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Due to the fact that the dynamic medical material distribution is vital to the quick response to urgent demand when the Ebola virus occurs, the optimal distribution approach is explored according to the Ebola virus diffusion rule and different severity of the epidemic. First, we choose the more serious epidemic state of Sierra Leone in West Africa as the research object and the SIQR (susceptible, infected, quarantined, required) epidemic model with pulse vaccination is introduced to describe the Ebola diffusion rule and obtain the demanded vaccine and drug in each pulse. Based on the SIQR model, thirteen areas in Sierra Leone are classified into three emergency levels by clustering analysis. Then a dynamic medical material distribution model is formulated, with goals of both reducing the transportation cost and shortages. The results indicate that the proposed approach can make an outstanding contribution to fight against the Ebola virus.

Mice are one of the most common biological models for laboratory use. However, wild‐type mice are not susceptible to COVID‐19 infection due to the low affinity of mouse ACE2, the entry protein for SARS‐CoV‐2. Although mice with human ACE2 (hACE2) driven by Ace2 promoter reflect its tissue specificity, these animals exhibit low ACE2 expression, potentially limiting their fidelity in mimicking COVID‐19 manifestations and their utility in viral studies. Here, we created and compared hACE2 mouse models generated with different strategies. Our findings show that distinct β‐globin insertion within hACE2 cassette significantly influences its expression, with downstream placement enhancing transcription. Moreover, optimizing hACE2 codons (opt‐hACE2) improves translation efficiency in multiple tissues. Notably, opt‐hACE2 mice displayed more active immune responses and severe COVID‐19 phenotypes following SARS‐CoV‐2 challenge compared to other models. Our study demonstrates the dual regulatory role of β‐globin element in transgene transcription and suggests that opt‐hACE2 mice might serve as valuable tools for SARS‐CoV‐2 research.

Abstract Aging is identified as a significant risk factor for severe coronavirus disease-2019 (COVID-19), often resulting in profound lung damage and mortality. Yet, the biological relationship between aging, aging-related comorbidities, and COVID-19 remains incompletely understood. This study aimed to elucidate the age-related COVID19 pathogenesis using an Hutchinson-Gilford progeria syndrome (HGPS) mouse model, a premature aging disease model, with humanized ACE2 receptors. Pathological features were compared between young, aged, and HGPS hACE2 mice following SARS-CoV-2 challenge. We demonstrated that young mice display robust interferon response and antiviral activity, whereas this response is attenuated in aged mice. Viral infection in aged mice results in severe respiratory tract hemorrhage, likely contributing a higher mortality rate. In contrast, HGPS hACE2 mice exhibit milder disease manifestations characterized by minor immune cell infiltration and dysregulation of multiple metabolic processes. Comprehensive transcriptome analysis revealed both shared and unique gene expression dynamics among different mouse groups. Collectively, our studies evaluated the impact of SARS-CoV-2 infection on progeroid syndromes using a HGPS hACE2 mouse model, which holds promise as a useful tool for investigating COVID-19 pathogenesis in individuals with premature aging.

