This study investigates how emotionally structured online interaction networks shape consumer perception of new energy vehicle (NEV) technology. Drawing on discussion forum data from two leading NEV brands, Brand_T and Brand_B, we focus on how users respond to brand technological narratives and how these responses translate into distinct patterns of peer-to-peer interaction. Using a behavioral network analysis framework, we integrate sentiment analysis, topic modeling, and Exponential Random Graph Modeling (ERGM) to uncover the psychological and structural mechanisms underlying consumer engagement. Three main findings emerge. First, users display brand-specific emotional-cognitive profiles: Brand_T communities show broader technological engagement but more heterogeneous emotional responses, whereas Brand_B communities exhibit more emotionally aligned discussions. Second, emotional homophily is a robust driver of interaction ties, particularly in Brand_B forums, where positive sentiment clusters into dense and supportive discussion subnetworks. Third, perceived technological benefits, rather than risk sensitivity, are consistently associated with higher interaction intensity, underscoring the motivational salience of anticipated gains over cautionary concerns in shaping engagement behavior. The study contributes to behavioral science and transportation behavior research by linking consumer sentiment, cognition, and social interaction dynamics in digital environments, offering an integrated theoretical account that bridges the Elaboration Likelihood Model, social identity processes, and behavioral network formation. This advances the understanding of technology perception from static individual evaluations to dynamic, group-structured outcomes. It highlights how emotionally patterned interaction networks can reinforce or recalibrate technology-related perceptions, offering practical implications for NEV manufacturers and policymakers seeking to design psychologically informed communication strategies that support sustainable technology adoption.
Abstract Superconducting transmission line resonators (TLRs) have been widely applied to circuit quantum electrodynamical systems for superconducting quantum computation and single-photon detections. Recently, such a right-handed TLR has been generalized to electromagnetic metamaterials (MTMs), and its unconventional mode structure has been experimentally characterized (Wang et al. in Phys Rev Appl 11:054062, 2019). Here, we demonstrate another kind of MTM TLR, i.e., the superconducting quarter-wavelength composite right/left-handed (CRLH) TLRs composed of lumped elements. We design the devices and analyze their transport properties by developing a real-space approach, wherein the physical parameters at the device boundaries are utilized conveniently. Superconducting MTM TLRs with typical three unit cells were experimentally prepared by etching a superconducting aluminum film on a SiO $$_2$$ substrate, and their microwave transport properties were measured at low temperatures of 50 mK. The results show that the modes spacing in such a quarter-wavelength CRLH-TLR is non-uniform, due to the nonlinear dispersion relation. This implies that it could be utilized to encode the superconducting qubits, analogously to the usual ones encoded by using the Josephson devices.
Hafiz Usman Ahmed, Salman Ahmad, Xinyi Yang
et al.
In the typical landscape of road transportation, about 90% of traffic accidents result from human errors. Vehicle automation enhances road safety by reducing driver fatigue and errors and improves overall mobility efficiency. The advancement of autonomous vehicle technology will significantly impact traffic safety, potentially saving more than 30,000 lives annually in the United States alone. The widespread acceptance of autonomous and connected autonomous vehicles (AVs and CAVs) will be a process spanning multiple decades, requiring their coexistence with traditional vehicles. This study explores the mobility and safety performance of CAVs in mixed-traffic environments using the cumulative-anticipative car-following (CACF) model. This research compares the CACF model with established Wiedemann 99 and cooperative adaptive cruise control (CACC) models using a VISSIM platform. The simulations include single-lane and multi-lane networks, incorporating sensitivity tests for mobility and safety parameters. The study reveals increased throughput, reduced delays, and enhanced travel times with CACF, emphasizing its advantages over CACC. Safety analyses demonstrate CACF’s ability to prevent traffic shockwaves and bottlenecks, emphasizing the significance of communication range and acceleration coefficients. The research recommends early investment in vehicle-to-infrastructure (V2I) communication technology, refining CACC logic, and expanding the study to diverse road scenarios.
Extended Abstract
Background: Despite possessing unique natural and economic potentials, the coastal villages of Sari and Miandoroud counties face numerous challenges, such as youth migration, declining employment, environmental degradation, and inefficiencies in utilizing local resources. These issues have led to reduced economic and social sustainability in these areas, emphasizing the urgent need for innovative and sustainable approaches to their development. In this context, sustainable rural entrepreneurship emerges as an effective strategy, playing a pivotal role in addressing these challenges. Sustainable entrepreneurship can serve as a driving force for transformation and progress by creating job opportunities, increasing income, enhancing public participation, activating social capital, and optimizing the use of human resources. Particularly, leveraging local potentials, such as coastal tourism and marine-related industries in these regions, offers a unique opportunity for economic and social transformation. Therefore, designing and presenting innovative and localized models for sustainable entrepreneurial development in these areas are of significant importance. This study aims to design a model for sustainable rural entrepreneurship development in the coastal areas of Sari and Miandoroud, addressing the specific needs of these regions while contributing to positive changes toward economic and social sustainability.
