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Abstract The design of intelligent expressway transportation system based on the Internet of Things is studied to improve the safety, travel experience, and operation management of expressway. The characteristics of the Internet of Things and cloud computing technology and its application on the expressway are analyzed, and the system design requirements of expressway intelligent transportation are understood. Besides, the overall architecture of the system is studied and designed. The IaaS layer, PaaS layer, and SaaS layer of the cloud platform are designed and deployed. The intelligent information system can make expressway highly informative. The simulation experiments reveal that the system only needs 120 milliseconds in accident processing time, which is far lower than the intelligent transportation system that only uses edge computing technology (201 milliseconds) and the intelligent transportation system that only uses cloud computing technology (443 milliseconds). Meanwhile, the accident response time is only 12 s, which is also superior to other models. In terms of cost-effectiveness, the monthly cost of the system is 7004 yuan, with a CPU utilization rate of 53%, demonstrating good cost-effectiveness and resource utilization efficiency. In addition, compared with the existing system, the average traffic congestion time has been reduced by 25%, the traffic accident rate has been reduced by 18%, and the accident rate has been reduced by 27%. The intelligent traffic system design of expressway, expressway safety, travel service, and operation management is effectively improved by researching the intelligent traffic system design of expressway.

With the rapid development of Telematics, Vehicle Self-Organizing Networks (VANETs) play an increasingly critical role in Intelligent Transportation Systems (ITS). Especially in the environment without roadside assistance units (RSUs), how to effectively manage inter-vehicle communication and improve the stability and communication efficiency of the network has become a hot topic of current research. In this paper, a Deep Reinforcement Learning-based Intelligent QoS-optimized efficient routing algorithm for vehicular networks (DRLIQ) is proposed for VANETs with/without RSU environments, and routing methods are proposed respectively. Among them, in RSU-free environment, the DRLIQ algorithm utilizes the powerful processing capability of deep reinforcement learning to intelligently select the optimal data transmission path by dynamically learning and adapting to the changes in the vehicular network, thus effectively reducing communication interruptions and delays, and improving the accuracy of data transmission. The performance of the DRLIQ algorithm under different vehicle densities is evaluated in simulation experiments and compared with current popular algorithms. The experimental results show that the DRLIQ algorithm outperforms the comparison algorithms in reducing the number of communication interruptions, BER and network delay, especially in vehicle-dense environments. In addition, the DRLIQ algorithm shows higher adaptability and stability in coping with network topology changes and vehicle dynamics.

Abstract Borehole instability in igneous rock formation has attracted more and more attention in recent ten years. In order to understand the mechanism of wellbore instability in igneous formation, a borehole stability model is established by applying the thermal, seepage and stress coupling model combined with a true triaxial rock strength criterion, which can reveal evolution of borehole collapse pressure with time. The effect of drilling cycle on borehole collapse pressure considering the coupling effects of temperature, seepage, and stress is quantitatively analyzed. Results show that, compared with only considering the effect of stress, wellbore collapse pressure increases with the coupling effect of temperature, seepage, and stress. Meanwhile, the stability of wellbore can be enhanced by reducing drilling fluid temperature; with the increase of formation porosity, the borehole collapse pressure increases rapidly, and then remains unchanged or decreases; while with the increase of formation permeability, borehole collapse pressure decreases rapidly, i.e. the shear failure of wellbore is mitigated. Besides, compared with vertical well, the horizontal well is more sensitive to the change of rock permeability. The investigation of drilling cycle shows that, the borehole collapse pressure increased sharply when the formation was drilled instantaneously. However, the subsequent growth trend slows down, which suggests that during the early stages of drilling operation, it is advisable to appropriately increase the mud weight to enhance the wellbore’s support capability by the bottomhole pressure. The research findings can enhance the understanding of the instability mechanism of igneous rock formations and reduce the risk of wellbore instability in igneous rock formations.

The impact of the thickness on the boiling phenomena of the water film on the liquid metal surface is compared, and various mechanisms are analyzed, using a molecular dynamics simulation. The findings demonstrated that the best heat transfer performance between the liquid metal surface and water film is obtained when employing a thickness of 9.56 Å, along with a shorter boiling time. Additionally, the boiling time on each surface was further accurately characterized by considering and examining the water film motion and the temperature distribution, in addition to comparing the kinetic energy and potential energy of the system. Also, the surface thickness affected the fluctuation of the liquid metal, the interfacial thermal conductance, and the interfacial thermal resistance. The thicker the liquid metal, the greater the fluctuation. However, a liquid metal surface with a thickness of 9.56 Å is characterized by a larger average interfacial thermal conductance, a smaller average interfacial thermal resistance. Based on the analysis, the difference in boiling time among the different cases was due to the combined effect of fluctuation, interfacial thermal conductance, and interfacial thermal resistance. The results enlighten new ideas and methods for augmenting the efficiency of boiling heat transfer.

Salinity represents a fatal factor affecting the productivity of alfalfa. But the regulation of salinity tolerance via lncRNAs and mRNAs remains largely unclear within alfalfa. For evaluating salinity stress resistance-related lncRNAs and mRNAs within alfalfa, we analyzed root transcriptomics in two alfalfa varieties, GN5 (salinity-tolerant) and GN3 (salinity-sensitive), after treatments with NaCl at 0 and 150 mM. There were altogether 117,677 lncRNAs and 172,986 mRNAs detected, including 1,466 lncRNAs and 2,288 mRNAs with significant differential expression in GN5150/GN50, GN3150/GN30, GN50/GN30, and GN5150/GN3150. As revealed by GO as well as KEGG enrichment, some ionic and osmotic stress-associated genes, such as HPCA1-LRR, PP2C60, PP2C71, CRK1, APX3, HXK2, BAG6, and ARF1, had up-regulated levels in GN5 compared with in GN3. In addition, NaCl treatment markedly decreased CNGC1 expression in GN5. According to co-expressed network analyses, six lncRNAs (TCONS_00113549, TCONS_00399794, TCONS_00297228, TCONS_00004647, TCONS_00033214 and TCONS_00285177) modulated 66 genes including ARF1, BAG6, PP2C71, and CNGC1 in alfalfa roots, suggesting that these nine genes and six lncRNAs probably facilitated the different salinity resistance in GN5 vs. GN3. These results shed more lights on molecular mechanisms underlying genotype difference in salinity tolerance among alfalfas.

This paper aims to provide new avenues for innovation in credit governance in the digital economy to provide more reliable credit evaluation solutions for financial, commercial, and social interactions. This paper integrates the potential value of Internet of Things (IoT) technology in credit governance and proposes a credit governance method that utilizes IoT data and an improved Long Short-Term Memory model. The proposed model introduces an adaptive mechanism to monitor changes in data in real-time and automatically adjust network parameters to improve the model performance. Experimental validation is conducted on the University of California Irvine dataset. It is found that the proposed model performs well in terms of accuracy, F1 value, and Area Under the Curve value, with values of 0.9, 0.91, and 0.94, respectively. This indicates that the proposed model has higher classification accuracy and performance in classification tasks while maintaining efficient training time. This indicates that the presented method has potential application prospects in credit governance research.

