A 10-year time series of zooplankton anomalies off the British Columbia coast [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): Zooplankton biomass and species composition have been sampled since 1985 at a set of standard locations off Vancouver Island. From these data, I have estimated multi-year average seasonal cycles and time series of anomalies from these averages.

Atmospheric circulation patterns associated with tree growth anomalies in the central and southern Sierra Nevada mountains [abstract]

EXTRACT (SEE PDF FOR FULL ABSTRACT): In this work, I examine patterns of atmospheric circulation associated with tree growth anomalies at mid-to-high latitudes (2000-3500 meters).

Dynamics of in-plane arch rocking: An energy approach

This study employs an analytical model to describe the rocking response of a masonry arch to in-plane seismic loading. Through evaluation of the rate of energy input to the system, the model reveals the ground motions that cause maximum rocking amplification. An experimental investigation of small-scale masonry arches subjected to past earthquake time histories is used to evaluate the analytical model and to explore arch rocking behaviour. The results demonstrate that rocking amplification can occur, but is highly sensitive to slight variations in the ground motion. Thus, the accuracy to which the arch response can be predicted is brought into perspective. The concept that the primary impulse of an expected ground motion is fundamentally important in predicting arch collapse is evaluated in light of the developed energy approach. Finally, a statistical method is proposed for predicting the probability of arch collapse during seismic loading.

Analytical method of predicating the instabilities of a micro arch-shaped beam under electrostatic loading

An arch-shaped beam with different configurations under electrostatic loading experiences either the direct pull-in instability or the snap-through first and then the pull-in instability. When the pull-in instability occurs, the system collides with the electrode and adheres to it, which usually causes the system failure. When the snap-through instability occurs, the system experiences a discontinuous displacement to flip over without colliding with the electrode. The snap-through instability is an ideal actuation mechanism because of the following reasons: (1) after snap-through the system regains the stability and capability of withstanding further loading; (2) the system flips back when the loading is reduced, i.e. the system can be used repetitively; and (3) when approaching snap-through instability the system effective stiffness reduces toward zero, which leads to a fast flipping-over response. To differentiate these two types of instability responses for an arch-shaped beam is vital for the actuator design. For an arch-shaped beam under electrostatic loading, the nonlinear terms of the mid-plane stretching and the electrostatic loading make the analytical solution extremely difficult if not impossible and the related numerical solution is rather complex. Using the one mode expansion approximation and the truncation of the higher-order terms of the Taylor series, we present an analytical solution here. However, the one mode approximation and the truncation error of the Taylor series can cause serious error in the solution. Therefore, an error-compensating mechanism is also proposed. The analytical results are compared with both the experimental data and the numerical multi-mode analysis. The analytical method presented here offers a simple yet efficient solution approach by retaining good accuracy to analyze the instability of an arch-shaped beam under electrostatic loading.

Geochemical anomalies of hydrothermal plume at EPR 13 degrees N

During the DY105-12, 14cruise (RN DAYANG YIHAO, November 2003) on East Pacific Rise (EPR) 12-13 degrees N, the submarine hydrothermal activity was investigated and the CTD hydrocast was carried out at EPR12 degrees 39 ' N - 12 degrees 54 ' N. From the temperature anomalies and the concentrations of magnesium, chlorine, bromine in seawater samples, we discover that magnesium depletes 9.3%-22.4%, chlorine and bromine enrich 10.3%-28.7% and 10.7%-29.0% respectively relative to normal seawater at the stations which have chemistry anomalies, moreover temperature and chemistry anomalies are at the same layer. The depletion of magnesium in the plume may be caused by a fluid lacking of magnesium which rises after the hydrothermal fluid reaches the equilibrium with ambient seawater, the enrichment of chlorine and bromine might be the result of inputting later brine which is generated by phase separation due to hydrothermal activity. In addition, the Br/CI ratio in the abnormal layers at the survey area is identical to that in seawater, which implies that halite dissolution (or precipitation) occurs neither when the fluid is vented nor when hydrothermal fluid entraining ambient seawater rises to form plume. From the abnormal instance at E55 station, it is very possible that there might exist a new hydrothermal vent site.

Safety of tetanus toxoid in pregnant women: A hospital-based case-control study of congenital anomalies

Reported are the results of the Latin American Collaborative Study of Congenital Malformations (ECLAMC), a hospital-based case-control study of 34 293 malformed and 34 477 matched nonmalformed newborn controls. No statistical differences were found between the malformed and control groups, exposed or not exposed to tetanus toroid.

Plasma acceleration above Martian magnetic anomalies

Grande, Manuel, et al., 'Plasma acceleration above Martian magnetic anomalies', Science (2006) 311(5763) pp.980-983 RAE2008

Diagnosing Network-Wide Traffic Anomalies

Anomalies are unusual and significant changes in a network's traffic levels, which can often involve multiple links. Diagnosing anomalies is critical for both network operators and end users. It is a difficult problem because one must extract and interpret anomalous patterns from large amounts of high-dimensional, noisy data. In this paper we propose a general method to diagnose anomalies. This method is based on a separation of the high-dimensional space occupied by a set of network traffic measurements into disjoint subspaces corresponding to normal and anomalous network conditions. We show that this separation can be performed effectively using Principal Component Analysis. Using only simple traffic measurements from links, we study volume anomalies and show that the method can: (1) accurately detect when a volume anomaly is occurring; (2) correctly identify the underlying origin-destination (OD) flow which is the source of the anomaly; and (3) accurately estimate the amount of traffic involved in the anomalous OD flow. We evaluate the method's ability to diagnose (i.e., detect, identify, and quantify) both existing and synthetically injected volume anomalies in real traffic from two backbone networks. Our method consistently diagnoses the largest volume anomalies, and does so with a very low false alarm rate.

