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The emergence and circulation of duck reovirus have caused severe threats to domestic waterfowl production because of the lethal infections they cause in ducks and geese. However, the evolution of circulating duck reoviruses and their replication and pathogenicity in domestic birds have not been fully investigated. In this study, we identified and isolated six duck reoviruses from clinical samples of sick or deceased farmed ducks and geese and sequenced their full genomes. Phylogenetic analysis revealed the evolutionary landscape of duck reoviruses and the complex reassortment of these circulating viruses with avian orthoreovirus and Muscovy duck reovirus. Animal infection studies revealed differences in the replication and pathogenicity of the reoviruses identified in this study in ducks, geese and chickens. Lethal infection with highly pathogenic viruses causes severe focal necrosis and hemorrhage in the liver, spleen, bursa of Fabricius and thymus, resulting in high mortality in inoculated birds. Importantly, chickens are susceptible to circulating duck reovirus, highlighting the potential risk of duck reovirus infection in chickens. Our study revealed the evolution, pathogenicity and potential cross-species transmission risk of duck reoviruses, further emphasizing the importance of continued and systemic surveillance at the interface of domestic waterfowl and chickens. [ABSTRACT FROM AUTHOR]

As a rare subtype of avian influenza virus, H16 viruses are predominant in gulls but rarely found in domestic birds. The low prevalence of H16 viruses has limited our understanding of their epidemiology and evolutionary dynamics. In this study, we isolated three novel H16N3 viruses from migratory gulls in East Asian–Australasian Flyway in eastern China in 2023, which are significantly different from previously identified isolates. To fully understand the epidemiology and genetics characteristics of the global H16 viruses, we compared the host divergence of several rare subtypes and determined that the H13 and H16 subtypes were predominantly pooled into different species of gulls by sharing their internal genes, whereas the waterfowl of Anatidae served as the primary natural reservoirs of the H8, H11, H12, H14, and H15 subtypes. Detailed phylogenetic analysis revealed the evolutionary divergence of globally circulating H16 viruses and their frequent gene reassortment. Furthermore, the gull origin H13 and H16 viruses collectively served as gene donors for the newly emerged highly pathogenic clade 2.3.4.4b H5N1 viruses because the H13/H16-like PA, NP, and NS genes have been introduced into circulating H5N1 viruses since May 2022 in Europe. To date, the H5N1 reassortants containing the H13/H16-like gene segments have been detected in wild and domestic birds and resulted in mammal and human infections. These results improve our knowledge of the ecology and genetics of H16 viruses and emphasize the need for surveillance to monitor the emergence of novel avian influenza viruses in migratory birds. [ABSTRACT FROM AUTHOR]

Persistent immunoglobulin G (IgG) production (PIP) provides long-term vaccine protection. While variations in the duration of protection have been observed with vaccines prepared from different pathogens, little is known about the factors that determine PIP. Here, we investigated the impact of three parameters on the duration of anti-peptide IgG production, namely amino acid sequences, protein carriers, and immunization programs. We show that anti-peptide IgG production can be transformed from transient IgG production (TIP) to PIP, by placing short peptides (Pi) containing linear B cell epitopes in different competitive environments using bovine serum albumin (BSA) conjugates instead of the original viral particles. When goats were immunized with the peste des petits ruminants (PPR) live-attenuated vaccine (containing Pi as the constitutive component) and BSA-Pi conjugate, anti-Pi IgG production exhibited TIP (duration < 60 days) and PIP (duration > 368 days), respectively. Further, this PIP was unaffected by subsequent immunization with the PPR live-attenuated vaccine in the same goat. When goats were coimmunized with PPR live-attenuated vaccine and BSA-Pi, the induced anti-Pi IgG production showed a slightly extended TIP (from ~60 days to ~100 days). This discovery provides new perspectives for studying the fate of plasma cells in humoral immune responses and developing peptide vaccines related to linear neutralizing epitopes from various viruses. [ABSTRACT FROM AUTHOR]

