Generation and quenching of intensity pulsations in semiconductor lasers coupled to external cavities

The behavior of self-pulsing and nonpulsing lasers coupled to external cavities is investigated experimentally and theoretically. We investigate the dependence of the pulsation characteristics on the external cavity length using a saturable absorber model for self-pulsing lasers. It was found that quenching of self-pulsation occurs only for a certain limited range of external cavity length, and the frequencies of external-cavity induced pulsations lies within a certain range determined by the coupling coefficient. Small-signal analysis allows these ranges to be derived analytically. Hitherto, complex pulsation phenomena can be explained very intuitively by interpreting the combined laser-external cavity system as a microwave oscillator with a limited gain band and discrete mode structure.     

Iron silicide thin film formation at low temperatures

The rate kinetics of the formation of compound phases from thin layers of 1000–1500 Å α-Fe deposited onto single-crystal Si have been studied by MeV ⁴He⁺ backscattering spectrometry. Si is observed to dissolve into the thin α-Fe layer before compound formation. A compound layer of FeSi is produced at about 450°C and FeSi₂ formation begins at about 550°C. The (100) surface of Si is slightly more reactive than the (111) surface. An inert diffusion marker of implanted Xe was used to investigate the relative movement of the two species.X-ray diffractometry identifies the structure of the compound species as identical to bulk FeSi and FeSi₂. The compounds formed on both (111) n-Si and (100) n-Si are apparently polycrystalline and untextured.     

A grid middleware for distributed Java computing with MPI binding and process migration supports

“Grid” computing has emerged as an important new research field. With years of efforts, grid researchers have successfully developed grid technologies including security solutions,resource management protocols, information query protocols, and data management services. How-ever, as the ultimate goal of grid computing is to design an infrastructure which supports dynarnic,cross-organizational resource sharing, there is a need of solutions for efficient and transparent task re-scheduling in the grid. In this research, a new grid middleware is proposed, called G-JavaMPI. This middleware adds the parallel computing capability of Java to the grid with the support of a Grid-enabled message passing interface (MPI) for inter-process communication between Java processes executed at dif-ferent grid points. A special feature of the proposed G-JavaMPI is the support of Java process migration with post-migration message redirection. With these supports, it is possible to migrate executing Java process from site to site for continuous computation, if some site is scheduled to be turned down for system reconfiguration. Moreover, the proposed G-JavaMPI middleware is very portable since it requires no modification of underlying OS, Java virtual machine, and MPI package. Preliminary performance tests have been conducted. The proposed mechanisms have shown good migration efficiency in a simulated grid environment.     

Guided Genetic Algorithm and its Application to Radio Link Frequency Assignment Problems

The Guided Genetic Algorithm (GCA) is a hybrid of Genetic Algorithm and Guided Local Search, a meta–heuristic search algorithm. As the search progresses, GGA modifies both the fitness function and fitness template of candidate solutions based on feedback from constraints. The fitness template is then used to bias crossover and mutation. The Radio Link Frequency Assignment Problem (RLFAP) is a class of problem that has practical relevance to both military and civil applications. In this paper, we show how GGA can be applied to the RLFAP. We focus on an abstraction of a real life military application that involves the assigning of frequencies to radio links. GGA was tested on a set of eleven benchmark problems provided by the French military. This set of problems has been studied intensively by a number of prominent groups in Europe. It covers a variety of needs in military applications, including the satisfaction of constraints, finding optimal solutions that satisfy all the constraints and optimization of some objective functions whenever no solution exist (partial constraint satisfaction). Not only do these benchmark problems vary in problem nature, they are reasonably large for military applications (up to 916 variables, and up to 5548 constraints). This makes them a serious challenge to the generality, reliability as well as efficiency of algorithms. We show in this paper that GGA is capable of producing excellent results reliably in the whole set of benchmark problems.     

Novel lipidic enaminones from a C18 keto-allenic ester

Primary amines (ammonia, methyl, propyl, octyl, octadecyl, phenyl, benzyl, phenethyl) including methyl esters of amino acids (glycine, dl-alanine, l-valine, l-leucine, L-tyrosine, and l-methionine), and secondary amines (dimethyl, diethyl, dipropyl, diisopropyl, dioctyl, and diphenyl) attack regiospecifically the central carbon atom of the allene system of methyl 12-keto-9,10-octadecadienoate (1) to give the corresponding lipidic enaminone derivatives (2–21) with an average yield of 77%. The E- and Z-configuration of the enaminone system of these novel lipid derivatives was confirmed by infrared and nuclear magnetic resonance spectroscopic techniques. Primary amines furnished Z-enaminones, while secondary amines gave E-enaminones.     

Software Component Models

Component-based development (CBD) is an important emerging topic in software engineering, promising long-sought-after benefits like increased reuse, reduced time to market, and, hence, reduced software production cost. The cornerstone of a CBD technology is its underlying software component model, which defines components and their composition mechanisms. Current models use objects or architectural units as components. These are not ideal for component reuse or systematic composition. In this paper, we survey and analyze current component models and classify them into a taxonomy based on commonly accepted desiderata for CBD. For each category in the taxonomy, we describe its key characteristics and evaluate them with respect to these desiderata.     

Genetic and environmental influences on interpersonal cognitions and associations with depressive symptoms in 8-year-old twins.

Less is known about depression in children than in adults. This study integrates fields by combining cognitive and interpersonal research investigating childhood depression symptoms through the use of a genetic framework. Three research questions are addressed. First, what are the associations among interpersonal cognitions, anxiety, and depression? Second, what are the relative magnitudes of genetic and environmental influences on interpersonal cognitions? Third, to what extent do genetic and environmental influences explain associations between interpersonal cognitions and depression? Three hundred pairs of 8-year-old twins reported on symptoms of depression and anxiety by completing the Children's Depression Inventory and the Screen for Childhood Anxiety-Related Emotional Disorders. The authors examined interpersonal cognitions with the Children's Expectation of Social Behaviors and the Perceptions of Peers and Self Questionnaires. Interpersonal cognitions were more strongly correlated with depression (mean r = .35) than with anxiety (mean r = .13). Genetic influence on interpersonal cognitions was small (M = 3%), and associations between interpersonal cognitions and depression were mainly explained by environmental influences. These latter findings may result from interpersonal cognitions in young children, reflecting life experiences as opposed to trait-like cognitive biases. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Pathways to childhood depressive symptoms: The role of social, cognitive, and genetic risk factors.

Childhood depressive conditions have been explored from multiple theoretical approaches but with few empirical attempts to address the interrelationships among these different domains and their combined effects. In the present study, the authors examined different pathways through which social, cognitive, and genetic risk factors may be expressed to influence depressive symptoms in 300 pairs of child twins from a longitudinal study. Path analysis supported several indirect routes. First, risks associated with living in a step- or single-parent family and punitive parenting did not directly influence depressive outcome but were instead mediated through maternal depressive symptoms and child negative attributional style. Second, the effects of negative attributional style on depressive outcome were greatly exacerbated in the presence of precipitating negative life events. Third, independent of these social and cognitive risk mechanisms, modest genetic effects were also implicated in symptoms, with some indication that these risks are expressed through exposure to negative stressors. Together, these routes accounted for approximately 13% of total phenotypic variance in depressive symptoms. Theoretical and analytical implications of these results are discussed in the context of several design-related caveats. (PsycINFO Database Record (c) 2010 APA, all rights reserved)