Einführung zu Teil II

L'articolo introduce la parte II del volume miscellaneo Textes et contextes de l’immigration, Texte und Kontexte der Migration, presentando i singoli contributi in essa contenuti e, anzitutto, mettendo a confronto le differenze e affinità tra Francia e Germania nell'ambito del tema trattato. Differenze tra le due nazioni si osservano nelle cause storiche della presenza di popolazioni non autoctone (passato imperialista vs. accordi politici per reclutamento forza lavoro nel dopoguerra), nei loro luoghi di alloggio (banlieues vs. quartieri urbani anche centrali), nell’approccio ideologico-concettuale al fenomeno (continuità nell’uso del termine “immigrante” vs. termini mutevoli da "lavoratori ospiti" a “persona con sfondo migratorio”). Affinità invece, ovvero una tendenza alla mondializzazione che (attraverso i media globali) va oltre i confini nazionali, si osserva nell’attuale fenomeno dei linguaggi giovanili ibridi

Interspecific and integroup interactions of mantled howling monkeys (Alouatta palliata) in primary versus secondary forest at El Zota Biological Field Station, Costa Rica

Four groups of mantled howling monkeys (Alouatta palliata) were observed at El Zota Biological Field Station in northeastern Costa Rica to assess whether resource scarcity caused by anthropogenic disturbance and hypothesized increased competition for limited resources would result in more frequent and more aggressive interactions between neighboring howling monkey groups and between howling monkeys and other, sympatric primate species, namely white-faced capuchins (Cebus capucinus) and black-handed spider monkeys (Ateles geoffroyi). Using a comparison between the primary forest, as a control, and anthropogenically-altered secondary forest, I examined whether a behavioral difference existed between groups with hypothesized varying degrees of resource competition. Intergroup encounters were broken down into long distance howling bouts, with 46 observed, and close proximity interactions, with 11 observed. Results showed an increased frequency of howling in the primary forest as compared with the secondary forest, but no difference between the frequency, duration, or type of close-proximity intergroup encounters. Forty-five interspecies interactions were observed between howling monkeys and sympatric primate species. These interactions showed no difference between forest type for frequency, duration, or type of interaction. These results suggest that the composition and resource availability of the secondary forest at this site that does not align with current assumptions of habitat degradation. Alternatively results may be a reflection of social pressures such as infanticide, intragroup competition, and genetic relatedness as factors shaping howling monkey behaviors in both primary and secondary forests

A MACHINE LEARNING APPROACH TO QUERY TIME-SERIES MICROARRAY DATA SETS FOR FUNCTIONALLY RELATED GENES USING HIDDEN MARKOV MODELS

Microarray technology captures the rate of expression of genes under varying experimental conditions. Genes encode the information necessary to build proteins; proteins used by cellular functions exhibit higher rates of expression for the associated genes. If multiple proteins are required for a particular function then their genes show a pattern of coexpression during time periods when the function is active within a cell. Cellular functions are generally complex and require groups of genes to cooperate; these groups of genes are called functional modules. Modular organization of genetic functions has been evident since 1999. Detecting functionally related genes in a genome and detecting all genes belonging to particular functional modules are current research topics in this field. The number of microarray gene expression datasets available in public repositories increases rapidly, and advances in technology have now made it feasible to routinely perform whole-genome studies where the behavior of every gene in a genome is captured. This promises a wealth of biological and medical information, but making the amount of data accessible to researchers requires intelligent and efficient computational algorithms. Researchers working on specific cellular functions would benefit from this data if it was possible to quickly extract information useful to their area of research. This dissertation develops a machine learning algorithm that allows one or multiple microarray data sets to be queried with a set of known and functionally related input genes in order to detect additional genes participating in the same or closely related functions. The focus is on time-series microarray datasets where gene expression values are obtained from the same experiment over a period of time from a series of sequential measurements. A feature selection algorithm selects relevant time steps where the provided input genes exhibit correlated expression behavior. Time steps are the columns in microarray data sets, rows list individual genes. A specific linear Hidden Markov Model (HMM) is then constructed to contain one hidden state for each of the selected experiments and is trained using the expression values of the input genes from the microarray. Given the trained HMM the probability that a sequence of gene expression values was generated by that particular HMM can be calculated. This allows for the assignment of a probability score for each gene in the microarray. High-scoring genes are included in the result set (of genes with functional similarities to the input genes.) P-values can be calculated by repeating this algorithm to train multiple individual HMMs using randomly selected genes as input genes and calculating a Parzen Density Function (PDF) from the probability scores of all HMMs for each gene. A feedback loop uses the result generated from one algorithm run as input set for another iteration of the algorithm. This iterated HMM algorithm allows for the characterization of functional modules from very small input sets and for weak similarity signals. This algorithm also allows for the integration of multiple microarray data sets; two approaches are studied: Meta-Analysis (combination of the results from individual data set runs) and the extension of the linear HMM across multiple individual data sets. Results indicate that Meta-Analysis works best for integration of closely related microarrays and a spanning HMM works best for the integration of multiple heterogeneous datasets. The performance of this approach is demonstrated relative to the published literature on a number of widely used synthetic data sets. Biological application is verified by analyzing biological data sets of the Fruit Fly D. Melanogaster and Baker‟s Yeast S. Cerevisiae. The algorithm developed in this dissertation is better able to detect functionally related genes in common data sets than currently available algorithms in the published literature

How organized is deep convection over Germany?

