A Readout Circuit for MEMS Gas Sensor

In recent years, the application of gas sensors is becoming more and more extensive. Driven by potential applications such as the Internet of Things, its technology development direction begins with miniaturization, integration, modularization, and intelligence. However, there is a bottleneck in the research of interface circuits, which restricts the development of gas sensors in volume, power consumption, and intelligence. To solve this problem, a MEMS gas sensor interface circuit based on ADC technology is proposed in this paper. Under the condition of the Huahong 110 nm process, the working voltage is 3.3 V, the resistance change of 100 Ω~1 MΩ can be detected, the conversion error is in the range of 0.5~1%, and the maximum power consumption is 986 μW. The overall layout area is 0.49 × 0.77 mm2. Finally, the correctness of the circuit function is verified by post-layout simulation

Data-Driven RBFNN-Enhanced Model-Free Adaptive Traffic Symmetrical Signal Control for a Multi-Phase Intersection with Fast-Changing Traffic Flow

Fast-changing demand in real traffic systems always leads to asymmetrical traffic flow and queues, which aggravates congestion and energy waste. In this paper, the traffic signal control problem of multi-phase intersections was studied with fast-changing traffic flows. First, a novel model-free adaptive control-based symmetrical queuing balancing method was designed by using the full-format dynamic linearization (FFDL) technique. Second, in order to deal with the fast-changing traffic flow, a radial basis function neural network (RBFNN) was added to adjust parameters in a two-layer structure. Moreover, a variable cycle tuning algorithm was introduced to further reduce the time loss. Using the simulation, the proposed algorithm was compared with three other control strategies under low and high traffic demand, respectively, and the results showed the capability of the proposed algorithm

Physiologically-based pharmacokinetic modeling for optimal dosage prediction of olaparib when co-administered with CYP3A4 modulators and in patients with hepatic/renal impairment

Abstract This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model to predict the maximum plasma concentration (Cmax) and trough concentration (Ctrough) at steady-state of olaparib (OLA) in Caucasian, Japanese and Chinese. Furthermore, the PBPK model was combined with mean and 95% confidence interval to predict optimal dosing regimens of OLA when co-administered with CYP3A4 modulators and administered to patients with hepatic/renal impairment. The dosing regimens were determined based on safety and efficacy PK threshold Cmax (< 12,500 ng/mL) and Ctrough (772–2500 ng/mL). The population PBPK model for OLA was successfully developed and validated, demonstrating good consistency with clinically observed data. The ratios of predicted to observed values for Cmax and Ctrough fell within the range of 0.5 to 2.0. When OLA was co-administered with a strong or moderate CYP3A4 inhibitor, the recommended dosing regimens should be reduced to 100 mg BID and 150 mg BID, respectively. Additionally, the PBPK model also suggested that OLA could be not recommended with a strong or moderate CYP3A4 inducer. For patients with moderate hepatic and renal impairment, the dosing regimens of OLA were recommended to be reduced to 200 mg BID and 150 mg BID, respectively. In cases of severe hepatic and renal impairment, the PBPK model suggested a dosing regimen of 100 mg BID for OLA. Overall, this present PBPK model can determine the optimal dosing regimens for various clinical scenarios involving OLA

Data-Driven Kalman Consensus Filtering for Connected Vehicle Speed Estimation in a Multi-Sensor Network

The autonomous traffic system has imposed higher requirements on the speed estimation of connected vehicles, where the speed of connected vehicles, as one of the control conditions for refined traffic management, plays a crucial role in the evaluation and optimization of network performance. In this paper, we propose a multi-source speed measurement sensor network consensus filtering (MSCF) algorithm based on information weight for the problem of optimal speed consistency estimation for connected vehicles. Specifically, we first utilize dynamic linearization techniques and data-driven parameter identification algorithms to handle the derived state equations of connected vehicles. We then establish observation models for four different types of sensors and construct distributed direct and indirect measurement models by dynamically adjusting the information weights of sensor nodes. Following this, we combine the Kalman consistency filtering algorithm to derive the speed state estimation update rate and design a new state estimator to achieve the optimal consistent convergence estimation for connected vehicles’ speed. The MSCF algorithm can solve the problem of consistency filtering for noisy sensor data under observation- and communication-constrained conditions, enabling each sensor node to obtain a consistent convergence estimation value for the speed of the connected vehicle. The convergence of the algorithm is proved using the Lyapunov function. Through numerical simulation, the results are verified, indicating that compared to existing methods, this method can achieve a higher precision speed estimation effect

Integrated Impacts of Non-Ideal Factors on the Vibration Characteristics of Permanent Magnet Synchronous Motors for Electric Vehicles

