Laboratory study of the influence of salinity on the relationship between electrical conductivity and wetness of snow

2010 ◽  
pp. n/a-n/a
Author(s):  
Nils Granlund ◽  
Angela Lundberg ◽  
David Gustafsson
Keyword(s):  
Electrical Conductivity ◽  
Laboratory Study ◽  
The Relationship

scholarly journals Prediction of Reproductive Success in Multiparous First Service Dairy Cows by Parameters from In-Line Sensors

Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 334
Author(s):  
Ramūnas Antanaitis ◽  
Vida Juozaitienė ◽  
Dovilė Malašauskienė ◽  
Mindaugas Televičius ◽  
Mingaudas Urbutis ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Blood Parameters ◽  
Negative Energy ◽  
Hydroxybutyric Acid ◽  
Pregnancy Status ◽  
Group A ◽  
Biochemical Indices ◽  
Relationship Of ◽  
The Relationship

The aim of the current study was to evaluate the relationship of different parameters from an automatic milking system (AMS) with the pregnancy status of multiparous cows at first service and to assess the accuracy of such a follow-up with regard to blood parameters. Before the insemination of cows, blood samples for measuring biochemical indices were taken from the coccygeal vessels and the concentrations of blood serum albumin (ALB), cortisol, non-esterified fatty acids (NEFA) and the activities of aspartate aminotransferase (AST) and gamma glutamyltransferase (GGT) were determined. From oestrus day to seven days after oestrus, the following parameters were registered: milk yield (MY), electric milk conductivity, lactate dehydrogenase (LDH) and β-hydroxybutyric acid (BHB). The pregnancy status was evaluated using ultrasound “Easy scan” 30–35 days after insemination. Cows were grouped by reproductive status: PG− (non-pregnant; n = 48) and PG+ (pregnant; n = 44). The BHB level in PG− cows was 1.2 times higher (p < 0.005). The electrical conductivity of milk was statistically significantly higher in all quarters of PG− cows (1.07 times) than of PG+ cows (p < 0.05). The arithmetic mean of blood GGT was 1.61 times higher in PG− cows and the NEFA value 1.23 times higher (p < 0.05) compared with the PG+ group. The liver function was affected, the average ALB of PG− cows was 1.19 times lower (p < 0.05) and the AST activity was 1.16 times lower (p < 0.05) compared with PG+ cows. The non-pregnant group had a negative energy balance demonstrated by high in-line milk BHB and high blood NEFA concentrations. We found a greater number of cows with cortisol >0.0.75 mg/dL in the non-pregnant group. A higher milk electrical conductivity in the non-pregnant cows pointed towards a greater risk of mastitis while higher GGT activities together with lower albumin concentrations indicated that the cows were more affected by oxidative stress.

scholarly journals Investigation of the relationship between landform classes and electrical conductivity (EC) of water and soil using a fuzzy model in a GIS environment

Solid Earth ◽  
2016 ◽  
Vol 7 (3) ◽  
pp. 873-880
Author(s):  
Marzieh Mokarram ◽  
Dinesh Sathyamoorthy
Keyword(s):  
Electrical Conductivity ◽  
Fuzzy Model ◽  
Chemical Properties ◽  
Geographical Information ◽  
Fars Province ◽  
Fuzzy Method ◽  
The North ◽  
The Relationship ◽  
Very High ◽  
Soil And Water

Abstract. Soil genesis is highly dependent on landforms as they control the erosional processes and the soil physical and chemical properties. The relationship between landform classification and electrical conductivity (EC) of soil and water in the northern part of Meharloo watershed, Fars province, Iran, was investigated using a combination of a geographical information system (GIS) and a fuzzy model. The results of the fuzzy method for water EC showed 36.6 % of the land to be moderately land suitable for agriculture; high, 31.69 %; and very high, 31.65 %. In comparison, the results of the fuzzy method for soil EC showed 24.31 % of the land to be as not suitable for agriculture (low class); moderate, 11.78 %; high, 25.74 %; and very high, 38.16 %. In total, the land suitable for agriculture with low EC is located in the north and northeast of the study area. The relationship between landform and EC shows that EC of water is high for the valley classes, while the EC of soil is high in the upland drainage class. In addition, the lowest EC levels for soil and water are in the plains class.

