scholarly journals Improved Application of Bomb Carbon in Teeth for Forensic Investigation

Radiocarbon ◽  
2010 ◽  
Vol 52 (2) ◽  
pp. 706-716 ◽  
Author(s):  
N Wang ◽  
C D Shen ◽  
P Ding ◽  
W X Yi ◽  
W D Sun ◽  
...  
Keyword(s):  
Organic Matter ◽  
Tooth Enamel ◽  
Isotopic Fractionation ◽  
Formation Time ◽  
Birth Date ◽  
Forensic Investigation ◽  
Enamel Formation ◽  
Data Set ◽  
Tooth Formation ◽  
The Difference

While radiocarbon is widely applied in dating ancient samples, recent studies reveal that 14C concentrations in modern samples can also yield precise ages due to the atmospheric testing of thermonuclear devices between 1950 and 1963. 14C concentrations in both enamel and organic matter of 13 teeth from 2 areas in China were examined to evaluate and improve this method of forensic investigation. Choosing enamel near the cervix of the tooth can reduce the error caused by the difference between the sample formation time and whole enamel formation time because tooth enamel formations take a long time to complete. A proper regional data set will be helpful to get an accurate result when calculating the age of the sample (T1) by the CALIBomb program. By subtracting the enamel formation time (t), the birth date of an individual (T2) can be confirmed by enamel F14C from 2 teeth formed at different ages. Calculated enamel formation dates by 14C concentration are basically consistent with corresponding actual values, with a mean error of 1.9 yr for all results and 0.2 yr for the samples formed after AD 1960. This method is more effective for dating samples completed after AD 1960. We also found that 14C concentrations in organic matter of tooth roots are much lower than atmospheric concentrations in root formation years, suggesting that the organic material keeps turning over even after tooth formation is complete. This might be a potential tool for identification of death age to extract a proper component for 14C dating. We also observed that δ13C values between hydroxyapatite and organic matter indicate that isotopic fractionation during the biomineralization is 8–9%‰ more positive in mineral fractions than in organic matter.

scholarly journals Methods to evaluate CaCO<sub>3</sub> cycle modules in coupled global biogeochemical ocean models

2014 ◽  
Vol 7 (5) ◽  
pp. 2393-2408 ◽  
Author(s):  
W. Koeve ◽  
O. Duteil ◽  
A. Oschlies ◽  
P. Kähler ◽  
J. Segschneider
Keyword(s):  
Organic Matter ◽  
Carbon Cycle ◽  
Numerical Models ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Biogeochemical Processes ◽  
Data Set ◽  
Ocean Physics ◽  
The Difference ◽  
Ocean Carbon

Abstract. The marine CaCO3 cycle is an important component of the oceanic carbon system and directly affects the cycling of natural and the uptake of anthropogenic carbon. In numerical models of the marine carbon cycle, the CaCO3 cycle component is often evaluated against the observed distribution of alkalinity. Alkalinity varies in response to the formation and remineralization of CaCO3 and organic matter. However, it also has a large conservative component, which may strongly be affected by a deficient representation of ocean physics (circulation, evaporation, and precipitation) in models. Here we apply a global ocean biogeochemical model run into preindustrial steady state featuring a number of idealized tracers, explicitly capturing the model's CaCO3 dissolution, organic matter remineralization, and various preformed properties (alkalinity, oxygen, phosphate). We compare the suitability of a variety of measures related to the CaCO3 cycle, including alkalinity (TA), potential alkalinity and TA*, the latter being a measure of the time-integrated imprint of CaCO3 dissolution in the ocean. TA* can be diagnosed from any data set of TA, temperature, salinity, oxygen and phosphate. We demonstrate the sensitivity of total and potential alkalinity to the differences in model and ocean physics, which disqualifies them as accurate measures of biogeochemical processes. We show that an explicit treatment of preformed alkalinity (TA0) is necessary and possible. In our model simulations we implement explicit model tracers of TA0 and TA*. We find that the difference between modelled true TA* and diagnosed TA* was below 10% (25%) in 73% (81%) of the ocean's volume. In the Pacific (and Indian) Oceans the RMSE of A* is below 3 (4) mmol TA m−3, even when using a global rather than regional algorithms to estimate preformed alkalinity. Errors in the Atlantic Ocean are significantly larger and potential improvements of TA0 estimation are discussed. Applying the TA* approach to the output of three state-of-the-art ocean carbon cycle models, we demonstrate the advantage of explicitly taking preformed alkalinity into account for separating the effects of biogeochemical processes and circulation on the distribution of alkalinity. In particular, we suggest to use the TA* approach for CaCO3 cycle model evaluation.