The prediction of expressway vehicle trajectories is a crucial aspect in the development of intelligent expressways. This paper proposes a novel approach, namely the W-GRU-Attention (WGA) model, which utilizes ETC transaction data to predict trajectory selection based on historical traffic paths and previous passed gantry information. In this study, we apply the concept of word embedding models to extract contextual semantics from the historical trajectories on expressways. Additionally, we introduce an average pooling technique for converting the historical vehicle trajectory into a fixed-length Historical Trajectory Vector (HTV), enabling us to capture dependency relationships within experience paths. By combining proximity gantry vectors during transit, we accurately predict the next gantry location. Finally, our proposed method is evaluated using a real-world expressway ETC dataset. It achieves an impressive accuracy rate of 96.14% in capturing the relationship between historical trajectories and adjacent gantries, surpassing other models in path prediction. [ABSTRACT FROM AUTHOR]

The urban public transport network is closely related to urban construction and is susceptible to external influences, especially the bus network (BN). The measurement of the changes in the performance of BN under disruptions plays an important role in the development of bus systems. This paper takes the land-use type around each bus stop to modify the standard coverage range and then combines the attractive service area of the stop and the passenger flow as the opportunity coefficient to propose an improved accessibility model. Finally, the vulnerability of the BN based on the improved accessibility model in different time periods under four disruptions is analyzed. Taking BN in the central area of Xi'an as a case study, the results show that the BN is less vulnerable when stops are associated with high land-use type attractiveness, and regions with a single land-use type have high vulnerability levels. In addition, the land-use disruption causes larger-scale network vulnerability than topological disruptions. An interesting result, opposed to common sense, is found in stops within the top 10% of topological disruption failure probabilities, i.e., the BN is the most vulnerable during the off-peak night period. This study supplements the coordinated development of public transport and land use in future planning. [ABSTRACT FROM AUTHOR]

The printed circuit board (PCB) is the core control unit of electromechanical equipment. In order to determine the influence of the coupling vibration caused by vehicle–road interaction on the PCB reliability of roadside electromechanical equipment, first, the dynamic load of the vehicle tire is solved by establishing the dynamic model of a vehicle road. Then, the acceleration response data generated by road vibration are obtained by solving the road finite element model. Finally, the power density spectrum of the acceleration response is taken as input excitation, and the deformation response of the PCB under vehicle–road coupling vibration is analyzed. The experimental results show that when the vehicle is driving close to the roadside, the vibration caused by vehicle–road coupling will lead to a large deformation of the PCB, and the deformation value reaches 0.170 mm, which can cause structural damage to the PCB. This shows that the vehicle–road coupling vibration can affect the reliability of the roadside electromechanical equipment; thus, the optimal design of the PCB layout is created. After optimization, the first-order modal frequency of the PCB is increase by 5.4%, which reduces the risk of the components breaking away from the PCB substrate. [ABSTRACT FROM AUTHOR]

The development trend of in vitro diagnostics is to obtain various biological information from a sample at extremely low concentration and volume, which has promoted its progress in accurate and sensitive multiplexed detection. Here, we developed a single color quantum dot (QD) based three-dimensional (3D) structure matrix microarray and conducted the detection of two inflammatory factors (C-reactive protein (CRP) and serum amyloid A (SAA)) by a self-built fluorescence detection system. This strategy increased detection sensitivity by immobilizing the antibody specifically on the 3D substrate because it captured more than about 7 times of 'effective' antibodies compared to the two-dimensional (2D) plane. Compared to the dual QDs-2D fluorescence-linked immunosorbent assay, the limit of detection (LOD) of 3D microarray based on QDs modified with amphiphilic polymers has been further improved to 0.11 ng ml−1 for SAA assay and to 0.16 ng ml−1 for CRP assay, respectively. By using QD microspheres (SiO2@QDs@SiO2-COOH, containing approximately 200–300 hydrophobic QDs on per SiO2 sphere) as fluorescent labels, the LOD for CRP and SAA of 3D microarray reached as high as 15 pg ml−1 and 86 pg ml−1, and the sensitivity was further improved by 28-fold and 425-fold, respectively. Because of its excellent performance, this QD microspheres-based 3D microarray has great application potential for highly sensitive and multiplexed quantitative detection of other biomarkers, small molecules, and antibiotic residues in biomedicine and food safety. [ABSTRACT FROM AUTHOR]

