Influence of low-frequency variability on high and low groundwater levels: example of aquifers in northern France

2021 ◽  
Author(s):  
Lisa Baulon ◽  
Nicolas Massei ◽  
Delphine Allier ◽  
Matthieu Fournier ◽  
Hélène Bessiere
Keyword(s):  
Groundwater Level ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Groundwater Levels ◽  
Low Level ◽  
Northern France ◽  
Low Frequency Variability ◽  
Low Levels ◽  
High Level ◽  
Very High

<p>Groundwater fluctuations exhibit very often well-pronounced low-frequency variability (multi-annual to decadal timescales), linked to catchment and aquifer ability to smooth out rapid fluctuations from precipitation (low-pass filtering), especially when their characteristic time is long. This low-frequency variability, generated by large-scale climate variability and modulated by the physical properties of hydrosystems, is clearly imprinted in aquifers of northern France. Many recent researches addressed the issue of the capability of global climate models to reproduce low-frequency variability (most of the time multidecadal). For hydrological processes such as groundwater levels, which variance can be dominated by such low-frequency ranges, it may then appear crucial to provide assessment on how very high or very low levels are sensitive to such low-frequency variability. In this study, we investigate how low-frequency variability (from multi-annual to interdecadal timescales) may generate very high or very low groundwater levels (higher or lower than percentiles 80% and 20%, respectively). To test such hypotheses, our approach consists of breaking down groundwater level signals into timescale components using maximum overlap discrete wavelet transform in order to get wavelet details at different timescales. Multi-annual ~7 yr and interdecadal ~17 yr components appeared to be the dominant components of low-frequency variability of the signals. We then substracted these components (either one or both) and simply examined how many values remained over or below the selected threshold.</p><p>Results highlight that the number of events generated by low-frequency components is consistently closely linked to their contribution to groundwater level variability. Nearly 100% of high and low groundwater levels in inertial aquifers, that exhibit a large predominance of interdecadal variability, are generated by this timescale. At least 50% of high and low groundwater levels in inertial aquifers displaying a combination of interdecadal and multi-annual variabilities are generated by the combination of these two timescales. Finally, less than 50% of high and low groundwater levels in mixed aquifers (i.e. with a well pronounced low-frequency variability superimposed to annual variability) are generated by the multi-annual and interdecadal variabilities. In all studied aquifers with various dynamics, we notice a higher sensitivity of low groundwater levels to low-frequency variability than high groundwater levels.</p><p>Across aquifers of northern metropolitan France, particularly in the chalk of the Paris Basin, we observe quite a clear dependence of well-known historical high and low groundwater levels to low-frequency variability. In particular, the 2001 high levels and the 1992 low levels are seemingly generated by concomitant multi-annual and interdecadal high levels, and concomitant multi-annual and interdecadal low levels, respectively. On the other hand, the 1995 high levels and 1998 low levels are produced by a multi-annual high level attenuated by an interdecadal low level, and a multi-annual low level attenuated by an interdecadal high level, respectively. These phasings are also observed in precipitation and effective precipitation a few time in advance (ranging from 2 months to 1.5 years). Finally, the contribution of multi-annual and interdecadal variabilities to make the groundwater levels reach or exceed one selected threshold is directly influenced by their prominence in groundwater levels variability.</p>

scholarly journals Building Extraction in Very High Resolution Imagery by Dense-Attention Networks

2018 ◽  
Vol 10 (11) ◽  
pp. 1768 ◽  
Author(s):  
Hui Yang ◽  
Penghai Wu ◽  
Xuedong Yao ◽  
Yanlan Wu ◽  
Biao Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Building Extraction ◽  
Learning Networks ◽  
Feature Maps ◽  
Low Level ◽  
High Resolution Imagery ◽  
Very High Resolution Imagery ◽  
High Level ◽  
Very High

Building extraction from very high resolution (VHR) imagery plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Compared with the traditional building extraction approaches, deep learning networks have recently shown outstanding performance in this task by using both high-level and low-level feature maps. However, it is difficult to utilize different level features rationally with the present deep learning networks. To tackle this problem, a novel network based on DenseNets and the attention mechanism was proposed, called the dense-attention network (DAN). The DAN contains an encoder part and a decoder part which are separately composed of lightweight DenseNets and a spatial attention fusion module. The proposed encoder–decoder architecture can strengthen feature propagation and effectively bring higher-level feature information to suppress the low-level feature and noises. Experimental results based on public international society for photogrammetry and remote sensing (ISPRS) datasets with only red–green–blue (RGB) images demonstrated that the proposed DAN achieved a higher score (96.16% overall accuracy (OA), 92.56% F1 score, 90.56% mean intersection over union (MIOU), less training and response time and higher-quality value) when compared with other deep learning methods.

