Vehicle Dynamics Modeling for Autonomous Racing Using Gaussian Processes

Autonomous racing is increasingly becoming a proving ground for autonomous vehicle technology at the limits of its current capabilities. The most prominent examples include the F1Tenth racing series, Formula Student Driverless (FSD), Roborace, and the Indy Autonomous Challenge (IAC). Especially necessary, in high speed autonomous racing, is the knowledge of accurate racecar vehicle dynamics. The choice of the vehicle dynamics model has to be made by balancing the increasing computational demands in contrast to improved accuracy of more complex models. Recent studies have explored learning-based methods, such as Gaussian Process (GP) regression for approximating the vehicle dynamics model. However, these efforts focus on higher level constructs such as motion planning, or predictive control and lack both in realism and rigor of the GP modeling process, which is often over-simplified. This paper presents the most detailed analysis of the applicability of GP models for approximating vehicle dynamics for autonomous racing. In particular we construct dynamic, and extended kinematic models for the popular F1TENTH racing platform. We investigate the effect of kernel choices, sample sizes, racetrack layout, racing lines, and velocity profiles on the efficacy and generalizability of the learned dynamics. We conduct 400+ simulations on real F1 track layouts to provide comprehensive recommendations to the research community for training accurate GP regression for single-track vehicle dynamics of a racecar.Comment: 12 pages, 6 figures, 10 table

Understanding the role of metakaolin towards mitigating the shrinkage behavior of alkali-activated slag

This research investigates the mechanism of metakaolin for mitigating the autogenous and drying shrinkages of alkali-activated slag with regard to the activator parameters, including concentration and modulus. The results indicate that the incorporation of metakaolin can decrease the initial viscosity and setting time. Increasing activator concentration can promote the reaction process and shorten the setting time. An increase in the metakaolin content induces a decrease in compressive strength due to reduced formation of reaction products. However, increasing activator dosage and modulus can improve the compressive strength of alkali-activated slag containing 30% metakaolin. The inclusion of metakaolin can mitigate the autogenous and drying shrinkage of alkali-activated slag by coarsening the pore structure. On the other hand, increases in activator concentration and modulus result in an increase in magnitude of the autogenous and drying shrinkage of alkali-activated slag containing metakaolin. The influence of the activator modulus on the shrinkage behavior of alkali-activated slag-metakaolin binary system should be further investigated

Lighting-Up Tumor for Assisting Resection via Spraying NIR Fluorescent Probe of γ-Glutamyltranspeptidas

For the precision resection, development of near-infrared (NIR) fluorescent probe based on specificity identification tumor-associated enzyme for lighting-up the tumor area, is urgent in the field of diagnosis and treatment. Overexpression of γ-glutamyltranspeptidase, one of the cell-membrane enzymes, known as a biomarker is concerned with the growth and progression of ovarian, liver, colon and breast cancer compared to normal tissue. In this work, a remarkable enzyme-activated NIR fluorescent probe NIR-SN-GGT was proposed and synthesized including two moieties: a NIR dicyanoisophorone core as signal reporter unit; γ-glutamyl group as the specificity identification site. In the presence of γ-GGT, probe NIR-SN-GGT was transformed into NIR-SN-NH2, the recovery of Intramolecular Charge Transfer (ICT), liberating the NIR fluorescence signal, which was firstly employed to distinguish tumor tissue and normal tissues via simple “spraying” manner, greatly promoting the possibility of precise excision. Furthermore, combined with magnetic resonance imaging by T2 weight mode, tumor transplanted BABL/c mice could be also lit up for first time by NIR fluorescence probe having a large stokes, which demonstrated that probe NIR-SN-GGT would be a useful tool for assisting surgeon to diagnose and remove tumor in clinical practice

