Analysis of the relationship binding in situ gamma count rates and soil sample activities: Implication on radionuclide inventory and uncertainty estimates due to spatial variability

2018 ◽  
Vol 192 ◽  
pp. 349-361 ◽  
Author(s):  
Huong Liên Nguyen ◽  
Chantal de Fouquet ◽  
Christelle Courbet ◽  
Rodolfo Gurriaran ◽  
Valery Kashparov ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Sample ◽  
Uncertainty Estimates ◽  
Radionuclide Inventory ◽  
The Relationship

scholarly journals High frequency un-mixing of soil samples using a submerged spectrophotometer in a laboratory setting—implications for sediment fingerprinting

2021 ◽  
Author(s):  
Niels F. Lake ◽  
Núria Martínez-Carreras ◽  
Peter J. Shaw ◽  
Adrian L. Collins
Keyword(s):  
Particle Size ◽  
Soil Sample ◽  
Suspended Sediment ◽  
Temporal Frequency ◽  
Soil Samples ◽  
Sediment Sources ◽  
High Temporal Frequency ◽  
Novel Method ◽  
The Relationship

Abstract Purpose This study tests the feasibility of using a submersible spectrophotometer as a novel method to trace and apportion suspended sediment sources in situ and at high temporal frequency. Methods Laboratory experiments were designed to identify how absorbance at different wavelengths can be used to un-mix artificial mixtures of soil samples (i.e. sediment sources). The experiment consists of a tank containing 40 L of water, to which the soil samples and soil mixtures of known proportions were added in suspension. Absorbance measurements made using the submersible spectrophotometer were used to elucidate: (i) the effects of concentrations on absorbance, (ii) the relationship between absorbance and particle size and (iii) the linear additivity of absorbance as a prerequisite for un-mixing. Results The observed relationships between soil sample concentrations and absorbance in the ultraviolet visible (UV–VIS) wavelength range (200–730 nm) indicated that differences in absorbance patterns are caused by soil-specific properties and particle size. Absorbance was found to be linearly additive and could be used to predict the known soil sample proportions in mixtures using the MixSIAR Bayesian tracer mixing model. Model results indicate that dominant contributions to mixtures containing two and three soil samples could be predicted well, whilst accuracy for four-soil sample mixtures was lower (with respective mean absolute errors of 15.4%, 12.9% and 17.0%). Conclusion The results demonstrate the potential for using in situ submersible spectrophotometer sensors to trace suspended sediment sources at high temporal frequency.

Profile Imaging of Silicon Surface Reconstructions

1985 ◽  
Vol 43 ◽  
pp. 262-263
Author(s):  
O.L. Krivanek ◽  
G.J. Wood
Keyword(s):  
Electron Microscopy ◽  
Surface Structure ◽  
Structure Determination ◽  
Silicon Surface ◽  
Good Resolution ◽  
Surface Reconstructions ◽  
Bulk Structure ◽  
Point To Point ◽  
The Relationship

Electron microscopy at 0.2nm point-to-point resolution, 10-10 torr specimei region vacuum and facilities for in-situ specimen cleaning presents intere; ing possibilities for surface structure determination. Three methods for examining the surfaces are available: reflection (REM), transmission (TEM) and profile imaging. Profile imaging is particularly useful because it giv good resolution perpendicular as well as parallel to the surface, and can therefore be used to determine the relationship between the surface and the bulk structure.

A combined ultrastructural and gene molecular research for the relationship between human uterine cervical carcinoma and human papillomavirus

1990 ◽  
Vol 48 (3) ◽  
pp. 204-205
Author(s):  
Kun Lee ◽  
Jingyi Si ◽  
Ricai Han ◽  
Wei Zhang ◽  
Bingbing Tan ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Human Papillomavirus ◽  
Intraepithelial Neoplasia ◽  
Hpv Infection ◽  
Dot Blot ◽  
Homologous Sequences ◽  
Normal Cervical Epithelium ◽  
The Relationship ◽  
Chronic Cervicitis