Abstract Neural network force fields have significantly advanced ab initio atomistic simulations across diverse fields. However, their application in the realm of magnetic materials is still in its early stage due to challenges posed by the subtle magnetic energy landscape and the difficulty of obtaining training data. Here we introduce a data-efficient neural network architecture to represent density functional theory total energy, atomic forces, and magnetic forces as functions of atomic and magnetic structures. Our approach incorporates the principle of equivariance under the three-dimensional Euclidean group into the neural network model. Through systematic experiments on various systems, including monolayer magnets, curved nanotube magnets, and moiré-twisted bilayer magnets of CrI3, we showcase the method’s high efficiency and accuracy, as well as exceptional generalization ability. The work creates opportunities for exploring magnetic phenomena in large-scale materials systems.

Polarimetric radar systems play a crucial role in enhancing microwave remote sensing and target identification by providing a refined understanding of electromagnetic scattering mechanisms. This study introduces the concept of polarization scattering regions as a novel tool for describing the polarization characteristics across three spectral regions: the polarization Rayleigh region, the polarization resonance region, and the polarization optical region. By using ellipsoidal models, we simulate and analyze scattering across varying electrical sizes, demonstrating how these sizes influence polarization characteristics. The research leverages Cameron decomposition to reveal the distinctive scattering behaviors within each region, illustrating that at higher-frequency bands, scattering approximates spherical symmetry, with minimal impact from the target shape. This classification provides a comprehensive view of polarization-based radar cross-section regions, expanding upon traditional single-polarization radar cross-section regions. The results show that polarization scattering regions are practical tools for interpreting polarimetric radar data across diverse frequency bands. The applications of this research in radar target recognition, weather radar calibration, and radar polarimetry are discussed, highlighting the importance of frequency selection for accurately capturing polarization scattering features. These findings have significant implications for advancing weather radar technology and target recognition techniques, particularly as radar systems move towards higher frequency bands.

This study conducted an in-depth analysis of the sediment dynamics in the lower reaches of the Changhua River and its estuary on Hainan Island. Through field collection of topographic data and sediment sampling, combined with advanced computational techniques, the study explored the transport pathways and depositional patterns of sediments. The grain size trend analysis (GSTA) method was utilized, in conjunction with the Flemming triangle diagram method, to classify the dynamic environment of the sediments. Furthermore, hydrodynamic modeling results were integrated to further analyze the transport trends of the sediments. The study revealed that the sediment types in the research area are complex, primarily consisting of gravelly sand and sandy gravel, indicating a generally coarse sedimentary environment in the region. The sediments in the lower reaches of the Changhua River generally transport towards the south and southwest (in the direction of Beili Bay). The net sediment transport directions inferred from the GSTA model are largely consistent with the Eulerian residual flow patterns, especially in the offshore area, where discrepancies are observed in the nearshore zone. The nearshore transport is influenced by the combined effects of alongshore currents, residual flows, and river inputs, while the offshore transport exhibits a shift from the northwest to southwest directions, reflecting the regional circulation patterns.

Within the realm of computer vision, the task of re-identifying targets across multiple video frames has emerged as a pivotal challenge, particularly in domains like video surveillance, smart transportation systems, and pedestrian flow analytics. Conventional re-identification techniques often grapple with constraints stemming from varying camera perspectives, inconsistent lighting conditions, and prevalent occlusions. Addressing these challenges, this research introduces MVF-Re, a sophisticated re-identification approach that synergizes adaptive attention mechanisms with multi-scale feature fusion. Initially, we architect a deep attention-enhanced feature pyramid network, a pioneering framework that dynamically tailors itself to video frame content, thereby capturing intricate target details. Subsequently, we incorporate a multi-input Siamese network, ensuring the derivation of consistent and resilient feature sets across diverse contexts. To augment feature distinctiveness, we conceptualize a context-sensitive dynamic attention mechanism, adept at judiciously allocating weights to individual video frames. Culminating our approach, we deploy an innovative multi-scale feature fusion methodology, offering a holistic and robust target representation. Empirical evaluations on multiple benchmark datasets underscore the superior performance of our methodology, underscoring its proficiency in multi-frame target re-identification.

In response to the problems of target loss and insufficient accuracy in existing target perception and action recognition algorithms, this paper proposes a target perception and action recognition algorithm based on saliency and feature extraction. This algorithm uses saliency detection techniques to obtain salient regions in images or videos to focus attention on the target. At the same time, feature extraction techniques are combined to extract key nodes and inter-frame correlations from the target information. The experimental results of the measurement data show that this algorithm is superior to traditional detection methods in detecting target behaviors. In addition, it has successfully solved the problems of motion misalignment and jumping in pedestrian detection. Although the node localization of the algorithm needs further improvement, it has shown good application prospects in smart cities and intelligent surveillance. Future work will focus on improving the positioning accuracy of key nodes to enhance its adaptability to different environments and scenarios, providing better support for smart city and other applications.

With the rapid progress of computer vision and deep learning techniques, accurately predicting continuous human motions from very few image inputs and generating high-quality 3D human models has become a cutting-edge research direction in this field. Despite the achievements in 2D to 3D conversion techniques, it is still a great challenge to capture coherent movements from limited image frames and generate texture-rich 3D models. In this paper, we propose a 3D clothed human body generation method based on Inter-Frame Motion Prediction (IFMP for short) of 2D images, which is capable of not only predicting a series of coherent human body motions, but also reconstructing a detailed textured 3D human body model from only two image frames. The method automatically focuses on key parts of the image through action coding and uses a conditional generative adversarial network to generate a series of consecutive intermediate frame images. A depth-aware implicit function representation is combined to map a 3D model from the 2D image, and high quality textures of the human body in a clothed state are obtained by texture mapping and model detail enhancement methods. Finally, the experimental results validate the advantages of the IFMP method in image action coherence prediction, as well as verifying the effectiveness of the human 3D model generated by the method in terms of geometric accuracy and texture quality.

Compared with the amplitude modulation of conventional interrupted sampling repeater jamming (ISRJ), the image feature control method based on phase modulation exhibits greater energy efficiency and, therefore, has received wide attention recently. In this paper, an Inverse Synthetic Aperture Radar (ISAR) image feature suppression method based on arbitrary phase encoding (APE) is proposed. The parameter design criterion is further analyzed. Through the nonperiodic segmented coding and modulation of the imaging signal in fast and slow time domains, the modulated signal produces a two-dimensional suppression region with uniform energy distribution in the ISAR image. Simulations via the measured Yak-42 aircraft data have verified the effectiveness of the proposed method for target feature control. Compared to binary phase modulation jamming, the APE method with a phase modulation accuracy of 1 degree can achieve the same jamming effect while reducing the jamming power requirement by 3 dB. By optimizing with the proposed method, the image entropy of the interfered image increases by 1.1 to 1.5 compared to the original image.

