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Asthma is characterized by inflammation and remodeling of the airways. Insulin‑like growth factor-1 (IGF‑1) serves an important role in the repair of lung tissue injury and airway remodeling by elevating collagen and elastin content, increasing the thickness of smooth muscle and promoting the proliferation of lung epithelial and interstitial cells, as well as fibroblasts; however, the content of IGF‑1 and its cellular origin in the lungs of patients with asthma remain unknown. In the present study, a mouse model of asthma was constructed. Following isolation of alveolar macrophages (AMs), the content of IGF‑1 in lung tissue and bronchoalveolar lavage fluid (BALF) was detected by ELISA. The proliferation and phagocytosis of alveolar epithelial cells (AECs) stimulated by IGF‑1 were detected by Cell Counting Kit‑8 method and flow cytometry, respectively. In the present study, IGF‑1 was upregulated in the lung tissues of asthmatic mice, and the content of IGF‑1 in BALF was also elevated. Depletion of AMs by treating mice with 2‑chloroadenosine via nose dripping reversed the increase of IGF‑1 by 80% in lung tissues and by ~100% in BALF of asthmatic mice, suggesting that elevated IGF‑1 in asthmatic mice predominantly originated from AMs. As IGF‑1 promotes the proliferation and phagocytosis of AECs, AM‑derived IGF‑1 may serve an important role in the regulation of airway inflammation and remodeling in asthmatic mice.

Vascular endothelial growth factor (VEGF) promotes angiogenesis during tumor growth, and its expression involves multiple signaling pathways and transcription factors. In the present study, transforming growth factor (TGF)‑β1 promoted upregulation of VEGF and downregulation of microRNA (miR)‑20b expression in mouse H22 hepatocellular carcinoma cells. miR‑20b negatively regulated both constitutive VEGF expression and TGF‑β1‑induced VEGF expression. The miRanda algorithm predicted that a binding site of the miR‑20b GCAAUCUGGGCACUUU sequence was present in the signal transducer and activator of transcription (STAT)3 3'‑untranslated region. Following transfection of miR‑20b mimics into H22 cells, expression of STAT3 protein was downregulated. A dual‑luciferase activity assay revealed that miR‑20b directly targeted STAT3 to regulate its expression, and that interference with STAT3 expression significantly downregulated VEGF mRNA and protein expression. Interference with STAT3 expression resulted in increased VEGF expression in H22 cells overexpressing miR‑20b, but expression was lower than that in quiescent H22 cells. This indicated that STAT3 was involved in the negative regulation of VEGF expression in H22 cells by miR‑20b. The data demonstrated that miR‑20b negatively regulated VEGF expression by directly targeting STAT3 in H22 cells.

miR-20b is a member of the miR-106a-363 gene cluster, located on the X chromosome. miR-20b regulates the expression of multiple genes in vivo and it is closely related to the occurrence and development of many diseases. These diseases include inflammatory diseases and tumor development, amongst others. However, few studies have focused on the regulation of the miR-20b gene itself. In this study, we are using the miRBase database to obtain the upstream 2000 bp sequence of the miR-20b precursor. Bio-informatics software P-MATCH 1.0 and AliBaba2 werethen used to predict transcription factor binding in the upstream region. Sp-1 was identified as one of the most probable transcription factors regulating miR-20b gene expression. After treatment with a Sp-1 siRNA, the expression of miR-20b was significantly increased in RAW264.7 cells, as well as peritoneal and alveolar macrophages. In addition, the interference with Sp-1 gene expression also reversed the decrease in miR-20b expression in RAW264.7 cells induced by TNF-α. These results indicate that Sp-1 negatively regulates the expression of miR-20b in macrophages. This finding suggests the potential of Sp-1 as a target for therapies in diseases that are associated with miR-20b overexpression.

