Enabling Richer Insight Into Runtime Executions Of Systems

Systems software of very large scales are being heavily used today in various important scenarios such as online retail, banking, content services, web search and social networks. As the scale of functionality and complexity grows in these software, managing the implementations becomes a considerable challenge for developers, designers and maintainers. Software needs to be constantly monitored and tuned for optimal efficiency and user satisfaction. With large scale, these systems incorporate significant degrees of asynchrony, parallelism and distributed executions, reducing the manageability of software including performance management. Adding to the complexity, developers are under pressure between developing new functionality for customers and maintaining existing programs. This dissertation argues that the manual effort currently required to manage performance of these systems is very high, and can be automated to both reduce the likelihood of problems and quickly fix them once identified. The execution logs from these systems are easily available and provide rich information about the internals at runtime for diagnosis purposes, but the volume of logs is simply too large for today\u27s techniques. Developers hence spend many human hours observing and investigating executions of their systems during development and diagnosis of software, for performance management. This dissertation proposes the application of machine learning techniques to automatically analyze logs from executions, to challenging tasks in different phases of the software lifecycle. It is shown that the careful application of statistical techniques to features extracted from instrumentation, can distill the rich log data into easily comprehensible forms for the developers

Sedimentation of an ellipsoid inside an infinitely long tube at low and intermediate Reynolds numbers

The motion of a heavy rigid ellipsoidal particle settling in an infinitely long circular tube filled with an incompressible Newtonian fluid has been studied numerically for three categories of problems, namely, when both fluid and particle inertia are negligible, when fluid inertia is negligible but particle inertia is present, and when both fluid and particle inertia are present. The governing equations for both the fluid and the solid particle have been solved using an arbitrary Lagrangian-Eulerian based finite-element method. Under Stokes flow conditions, an ellipsoid without inertia is observed to follow a perfectly periodic orbit in which the particle rotates and moves from side to side in the tube as it settles. The amplitude and the period of this oscillatory motion depend on the initial orientation and the aspect ratio of the ellipsoid. An ellipsoid with inertia is found to follow initially a similar oscillatory motion with increasing amplitude. Its orientation tends towards a flatter configuration, and the rate of change of its orientation is found to be a function of the particle Stokes number which characterizes the particle inertia. The ellipsoid eventually collides with the tube wall, and settles into a different periodic orbit. For cases with non-zero Reynolds numbers, an ellipsoid is seen to attain a steady-state configuration wherein it falls vertically. The location and configuration of this steady equilibrium varies with the Reynolds number

Effect of a Soluble Surfactant on a Finite-Sized Bubble Motion in a Blood Vessel

We present detailed results for the motion of a finite-sized gas bubble in a blood vessel. The bubble (dispersed phase) size is taken to be such as to nearly occlude the vessel. The bulk medium is treated as a shear thinning Casson fluid and contains a soluble surfactant that adsorbs and desorbs from the interface. Three different vessel sizes, corresponding to a small artery, a large arteriole, and a small arteriole, in normal humans, are considered. The haematocrit (volume fraction of RBCs) has been taken to be 0.45. For arteriolar flow, where relevant, the Fahraeus–Lindqvist effect is taken into account. Bubble motion causes temporal and spatial gradients of shear stress at the cell surface lining the vessel wall as the bubble approaches the cell, moves over it and passes it by. Rapid reversals occur in the sign of the shear stress imparted to the cell surface during this motion. Shear stress gradients together with sign reversals are associated with a recirculation vortex at the rear of the moving bubble. The presence of the surfactant reduces the level of the shear stress gradients imparted to the cell surface as compared to an equivalent surfactant-free system. Our numerical results for bubble shapes and wall shear stresses may help explain phenomena observed in experimental studies related to gas embolism, a significant problem in cardiac surgery and decompression sickness

Non-covalent polyhedral oligomeric silsesquioxane-polyoxometalates as inorganic-organic-inorganic hybrid materials for visible-light photocatalytic splitting of water (vol 5, pg 2666, 2018)

Correction for Non-covalent polyhedral oligomeric silsesquioxane-polyoxometalates as inorganic-organic-inorganic hybrid materials for visible-light photocatalytic splitting of water' by Rajendran Prabu et al., Inorg. Chem. Front., 2018, DOI: 10.1039/c8qi00449h

Recent Advances in Synthetic Bioelastomers

This article reviews the degradability of chemically synthesized bioelastomers, mainly designed for soft tissue repair. These bioelastomers involve biodegradable polyurethanes, polyphosphazenes, linear and crosslinked poly(ether/ester)s, poly(ε-caprolactone) copolymers, poly(1,3-trimethylene carbonate) and their copolymers, poly(polyol sebacate)s, poly(diol-citrates) and poly(ester amide)s. The in vitro and in vivo degradation mechanisms and impact factors influencing degradation behaviors are discussed. In addition, the molecular designs, synthesis methods, structure properties, mechanical properties, biocompatibility and potential applications of these bioelastomers were also presented

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There are thresholds in visual perception that affect a persons interaction with a smaller screen. In this article we will look into some of the research done in cognitive psychology on perception, memory and attention and how this applies to designing games for mobile phones and other small networked devices that are limited in screen size. Examples will be taken from mobile games and the GameBoy Advance to show how this approach can be used to improve screen interaction and game play. Limitations of the Small Screen We must first ask the question; why would anyone play games on a mobile phone? A portable device such as a mobile phone does have certain advantages that are given by it’s size, a miniature networked device that one has on ones self at nearly all times. We will look further into a smaller segment of the phone, in most cases smaller than the touch tone pad, the screen utilized in these phones that are used as the main means of visual feedback towards the actions of the user. This is a small screen interface and this is where we will find the biggest limitations that thes

The Ribosome Hypothesis: Decoding Mood Disorder Complexity

Several types of mood disorders lie along a continuum, with nebulous boundaries between them. Understanding the mechanisms that contribute to mood disorder complexity is critical for effective treatment. However, present treatments are largely centered around neurotransmission and receptor-based hypotheses, which, given the high instance of treatment resistance, fail to adequately explain the complexities of mood disorders. In this opinion piece, based on our recent results, we propose a ribosome hypothesis of mood disorders. We suggest that any hypothesis seeking to explain the diverse nature of mood disorders must incorporate infrastructure diversity that results in a wide range of effects. Ribosomes, with their mobility across neurites and complex composition, have the potential to become specialized during stress; thus, ribosome diversity and dysregulation are well suited to explaining mood disorder complexity. Here, we first establish a framework connecting ribosomes to the current state of knowledge associated with mood disorders. Then, we describe the potential mechanisms through which ribosomes could homeostatically regulate systems to manifest diverse mood disorder phenotypes and discuss approaches for substantiating the ribosome hypothesis. Investigating these mechanisms as therapeutic targets holds promise for transdiagnostic avenues targeting mood disorders