Comparing Sliding Block Procedures for Displacement-Based Design of Earth Structures in Light of Major Chilean Earthquakes

2017 ◽  
Vol 21 ◽  
pp. 3-14
Author(s):  
Juan Carlos Tiznado ◽  
Maria Paz Silva ◽  
Natalia Viejo
Keyword(s):  
Quantitative Estimation ◽  
Strong Motion ◽  
Soil Mass ◽  
Soil Conditions ◽  
Earthquake Parameters ◽  
Critical Acceleration ◽  
Practical Applications ◽  
Earth Structures ◽  
Displacement Based ◽  
Selection Of

Current practice for seismic design of earth structures considers the use of displacement-based methods, which allow a quick and quantitative estimation of the movement of soil masses under earthquake loading. This type of procedures are aimed to establish a relationship between (i) the main earthquake parameters, (ii) the critical acceleration, and (iii) the corresponding permanent displacements of the soil structure. In this sense, based on the well-known Newmark’s sliding block method, several regression models intended for design purposes have been proposed during last decades. However, the selection of an appropriate method to predict the expected permanent displacements of a soil mass remains a difficult and somewhat arbitrary practice. In this paper, strong-motion records from four major Chilean earthquakes, grouped by soil conditions, are used to compare and evaluate the suitability of the reviewed methods for assessing the seismic performance of earth structures. From the results obtained, general conclusions and recommendations for practical applications on sites with similar characteristics to the Chilean subduction zone are elaborated.

scholarly journals Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at Plot Scale

2018 ◽  
Vol 10 (8) ◽  
pp. 1285 ◽  
Author(s):  
Reza Attarzadeh ◽  
Jalal Amini ◽  
Claudia Notarnicola ◽  
Felix Greifeneder
Keyword(s):  
Soil Moisture ◽  
Optical Data ◽  
Estimation Accuracy ◽  
Support Vector ◽  
Practical Applications ◽  
Initial Stage ◽  
Object Based ◽  
Single Polarization ◽  
Selection Of

This paper presents an approach for retrieval of soil moisture content (SMC) by coupling single polarization C-band synthetic aperture radar (SAR) and optical data at the plot scale in vegetated areas. The study was carried out at five different sites with dominant vegetation cover located in Kenya. In the initial stage of the process, different features are extracted from single polarization mode (VV polarization) SAR and optical data. Subsequently, proper selection of the relevant features is conducted on the extracted features. An advanced state-of-the-art machine learning regression approach, the support vector regression (SVR) technique, is used to retrieve soil moisture. This paper takes a new look at soil moisture retrieval in vegetated areas considering the needs of practical applications. In this context, we tried to work at the object level instead of the pixel level. Accordingly, a group of pixels (an image object) represents the reality of the land cover at the plot scale. Three approaches, a pixel-based approach, an object-based approach, and a combination of pixel- and object-based approaches, were used to estimate soil moisture. The results show that the combined approach outperforms the other approaches in terms of estimation accuracy (4.94% and 0.89 compared to 6.41% and 0.62 in terms of root mean square error (RMSE) and R2), flexibility on retrieving the level of soil moisture, and better quality of visual representation of the SMC map.

scholarly journals The Influence of Soil Humidity Stress on Eggplant Crop

2017 ◽  
Vol 74 (1) ◽  
pp. 74 ◽  
Author(s):  
Gicuța SBÎRCIOG
Keyword(s):  
Soil Conditions ◽  
Soil Humidity ◽  
Major Objective ◽  
Hydric Stress ◽  
Selection Of

In order to meet consumption requirements, according to the crops destination and way of preparing the fruits, the eggplant breeding process aims at obtaining some cultivars properly adapted to the climate and soil conditions from different culture areas.  In this context, the selection of genotypes which are tolerant to the thermal and hydric stress represents a major objective of the eggplant breeding.

Efficacy and Rate of Release of EPTC and Butylate from Starch Encapsulated Formulations Under Greenhouse Conditions

Weed Science ◽  
1978 ◽  
Vol 26 (6) ◽  
pp. 679-686 ◽  
Author(s):  
M. M. Schreiber ◽  
B. S. Shasha ◽  
M. A. Ross ◽  
P. L. Orwick ◽  
D. W. Edgecomb
Keyword(s):  
Controlled Release ◽  
Slow Release ◽  
Residual Activity ◽  
Biological Evaluation ◽  
Soil Conditions ◽  
Short Term ◽  
Rapid Release ◽  
Initial Release ◽  
Wet Chemical ◽  
Selection Of

