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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.

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.

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%.