Cloud scheduling optimization: a reactive model to enable dynamic deployment of virtual machines instantiations

This study proposes a model for supporting the decision making process of the cloud policy for the deployment of virtual machines in cloud environments. We explore two configurations, the static case in which virtual machines are generated according to the cloud orchestration, and the dynamic case in which virtual machines are reactively adapted according to the job submissions, using migration, for optimizing performance time metrics. We integrate both solutions in the same simulator for measuring the performance of various combinations of virtual machines, jobs and hosts in terms of the average execution and total simulation time. We conclude that the dynamic configuration is prosperus as it offers optimized job execution performance

Molecular and catalytic characterization of the herbicide-inducible glutathione transferases from Phaseolus vulgaris

Plant glutathione transferases (GSTs) comprise a large family of inducible enzymes that play important roles in stress tolerance and herbicide detoxification. Treatment of Phaseolus vulgaris leaves with the aryloxyphenoxypropionic herbicide fluazifop-p-butyl resulted in induction of GST activities. Three inducible GST isoenzymes were identified and separated by affinity chromatography. Their full-length cDNAs with complete open reading frame were isolated using RACE-RT and information from N-terminal amino acid sequences. Analysis of the cDNA clones showed that the deduced amino acid sequences share high homology with GSTs that belong to phi and tau classes. The three isoenzymes were expressed in E. coli and their substrate specificity was determined towards 20 different substrates. The results showed that the fluazifop-inducible glutathione transferases from P. vulgaris (PvGSTs) catalyze a broad range of reactions and exhibit quite varied substrate specificity. Molecular modeling and structural analysis was used to identify key structural characteristics and to provide insights into the substrate specificity and the catalytic mechanism of these enzymes. These results provide new insights into catalytic and structural diversity of GSTs and the detoxifying mechanism used by P. vulgaris

Catalytic and structural diversity of the fluazifop-inducible glutathione transferases from Phaseolus vulgaris

Plant glutathione transferases (GSTs) comprise a large family of inducible enzymes that play important roles in stress tolerance and herbicide detoxification. Treatment of Phaseolus vulgaris leaves with the aryloxyphenoxypropionic herbicide fluazifop-p-butyl resulted in induction of GST activities. Three inducible GST isoenzymes were identified and separated by affinity chromatography. Their full-length cDNAs with complete open reading frame were isolated using RACE-RT and information from N-terminal amino acid sequences. Analysis of the cDNA clones showed that the deduced amino acid sequences share high homology with GSTs that belong to phi and tau classes. The three isoenzymes were expressed in E. coli and their substrate specificity was determined towards 20 different substrates. The results showed that the fluazifop-inducible glutathione transferases from P. vulgaris (PvGSTs) catalyze a broad range of reactions and exhibit quite varied substrate specificity. Molecular modeling and structural analysis was used to identify key structural characteristics and to provide insights into the substrate specificity and the catalytic mechanism of these enzymes. These results provide new insights into catalytic and structural diversity of GSTs and the detoxifying mechanism used by P. vulgaris

Isolation of GST isoenzymes from Phaseolus vulgaris L. and characterization of detoxifying mechanism under biotic and abiotic stress

Three Glutathione transferase (GSTs) isoenzymes have been isolated from P. vulgaris leaves after in vivo treatment with 1/250 fluazifop-p-butyl herbicide. The inducible GST isoenzymes were identified and separated by affinity chromatography. They found to belong to phi and tau classes. Moreover, the fluazifop-inducible glutathione transferases from P. vulgaris (PvGSTs, termed PvGSTU2-2, PvGSTF1-1 and PvGSTU3-3) were found to catalyze a broad range of reactions and exhibit quite varied substrate specificity. Another GST isoenzyme was isolated from P. vulgaris (PvGST, termed PvGSTU3-3), after its induction with biotic stress treatment (Uromyces appendiculatus infection). PvGSTU3-3 shares high homology the tau class plant and catalyzes several different reactions and exhibits wide substrate specificity. Of particular importance are the high antioxidant catalytic function and hydroperoxidase, thioltransferase, and dehydroascorbate reductase action of Pv-GSTU3-3. Transgenic tobacco plants over-expressing PvGSTU2-2 isoenzyme have been developed via Agrobacteriun tumefaciens in order to study their in planta potential to confer biotic and abiotic resistance as a means of plant breeding. Our results provide new insights into catalytic and structural diversity of GSTs and the detoxifying mechanism used by P. vulgaris. Moreover, highlight the functional and catalytic diversity of plant GSTs and demonstrate their pivotal role for addressing biotic stresses in P. vulgaris

