Gen-LaneNet: A Generalized and Scalable Approach for 3D Lane Detection

We present a generalized and scalable method, called Gen-LaneNet, to detect 3D lanes from a single image. The method, inspired by the latest state-of-the-art 3D-LaneNet, is a unified framework solving image encoding, spatial transform of features and 3D lane prediction in a single network. However, we propose unique designs for Gen-LaneNet in two folds. First, we introduce a new geometry-guided lane anchor representation in a new coordinate frame and apply a specific geometric transformation to directly calculate real 3D lane points from the network output. We demonstrate that aligning the lane points with the underlying top-view features in the new coordinate frame is critical towards a generalized method in handling unfamiliar scenes. Second, we present a scalable two-stage framework that decouples the learning of image segmentation subnetwork and geometry encoding subnetwork. Compared to 3D-LaneNet, the proposed Gen-LaneNet drastically reduces the amount of 3D lane labels required to achieve a robust solution in real-world application. Moreover, we release a new synthetic dataset and its construction strategy to encourage the development and evaluation of 3D lane detection methods. In experiments, we conduct extensive ablation study to substantiate the proposed Gen-LaneNet significantly outperforms 3D-LaneNet in average precision(AP) and F-score

Anisotropic linear and nonlinear charge-spin conversion in topological semimetal SrIrO3

Over the past decade, utilizing spin currents in the linear response of electric field to manipulate magnetization states via spin-orbit torques (SOTs) is one of the core concepts for realizing a multitude of spintronic devices. Besides the linear regime, recently, nonlinear charge-spin conversion under the square of electric field has been recognized in a wide variety of materials with nontrivial spin textures, opening an emerging field of nonlinear spintronics. Here, we report the investigation of both linear and nonlinear charge-spin conversion in one single topological semimetal SrIrO3(110) thin film that hosts strong spin-orbit coupling and nontrivial spin textures in the momentum space. In the nonlinear regime, the observation of crystalline direction dependent response indicates the presence of anisotropic surface states induced spin-momentum locking near the Fermi level. Such anisotropic spin textures also give rise to spin currents in the linear response regime, which mainly contributes to the fieldlike SOT component. Our work demonstrates the power of combination of linear and nonlinear approaches in understanding and utilizing charge-spin conversion in topological materials.Comment: 18 pages, 5 figure

Deciphering the phase transition-induced ultrahigh piezoresponse in (K,Na)NbO3_{3}-based piezoceramics

Here, we introduce phase change mechanisms in lead-free piezoceramics as a strategy to utilize attendant volume change for harvesting large electrostrain. In the newly developed (K,Na)NbO$_{3}$ solid-solution at the polymorphic phase boundary we combine atomic mapping of the local polar vector with in situ synchrotron X-ray diffraction and density functional theory to uncover the phase change and interpret its underlying nature. We demonstrate that an electric field-induced phase transition between orthorhombic and tetragonal phases triggers a dramatic volume change and contributes to a huge effective piezoelectric coefficient of 1250 pm V$^{-1}$ along specific crystallographic directions. The existence of the phase transition is validated by a significant volume change evidenced by the simultaneous recording of macroscopic longitudinal and transverse strain. The principle of using phase transition to promote electrostrain provides broader design flexibility in the development of high-performance piezoelectric materials and opens the door for the discovery of high-performance future functional oxides

An Assessment of Multimodel Simulations for the Variability of Western North Pacific Tropical Cyclones and Its Association with ENSO

An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño–Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation. Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño—namely, eastern Pacific (EP) and central Pacific (CP) El Niño—and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño

The North American Multi-Model Ensemble (NMME): Phase-1 Seasonal to Interannual Prediction, Phase-2 Toward Developing Intra-Seasonal Prediction

The recent US National Academies report "Assessment of Intraseasonal to Interannual Climate Prediction and Predictability" was unequivocal in recommending the need for the development of a North American Multi-Model Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multi-model ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation, and has proven to produce better prediction quality (on average) then any single model ensemble. This multi-model approach is the basis for several international collaborative prediction research efforts, an operational European system and there are numerous examples of how this multi-model ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test Bed (CTB) NMME workshops (February 18, and April 8, 2011) a collaborative and coordinated implementation strategy for a NMME prediction system has been developed and is currently delivering real-time seasonal-to-interannual predictions on the NOAA Climate Prediction Center (CPC) operational schedule. The hindcast and real-time prediction data is readily available (e.g., http://iridl.ldeo.columbia.edu/SOURCES/.Models/.NMME/) and in graphical format from CPC (http://origin.cpc.ncep.noaa.gov/products/people/wd51yf/NMME/index.html). Moreover, the NMME forecast are already currently being used as guidance for operational forecasters. This paper describes the new NMME effort, presents an overview of the multi-model forecast quality, and the complementary skill associated with individual models

