Search Results (473)

The rapid development of the logistics industry has underscored the urgent need for efficient and sustainable urban freight systems. As a core component of freight systems, heavy-duty trucks (HDT) have been researched regarding surface-level descriptive statistics of their heterogeneities, such as trip volume, frequency, etc., but there is a lack of in-depth analyses of the spatial interaction between freight travel and freight functional clustering, which restricts a systematic understanding of freight systems. Against this backdrop, this study develops a data-driven framework to analyze HDT behavioral heterogeneity and its spatial interactions with a freight functional zone in Shanghai. Leveraging the high-frequency trajectory data of nearly 160,000 HDTs across seven types, we construct a set of regional indicators and employ hierarchical clustering, dividing the city into six freight functional zones. Combined with the HDTs’ application scenarios, functional characteristics, and trip distributions, we further analyze the spatial interaction between the HDTs and clustered zones. The results show that HDT travel patterns are not merely responses to freight demand but complex reflections of urban industrial structures, infrastructure networks, and policy environments. By embedding vehicle behaviors within their spatial and functional contexts, this study reveals a layered freight system in which each HDT type plays a distinct role in supporting economic activities. This research provides a new perspective for deeply understanding the formation mechanisms of HDT trip distributions and offers critical evidence for promoting targeted freight management strategies. Full article

The COVID-19 pandemic significantly disrupted higher education worldwide, imposing strict isolation measures, transitioning learning online, and exacerbating existing social and economic inequalities. This literature review examines the pandemic’s impact on the mental health of college students, with a focus on those belonging to minority groups, including racial, ethnic, migrant, gender, sexuality-based, and low-income populations. While elevated levels of anxiety, depression, and loneliness were observed across all students, findings indicate that LGBTQ+ and low-income students faced the highest levels of psychological distress, due to compounded stressors such as family rejection, unsafe home environments, and financial insecurity. Racial and ethnic minority students reported increased experiences of discrimination and reduced access to culturally competent mental healthcare. International and migrant students were disproportionately affected by travel restrictions, legal uncertainties, and social disconnection. These disparities underscore the need for higher education institutions to implement targeted, inclusive mental health policies that account for the unique needs of at-risk student populations during health crises. Full article

Predicting passenger flows in rail transport systems plays an important role for traffic management centers to make fast decisions during service disruptions. This paper presents an innovative cross-disciplinary approach based on digital twins, deep learning, and traffic simulation to predict the total number of passengers in each train stations and evaluate the impact of service disruptions across stations. First, we present a four-layer system architecture for building a digital twin which ingests real-time data streams, including train movements and timetable scheduling. Second, we deploy several deep learning models to predict the total number of passengers in each station using mobile data. The results showcase significant accuracy for recurrent versus non-recurrent traffic conditions even under severe large disruptions such as the COVID-19 travel restrictions. Our case study of the Sydney rail network demonstrates that the proposed digital twin powered by deep learning can provide more granular real-time insights into the impact on passengers, allowing rail operation centers to better mitigate service disruptions. Full article

Synergetic transportation schemes are extensively used in package delivery operations, exploiting the best features of different modes. This paper proposes a methodology to solve the mode assignment and routing problem for the case of combined conventional vehicle and unmanned aerial vehicle (CV–UAV) parcel deliveries under uncertainty for next-day operations. This research incorporates ground and air uncertainties: travel times are assumed for conventional vehicles, while UAV paths are affected by weather conditions and restricted flying zones. A nested genetic algorithm is initially used to solve the problem under fixed conditions. Then, a robust optimization approach is employed to propose the best solution that will perform well in a stochastic environment. The framework is applied to a case study of realistic urban–suburban size, and results are discussed. The entire platform is useful for strategic decisions on infrastructure and for operation planning with satisfactory performance and less risk. Full article

