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Ancient architecture, with its long history, has a high cultural value, artistic achievement, and scientific value. The Nanjing City Wall was constructed in the mid-to-late 14th century, and it ranks first among the world’s city walls in terms of both length and size, whether historically or in the contemporary era. However, these sites are subject to long-term degradation and are sensitive to disturbances from the surrounding landscape, resulting in the potential deterioration of the architecture. Therefore, it is urgent to detect the defects and repair and protect Nanjing City Wall. In this paper, a novel method is proposed to detect the surface defects of the city walls by using the unmanned aerial vehicle (UAV) oblique photogrammetry and terrestrial laser scanning (TLS) data. On the one hand, the UAV oblique photogrammetry was used to collect the image data of the city wall, and a three-dimensional (3D) model of the wall was created using the oblique images. With this model, 43 cracks with lengths greater than 30 cm and 15 shedding surfaces with an area greater than 300 cm2 on the wall can be effectively detected. On the other hand, the point cloud data obtained by TLS were firstly preprocessed, and then, the KNN algorithm was used to construct a local neighborhood for each sampling point, and the neighborhood was fitted using the least squares method. Next, five features of the point cloud were calculated, and the results were visualized. Based on the visualization results, surface defects of the wall were identified, and 18 cracks with lengths greater than 30 cm and 5 shedding surfaces with an area greater than 300 cm2 on the wall were detected. To verify the accuracy of these two techniques in measuring cracks, the coordinates of some cracks were surveyed using a prism-free total station, and the lengths were calculated. The root mean square error (RMSE) of crack lengths based on the UAV oblique photogrammetry model and TLS point cloud model were calculated to be 0.73 cm and 0.34 cm, respectively. The results of the study showed that both techniques were able to detect the defects on the wall surface, and the measurement accuracy could meet the accuracy requirements of the surface defect detection of the city wall. Considering their low cost and high efficiency, these two techniques provide help for the mapping and conservation of historical buildings, which is of great significance for the conservation and repair of ancient buildings.

In recent years, flash droughts with a rapid onset and strong intensity have attracted extensive attention due to their impact on agriculture and ecosystems. However, there is still no feasible method for flash drought forecasting and early warning. This paper employs the thresholds of several meteorological variables to identify flash droughts in Zhejiang Province, China, and build a probabilistic flash drought forecasting model through numeric weather forecast (NWF) and the generalized Bayesian model (GBM). The results show that the northern part of Zhejiang Province has the highest risk of flash drought. The NWF is a viable method to provide future information for flash drought forecasting and early warning, but its forecasting accuracy tends to decline with the increase in the lead time and is very limited when the lead time is over 5 days, especially for the precipitation forecast. Due to the low performance of the NWF, the flash drought forecast based on the raw NWF may be unreliable when the lead time is over 5 days. To solve this problem, probabilistic forecasting based on GBM is employed to quantify the uncertainty in the NWF and is tested through an example analysis. In the example analysis, it was found that the probability of a flash drought exceeds 30% from the probabilistic forecasting when the lead time is 12 days, while the deterministic forecasting via the raw NWF cannot identify a flash drought when the lead time is over 5 days. In conclusion, probabilistic forecasting can identify a potential flash drought earlier and can be used to evaluate the risk of a flash drought, which is conducive for the early warning of flash droughts and the development of response measures.

To estimate the probable maximum precipitation (PMP) in a changing climate, this study proposes a new PMP estimation framework based on weather research forecasting (WRF) initialed with temperature (predicted by post-processing) for changing climate conditions. First, in order to determine temperature disturbance influencing PMP under climate change, a random forest (RF) model considering error correction is introduced to predict the temperature in the future. Results show that the revised RF model could improve accuracy in temperature prediction. Furthermore, numerical experiments of disturbance amplification of three factors (humidity, wind speed, and temperature) using the WRF model are conducted. This new scheme could consider the effect of three elements (horizontal range, vertical layer, and ratio) of influencing factors’ maximization on PMP. Results indicate that for the most unfavorable precipitation scenario of each factor magnification, the combination of three elements is different. Then, the joint amplification numerical experiments of three factors proved the existence of their interactions when multi-factors changed simultaneously. Finally, this method was tested in a high-mountain basin, the Upper Nujiang River Basin. Results showed that the increase of wind speed plays a leading role in rainfall enhancement, and the rising of relative humidity and temperature has a certain disturbance effect on rainfall. HIGHLIGHTS An improved probable maximum precipitation (PMP) estimation method based on weather research forecasting initialed with temperature for changing climate conditions.; A revised RF model improving temperature prediction accuracy.; A new scheme considering the effect of three elements (horizontal range, vertical layers, and ratio).; Physical PMP estimation considering their interactions when multi-factors change simultaneously.; More accurate extreme hydrological design value.

