Tooth loss and implant outcomes in patients refractory to treatment in a periodontal practice

Aim: The aim of this study was to investigate the factors associated with continued significant tooth loss due to periodontal reasons during maintenance following periodontal therapy in a specialist periodontal practice in Norway.
Material and Methods: A case-control design was used. Refractory cases were patients who lost multiple teeth during a maintenance period of 13.4 (range 8-19) years following definitive periodontal treatment in a specialist practice. Controls were age- and gender-matched maintenance patients from the same practice. Characteristics and treatment outcomes were assessed, and all teeth classified as being lost due to periodontal disease during follow-up were identified. The use of implants in refractory cases and any complications relating to such a treatment were recorded.
Results: Only 27 (2.2%) patients who received periodontal treatment between 1986 and 1998 in a specialist practice met the criteria for inclusion in the refractory to treatment group. Each refractory subject lost 10.4 (range 4-16) teeth, which represented 50% of the teeth present at baseline. The rate of tooth loss in the refractory group was 0.78 teeth per year, which was 35 times greater than that in the control group. Multivariate analysis indicated that being in the refractory group was predicted by heavy smoking (p=0.026), being stressed (p=0.016) or having a family history of periodontitis (p=0.002). Implants were placed in 14 of the refractory patients and nine (64%) of these lost at least one implant. In total, 17 (25%) of the implants placed in the refractory group were lost during the study period.
Conclusions: A small number of periodontal maintenance patients are refractive to treatment and go on to experience significant tooth loss. These subjects also have a high level of implant complications and failure. Heavy smoking, stress and a family history of periodontal disease were identified as factors associated with a refractory outcome.

Cross-validation of geo-electrical and hydrogeological models to evaluate seawater intrusion in coastal aquifers

The validation of variable-density flow models simulating seawater intrusion in coastal aquifers requires information about concentration distribution in groundwater. Electrical resistivity tomography (ERT) provides relevant data for this purpose. However, inverse modeling is not accurate because of the non-uniqueness of solutions. Such difficulties in evaluating seawater intrusion can be overcome by coupling geophysical data and groundwater modeling. First, the resistivity distribution obtained by inverse geo-electrical modeling is established. Second, a 3-D variable-density flow hydrogeological model is developed. Third, using Archie's Law, the electrical resistivity model deduced from salt concentration is compared to the formerly interpreted electrical model. Finally, aside from that usual comparison-validation, the theoretical geophysical response of concentrations simulated with the groundwater model can be compared to field-measured resistivity data. This constitutes a cross-validation of both the inverse geo-electrical model and the groundwater model.
[Comte, J.-C., and O. Banton (2007), Cross-validation of geo-electrical and hydrogeological models to evaluate seawater intrusion in coastal aquifers, Geophys. Res. Lett., 34, L10402, doi:10.1029/2007GL029981.]

Experimental investigation of negative pressure intrusion techniques of acetabular cementation in total hip arthroplasty

The main mode of failure of the acetabular component in total hip arthroplasty is aseptic loosening. Successive generations of cementation techniques have evolved to alleviate this problem.

Measuring inconsistency in network intrusion rules

In this preliminary case study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. Finally, we measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. We conclude that such measures are useful for the network intrusion domain assuming that incorporating domain knowledge for correlation of rules is feasible.

Measuring Inconsistency in a Network Intrusion Detection Rule Set Based on Snort

In this preliminary study, we investigate how inconsistency in a network intrusion detection rule set can be measured. To achieve this, we first examine the structure of these rules which are based on Snort and incorporate regular expression (Regex) pattern matching. We then identify primitive elements in these rules in order to translate the rules into their (equivalent) logical forms and to establish connections between them. Additional rules from background knowledge are also introduced to make the correlations among rules more explicit. We measure the degree of inconsistency in formulae of such a rule set (using the Scoring function, Shapley inconsistency values and Blame measure for prioritized knowledge) and compare the informativeness of these measures. Finally, we propose a new measure of inconsistency for prioritized knowledge which incorporates the normalized number of atoms in a language involved in inconsistency to provide a deeper inspection of inconsistent formulae. We conclude that such measures are useful for the network intrusion domain assuming that introducing expert knowledge for correlation of rules is feasible.

Local delivery of chlorhexidine using a tooth-bonded delivery system

Films containing 20% w/w chlorhexidine base (particle size 63-125 mu m) in poly(epsilon-caprolactone), MW 35 000-45 000, were prepared by solvent evaporation and sections attached to the mesio-lingual and mesio-buccal surfaces of the lower first molar in healthy volunteers. Saliva (

Unique Challenges in WiFi Intrusion Detection

The Intrusion Detection System (IDS) is a common means of protecting networked systems from attack or malicious misuse. The deployment of an IDS can take many different forms dependent on protocols, usage and cost. This is particularly true of Wireless Intrusion Detection Systems (WIDS) which have many detection challenges associated with data transmission through an open, shared medium, facilitated by fundamental changes at the Physical and MAC layers. WIDS need to be considered in more detail at these lower layers than their wired counterparts as they face unique challenges. The remainder of this chapter will investigate three of these challenges where WiFi deviates significantly from that of wired counterparts:

• Attacks Specific to WiFi Networks: Outlining the additional threats which WIDS must account for: Denial of Service, Encryption Bypass and AP Masquerading attacks.

• The Effect of Deployment Architecture on WIDS Performance: Demonstrating that the deployment environment of a network protected by a WIDS can influence the prioritisation of attacks.

• The Importance of Live Data in WiFi Research: Investigating the different choices for research data sources with an emphasis on encouraging live network data collection for future WiFi research.

Introduction to Wireless Intrusion Detection Systems

The IDS (Intrusion Detection System) is a common means of protecting networked systems from attack or malicious misuse. The development and rollout of an IDS can take many different forms in terms of equipment, protocols, connectivity, cost and automation. This is particularly true of WIDS (Wireless Intrusion Detection Systems) which have many more opportunities and challenges associated with data transmission through an open, shared medium.
The operation of a WIDS is a multistep process from origination of an attack through to human readable evaluation. Attention to the performance of each of the processes in the chain from attack detection to evaluation is imperative if an optimum solution is to be sought. At present, research focuses very much on each discrete aspect of a WIDS with little consideration to the operation of the whole system. Taking a holistic view of the technology shows the interconnectivity and inter-dependence between stages, leading to improvements and novel research areas for investigation.
This chapter will outline the general structure of Wireless Intrusion Detection Systems and briefly describe the functions of each development stage, categorised into the following 6 areas:
• Threat Identification,
• Architecture,
• Data Collection,
• Intrusion Detection,
• Alert Correlation,
• Evaluation.
These topics will be considered in broad terms designed for those new to the area. Focus will be placed on ensuring the readers are aware of the impact of choices made at early stages in WIDS development on future stages.