Search Results (37)

Emerging from the Bengali Muslim char-dwellers in the riverine environments of the Brahmaputra and its tributaries, the Miya Poetry movement is a unique environmentalism of the marginalized in contemporary Assam, India. Writing as a native scholar of Assam, I look at how the poetry movement displays the ethos of an ecopolitical spirituality that embodies the riverine ecology, environmental politics, and sacrality and how it challenges the majoritarian state’s narrative of the Bengali Muslim char-dwellers being denigrated as the “environmental waste producers”. My concept of “ecopolitical spirituality” is in tandem with Carol White’s ‘African American religious naturalism’, which elucidates the remembrance and evocation of traditional environmental relationships of and by the marginalized communities with the purpose of healing and rehumanizing themselves. I begin with a short history of the Miya Poetry movement among the Bengali Muslim char-dwellers in Assam. It narrates how the leading Miya poets adopt the local “Miya” dialect to express the traditional and continued relationships of Bengali Muslim char-dwellers who find themselves entangled with and nurtured by the land, rivers, plants, and animals. I then examine how Bengali Muslims have been framed by the majoritarian state and Assamese society as “environmental waste producers”. With climate change-induced destructive floods, along with post-colonial state’s rampant building of embankments leading to violent floods and erosion, Bengali Muslim char-dwellers are forced to migrate to nearby government grazing reserves or national parks. There, the majoritarian state projects them to be damaging the environment and issues violent evictions. In state reports too, the Bengali Muslim char-dwellers have been equated with “rats”, “crows”, and “vultures”. I use the concept of “environmental racism” to show how this state-led denigration justifies the allegation of the Muslim char-dwellers as “environmental waste producers” and how the Miya Poetry movement counters the racist allegation with new metaphors by highlighting the traditional relationships of the marginalized community with the riverine environment. In the final section, I look in detail at the characteristics and reasons that make the poetry movement ecopolitically spiritual in nature. I thus lay out an argument that the ecopolitical spirituality of the Miya Poetry movement resists the statist dehumanization and devaluation of Miya Muslims by not mocking, violating, or degrading the majoritarian Assamese but by rehumanizing themselves and their relationship with the environment. Full article

Kruger National Park is one of the most well-preserved national parks in the Southern Hemisphere. However, cases of visitors participating in deviant leisure practices (DLPs) are reported in the park, threatening the sustainability of sensitive tourism resources. Adopting a deviant leisure lens, this study assesses the extent to which visitors participate in DLPs at the Kruger National Park (KNP) and the causes of those behaviours. Variables adopted from the KNP codes of conduct for visitors were used to measure the DLPs based on the visitors’ perception of the park. A quantitative survey design, with a sample size of 237 respondents, assessed respondents’ participation in DLPs. The study results reveal that visitors participate in DLPs at KNP. However, the level at which visitors participate in DLPs is inconsistent. The most common DLPs by visitors are getting close to animals to take pictures and driving off-road to see animals. The reasons for visitors participating in these behaviours are the need to create memorable experiences and being in “holiday mode”. The least violated codes of conduct in the park are picking up archaeological objects to keep them as souvenirs and bringing prohibited items into the park without declaring. This study is significant as it is the first to investigate the extent visitors participate in DLPs using a self-reported instrument. Based on the results, park managers may develop effective strategies to reduce the number of visitors getting close to animals to take pictures and driving off-road to observe animals at close range. Full article

Traffic violations are among the leading causes of accidents and significantly compromise urban road safety. This study analyzed traffic violation and incident data collected by automated enforcement systems in urban Beijing from 2019 to 2023, consisting of 3264 traffic accident records and 147,876 traffic violation records. Through a spatiotemporal data association method, 2126 violations directly associated with accidents were identified. The FP-growth algorithm was then applied to derive 18 robust association rules encompassing five categories of accidents and four categories of violations. The findings indicate that the correlation between traffic accidents and violations displays clear peak periods during the morning (8:00–9:00) and evening (17:00–18:00). Violations such as red light running, stopping beyond the stop line during a red light, and ignoring prohibitions strongly correlate with traffic accidents under specific spatiotemporal conditions. Illegally parked vehicles not only reduce road transport efficiency but also significantly elevate the risk of traffic accidents in the surrounding area. The association rules identified in this study can assist traffic managers in formulating more effective measures to mitigate traffic violations, tackle traffic accidents at their source, enhance urban traffic safety, and promote the long-term sustainability of urban transportation systems. Full article

