluation methods fail to fully exploit transportation infrastructure, travel behavior and their synergistic relationships, resulting in coarse-grained and low-dynamic evaluation results. In this study, we develop an urban Intersection Evaluation framework from a Fine-grained Spatio-Temporal perspective (IE-FST). The framework is divided into three parts: fine-grained extraction of intersection information, multi-perspective assessment of node importance, and dynamic perception of spatio-temporal patterns in importance ranking. Specifically, IE-FST upgrades the intersection evaluation scale to turn-level, proposes the concept of Turning Sub-Node (TSN) and constructs a refined TSN topology network. Then, by finely extracting the network properties and mobility patterns of TSNs and mining the association patterns among TSNs, IE-FST proposes a Critical Fine-grained node Identification (CFI) algorithm to achieve a refined and dynamic evaluation of urban intersections. Finally, IE-FST analyzes the temporal characteristics and spatial distribution of TSN importance rankings, and provides traffic management measures for different types of TSNs to improve urban transport efficiency. Experiments are performed in Wuhan, China, and the results indicate that the proposed IE-FST framework achieves an accurate perception of urban intersections with high spatial and temporal resolution. This study promotes a better understanding of the synergistic relationships between crowd travel movements and urban transportation infrastructure, and provides theoretical support for infrastructure siting, refined traffic supervision, and rational resource allocation, thus contributing to the resilient and sustainable development of transportation systems and society.

Implementation of Traffic Light Controlling System for a Simple Intersection with VHDL using Quartus II

In the era of urbanization in the 21st century, the number of vehicles on the road has increased drastically to cope with the increased population of the city which directly affects the traffic on the street and more importantly on intersections. Automatic traffic signaling system can plays a vital role to mitigate vehicle congestion in the critical intersections of the busy roads. To ensure hassle free mobility of vehicles in the intersection on the street, the appropriate traffic signal lights are necessary that coordinate traffic in various directions on the streets. A simple intersection on the road is considered for the simulation of traffic signaling system. VHDL code was written in Quartus II to implement traffic light system for specific intersections on the road. The vehicles are always moving on the main road, meaning green light is always ‘1’ until there are vehicles approaching the side road. When the vehicles arrive on the side road which is sensed by sensor, then the traffic controller takes the initiative to schedule the traffic light, from green to red light in the main road and red to green light in the side road. The proposed traffic signaling system works properly, which is verified during simulation. In this paper, simple intersection is considered due to simple design and easy implementation.

Translanguaging and Learning Stories in preschool: Supporting language rights and social justice for Latinx children, families, and educators

This article focuses on elements of successful sociocultural inclusion and linguistic participation in a bilingual dual-language preschool for Latinx children. It presents a subset of findings from a three-year qualitative research project in which Latinx critical race theory and a translanguaging framework were used to illuminate critical intersections between children's funds of knowledge, their translanguaging talents, and their interests in play and social interaction. Learning Stories served as both the focus for documentation and the unit of analysis for understanding children's translanguaging experiences, as well as for promoting new forms of authentic assessment for family engagement.

Frequent Congestion Detection Model Based on Critical Intersection Identification

Intersection information in urban transportation networks is critical to the safe and efficient operation of road traffic. The controllability of the road network can be increased by controlling critical intersections during peak traffic periods. On the one hand, based on the improved intra- and inter-level correlation description matrix of time steps, a directed supra-adjacency matrix (DSAM) temporal network model is built to verify the validity of the model using the road network data of urban core areas and compare the results with those obtained from static critical intersection identification. The results show that the DSAM model has a phase continuity feature in ranking the intersection importance, which has richer connotation than the critical intersection identification results based on a single indicator and has better consistency at different time granularity. On the other hand, based on the DSAM model to identify critical intersections of road network, short-term traffic flow prediction is performed with the help of a road network adjacency matrix, and the results show that the Chebyshev diagram convolution neural network (ChebNet) has the best performance. It can be used in the detection of recurrent congestion of urban road networks, and corresponding control measures are made in shorter time steps, which can prevent the possibility of widespread congestion and reduce the blockage of the whole road network. In summary, the model can be used for critical intersection identification and congestion detection in urban road networks.

Toward a Plausible Methodology to Assess Rock Slope Instabilities at a Regional Scale

Slope failures along road cuts and highways, occurring due to heavy rainfalls or earthquakes, pose significant threats to people, vehicles, and emergency plans. In the present study, a methodology to assess the stability of rock slopes at a regional scale is proposed using a kinematic analysis and a probabilistic limit equilibrium analysis for plane sliding and wedge failure modes. The workflow adopted is described through its implementation along the main road network of the island of Thasos, located in northern Greece. On-site investigations and measurements along the island’s road network formed the basis of the present study. The results of the kinematic analysis showed that the joint sets, which were identified during the on-site investigations, formed critical intersections that could lead to wedge and plane sliding failures. The on-site measurements and the results of the kinematic analysis were utilized to perform limit equilibrium back-analyses at sites of identified failures due to the water pressure effects to probabilistically estimate the material strength properties of the joints. Subsequently, numerous limit equilibrium analyses were executed within a Monte Carlo simulation framework to produce representative fragility curves of rock slopes against plane sliding and wedge failures along the main road network, due to earthquake loading and water pressures.