Methods: Since this research aims to identify the components of a sustainable rural entrepreneurship model and configure these components while determining their levels of influence, it is of a "survey" type in terms of data collection. It is also classified as "non-experimental" in terms of the level of control and supervision. The research approach is a mixed "qualitative-quantitative" method, conducted in 2024. Data were collected using semi-structured interviews and questionnaires. In the first phase, a deep understanding of the issue was achieved through a systematic literature review. To localize the model according to the context and limitations of the community, components were then identified and categorized using expert opinions in the fields of entrepreneurship and rural business through purposeful sampling and the snowball technique. In the second phase, Interpretive Structural Modeling (ISM) and MICMAC analysis were used to design the intended model and establish relationships between the model dimensions. The statistical population in the quantitative section included experts, entrepreneurs, and business owners from 14 coastal villages of Sari and Miandorud, with a total of 60 individuals selected through snowball sampling. MAXQDA version 10 was used for content analysis, SPSSv23 for descriptive statistics, and Excel for ISM.
Results: Fifteen influencing factors were identified in the sustainable development of rural entrepreneurship in coastal villages. Among these, individual and personality traits, marketing and commerce, and policy and legal facilitation had the highest frequency of initial codes. The ISM findings revealed that regional natural capacities and social and participatory capacities served as fundamental pillars for entrepreneurship development in coastal rural areas. These components were placed at the fifth level of the ISM model, indicating their strategic and foundational significance. Neglecting these factors could render other efforts for entrepreneurship development ineffective. Variables such as policy and legal facilitation, government support, and prevailing cultural values were identified at the fourth level. The third level included six interconnected variables: financial facilities and credits, communication and associations, the macroeconomic environment, physical infrastructure, education and extension services, and management and planning. Finally, variables such as access to technology and industries, individual and professional traits, environmental conservation, and marketing and commerce were placed at the second and first levels. The MICMAC analysis showed that most variables were in the dependent and linkage category due to their high dependence and influence in the region.
Conclusion: The results of this study indicate that the sustainable development of rural entrepreneurship in the coastal villages of Sari and Miandorud counties is strongly influenced by the natural, social, and participatory capacities of these areas. As fundamental pillars of entrepreneurial development, these factors occupy the highest level in the ISM model. Their strategic importance highlights that without the provision and enhancement of these capacities, the development of other dimensions of entrepreneurship will face serious challenges. Based on the study findings, sustainable entrepreneurial development in coastal rural areas generally requires comprehensive planning and attention to the natural and social capacities of these regions. To leverage these capacities, policymakers are recommended to focus on strengthening social and economic infrastructure, such as transportation, access to modern technologies, and the development of communication networks. On the other hand, individual and professional factors, such as the personality traits of entrepreneurs and their specialized skills, play a significant role in facilitating forces at the executive level. To achieve sustainable entrepreneurial development in these areas, it is suggested to implement programs aimed at enhancing natural and social capacities, such as environmental resource conservation and increasing social interactions. Establishing marketing cooperatives, developing marketing and management skills, improving physical and transportation infrastructure, and optimizing the use of coastal tourism capacities are among the actions that can empower rural residents and contribute to the sustainable development of these regions. Additionally, access to advanced technologies, government support policies, and regulatory facilitation can pave the way for greater utilization of local resources and sustainable economic growth.
Egypt faces extreme traffic congestion in its cities, which results in long travel times, large lines of parked cars, and increased safety hazards. Our study suggests a multi-modal approach that combines critical infrastructure improvements with cutting-edge technologies to address the ubiquitous problem of traffic congestion. Assuring vehicles owners of their timely arrival, cutting down on fuel usage, and improving communication using deep learning approach and optimization algorithm within the potential of IoT enabled 5G framework are the main goals. The traffic management system incorporates detection cameras, Raspberry Pi 3 microcontroller, an Android application, cloud connectivity, and traditional traffic lights that are powered using PV modules and batteries to secure the traffic controllers operation in case of grid outage and assure service continuity. The model examines the difficulties associated with Internet of Things (IoT) communication, highlighting possible interference from device-to-device (D2D) devices and cellular user equipment. This all-encompassing strategy aims to reduce fuel consumption, increase road safety and improve traffic efficiency. The model predicts a significant increase in Egypt's urban mobility by utilizing the possibilities of IoT and 5G technologies, which would improve Egypt's towns' livability and efficiency. The goal of this paper is to modernize Egypt's traffic management system and bring it into compliance with global guidelines for intelligent transportation networks.
