Traditional Routing Research Articles

Development of Highway Construction Route Selection Based on Ecological Sensitivity Evaluation and Intervention Optimization Strategy Research

Ecological sensitivity is an essential indicator for measuring the degree of ecological fragility of a region, and traditional highway routing ignores the ecological benefits of regional nature, which causes irreversible impacts on the natural environment. Based on the AHP method, this paper carries out a comprehensive assessment of the ecological sensitivity of the K0+000~K56+438 section of the Guanzhuang Tourist Highway in the Zhangjiajie Wuling Mountain Area from 2000 to 2020, and it utilizes the spatial autocorrelation analysis method to reveal the pattern of its spatial and temporal changes in ecological sensitivity. The following results were obtained. (1) The ecological condition of the study area is gradually improving, and the areas with higher sensitivity are mainly distributed in the northeast and southwest of the study area. (2) The ecological sensitivity of the study area has strong spatial autocorrelation, but the autocorrelation has been reduced in recent years, and the distribution of the ecological sensitivity has been gradually discretized. (3) There are problems of high ecological risk and construction difficulty in the traditional highway route selection scheme of the A line. The optimized route selection scheme, the K line, can effectively avoid highly sensitive areas by adjusting the route and bridge settings. Finally, the article proposes engineering construction suitability and ecological restoration strategies for different road sections regarding vegetation cover, landscape risk, and geological hazards. This study establishes a set of comprehensive technical chains for tourism highway routing in ecologically fragile areas based on the spatial and temporal evolution of sensitivity, which provides new ideas for traditional highway routing and is of great significance for maintaining the balance and stability of ecosystems within the road area.

Robust and energy-efficient RPL optimization algorithm with scalable deep reinforcement learning for IIoT

The increasing complexity and quantity of the Industrial Internet of Things (IIoT) pose new challenges to the traditional routing protocol for low-power and lossy networks (RPL) in terms of dynamic management, data transmission reliability, and energy efficiency optimization. This paper proposes a scalable deep reinforcement learning (DRL) algorithm with a multi-attention actor double critic model for routing optimization (MADC) to meet the requirements of IIoT for efficient and intelligent routing decisions while improving data transmission reliability and energy efficiency. Specifically, MADC employs the centralized training and decentralized execution (CTDE) learning paradigm to decouple the model’s training and inference tasks, which reduces the difficulty and computational cost of model learning and improves the training efficiency. In addition, a lightweight actor network based on multi-scale convolutional attention mechanism is designed in MADC, which can provide intelligent and real-time decision-making capabilities for resource-constrained nodes with low computational and storage complexities. Moreover, a scalable critic network utilizing multiple attention mechanisms is proposed. It is not only suitable for dynamic and changing network environments but also can more comprehensively and accurately evaluate local observation states, providing more accurate and efficient guidance for model optimization. Furthermore, MADC incorporates a double critic network architecture to mitigate potential overestimation issues during training, thereby ensuring the model’s robustness and reliability. Simulation results demonstrate that MADC outperforms existing RPL optimization algorithms in terms of energy efficiency, data transmission reliability, and adaptability.

Closing gaps in emergency care

Abstract: Current socio, political, and economic events may disproportionately affect those who are identified as vulnerable, as well as their presentation to Canadian emergency departments. The housing crisis, food instability, and concurrent issues with mental health and addictions are a harsh reality for many of these individuals. The emergency department may not be suited to complex health and social issues, but it provides an essential safety net for the vulnerable who cannot access care through traditional primary care routes. Alternative, patient-centered solutions to the problem are necessary, and advanced practice nurses can be the key to appropriately organizing and delivering integrated care innovative models. Raising awareness and influencing public policy to drive meaningful social change and address alarming health inequities is an important consideration for nurses working in emergency departments.

Syntheses of Tungsten Imido Cyclohexylidene Complexes Using Perfluoro-t-Butanol or Hexafluoro-t-Butanol as Acids.

