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In heat flux differential scanning calorimetry, a pair of identical crucibles, one empty as reference and the other filled with the sample, is heated in a furnace with a prescribed rate. The (empty) reference crucible heats faster, resulting in a temperature difference that is detected by thermocouples. Slow heating of the furnace results in weak and noisy signals; higher heating rates induce strong signals but lead to smearing if applied to materials undergoing a phase transition: The recorded peak signal is shifted toward higher temperatures. To determine the peak, the onset/endset temperatures, and the phase transition enthalpy, multiple heating rates are used to find a trade-off between noise and smearing. When plotting the melting peaks over temperature and heating rate, the visual similarity to the time evolution of a probability density under drift and diffusion catches the eye. Such a density evolution can be described by the Fokker–Planck equations. In this analogon, the de-smeared signal corresponds to the initial distribution. We propose a data-driven de-smearing approach, based on an extrapolation to a (hypothetical) zero heating rate signal. This zero rate signal is low-dimensionally parameterized and its parameters together with the drift and diffusion of the Fokker–Planck equation are fitted against the calorimetric measurements. The method is successfully tested on heat capacity data of a technical-grade high-density polyethylene (HDPE) using mid-range heating rates. The data are strongly affected by smearing, and the proposed de-smearing method FPEX 0 delivers reliable estimates of characteristic shape parameters of the phase transition peak effectively overcoming the problem of a deteriorating signal-to-noise ratio for heating rates approaching zero. [ABSTRACT FROM AUTHOR]

Individualized resistance training is necessary to optimize training results. A model-based optimization of loading schemes could provide valuable impulses for practitioners and complement the predominant manual program design by customizing the loading schemes to the trainee and the training goals. We compile a literature overview of model-based approaches used to simulate or optimize the response to single resistance training sessions or to long-term resistance training plans in terms of strength, power, muscle mass, or local muscular endurance by varying the loading scheme. To the best of our knowledge, contributions employing a predictive model to algorithmically optimize loading schemes for different training goals are nonexistent in the literature. Thus, we propose to set up optimal control problems as follows. For the underlying dynamics, we use a phenomenological model of the time course of maximum voluntary isometric contraction force. Then, we provide mathematical formulations of key performance indicators for loading schemes identified in sport science and use those as objective functionals or constraints. We then solve those optimal control problems using previously obtained parameter estimates for the elbow flexors. We discuss our choice of training goals, analyze the structure of the computed solutions, and give evidence of their real-life feasibility. The proposed optimization methodology is independent from the underlying model and can be transferred to more elaborate physiological models once suitable ones become available. [ABSTRACT FROM AUTHOR]

Purpose: Critical torque (CT) is an important fatigue threshold in exercise physiology and can be used to analyze, predict, or optimize performance. The objective of this work is to reduce the experimental effort when estimating CTs for sustained and intermittent isometric contractions using a model-based approach.Materials and Methods: We employ a phenomenological model of the time course of maximum voluntary isometric contraction (MVIC) torque and compute the highest sustainable torque output by solving an optimization problem. We then show that our results are consistent with the steady states obtained when simulating periodic maximum loading schemes. These simulations correspond to all-out tests, which are used to estimate CTs in practice. Based on these observations, the estimation of CTs can be formulated mathematically as a parameter estimation problem. To minimize the statistical uncertainty of the parameter estimates and consequently of the estimated CTs, we compute optimized testing sessions. This reduces the experimental effort even further.Results: We estimate CTs of the elbow flexors for sustained isometric contractions to be 28% of baseline MVIC torque and for intermittent isometric contractions consisting of a 3 s contraction followed by 2 s rest to be 41% of baseline MVIC torque. We show that a single optimized testing session is sufficient when using our approach.Conclusions: Our approach reduces the experimental effort considerably when estimating CTs for sustained and intermittent isometric contractions. [ABSTRACT FROM AUTHOR]

Objective: This aims to evaluate the efficiency of three different powered interproximal enamel reduction (IER) systems and to assess enamel roughness before and after polishing using different polishing times. Material and methods: Four metal strips of the G5 ProLign Set (swissdentacare, SDC, Grancia, Switzerland), four segmental discs of the ASR-Set 4594 and two sonic tips of the SonicLine Set (both Gebr. Basseler GmbH & Co. KG, Komet, Lemgo, Germany) were evaluated. Human extracted incisors served as the medium. Enamel reduction was determined in five intervals of 15 s each. Polishing was performed for 15 and 30 s using the manufacturers' recommended polishing systems. Enamel roughness (Ra) was quantitatively assessed by confocal laser scanning microscopy (CLSM). Results: Significant differences in terms of enamel reduction were found among the working ends of all tested systems. The time needed to remove 0.1, 0.2 and 0.3 mm of enamel was determined. Surface analysis showed significantly higher mean Ra values for nine out of ten working ends before polishing. This was still the case for five working ends after 15 s and for two after 30 s of polishing. Conclusion: The graining and the system used have a significant influence on enamel reduction. The time needed for polishing depends on the last working end used; a polishing time of 30 s is not always appropriate. Clinical relevance: Knowledge about the cutting efficiency of powered IER working ends might help the clinician to estimate better the amount of enamel reduction during the stripping process. [ABSTRACT FROM AUTHOR]

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