Objectives: Vein graft adaptation (VGA) is a process that vein as a vascular graft conduits in arterial reconstructive surgery; VGA can lead to postoperative vein graft stenosis (VGS) and complications after coronary artery bypass graft and other peripheral artery bypass surgeries. VGA is characterized by vein graft loss the venous features without exhibiting arterial features; furthermore, the activation of ERK inhibited the maintenance of venous properties of the vein graft. We hypothesized that ERK inhibition can affect vein VGS through regulating the expression of EphB4. Methods: Rat vein transplantation model was established using wild-type and EphB4+/− Sprague-Dawley rats. Hematoxylin-eosin, Masson, Verhoeff, actin staining, and immunohistochemistry were applied to observe the structure of the vein grafts. Vascular smooth muscle cells (VSMCs) were isolated from the vein and vein grafts. Western blotting was used to determine the expression of p-ERK1/2 and EphB4, and immunofluorescence was applied to detect the expression and location of EphB4. Cell wound scratch assay and CCK8 assay were used to determine the migration and proliferation of VSMCs. Real-time polymerase chain reaction was used to determine the mRNA expression of EphB4. Results: Western blotting in vein sample and vein graft sample detected p-ERK1/2 and ERK1/2 expression in both EphB4+/+ and EphB4+/− rats. The expression of p-ERK was increased in vein graft compared to vein. Immunofluorescence in VSMCs form EphB4+/+ and EphB4+/− rats detected EphB4 expression in both cells, and the expression of EphB4 was increased in VSMCs form EphB4+/+ rats. SCH772984 reduces the proliferation and migration of VSMCs. Inhibition of ERK suppressed the increase of vein graft wall thickness, and the expression of collagen fibers, elastic fibers, and α-actin was decreased. Vein graft from EphB4+/− rats reduces the expression of EphB4, and SCH772984 suppressed the decrease of EphB4 in vivo. Vein graft from EphB4+/− rats increased the expression of EphB4, and SCH772984 suppressed the increase of EphB4 in vivo. Conclusions: The inhibition of ERK1/2 suppressed the process of VGS by decreasing the proliferation of VSMCs. The ERK-inhibitor SCH772984 suppressed the level of VGS by extending the time of EphB4 expression during the process of VGA, thus maintaining the venousization of vein graft. The mechanism may be that the inhibitor SCH772984 suppresses the level of VGS by extending the time of EphB4 expression during the process of VGA. Therefore, our research provides a new target of VGS treatment by inhibiting the expression of ERK1/2 through the process of VGA. [ABSTRACT FROM AUTHOR]

[Objectives] With the development of modern ship technology and the higher requirement for the ship hull's own resistance capability to the anti-ship weapons,the composite materials have been more widely used in warship protective structure. In order to analyze anti-explosion performance of protective structures with Kevlar materials under the action of explosion in cabin,[Methods] based on the finite element model from full-scale ship compartment with multi decks,a structural model of the cabin between two decks is established,and armored protective structure with Kevlar materials is laid inside the surrounding wall of the cabin. The dynamic response and damage of the armored protective structure with Kevlar materials under the action of explosion are calculated in this way. In order to correctly simulate the material properties of the anisotropy of Kevlar materials,the armored protective layer is established by solid elements. The upper unit nodes of the surrounding wall and unit nodes of the Kevlar materials are constrained by ‘tie’ to make these two types of nodes move together.[Results] The bulkhead without protective material is completely torn and destroyed by explosion load,while the bulkhead with protective material is only partially torn and destroyed in the position where shock wave is directly impacting.[Conclusions] By comparing and analyzing the cabin damage characteristics of different explosion initiation positions as well as armored protective structure with or without Kevlar materials, the anti-explosion protective design of the cabin can be supported to some extent.

Abstract: The progresses of statistical texture analysis have been playing a more and more important roles in remote sensing mapping, pattern recognition and computer vision. The achievements and research approaches have found important applications in many fields, including industry inspection, remote sensed data analysis and mapping, medical imaging, textile defect detection, video image analysis, food grading, and natural texture recognition and retrieval, object recognition, etc.[1] This paper starts with the principles and algorithms of second order statistics. Based on the theoretical analysis, we selected 5 typical texture class samples from Quick Bird RGB fused data with 0.61m resolution. We used GLCMs to quantitatively calculate texture features, which parameter values are suitable for the specific texture classifications. GLCMs of 5 typical texture class samples from the data set were calculated. Six statistical features for every class sample in four orientations and 1 pixel of pair-wise distance were obtained, including: energy, entropy, contrast, homogeneity, correlation, and dissimilarity respectively. The average values in four directions were computed and compared. The results show that dissimilarity and entropy have biggest value differences among six samples. They are the most important features for classification or recognition of class samples. The statistics of dissimilarity, entropy, homogeneity, contrast have been demonstrated a decrease in classification ability. But the average contrast can discriminate the complex building sample from other textures in spite of small differences with others. The results of the research supplied important references for the quantitative interpretation of VHR Quick Bird imagery in the applications of land cover/use classification and mapping. [Copyright &y& Elsevier]