Future frame prediction in video is one of the most important problem in computer vision, and useful for a range of practical applications, such as intention prediction or video anomaly detection. However, this task is challenging because of the complex and dynamic evolution of scene. The difficulty of video frame prediction is to model the inherent spatio-temporal correlation between frames and pose an adaptive and flexible framework for large motion change or appearance variation. In this paper, we construct a deep multi-branch mask network (DMMNet) which adaptively fuses the advantages of optical flow warping and RGB pixel synthesizing methods, i.e., the common two kinds of approaches in this task. In the procedure of DMMNet, we add mask layer in each branch to adaptively adjust the magnitude range of estimated optical flow and the weight of predicted frames by optical flow warping and RGB pixel synthesizing, respectively. In other words, we provide a more flexible masking network for motion and appearance fusion on video frame prediction. Exhaustive experiments on Caltech pedestrian and UCF101 datasets show that the proposed model can obtain favorable video frame prediction performance compared with the state-of-the-art methods. In addition, we also put our model into the video anomaly detection problem, and the superiority is verified by the experiments on UCSD dataset. [ABSTRACT FROM AUTHOR]

To broaden the application of the basalt fiber in the preventive maintenance of asphalt pavement, this study investigated the bonding performance and evaluated the comprehensive performance of the basalt fiber asphalt macadam seal. Firstly, different types of basalt fiber asphalt macadam seal were prepared. The influences of content and length of the basalt fiber and dosage of emulsified asphalt on the bonding performance of the asphalt macadam seal were analyzed and compared. Next, by using the efficacy coefficient method, comprehensive performance considering both mechanical and economic characteristics of the basalt fiber asphalt macadam seal was evaluated. After that, reasonable content of each material was determined. Finally, the strengthening mechanism of the fiber on the bonding performance of macadam seals was revealed from a microscopic view. The results showed that compared with the ordinary asphalt macadam seal, the loss aggregate rate of the basalt fiber asphalt macadam seal was 11.0–30.5% lower, and the pull-out strength, shear strength, and torsional shear strength were 11.7–16.3%, 9.7–22.4%, and 4.2–20.6% higher, respectively. Considering the bonding performance and economic benefits, the optimal amount of emulsified asphalt and basalt fiber was 1.6 kg/m2 and 70 g/m2, respectively. Basalt fiber increased the cohesion of the asphalt material and improved the bonding performance of asphalt macadam seals through formation of the three-dimensional network structure. This study can provide reference to the application of basalt fibers in asphalt pavement maintenance. [ABSTRACT FROM AUTHOR]

The growth of electric vehicles (EVs) and renewable generation on the highway will magnify the imbalance between the energy supply and traffic electricity demand. Reshaping EV charging loads to address the above imbalance is challenging. Scheduling mobile energy storage vehicles (MESVs) to consume renewable energy is a promising way to balance supply and demand. Therefore, leveraging the spatiotemporal transferable characteristics of MESVs and EVs for energy, we propose a co-optimization method for the EV charging scheme and MESV scheduling on the highway, considering locational marginal price, renewable generation, and EV users' benefit. Furthermore, by building a time–space–energy model for MESVs and EVs, we develop a bi-level optimization model to simulate the interaction between EV users and the highway operator (HO). In detail, the upper-level model optimizes EV charging pricing and MESV scheduling strategies to maximize HO profit, while the lower-level model considers EV users' characteristics to minimize their charging-parking costs. The column-and-constraint generation algorithm is adopted due to the objective conflict between two levels. The study shows a 32.0% increase in renewable energy utilization and a reduction of 3190.1 kWh in electricity purchased from the main grid, promoting environmental and economic sustainability for the HO. • Co-optimize electric vehicle charging and mobile energy storage vehicle scheduling. • Build a time–space–energy model with highway characteristics. • Model a bi-level optimization to balance highway operator's benefit with users' cost. • Increase renewable generation utilization by reshaping supply–demand distribution. [ABSTRACT FROM AUTHOR]

