RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions

The recent advances in camera-based bird's eye view (BEV) representation exhibit great potential for in-vehicle 3D perception. Despite the substantial progress achieved on standard benchmarks, the robustness of BEV algorithms has not been thoroughly examined, which is critical for safe operations. To bridge this gap, we introduce RoboBEV, a comprehensive benchmark suite that encompasses eight distinct corruptions, including Bright, Dark, Fog, Snow, Motion Blur, Color Quant, Camera Crash, and Frame Lost. Based on it, we undertake extensive evaluations across a wide range of BEV-based models to understand their resilience and reliability. Our findings indicate a strong correlation between absolute performance on in-distribution and out-of-distribution datasets. Nonetheless, there are considerable variations in relative performance across different approaches. Our experiments further demonstrate that pre-training and depth-free BEV transformation has the potential to enhance out-of-distribution robustness. Additionally, utilizing long and rich temporal information largely helps with robustness. Our findings provide valuable insights for designing future BEV models that can achieve both accuracy and robustness in real-world deployments.Comment: Preprint; 27 pages, 18 figures, 33 tables; Code at https://github.com/Daniel-xsy/RoboBE

Robo3D: Towards Robust and Reliable 3D Perception against Corruptions

The robustness of 3D perception systems under natural corruptions from environments and sensors is pivotal for safety-critical applications. Existing large-scale 3D perception datasets often contain data that are meticulously cleaned. Such configurations, however, cannot reflect the reliability of perception models during the deployment stage. In this work, we present Robo3D, the first comprehensive benchmark heading toward probing the robustness of 3D detectors and segmentors under out-of-distribution scenarios against natural corruptions that occur in real-world environments. Specifically, we consider eight corruption types stemming from adversarial weather conditions, external disturbances, and internal sensor failure. We uncover that, although promising results have been progressively achieved on standard benchmarks, state-of-the-art 3D perception models are at risk of being vulnerable to corruptions. We draw key observations on the use of data representations, augmentation schemes, and training strategies, that could severely affect the model's performance. To pursue better robustness, we propose a density-insensitive training framework along with a simple flexible voxelization strategy to enhance the model resiliency. We hope our benchmark and approach could inspire future research in designing more robust and reliable 3D perception models. Our robustness benchmark suite is publicly available.Comment: 33 pages, 26 figures, 26 tables; code at https://github.com/ldkong1205/Robo3D project page at https://ldkong.com/Robo3

Rethinking China's new great wall

China’s position as the world’s second largest economy is largely due to its rapid economic growth in the coastal region, which composes only 13% of China’s total land area, yet contributes 60% of the gross domestic product (GDP). To create extra land for the rapidly growing economy, coastal wetlands have been enclosed by thousands of kilometers of seawalls, whose length exceeds that of China’s famous ancient “Great Wall” (see photos and map). This new “Great Wall,” covering 60% of the total length of coast-line along mainland China ( 1), caused a dramatic decline in internationally shared biodiversity and associated ecosystem services and will threaten regional ecological security and sustainable development. Here, we outline these problems, analyze the drivers behind wetland reclamation, and propose measures for effective wetland management

Synchronous multimode ultrasound for assessing right-to-left shunt: a prospective clinical study

BackgroundRight-to-left shunt (RLS) is associated with several conditions and causes morbidity. In this study, we aimed to evaluate the effectiveness of synchronous multimode ultrasonography in detecting RLS.MethodsWe prospectively enrolled 423 patients with high clinical suspicion of RLS and divided them into the contrast transcranial Doppler (cTCD) group and synchronous multimode ultrasound group, in which both cTCD and contrast transthoracic echocardiography (cTTE) were performed during the same process of contrast-enhanced ultrasound imaging. The simultaneous test results were compared with those of cTCD alone.ResultsThe positive rates of grade II (22.0%:10.0%) and III (12.7%:10.8%) shunts and the total positive rate (82.1748%) in the synchronous multimode ultrasound group were higher than those in the cTCD alone group. Among patients with RLS grade I in the synchronous multimode ultrasound group, 23 had RLS grade I in cTCD but grade 0 in synchronous cTTE, whereas four had grade I in cTCD but grade 0 in synchronous cTTE. Among patients with RLS grade II in the synchronous multimode ultrasound group, 28 had RLS grade I in cTCD but grade II in synchronous cTTE. Among patients with RLS grade III in the synchronous multimode ultrasound group, four had RLS grade I in cTCD but grade III in synchronous cTTE. Synchronous multimode ultrasound had a sensitivity of 87.5% and specificity of 60.6% in the patent foramen ovale (PFO) diagnosis. Binary logistic regression analyses showed that age (odds ratio [OR] = 1.041) and risk of paradoxical embolism score ≥ 7 (OR = 7.798) were risk factors for stroke recurrence, whereas antiplatelets (OR = 0.590) and PFO closure with antiplatelets (OR = 0.109) were protective factors.ConclusionSynchronous multimodal ultrasound significantly improves the detection rate and test efficiency, quantifies RLS more accurately, and reduces testing risks and medical costs. We conclude that synchronous multimodal ultrasound has significant potential for clinical applications