Optimized rain gauge networks minimize their input and maintenance costs. Satellite precipitation observations are particularly susceptible to the effects of terrain elevation, vegetation, and other topographical factors, resulting in large deviations between satellite and ground-based precipitation data. Satellite precipitation observations are more inaccurate where the deviations change more drastically, indicating that rain gauge stations should be utilized at these locations. This study utilized satellite precipitation observation data to facilitate rain gauge network optimization. The deviations between ground-based precipitation data and three types of satellite precipitation observation data were used for entropy estimation. The rain gauge network in the Oujiang River Basin of China was optimally designed according to the principle of maximum joint entropy. Two optimization schemes of culling and supplementing 40 existing sites and 35 virtual sites were explored. First, the optimization and ranking of the rain gauge station network showed good stability and consistency. In addition, the joint entropy of deviation was larger than that of ground-based precipitation data alone, leading to a higher degree of discrimination between rain gauge stations and enabling the use of deviation data instead of ground-based precipitation data to assist network optimization, with more reasonable and interpretable results.

With the gradual maturity of the terrestrial laser scanners (TLS) technology, it is widely used in the field of deformation monitoring due to its fast, automated, and non-contact data acquisition capabilities. The TLS technology has changed the traditional deformation monitoring mode which relies on single-point monitoring. This paper analyzes the application of TLS in deformation monitoring, especially in the field of ground surface, dam, tunnel, and tall constructions. We divide the methods for obtaining ground surface deformation into two categories: the method based on point cloud distance and the method based on displacement field. The advantages and disadvantages of the four methods (M2M, C2C, C2M, M3C2) based on point cloud distance are analyzed and summarized. The deformation monitoring methods and precisions based on TLS for dams, tunnels, and tall constructions are summarized, as well as the various focuses of different monitoring objects. Additionally, their limitations and development directions in the corresponding fields are analyzed. The error sources of TLS point cloud data and error correction models are discussed. Finally, the limitations and future research directions of TLS in the field of deformation monitoring are presented in detail.

Funding Information: This study is supported by the National Natural Science Foundation of China, China (Grant No. 52171351 ). Publisher Copyright: © 2022 The Author(s) Corona Virus Disease 2019 (COVID-19) outbreak leads to a significant downturn in the global economy and supply chain. In the maritime sector, trade volume slumped by 3.8% in 2020 compared with 2019. To explore the impacts of COVID-19 on ship visiting behaviors, a framework is proposed to analyze the impact of COVID-19 on port traffic using Automatic Identification System (AIS) data. Firstly, a ship travel behavior-based model is proposed to identify the vessel anchoring and berthing. Then, the diversity in vessel anchoring and berthing time are analyzed, reflecting the impact of COVID-19. The port congestion caused by COVID-19 is quantified by accounting for the number of visiting ships and their residence time. Finally, a case study is carried out on vessels in the Beibu Gulf, China, operating from 2019 to 2020. The results show that the average anchoring time and berthing time increase by 62% and 11% for cargo ships and by 112% and 63% for oil tankers after the outbreak of COVID-19 compared with that beforeCOVID-19. And the density of ships increases in the port area in 2020. Accordingly, the relevant improvements and countermeasures are proposed to reduce the adverse impact of the epidemic on the port navigation system. The paper has the potential to provide a reference for port management and improving port navigation efficiency in the post-pandemic era.

The great-circle passage is the shortest distance between two points on the surface of the earth. When planning a ship’s sailing route (waypoints and forward speeds) for a specific voyage, the great circle route is commonly considered as a reference route, especially for ocean-crossing seaborne transport. During the planning process, the upcoming sea weather condition is one of the most important factors affecting the ship’s route optimization/planning results. To avoid encountering harsh conditions, conventional routing optimization algorithms, such as Isochrone method and Dynamic Programming method, have been developed/implemented to schedule a ship’s optimal routes by selecting waypoints around the great circle reference route based on the ship’s operational performances at sea. Due to large uncertainties in sea weather forecast that used as inputs of these optimization algorithms, the “optimized” routes may have worse performances than the traditional great circle sailing. In addition, some shipping companies are still sailing in or making charting contracts based on the great circle routes. Therefore, in this study, a new optimization algorithm is proposed to consider the voluntary speed reduction with optimal speed configuration along the great circle course. The efficiency of this method is investigated by comparing these two methods for optimal route planning with respect to ETA and minimum fuel consumption. A container ship sailing in the North Atlantic with full-scale performance measurements are employed as the case study vessels for the comparison.