Carlos Danilo Miranda Regis, Ittalo Dos Santos Silva, Pedro Ivo Arag Ao Guimaraes
et al.
Astrocytes have the ability to modulate neuronal communication by regulating various levels of ionic concentrations. The development of models for molecular communication ought to investigate the utilisation of various ionic transportation mechanisms, with the aim of enhancing performance and biocompatibility, thereby facilitating co-existence within cellular tissues. In this study, we suggest the utilisation of both Ca<inline-formula> <tex-math notation="LaTeX">$^{2+}$ </tex-math></inline-formula> and Na<inline-formula> <tex-math notation="LaTeX">$^{+}$ </tex-math></inline-formula> ions to investigate the non-linearities of propagation in cellular tissues for MC. In this study, we also investigated the impact of various ionic transport mechanisms, including the sodium-calcium exchanger, sodium-potassium pump, and calcium pump, to assess their impact on the intracellular propagation of Ca<inline-formula> <tex-math notation="LaTeX">$^{2+}$ </tex-math></inline-formula>. We analysed four communication metrics metrics, namely channel capacity, bit error rate (BER), communication gain, and signal-to-noise ratio, to evaluate the effects of the transport mechanisms on the communication channel.
REZAUL HOQUE, MD. INJA-MAMUN HAQUE, MAHMUD HASAN
et al.
In March 2020, the COVID-19 pandemic rapidly spread across Bangladesh, affecting various sectors, including aquaculture. However, there is a lack of evidence regarding the effects on aquaculture production and profitability in the country. The present study addresses this gap and investigates the impact of the COVID-19 pandemic using a convenience questionnaire survey utilising face-to-face and telephonic interviews with 499 fish farmers from five prominent fish-culture regions (Satkhira, Khulna, Madaripur, Bhola, and Mymensingh) in Bangladesh from April to August 2020. The results show aquaculture production losses averaging 29.1 % during the pandemic compared to the pre-pandemic period. Before the COVID-19 pandemic outbreak, the farmers reported a profit of USD3813 per hectare, which turned into a loss of USD2565.4 per hectare during the pandemic period. The standard multiple linear regression analysis indicated that large farms experienced a more significant impact on aquaculture production loss and economic loss during the pandemic period compared to small farms [β = 0.15, P = 0.029]. The causes for the production loss were identified by rank based quotient (RBQ), indicating that increased fish transportation costs and prices of seed and feed dominated during the lockdown. The lockdown and movement restrictions also reduced selling prices because of fewer buyers. The government provided financial support to the fish farmers, but only onethird (36 %) of the respondents received financial aid. The study suggests implementing medium and long-term measures, such as strengthening communication networks, digital marketing strategies and developing strategic planning initiatives to improve disaster management and resilience to mitigate the effects of the pandemic.
Menglikulov Bakhtiyor, Umarov Sukhrob, Safarov Alisher
et al.
In the research article, it is emphasized that the logistics information system has a high role in the world and in the economy of the Republic of Uzbekistan, in order to create effective logistics systems and speed up the process of cargo delivery, the author is asked to organize transportation and logistics information centers based in Uzbekistan on information resources in the railway sector. indicates that it occupies an important place in the practice of the main trends in the development of the transport-logistics sector of the Republic of Uzbekistan and the factors hindering the development of the local transport-logistics information system are revealed. The object of research is the transportation logistics information system of the Republic of Uzbekistan and improving its efficiency. The method of analysis, grouping, synthesis, organizational-operational model was chosen as research methods. The model proposed in the study is divided into a number of modules united by the decision of common functional tasks. With this method, it is achieved by expanding the scope of services provided, fulfilling the order on time, increasing the volume of transportation and reducing the overall operational and logistics costs. As a result of the studies, proposals were developed to increase the potential of the transport communication system of our country, to create an effective system of transport-logistics and communication services.
Christopher W. Reynolds, Madison Horton, HaEun Lee
et al.