Laboratory test of snow wetness influence on electrical conductivity measured with ground penetrating radar

2009 ◽  
Vol 40 (1) ◽  
pp. 33-44 ◽  
Author(s):  
Nils Granlund ◽  
Angela Lundberg ◽  
James Feiccabrino ◽  
David Gustafsson
Keyword(s):  
Electrical Conductivity ◽  
Electrical Properties ◽  
Laboratory Test ◽  
Liquid Water ◽  
Ground Penetrating Radar ◽  
Wave Attenuation ◽  
Radar Measurements ◽  
Ground Penetrating ◽  
Radar Wave ◽  
The Relationship

Ground penetrating radar operated from helicopters or snowmobiles is used to determine snow water equivalent (SWE) for annual snowpacks from radar wave two-way travel time. However, presence of liquid water in a snowpack is known to decrease the radar wave velocity, which for a typical snowpack with 5% (by volume) liquid water can lead to an overestimation of SWE by about 20%. It would therefore be beneficial if radar measurements could also be used to determine snow wetness. Our approach is to use radar wave attenuation in the snowpack, which depends on electrical properties of snow (permittivity and conductivity) which in turn depend on snow wetness. The relationship between radar wave attenuation and these electrical properties can be derived theoretically, while the relationship between electrical permittivity and snow wetness follows a known empirical formula, which also includes snow density. Snow wetness can therefore be determined from radar wave attenuation if the relationship between electrical conductivity and snow wetness is also known. In a laboratory test, three sets of measurements were made on initially dry 1 m thick snowpacks. Snow wetness was controlled by stepwise addition of water between radar measurements, and a linear relationship between electrical conductivity and snow wetness was established.

Studies on water damage in mungbean. II. Electrical conductivity of seed leachate as an assay of level of damage

1995 ◽  
Vol 46 (5) ◽  
pp. 901 ◽  
Author(s):  
RW Williams ◽  
RJ Lawn ◽  
BC Imrie ◽  
DE Byth
Keyword(s):  
Electrical Conductivity ◽  
Previous Exposure ◽  
Wetting And Drying ◽  
Resistant Cultivars ◽  
Visual Damage ◽  
Seed Leachate ◽  
Weather Damage ◽  
The Relationship ◽  
Weathering Process ◽  
Bean Sprouts

Weather-damaged seeds of mungbean are unsuitable for the production of bean sprouts and some other food uses. The breeding of resistant cultivars requires an understanding of the weathering process and the use of suitable criteria for measuring the degree of weather damage. The aim of this research was to describe the effect of weathering on the electrical conductivity of leachate from exposed seeds and to evaluate this technique as a means of discriminating among levels of weather damage. Seeds were weathered in the field or immersed in water in the laboratory for varying durations during one or more cycles of wetting and drying. Leachate conductivities generally increased with increasing visual damage and decreasing viability of seeds. When measurements of conductivity were delayed, the results appeared to be confounded by the extent to which solutes were lost during previous exposure/s to weathering. Measurements soon after immersion tended to reduce this effect and to better reflect the level of weather damage in seeds of mungbean. It was concluded that leachate conductivity technique can provide a reliable assay of weather damage in mungbean. When seeds have been exposed to severe weathering, however, the relationship breaks down, and the technique can give misleading results.

An improvement to the ANN-enhanced flow rating method

2021 ◽  
Author(s):  
Bernhard Schmid
Keyword(s):  
Neural Network ◽  
Electrical Conductivity ◽  
Water Resources ◽  
Flow Rate ◽  
Major Ions ◽  
Rate Of Change ◽  
Data Set ◽  
Input Variables ◽  
Relationship Of ◽  
The Relationship

