Development of a Control Board for Walking Mechatronic Systems: Principle of Operation and Implementation

Abstract Objectives Opioid analgesics are essential in clinical practice, but their excessive use is associated with addiction risk. Increases in opioid prescription rates have fuelled an epidemic of opioid addiction in the USA, making statistics on medical opioid use a critical warning signal. A dramatic 150% increase in Swedish opioid access 2001–2013 was recently reported based on data from the International Narcotics Control Board (INCB; Berterame et al. 2016) in conflict with other studies of opioid use in the Nordic countries. This article aims to analyse to what degree published INCB statistics on opioids in Scandinavia (Denmark, Norway and Sweden) reflect actual medical use and study the methodological reasons for putative discrepancies. Methods Data on aggregated total national sales of opioids for the whole population, including hospitals, were collected from the Swedish e-Health Authority. Total sales data for Denmark and drugs dispensed at pharmacies in Norway are publicly available through the relevant authorities’ websites. Results INCB opioid statistics during the period 2001–2013 were markedly inconsistent with sales data from Scandinavia, calling the reliability of INCB data into question. INCB-data were flawed by (a) over-representing the volume of fentanyl, (b) under-reporting of codeine, and (c) by not including tramadol. Conclusions Opioid availability, as expressed by INCB statistics, does not reflect medical opioid use. It is crucial to underline that INCB statistics are based on the manual compilation of national production, import and export data from manufacturers and drug companies. This is not the same amount that is prescribed and consumed within the health care system. Moreover, there are methodological problems in the INCB reports, in particular concerning fentanyl, codeine and tramadol. We suggest that INCB should carefully review the quality of their data on medical opioids.

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Feasibility and preliminary data for a State-wide South Carolina Lupus Registry

Lupus ◽

10.1177/09612033211014591 ◽

2021 ◽

pp. 096120332110145

Author(s):

Brittany L Smalls ◽

Trevor D Faith ◽

Hetlena Johnson ◽

Edith M Williams

Keyword(s):

South Carolina ◽

Lupus Erythematosus ◽

Preliminary Data ◽

Autoimmune Disorder ◽

Medical Community ◽

Small Samples ◽

Control Board ◽

Prospective Survey ◽

And Control ◽

The Impact

Background Systemic lupus erythematosus (SLE) or lupus is an autoimmune disorder whose cause and reason for disproportionate impact on minorities remains enigmatic. Furthermore, statistics describing lupus incidence and prevalence are outdated and often based on small samples. To begin to address this disparity this report describes preliminary data to be utilized in the development of a state-wide lupus registry in South Carolina. Methods A prospective survey and retrospective data from the South Carolina Budget and Control Board Office of Research & Statistics were used to capture data pertaining to knowledge of lupus, prevalence, and access to lupus care. Results Retrospective ORS data indicated there were 11,690 individuals living with lupus in 2014 with the average direct cost of $69,999.40 in medical care. Prospective surveys (N = 325), in over 16 locations in South Carolina, showed 31% knew someone with lupus, 16% had been diagnosed with lupus, and 50% did not know of a medical facility that treated lupus. Conclusion A lupus registry and repository will provide ongoing access for researchers on the impact of lupus on communities in South Carolina. Lupus is highly prevalent, but disproportionately represented in terms of patient information and participation in clinical trials, so it is also expected that this preliminary work will provide an ongoing process in which the medical community can better engage lupus patients.

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Multi-Touch Interaction Generation Device by Spatiotemporally Switching Electrodes

Electronics ◽

10.3390/electronics10121475 ◽

2021 ◽

Vol 10 (12) ◽

pp. 1475

Author(s):

Masahiro Okamoto ◽

Kazuya Murao

Keyword(s):

High Speed ◽

High Accuracy ◽

Conductive Ink ◽

Control Board ◽

Touch Panel ◽

Electrode Size ◽

Touch Input ◽

Touch Interaction ◽

Multiple Electrodes ◽

Touch Panels

With the spread of devices equipped with touch panels, such as smartphones, tablets, and laptops, the opportunity for users to perform touch interaction has increased. In this paper, we constructed a device that generates multi-touch interactions to realize high-speed, continuous, or hands-free touch input on a touch panel. The proposed device consists of an electrode sheet printed with multiple electrodes using conductive ink and a voltage control board, and generates eight multi-touch interactions: tap, double-tap, long-press, press-and-tap, swipe, pinch-in, pinch-out, and rotation, by changing the capacitance of the touch panel in time and space. In preliminary experiments, we investigated the appropriate electrode size and spacing for generating multi-touch interactions, and then implemented the device. From the evaluation experiments, it was confirmed that the proposed device can generate multi-touch interactions with high accuracy. As a result, tap, press-and-tap, swipe, pinch-in, pinch-out, and rotation can be generated with a success rate of 100%. It was confirmed that all the multi-touch interactions evaluated by the proposed device could be generated with high accuracy and acceptable speed.

