Graph Annotations in Modeling Complex Network Topologies

The coarsest approximation of the structure of a complex network, such as the Internet, is a simple undirected unweighted graph. This approximation, however, loses too much detail. In reality, objects represented by vertices and edges in such a graph possess some non-trivial internal structure that varies across and differentiates among distinct types of links or nodes. In this work, we abstract such additional information as network annotations. We introduce a network topology modeling framework that treats annotations as an extended correlation profile of a network. Assuming we have this profile measured for a given network, we present an algorithm to rescale it in order to construct networks of varying size that still reproduce the original measured annotation profile. Using this methodology, we accurately capture the network properties essential for realistic simulations of network applications and protocols, or any other simulations involving complex network topologies, including modeling and simulation of network evolution. We apply our approach to the Autonomous System (AS) topology of the Internet annotated with business relationships between ASs. This topology captures the large-scale structure of the Internet. In depth understanding of this structure and tools to model it are cornerstones of research on future Internet architectures and designs. We find that our techniques are able to accurately capture the structure of annotation correlations within this topology, thus reproducing a number of its important properties in synthetically-generated random graphs

A smartphone-based Teleradiology system

The development of a teleradiology application for remote monitoring and processing of patient image data using 2nd generation mobile devices with enhanced network services, is of extreme interest, especially when the final means of display is a smartphone, a very light and compact handheld device. In the following paper the development of applications, that are responsible for remote monitoring and processing of medical images, is investigated

On the contribution of density perturbations and gravitational waves to the lower order multipoles of the Cosmic Microwave Background Radiation

The important studies of Peebles, and Bond and Efstathiou have led to the formula C_l = const/[l(l +1)] aimed at describing the lower order multipoles of the CMBR temperature variations caused by density perturbations with the flat spectrum. Clearly, this formula requires amendments, as it predicts an infinitely large monopole C_0, and a dipole moment C_1 only 6/2 times larger than the quadrupole C_2, both predictions in conflict with observations. We restore the terms omitted in the course of the derivation of this formula, and arrive at a new expression. According to the corrected formula, the monopole moment is finite and small, while the dipole moment is sensitive to short-wavelength perturbations, and numerically much larger than the quadrupole, as one would expect on physical grounds. At the same time, the function l(l +1)C_l deviates from a horizontal line and grows with l, for l \geq 2. We show that the inclusion of the modulating (transfer) function terminates the growth and forms the first peak, recently observed. We fit the theoretical curves to the position and height of the first peak, as well as to the observed dipole, varying three parameters: red-shift at decoupling, red-shift at matter-radiation equality, and slope of the primordial spectrum. It appears that there is always a deficit, as compared with the COBE observations, at small multipoles, l \sim 10. We demonstrate that a reasonable and theoretically expected amount of gravitational waves bridges this gap at small multipoles, leaving the other fits as good as before. We show that the observationally acceptable models permit somewhat `blue' primordial spectra. This allows one to avoid the infra-red divergence of cosmological perturbations, which is otherwise present.Comment: prints to 25 pages including 14 figures, several additional sentences on interpretation, new references, to appear in Int. Journ. Mod. Physics

Orbital domain state and finite size scaling in ferromagnetic insulating manganites

55Mn and 139La NMR measurements on a high quality single crystal of ferromagnetic (FM) La0.80Ca20MnO3 demonstrate the formation of localized Mn(3+,4+) states below 70 K, accompanied with strong anomalous increase of certain FM neutron Bragg peaks. (55,139)(1/T1) spin-lattice relaxation rates diverge on approaching this temperature from below, signalling a genuine phase transition at T(tr) approx. 70 K. The increased local magnetic anisotropy of the low temperature phase, the cooling-rate dependence of the Bragg peaks, and the observed finite size scaling of T(tr) with Ca (hole) doping, are suggestive of freezing into an orbital domain state, precursor to a phase transition into an inhomogeneous orbitally ordered state embodying hole-rich walls.Comment: 4 pages, 4 figure

