Search Results (104)

A graph’s minimum cycle basis is defined as the smallest collection of cycles that exhibit linear independence in the cycle space, serving as fundamental building blocks for constructing any cyclic structure within the graph. These bases are useful in various contexts, including the intricate analysis of electrical networks, structural engineering endeavors, chemical processes, and surface reconstruction techniques, etc. This study investigates the urban road networks of six Chinese cities to analyze their topological features, node centrality, and robustness (resilience to traffic disruptions) using motif analysis and minimum cycle bases methodologies. Some interesting conclusions are obtained: the frequency of motifs containing cycles exceeds that of random networks with equivalent degree sequences; the frequency distribution of minimum cycle lengths and surface areas obeys the power-law distribution. The cycle contribution rate is introduced to investigate the centrality of nodes within road networks, and has a significant impact on the total number of cycles in the robustness analysis. Finally, we construct two types of cycle-based dual networks for urban road networks by representing cycles as nodes and establishing edges between two cycles sharing a common node and edge, respectively. The results show that cycle-based dual networks exhibit small-world and scale-free properties. The research facilitates a comprehensive understanding of the cycle structure characteristics in urban road networks, thereby providing a theoretical foundation for both subsequent modeling endeavors of transportation networks and optimization strategies for existing road infrastructure. Full article

The sea–rail intermodal container terminal serves as a key transportation hub for green logistics, where efficient resource coordination directly enhances multimodal connectivity and operational synergy. To address limited storage capacity and trans-shipment inefficiencies, this study innovatively proposes a resource-sharing strategy between the seaport and the railway container terminal, focusing on the joint allocation of yard space and internal trucks. For indirect trans-shipment operations between ships, the port, the railway container terminal, and trains, a mixed-integer programming model is formulated with the objective of minimizing the container trans-shipment cost and the weighted turnaround time of ships and trains. This model simultaneously determines yard allocation, container transfers, and truck allocation. A two-layer hybrid heuristic algorithm incorporating adaptive Particle Swarm Optimization and Greedy Rules is designed. Numerical experiments verify the model and algorithm performance, revealing that the proposed method achieves an optimality gap of only 1.82% compared to CPLEX in small-scale instances while outperforming benchmark algorithms in solution quality. And the shared yard strategy enhances ship and train turnaround efficiency by an average of 33.45% over traditional storage form. Sensitivity analysis considering multiple realistic factors further confirms the robustness and generalizability. This study provides a theoretical foundation for sustainable port–railway collaboration development. Full article

Container shipping networks are vulnerable to cascading failures due to seaport disruptions, underscoring the need for resilient multimodal transport systems. This study proposes a cascading failure model for the seaport–dry-port network in container transport, incorporating a multi-stage load redistribution strategy (CM-SDNCT-MLRS) to enhance network resilience. Extending the Motter–Lai framework, the model introduces multiple port state transitions and accounts for uncertainties in load redistribution, tailoring it to the cascading failure dynamics of SDNCT. Using empirical data from China’s coastal port system, the proposed MLRS dynamically reallocates loads through dry-port buffering, neighboring seaport sharing, and port skipping. This strategy effectively contains cascading failures, mitigates network efficiency losses, and protects major seaports while reducing mutual disruptions. Resilience analysis demonstrates that the network exhibits scale-free properties, with its resilience being highly sensitive to random port failures and critical port vulnerabilities. The experimental results highlight the pivotal role of dry ports, where operational numbers influence resilience more significantly than capacity. In addition, the study identifies the optimal port-skipping probability that mitigates cascading disruptions. These findings provide valuable insights for port management and logistics planning, contributing to the development of more resilient container transport networks. Full article