Abstract: This paper presents a technique of land cover classification of high-spatial resolution image which consists of two Quick Bird data with obvious differences to implement classification and improve classification accuracy, one of the data is covered by snow. The study area locates at the sub-watershed of Kunming Dianchi Lake watershed. There is an obvious border between two images after data fusion, which cannot be cancelled by data processing. Hence, the classification of land cover by use of a same process set in Definiens developer 7.0 becomes difficult or causes errors, that is so called edge effect. Our research develops a practical process to extract the classification information from these special regions to form thematic map for environmental and socioeconomic applications. Six classes, including forest, cultivated land, architecture, water, bare soil and shadow are classified successfully. In the class thematic map, the border effect was cancelled completely. The methodology was developed in an experimental way by suitable selection of processes, parameters and methods. Overall accuracy of classification reaches 92.32%, with Kappa statistics 0.8914. [Copyright &y& Elsevier]

Abstract: In this paper, we proposed a contextual and Object-based Image Analysis (OBIA) classification approach through the experiment, which was using Cognition Network Language (CNL) of commercial software eCognition Developer. Combination of spectrum and texture explored the rich information contents in the Very High-spatial Resolution (VHR) satellite imagery. Meanwhile, contextual relation was adopted in the experiment to improve the classification accuracy. In the research, a few land cover characteristics (contrast, entropy, etc.) were studied for the local land covers. By the experiment, six different classes were extracted: building, road, forest, water, farmland and bare soil. 94.05% classification overall accuracy and 0.92 Kappa coefficient were achieved by the approach for the complex land covers. Data set was five bands QuickBird imagery located nearby Kunming Dianchi Lake (KDL), which is a very important highland lake in China, also in the world. The results may be used in lake protection, environment protection, land planning and land use management, and government decision making around KDL. [Copyright &y& Elsevier]

Vibration prediction for stern cabins is an important part of research into the global vibration of ships. To address the need to improve precision and efficiency, a study is carried out on the proportion of a mixed model and the length of a 3D stern cabin model to investigate the natural frequency of a ship. Using the FE method, different types of model are established for a research vessel, including six mixed models that are used for the basis of a detailed discussion on the different proportions of mixed models, and five stern cabin models that are used to analyze the impact of the modeling range on the natural frequency. Moreover, the Lewis method and virtual mass method are both used to consider the impact of outside water in the analysis of the wet mode. It is observed that the results of the calculated natural frequency of the mixed models are approximately the same when the proportion of the mixed models is over 1/5 the length of the ship, and in good agreement with the results of the calculations when the modeling range of the stern cabin models is exactly in the vicinity of the vibration node of the ship. For the local vibration calculation of ships using the Lewis method and virtual mass method, the results of various schemes differ greatly when applied to the stern cabin models. The results suggest that the proportion of local cabin models should be 1/4 the length of the ship in the natural frequency calculation, and the virtual mass method is recommended for considering the impact of local additional water mass.

Non-contact underwater explosion can generate violent movement on hull girders,which may cause longitudinal strength problems. The explosion bending moment can be calculated using a detailed finite element ship model,but this costs considerable working time. This paper advances a new method for calculating explosion bending moment by a hull girder model. The explosion bending moment of typical ship sections is calculated according to a detailed ship model and simplified hull girder model using ABAQUS software. Comparisons between the results indicate that the simplified hull girder model is easily created and has good precision,enabling it to provide a reference for the estimation of explosion bending moment in hull girders subjected to non-contact underwater explosion.