TrafficNet: An Open Naturalistic Driving Scenario Library

The enormous efforts spent on collecting naturalistic driving data in the recent years has resulted in an expansion of publicly available traffic datasets, which has the potential to assist the development of the self-driving vehicles. However, we found that many of the attempts to utilize these datasets have failed in practice due to a lack of usability concern from the organizations that host these collected data. For example, extracting data associated with certain critical conditions from naturalistic driving data organized in chronological order may not be convenient for a vehicle engineer that doesn't have big data analytics experiences. To address the general usability challenges of these publicly available traffic datasets, we propose TrafficNet, a large-scale and extensible library of naturalistic driving scenarios, aiming at bridging the gap between research datasets and practically usable information for vehicle engineers and researchers. The proposed web-based driving scenario database preprocesses massive raw traffic data collected in chronological order into an organized scenario-based dataset by applying a set of categorization algorithms to label the naturalistic driving data with six different critical driving scenarios. TrafficNet opens not only the scenario library but also the source code of these categorization methods to the public, which will foster more sophisticated and accurate scenario-based categorization algorithms to advance the intelligent transportation research. The source code and the scenario database can be accessed at https://github.com/TrafficNet.Comment: IEEE 20th International Conference on Intelligent Transportatio

Towards Secure and Safe Appified Automated Vehicles

The advancement in Autonomous Vehicles (AVs) has created an enormous market for the development of self-driving functionalities,raising the question of how it will transform the traditional vehicle development process. One adventurous proposal is to open the AV platform to third-party developers, so that AV functionalities can be developed in a crowd-sourcing way, which could provide tangible benefits to both automakers and end users. Some pioneering companies in the automotive industry have made the move to open the platform so that developers are allowed to test their code on the road. Such openness, however, brings serious security and safety issues by allowing untrusted code to run on the vehicle. In this paper, we introduce the concept of an Appified AV platform that opens the development framework to third-party developers. To further address the safety challenges, we propose an enhanced appified AV design schema called AVGuard, which focuses primarily on mitigating the threats brought about by untrusted code, leveraging theory in the vehicle evaluation field, and conducting program analysis techniques in the cybersecurity area. Our study provides guidelines and suggested practice for the future design of open AV platforms

Tracing blastomere fate choices of early embryos in single cell culture

Blastomeres of early vertebrate embryos undergo numerous fate choices for division, motility, pluripotency maintenance and restriction culminating in various cell lineages. Tracing blastomere fate choices at the single cell level in vitro has not been possible because of the inability to isolate and cultivate early blastomeres as single cells. Here we report the establishment of single cell culture system in the fish medaka, enabling the isolation and cultivation of individual blastomeres from 16- to 64-cell embryos for fate tracing at the single cell level in vitro. Interestingly, these blastomeres immediately upon isolation exhibit motility, lose synchronous divisions and even stop dividing in ≥50% cases, suggesting that the widely accepted nucleocytoplasmic ratio controlling synchronous divisions in entire embryos does not operate on individual blastomeres. We even observed abortive division, endomitosis and cell fusion. Strikingly, ~5% of blastomeres in single cell culture generated extraembryonic yolk syncytial cells, embryonic stem cells and neural crest-derived pigment cells with timings mimicking their appearance in embryos. We revealed the maternal inheritance of key lineage regulators and their differential expression in cleavage embryos. Therefore, medaka blastomeres possess the accessibility for single cell culture, previously unidentified heterogeneity in motility, division, gene expression and intrinsic ability to generate major extraembryonic and embryonic lineages without positioning cues. Our data demonstrate the fidelity and potential of the single cell culture system for tracking blastomere fate decisions under defined conditions in vitro