The vigorous development of urban air mobility (UAM) is reshaping the urban travel landscape, but it also poses severe challenges to the safe and efficient operation of dense and complex airspace. Potential conflicts between flight plans have become a core bottleneck restricting its development. Traditional flight plan adjustment and management methods often rely on deterministic trajectory predictions, ignoring the inherent temporal uncertainties in actual operations, which may lead to the underestimation of potential risks. Meanwhile, existing global optimization strategies often face issues of inefficiency and overly broad adjustment scopes when dealing with large-scale plan conflicts. To address these challenges, this study proposes an innovative flight plan conflict management framework. First, by introducing a probabilistic model of flight time errors, a new conflict detection mechanism based on confidence intervals is constructed, significantly enhancing the ability to foresee non-obvious conflict risks. Furthermore, based on complex network theory, the framework accurately identifies a small number of “critical flight plans” that play a core role in the conflict network, revealing their key impact on chain reactions of conflicts. On this basis, a phased optimization strategy is adopted, prioritizing the adjustment of spatiotemporal parameters (departure time and speed) for these critical plans to systematically resolve most conflicts. Subsequently, only fine-tuning the speeds of non-critical plans is required to address remaining local conflicts, thereby minimizing interference with the overall operational order. Simulation results demonstrate that this framework not only significantly improves the comprehensiveness of conflict detection but also effectively reduces the total number of conflicts. Additionally, the proposed phased artificial lemming algorithm (ALA) outperforms traditional optimization algorithms in terms of solution quality. This work provides an important theoretical foundation and a practically valuable solution for developing robust and efficient UAM dynamic scheduling systems, holding promise to support the safe and orderly operation of large-scale urban air traffic in the future. Full article

Recent advancements in aviation and automation technologies have catalyzed the emergence of Urban Air Mobility (UAM), an innovative transportation paradigm involving the use of automated vertical take-off and landing aircraft for intra-city passenger travel. Despite growing global interest, the development and application of integrated geospatial frameworks for UAM infrastructure planning—particularly vertiport siting—remain limited. Thus, this study proposes a three-stage geospatial analysis framework, which consists of (1) Suitability analysis, employing multi-criteria decision-making techniques; (2) Regulation analysis, which screens out parcels restricted by aviation safety standards, land-use policies, and other statutory constraints; and (3) Location-allocation analysis, which spatially optimizes vertiport distribution in accordance with urban master plans and strategic transport priorities. Then, this framework is empirically applied to two South Korean UAM pilot sites—Busan and Jeju. The findings reveal that high-suitability areas are predominantly concentrated in dense urban cores with strong multimodal connectivity and mixed land-use configurations. However, a significant proportion of these zones are rendered infeasible due to regulatory exclusions, such as military flight paths and restricted airspace. Additionally, areas with lower suitability—often home to marginalized populations—raise critical equity concerns. This study contributes to the advancement of urban geospatial analytics by presenting a replicable methodological framework for vertiport site selection, while offering strategic insights to inform early-stage UAM deployment initiatives. Full article

This study quantified the effects of seven proposed traffic management strategies (MS) to leverage the synergy between Active Traffic Management (ATM) and connected and automated vehicles (CAV) to mitigate congestion, reduce queue lengths, and improve travel time after incident occurrence. First, three proposed MS are discussed: (a) controlling speed limit but not restricting lane changes, (b) directing CAV to change lanes earlier, and (c) restricting CAV in open lanes from lane changes near incidents. Then, combinations of these strategies are presented. At 10% CAV MP, MS1 that focuses on longitudinal control reduced travel time by 11.6% compared to 1.9% with no MS. Similarly, MS2, which directs CAV to change lanes earlier, were most effective when applied at 1-mile upstream of the incident site, achieving a notable 6.0% travel time reduction compared to 1.9% with no MS. The beneficial impact of MS3, which restricts CAV in open lanes from making lane changes near incident sites, became more pronounced with increasing CAV MP. Among the combined strategies (MS4 to MS7), some strategies proved more effective than others. Findings from Vissim simulation runs showed the importance of combining CAV and MS. Full article

