Papers.

Smooth and collision-free navigation for multiple robots under differential-drive constraints

We present a method for smooth and collision-free navigation for multiple independent robots under differential-drive constraints. Our algorithm is based on the optimal reciprocal collision avoidance formulation and guarantees both smoothness in the trajectories of the robots and locally collision-free paths. We provide proofs of these guarantees and demonstrate the effectiveness of our method in experimental scenarios using iRobot Create mobile robots navigating amongst each other.

Techniques for low-latency proxy selection in wide-area P2P networks

Modeling and analyzing the effects of firewalls and NATs in P2P swarming systems

Deetoo: Scalable unstructured search built on a structured overlay

MapReduce programming with apache Hadoop

An explanation for the efficiency of scale invariant dynamics of information fusion in large teams

An MDE-Based Process for the Design, Implementation and Validation of Safety-Critical Systems

Distributed Real-Time Embedded (DRE) systems have critical requirements that need to be verified. They are either related to functional (e. g. stability of a furnace controller) or non-functional (e. g. meeting deadlines) aspects. Model-Driven Engineering (MDE) tools have emerged to ease DRE systems design. These tools are also capable of generating code. However, these tools either focus on the functional aspects or on the runtime architecture. Hence, the development cycle is partitioned into pieces with heterogeneous modeling notations and poor coordination. In this paper, we propose a MDE-based process to create DRE systems without manual coding. We show how to integrate functional and architecture concerns in a unified process. We use industry-proven modeling languages to design functional elements of the system, and automatically integrate them using our AADL toolchain.

Discovering Overlapping Groups in Social Media

Improving Efficiency and Fairness in P2P Systems with Effort-Based Incentives

Robust speaking rate estimation using broad phonetic class recognition

No more crash or crunch: Sustainable credit dynamics in a P2P community

State Space Reductions for Scalable Verification of Asynchronous Designs

Single Image Depth Estimation From Predicted Semantic Labels

We consider the problem of estimating the depth of each pixel in a scene from a single monocular image. Unlike traditional approaches, which attempt to map from appearance features to depth directly, we first perform a semantic segmentation of the scene and use the semantic labels to guide the 3D reconstruction. This approach provides several advantages: By knowing the semantic class of a pixel or region, depth and geometry constraints can be easily enforced (e.g., “sky” is far away and “ground” is horizontal). In addition, depth can be more readily predicted by measuring the difference in appearance with respect to a given semantic class.

Characterization of Hadoop Jobs Using Unsupervised Learning

Evaluation and Analysis of GreenHDFS: A Self-Adaptive, Energy-Conserving Variant of the Hadoop Distributed File System

Performance evaluation of a Python implementation of the new LEDBAT congestion control algorithm

Modeling, estimation, and control challenges for lithium-ion batteries

State estimation of a reduced electrochemical model of a lithium-ion battery

The Dark Matter at the End of the Galaxy

Poker face of inelastic dark matter: Prospects at upcoming direct detection experiments

Dark-Matter Decays and Self-Gravitating Halos

We consider models in which a dark-matter particle decays to a slightly less massive daughter particle and a noninteracting massless particle. The decay gives the daughter particle a small velocity kick. Self-gravitating dark-matter halos that have a virial velocity smaller than this velocity kick may be disrupted by these particle decays, while those with larger virial velocities will be heated. We use numerical simulations to follow the detailed evolution of the total mass and density profile of self-gravitating systems composed of particles that undergo such velocity kicks as a function of the kick speed (relative to the virial velocity) and the decay time (relative to the dynamical time). We show how these decays will affect the halo mass-concentration relation and mass function. Using measurements of the halo mass-concentration relation and galaxy-cluster mass function to constrain the lifetime--kick-velocity parameter space for decaying dark matter, we find roughly that the observations rule out the combination of kick velocities greater than 100 km/s and decay times less than a few times the age of the Universe.

Quantum theory of spontaneous and stimulated emission of surface plasmons

We introduce a quantization scheme that can be applied to surface waves propagating along a plane interface. An important result is the derivation of the energy of the surface wave for dispersive nonlossy media without invoking any specific model for the dielectric constant. Working in Coulomb's gauge, we use a modal representation of the fields. Each mode can be associated with a quantum harmonic oscillator. We have applied the formalism to derive quantum mechanically the spontaneous emission rate of surface plasmon by a two-level system.

