On the Use of 210Pb-based Records of Sedimentation Rates and Activity Concentrations for Tracking Past Environmental Changes

Lead-210 from natural atmospheric fallout is widely used in multidisciplinary studies to date recent sediments. Some of the 210Pb-based dating models can produce historical records of sediment accumulation rates (SAR) and initial activity concentrations ( ). The former have been profusely used to track past changes in the sedimentary conditions. Both physical magnitudes are differently affected by model errors (those arising for the partial or null accomplishment of some model assumptions). This work is aimed at assessing the effects on SAR and of model errors in the CRS, CS, PLUM and TERESA dating models, due to random variability in 210Pb fluxes, which is a usual sedimentary condition. Synthetic cores are used as virtual laboratories for this goal. Independently of the model choice, SARs are largely affected by model errors, resulting in some large and spurious deviations from the true values. This questions their general use for tracking past environmental changes. are less sensitive to model errors and their trends of change with time may reflect real changes in sedimentary conditions, as it is shown with some real cores from varved sediments.

Genetic Control of Rhizosphere Microbiome of Cotton Plant Under Field Conditions

Background: Understanding the extent of heritability of plant-associated microbiome (phytobiome) is critical for exploitation of phytobiome in agriculture. Two crosses were made between pairs of cotton cultivars with differential resistance to the Verticillium wilt. F2 plants were grown together with the four parents to study the heritability of cotton rhizosphere microbiome. Amplicon sequencing was used to profile bacterial and fungal communities.Results: F2 hybrid offspring of both crosses had higher alpha diversity indices as well as greater variability than the two parents. Two types of data were used generated to study the heritability of rhizosphere microbiome: principal components (PCs) and individual top microbial OTUs. For the L1×Z49 cross, the variance among the 100 progeny genotypes (VT) was significantly greater than the random variability (VE) for 12 and 34 out of top 100 fungal and bacterial PCs, respectively. For the Z2×J11 cross, the corresponding values were 10 and 20 PCs. Out of the top 100 OTUs, 29 fungal OTUs and 10 bacterial OTUs had VT that was significantly greater than VE for the L1×Z49 cross; the corresponding value for the Z2×J11 cross were 24 and one. The estimated heritability was mostly in the range of 40% to 60%.Conclusions: These results suggested the existence of genetic control in terms of rhizosphere microbiome in cotton.

Considerations regarding the variables of the ship repair process in the shipyards

The ship repair process in shipyards is a complex one and its components are usually influenced by a significant number of factors with random variability. The retention period of a ship in the shipyard for repair works present a particular interest, both for the shipyard and for the beneficiary of the repair works. In the most general way, the variables that could be the basis for the prognosis of the total period of repair works are selected from the content of the technical specification of works prepared by the owner / technical manager of the ship.. The paper highlights some independent variables that can be taken into account when estimating the period of repair work. The case studies presented in the paper refer to a portfolio of 400 tank type ships for which repair works were carried out in the Constanta Shipyard.

A Randomness Perspective on Intelligence Processes

We study intelligence processes using a diffusion IRT model with random variability in cognitive model parameters: variability in drift rate (the trend of information accumulation toward a correct or incorrect response) and variability in starting point (from where the information accumulation starts). The random variation concerns randomness across person-item pairs and cannot be accounted for by individual and inter-item differences. Interestingly, the models explain the conditional dependencies between response accuracy and response time that are found in previous studies on cognitive ability tests, leading us to the formulation of a randomness perspective on intelligence processes. For an empirical test, we have analyzed verbal analogies data and matrix reasoning data using diffusion IRT models with different variability assumptions. The results indicate that 1) models with random variability fit better than models without, with implications for the conditional dependencies in both types of tasks; 2) for verbal analogies, random variation in drift rate seems to exist, which can be explained by person-by-item word knowledge differences; and 3) for both types of tasks, the starting point variation was also established, in line with the inductive nature of the tasks, requiring a sequential hypothesis testing process. Finally, the correlation of individual differences in drift rate and SAT suggests a meta-strategic choice of respondents to focus on accuracy rather than speed when they have a higher cognitive capacity and when the task is one for which investing in time pays off. This seems primarily the case for matrix reasoning and less so for verbal analogies.

On the application of the averaged correlation matrix in craniometry

The article presents an averaged correlation matrix for 20 craniometric features, calculated for 24 male Eurasian samples. In some cases, correlation matrices calculated for different samples vary significantly; however, the fluctuations in the coefficients are usually random. Most correlation coefficients between craniometric traits have low positive values. The Mantel test, often used to compare matrices, produces incorrect results, since it is insensitive to the relationship between the value of the correlation coefficient and its stability: the lower the value of the correlation coefficient, the higher its random variability. At the same time, averaged correlation matrix based on individual data is similar to the averaged correlation matrices based on worldwide data used by Russian anthropologists at present. The usefullness of averaged correlation matrices for intergroup comparisons has been tested. It was also shown that the use of the averaged matrix for calculating the Mahalanobis distances produces results comparable to the calculations based on individual data. The analyzed samples can represent populations both from the local settlements and territorial communities. That was confirmed by the results of a series of tests for the Eastern European cranial samples, which were not used in the calculation of the averaged matrix. In conclusion some biases in the analysis of correlation coefficients caused by false ideas about their properties are considered.

Determination of critical community size from an HIV/AIDS model

After an epidemic outbreak, the infection persists in a community long enough to engulf the entire susceptible population. Local extinction of the disease could be possible if the susceptible population gets depleted. In large communities, the tendency of eventual damp down of recurrent epidemics is balanced by random variability. But, in small communities, the infection would die out when the number of susceptible falls below a certain threshold. Critical community size (CCS) is considered to be the mentioned threshold, at which the infection is as likely as not to die out after a major epidemic for small communities unless reintroduced from outside. The determination of CCS could aid in devising systematic control strategies to eradicate the infectious disease from small communities. In this article, we have come up with a simplified computation based approach to deduce the CCS of HIV disease dynamics. We consider a deterministic HIV model proposed by Silva and Torres, and following Nåsell, introduce stochasticity in the model through time-varying population sizes of different compartments. Besides, Metcalf’s group observed that the relative risk of extinction of some infections on islands is almost double that in the mainlands i.e. infections cease to exist at a significantly higher rate in islands compared to the mainlands. They attributed this phenomenon to the greater recolonization in the mainlands. Interestingly, the application of our method on demographic facts and figures of countries in the AIDS belt of Africa led us to expect that existing control measures and isolated locations would assist in temporary eradication of HIV infection much faster. For example, our method suggests that through systematic control strategies, after 7.36 years HIV epidemics will temporarily be eradicated from different communes of island nation Madagascar, where the population size falls below its CCS value, unless the disease is reintroduced from outside.

Performance analysis of professional soccer goalkeepers by Composition of Probabilistic Preferences

ABSTRACT This research aims to assist managers and technical commissions to choose professional soccer goalkeepers. A sample of 64 goalkeepers playing in Argentina and Brazil was studied. Their performance in the matches of two seasons were analyzed considering three criteria: goals against per minute played, percentage of goals and percentage of matches without conceded goals. The Composition of Probabilistic Preferences (CPP) was the method chosen for modeling, considering the random variability in the problem data and in football, considered one of the most unpredictable sports. CPP allowed to compare the choice based on the data analysis to the latest goalkeeper call-ups for these countries’ national teams. The selected goalkeepers corresponded to those presenting the best individual performance, which confirms the model.