There are more supports for the view that human papillomavirus (HPV) infection might be an etiological factor in the development of cervical cancer when the association of persistent condylomata is considered. Biopsies from 318 cases with squamous cell carcinoma of uterine cervix, 48 with cervical and vulvar condylomata, 14 with cervical intraepithelial neoplasia (CIN), 34 with chronic cervicitis and 24 normal cervical epithelium were collected from 5 geographic regions of China with different cervical cancer mortalities. All specimens were prepared for Dot blot, Southern blot and in situ DNA-DNA hybridizations by using HPV-11, 16, 18 DNA labelled with 32P and 3H as probes to detect viral homologous sequences in samples. Among them, 32 cases with cervical cancer, 27 with condyloma and 10 normal cervical epitheliums were randomly chosen for comparative EM observation. The results showed that: 1), 192 out of 318 (60.4%) cases of cervical cancer were positive for HPV-16 DNA probe (Table I)

scholarly journals Novel hydrogen chemisorption properties of amorphous ceramic compounds consisting of p-block elements: exploring Lewis acid-base Al–N pair site formed in-situ within polymer-derived silicon-aluminum-nitrogen-based system

2021 ◽  
Author(s):  
Shotaro Tada ◽  
Norifumi Asakuma ◽  
Shiori Ando ◽  
Toru Asaka ◽  
Yusuke Daiko ◽  
...  
Keyword(s):  
Lewis Acid ◽  
Active Site ◽  
Hydrogen Chemisorption ◽  
Acid Base ◽  
Polymer Derived Ceramics ◽  
System P ◽  
Ceramic Compounds ◽  
The Relationship

This paper reports on the relationship between the H2 chemisorption properties and reversible structural reorientation of the possible active site around Al formed in-situ within polymer-derived ceramics (PDCs) based on...

scholarly journals Comparison of the Concentration of Risk Elements in Alluvial Soils Determined by pXRF In Situ, in the Laboratory, and by ICP-OES

Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 938
Author(s):  
Ladislav Menšík ◽  
Lukáš Hlisnikovský ◽  
Pavel Nerušil ◽  
Eva Kunzová
Keyword(s):  
Precision Agriculture ◽  
Alluvial Soil ◽  
Coefficient Of Determination ◽  
Fast Method ◽  
Agricultural Practice ◽  
Regression Equations ◽  
Icp Oes ◽  
Risk Elements ◽  
The Relationship

The aim of the study was to compare the concentrations of risk elements (As, Cu, Mn, Ni, Pb, Zn) in alluvial soil, which were measured by a portable X-ray fluorescence analyser (pXRF) in situ (FIELD) and in the laboratory (LABORATORY). Subsequently, regression equations were developed for individual elements through the method of construction of the regression model, which compare the results of pXRF with classical laboratory analysis (ICP-OES). The accuracy of the measurement, expressed by the coefficient of determination (R2), was as follows in the case of FIELD–ICP-OES: Pb (0.96), Zn (0.92), As (0.72), Mn (0.63), Cu (0.31) and Ni (0.01). In the case of LABORATORY–ICP-OES, the coefficients had values: Pb (0.99), Zn (0.98), Cu and Mn (0.89), As (0.88), Ni (0.81). A higher dependence of the relationship was recorded between LABORATORY–ICP-OES than between FIELD–ICP-OES. An excellent relationship was recorded for the elements Pb and Zn, both for FIELD and LABORATORY (R2 higher than 0.90). The elements Cu, Mn and As have a worse tightness in the relationship; however, the results of the model have shown its applicability for common use, e.g., in agricultural practice or in monitoring the quality of the environment. Based on our results, we can say that pXRF instruments can provide highly accurate results for the concentration of risk elements in the soil in real time for some elements and meet the principle of precision agriculture: an efficient, accurate and fast method of analysis.