Cutaneous leishmaniasis (CL) is a significant public health concern that affects many countries. This disease is caused by the protozoan parasite Leishmania spp. and is transmitted through the sandflies from the genus Phlebotomus and Lutzomyia. The clinical manifestations of CL can vary, often leading to challenges in accurate diagnosis and treatment. In 2022, a 51-year-old male patient presented to a tertiary care hospital in Puducherry, India, with progressively worsening facial lesions and granulomatous plaques. The patient had recently returned from Saudi Arabia, where he likely contracted the infection. Before he visited the tertiary care hospital in Puducherry, the patient had been misdiagnosed and treated for conditions such as Erysipelas and Acute Cutaneous Lupus Erythematosus (ACLE), highlighting the diagnostic challenges associated with CL. Skin scrapings from the patient were subjected to real-time PCR, confirming Leishmania spp.’s presence. Cytological examinations revealed the amastigote-like structures within macrophages, thereby establishing the identity of the parasite. For precise species-level identification, PCR-Restriction Fragment Length Polymorphism (PCR-RFLP) and Sanger sequencing of the Internal Transcribed Spacer-1 (ITS-1) region were performed. Molecular techniques confirmed the infection as being caused by Leishmania tropica. Following the accurate diagnosis, the patient was successfully treated with Liposomal Amphotericin B, a treatment known for its efficacy against Leishmania infections. This case underscores the critical importance of considering cutaneous leishmaniasis in the differential diagnosis of travelers returning from endemic areas who present with dermatological manifestations. The initial misdiagnosis and inappropriate treatment highlight the need for heightened clinical awareness and the utilization of advanced diagnostic tools for accurate identification. Effective and timely treatment, as demonstrated in this case, is essential for the management and control of the disease. This report emphasizes the necessity of vigilance among healthcare providers to recognize and appropriately address imported cases of cutaneous leishmaniasis. Full article

New energy vehicles produce zero tailpipe emissions and are an effective method for addressing traffic pollution. This study establishes a system dynamics management model to explore the mid- and long-term effects of the new energy vehicle promotion policy on urban traffic and environment. Additionally, we propose a nonlinear function optimization algorithm integrating system dynamics with an optimized even difference grey model to improve the model’s accuracy and validity. The dynamic simulation results show that (1) promoting new energy vehicles reduces tailpipe emissions and alleviates traffic pollution but may lead to a “green paradox” effect in the long term. Positive traffic control measures, such as driving restrictions, accelerate the “substitution effect” of new energy vehicles, and congestion and fuel consumption show a “rebound effect” in later stages. (2) A congestion charging policy reduces vehicle travel attractiveness and alleviates congestion. A sensitivity analysis indicates that a reasonable charging range is 20–40 yuan/(day × vehicle). (3) Introducing congestion charging and improving public transport supply level can effectively weaken the “paradox” effect. This combination not only mitigates congestion and pollution but also reduces economic losses and improves residents’ health. The strategy has a “lag effect” in the early stage but shows effectiveness in the middle (congestion alleviation) and later (pollution control) stages. Full article

