scholarly journals Research on Key Technical Indexes of Coastal Reclamation Planning and Design

2021 ◽  
Vol 283 ◽  
pp. 02002
Author(s):  
Zhang Shixia ◽  
Zhan Zhenyu ◽  
Cao Guangtian
Keyword(s):  
Large Scale ◽  
Reduction Rate ◽  
Tidal Energy ◽  
Economic Benefits ◽  
Ocean Dynamics ◽  
Tidal Range ◽  
Disaster Prevention ◽  
Coastal Landscape ◽  
Range Reduction ◽  
Coastal Reclamation

Large-scale coastal reclamation has become a significant land use issue worldwide for urban construction and economic development. The reclamation of coastal wetlands brings substantial economic benefits, however, the structure and function of coastal ecosystem are affected by drivers of human-caused landscape change. This research takes Hangzhou Bay and Zhoushan Islands as the case study to investigate the correlation between the coastal geomorphic complexity and the tidal range reduction rate, and to explore the control technical indexes of the design in reclamation area by a multidisciplinary approach that integrates the basic theories and quantitative methods of fractal geometry with the hydrodynamic mechanism of ocean dynamics. The results show that the coastal tidal range reduction rate is closely related to the coastline fractal dimension and patch shape index (D, S), and reveals the influence of the complexity of the coastal landscape on the tidal energy loss. In addition, based on model predictions, it can be found that the large-scale reclamation in Zhoushan will cause a serious decline in the complexity of the coastal landscape and the reduction of tidal energy, which is extremely detrimental to coastal disaster prevention. In the end, the scientific design theory and quantitative control indexes of reclamation are put forward to provide theoretical basis and design reference for future coastal reclamation and disaster prevention.

Screening for the FV: Q506 Mutation – Evaluation of Thirteen Plasma-based Methods for their Diagnostic Efficacy in Comparison with DNA Analysis

1997 ◽  
Vol 77 (03) ◽  
pp. 436-439 ◽  
Author(s):  
Armando Tripodi ◽  
Barbara Negri ◽  
Rogier M Bertina ◽  
Pier Mannuccio Mannucci
Keyword(s):  
Venous Thrombosis ◽  
Large Scale ◽  
Dna Analysis ◽  
Genetic Defect ◽  
Laboratory Diagnosis ◽  
Economic Benefits ◽  
Factor V ◽  
Factor X ◽  
Diagnostic Efficacy ◽  
Dna Test

SummaryThe factor V (FV) mutation Q506 that causes resistance to activated protein C (APC) is the genetic defect associated most frequently with venous thrombosis. The laboratory diagnosis can be made by DNA analysis or by clotting tests that measure the degree of prolongation of plasma clotting time upon addition of APC. Home-made and commercial methods are available but no comparative evaluation of their diagnostic efficacy has so far been reported. Eighty frozen coded plasma samples from carriers and non-carriers of the FV: Q506 mutation, diagnosed by DNA analysis, were sent to 8 experienced laboratories that were asked to analyze these samples in blind with their own APC resistance tests. The APTT methods were highly variable in their capacity to discriminate between carriers and non-carriers but this capacity increased dramatically when samples were diluted with FV-deficient plasma before analysis, bringing the sensitivity and specificity of these tests to 100%. The best discrimination was obtained with methods in which fibrin formation is triggered by the addition of activated factor X or Russell viper venom. In conclusion, this study provides evidence that some coagulation tests are able to distinguish carriers of the FV: Q506 mutation from non-carriers as well as the DNA test. They are inexpensive and easy to perform. Their use in large-scale clinical trials should be of help to determine the medical and economic benefits of screening healthy individuals for the mutation before they are exposed to such risk factors for venous thrombosis as surgery, pregnancy and oral contraceptives.

