Relationship of Electrical Conductivity in the Detonation of Condensed Explosives with Their Carbon Content

2016 ◽  
Keyword(s):  
Electrical Conductivity ◽  
Carbon Content ◽  
Condensed Explosives ◽  
Relationship Of

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 Manipulation of Chemical Properties in Soil under Wetland Rice through Industrial Effluents

2019 ◽  
pp. 1-15
Author(s):  
Md. Rafiqul Islam ◽  
Golam Kibria Muhammad Mustafizur Rahman ◽  
Md. Abu Saleque
Keyword(s):  
Electrical Conductivity ◽  
Organic Carbon ◽  
Carbon Content ◽  
Rice Field ◽  
Soil Depth ◽  
Chemical Properties ◽  
Industrial Effluents ◽  
Rice Fields ◽  
Organic Carbon Content ◽  
Irrigated Rice

A laboratory experiment was conducted in Soil Science Division of Bangladesh Rice Research Institute (BRRI) during 2010-11 aimed to determine the effects of different industrial effluents on some soil chemical properties under long-term industrial wastewater irrigated rice field. Effluents irrigation created some differences in soil pH, electrical conductivity and organic carbon. The pH in all soil depth was higher with wastewater irrigated rice field. Irrigation with wastewater increased in all the effluents irrigated rice fields; the electrical conductivity (EC) was remarkable higher with  all soil depth than the control field. In all the rice fields soil (Control + effluents irrigated fields), the organic carbon content (%) started to decrease sharply with the increase in soil depth. Organic carbon content was slightly higher with wastewater irrigated rice soils. Exchangeable cations (Ca, Mg, K and Na), trace elements (Zn, Fe, Mn and Cu) and heavy metals (Pb, Cd, Cr and Ni) were increased through irrigation with wastewater in rice–rice cropping pattern.

Structure-Electrical Transport Property Relationship of Anisotropic iPP/CNT Films

2013 ◽  
Vol 1499 ◽  
Author(s):  
Parvathalu Kalakonda ◽  
Michael Daly ◽  
Kaikai Xu ◽  
Yaniel Cabrera ◽  
Robert Judith ◽  
...  
Keyword(s):  
Electrical Conductivity ◽  
Electrical Transport ◽  
Preparation Method ◽  
Weight Percent ◽  
Electrical Transport Properties ◽  
Oriented Polymer ◽  
Nano Composite ◽  
Nano Structure ◽  
Relationship Of ◽  
Fine Tune

ABSTRACTThe internal micro/nano-structure of anisotropically oriented polymer/CNTs composites determines their macroscopic properties. However, the connections between the two are not fully understood. The varying of CNT concentration, preparation method, and a thermodynamic parameter (e.g. temperature) can all play interconnected role. In this work, the macroscopic electrical conductivity was measured perpendicular to the film thickness of an insulating polymer (isotactic PolyPropylene, iPP) and a nano-composite of iPP with 5 weight percent of CNT. The thin films studied were sheared (anisotropically nano-structured) and non-sheared (with random internal structure). In general the effect of melt shearing induces anisotropy on the electrical transport properties of the iPP/CNT films in directions parallel and perpendicular to the direction of orientation. Our results show that for the pure iPP, resistivity slightly increases with shear at higher temperatures. When CNTs are introduced, there is a large difference between the resistivity of the sheared and non-sheared nanocomposite. The sheared PNCs when the CNTs are aligned parallel to each other, have higher resistivity, which is possibly due to the higher concentration at which the percolation threshold occurs in this arrangement. The resistivity decreases overall, as the temperature increases from 0 to 50 °C. These results show that CNTs can be used to control and fine tune the desired macroscopic physical properties of nanocomposites, by concentration and orientation, such as electrical conductivity, for applications where such properties are necessary.

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;

First Pan-Arctic Assessment of Dissolved Organic Carbon Concentration in Permafrost-Region Lakes

2020 ◽  
Author(s):  
Lydia Stolpmann ◽  
Anne Morgenstern ◽  
Julia Boike ◽  
Michael Fritz ◽  
Ulrike Herzschuh ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Permafrost Region ◽  
Organic Carbon Content ◽  
Soil Organic Carbon Content ◽  
Doc Concentration ◽  
Deposit Type ◽  
Relationship Of ◽  
Global Carbon

&lt;p&gt;Permafrost-region lakes are dynamic landscape systems and play an important role for climate change feedbacks. Lake processes such as mineralization and flocculation of DOC, one of the main carbon fraction in lakes, contribute to the global carbon cycle. These processes are in focus of climate research but studies have been limited in geographic extent. We synthesized published datasets and unpublished datasets from the author team totaling 1,691 water samples from 1,387 lakes across the Subarctic and Arctic in permafrost regions of Alaska, Canada, Siberia, and Greenland to provide first insights for linkages between DOC concentration to the basin. In our synthesis, we find regional differences in DOC concentration of permafrost-region lakes. We focussed on relations between lake DOC concentration and latitude, permafrost zones, ecoregions, lake surrounding deposit type, and ground ice classification of each lake basin. Additionally, we analysed the lake surrounding soil organic carbon content from 0-100 cm depth and 0-300 cm depth. Individual lake DOC concentrations of our dataset range from below detection limit assigned to 0 mg L&lt;sup&gt;-1&lt;/sup&gt; (North Slope, Alaska) to 1,130 mg L&lt;sup&gt;-1&lt;/sup&gt; (Yukon Flats, Alaska). We found regional median lake DOC concentrations of 18.8 mg L&lt;sup&gt;-1&lt;/sup&gt; (Greenland, n=25), 12.2 mg L&lt;sup&gt;-1&lt;/sup&gt; (Alaska, n= 1,135), 9.6 mg L&lt;sup&gt;-1&lt;/sup&gt; (Siberia, n=252), and 7.2 mg L&lt;sup&gt;-1&lt;/sup&gt; (Canada, n=279). Lakes in the isolated permafrost zone had the highest median DOC concentration compared to lakes in the sporadic, discontinuous, and continuous permafrost zones. Our synthesis shows increasing lake DOC concentration with decreasing latitude and, due to a larger availability of biomass and organic carbon, a significant relationship of lake DOC concentration and ecoregion of the lake. We found higher lake DOC concentrations in boreal permafrost sites compared to tundra sites. About 22 % of lakes in our dataset are located in regions with ice-rich syngenetic permafrost deposits (yedoma). Because yedoma contains large amounts of organic carbon, we assumed to find higher DOC concentrations in yedoma lakes compared to non-yedoma lakes. Our analysis shows a significant relationship of lake DOC concentration and surrounding deposit type but not a higher DOC concentration in yedoma lakes compared to non-yedoma lakes. Finally, we found a relationship of soil organic carbon content from 0-100 cm depth and lake DOC concentration. In contrast, a comparison of soil organic carbon content from 0-300 cm depth and lake DOC concentration shows no significant correlation. This was also found for ground-ice content and lake DOC concentration. Our dataset of lakes across the Arctic shows that the DOC concentration of a lake strongly depends on its environmental properties. This dataset will be fundamental to establish a pan-Arctic lake DOC pool for estimations of the impact of lake DOC on the global carbon cycle and further on climate change.&lt;/p&gt;

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