The L-space and P-space are two essential representations for studying complex networks that contain different clusters. Existing network models can successfully generate networks in L-space, but generating networks in P-space poses significant challenges. In this study, we present an empirical analysis of the distribution of the number of a line’s nodes and the properties of the networks generated by these data in P-space. To gain insights into the operational mechanisms of the network of these data, we propose an event–link model that incorporates new nodes and links in P-space based on actual data characteristics using real data from marine and public transportation networks. The entire network consists of a series of events that consist of many nodes, and all nodes in an event are connected in the P-space. We conduct simulation experiments to explore the model’s topological features under different parameter conditions, demonstrating that the simulation outcomes are consistent with the theoretical analysis of the model. This model exhibits small-world characteristics, scale-free behavior, and a high clustering coefficient. The event–link model, with its adjustable parameters, effectively generates networks with stable structures that closely resemble the statistical characteristics of real-world networks that share similar growth mechanisms. Moreover, the network’s growth and evolution can be flexibly adjusted by modifying the model parameters. Full article

Osmanthus fragrans is a highly valued ornamental tree species in China, but its short flowering period limits its ornamental appeal. Investigating the mechanisms of flower senescence in O. fragrans is therefore of significant importance. Ethylene, a key endogenous hormone, plays a central role in flower senescence, and the AP2/ERF gene family, which includes ethylene response factors, is known to regulate this process in various plants. Transcriptome sequencing and expression analysis identified OfERF17 as a critical gene influencing petal senescence in O. fragrans. Bioinformatics analysis revealed that OfERF17 lacks transmembrane transport structures but contains multiple phosphorylation sites and shares a close phylogenetic relationship with the Olea europaea var. Sylvestris. Subcellular targeting and yeast-based auto-activation tests revealed that OfERF17 resides in the nucleus and possesses a transcriptional self-activation capability. Transient expression studies conducted in O. fragrans petals indicated a decrease in the expressions of two genes associated with senescence, namely, OfSAG21 and OfACO3, when compared to the control group. Additionally, the levels of hydrogen peroxide (H₂O₂) and malondialdehyde (MDA) were markedly reduced. Transgenic Nicotiana tabacum blooms one day more than the wild type, and NtSAG12 and NtACO1 expressions were lower than wild type. These results suggest that OfERF17 functions to delay petal senescence in O. fragrans. This study enhances our knowledge of the molecular mechanisms underlying O. fragrans petal senescence and provides insights into strategies for prolonging its flowering period. Full article

Increasing the share of circulating scrap in produced castings is not only due to optimizing production costs, but also the need to protect the environment realized by reducing production energy intensity, generating less waste, mitigating greenhouse gas emissions, and consuming fewer natural resources. However, this is associated with maintaining the required properties of castings and considering the impact of impurities on the formation of the structure of aluminum alloys. This research concerns the AlSi10MnMg alloy, which introduces 50 to 75% (every 5%) of circulating scrap. This alloy is one of the most commonly used for producing gravity and pressure die-castings (HPDC), including engine parts and transport structural elements. Based on microscopic research, it was found that the increase in scrap content causes an increase in the share of iron, which results in pre-eutectic (from about 0.45 wt.% to 0.7 wt.% Fe) or even primary crystallization of iron phases (over 0.7 wt.% Fe), mainly the plate–needle phase β-Al₅FeSi. Its unfavorable morphology and size cause the formation of numerous shrinkage porosity areas, which has an impact on the reduction in mechanical properties (reduction in UTS and YS by approx. 16% and elongation by approx. 18%, compared to the AlSi10MnMg alloy with 50% scrap content). It was found that the increase in the share of recycled scrap (from 50 to 75%) can be used only when the manganese content is increased. Its effect is to change the morphology of the β-Al₅FeSi phase into α-Al₁₅(Fe,Mn)₃Si₂, whose crystallization occurs in the temperature range of 540 to 555 °C and increases slightly with increasing manganese addition. It is essential to consider the appropriate value of the Mn/Fe quotient, which should be about 1/2, because a higher value may cause the formation of a sludge factor. This work aimed to determine the limiting iron content (contained in the scrap) at which the sequence of the β-Al₅FeSi phase release (pre-eutectic or primary crystallization) changes. This sequence mainly affects the form of morphology, the dimensions of the β-Fe phase, and the proportion of shrinkage porosity. Full article