For aim to find a simple multiple configuration solution and achieve higher refractive efficiency, and based on to reduce the situation disturbed by FOV change, especially in a two-dimensional spatial expansion. Coded aperture system is designed by these special structure, which includes an objective，a coded component，a prism reflex system components, a compensatory plate and an imaging lens．Correlative algorithms and perfect imaging methods are available to ensure this system can be corrected and optimized adequately. Simulation results show that the system can meet the application requirements in MTF, REA, RMS and other related criteria. Compared with the conventional design, the system has reduced in volume and weight significantly. Therefore, the determining factors are the prototype selection and the system configuration.

For aim to find an effective method to structure to enhance these adaptive system with some complex function and look forward to establish an universally applicable solution in prototype and optimization. As the most attractive component in adaptive system, wave front corrector is constrained by some conventional technique and components, such as polarization dependence and narrow working waveband. Advanced configuration based on a polarized beam split can optimized energy splitting method used to overcome these problems effective. With the global algorithm, the bandwidth has been amplified by more than five times as compared with that of traditional ones. Simulation results show that the system can meet the application requirements in MTF and other related criteria. Compared with the conventional design, the system has reduced in volume and weight significantly. Therefore, the determining factors are the prototype selection and the system configuration, Results show their effectiveness.

A system method of constructing stereo vision by using neural network is proposed, and the operation and control mechanism in actual operation are proposed. This method makes effective use of the neural network in learning and memory function, by after training with samples. Moreover, the neural network can learn the nonlinear relationship in the stereoscopic vision system and the internal and external orientation elements. These considerations are Worthy of attention, which includes limited constraints, the scientific of critical group, the operating speed and the operability in technical aspects. The results support our theoretical forecast.

Bronchial asthma is a common chronic airway inflammatory disease. MicroRNAs (miRNAs) play an important role in the pathogenesis of asthma. We have previously shown that miR-20b can inhibit airway inflammation in asthmatic mice, but the exact mechanism is unknown. In the present study, we show that administration of nasal drops containing miR-20b induced an increase in the percentage of Gr1

Safety and energy efficiency are two of the key issues in the maritime transport community. A sail plan system, which combines the concepts of weather routing and voyage optimization, are recognized by the shipping industry as an efficient measure to ensure a ship’s safety, gain more economic benefit, and reduce negative effects on our environment. In such a system, the key component is to develop a proper optimization algorithm to generate potential ship routes between a ship’s departure and destination. In the weather routing market, four routing optimization algorithms are commonly used. They are the so-called modified Isochrone and Isopone methods, dynamic programming, threedimensional dynamic programming, and Dijkstra’s algorithm, respectively. Each optimization algorithm has its own advantages and disadvantages to estimate a ship routing with shortest sailing time or/and minimum fuel consumption. This paper will present a benchmark study that compare these algorithms for routing optimization aiming at minimum fuel consumption. A merchant ship sailing in the North Atlantic with full-scale performance measurements, are employed as the case study vessels for the comparison. The ship’s speed/power performance is based on the ISO2015 methods combined with the measurement data. It is expected to demonstrate the pros and cons of different algorithms for the ship’s sail planning.

Ocean crossing ship structures are continuously suffering from wave loads when sailing at sea. The wave loads cause large variation of structural stresses, leading to fatigue accumulation in ship structures. For the fatigue life prediction of ship structures, it is important to obtain both the long-term distribution and the time history of wave-induced loads. An essential step is to get reliable wave statistics and accurate description of the stochastic nature of sea state along a ship's sailing routes during her service time. Generally, the wave statistics are provided by the classification societies as a joint probability of significant wave height and mean wave period, also known as wave scatter diagram. In addition, different statistical wave models have been developed to describe wave environments along arbitrary shipping routes based on different data sources, e.g., hindcast data, satellite measurements, buoys, etc. In this paper, two statistical wave models based on hindcast data and satellite wave measurements are briefly introduced and compared with the wave measurements carried out by onboard radar. Both of the wave models are then used to generate the wave environments along given shipping routes. The effectiveness of the wave models is demonstrated by comparing the stochastic nature and the statistical characteristics of simulated sea state histories with those of the source oceanographic data. Finally, an application of the wave model to the fatigue assessment is presented.