Background: Maternal mortality continues to disproportionately affect low- and middle-income countries, including Liberia. Though the relationship between obstetric triage systems and improved maternal outcomes is well documented, standardized triage protocols are lacking in rural Liberia. Mobile health interventions are a promising method to triage obstetric patients. Objectives: This study explores the acceptability of a WhatsApp Triage, Referral, and Transfer (WAT-RT) system among Liberian midwives and community health assistants. Methods: Individual interviews and focus group discussions were conducted among midwives (n = 18) and community health assistants (n = 112). Interviews were designed to understand the current referral system in rural Liberia, how a WAT-RT System can address referral limitations, and the acceptability of the WAT-RT System. Data were audio recorded, transcribed, and translated into English. Data analysis was conducted via NVivo12 with independent and cooperative techniques among multiple researchers. Findings: The current referral system is not standardized with limitations including a lack of triage protocols, transportation difficulties, and inconsistent communication of patient information, which could be addressed by a WAT-RT System. The acceptability for the WAT-RT System was high. Facilitators to implementation included utilizing a pre-existing communication and referral infrastructure, access and competency surrounding mobile phones, and increased opportunities for training and inter-provider collaboration. Barriers included disproportionate phone access between midwives and community health assistants, network reliability, and a lack of data standards. Recommendations for successful implementation included centralizing phone financing and standardizing triage protocols. Conclusions: The WAT-RT System demonstrated high acceptability among frontline health care providers in rural Liberia. Barriers to program success could be reasonably addressed with simple interventions and planning. Multiple benefits included addressing care delays for obstetric patients, promoting bidirectional provider communication, and increasing the quality of obstetric triage. Future studies should focus on piloting the WAT-RT System among this population and recruiting other key stakeholders to determine intervention feasibility.
Infectious and parasitic diseases, Public aspects of medicine
Wireless communication is an essential element within Intelligent Transportation Systems and motivates new approaches to intersection management, allowing safer and more efficient road usage. With lives at stake, wireless protocols should be readily available and guarantee safe coordination for all involved traffic participants, even in the presence of radio failures. This work introduces STARC, a coordination primitive for safe, decentralized resource coordination. Using STARC, traffic participants can safely coordinate at intersections despite unreliable radio environments and without a central entity or infrastructure. Unlike other methods that require costly and energy-consuming platforms, STARC utilizes affordable and efficient Internet of Things devices that connect cars, bicycles, electric scooters, pedestrians, and cyclists. For communication, STARC utilizes low-power IEEE 802.15.4 radios and Synchronous Transmissions for multi-hop communication. In addition, the protocol provides distributed transaction, election, and handover mechanisms for decentralized, thus cost-efficient, deployments. While STARC’s coordination remains resource-agnostic, this work presents and evaluates STARC in a roadside scenario. Our simulations have shown that using STARC at intersections leads to safer and more efficient vehicle coordination. We found that average waiting times can be reduced by up to 50% compared to using a fixed traffic light schedule in situations with fewer than 1000 vehicles per hour. Additionally, we design platooning on top of STARC, improving scalability and outperforming static traffic lights even at traffic loads exceeding 1000 vehicles per hour.
In recent years, intelligent transportation systems and automatic train control technologies have been developed rapidly. The communication-based train control (CBTC) system through train-to-train communications is very important in the intelligent transportation system and it uses wireless communication links to transmit the train control commands. However, the CBTC system is sensitive to information security attacks. Therefore, a comprehensive resilient control strategy is proposed for the CBTC system under Denial of Service (DoS) attacks. As a cyber physical system, the CBTC system includes two layers. In the communication layer, a strongly robust train-to-train communication topology is proposed which adopts a bidirectional communication strategy and a three times communication protocol to achieve the goal of resisting multi-channel DoS attacks. In the physical layer, an observer-based distributed intrusion detection method is firstly proposed to detect the attack. Further, a resilient control method based on a distributed state observer of the leader train is proposed to avoid triggering the train safety protection mechanism frequently. Finally, simulation results prove that the proposed comprehensive resilient control algorithm is effective in the CBTC system.
Vehicular Ad Hoc Network (VANET) and Internet of Vehicle (IoV) technologies are particularly attracting attention from industrial communities because of the intelligent transportation systems of smart city technologies. Vehicle-to-vehicle (V2V) communication of VANET can guarantee traffic system management and road safety. However, V2V communication cannot manage many vehicles as a whole, so it needs to be segmented and communicated by region. Therefore, considering locality, key agreement is made for V2V communication of the same or different regions. Moreover, traditional public key infrastructure (PKI) and Kerberos systems to be applied in a real environment incur computational overhead. Therefore, we proposed a lightweight protocol for dynamic properties of vehicles for regional segmentation management and overhead resolution. In addition, because vehicle information is transmitted through public channels, our protocol uses mutual authentication and honey_list technology to ensure security against a variety of attacks. It provides verification of safety through a detailed security analysis using the formal analysis using the widely-accepted Real-Or-Random (ROR) model, and verifies formal security using the Automated Validation of Internet Security Protocols and Applications (AVISPA) software tool and non-mathematical (informal) security analysis. In addition, a detailed comparative study that the proposed scheme can be applied in the communication environment between actual vehicles as compared to other existing competing schemes.