Intelligent Transport Systems (ITSs) are essential for secure and privacy-preserving communications in Autonomous Vehicles (AVs) and enhance facilities like connectivity and roadside assistance. Earlier research models used for traffic management compromised user privacy and exposed sensitive data to potential adversaries while handling real-time data from numerous vehicles. This research introduces a Federated Learning-based Predictive Traffic Management (FLPTM) system designed to optimize service access and privacy for Autonomous Vehicles (AVs) within an ITS. Moreover, a CPPS will provide strong security to mitigate adversarial threats through state modelling and authenticated access permissions for the integrity of vehicle communication networks from man-in-the-middle attacks. The suggested FLPTM system utilizes a Contained Privacy-Preserving Scheme (CPPS) that decentralizes data processing and allows vehicles to train local models without sharing raw data. The CPPS framework combines a classifier-based learning technique with state modelling and access permissions to protect user data against invasions and man-in-the-middle attacks. The proposed model leverages Federated Learning (FL) to enhance data security in collaborative machine learning processes by allowing updates that preserve privacy, enabling joint learning without exposing raw data. It addresses key challenges such as high communication costs, the impact of adversarial attacks, and access time inefficiencies. Using FL, the model reduces communication costs by 23.29%, mitigates adversarial effects by 16.1%, and improves access time by 18.95%, achieving significant cost savings and maintaining data privacy throughout the learning process. Full article

The RED II Directive requires European Union member states to increase the share of renewable energy in the transport sector to at least 14% by 2030. In January 2024, Poland replaced E5 gasoline (95 octane) with E10, which contains up to 10% bioethanol derived from second-generation sources such as agricultural residues. The transition to E10 raises concerns about the ability of engine management systems to adapt to its different air–fuel ratio (AFR) requirements. The AFR for E10 (13.82) is 1.98% lower than for E5 (14.25) and 3.88% lower than for pure gasoline (14.7). Research conducted on a spark-ignition engine (with AFR regulation) using an exhaust gas analyzer demonstrated that during the combustion of E5 and E10 fuels with correctly adjusted AFR and operation at λ = 1, the use of E10 potentially increases CO₂ and NO_x emissions despite reductions in CO and HC. However, when calibrated for E5 and operated with E10 fuel, an increase in CO₂ and HC concentrations in the exhaust gases is observed, along with a reduction in CO and NO_x. This phenomenon is attributed to operation with lean mixtures, at λ = 1.02. This study investigates both the theoretical and experimental impact of this fuel transition. Fuel systems typically adjust engine operation based on exhaust gas analysis but cannot recognize fuel type, leading to incorrect λ values when the AFR differs from the ECU’s programming. Effective adaptation would require additional fuel composition sensors and editable ECU mappings. For older vehicles or small non-road engines, manual adjustments to injection or carburetor systems may be necessary. Full article

The logistics and transportation sectors are struggling to manage empty containers (ECs), resulting in unused resources, inefficiencies, and increased CO₂ emissions. The Physical Internet (PI) concept provides an opportunity to improve container sharing and transportation by intelligently organising logistics resources. This paper shows how PI principles can address the EC problem in truck transportation. The objective is to reduce CO₂ emissions with improved space-sharing strategies. The problem is formulated and solved using a two-stage optimisation approach (2Stage-Opt) to optimise container motion. The validity of the 2Stage-Opt solutions is tested using a developed multi-agent system simulation (MASS) model to replicate the behaviour of real multi-modal hubs. This approach is evaluated using a real-world case study from a multi-modal logistics centre in the north of France. The results indicate that utilising PI-container solutions offers significant sustainability benefits, especially in reducing the number of trucks used in the simulation and the CO₂ emissions from ECs. Full article

Renewable Energy Sources (RESs) are characterized by high unevenness, cyclicality, and seasonality of energy production. Due to the trends in the production of electricity itself and the utilization of hydrogen, distributed generation systems are preferred. They can be connected to the energy distribution network or operate without its participation (off-grid). However, in both cases, such distributed energy sources should be balanced in terms of power generation. According to the authors, it is worth combining different RESs to ensure the stability of energy production from such a mix. Within the mix, the sources can complement and replace each other. According to the authors, an effective system for generating energy from RESs should contain at least two different sources and energy storage. The purpose of the analyses and calculations performed is to determine the characteristics of energy generation from a photovoltaic system and a wind turbine with a specific power and geographical location in the Lublin region in Poland. Another important goal is to determine the substitutability of the sources studied. Probabilistic analysis will be used to determine the share of given energy sources in the energy mix and will allow us to estimate the size of the stationary energy storage. The objective of these procedures is to strive for the highest possible share of renewable energy in the total energy required to charge electric vehicle fleets and to produce low-emission hydrogen for transportation. The article proves that the appropriately selected components of the photovoltaic and wind energy mix located in the right place lead to the self-balancing of the local energy network using a small energy storage. The conclusions drawn from the conducted research can be used by RES developers who intend to invest in new sources of power generation to produce low-emission hydrogen. This is in line with the current policy of the European Union aimed at climate and energy transformation of many companies using green hydrogen. Full article

