Search

This study intends to investigate the mechanism by how microRNA (miRNA)-23b alleviates kidney damage in septic rats. Herein, septic rat model, control group and sham-operated model were set up to assess kidney tissue damage. Tissues were extracted from the rats and isolated into cells. Then cells were transfected with plasmids expressing miR-23b followed by analysis of the expression of miR-23b, Smad3, TLR4, HMGB1 and autophagy-related proteins (LC3, beclin-1) by western blot and RT-qPCR. The level of TNF-α, IL-6 and BUN and SCr were elevated in the model group and decreased after upregulation of miR-23b with increased LC3-II, Smad3 and Beclin-1 expression. miR-23b mimic group showed highest miR-23b expression followed by miR-23b NC group and miR-23b inhibitor group. The levels of TLR4, and HMGB1 and positive rate of NF-κBp65 in miR-23b mimic group were significantly lower than those in miR-23b inhibitor group (p < 0.05). Importantly, miR-23b directly targeted Smad3 and inhibited its expression. In conclusion, overexpressed miR-23b induces autophagy by promoting Smad3 expression, alleviates kidney damage in septic rats, and reduces inflammation and inactivates NF-κB signaling pathway.

Benefit from multi-scale feature pyramid methods, recently single-stage object detectors have achieved promising accuracy and fast inference speed. However, the majority of existing feature pyramid detection techniques only simply describe complex contextual relationships from different scales. Not only are there no effective modules that adaptively extend appropriate semantic information from deeper layers, but the finer spatial localization cues from lower layers are often ignored. In this paper, we present a Local Enhancement and Bidirectional Feature Refinement Network (LFBFR), which includes two optimization methods to achieve remarkable improvements in detection accuracy. Firstly, to make the backbone more suitable for detection task, we modify the pre-trained classification backbone to mitigate the loss of details in small objects due to consecutive decrease of the image resolution. Then we propose a Bidirectional Feature Refinement Pyramid, which can effectively utilize the inter-channel relationship of higher-level features and fine appearance cues from lower-level features by using the attention residual refinement module and the feature reuse module. Ultimately, to assess the performance of the proposed LFBFR, we design a powerful end-to-end single-stage detector called LFBFR-SSD by embedding it into the framework of SSD. Extensive experiments on the PASCAL VOC and MS COCO verify that our LFBFR-SSD outperforms a lot of state-of-the-art detectors while maintaining a real-time speed.

With the widespread application of Internet of things (IoT), the interference problem becomes more and more serious, which results in not only the poor network performance but also the increased energy consumption of IoT nodes. Therefore, in this paper, we investigate the problem of how to locate the interference sources and infer their communication relationships in the cognitive radio IoT (CR-IoT) deployment scenario. First, we utilize MDS-MAP(P) algorithm with dynamic power control to realize cooperative self-localization of the CR-IoT nodes, which is more energy-efficient than all the IoT nodes equipped with global positioning system (GPS) receivers. Then, we propose a non-cooperative localization method to determine the inference sources with the angle of arrivals (AoAs) measured by the CR-IoT nodes. Finally, the communication relationship between interference sources can be inferred based on the association rule of signals. The network simulation results validate that the proposed methods can locate the interference sources accurately with low energy consumption and correctly infer their communication relationships, which is helpful for the interrupted CR-IoT nodes to take a specific opportunistic transmission policy to reduce their energy consumption.

In heterogeneous environments, the Internet of Things (IoT) combined with mobile ad hoc network (MANET), i.e., MANET-IoT network, becomes more attractive to end users and economically successful. However, the introduction of MANET potentially makes the system more prone to attacks due to its lack of centralized management, weak connectivity, and resource constraints. To enhance the network robustness to intentional attacks, the critical nodes of the MANET-IoT network should be firstly identified and then protected. Most of the existing methods for identifying critical nodes usually focus on static networks or a single topology snapshot in dynamic networks without considering the correlation between topology snapshots, which cannot effectively deal with the dynamic changes in the topology of MANET-IoT networks. In this paper, a dynamic critical node identification (DCNI) method is proposed. First, we propose a comprehensive metric to measure the node importance in the topology snapshot. Then, we introduce a sliding time window to filter out the topology snapshots which have a close correlation with the current snapshot, and fuse the importance values of the same node in different topology snapshots. Finally, the critical nodes are selected based on the ranking result of fused importance. Thereafter, the port hopping mechanism could be applied to the critical nodes for enhancing network defense capability. The simulation results show that the proposed method is more effective in identifying critical nodes than existing static methods in MANET-IoT networks, and the port hopping mechanism can improve network defense significantly to denial of service (DoS) attacks.