The fluorinated alcohols, (CF3)3COH (RF9OH) and (CF3)2MeCOH (RF6OH), react with W(NR)2Cy2 (Cy=Cyclohexyl; R=2,6-diisopropylphenyl or 1-adamantyl) in C6D6 at 55 °C to give cyclohexylidene complexes. Traditional routes to terminal alkylidene complexes (neopentylidene or neophylidene) have used either triflic acid or HCl (rarely), but relatively weak fluorinated acids are sufficient and active bisalkoxide catalysts are therefore prepared directly. An α hydrogen abstraction reaction to give a cyclohexylidene complex from a biscyclohexyl complex appears to be as facile as α hydrogen abstraction to give a neopentylidene or neophylidene ligand, but isomerization of a cyclohexene formed through β hydrogen abstraction is also a possibility. The ORF9 ligands can be replaced readily with dimethylpyrrolide (Me2Pyr) or other more basic alkoxides. Single crystal X-ray studies were carried out on W(NAr)2Cy2, W(NAr)(ORF9)2(C6H10)(ArNH2), W(NAr)(ORF6)2(C6H10)(ArNH2), W(NAd)(ORF9)2(C6H10)(AdNH2), W(NAr)(O-i-PrF6)3Cy, and W(NAd)(η1-Me2Pyr)2(C6H10) (C6H10=cyclohexylidene).

Implementation of A Delay-Tolerant Routing Protocol in the Network Simulator NS-3

The paper explores the implementation of the Epidemic Routing Protocol using the NS-3 simulator, focusing on its application in intermittently connected networks like Mobile Adhoc Networks (MANETs). The Epidemic Protocol maximizes message delivery by flooding the network with multiple copies, ensuring reliability even in sparse or highly mobile environments. Through NS-3 simulations, the study examines the protocol’s performance, considering factors such as network size, node mobility, and message Time-To-Live (TTL). The simulation, which models an ad-hoc wireless network using IEEE 802.11b, demonstrates that the protocol achieves a 100-percentage packet delivery ratio with minimal latency. Tools like NetAnim provide detailed insights into node interactions and message dissemination, highlighting the protocol’s effectiveness in maintaining communication under challenging conditions. The paper concludes that while the Epidemic Protocol is resource- intensive, it is highly effective for scenarios where traditional routing methods fail, offering a reliable solution for dynamic and partitioned network.

User Preference Maps: Quantifying the Built Environment

The built environment in which we live holds the potential to provide life experiences that allow pedestrians to observe, feel, learn, and grow through their surroundings in everyday urban spaces. If a city offers opportunities for careful observation and exploration according to users’ preferences, it will become more appealing to many people. This study selected Midtown, New York, as the research site and collected a total of seven datasets based on 30 intersections in the area. The data, categorized into three main areas—activity, comfort, and natural elements—were evaluated, visualized, and restructured using a path exploration algorithm to produce a final user-based map. For this, 3D modeling software Rhino version 7, visual programming tool Grasshopper, and Grasshopper verion 2023 plugin programs were used. The final result included 3D route information, quantitative measurement data, and multidimensional visual materials. This approach presents an alternative to traditional route navigation based on uniform criteria and, through data-driven design, is believed to ultimately enhance walkability, activate urban spaces, and contribute to the development of sustainable cities. The scope of related research can further expand as the targets, duration, and methods of data collection continue to evolve and as case studies in various cities increase.

DFRDRL: a dynamic fuzzy routing algorithm based on deep reinforcement learning with guaranteed latency and bandwidth for software-defined networks

Traditional routing algorithms have several limitations that become increasingly significant in the context of Software-Defined Networking (SDN). Firstly, these algorithms often have limited support for Quality of Service (QoS) requirements, making them less suitable for handling diverse traffic types efficiently. Moreover, current SDN controllers leverage a default shortest-path routing approach, which does not allow for more dynamic and flexible traffic management based on real-time network policies. To address these issues, this paper introduces a Dynamic Fuzzy Routing algorithm based on Deep Reinforcement Learning (DRL) for SDN that provides guaranteed latency and bandwidth (DFRDRL). DFRDRL provides intelligent and efficient routing that adapts to dynamic traffic by considering path-state criteria and using DRL. Fuzzy logic mainly performs online routing between an ingress-egress pair. To adapt to dynamic traffic changes, DFRDRL can predict the traffic matrix in real time. Meanwhile, DFRDRL reduces the routing reliance on network topology by weighting the network based on critical nodes. Additionally, when the network experiences congestion based on the traffic matrix, a deferral mechanism is applied to prioritize requests with lower resource demands. This mechanism helps ensure efficient resource allocation by temporarily postponing or queuing higher-demand requests, thereby optimizing overall network performance during periods of congestion. The simulation results show that the performance of DFRDRL is better than the equivalent algorithms in terms of latency and throughput. Also, DFRDRL is about 2.5% more efficient than the best existing algorithm in terms of admission rate of routing requests.

