The state of the art and future trends of root canal files from the perspective of patent analysis: a study design.

The goal of this review is to present a detailed and comprehensive description of the published work from the past decade regarding methods of improved material, geometric design, and additional functions in root canal files. The main improved methods of files and the most common technologies were further addressed, underlining their advantages and main limitations. Online databases (the Derwent Innovations Index) were consulted on this topic. Published work from 2010 to 2022 was collected and analyzed the relevant papers were chosen for inclusion in this review. The patent map classified the latest phase of the root canal files based on the analysis of the number of patents. The performance of the root canal files, such as materials. Directly affects the quality of the root canal therapy. We provided a thorough review of advances in the field of root canal files. In particular, three categories of improved methods were examined and compared, including material-based methods, geometry-based methods, and those based on additional functions. To understand this state of the art of different improved methods of root canal files, we conducted a literature analysis and a series of comparisons between different methods. The features and limitations of each method of root canal files were further discussed. Finally, we identified promising research directions in advancing the methods for the improved performance of root canal files. There is no perfect technology for all material/geometric design/additional functions, capable alone of fulfilling all the specificity and necessities of every patient. Although it is very promising, the material of the files remains understudied, and further work is required to make material science a pervasive technology in root canal therapy, and contribute to endodontic and periapical diseases by assisting in the subsequent development of root canal files.

Deep Learning-Based Complete Coverage Path Planning With Re-Joint and Obstacle Fusion Paradigm.

With the introduction of autonomy into the precision agriculture process, environmental exploration, disaster response, and other fields, one of the global demands is to navigate autonomous vehicles to completely cover entire unknown environments. In the previous complete coverage path planning (CCPP) research, however, autonomous vehicles need to consider mapping, obstacle avoidance, and route planning simultaneously during operating in the workspace, which results in an extremely complicated and computationally expensive navigation system. In this study, a new framework is developed in light of a hierarchical manner with the obtained environmental information and gradually solving navigation problems layer by layer, consisting of environmental mapping, path generation, CCPP, and dynamic obstacle avoidance. The first layer based on satellite images utilizes a deep learning method to generate the CCPP trajectory through the position of the autonomous vehicle. In the second layer, an obstacle fusion paradigm in the map is developed based on the unmanned aerial vehicle (UAV) onboard sensors. A nature-inspired algorithm is adopted for obstacle avoidance and CCPP re-joint. Equipped with the onboard LIDAR equipment, autonomous vehicles, in the third layer, dynamically avoid moving obstacles. Simulated experiments validate the effectiveness and robustness of the proposed framework.

Simulation-Based Design and Optimization of Accelerometers Subject to High-Temperature and High-Impact Loads.

Due to multi-factor coupling behavior, the performance evaluation of an accelerometer subject to high-temperature and high-impact loads poses a significant challenge during its design phase. In this paper, the simulation-based method is applied to optimize the design of the accelerometer. The proposed method can reduce the uncertainties and improve the fidelity of the simulation in the sense that (i) the preloading conditions of fasteners are taken into consideration and modeled in static analysis; (ii) all types of loadings, including bolt preloads, thermal loads, and impact loads, are defined in virtual dynamic prototype of the accelerometer. It is our finding that from static and dynamic analysis, an accelerometer is exposed to the risk of malfunction and even a complete failure if the temperature rises to a certain limit; it has been proved that the thermal properties of sensing components are the most critical factors for an accelerometer to achieve its desired performance. Accordingly, we use a simulation-based method to optimize the thermal expansion coefficient of the sensing element and get the expected design objectives.

Modeling and Quantification of Impact of Psychological Factors on Rehabilitation of Stroke Patients.

The brain damage could lead to the loss of the central nervous system, so a stroke patient may lose the function of dominating his/her body. The rehabilitation aims to maximize the potential to restore a patient who has an impairment. Traditional rehabilitation is to train a patient's muscles and joints under the guidance of doctors to improve the strength of muscles and restore the motor function of joints. However, stroke patients are usually depressed, lonely, and irritable, and they might easily generate negative emotions during a rehabilitation process. With a sole goal of helping patients restore their body functions from the physiology perspective, the traditional rehabilitation took little consideration on the impact of rehabilitation, which is reflected and measured from the perspective of emotions. Therefore, we suggest adding affective regulation to the stroke rehabilitation; in such a way, the patients' exercise could be completed with high intrinsic motivation, and the performance of the rehabilitation process can be enhanced. Two main contributions in the presented works are: 1) the expanded emotional model to represent the status of stroke patients where the impact of psychological factors can be taken into consideration and 2) the quantifiable measurement of rehabilitation performance as well as the corresponding design of experiments to verify the positive impact of psychological adjustment on human subjects. Note that due to the limited conditions, the experimental verification was performed on healthy college students. Since our work focused on modeling and quantification of psychological factors, it is reasonable to expend our work to other human subjects including stoke patients.