Important location inference is one of the main content in location big data intelligence mining, and it has important application value in tracking target users and LBA. This paper takes regional ID type location data as input. Aiming at the problem that the current inference methods based on the frequency statistics of the work and rest periods do not take into account the difference in user time activity rules, the accuracy of the inference is poor, and a personal important location inference method based on the time state distribution is proposed. The method first divides the mobile user's work and rest time period, and then estimates the parameters of the state distribution of the user registration time in each base station area. Finally, match the estimated result with the work and rest time period and output the home or work label to complete the inference of personal important locations. The experimental results show that compared with the frequency statistics method, this method has higher accuracy rate and lower parameter estimation error, and it has certain reference significance for the inference of personal important locations with regional ID type location as input.

As the demand for location services increases, research on location technology has aroused great interest. In particular, signal-based fingerprint location positioning technology has become a research hotspot owing to its high positioning performance. In general, the received signal strength indicator (RSSI) will be used as a location feature to build a fingerprint database. However, at different locations, this feature distinction may not be obvious, resulting in low positioning accuracy. Considering the wavelet transform can get valuable features from the signals, the long-term evolution (LTE) signals were converted into wavelet feature images to construct the fingerprint database. To fully extract the signal features, a two-level hierarchical structure positioning system is proposed to achieve satisfactory positioning accuracy. A deep residual network (ResNet) rough locator is used to learn useful features from the wavelet feature fingerprint image database. Then, inspired by the transfer learning idea, a fine locator based on multilayer perceptron (MLP) is leveraged to further learn the features of the wavelet fingerprint image to obtain better localization performance. Additionally, multiple data enhancement techniques were adopted to increase the richness of the fingerprint dataset, thereby enhancing the robustness of the positioning system. Experimental results indicate that the proposed system leads to improved positioning performance in outdoor environments.

Security risk assessment is an important part of network security operation. The existing risk assessment methods are mainly divided into qualitative assessment, quantitative assessment and comprehensive assessment. This paper summarizes the advantages and disadvantages of related methods through analyzing, and provides certain assistance for the assessors to choose methods when implementing assessment.

Green pepper automatic picking has been a long-standing challenge in agriculture due to the similar color between green peppers and green leaves. To tackle this intractable problem, we tried to distinguish between them by using hyperspectral information as prior knowledge. As our core insight, a novel optical filter was designed as a pre-processing tool to find valuable wavelengths where peppers differ a lot from leaves. To this end, firstly, the parameters of the optical filter were learned by end-to-end training with a neural network for pixel-wise hyperspectral input. Secondly, the learned optical filter was applied to hyperspectral data to obtain filtering RGB images, which will be sent to further segmentation framework. Thereby, a two-stage method for green pepper segmentation was proposed, and promising results were achieved owing to the incorporation of the optical filter.

Identifying critical nodes from the point of view that destructiveness equals to criticality, the traditional identification methods usually consider the degree of damage but does not analyze the type of damage. The critical nodes identified have a certain universality, but the pertinence is not strong. In this paper, a critical node identification method based on the analysis of network partition for Ad Hoc network is proposed. Firstly, the Kernighan-Lin algorithm is applied to group the nodes in the network, and then the boundary nodes between different groups are selected from the grouping results. Finally, the boundary nodes are re-screened by combining the node’s degree value to select the nodes that can lead to the partition of the network. The experimental results show that the failure of identified critical nodes can directly lead to network partitioned into multiple subnets, destroy the connectivity of the network seriously.

The environmental risk controllability assessment system and its method of controlling volatile organic compounds (VOCs) during remediation of contaminated sites are established in this article based on soil vapor extraction (SVE) technology. According to the properties of VOCs and the technical and operational characteristics of the site remediation process, the environmental risk controllability index system includes environmental risk identification, risk source analysis, and risk assessment. Environmental risk management during site remediation was focused on technical control methods and engineering control technologies. Specifically, acceptance based on risk management was suitable for low-risk levels such as RRI3 and RRI4. Furthermore, control methods for high-level risk (RRI1 or RRI2) could be developed along with transformation and control, combined with the necessary emergency risk plan.