Photocatalytic Semi-Hydrogenation of Acetylene to Polymer-Grade Ethylene with Molecular and Metal-Organic Framework Cobaloximes.

The semi-hydrogenation of acetylene in ethylene-rich gas streams is a high-priority industrial chemical reaction for producing polymer-grade ethylene. Traditional thermocatalytic routes for acetylene reduction to ethylene, despite progress, still require high temperatures and high H2 consumption, possess relatively low selectivity, and use a noble metal catalyst. Light-powered strategies are starting to emerge, given that they have the potential to use directly the abundant and sustainable solar irradiation, but are ineffective. Here an efficient, >99.9% selective, visible-light powered, catalytic conversion of acetylene to ethylene is reported. The catalyst is a homogeneous molecular cobaloxime that operates in tandem with a photosensitizer at room temperature and bypasses the use of non-environmentally friendly and flammable H2 gas feed. The reaction proceeds through a cobalt-hydride intermediate with ≈100% conversion of acetylene under competitive (ethylene co-feed) conditions after only 50 min, and with no evolution of H2 or over-hydrogenation to ethane. The cobaloxime is further incorporated as a linker in a metal-organic framework; the result is a heterogeneous catalyst for the conversion of acetylene under competitive (ethylene co-feed) conditions that can be recycled up to six times and remains catalytically active for 48 h, before significant loss of performance is observed.

Iontophoresis and electroporation-assisted microneedles: advancements and therapeutic potentials in transdermal drug delivery.

Transdermal drug delivery (TDD) using electrically assisted microneedle (MN) systems has emerged as a promising alternative to traditional drug administration routes. This review explores recent advancements in this technology across various therapeutic applications. Integrating iontophoresis (IP) and electroporation (EP) with MN technology has shown significant potential in improving treatment outcomes for various conditions. Studies demonstrate their effectiveness in enhancing vaccine and DNA delivery, improving diabetes management, and increasing efficacy in dermatological applications. The technology has also exhibited promise in delivering nonsteroidal anti-inflammatory drugs (NSAIDs), treating multiple sclerosis, and advancing obesity and cancer therapy. These systems offer improved drug permeation, targeted delivery, and enhanced therapeutic effects. While challenges remain, including safety concerns and technological limitations, ongoing research focuses on optimizing these systems for broader clinical applications. The future of electrically assisted MN technologies in TDD appears promising, with potential advancements in personalized medicine, smart monitoring systems, and expanded therapeutic applications.

A USUCAPIÃO EXTRAJUDICIAL NO ORDENAMENTO JURÍDICO BRASILEIRO: ALTERNATIVA PARA SOLUÇÃO DE LITÍGIOS

This paper refers to scientific production that has as its theme extrajudicial usucaption and specifically addresses extrajudicial usucaption in light of the Brazilian legal system. Its main objective is to study extrajudicial usucaption as a form of original acquisition of real estate. Its objective is to demonstrate the dejudicialization of the process and, consequently, provide protection, relieving the burden on Brazilian courts, allowing the process to be expedited, which is much more effective than the judicial one, when analyzing the time factor. It is correct to state that extrajudicial usucaption has a greater advantage because it is permeated by less bureaucracy and it is possible to do it without the traditional route, which is the judicial one and, therefore, based on the reduction of bureaucracy, through the registration of real estate. The extrajudiciality process emerges in the Brazilian legal scenario as an alternative to resolve part of the delay in the Judiciary, existing due to the large number of lawsuits. Therefore, the use of the extrajudicial option gives the Judiciary conditions to deal with the issues that effectively justify its action. The general objective of this study is to identify the function of extrajudicial usucaption in Brazil and its socioeconomic impacts. The methodology used was a qualitative bibliographic review, using a deductive method, with a monographic approach and exploratory research.

Energy-Saving Multi-Agent Deep Reinforcement Learning Algorithm for Drone Routing Problem.

