Learning Residual Model of Model Predictive Control via Random Forests for Autonomous Driving

One major issue in learning-based model predictive control (MPC) for autonomous driving is the contradiction between the system model's prediction accuracy and computation efficiency. The more situations a system model covers, the more complex it is, along with highly nonlinear and nonconvex properties. These issues make the optimization too complicated to solve and render real-time control impractical.To address these issues, we propose a hierarchical learning residual model which leverages random forests and linear regression.The learned model consists of two levels. The low level uses linear regression to fit the residues, and the high level uses random forests to switch different linear models. Meanwhile, we adopt the linear dynamic bicycle model with error states as the nominal model.The switched linear regression model is added to the nominal model to form the system model. It reformulates the learning-based MPC as a quadratic program (QP) problem and optimization solvers can effectively solve it. Experimental path tracking results show that the driving vehicle's prediction accuracy and tracking accuracy are significantly improved compared with the nominal MPC.Compared with the state-of-the-art Gaussian process-based nonlinear model predictive control (GP-NMPC), our method gets better performance on tracking accuracy while maintaining a lower computation consumption.Comment: 8 pages, 8 figure

Membrane Contact Demulsification: A Superhydrophobic ZIF-8@rGO Membrane for Water-in-Oil Emulsion Separation

Achieving a water–oil interface imbalance has been identified as a critical factor in the demulsification of water-in-oil emulsions. However, conventional demulsifying membranes generally break the interface balance by depending on a relatively high transmembrane pressure. Here, we present a “contact demulsification” concept to naturally and quickly achieve disruption of the water–oil interface balance. For this purpose, a novel demulsifying membrane with a high flux of the organic component has been developed via the simple vacuum assembly of zeolitic imidazolate framework-8 (ZIF-8)@reduced graphene oxide (rGO) microspheres (ZGS) on a polytetrafluoroethylene (PTFE) support, followed by immobilization processing in a polydimethylsiloxane (PDMS) crosslinking solution. Due to the micro-nano hierarchies of the ZGS, the prepared ZIF-8@rGO@PDMS/PTFE (ZGPP) membranes feature a unique superhydrophobic surface, which results in a water–oil interface imbalance when a surfactant-stabilized water-in-oil emulsion comes into contact with the membrane surface. Under a low transmembrane pressure of 0.15 bar (15 kPa), such membranes show an excellent separation efficiency (∼99.57%) and a high flux of 2254 L·m−2·h−1, even for surfactant-stabilized nanoscale water-in-toluene emulsions (with an average droplet size of 57 nm). This “contact demulsification” concept paves the way for developing next-generation demulsifying membranes for water-in-oil emulsion separation

Characterization of Shiga toxin-producing Escherichia coli isolated from healthy pigs in China

BACKGROUND: Shiga toxin-producing Escherichia coli (STEC) is recognized as an important human diarrheal pathogen. Swine plays an important role as a carrier of this pathogen. In this study we determined the prevalence and characteristics of STEC from healthy swine collected between May 2011 and August 2012 from 3 cities/provinces in China. RESULTS: A total of 1003 samples, including 326 fecal, 351 small intestinal contents and 326 colon contents samples, was analyzed. Two hundred and fifty five samples were stx-positive by PCR and 93 STEC isolates were recovered from 62 stx-positive samples. Twelve O serogroups and 19 O:H serotypes including 6 serotypes (O100:H20/[H20], O143:H38/[H38], O87:H10, O172:H30/[H30], O159:H16, O9:H30/[H30]) rarely found in swine and ruminants were identified. All 93 STEC isolates harbored stx(2) only, all of which were stx(2e) subtype including 1 isolate being a new variant of stx(2e). 53.76%, 15.05% and 2.15% STEC isolates carried astA, hlyA and ehxA respectively. Four STEC isolates harbored the high-pathogenicity island. Of the 15 adherence-associated genes tested, 13 (eae, efa1, iha, lpfA(O113), lpfA(O157/OI-154), lpfA(O157/OI-141), toxB, saa, F4, F5, F6, F17 or F41) were all absent while 2 (paa and F18) were present in 7 and 4 STEC isolates respectively. The majority of the isolates were resistant to tetracycline (79.57%), nalidixic acid (78.49%), trimethoprim-sulfamethoxazole (73.12%) and kanamycin (55.91%). The STEC isolates were divided into 63 pulsed-field gel electrophoresis patterns and 21 sequence types (STs). Isolates of the same STs generally showed the same or similar drug resistance patterns. A higher proportion of STEC isolates from Chongqing showed multidrug resistance with one ST (ST3628) resistant to 14 antimicrobials. CONCLUSIONS: Our results indicate that swine is a significant reservoir of STEC strains in China. Based on comparison by serotypes and sequence types with human strains and presence of virulence genes, the swine STEC may have a low potential to cause human disease

The Photoperiod-Insensitive Allele Ppd-D1a Promotes Earlier Flowering in Rht12 Dwarf Plants of Bread Wheat