The PaaS platform based on cloud computing technology provides a large number of professional and flexible services in the fields of intelligent voice and computer vision. The large-scale application of 5G technology enables the software and hardware of the Internet of Things to use the PaaS service to improve the intelligence level of the system and reduce development costs. However, the problem of service invocation and service selection in the process of combining the IoT system with multiple PaaS platforms directly affects the interaction between the IoT perception layer and the application layer. This paper proposes a 5G multi-PaaS-oriented IoT dual middleware model. The unified communication protocol DMCP is designed. DMCP implements unified parsing of messages based on variable-length data items, which reduces the protocol conversion between the perception layer terminal device and multiple PaaS platforms. Complexity and high communication efficiency. Designed the PaaS service selection algorithm DMPS, DMPS comprehensively according to the equipment demand preferences and the overall performance of PaaS services, to achieve accurate service selection in the multi-PaaS platform at the application layer. Finally, examples and comparative tests verify the feasibility and effectiveness of the proposed model, protocol and algorithm.

Ubiquitous power Internet of things is an important direction of the development of smart grid, and distribution Internet of things is the application of ubiquitous power Internet of things in the field of distribution. As the terminal unit of state perception, intelligent decision-making and control subject in the distribution Internet of things, intelligent distribution and transformation terminal is the foundation to realize the distribution Internet of things. In order to solve the problems of complex software architecture of traditional distribution and transformation terminal, which is not conducive to expansion, maintenance and transplantation, Microservice + container technology is adopted as the software architecture of intelligent distribution and transformation terminal, which reduces the complexity of development, improves the efficiency of operation and maintenance, and meets the diverse and rapidly changing service requirements of distribution network.

Since sea clutter samples are often contaminated by high-intensity outliers, target detection in nonhomogeneous sea clutter environments is challenging. An adaptively truncated clutter-statistics-based variability index constant false-alarm-rate (TSVI-CFAR) detector of Gaussian clutter in synthetic aperture radar (SAR) imagery is proposed. The proposed method is designed to improve the CFAR detection performance in a heterogeneous multitarget environment. TSVI-CFAR consists of three stages, i.e., clutter truncation, statistical parameter estimation, and CFAR detection. In the clutter truncation stage, the high-intensity outliers in the background window are eliminated through an adaptive threshold-based clutter truncation method. In the statistical parameter estimation stage, the parameters can be accurately estimated through the maximum-likelihood estimator. In the detection stage, the clutter background is categorized using the adaptively truncated clutter. Different types of CFAR detection methods are applied to the pixels under test of the categorized backgrounds. TSVI-CFAR has a higher detection rate and a low observed false alarm rate. The effectiveness of the proposed algorithm is demonstrated using Gaofen-3 SAR data and Envisat-ASAR data.

Topology is the basis of connectivity analysis and critical nodes identification for Ad Hoc network. The existing methods of topology inference are divided into two types: cooperative and non-cooperative. The cooperative inference methods are usually based on the premise of network access. It usually needs to send a large number of detection packets, and the operation cost is large. The non-cooperative inference methods are usually based on the analysis of a large number of detection data, but the data acquisition is difficult and takes a long time. From the view of coverage, this paper inferred the physical topology of Ad Hoc network with critical transmission distance under the condition that the location information and the number of nodes, the size of the deployment area are known. The simulation results on Exata demonstrate the feasibility of the inference method.

Exata has excellent performance in wireless communication, but in the process of Ad Hoc network simulation, it can not realize the inference and visualization of network topology. In this paper, we analyze the AODV protocol, and use the information contained in the RREP message to realize the inference of the network topology. The experimental results prove the feasibility of the method.

Critical nodes have global significance for the network, the existing methods on the identification of critical nodes in Ad-hoc network usually based on the premise of topology is known, considering that there exists a link if the two nodes are in the other’s communication range, so the topology we get at last is relatively complex, but there are many links that aren’t exist in real which leading the identification of critical nodes with deviation. For this problem, in the paper we used Delaunay triangulation to optimize the network topology, based on identifying virtual backbone nodes by the unified connected dominating set, we measured the importance of the nodes by the average betweenness centrality. Experimental results show that the method proposed can identify the critical nodes in Ad-hoc networks effectively.

Multi-class classification algorithm of support vector machine (SVM) has always been a research hotspot. A new multi-class SVM algorithm, naming recall reordering adaptive directed acyclic graphs (RRADAG), is proposed from the perspective of error detection to solve the error accumulation existed in multi-class SVM algorithm of which is based on Directed Acyclic Graphs (DAG). By detecting the output of the classifier and recalling the possible error decision, RADAR has solved the problem of error accumulation. The experimental results generated on UCI standard data sets show that RRADAG outperforms the previously existing algorithms on accuracy.