With the rapid advancement of drone technology, the efficient distribution of drones has garnered significant attention. Central to this discourse is the energy consumption of drones, a critical metric for assessing energy-efficient distribution strategies. Accordingly, this study delves into the energy consumption factors affecting drone distribution. A primary challenge in drone distribution lies in devising optimal, energy-efficient routes for drones. However, traditional routing algorithms, predominantly heuristic-based, exhibit certain limitations. These algorithms often rely on heuristic rules and expert knowledge, which can constrain their ability to escape local optima. Motivated by these shortcomings, we propose a novel multi-agent deep reinforcement learning algorithm that integrates a drone energy consumption model, namely EMADRL. The EMADRL algorithm first formulates the drone routing problem within a multi-agent reinforcement learning framework. It subsequently designs a strategy network model comprising multiple agent networks, tailored to address the node adjacency and masking complexities typical of multi-depot vehicle routing problem. Training utilizes strategy gradient algorithms and attention mechanisms. Furthermore, local and sampling search strategies are introduced to enhance solution quality. Extensive experimentation demonstrates that EMADRL consistently achieves high-quality solutions swiftly. A comparative analysis against contemporary algorithms reveals EMADRL's superior energy efficiency, with average energy savings of 5.96% and maximum savings reaching 12.45%. Thus, this approach offers a promising new avenue for optimizing energy consumption in last-mile distribution scenarios.

A competent CCHFMO with AMDH for QoS improvisation and efficient route protection in MANET

SummaryThe ability of mobile ad hoc networks (MANET) to be used as communication tools in a variety of industries, including healthcare, the military, smart traffic, and smart cities, has drawn special consideration. Traditional Manet's multicast routing methods seem to be inappropriate to massive with Adaptive systems because the problem is NP‐complete, resulting in an enchanting QoS restrictions. In order to conquer that the paper proficiently introduces the Conglomerate Crumb Horde Formicary Meta‐Heuristic (CCHFMO) with Asymmetrical Meander Diffie‐Hellman (AMDH) to tackle the major obstacles are multicast routing problems and lack of data protection. Initially, the fusion of crumb horde optimization (CHO) and formicary optimization (FO) is exploited to strengthen QoS limitations and reduce QoS data loss. However, the massive and dynamic nature of the network with the combination of more QoS restrictions, deficient security has become extremely difficult. Therefore, the research work establishes the asymmetrical meander Diffie‐Hellman (AMDH) to significantly improve performance and concealment while ensuring channel security during data transfer. Finally, the results demonstrated that by employing the novel optimization approaches, the MANET can increase data protection while still achieving high transmission rates and sophistication of communication. As a consequence, it adequately explicates the article to improve QoS performances.

Traffic Engineering with Specified Quality of Service Parameters in Software-defined Networks

A method of traffic engineering (TE) based on the method of multi-path routing is proposed in the study. Today, one of the main challenges in networking is to organize an efficient TE system that will provide such parameters of quality of service (QoS) as the allowable value of packet loss and time for traffic re-routing. Traditional one-way routing facilities do not provide the required quality of service (QoS) parameters for TE. Modern computer networks use static and dynamic routing algorithms, which are characterized by big time complexity and a large amount of service information. This negatively affects the overall state of the network, namely: leads to network congestion, device failure, loss of information during routing and increases the time for traffic re-routing. Research has shown that the most promising way to solve the TE problem in computer networks is a comprehensive approach, which consists of multi-path routing, SDN technology and monitoring of the overall situation of the network. This paper proposes a method of traffic engineering in a software-defined network with specified quality of service parameters, which has reduced the time of traffic re-routing and the percentage of packet loss due to the combination of the centralized TE method and multi-path routing. From a practical point of view, the obtained method, will improve the quality of service in computer networks in comparison with the known method of traffic construction.

Quality of Service and Congestion Control in Software-Defined Networking Using Policy-Based Routing

Managing queuing delays is crucial for maintaining Quality of Service (QoS) in real-time media communications. Customizing traditional routing protocols to meet specific QoS requirements—particularly in terms of minimizing delay and jitter for real-time media—can be both complex and time-intensive. Furthermore, these protocols often encounter challenges when adapted for vendor-specific hardware implementations. To address these issues, this paper leverages the programmable features of Software-Defined Networking (SDN) to simplify the process of achieving user-defined QoS, bypassing the limitations of traditional routing protocols. In this work, we propose a policy-based routing module that integrates with traditional routing protocols to ensure QoS for real-time media flows. QoS is achieved by rerouting the flow along a new low-latency path calculated by the proposed module when the queuing delay exceeds a certain threshold. The experimental results demonstrate that the proposed solution significantly enhances the performance of traditional routing protocols within an SDN framework, effectively reducing the average end-to-end delay by 80% and total packet loss by 73%, while also improving jitter and alleviating network congestion.

