Metformin Use and Cognitive Function in Older Adults With Type 2 Diabetes Following a Mediterranean Diet Intervention

Background and Purpose: Both adherence to the Mediterranean diet (MedDiet) and the use of metformin could benefit the cognitive performance of individuals with type 2 diabetes, but evidence is still controversial. We examined the association between metformin use and cognition in older adults with type 2 diabetes following a MedDiet intervention.Methods: Prospective cohort study framed in the PREDIMED-Plus-Cognition sub-study. The PREDIMED-Plus clinical trial aims to compare the cardiovascular effect of two MedDiet interventions, with and without energy restriction, in individuals with overweight/obesity and metabolic syndrome. The present sub-study included 487 cognitively normal subjects (50.5% women, mean ± SD age of 65.2 ± 4.7 years), 30.4% of them (N = 148) with type 2 diabetes. A comprehensive battery of neurocognitive tests was administered at baseline and after 1 and 3 years. Individuals with type 2 diabetes that exhibited a good glycemic control trajectory, either using or not using metformin, were compared to one another and to individuals without diabetes using mixed-effects models with inverse probability of treatment weights.Results: Most subjects with type 2 diabetes (83.1%) presented a good and stable glycemic control trajectory. Before engaging in the MedDiet intervention, subjects using metformin scored higher in executive functions (Cohen's d = 0.51), memory (Cohen's d = 0.38) and global cognition (Cohen's d = 0.48) than those not using metformin. However, these differences were not sustained during the 3 years of follow-up, as individuals not using metformin experienced greater improvements in memory (β = 0.38 vs. β = 0.10, P = 0.036), executive functions (β = 0.36 vs. β = 0.02, P = 0.005) and global cognition (β = 0.29 vs. β = −0.02, P = 0.001) that combined with a higher MedDiet adherence (12.6 vs. 11.5 points, P = 0.031). Finally, subjects without diabetes presented greater improvements in memory than subjects with diabetes irrespective of their exposure to metformin (β = 0.55 vs. β = 0.10, P < 0.001). However, subjects with diabetes not using metformin, compared to subjects without diabetes, presented greater improvements in executive functions (β = 0.33 vs. β = 0.08, P = 0.032) and displayed a higher MedDiet adherence (12.6 points vs. 11.6 points, P = 0.046).Conclusions: Although both metformin and MedDiet interventions are good candidates for future cognitive decline preventive studies, a higher adherence to the MedDiet could even outweigh the potential neuroprotective effects of metformin in subjects with diabetes.

Research on Taproots Identification Technology in Panax notoginseng Quality Intelligent Management System

In the Panax notoginseng quality intelligent management system, the big roots and fibrous roots cannot be cut automatically because the machine cannot distinguish the taproot, big roots, and fibrous roots of Panax notoginseng, resulting in the automatic cutting mechanism unable to obtain the control trajectory coordinate reference of the tool feed. To solve this problem, this paper proposes a visual optimal network model detection method, which uses the image detection method of marking anchor frames to improve the detection accuracy. A variety of deep learning network models are modified by the TensorFlow framework, and the best training model is optimized by comparing the results of training, testing, and verification data. This model is used to automatically identify the taproots and provide the control trajectory coordinate reference for the actuator that cuts big roots and fibrous roots automatically. The experimental results show that the optimal network model studied in this paper is effective and accurate in identifying the taproots of Panax notoginseng.

Solar Field Output Temperature Optimization Using a MILP Algorithm and a 0D Model in the Case of a Hybrid Concentrated Solar Thermal Power Plant for SHIP Applications

Using solar power for industrial process heat is an increasing trend to fight against climate change thanks to renewable heat. Process heat demand and solar flux can both present intermittency issues in industrial systems, therefore solar systems with storage introduce a degree of freedom on which optimization, on a mathematical basis, can be performed. As the efficiency of solar thermal receivers varies as a function of temperature and solar flux, it seems natural to consider an optimization on the operating temperature of the solar field. In this paper, a Mixed Integer Linear Programming (MILP) algorithm is developed to optimize the operating temperature in a system consisting of a concentrated solar thermal field with storage, hybridized with a boiler. The MILP algorithm optimizes the control trajectory on a time horizon of 48 h in order to minimize boiler use. Objective function corresponds to the boiler use, for completion of the heat from the solar field, whereas the linear constraints are a simplified representation of the system. The solar field mass flow rate is the optimization variable which is directly linked to the outlet temperature of the solar field. The control trajectory consists of the solar field mass flow rate and outlet temperature, along with the auxiliary mass flow rate going directly to the boiler. The control trajectory is then injected in a 0D model of the plant which performs more detailed calculations. For the purpose of the study, a Linear Fresnel system is investigated, with generic heat demand curves and constant temperature demand. The value of the developed algorithm is compared with two other control approaches: one operating at the nominal solar field output temperature, and the other one operating at the actual demand mass flow rate. Finally, a case study and a sensitivity analysis are presented. The MILP’s control shows to be more performant, up to a relative increase of the annual solar fraction of 4% at 350 °C process temperature. Novelty of this work resides in the MILP optimization of temperature levels presenting high non-linearities, applied to a solar thermal system with storage for process heat applications.