Automatic extraction of the skeleton lines of river systems from high-resolution remote-sensing images has great significance for surveying and managing water resources. A large number of existing methods for the automatic extraction of skeleton lines from raster images are primarily used for simple graphs and images (e.g., fingerprint, text, and character recognition). These methods generally are memory intensive and have low computational efficiency. These shortcomings preclude their direct use in the extraction of skeleton lines from large volumes of high-resolution remote-sensing images. In this study, we developed a method to extract river skeleton lines based entirely on run-length encoding. This method attempts to replace direct raster encoding with run-length encoding for storing river data, which can considerably compress raster data. A run-length boundary tracing strategy is used instead of complete raster matrix traversal to quickly determine redundant pixels, thereby significantly improving the computational efficiency. An experiment was performed using a 0.5 m-resolution remote-sensing image of Yiwu city in the Chinese province of Zhejiang. Raster data for the rivers in Yiwu were obtained using both the DeepLabv3+ deep learning model and the conventional visual interpretation method. Subsequently, the proposed method was used to extract the skeleton lines of the rivers in Yiwu. To compare the proposed method with the classical raster-based skeleton line extraction algorithm developed by Zhang and Suen in terms of memory consumption and computational efficiency, the visually interpreted river data were used to generate skeleton lines at different raster resolutions. The results showed that the proposed method consumed less than 1% of the memory consumed by the classical method and was over 10 times more computationally efficient. This finding suggests that the proposed method has the potential for river skeleton line extraction from terabyte-scale remote-sensing image data on personal computers.

Surface passivation, which has been intensively studied recently, is essential for the perovskite solar cells (PSCs), due to the intrinsic defects in perovskite crystal. A series of chemical or physical methods have been published for passivating the defects of perovskites, which effectively suppressed the charge recombination and enhanced the photovoltaic performance. In this study, the n-type semiconductor of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) is dissolved in chlorobenzene (CB) for the surface passivation during the spin-coating process for depositing the two-dimensional (2D) perovskite film. This approach simplifies the fabrication process of 2D PSCs and benefits the film quality. As a result, the defects of perovskite film are effectively passivated by this method. A better perovskite/PCBM heterojunction is generated, exhibiting an increased film coverage and improved film morphology of PCBM. It is found that this technology results in an improved electron transporting performance as well as suppressed charge recombination for electron transport layer. As a result, PSCs based on the one-step formed perovskite/PCBM heterojunctions exhibit the optimized power conversion efficiency of 15.69% which is about 37% higher than that of regular perovskite devices. The device environmental stability is also enhanced due to the quality improved electron transport layer.

With the rapid development of meteorological models, numerical weather prediction is increasingly used in flood forecasting and reservoir regulation, but its forecasting ability is limited by the large amount of uncertainty from meteorological systems. In this paper, a new, hybrid framework is developed to improve numerical precipitation forecasting by combining the multimodel ensemble and probabilistic postprocessing methods. The results show that the multimodel ensemble method used in this paper is an efficient way to reduce prediction errors, especially missing alarm errors. In a comparison of the probabilistic postprocessors based the generalized Bayesian model (GBM) and bivariate probabilistic model (BPM), the GBM shows better performance from the aspects of indicators and is more suitable for real-time applications. Meanwhile, the assessment of probabilistic results shows that the skill of probabilistic precipitation forecasts is related to the quality of their inputs. According to these results, a new hybrid framework is proposed by taking the results from multimodel ensemble as the input of probabilistic postprocessor. Compared to using the raw numerical in GBM, the hybrid framework improves the accuracy, sharpness, reliability, and resolution ability from different lead times by 2–13%, 1–22%, and 0–12% respectively, especially when the lead time is less than 4 d, the improvement can reach 9–13%, 10–22%, and 5–12% respectively. In conclusion, the hybrid two-step framework can provide a more skillful precipitation forecast, which can be useful for flood forecasting and reservoir regulation.