Conversion of Nitrate to Ammonia by Amidinothiourea-Coordinated Metal Molecular Electrocatalysts with d-π Conjugation.

The electrochemical reduction of nitrate to ammonia (NO3RR) provides a desired alternative of the traditional Haber-Bosch route for ammonia production, igniting a research boom in the development of electrocatalysts with high activity. Among them, molecular electrocatalysts hold considerable promise for the NO3RR, suppressing the competing hydrogen evolution reaction. However, the complicated synthesis procedure, usage of environmentally unfriendly organic solvents, and poor stability of Cu-based molecular electrocatalysts greatly limit their employment in NO3RR, and the development of desired Cu-based molecular catalysts remains challenging. Herein, a simple nonorganic solvent involving a one-step strategy was proposed to synthesize d-π-conjugated molecular electrocatalysts metal-amidinothiourea (M-ATU). Cu-ATU is composed of Cu coordinated with two S and two N atoms, whereas Ni-ATU is formed by Ni with four N atoms from two ATU ligands. Remarkably, Cu-ATU with a Cu-N2S2 coordination configuration exhibits superior NO3RR activity with a NH3 yield rate of 159.8 mg h-1 mgcat-1 (-1.54 V) and Faradaic efficiency of 91.7% (-1.34 V), outperforming previously reported molecular catalysts. Compared to Ni-ATU, Cu-ATU transfers more electrons to the *NO intermediate, effectively breaking the strong sp2 hybridization system and weakening the energy of N═O bonds. The increase in free energy of *NO reduced the energy barriers of the rate-determining step, facilitating the further hydrogenation process over Cu-ATU. Our work opened up a new horizon for exploring molecular electrocatalysts for nitrate activation and paved a way for the in-depth understanding of catalytic behaviors, aligning more closely with industrial demands.

Green Communication in IoT for Enabling Next-Generation Wireless Systems

Recent developments and the widespread use of IoT-enabled technologies has led to the Research and Development (R&D) efforts in green communication. Traditional dynamic-source routing is one of the well-known protocols that was suggested to solve the information dissemination problem in an IoT environment. However, this protocol suffers from a high level of energy consumption in sensor-enabled device-to-device and device-to-base station communications. As a result, new information dissemination protocols should be developed to overcome the challenge of dynamic-source routing, and other similar protocols regarding green communication. In this context, a new energy-efficient routing protocol (EFRP) is proposed using the hybrid adopted heuristic techniques. In the densely deployed sensor-enabled IoT environment, an optimal information dissemination path for device-to-device and device-to-base station communication was identified using a hybrid genetic algorithm (GA) and the antlion optimization (ALO) algorithms. An objective function is formulated focusing on energy consumption-centric cost minimization. The evaluation results demonstrate that the proposed protocol outperforms the Greedy approach and the DSR protocol in terms of a range of green communication metrics. It was noticed that the number of alive sensor nodes in the experimental network increased by more than 26% compared to the other approaches and lessened energy consumption by about 33%. This leads to a prolonged IoT network lifetime, increased by about 25%. It is evident that the proposed scheme greatly improves the information dissemination efficiency of the IoT network, significantly increasing the network’s throughput.

Clarification of a unique mucosal vaccination route for improved systemic and mucosal immune response in broiler