scholarly journals Evaluation of Resistance Development in Bemisia tabaci Genn. (Homoptera: Aleyrodidae) in Cotton against Different Insecticides

Insects ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 996
Author(s):  
Muhammad Zaryab Khalid ◽  
Sohail Ahmed ◽  
Ibrahim Al-ashkar ◽  
Ayman EL Sabagh ◽  
Liyun Liu ◽  
...  
Keyword(s):  
Bemisia Tabaci ◽  
The Other ◽  
Resistance Development ◽  
Susceptible Population ◽  
Low Level ◽  
Development Of Resistance ◽  
Major Pest ◽  
Selection For ◽  
High Level ◽  
Very High

Cotton is a major crop of Pakistan, and Bemisia tabaci (Homoptera: Aleyrodidae) is a major pest of cotton. Due to the unwise and indiscriminate use of insecticides, resistance develops more readily in the whitefly. The present study was conducted to evaluate the resistance development in the whitefly against the different insecticides that are still in use. For this purpose, the whitefly population was selected with five concentrations of each insecticide, for five generations. At G1, compared with the laboratory susceptible population, a very low level of resistance was observed against bifenthrin, cypermethrin, acetamiprid, imidacloprid, thiamethoxam, nitenpyram, chlorfenapyr, and buprofezin with a resistance ratio of 3-fold, 2-fold, 1-fold, 4-fold, 3-fold, 3-fold, 3-fold, and 3-fold, respectively. However, the selection for five generations increased the resistance to a very high level against buprofezin (127-fold), and to a high level against imidacloprid (86-fold) compared with the laboratory susceptible population. While, a moderate level of resistance was observed against cypermethrin (34-fold), thiamethoxam (34-fold), nitenpyram (30-fold), chlorfenapyr (29-fold), and acetamiprid (21-fold). On the other hand, the resistance was low against bifenthrin (18-fold) after selection for five generations. A very low level of resistance against the field population of B. tabaci, at G1, showed that these insecticides are still effective, and thus can be used under the field conditions for the management of B. tabaci. However, the proper rotation of insecticides among different groups can help to reduce the development of resistance against insecticides.

scholarly journals Intelligent Dermatologist Tool for Classifying Multiple Skin Cancer Subtypes by Incorporating Manifold Radiomics Features Categories

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Omneya Attallah ◽  
Maha Sharkas
Keyword(s):  
Skin Cancer ◽  
Binary Classification ◽  
Survival Rates ◽  
Skin Lesions ◽  
Accurate Diagnosis ◽  
Computer Assisted ◽  
Discrete Wavelet ◽  
Cancer Subtypes ◽  
Low Level ◽  
High Level

The rates of skin cancer (SC) are rising every year and becoming a critical health issue worldwide. SC’s early and accurate diagnosis is the key procedure to reduce these rates and improve survivability. However, the manual diagnosis is exhausting, complicated, expensive, prone to diagnostic error, and highly dependent on the dermatologist’s experience and abilities. Thus, there is a vital need to create automated dermatologist tools that are capable of accurately classifying SC subclasses. Recently, artificial intelligence (AI) techniques including machine learning (ML) and deep learning (DL) have verified the success of computer-assisted dermatologist tools in the automatic diagnosis and detection of SC diseases. Previous AI-based dermatologist tools are based on features which are either high-level features based on DL methods or low-level features based on handcrafted operations. Most of them were constructed for binary classification of SC. This study proposes an intelligent dermatologist tool to accurately diagnose multiple skin lesions automatically. This tool incorporates manifold radiomics features categories involving high-level features such as ResNet-50, DenseNet-201, and DarkNet-53 and low-level features including discrete wavelet transform (DWT) and local binary pattern (LBP). The results of the proposed intelligent tool prove that merging manifold features of different categories has a high influence on the classification accuracy. Moreover, these results are superior to those obtained by other related AI-based dermatologist tools. Therefore, the proposed intelligent tool can be used by dermatologists to help them in the accurate diagnosis of the SC subcategory. It can also overcome manual diagnosis limitations, reduce the rates of infection, and enhance survival rates.