Abstract In this study, we examined the impact of demyelinating and neuroinflammation on trigeminal neuralgia (TN) by utilizing models of chronic constriction injury to the infraorbital nerve (CCI). The CCI rats were treated with either VX-765 (an inhibitor of caspase-1) or a control solution of PBS/DMSO to observe the effects on neurobehavioral and neuropathological outcomes. The histochemical changes, pyroptosis-related proteins were assessed using immunohistochemistry, Elisa, and western blotting. RSC96 cells were pretreated with belnacasan (VX-765, an inhibitor of caspase-1), Gasdermin D(GSDMD)-targeting siRNAs, cobalt protoporphyrin (CoPP) or zinc protoporphyrin (Znpp) before being exposed to H2O2. Following these treatments, the Reactive oxygen species (ROS) level, cell viability, percentage of pyroptosis, pyroptosis-related proteins, nuclear factor erythroid 2-related factor 2 (Nrf2) and HO-1 level was measured. The scanning electron microscopy revealed increased ball-like bulge and membrane pore formation in the CCI group. In the CCI and CCI+ Vehicle groups, we found ROS level and expression of pyroptosis-related proteins increased. While, treatment with VX-765resulted in a decreased expression of GSDMD, IL-1, IL-18, and caspase-1 decreased. In the in-vitro study, RSC96 cells showed mild pyroptosis and overall mild edema after being exposed to H2O2. The ROS level, percentage of pyroptosis, pyroptosis-related proteins, Nrf2 and HO-1 level increased significantly in the H2O2 group. While, the percentage of pyroptosis and pyroptosis-related proteins decreased significantly in the H2O2 + VX-765 group, H2O2 + siRNA group, and H2O2 + VX-765 + siRNA group. After treatment with HO-1-inhibitor Znpp and HO-1-activator Copp, the percentage of pyroptosis and pyroptosis-related proteins increased and decreased significantly respectively. In conclusions, the pyroptosis of Schwann cell in the CCI model generated the demyelination of TN nerve. The ROS is an upstream event of NLRP3 inflammasome activation which induced eventual pyroptosis. The Nrf2/HO-1 signaling pathway could protect the H2O2-induced pyroptosis in RSC96 cells.

Abstract Synthetic Aperture Radar (SAR) jamming is of vital significance in the national defence aspect. In this study, a flexible blanket jamming method against SAR is proposed using joint frequency and phase modulation. The proposed method can form two‐dimensional square‐shaped blanket sidelobes in the SAR image by coded phase modulation in both fast and slow time domain. Then an extra frequency modulation is further executed to flexibly adjust the jamming centre. The target of interest (TOI) can get more effectively protected according to the different relative locations between the TOI and jammer. On this basis, the jamming performance evaluation and parameter design principles are discussed in detail. Finally, the validity of the proposed jamming method is verified by both the Yake‐42 aircraft simulation and measured SAR data experiment.

Light pollution from the use of artificial lighting poses significant impacts on human health, traffic safety, ecological environment, astronomy, and energy use. The advancement of characteristics of light pollution assessment technology has played a significant role in shaping prevention and control policies, thereby enabling measures, such as environmental standards and legislation and product procurement guidelines, but considerable variation in the definition, control strategies, and regulatory frameworks remains. Therefore, there is a need to review the characteristics of light pollution, including the assessment technique, policy, and legislation. Through the literature review, it can be found that technical standards are required to prevent light pollution. For example, light pollution is decreased by 6% in France through the legislation of artificial light. Key approaches are suggested to control global light pollution, including implementing ambient brightness zoning, regulating lighting product usage, and establishing dark sky reserves. Technology and policy should be integrated. The precise data coming from satellite imagery, drones, and balloons could provide guidance when making the policies.

To address the problem of large deformations in weak surrounding rock tunnels under high ground stress, which cause damage to initial support structures, this study proposes a novel type of circumferential pressure-relief joint based on the concept of relieving deformation pressure of the surrounding rock. Key parameters of the pressure-relief joint, such as initial bearing capacity peak, constant bearing capacity, and allowable pressure-relief displacement, were obtained through numerical simulations and laboratory experiments. A comparison was made between the mechanical characteristics of rigid joints and the new type of pressure-relief joint. The applicability of the pressure-relief joint was verified through field tests, monitoring the surrounding rock pressure, internal forces in the steel frames, and the convergence displacement of the support structure. The results show that: (1) In the elastic stage, the stiffness of the new pressure-relief joint is similar to that of rigid joints. In the plastic stage, rigid joints fail directly, whereas the pressure-relief joint can control deformation and effectively release the deformation pressure of the surrounding rock while providing a constant bearing capacity. (2) The right arch foot in the experiment had poor rock quality, leading to high stress in the steel frame and significant horizontal displacement. After the deformation of the pressure-relief joint, the stress in the surrounding rock and steel frame significantly reduced, and the rate of horizontal deformation of the support structure slowed down. (3) The vertical and horizontal final displacements of the pressure-relief joint in the experiment were 61mm and 15mm, respectively, which did not exceed the allowable deformation values. The components of the support structure remained intact, ensuring safety. However, this study has limitations: the design of the new pressure-relief joint only allows for a vertical deformation of 150mm and a horizontal deformation of 50mm, limiting the range of pressure-relief deformation.

For a narrow-brand seismograph with a flat response range limited, it cannot precisely record the signal of a ground motion and output the records with the low-frequency components cut down. A transfer function is usually used to spread the spectrum of the narrow-brand seismic records. However, the accuracy of the commonly used transfer function is not high. The authors derive a new transfer function based on the Laplace transform, bilinear transform, and Nyquist sampling theory to solve this problem. And then, the derived transfer function is used to correct the narrow-band velocity records from the Hi-net. The corrected velocity records are compared with the velocities integrated from the synchronously recorded broad-band acceleration at the same station with Hi-net. Meanwhile, the corrected records are compared with those corrected by the Nakata transfer function. The results show that the calculation accuracy of the derived transfer function is higher than the Nakata transfer function. However, when the signal-to-noise ratio is below 24, its accuracy diminishes, and it is unable to recover signals within the 0.05-0.78Hz frequency band.