Compared with traditional immunoassay methods, microfluidic immunoassay restricts the immune response in confined microchannels, significantly reducing sample consumption and improving reaction efficiency, making it worthy of widespread application. This paper proposes an exciting multi-frequency electrothermal flow (MET) technique by applying combined standing-wave and traveling-wave voltage signals with different oscillation frequencies to a three-period quadra-phase discrete electrode array, achieving rapid immunoreaction on functionalized electrode surfaces within straight microchannels, by virtue of horizontal pumping streamlines and transverse stirring vortices induced by nonlinear electrothermal convection. Under the approximation of a small temperature rise, a linear model describing the phenomenon of MET is derived. Although the time-averaged electrothermal volume force is a simple superposition of the electrostatic body force components at the two frequencies, the electro-thermal-flow field undergoes strong mutual coupling through the dual-component time-averaged Joule heat source term, further enhancing the intensity of Maxwell–Wagner smeared structural polarization and leading to mutual influence between the standing-wave electrothermal (SWET) and traveling-wave electrothermal (TWET) effects. Through thorough numerical simulation, the optimal working frequencies for SWET and TWET are determined, and the resulting synthetic MET flow field is directly utilized for microfluidic immunoassay. MET significantly promotes the binding kinetics on functionalized electrode surface by simultaneous global electrokinetic transport along channel length direction and local chaotic stirring of antigen samples near the reaction site, compared to the situation without flow activation. The MET investigated herein satisfies the requirements for early, rapid, and precise immunoassay of test samples on-site, showing great application prospects in remote areas with limited resources. Full article

In the mechanized harvesting of root vegetables, loosening is a key factor that restricts harvesting efficiency. Existing mechanical loosening methods have poor loosening effect and high operational resistance. Therefore, more efficient agricultural machinery is needed to reduce energy consumption and improve harvesting efficiency. To this end, based on the efficient excavation mechanism of the first claw toe structure of the mole cricket forefoot, this paper designs the shovel tip structure of the bionic loosening shovel by extracting its contour curve and analyzing the excavation process, constructs the working resistance model and dynamic balance equation of the bionic loosening shovel, determines the optimal working parameters through two-factor and three-level orthogonal simulation experiments, and carries out comparative simulation experiments with the common loosening shovels. The results show that the optimal combination of operating parameters for the bionic loosening shovel is the rotational speed $\omega$ = 5 r/s and the traveling speed of the whole machine v = 0.5 m/s. The disturbance performance of the 31 bionic loosening shovel on the soil is improved by 51.59% compared with that of the common loosening shovel, and the working resistance is reduced by 12.17%. The results of this study proved that the bionic structure of the first claw toe of the mole cricket can significantly improve the working performance of the loosening shovel, which can effectively improve the cutting effect of the soil and reduce the energy loss during the working process. Full article

Bikeshare has emerged as a sustainable mobility solution not only for addressing the first- and last-kilometer problem but facilitating short- and medium-distance travel. While existing research predominantly focuses on city-level Bikeshare Programs (BSPs), there is a paucity of studies examining university campus BSPs, particularly in terms of quantitative analysis of trip frequency and system operation sustainability. This paper presents a systematical framework to investigate university campus BSPs from two complementary perspectives: users’ travel characteristics and operational sustainability. To achieve this, two successive self-reported questionnaire surveys were conducted on the campus of South China University of Technology in 2017 and 2020, respectively. Subsequently, a multinomial logistic regression model was developed to identify the key factors influencing users’ travel frequency. Finally, a cost–benefit analysis was developed to assess the operational sustainability of the system. The findings reveal two significant insights: (1) the system was profitable under the 2017 fare policy, with the potential to maximize profits by strategically increasing fares while enhancing service quality; and (2) in 2020, when the fare is adjusted closer to the predicted optimal value, there is an increase in the proportion of high-frequency users, accompanied by improved user experience, reduced difficulty in bike access/return, and slightly lower pricing satisfaction. This study provides a valuable method that can be extended to the restricted service communities for effective planning and evaluation of bikeshare systems. Full article