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Rest of authors: Decky Junaedi, Robert R. Junker, Eric Justes, Richard Kabzems, Jeffrey Kane, Zdenek Kaplan, Teja Kattenborn, Lyudmila Kavelenova, Elizabeth Kearsley, Anne Kempel, Tanaka Kenzo, Andrew Kerkhoff, Mohammed I. Khalil, Nicole L. Kinlock, Wilm Daniel Kissling, Kaoru Kitajima, Thomas Kitzberger, Rasmus Kjøller, Tamir Klein, Michael Kleyer, Jitka Klimešová, Joice Klipel, Brian Kloeppel, Stefan Klotz, Johannes M. H. Knops, Takashi Kohyama, Fumito Koike, Johannes Kollmann, Benjamin Komac, Kimberly Komatsu, Christian König, Nathan J. B. Kraft, Koen Kramer, Holger Kreft, Ingolf Kühn, Dushan Kumarathunge, Jonas Kuppler, Hiroko Kurokawa, Yoko Kurosawa, Shem Kuyah, Jean-Paul Laclau, Benoit Lafleur, Erik Lallai, Eric Lamb, Andrea Lamprecht, Daniel J. Larkin, Daniel Laughlin, Yoann Le Bagousse-Pinguet, Guerric le Maire, Peter C. le Roux, Elizabeth le Roux, Tali Lee, Frederic Lens, Simon L. Lewis, Barbara Lhotsky, Yuanzhi Li, Xine Li, Jeremy W. Lichstein, Mario Liebergesell, Jun Ying Lim, Yan-Shih Lin, Juan Carlos Linares, Chunjiang Liu, Daijun Liu, Udayangani Liu, Stuart Livingstone, Joan Llusià, Madelon Lohbeck, Álvaro López-García, Gabriela Lopez-Gonzalez, Zdeňka Lososová, Frédérique Louault, Balázs A. Lukács, Petr Lukeš, Yunjian Luo, Michele Lussu, Siyan Ma, Camilla Maciel Rabelo Pereira, Michelle Mack, Vincent Maire, Annikki Mäkelä, Harri Mäkinen, Ana Claudia Mendes Malhado, Azim Mallik, Peter Manning, Stefano Manzoni, Zuleica Marchetti, Luca Marchino, Vinicius Marcilio-Silva, Eric Marcon, Michela Marignani, Lars Markesteijn, Adam Martin, Cristina Martínez-Garza, Jordi Martínez-Vilalta, Tereza Mašková, Kelly Mason, Norman Mason, Tara Joy Massad, Jacynthe Masse, Itay Mayrose, James McCarthy, M. Luke McCormack, Katherine McCulloh, Ian R. McFadden, Brian J. McGill, Mara Y. McPartland, Juliana S. Medeiros, Belinda Medlyn, Pierre Meerts, Zia Mehrabi, Patrick Meir, Felipe P. L. Melo, Maurizio Mencuccini, Céline Meredieu, Julie Messier, Ilona Mészáros, Juha Metsaranta, Sean T. Michaletz, Chrysanthi Michelaki, Svetlana Migalina, Ruben Milla, Jesse E. D. Miller, Vanessa Minden, Ray Ming, Karel Mokany, Angela T. Moles, Attila Molnár V, Jane Molofsky, Martin Molz, Rebecca A. Montgomery, Arnaud Monty, Lenka Moravcová, Alvaro Moreno-Martínez, Marco Moretti, Akira S. Mori, Shigeta Mori, Dave Morris, Jane Morrison, Ladislav Mucina, Sandra Mueller, Christopher D. Muir, Sandra Cristina Müller, François Munoz, Isla H. Myers-Smith, Randall W. Myster, Masahiro Nagano, Shawna Naidu, Ayyappan Narayanan, Balachandran Natesan, Luka Negoita, Andrew S. Nelson, Eike Lena Neuschulz, Jian Ni, Georg Niedrist, Jhon Nieto, Ülo Niinemets, Rachael Nolan, Henning Nottebrock, Yann Nouvellon, Alexander Novakovskiy, The Nutrient Network, Kristin Odden Nystuen, Anthony O'Grady, Kevin O'Hara, Andrew O'Reilly-Nugent, Simon Oakley, Walter Oberhuber, Toshiyuki Ohtsuka, Ricardo Oliveira, Kinga Öllerer, Mark E. Olson, Vladimir Onipchenko, Yusuke Onoda, Renske E. Onstein, Jenny C. Ordonez, Noriyuki Osada, Ivika Ostonen, Gianluigi Ottaviani, Sarah Otto, Gerhard E. Overbeck, Wim A. Ozinga, Anna T. Pahl, C. E. Timothy Paine, Robin J. Pakeman, Aristotelis C. Papageorgiou, Evgeniya Parfionova, Meelis Pärtel, Marco Patacca, Susana Paula, Juraj Paule, Harald Pauli, Juli G. Pausas, Begoña Peco, Josep Penuelas, Antonio Perea, Pablo Luis Peri, Ana Carolina Petisco-Souza, Alessandro Petraglia, Any Mary Petritan, Oliver L. Phillips, Simon Pierce, Valério D. Pillar, Jan Pisek, Alexandr Pomogaybin, Hendrik Poorter, Angelika Portsmuth, Peter Poschlod, Catherine Potvin, Devon Pounds, A. Shafer Powell, Sally A. Power, Andreas Prinzing, Giacomo Puglielli, Petr Pyšek, Valerie Raevel, Anja Rammig, Johannes Ransijn, Courtenay A. Ray, Peter B. Reich, Markus Reichstein, Douglas E. B. Reid, Maxime Réjou-Méchain, Victor