Objectives and Review of the International Milk Fluoridation Program

1995 ◽  
Vol 9 (2) ◽  
pp. 110-111 ◽  
Author(s):  
G.N. Pakhomo
Keyword(s):  
Dental Caries ◽  
National Level ◽  
Data Bank ◽  
Epidemiological Studies ◽  
Weighted Mean ◽  
Number Of Children ◽  
The World ◽  
Low Levels ◽  
High Level ◽  
Very High

The WHO Global Oral Data Bank (GODB) demonstrates wide varieties of dental caries levels. During the last 10 years, dental caries prevalence in many countries has decreased from very high and high to moderate and low levels. However, there also are countries where dental caries has increased from very low and low to a moderate level. In total in 1993, of the 158 countries for which the WHO GODB has data available, 16 countries indicate a very low level (69 - low, 53 - moderate, 17 - high), and only three a very high level of dental caries. Very high levels of dental caries have been recorded in Costa Rica, Jamaica, and Uruguay. All these data, based on the weighted mean of DMF in 12-year-old children, have been obtained from national surveys or collected from published papers on oral health surveys conducted in selected areas of the countries. Very often, these papers indicated an increase (or decrease) in dental caries in people living in different areas of a particular country; however, the DMF weighted mean at the national level is still without change. One of the most populated countries in the world, China, shows clear evidence from several recent epidemiological studies that the level of dental caries in the urban population is persistently increasing. Dental caries still remains one of the most common diseases affecting a substantial number of children and adults around the world. There is evidence that water or

scholarly journals Efficacy of vancomycin and teicoplanin alone and in combination with streptomycin in experimental, low-level vancomycin-resistant, VanB-type Enterococcus faecalis endocarditis.

1996 ◽  
Vol 40 (1) ◽  
pp. 55-60 ◽  
Author(s):  
D P Nicolau ◽  
M N Marangos ◽  
C H Nightingale ◽  
K B Patel ◽  
B W Cooper ◽  
...  
Keyword(s):  
Enterococcus Faecalis ◽  
Resistant Strain ◽  
Low Level ◽  
Vancomycin Resistant ◽  
Low Levels ◽  
High Level ◽  
Isogenic Strains ◽  
Level Resistance

The efficacy of vancomycin (VM) and teicoplanin (TE), alone and in combination with streptomycin (SM), against enterococci that express low-level VanB-type VM resistance was investigated in experimental endocarditis using isogenic strains of Enterococcus faecalis susceptible to glycopeptides and aminoglycosides or inducibly resistant to low levels of VM (MIC = 16 micrograms/ml). VM was significantly less active against the resistant strain than against the susceptible strain, establishing that low-level VanB-type VM resistance can influence therapeutic efficacy. By contrast, TE had equally good activity against both strains. VM or TE combined with SM was synergistic and bactericidal against the resistant strain in vitro. While both combinations were efficient in reducing bacterial density in vivo, TE plus SM was significantly superior to VM plus SM if valve sterilization was considered. These data suggest that despite the presence of low-level VanB-type resistance, combination therapy with a glycopeptide and SM (and presumably other aminoglycosides to which there is not high-level resistance) will nevertheless provide effective bactericidal activity.

Influence of low-frequency variability on groundwater level trends

2022 ◽  
pp. 127436
Author(s):  
Lisa Baulon ◽  
Delphine Allier ◽  
Nicolas Massei ◽  
Hélène Bessiere ◽  
Matthieu Fournier ◽  
...  
Keyword(s):  
Groundwater Level ◽  
Low Frequency ◽  
Low Frequency Variability

A dynamic very high-level debugger for low-level microprograms

1986 ◽  
Vol 17 (4) ◽  
pp. 148-155
Author(s):  
N. J. Wahl ◽  
S. R. Schach ◽  
R. I. Winner
Keyword(s):  
Low Level ◽  
High Level ◽  
Very High

scholarly journals Heat-Intolerance Syndrome subsequent Foot-and-Mouth Disease in Cattle; ThiQar –Iraq