This paper designs an integrated electromechanical servo system of control, drive and actuator to solve the technical problems of large weight and volume caused by the low degree of integration of traditional servo systems. It mainly includes the following aspects, the design composition and working principle of the integrated integrated electromechanical servo system, the simulation analysis of integrated integrated servo system, and the experimental research of integrated integrated servo system.

This paper designs and analyzes a drive module suitable for a certain integrated integrated design servo actuator. According to the limited installation space of the product, the combined miniaturization design is carried out, and relevant simulation analysis and experimental research are carried out to guide the The design of similar products has certain guiding significance.

Ocean-going vessels are under the continuous influence on the effect of the weather, e.g. wind, waves, ocean currents. Since the weather conditions are random in nature, there are situations where the shipmaster changes the ship speed or/and heading of the original sailing path to avoid harsh weather conditions according to his judgment, experience and/or using voyage optimization systems (e.g. weather routing systems). However, ship operators hardly prioritize the ship fatigue routing in their operations. It is preferable to consider the effect of different wave environment due to ship operation in the design process to make a more rational ship design of the structural members. In this study, sailing paths are planned, adopting voyage optimization in order to reduce the probability of encountering severe sea conditions and the minimization of the fatigue accumulation in ship structures. Short-sea sequences are generated by a statistical wave storm model. The storm profiles are determined by using the cumulative frequency of short-seas which are experienced in the different voyages optimized by the algorithm. The influence of the difference in short-seas encountered by the target ship following the optimized voyages on the cumulative damage is demonstrated by a container vessel, which also considers a weather routing system in her operations. Full-scale measurement data for two years’ voyages are considered for the verification. The benefits of using voyages optimization systems focus on reducing fatigue damage to mitigate the risk of structural failure is discussed.

In this study, different operation factors affecting a ship’s wave statistics are studied, such as the slow steaming and voyage optimizations. Especially, the impact of various voyage optimization methods on the long-term wave statistics and corresponding fatigue damage during ship operations is investigated by comparing the encountered waves with the design wave scatter diagram. Three years of full-scale measurements from a container ship sailing in the North Atlantic are employed to study the impact, in addition to noon reports from two fleets of container ships and VLCCs. Furthermore, the benefits of using voyage optimizations for minimum fatigue damage accumulation during operation are discussed. The large difference of wave statistics is found when the ship follows routes generated by various optimization methods and the design diagram. For some westbound voyages, the voyage optimization methods can significantly decrease the ship’s fatigue damage accumulations, leading to longer fatigue life.

Fatigue damage in ship structures starts to be accumulated from the first day when a ship is launched, while the average age of current ship fleets in different shipping segments is often older than 15 years. After many years of fatigue accumulation, fatigue cracks are widely existing in today’s ocean-crossing ships. The existence of fatigue cracks brings great challenges to ship safety, structural maintenance, associated operation cost, and so on. In order to reduce the crack propagation and enhance a ship’s structural safety during its service period, various methods could be implemented, such as decreasing cargo loadings, reducing ship speed, or even changing trade regions to be sailed in moderate sea environments. In this article, the so-called voyage optimization is proposed to plan a ship’s sailing courses with a well-designed schedule to minimize the fatigue accumulation in ship structures. Two types of optimization algorithms are used for the voyage planning, namely, the static waypoint/grid–based and dynamic waypoint/grid–based optimization systems. The capabilities of these two optimization systems are demonstrated by a 2800TEU container vessel, which was also instrumented with an old style weather routing system. One entire year of full-scale measurement data are available for the demonstration, and the crack propagation is estimated by a linear fracture mechanics–based spectral method. It is concluded that the benefits of using the proposed voyage optimization to mitigate the risk associated with a structural crack failure by more than 50%.

Visual context is fundamental to understand human actions in videos. However, the discriminative temporal information of videos is usually sparse and most frames are redundant mixed with a large amount of interference information, which may result in redundant computation and recognition failure. Hence, an important question is how to efficiently employ temporal context information. In this paper, we propose a learnable temporal attention mechanism to automatically select important time points from action sequences. We design an unsupervised Recurrent Temporal Sparse Autoencoder (RTSAE) network, which learns to extract sparse keyframes to sharpen discriminative yet to retain descriptive capability, as well to shield interference information. By applying this technique to a dual-stream convolutional neural network, we significantly improve the performance in both accuracy and efficiency. Experiments demonstrate that, with the help of the RTSAE, our method achieves competitive results to state of the art on UCF101 and HMDB51 datasets.