Many-task computing on many-core architectures

Many-Task Computing (MTC) is a common scenario for multiple parallel systems, such as cluster, grids, cloud and supercomputers, but it is not so popular in shared memory parallel processors. In this sense and given the spectacular growth in performance and in number of cores integrated in many-core architectures, the study of MTC on such architectures is becoming more and more relevant. In this paper, authors present what are those programming mechanisms to take advantages of such massively parallel features for the particular target of MTC. Also, the hardware features of the two dominant many-core platforms (NVIDIA's GPUs and Intel Xeon Phi) are also analyzed for our specific framework. Given the important differences in terms of hardware and software in our two many-core platforms, we have considered different strategies based on CUDA (for GPUs) and OpenMP (for Intel Xeon Phi). We carried out several test cases based on an appropriate and widely studied problem for benchmarking as matrix multiplication. Essentially, this study consisted of comparing the time consumed for computing in parallel several tasks one by one (the whole computational resources are used just to compute one task at a time) with the time consumed for computing in parallel the same set of tasks simultaneously (the whole computational resources are used for computing the set of tasks at very same time). Finally, we compared both software-hardware scenarios to identify the most relevant computer features in each of our many-core architectures

Not Quite this and not Quite that: Anorexia Nervosa, Counselling Psychology, and Hermeneutic Inquiry in a Tapestry of Ambiguity

As a group of researchers exploring how to best understand the complex topic of families discovering their loved one has anorexia nervosa (AN), we found that we had to weave ambiguity into our design. Embracing ambiguity allowed us to create a tapestry that acknowledges the ambiguity of AN, counselling psychology (and other helping professions), and hermeneutic inquiry. In fact, the “not quite this and not quite that” features of these three constructs emerged as the thread that holds the inquiry together. We review the topic of AN through a lens of ambiguity.  Further, we position both the field of counselling psychology and the research method of hermeneutic inquiry as compatible frameworks in the study of AN, in both practice and research. By acknowledging, and at times even embracing, ambiguity, we respect the complexity of the situation we are studying. 

Survival and quality of life benefit after endoscopic management of malignant central airway obstruction

Although interventional management of malignant central airway obstruction (mCAO) is well established, its impact on survival and quality of life (QoL) has not been extensively studied.We prospectively assessed survival, QoL and dyspnea (using validated EORTC questionnaire) in patients with mCAO 1 day before interventional bronchoscopy, 1 week after and every following month, in comparison to patients who declined this approach. Material/Patients/Methods: 36 patients underwent extensive interventional bronchoscopic management as indicated, whereas 12 declined. All patients received full chemotherapy and radiotherapy as indicated. Patients of the 2 groups were matched for age, comorbidities, type of malignancy and level of obstruction. Follow up time was 8.0±8.7 (range 1-38) months.Mean survival for intervention and control group was 10±9 and 4±3 months respectively (p=0.04). QoL improved significantly in intervention group patients up to the 6(th) month (p<0.05) not deteriorating for those surviving up to 12 months. Dyspnea decreased in patients of the intervention group 1 month post procedure remaining reduced for survivors over the 12th month. Patients of the control group had worse QoL and dyspnea in all time points.Interventional management of patients with mCAO, may achieve prolonged survival with sustained significant improvement of QoL and dyspnea

Hyperbolic Geometry of Complex Networks

We develop a geometric framework to study the structure and function of complex networks. We assume that hyperbolic geometry underlies these networks, and we show that with this assumption, heterogeneous degree distributions and strong clustering in complex networks emerge naturally as simple reflections of the negative curvature and metric property of the underlying hyperbolic geometry. Conversely, we show that if a network has some metric structure, and if the network degree distribution is heterogeneous, then the network has an effective hyperbolic geometry underneath. We then establish a mapping between our geometric framework and statistical mechanics of complex networks. This mapping interprets edges in a network as non-interacting fermions whose energies are hyperbolic distances between nodes, while the auxiliary fields coupled to edges are linear functions of these energies or distances. The geometric network ensemble subsumes the standard configuration model and classical random graphs as two limiting cases with degenerate geometric structures. Finally, we show that targeted transport processes without global topology knowledge, made possible by our geometric framework, are maximally efficient, according to all efficiency measures, in networks with strongest heterogeneity and clustering, and that this efficiency is remarkably robust with respect to even catastrophic disturbances and damages to the network structure