In this paper, a novel lost packets recovery scheme which encrypts the effective parts of an original packet into two shadow packets based on (2, 2)-threshold XOR-based visual Secret Sharing (VSS) is proposed. The two shadow packets used as watermarks would be embedded into two normal data packets with digital watermarking embedding technology and then sent from one sensor node to another. Each shadow packet would reveal no information of the original packet, which can improve the security of original packet delivery greatly. The two shadow packets which can be extracted from the received two normal data packets delivered from a sensor node can recover the original packet lossless based on XOR-based VSS. The Performance analysis present that the proposed scheme provides essential services as long as possible in the presence of selective forwarding attack. The proposed scheme would not increase the amount of additional traffic, namely, lower energy consumption, which is suitable for Wireless Sensor Network...

The sea-crossing bridge construction takes orders the design idea of maximization, the factorization, the standardization and the assembly, which pile caps and pier shafts of the non-navigable span are prefabricated at the focus of prefabricated. In the paper, the precast solutions are put forward to pile caps and pier shafts of the non-navigable span, and the key technical problems of all kinds of precast solutions are analyzed. On this basis, the optimal pier factory prefabrication is proposed by the comparison of various schemes, which is carried out about advantages and disadvantages of prefabricated matching accuracy control, factory prefabrication, concrete placing, transport in the precast yard, transport style and the impact on follow-up construction.

The cracking and deformation analysis of concrete tunnel segment in the jacking process is made by ANSYS. First, we analyzed the effect of such measures as placing a hydraulic jack between the section and rail beam sliding plane described in the four sliding rails scheme upon the cracking and deformation of segment concrete, then the influence of change in spacing of two sliding rails at the same side on the cracking and deformation of segment concrete stated in the six sliding rails scheme. Meanwhile, we made a comparison between the two layout schemes, thereby providing a basis and reference for the layout scheme of sliding rails in the practice.

Caisson is a commonly used foundation in modern bridge engineering. When the caisson is sinking towards the seabed, it will suffer from the coupled effects of wind, current and its mooring system, under which an intense horizontal oscillation might occur. The mechanism of this kind of oscillation can be concluded as Vortex Induced Motions (VIM) of a large floating object in resilience mooring system. In this paper, through numerical simulation of the viscous flow field around a certain caisson, the mechanism of vortex shedding under different current velocity is discussed.

In the paper, relying on the full-scale model test of embedded pile cap of the HZM Bridge, the method of combining the theoretical calculation analysis and in-situ monitoring test are used to study the slope stability and over-break depth of foundation excavation. In the theoretical calculation analysis, an empirical formula of the Hydtology of Sea-port is adopted for the over-break depth while the G-slope software is for the safety factor of slope stability; in the in-situ monitoring test, the single-beam is used for the topographic survey underwater at random after the foundation excavation. Analysising on the theoretical calculation analysis and the result of in-situ monitoring test, proper slope ratio and over-break depth of pile cap foundation excavation is put forward to provide key construction parameters for the main project of the HZM Bridge.

Objective The purpose of this research was mainly two-fold: first, to get an understanding of current researches conducted on Alzheimer disease in China; second, to systematically evaluate and compare Alzheimer's treatment delivered by traditional Chinese medicine (TCM) and Western medicine. Methods Two steps were employed in this research. They were data collection and cleaning, followed by systemic review and qualitative analysis. The data were selected from the following two databases: CNKI (http://www.cnki.net) and Wanfang Data (http://www.wanfangdata.com.cn). Inclusion criteria were: (1) Chinese literature; (2) Published between year 1994 and year 2004; (3) Using TCM as treatment and Western medicine as control; (4) Similar research purposes and methodology; (5) Subjects were diagnosed as Alzheimer disease. Descriptive analysis, homogeneity test, meta analysis, sensitivity analysis and subgroup analysis were performed in the second step. Results Supposing all qualified studies were of high quality, we got the following conclusion: the advantage of TCM was losing because of the newly-developed acetylcholinesterase inhibitors came in market. Moreover, the studies conducted after year 2002 were more homogeneous in comparison with those conducted in early years. Those studies using mini-mental status examination (MMSE) as outcome measurement were also more homogeneous than non-MMSE measurement groups. Combined odds ratio in comparative studies was 1.5 fold higher than that in experimental studies. Regarding to different outcome measurement, those studies using TCM assessment profile were 2.58(4.79/1.86) fold higher than those using MMSE as outcome measurement. Conclusions After systemic literature search, we found that only 40 out of 2,403 studies met our inclusion criteria. Moreover, those qualified studies were of low quality. Therefore, the external validity of this study would be compromised. The solution to this would be to improve study quality by strengthening study design and carefully select more homogeneous subjects in terms of syndrome differentiation, by so doing, the results of meta analysis will be more convincing and easily recognized by international society.