Purpose This study evaluates the correlation between the susceptibility of the γ passing rate of IMRT plans to the multi-leaf collimator (MLC) position errors and a quantitative plan complexity metric. Methods Twenty patients were selected for this study. For each patient, two IMRT plans were generated using sliding window and step-&-shoot techniques, respectively. Modulation complexity score (MCS) was calculated for all IMRT plans, and symmetric MLC leaf bank errors, ranging from 0.3 mm to 1 mm, were introduced. Original and modified plans were delivered using Varian’s Clinac iX. The obtained dose distribution using ArcCHECK was then compared with the TPS calculated dose distribution of the original plans. 3D gamma analysis was performed for each verification with passing criteria of 2%/2 mm. The γ passing rate decreasing gradient were calculated to evaluate relationship between variation of γ passing rate due to MLC errors and complexity. Results A linear regression analysis was applied between γ gradient and complexity, and the results showed a linear correlation (R2 = 0.81 and 0.82 for open and closed MLC error types, respectively) indicating the more complex plans are more susceptible to MLC leaf bank errors. Meanwhile, correlation of re-normalized γ passing rate and complexity for all errors scenarios also presented a strong correlation (r > 0.75). Conclusion The statistics results revealed variation relationship of dosimetry robust of plans with various complexities to MLC errors. Our results also suggested that the observed susceptibility is independent of the delivery techniques.

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+Ly6C low 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.

Airway inflammation can be mitigated when apoptotic cells are engulfed by pulmonary epithelial cells. Insulin-like growth factor 1 (IGF-1), a single chain polypeptide growth factor, is the main mediator of growth hormone activity in vivo. IGF-1 has many biological activities, such as the regulation of cell survival, proliferation, differentiation and metabolism. However, its effect on the engulfment of cells, especially by non-professional phagocytes such as alveolar epithelial cells (AECs), has not been fully elucidated. We report that IGF-1 increases endocytosis in a mouse alveolar epithelial cell line, MLE-12. The PI3K-Akt pathway is involved in this effect of IGF-1. Furthermore, IGF-1 can inhibit the production of interleukin-6 in lipopolysaccharide-stimulated AECs. We have found that IGF-1 can enhance endocytosis of AECs through the PI3K pathway and exhibit anti-inflammatory properties. These two observations suggest that IGF-1 is a potential mediator in the regulation of airway inflammation.

MicroRNAs (miRNAs/miRs) are small, noncoding RNA molecules that are closely associated with the occurrence and development of tumors. miR-20b is overexpressed in hepatocellular carcinoma cell lines and tissues. However, it is not clear whether miR-20b can promote the proliferation of hepatocellular carcinoma cells. In the present study, the proliferation of H22 mouse hepatocellular carcinoma cells was detected using the Cell Counting Kit-8 assay. MiRanda software was used to predict the binding sites of miR-20b to the 3′-untranslated region (3′-UTR) of phosphatase and tensin homolog (PTEN). The 3′-UTR sequence of the PTEN gene was amplified using the polymerase chain reaction in H22 cells. The recombinant plasmid or empty plasmid was co-transfected with miR-20b mimics or miR-20b scramble into HeLa cells, and luciferase activity was assessed by Dual-Luciferase(®) Reporter Assay System 24 h post-transfection. In the present study, miR-20b knockdown significantly inhibited the proliferation of H22 mouse hepatocellular carcinoma cells. In addition, miR-20b inhibition upregulated the expression of PTEN, and it was revealed that miR-20b may directly target the 3′-untranslated region of the PTEN gene. Downregulation of PTEN partially reversed the anti-proliferative effect of miR-20b on H22 cells. In conclusion, miR-20b may promote H22 cell proliferation by targeting PTEN, providing a rationale for further study investigating novel therapeutic strategies for liver cancer.

In this work, we report a facile method to passivate the defects of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) by forming the integrated ETLs of PCBM/C60, which exhibits the improved electron extraction performance compared with the single PCBM layer. It is found that depositing the C60 layer on top of PCBM benefits the film morphology of ETL and leads to more appropriate energy alignment. As a result, the optimized group using PCBM/C60 as the integrated ETLs exhibit decreased photocurrent hysteresis and increased power conversion efficiency of 12.5%, which is about 35% higher than that of control group.