Performance evaluation of interoperable micro-clouds

The Internet of Things (IoT) is defined as a paradigm transforming physical objects to smart objects that are inter- connected via Internet. Today, IoT objects offer embedded intelligence that can be powerful in case of fully integration of a collective manner towards the satisfaction of user needs. This work is based on the micro-clouds that are a new proposing paradigm to highlight the collective intelligence of IoT objects. Specifically, a micro-cloud could be seen as a pool of cooperated devices and their resources that form transient smart environments. Further to this, we anticipate that the inter-cloud model can expand the micro-cloud capabilities by allowing multiple micro-clouds to communicate in order to achieve a common aim. This will further push the boundaries for studying the interaction and synergetic collaborative nature between micro-cloud systems in terms of their interoperability and performance. However as the size of the system is increased the complexity of performance is additionally increased. This emphasizes the need for decentralization where resources are changing over time without any notice. The vision of this work is that micro-clouds shall be linked together to enable a full network of usable IoT objects and at the same time maintain the required quality of service from an end-user's perspective. Specifically, the aim is to identify the specific criteria which are the most relevant to optimize performance when several micro-clouds collaborate (e.g. load-balancing, throughput, turn-around times, utilization level, etc.) as well as classify their functional requirements. So the focus is on the performance analysis and evaluation of results based on a simulated specific use case scenario

Centralized micro-clouds: an infrastructure for service distribution in collaborative smart devices

In the current information-driven society, the massive use and impact of communications and mobile devices challenge the design of communication networks. This highlights the emergency of a new Internet structure namely the Internet of Things that refers to the transformation of physical objects to smart objects and their communication. Based on that the communication of such objects will offer an augmented infrastructure that is formed dynamically and on the fly based on transient links among objects. This is the concept behind cloud computing, to provide a computer-based environment where various services are available to be consumed by everyday users, anywhere and at anytime. Our vision encompasses a dynamic micro-cloud environment that is formed from devices that share computational power. This encompasses inter-linked smart objects and smart mobile devices available from a smart environment that can be formed dynamically. The proposed micro-cloud notion will be of apparent significance to maintain the required quality of service in dynamic scenarios such as those found in emergency and disaster situations. To represent such system we are focused on the development of such architecture into a novel simulation toolkit that allows the replication of Internet of Things scenarios

Online dynamic flat-field correction for MHz Microscopy data at European XFEL

The X-ray microscopy technique at the European X-ray free-electron laser (EuXFEL), operating at a MHz repetition rate, provides superior contrast and spatial-temporal resolution compared to typical microscopy techniques at other X-ray sources. In both online visualization and offline data analysis for microscopy experiments, baseline normalization is essential for further processing steps such as phase retrieval and modal decomposition. In addition, access to normalized projections during data acquisition can play an important role in decision-making and improve the quality of the data. However, the stochastic nature of XFEL sources hinders the use of existing flat-flied normalization methods during MHz X-ray microscopy experiments. Here, we present an online dynamic flat-field correction method based on principal component analysis of dynamically evolving flat-field images. The method is used for the normalization of individual X-ray projections and has been implemented as an online analysis tool at the Single Particles, Clusters, and Biomolecules and Serial Femtosecond Crystallography (SPB/SFX) instrument of EuXFEL.Comment: 14 pages, 7 figure

Data on diabetes-specific distress are needed to improve the quality of diabetes care [Correspondence]

no abstract availabl