Inference and Labeling of Metric-Induced Network Topologies

The development and deployment of distributed network-aware applications and services over the Internet require the ability to compile and maintain a model of the underlying network resources with respect to (one or more) characteristic properties of interest. To be manageable, such models must be compact, and must enable a representation of properties along temporal, spatial, and measurement resolution dimensions. In this paper, we propose a general framework for the construction of such metric-induced models using end-to-end measurements. We instantiate our approach using one such property, packet loss rates, and present an analytical framework for the characterization of Internet loss topologies. From the perspective of a server the loss topology is a logical tree rooted at the server with clients at its leaves, in which edges represent lossy paths between a pair of internal network nodes. We show how end-to-end unicast packet probing techniques could b e used to (1) infer a loss topology and (2) identify the loss rates of links in an existing loss topology. Correct, efficient inference of loss topology information enables new techniques for aggregate congestion control, QoS admission control, connection scheduling and mirror site selection. We report on simulation, implementation, and Internet deployment results that show the effectiveness of our approach and its robustness in terms of its accuracy and convergence over a wide range of network conditions.

Measuring Bottleneck Bandwidth of Targeted Path Segments

Accurate measurement of network bandwidth is crucial for flexible Internet applications and protocols which actively manage and dynamically adapt to changing utilization of network resources. These applications must do so to perform tasks such as distributing and delivering high-bandwidth media, scheduling service requests and performing admission control. Extensive work has focused on two approaches to measuring bandwidth: measuring it hop-by-hop, and measuring it end-to-end along a path. Unfortunately, best-practice techniques for the former are inefficient and techniques for the latter are only able to observe bottlenecks visible at end-to-end scope. In this paper, we develop and simulate end-to-end probing methods which can measure bottleneck bandwidth along arbitrary, targeted subpaths of a path in the network, including subpaths shared by a set of flows. As another important contribution, we describe a number of practical applications which we foresee as standing to benefit from solutions to this problem, especially in emerging, flexible network architectures such as overlay networks, ad-hoc networks, peer-to-peer architectures and massively accessed content servers.

Robust Identification of Shared Losses Using End-to-End Unicast Probes

Current Internet transport protocols make end-to-end measurements and maintain per-connection state to regulate the use of shared network resources. When two or more such connections share a common endpoint, there is an opportunity to correlate the end-to-end measurements made by these protocols to better diagnose and control the use of shared resources. We develop packet probing techniques to determine whether a pair of connections experience shared congestion. Correct, efficient diagnoses could enable new techniques for aggregate congestion control, QoS admission control, connection scheduling and mirror site selection. Our extensive simulation results demonstrate that the conditional (Bayesian) probing approach we employ provides superior accuracy, converges faster, and tolerates a wider range of network conditions than recently proposed memoryless (Markovian) probing approaches for addressing this opportunity.

Modulated electrostatic modes in pair plasmas: Modulational stability profile and envelope excitations

A pair plasma consisting of two types of ions, possessing equal masses and opposite charges, is considered. The nonlinear propagation of modulated electrostatic wave packets is studied by employing a two-fluid plasma model. Considering propagation parallel to the external magnetic field, two distinct electrostatic modes are obtained, namely a quasiacoustic lower moddfe and a Langmuir-like, as optic-type upper one, in agreement with experimental observations and theoretical predictions. Considering small yet weakly nonlinear deviations from equilibrium, and adopting a multiple-scale technique, the basic set of model equations is reduced to a nonlinear Schrodinger equation for the slowly varying electric field perturbation amplitude. The analysis reveals that the lower (acoustic) mode is stable and may propagate in the form of a dark-type envelope soliton (a void) modulating a carrier wave packet, while the upper linear mode is intrinsically unstable, and may favor the formation of bright-type envelope soliton (pulse) modulated wave packets. These results are relevant to recent observations of electrostatic waves in pair-ion (fullerene) plasmas, and also with respect to electron-positron plasma emission in pulsar magnetospheres. (c) 2006 American Institute of Physics.

Assessment of oral proficiency in EAP programs : a case for pair interaction

Reliability and validity in the testing of spoken language are essential in order to assess learners' English language proficiency as evidence of their readiness to begin courses in tertiary institutions. Research has indicated that the task chosen to elicit language samples can have a marked effect on both the nature of the interaction, including the power differential, and assessment, raising the issue of ethics. This exploratory studey, with a group of 32 students from the Peoples's Republic of China preparing for tertiary study in Singapore, compares test-takers' reactions to the use of an oral proficiency interview and a pair interaction.

Classification of packet contents for malware detection

Many existing schemes for malware detection are signature-based. Although they can effectively detect known malwares, they cannot detect variants of known malwares or new ones. Most network servers do not expect executable code in their in-bound network traffic, such as on-line shopping malls, Picasa, Youtube, Blogger, etc. Therefore, such network applications can be protected from malware infection by monitoring their ports to see if incoming packets contain any executable contents. This paper proposes a content-classification scheme that identifies executable content in incoming packets. The proposed scheme analyzes the packet payload in two steps. It first analyzes the packet payload to see if it contains multimedia-type data (such as . If not, then it classifies the payload either as text-type (such as or executable. Although in our experiments the proposed scheme shows a low rate of false negatives and positives (4.69% and 2.53%, respectively), the presence of inaccuracies still requires further inspection to efficiently detect the occurrence of malware. In this paper, we also propose simple statistical and combinatorial analysis to deal with false positives and negatives.

