ADriver-I: A General World Model for Autonomous Driving

Typically, autonomous driving adopts a modular design, which divides the full stack into perception, prediction, planning and control parts. Though interpretable, such modular design tends to introduce a substantial amount of redundancy. Recently, multimodal large language models (MLLM) and diffusion techniques have demonstrated their superior performance on comprehension and generation ability. In this paper, we first introduce the concept of interleaved vision-action pair, which unifies the format of visual features and control signals. Based on the vision-action pairs, we construct a general world model based on MLLM and diffusion model for autonomous driving, termed ADriver-I. It takes the vision-action pairs as inputs and autoregressively predicts the control signal of the current frame. The generated control signals together with the historical vision-action pairs are further conditioned to predict the future frames. With the predicted next frame, ADriver-I performs further control signal prediction. Such a process can be repeated infinite times, ADriver-I achieves autonomous driving in the world created by itself. Extensive experiments are conducted on nuScenes and our large-scale private datasets. ADriver-I shows impressive performance compared to several constructed baselines. We hope our ADriver-I can provide some new insights for future autonomous driving and embodied intelligence.Comment: Tech Repor

Panacea: Panoramic and Controllable Video Generation for Autonomous Driving

The field of autonomous driving increasingly demands high-quality annotated training data. In this paper, we propose Panacea, an innovative approach to generate panoramic and controllable videos in driving scenarios, capable of yielding an unlimited numbers of diverse, annotated samples pivotal for autonomous driving advancements. Panacea addresses two critical challenges: 'Consistency' and 'Controllability.' Consistency ensures temporal and cross-view coherence, while Controllability ensures the alignment of generated content with corresponding annotations. Our approach integrates a novel 4D attention and a two-stage generation pipeline to maintain coherence, supplemented by the ControlNet framework for meticulous control by the Bird's-Eye-View (BEV) layouts. Extensive qualitative and quantitative evaluations of Panacea on the nuScenes dataset prove its effectiveness in generating high-quality multi-view driving-scene videos. This work notably propels the field of autonomous driving by effectively augmenting the training dataset used for advanced BEV perception techniques.Comment: Project page: https://panacea-ad.github.io

Dynamics and Drivers of the Alpine Timberline on Gongga Mountain of Tibetan Plateau-Adopted from the Otsu Method on Google Earth Engine

The alpine timberline, an ecosystem ecotone, indicates climatic change and is tending to shift toward higher altitudes because of an increase in global warming. However, spatiotemporal variations of the alpine timberline are not consistent on a global scale. The abundant and highest alpine timberline, located on the Tibetan Plateau, is less subject to human activity and disturbance. Although many studies have investigated the alpine timberline on the Tibetan Plateau, large-scale monitoring of spatial-temporal dynamics and driving mechanisms of the alpine timberline remain uncertain and inaccurate. Hence, the Gongga Mountain on the southeastern Tibetan Plateau was chosen as the study area because of the most complete natural altitudinal zonation. We used the Otsu method on Google Earth Engine to extract the alpine timberline from 1987–2019 based on the normalized difference vegetation index (NDVI). Then, the alpine timberline spatiotemporal patterns and the effect of topography on alpine timberline distribution were explored. Four hillsides on the western Gongga Mountain were selected to examine the hillside differences and drivers of the alpine timberline based on principal component analysis (PCA) and multiple linear regression (MLR). The results indicated that the elevation range of alpine timberline was 3203–4889 m, and the vegetation coverage increased significantly (p < 0.01) near the alpine timberline ecotone on Gongga Mountain. Moreover, there was spatial heterogeneity in dynamics of alpine timberline, and some regions showed no regular trend in variations. The spatial pattern of the alpine timberline was generally high in the west, low in the east, and primarily distributed on 15–55° slopes. Besides, the drivers of the alpine timberline have the hillside differences, and the sunny and shady slopes possessed different driving factors. Thus, our results highlight the effects of topography and climate on the alpine timberline on different hillsides. These findings could provide a better approach to study the dynamics and formation of alpine timberlines

Dynamics and controls of ecosystem multiserviceability across the Qingzang Plateau

Ecosystem multiserviceability (EMS), a comprehensive and significant ecological indicator, reflects the capacity of ecosystems to offer multiple services concurrently. Intensified climate change and human activity are continuously altering ecosystem functions, services, and EMSs. However, numerous studies have only focused on one or a few ecosystem services, rarely taking into account spatial-temporal distribution and drivers of EMS on behalf of different agencies. We calculated EMS including pastoralist (PA), environmental protection agency (EPA), biodiversity conservation agency (BCA), and climate change mitigation agency (CCMA) using grassland production, habitat quality, water conservation, and carbon sequestration. Then, the effects of geographical features, climate factors, and human activities on spatial-temporal patterns of EMS were explored. The result indicated that EMS showed a decreasing tendency from the southeast to northwest on the Qingzang Plateau (QZP). Meanwhile, there were no obvious fluctuations in four simulated scenarios (PA, EPA, BCA and CCMA) among different vegetation types during 2000 to 2015. Notably, EMS of all simulated scenarios decreased in the alpine steppe ecosystem, but negligible changes were found in other ecosystems from 2015 to 2020. Moreover, the relative importance of precipitation in annual mean value (from 2000 to 2020) of PA, EPA, BCA and CCMA were 0.13, 0.11, 0.30 and 0.19, respectively. Overall, precipitation played the dominant role on the dynamics of EMS, followed by elevation and human footprint. Our findings highlighted that understanding the patterns and drivers of EMS could provide a reference for the regional management and maintenance of ecosystem stability on QZP