NONLINEAR ROLL CONTROL ALGORITHM FOR THE DERIVATION OF AN AIRCRAFT LEAVING ON A PRESCRIBED WAY LINE

The conclusion of the aircraft to a given track line is considered. The possibility of using for this purpose a nonlinear roll control algorithm with functions of functions is analyzed. The results of modeling of the guidance process are given, showing that the investigated nonlinear algorithm ensures the withdrawal of an aircraft from any points in space on a given path for any initial course in a calm atmosphere and in the presence of wind. Key words: line of a given path, roll control, trajectory control algorithm, motion control of the center of mass, lateral deviation.

On mixed-integer optimal control with constrained total variation of the integer control

The combinatorial integral approximation (CIA) decomposition suggests solving mixed-integer optimal control problems by solving one continuous nonlinear control problem and one mixed-integer linear program (MILP). Unrealistic frequent switching can be avoided by adding a constraint on the total variation to the MILP. Within this work, we present a fast heuristic way to solve this CIA problem and investigate in which situations optimality of the constructed feasible solution is guaranteed. In the second part of this article, we show tight bounds on the integrality gap between a relaxed continuous control trajectory and an integer feasible one in the case of two controls. Finally, we present numerical experiments to highlight the proposed algorithm’s advantages in terms of run time and solution quality.

Research on the Motion Control Trajectory and Structure Design of a Lower Limb Standing Rehabilitation Training Device

Aiming at the problem of standing rehabilitation of lower limb motor dysfunction patient. Firstly, the standing movement process of human body is analyzed. Secondly, the exercise trajectory test and pressure distribution measurement test of healthy human body are studied. Thirdly, the structure of the lower limb standing rehabilitation training device is designed according to the collected joint trajectory. Finally, the movement control trajectory simulation of the lower limb standing rehabilitation training device is carried out according to the collected regional pressure. The simulation results of virtual prototype coincide with the test trajectory, which shows that the structure of the designed lower limb standing rehabilitation training device is reasonable, and the hybrid control method of force and position can realize the standing rehabilitation training for lower limb motor dysfunction patient in the light of the set exercise trajectory.

Review of Conflict Resolution Methods for Manned and Unmanned Aviation

Current investigations into urban aerial mobility, as well as the continuing growth of global air transportation, have renewed interest in Conflict Detection and Resolution (CD&R) methods. With the new applications of drones, and the implications of a profoundly different urban airspace, new demands are placed on such algorithms, further spurring new research. This paper presents a review of current CR methods for both manned and unmanned aviation. It presents a taxonomy that categorises algorithms in terms of their approach to avoidance planning, surveillance, control, trajectory propagation, predictability assumption, resolution manoeuvre, multi-actor conflict resolution, considered obstacle types, optimization, and method category. More than a hundred CR methods were considered, showing how most work on a tactical, distributed framework. To enable a reliable comparison between methods, this paper argues that an open and ideally common simulation platform, common test scenarios, and common metrics are required. This paper presents an overview of four CR algorithms, each representing a commonly used CR algorithm category. Both manned and unmanned scenarios were tested, through fast-time simulations on an open-source airspace simulation platform.

Level Control of Quadruple Tank Process using Laguerre Functions based Model Predictive Control Algorithm

This paper aims to present a model predictive controller based on discrete state-space modeling, where the future control trajectory is approximated by a set of discrete-time Laguerre functions instead of shift forward operators. The benefit of using these orthonormal Laguerre functions is that they have fewer parameters to adjust in the optimization problem and the computation load is significantly lower than the standard predictive control. The effectiveness of this controller is illustrated through the quadruple tank process, which is a highly interacted, multivariable and constrained system.