Particle motion in weak relativistic gravitational fields

We derive the geodesic equation of motion in the presence of weak gravitational fields produced by relativistic sources such as cosmic strings, decomposed into scalar, vector and tensor parts. We find that the vector (gravito-magnetic) force is an important contributor, and for non-relativistic particles we recover the well-known result for the impulse from a moving straight string. Our results can be straightforwardly incorporated into N-body simulations to allow for the presence of cosmic defects or other sources of weak gravitational fields.Comment: 9 pages, 5 figure

Viewing the efficiency of chaos control

This paper aims to cast some new light on controlling chaos using the OGY- and the Zero-Spectral-Radius methods. In deriving those methods we use a generalized procedure differing from the usual ones. This procedure allows us to conveniently treat maps to be controlled bringing the orbit to both various saddles and to sources with both real and complex eigenvalues. We demonstrate the procedure and the subsequent control on a variety of maps. We evaluate the control by examining the basins of attraction of the relevant controlled systems graphically and in some cases analytically

Polyphenol Content and Antioxidant Activity of Sour Cherries From Serbia

The aim of this study was to evaluate the content of phenolics: the total phenols (TP), flavonoids (TF), anthocyanins (TA), as well as the total antioxidant\ud capacity (TAC) in three sour cherry cultivars (Prunus cerasus L.) introduced to the southeast Serbia climate conditions. Among the investigated sour cherries,\ud „Oblačinska“ cultivar contained the highest amounts of all groups of phenolics, followed by „Cigančica“ > „Marela“. A significant difference were observed in the phenolic content among different cultivars and growing seasons (p  0.05), and the phenolic compounds were significantly higher in the growing season 2009. The examined cultivars possess a high antioxidant capacity, and all phenolics of highy correlation with TAC. The following compounds were identified and quantified using HPLC-DAD: 4 anthocyanins, the most abundant of which was cyanidin-3-glucoside in “Marela” and “Oblačinska”, and cyanidin-3-glucosylrutinoside in „Cigančica“, and 4 hydroxycinnamic acids, the most abundant of which was neochlorogenic acid in all sour cherry cultivars. The growing and ripening process on the tree of sour cherry cv. „Oblačinska“ was evaluated also. The results showed significant increases in total phenols during the ripening, the total anthocyanins and total antioxidant capacity and 4 quantified anthocyanins, however the neochlorogenic acid decreased during the ripening. The study indicated that the growing and climate conditions in southeast Serbia are convenient for introducing sour cherry cultivars.\u

Editorial: Non-coding RNA in diabetes and cardiovascular diseases

Editorial on the Research Topic: [https://www.frontiersin.org/research-topics/33365/non-coding-rna-in-diabetes-and-cardiovascular-diseases

Prosocial and aggressive behavior occurrence in young athletes: Field research results in six European countries

Aggression and violence among youth areresearched as social phenomena in sport. This paper was designed to determine the occurrence of these behaviors as well as prosocial behaviorsamong young athletes. The current paper is a research report aiming to detect the frequency of aggressive behavior, social exclusion, prosocial behavior and cohesion in the youth environment, the frequency of personal experience of peer violence or social exclusion, and to evaluate cross-national differences in terms of occurrence of these phenomena. The field research was conducted in six European countries (Austria, Bosnia and Herzegovina, Croatia, Italy, Lithuania, and Serbia) on a sample of 482 children aged 6 to 16. The conducted questionnaire consisted of pre-existing scales and measures for specific behaviors and social aspects that formed the Youth Environment Assessment and Youth Characteristics Questionnaire. Previous personal experience of violence and social exclusion determined groups in the sample. One-way ANOVA and discriminant analysis were conducted to compare various variables and groups within the sample. The results have shown that aggressive and social exclusion behaviors are rare or very rare, predominantly in the form of verbal aggression in the sports club environment. The results of the conducted discriminant analysis indicate that prosocial and cohesion behaviors occur "quite often" to "often" among sports club athletes' samples. The percentage of athletes who have had personal experience of violence or social exclusion in the last two years and whose feeling of hurt by that experience was assessed as "a lot" or "fully" on the measurement scale is estimated to be approximately 25%. Mild cross-national differences emerged in the overmentioned variables, probably due to the sample specificity, or to cultural variety. The results indicate the need for longitudinal research on this topic since the sport is an environment in which cohesion can be developed among young athletes, but it is not free from social exclusion or aggression

Modeling Single Electron Transfer in Si:P Double Quantum Dots

Solid-state systems such as P donors in Si have considerable potential for realization of scalable quantum computation. Recent experimental work in this area has focused on implanted Si:P double quantum dots (DQDs) that represent a preliminary step towards the realization of single donor charge-based qubits. This paper focuses on the techniques involved in analyzing the charge transfer within such DQD devices and understanding the impact of fabrication parameters on this process. We show that misalignment between the buried dots and surface gates affects the charge transfer behavior and identify some of the challenges posed by reducing the size of the metallic dot to the few donor regime.Comment: 11 pages, 7 figures, submitted to Nanotechnolog

Replica theory for learning curves for Gaussian processes on random graphs

Statistical physics approaches can be used to derive accurate predictions for the performance of inference methods learning from potentially noisy data, as quantified by the learning curve defined as the average error versus number of training examples. We analyse a challenging problem in the area of non-parametric inference where an effectively infinite number of parameters has to be learned, specifically Gaussian process regression. When the inputs are vertices on a random graph and the outputs noisy function values, we show that replica techniques can be used to obtain exact performance predictions in the limit of large graphs. The covariance of the Gaussian process prior is defined by a random walk kernel, the discrete analogue of squared exponential kernels on continuous spaces. Conventionally this kernel is normalised only globally, so that the prior variance can differ between vertices; as a more principled alternative we consider local normalisation, where the prior variance is uniform