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In this paper, a combined model is proposed to predict spare parts inventory in accordance with equipment characteristics and defect elimination records. Fourier series is employed to process the periodicity of the data, autoregressive moving average (ARMA) is used to deal with the linear autocorrelation of the data, and backpropagation (BP) neural network is used to settle the nonlinearity of the data. The prediction results, comparisons, and error analyses show that the combined model is accurate and meets the practical requirements. The combined model not only fully utilizes the information contained in the data but also provides a reasonable decision basis for the procurement of spare parts, making the inventory in a safe state and saving holding costs.

The quantitative study of earthquake-triggered rockfall debris along seismogenic fault zones has proven to be a valid approach for use in identifying paleo-earthquakes and faulting activities. After the 2010 Yushu earthquake, paleo-rockfall research employed U-series dating of calcareous coats on the rockfall surface, and the results provided chronological evidence of multi-period features relating to earthquake-triggered rockfalls that have occurred along the Yushu fault. In this study, the mechanism involved in forming the calcareous coat on seismic rockfall surfaces was analyzed to further explain the significance of conducting associated U–Th aging analyses. For earthquake-triggered rockfall regions, the U–Th age of the calcareous coat can be used as a proxy age of the rockfall formation, and the timing of the related paleo-earthquake event can be constrained. Based on all current existing age data, an in-depth comparison was made between the U–Th ages of calcareous coats obtained from five seismic rockfall sites and other 14C dating results obtained from trenches and paleo-seismic landslides relating to paleo-earthquakes. Combined with the results of field investigations, four individual paleo-earthquakes that triggered rockfalls of different scales in historical time were identified. These results imply that multi-period earthquake-triggered rockfalls along the Yushu fault may be valid time indicators of seismic events and reflect the intensity and meizoseismal scale of relevant paleo-earthquake events. This exploratory research on the U-series dating of calcareous coats from earthquake-triggered rockfalls in Yushu can be used as a valuable reference for paleo-earthquake studies in other tectonically active regions.

A large variety of high-value substation relay protection equipment occupies a considerable amount of inventory space and capital in electric power companies. To improve this problem, this study proposes an inventory prediction model based on the remaining useful life (RUL) of equipment. The model acquires the RUL data of equipment by using the support vector regression (SVR) algorithm, and then, by taking this data as the main factor and the environmental factors and human factors during the operation of equipment as secondary factors, the model can realize the prediction of relay protection equipment in the substation. At the same time, the nature of the enterprise and the requirements for safety inventory are considered. The comparison of calculation results and error analysis, as well as the calculation time, all indicate that the RUL-based inventory forecasting is the best one. This model not only has high prediction accuracy but also has strong stability and portability. The model can provide a strong decision basis for improving the inventory management of the enterprise, enhancing the resource allocation capability, and formulating the spare parts procurement plan under the condition that the spare parts inventory reaches the safety stock.

Parkinson’s disease (PD) is characterized by the degeneration of dopaminergic neurons and excessive microglial activation in the substantia nigra pars compacta (SNpc). In the present study, we aimed to demonstrate the therapeutic effectiveness of the potent sphingosine-1-phosphate receptor antagonist fingolimod (FTY720) in an animal model of PD induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), and to identify the potential mechanisms underlying these therapeutic effects. C57BL/6J mice were orally administered FTY720 before subcutaneous injection of MPTP. Open-field and rotarod tests were performed to determine the therapeutic effect of FTY720. The damage to dopaminergic neurons and the production of monoamine neurotransmitters were assessed using immunohistochemistry, high-performance liquid chromatography, and flow cytometry. Immunofluorescence (CD68- positive) and enzyme-linked immunosorbent assay were used to analyze the activation of microglia, and the levels of activated signaling molecules were measured using Western blotting. Our findings indicated that FTY720 significantly attenuated MPTP-induced behavioral deficits, reduced the loss of dopaminergic neurons, and increased dopamine release. FTY720 directly inhibited MPTP-induced microglial activation in the SNpc, suppressed the production of interleukin (IL)-6, IL-1β, and tumor necrosis factor-α in BV-2 microglial cells treated with 1-methyl-4-phenylpyridinium (MPP+), and subsequently decreased apoptosis in SH-SY5Y neuroblastoma cells. Moreover, in MPP+-treated BV-2 cells and primary microglia, FTY720 treatment significantly attenuated the increases in the phosphorylation of PI3K/AKT/GSK-3β, reduced ROS generation and p65 activation, and also inhibited the activation of NLRP3 inflammasome and caspase-1. In conclusion, FTY720 may reduce PD progression by inhibiting NLRP3 inflammasome activation via its effects on ROS generation and p65 activation in microglia. These findings provide novel insights into the mechanisms underlying the therapeutic effects of FTY720, suggesting its potential as a novel therapeutic strategy against PD.