There are often outbreaks of infectious diseases on farms, which not only disrupt production but also cause significant economic losses. Vaccines are given to prevent the spread of these infectious diseases, but they produce only systemic antibodies or antibodies in the mucosa of a particular system. So, a new mucosal vaccination route is needed where the vaccine will produce antibodies in the systemic circulation as well as in the mucosa of many systems. In our study, the cloaca was targeted because it is associated with the mucosa of many systems. Whole-mount and routine histological staining show both lymphatic nodules and diffuse lymphatic tissues in the lamina propria of cloaca. These lymphatic tissues are made up of Bu-1+ B-cells, CD3+ T-cells, and KUL01+ macrophages and monocytes. So, this is a new mucosa-associated lymphoid tissue, named cloaca-associated lymphoid tissue (CALT). The CALT contains antigen-presenting cells (dendritic cells, macrophages, B cells, MHC II molecules, and T cells) and is equipped with blood vessels and high endothelial venules, which indicate its functional status. More antibodies were produced in the treatment group compared to the vehicle control group after administration of the infectious bursal disease (IBD) and the Newcastle disease (ND) vaccine through cloaca. In addition, the cloaca-associated route produces a higher number of antibodies than the other traditional routes, which reveals the uniqueness of this route. Cloacal-vaccinated chickens showed less damage to the follicle and epithelium of the bursa of Fabricius compared to other groups, indicating its lower cytotoxic effect. Therefore, the cloaca-associated mucosal vaccination route produces more antibodies than other mucosal vaccination routes, which will protect the chickens on the farm to a greater extent.

Microwave-assisted Synthesis of Benzimidazole Derivatives: A Green and Effective Approach

Benzimidazole derivatives are pivotal in medicinal chemistry due to their diverse therapeutic applications. Traditional synthesis methods often require catalysts and long reaction times, which can be inefficient and environmentally unfriendly. Hence, there is a growing need for more efficient and eco-friendly synthetic methodologies. A newly devised and efficacious synthetic methodology has been established for the synthesis of benzimidazole derivatives, employing microwave assistance without the requirement for a catalyst. This method facilitated the synthesis of fifteen derivatives with notable efficiency, characterized by significantly reduced reaction times ranging from 5 to 10 minutes and impressive yields ranging from 94% to 98%. The identity and purity of the synthesized benzimidazole derivatives were meticulously verified through a comprehensive analysis, encompassing a comparison of their physicochemical properties and spectral characteristics with authenticated reference data. This method represents a significant advancement in the synthesis of benzimidazole derivatives, offering a rapid and high-yielding alternative to traditional synthetic routes.

Polish Conductresses and the Insecurities of Female Labour Migration to France, 1925–1929

In this article we argue that the reports of conductresses accompanying female migrants shed new light on the nature of interwar labour migration. As they mitigated the anxiety and insecurity that women faced during the process of migration, they fulfilled a crucial role in the highly restrictive post-1918 international migration regime. The Polish government introduced conductresses in 1925 to respond to news of the mistreatment and sexual exploitation of Polish women working in France. Developed in close collaboration with international organizations and the League of Nations, the work of these conductresses on land and sea routes was framed as those of ‘moral guardians’ protecting female migrants from the dangers of sex trafficking. However, we argue that their main function was to mitigate the uncertainties of the post-war international order, as traditional routes of migration were ruptured and both dispatching and receiving countries attempted to control and restrict migration. Female migrants had no networks with existing diasporas, were often illiterate, and mistrusted both Polish and French institutions. By addressing these challenges, the conductresses took on roles far beyond their function as moral authority: they acted as translators, knowledge imparters, mediators, and network forgers. Both in Poland and at the international level, the Polish conductress scheme was regarded a success, as they managed to provide a relatively ‘secure’ migration experience within a migration regime designed to walk a fine line between demands for foreign labour on the one hand and the rising ideal of economic protectionism on the other.

Comparative pathogenicity of influenza virus-induced pneumonia mouse model following intranasal and aerosolized intratracheal inoculation

BackgroundInfection of mice with mouse-adapted strains of influenza virus has been widely used to establish mouse pneumonia models. Intranasal inoculation is the traditional route for constructing an influenza virus-induced pneumonia mouse model, while intratracheal inoculation has been gradually applied in recent years. In this article, the pathogenicity of influenza virus-induced pneumonia mouse models following intranasal and aerosolized intratracheal inoculation were compared.MethodsBy comparing the two ways of influenza inoculation, intranasal and intratracheal, a variety of indices such as survival rate, body weight change, viral titer and load, pathological change, lung wet/dry ratio, and inflammatory factors were investigated. Meanwhile, the transcriptome was applied for the initial exploration of the mechanism underlying the variations in the results between the two inoculation methods.ResultsThe findings suggest that aerosolized intratracheal infection leads to more severe lung injury and higher viral loads in the lungs compared to intranasal infection, which may be influenced by the initial site of infection, sialic acid receptor distribution, and host innate immunity.ConclusionIntratracheal inoculation is a better method for modelling severe pneumonia in mice than intranasal infection.