Rollover crashes are among the most prevalent types of accidents in developing countries. Various factors may contribute to the occurrence of rollover crashes. However, limited studies have simultaneously investigated both traffic stream and road-related variables. For instance, the effects of T-intersection density, U-turns, roadside parking lots, the entry and exit ramps of side roads, as well as traffic stream characteristics (e.g., standard deviation of vehicle speeds, speed violations, presence or absence of speed cameras, and road surface deterioration) have not been thoroughly explored in previous research. Additionally, the simultaneous modeling of crash frequency and intensity remains underexplored. This study examines single-vehicle rollover crashes in Yazd Province, located in central Iran, as a case study and simultaneously evaluates all the variables. A dataset comprising three years of crash data (2015–2017) was collected and analyzed. A crash index was developed based on the weight of crash intensity, road type, road length (as dependent variables), and road infrastructure and traffic stream properties (as independent variables). Initially, the dataset was refined to determine the significance of explanatory variables on the crash index. Correlation analysis was conducted to assess the linear independence between variable pairs using the variance inflation factor (VIF). Subsequently, various models were compared based on goodness of fit (GOF) indicators and odds ratio (OR) calculations. The results indicated that among ten crash modeling techniques, namely, Poisson, negative binomial (NB), zero-truncated Poisson (ZTP), zero-truncated negative binomial (ZTNB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), fixed-effect Poisson (FEP), fixed-effect negative binomial (FENB), random-effect Poisson (REP), and random-effect negative binomial (RENB), the FENB model outperformed the others. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) values for the FENB model were 1305.7 and 1393.6, respectively, demonstrating its superior performance. The findings revealed a declining trend in the frequency and severity of rollover crashes. Full article

Set in a wide open plain, the monolith of Uluṟu (‘Ayers Rock’) has become an internationally recognizable symbol for the Australian outback, currently attracting hundreds of thousands of tourists each year. Promoted since the 1950s as an exotic tourist destination, one of the major activities has been the ‘conquest’ of Uluṟu by completing the steep climb to the top. Always disapproved by the Aṉangu, the Indigenous Australian community of the area, and actively discouraged since 1990, the climb became an extremely contentious issue in the final two years before it was permanently closed to tourists on 26 October 2019. Given that climbing Uluṟu as a tourist activity has become an event of the past, this paper will examine the nature, materiality, and potential heritage value of the portable material culture associated with the climb. The background to the history of climbing Uluṟu in the context of European invasion (‘exploration’), the nature of tourism at Uluṟu and the role climbing played in this, as well as the management decisions that led to the closure of the climb can be grouped into four thematic periods: the beginnings of settler colonialist ascents (1873–1950), the ‘heroic’ age of Uluṟu tourism (1950–1958), lodges in a National Park (1958–1985), and joint management and the eventual closure of the climb (1985–2019). Based on a description of the material culture associated with the climb, particularly badges, patches and certificates, and drawing on the methodologies of historic and material culture studies, this paper will discuss the various interpretations of climbing Uluṟu and how the portable material culture reflects or exemplifies climbing as a conquest and heroic deed, as a spiritual ritual, and as a violation of cultural rights. After examining the materiality of the wearable material culture, we conclude by exploring which of these portable items are culturally significant and which, if any, should be curated in public collections. Full article

Despite the increasing sophistication of autonomous vehicles (AVs) and promises of increased safety, accidents will occur. These will corrode public trust and negatively impact user acceptance, adoption and continued use. It is imperative to explore methods that can potentially reduce this impact. The aim of the current paper is to investigate the efficacy of informational assistants (IAs) varying by anthropomorphism (humanoid robot vs. no robot) and dialogue style (conversational vs. informational) on trust in and blame on a highly autonomous vehicle in the event of an accident. The accident scenario involved a pedestrian violating the Highway Code by stepping out in front of a parked bus and the AV not being able to stop in time during an overtake manoeuvre. The humanoid (Nao) robot IA did not improve trust (across three measures) or reduce blame on the AV in Experiment 1, although communicated intentions and actions were perceived by some as being assertive and risky. Reducing assertiveness in Experiment 2 resulted in higher trust (on one measure) in the robot condition, especially with the conversational dialogue style. However, there were again no effects on blame. In Experiment 3, participants had multiple experiences of the AV negotiating parked buses without negative outcomes. Trust significantly increased across each event, although it plummeted following the accident with no differences due to anthropomorphism or dialogue style. The perceived capabilities of the AV and IA before the critical accident event may have had a counterintuitive effect. Overall, evidence was found for a few benefits and many pitfalls of anthropomorphising an AV with a humanoid robot IA in the event of an accident situation. Full article