Deep moist convection shows a tendency to organize into mesoscale structures. To be able to understand the potential effect of convective organization on the climate, one needs first to characterize organization. In this study, we systematically characterize the organizational state of convection over Germany based on two years of cloud-top observations derived from the Meteosat Second Generation satellite and of precipitation cores detected by the German C-band radar network. The organizational state of convection is characterized by commonly employed organization indices, which are mostly based on the object numbers, sizes and nearest-neighbour distances. According to the organization index Iorg, cloud tops and precipitation cores are found to be in an organized state for 69% and 92% of the time, respectively. There is an increase in rainfall when the number of objects and their sizes increase, independently of the organizational state. Case-studies of specific days suggest that convectively organized states correspond to either local multi-cell clusters, with less numerous, larger objects close to each other, or to scattered clusters, with more numerous, smaller organized objects spread out over the domain. For those days, simulations are performed with the large-eddy model ICON with grid spacings of 625, 312 and 156?m. Although the model underestimates rainfall and shows a too large cold cloud coverage, the organizational state is reasonably well represented without significant differences between the grid spacings

Size-resolved evaluation of simulated deep tropical convection

Deep moist convection is an inherently multiscale phenomenon with organization processes coupling convective elements to larger-scale structures. A realistic representation of the tropical dynamics demands a simulation framework that is capable of representing physical processes across a wide range of scales. Therefore, storm-resolving numerical simulations at 2.4 km have been performed covering the tropical Atlantic and neighboring parts for 2 months. The simulated cloud fields are combined with infrared geostationary satellite observations, and their realism is assessed with the help of object-based evaluation methods. It is shown that the simulations are able to develop a well-defined intertropical convergence zone. However, marine convective activity measured by the cold cloud coverage is considerably underestimated, especially for the winter season and the western Atlantic. The spatial coupling across the resolved scales leads to simulated cloud number size distributions that follow power laws similar to the observations, with slopes steeper in winter than summer and slopes steeper over ocean than over land. The simulated slopes are, however, too steep, indicating too many small and too few large tropical cloud cells. It is also discussed that the number of larger cells is less influenced by multiday variability of environmental conditions. Despite the identified deficits, the analyzed simulations highlight the great potential of this modeling framework for process-based studies of tropical deep convection. © 2018 American Meteorological Society

Design of a Low Cost Short Takeoff-vertical Landing Export Fighter/attack Aircraft

The design of a supersonic short takeoff and vertical landing (STOVL) aircraft is presented that is suitable for export. An advanced four poster, low bypass turbofan engine is to be used for propulsion. Preliminary aerodynamic analysis is presented covering a determination of CD versus CL, CD versus Mach number, as well as best cruise Mach number and altitude. Component locations are presented and center of gravity determined. Cost minimization is achieved through the use of developed subsystems and standard fabrication techniques using nonexotic materials. Conclusions regarding the viability of the STOVL design are presented

Gravity waves, scale asymptotics, and the pseudo-incompressible equations

Multiple-scale asymptotics is used to analyze the Euler equations for the dynamical situation of a gravity wave (GW) near breaking level. A simple saturation argument in combination with linear theory is used to obtain the relevant dynamical scales. As small expansion parameter the ratio of inverse of the vertical wave number and potentialtemperature and pressure scale heights is used, which we allow to be of the same order of magnitude here. It is shown that the resulting equation hierarchy is consistent with that obtained from the pseudo-incompressible equations, both for non-hydrostatic and hydrostatic gravity waves, while this is not the case for the anelastic equations unless the additional assumption of sufficiently weak stratication is adopted. To describe vertical propagation of wave packets over several atmospheric scale heights, WKB theory is used to show that the pseudo-incompressible flow divergence generates the same amplitude equation that also obtains from the full Euler equations. This gives a mathematical justication for the use of the pseudo-incompressible equations for studies of gravity-wave breaking in the atmosphere for arbitrary background stratication. The WKB theory interestingly also holds at wave amplitudes close to static instability. In the mean-flow equations we obtain in addition to the classic wave-induced momentum-flux divergences a wave-induced correction of hydrostatic balance in the vertical-momentum equation which cannot be obtained from Boussinesq or anelastic dynamics

IMPLAN MODELING APPLICATIONS IN STATE AND REGIONAL DEVELOPMENT

Community/Rural/Urban Development,