Economic benefit of shale gas exploitation based on back propagation neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8823-8830
Author(s):  
Jiafeng Li ◽  
Hui Hu ◽  
Xiang Li ◽  
Qian Jin ◽  
Tianhao Huang
Keyword(s):  
Neural Network ◽  
Shale Gas ◽  
Bp Neural Network ◽  
Large Scale ◽  
Linear Prediction ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Economic Benefits ◽  
Gas Well ◽  
Well Production

Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods

scholarly journals Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations

2021 ◽  
Vol 13 (3) ◽  
pp. 1274
Author(s):  
Loau Al-Bahrani ◽  
Mehdi Seyedmahmoudian ◽  
Ben Horan ◽  
Alex Stojcevski
Keyword(s):  
Large Scale ◽  
Thermal Power ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Pso Algorithm ◽  
Search Space ◽  
Economic Benefits ◽  
Optimization Techniques ◽  
Ramp Rate ◽  
Dynamic Economic Dispatch

Few non-traditional optimization techniques are applied to the dynamic economic dispatch (DED) of large-scale thermal power units (TPUs), e.g., 1000 TPUs, that consider the effects of valve-point loading with ramp-rate limitations. This is a complicated multiple mode problem. In this investigation, a novel optimization technique, namely, a multi-gradient particle swarm optimization (MG-PSO) algorithm with two stages for exploring and exploiting the search space area, is employed as an optimization tool. The M particles (explorers) in the first stage are used to explore new neighborhoods, whereas the M particles (exploiters) in the second stage are used to exploit the best neighborhood. The M particles’ negative gradient variation in both stages causes the equilibrium between the global and local search space capabilities. This algorithm’s authentication is demonstrated on five medium-scale to very large-scale power systems. The MG-PSO algorithm effectively reduces the difficulty of handling the large-scale DED problem, and simulation results confirm this algorithm’s suitability for such a complicated multi-objective problem at varying fitness performance measures and consistency. This algorithm is also applied to estimate the required generation in 24 h to meet load demand changes. This investigation provides useful technical references for economic dispatch operators to update their power system programs in order to achieve economic benefits.

scholarly journals Impact of the municipal merger on watershed management: a study of Lake Kasumigaura, Japan

2021 ◽  
Author(s):  
Takeshi Mizunoya ◽  
Noriko Nozaki ◽  
Rajeev Kumar Singh
Keyword(s):  
Watershed Management ◽  
Large Scale ◽  
Environmental Changes ◽  
Water Environment ◽  
Reduction Rate ◽  
Oxygen Demand ◽  
Policy Implications ◽  
Pollution Reduction ◽  
Lake Kasumigaura ◽  
The Impact

AbstractIn the early 2000s, Japan instituted the Great Heisei Consolidation, a national strategy to promote large-scale municipal mergers. This study analyzes the impact that this strategy could have on watershed management. We select the Lake Kasumigaura Basin, the second largest lake in Japan, for the case study and construct a dynamic expanded input–output model to simulate the ecological system around the Lake, the socio-environmental changes over the period, and their mutual dependency for the period 2012–2020. In the model, we regulate and control the following water pollutants: total nitrogen, total phosphorus, and chemical oxygen demand. The results show that a trade-off between economic activity and the environment can be avoided within a specific range of pollution reduction, given that the prefectural government implements optimal water environment policies, assuming that other factors constraining economic growth exist. Additionally, municipal mergers are found to significantly reduce the budget required to improve the water environment, but merger budget efficiency varies nonlinearly with the reduction rate. Furthermore, despite the increase in financial efficiency from the merger, the efficiency of installing domestic wastewater treatment systems decreases drastically beyond a certain pollution reduction level and eventually reaches a limit. Further reductions require direct regulatory instruments in addition to economic policies, along with limiting the output of each industry. Most studies on municipal mergers apply a political, administrative, or financial perspective; few evaluate the quantitative impact of municipal mergers on the environment and environmental policy implications. This study addresses these gaps.

scholarly journals On the tides and resonances of Hudson Bay and Hudson Strait

Ocean Science ◽  
2014 ◽  
Vol 10 (3) ◽  
pp. 411-426 ◽  
Author(s):  
D. J. Webb
Keyword(s):  
Numerical Model ◽  
Shallow Water ◽  
World Ocean ◽  
Tidal Energy ◽  
Tidal Range ◽  
Hudson Bay ◽  
Foxe Basin ◽  
Important Region ◽  
The World ◽  
Diurnal Tides

Abstract. The resonances of Hudson Bay, Foxe Basin and Hudson Strait are investigated using a linear shallow water numerical model. The region is of particular interest because it is the most important region of the world ocean for dissipating tidal energy. The model shows that the semi-diurnal tides of the region are dominated by four nearby overlapping resonances. It shows that these not only affect Ungava Bay, a region of extreme tidal range, but they also extend far into Foxe Basin and Hudson Bay and appear to be affected by the geometry of those regions. The results also indicate that it is the four resonances acting together which make the region such an important area for dissipating tidal energy.