Resco de Dios, Sabina Ribeiro, Sarah Richardson, Kersti Riibak, Matthias C. Rillig, Fiamma Riviera, Elisabeth M. R. Robert, Scott Roberts, Bjorn Robroek, Adam Roddy, Arthur Vinicius Rodrigues, Alistair Rogers, Emily Rollinson, Victor Rolo, Christine Römermann, Dina Ronzhina, Christiane Roscher, Julieta A. Rosell, Milena Fermina Rosenfield, Christian Rossi, David B. Roy, Samuel Royer-Tardif, Nadja Rüger, Ricardo Ruiz-Peinado, Sabine B. Rumpf, Graciela M. Rusch, Masahiro Ryo, Lawren Sack, Angela Saldaña, Beatriz Salgado-Negret, Roberto Salguero-Gomez, Ignacio Santa-Regina, Ana Carolina Santacruz-García, Joaquim Santos, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Matthias Schleuning, Bernhard Schmid, Marco Schmidt, Sylvain Schmitt, Julio V. Schneider, Simon D. Schowanek, Julian Schrader, Franziska Schrodt, Bernhard Schuldt, Frank Schurr, Galia Selaya Garvizu, Marina Semchenko, Colleen Seymour, Julia C. Sfair, Joanne M. Sharpe, Christine S. Sheppard, Serge Sheremetiev, Satomi Shiodera, Bill Shipley, Tanvir Ahmed Shovon, Alrun Siebenkäs, Carlos Sierra, Vasco Silva, Mateus Silva, Tommaso Sitzia, Henrik Sjöman, Martijn Slot, Nicholas G. Smith, Darwin Sodhi, Pamela Soltis, Douglas Soltis, Ben Somers, Grégory Sonnier, Mia Vedel Sørensen, Enio Egon Sosinski Jr, Nadejda A. Soudzilovskaia, Alexandre F. Souza, Marko Spasojevic, Marta Gaia Sperandii, Amanda B. Stan, James Stegen, Klaus Steinbauer, Jörg G. Stephan, Frank Sterck, Dejan B. Stojanovic, Tanya Strydom, Maria Laura Suarez, Jens-Christian Svenning, Ivana Svitková, Marek Svitok, Miroslav Svoboda, Emily Swaine, Nathan Swenson, Marcelo Tabarelli, Kentaro Takagi, Ulrike Tappeiner, Rubén Tarifa, Simon Tauugourdeau, Cagatay Tavsanoglu, Mariska te Beest, Leho Tedersoo, Nelson Thiffault, Dominik Thom, Evert Thomas, Ken Thompson, Peter E. Thornton, Wilfried Thuiller, Lubomír Tichý, David Tissue, Mark G. Tjoelker, David Yue Phin Tng, Joseph Tobias, Péter Török, Tonantzin Tarin, José M. Torres-Ruiz, Béla Tóthmérész, Martina Treurnicht, Valeria Trivellone, Franck Trolliet, Volodymyr Trotsiuk, James L. Tsakalos, Ioannis Tsiripidis, Niklas Tysklind, Toru Umehara, Vladimir Usoltsev, Matthew Vadeboncoeur, Jamil Vaezi, Fernando Valladares, Jana Vamosi, Peter M. van Bodegom, Michiel van Breugel, Elisa Van Cleemput, Martine van de Weg, Stephni van der Merwe, Fons van der Plas, Masha T. van der Sande, Mark van Kleunen, Koenraad Van Meerbeek, Mark Vanderwel, Kim André Vanselow, Angelica Vårhammar, Laura Varone, Maribel Yesenia Vasquez Valderrama, Kiril Vassilev, Mark Vellend, Erik J. Veneklaas, Hans Verbeeck, Kris Verheyen, Alexander Vibrans, Ima Vieira, Jaime Villacís, Cyrille Violle, Pandi Vivek, Katrin Wagner, Matthew Waldram, Anthony Waldron, Anthony P. Walker, Martyn Waller, Gabriel Walther, Han Wang, Feng Wang, Weiqi Wang, Harry Watkins, James Watkins, Ulrich Weber, James T. Weedon, Liping Wei, Patrick Weigelt, Evan Weiher, Aidan W. Wells, Camilla Wellstein, Elizabeth Wenk, Mark Westoby, Alana Westwood, Philip John White, Mark Whitten, Mathew Williams, Daniel E. Winkler, Klaus Winter, Chevonne Womack, Ian J. Wright, S. Joseph Wright, Justin Wright, Bruno X. Pinho, Fabiano Ximenes, Toshihiro Yamada, Keiko Yamaji, Ruth Yanai, Nikolay Yankov, Benjamin Yguel, Kátia Janaina Zanini, Amy E. Zanne, David Zelený, Yun-Peng Zhao, Jingming Zheng, Ji Zheng, Kasia Ziemińska, Chad R. Zirbel, Georg Zizka, Irié Casimir Zo-Bi, Gerhard Zotz, Christian Wirth.Max Planck Institute for Biogeochemistry; Max Planck Society; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig; International Programme of Biodiversity Science (DIVERSITAS); International Geosphere-Biosphere Programme (IGBP); Future Earth; French Foundation for Biodiversity Research (FRB); GIS ‘Climat, Environnement et Société'.http://wileyonlinelibrary.com/journal/gcbhj2021Plant Production and Soil Scienc