Digital elevation models (DEMs) derived from remote sensing data provide a valuable and consistent data source for mapping coastal flooding at local and global scales. Mapping of flood risk requires quantification of the error in DEM elevations and its effect on delineation of flood zones. The ASTER, SRTM, ALOS, and TanDEM-X (TDX) DEMs for the island of Hispaniola were examined by comparing them with GPS and LiDAR measurements. The comparisons were based on a series of error measures including root mean square error (RMSE) and absolute error at 90% quantile (LE90). When compared with >2000 GPS measurements with elevations below 7 m, RMSE and LE90 values for ASTER, SRTM, ALOS, TDX DEMs were 8.44 and 14.29, 3.82 and 5.85, 2.08 and 3.64, and 1.74 and 3.20 m, respectively. In contrast, RMSE and LE90 values for the same DEMs were 4.24 and 6.70, 4.81 and 7.16, 4.91 and 6.82, and 2.27 and 3.66 m when compared to DEMs from 150 km2 LiDAR data, which included elevations as high as 20 m. The expanded area with LiDAR coverage included additional types of land surface, resulting in differences in error measures. Comparison of RMSEs indicated that the filtering of TDX DEMs using four methods improved the accuracy of the estimates of ground elevation by 20–43%. DTMs generated by interpolating the ground pixels from a progressive morphological filter, using an empirical Bayesian kriging method, produced an RMSE of 1.06 m and LE90 of 1.73 m when compared to GPS measurements, and an RMSE of 1.30 m and LE90 of 2.02 m when compared to LiDAR data. Differences in inundation areas based on TDX and LiDAR DTMs were between −13% and −4% for scenarios of 3, 5, 10, and 15 m water level rise, a much narrower range than inundation differences between ASTER, SRTM, ALOS and LiDAR. The TDX DEMs deliver high resolution global DEMs with unprecedented elevation accuracy, hence, it is recommended for mapping coastal flood risk zones on a global scale, as well as at a local scale in developing countries where data with higher accuracy are unavailable.

In this study, the first ever Sea, Lake, Overland Surges from Hurricanes (SLOSH) grid was built for the Yucatan Peninsula. The SLOSH model was used to simulate storm surges in the coastal area of the states of Yucatan and Campeche (Mexico). Based on climatology, more than 39,900 hypothetical hurricanes covering all possible directions of motion were synthesized. The storm intensity (category), forward speed, radius of maximum winds and the tide anomaly were varied for each hypothetical track. According to these scenarios, the potential storm surge and associated inundation threat were computed. Subsequently, the Maximum Envelope of Water (MEOW) and the Maximum of the MEOWs (MOMs) were calculated to assess the flood hazard induced by tropical cyclones under varying conditions. In addition, for each MOM, the socioeconomic vulnerability aspects were taken into account in order to assess the hurricane flood risk for the states of Yucatan and Campeche. Results show that the most vulnerable areas are the surroundings of Terminos lagoon, Campeche City and its neighboring areas in the state of Campeche. For Yucatan, the towns located in the Northwest (Celestun, Hunucma and Progreso) and the eastern part of the state presented the highest risk values. The methodology used in this study can be applied to other coastal zones of Mexico as well as places with similar attributes. Furthermore, the MEOW and MOM are very useful as a decision-making tool for prevention, preparedness, evacuation plans, mitigation of the flood hazard and its associated risk, and also for insurance companies.