Composition optimization of the asphalt mixture of pavement is one effective measures to reduce the harm of traffic noise. To improve the noise reduction effect of porous asphalt mixture (PAM) and promote the recycling of crumb rubber in highway engineering, the preparation parameters of high-viscosity modified asphalt for PAM were optimized in this study, and the mixture gradation was optimized based on the unbalance force and contact force of mixed aggregate. The effects of crumb rubber content and particle size on the damping performance and dynamic shear modulus of the mixture were studied. The effects of different preparation parameters on the performance of the PAM were comprehensively evaluated based on the orthogonal test, and preparation parameters of PAM were recommended. The results show that with the increase of crumb rubber content, the damping ratio of the mixed aggregate increases gradually. The addition of crumb rubber is conducive to improving the damping performance and toughness of the PAM, but it has an adverse impact on the bearing capacity. Under the condition of low strain, the damping ratio of the mixed aggregate containing 2–5 mm crumb rubber is 1.2–5 times that of the mixed aggregate containing 0.6–1 mm crumb rubber. The recommended optimum content of crumb rubber in PAM is 4%, and the optimum particle size of alternative aggregate is 2.36–4.75 mm. The significant factors affecting Marshall stability are rubber particle content, asphalt aggregate ratio, mixing temperature, compaction times, and forming temperature. The rational utilization of crumb rubber in PAM is of positive significance to promoting the green development of highway construction and the harmless treatment of waste resources. [ABSTRACT FROM AUTHOR]

For analyzing the traffic anomaly within dashcam videos from the perspective of ego-vehicles, the agent should spatial-temporally localize the abnormal occasion and regions and give a semantically recounting of what happened. Most existing formulations concentrate on the former spatial-temporal aspect and mainly approach this goal by training normal pattern classifiers/regressors/dictionaries with large-scale availably labeled data. However, anomalies are context-related, and it is difficult to distinguish the margin of abnormal and normal clearly. This paper proposes a progressive unsupervised driving anomaly detection and recounting (D&R) framework. The highlights are three-fold: (1) We formulate driving anomaly D&R as a temporal-spatial-semantic (TSS) model, which achieves a coarse-to-fine focusing and generates convincing driving anomaly D&R. (2) This work contributes an unsupervised D&R without any training data while performing an effective performance. (3) We novelly introduce the traffic saliency, isolation forest, visual semantic causal relations of driving scene to effectively construct the TSS model. Extensive experiments on a driving anomaly dataset with 106 video clips (temporal-spatial-semantically labeled carefully by ourselves) demonstrate superior performance over existing techniques. [ABSTRACT FROM AUTHOR]

Linear B-cell epitopes are ideal biomarkers for the serodiagnosis of infectious diseases. However, the long-predicted diagnostic value of epitopes has not been realized. Here, we demonstrated a method, diagnostic epitopes in four steps (DEIFS), that delivers a combination of epitopes for the serodiagnosis of infectious diseases with a high success rate. Using DEIFS for malaria, we identified 6 epitopes from 8 peptides and combined them into 3 chimeric peptide constructs. Along with 4 other peptides, we developed a rapid diagnostic test (RDT), which is able to differentiate Plasmodium falciparum (P. falciparum) from Plasmodium vivax (P. vivax) infections with 95.6% overall sensitivity and 99.1% overall specificity. In addition to applications in diagnosis, DEIFS could also be used in the diagnosis of virus and bacterium infections, discovery of vaccine candidates, evaluation of vaccine potency, and study of disease progression. [ABSTRACT FROM AUTHOR]