The rapid advancements in vehicular technologies have enabled modern autonomous vehicles (AVs) to perform complex tasks, such as augmented reality, real-time video surveillance, and automated parking. However, these applications require significant computational resources, which AVs often lack. To address this limitation, Vehicular Edge Computing (VEC) has emerged as a promising solution, allowing AVs to offload computational tasks to nearby vehicles and edge servers. This offloading process, however, is complicated by factors such as high vehicle mobility and intermittent connectivity. In this paper, we propose the Hungarian Algorithm for Task Offloading (HATO), a novel approach designed to optimize the distribution of computational tasks in 5G-enabled VEC systems. HATO leverages 5G’s low-latency, high-bandwidth communication to efficiently allocate tasks across edge servers and nearby vehicles, utilizing the Hungarian algorithm for optimal task assignment. By designating an edge server to gather contextual information from surrounding nodes and compute the best offloading scheme, HATO reduces computational burdens on AVs and minimizes task failures. Through extensive simulations in both urban and highway scenarios, HATO achieved a significant performance improvement, reducing execution time by up to 75.4% compared to existing methods under full 5G coverage in high-density environments. Additionally, HATO demonstrated zero energy constraint violations and achieved the highest task processing reliability, with an offloading success rate of 87.75% in high-density urban areas. These results highlight the potential of HATO to enhance the efficiency and scalability of VEC systems for autonomous vehicles. Full article

The advent of internet of things (IoT) technology has ushered in a new dawn for the digital realm, offering innovative avenues for real-time surveillance and assessment of the operational conditions of intricate mechanical systems. Nowadays, mechanical system monitoring technologies are extensively utilized in various sectors, such as rotating and reciprocating machinery, expansive bridges, and intricate aircraft. Nevertheless, in comparison to standard mechanical frameworks, large amusement facilities, which constitute the primary manned electromechanical installations in amusement parks and scenic locales, showcase a myriad of structural designs and multiple failure patterns. The predominant method for fault diagnosis still relies on offline manual evaluations and intermittent testing of vital elements. This practice heavily depends on the inspectors’ expertise and proficiency for effective detection. Moreover, periodic inspections cannot provide immediate feedback on the safety status of crucial components, they lack preemptive warnings for potential malfunctions, and fail to elevate safety measures during equipment operation. Hence, developing an equipment monitoring system grounded in IoT technology and sensor networks is paramount, especially considering the structural nuances and risk profiles of large amusement facilities. This study aims to develop customized operational status monitoring sensors and an IoT platform for large roller coasters, encompassing the design and fabrication of sensors and IoT platforms and data acquisition and processing. The ultimate objective is to enable timely warnings when monitoring signals deviate from normal ranges or violate relevant standards, thereby facilitating the prompt identification of potential safety hazards and equipment faults. Full article

The widespread adoption of electric vehicles (EVs) poses challenges associated with charging infrastructures and their impact on the electrical grid. To address these challenges, smart charging approaches have emerged as a key solution that optimizes charging processes and contributes to a smarter and more efficient grid. This paper presents an innovative multi-objective optimization framework for EV smart charging (EVSC) using the Dynamic Hunting Leadership (DHL) method. The framework aims to improve the voltage profile of the system in addition to eliminating voltage violations and energy not supplied (ENS) to EVs within the network. The proposed approach considers both residential EV chargers and parking stations, incorporating realistic EV charger behaviors based on constant current charging and addressing the problem as a mixed integer non-linear programming (MINLP) problem. The performance of the optimization method is evaluated on a distribution network with varying levels of EV penetration connected to the chargers in the grid. The results demonstrate the effectiveness of the DHL algorithm in minimizing conflicting objectives and improving the grid’s voltage profile while considering operational constraints. This study provides a road map for EV aggregators and EV owners, guiding them on how to charge EVs based on preferences while minimizing adverse technical impacts on the grid. Full article