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Understanding Hydrothermal Dechlorination of PVC by Focusing on the Operating Conditions and Hydrochar Characteristics

To remove chlorine from chlorinated wastes efficiently, the hydrothermal treatment (HT) of PVC was investigated with a lower alkaline dosage in this work. Some typical operating conditions were investigated to find out the most important factor affecting the dechlorination efficiency (DE). The FTIR technique was employed to detect the functional groups in PVC and hydrochars generated to reveal the possible pathways for chlorine removal. The results show that the HT temperature was a key parameter to control the dechlorination reaction rate. At a HT temperature of 240 °C, about 94.3% of chlorine could be removed from the PVC with 1% NaOH. The usage of NaOH was helpful for chlorine removal, while a higher dosage might also hinder this process because of the surface poisoning and coverage of free sites. To some extent, the DE was increased with the residence time. At a residence time of 30 min, the DE reached a maximum of 76.74%. A longer residence time could promote the generation of pores in hydrochar which is responsible for the reduction in DE because of the re-absorption of water-soluble chlorine. According to the FTIR results, the peak intensities of both C=CH and C=C stretching vibrations in hydrochar were increased, while the peak at around 3300 cm−1 representing the –OH group was not obvious, indicating that the dehydrochlorination (elimination reaction) was a main route for chlorine removal under these conditions studied in this work

Tar In-situ Conversion for Biomass Gasification via Mixing-simulation with Rice Husk Char-supported Catalysts

AbstractThis paper initially proposed a catalytic pyrolysis technology for tar conversion using the rice husk char (RHC) and rice husk ash (RHA) supported nickel-iron catalyst during biomass pyrolysis/gasification. Biomass tar could be in-situ transformed effectively in the gasifer by co-pyrolysis with the RHC/RHA supported catalysts at 800 oC, simplifying the follow-up tar elimination process. Under the optimized conditions, the tar conversion efficiency can reach about 92.3% using the Ni-Fe char (namely RHC Ni-Fe, without calcination), which exhibited more advantages of convenient and energy-saving. Significantly, the partial metal oxides (e.g., NiO) in char matrix could be in-situ deoxidized by reducing gases (e.g., H2, CO) or carbon atoms into the metallic status (e.g., Ni0), enhancing the catalytic performance of tar conversion. In addition, mixing with other solid particles (e.g., sand, RHC/RHA supported catalysts) can improve biomass (e.g., RH) fluidization behavior by optimizing the operation parameters (e.g., particle size, mass fraction) in the mode of fluidized bed gasifier (FBG). After the solid-solid mixing simulation, the RH mass fraction of 0.5 and the particle diameter of 0.5mm can be employed in the binary mixture of RH and RHC/RHA

Measurement of Soot Volume Fraction and Temperature for Oxygen-Enriched Ethylene Combustion Based on Flame Image Processing

A method for simultaneously visualizing the two-dimensional distributions of temperature and soot volume fraction in an ethylene flame was presented. A single-color charge-coupled device (CCD) camera was used to capture the flame image in the visible spectrum considering the broad-response spectrum of the R and G bands of the camera. The directional emissive power of the R and G bands were calibrated and used for measurement. Slightly increased temperatures and reduced soot concentration were predicted in the central flame without self-absorption effects considered, an iterative algorithm was used for eliminating the effect of self-absorption. Nine different cases were presented in the experiment to demonstrate the effects of fuel mass flow rate and oxygen concentration on temperature and soot concentration in three different atmospheres. For ethylene combustion in pure-air atmosphere, as the fuel mass flow rate increased, the maximum temperature slightly decreased, and the maximum soot volume fraction slightly increased. For oxygen fractions of 30%, 40%, and 50% combustion in O2/N2 oxygen-enhanced atmospheres, the maximum flame temperatures were 2276, 2451, and 2678 K, whereas combustion in O2/CO2 atmospheres were 1916, 2322, and 2535 K. The maximum soot volume fractions were 4.5, 7.0, and 9.5 ppm in oxygen-enriched O2/N2 atmosphere and 13.6, 15.3, and 14.8 ppm in oxygen-enriched O2/CO2 atmosphere. Compared with the O2/CO2 atmosphere, combustion in the oxygen-enriched O2/N2 atmosphere produced higher flame temperature and larger soot volume fraction. Preliminary results indicated that this technique is reliable and can be used for combustion diagnosis