Background and objectivesEndovascular thrombectomy (EVT) improves long-term outcomes and decreases mortality in ischemic stroke patients. However, a significant proportion of patients do not benefit from EVT recanalization, a phenomenon known as futile recanalization or reperfusion without functional independence (RFI). In this study, we aim to identify the major stroke risk factors and patient characteristics associated with RFI.MethodsThis is a retrospective cohort study of 297 consecutive patients with ischemic stroke who received EVT at three academic stroke centers in China from March 2019 to March 2022. Patient age, sex, modified Rankin Scale (mRS), National Institute of Health Stroke Scale (NIHSS), Alberta stroke program early CT score (ASPECTS), time to treatment, risk factors and comorbidities associated with cerebrovascular diseases were collected, and potential associations with futile recanalization were assessed. RFI was successful reperfusion defined as modified thrombolysis in cerebral infarction (mTICI) ≥ 2b without functional independence at 90 days (mRS ≥ 3).ResultsOf the 297 initial patients assessed, 231 were included in the final analyses after the application of the inclusion and exclusion criteria. Patients were divided by those who had RFI (n = 124) versus no RFI (n = 107). Older age (OR 1.041, 95% CI 1.004 to 1.073; p = 0.010), chronic kidney disease (OR 4.399, 0.904–21.412; p = 0.067), and higher 24-h NIHSS (OR 1.284, 1.201–1.373; p

Despite the industrial significance of grain size for enhancing mechanical properties and formability, the in-depth deformation mechanisms at elevated temperature are still unclear. To investigate the functions of grain size on hot workability and deformation mechanisms, three groups of Mg-1.2Zn-0.2Y alloy specimens with different grain sizes were hot compressed and then studied by combining constitutive model, processing map and microstructural observations. The results showed that the enhanced hot workability accompanying low deformation activation energy and small instability regime was obtained with refined grain size. During hot deformation, the decreased grain size in Mg-1.2Zn-0.2Y alloy mainly improved the plastic deformation homogeneity, especially for the weakened local straining around grain boundaries. As a result, the dynamic recrystallization nucleation and texture development at lower strain level were influenced by the initial grain size. At higher strain magnitude, the growth and coarsening of dynamic recrystallized grains would further release strain localization and improve hot workability, while the texture was less impacted. Further, unlike the primary basal slip and deformation twinning in the specimen with coarse grain at low temperature, non-basal slips of dislocations were initiated with less deformation twins in the specimens with refined grain size.

As the electric capacity of wind turbine increases, heat dissipation in pitch cabinets becomes challenging owing to the limited space and rotating conditions. To cool down the pitch cabinet more effectively and allow heat dissipation, we designed and implemented a pulsating heat pipe (PHP) in this study. We designed PHP parameters and conducted performance tests to compare the cooling performance of the fabricated PHP with that of an air-based cooling system in a 1.5 MW wind turbine. The results demonstrated steady PHP operation under rotating conditions (17.3 rpm). At a heat load of 1000 W, the evaporator outlet temperature was only 76.1 °C. However, increasing the ambient temperature adversely affected PHP operation, resulting in higher temperature and thermal resistance. The heat-pipe-based cooling system lowered the insulated gate bipolar transistor (IGBT) temperature by about 20.4 °C in relation to the air-based cooling system, while being suitable under varied conditions. Additionally, the system could successfully operate when the heat load of IGBT was 2350 W, corresponding to a 7 MW electric capacity of the wind turbine. Reducing the manufacturing cost of the heat pipe would further enhance the applicability of this system for pitch cabinet IGBT cooling, such as decreasing payback period.

To address the issue of image denoising algorithms blurring image details during the denoising process, we propose an adaptive denoising algorithm for the 3D reconstruction of 2D images. This algorithm takes into account the inherent visual characteristics of human eyes and divides the image into regions based on the entropy value of each region. The background region is subject to threshold denoising, while the target region undergoes processing using an adversarial generative network. This network effectively handles 2D target images with noise and generates a 3D model of the target. The proposed algorithm aims to enhance the noise immunity of 2D images during the 3D reconstruction process and ensure that the constructed 3D target model better preserves the original image’s detailed information. Through experimental testing on 2D images and real pedestrian videos contaminated with noise, our algorithm demonstrates stable preservation of image details. The reconstruction effect is evaluated in terms of noise reduction and the fidelity of the 3D model to the original target. The results show an average noise reduction exceeding 95% while effectively retaining most of the target’s feature information in the original image. In summary, our proposed adaptive denoising algorithm improves the 3D reconstruction process by preserving image details that are often compromised by conventional denoising techniques. This has significant implications for enhancing image quality and maintaining target information fidelity in 3D models, providing a promising approach for addressing the challenges associated with noise reduction in 2D images during 3D reconstruction.

Abstract Background Microglia-mediated neuroinflammatory response following traumatic brain injury (TBI) is considered as a vital secondary injury factor, which drives trauma-induced neurodegeneration and is lack of efficient treatment. ACT001, a sesquiterpene lactone derivative, is reportedly involved in alleviation of inflammatory response. However, little is known regarding its function in regulating innate immune response of central nervous system (CNS) after TBI. This study aimed to investigate the role and underlying mechanism of ACT001 in TBI. Methods Controlled cortical impact (CCI) models were used to establish model of TBI. Cresyl violet staining, evans blue extravasation, neurobehavioral function assessments, immunofluorescence and transmission electron microscopy were used to evaluate therapeutic effects of ACT001 in vivo. Microglial depletion was induced by administering mice with colony stimulating factor 1 receptor (CSF1R) inhibitor, PLX5622. Cell-cell interaction models were established as co-culture system to simulate TBI conditions in vitro. Cytotoxic effect of ACT001 on cell viability was assessed by cell counting kit-8 and activation of microglia cells were induced by Lipopolysaccharides (LPS). Pro-inflammatory cytokines expression was determined by Real-time PCR and nitric oxide production. Apoptotic cells were detected by TUNEL and flow cytometry assays. Tube formation was performed to evaluate cellular angiogenic ability. ELISA and western blot experiments were used to determine proteins expression. Pull-down assay was used to analyze proteins that bound ACT001. Results ACT001 relieved the extent of blood-brain barrier integrity damage and alleviated motor function deficits after TBI via reducing trauma-induced activation of microglia cells. Delayed depletion of microglia with PLX5622 hindered therapeutic effect of ACT001. Furthermore, ACT001 alleviated LPS-induced activation in mouse and rat primary microglia cells. Besides, ACT001 was effective in suppressing LPS-induced pro-inflammatory cytokines production in BV2 cells, resulting in reduction of neuronal apoptosis in HT22 cells and improvement of tube formation in bEnd.3 cells. Mechanism by which ACT001 functioned was related to AKT/NFκB/NLRP3 pathway. ACT001 restrained NFκB nuclear translocation in microglia cells through inhibiting AKT phosphorylation, resulting in decrease of NLRP3 inflammasome activation, and finally down-regulated microglial neuroinflammatory response. Conclusions Our study indicated that ACT001 played critical role in microglia-mediated neuroinflammatory response and might be a novel potential chemotherapeutic drug for TBI. Video Abstract

An integrated Eulerian model for fouling in turbulent flow was developed to simulate the particle fouling characteristics. The model comprises a deposition process and removal process. The deposition process considers four various factors affecting the particle deposition which are Brownian and eddy diffusion, gravity, thermophoretic, and turbophoretic forces. This study compares the Lagrangian and Eulerian approaches under the same operating conditions with an emphasis on their performance in predicting particle deposition. The deposition height calculated by using the Eulerian approach is in good agreement with the experimental data and the deposition morphology is similar to that observed in experiments. Furthermore, this paper explores the deposition characteristics and predicts the deposition morphology under different particle sizes.

