The effects of food essential oils on cardiovascular diseases: A review

Essential oils (EO) are complex secondary metabolites, which are produced by aromatic plants and identified by their powerful odors. Present studies on EO and their isolated ingredients have drawn the attention of researchers to screen these natural products and evaluate their effect on the cardiovascular system. Some EO, and their active ingredients, have been reported to improve the cardiovascular system significantly by affecting vaso-relaxation, and decreasing the heart rate and exert a hypotension activity. Several mechanisms have been proposed for the role of EO and their main active components in promoting the health of the cardiovascular system. The objective of this review is to highlight the current state of knowledge on the functional role of EO extracted from plants for reducing the risk of cardiovascular diseases and their mechanisms of action. Research on EO has the potential to identify new bioactive compounds and formulate new functional products for the treatment of cardiovascular diseases such as arterial hypertension, angina pectoris, heart failure, and myocardial infarction.     

OSPM: A design methodology for open strategic planning

This study employs a design science perspective to propose a methodology for open strategic planning (OSP). Habermas’ discourse theory and Bryson’s strategy change cycle are used as informing kernel theories. A methodology is proposed to satisfy the requirements retrieved from the kernel theories. The proposed methodology contains modules for a planning system and a planning process. Design principles are explained through a blueprint of the system and process. The proposed methodology is applied and evaluated in two cases. Contributions to the literature involve extending the literature on OSP to an applicable methodology with guidelines on how to implement open strategy.     

Dynamic modeling and CPG-based trajectory generation for a masticatory rehab robot

Human mastication is a complex and rhythmic biomechanical process which is regulated by a brain stem central pattern generator (CPG). Masticatory patterns, frequency and amplitude of mastication are different from person to person and significantly depend on food properties. The central nervous system controls the activity of muscles to produce smooth transitions between different movements. Therefore, to rehab human mandibular system, there is a real need to use the concept of CPG for development of a new methodology in jaw exercises and to help jaw movements recovery. This paper proposes a novel method for real-time trajectory generation of a mastication rehab robot. The proposed method combines several methods and concepts including kinematics, dynamics, trajectory generation and CPG. The purpose of this article is to provide a methodology to enable physiotherapists to perform the human jaw rehabilitation. In this paper, the robotic setup includes two Gough–Stewart platforms. The first platform is used as the rehab robot, while the second one is used to model the human jaw system. Once the modeling is completed, the second robot will be replaced by an actual patient for the selected physiotherapy. Gibbs–Appell’s formulation is used to obtain the dynamics equations of the rehab robot. Then, a method based on the Fourier series is employed to tune parameters of the CPG. It is shown that changes in leg lengths, due to the online changes of the mastication parameters, occur in a smooth and continuous manner. The key feature of the proposed method, when applied to human mastication, is its ability to adapt to the environment and change the chewing pattern in real-time parameters, such as amplitudes as well as jaw movements velocity during mastication.     

Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

Human Cellular Retinol Binding Protein II Forms a Domain-Swapped Trimer Representing a Novel Fold and a New Template for Protein Engineering

Domain-swapping is a mechanism for evolving new protein structure from extant scaffolds, and has been an efficient protein-engineering strategy for tailoring functional diversity. However, domain swapping can only be exploited if it can be controlled, especially in cases where various folds can coexist. Herein, we describe the structure of a domain-swapped trimer of the iLBP family member hCRBPII, and suggest a mechanism for domain-swapped trimerization. It is further shown that domain-swapped trimerization can be favored by strategic installation of a disulfide bond, thus demonstrating a strategy for fold control. We further show the domain-swapped trimer to be a useful protein design template by installing a high-affinity metal binding site through the introduction of a single mutation, taking advantage of its threefold symmetry. Together, these studies show how nature can promote oligomerization, stabilize a specific oligomer, and generate new function with minimal changes to the protein sequence.     

Corrosion behavior of porous magnesium coated by plasma electrolytic oxidation in simulated body fluid

Porous magnesium has a great potential to be used as degradable bone scaffolds. In this study, porous magnesium with 35% percolating porosity has been successfully fabricated through powder metallurgy route utilizing space holders. The intrinsic mechanical properties of the porous magnesium were measured by nanoindentation testing and analyzed with the Oliver–Pharr method. Afterward, a ceramic coating on the surface of the porous magnesium was performed by plasma electrolytic oxidation (PEO) treatment in a silicate‐based solution. The morphology and composition results of the PEO coatings indicated that it is possible to apply a homogenous and adhesive ceramic coating layer on all free surface of the porous magnesium through PEO method. The protective performance of the PEO coatings was evaluated using by potentiodynamic polarization and electrochemical impedance spectroscopy tests in simulated body fluid. The results revealed the PEO coating significantly improves biocorrosion resistance of the porous magnesium. Therefore, it can be used as an effective method to control the degradation rate of porous magnesium implants in the human body.     

Passivity‐based adaptive control of a 2‐DOF serial robot manipulator with temperature dependent joint frictions

Mechanical systems are always suffering from the effects of temperature dependent friction forces where the system is operated in a wide range of temperature. Temperature and its variation play an important role in friction force in mechanical systems. If it is not compensated, it will tend to unwanted consequences, including steady‐state errors, limit cycling, and hunting. Therefore, it is necessary to take the temperature effects into account. This has been a strong motivation for the researchers to work on temperature effects on joint friction. In this paper, an adaptive compensation (control) scheme is proposed and applied to a 2‐degree‐of‐freedom serial robot manipulator by taking the temperature effects into account on the joints friction. In the proposed control scheme, the temperature is not required to be sensed. In this paper, joint friction is described by LuGre dynamic model with temperature dependent parameters. These parameters are described by some functions with unknown temperature dependent terms. According to the mathematical and practical concepts, the temperature dependent friction is decomposed into a viscous term and a disturbance term. An adaptive controller is designed to compensate the friction effect and it is shown that the proposed controller relaxes the condition for a priori knowledge about the environment characteristics, including the upper and lower bounds of the environment temperature and the parameters of the functions, describing the temperature dependent joint frictions. The stability and convergence of the joint position and velocity are proved in the sense of Lyapunov and then the proposed method is confirmed by the simulations.