Dockless bike-sharing has experienced explosive growth, establishing itself as an integral component of urban public transport systems. Challenges such as parking violations have spurred operators and users to pursue standardized management. While electronic parking spots are employed to promote standard parking, suboptimal parking layouts can lead to illegal parking. Inadequate post-violation penalties fail to achieve standard parking, while excessive punishment diminishes user engagement. This study combines parking spot density and penalties to incentivize standard parking, and Beijing, China, was selected as the research object. Using an SP questionnaire survey, a binary logistic model analyzes bike-sharing users’ standard parking behavior and willingness to adhere to different rules. Findings reveal that optimal walking distances range from 300 to 450 m for service levels and exceed 400 m for service efficiency. Influential factors include gender, age, occupation, usage behavior, and travel preferences. Users with high-frequency, low-convenience expectations, low travel costs, and flexible travel exhibit strong adherence. Additionally, user acceptance of the maximum distances without penalties follows an exponential distribution, with 80% accepting 400 m and 40% accepting 800 m. Enforcement has a visible effect within 300 m, but diminishes with longer distances. Excessive penalties result in significant user loss. Full article

The Belt and Road Initiative (BRI) has become a household name for developing countries, especially in Africa. The BRI proposal by Chinese President Xi Jinping was positively received by many countries, including policymakers in China. In response, the Chinese Government committed to investing USD 1 trillion over ten years from 2013 to 2023. As a result, 152 countries signed a cooperation agreement with China to work under the BRI framework. The BRI has played a vital role in addressing the global infrastructures gap through the construction of modern highways, airports, high-speed railways, bridges, power generation (hydropower), and industrial parks. As a result, this has enhanced connectivity and economic growth between Asia, Europe, and Africa. Despite the BRI’s significant role in strengthening trade, infrastructure and investment links between China and other countries, there is limited literature on specific countries’ experience with the initiative. This study, therefore, will advance our understanding of the BRI, especially on the conceptualization of the term; comparative analysis of Africa–China relationships before and after the BRI; the benefits in relation to the “Five Connectivities” and the challenges the BRI is facing in Africa. The article is based on a literature review and case study as research methodologies mainly used the Policies, Projects, Initiatives, and Strategies (PPIS) as a data source. The study focuses on five African countries; Uganda, Kenya, Egypt, Djibouti, and Mozambique. These countries were selected purposefully for analysis because of their experience, long-term relationships with China, and strategic locations. The findings revealed that the BRI lacked a clear description and that it was difficult to distinguish between BRI projects and other regular economic or diplomatic relations. The study also identified four differences between Africa–China relationships before and after the BRI. Furthermore, the findings revealed that the BRI has positively contributed to all five connectivity pillars. However, the major challenges reported concerning the initiative from the various countries were: procurement corruption, low/lack of involvement of stakeholders, high compensation prices, labor violations, increasing debts, and environmental hazards. In conclusion, while the BRI has brought about significant infrastructure development and economic benefits, the project has also experienced some challenges. This study, therefore, contributes to the body of knowledge on China’s Belt and Road Initiative and its impact on African countries, specifically in Uganda, Kenya, Djibouti, Mozambique, and Egypt. The paper then provides conclusions and policy implications as well as future research opportunities in the current body of the literature. Full article

The major problem in Thailand related to parking is time violation. Vehicles are not allowed to park for more than a specified amount of time. Implementation of closed-circuit television (CCTV) surveillance cameras along with human labor is the present remedy. However, this paper presents an approach that can introduce a low-cost time violation tracking system using CCTV, Deep Learning models, and object tracking algorithms. This approach is fairly new because of its appliance of the SOTA detection technique, object tracking approach, and time boundary implementations. YOLOv8, along with the DeepSORT/OC-SORT algorithm, is utilized for the detection and tracking that allows us to set a timer and track the time violation. Using the same apparatus along with Deep Learning models and algorithms has produced a better system with better performance. The performance of both tracking algorithms was well depicted in the results, obtaining MOTA scores of (1.0, 1.0, 0.96, 0.90) and (1, 0.76, 0.90, 0.83) in four different surveillance data for DeepSORT and OC-SORT, respectively. Full article