The efficiency of photovoltaic(PV) panels decreases as their temperature increases, so effective cooling of them is necessary. The cooling of PV panels based on phase change materials(PCMs) is an emerging cooling method that has recently received the attention of scholars around the world. Herein, the cooling characteristics of PCM on PV panels are experimentally investigated to study the cooling effect of PCM on solar PV panel cooling technology (PV-PCM) and explore the effect of inverse process of PCM from molten to solidified state on the temperature of solar PV panels after cooling. The results reveal that the PCM can effectively reduce the temperature of solar PV panels under the condition of no wind, irradiance of 1000 W/m2 and ambient temperature of 7.3 °C. The PCM can reduce the average temperature of the upper and back surfaces of solar PV panels by 33.94 °C and 36.51 °C within 300 min, respectively. Moreover, the PCM increased the average maximum power generation efficiency of solar PV panels by 1.63% and the average maximum output power by 1.35 W. The solar PV panels cooled without PCM took only 60 min to cool from the maximum temperature to room temperature, whereas the solar PV panels in PV-PCM system took 480 min to cool down to room temperature.

The fly ash particle deposition in the heat recovery process of the heat exchanger is an urgent issue that must be addressed. In this work, the particle deposition model is improved using the dynamic mesh technology and random function method. We simulated and predicted the fouling morphology and particle size distribution of the fly ash layer using the deposition characteristics of particles of various sizes. The results indicated that when dynamic mesh technology is adopted, the tube wall's boundary will be deformed geometrically with the deposition of particles, allowing the changes in the fouling morphology to be expressed more effectively. Under this study conditions, the particle deposition mass on the windward and leeward sides of the tube increased initially and then decreased with the particle size increased. When particles of different sizes are mixed, the first layer of particles accelerates the deposition of subsequent particles, and the first layer of particles is generally composed of particles of small size.

In the midcourse trajectory of ballistic targets, warhead releasing and decoy throwing are two of the several types of target separation events. In the early stages, multiple targets are close to each other, and coupling scattering usually leads to variations in the radar cross section and polarization. If these variation features are investigated clearly, the tracking and recognition ability of an early warning radar will improve for ballistic targets. In this study, dynamic scattering of ballistic targets with three types of separation movements is analyzed; and several separation features that promote the action recognition development of midcourse ballistic targets are proposed.

Background: Mesenchymal Stem Cells (MSCs) therapy has become a new coming focus of clinical research in regenerative medicine. However, only a small number of implanted MSCs could successfully reach the injured areas. The previous studies have shown that fracture healing time is inversely proportional to concentration of MSCs in injured tissue. Methods: The migration and osteogenesis of MSCs were assessed by transwell assay and Alizarin Red S staining. Levels of gene and protein expression were checked by qPCR and Western Blot. On the other hand, the enhanced migration ability of MSCs induced by Cyasterone was retarded by CXCR4 siRNA. In addition, the rat model of femoral fracture was established to evaluate the effect of Cyasterone on fracture healing. What's more, we also checked the effect of Cyasterone on mobilisation of MSCs in vivo. Results: The results showed that Cyasteron increased the number of MSCs in peripheral blood. The concentrations of SDF-1α in serum at different time points were determined by ELISA assay. Micro-CT and histological analysis were used to evaluate the fractured femurs.Our results showed that Cyasterone could promote the migration and osteogenesis capacities of MSCs. The fractured femurs healed faster with treatment of Cyasterone. Meanwhile, Cyasterone could significantly increase the level of SDF-1α in rats with femur fracture. Conclusion: Cyasterone could promote migration and osteogenesis of MSCs, and most importantly, it could accelerate bone fracture healing.Translational Potential statement: These findings provide evidence that Cyasterone could be used as a therapeutic reagent for MSCs mobilisation and osteogenesis. What's more, it could acclerate fracture healing.

Abstract Background MicroRNAs (miRNAs) are a class of noncoding small RNAs that play important roles in many physiological processes by regulating gene expression. Previous studies have shown that the expression levels of total miRNAs increase during mouse embryonic development, and some miRNAs control the regulatory network in development progression. However, few studies have focused on the effects of miRNAs on early human embryonic development. The relationship between miRNAs and early human embryogenesis is still unknown. Results In this study, RNA-seq data collected from sperm samples from 102 patients with a normal sperm index but treated with assisted reproductive technology (ART) were analyzed for the relationships between differentially expressed small RNAs and the fertilization rate (FR), blastocyst rate and high-quality embryo rate (HQER). The sperm samples with high hsa-mir-191 expression had a higher FR, effective embryo rate (EER) and HQER. hsa-mir-191 was used as a single indicator to predict the HQER. The receiver operating characteristic (ROC) curve had an area under the ROC curve (AUC) of 0.686. We also found that hsa-mir-191 expression is correlated with an abnormal sperm rate (cor = 0.29, p

The gradual establishment of large-scale distributed camera networks and the rapid development of “Internet +” have resulted in the recent popularization of massive video surveillance systems. As pedestrians are the key monitoring targets in video surveillance systems, many studies are focusing on pedestrian re-identification monitoring algorithms across cameras. At present, the pedestrian re-identification model is not only faced with the difficulty of training the network model due to the huge quantity difference between different types of training samples, but also needs to reduce the impact of the large difference in visual performance on the model identification accuracy. To solve these difficulties, this paper proposed a deep learning model and designed a system based on a deep convolutional neural network for pedestrian re-identification. In particular, we determined the difference between the system input neighborhoods in order to derive the local relationship between the two input images, thus reducing the effects of illumination and perspective. Furthermore, we employed focal loss to solve the phenomenon of sample imbalance in the pedestrian re-identification process in order to enhance the actual application potential of the model. The proposed method was implemented in our developed end-to-end monitoring system for pedestrian re-identification. The hardware component of the system design framework was composed of a digital matrix, streaming media storage server and a network high-speed dome, with the ability to extend to additional tasks in the future. Our approach reduces the effects of data imbalances and visual performance differences, with a score of 76.0% for rank-1 and 99.5% for rank-20 on large data sets (CUHK03), which is not only a significant improvement over the previous IDLA, but also superior to other existing approaches.