Active Calcium/Calmodulin-Dependent Protein Kinase II (CaMKII) Regulates NMDA Receptor Mediated Postischemic Long-Term Potentiation (i-LTP) by Promoting the Interaction between CaMKII and NMDA Receptors in Ischemia

Active calcium/calmodulin-dependent protein kinase II (CaMKII) has been reported to take a critical role in the induction of long-term potentiation (LTP). Changes in CaMKII activity were detected in various ischemia models. It is tempting to know whether and how CaMKII takes a role in NMDA receptor (NMDAR)-mediated postischemic long-term potentiation (NMDA i-LTP). Here, we monitored changes in NMDAR-mediated field excitatory postsynaptic potentials (NMDA fEPSPs) at different time points following ischemia onset in vitro oxygen and glucose deprivation (OGD) ischemia model. We found that 10 min OGD treatment induced significant i-LTP in NMDA fEPSPs, whereas shorter (3 min) or longer (25 min) OGD treatment failed to induce prominent NMDA i-LTP. CaMKII activity or CaMKII autophosphorylation displays a similar bifurcated trend at different time points following onset of ischemia both in vitro OGD or in vivo photothrombotic lesion (PT) models, suggesting a correlation of increased CaMKII activity or CaMKII autophosphorylation with NMDA i-LTP. Disturbing the association between CaMKII and GluN2B subunit of NMDARs with short cell-permeable peptides Tat-GluN2B reversed NMDA i-LTP induced by OGD treatment. The results provide support to a notion that increased interaction between NMDAR and CaMKII following ischemia-induced increased CaMKII activity and autophosphorylation is essential for induction of NMDA i-LTP

A focusing method on refraction topography measurement

Abstract This paper introduces a novel focusing method Refraction Topography (RT) for wide-angle refraction measurement. The agreement of the test results obtained using RT is evaluated against simulation results and expected refraction. RT develops a refraction algorithm on fundus images at various focusing statuses. Unlike conventional techniques for peripheral refraction measurement, RT requires the subject to stare at a stationary fixation target. The refraction algorithm calculates the focus measure for multiple images at the Point of Interest and formulates them into a focus profile. The maximum focus measure correlates with the optimal focus position. Refraction Characterization Function (RCF) is proposed to translate the focus position into refraction determination, thus forming the refraction topography. The refraction characterization of RT optical system is performed using Isabel schematic eye. Three test eyes of − 15 D, 0 D, and + 15 D are defined, and expected refraction is obtained through simulation on an independent test schematic eye. Both simulation results and experimental results are obtained by combining the test eyes and RT system. Test results are compared with simulation results and expected refraction. The study demonstrates agreement among the test results, simulation results, and expected refraction on three test eyes

Study of the Anti-Inflammatory Mechanism of β-Carotene Based on Network Pharmacology