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes

Motivation: PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program. Results: We developed PSORTb version 3.0 with improved recall, higher proteome-scale prediction coverage, and new refined localization subcategories. It is the first SCL predictor specifically geared for all prokaryotes, including archaea and bacteria with atypical membrane/cell wall topologies. It features an improved standalone program, with a new batch results delivery system complementing its web interface. We evaluated the most accurate SCL predictors using 5-fold cross validation plus we performed an independent proteomics analysis, showing that PSORTb 3.0 is the most accurate but can benefit from being complemented by Proteome Analyst predictions. Availability: http://www.psort.org/psortb (download open source software or use the web interface). Contact: [contact redacted] Supplementary Information: Supplementary data are availableat Bioinformatics online.

Tunable superconducting nanoinductors

We characterize inductors fabricated from ultra-thin, approximately 100 nm wide strips of niobium (Nb) and niobium nitride (NbN). These nanowires have a large kinetic inductance in the superconducting state. The kinetic inductance scales linearly with the nanowire length, with a typical value of 1 nH µm − 1 for NbN and 44 pH µm − 1 for Nb at a temperature of 2.5 K. We measure the temperature and current dependence of the kinetic inductance and compare our results to theoretical predictions. We also simulate the self-resonant frequencies of these nanowires in a compact meander geometry. These nanowire inductive elements have applications in a variety of microwave frequency superconducting circuits.

Health Outcomes and Costs of Community Mitigation Strategies for an Influenza Pandemic in the United States

A naturally chimeric type IIA topoisomerase in Aquifex aeolicus highlights an evolutionary path for the emergence of functional paralogs

Bacteria frequently possess two type IIA DNA topoisomerases, gyrase and topo IV, which maintain chromosome topology by variously supercoiling, relaxing, and disentangling DNA. The deeply rooted organism Aquifex aeolicus encodes one type IIA topoisomerase conflictingly categorized as either DNA gyrase or topo IV. To resolve this enzyme's catalytic properties and heritage, we conducted a series of structural and biochemical studies on the isolated GyrA/ParC CTD and the holoenzyme.

Reset dynamics and latching in niobium superconducting nanowire single-photon detectors

We study the reset dynamics of niobium(Nb)superconductingnanowire single-photon detectors (SNSPDs) using experimental measurements and numerical simulations. The numerical simulations of the detection dynamics agree well with experimental measurements, using independently determined parameters in the simulations. We find that if the photon-induced hotspot cools too slowly, the device will latch into a dc resistive state. To avoid latching, the time for the hotspot to cool must be short compared to the inductive time constant that governs the resetting of the current in the device after hotspot formation. From simulations of the energy relaxation process, we find that the hotspot cooling time is determined primarily by the temperature-dependent electron-phonon inelastic time. Latching prevents reset and precludes subsequent photon detection. Fast resetting to the superconducting state is, therefore, essential, and we demonstrate experimentally how this is achieved. We compare our results to studies of reset and latching in niobium nitride SNSPDs.

The Simple Publishing Interface (SPI)

Taming the Metadata Beast: ILOX

2020 visions

Role of the plasmapause in dictating the ground accessibility of ELF/VLF chorus

A computer-verified monadic functional implementation of the integral

It's On: Early Interpretations of ATLAS Results in Jets and Missing Energy Searches

Sync/Async parallel search for the efficient design and construction of web search engines

Dementia induces correlated reductions in white matter integrity and cortical thickness: A multivariate neuroimaging study with sparse canonical correlation analysis

On using moving windows in finite element time domain simulation for long accelerator structures

The statistical mechanics of belief sharing in multi-agent systems

SocialVPN: Enabling wide-area collaboration with integrated social and overlay networks

Analyzing Social Media Networks with NodeXL: Insights from a Connected World

Part III. Social Media Network Analysis Case Studies

Part II. NodeXL TutorialLearning by Doing

Part I. Getting Started with Analyzing Social Media Networks

Thread Networks

Email: The Lifeblood of Modern Communication

Clustering and Grouping

Preparing Data and Filtering

Getting Started with NodeXL, Layout, Visual Design, and Labeling

Social Network Analysis

Social Media

Decentralising a service-oriented architecture