Correlational studies of order noise sample tuning and subjective evaluation test of sound quality were conducted to achieve sporty sound quality and confirm the correlation between the auditory sense (subjective) and the order noise level (objective) of vehicle exhaust noise under acceleration. First, the frequency range and the order ingredient of sporty quality noise were confirmed by a study of ear-hearing subjective feeling on the basis of physiological acoustics. By using an order tuning software that was developed independently, the second, fourth, and sixth order noise A-weighting sound pressure level (dB(A)) of the exhaust noise of an objective vehicle were tuned segmentally into numerous sound samples. Furthermore, samples with high sporty sound quality were selected through subjective evaluation, and the A-weighting sound pressure level (dB(A)) distributions of the second, fourth, and sixth order noise of these samples were analyzed. Consequently, the relative size relations of the second, fourth, and sixth order noise of all the exhaust noise with sporty sound quality were determined. In addition, the curve distribution zones of the corresponding order noise were formed and the order quantitative target of the sporty sound quality was considered. Finally, four passenger vehicles with representative sound qualities (sporty, quiet, and characterless) on the market were selected as the benchmark vehicles; their order noise was objectively tested and their sound qualities subjectively evaluated. Meanwhile, the order noise objective test result was compared with the order target. Results showed that when the fourth and sixth order noise curves relative to the second order noise curves were within the order target zones at most of the engine speeds, the exhaust noise of the vehicle had considerable sporty sound quality; otherwise, it did not have such a sound. Therefore, the order target of the sporty sound quality was accurate and effective.

Combining substructure and power flow theory, in this paper an external program is written to control MSC. Nastran solution process and the substructure frequency response are also formulated accordingly. Based on a simple vehicle model, characteristics of vibration, noise, and power flow are studied, respectively. After being compared with the result of conventional FEM (finite element method), the new method is confirmed to be feasible. When it comes to a vehicle with the problem of low-frequency noise, finite element models of substructures for vehicle body and chassis are established, respectively. In addition, substructure power flow method is also employed to examine the transfer characteristics of multidimensional vibration energy for the whole vehicle system. By virtue of the adjustment stiffness of drive shaft support and bushes at rear suspension lower arm, the vehicle interior noise is decreased by about 3 dB when the engine speed is near 1050 rpm and 1650 rpm in experiment. At the same time, this method can increase the computation efficiency by 78%, 38%, and 98% when it comes to the optimization of chassis structure, body structure, and vibration isolation components, respectively.

Precision medicine, particularly therapeutic drug monitoring (TDM), is essential for optimizing drug dosage and minimizing toxicity. However, current TDM methods have limitations, including the need for skilled operators, patient discomfort, and the inability to monitor dynamic drug level changes. In recent years, wearable sensors have emerged as a promising solution for drug monitoring. These sensors offer real-time and continuous measurement of drug concentrations in biofluids, enabling personalized medicine and reducing the risk of toxicity. This review provides an overview of drugs detectable by wearable sensors and explores biosensing technologies that can enable drug monitoring in the future. It presents a comparative analysis of multiple biosensing technologies and evaluates their strengths and limitations for integration into wearable detection systems. The promising capabilities of wearable sensors for real-time and continuous drug monitoring offer revolutionary advancements in diagnostic tools, supporting personalized medicine and optimal therapeutic effects. Wearable sensors are poised to become essential components of healthcare systems, catering to the diverse needs of patients and reducing healthcare costs.

The noise characteristic of an entire single-cylinder gasoline engine was tested through acoustic spectral and intensity analyses to solve its abnormal noise problem in idling condition. Then, the abnormal noises were identified as piston impact noises caused by the anomalous dynamic performance of the piston mechanism. A piston multibody dynamic model was established on the basis of the key performance and the structure parameters of the piston to eliminate the abnormal noise. Then, the piston dynamic performance was improved by optimizing the piston structures. Analysis results showed that the lateral force, secondary kinetic energy, and friction power loss of the piston were reduced by approximately 51.3%, 40.2%, and 31.8%, respectively. Finally, the acoustic verification tests were implemented on the basis of the original engine when the optimized sample was manufactured and installed in the engine. The results showed that the abnormal noise was eliminated and the overall sound pressure level of the engine was reduced by 2.5 dB(A) in idling condition. Meanwhile, the subjective evaluation results showed that the sound quality was obviously improved. The dynamic performance of the piston could be improved by optimizing the piston structure to reduce the impact noise.