Four starch-encapsulated formulations of EPTC(S-ethyl dipropylthiocarbamate) and of butylate(S-ethyl diisobutylthiocarbamate) were prepared and evaluated by comparison with their respective emulsifiable concentrate formulations for their slow-release capabilities and efficacies. Chemical and biological evaluation indicated that difference in controlled-release could be achieved by the selection of the starch xanthate and oxidant used in the formualtion process. EPTC and butylate released slower when formulated as starch-encapsulated granules than when formulated as emulsifiable concentrates under soil conditions that favored rapid release. The initial release was adequate for weed control and slow enough for desired residual activity. Repeated seeding and harvesting the treated soils and bioassays of treated soils generally produced release rate anticipated from short term dry and wet chemical tests.

scholarly journals Understanding Mental Health and Cognitive Restructuring With Ecological Neuroscience

2021 ◽  
Vol 12 ◽  
Author(s):  
James Crum
Keyword(s):  
Mental Health ◽  
Near Infrared ◽  
Ecological Validity ◽  
Experimental Designs ◽  
Functional Near Infrared Spectroscopy ◽  
Practical Applications ◽  
Recent Developments ◽  
The Brain ◽  
Neuroimaging Techniques ◽  
Selection Of

Neuroimaging and neuropsychological methods have contributed much toward an understanding of the information processing systems of the human brain in the last few decades, but to what extent do cognitive neuroscientific findings represent and generalize to the inter- and intra-brain dynamics engaged in adapting to naturalistic situations? If it is not marked, and experimental designs lack ecological validity, then this stands to potentially impact the practical applications of a paradigm. In no other domain is this more important to acknowledge than in human clinical neuroimaging research, wherein reduced ecological validity could mean a loss in clinical utility. One way to improve the generalizability and representativeness of findings is to adopt a more “real-world” approach to the development and selection of experimental designs and neuroimaging techniques to investigate the clinically-relevant phenomena of interest. For example, some relatively recent developments to neuroimaging techniques such as functional near-infrared spectroscopy (fNIRS) make it possible to create experimental designs using naturalistic tasks that would otherwise not be possible within the confines of a conventional laboratory. Mental health, cognitive interventions, and the present challenges to investigating the brain during treatment are discussed, as well as how the ecological use of fNIRS might be helpful in bridging the explanatory gaps to understanding the cultivation of mental health.

scholarly journals Research on Robustness of Related Images for Power Equipment Inspection

2021 ◽  
Vol 2113 (1) ◽  
pp. 012045
Author(s):  
Chunlei Zhou ◽  
Xiangzhou Chen ◽  
Wenli Liu ◽  
Tianyu Dong ◽  
Huang Yun
Keyword(s):  
Deep Learning ◽  
Image Recognition ◽  
Feature Fusion ◽  
Power Equipment ◽  
Actual Measurement ◽  
Practical Applications ◽  
Detection Algorithms ◽  
Traction Substations ◽  
Deep Learning Model ◽  
Selection Of

Abstract With the increase in the number of traction substations year by year, manual inspections are gradually being replaced by unattended inspections. Target detection algorithms based on deep learning are more widely used in intelligent inspections of power equipment. However, in practical applications, it is found that due to the small target to be detected, the accuracy of the deep learning model will decrease when the shooting angle is inclined and the light conditions are poor. This is because the algorithm’s robustness is low, and the detection ability of the model will be seriously affected when the angle or illumination difference with the sample is large. Based on this, the feature fusion part of the YOLOv3 algorithm and the selection of the loss function and the size of the anchor frame are improved, and the improved ASFF fusion method is used to classify various images in the power equipment. Actual measurement and repeated experiments show that the proposed method can be effectively applied to image recognition of various power equipment, optimize robustness, and greatly improve the image recognition efficiency of power equipment.

scholarly journals A service evaluation of the healthy lifestyle groups in a female medium secure unit- what do our patients know about nutrition?

BJPsych Open ◽  
2021 ◽  
Vol 7 (S1) ◽  
pp. S350-S350
Author(s):  
Lauren Shipperbottom ◽  
Ruth Scally
Keyword(s):  
Salt Intake ◽  
Healthy Lifestyle ◽  
Service Evaluation ◽  
Nutritional Knowledge ◽  
Practical Applications ◽  
Oily Fish ◽  
University College London ◽  
Secure Unit ◽  
Starchy Foods ◽  
Selection Of