Bioenergetic membranes of mitochondria, thylakoids, and chromatophores are primary sites of ATP production in living cells. These membranes contain an electron transport chain (ETC) in which electrons are shuttled between a series of redox proteins during the generation of ATP via oxidative phosphorylation. The phospholipid composition of these membranes, which often include negative lipids, plays a role in determining the electrostatics of their surface owing to the spatial distribution of their charged head groups. Cardiolipin (CDL) is a phospholipid commonly associated with bioenergetic membranes and is also a significant contributor to the negative surface charge. Interactions between cytochromes and phospholipid head groups in the membrane can in principle affect the rate of its travel between ETC components, hence influencing the rate of ATP turnover. Here, we use molecular dynamic (MD) simulations that feature an accelerated membrane model, termed highly mobile membrane mimetic (HMMM), to study protein–lipid interactions during the diffusion of cytochrome c₂ between redox partners in a bioenergetic membrane. We observe a “skipping” mode of diffusion for cytochromes along with a bias for binding to anionic lipids, particularly with a strong preference for CDL. During diffusion, cytochrome c₂ maintains a relatively fixed tilt with respect to the membrane normal with wider fluctuations in its angle with respect to the plane of the membrane. The obtained results describing the behavior of cytochrome c₂ on a representative bioenergetic membrane have direct ramifications in shuttling motions of other similar electron-carrying elements in other bioenergetic membranes, which are composed of a significant amount of anionic lipids. The mode of surface-restricted diffusion reported here would modulate rapid electron transfer between the ETC complexes anchored in bioenergetic membranes by reducing the search space between them. Full article

Viewing high-redshift sources at near-opposite directions on the sky can ensure, using light-travel-time arguments, acausality between their emitted photons. One utility would be true random-number generation through sensing these via two independent telescopes that each flip a switch based on the latest-arrived colours; for example, to autonomously control a quantum-mechanical (QM) experiment. Although demonstrated with distant quasars, those were not fully acausal pairs, which are restricted when simultaneously viewed from the ground at any single observatory. In optical light, such faint sources also require a large telescope aperture to avoid sampling assumptions when imaged at fast camera framerates: unsensed intrinsic correlations between them or equivalently correlated noise may ruin the expectation of pure randomness. One such case that could spoil a QM test is considered. Based on that, the allowed geometries and instrumental limits are modelled for any two ground-based sites, and their data are simulated. For comparison, an analysis of photometry from the Gemini twin 8 m telescopes is presented using the archival data of well-separated bright stars obtained with the instruments ‘Alopeke (on Gemini North in Hawai’i) and Zorro (on Gemini-South in Chile) simultaneously in two bands (centred at $562\mathrm{nm}$ and $832\mathrm{nm}$) with 17 Hz framerate. No flux correlation is found; these results were used to calibrate an analytic model predicting where a search with a signal-to-noise over 50 at 50 Hz can be made using the same instrumentation. Finally, the software PDQ (Predict Different Quasars) is presented, which searches a large catalogue of known quasars, reporting those with a brightness and visibility suitable to verify acausal, uncorrelated photons at these limits. Full article

Burgeoning two-dimensional (2D) materials provide more opportunities to overcome the shortcomings of silicon-based photodetectors. However, the inevitable carrier loss in the 2D material/Si heterojunction has seriously hindered further improvement in responsivity and detection speed. Here, we propose a graphene/PtSe₂/ultra-thin SiO₂/Si photodetector (PD) with multiple optimization mechanisms. Due to the fact that photo-generated carriers can travel in the graphene plane toward the Au electrode, the introduction of a top graphene contact with low sheet resistance provides a carrier collection path in the vertical direction and further restricts the carrier recombination behavior at the lateral grain boundary of PtSe₂ film. The ultra-thin SiO₂ passivation layer reduces the defects at the PtSe₂/Si heterojunction interface. As compared to the counterpart device without the graphene top contact, the responsivity, specific detectivity, and response speed of graphene/PtSe₂/ultra-thin SiO₂/Si PD under 808 nm illumination are improved to 0.572 A/W, 1.50 × 10¹¹ Jones, and 17.3/38.8 µs, respectively. The device can detect broad-spectrum optical signals as measured from 375 nm to 1550 nm under zero bias. The PD line array with 16-pixel units shows good near-infrared imaging ability at room temperature. Our study will provide guiding significance for how to improve the comprehensive properties of PDs based on 2D/Si heterostructure for practical applications. Full article