Computer methods for automating preoperative dental implant planning: implant positioning and size assignment

The paper presents computer-aided methods that allocate a dental implant and suggest its size, during the pre-operative planning stage, in conformance with introduced optimization criteria and established clinical requirements. Based on computed tomography data of the jaw and prosthesis anatomy, single tooth cases are planned for the best-suited implant insertion at a user-defined region. An optimum implantation axis line is produced and cylindrical implants of various candidate sizes are then automatically positioned, while their occlusal end is leveled to bone ridge, and evaluated. Radial safety margins are used for the assessment of the implant safety distance from neighboring anatomical structures and bone quantity and quality are estimated and taken into consideration. A case study demonstrates the concept and allows for its discussion.     

THE GAIA2JADE PROCESS FOR MULTI-AGENT SYSTEMS DEVELOPMENT

In this paper we present the Gaia2JADE process concerning how one can implement a multi-agent system with the JADE framework using the Gaia methodology for analysis and design purposes. This process is particularly dedicated to the conversion of Gaia models to JADE code. It is described using the Software Process Engineering Metamodel (SPEM) and extends the one proposed by FIPA for describing the Gaia modeling process. Thus, it proposes to potential MAS developers a process that covers the full software development lifecycle. This work is based on the experience we have acquired by applying this process for implementing a real-word multi-agent system conceived for providing e-services to mobile users. With this paper, we share this experience with future multi-agent systems (MAS) developers, who would like to follow this process, taking into account several technical issues that emerged during the implementation phase, helping them to easily model and implement their systems.     

Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures

Shape matching and indexing is important topic in its own right, and is a fundamental subroutine in most shape data mining algorithms. Given the ubiquity of shape, shape matching is an important problem with applications in domains as diverse as biometrics, industry, medicine, zoology and anthropology. The distance/similarity measure for used for shape matching must be invariant to many distortions, including scale, offset, noise, articulation, partial occlusion, etc. Most of these distortions are relatively easy to handle, either in the representation of the data or in the similarity measure used. However, rotation invariance is noted in the literature as being an especially difficult challenge. Current approaches typically try to achieve rotation invariance in the representation of the data, at the expense of discrimination ability, or in the distance measure, at the expense of efficiency. In this work, we show that we can take the slow but accurate approaches and dramatically speed them up. On real world problems our technique can take current approaches and make them four orders of magnitude faster without false dismissals. Moreover, our technique can be used with any of the dozens of existing shape representations and with all the most popular distance measures including Euclidean distance, dynamic time warping and Longest Common Subsequence. We further show that our indexing technique can be used to index star light curves, an important type of astronomical data, without modification. Reproducible Research Statement: All datasets and images used in this work are freely available at .     

Effect of Lactobacillus cultures on microbiological,chemical and odour changes during storage of rainbow trout fillets

The purpose of this study was to investigate the effect of applying two Lactobacillus protective cultures on microbiological, chemical and odour changes during storage of refrigerated vacuum‐packed rainbow trout (Oncorrynchus mykiss) fillets. Lactobacillus sakei CECT 4808 and Lb. curvatus CECT 904^T were inoculated individually or in combination into rainbow trout fillets. The samples were vacuum‐packed and stored at 4 ± 0.5 °C and were assessed during a 20‐day storage period for microbiological (Enterobacteriaceae, Pseudomonas spp., lactic acid bacteria (LAB), H₂S‐producing bacteria, yeasts and moulds) and chemical (pH, total volatile basic nitrogen, lipid oxidation) parameters and off‐odour. Samples inoculated with Lb. sakei and with both strains had significantly (P≤0.05) lower counts of all microbiological spoilage indicator organisms (Enterobacteriaceae, Pseudomonas spp., H₂S‐producing bacteria, yeasts and moulds) than those inoculated with Lb. curvatus or the controls. All chemical parameters examined and off‐odour scores were also significantly (P≤0.05) improved in the samples inoculated with Lb. sakei or with both strains compared with those inoculated with Lb. curvatus or the controls. Lb. sakei generally showed a better preservative effect (P≤0.05) than the combination of strains. Inoculation with Lb. sakei CECT 4808 could provide an additional hurdle to improve shelf‐life of refrigerated vacuum‐packaged trout fillets, as inoculation with this strain resulted in extension of shelf‐life by 5 days. Furthermore, this strain showed some antioxidative ability, which could retard lipid oxidation in fish. Copyright © 2006 Society of Chemical Industry     

Does the presence of desert dust modify the effect of PM10 on mortality in Athens, Greece?

Recent reports investigate whether windblown desert dust may exacerbate the short-term health effects associated with particulate pollution in urban centers. We have tested this hypothesis by using daily air pollution and mortality data for Athens, Greece during the period 2001-2006.We investigated the effects of exposure to particulate matter with aerodynamic diameter < 0 μg/m³ (PM₁₀) on total and cause specific mortality, during days with and without windblown desert dust, for all ages, stratified by age groups and by sex. We identified 141 dust days between 2001 and 2006. We used Poisson regression models with penalized splines to control for possible confounding by season, meteorology, day of the week and holiday effect.A 10 μg/m³ increase in PM₁₀ was associated with a 0.71% (95% confidence interval (CI): 0.42% to 0.99%) increase in all deaths. The effects for total and cause specific mortality were greater for those ≥ 75 years of age, while for total mortality higher effects were observed among females. The main effect of desert dust days and its interaction with PM₁₀ concentrations were significant in all cases except for respiratory mortality and cardiovascular mortality among those < 75 years. The negative interaction pointed towards lower particle effects on mortality during dust events.We found evidence of modification of the adverse health effects of PM₁₀ on mortality in Athens, Greece with desert dust events: the particle effects were significantly higher during non-desert dust days. Our analyses indicate that traffic related particles, which prevail on non-desert dust days, have more toxic effects than the ones originating from long-range transport, such as Sahara dust.     

Modular Representation of Agent Interaction Rules through Argumentation

Communication between agents needs to be flexible enough to encompass together a variety of different aspects such as, conformance to society protocols, private tactics of the individual agents, strategies that reflect different classes of agent types (or personal attitudes) and adaptability to the particular external circumstances at the time when the communication takes place. In this paper, we propose an argument-based framework for representing communication theories of agents that can take into account in a uniform way these different aspects. We show how this approach can be used to realize existing types of dialogue strategies and society protocols in a way that facilitates their modular development and extension to make them more flexible in handling different or special circumstances.     

Multi-dimensional confocal laser scanning microscopy image correlation for nanoparticle flow velocimetry

We present a new multi-dimensional confocal laser scanning microscopy (CLSM) image correlation for nanoparticle flow velocimetry that is robust to sources of decorrelating errors. Random and bias errors from nanoparticle flow measurements exacerbate with increased dimensionality in CLSM images, rendering measurements unusable. Our new algorithm tackles these measurement limitations in twofold. First, we model and correct for the bias errors introduced by the effects of the volumetric laser scanning image acquisition. Second, we developed a new spectral filter using a phase-quality masking technique that optimizes its size for the spectral content of CLSM images, without requiring a priori knowledge of displacement fields or flow tracer properties. We validated our algorithm using synthetic images and experimentally obtained 2D and 3D CLSM images of nanoparticle flow through a micro-channel. We show that our technique significantly outperforms the standard cross-correlation (SCC) in reducing both the random and bias errors and accelerated the convergence of ensemble correlation velocity measurements from CLSM images.