scholarly journals Evaluating CaCO<sub>3</sub>-cycle modules in coupled global biogeochemical ocean models

2013 ◽  
Vol 6 (4) ◽  
pp. 6117-6155 ◽  
Author(s):  
W. Koeve ◽  
O. Duteil ◽  
A. Oschlies ◽  
P. Kähler ◽  
J. Segschneider
Keyword(s):  
Organic Matter ◽  
Carbon Cycle ◽  
Numerical Models ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Biogeochemical Processes ◽  
Data Set ◽  
Ocean Physics ◽  
The Difference ◽  
Ocean Carbon

Abstract. The marine CaCO3 cycle is an important component of the oceanic carbon system and directly affects the cycling of natural and the uptake of anthropogenic carbon. In numerical models of the marine carbon cycle, the CaCO3 cycle component is often evaluated against the observed distribution of alkalinity. Alkalinity varies in response to the formation and remineralisation of CaCO3 and organic matter. However, it also has a large conservative component, which may strongly be affected by a deficient representation of ocean physics (circulation, evaporation, and precipitation) in models. Here we apply a global ocean biogeochemical model run into preindustrial steady state featuring a number of idealized tracers, explicitly capturing the model's CaCO3 dissolution, organic matter remineralisation, and various preformed properties (alkalinity, oxygen, phosphate). We compare the suitability of a variety of measures related to the CaCO3 cycle, including alkalinity (TA), potential alkalinity and TA*, the latter being a measure of the time-integrated imprint of CaCO3 dissolution in the ocean. It can be diagnosed from any data set of TA, temperature, salinity, oxygen and phosphate. We demonstrate the sensitivity of total and potential alkalinity to the differences in model and ocean physics, which disqualifies them as accurate measures of biogeochemical processes. We show that an explicit treatment of preformed alkalinity (TA0) is necessary and possible. In our model simulations we implement explicit model tracers of TA0 and TA*. We find that the difference between modeled true TA* and diagnosed TA* was below 10% (25%) in 73% (81%) of the ocean's volume. In the Pacific (and Indian) Oceans the RMS error of TA* is below 3 (4) mmol TA m−3, even when using a global rather than regional algorithms to estimate preformed alkalinity. Errors in the Atlantic Ocean are significantly larger and potential improvements of TA0 estimation are discussed. Applying the TA* approach to the output of three state-of-the-art ocean carbon cycle models we demonstrate the advantage of explicitly taking preformed alkalinity into account for separating the effects of biogeochemical processes and circulation on the distribution of alkalinity. In particular, we suggest to use the TA* approach for CaCO3-cycle model evaluation.

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

Event detection of different English data sources based on transfer learning

2021 ◽  
pp. 1-11
Author(s):  
Yanan Huang ◽  
Yuji Miao ◽  
Zhenjing Da
Keyword(s):  
Transfer Learning ◽  
Event Detection ◽  
Visual Analysis ◽  
Learning Algorithm ◽  
Data Sources ◽  
Data Set ◽  
Data Source ◽  
Single Data Source ◽  
The Difference ◽  
Single Data

