Effect of Silicon Carbide Nanoparticles on the Friction-Wear Properties of Copper-Based Friction Discs

To study the influence of nano-additives on the friction-wear characteristics of friction materials, the nano-sized silicon carbide particles which have excellent chemical and physical properties are considered to add in composite to form the modified friction material. The influence of the silicon carbide nanoparticles (SCN) on the friction-wear characteristics of copper-based friction materials (CBFM) is investigated via the SAE#2 (made in Hangzhou, China) clutch bench test with the applied pressure, rotating speed, and automatic transmission fluid (ATF) temperature taken into account. Moreover, the variations of friction torque and temperature are considered to evaluate the friction performance, and the variable coefficient is employed to describe the friction stability. The wear characteristics of friction materials are investigated by the disc changes in thickness and micro-morphology. The results show that the CBFM with SCN can provide a higher friction torque, which increased by 30% to 50% compared with CBFM. The variable coefficient of CBFM with SCN changes from 674 to 52 with the rotating speed raised from 600 rpm to 3000 rpm, which shows that the friction stability is relatively worse. Furthermore, the micromorphology shows that the CBFM with SCN has lower porosity and surface roughness, which increases the microscopic contact area and the coefficient of friction (COF). Simultaneously, the reduction in porosity also leads to a decrease in the cooling quality, bringing about a rapid temperature rise. Thus, the wear amount of CBFM with SCN increases significantly, especially for the friction disc in the axial middle position.

Home Telemonitoring of Patients With Type 2 Diabetes: A Meta-Analysis and Systematic Review

Telehealth has emerged as an evolving care management strategy that is playing an increasingly vital role, particularly with the onset of the coronavirus disease 2019 pandemic. A meta-analysis of 20 randomized controlled trials was conducted to test the effectiveness of home telemonitoring (HTM) in patients with type 2 diabetes in reducing A1C, blood pressure, and BMI over a median 180-day study duration. HTM was associated with a significant reduction in A1C by 0.42% (P = 0.0084). Although we found statistically significant changes in both systolic and diastolic blood pressure (−0.10 mmHg [P = 0.0041], and −0.07 mmHg [P = 0.044], respectively), we regard this as clinically nonsignificant in the context of HTM. Comparisons across different methods of transmitting vital signs suggest that patients logging into systems with moderate interaction with the technology platform had significantly higher reductions in A1C than those using fully automatic transmission methods or fully manual uploading methods. A1C did not vary significantly by study duration (from 84 days to 5 years). HTM has the potential to provide patients and their providers with timely, up-to-date information while simultaneously improving A1C.

Vehicle diagnostic technology

In the article, using the example of a mechatronic control system for the engine and transmission of vehicles (automobiles), the features of the technology of their diagnosis are shown. In an electronic transmission control system, the object of regulation is mainly an automatic transmission. Also, the laws of control (programs) of gear shifting in an automatic transmission ensure the optimal transfer of engine energy to the wheels of the vehicle (TC), taking into account the required traction and speed properties and fuel economy. At the same time, the programs for achieving optimal traction-speed properties and minimum fuel consumption differ from each other, since the simultaneous achievement of these goals is not always possible. Therefore, depending on the driving conditions and the desire of the driver, using a special switch, you can select the "economy" program to reduce fuel consumption, the "power" program - to improve traction and speed properties, or the "manual" program to switch gears by the driver. In turn, self-diagnostic capabilities include: system identification and electronic control units (ECU) (ECU); recognition, storage and reading of information about static and single malfunctions; reading current real data, including environmental conditions and specifications; modeling of system functions; programming of system parameters. The individual programs for the test block are stored in the plug-in modules, while the correction and data transfer in the system is carried out via the data interface. Note also that the diagnostic process begins with the initialization of the systems - their detection in the electrical equipment of the vehicle. Upon successful initialization, it is possible to: read the error memory; erase the error memory; view the data of the next detected system or exit to the main menu; change the readings of the selected category; correct the current time; correct the current date and perform a number of additional functions.

A supervised machine-learning method for optimizing the automatic transmission system of wind turbines

Large-scale wind turbines mostly use Continuously Variable Transmission (CVT) as the transmission system, which is highly efficient. However, it comes with high complexity and cost too. In contrast, the small-scale wind turbines that are available in the market offer a one-speed gearing system only where no gear ratios are varied, resulting in low efficiency of harvesting energy and leading to gears failure. In this research, an unsupervised machine-learning algorithm is proposed to address the energy efficiency of the automatic transmission system in vertical axis wind turbines (VAWT), to increase its efficiency in harvesting energy. The aim is to find the best adjustment for VAWT while the automatic transmission system is taken into account. For this purpose, the system is simulated and tested under various gear ratios conditions while a centrifugal clutch is applied to automatic gear shifting. The outcomes indicated that the automatic transmission system could successfully adjust the spinning in line with the wind speed. As a result, the obtained level of harvested voltage and power by VAWT with the automatic transmission system are improved significantly. Consequently, it is concluded that automatic VAWTs, equipped with the machine-learning capability can readjust themselves with the wind speed more efficiently.