Intertidal environments, including bare mudflats, tidal creeks, and vegetated salt marshes, are of significant physical and ecological importance in estuaries. Their morphodynamics are closely linked by mudflats and creek networks. Understanding water motion and sediment transport in mudflats and tidal creeks is fundamental to understand intertidal morphodynamics in intertidal environments. To explore dynamic interactions between tidal creeks and mudflats, we conducted field campaigns monitoring water depths, tidal currents, waves, suspended sediments, and bed-level changes at sites in both mudflats and tidal creeks in the Eastern Chongming tidal wetland in the Yangtze Delta for a full spring-neap tidal cycle. We saw that under fair weather conditions, the bed-level changes of the tidal creek site displayed a contrary trend compared with those of the mudflat site, indicating the source-sink relationship between tidal creek and mudflat. During over-marsh tides, the tidal creek site with relatively high bed shear stresses (averagely, 0.37 N/m2) was eroded by 35 mm whereas the mudflat site was accreted by 29 mm under low bed shear stresses (averagely, 0.18 N/m2). To the contrast, during creek-restricted tides, deposition occurred in the tidal creek site by 20 mm under low bed shear stresses (averagely, 0.09 N/m2) whereas erosion occurred in the mudflat site by 25 mm under relatively high bed shear stresses (averagely, 0.21 N/m2). Over a spring-neap tidal cycle, the net bed level changes were −15 mm (erosion) and 4 mm (deposition) in tidal creeks and mudflats, respectively. These results suggested that there were alternated erosion-deposition patterns in spring and neap tides, and a sediment source and sink shift between mudflats and creeks. We found that the eroded sediments in mudflats were transported landward into tidal creeks and deposited therein in neap tides, and these newly deposited sediments would be resuspended and transported to surrounding marshes (over-marsh deposition) at spring tides. The coherent sediment transport and associated erosion-deposition pattern within the mudflat-creek system at spring-neap tidal time scales thus played a fundamental role in intertidal morphodynamic development. These findings suggest that management and restoration of intertidal ecosystem need to take the entire mudflat-creek-marsh system as a unit into consideration rather than focusing on single elements.

Crustal material eastward extrusion from the Tibetan Plateau is closely related to the strike-slip faults in the SE margin of the Tibetan Plateau. The left-lateral strike-slip Xianshuihe–Xiaojiang ...

The increasing integration of renewable energy sources has brought about a great computational burden for the traditional methods that assess the power system reliability. To reduce the computational costs, an extendable Latin hypercube importance sampling (ELHIS) method that combines importance sampling (IS) and Latin hypercube sampling (LHS) is proposed in this paper. First, the challenge of combining IS and LHS is analysed, and a customized sampling process of LHS is designed accordingly. Then, in the IS part of ELHIS, the cross entropy theory and Gaussian mixture model are adopted in the stage that constructs the quasi-optimal probability distribution of random variables. In addition, the samples in this stage are also utilized in the estimation of reliability indices to reduce the waste of computational efforts. In the LHS part, an extendable LHS approach is used to make ELHIS adaptive and flexible in determining the sample size to reach the required accuracy. Finally, numerical tests are performed on the modified IEEE-RTS 79 test system, where the real historical data from three wind farms and a photovoltaic station in Northwest China are employed. The results show that ELHIS is obviously faster than recent IS methods when used to assess the power system reliability.

High Dynamic Range (HDR) Imaging/Video is an important part of the microscopic analysis. In this paper, common methods for obtaining a well-exposed image/video are briefly reviewed, then an alternative method to generate high- quality HDR video in real-time is proposed and compared using general objective metrics for its correct interpretation. The primary application of this implemen- tation is for real-time of non-high speed microscopic inspection systems. Several highly reflective samples are evaluated and compared between this state-of-the-art algorithm and other common methods. Results have shown the success of the de- scribed method. This publication can serve as a baseline for further evaluation and inspection in the field of HDR Microscopy.