The gibberellin-responsive dwarfing gene Rht12 can significantly reduce plant height without changing seedling vigor and substantially increase ear fertility in bread wheat (Triticum aestivum. L). However, Rht12 delays heading date and anthesis date, hindering the use of Rht12 in wheat improvement. To promote early flowering of the Rht12 dwarf plants, the photoperiod-insensitive allele Ppd-D1a was introduced through a cross between Jinmai47 (Ppd-D1a) and Karcagi (Rht12). The results showed that Ppd-D1a can rescue the delaying effect of Rht12 on flowering time and promote earlier flowering by 9.0 days (163.2°Cd) in the Rht12 dwarf plants by shortening the late reproduction phase. Plant height was reduced by Rht12 (43.2%) and Ppd-D1a (10.9%), achieving dwarf plants with higher lodging resistance. Ear fertility, like the grain number per spike, was significantly increased by Rht12 (21.3%), while it was reduced by Ppd-D1a (6.5%). However, thousand kernel weight was significantly reduced by Rht12 (12.9%) but significantly increased by Ppd-D1a (16.9%). Finally, plant yield was increased by 16.4 and 8.2%, and harvest index was increased by 24.9 and 15.4% in the Rht12 dwarf lines and tall lines with Ppd-D1a, respectively. Clearly, there was an additive interaction between Rht12 and Ppd-D1 and the introduction of Ppd-D1a advanced the flowering time and improved the yield traits of Rht12 dwarf plants, suggesting that the combination of Rht12 and Ppd-D1a would be conducive to the successful use of Rht12 in wheat breeding programs

A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

Simulation Analysis of Tilted Polyhedron-Shaped Thermoelectric Elements

The generation of thermoelectricity is considered a promising approach to harness the waste heat generated in industries, automobiles, gas fields, and other man-made processes. The waste heat can be converted to electricity via a thermoelectric (TE) generator. In this light, the generator performance depends on the geometric configuration of its constituent elements as well as their material properties. Our previous work reported TE behaviors for modules consisting of parallelogram-shaped elements, because elements with tilted laminate structures provide increased mechanical stability and efficient heat-transferring ability from the hot surface to the cold surface. Here, we study TE elements in the shape of a polyhedron that is obtained by mechanically truncating the edges of a parallelogram element in order to further enhance the generator performance and reduce TE material usage. The TE performance of the modules consisting of these polyhedron elements is numerically simulated by using the finite-volume method. The output power, voltage, and current of the polyhedral TE module are greater than those of the parallelogram-element module. The polyhedron shape positively affects heat transfer and the flow of electric charges in the light of increasing the efficiency of conversion from heat to electricity. By varying the shape of the truncated portions, we determine the optimal shape that enables homogeneous heat flux distribution and slow diffusion of thermal energy to obtain the better efficiency of conversion of heat into electricity. We believe that the findings of our study can significantly contribute to the design policy in TE generation

Cross-Scale Modeling of MnS Precipitation for Steel Solidification

One of the advantages of numerical simulations over traditional experimental methodologies is that they can synchronize nucleation, growth and coarsening during solidification from the point of view of microstructural analysis. However, the computational cost and accuracy are bottlenecks restricting simulation approaches. Here, two cellular automaton (CA) modules with different grid dimensions are coupled to form a cross-scale model in order to simulate MnS precipitation, accompanied by the matrix growth of dendrites during the solidification of a Fe-C-Mn-S steel, where the matrix growth is computed through the CA module with large grids based on the solute conservation and the undercooling of thermal, constitutional, and curvature, and increments of solid fraction of MnS are solved in combination with the transient thermodynamic equilibrium on the locally re-meshed grids once the MnS precipitation is formed. We utilize the cross-scale mode to illustrate MnS evolution in a solidifying matrix and explain the reason why it coexists in three shapes. Further, we study the effects of the content of elements Mn and S on MnS precipitation based on two continuously cast steel objects, with the factor of concentration product fixed as a constant. A re-precipitation of MnS is observed during the solidification of a system with a high content of Mn and low content of S. Simultaneous computation using cross-scale modeling can effectively save on computational resources, and the simulation results agree well with the experimental cases, which confirm its reliable accuracy

Thermoelectric Analysis for Helical Power Generation Systems

The performance of a three-dimensional helical thermoelectric generation (TEG) system is examined by exposing it to a temperature difference with hot and cold sources. The helical paths for the two thermal fluids give the TEG device the potential to efficiently convert thermal energy. The characteristic performance of the helical system is numerically analyzed by using the finite-volume method in a compact system. The helical system is compared with a straight system in which all the thermoelectric (TE) elements present equivalent geometry. The difference in the TE performance between the two systems is not significant when the TE surfaces are maintained at constant temperatures. Both the electromotive force and the current in the TEG system increase linearly with the temperature difference Delta T applied at the two module surfaces. The current preferentially flows through a main path determined by the geometry of the TE element. The merits of the helical design are its compactness, space saving, and smooth fluid flow due to gravity, compared with the straight system