Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

CD4 T cells are required for both development and maintenance of disease in a new mouse model of reversible colitis

Current therapies to treat inflammatory bowel diseases have limited efficacy, significant side effects, and often wane over time. Little is known about the cellular and molecular mechanisms operative in the process of mucosal healing from colitis. To study such events, we developed a new model of reversible colitis in which adoptive transfer of CD4(+)CD45RB(hi) T cells into Helicobacter typhlonius-colonized lymphopenic mice resulted in a rapid onset of colonic inflammation that was reversible through depletion of colitogenic T cells. Remission was associated with an improved clinical and histopathological score, reduced immune cell infiltration to the intestinal mucosa, altered intestinal gene expression profiles, regeneration of the colonic mucus layer, and the restoration of epithelial barrier integrity. Notably, colitogenic T cells were not only critical for induction of colitis but also for maintenance of disease. Depletion of colitogenic T cells resulted in a rapid drop in tumor necrosis factor α (TNFα) levels associated with reduced infiltration of inflammatory immune cells to sites of inflammation. Although neutralization of TNFα prevented the onset of colitis, anti-TNFα treatment of mice with established disease failed to resolve colonic inflammation. Collectively, this new model of reversible colitis provides an important research tool to study the dynamics of mucosal healing in chronic intestinal remitting-relapsing disorders.Mucosal Immunology advance online publication 16 September 2015; doi:10.1038/mi.2015.93.

Inhibition of photosynthesis by high temperature in oak (Quercus pubescens L.) leaves grown under natural conditions closely correlates with a reversible heat-dependent reduction of the activation state of ribulose-1,5-bisphosphate carboxylase/oxygenase

Inhibition of the net photosynthetic CO2 assimilation rate (Pn) by high temperature was examined in oak (Quercus pubescens L.) leaves grown under natural conditions. Combined measurements of gas exchange and chlorophyll (Chl) a fluorescence were employed to differentiate between inhibition originating from heat effects on components of the thylakoid membranes and that resulting from effects on photosynthetic carbon metabolism. Regardless of whether temperature was increased rapidly or gradually, Pn decreased with increasing leaf temperature and was more than 90% reduced at 45 °C as compared to 25 °C. Inhibition of Pn by heat stress did not result from reduced stomatal conductance (gs), as heat-induced reduction of gs was accompanied by an increase of the intercellular CO2 concentration (Ci). Chl a fluorescence measurements revealed that between 25 and 45 °C heat-dependent alterations of thylakoid-associated processes contributed only marginally, if at all, to the inhibition of Pn by heat stress, with photosystem II being remarkably well protected against thermal inactivation. The activation state of ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) decreased from about 90% at 25 °C to less than 30% at 45 °C. Heat stress did not affect Rubisco per se, since full activity could be restored by incubation with CO2 and Mg2+. Western-blot analysis of leaf extracts disclosed the presence of two Rubisco activase polypeptides, but heat stress did not alter the profile of the activase bands. Inhibition of Pn at high leaf temperature could be markedly reduced by artificially increasing Ci. A high Ci also stimulated photosynthetic electron transport and resulted in reduced non-photochemical fluorescence quenching. Recovery experiments showed that heat-dependent inhibition of Pn was largely, if not fully, reversible. The present results demonstrate that in Q. pubescens leaves the thylakoid membranes in general and photosynthetic electron transport in particular were well protected against heat-induced perturbations and that inhibition of Pn by high temperature closely correlated with a reversible heat-dependent reduction of the Rubisco activation state.

Medical image computing in diagnosis and intervention of spinal diseases

Spinal image analysis and computer assisted intervention have emerged as new and independent research areas, due to the importance of treatment of spinal diseases, increasing availability of spinal imaging, and advances in analytics and navigation tools. Among others, multiple modality spinal image analysis and spinal navigation tools have emerged as two keys in this new area. We believe that further focused research in these two areas will lead to a much more efficient and accelerated research path, avoiding detours that exist in other applications, such as in brain and heart.