This study evaluated the impact of human modifications and natural variations (e.g., seasonal riverine fluxes, plant growth, and estuarine environments) on the short-term morphological changes in estuarine tidal flats. Central to the study was an embankment, constructed in 2014, which changed the path of a tidal flat evolution in the Yangtze Estuary and resulted in a remarkable shift of the erosion-deposition pattern in the study area. To examine the embankment’s impact, we used a terrestrial laser scanner to collect seven topographic data sets for the tidal flat, during different seasons from 2012 to 2016. The rates of elevation change varied from − 19.3 cm year−1 before embankment construction to 17.2 cm year−1 after embankment construction. The field measurements also showed that the new embankment led to an increase of suspended sediment concentration from 1.4 to 2.7 kg m−3 on average in the mudflat and from 1.0 to 2.6 kg m−3 in the salt marsh. These results indicated that the increase in sediment availability caused by human modifications played an important role in tidal flat evolution and were able to promote the accretion of the tidal flats. Furthermore, there were significant spatiotemporal variations in the morphological changes in different regions of the tidal flat. Depositional changes were more likely to occur during the wet seasons and salt marshes were more stable than mudflats and tidal creeks.

Mangroves have been proven to be effective in storm surge attenuation but it remains an important challenge to accurately quantify such bio-shielding effects using numerical simulations, as it is very difficult to comprehensively represent the ecological characteristics of mangroves at both large and small scales. In this study, a numerical method is developed and implemented in the Coastal and Estuarine Storm Tide (CEST) model in order to investigate the attenuation effect of mangroves on storm surge. This numerical method employs an improved drag force formula, which involves the development of new abstract tree models and use of a landscape scale data map of mean mangrove tree height for the study area. The storm surge observed in the South Florida mangrove zone caused by Hurricane Wilma (2005) is used to verify the numerical model. The numerical results indicate a maximum surge of approximately 4.3 m, and a decay rate of peak storm surge height of approximately 18 cm/km across the areas with a mixture of mangrove islands and open water, and nearly 24 cm/km through areas with dense mangrove forest. Results also show that short mangroves ( 4 m) can outperform tall mangroves on surge attenuation when the water depth is low ( 4 m). Extensive comparisons are also made with the conventional Manning coefficient based method that incorporates the mangrove drag force into bed friction; it is found that the current method predicts better inundation extents for Wilma (2005), hence a more accurate quantification of the attenuation of storm surge due to mangroves.

Quantification of tidal flat morphological changes at varying timescales is critical from a management point of view. High-resolution tidal flat morphology data, including those for mudflats and salt-marshes, are rare due to monitoring difficulty by traditional methods. Recent advances in Terrestrial Laser Scanner (TLS) technology allow rapid acquisition of high-resolution and large-scale morphological data, but it remains problematic for its application on salt-marshes due to the presence of dense vegetation. In this study, we applied a TLS system to retrieve high-accuracy digital elevation models in a tidal flat of the Yangtze Estuary by using a robust and accurate Progressive Morphological filter (PM) to separate ground and non-ground points. Validations against GPS-supported RTK measurements suggested remarkable performance. In this case the average estimation error was about 0.3 cm, while the Root Mean Square Error (RMSE) was 2.0 cm. We conducted three TLS surveys on the same field including salt-marshes and mudflats at the time points 5 days before, 3 days after, and 45 days after a typhoon event. The retrieved data showed that the mudflats suffered from profound erosion while the salt-marshes slightly accreted during the typhoon period. The average elevation change of the total area was about − 4 cm (− 0.28 cm per day). However, both the mudflats and salt-marshes deposited in the post-typhoon period and the accretion over salt-marshes occurred at a higher rate than that during the typhoon. The elevation of the total area increased by 15.9 cm (0.37 cm per day), suggesting fast recovery under calm conditions. Quantification of the erosion and deposition rates was aided by the high quality TLS data. This study shows the effectiveness of TLS in quantifying morphological changes of tidal flats at an event (and post-event) timescale. The data and analysis also provide sound evidence on vegetation impact in stimulating salt-marsh development and restoration, shedding lights on bio-morphological interactions.

