Ethical Decision-making for Autonomous Driving based on LSTM Trajectory Prediction Network

The development of autonomous vehicles has brought a great impact and changes to the transportation industry, offering numerous benefits in terms of safety and efficiency. However, one of the key challenges that autonomous driving faces is how to make ethical decisions in complex situations. To address this issue, in this article, a novel trajectory prediction method is proposed to achieve ethical decision-making for autonomous driving. Ethical considerations are integrated into the decision-making process of autonomous vehicles by quantifying the utility principle and incorporating them into mathematical formulas. Furthermore, trajectory prediction is optimized using LSTM network with an attention module, resulting in improved accuracy and reliability in trajectory planning and selection. Through extensive simulation experiments, we demonstrate the effectiveness of the proposed method in making ethical decisions and selecting optimal trajectories.Comment: 7 pages, 4 figure

Mani-GPT: A Generative Model for Interactive Robotic Manipulation

In real-world scenarios, human dialogues are multi-round and diverse. Furthermore, human instructions can be unclear and human responses are unrestricted. Interactive robots face difficulties in understanding human intents and generating suitable strategies for assisting individuals through manipulation. In this article, we propose Mani-GPT, a Generative Pre-trained Transformer (GPT) for interactive robotic manipulation. The proposed model has the ability to understand the environment through object information, understand human intent through dialogues, generate natural language responses to human input, and generate appropriate manipulation plans to assist the human. This makes the human-robot interaction more natural and humanized. In our experiment, Mani-GPT outperforms existing algorithms with an accuracy of 84.6% in intent recognition and decision-making for actions. Furthermore, it demonstrates satisfying performance in real-world dialogue tests with users, achieving an average response accuracy of 70%

Simultaneously suppressing the dendritic lithium growth and polysulfides migration by a polyethyleneimine grafted bacterial cellulose membrane in lithium-sulfur batteries

Owing to the ultrahigh theoretical energy density and low-cost, lithium-sulfur (Li-S) batteries hold broad prospects as one of the promising substitutes for commercial lithium-ion batteries. The polysulfides shuttling originated from sulfur cathode and the lithium dendrite growth from lithium anode are the main challenges that hinder the commercial survival of Li-S batteries. Herein, thermal stable bacterial cellulose (BC) separator is successfully fixed with polyethyleneimine (PEI) by a scalable chemical grafting. The hydroxyl groups and amino groups in PEI grafted BC (PEI@BC) separator can participate in the formation of Li2O and Li3N, respectively, contributing to robust solid electrolyte interface with high ionic conductivity. Therefore, the lithium deposition is well regulated, resulting in a spherical and dendrite-free Li deposit pattern. The Li/Li symmetrical cell assembled with PEI@BC separator exhibits excellent cyclic stability, which can continuously plate/stripe for more than 820 h with an overpotential of ∼ 40 mV at 2 mA cm−2. Meanwhile, the polar amino group can restrain the polysulfides migration via chemosorption. As a consequence of these merits, ultrahigh initial capacity (1402 mAh g−1 at 0.1C) and excellent rate performance (440.5 mAh g−1 at 2C) for Li-S full cell are achieved, presenting new insights into the fabrication of multifunctional separators for Li-S batteries

Driving Control Research for Longitudinal Dynamics of Electric Vehicles with Independently Driven Front and Rear Wheels

This paper takes the electric off-road vehicle with separated driven axles as the research object. To solve the longitudinal dynamics driving control problems, vehicle dynamics model, and control strategies were studied and the corresponding simulation was carried out. An 8-DOF vehicle dynamics model with separated driven axles was built. The driving control strategies on the typical roads were put forward. The recognition algorithm of the typical road surfaces based on the wheels’ slip rates was proposed. And the two control systems were designed including the pedal opening degree adjustment control system based on PI algorithm and the interaxle torque distribution control system based on sliding mode control algorithm. The driving control flow of the proposed vehicle combining the pedal adjustment control system with the interaxle torque distribution control system was developed. And the driven control strategies for the typical roads were simulated. Simulation results show that the proposed drive control strategies can adapt to different typical road surfaces, limit the slip rates of the driving wheels within the stable zone, and ensure the vehicle driving safely and stably in accordance with the driver's intention

Corrigendum to “Simultaneously suppressing the dendritic lithium growth and polysulfides migration by a polyethyleneimine grafted bacterial cellulose membrane in lithium-sulfur batteries” [Appl. Surf. Sci. 597 (2022) 153683]

The authors regret the error in the first author's name and the correct author list is updated as above. The authors would like to apologise for any inconvenience caused.</p

Virtual Reality Based Robot Teleoperation via Human-Scene Interaction

Robot teleoperation gains great success in various situations, including chemical pollution rescue, disaster relief, and long-distance manipulation. In this article, we propose a virtual reality (VR) based robot teleoperation system to achieve more efficient and natural interaction with humans in different scenes. A user-friendly VR interface is designed to help users interact with a desktop scene using their hands efficiently and intuitively. To improve user experience and reduce workload, we simulate the process in the physics engine to help build a preview of the scene after manipulation in the virtual scene before execution. We conduct experiments with different users and compare our system with a direct control method across several teleoperation tasks. The user study demonstrates that the proposed system enables users to perform operations more instinctively with a lighter mental workload. Users can perform pick-and-place and object-stacking tasks in a considerably short time, even for beginners. Our code is available at https://github.com/lingxiaomeng/VR_Teleoperation_Gen3