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Gradual Wear Diagnosis of Outer-Race Rolling Bearing Faults through Artificial Intelligence Methods and Stray Flux Signals

Electronics ◽

10.3390/electronics10121486 ◽

2021 ◽

Vol 10 (12) ◽

pp. 1486

Author(s):

Israel Zamudio-Ramirez ◽

Roque A. Osornio-Rios ◽

Jose A. Antonino-Daviu ◽

Jonathan Cureño-Osornio ◽

Juan-Jose Saucedo-Dorantes

Keyword(s):

Kinematic Chain ◽

Industrial Applications ◽

Electric Motors ◽

Feed Forward Neural Network ◽

Mechatronic Systems ◽

Linear Discriminant ◽

Bearing Faults ◽

Outer Race ◽

Non Invasive ◽

Operation Conditions

Electric motors have been widely used as fundamental elements for driving kinematic chains on mechatronic systems, which are very important components for the proper operation of several industrial applications. Although electric motors are very robust and efficient machines, they are prone to suffer from different faults. One of the most frequent causes of failure is due to a degradation on the bearings. This fault has commonly been diagnosed at advanced stages by means of vibration and current signals. Since low-amplitude fault-related signals are typically obtained, the diagnosis of faults at incipient stages turns out to be a challenging task. In this context, it is desired to develop non-invasive techniques able to diagnose bearing faults at early stages, enabling to achieve adequate maintenance actions. This paper presents a non-invasive gradual wear diagnosis method for bearing outer-race faults. The proposal relies on the application of a linear discriminant analysis (LDA) to statistical and Katz’s fractal dimension features obtained from stray flux signals, and then an automatic classification is performed by means of a feed-forward neural network (FFNN). The results obtained demonstrates the effectiveness of the proposed method, which is validated on a kinematic chain (composed by a 0.746 KW induction motor, a belt and pulleys transmission system and an alternator as a load) under several operation conditions: healthy condition, 1 mm, 2 mm, 3 mm, 4 mm, and 5 mm hole diameter on the bearing outer race, and 60 Hz, 50 Hz, 15 Hz and 5 Hz power supply frequencies

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Electronic control board for student Rocket

2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS) ◽

10.1109/dcis51330.2020.9268644 ◽

2020 ◽

Author(s):

Jesus Lazaro ◽

Laura Burgos ◽

Leire Muguira ◽

Armando Astarloa ◽

Jaime Jimenez

Keyword(s):

Electronic Control ◽

Control Board

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Learning Feedforward Control Using Multiagent Control Approach for Motion Control Systems

Energies ◽

10.3390/en14020420 ◽

2021 ◽

Vol 14 (2) ◽

pp. 420

Author(s):

Phong B. Dao

Keyword(s):

Real Time ◽

Feedforward Control ◽

Design Method ◽

Mechatronic Systems ◽

Control Approach ◽

Runtime Environment ◽

Multiagent Control ◽

On Line ◽

Promising Solution ◽

Function Approximator

Multiagent control system (MACS) has become a promising solution for solving complex control problems. Using the advantages of MACS-based design approaches, a novel solution for advanced control of mechatronic systems has been developed in this paper. The study has aimed at integrating learning control into MACS. Specifically, learning feedforward control (LFFC) is implemented as a pattern for incorporation in MACS. The major novelty of this work is that the feedback control part is realized in a real-time periodic MACS, while the LFFC algorithm is done on-line, asynchronously, and in a separate non-real-time aperiodic MACS. As a result, a MACS-based LFFC design method has been developed. A second-order B-spline neural network (BSN) is used as a function approximator for LFFC whose input-output mapping can be adapted during control and is intended to become equal to the inverse model of the plant. To provide real-time features for the MACS-based LFFC system, the open robot control software (OROCOS) has been employed as development and runtime environment. A case study using a simulated linear motor in the presence of nonlinear cogging and friction force as well as mass variations is used to illustrate the proposed method. A MACS-based LFFC system has been designed and implemented for the simulated plant. The system consists of a setpoint generator, a feedback controller, and a time-index LFFC that can learn on-line. Simulation results have demonstrated the applicability of the design method.

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