In this paper, a Three-Dimensional Dijkstra’s optimization algorithm is proposed to allow a ship to plan her waypoints and sailing speeds along each waypoint. It is expected to generate global optimum solutions for ship routes. Its capability of fuel saving as objectives is demonstrated by comparing its results with those obtained from other conventional voyage optimization algorithms, and the actual fuel consumption of a container ship with full-scale measurements. The proposed Three-Dimensional Dijkstra’s algorithm can generate global opti- mum ship routing encountering less harsh sea environment, leading to at least 5% reduction of fuel consumption within the analysed cases. Furthermore, it can perform multi-objective voyage optimization, such as minimum fuel, minimum damage accumulation, lowest crack propagation, etc., with accurate ETA in the planning process.

The second harmonic generation (SHG) of Q-switched Ho:LuAG laser in a KTP crystal was demonstrated. Under the Type II phase matching conditions, we obtained the maximum second harmonic energy per pulse of 6.82μJ and the minimum pulse width of 67.3ns at 1050.30nm in the fundamental wavelength of 2100.65nm, corresponding to a peak power of about 0.101kW. By inserting a 0.05mm-thickness YAG uncoated etalon, the maximum second harmonic energy per pulse of 4.83μJ and the minimum pulse width of 70.6ns at 1046.89nm was obtained in the fundamental wavelength of 2093.86nm, corresponding to a peak power of about 0.068kW.

miR-20b is a member of the miR-106a-363 gene cluster, which has been shown to play an important role in a variety of diseases, including cancer, inflammation, and autoimmune diseases. Our previous study indicated that miR-20b has an inhibitory effect on airway inflammation in asthmatic mice, but the exact mechanism is unclear. In this study, we report that the ratio of CD11b+Ly6G+Ly6Clow cells, but not the amount of CD11b+Ly6C+Ly6G– cells, was increased in the lung tissue of asthmatic mice after intranasal instillation with miR-20b mimics, while Th2-type cytokines (interleukin (IL)-4 and IL-13) were significantly decreased in the bronchoalveolar lavage fluid. In addition, the transcription factor CREB regulated the expression of miR-20b. Our findings suggest that miR-20b can induce the accumulation of myeloid-derived suppressor cells in the lungs of asthmatic mice, which may be a mechanism by which miR-20b inhibits airway inflammation in asthmatic mice. Thus, miR-20b may be used as a target for the effective treatment of asthma in the future.

Recognition of human actions from digital video is a challenging task due to complex interfering factors in uncontrolled realistic environments. In this paper, we propose a learning framework using static, dynamic and sequential mixed features to solve three fundamental problems: spatial domain variation, temporal domain polytrope, and intra- and inter-class diversities. Utilizing a cognitive-based data reduction method and a hybrid “network upon networks” architecture, we extract human action representations which are robust against spatial and temporal interferences and adaptive to variations in both action speed and duration. We evaluated our method on the UCF101 and other three challenging datasets. Our results demonstrated a superior performance of the proposed algorithm in human action recognition.

Model-free online object tracking is an important research topic of a wide range of applications in computer vision. A main challenge for object tracking is the model drift problem. In this paper, we proposed a multi-expert selection tracking algorithm that can not only prevent adding bad examples to object model but also can correct the effect of bad updates even if the bad examples are involved. Multi-expert ensemble is constructed of a base tracker and its former snapshots. We choose compressive tracker as our base tracker and introduce an efficient mechanism based on Hash algorithm to prevent bad model updates. Extensive experimental results show that the proposed algorithm performs favorably against state-of-the-art methods. In addition, experiment results on a newly collected dataset with challenging situations demonstrate the better performance of our method.

