PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction

Semantic segmentation in autonomous driving has been undergoing an evolution from sparse point segmentation to dense voxel segmentation, where the objective is to predict the semantic occupancy of each voxel in the concerned 3D space. The dense nature of the prediction space has rendered existing efficient 2D-projection-based methods (e.g., bird's eye view, range view, etc.) ineffective, as they can only describe a subspace of the 3D scene. To address this, we propose a cylindrical tri-perspective view to represent point clouds effectively and comprehensively and a PointOcc model to process them efficiently. Considering the distance distribution of LiDAR point clouds, we construct the tri-perspective view in the cylindrical coordinate system for more fine-grained modeling of nearer areas. We employ spatial group pooling to maintain structural details during projection and adopt 2D backbones to efficiently process each TPV plane. Finally, we obtain the features of each point by aggregating its projected features on each of the processed TPV planes without the need for any post-processing. Extensive experiments on both 3D occupancy prediction and LiDAR segmentation benchmarks demonstrate that the proposed PointOcc achieves state-of-the-art performance with much faster speed. Specifically, despite only using LiDAR, PointOcc significantly outperforms all other methods, including multi-modal methods, with a large margin on the OpenOccupancy benchmark. Code: https://github.com/wzzheng/PointOcc.Comment: Code is available at https://github.com/wzzheng/PointOc

The Role of Iron, Its Metabolism and Ferroptosis in Traumatic Brain Injury

Traumatic brain injury (TBI) is a structural and physiological disruption of brain function caused by external forces. It is a major cause of death and disability for patients worldwide. TBI includes both primary and secondary impairments. Iron overload and ferroptosis highly involved in the pathophysiological process of secondary brain injury. Ferroptosis is a form of regulatory cell death, as increased iron accumulation in the brain leads to lipid peroxidation, reactive oxygen species (ROS) production, mitochondrial dysfunction and neuroinflammatory responses, resulting in cellular and neuronal damage. For this reason, eliminating factors like iron deposition and inhibiting lipid peroxidation may be a promising therapy. Iron chelators can be used to eliminate excess iron and to alleviate some of the clinical manifestations of TBI. In this review we will focus on the mechanisms of iron and ferroptosis involving the manifestations of TBI, broaden our understanding of the use of iron chelators for TBI. Through this review, we were able to better find novel clinical therapeutic directions for further TBI study

A Systematic Evaluation of Federated Learning on Biomedical Natural Language Processing

Language models (LMs) like BERT and GPT have revolutionized natural language processing (NLP). However, privacy-sensitive domains, particularly the medical field, face challenges to train LMs due to limited data access and privacy constraints imposed by regulations like the Health Insurance Portability and Accountability Act (HIPPA) and the General Data Protection Regulation (GDPR). Federated learning (FL) offers a decentralized solution that enables collaborative learning while ensuring the preservation of data privacy. In this study, we systematically evaluate FL in medicine across $2$ biomedical NLP tasks using $6$ LMs encompassing $8$ corpora. Our results showed that: 1) FL models consistently outperform LMs trained on individual client's data and sometimes match the model trained with polled data; 2) With the fixed number of total data, LMs trained using FL with more clients exhibit inferior performance, but pre-trained transformer-based models exhibited greater resilience. 3) LMs trained using FL perform nearly on par with the model trained with pooled data when clients' data are IID distributed while exhibiting visible gaps with non-IID data. Our code is available at: https://github.com/PL97/FedNLPComment: Accepted by KDD 2023 Workshop FL4Data-Minin

Post-Failure Behavior of Point-Fixing Laminated Glass Plates under Out-of-Plane Uniform Pressure

This paper presents the results of an experimental and numerical investigation of the mechanical response of undamaged and damaged 2-ply laminated glass plates. Two types of glass plies, thermally toughened and heat-strengthened, coupled with SentryGlas (SG) were considered. Laminated glass plates supported with articulated point fixing bolt under out-of-plane uniform pressure were investigated under four different damage configurations: (i) undamaged; (ii) partially damaged, with the bottom ply broken; (iii) partially damaged, over-flipping the specimen of mode II; (iv) both two glass plies broken, which was applicable for LG plates made by heat-strengthened glass. In the above four modes, the top ply is always subjected to compression while the bottom one is in tension. The different responses of each configuration (different glass types and damage modes) were discussed and compared in this study. In addition, numerical models were adopted to reproduce the experimental results. The influence of the hitting location and glass types on the mechanical behavior of LG plates was analyzed. The results showed that the contribution of the broken glass ply could not be disregarded in the evaluation of the global stiffness of partially damaged LG plates and their bearing capacity

Peixin Yang's Economic thought and its Outcomes in the 1980s, Early in China's Reform, and China's Reform Miracle

During the initial period of reform, China's prudent handling of the money—price relationship while simultaneously bringing inflation and unemployment under control had a far-reaching influence on economic theory as well as practical significance. The country's successful experience constituted a miracle beyond the dreams of authoritative international financial authorities and experts. The famous American Nobel Prize winner, the economist Milton Friedman, once said that anyone who could explain China's success could win the Nobel Prize. In today's complex world, with its recurrent financial turmoil and intensified threat of war, China's successful experience in the early phases of reform has important significance for developing socialism with Chinese characteristics and maintaining the country's economic and financial security and the interests of the great mass of the people. We should sum up this experience to strengthen confidence in our institutions, our path, and our theory

A Review of Reinforcement Learning for Natural Language Processing, and Applications in Healthcare

Reinforcement learning (RL) has emerged as a powerful approach for tackling complex medical decision-making problems such as treatment planning, personalized medicine, and optimizing the scheduling of surgeries and appointments. It has gained significant attention in the field of Natural Language Processing (NLP) due to its ability to learn optimal strategies for tasks such as dialogue systems, machine translation, and question-answering. This paper presents a review of the RL techniques in NLP, highlighting key advancements, challenges, and applications in healthcare. The review begins by visualizing a roadmap of machine learning and its applications in healthcare. And then it explores the integration of RL with NLP tasks. We examined dialogue systems where RL enables the learning of conversational strategies, RL-based machine translation models, question-answering systems, text summarization, and information extraction. Additionally, ethical considerations and biases in RL-NLP systems are addressed

Fault Separation Based on An Excitation Operator with Application to a Quadrotor UAV

This paper presents an excitation operator based fault separation architecture for a quadrotor unmanned aerial vehicle (UAV) subject to loss of effectiveness (LoE) faults, actuator aging, and load uncertainty. The actuator fault dynamics is deeply excavated, containing the deep coupling information among the actuator faults, the system states, and control inputs. By explicitly considering the physical constraints and tracking performance, an excitation operator and corresponding integrated state observer are designed to estimate separately actuator fault and load uncertainty. Moreover, a fault separation maneuver and a safety controller are proposed to ensure the tracking performance when the excitation operator is injected. Both comparative simulation and flight experiments have demonstrated the effectiveness of the proposed scheme while maintaining high levels of tracking performance