The degradation of optical microscopic imaging is space-variant, and how to fast restore optical degraded image remains a special problem. Based on point spread function (PSF) estimation under each field of view (FOV), a L0 gradient-constrained image restoration method is proposed to solve optical degradation in microscopic imaging. Firstly, the whole scene is segmented into several different regions according to different FOV. The PSFs for each region are estimated from modulation transfer function (MTF) measured in advance. Secondly, a penalty function is designed using L0 gradient constraint to deblur the degraded images of each sub-FOV. Finally, a weighted stitching approach is used to stitch the restored images of multiple FOV (m-FOV). Experimental results indicate that the m-FOV analysis could well solve the problem of space-variant degradation. Compared with the other methods, both subjective and objective evaluation results prove that the L0 norm idea could rapidly and effectively restore the degraded image. The approach could be well applied to a real product.

Hurricanes Frances, Jeanne, and Wilma passed over Lake Okeechobee, Florida, in September 2004 and October 2005, respectively. Strong winds caused a large surface seiche on the lake during all three storms. These storms resulted in erosion damage to the Herbert Hoover Dike (HHD) on Lake Okeechobee. In this paper, we use the Fully Adaptive Storm Tide (FAST) model (Kelly et al. in Coast Eng J 57(4):1–30, 2015, Nat Hazards 83:53–74, 2016) to study the response of the lake (in terms of the water level fluctuations and induced currents) to hurricanes Frances, Jeanne, and Wilma. Comparisons of the modeled surface water level with the observations are in overall good agreement for all three hurricanes. The modeled results suggest that the strong currents induced by the storm winds may be the dominant factor controlling the dike erosion observed at the lake side. The locations of erosion damage to the dike are consistent with the modeled high velocity zones during these three storms. In addition, numerical experiments have been conducted with eight hypothetical category 5 hurricanes approaching from different directions to investigate the erosion-prone zones related to high velocities in the vicinity of the dike. The results of the study should help to provide insight into vulnerable reaches of the HHD and inform flood control in the Okeechobee region.

Kelly et al. (Coast Eng J 57(4):1–30, 2015) present a finite volume dynamic adaptive mesh model based on Osher’s approximate Riemann solver for the prediction of storm surges over complex landscapes. Here, the model described in that paper is extended to use distributed memory parallel block tree-based mesh refinement via the PARAMESH library. The resulting model, called the fully adaptive storm tide (FAST) model, can thus be run on massively parallel supercomputers. In this paper, we validate the FAST model by conducting numerical simulations of the storm surges due to hurricanes Wilma (2005) on Lake Okeechobee and Ike (2008) in the Gulf of Mexico. The storm surge due to Wilma on Lake Okeechobee is interesting as it can be considered as an almost idealized case which comprises a closed system. The case of hurricane Ike is more complex as it involves a coastline and additional features such as barrier islands and tidally controlled boundaries. For both cases, results obtained using the FAST model compare favorably with the measured water elevation and high-water mark data. Moreover, we show that, with sufficient computational resource, low runtimes are possible for real-world surge simulations. The FAST model therefore has the potential to run the ensemble predictions necessary to account for the variability that is inherent in hurricane forecasting.

Zhang, K.; Zhang, M.C.; Leatherman, S.B., and Leatherman, S.P., 2020. Rip current hazard analysis. In: Malvarez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 969–973. Coconut Creek (Florida), ISSN 0749-0208.The effect of rip currents on swimmers was analyzed based on the drag force acting on swimmers and the power they need to generate to overcome the drag force. The drag force and power increase quadratically and cubically, respectively, with increase of rip current and swimming speeds. An additional 50% increase in rip current speed above swimmer's speed results in a 125% increase in drag force, requiring a 238% increase in power by the swimmer to overcome the additional drag. Hence, even rip currents of low velocity can be dangerous and swimming against the current should be avoided.

