Decoupling Cache Coherence From XML in Model Checking

Many electrical engineers would agree that, had it not been for link-level acknowledgements, the eval- uation of congestion control might never have occurred. After years of significant research into Smalltalk, we validate the visualization of vacuum tubes. Our focus in our research is not on whether the famous encrypted algorithm for the visualization of simulated annealing by Garcia [5] is impossible, but rather on describing a novel application for the investigation of Lamport clocks (LealEst)

Hybrid Deterministic-Stochastic Methods for Data Fitting

Many structured data-fitting applications require the solution of an optimization problem involving a sum over a potentially large number of measurements. Incremental gradient algorithms offer inexpensive iterations by sampling a subset of the terms in the sum. These methods can make great progress initially, but often slow as they approach a solution. In contrast, full-gradient methods achieve steady convergence at the expense of evaluating the full objective and gradient on each iteration. We explore hybrid methods that exhibit the benefits of both approaches. Rate-of-convergence analysis shows that by controlling the sample size in an incremental gradient algorithm, it is possible to maintain the steady convergence rates of full-gradient methods. We detail a practical quasi-Newton implementation based on this approach. Numerical experiments illustrate its potential benefits.Comment: 26 pages. Revised proofs of Theorems 2.6 and 3.1, results unchange

Adding Isolated Vertices Makes some Online Algorithms Optimal

An unexpected difference between online and offline algorithms is observed. The natural greedy algorithms are shown to be worst case online optimal for Online Independent Set and Online Vertex Cover on graphs with 'enough' isolated vertices, Freckle Graphs. For Online Dominating Set, the greedy algorithm is shown to be worst case online optimal on graphs with at least one isolated vertex. These algorithms are not online optimal in general. The online optimality results for these greedy algorithms imply optimality according to various worst case performance measures, such as the competitive ratio. It is also shown that, despite this worst case optimality, there are Freckle graphs where the greedy independent set algorithm is objectively less good than another algorithm. It is shown that it is NP-hard to determine any of the following for a given graph: the online independence number, the online vertex cover number, and the online domination number.Comment: A footnote in the .tex file didn't show up in the last version. This was fixe

DeepWalk: Online Learning of Social Representations

We present DeepWalk, a novel approach for learning latent representations of vertices in a network. These latent representations encode social relations in a continuous vector space, which is easily exploited by statistical models. DeepWalk generalizes recent advancements in language modeling and unsupervised feature learning (or deep learning) from sequences of words to graphs. DeepWalk uses local information obtained from truncated random walks to learn latent representations by treating walks as the equivalent of sentences. We demonstrate DeepWalk's latent representations on several multi-label network classification tasks for social networks such as BlogCatalog, Flickr, and YouTube. Our results show that DeepWalk outperforms challenging baselines which are allowed a global view of the network, especially in the presence of missing information. DeepWalk's representations can provide $F_1$ scores up to 10% higher than competing methods when labeled data is sparse. In some experiments, DeepWalk's representations are able to outperform all baseline methods while using 60% less training data. DeepWalk is also scalable. It is an online learning algorithm which builds useful incremental results, and is trivially parallelizable. These qualities make it suitable for a broad class of real world applications such as network classification, and anomaly detection.Comment: 10 pages, 5 figures, 4 table

Impact of proctoring on success rates for percutaneous revascularisation of coronary chronic total occlusions.

OBJECTIVE: To assess the impact of proctoring for chronic total occlusion (CTO) percutaneous coronary intervention (PCI) in six UK centres. METHODS: We retrospectively analysed 587 CTO procedures from six UK centres and compared success rates of operators who had received proctorship with success rates of the same operators before proctorship (pre-proctored) and operators in the same institutions who had not been proctored (non-proctored). There were 232 patients in the pre-proctored/non-proctored group and 355 patients in the post-proctored group. Complexity was assessed by calculating the Japanese CTO (JCTO) score for each case. RESULTS: CTO PCI success was greater in the post-proctored compared with the pre-proctored/non-proctored group (77.5% vs 62.1%, p<0.0001). In more complex cases where JCTO≥2, the difference in success was greater (70.7% vs 49.5%, p=0.0003). After proctoring, there was an increase in CTO PCI activity in centres from 2.5% to 3.5%, p<0.0001 (as a proportion of total PCI), and the proportion of very difficult cases with JCTO score ≥3 increased from 15.3% (35/229) to 29.7% (105/354), p<0.0001. CONCLUSIONS: Proctoring resulted in an increase in procedural success for CTO PCI, an increase in complex CTO PCI and an increase in total CTO PCI activity. Proctoring may be a valuable way to improve access to CTO PCI and the likelihood of procedural success

Toward the PSTN/Internet Inter-Networking--Pre-PINT Implementations

This document contains the information relevant to the development of the inter-networking interfaces underway in the Public Switched Telephone Network (PSTN)/Internet Inter-Networking (PINT) Working Group. It addresses technologies, architectures, and several (but by no means all) existing pre-PINT implementations of the arrangements through which Internet applications can request and enrich PSTN telecommunications services. The common denominator of the enriched services (a.k.a. PINT services) is that they combine the Internet and PSTN services in such a way that the Internet is used for non-voice interactions, while the voice (and fax) are carried entirely over the PSTN. One key observation is that the pre-PINT implementations, being developed independently, do not inter-operate. It is a task of the PINT Working Group to define the inter-networking interfaces that will support inter-operation of the future implementations of PINT services