With the increasing and diversified Internet of Things (IoT) devices, more IoT heterogeneous wireless networks have emerged, providing more network services for IoT devices, especially mobile phones and other roaming devices. However, there are also some malicious users who use different means to attack the security of the network, so that more users begin to pay attention to the identity authentication and privacy protection of the Internet of Things. This paper designs an IoT node roaming authentication model, which is used to enhance the security authentication capability of the Internet of Things to roaming devices. In order to effectively prevent malicious nodes from connecting to the network, this paper proposes a roaming authentication protocol based on heterogeneous fusion mechanism (HFM-IoT). The authentication protocol uses the remote authentication server in the local and remote areas to perform interactive authentication on the roaming device, which increases the difficulty of attacking or infecting multiple network areas by malicious nodes. According to the security analysis, the protocol can protect against multiple network attacks, and it can be seen from the experimental simulation results that the protocol has lower energy burden and authentication delay.

Abstract A Canadian in situ oilsands bitumen-derived vacuum residue (VR) was subjected to supercritical fluid extraction and fractionation (SFEF) into 13 extractable fractions and an unextractable end-cut and characterized by positive- and negative-ion electrospray ionization (ESI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). The results of negative-ion ESI FT-ICR MS showed that the N1 class species was the most abundant and the multifunctional group compounds, such as N1O1, N1O2, N1S1, N1S2, and N2 class species became abundant as the SFEF fraction became heavier. In positive-ion ESI mode, the relative abundance of N1 class species decreased gradually in the heavy SFEF fractions while that of multifunctional group compounds increased. The relative abundance of N4V1O1 increased dramatically in heavy fractions and the end-cut. The distributions of polar heteroatom species of VR derived from oilsands bitumen were similar with those of VR derived from the Venezuela Orinoco extra heavy oil.

The composition distribution of slurry oil has a significant impact on the structure and performance of the mesophase. In this study, supercritical fluid extraction oil (SFEO) and extraction components were extracted from two slurry oils (SLOs) using the supercritical fluid extraction (SFE) technique. The fundamental properties and composition distribution of two SLOs and associated SFEOs were thoroughly investigated. Electron microscopy and spectroscopic techniques were employed to study the morphology and structures of mesophase pitch produced by carbonizing SLOs and their extraction components under the same conditions. The findings revealed that, compared to SLO–LH, SLO–SH has a higher proportion of 4–5 aromatic rings and a narrower hydrocarbon distribution range. In SLO–LH, O1, N1, and N1O1 molecules with long side chains and poor flatness make up the majority of the heterocyclic aromatic hydrocarbons. The distribution of CH compounds can be narrowed by using supercritical fluid extraction to efficiently separate various heteroatom-containing compounds with a higher condensation degree. After supercritical extraction, the mesophase content, texture distribution, and graphitization degree of the mesophase were improved. Polycyclic aromatic hydrocarbons with high planarity help polymer macromolecules stick together and build up in an orderly way. Heterocyclic aromatic hydrocarbons with high condensation and low planarity, on the other hand, play an important role in the formation of mosaic structures.

MiR-223 is a miRNA with important functions in apoptosis, carcinogenesis, and inflammation, and it was demonstrated to be over-expressed in brain tissue after traumatic brain injury (TBI). However, few studies have focused on its role in protecting brain microvascular endothelial cells (BMECs). This study evaluated the protective effect of miR-223 on BMECs after stretch injury (SI). bEnd.3 cells (BMECs of mouse) were transfected with overexpressing and blocking lentivirus of miR-223, then were subjected to SI. After immunofluorescence assay, it was demonstrated that miR-223 overexpression significantly rescued the SI-induced loss of ZO-1 (Zonula Occludens 1, tight junction protein) (p < 0.01), while miR-223 blocking exacerbated the loss of ZO-1 (p < 0.05). Flow cytometry confirmed a significant increase in the proportion of apoptotic bEnd.3 cells after SI, and miR-223 overexpression reduced this proportion (p < 0.001). The result of Western blot revealed that miR-223 overexpression significantly reduced the expression of cleaved caspase-3 (cl-caspase 3) (p < 0.05) and RhoB (p < 0.01), while miR-223 blocking increased the expression of these proteins (p < 0.05, p < 0.001). Additionally, knockdown of RhoB significantly reduced the expression of cl-caspase 3 (p < 0.001). These findings suggested that miR-223 can alleviate SI-induced apoptosis of BMECs, and this anti-apoptotic effect is at least partially achieved by inhibiting the expression of RhoB. Moreover, miR-223 may play a role in maintaining the integrity of BBB during TBI.

Objective: A reliable prediction of clinical outcome is important for clinicians to set appropriate medical strategies in treating patients with aneurysmal subarachnoid hemorrhage (aSAH). In this study, we aim to establish a perioperative nomogram involving serum lipid signatures for predicting poor outcomes at 3 months in patients with aSAH following endovascular therapy.Methods: Data of patients with aSAH receiving endovascular therapy were collected. Univariable and multivariable analyses were performed to screen independent predictors related to unfavorable outcomes defined by the modified Rankin Scale (mFS) ≥3. A novel nomogram based on these significant features was conducted. The clinical application of this nomogram was assessed by decision curve analysis (DCA) and clinical impact curve.Results: A total number of patients included in this study were 213 (average age 58.9 years, 65.7% female), representing a poor 3-month outcome rate of 48.8%. Free fatty acid (FFA) levels on admission were efficient in predicting poor outcomes compared with other contents in serum lipids. Univariable and multivariable analyses revealed advanced age (P = 0.034), poor Hunt Hess (HH) (odds ratio, OR = 3.7, P < 0.001) and mFS (OR = 6.0, P < 0.001), aneurysms in the posterior circulation (OR = 4.4, P = 0.019), and higher FFA levels on admission (OR = 3.1, P = 0.021) were negative independent predictors of poor 3 months outcome. A novel nomogram composed of these significant features presented a concordance index (C-index) of 0.831 while the practical benefit was validated by DCA and clinical impact curve. An online calculator based on R programming promoted the clinical application of this nomogram.Conclusion: Nomogram involving age, HH grade, mFS, aneurysm location, and serum FFA levels was sufficient to provide an individualized prediction of 3-month poor outcome for each patient with aSAH who underwent endovascular therapy.