Characterization of Network-Wide Anomalies in Traffic Flows

Detecting and understanding anomalies in IP networks is an open and ill-defined problem. Toward this end, we have recently proposed the subspace method for anomaly diagnosis. In this paper we present the first large-scale exploration of the power of the subspace method when applied to flow traffic. An important aspect of this approach is that it fuses information from flow measurements taken throughout a network. We apply the subspace method to three different types of sampled flow traffic in a large academic network: multivariate timeseries of byte counts, packet counts, and IP-flow counts. We show that each traffic type brings into focus a different set of anomalies via the subspace method. We illustrate and classify the set of anomalies detected. We find that almost all of the anomalies detected represent events of interest to network operators. Furthermore, the anomalies span a remarkably wide spectrum of event types, including denial of service attacks (single-source and distributed), flash crowds, port scanning, downstream traffic engineering, high-rate flows, worm propagation, and network outage.

Mining Anomalies Using Traffic Feature Distributions

The increasing practicality of large-scale flow capture makes it possible to conceive of traffic analysis methods that detect and identify a large and diverse set of anomalies. However the challenge of effectively analyzing this massive data source for anomaly diagnosis is as yet unmet. We argue that the distributions of packet features (IP addresses and ports) observed in flow traces reveals both the presence and the structure of a wide range of anomalies. Using entropy as a summarization tool, we show that the analysis of feature distributions leads to significant advances on two fronts: (1) it enables highly sensitive detection of a wide range of anomalies, augmenting detections by volume-based methods, and (2) it enables automatic classification of anomalies via unsupervised learning. We show that using feature distributions, anomalies naturally fall into distinct and meaningful clusters. These clusters can be used to automatically classify anomalies and to uncover new anomaly types. We validate our claims on data from two backbone networks (Abilene and Geant) and conclude that feature distributions show promise as a key element of a fairly general network anomaly diagnosis framework.

Applications of finite element computer modelling and thermal infrared remote sensing to the study of geothermal anomalies

Buried heat sources can be investigated by examining thermal infrared images and comparing these with the results of theoretical models which predict the thermal anomaly a given heat source may generate. Key factors influencing surface temperature include the geometry and temperature of the heat source, the surface meteorological environment, and the thermal conductivity and anisotropy of the rock. In general, a geothermal heat flux of greater than 2% of solar insolation is required to produce a detectable thermal anomaly in a thermal infrared image. A heat source of, for example, 2-300K greater than the average surface temperature must be a t depth shallower than 50m for the detection of the anomaly in a thermal infrared image, for typical terrestrial conditions. Atmospheric factors are of critical importance. While the mean atmospheric temperature has little significance, the convection is a dominant factor, and can act to swamp the thermal signature entirely. Given a steady state heat source that produces a detectable thermal anomaly, it is possible to loosely constrain the physical properties of the heat source and surrounding rock, using the surface thermal anomaly as a basis. The success of this technique is highly dependent on the degree to which the physical properties of the host rock are known. Important parameters include the surface thermal properties and thermal conductivity of the rock. Modelling of transient thermal situations was carried out, to assess the effect of time dependant thermal fluxes. One-dimensional finite element models can be readily and accurately applied to the investigation of diurnal heat flow, as with thermal inertia models. Diurnal thermal models of environments on Earth, the Moon and Mars were carried out using finite elements and found to be consistent with published measurements. The heat flow from an injection of hot lava into a near surface lava tube was considered. While this approach was useful for study, and long term monitoring in inhospitable areas, it was found to have little hazard warning utility, as the time taken for the thermal energy to propagate to the surface in dry rock (several months) in very long. The resolution of the thermal infrared imaging system is an important factor. Presently available satellite based systems such as Landsat (resolution of 120m) are inadequate for detailed study of geothermal anomalies. Airborne systems, such as TIMS (variable resolution of 3-6m) are much more useful for discriminating small buried heat sources. Planned improvements in the resolution of satellite based systems will broaden the potential for application of the techniques developed in this thesis. It is important to note, however, that adequate spatial resolution is a necessary but not sufficient condition for successful application of these techniques.

Policy impacts on Vietnam stock markets: a case of anomalies and disequilibria 2000-2006

Vietnam launched its first-ever stock market, named as Ho Chi Minh City Securities Trading Center (HSTC) on July 20, 2000. This is one of pioneering works on HSTC, which finds empirical evidences for the following: Anomalies of the HSTC stock returns through clusters of limit-hits, limit-hit sequences; Strong herd effect toward extreme positive returns of the market portfolio;The specification of ARMA-GARCH helps capture fairly well issues such as serial correlations and fat-tailed for the stabilized period. By using further information and policy dummy variables, it is justifiable that policy decisions on technicalities of trading can have influential impacts on the move of risk level, through conditional variance behaviors of HSTC stock returns. Policies on trading and disclosure practices have had profound impacts on Vietnam Stock Market (VSM). The over-using of policy tools can harm the market and investing mentality. Price limits become increasingly irrelevant and prevent the market from self-adjusting to equilibrium. These results on VSM have not been reported before in the literature on Vietnam’s financial markets. Given the policy implications, we suggest that the Vietnamese authorities re-think the use of price limit and give more freedom to market participants.

New empirical results on anomalies and herd behaviour: Vietnam stock market 2000-2004

info:eu-repo/semantics/published

Some new results on anomalies and herd behavior: Vietnam stock market

info:eu-repo/semantics/published