Visibility graphs of random scalar fields and spatial data

The family of visibility algorithms were recently introduced as mappings between time series and graphs. Here we extend this method to characterize spatially extended data structures by mapping scalar fields of arbitrary dimension into graphs. After introducing several possible extensions, we provide analytical results on some topological properties of these graphs associated to some types of real-valued matrices, which can be understood as the high and low disorder limits of real-valued scalar fields. In particular, we find a closed expression for the degree distribution of these graphs associated to uncorrelated random fields of generic dimension, extending a well known result in one-dimensional time series. As this result holds independently of the field's marginal distribution, we show that it directly yields a statistical randomness test, applicable in any dimension. We showcase its usefulness by discriminating spatial snapshots of two-dimensional white noise from snapshots of a two-dimensional lattice of diffusively coupled chaotic maps, a system that generates high dimensional spatio-temporal chaos. We finally discuss the range of potential applications of this combinatorial framework, which include image processing in engineering, the description of surface growth in material science, soft matter or medicine and the characterization of potential energy surfaces in chemistry, disordered systems and high energy physics. An illustration on the applicability of this method for the classification of the different stages involved in carcinogenesis is briefly discussed

A Neural Framework for Organization and Flexible Utilization of Episodic Memory in Cumulatively Learning Baby Humanoids

Cumulatively developing robots offer a unique opportunity to reenact the constant interplay between neural mechanisms related to learning, memory, prospection, and abstraction from the perspective of an integrated system that acts, learns, remembers, reasons, and makes mistakes. Situated within such interplay lie some of the computationally elusive and fundamental aspects of cognitive behavior: the ability to recall and flexibly exploit diverse experiences of one’s past in the context of the present to realize goals, simulate the future, and keep learning further. This article is an adventurous exploration in this direction using a simple engaging scenario of how the humanoid iCub learns to construct the tallest possible stack given an arbitrary set of objects to play with. The learning takes place cumulatively, with the robot interacting with different objects (some previously experienced, some novel) in an open-ended fashion. Since the solution itself depends on what objects are available in the “now,” multiple episodes of past experiences have to be remembered and creatively integrated in the context of the present to be successful. Starting from zero, where the robot knows nothing, we explore the computational basis of organization episodic memory in a cumulatively learning humanoid and address (1) how relevant past experiences can be reconstructed based on the present context, (2) how multiple stored episodic memories compete to survive in the neural space and not be forgotten, (3) how remembered past experiences can be combined with explorative actions to learn something new, and (4) how multiple remembered experiences can be recombined to generate novel behaviors (without exploration). Through the resulting behaviors of the robot as it builds, breaks, learns, and remembers, we emphasize that mechanisms of episodic memory are fundamental design features necessary to enable the survival of autonomous robots in a real world where neither everything can be known nor can everything be experienced

Passenger transport decarbonization in emerging economies: policy lessons from modelling long-term deep decarbonization pathways

Reaching the goal of the Paris Agreement will not be possible without a deep decarbonization of the passenger transport sector. In emerging economies experiencing rapid economic growth and social transformations, and large-scale development of urban areas and associated infrastructure, opportunities and challenges exist when considering a broader set of mitigation options. In this paper, we apply the Deep Decarbonization Pathways (DDP) approach to develop and report scenarios on the passenger transport sector in Brazil, India, Indonesia, and South Africa. This approach supports an increase in the sectoral ambition of covering all drivers of change in transport mobility and facilitating collective comparison and policy discussions on the barriers and enablers of transitions. The scenario analysis illustrates that all four countries can achieve reductions in emissions per passenger kilometres of 59% and up to 92% by 2050 while meeting growing mobility needs. Lastly, the analysis identifies short-term policy needed to address barriers and promote enablers

Encapsulation of olanzapine into beeswax microspheres: preparation, characterization and release kinetics

The objective of the present study was to minimise the unwanted side effects of olanzapine (OZ) drug by kinetic control of drug release by entrapping into gastro resistant, biodegradable waxes such as beeswax (BW) microspheres using meltable emulsified dispersion cooling induced solidification technique utilizing a wetting agent. Solid, discrete, reproducible free flowing microspheres were obtained. The yield of the microspheres was up to 94.0 %. The microspheres had smooth surfaces, with free flowing and good packing properties, indicating that the obtained angle of repose, % Carr’s index and tapped density values were well within the limit. More than 97.0 % of the isolated spherical microspheres were in the particle size range of 312-330 μm were confirmed by scanning electron microscopy (SEM) photographs. The drug loaded in microspheres was stable and compatible, as confirmed by DSC and FTIR studies. The release of drug was controlled for more than 8 h. Intestinal drug release from microspheres was studied and compared with the release behaviour of commercially available formulation Olanex®. The release kinetics followed different transport mechanisms. The drug release from the bees wax microspheres was found sufficient for oral delivery and the drug release profile was significantly affected by the properties of wax used in the preparation of microspheres. These results demonstrate the potential use of wax for the fabrication of controlled delivery devices for many water soluble drugs.Colegio de Farmacéuticos de la Provincia de Buenos Aire