The methods of multi-modal English event detection under a single data source and isomorphic event detection of different English data sources based on transfer learning still need to be improved. In order to improve the efficiency of English and data source time detection, based on the transfer learning algorithm, this paper proposes multi-modal event detection under a single data source and isomorphic event detection based on transfer learning for different data sources. Moreover, by stacking multiple classification models, this paper makes each feature merge with each other, and conducts confrontation training through the difference between the two classifiers to further make the distribution of different source data similar. In addition, in order to verify the algorithm proposed in this paper, a multi-source English event detection data set is collected through a data collection method. Finally, this paper uses the data set to verify the method proposed in this paper and compare it with the current most mainstream transfer learning methods. Through experimental analysis, convergence analysis, visual analysis and parameter evaluation, the effectiveness of the algorithm proposed in this paper is demonstrated.

scholarly journals Genetic and Genome-Wide Association Analysis of Yearling Weight Gain in Israel Holstein Dairy Calves

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 708
Author(s):  
Moran Gershoni ◽  
Joel Ira Weller ◽  
Ephraim Ezra
Keyword(s):  
Weight Gain ◽  
Milk Fat ◽  
Variance Components ◽  
Complete Data ◽  
Variance Component Analysis ◽  
Coefficient Of Determination ◽  
Birth Date ◽  
Analysis Model ◽  
Data Set ◽  
Genetic Evaluations

Yearling weight gain in male and female Israeli Holstein calves, defined as 365 × ((weight − 35)/age at weight) + 35, was analyzed from 814,729 records on 368,255 animals from 740 herds recorded between 1994 and 2021. The variance components were calculated based on valid records from 2008 through 2017 for each sex separately and both sexes jointly by a single-trait individual animal model analysis, which accounted for repeat records on animals. The analysis model also included the square root, linear, and quadratic effects of age at weight. Heritability and repeatability were 0.35 and 0.71 in the analysis of both sexes and similar in the single sex analyses. The regression of yearling weight gain on birth date in the complete data set was −0.96 kg/year. The complete data set was also analyzed by the same model as the variance component analysis, including both sexes and accounting for differing variance components for each sex. The genetic trend for yearling weight gain, including both sexes, was 1.02 kg/year. Genetic evaluations for yearling weight gain was positively correlated with genetic evaluations for milk, fat, protein production, and cow survival but negatively correlated with female fertility. Yearling weight gain was also correlated with the direct effect on dystocia, and increased yearling weight gain resulted in greater frequency of dystocia. Of the 1749 Israeli Holstein bulls genotyped with reliabilities >50%, 1445 had genetic evaluations. As genotyping of these bulls was performed using several single nucleotide polymorhphism (SNP) chip platforms, we included only those markers that were genotyped in >90% of the tested cohort. A total of 40,498 SNPs were retained. More than 400 markers had significant effects after permutation and correction for multiple testing (pnominal < 1 × 10−8). Considering all SNPs simultaneously, 0.69 of variance among the sires’ transmitting ability was explained. There were 24 markers with coefficients of determination for yearling weight gain >0.04. One marker, BTA-75458-no-rs on chromosome 5, explained ≈6% of the variance among the estimated breeding values for yearling weight gain. ARS-BFGL-NGS-39379 had the fifth largest coefficient of determination in the current study and was also found to have a significant effect on weight at an age of 13–14 months in a previous study on Holsteins. Significant genomic effects on yearling weight gain were mainly associated with milk production quantitative trait loci, specifically with kappa casein metabolism.

Soil stripping and replacement for the rehabilitation of bauxite-mined land at Weipa. I. Initial changes to soil organic matter and related parameters

Soil Research ◽  
2000 ◽  
Vol 38 (2) ◽  
pp. 345 ◽  
Author(s):  
G. D. Schwenke ◽  
D. R. Mulligan ◽  
L. C. Bell
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Field Experiments ◽  
Surface Soil ◽  
Soil Disturbance ◽  
Microbial Biomass C ◽  
Low Grade ◽  
Double Pass ◽  
Organic C ◽  
The Difference