We introduce a facile method to form a well-deposited [6] , [6] -phenyl-C61-butyric acid methyl ester (PCBM) film on the surface of 2D perovskite by mixing the poly[(9,9-bis(3′-(N,N-dimethylamino)propyl)-2,7-fluorene)-alt-2,7-(9,9–dioctylfluorene)] (PFN), which can benefit the film formation of PCBM as well as improve the electron extraction efficiency of electron transport layer (ETL). As a result, the optimized group presents an enhanced photovoltaic performance with power conversion efficiency of 12.7%, which is attributed to the improved interfacial contact and better matched energy alignment. It is observed that the fully covered and dense ETL (PCBM:PFN) leads to a better environmental stability of devices in ambient air condition without encapsulation.

Aiming at the water cycle simulation of multi-sources and multi-functional irrigation area, the coupling relationship between natural water cycle and social water cycle was established based on SWAT model. The methods of sub basins divisions in SWAT model were improved, which were incorporated into the improved SWAT model. The water cycle process of complex water resource system and the response to various human activities in irrigation area were simulated accurately and quantitatively to meet the needs of accurate water resource management.

Aiming at the water cycle simulation in multi-sources and multi-functional irrigation area, the improved SWAT model was constructed and applied to Wanyao irrigation area, which is located in Jiangshan county, Zhejiang province. The measured data from 1990 to 2006 of the watershed outlet observation stations named Jiangshan and Daqiao were used to calibrate the model parameters, which measured data from 2007 to 2017 were used to validate the model. The correlation coefficient of verification period of monthly runoff simulation was 0.91, Nash coefficient was 0.90, relative errors of simulated results and measured data of 16 monitoring facilities in irrigation area were within 10%. The improved SWAT model simulation results were used to construct the statistical models of irrigation water consumption in Wanyao irrigation area on a monthly scale and an annual scale respectively. The mean relative error of the monthly scale model is 4.5% and the mean relative error of the annual scale model is 1.2%, which satisfy the needs of accurate water resources management.

Irrigation water consumption statistical work is very important to water resources management. As for Zhejiang province, the problems of irrigation water consumption statistics are that there are too many water sources to monitor which discharge and too many usages to separate from a certain amount of water. At the meantime, the irrigation water can return to the downstream fields and be reused in its irrigation, but the amount of reuse water is very difficult to monitor and count. Taking Wanyao irrigation area as the study object, the layout methods of monitoring facilities built to monitor the key sectors of water circulation were proposed, including the supplication sector, the utilization sector and the drainage sector. The water circulation model of irrigation area was constructed based on the monitoring facilities’ observed data, then the constructed model was applied to simulate the natural water circulation and the social water circulation. The supplication and utilization progress of irrigation water were extracted from the simulation results, and the reuse progress of irrigation water was analysed. Actual irrigation water consumption in irrigation area was counted in the last. The result shows that it’s feasible economically and technically to layout the monitoring facilities based on water circulation simulation of irrigation area, and the statistics method of irrigation water consumption by simulating the water circulation is reliable and high precise.

Ship voyage optimization systems are widely used in today's ocean-crossing ships to consider a ship's sailing safety and energy efficiency. Large uncertainties from the inputs of today's voyage optimization algorithms can reduce the reliability of voyage optimization systems, especially for more complex algorithms that involve more control variables in the optimization. This study first proposes a speed optimization algorithm, which considers the voluntary speed reduction for a ship voyage with fixed trajectories. Then, the capability of the proposed speed optimization method is investigated by comparing with conventional voyage planning methods that optimize a ship's sailing courses/trajectories. In particular, the effectiveness of handling uncertain inputs during the optimization process, such as ship speed-power performance models, metocean forecasts, is investigated for the two types of voyage optimization methods. Finally, the benefits of potential fuel saving are studied by incorporating this proposed algorithm for a ship's slow steaming strategies.

KYbxY1−xW(O4)2 (KYbxY1−xW, x = 0.05–0.20) crystals were successfully grown by the top seeded solution growth method (TSSG) with K2W2O7 as flux. The KYbxY1−xW crystals maintain monoclinic structure, and the crystal unit cell volume decreases as the Yb3+ ions doping concentration increases. The emission cross-sections σem in KYbxY1−xW(x = 0.05–0.20) crystals are 0.805 × 10-20 cm2, 0.599 × 10-20 cm2, 1.147 × 10-20 cm2 and 1.008 × 10-20 cm2 at 980 nm. A direct continuous-wave diode pumped KYb0.05Y0.95W laser crystal could generate an output power of 1.31 W with slope efficiency of 44.8% by using an output coupler with a transmission T = 1%.

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.