Reversible accumulation of (1→3,1→4)‐β‐glucan endohydrolase in wheat leaves under sugar depletion

A (1→3,1→4)‐β‐D‐glucan endohydrolase [(1→3,1→4)‐β‐glucanase, EC 3.2.1.73] was detected in wheat (Triticum aestivum L.) leaves by Western analyses and activity measurements. This enzyme is able to degrade the (1→3,1→4)‐β‐glucans present in the cell walls of cereals and other grass species. In wheat, enzyme levels clearly increased during leaf development, reaching maximum values at full expansion and then decreasing upon leaf ageing. To test whether the abundance of (1→3,1→4)‐β‐glucanase might be controlled by the carbohydrate status, environmental and nutritional conditions capable of altering the leaf soluble sugar contents were used. Both the activity and enzyme protein levels rapidly and markedly increased when mature leaves were depleted of sugars (e.g. during extended dark periods), whereas elevated carbohydrate contents (e.g. following continuous illumination, glucose supply in the dark or nitrogen deficiency during a light/dark cycle) caused a rapid decrease in (1→3,1→4)‐β‐glucanase abundance or prevented its accumulation in the leaves. The physiological significance of (1→3,1→4)‐β‐glucanase accumulation under sugar depletion remains to be elucidated.

Drought stress and carbon assimilation in a warming climate: Reversible and irreversible impacts

Abstract Global change is characterized by increased {CO2} concentration in the atmosphere, increasing average temperature and more frequent extreme events including drought periods, heat waves and flooding. Especially the impacts of drought and of elevated temperature on carbon assimilation are considered in this review. Effects of extreme events on the subcellular level as well as on the whole plant level may be reversible, partially reversible or irreversible. The photosynthetically active biomass depends on the number and the size of mature leaves and the photosynthetic activity in this biomass during stress and subsequent recovery phases. The total area of active leaves is determined by leaf expansion and senescence, while net photosynthesis per leaf area is primarily influenced by stomatal opening (stomatal conductance), mesophyll conductance, activity of the photosynthetic apparatus (light absorption and electron transport, activity of the Calvin cycle) and {CO2} release by decarboxylation reactions (photorespiration, dark respiration). Water status, stomatal opening and leaf temperature represent a "magic triangle" of three strongly interacting parameters. The response of stomata to altered environmental conditions is important for stomatal limitations. Rubisco protein is quite thermotolerant, but the enzyme becomes at elevated temperature more rapidly inactivated (decarbamylation, reversible effect) and must be reactivated by Rubisco activase (carbamylation of a lysine residue). Rubisco activase is present under two forms (encoded by separate genes or products of alternative splicing of the pre-mRNA from one gene) and is very thermosensitive. Rubisco activase was identified as a key protein for photosynthesis at elevated temperature (non-stomatal limitation). During a moderate heat stress Rubisco activase is reversibly inactivated, but during a more severe stress (higher temperature and/or longer exposure) the protein is irreversibly inactivated, insolubilized and finally degraded. On the level of the leaf, this loss of photosynthetic activity may still be reversible when new Rubisco activase is produced by protein synthesis. Rubisco activase as well as enzymes involved in the detoxification of reactive oxygen species or in osmoregulation are considered as important targets for breeding crop plants which are still productive under drought and/or at elevated leaf temperature in a changing climate.

A new Stata command for computing and graphing percentile shares

Percentile shares provide an intuitive and easy-to-understand way for analyzing income or wealth distributions. A celebrated example are the top income shares sported by the works of Thomas Piketty and colleagues. Moreover, series of percentile shares, defined as differences between Lorenz ordinates, can be used to visualize whole distributions or changes in distributions. In this talk, I present a new command called pshare that computes and graphs percentile shares (or changes in percentile shares) from individual level data. The command also provides confidence intervals and supports survey estimation.

A new Stata command for computing and graphing percentile shares

Percentile shares provide an intuitive and easy-to-understand way for analyzing income or wealth distributions. A celebrated example is the top income shares sported by the works of Thomas Piketty and colleagues. Moreover, series of percentile shares, defined as differences between Lorenz ordinates, can be used to visualize whole distributions or changes in distributions. In this talk, I present a new command called pshare that computes and graphs percentile shares (or changes in percentile shares) from individual level data. The command also provides confidence intervals and supports survey estimation.

L'Hopital's Rule in Chemistry: Irreversible Morphing into Reversible Isothermal Expansions

L'Hopital's Rule is discussed in the cvase of an irreversible isothermal expansion.