β-carotene is known to have pharmacological effects such as anti-inflammatory, antioxidant, and anti-tumor properties. However, its main mechanism and related signaling pathways in the treatment of inflammation are still unclear. In this study, component target prediction was performed by using literature retrieval and the SwissTargetPrediction database. Disease targets were collected from various databases, including DisGeNET, OMIM, Drug Bank, and GeneCards. A protein–protein interaction (PPI) network was constructed, and enrichment analysis of gene ontology and biological pathways was carried out for important targets. The analysis showed that there were 191 unique targets of β-carotene after removing repeat sites. A total of 2067 targets from the three databases were integrated, 58 duplicate targets were removed, and 2009 potential disease action targets were obtained. Biological function enrichment analysis revealed 284 biological process (BP) entries, 31 cellular component (CC) entries, 55 molecular function (MF) entries, and 84 cellular pathways. The biological processes were mostly associated with various pathways and their regulation, whereas the cell components were mainly membrane components. The main molecular functions included RNA polymerase II transcription factor activity, DNA binding specific to the ligand activation sequence, DNA binding, steroid binding sequence-specific DNA binding, enzyme binding, and steroid hormone receptors. The pathways involved in the process included the TNF signaling pathway, sphingomyelin signaling pathway, and some disease pathways. Lastly, the anti-inflammatory signaling pathway of β-carotene was systematically analyzed using network pharmacology, while the molecular mechanism of β-carotene was further explored by molecular docking. In this study, the anti-inflammatory mechanism of β-carotene was preliminarily explored and predicted by bioinformatics methods, and further experiments will be designed to verify and confirm the predicted results, in order to finally reveal the anti-inflammatory mechanism of β-carotene

Soil Physicochemical Properties and the Rhizosphere Soil Fungal Community in a Mulberry (<i>Morus alba</i> L.)/Alfalfa (<i>Medicago sativa</i> L.) Intercropping System

A better understanding of soil fungal communities is very useful in revealing the effects of an agroforestry system and would also help us to understand the fungi-mediated effects of agricultural practices on the processes of soil nutrient cycling and crop productivity. Compared to conventional monoculture farming, agroforestry systems have obvious advantages in improving land use efficiency and maintaining soil physicochemical properties, reducing losses of water, soil material, organic matter, and nutrients, as well as ensuring the stability of yields. In this study, we attempted to investigate the impact of a mulberry/alfalfa intercropping system on the soil physicochemical properties and the rhizosphere fungal characteristics (such as the diversity and structure of the fungal community), and to analyze possible correlations among the planting pattern, the soil physicochemical factors, and the fungal community structure. In the intercropping and monoculture systems, we determined the soil physicochemical properties using chemical analysis and the fungal community structure with MiSeq sequencing of the fungal ITS1 region. The results showed that intercropping significantly improved the soil physicochemical properties of alfalfa (total nitrogen, alkaline hydrolysable nitrogen, available potassium, and total carbon contents). Sequencing results showed that the dominant taxonomic groups were Ascomycota, Basidiomycota, and Mucoromycota. Intercropping increased the fungal richness of mulberry and alfalfa rhizosphere soils and improved the fungal diversity of mulberry. The diversity and structure of the fungal community were predominantly influenced by both the planting pattern and soil environmental factors (total nitrogen, total phosphate, and total carbon). Variance partitioning analysis showed that the planting pattern explained 25.9% of the variation of the fungal community structure, and soil environmental factors explained 63.1% of the variation. Planting patterns and soil physicochemical properties conjointly resulted in changes of the soil fungal community structure in proportion

Research on the Influence of Weather Patterns on Ozone Concentration: A Case Study in Tianjin

Ozone (O3) is an important secondary substance that plays a significant role in atmospheric chemistry and climate change. Although O3 is essential in the stratosphere, it is harmful to human health in the troposphere, where this study was conducted. In recent years, O3 pollution in the Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) regions has deteriorated, which has become an important environmental problem. The generation of O3 is closely related to meteorological factors. In this study, the weather classification method was adopted to study the effect of meteorological conditions on O3 concentration. In the BTH region, Tianjin was selected as the representative city for the research. The real-time pollutants data, meteorological re-analysis data, and meteorological data in 2019 were combined for the analysis. The subjective weather classification method was adopted to investigate the effects of different weather types on O3 concentration. The backward trajectory tracking model was used to explore the characteristics and changes of O3 pollution under two extreme weather types. The results indicate there is a good correlation between O3 concentration and ambient temperature. Under the control of low pressure on the ground and the influence of southwest airflow in the upper air for Tianjin, heavy O3 pollution occurred frequently. The addition of external transport and local generation will cause high O3 values when the weather system is weak. The O3 concentration is closely related to ambient temperature. Continuous high-temperature weather is conducive to the photochemical reaction. The multi-day O3 pollution process would occur when the weather system is robust. The first and second types of extreme weather are more likely to cause persistent O3 pollution processes. Under the premise of stable emission sources, the change in weather patterns was the main reason affecting the O3 concentration. This study aims to improve O3 pollution control and air quality prediction in the BTH region and large cities in China