Blue carbon ecosystems (BCEs) provide many ecosystem services as “the benefits people obtain from ecosystems.” These include important recreational and tourism opportunities, key fishery habitat, water quality improvements, and flood and erosion mitigation. These are co-benefits of BCEs in addition to carbon sequestration. The monetary value of these services are best known for coastal protection and carbon sequestration, with monetary value of coastal protection services estimated at \23 billion year− 1 between 1980 and 2008.

Parkinson's disease (PD) is characterized by the degeneration of dopaminergic neurons and excessive microglial activation in the substantia nigra pars compacta (SNpc). In the present study, we aimed to demonstrate the therapeutic effectiveness of the potent sphingosine-1-phosphate receptor antagonist fingolimod (FTY720) in an animal model of PD induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), and to identify the potential mechanisms underlying these therapeutic effects. C57BL/6J mice were orally administered FTY720 before subcutaneous injection of MPTP. Open-field and rotarod tests were performed to determine the therapeutic effect of FTY720. The damage to dopaminergic neurons and the production of monoamine neurotransmitters were assessed using immunohistochemistry, high-performance liquid chromatography, and flow cytometry. Immunofluorescence (CD68- positive) and enzyme-linked immunosorbent assay were used to analyze the activation of microglia, and the levels of activated signaling molecules were measured using Western blotting. Our findings indicated that FTY720 significantly attenuated MPTP-induced behavioral deficits, reduced the loss of dopaminergic neurons, and increased dopamine release. FTY720 directly inhibited MPTP-induced microglial activation in the SNpc, suppressed the production of interleukin (IL)-6, IL-1β, and tumor necrosis factor-α in BV-2 microglial cells treated with 1-methyl-4-phenylpyridinium (MPP

The geographic area that the Joint Airborne LiDAR Bathymetry Technical Center of Expertise (JALBTCX) covers with their Light Detection and Ranging (LiDAR) program allows for researchers to quantify coastal metrics on national, regional and local scales. As these studies progressed, it has become apparent that software needs to be developed to quantify coastal change from LiDAR at multiple scales. The purpose of this research is to provide coastal managers with quantities and locations of change that occurred on eastern US coastlines, and if the researcher would like additional information, provide the tools necessary for additional metrics to be quantified and additional questions to be answered.

The snake algorithm has been proposed to solve many remote sensing and computer vision problems such as object segmentation, surface reconstruction, and object tracking. This paper introduces a framework for 3-D building model construction from LIDAR data based on the snake algorithm. It consists of nonterrain object identification, building and tree separation, building topology extraction, and adjustment by the snake algorithm. The challenging task in applying the snake algorithm to building topology adjustment is to find the global minima of energy functions derived for 2-D building topology. The traditional snake algorithm uses dynamic programming for computing the global minima of energy functions which is limited to snake problems with 1-D topology (i.e., a contour) and cannot handle problems with 2-D topology. In this paper, we have extended the dynamic programming method to address the snake problems with a 2-D planar topology using a novel graph reduction technique. Given a planar snake, a set of reduction operations is defined and used to simplify the graph of the planar snake into a set of isolated vertices while retaining the minimal energy of the graph. Another challenging task for 3-D building model reconstruction is how to enforce different kinds of geometric constraints during building topology refinement. This framework proposed two energy functions, deviation and direction energy functions, to enforce multiple geometric constraints on 2-D topology refinement naturally and efficiently. To examine the effectiveness of the framework, the framework has been applied on different data sets to construct 3-D building models from airborne LIDAR data. The results demonstrate that the proposed snake algorithm successfully found the global optima in polynomial time for all of the building topologies and generated satisfactory 3-D models for most of the buildings in the study areas.