Régularisation spatiale de représentations distribuées de mots

Stimulée par l’usage intensif des téléphones mobiles, l’exploitation conjointe des don-nées textuelles et des données spatiales présentes dans les objets spatio-textuels (p. ex. tweets)est devenue la pierre angulaire à de nombreuses applications comme la recherche de lieux d’attraction. Du point de vue scientifique, ces tâches reposent de façon critique sur la représentation d’objets spatiaux et la définition de fonctions d’appariement entre ces objets. Dans cet article,nous nous intéressons au problème de représentation de ces objets. Plus spécifiquement, confortés par le succès des représentations distribuées basées sur les approches neuronales, nous proposons de régulariser les représentations distribuées de mots (c.-à-d. plongements lexicaux ou word embeddings), pouvant être combinées pour construire des représentations d’objets,grâce à leurs répartitions spatiales. L’objectif sous-jacent est de révéler d’éventuelles relations sémantiques locales entre mots ainsi que la multiplicité des sens d’un même mot. Les expérimentations basées sur une tâche de recherche d’information qui consiste à retourner le lieu physique faisant l’objet (sujet) d’un géo-texte montrent que l’intégration notre méthode de régularisation spatiale de représentations distribuées de mots dans un modèle d’appariement de base permet d’obtenir des améliorations significatives par rapport aux modèles de référence

Transient-spatial pattern mining of eddy current pulsed thermography using wavelet transform

Eddy current pulsed thermography(ECPT) is an emerging Non-destructive testing and evaluation(NDT & E) technique, which uses hybrid eddy current and thermography NDT & E techniques that enhances the detectability from their compensation. Currently, this technique is limited by the manual selection of proper contrast frames and the issue of improving the efficiency of defect detection of complex structure samples remains a challenge. In order to select a specific frame from transient thermal image sequences to maximize the contrast of thermal variation and defect pattern from complex structure samples, an energy driven approach to compute the coefficient energy of wavelet transform is proposed which has the potential of automatically selecting both optimal transient frame and spatial scale for defect detection using ECPT. According to analysis of the variation of different frequency component and the comparison study of the detection performance of different scale and wavelets, the frame at the end of heating phase is automatically selected as an optimal transient frame for defect detection. In addition, the detection capabilities of the complex structure samples can be enhanced through proper spatial scale and wavelet selection. The proposed method has successfully been applied to low speed impact damage detection of carbon fibre reinforced polymer(CFRP) composite as well as providing the guidance to improve the detectability of ECPT technique

Serum Biomarker Identification by Mass Spectrometry in Acute Aortic Dissection

Background/Aims: Aortic dissection (AD) is also known as intramural hematoma. This study aimed to screen peripheral blood biomarkers of small molecule metabolites for AD using high-performance liquid chromatography-mass spectrometry (HPLC-MS). Methods: Sera from 25 healthy subjects, 25 patients with well-established AD, and 25 patients with well-established hypertension were investigated by HPLC-MS to detect metabolites, screen differentially expressed metabolites, and analyze metabolic pathways. Results: Twenty-six and four metabolites were significantly up- and down-regulated in the hypertensive patients compared with the healthy subjects; 165 metabolites were significantly up-regulated and 109 significantly down-regulated in the AD patients compared with the hypertensive patients. Of these metabolites, 35 were up-regulated and 105 down-regulated only in AD patients. The metabolites that were differentially expressed in AD are mainly involved in tryptophan, histidine, glycerophospholipid, ether lipid, and choline metabolic pathways. As AD alters the peripheral blood metabolome, analysis of peripheral blood metabolites can be used in auxiliary diagnosis of AD. Conclusion: Eight metabolites are potential biomarkers for AD, 3 of which were differentially expressed and can be used for auxiliary diagnosis of AD and evaluation of treatment effectiveness

Glucose to Platelet Ratio: A Potential Predictor of Hemorrhagic Transformation in Patients with Acute Ischemic Stroke

Glucose and platelet are two easily obtained clinical indicators; the present research aimed to demonstrate their association with hemorrhagic transformation (HT) in acute ischemic stroke (AIS) patients without thrombolytic or thrombectomy therapy. This was a single-center retrospective study. Patients who were diagnosed with HT after AIS were included in the HT group. Meanwhile, using the propensity score matching (PSM) approach, with a ratio of 1:2, matched patients without HT were included in the non-HT group. Serum G/P levels were measured on the first morning after admission (at least eight hours after the last meal). Characteristics were compared between the two groups. Multivariate logistic regression was used to determine the independent relationship between G/P and HT after AIS, with G/P being divided into quartiles. From January 2013 to March 2022, we consecutively included 643 AIS patients with HT (426/643 [66.25%] with HI and 217/643 [33.75%] with PH), and 1282 AIS patients without HT, at the First Affiliated Hospital of Wenzhou Medical University. The HT group had higher G/P levels than the non-HT group (0.04 ± 0.02 vs. 0.03 ± 0.02, p < 0.001). However, there was no difference in G/P levels between HI and PH subgroups (0.04 ± 0.02 vs. 0.04 ± 0.02, p > 0.05). Moreover, the G/P levels were divided into quartiles (Q1 ≤ 0.022; Q2 = 0.023–0.028; Q3 = 0.029–0.039; Q4 ≥ 0.040), with Q1 being settled as the reference layer. After controlling the confounders, multivariate regression analyses showed that the Q4 layer (Q4: G/P ≥ 0.040) was independently associated with elevated HT risk (odds ratio [OR] = 1.85, 95% CI = 1.31–2.63, p < 0.001). G/P levels on admission were independently associated with HT risk in AIS patients. In clinical practice, adequate attention should be paid to AIS patients with elevated G/P levels (G/P ≥ 0.040)