&lt;p&gt;The work reported here builds upon a previous pilot study by the author on ANN-enhanced flow rating (Schmid, 2020), which explored the use of electrical conductivity (EC) in addition to stage to obtain &amp;#8216;better&amp;#8217;, i.e. more accurate and robust, estimates of streamflow. The inclusion of EC has an advantage, when the relationship of EC versus flow rate is not chemostatic in character. In the majority of cases, EC is, indeed, not chemostatic, but tends to decrease with increasing discharge (so-called dilution behaviour), as reported by e.g. Moatar et al. (2017), Weijs et al. (2013) and Tunqui Neira et al.(2020). This is also in line with this author&amp;#8217;s experience.&lt;/p&gt;&lt;p&gt;The research presented here takes the neural network based approach one major step further and incorporates the temporal rate of change in stage and the direction of change in EC among the input variables (which, thus, comprise stage, EC, change in stage and direction of change in EC). Consequently, there are now 4 input variables in total employed as predictors of flow rate. Information on the temporal changes in both flow rate and EC helps the Artificial Neural Network (ANN) characterize hysteretic behaviour, with EC assuming different values for falling and rising flow rate, respectively, as described, for instance, by Singley et al. (2017).&lt;/p&gt;&lt;p&gt;The ANN employed is of the Multilayer Perceptron (MLP) type, with stage, EC, change in stage and direction of change in EC of the M&amp;#246;dling data set (Schmid, 2020) as input variables. Summarising the stream characteristics, the M&amp;#246;dling brook can be described as a small Austrian stream with a catchment of fairly mixed composition (forests, agricultural and urbanized areas). The relationship of EC versus flow reflects dilution behaviour. Neural network configuration 4-5-1 (the 4 input variables mentioned above, 5 hidden nodes and discharge as the single output) with learning rate 0.05 and momentum 0.15 was found to perform best, with testing average RMSE (root mean square error) of the scaled output after 100,000 epochs amounting to 0.0138 as compared to 0.0216 for the (best performing) 2-5-1 MLP with stage and EC as inputs only. &amp;#160;&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References&lt;/p&gt;&lt;p&gt;Moatar, F., Abbott, B.W., Minaudo, C., Curie, F. and Pinay, G.: Elemental properties, hydrology, and biology interact to shape concentration-discharge curves for carbon, nutrients, sediment and major ions. Water Resources Res., 53, 1270-1287, 2017.&lt;/p&gt;&lt;p&gt;Schmid, B.H.: Enhanced flow rating using neural networks with water stage and electrical conductivity as predictors. EGU2020-1804, EGU General Assembly 2020.&lt;/p&gt;&lt;p&gt;Singley, J.G., Wlostowski, A.N., Bergstrom, A.J., Sokol, E.R., Torrens, C.L., Jaros, C., Wilson, C.,E., Hendrickson, P.J. and Gooseff, M.N.: Characterizing hyporheic exchange processes using high-frequency electrical conductivity-discharge relationships on subhourly to interannual timescales. Water Resources Res. 53, 4124-4141, 2017.&lt;/p&gt;&lt;p&gt;Tunqui Neira, J.M., Andr&amp;#233;assian, V., Tallec, G. and Mouchel, J.-M.: A two-sided affine power scaling relationship to represent the concentration-discharge relationship. Hydrol. Earth Syst. Sci. 24, 1823-1830, 2020.&lt;/p&gt;&lt;p&gt;Weijs, S.V., Mutzner, R. and Parlange, M.B.: Could electrical conductivity replace water level in rating curves for alpine streams? Water Resources Research 49, 343-351, 2013.&lt;/p&gt;

Relation of Spelling and Writing in Learning Disabilities

1987 ◽  
Vol 64 (1) ◽  
pp. 219-236 ◽  
Author(s):  
Nils Søvik ◽  
Oddvar Arntzen ◽  
Ragnar Thygesen
Keyword(s):  
Learning Disabilities ◽  
Laboratory Study ◽  
Orthogonal Design ◽  
Type Structure ◽  
Spelling Errors ◽  
Independent Variables ◽  
Psychomotor Functions ◽  
Writing Accuracy ◽  
The Relationship

The paper describes a study in which the relationship between the cognitive and psychomotor aspects of children's spelling and writing performances was investigated. By comparing data from various categories of children the relationship between the semantic and psychomotor functions could be examined, and differences between the skill performances of the three groups of students were predicted. A four-way 3 × 3 × 2 × 2 orthogonal design with categories of subjects, type, structure, and length of task as independent variables was used in the laboratory study, with 24 “normal”, 24 dyslexic, and 24 dysgraphic nine-year-old children as subjects. Most of the 16 hypotheses were verified by data identifying some of the spelling and writing characteristics of the three groups of children and the effects of contextual parameters on their performances. Dyslexic children, for example, seemed to write more slowly than the others, and their mean score of spelling errors was the highest one, whereas the dysgraphic children had the lowest mean score in writing accuracy and rhythm.

Analysis of Characteristics of Bubble on Electrode Surface of Forced Convective Electrolyte Using Image Processing

2019 ◽  
Author(s):  
Jaewon Lee ◽  
Dong Kee Sohn ◽  
Han Seo Ko
Keyword(s):  
Electrical Conductivity ◽  
Forced Convection ◽  
Storage Systems ◽  
Potential Drop ◽  
Electrolyte Flow ◽  
Flow Configuration ◽  
The Difference ◽  
Gas Layer ◽  
The Relationship ◽  
Electrolysis System

Abstract ‘Electrolysis’ is a technology about the transport of electrons caused by placing electrodes in an electrolyte using the difference of electric potential. It has been applied to various industrial fields, e.g., energy storage systems (ESS), fuel cells, and water treatment. Despite the outwardly simple phenomenon of this technology, it has been investigated because of the complex electro-physical process inside the electrolysis system, which can be designed in various ways. Two plate electrodes placed on a bulk of electrolyte is the most common electrolysis system. The electrolysis systems can be identified by the electrolyte flow, such as Forced convection configuration (FCC), Forced convection-induced circulation configuration (FCICC), and No net flow configuration (NNFC). The purpose of the study about the bubbles around the electrodes was to characterize the potential drop induced by the existence of the bubbles in the electric field. The dispersed bubbles, which have less electrical conductivity than does the bulk of the electrolyte, can reduce the efficiency of electrolysis. Therefore, in order to study the relationship between the electrical properties in the channel and the gas layer, the equation was derived with the void fraction and other electrical variables.

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