How landscape and climate affect the spatial variability of the Italian rainfall extremes? Some initial clues based on I2-RED

2021 ◽  
Author(s):  
Paola Mazzoglio ◽  
Ilaria Butera ◽  
Pierluigi Claps
Keyword(s):  
Spatial Variability ◽  
Linear Regression Analysis ◽  
Alpine Region ◽  
Annual Rainfall ◽  
Mean Values ◽  
Rainfall Extremes ◽  
Geomorphological Parameters ◽  
The Mean ◽  
The Relationship ◽  
Italian Territory

<p>The intensity and the spatial distribution of precipitation depths are known to be highly dependent on relief and geomorphological parameters. Complex environments like mountainous regions are prone to intense and frequent precipitation events, especially if located near the coastline. Although the link between the mean annual rainfall and geomorphological parameters has received substantial attention, few literature studies investigate the relationship between the sub-daily maximum annual rainfall depth and geographical or morphological landscape features.<br>In this study, the mean of the rainfall extremes in Italy, recently revised in the so-called I<sup>2</sup>-RED dataset, are investigated in their spatial variability in comparison with some landscape and also some broad climatic characteristics. The database includes all sub-daily rainfall extremes recorded in Italy from 1916 until 2019 and this analysis considers their mean values (from 1 to 24 hours) in stations with at least 10 years of records, involving more than 3700 stations.<br>The geo-morpho-climatic factors considered range from latitude, longitude and minimum distance from the coastline on the geographic side, to elevation, slope, openness and obstruction morphological indices, and also include an often-neglected robust climatological information, as the local mean annual rainfall.<br>Obtained results highlight that the relationship between the annual maximum rainfall depths and the hydro-geomorphological parameters is not univocal over the entire Italian territory and over different time intervals. Considering the whole of Italy, the highest correlation is reached between the mean values of the 24-hours records and the mean annual precipitation (correlation coefficient greater than 0.75). This predominance remains also in sub-areas of the Italian territory (i.e., the Alpine region, the Apennines or the coastal areas) but correlation decreases as the time interval decreases, except for the Alpine region (0.73 for the 1-hour maximum). The other geomorphological parameters seem to act in conjunction, making it difficult to evaluate, with a simple linear regression analysis, their impact. As an example, the absolute value of the correlation coefficient between the elevation and the 1-hour extremes is greater than 0.35 for the Italian and the Alpine regions, while for the 24-hours interval it is greater than 0.35 over the coastal areas.<br>To further investigate the spatial variability of the relationship between rainfall and elevation, a spatial linear regression analysis has been undertaken. Local linear relationships have been fitted in circles centered on any of the 0.5-km size pixels in Italy, with 1 to 30 km radius and at least 5 stations included. Results indicate the need of more comprehensive terrain analysis to better understand the causes of local increasing or decreasing relations, poorly described in the available literature.</p>

Mechanically Aspirated Solar Radiation Shields: A CFD and Neural Network Design Analysis

2001 ◽  
Author(s):  
B. M. Fichera ◽  
R. L. Mahajan ◽  
T. W. Horst
Keyword(s):  
Neural Network ◽  
Solar Radiation ◽  
Temperature Sensor ◽  
Temperature Measurements ◽  
Analysis And Design ◽  
Computational Fluid Dynamics Analysis ◽  
Radiation Shields ◽  
Input Variables ◽  
The Relationship

Abstract Accurate air temperature measurements made by surface meteorological stations are demanded by climate research programs for various uses. Heating of the temperature sensor due to inadequate coupling with the environment can lead to significant errors. Therefore, accurate in-situ temperature measurements require shielding the sensor from exposure to direct and reflected solar radiation, while also allowing the sensor to be brought into contact with atmospheric air at the ambient temperature. The difficulty in designing a radiation shield for such a temperature sensor lies in satisfying these two conditions simultaneously. In this paper, we perform a computational fluid dynamics analysis of mechanically aspirated radiation shields (MARS) to study the effect of geometry, wind speed, and interplay of multiple heat transfer processes. Finally, an artificial neural network model is developed to learn the relationship between the temperature error and specified input variables. The model is then used to perform a sensitivity analysis and design optimization.

Sign in / Sign up

Export Citation Format

Share Document