Spatial data play a critical role in various domains such as cadastre, environment, navigation, and transportation. Therefore, ensuring the quality of geospatial data is essential to obtain reliable results and make accurate decisions. Typically, data are generated by institutions according to specifications including application schemas and can be shared through the National Spatial Data Infrastructure. The compliance of the produced data to the specifications must be assessed by institutions. Quality assessment is typically performed manually by domain experts or with proprietary software. The lack of a standards-based method for institutions to evaluate data quality leads to software dependency and hinders interoperability. The diversity in application domains makes an interoperable, reusable, extensible, and web-based quality assessment method necessary for institutions. Current solutions do not offer such a method to institutions. This results in high costs, including labor, time, and software expenses. This paper presents a novel framework that employs an ontology-based approach to overcome these drawbacks. The framework is primarily based on two types of ontologies and comprises several components. The ontology development component is responsible for formalizing rules for specifications by using a GUI. The ontology mapping component incorporates a Specification Ontology containing domain-specific concepts and a Spatial Data Quality Ontology with generic quality concepts including rules equipped with Semantic Web Rule Language. These rules are not included in the existing data quality ontologies. This integration completes the framework, allowing the quality assessment component to effectively identify inconsistent data. Domain experts can create Specification Ontologies through the GUI, and the framework assesses spatial data against the Spatial Data Quality Ontology, generating quality reports and classifying errors. The framework was tested on a 1/1000-scale base map of a province and effectively identified inconsistencies. Full article

Single crystals of the new modification of copper pyrovanadate, δ-Cu₂V₂O₇, were prepared using the chemical vapor transport reaction method. The crystal structure (monoclinic, P2₁/n, a = 5.0679(3), b = 11.4222(7), c = 9.4462(6) Å, β = 97.100(6)°, V = 542.61(6) ų, Z = 4) was solved by direct methods and refined to R₁ = 0.029 for 1818 independent observed reflections. The crystal structure contains two Cu sites: the Cu1 site in [4 + 2]-octahedral coordination and the Cu2 site in [4 + 1]-tetragonal pyramidal coordination. There are two V⁵⁺ sites, both tetrahedrally coordinated by O atoms. Two adjacent V1O₄ and V2O₄ tetrahedra share the O4 atom to form a V₂O₇ dimer. The crystal structure of δ-Cu₂V₂O₇ can be described as based upon layers of V₂O₇ dimers of tetrahedra parallel to the (001) plane and interlined by chains of the edge-sharing Cu1O₆ and Cu2O₅ polyhedra running parallel to the a axis and arranged in the layers parallel to the (001) plane. The crystal chemical analysis of the three other known Cu₂V₂O₇ polymorphs indicates that, by analogy with δ-Cu₂V₂O₇, they are based upon layers of V₂O₇ groups interlinked by layers consisting of chains of CuO_n coordination polyhedra (n = 5, 6). The crystal structures of the Cu₂V₂O₇ polymorphs can be classified according to the mutual relations between the Cu-O chains, on the one hand, and the V₂O₇ groups, on the other hand. The analysis of the literature data and physical density values suggests that, at ambient pressure, α- and β-Cu₂V₂O₇ are the low- and high-temperature polymorphs, respectively, with the phase transition point at 706–710 °C. The β-phase (ziesite) may form metastably under temperatures below 560 °C and, under heating, transform into the stable α-phase (blossite) at 605 °C. The δ- and γ-polymorphs have the highest densities and most probably are the high-pressure phases. The structural complexity relations among the polymorphs correspond to the sequence α = β < γ < δ; i.e., the δ phase described herein possesses the highest complexity, which supports the hypothesis about its stability under high-pressure conditions. Full article