AimsTo assess whether patients have a good knowledge of basic nutrition compared to a group of staff. We hypothesise that the patient's knowledge will show deficits compared to the staff despite the group interventions.BackgroundThe Royal College of Psychiatrist's core standards for inpatient physical health outlines that patients should be engaged in healthy lifestyle groups. The women's secure service at Ardenleigh has developed healthy lifestyles groups to promote a better understanding of nutrition.MethodAn adapted University College London general knowledge nutrition questionnaire was used to investigate nutritional knowledge.All 22 inpatients and a random selection of staff were offered the chance to complete the questionnaire. As the groups run on a regular basis, it was presumed all patients had attended at least one group session. The staff are the comparator group.18 staff responses and 12 inpatient responses were obtained (54.5% response rate for inpatients).ResultNo participant in either group scored 100%. Both groups had a good awareness of what foods they should be eating more and less of. 83.3% of patients were aware that they should be eating breakfast everyday as opposed to 100% of staff.Poor areas of knowledge included knowledge of the number of oily fish servings per week. Staff and patients also performed poorly when estimating their recommended daily salt intake. 1/3 of patients were unable to provide an example of a serving of fruit and vegetables.The knowledge of the structure of the Eat-Well plate was poor in both groups. Only 16% of patients and 22% of staff were aware that starchy foods should make up 1/3 of the Eat-well plate. Knowledge of protein sources was poor. 25% of patients and 16.6% of staff thought that fruit and butter were good sources of proteinFurthermore, only 50% of patients were able to choose the healthiest evening meal choice from a list of 3 options compared to 100% of staff.ConclusionIn conclusion staff had better knowledge of nutrition than patients but knowledge was poor in areas amongst both groups. We conclude that groups should have more focus around practical applications of nutritional knowledge to everyday life.

Real-time seismology at UC Berkeley: The Rapid Earthquake Data Integration project

1996 ◽  
Vol 86 (4) ◽  
pp. 936-945 ◽  
Author(s):  
Lind S. Gee ◽  
Douglas S. Neuhauser ◽  
Douglas S. Dreger ◽  
Michael E. Pasyanos ◽  
Robert A. Uhrhammer ◽  
...  
Keyword(s):  
Data Integration ◽  
Strong Motion ◽  
Seismic Network ◽  
Prototype System ◽  
Earthquake Parameters ◽  
Moment Tensors ◽  
Automatic Information ◽  
Integration Project ◽  
Earthquake Data

Abstract The Rapid Earthquake Data Integration project is a system for the fast determination of earthquake parameters in northern and central California based on data from the Berkeley Digital Seismic Network and the USGS Northern California Seismic Network. Program development started in 1993, and a prototype system began providing automatic information on earthquake location and magnitude in November of 1993 via commercial pagers and the Internet. Recent enhancements include the exchange of phase data with neighboring networks and the inauguration of processing for the determination of strong-motion parameters and seismic moment tensors.

scholarly journals Monitoring Soil Condition in the Northern Tibetan Plateau Using SSM/I Data

1996 ◽  
Vol 27 (3) ◽  
pp. 175-184 ◽  
Author(s):  
A. T. C. Chang ◽  
M. S. Cao
Keyword(s):  
Tibetan Plateau ◽  
Brightness Temperature ◽  
Geographic Location ◽  
Soil Condition ◽  
Soil Conditions ◽  
Temperature Threshold ◽  
Freeze Thaw ◽  
Northern Tibetan Plateau ◽  
Scattering Centers ◽  
Selection Of

A combination of a low 37 GHz brightness temperature and a negative 19 and 37 GHz spectral gradient can be an effective discriminant for frozen and thawed soil. SSM/I data for 1988 are used to study the freeze/thaw of soil in the Northern Tibetan Plateau, China. In this study, a previously derived freeze/thaw classification scheme was tested for this unique geographic location. It was found that the 37 GHz threshold needed to be refined for this region. It was also found that the 37 GHz emission is sensitive to the scattering centers embedded in the soil, which may account for the observed low brightness temperature. The selection of the 37 GHz brightness temperature threshold depends on the atmospheric and soil conditions inherent in a particular region.

scholarly journals Selection of promising black locust (Robinia pseudoacacia L.) cultivars in Hungary

2017 ◽  
Vol 63 (No. 8) ◽  
pp. 339-343
Author(s):  
Rédei Károly ◽  
Csiha Imre ◽  
Rásó János ◽  
Keserű Zsolt
Keyword(s):  
Black Locust ◽  
Robinia Pseudoacacia ◽  
Soil Conditions ◽  
Brown Forest Soil ◽  
Stem Form ◽  
Climate Change Effects ◽  
Selection Programme ◽  
Yield Production ◽  
Robinia Pseudoacacia L ◽  
Selection Of

In Hungary the black locust (Robinia pseudoacacia Linnaeus) is one of the most important exotic stand-forming tree species growing mostly under unfavourable ecological conditions. Considering the climate change effects its importance is increasing also in many other countries. As a result of a selection programme several black locust cultivars have been improved for setting up cultivar trials. In the paper four black locust cultivars were evaluated in Central Hungary under arid hydrological and brown forest soil conditions. Significant differences (P < 5%) were found in height, DBH, mean tree volume and average stem form value (SFV). At the age of 35 years the cultivar “R.p. Jászkiséri” appeared to be the most promising one for yield production and “R.p. Zalai” and “R.p. Nyírségi” for SFV.

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