Population and Social Biology of Free-Ranging Dogs, Canis familiaris

Population size and density, age structure, survivorship patterns, sex ratios, social organization of urban, rural, and feral dog (Canis familiaris) populations were examined in Cd. Juarez, Mexico (urban site) and on the Navajo reservation (rural and wild sites) between June 1983 and December 1984. Urban and rural dogs were less social than expected whereas dogs characteristically lived in packs. Seasonal variation in the structure of feral dog packs influenced by reproduction, both directly (pups born into the pack) and indirectly (pregnant females may temporarily emigrate form the pack to give birth)

CLUSTERED HIERARCHICAL ANOMALY AND OUTLIER DETECTION ALGORITHMS

Anomaly and outlier detection is a long-standing problem in machine learning. In some cases, anomaly detection is easy, such as when data are drawn from well-characterized distributions such as the Gaussian. However, when data occupy high-dimensional spaces, anomaly detection becomes more difficult. We present CLAM (Clustered Learning of Approximate Manifolds), a manifold mapping technique in any metric space. CLAM begins with a fast hierarchical clustering technique and then induces a graph from the cluster tree, based on overlapping clusters as selected using several geometric and topological features. Using these graphs, we implement CHAODA (Clustered Hierarchical Anomaly and Outlier Detection Algorithms), exploring various properties of the graphs and their constituent clusters to find outliers. CHAODA employs a form of transfer learning based on a training set of datasets, and applies this knowledge to a separate test set of datasets of different cardinalities, dimensionalities, and domains. On 24 publicly available datasets, we compare CHAODA (by measure of ROC AUC) to a variety of state-of-the-art unsupervised anomaly-detection algorithms. Six of the datasets are used for training. CHAODA outperforms other approaches on 16 of the remaining 18 datasets. CLAM and CHAODA scale to large, high-dimensional “big data” anomalydetection problems, and generalize across datasets and distance functions. Source code to CLAM and CHAODA are freely available on GitHub1

Dynamics of Gas-Fluidized Granular Rods

We study a quasi-two-dimensional monolayer of granular rods fluidized by a spatially and temporally homogeneous upflow of air. By tracking the position and orientation of the particles, we characterize the dynamics of the system with sufficient resolution to observe ballistic motion at the shortest time scales. Particle anisotropy gives rise to dynamical anisotropy and superdiffusive dynamics parallel to the rod’s long axis, causing the parallel and perpendicular mean-square displacements to become diffusive on different time scales. The distributions of free times and free paths between collisions deviate from exponential behavior, underscoring the nonthermal character of the particle motion. The dynamics show evidence of rotationaltranslational coupling similar to that of an anisotropic Brownian particle. We model rotational-translational coupling in the single-particle dynamics with a modified Langevin model using nonthermal noise sources. This suggests a phenomenological approach to thinking about collections of self-propelling particles in terms of enhanced memory effects

A Very Late Viral Protein Triggers the Lytic Release of SV40

How nonenveloped viruses such as simian virus 40 (SV40) trigger the lytic release of their progeny is poorly understood. Here, we demonstrate that SV40 expresses a novel later protein termed VP4 that triggers the timely lytic release of its progeny. Like VP3, VP4 synthesis initiates from a downstream AUG start codon within the VP2 transcript and localizes to the nucleus. However, VP4 expression occurs ∼24 h later at a time that coincides with cell lysis, and it is not incorporated into mature virions. Mutation of the VP4 initiation codon from the SV40 genome delayed lysis by 2 d and reduced infectious particle release. Furthermore, the co-expression of VP4 and VP3, but not their individual expression, recapitulated cell lysis in bacteria. Thus, SV40 regulates its life cycle by the later temporal expression of VP4, which results in cell lysis and enables the 50-nm virus to exit the cell. This study also demonstrates how viruses can generate multiple proteins with diverse functions and localizations from a single reading frame

Using Lunar Observations to Validate Pointing Accuracy and Geolocation, Detector Sensitivity Stability and Static Point Response of the CERES Instruments

Validation of in-orbit instrument performance is a function of stability in both instrument and calibration source. This paper describes a method using lunar observations scanning near full moon by the Clouds and Earth Radiant Energy System (CERES) instruments. The Moon offers an external source whose signal variance is predictable and non-degrading. From 2006 to present, these in-orbit observations have become standardized and compiled for the Flight Models -1 and -2 aboard the Terra satellite, for Flight Models-3 and -4 aboard the Aqua satellite, and beginning 2012, for Flight Model-5 aboard Suomi-NPP. Instrument performance measurements studied are detector sensitivity stability, pointing accuracy and static detector point response function. This validation method also shows trends per CERES data channel of 0.8% per decade or less for Flight Models 1-4. Using instrument gimbal data and computed lunar position, the pointing error of each detector telescope, the accuracy and consistency of the alignment between the detectors can be determined. The maximum pointing error was 0.2 Deg. in azimuth and 0.17 Deg. in elevation which corresponds to an error in geolocation near nadir of 2.09 km. With the exception of one detector, all instruments were found to have consistent detector alignment from 2006 to present. All alignment error was within 0.1o with most detector telescopes showing a consistent alignment offset of less than 0.02 Deg

Evaluation of Technology Concepts for Energy, Automation, and System State Awareness in Commercial Airline Flight Decks

A pilot-in-the-loop flight simulation study was conducted at NASA Langley Research Center to evaluate flight deck systems that (1) provide guidance for recovery from low energy states and stalls, (2) present the current state and expected future state of automated systems, and/or (3) show the state of flight-critical data systems in use by automated systems and primary flight instruments. The study was conducted using 13 commercial airline crews from multiple airlines, paired by airline to minimize procedural effects. Scenarios spanned a range of complex conditions and several emulated causal and contributing factors found in recent accidents involving loss of state awareness by pilots (e.g., energy state, automation state, and/or system state). Three new technology concepts were evaluated while used in concert with current state-of-the-art flight deck systems and indicators. The technologies include a stall recovery guidance algorithm and display concept, an enhanced airspeed control indicator that shows when automation is no longer actively controlling airspeed, and enhanced synoptic pages designed to work with simplified interactive electronic checklists. An additional synoptic was developed to provide the flight crew with information about the effects of loss of flight critical data. Data was collected via questionnaires administered at the completion of flight scenarios, audio/video recordings, flight data, head and eye tracking data, pilot control inputs, and researcher observations. This paper presents findings derived from the questionnaire responses and subjective data measures including workload, situation awareness, usability, and acceptability as well as analyses of two low-energy flight events that resulted in near-stall conditions