The nonlinear electromagnetic vibration of the motor is a major factor that deteriorates the noise, vibration, and hardness (NVH) performance of a vehicle’s electric drive system. Considering the nonlinear characteristics of the inverter, the nonsinusoidal distribution of the air-gap magnetic field, the cogging torque, and the current measurement error, a mathematical model of a permanent magnet synchronous motor of an electric vehicle was established, and its dynamic and electromagnetic vibration characteristics under different speed–load conditions were simulated and analyzed. The results show that the nonlinear characteristics of the inverter and nonsinusoidal distribution of the air-gap magnetic field cause the odd current harmonics, such as the 5th, 7th, 11th, and 13th, which lead to the 6th and its integer multiple order fluctuations of the electromagnetic torque. Moreover, the vibration amplitude is intensified under the coupling action of the nonlinear characteristics of the inverter and the nonsinusoidal distribution of the air-gap magnetic field. The current measurement error produces the 1st and 2nd harmonics of the d- and q-axes currents, which result in the 1st and 2nd order fluctuations of the electromagnetic torque. The cogging torque mainly leads to a 12th order torque ripple of the electromagnetic torque. In addition, the non-ideal factors cause a sharp deterioration in the system vibration state under high-speed and heavy-load conditions. This study provides a theoretical reference for the mathematical modeling and electromagnetic vibration research of permanent magnet synchronous motors, considering non-ideal factors comprehensively

A New Calculation Method of Dynamic Kill Fluid Density Variation during Deep Water Drilling

There are plenty of uncertainties and enormous challenges in deep water drilling due to complicated shallow flow and deep strata of high temperature and pressure. This paper investigates density of dynamic kill fluid and optimum density during the kill operation process in which dynamic kill process can be divided into two stages, that is, dynamic stable stage and static stable stage. The dynamic kill fluid consists of a single liquid phase and different solid phases. In addition, liquid phase is a mixture of water and oil. Therefore, a new method in calculating the temperature and pressure field of deep water wellbore is proposed. The paper calculates the changing trend of kill fluid density under different temperature and pressure by means of superposition method, nonlinear regression, and segment processing technique. By employing the improved model of kill fluid density, deep water kill operation in a well is investigated. By comparison, the calculated density results are in line with the field data. The model proposed in this paper proves to be satisfactory in optimizing dynamic kill operations to ensure the safety in deep water

New evidence confirming the CD genomic constitutions of the tetraploid Avena species in the section Pachycarpa Baum.

The tetraploid Avena species in the section Pachycarpa Baum, including A. insularis, A. maroccana, and A. murphyi, are thought to be involved in the evolution of hexaploid oats; however, their genome designations are still being debated. Repetitive DNA sequences play an important role in genome structuring and evolution, so understanding the chromosomal organization and distribution of these sequences in Avena species could provide valuable information concerning genome evolution in this genus. In this study, the chromosomal organizations and distributions of six repetitive DNA sequences (including three SSR motifs (TTC, AAC, CAG), one 5S rRNA gene fragment, and two oat A and C genome specific repeats) were investigated using non-denaturing fluorescence in situ hybridization (ND-FISH) in the three tetraploid species mentioned above and in two hexaploid oat species. Preferential distribution of the SSRs in centromeric regions was seen in the A and D genomes, whereas few signals were detected in the C genomes. Some intergenomic translocations were observed in the tetraploids; such translocations were also detected between the C and D genomes in the hexaploids. These results provide robust evidence for the presence of the D genome in all three tetraploids, strongly suggesting that the genomic constitution of these species is DC and not AC, as had been thought previously

IMPACT TEST AND SIMULATION OF PROTABLE ELECTRONIC DEVICES: AN ASSESSMENT

ABSTRACT Portable electronics devices are well known to be susceptible to drop impact which can cause various damage modes such as interconnect breakage, battery separation, possible cracking/debonding along interfaces, display damage, leaking in insulin pump, etc.. Drop/impact performance of these products is one of important concerns of product design. Because of the small size of this type of electronics products, it is very expensive, time-consuming and difficult to conduct drop tests to directly detect the failure mechanisms and identify their drop behaviors. A brief review is given in terms of the development in testing standards, material modeling and structure modeling. Barriers and needs are given for both the measurement and modeling, with particular attention to the material rate dependent constitutive modeling, testing facilities development, and nonlinear contact mechanics modeling

Copper fiber reinforced needle-coke/carbon composite for pantograph slide and its current-carrying wear performance

Copper fiber reinforced needle-coke/carbon (CF-NC/C) composites with different copper fiber contents have been successfully developed for urban rail pantograph slide block. The mechanical properties of needle coke samples containing 0 wt%, 4 wt%, 8 wt%, 12 wt% and 16 wt% were examined separately. It is found that the presence of needle coke with high aspect ratio, strength and electrical conductivity can greatly improves the physical properties of the pure carbon matrix. Therefore, we have obtained a novel carbon matrix composite. It is also revealed that the optimized CF-NC/C with 5 wt% copper fibers (CF-NC/C-5) composite has outstanding mechanical properties, current-carrying friction wear properties. The density, resistivity, and impact strength of the CF-NC/C-5 composite are 1.8788 g cm ^−3 , 35.18 μ Ω·m, 0.16 J cm ^−2 , respectively. In current-carrying friction wear tests (0 A, 5 A, 10 A and 15 A), the CF-NC/C-5 shows an optimum friction wear performance. To avoid agglomeration of copper fibers, the copper fibers are added innovatively during the rolling process and uniformly distributed in the carbon matrix under the tangential force of rolling, which exhibits an improved effect on reinforcing the NC/C composites. Our results greatly advance the development of the needle-coke/carbon composite, which makes the new CF-NC/C composite an ideal candidate for sliding plate material with excellent properties