Safety-driven Interactive Planning for Neural Network-based Lane Changing

Neural network-based driving planners have shown great promises in improving task performance of autonomous driving. However, it is critical and yet very challenging to ensure the safety of systems with neural network based components, especially in dense and highly interactive traffic environments. In this work, we propose a safety-driven interactive planning framework for neural network-based lane changing. To prevent over conservative planning, we identify the driving behavior of surrounding vehicles and assess their aggressiveness, and then adapt the planned trajectory for the ego vehicle accordingly in an interactive manner. The ego vehicle can proceed to change lanes if a safe evasion trajectory exists even in the predicted worst case; otherwise, it can stay around the current lateral position or return back to the original lane. We quantitatively demonstrate the effectiveness of our planner design and its advantage over baseline methods through extensive simulations with diverse and comprehensive experimental settings, as well as in real-world scenarios collected by an autonomous vehicle company

TAE: A Semi-supervised Controllable Behavior-aware Trajectory Generator and Predictor

Trajectory generation and prediction are two interwoven tasks that play important roles in planner evaluation and decision making for intelligent vehicles. Most existing methods focus on one of the two and are optimized to directly output the final generated/predicted trajectories, which only contain limited information for critical scenario augmentation and safe planning. In this work, we propose a novel behavior-aware Trajectory Autoencoder (TAE) that explicitly models drivers' behavior such as aggressiveness and intention in the latent space, using semi-supervised adversarial autoencoder and domain knowledge in transportation. Our model addresses trajectory generation and prediction in a unified architecture and benefits both tasks: the model can generate diverse, controllable and realistic trajectories to enhance planner optimization in safety-critical and long-tailed scenarios, and it can provide prediction of critical behavior in addition to the final trajectories for decision making. Experimental results demonstrate that our method achieves promising performance on both trajectory generation and prediction.Comment: an updated version, change figures and references. 8 pages, robotics conference, about trajectory augmentation and prediction for intelligent vehicle system

Example-based image colorization using locality consistent sparse representation

—Image colorization aims to produce a natural looking color image from a given grayscale image, which remains a challenging problem. In this paper, we propose a novel examplebased image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target grayscale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target grayscale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms state-ofthe-art methods, both visually and quantitatively using a user stud

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Development Of An On-line Adaptive ANN-based Controller For A Direct Expansion Air Conditioning System

An on-line adaptive artificial neural network (ANN)-based controller has been developed for an experimental DX A/C system. It controls the indoor air temperature and humidity simultaneously by varying the compressor speed and supply fan speed in a space served by the experimental DX A/C system. The ANN-based direct inverse control (DIC) strategy was adopted in the development of the controller and the specialized training method was used to on-line update an ANN-based model and an inverse model used in the controller. The controllability tests including the command following test and the disturbance rejection test were carried out using the experimental DX A/C system, and the test results showed that the on-line adaptive ANN-based controller developed was able to control indoor air dry-bulb temperature and wet-bulb temperature outside the operating conditions within which the models were trained, with a high control accuracy

Advances and Prospects of Information Extraction from Point Clouds

Point cloud is one type of the widely used data sources in many communities such as photogrammetry, remote sensing, and computer vision etc. Moreover, information extraction is a necessary step in the process of point cloud processing, analysis and applications. As result, the scholars have proposed a great number of methods for point cloud information extraction. According to the three view points of primitive types, extracted features, and methods for feature selection and classification, this review paper summarizes the research status of point cloud information extraction. This paper also point out five main problems and six main trends in point cloud information extraction, especially introduces a new paradigm:fusion of multiple primitives for point cloud information extraction

A Study on Ginseng Price Fluctuations in China and South Korea

China and South Korea are the main producers and exporters of ginseng. This paper mainly discusses the characteristics of ginseng price fluctuations in China and South Korea. As people continue to understand the concept of homology of medicine and food, there is still an increasing international demand for ginseng, and the favorable market can be expected

IFN-α as an Adjuvant for Adenovirus-Vectored FMDV Subunit Vaccine through Improving the Generation of T Follicular Helper Cells.

IFN-α exhibits either direct antiviral effects or distinct immunomodulatory properties, which was identified as a 'natural immune adjuvant' for both the innate and the adaptive immune responses. Here we have investigated the effects of IFN-α as an adjuvant on the generation of T follicular helper (Tfh) cells and antigen-specific antibody responses. The data showed that adenoviral vectors co-expressing FMDV VP1 proteins and porcine IFN-α potently enhanced the generation of Tfh cells, the secretion of IL-21 protein and the expression of Bcl-6 mRNA, compared with adenoviral vectors sole expressing VP1 alone. Additionally, IFN-α substantial increased the number of germinal-center (GC) B cells and formation of GCs. Furthermore, IFN-α enhanced the antibody response, as shown by increased production of all IgG and subclasses of IgG1 and IgG2a. Thus, our results revealed the potent adjuvant activity of IFN-α which enhanced the generation of Tfh cells and regulated the humoral immunity by promoting germinal-center reactions and antibody responses

α-Fe2O3/Reduced Graphene Oxide Composites as Cost-Effective Counter Electrode for Dye-Sensitized Solar Cells

The counter electrode (CE) is an important and vital part of dye-sensitized solar cells (DSSCs). Pt CEs show high-performance in DSSCs using iodide-based electrolytes. However, the high cost of Pt CEs restricts their large-scale application in DSSCs and the development of Pt-free CE is expected. Here, α-Fe2O3/reduced graphene oxide (α-Fe2O3/RGO) composites are prepared as the Pt-free CE materials for DSSCs. A simple hydrothermal technique was used to disseminate the α-Fe2O3 solid nanoparticles uniformly throughout the RGO surface. The presence of the α-Fe2O3 nanoparticles increases the specific surface area of RGO and allows the composites to be porous, which improves the diffusion of liquid electrolyte into the CE material. Then, the electrocatalytic properties of CEs with α-Fe2O3/RGO, α-Fe2O3, RGO, and Pt materials are compared. The α-Fe2O3/RGO CE has a similar electrocatalytic performance to Pt CE, which is superior to those of the pure α-Fe2O3 and RGO CEs. After being fabricated as DSSCs, the current–voltage measurements reveal that the DSSC based on α-Fe2O3/RGO CE has a power conversion efficiency (PCE) of 6.12%, which is 88% that of Pt CE and much higher than that of pure α-Fe2O3 and pure RGO CEs. All the results show that this work describes a promising material for cost-effective, Pt-free CEs for DSSCs