SIAP: an intelligent algorithm for multiple prescription pattern recognition based on weighted similarity distances

Abstract Background Clinical practices have demonstrated that disease treatment can be very complex. Patients with chronic diseases often suffer from more than one disease. Complex diseases are often treated with a variety of drugs, including both primary and auxiliary treatments. This complexity and multidimensionality increase the difficulty of extracting knowledge from clinical data. Methods In this study, we proposed a subgroup identification algorithm for complex prescriptions (SIAP). We applied the SIAP algorithm to identify the importance level of each drug in complex prescriptions. The algorithm quickly classified and determined valid prescription combinations for patients. The algorithm was validated through classification matching of classical prescriptions in traditional Chinese medicine. We collected 376 formulas and their compositions from a formulary to construct a database of standard prescriptions. We also collected 1438 herbal prescriptions from clinical data for automated prescription identification. The prescriptions were divided into training and test sets. Finally, the parameters of the two sub-algorithms of SIAP and SIAP-All, as well as those of the combination algorithm SIAP + All, were optimized on the training set. A comparison analysis was performed against the baseline intersection set rate (ISR) algorithm. The algorithm for this study was implemented with Python 3.6. Results The SIAP-All and SIAP + All algorithms outperformed the benchmark ISR algorithm in terms of accuracy, recall, and F1 value. The F1 values were 0.7568 for SIAP-All and 0.7799 for SIAP + All, showing improvements of 8.73% and 11.04% over the existing ISR algorithm, respectively. Conclusion We developed an algorithm, SIAP, to automatically match sub-prescriptions of complex drugs with corresponding standard or classic prescriptions. The matching algorithm weights the drugs in the prescription according to their importance level. The results of this study can help to classify and analyse the drug compositions of complex prescriptions

Dynamic Recrystallization Behavior and Corrosion Resistance of a Dual-Phase Mg-Li Alloy

The hot deformation and dynamic recrystallization behavior of the dual-phase Mg-9Li-3Al-2Sr-2Y alloy had been investigated using a compression test. The typical dual-phase structure was observed, and average of grain size of as-homogenized alloy is about 110 µm. It mainly contains β-Li, α-Mg, Al4Sr and Al2Y phases. The dynamic recrystallization (DRX) kinetic was established based on an Avrami type equation. The onset of the DRX process occurred before the peak of the stress–strain flow curves. It shows that the DRX volume fraction increases with increasing deformation temperature or decreasing strain rate. The microstructure evolution during the hot compression at various temperatures and strain rates had been investigated. The DRX grain size became larger with the increasing testing temperature or decreasing strain rate because the higher temperature or lower strain rate can improve the migration of DRX grain boundaries. The fully recrystallized microstructure can be achieved in a small strain due to the dispersed island-shape α-Mg phases, continuous the Al4Sr phases and spheroidal Al2Y particles, which can accelerate the nucleation. The continuous Al4Sr phases along the grain boundaries are very helpful for enhancing the corrosion resistance of the duplex structured Mg-Li alloy, which can prevent the pitting corrosion and filiform corrosion

Risk factors associated with 31-day unplanned readmission in 50,912 discharged patients after stroke in China

Abstract Background Unplanned readmission within 31 days of discharge after stroke is a useful indicator for monitoring quality of hospital care. We evaluated the risk factors associated with 31-day unplanned readmission of stroke patients in China. Methods We identified 50,912 patients from 375 hospitals in 29 provinces, municipalities or autonomous districts across China who experienced an unplanned readmission after stroke between 2015 and 2016, and extracted data from the inpatients’ cover sheet data from the Medical Record Monitoring Database. Patients were grouped into readmission within 31 days or beyond for analysis. Chi-squared test was used to analyze demographic information, health system and clinical process-related factors according to the data type. Multilevel logistic modeling was used to examine the effects of patient (level 1) and hospital (level 2) characteristics on an unplanned readmission ≤31 days. Results Among 50,912 patients, 14,664 (28.8%) were readmitted within 31 days after discharge. The commonest cause of readmissions were recurrent stroke (34.8%), hypertension (22.94%), cardio/cerebrovascular disease (13.26%) and diabetes/diabetic complications (7.34%). Higher risks of unplanned readmissions were associated with diabetes (OR = 1.089, P = 0.001), use of clinical pathways (OR = 1.174, P < 0.001), and being discharged without doctor’s advice (OR = 1.485, P < 0.001). Lower risks were associated with basic medical insurances (OR ranging from 0.225 to 0.716, P < 0.001) and commercial medical insurance (OR = 0.636, P = 0.021), compared to self-paying for medical services. And patients aged 50 years old and above (OR ranging from 0.650 to 0.985, P < 0.05), with haemorrhagic stroke (OR = 0.467, P < 0.001), with length of stay more than 7 days in hospital (OR ranging from 0.082 to 0.566, P < 0.001), also had lower risks. Conclusions Age, type of stroke, medical insurance status, type of discharge, use of clinical pathways, length of hospital stay and comorbidities were the most influential factors for readmission within 31 days