In order to obtain optimum decision making in selecting main diesel engine for ships, the life cycle cost technology is proposed. The breakdown structure and calculation model of life cycle cost for main diesel engine of ships are established. Taking a specific selection for main diesel engine of one ship as the instance, the purchase cost and life cycle cost for three types of main diesel engine are compared and analyzed. The type of main diesel engine is selected based on the calculation result of life cycle cost. The instance shows that the life cycle cost technology is a powerful decision-making tool, which is worthy of popularization and application in ship design and development stages.

Dynamic responses of a heavy cycloidal object hanged by a large floating crane in the process of immersing into waves were studied experimentally and numerically in this paper. A floating crane with displacement of 14000t was selected as the reference. A model with the scale of 1:20 was conducted in a towing tank. The movement responses and forces of the heavy cycloidal object in the process of immersing in waves were researched. Ocean engineering construction is always affected significantly by waves, so the selection of a shield to attenuate incoming waves is an important aspect for ocean engineering construction. The sea condition in our project is 3-state sea condition; it’s not an acceptable condition for real construction considering safety of crews and the ability of equipments. So an effective floating breakwater validated experimentally in a towing tank in our project was proposed as effective shields. The steel cylinder lifted by a floating crane in the process of water-entering was experimented, the movements of the steel cylinder and the subjected forces of the hoist were recorded; the effects of different shields on the responses of steel cylinder with different depth in water were studied. Numerical simulations of the motion of steel cylinder subjected to waves in the process of immersing were conducted to illustrate the effects of headings. The basis of model design, model-making and measurement methods are also introduced in this paper. The results are translated into full scale results which will be the basis for safety construction of ocean engineering and measurement proposed for accurate positioning and installation of the steel cylinder.

As the development of ocean engineering, safety construction is becoming a significant aspect that attracted more and more attention. The general aims of this paper were to present the effects of different floating breakwater on wave absorbing and provide a basis for the design of floating breakwater of an offshore project. Three different kinds of floating breakwater were studied; they are soft wall-sided pontoon, solid wall-sided pontoon and a circular cross-section breakwater filled with water. Various factors including wave period, wave steepness and geometrical characteristics were considered. The results had shown that the three proposed floating breakwater revealed favorable performance and the geometrical configuration could impact wave attenuation significantly. The circular cross-section breakwater had greater effects on wave absorbing compared with two other floating breakwaters, more detailed experiments were conducted to the circular cross-section breakwater, a V-shaped floating breakwater consists of two single circular cross-section breakwater were studied, the effects of angle of the two singles, wave period and wave height were considered. The results revealed that the geometrical configuration and water depth could impact wave attenuation and mooring force significantly. Researches are expected to offer some information for the design of floating breakwater for an offshore project.Copyright © 2014 by ASME

AIM: To study the role of hepatic sinusoidal capillarization and perisinusoidal fibrosis in rats with alcohol-induced portal hypertension and to discuss the pathological mechanisms of alcohol-induced hepatic portal hypertension. METHODS: Fifty SD rats were divided into control group (n=20) and model group (n=30). Alcoholic liver fibrosis rat model was induced by intragastric infusion of a mixture containing alcohol, corn oil and pyrazole (1 000:250:3). Fifteen rats in each group were killed at wk 16. The diameter and pressure of portal vein were measured. Plasma hyaluronic acid (HA), type IV collagen (CoIV) and laminin (LN) were determined by radioimmunoassay. Liver tissue was fixed in formalin (10%) and 6-μm thick sections were routinely stained with Mallory and Sirius Red. Liver tissue was treated with rabbit polyclonal antibody against LN and ColIV. Hepatic non-parenchymal cells were isolated, total protein was extracted and separated by SDS-PAGE. MMP-2 and TIMP-1 protein expression was estimated by Western blotting. RESULTS: The diameter (2.207 ± 0.096 vs 1.528 ± 0.054 mm, P