Unwanted memories of assault: what intrusion characteristics are associated with PTSD?

Intrusive memories are common in the immediate aftermath of traumatic events, but neither their presence or frequency are good predictors of the persistence of posttraumatic stress disorder (PTSD). Two studies of assault survivors, a cross-sectional study (N = 81) and a 6-month prospective longitudinal study (N = 73), explored whether characteristics of the intrusive memories improve the prediction. Intrusion characteristics were assessed with an Intrusion Interview and an Intrusion Provocation Task. The distress caused by the intrusions, their "here and now" quality, and their lack of a context predicted PTSD severity. The presence of intrusive memories only explained 9% of the variance of PTSD severity at 6 months after assault. Among survivors with intrusions, intrusion frequency only explained 8% of the variance of PTSD symptom severity at 6 months. Nowness, distress and lack of context explained an additional 43% of the variance. These intrusion characteristics also predicted PTSD severity at 6 months over and above what could be predicted from PTSD diagnostic status at initial assessment. Further predictors of PTSD severity were rumination about. the intrusive memories, and the ease and persistence with which intrusive memories could be triggered by photographs depicting assaults. The results have implications for the early identification of trauma survivors at risk of chronic PTSD. (c) 2004 Elsevier Ltd. All rights reserved.

Unsupervised genetic algorithm deployed for intrusion detection

This paper represents the first step in an on-going work for designing an unsupervised method based on genetic algorithm for intrusion detection. Its main role in a broader system is to notify of an unusual traffic and in that way provide the possibility of detecting unknown attacks. Most of the machine-learning techniques deployed for intrusion detection are supervised as these techniques are generally more accurate, but this implies the need of labeling the data for training and testing which is time-consuming and error-prone. Hence, our goal is to devise an anomaly detector which would be unsupervised, but at the same time robust and accurate. Genetic algorithms are robust and able to avoid getting stuck in local optima, unlike the rest of clustering techniques. The model is verified on KDD99 benchmark dataset, generating a solution competitive with the solutions of the state-of-the-art which demonstrates high possibilities of the proposed method.

Design and evaluation of intelligent classifier based intrusion detection system

We have discovered a novel approach of intrusion detection system using an intelligent data classifier based on a self organizing map (SOM). We have surveyed all other unsupervised intrusion detection methods, different alternative SOM based techniques and KDD winner IDS methods. This paper provides a robust designed and implemented intelligent data classifier technique based on a single large size (30x30) self organizing map (SOM) having the capability to detect all types of attacks given in the DARPA Archive 1999 the lowest false positive rate being 0.04 % and higher detection rate being 99.73% tested using full KDD data sets and 89.54% comparable detection rate and 0.18% lowest false positive rate tested using corrected data sets.

A refined sampling strategy for intra-tooth stable isotope analysis of mammalian enamel

Serial sampling and stable isotope analysis performed along the growth axis of vertebrate tooth enamel records differences attributed to seasonal variation in diet, climate or animal movement. Because several months are required to obtain mature enamel in large mammals, modifications in the isotopic composition of environmental parameters are not instantaneously recorded, and stable isotope analysis of tooth enamel returns a time-averaged signal attenuated in its amplitude relative to the input signal. For convenience, stable isotope profiles are usually determined on the side of the tooth where enamel is thickest. Here we investigate the possibility of improving the time resolution by targeting the side of the tooth where enamel is thinnest. Observation of developing third molars (M3) in sheep shows that the tooth growth rate is not constant but decreases exponentially, while the angle between the first layer of enamel deposited and the enamel–dentine junction increases as a tooth approaches its maximal length. We also noted differences in thickness and geometry of enamel growth between the mesial side (i.e., the side facing the M2) and the buccal side (i.e., the side facing the cheek) of the M3. Carbon and oxygen isotope variations were measured along the M3 teeth from eight sheep raised under controlled conditions. Intra-tooth variability was systematically larger along the mesial side and the difference in amplitude between the two sides was proportional to the time of exposure to the input signal. Although attenuated, the mesial side records variations in the environmental signal more faithfully than the buccal side. This approach can be adapted to other mammals whose teeth show lateral variation in enamel thickness and could potentially be used as an internal check for diagenesis.

Season of birth and sheep husbandry in late Roman and Medieval coastal Flanders: a pilot study using tooth enamel d18O analysis

From the early Roman period, there is archaeological evidence for the exploitation of the Flemish coastal plain (Belgium) for a range of activities, such as sheep herding on the then developing salt-marshes and salt-meadows for the production of wool. During the early Middle Ages, this culminated in the establishment of dedicated ‘sheep estates’. This phase of exploitation was followed by extensive drainage and land reclamation measures in the high Medieval period, transforming areas into grassland, suited for cattle breeding. As part of a larger project investigating the onset, intensification and final decline of sheep management in coastal Flanders in the historical period, this pilot study presents the results of sequential sampling and oxygen isotope analysis of a number of sheep teeth (M2, n = 8) from four late Roman and Medieval sites (dating from 4th to 15th century AD), in order to assess potential variations in season of birth between the different sites and through time. In comparison with published data from herds of known birth season, incremental enamel data from the Flemish sites are consistent with late winter/spring births, with the possibility of some instances of slightly earlier parturition. These findings suggest that manipulation of season of birth was not a feature of the sheep husbandry-based economies of early historic Flanders, further evidencing that wool production was the main purpose of contemporary sheep rearing in the region. Manipulation of season of birth is not likely to have afforded economic advantage in wool-centred economies, unlike in some milk- or meat-based regimes.