281 research outputs found

    Development and evaluation of a reference measurement model for assessing the resource and energy efficiency of software products and components—Green Software Measurement Model (GSMM)

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    In the past decade, research on measuring and assessing the environmental impact of software has gained significant momentum in science and industry. However, due to the large number of research groups, measurement setups, procedure models, tools, and general novelty of the research area, a comprehensive research framework has yet to be created. The literature documents several approaches from researchers and practitioners who have developed individual methods and models, along with more general ideas like the integration of software sustainability in the context of the UN Sustainable Development Goals, or science communication approaches to make the resource cost of software transparent to society. However, a reference measurement model for the energy and resource consumption of software is still missing. In this article, we jointly develop the Green Software Measurement Model (GSMM), in which we bring together the core ideas of the measurement models, setups, and methods of over 10 research groups in four countries who have done pioneering work in assessing the environmental impact of software. We briefly describe the different methods and models used by these research groups, derive the components of the GSMM from them, and then we discuss and evaluate the resulting reference model. By categorizing the existing measurement models and procedures and by providing guidelines for assimilating and tailoring existing methods, we expect this work to aid new researchers and practitioners who want to conduct measurements for their individual use cases

    On the Origin and Characteristics of Noise-Induced Lévy Walks of E. Coli

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    Lévy walks as a random search strategy have recently attracted a lot of attention, and have been described in many animal species. However, very little is known about one of the most important issues, namely how Lévy walks are generated by biological organisms. We study a model of the chemotaxis signaling pathway of E. coli, and demonstrate that stochastic fluctuations and the specific design of the signaling pathway in concert enable the generation of Lévy walks. We show that Lévy walks result from the superposition of an ensemble of exponential distributions, which occurs due to the shifts in the internal enzyme concentrations following the stochastic fluctuations. With our approach we derive the power-law analytically from a model of the chemotaxis signaling pathway, and obtain a power-law exponent , which coincides with experimental results. This work provides a means to confirm Lévy walks as natural phenomenon by providing understanding on the process through which they emerge. Furthermore, our results give novel insights into the design aspects of biological systems that are capable of translating additive noise on the microscopic scale into beneficial macroscopic behavior

    Genetic Contribution to Alcohol Dependence: Investigation of a Heterogeneous German Sample of Individuals with Alcohol Dependence, Chronic Alcoholic Pancreatitis, and Alcohol-Related Cirrhosis

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    The present study investigated the genetic contribution to alcohol dependence (AD) using genome-wide association data from three German samples. These comprised patients with: (i) AD; (ii) chronic alcoholic pancreatitis (ACP); and (iii) alcohol-related liver cirrhosis (ALC). Single marker, gene-based, and pathway analyses were conducted. A significant association was detected for the ADH1B locus in a gene-based approach (puncorrected = 1.2 × 10−6; pcorrected = 0.020). This was driven by the AD subsample. No association with ADH1B was found in the combined ACP + ALC sample. On first inspection, this seems surprising, since ADH1B is a robustly replicated risk gene for AD and may therefore be expected to be associated also with subgroups of AD patients. The negative finding in the ACP + ALC sample, however, may reflect genetic stratification as well as random fluctuation of allele frequencies in the cases and controls, demonstrating the importance of large samples in which the phenotype is well assessed

    Optogenetic acidification of synaptic vesicles and lysosomes

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    Acidification is required for the function of many intracellular organelles, but methods to acutely manipulate their intraluminal pH have not been available. Here we present a targeting strategy to selectively express the light-driven proton pump Arch3 on synaptic vesicles. Our new tool, pHoenix, can functionally replace endogenous proton pumps, enabling optogenetic control of vesicular acidification and neurotransmitter accumulation. Under physiological conditions, glutamatergic vesicles are nearly full, as additional vesicle acidification with pHoenix only slightly increased the quantal size. By contrast, we found that incompletely filled vesicles exhibited a lower release probability than full vesicles, suggesting preferential exocytosis of vesicles with high transmitter content. Our subcellular targeting approach can be transferred to other organelles, as demonstrated for a pHoenix variant that allows light-activated acidification of lysosomes
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