Background: We investigated impacts of COVID-19 on cardiac rehabilitation (CR) delivery around the globe, including virtual delivery, as well as effects on providers and patients. Methods: In this cross-sectional study, a piloted survey was administered to CR programs globally via REDCap from April to June 2020. The 50 members of the International Council of Cardiovascular Prevention and Rehabilitation (ICCPR) and personal contacts facilitated program identification. Results: Overall, 1062 (18.3% program response rate) responses were received from 70/111 (63.1% country response rate) countries in the world with existent CR programs. Of these, 367 (49.1%) programs reported they had stopped CR delivery, and 203 (27.1%) stopped temporarily (mean = 8.3 ± 2.8 weeks). Alternative models were delivered in 322 (39.7%) programs, primarily through low-tech modes (n = 226,19.3%). Furthermore, 353 (30.2%) respondents were re-deployed, and 276 (37.3%) felt the need to work due to fear of losing their job, despite the perceived risk of contracting COVID-19 (mean = 30.0% ± 27.4/100). Also, 266 (22.5%) reported anxiety, 241(20.4%) were concerned about exposing their family, 113 (9.7%) reported increased workload to transition to remote delivery, and 105 (9.0%) were juggling caregiving responsibilities during business hours. Patients were often contacting staff regarding grocery shopping for heart-healthy foods (n = 333, 28.4%), how to use technology to interact with the program (n = 329, 27.9%), having to stop their exercise because they have no place to exercise (n = 303, 25.7%), and their risk of death from COVID-19 due to pre-existing cardiovascular disease (n = 249, 21.2%). Respondents perceived staff (n = 488, 41.3%) and patient (n = 453, 38.6%) personal protective equipment, as well as COVID-19 screening (n = 414, 35.2%), and testing (n = 411, 35.0%) as paramount to in-person service resumption. Conclusion: Given the estimated number of CR programs globally, these results suggest approximately 4400 CR programs globally have ceased or temporarily stopped service delivery. Those that remain open are implementing new technologies to ensure their patients receive CR safely, despite the challenges. Highlights: COVID-19 has impacted cardiac rehabilitation (CR) delivery around the globe. In this cross-sectional study, a survey was completed by 1062 (18.3%) CR programs from 70 (63.1%) countries. The pandemic has resulted in at least temporary cessation of ~75% of CR programs, with others ceasing initiation of new patients, reducing components delivered, and/or changing of mode delivery with little opportunity for planning and training. There is also significant psychosocial and economic impact on CR providers. Alternative CR model (e.g., home-based, virtual) reimbursement advocacy is needed, to ensure safe, accessible secondary prevention delivery.

The reversible/irreversible recovery of mechanical properties, and the microstructure characteristics of a typical hot-stamped steel B1500HS have been studied under different conditions of hydrogen permeation. Initially, all tested specimens were permeated by hydrogen atoms through an electrochemical hydrogen charging scheme. Then, the comparisons between different currents and charging time were performed. The influence of different storage time was compared as well. Additionally, the effect of the plastic strain introduced by pre-stretching was also investigated. The experimental results showed that the negative impact of hydrogen embrittlement was altered from reversible to irreversible as the magnitude of the charging current increased. The hydrogen blistering and the hydrogen charging-induced cracks were both observed and inspected in the tested samples regarding the irreversible situation. Moreover, the adverse influence of hydrogen embrittlement was enhanced by plastic pre-straining or extending the charging period. At the micro-level, hydrogen charging-induced cracks generally were generated at defect locations, such as the prior austenite grain boundaries and lath martensite interfaces. Particularly, crack direction occurred perpendicular to the orientation of lath martensite, and transgranular fracture occurred at the prior austenite grains.

Traumatic brain injury (TBI) could highly induce coagulopathy through breaking the dynamic balance between coagulation and fibrinolysis systems, which may be a major contributor to the progressive secondary injury cascade that occurs after TBI. Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) inhibition is reported to exert neuroprotection in TBI, making it a potential regulatory target involved in TBI-induced coagulation disorder. PTEN level is controlled in a major way by E3 ligase-mediated degradation through the ubiquitin–proteasome system. The C terminus of Hsc70-interacting protein (CHIP) has been shown to regulate proteasomal degradation and ubiquitination level of PTEN. In the present study, CHIP was overexpressed and knocked down in mouse brain microvascular endothelial cells (bEnd.3) and tissues during the early phase of TBI. In vitro cell proliferation, cell apoptosis, migration capacity, and invasion capacity were determined. The changes of procoagulant and apoptosis molecules after TBI were also detected as well as the micrangium density and blood–brain barrier permeability after in vivo TBI. In vitro results demonstrated that CHIP overexpression facilitated bEnd.3 cell proliferation, migration, and invasion and downregulated cell apoptosis and the expressions of procoagulant molecules through promoting PTEN ubiquitination in a simulated TBI model with stretch-induced injury treatment. In vivo experiments also demonstrated that CHIP overexpression suppressed post-TBI apoptosis and procoagulant protein expressions, as well as increased microvessel density, reduced hemorrhagic injury, and blood–brain barrier permeability. These findings suggested that the upregulation of CHIP may attenuate apoptosis and procoagulant activity, facilitate brain repair, and thus exerts neuroprotective effects in TBI.

The micro-motional period is an important feature for spatial target discrimination. Firstly, the movement and wideband echo models of wobbling targets with bistatic observations are introduced. Then, the characteristics of the mono-/bi-static high-resolution range profiles (HRRPs) with different polarizations are analyzed based on the simulation echoes of the wobbling target via the electromagnetic calculations. Finally, the observed HRRP sequence is employed to construct a time-range distribution matrix, and an estimation method of the micro-motional period is proposed based on the time-range distribution matrix correlation, which is validated by the measurement experiments in the anechoic chamber.

Vehicle mobile Internet of Things uses sensor technology, mobile Internet technology, and intelligent computing technology to effectively monitor and provide comprehensive services for vehicle operation status. It is an important part of building a smart city, making urban transportation more efficient, environmentally friendly, intelligent, and safety. In the vehicle mobile Internet of Things, when in-vehicle sensors are in communication with each other, they are often affected by factors, such as network mobility, transmission range, and signal interference. Therefore, in order to ensure the continuity of communication between nodes and improve the quality of network communication, this paper proposes a vehicle mobile Internet of Things coverage enhancement algorithm (PANM). First, we derive the probabilistic analysis model of communication duration by analyzing the functional relationship of vehicle initial velocity, acceleration, spacing distance, and communication duration. Then, under the premise of ensuring the communication duration, in order to improve the coverage of the vehicle mobile Internet of Things, the network overlap ratio is introduced in the probability analysis model. Finally, we improve the network coverage performance of omnidirectional radiation and fan-shaped radiation communication models of vehicle mobile Internet of Things by limiting the overlap ratio threshold. The experimental simulation results indicate that the PANM algorithm can reduce the packet loss rate of the vehicle network and have a shorter communication delay.