Abstract Natural resources plays efficient contribution in the human world in the way of consuming energy resources for the daily life cycle. The main concerns rely on the transporting oil from refining to the consumer usages through different modes. In the transportation passages, its performances are calibrated in the robust manner through sensor network communication and the periodical pigging inspection on the pipeline system. This chapter enumerates about the layout of oil pipeline system and its sensor measurement and instrumentation deliberately placed on the long run pipelines. The evolution of smart grid application enhances this oil transportation in a much corporate band by accumulatively orienting the sensor network in the utilization of power resources. Further, through the wireless communication associated with the smart grid, the pigging inspection gauges are exploited in the desired geographical area with better power consumption. Existing research on communication technologies in SG is briefly overviewed with the main focus on Cloud computing approaches. In this paper, the Smart Grid architecture and its applications are focused on entire oil pipeline from inlet to distribution substations first. The Cloud Computing architecture is explained thoroughly. Then, Cloud Computing for Smart Grid applications are also introduced in terms of efficiency, security and usability. Cloud platforms technical and security protocols are analyzed. Finally, the inspection of oil pipeline system by receiving sensor data of smart pigs incorporated with the cloud computing technique associated with smart grid application is elaborated with its SCADA hierarchical architecture. Further, simulation analysis of wireless sensor nodes with Flexmeter platform for power monitoring over smart pig case scenario is also presented with its layer-wise characterization.
V2X (vehicle-to-everything) is a promote and profound reform-and-innovation in transportation and automobile industries.It is changing the people’s travel mobility modes and ways of society energy consumption.The requirements and challenges of V2X communication performance in data rate, latency, and reliability, being required and challenged by intelligent transportation and automated driving applications were analyzed.The critical technologies and international standards evolutions of cellular vehicle-to-everything (C-V2X) were introduced, including LTE-V2X and NR-V2X.Then, the advantages of applying C-V2X were analyzed for vehicle-vehicle and vehicle-infrastructure cooperation in intelligent transportation and automated driving.Meanwhile, the field testing and industrial practice of C-V2X in China were presented, and the roadmap was envisioned for developing intelligent transportation and intelligent connected vehicles (ICV) in China.For example, the envisions include actively promoting the construction of “5G+C-V2X” and new type infrastructure, exploring the development mode of vehicle-infrastructure cooperation based on V2X, and eventually supporting China to reach the national low “carbon peak” and to achieve the national “carbon neutralization” strategic goals.
Ali R. Abdellah, Ammar Muthanna, Mohamed H. Essai
et al.
Artificial intelligence (AI) is capable of addressing the complexities and difficulties of fifth-generation (5G) mobile networks and beyond. In this paradigm, it is important to predict network metrics to meet future network requirements. Vehicle-to-everything (V2X) networks are promising wireless communication methods where traffic information exchange in an intelligent transportation system (ITS) still faces challenges, such as V2X communication congestion when many vehicles suddenly appear in an area. In this paper, a deep learning algorithm (DL) based on the unidirectional long short-term memory (LSTM) model is proposed to predict traffic in V2X networks. The prediction problems are studied in different cases depending on the number of packets sent per second. The prediction accuracy is measured in terms of root-mean-square error (RMSE), mean absolute percentage error (MAPE), and processing time.
S. Parkvall, Y. Blankenship, Ricardo Blasco
et al.
Standardization of the first release of 5G New Radio has been completed in the 3rd Generation Partnership Project, and the evolution has started. On a high level, the enhancements in Release 16 can be grouped into two categories: improvements of existing features, and introduction of new features addressing new verticals and deployment scenarios. This article provides a brief overview of the enhancements in the first category, followed by a more in-depth discussion of features in the second category. These features include integrated access-backhaul, operation in unlicensed spectrum, intelligent transportation and vehicular-to-anything communication, the Industrial Internet of Things, ultra-reliable low-la-tency communication, and positioning. The article concludes with an outlook on enhancements planned for Release 17.