At Weipa, in Queensland, Australia, sown tree and shrub species sometimes fail to establish on bauxite-mined land, possibly because surface-soil organic matter declines during soil stripping and replacement. We devised 2 field experiments to investigate the links between soil rehabilitation operations, organic matter decline, and revegetation failure. Experiment 1 compared two routinely practiced operations, dual-strip (DS) and stockpile soil, with double-pass (DP), an alternative method, and subsoil only, an occasional result of the DS operation. Other treatments included variations in stripping-time, ripping-time, fertiliser rate, and cultivation. Dilution of topsoil with subsoil, low-grade bauxite, and ironstone accounted for the 46% decline of surface-soil (0–10 cm) organic C in DS compared with pre-strip soil. In contrast, organic C in the surface-soil (0–10 cm) of DP plots (25.0 t/ha) closely resembled the pre-strip area (28.6 t/ha). However, profile (0–60 cm) organic C did not differ between DS (91.5 t/ha), DP (107 t/ha), and pre-strip soil (89.9 t/ha). Eighteen months after plots were sown with native vegetation, surface-soil (0–10 cm) organic C had declined by an average of 9% across all plots. In Experiment 2, we measured the potential for post-rehabilitation decline of organic matter in hand-stripped and replaced soil columns that simulated the DS operation. Soils were incubated in situ without organic inputs. After 1 year’s incubation, organic C had declined by up to 26% and microbial biomass C by up to 61%. The difference in organic C decline between vegetated replaced soils (Expt 1) and bare replaced soils (Expt 2) showed that organic inputs affect levels of organic matter more than soil disturbance. Where topsoil was replaced at the top of the profile (DP) and not ploughed, inputs from volunteer native grasses balanced oxidation losses and organic C levels did not decline.

Magnetotelluric static shift: Estimation and removal using the cokriging method

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. F25-F34 ◽  
Author(s):  
Benoit Tournerie ◽  
Michel Chouteau ◽  
Denis Marcotte
Keyword(s):  
Apparent Resistivity ◽  
A Priori ◽  
Shift Factor ◽  
Static Shift ◽  
Geostatistical Model ◽  
Data Set ◽  
Resistivity Sounding ◽  
The Difference ◽  
Cross Variogram

We present and test a new method to correct for the static shift affecting magnetotelluric (MT) apparent resistivity sounding curves. We use geostatistical analysis of apparent resistivity and phase data for selected periods. For each period, we first estimate and model the experimental variograms and cross variogram between phase and apparent resistivity. We then use the geostatistical model to estimate, by cokriging, the corrected apparent resistivities using the measured phases and apparent resistivities. The static shift factor is obtained as the difference between the logarithm of the corrected and measured apparent resistivities. We retain as final static shift estimates the ones for the period displaying the best correlation with the estimates at all periods. We present a 3D synthetic case study showing that the static shift is retrieved quite precisely when the static shift factors are uniformly distributed around zero. If the static shift distribution has a nonzero mean, we obtained best results when an apparent resistivity data subset can be identified a priori as unaffected by static shift and cokriging is done using only this subset. The method has been successfully tested on the synthetic COPROD-2S2 2D MT data set and on a 3D-survey data set from Las Cañadas Caldera (Tenerife, Canary Islands) severely affected by static shift.

scholarly journals What Countries Select More Experienced Leaders? The PolEx Measure of Political Experience

2021 ◽  
pp. 1-10
Author(s):  
Alexander Baturo ◽  
Johan A. Elkink
Keyword(s):  
Career Paths ◽  
Latent Variable ◽  
Empirical Studies ◽  
Future Research ◽  
Variable Model ◽  
Data Set ◽  
Political Experience ◽  
National Leaders ◽  
Regime Types ◽  
The Difference

Abstract How can one assess which countries select more experienced leaders for the highest office? There is wide variation in prior career paths of national leaders within, and even more so between, regime types. It is therefore challenging to obtain a truly comparative measure of political experience; empirical studies have to rely on proxies instead. This article proposes PolEx, a measure of political experience that abstracts away from the details of career paths and generalizes based on the duration, quality and breadth of an individual's experience in politics. The analysis draws on a novel data set of around 2,000 leaders from 1950 to 2017 and uses a Bayesian latent variable model to estimate PolEx. The article illustrates how the new measure can be used comparatively to assess whether democracies select more experienced leaders. The authors find that while on average they do, the difference with non-democracies has declined dramatically since the early 2000s. Future research may leverage PolEx to investigate the role of prior political experience in, for example, policy making and crisis management.