Object: Primary osteoporosis (PO) is the most common bone disease, which is characterized by decreased bone mass, damage of bone tissue microstructure, increased bone fragility, and is prone to fracture. Gut microbiome may be involved in bone metabolism of PO through gut–brain axis regulation of immune system and endocrine system, however, the specific mechanism is still unclear. The purpose of this study was to characterize the gut microbiome of patients with PO and its possible role in the occurrence and development of the disease.Methods: Fecal samples were collected from 48 PO patients and 48 healthy controls (HC). The composition of gut microbiome community was analyzed by 16s rDNA amplification sequencing, and the difference of gut microbiome composition between PO patients and HC individuals was compared. PICRUSt was also used to predict the biological function of gut microbiome in patients with PO, and to explore its possible role in the occurrence and development of this disease. The classification model is constructed by random forest algorithm so as to screen the key biomarkers.Result: The diversity of gut microorganisms in PO patients was significantly higher than that in HC group (p < 0.05) and there was significant difference in microbial composition in PO group. The abundance of Dialister (0.036 vs. 0.004, p < 0.001) and Faecalibacterium (0.331 vs. 0.132, p < 0.001) were significantly enriched which were the key flora related to PO. Although no significant correlation between bone mineral density and the richness of microbial communities are found, PICRUST results show that there are a wide range of potential pathways between gut microbiome and PO patients, including genetic information processing, metabolism, environmental information processing, cellular processes, human diseases, and organic systems. Notably, the discriminant model based on dominant microflora can effectively distinguish PO from HC (AUC = 93.56).Conclusions: The findings show that PO is related to the change of gut microbiome, especially the enriched Dialister and Faecalibacterium genera, which give new clues to understand the disease and provide markers for the diagnosis and new strategies for intervention treatment of the disease.

Passive radar based on the global navigation satellite positioning system (GNSS) has become the focus of attention in the field of radar. A parameter estimation method is proposed in the forward scatter radar (FSR) network based on GNSS to extend the application scenarios. For uniformly accelerating moving targets, only the instant times when the target crosses the individual baselines are used to retrieve the target motion parameters. The target position, velocity, and acceleration information can be obtained. Firstly, the minimum network configuration is derived theoretically. Then, the effects of crossing time error, station location error, transmitting/receiving station deployment, and target height on the accuracy are analyzed through Monte Carlo simulations. Finally, the simulation results indicate that the target position estimation error is in the order of 100 m. This paper provides the fundamental theory of aerial target positioning with a GNSS-based FSR network.

Oral squamous cell carcinoma (OSCC) is one of the most common head and neck malignancies. Advanced stages of the disease are associated with poor survival, highlighting a need for new treatment modalities. We previously showed that the proinflammatory cytokine interleukin‐18 (IL‐18) has a tumor suppressive role in OSCC. Here, we investigated the effects of IL‐18 on proliferation, migration, and invasion of OSCC cells ex vivo and in vitro, and in nude mouse xenografts. We report that expression of tankyrase 2 (TNKS2), β‐catenin, and N‐cadherin was higher in tumor cells than in normal mucosae, whereas the expression of IL‐18 and E‐cadherin was higher in normal than in tumor tissues. Elevated expression of IL‐18 (P

Diesel engine has attracted much attention because of its good power performance, fuel economy, reliability and durability, but the exhaust gas containing soot has significant impact on environment and human health. Catalyzed diesel particulate filter (CDPF) that reduces the activation energy of soot oxidation by catalysts are used to eliminate soot. In this work, MFe _2 O _4 spinel (M = Cu, Ni and Co) was synthesized by sol-gel method to catalyze the oxidation of soot. The characterization results of MFe _2 O _4 showed that CuFe _2 O _4 possessed the smallest average grain size (65.6 nm) and the best redox performance. The activity tests of the catalysts showed that the activity order of the catalyst is CuFe _2 O _4 (330 °C > CoFe _2 O _4 (411 °C > NiFe _2 O _4 (464 °C. DFT results showed that soot is more easily adsorbed on the O-terminal surface of CuFe _2 O _4 and reacts with oxygen vacancies, resulting in the promotion of soot oxidation by the diffusion of oxygen from the inside to the surface. It also proves that CuFe _2 O _4 has the best catalytic effect on soot.

Imaging radar is widely applied in both military and civil fields, including remote sensing. In recent years, polarization information has attracted more and more attention in the imaging radar. The orthogonality between different channels is always the core problem for the full-polarization imaging radar. To solve this problem, an image reconstruction method using orthogonal coding apertures technique is proposed for full-polarization imaging radar in this paper. Firstly, the signal model of the orthogonal coding apertures is proposed. This model realizes the ideal time-domain orthogonality between switching two channels by the apertures with two trains of orthogonal codes. Then, a multichannel joint reconstruction method based on compressed sensing is proposed for the imaging processing, which is named the coded aperture simultaneous orthogonal matching pursuit (CAS-OMP) algorithm. The proposed algorithm combines the information of all polarization channels so as to ensure the consistency of the scattering point position obtained by each polarization channel and also improves the reconstruction accuracy. Finally, the simulation experiments using both the simple scaled model of the satellite and measured data of an unmanned aerial vehicle (UAV) are conducted, and the effectiveness of the proposed method is verified.

The scattering mechanisms of dihedral corner reflectors have attracted great attention in the past decades. However, the scattering centers of dihedral corners are not discussed systematically. In this paper, the multi-bouncing scattering mechanism of dihedral corners is analyzed in detail based on the scattering characteristics of polygon plates and ray-tracing technique. Furthermore, the coupling scattering center (CSC) is proposed as a detailed explanation of the multi-bouncing scattering mechanism of dihedral corners and the locations of CSCs in the high-resolution range profile are deduced based on the monostatic-and-bistatic equivalence theorem. CSCs give a precise description of target structures and can improve the ability of radar target recognition. Finally, the simulation results via electromagnetic computation validate the theoretical analysis.

Abstract Background Sesamin is a well-known antioxidant extracted from sesame seeds that exhibits various curative effects. The present study investigated whether sesamin would protect neuroblastoma SH-SY5Y cells against mechanical stretch injury-induced increases in reactive oxygen species (ROS) and apoptosis. Additionally, the mechanisms underlying these actives were investigated. Following exposure to mechanical stretch injury, cells were incubated for further investigations. Lactate dehydrogenase and Cell Counting Kit-8 assays were used to assess cell viability, and a terminal deoxynucleotidyl transferase dUTP nick end labeling assay and flow cytometric analysis were performed to evaluate changes in mitochondrial membrane potential (ΔΨm). Furthermore, intracellular levels of ROS production were measured by 20, 70-dichlorofluorescein diacetate staining, the mRNA levels of matrix metallopeptidase 9 (MMP-9) were evaluated using real-time polymerase chain reaction analysis, and the determinations had also been made on related proteins by Western blot analysis. Results Exposure to mechanical stretch injury significantly decreased cell viability but this decrease was attenuated by pretreatment with sesamin (50 μM). Sesamin also significantly inhibited mechanical stretch injury-induced increases in intracellular ROS production, attenuated declines in ΔΨm, diminished the expressions of pro-apoptotic proteins, and decreased cell apoptosis. Stretch injury increased Bax and cleaved caspase 3 levels, enhanced the gene expression of MMP-9, increased the phosphorylation levels of Akt, p38, and JNK and decreased Bcl-2 levels in the cells. However, pretreatment with sesamin reduced the mechanical stretch injury-induced overexpression of MMP-9. Conclusions Sesamin protected SH-SY5Y cells against stretch injury by attenuating increases in ROS levels and suppressing apoptosis. Accordingly, sesamin seems to be a potentially therapeutic agent in the treatment of traumatic brain injury.