Determining appropriate measurement methods for etiological research of computing-related musculoskeletal symptoms and disorders

Two studies among college students were conducted to evaluate appropriate measurement methods for etiological research on computing-related upper extremity musculoskeletal disorders (UEMSDs). ^ A cross-sectional study among 100 graduate students evaluated the utility of symptoms surveys (a VAS scale and 5-point Likert scale) compared with two UEMSD clinical classification systems (Gerr and Moore protocols). The two symptom measures were highly concordant (Lin's rho = 0.54; Spearman's r = 0.72); the two clinical protocols were moderately concordant (Cohen's kappa = 0.50). Sensitivity and specificity, endorsed by Youden's J statistic, did not reveal much agreement between the symptoms surveys and clinical examinations. It cannot be concluded self-report symptoms surveys can be used as surrogate for clinical examinations. ^ A pilot repeated measures study conducted among 30 undergraduate students evaluated computing exposure measurement methods. Key findings are: temporal variations in symptoms, the odds of experiencing symptoms increased with every hour of computer use (adjOR = 1.1, p < .10) and every stretch break taken (adjOR = 1.3, p < .10). When measuring posture using the Computer Use Checklist, a positive association with symptoms was observed (adjOR = 1.3, p < 0.10), while measuring posture using a modified Rapid Upper Limb Assessment produced unexpected and inconsistent associations. The findings were inconclusive in identifying an appropriate posture assessment or superior conceptualization of computer use exposure. ^ A cross-sectional study of 166 graduate students evaluated the comparability of graduate students to College Computing & Health surveys administered to undergraduate students. Fifty-five percent reported computing-related pain and functional limitations. Years of computer use in graduate school and number of years in school where weekly computer use was ≥ 10 hours were associated with pain within an hour of computing in logistic regression analyses. The findings are consistent with current literature on both undergraduate and graduate students. ^

Code and readme of a MATLAB-based graphical user interface program for computing functionals of the geopotential

We present a novel graphical user interface program GrafLab (GRAvity Field LABoratory) for spherical harmonic synthesis (SHS) created in MATLAB®. This program allows to comfortably compute 38 various functionals of the geopotential up to ultra-high degrees and orders of spherical harmonic expansion. For the most difficult part of the SHS, namely the evaluation of the fully normalized associated Legendre functions (fnALFs), we used three different approaches according to required maximum degree: (i) the standard forward column method (up to maximum degree 1800, in some cases up to degree 2190); (ii) the modified forward column method combined with Horner's scheme (up to maximum degree 2700); (iii) the extended-range arithmetic (up to an arbitrary maximum degree). For the maximum degree 2190, the SHS with fnALFs evaluated using the extended-range arithmetic approach takes only approximately 2-3 times longer than its standard arithmetic counterpart, i.e. the standard forward column method. In the GrafLab, the functionals of the geopotential can be evaluated on a regular grid or point-wise, while the input coordinates can either be read from a data file or entered manually. For the computation on a regular grid we decided to apply the lumped coefficients approach due to significant time-efficiency of this method. Furthermore, if a full variance-covariance matrix of spherical harmonic coefficients is available, it is possible to compute the commission errors of the functionals. When computing on a regular grid, the output functionals or their commission errors may be depicted on a map using automatically selected cartographic projection.

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

Managing large medical image collections is an increasingly demanding important issue in many hospitals and other medical settings. A huge amount of this information is daily generated, which requires robust and agile systems. In this paper we present a distributed multi-agent system capable of managing very large medical image datasets. In this approach, agents extract low-level information from images and store them in a data structure implemented in a relational database. The data structure can also store semantic information related to images and particular regions. A distinctive aspect of our work is that a single image can be divided so that the resultant sub-images can be stored and managed separately by different agents to improve performance in data accessing and processing. The system also offers the possibility of applying some region-based operations and filters on images, facilitating image classification. These operations can be performed directly on data structures in the database.

Cloud Computing en salud: Sistema para Administrar Imagenes Biomedicas

En el campo de la biomedicina se genera una inmensa cantidad de imágenes diariamente. Para administrarlas es necesaria la creación de sistemas informáticos robustos y ágiles, que necesitan gran cantidad de recursos computacionales. El presente artículo presenta un servicio de cloud computing capaz de manejar grandes colecciones de imágenes biomédicas. Gracias a este servicio organizaciones y usuarios podrían administrar sus imágenes biomédicas sin necesidad de poseer grandes recursos informáticos. El servicio usa un sistema distribuido multi agente donde las imágenes son procesadas y se extraen y almacenan en una estructura de datos las regiones que contiene junto con sus características. Una característica novedosa del sistema es que una misma imagen puede ser dividida, y las sub-imágenes resultantes pueden ser almacenadas por separado por distintos agentes. Esta característica ayuda a mejorar el rendimiento del sistema a la hora de buscar y recuperar las imágenes almacenadas.