The aim of this paper is to study the value function of a time-continuous linear quadratic optimal control problem with input and state constraints. No coercive assumptions are made, which leads to optimal control problems whose trajectories are of bounded variation rather than merely absolutely continuous. Our approach is based on classical convex analysis, and we establish a Legendre-Fenchel type equality between the value function of the linear quadratic problem and its dual problem.

The amplitude of auditory steady-state responses (ASSRs) generated in the brainstem of rats exponentially decreases over the sequential averaging of EEG epochs. This behavior is partially due to the adaptation of the ASSR induced by the continuous and monotonous stimulation. In this study, we analyzed the potential clinical relevance of the ASSR adaptation. ASSR were elicited in eight anesthetized adult rats by 8-kHz tones, modulated in amplitude at 115 Hz. We called independent epochs to those EEG epochs acquired with sufficiently long inter-stimulus interval, so the ASSR contained in any given epoch is not affected by the previous stimulation. We tested whether the detection of ASSRs is improved when the response is computed by averaging independent EEG epochs, containing only unadapted auditory responses. The improvements in the ASSR detection obtained with standard, weighted and sorted averaging were compared. In the absence of artifacts, when the ASSR was elicited by continuous acoustic stimulation, the computation of the ASSR amplitude relied upon the averaging method. While the adaptive behavior of the ASSR was still evident after the weighting of epochs, the sorted averaging resulted in under-estimations of the ASSR amplitude. In the absence of artifacts, the ASSR amplitudes computed by averaging independent epochs did not depend on the averaging procedure. Averaging independent epochs resulted in higher ASSR amplitudes and halved the number of EEG epochs needed to be acquired to achieve the maximum detection rate of the ASSR. Acquisition protocols based on averaging independent EEG epochs, in combination with appropriate averaging methods for artifact reduction might contribute to develop more accurate hearing assessments based on ASSRs.

Previous vocal fold modeling studies have generally focused on generating detailed data regarding a narrow subset of possible model configurations. These studies can be interpreted to be the investigation of a single subject under one or more vocal conditions. In this study, a broad population-based sensitivity analysis is employed to examine the behavior of a virtual population of subjects and to identify trends between virtual individuals as opposed to investigating a single subject or model instance. Four different sensitivity analysis techniques were used in accomplishing this task. Influential relationships between model input parameters and model outputs were identified, and an exploration of the model's parameter space was conducted. Results indicate that the behavior of the selected two-mass model is largely dominated by complex interactions, and that few input-output pairs have a consistent effect on the model. Results from the analysis can be used to increase the efficiency of optimization routines of reduced-order models used to investigate voice abnormalities. Results also demonstrate the types of challenges and difficulties to be expected when applying sensitivity analyses to more complex vocal fold models. Such challenges are discussed and recommendations are made for future studies.

Abstract The combination of maintenance planning and key performance indicators are relevant to create a more holistic scenario of the mining activities. On the one hand, reliability and maintainability are system characteristics suitable for planning maintenance strategies. On the other hand, key performance indicators are suitable to analyze cost and resource consumption information about mining equipment. Nevertheless in practice, both approaches are modeled separately and frequently by different team-works of a mining company. With this in mind, a computer-aided application was conceived to drive with better efficacy the operational and maintenance strategy in a complex process where the equipment is in continuous movement such as the transportation process in an open-mine pit.

In high-voltage (HV) insulation, electrical trees are an important degradation phenomenon strongly linked to partial discharge (PD) activity. Their initiation and development have attracted the attention of the research community and better understanding and characterization of the phenomenon are needed. They are very damaging and develop through the insulation material forming a discharge conduction path. Therefore, it is important to adequately measure and characterize tree growth before it can lead to complete failure of the system. In this paper, the Gaussian mixture model (GMM) has been applied to cluster and classify the different growth stages of electrical trees in epoxy resin insulation. First, tree growth experiments were conducted, and PD data captured from the initial to breakdown stage of the tree growth in epoxy resin insulation. Second, the GMM was applied to categorize the different electrical tree stages into clusters. The results show that PD dynamics vary with different stress voltages and tree growth stages. The electrical tree patterns with shorter breakdown times had identical clusters throughout the degradation stages. The breakdown time can be a key factor in determining the degradation levels of PD patterns emanating from trees in epoxy resin. This is important in order to determine the severity of electrical treeing degradation, and, therefore, to perform efficient asset management. The novelty of the work presented in this paper is that for the first time the GMM has been applied for electrical tree growth classification and the optimal values for the hyperparameters, i.e., the number of clusters and the appropriate covariance structure, have been determined for the different electrical tree clusters.

The aim of this study was to prepare a novel targeting drug delivery system for 2-Methoxyestradiol (2ME) in order to improve the clinical application of this antitumor drug. It is based in nanoparticles (NPs) of titanium dioxide (TiO2) coated with polyethylene glycol (PEG) and loaded with 2ME. A complete IR and Raman characterization have been made to confirm the formation of TiO2–PEG–2ME composite. Vibrational modes have been assigned for TiO2, PEG, and 2ME and functionalized TiO2–PEG and TiO2–PEG–2ME. The observed variation in peak position of FTIR and Raman of each for these composites has been elucidated in terms of intermolecular interactions between PEG–2ME and TiO2, obtaining step-by-step the modification processes that were attributed to the conjugation of PEG and 2ME to TiO2 NPs. Modifying TiO2 NPs with PEG loaded with the 2ME drug revealed that the titanium dioxide nanocarrier possesses an effective adsorption capability, and we discuss their potential application as a system of drug delivery.

A great variety of powder metallurgy techniques can produce biomimetic porous titanium structures with similar mechanical properties to host bone tissue. In this work, loose sintering and space holder techniques, two frequently used metallurgical techniques, are compared to evaluate the influences of porosity (content, size, morphology and wall roughness), mechanical properties (stiffness and yield strength) and in-vitro cellular responses (adhesion and proliferation of myoblasts and osteoblasts). These comparisons are made to achieve the best balance between biomechanical and bifunctional behavior of a partial porous implant for cortical bone replacement. Cell adhesion (filopodia presence) and spreading were promoted on both porous surfaces and fully dense substrates (non-porous control surfaces). Porous scaffold samples designed using 50 vol.% NaCl space holder technique had an improved bioactive response over those obtained with the loose sintering technique due to higher roughness and scaffold pore diameter. However, the presence of large and heterogeneous pores compromises the mechanical reliability of the implant. Considering both scenarios, the substrates obtained with 40 vol.% NH4HCO3 and pore size ranges between 100 and 200 μm provide a balanced optimization of size and strength to promote in-vitro osseointegration.

This article presents a model of performance analysis for a truck fleet system in an openpit mine, considering special characteristics of haul fleets. In these systems, the expected availability of each piece of equipment and its operating capacity are the fundamental variables to construct a global fleet performance function. Our analytical algorithm considers heterogeneous fleets with known individual characteristics of transport capacity and failure and repair behavior. The results converge to a new indicator denominated “Equivalent Availability” (EA), which arises from the need to evaluate the capacity of the truck fleet to operate at a lower payload than required using different combinations of equipment to achieve an availability goal. EA is a key indicator to determine the productive capacity of a process, and for selecting equipment and their combinations to achieve production objectives. To exemplify the potentialities of the EA, a case study is implemented in a Chilean copper truck fleet mining process.