The task of salient region detection aims at establishing the most important and informative regions of an image. In this work, we propose a novel method that tackles such task as a process from superpixel-level locating to pixel-level refining. Firstly, we over-segment the image into superpixels and compute an affinity matrix to estimate the similarity between each two superpixels according to both color contrast and space distribution. The matrix is then applied to aggregate superpixels into several clusters by using affinity propagation. To measure the saliency of each cluster, three parameters are taken into account including color contrast, cluster compactness and proximity to the focus. We appoint the most salient one to three clusters as the crude salient region. For the refining step, we regard each selected superpixel as an influential center. Hence, the saliency value of a pixel is simultaneously determined by all the selected superpixels. Practically, several Gauss curves are constructed based on the selected superpixels. Pixel-wise saliency value is decided by the color distinction and spatial distance between one pixel and the curves’ centers. We evaluate our algorithm on the publicly available dataset with human annotations, and experimental results show that our approach has competitive performance.

We propose a cross-trees structure to perform the non-local cost aggregation for dense stereo matching. The cross-trees structure consists of a horizontal-tree and a vertical-tree. Compared to other spanning trees, the significant superiority of the cross-trees is that the trees' constructions are efficient and independent on any local or global property. Moreover, the trees are exactly unique. By traversing the two crossed trees successively, a fast non-local cost aggregation algorithm is performed to filter the matching cost volume and then the disparity maps are established with the Winner-Take-All (WTA) strategy. Additionally, two different priors: edge prior and super pixel prior, are proposed to tackle the false smoothing at the depth boundaries. Hence, our method contains two different algorithms in terms of the cross-trees prior in this paper. Performance evaluation on the 27 Middlebury data sets shows that both our algorithms outperform the other two tree-based methods, namely minimum spanning tree (MST) and segment-tree (ST). By performing the non-local cost aggregation on different trees, MST, ST and our method all have competitive rankings on the Middlebury website compared to the local cost aggregation methods.

Optical transmission estimation is a key procedure for removing haze from certain outdoor images. In this paper, we propose a novel transmission estimation model called the luminance reference model. A luminance reference, which is the intensity lower bound of a local region in the haze free image, is assumed to be a global constant across the image. Based on this assumption, we theoretically prove that, with an appropriate luminance reference, the transmission can be estimated accurately. By using a scene-dependent estimate of the luminance reference, our method can be applied to different types of images. We further propose a two-step guided approach to rapid and robust computation of a transmission map. Our experimental results show that the proposed method is computationally efficient, while producing comparable visual results to the existing state-of-the-art, but more complex methods.

The EONav ship routing service uses near real time observations of ocean surface currents, waves, wind and sea ice conditions, in conjunction with forecasts from numerical weather and ocean models, to plan the optimal route for a vessel. Products from the Copernicus Marine Environment Monitoring Service (CMEMS) and several national weather services are used together with in-house products developed for Synthetic Aperture Radar (SAR) data from satellites such as Sentinel-1, Radarsat-2 and COSMO-SkyMed. A novel data selection algorithm automatically ranks the various data sets and combines them to provide the most reliable met-ocean information. A sail plan optimized e.g. to reduce fuel consumption is determined based on the met-ocean information and is communicated to the ships to assist captains in selecting the best route and speed pattern to their destination.

Deterministic optimization algorithms generate optimal routes/paths and speeds along ship voyages. However, a ship can rarely follow pre-defined speeds because dynamic sea environments lead to continuous speed variation. In this paper, a voyage optimization method is proposed to optimize ship engine power to reduce fuel and air emissions. It is a combination of dynamic programming and genetic algorithm to solve voyage planning in three-dimensions. In this method, the engine power is discretized into several levels. The potential benefit of using this algorithm is investigated by a medium-size chemical tanker. A ship's actual sailing is used to demonstrate benefits of the proposed method. On average 3.4% of fuel-saving and emission reduction can be achieved than state-of-the-art deterministic methods. If compared with the actual full-scale measurements, on average 5.6% reduction of fuel consumption and GHG emissions (about 275 tons) can be expected by the proposed method for the six case study voyages.