Combustion Conduct Of A Single-Cylinder Spark-Ignition Affected By Ethanol Fuel Mixtures of Supplement Hydroxy Gas (HHO)

Ethanol is an alternative fuel to replace fossil fuels. Ethanol's high octane value can substitute for power in spark-ignition engines (SI). Gasoline mixed with ethanol will reduce the calorific value generated and intensify the combustion process in the combustion chamber. Through the engine performance test, we can find out the increase in the performance of the SI engine. Several essential variables can improve engine performance, such as gasoline-ethanol variations, iridium spark plugs, and hydroxy gas generators (HHO). This research uses an experimental method by utilizing gasoline (octane-92)-ethanol variations (35%, 45%, and 55% v/v) with the intake of hydroxy gas during the combustion process. The SI automatic transmission engine has a capacity of 124.8 cubic centimeters (one cylinder-four stroke), a compression ratio of 11/1, fuel injection, and iridium spark plugs. Engine performance test using chassis dyno test with engine speed variations of 4000-9000 rpm. This study resulted in optimal performance on a 55% increase in gasoline-ethanol mixture with an intensify in output-power, pressure, and thermal efficiency at an engine-speed of 8000 rpm. It is contrary to the specific fuel consumption has decreased.

Wireless Radio Frequency Automation of Intelligent Optical Fiber Transmission System Based on the Differential Evolution Method

With the continuous development and improvement of science and technology, optical fiber transmission has been transformed from traditional manual transmission to automatic transmission, and the transmission efficiency is constantly improving. In order to further analyze the performance of the intelligent optical fiber transmission process, the differential evolution analysis method is introduced in this paper, integrated architecture is built through the integrated optical and intelligent optical fiber, and the corresponding vector signal error value is solved through the comparison of transmission schemes. The error value is about 9%, through simulation experiments, which can effectively meet the requirement of automation of the wireless radio frequency of the intelligent optical fiber transmission system and realize long-distance transmission.

Telehealth for patients with interstitial lung diseases (ILD): results of an international survey of clinicians

IntroductionClinicians and policymakers are promoting widespread use of home technology including spirometry to detect disease progression for patients with interstitial lung disease (ILD); the COVID-19 pandemic has accelerated this. Data collating clinicians’ views on the potential utility of telehealth in ILD are limited.AimThis survey investigated clinicians’ opinions about contemporary methods and practices used to monitor disease progression in patients with ILD using telehealth.MethodsClinicians were invited to participate in a cross-sectional survey (SurveyMonkey) of 13 questions designed by an expert panel. Telehealth was defined as home monitoring of symptoms and physiological parameters with regular automatic transmission of data from the patient’s home to the clinician. Data are presented as percentages of respondents.ResultsA total of 207 clinicians from 23 countries participated in the survey. A minority (81, 39%) reported using telehealth. 50% (n=41) of these respondents completed a further question about the effectiveness of telehealth. A majority of respondents (32, 70%) rated it to be quite or more effective than face-to-face visit. There were a greater number of respondents using telehealth from Europe (94, 45%) than Asia (51, 25%) and America (24%). Clinicians reported the most useful telehealth monitoring technologies as smartphone apps (59%) and wearable sensors (30%). Telehealth was most frequently used for monitoring disease progression (70%), quality of life (63%), medication use (63%) and reducing the need for in-person visits (63%). Clinicians most often monitored symptoms (93%), oxygen saturation (74%) and physical activity (72%). The equipment perceived to be most effective were spirometers (43%) and pulse oximeters (33%). The primary barriers to clinicians’ participation in telehealth were organisational structure (80%), technical challenges (63%) and lack of time and/or workload (63%). Clinicians considered patients’ barriers to participation might include lack of awareness (76%), lack of knowledge using smartphones (60%) and lack of confidence in telehealth (56%).ConclusionThe ILD clinicians completing this survey who used telehealth to monitor patients (n=81) supported its’ clinical utility. Our findings emphasise the need for robust research in telehealth as a mode for the delivery of cost-effective healthcare services in ILD and highlight the need to assess patients’ perspectives to improve telehealth utility in patients with ILD.