Peri-implant soft tissue conditioning with provisional restorations in the esthetic zone: the dynamic compression technique

An optimal esthetic implant restoration is a combination of a visually pleasing prosthesis and surrounding peri-implant soft tissue architecture. This article introduces a clinical method, the dynamic compression technique, of conditioning soft tissues around bone-level implants with provisional restorations in the esthetic zone. The technique has several goals: to establish an adequate emergence profile; to recreate a balanced mucosa course and level in harmony with the gingiva of the adjacent teeth, including papilla height/width, localization of the mucosal zenith and the tissue profile's triangular shape; as well as to establish an accurate proximal contact area with the adjacent tooth/implant crown.

Distance-based kriging relying on proxy simulations for inverse conditioning

Let us consider a large set of candidate parameter fields, such as hydraulic conductivity maps, on which we can run an accurate forward flow and transport simulation. We address the issue of rapidly identifying a subset of candidates whose response best match a reference response curve. In order to keep the number of calls to the accurate flow simulator computationally tractable, a recent distance-based approach relying on fast proxy simulations is revisited, and turned into a non-stationary kriging method where the covariance kernel is obtained by combining a classical kernel with the proxy. Once the accurate simulator has been run for an initial subset of parameter fields and a kriging metamodel has been inferred, the predictive distributions of misfits for the remaining parameter fields can be used as a guide to select candidate parameter fields in a sequential way. The proposed algorithm, Proxy-based Kriging for Sequential Inversion (ProKSI), relies on a variant of the Expected Improvement, a popular criterion for kriging-based global optimization. A statistical benchmark of ProKSI’s performances illustrates the efficiency and the robustness of the approach when using different kinds of proxies.

From transient to steady state deformation and grain size: A thermodynamic approach using elasto-visco-plastic numerical modeling

Numerical simulation experiments give insight into the evolving energy partitioning during high-strain torsion experiments of calcite. Our numerical experiments are designed to derive a generic macroscopic grain size sensitive flow law capable of describing the full evolution from the transient regime to steady state. The transient regime is crucial for understanding the importance of micro structural processes that may lead to strain localization phenomena in deforming materials. This is particularly important in geological and geodynamic applications where the phenomenon of strain localization happens outside the time frame that can be observed under controlled laboratory conditions. Ourmethod is based on an extension of the paleowattmeter approach to the transient regime. We add an empirical hardening law using the Ramberg-Osgood approximation and assess the experiments by an evolution test function of stored over dissipated energy (lambda factor). Parameter studies of, strain hardening, dislocation creep parameter, strain rates, temperature, and lambda factor as well asmesh sensitivity are presented to explore the sensitivity of the newly derived transient/steady state flow law. Our analysis can be seen as one of the first steps in a hybrid computational-laboratory-field modeling workflow. The analysis could be improved through independent verifications by thermographic analysis in physical laboratory experiments to independently assess lambda factor evolution under laboratory conditions.

Extending in vitro conditioning in Aplysia to analyze operant and classical processes in the same preparation.

Operant and classical conditioning are major processes shaping behavioral responses in all animals. Although the understanding of the mechanisms of classical conditioning has expanded significantly, the understanding of the mechanisms of operant conditioning is more limited. Recent developments in Aplysia are helping to narrow the gap in the level of understanding between operant and classical conditioning, and have raised the possibility of studying the neuronal processes underlying the interaction of operant and classical components in a relatively complex learning task. In the present study, we describe a first step toward realizing this goal, by developing a single in vitro preparation in which both operant and classical conditioning can be studied concurrently. The new paradigm reproduced previously published results, even under more conservative and homogenous selection criteria and tonic stimulation regime. Moreover, the observed learning was resistant to delay, shortening, and signaling of reinforcement.

In vitro analog of classical conditioning of feeding behavior in aplysia.

The feeding behavior of Aplysia californica can be classically conditioned using tactile stimulation of the lips as a conditioned stimulus (CS) and food as an unconditioned stimulus (US). Moreover, several neural correlates of classical conditioning have been identified. The present study extended previous work by developing an in vitro analog of classical conditioning and by investigating pairing-specific changes in neuronal and synaptic properties. The preparation consisted of the isolated cerebral and buccal ganglia. Electrical stimulation of a lip nerve (AT4) and a branch of the esophageal nerve (En2) served as the CS and US, respectively. Three protocols were used: paired, unpaired, and US alone. Only the paired protocol produced a significant increase in CS-evoked fictive feeding. At the cellular level, classical conditioning enhanced the magnitude of the CS-evoked synaptic input to pattern-initiating neuron B31/32. In addition, paired training enhanced both the magnitude of the CS-evoked synaptic input and the CS-evoked spike activity in command-like neuron CBI-2. The in vitro analog of classical conditioning reproduced all of the cellular changes that previously were identified following behavioral conditioning and has led to the identification of several new learning-related neural changes. In addition, the pairing-specific enhancement of the CS response in CBI-2 indicates that some aspects of associative plasticity may occur at the level of the cerebral sensory neurons.

Combined effect of heterogeneity, anisotropy and saturation on steady state flow and transport: Structure recognition and numerical simulation

1 Natural soil profiles may be interpreted as an arrangement of parts which are characterized by properties like hydraulic conductivity and water retention function. These parts form a complicated structure. Characterizing the soil structure is fundamental in subsurface hydrology because it has a crucial influence on flow and transport and defines the patterns of many ecological processes. We applied an image analysis method for recognition and classification of visual soil attributes in order to model flow and transport through a man-made soil profile. Modeled and measured saturation-dependent effective parameters were compared. We found that characterizing and describing conductivity patterns in soils with sharp conductivity contrasts is feasible. Differently, solving flow and transport on the basis of these conductivity maps is difficult and, in general, requires special care for representation of small-scale processes.