Helicity Analysis of Semileptonic Hyperon Decays Including Lepton Mass Effects

Using the helicity method we derive complete formulas for the joint angular decay distributions occurring in semileptonic hyperon decays including lepton mass and polarization effects. Compared to the traditional covariant calculation the helicity method allows one to organize the calculation of the angular decay distributions in a very compact and efficient way. In the helicity method the angular analysis is of cascade type, i.e. each decay in the decay chain is analyzed in the respective rest system of that particle. Such an approach is ideally suited as input for a Monte Carlo event generation program. As a specific example we take the decay $\Xi^0 \to \Sigma^+ + l^- + \bar{\nu}_l$ ($l^-=e^-, \mu^-$) followed by the nonleptonic decay $\Sigma^+ \to p + \pi^0$ for which we show a few examples of decay distributions which are generated from a Monte Carlo program based on the formulas presented in this paper. All the results of this paper are also applicable to the semileptonic and nonleptonic decays of ground state charm and bottom baryons, and to the decays of the top quark.Comment: Published version. 40 pages, 11 figures included in the text. Typos corrected, comments added, references added and update

Effects of Interplanetary Dust on the LISA drag-free Constellation

The analysis of non-radiative sources of static or time-dependent gravitational fields in the Solar System is crucial to accurately estimate the free-fall orbits of the LISA space mission. In particular, we take into account the gravitational effects of Interplanetary Dust (ID) on the spacecraft trajectories. The perturbing gravitational field has been calculated for some ID density distributions that fit the observed zodiacal light. Then we integrated the Gauss planetary equations to get the deviations from the LISA keplerian orbits around the Sun. This analysis can be eventually extended to Local Dark Matter (LDM), as gravitational fields are expected to be similar for ID and LDM distributions. Under some strong assumptions on the displacement noise at very low frequency, the Doppler data collected during the whole LISA mission could provide upper limits on ID and LDM densities.Comment: 11 pages, 6 figures, to be published on the special issue of "Celestial Mechanics and Dynamical Astronomy" on the CELMEC V conferenc

Mitochondrial diversity analysis of Glossina palpalis gambiensis from Mali and Senegal

West African riverine tsetse populations of Glossina palpalis gambiensis Vanderplank (Diptera: Glossinidae) were investigated for gene flow, inferred from mitochondrial diversity in samples of 69 flies from Senegal and 303 flies from three river drainages in Mali. Four polymorphic mitochondrial loci were scored. Mean haplotype diversities were 0.30 in Mali and 0.18 over both Mali and Senegal. These diversities estimate the probabilities that two randomly chosen tsetse have different haplotypes. Substantial rates of gene flow were detected among flies sampled along tributaries belonging to the river basins of the Senegal, Niger, and Bani in Mali. There was virtually no gene flow between tsetse in Senegal and Mali. No seasonal effects on gene flow were detected. The implications of these preliminary findings for the implementation of area-wide integrated pest management (AW-IPM) programmes against riverine tsetse in West Africa are discussed

Subgraphs in random networks

Understanding the subgraph distribution in random networks is important for modelling complex systems. In classic Erdos networks, which exhibit a Poissonian degree distribution, the number of appearances of a subgraph G with n nodes and g edges scales with network size as \mean{G} ~ N^{n-g}. However, many natural networks have a non-Poissonian degree distribution. Here we present approximate equations for the average number of subgraphs in an ensemble of random sparse directed networks, characterized by an arbitrary degree sequence. We find new scaling rules for the commonly occurring case of directed scale-free networks, in which the outgoing degree distribution scales as P(k) ~ k^{-\gamma}. Considering the power exponent of the degree distribution, \gamma, as a control parameter, we show that random networks exhibit transitions between three regimes. In each regime the subgraph number of appearances follows a different scaling law, \mean{G} ~ N^{\alpha}, where \alpha=n-g+s-1 for \gamma<2, \alpha=n-g+s+1-\gamma for 2<\gamma<\gamma_c, and \alpha=n-g for \gamma>\gamma_c, s is the maximal outdegree in the subgraph, and \gamma_c=s+1. We find that certain subgraphs appear much more frequently than in Erdos networks. These results are in very good agreement with numerical simulations. This has implications for detecting network motifs, subgraphs that occur in natural networks significantly more than in their randomized counterparts.Comment: 8 pages, 5 figure

An overview of the Jordanian oil shale: its chemical and geologic characteristics, exploration, reserves and feasibility for oil and cement production

Abstract Oil shale is the most abundant fossil energy resource discovered in Jordan, ranking third after the USA and Brazil in terms of oil shale reserves. This asset is considered to be Jordan's most extensive domestic fossil-fuel source. The identified reserves of this oil shale are huge and sufficient to satisfy the national energy needs for hundreds of years. Numerous geologic studies have shown that the country contains several oil shale deposits. These deposits are regarded as the richest in organic bituminous marl and limestone that occur at shallow depth. Jordanian oil shale is generally of a good quality, with relatively low ash and moisture contents, a gross calorific value of 7.5 MJ/kg, and an oil yield of 8 to 12%. The spent shale has residual carbon content that may be burned to produce further energy, and ash that can be used for cement and building materials. The current study summarizes the results of the former feasibility studies and discuses the scope of future usage of Jordanian oil shale. The value of this oil shale and its associated products is highlighted herein

Nonlinear effects in resonant layers in solar and space plasmas

The present paper reviews recent advances in the theory of nonlinear driven magnetohydrodynamic (MHD) waves in slow and Alfven resonant layers. Simple estimations show that in the vicinity of resonant positions the amplitude of variables can grow over the threshold where linear descriptions are valid. Using the method of matched asymptotic expansions, governing equations of dynamics inside the dissipative layer and jump conditions across the dissipative layers are derived. These relations are essential when studying the efficiency of resonant absorption. Nonlinearity in dissipative layers can generate new effects, such as mean flows, which can have serious implications on the stability and efficiency of the resonance

A mathematical framework for critical transitions: normal forms, variance and applications

Critical transitions occur in a wide variety of applications including mathematical biology, climate change, human physiology and economics. Therefore it is highly desirable to find early-warning signs. We show that it is possible to classify critical transitions by using bifurcation theory and normal forms in the singular limit. Based on this elementary classification, we analyze stochastic fluctuations and calculate scaling laws of the variance of stochastic sample paths near critical transitions for fast subsystem bifurcations up to codimension two. The theory is applied to several models: the Stommel-Cessi box model for the thermohaline circulation from geoscience, an epidemic-spreading model on an adaptive network, an activator-inhibitor switch from systems biology, a predator-prey system from ecology and to the Euler buckling problem from classical mechanics. For the Stommel-Cessi model we compare different detrending techniques to calculate early-warning signs. In the epidemics model we show that link densities could be better variables for prediction than population densities. The activator-inhibitor switch demonstrates effects in three time-scale systems and points out that excitable cells and molecular units have information for subthreshold prediction. In the predator-prey model explosive population growth near a codimension two bifurcation is investigated and we show that early-warnings from normal forms can be misleading in this context. In the biomechanical model we demonstrate that early-warning signs for buckling depend crucially on the control strategy near the instability which illustrates the effect of multiplicative noise.Comment: minor corrections to previous versio