scholarly journals Spectral Minutiae Fingerprint Recognition System

2014 ◽  
pp. 103-108
Author(s):  
S. Shanawaz Basha ◽  
N. Musrat Sultana
Keyword(s):  
Large Scale ◽  
Reduction Rate ◽  
Principal Component ◽  
Rejection Rate ◽  
Recognition System ◽  
Feature Reduction ◽  
Fingerprint Recognition ◽  
Identification System ◽  
Behavioral Characteristics ◽  
Template Size

Biometrics refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics, such as faces, finger prints, iris, and gait. In this paper, we focus on the application of finger print recognition system. The spectral minutiae fingerprint recognition is a method to represent a minutiae set as a fixedlength feature vector, which is invariant to translation, and in which rotation and scaling become translations, so that they can be easily compensated for. Based on the spectral minutiae features, this paper introduces two feature reduction algorithms: the Column Principal Component Analysis and the Line Discrete Fourier Transform feature reductions, which can efficiently compress the template size with a reduction rate of 94%.With reduced features, we can also achieve a fast minutiae-based matching algorithm. This paper presents the performance of the spectral minutiae fingerprint recognition system, this fast operation renders our system suitable for a large-scale fingerprint identification system, thus significantly reducing the time to perform matching, especially in systems like, police patrolling, airports etc,. The spectral minutiae representation system tends to significantly reduce the false acceptance rate with a marginal increase in the false rejection rate.

scholarly journals Cost-Effectiveness Analysis of a Large-Scale Crèche Intervention to Prevent Child Drowning in Rural Bangladesh

2021 ◽  
Author(s):  
Y. Natalia Alfonso ◽  
Adnan A Hyder ◽  
Olakunle Alonge ◽  
Shumona Sharmin Salam ◽  
Kamran Baset ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Societal Perspective ◽  
Large Scale ◽  
Operating Cost ◽  
Cost Effective ◽  
Economic Benefits ◽  
Program Cost ◽  
Rural Bangladesh ◽  
Life Years ◽  
The Cost

Abstract Drowning is the leading cause of death among children 12-59 months old in rural Bangladesh. This study evaluated the cost-effectiveness of a large-scale crèche intervention in preventing child drowning. Estimates of the effectiveness of the crèches was based on prior studies and the program cost was assessed using monthly program expenditures captured prospectively throughout the study period from two different implementing agencies. The study evaluated the cost-effectiveness from both a program and societal perspective. Results showed that from the program perspective the annual operating cost of a crèche was $416.35 (95%C.I.: $222 to $576), the annual cost per child was $16 (95%C.I.: $9 to $22) and the incremental-cost-effectiveness ratio (ICER) per life saved with the crèches was $17,803 (95%C.I.: $9,051 to $27,625). From the societal perspective (including parents time valued) the ICER per life saved was -$176,62 (95%C.I.: -$347,091 to -$67,684)—meaning crèches generated net economic benefits per child enrolled. Based on the ICER per disability-adjusted-life years averted from the societal perspective (excluding parents time), $2,020, the crèche intervention was cost-effective even when the societal economic benefits were ignored. Based on the evidence, the creche intervention has great potential for reducing child drowning at a cost that is reasonable.

scholarly journals State and Perspectives of the Concept of Large‐Scale Conditioning of Regional Climate Modelling

2018 ◽  
Author(s):  
Hans von Storch ◽  
Leone Cavicchia ◽  
Frauke Feser ◽  
Delei Li
Keyword(s):  
Large Scale ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Ocean Dynamics ◽  
Small Scale ◽  
Climate Modelling ◽  
Coastal Regions ◽  
Global Models ◽  
Atmospheric Disturbances ◽  
Low Level Jets

We review the state of dynamical downscaling with scale-constrained regional and global models. The methodology, in particular spectral nudging, has become a routine and well-researched tool for hindcasting climatologies of sub-synoptic atmospheric disturbances in coastal regions. At present, the spectrum of applications is expanding to other phenomena, but also to ocean dynamics and to extended forecasting. Also new diagnostic challenges are appearing such as spatial characteristics of small-scale phenomena such as Low Level Jets.

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