2012 ◽  
Vol 36 (0E) ◽  
pp. 286-292
Author(s):  
Adil M. Abbas
Keyword(s):  
Cortisol Level ◽  
Clinical Signs ◽  
Foot And Mouth Disease ◽  
Mouth Disease ◽  
Infected Cattle ◽  
Low Level ◽  
Foot And Mouth ◽  
Radio Immunoassay ◽  
Low Levels ◽  
High Level

The investigation on Heat-Intolerance Syndrome following foot and mouth disease (FMD) infection in cattle in ThiQar–Iraq, used 3ABC FMD ELISA kit, and Radio- immunoassay (RIA) to detect the cortisol level. From 105 there were 65(62%) infected cattle with FMD, which was high at 5- less 8 years old, while the cortrisol level showed three levels; normal (13-21 nmol⁄L), high and low levels were; 6(5.6%), 44(42%) and 55(52%) subsequently. More over the combined result of ELISA and RIA had divided cattle into six groups. First group of 40(38%) cattle infected with FMD and had low level of cortisol, this group containing 21(20%) with clinical signs of heat intolerance. Second group contain 22(21%) FMD infected cattle with high level of cortisol. Third group of 3(2.8%) FMD Infected cattle but normal cortisol level. Fourth group included 3(2.8%) not infected by FMD with normal cortisol level. Fifth group contain 22(21%) not infected with FMD but had high level of cortisol may related to stress. Sixth group consisted 15 (14%) cattle not infected with FMD and had low level of cortisol due to un known cause.Clinical signs of heat intolerance that showed in 21 head of cattle in the first group were: panting, overgrowth of hair coat, emaciation and seeking for shad. The diseased cow known locally as ”Mahrorah” meaning heat-intolerance.

scholarly journals Exploration of the Relationships Among Narcissism, Life Satisfaction, and Loneliness of Instagram Users and the High- and Low-Level Features of Their Photographs

2021 ◽  
Vol 12 ◽  
Author(s):  
Yunhwan Kim ◽  
Dongyan Nan ◽  
Jang Hyun Kim
Keyword(s):  
Life Satisfaction ◽  
Online Survey ◽  
Predictive Analysis ◽  
Low Level ◽  
Acceptable Accuracy ◽  
Cognitive Services ◽  
Application Programming ◽  
Low Levels ◽  
High Level ◽  
Programming Interfaces

We examined the associations between the characteristics of Instagram users and the features of their photographs. Narcissism, life satisfaction, and loneliness were employed for user variables and the features at high- (content) and low-levels (pixel) were employed to analyze the Instagram photographs. An online survey was conducted with 179 university students, and their Instagram photographs, 25,394 in total, were collected and analyzed. High-level features were extracted using Computer Vision and Emotion Application Programming Interfaces (APIs) in Microsoft Azure Cognitive Services, and low-level features were extracted utilizing the program written by the authors. The results of correlation analysis indicate that narcissism, life satisfaction, and loneliness were significantly associated with a part of photograph features at high- and low-levels. The results of the predictive analysis suggest that narcissism, loneliness in total, and social loneliness could be predicted with acceptable accuracy from Instagram photograph features, while characteristics such as life satisfaction, family loneliness, and romantic loneliness could not be predicted. Implications of this research and suggestions for further research were presented.

scholarly journals THE STUDENTS’ COMPREHENSION IN ANALYZING ENGLISH TEXT OF THE MA DARUL FURQAN NW MENGKURU GRADERS

2019 ◽  
Vol 4 (5) ◽  
Author(s):  
Mul Muliadi
Keyword(s):  
English Text ◽  
Average Level ◽  
Low Level ◽  
The Mean ◽  
High Level ◽  
Very High

This research is aimed to measure the students’ compression in analyzing English text for the students of MA Darul Furqan NW Mengkuru. The students’ comprehension in analyzing English text for the tenth year students of MA Darul Furqan NW Mengkuru are in average level. It can be seen from the mean score of the students that is 31.35 in which this number belongs average level. The percentages of successes of students’ comprehension in analyzing English text for the tenth year students of MA Darul Furqan NW Mengkuru are low. After the scores were classified for the students’ comprehension in analyzing English text, the researcher found 4 students who got very high score. It means that there were 13.33% of them were categorized very high level. Furthermore, there were 4 students who got high level; it means that there were 13.33% of students who were categorized high level. There were7 students who got sufficient level; it means that there were 23.33% of students who were categorized high level, and there were 15 students who got low level; it means that there were 50% of students who were categorized low level, moreover, there were none of students who got very. 

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