Prevention of growth failure caused by glucocorticoid treatment

Children with chronic inflammation often suffer from growth failure and many of these children are treated with high doses of glucocorticoids (GCs). However, the underlying mechanisms of growth failure under conditions of chronic inflammation and the relative contributions of inflammation per se and commonly used GC treatment are still unknown. Existing treatments of chronic inflammatory conditions are often associated with various side including bone growth impairment. Therefore, new treatment strategies preventing growth failure in these children are ultimately needed. Humanin is a protective protein locally produced in various tissues with the capacity to defend cells from undesired cell death and many other cytotoxic agents. It has been reported that humanin exerts its anti-apoptotic action by interacting with Bax and interestingly, ablation of Bax in mice can protect against GC-induced bone growth impairment. This thesis aimed to investigate the molecular mechanisms of GC-induced growth failure under conditions of chronic inflammation and if humanin and its analogue HNG have the potential to prevent growth failure caused by GC treatment. In study I, we investigated the relative contributions of GC treatment and the inflammation per se to the growth failure commonly seen in conditions of chronic inflammation. In a transgenic mouse line (huTNFTg) over-expressing human TNF, we first observed that bone growth and growth plate chondrogenesis were suppressed by TNF overexpression. To investigate the effects of GCs on bone growth and growth plate chondrogenesis in a condition of chronic inflammation, huTNFTg mice were treated with saline or dexamethasone. Interestingly, dexamethasone then further suppressed bone growth, predominantly by accelerating apoptosis in the growth plate causing chondrocyte columns to become more disorganized. In study II, we assessed the potential for humanin and its analogues HNG to prevent growth failure caused by GCs. We discovered that humanin is expressed in growth plate cartilage and humanin over-expressing mice (HNtg) were resistant to GC-induced bone growth impairment. Treatment with the humanin analogue HNG prevented GC-induced bone growth retardation in cultured fetal rat metatarsal bones and also in vivo in mice. Mechanistic studies showed that humanin overexpression or HNG treatment prevented GC-induced apoptosis in vitro and in vivo, and humanin/HNG were found to be a novel regulator of Hh signalling. Importantly, HNG did not interfere with the anti-inflammatory effects of GCs. In study III, a link between humanin regulation and chronic inflammation per se was identified. We found that serum humanin levels were decreased in IBD children with known poor bone health. Mechanistic studies in ex vivo cultured human growth plate cartilage showed suppressed endogenous humanin expression in tissues exposed to IBD serum or the pro-inflammatory cytokine TNF. Interestingly, we also observed that the expression of PCNA, SOX-9 and TNF Receptor Associated Factor 2 (TRAF2) were decreased in human growth plates exposed to TNF. In conclusion, our results show that GCs and inflammation per se can suppress chondrogenesis and bone growth separately, and that humanin and its analogue HNG could could offer a novel strategy to rescue bone growth impairment caused by GC treatment in children. In addition, we propose a direct link between chronic inflammation and humanin regulation, a novel finding of potential clinical significance

Leveraging Depth for 3D Scene Perception

3D scene perception aims to understand the geometric and semantic information of the surrounding environment. It is crucial in many downstream applications, such as autonomous driving, robotics, AR/VR, and human-computer interaction. Despite its significance, understanding the 3D scene has been a challenging task, due to the complex interactions between objects, heavy occlusions, cluttered indoor environments, major appearance, viewpoint and scale changes, etc. The study of 3D scene perception has been significantly reshaped by the powerful deep learning models. These models are capable of leveraging large-scale training data to achieve outstanding performance. Learning-based models unlock new challenges and opportunities in the field.In this dissertation, we first present learning-based approaches to estimate depth maps, one of the crucial information in many 3D scene perception models. We describe two overlooked challenges in learning monocular depth estimators and present our proposed solutions. Specifically, we address the high-level domain gap between real and synthetic training data and the shift in camera pose distribution between training and testing data. Following that we present two application-driven works that leverage depth maps to achieve better 3D scene perception. We explore in detail the tasks of reference-based image inpainting and 3D object instance tracking in scenes from egocentric videos

Roaring tiger or bounce tigger? : examining corruption seriousness perception in China from a socio-cultural perspective

Recent years have witnessed a steadily increasing scholarly interest in perceptions of corruption, particularly in terms of level and prevalence. However, previous studies have largely overlooked perceived seriousness as another unique dimension of corruption perception. Furthermore, previous studies seeking causes of corruption perception have failed to consider cultural factors at either the individual or aggregate level as potential predictors. To fill the gap, the current dissertation employs the 2014 Chinese Family Panel Studies and other relevant data to explore the relationships between corruption seriousness perception and cultural factors. This dissertation strategically examines two individual cultural attachments (i.e., Confucianism and Legalism attachments) and an overarching socio-cultural context (i.e., structural anomie). In addition to their direct effects, this research also explores potential indirect effects of structural anomie and its effect as a moderator. Using cluster robust-standard errors modeling, this dissertation finds that 1) stronger attachments to Confucianism and Legalism increase corruption seriousness perception; 2) structural anomie reduces corruption seriousness perception indirectly via decreased Legalism attachment; 3) structural anomie works as a moderator to attenuate the effect of Confucianism attachment. Research and policy implications are discussed. The dissertation concludes with a discussion on possible directions future research on corruption perception could take