Predictive compensation for variable network delays and packet losses in networked control systems

Networked control systems (NCSs) offer many advantages over conventional control; however, they also demonstrate challenging problems such as network-induced delay and packet losses. This paper proposes an approach of predictive compensation for simultaneous network-induced delays and packet losses. Different from the majority of existing NCS control methods, the proposed approach addresses co-design of both network and controller. It also alleviates the requirements of precise process models and full understanding of NCS network dynamics. For a series of possible sensor-to-actuator delays, the controller computes a series of corresponding redundant control values. Then, it sends out those control values in a single packet to the actuator. Once receiving the control packet, the actuator measures the actual sensor-to-actuator delay and computes the control signals from the control packet. When packet dropout occurs, the actuator utilizes past control packets to generate an appropriate control signal. The effectiveness of the approach is demonstrated through examples.

Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions

We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.

My Kitchen Rules pair are all the rage on social media – for now

The launch of the current series of My Kitchen Rules has undoubtedly been successful, both in terms of television ratings and in capturing a social media audience, clearly winning the battle for the Twitter audience on premiere night, and maintaining a lead over both The Block and The Biggest Loser since then. But it is the controversy surrounding Perth contestants Kelly Ramsay and Chloe James that has dominated media coverage today, detailing the abuse to which they have been subjected on social media.

Distinguishing between mechanisms of cell aggregation using pair-correlation functions

Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.

Interpreting scratch assays using pair density dynamics and approximate Bayesian computation

Quantifying the impact of biochemical compounds on collective cell spreading is an essential element of drug design, with various applications including developing treatments for chronic wounds and cancer. Scratch assays are a technically simple and inexpensive method used to study collective cell spreading; however, most previous interpretations of scratch assays are qualitative and do not provide estimates of the cell diffusivity, D, or the cell proliferation rate,l. Estimating D and l is important for investigating the efficacy of a potential treatment and provides insight into the mechanism through which the potential treatment acts. While a few methods for estimating D and l have been proposed, these previous methods lead to point estimates of D and l, and provide no insight into the uncertainty in these estimates. Here, we compare various types of information that can be extracted from images of a scratch assay, and quantify D and l using discrete computational simulations and approximate Bayesian computation. We show that it is possible to robustly recover estimates of D and l from synthetic data, as well as a new set of experimental data. For the first time, our approach also provides a method to estimate the uncertainty in our estimates of D and l. We anticipate that our approach can be generalized to deal with more realistic experimental scenarios in which we are interested in estimating D and l, as well as additional relevant parameters such as the strength of cell-to-cell adhesion or the strength of cell-to-substrate adhesion.

Expression of mammalian glutathione S-transferase 5-5 in Salmonella typhimurium TA1535 leads to base-pair mutations upon exposure to dihalomethanes

Dihalomethanes can produce liver tumors in mice but not in rats, and concern exists about the risk of these compounds to humans. Glutathione (GSH) conjugation of dihalomethanes has been considered to be a critical event in the bioactivation process, and risk assessment is based upon this premise; however, there is little experimental support for this view or information about the basis of genotoxicity. A plasmid vector containing rat GSH S-transferase 5-5 was transfected into the Salmonella typhimurium tester strain TA1535, which then produced active enzyme. The transfected bacteria produced base-pair revertants in the presence of ethylene dihalides or dihalomethanes, in the order CH2Br2 > CH2BrCl > CH2Cl2. However, revertants were not seen when cells were exposed to GSH, CH2Br2, and an amount of purified GSH S-transferase 5-5 (20-fold excess in amount of that expressed within the cells). HCHO, which is an end product of the reaction of GSH with dihalomethanes, also did not produce mutations. S-(1-Acetoxymethyl)GSH was prepared as an analog of the putative S-(1-halomethyl)GSH reactive intermediates. This analog did not produce revertants, consistent with the view that activation of dihalomethanes must occur within the bacteria to cause genetic damage, presenting a model to be considered in studies with mammalian cells. S-(1-Acetoxymethyl)GSH reacted with 2′-deoxyguanosine to yield a major adduct, identified as S-[1-(N2-deoxyguanosinyl)methyl]GSH. Demonstration of the activation of dihalomethanes by this mammalian GSH S-transferase theta class enzyme should be of use in evaluating the risk of these chemicals, particularly in light of reports of the polymorphic expression of a similar activity in humans.

Genomic architecture of ecologically divergent body shape in a pair of sympatric crater lake cichlid fishes

Determining the genetic bases of adaptations and their roles in speciation is a prominent issue in evolutionary biology. Cichlid fish species flocks are a prime example of recent rapid radiations, often associated with adaptive phenotypic divergence from a common ancestor within a short period of time. In several radiations of freshwater fishes, divergence in ecomorphological traits - including body shape, colour, lips and jaws - is thought to underlie their ecological differentiation, specialization and, ultimately, speciation. The Midas cichlid species complex (Amphilophus spp.) of Nicaragua provides one of the few known examples of sympatric speciation where species have rapidly evolved different but parallel morphologies in young crater lakes. This study identified significant QTL for body shape using SNPs generated via ddRAD sequencing and geometric morphometric analyses of a cross between two ecologically and morphologically divergent, sympatric cichlid species endemic to crater Lake Apoyo: an elongated limnetic species (Amphilophus zaliosus) and a high-bodied benthic species (Amphilophus astorquii). A total of 453 genome-wide informative SNPs were identified in 240 F-2 hybrids. These markers were used to construct a genetic map in which 25 linkage groups were resolved. Seventy-two segregating SNPs were linked to 11 QTL. By annotating the two most highly supported QTL-linked genomic regions, genes that might contribute to divergence in body shape along the benthic-limnetic axis in Midas cichlid sympatric adaptive radiations were identified. These results suggest that few genomic regions of large effect contribute to early stage divergence in Midas cichlids.