Numerous insects are attracted to low levels of ammonia, utilizing it as a cue to locate food sources. The Ammonium Transporter (Amt), a highly conserved, atypical olfactory receptor, has been shown to mediate the detection of ammonia in insects. While the attraction of Tephritidae to ammonia is well established, knowledge about the Amt in this family is limited. The species Bactrocera dorsalis (Hendel 1912), Bactrocera cucurbitae (Coquillett 1899), Bactrocera correcta Bezzi 1916 and Bactrocera tau (Walker 1849), which are common agricultural pests within Tephritidae, exhibit numerous ecological similarities, offering a solid foundation for studying Amt characteristics in this family. In this study, we elucidated the sequences, evolutionary relationships, and expression patterns of Amt in these four species. The results indicated that these Amts share the same open reading frame, containing 1770 bp that encode a protein of 589 amino acid residues. These Amt proteins exhibit the typical structural characteristics of Amts, including an 11-transmembrane domain with an extracellular N-terminus and an intracellular C-terminus. They also have the ability to form trimers in the membrane. Additionally, they contain three conserved amino acid residues essential for ammonia transport: A189, H195, and H352. Phylogenetic and expression pattern analyses showed that they are highly conserved in Diptera and are significantly expressed in antennae. This study is the first report characterizing the Amt gene in four Tephritidae species. These findings provide a foundation for further exploration into the roles of these genes in their particular biological contexts. Full article

Polyhalogenated carbazoles (PHCZs) are a class of nitrogen-containing heterocyclic compounds that are widely distributed throughout the marine environment and sediment. These compounds share structural and toxicity similarities with dioxins. However, our understanding of the toxicological effects of PHCZs on marine organisms and their underlying molecular mechanisms remains limited. In this study, we employed the marine model organism Mugilogobius chulae as the experimental subject and selected 2,7-dibromocarbazole (2,7-DBCZ), a compound known for its high toxicity and detection frequency, to conduct both an acute toxicity test and transcriptome analysis on M. chulae embryos. Our findings revealed that the 96 h median lethal concentration (LC₅₀) of 2,7-DBCZ for M. chulae embryos was 174 μg/L, with a median effective concentration (EC₅₀) resulting in pericardial edema deformity of 88.82 μg/L. Transcriptome analysis revealed significant impacts on various systems in M. chulae embryos following exposure to 2,7-DBCZ, including the sensory, cardiovascular, immune, and endocrine systems. Furthermore, this compound perturbed signaling pathways such as phototransduction, protein folding and processing, amino acid metabolism, lipid transport, and exogenous compound metabolism. Notably, transcript abundance of the CYP1A gene associated with the activation of the AhR signaling pathway, similar to dioxin-like compounds, was 18.18 times higher than that in the control group. This observation suggests that M. chulae embryos mount a stress response when exposed to PHCZs. In summary, this study contributes to our understanding of the toxicological implications of PHCZ in marine fish and offers a theoretical foundation for risk assessment and regulatory frameworks for PHCZs in the marine environment. Full article

The assembly building M&E (Monitoring and Evaluation) system is a vital part of the transformation of China’s construction industry, featuring intelligent control, high efficiency, and high safety. The article provides a comprehensive review of research related to assembly M&E systems from the perspective of the whole life cycle of assembly, containing 125 journal articles from 1993 to 2024. The article analyzes some policies with updated iterations in the United States, Japan, Germany, Denmark, France, and the European Union. The literature review and semi-structured interviews with experts identified significant constraints limiting the various stages of the entire life cycle of assembled MEP (mechanical, electrical, and plumbing) systems. The absence of uniform design standards, personnel collaboration, prefabricated component testing, transportation, information utilization, intelligent testing, and recycling of disassemblability that can occur in the entire life cycle of assembled MEP systems are summarized. Finally, the article suggests that assembly M&E systems can be shared and marketed to improve the economic viability of assembly M&E systems and their wide application in the areas of technology, platform, and demand. Full article