High-precision ground point cloud data has a wide range of applications in various fields, and the separation of ground points from non-ground points is a crucial preprocessing step. Therefore, designing an efficient, accurate, and stable ground extraction algorithm is highly significant for improving the processing efficiency and analysis accuracy of point cloud data. The study area in this article was a park in Guilin, Guangxi, China. The point cloud was obtained by utilizing the UAV platform. In order to improve the stability and accuracy of the filter algorithm, this article proposed a triangular grid filter based on the Slope Filter, found violation points by the spatial position relationship within each point in the triangulation network, improved KD-Tree-Based Euclidean Clustering, and applied it to the non-ground point extraction. This method is accurate, stable, and achieves the separation of ground points from non-ground points. Firstly, the Slope Filter is used to remove some non-ground points and reduce the error of taking ground points as non-ground points. Secondly, a triangular grid based on the triangular relationship between each point is established, and the violation triangle is determined through the grid; thus, the corresponding violation points are found in the violation triangle. Thirdly, according to the three-point collinear method to extract the regular points, these points are used to extract the regular landmarks by the KD-Tree-Based Euclidean Clustering and Convex Hull Algorithm. Finally, the dispersed points and irregular landmarks are removed by the Clustering Algorithm. In order to confirm the superiority of this algorithm, this article compared the filter effects of various algorithms on the study area and filtered the 15 data samples provided by ISPRS, obtaining an average error of 3.46%. The results show that the algorithm presented in this article has high processing efficiency and accuracy, which can significantly improve the processing efficiency of point cloud data in practical applications. Full article

Street children are among the most marginalized children, globally, who experience severe violations of their rights and face multiple deprivations. This study aimed to describe street children’s characteristics and working conditions in Iran. Method: This cross-sectional rapid survey was conducted from March to May 2017 in six major cities in Iran. The sample group consisted of Iranian and non-Iranian girls and boys, aged 10 to 18, who worked on the streets for at least one month prior to the survey. Time–location based sampling was used. A total of 856 Children were randomly selected from 464 venues, including corners of streets, parks, metro gates, bus stations, shopping malls, and shopping centers frequented by street children. Results: Findings showed that 90% of participants were boys, 60% were between 10 and 14 years old, almost 50% attended school, 12% were illiterate, and 32% had quit school. Children of Afghan nationality comprised 54% of the study participants, and the rest were Iranian. Of all participants, 85% resided with family or relatives. Most children (75.5%) worked more than 5 h daily, and vending (71.2%) and waste picking (16.1%) were common activities. Street children suffered, mainly, from harsh weather (22.7%), insults and beatings of everyday people (21%), starvation (20.7%), and police repression (15.4%). More than half of the study participants were not involved in intervention programs, and just 7% of them had attended any health education programs. Conclusion: Street children reported little to no service use, which may contribute to poor health. Street children require immediate attention to improve their wellbeing. Decision-makers and academicians should collaborate on intervention development research to design appropriate health and social interventions targeted at street children. Full article

The Pauli limiting field represents a fundamental magnetic field at which the superconducting state collapses due to the spin-paramagnetic Cooper pair-breaking effect. Cao et al. (Nature 2021, 595, 526) reported that the magic-angle twisted trilayer graphene (MATNG, N = 3) exhibits the upper critical field which exceeds the Pauli limiting field by two to three times. This observation was interpreted as a violation of the Pauli-limiting field in MAT3G. Similar conclusions were recently reported by the same research group in MATNG (N = 4, 5) superlattices (Park, J.M. et al. Nat. Mater.2022, 21, 877). Here, we point out that Cao et al. (Nature 2021, 595, 526) calculated the Pauli limiting field by the use of reduced form (to the weak-coupling limit) of full equation of the theory of the electron–phonon-mediated superconductivity. Considering that in the same paper, Cao et al. (Nature 2021, 595, 526) reported that MATNGs are strong coupled superconductors, we calculate the Pauli limiting field for a strong coupled case and show that the observed upper critical fields in MATNGs comply with the Pauli limit. This implies that there is no violation of the Pauli limiting field in the Moiré multilayer graphene superlattices. Full article