Prophylactic abdominal drainage following appendectomy for complicated appendicitis: A meta-analysis

BackgroundTo date, the value of prophylactic abdominal drainage (AD) following appendectomy in patients with complicated appendicitis (CA), including adults and children, has yet to be determined. This paper presents a meta-analysis of the effects of prophylactic AD on postoperative complications in patients with CA, with the goal of exploring the safety and effectiveness of prophylactic AD.MethodsPubMed, Science Direct, Web of Science, Cochrane Library, and Embase databases were searched for relevant articles published before August 1, 2022. The primary outcomes were the complication rates [overall incidence of postoperative complications, incidence of intra-abdominal abscess (IAA), wound infection (WI), and postoperative ileus (PI), and the secondary outcome was the perioperative outcome]. The meta-analysis was performed with STATA V. 16.0A.ResultsA total of 2,627 articles were retrieved and 15 high-quality articles were eventually included after screening, resulting in a total of 5,123 patients, of whom 1,796 received AD and 3,327 did not. The results of this meta-analysis showed that compared with patients in the non-drainage group, patients in the drainage group had longer postoperative length of hospitalization (LOH) (SMD = 0.68, 95% CI: 0.01–1.35, P = 0.046), higher overall incidence of postoperative complications (OR = 0.50, 95% CI: 0.19–0.81, P = 0.01), higher incidence of WI (OR = 0.30, 95% CI: 0.08–0.51, P = 0.01) and PI (OR = 1.05, 95% CI: 0.57–1.54, P = 0.01), the differences were statistically significant. However, there was no significant difference in the incidence of IAA (OR = 0.10, 95% CI: −0.10 to 0.31, P = 0.31) between the two groups. The results of subgroup meta-analysis showed that in the adult subgroup, the overall incidence of postoperative complications in the drainage group was higher than that in the non-drainage group (OR = 0.67, 95% CI: 0.37–0.96, P = 0.01). However, there were no significant differences in IAA (OR = 0.18, 95% CI: −0.28 to 0.64, P = 0.45) and WI (OR = 0.13, 95% CI: (−0.40 to 0.66, P = 0.63) and PI (OR = 2.71, 95% CI: −0.29 to 5.71, P = 0.08). In the children subgroup, there were no significant differences in the incidence of IAA (OR = 0.51, 95% CI: −0.06 to 1.09, P = 0.08) between the two groups. The overall incidence of postoperative complications (OR = 0.46, 95% CI: 0.02–0.90, P = 0.04), incidences of WI (OR = 0.43, 95% CI: 0.14–0.71, P = 0.01) and PI (OR = 0.75, 95% CI: 0.10–1.39, P = 0.02) were significantly higher than those in the non-drainage group.ConclusionThis meta-analysis concluded that prophylactic AD did not benefit from appendectomy, but increased the incidence of related complications, especially in children with CA. Thus, there is insufficient evidence to support the routine use of prophylactic AD following appendectomy

Clinical management of gastric cancer: results of a multicentre survey

<p>Abstract</p> <p>Background</p> <p>The National Comprehensive Cancer Network clinical practice guidelines in oncology-gastric cancer guidelines have been widely used to provide appropriate recommendations for the treatment of patients with gastric cancer. The aim of this study was to examine the adherence of surgical oncologists, medical oncologists, and radiation oncologists' to the recommended guidelines.</p> <p>Methods</p> <p>A questionnaire asking the treatment options for gastric cancer cases was sent to 394 Chinese oncology specialists, including surgical oncologists, medical oncologists, and radiation oncologists working in hospitals joined in The Western Cooperative Gastrointestinal Oncology Group of China. The questionnaire involved a series of clinical scenarios regarding the interpretation of surgery, neoadjuvant, adjuvant, and advanced treatment planning of gastric cancer.</p> <p>Results</p> <p>Analysis of 358 respondents (91%) showed variations between each specialization and from the recommended guidelines in the management approaches to specific clinical scenarios. The majority of specialists admitted that less than 50% of patients received multidisciplinary evaluation before treatment. The participants gave different responses to questions involving adjuvant, neoadjuvant, and advanced settings, compared to the recommended guidelines.</p> <p>Conclusions</p> <p>These results highlight the heterogeneity of the treatment of gastric cancer. Surgical oncologists, medical oncologists, and radiation oncologists are not adhering to the recommended guidelines.</p

Electric Vehicle Fire Trace Recognition Based on Multi-Task Semantic Segmentation

Conflagration is the major safety issue of electric vehicles (EVs). Due to their well-kept appearance and structure, which demonstrate salient visual changes after combustion, EV bodies are recognized as an important basis for on-spot inspection of burnt EVs and make application using semantic segmentation possible. The combination of deep learning-based semantic segmentation and recognition of visual traces of burnt EVs would provide preliminary analytical results of fire spread trends and output status descriptions of burnt EVs for further investigation. In this paper, a dataset of image traces of burnt EVs was built, and a two-branch network structure that splits the whole task into two sub-tasks separately concentrated on foreground extraction and severity segmentation is proposed. The proposed network is trained on the dataset via the transfer learning method and is tested using 5-fold cross validation. The foreground extraction branch achieved a mean intersection over union (mIoU) of 95.16% in the burnt EV foreground extraction task, and the burnt severity branch achieved a mIoU of 66.96% for the severity segmentation task. By jointly training two branches and applying a foreground mask to 3-class severity output, the mIoU was improved to 68.92%