[Implant-supported bridges in the edentulous jaw. Clinical aspects of a simple treatment concept]

Clinical aspects of a simple treatment concept with fixed prostheses in the edentulous jaw are described. Fixed implant-supported reconstructions in the edentulous jaw require multiple implants, are technically complex, aesthetically demanding and metal-ceramic solutions are expensive. Specific surgical techniques to enhance the hard and soft tissue conditions become often necessary. Thus the bar-supported overdenture may be preferred, because problems with aesthetics and alveolar ridge deficiencies can be solved more easily and the number of implants is reduced. Both, the "All-on-Four" technique and the "Procera implant bridge" are simple type of fixed prostheses, comparable to overdentures or complete dentures with regard to design and technology. They present a cost-effective alternative, with predictable aesthetics and optimum passive fit.

A systematic review of the survival and complication rates of resin-bonded bridges after an observation period of at least 5 years

OBJECTIVES: The objectives of this systematic review were to assess the 5-year survival of resin-bonded bridges (RBBs) and to describe the incidence of technical and biological complications. METHODS: An electronic Medline search complemented by manual searching was conducted to identify prospective and retrospective cohort studies on RBBs with a mean follow-up time of at least 5 years. Patients had to have been examined clinically at the follow-up visit. Assessment of the identified studies and data extraction were performed independently by two reviewers. Failure and complication rates were analyzed using random-effects Poissons regression models to obtain summary estimates of 5-year proportions. RESULTS: The search provided 6110 titles and 214 abstracts. Full-text analysis was performed for 93 articles, resulting in 17 studies that met the inclusion criteria. Meta-analysis of these studies indicated an estimated survival of RBBs of 87.7% (95% confidence interval (CI): 81.6-91.9%) after 5 years. The most frequent complication was debonding (loss of retention), which occurred in 19.2% (95% CI: 13.8-26.3%) of RBBs over an observation period of 5 years. The annual debonding rate for RBBs placed on posterior teeth (5.03%) tended to be higher than that for anterior-placed RBBs (3.05%). This difference, however, did not reach statistical significance (P=0.157). Biological complications, like caries on abutments and RBBs lost due to periodontitis, occurred in 1.5% of abutments and 2.1% of RBBs, respectively. CONCLUSION: Despite the high survival rate of RBBs, technical complications like debonding are frequent. This in turn means that a substantial amount of extra chair time may be needed following the incorporation of RBBs. There is thus an urgent need for studies with a follow-up time of 10 years or more, to evaluate the long-term outcomes.

Suicide by jumping and accessibility of bridges: results from a national survey in Switzerland

Rates of suicide by jumping show large regional differences. Barriers on bridges may prevent suicides but also may lead to a substitution of jumping site or method. The aim of our study was to compare suicide data from regions with and without suicide bridges and to estimate the effects on method and site substitution if bridges were to be secured. In a national survey, suicide data for the years 1990 to 2003 were collected. Regions with high rates of bridge suicides were identified and compared with regions with low rates, and the analysis revealed that only about one third of the individuals would be expected to jump from buildings or other structures if no bridge was available. The results suggest no method substitution for women. For men, a trend of a substituting jumping by overdosing in regions without suicide bridges was found. We conclude that restricted access to suicide bridges will not automatically lead suicidal individuals to choose another jumping site or suicide method. The results support the notion that securing bridges may save lives.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

DC MICROGRID STABILIZATION THROUGH FUZZY CONTROL OF INTERLEAVED, HETEROGENEOUS STORAGE ELEMENTS

As microgrid power systems gain prevalence and renewable energy comprises greater and greater portions of distributed generation, energy storage becomes important to offset the higher variance of renewable energy sources and maximize their usefulness. One of the emerging techniques is to utilize a combination of lead-acid batteries and ultracapacitors to provide both short and long-term stabilization to microgrid systems. The different energy and power characteristics of batteries and ultracapacitors imply that they ought to be utilized in different ways. Traditional linear controls can use these energy storage systems to stabilize a power grid, but cannot effect more complex interactions. This research explores a fuzzy logic approach to microgrid stabilization. The ability of a fuzzy logic controller to regulate a dc bus in the presence of source and load fluctuations, in a manner comparable to traditional linear control systems, is explored and demonstrated. Furthermore, the expanded capabilities (such as storage balancing, self-protection, and battery optimization) of a fuzzy logic system over a traditional linear control system are shown. System simulation results are presented and validated through hardware-based experiments. These experiments confirm the capabilities of the fuzzy logic control system to regulate bus voltage, balance storage elements, optimize battery usage, and effect self-protection.

[Rehabilitation of a periodontally compromised dentition with implant-supported zirconia bridges. Case report]

Clinical aspects of reconstruction with fix prosthesis and dental implants in a patient with a history of periodontitis is shown. A successful stabilization and rehabilitation of the periodontally involved dentition can be achieved with tooth-worn crown and bridge reconstructions. From a functional and aesthetic point of view the result may not be satisfying due to mobility and overlength of the teeth and open approximal spaces. Today, dentist and patient have often to weigh if teeth shall be maintained or replaced by dental implants. Thereby, both must be aware of the fact that in complex cases long-term success and aesthetic outcome may be difficult to predict. An intense discussion with the patient on his expectations, invasive treatment, risks with regard to biologic and prosthetic aspects is mandatory and must be based on the best scientific evidence available. The present case report shows different considerations and describes a radical solution which meets the patient's needs and is based on modern CAD-CAM technology.

Fuzzy Multi-Objective Linear Programming and Simulation Approach to the Development of Valid and Realistic Master Production Schedule

Master production schedule (MPS) plays an important role in an integrated production planning system. It converts the strategic planning defined in a production plan into the tactical operation execution. The MPS is also known as a tool for top management to control over manufacture resources and becomes input of the downstream planning levels such as material requirement planning (MRP) and capacity requirement planning (CRP). Hence, inappropriate decision on the MPS development may lead to infeasible execution, which ultimately causes poor delivery performance. One must ensure that the proposed MPS is valid and realistic for implementation before it is released to real manufacturing system. In practice, where production environment is stochastic in nature, the development of MPS is no longer simple task. The varying processing time, random event such as machine failure is just some of the underlying causes of uncertainty that may be hardly addressed at planning stage so that in the end the valid and realistic MPS is tough to be realized. The MPS creation problem becomes even more sophisticated as decision makers try to consider multi-objectives; minimizing inventory, maximizing customer satisfaction, and maximizing resource utilization. This study attempts to propose a methodology for MPS creation which is able to deal with those obstacles. This approach takes into account uncertainty and makes trade off among conflicting multi-objectives at the same time. It incorporates fuzzy multi-objective linear programming (FMOLP) and discrete event simulation (DES) for MPS development.

Fuzzy Web Knowledge Aggregation, Representation, and Reasoning for Online Privacy and Reputation Management

A social Semantic Web empowers its users to have access to collective Web knowledge in a simple manner, and for that reason, controlling online privacy and reputation becomes increasingly important, and must be taken seriously. This chapter presents Fuzzy Cognitive Maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. With this in mind, a conceptual framework for Web knowledge aggregation, representation, and reasoning is introduced along with a use case, in which the importance of investigative searching for online privacy and reputation is highlighted. Thereby it is demonstrated how a user can establish a positive online presence.