A generally applicable pedotransfer function that estimates field capacity and permanent wilting point from soil texture and bulk density

2008 ◽  
Vol 88 (5) ◽  
pp. 761-774 ◽  
Author(s):  
J. A. P. Pollacco
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Bulk Density ◽  
Soil Texture ◽  
The United States ◽  
Pedotransfer Functions ◽  
Pedotransfer Function ◽  
Data Set ◽  
Wide Range ◽  
Fitting Parameters

Hydrological models require the determination of fitting parameters that are tedious and time consuming to acquire. A rapid alternative method of estimating the fitting parameters is to use pedotransfer functions. This paper proposes a reliable method to estimate soil moisture at -33 and -1500 kPa from soil texture and bulk density. This method reduces the saturated moisture content by multiplying it with two non-linear functions depending on sand and clay contents. The novel pedotransfer function has no restrictions on the range of the texture predictors and gives reasonable predictions for soils with bulk density that varies from 0.25 to 2.16 g cm-3. These pedotransfer functions require only five parameters for each pressure head. It is generally accepted that the introduction of organic matter as a predictor improves the outcomes; however it was found by using a porosity based pedotransfer model, using organic matter as a predictor only modestly improves the accuracy. The model was developed employing 18 559 samples from the IGBP-DIS soil data set for pedotransfer function development (Data and Information System of the International Geosphere Biosphere Programme) database that embodies all major soils across the United States of America. The function is reliable and performs well for a wide range of soils occurring in very dry to very wet climates. Climatical grouping of the IGBP-DIS soils was proposed (aquic, tropical, cryic, aridic), but the results show that only tropical soils require specific grouping. Among many other different non-climatical soil groups tested, only humic and vitric soils were found to require specific grouping. The reliability of the pedotransfer function was further demonstrated with an independent database from Northern Italy having heterogeneous soils, and was found to be comparable or better than the accuracy of other pedotransfer functions found in the literature. Key words: Pedotransfer functions, soil moisture, soil texture, bulk density, organic matter, grouping

Investigation of Regression-Based Effect Size Methods Developed in Single-Subject Studies

2021 ◽  
pp. 014544552110540
Author(s):  
Nihal Sen
Keyword(s):  
Effect Size ◽  
Experimental Studies ◽  
Single Subject ◽  
Single Subject Design ◽  
Data Set ◽  
Design Studies ◽  
Sample Data ◽  
The Difference ◽  
D Values ◽  
Effect Size Calculation

The purpose of this study is to provide a brief introduction to effect size calculation in single-subject design studies, including a description of nonparametric and regression-based effect sizes. We then focus the rest of the tutorial on common regression-based methods used to calculate effect size in single-subject experimental studies. We start by first describing the difference between five regression-based methods (Gorsuch, White et al., Center et al., Allison and Gorman, Huitema and McKean). This is followed by an example using the five regression-based effect size methods and a demonstration how these methods can be applied using a sample data set. In this way, the question of how the values obtained from different effect size methods differ was answered. The specific regression models used in these five regression-based methods and how these models can be obtained from the SPSS program were shown. R2 values obtained from these five methods were converted to Cohen’s d value and compared in this study. The d values obtained from the same data set were estimated as 0.003, 0.357, 2.180, 3.470, and 2.108 for the Allison and Gorman, Gorsuch, White et al., Center et al., as well as for Huitema and McKean methods, respectively. A brief description of selected statistical programs available to conduct regression-based methods was given.

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