A Fusion Algorithm for Estimating Time-Independent/-Dependent Parameters and States

Vehicle parameters are essential for dynamic analysis and control systems. One problem of the current estimation algorithm for vehicles’ parameters is that: real-time estimation methods only identify parts of vehicle parameters, whereas other parameters such as suspension damping coefficients and suspension and tire stiffnesses are assumed to be known in advance by means of an inertial parameter measurement device (IPMD). In this study, a fusion algorithm is proposed for identifying comprehensive vehicle parameters without the help of an IPMD, and vehicle parameters are divided into time-independent parameters (TIPs) and time-dependent parameters (TDPs) based on whether they change over time. TIPs are identified by a hybrid-mass state-variable (HMSV). A dual unscented Kalman filter (DUKF) is applied to update both TDPs and online states. The experiment is conducted on a real two-axle vehicle and the test data are used to estimate both TIPs and TDPs to validate the accuracy of the proposed algorithm. Numerical simulations are performed to further investigate the algorithm’s performance in terms of sprung mass variation, model error because of linearization and various road conditions. The results from both the experiment and simulation show that the proposed algorithm can estimate TIPs as well as update TDPs and online states with high accuracy and quick convergence, and no requirement of road information

Role of circRNA in E3 Modification under Human Disease

Circular RNA (circRNA) is often regarded as a special kind of non-coding RNA, involved in the regulation mechanism of various diseases, such as tumors, neurological diseases, and inflammation. In a broad spectrum of biological processes, the modification of the 76-amino acid ubiquitin protein generates a large number of signals with different cellular results. Each modification may change the result of signal transduction and participate in the occurrence and development of diseases. Studies have found that circRNA-mediated ubiquitination plays an important role in a variety of diseases. This review first introduces the characteristics of circRNA and ubiquitination and summarizes the mechanism of circRNA in the regulation of ubiquitination in various diseases. It is hoped that the emergence of circRNA-mediated ubiquitination can broaden the diagnosis and prognosis of the disease

Anomaly detection in radiotherapy plans using deep autoencoder networks

PurposeTreatment plans are used for patients under radiotherapy in clinics. Before execution, these plans are checked for safety and quality by human experts. A few of them were identified with flaws and needed further improvement. To automate this checking process, an unsupervised learning method based on an autoencoder was proposed.MethodsFirst, features were extracted from the treatment plan by human experts. Then, these features were assembled and used for model learning. After network optimization, a reconstruction error between the predicted and target signals was obtained. Finally, the questionable plans were identified based on the value of the reconstruction error. A large value of the reconstruction error indicates a longer distance from the standard distribution of normal plans. A total of 576 treatment plans for breast cancer patients were used for the test. Among them, 19 were questionable plans identified by human experts. To evaluate the performance of the autoencoder, it was compared with four baseline detection algorithms, namely, local outlier factor (LOF), hierarchical density-based spatial clustering of applications with noise (HDBSCAN), one-class support vector machine (OC-SVM), and principal component analysis (PCA).ResultsThe results showed that the autoencoder achieved the best performance than the other four baseline algorithms. The AUC value of the autoencoder was 0.9985, while the second one was 0.9535 (LOF). While maintaining 100% recall, the average accuracy and precision of the results by the autoencoder were 0.9658 and 0.5143, respectively. While maintaining 100% recall, the average accuracy and precision of the results by LOF were 0.8090 and 0.1472, respectively.ConclusionThe autoencoder can effectively identify questionable plans from a large group of normal plans. There is no need to label the data and prepare the training data for model learning. The autoencoder provides an effective way to carry out an automatic plan checking in radiotherapy

Study of Thermal Stress Fluctuations at the Die-Attach Solder Interface Using the Finite Element Method

Solder joints in electronic packages are frequently exposed to thermal cycling in both real-life applications and accelerated thermal cycling tests. Cyclic temperature leads the solder joints to be subjected to cyclic mechanical loading and often accelerates the cracking failure of the solder joints. The cause of stress generated in thermal cycling is usually attributed to the coefficients of thermal expansion (CTE) mismatch of the assembly materials. In a die-attach structure consisting of multiple layers of materials, the effect of their CTE mismatch on the thermal stress at a critical location can be very complex. In this study, we investigated the influence of different materials in a die-attach structure on the stress at the chip–solder interface with the finite element method. The die-attach structure included a SiC chip, a SAC solder layer and a DBC substrate. Three models covering different modeling scopes (i.e., model I, chip–solder layer; model II, chip–solder layer and copper layer; and model III, chip–solder layer and DBC substrate) were developed. The 25–150 °C cyclic temperature loading was applied to the die-attach structure, and the change of stress at the chip–solder interface was calculated. The results of model I showed that the chip–solder CTE mismatch, as the only stress source, led to a periodic and monotonic stress change in the temperature cycling. Compared to the stress curve of model I, an extra stress recovery peak appeared in both model II and model III during the ramp-up of temperature. It was demonstrated that the CTE mismatch between the solder and copper layer (or DBC substrate) not only affected the maximum stress at the chip–solder interface, but also caused the stress recovery peak. Thus, the combined effect of assembly materials in the die-attach structure should be considered when exploring the joint thermal stresses

Study of Thermal Stress Fluctuations at the Die-Attach Solder Interface Using the Finite Element Method

Solder joints in electronic packages are frequently exposed to thermal cycling in both real-life applications and accelerated thermal cycling tests. Cyclic temperature leads the solder joints to be subjected to cyclic mechanical loading and often accelerates the cracking failure of the solder joints. The cause of stress generated in thermal cycling is usually attributed to the coefficients of thermal expansion (CTE) mismatch of the assembly materials. In a die-attach structure consisting of multiple layers of materials, the effect of their CTE mismatch on the thermal stress at a critical location can be very complex. In this study, we investigated the influence of different materials in a die-attach structure on the stress at the chip–solder interface with the finite element method. The die-attach structure included a SiC chip, a SAC solder layer and a DBC substrate. Three models covering different modeling scopes (i.e., model I, chip–solder layer; model II, chip–solder layer and copper layer; and model III, chip–solder layer and DBC substrate) were developed. The 25–150 °C cyclic temperature loading was applied to the die-attach structure, and the change of stress at the chip–solder interface was calculated. The results of model I showed that the chip–solder CTE mismatch, as the only stress source, led to a periodic and monotonic stress change in the temperature cycling. Compared to the stress curve of model I, an extra stress recovery peak appeared in both model II and model III during the ramp-up of temperature. It was demonstrated that the CTE mismatch between the solder and copper layer (or DBC substrate) not only affected the maximum stress at the chip–solder interface, but also caused the stress recovery peak. Thus, the combined effect of assembly materials in the die-attach structure should be considered when exploring the joint thermal stresses

A Review of Cyclodextrin Encapsulation and Intelligent Response for the Release of Curcumin

To overcome the low water solubility and low bioavailability of curcumin (CUR), multiple delivery strategies have been proposed. Among these, cyclodextrin-based carriers have been widely used for the encapsulation and delivery of CUR. Cyclodextrins (CDs), as natural oligosaccharides, have been well known for their biodegradability, biocompatibility, non-toxicity, and internal hydrophobic and external hydrophilic structural features. This paper summarizes the recently reported CD-based carriers for encapsulating CUR. Particularly, the polymerization properties of CD self-assembly to enhance the encapsulation of CUR are discussed. In addition, the current progress on stimuli-responsive CD carriers for controlled release of CUR is described, which laid an important foundation for the development of CUR-based precision therapy in clinical practice. In conclusion, this review may provide ideas for the future development of a CD-based encapsulant for CUR