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5461.Unified Harmonics Based Method to Reduce Reactive Power of the Dual Active Bridge Converter

Author:Shi, HC;Wen, HQ;Chen, J;Hu, YH

Source:2016 IEEE INTERNATIONAL CONFERENCE ON RENEWABLE ENERGY RESEARCH AND APPLICATIONS (ICRERA),2016,Vol.

Abstract:In order to improve the efficiency of the dual active bridge (DAB) converter for a wide operating range, a novel unified-harmonics analysis based control strategy under 3-level modulated phase-shift framework is proposed. The mathematic model of the transmission power of the DAB converter is derived and the zero-voltage-switch soft-switching region is presented. Compared with piecewise time domain model, the expressions are simplified and easy online implementation. Then, a reactive-power-minimization method and its control implementation are presented. Both of the simulation and experiment results verify the feasibility of the proposed control method.

5462.Rearrangements and minimization of the principal eigenvalue of a nonlinear Steklov problem

Author:Emamizadeh, B;Zivari-Rezapour, M

Source:NONLINEAR ANALYSIS-THEORY METHODS & APPLICATIONS,2011,Vol.74

Abstract:This paper, motivated by Del Pezzo et al. (2006) [1], discusses the minimization of the principal eigenvalue of a nonlinear boundary value problem. In the literature, this type of problem is called Steklov eigenvalue problem. The minimization is implemented with respect to a weight function. The admissible set is a class of rearrangements generated by a bounded function. We merely assume the generator is non-negative in contrast to [1], where the authors consider weights which are positively away from zero, in addition to being two-valued. Under this generality, more physical situations can be modeled. Finally, using rearrangement theory developed by Geoffrey Burton, we are able to prove uniqueness of the optimal solution when the domain of interest is a ball. (C) 2011 Elsevier Ltd. All rights reserved.

5463.Traffic Sign Detection by Template Matching based on Multi-Level Chain Code Histogram

Author:Qian, RQ;Zhang, BL;Yue, Y;Coenen, F

Source:2015 12TH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (FSKD),2015,Vol.

Abstract:This paper proposes a real-time system for traffic signs detection, which features of template matching based on a new feature expression for geometric shapes, namely, multi-level chain code histogram (MCCH). For all of the different shapes associated with Chinese traffic signs, e.g., circle, triangle, inverted triangle and octagon, MCCH is a robust feature expression with remarkable low computational cost, which is particularly important for real-time applications. The proposed system consists of three stages: 1) segmentation based on color; 2) MCCH extraction; 3) template matching. Extensive experiments were conducted using different datasets, demonstrating outstanding performance with regard to high processing speed and accuracy. The system robustness to rotation, scale, and illumination has also been illustrated.

5464.Numerical simulation of a degenerate parabolic problem occurring in the spatial diffusion of biological population

Author:Nikan,O.;Avazzadeh,Z.;Tenreiro Machado,J. A.

Source:Chaos, Solitons and Fractals,2021,Vol.151

Abstract:This paper studies a localized meshless algorithm for calculating the solution of a nonlinear biological population model (NBPM). This model describes the dynamics in the biological population and may provide valuable predictions under different scenarios. The solution of the NBPM is approximated by means of local radial basis function based on the partition of unity (LRBF-PU) technique. First, the partial differential equation (PDE) is converted into a system of ordinary differential equations (ODEs) with the help of radial kernels. Afterwards, the system of ODEs is solved through an ODE solver of high-order. The major advantage of this scheme is that it does not requires any linearization. The LRBF-PU approximation helps handling the issue of the matrix ill conditioning that arises in a global RBF approximation. Three examples highlight the efficiency and accuracy of the numerical method. It is verified that the proposed strategy is more efficient in terms of computational time and accuracy in comparison with others available in the literature.

5465.A review and future direction of agile, business intelligence, analytics and data science

Author:Larson, D;Chang, V

Source:INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT,2016,Vol.36

Abstract:Agile methodologies were introduced in 2001. Since this time, practitioners have applied Agile methodologies to many delivery disciplines. This article explores the application of Agile Methodologies and principles to business intelligence delivery and how Agile has changed with the evolution of business intelligence. Business intelligence has evolved because the amount of data generated through the internet and smart devices has grown exponentially altering how organizations and individuals use information. The practice of business intelligence delivery with an Agile methodology has matured; however, business intelligence has evolved altering the use of Agile principles and practices. The Big Data phenomenon, the volume, variety, and velocity of data, has impacted business intelligence and the use of information. New trends such as fast analytics and data science have emerged as part of business intelligence. This paper addresses how Agile principles and practices have evolved with business intelligence, as well as its challenges and future directions. (C) 2016 Elsevier Ltd. All rights reserved.

5466.Evaluation of Several Denial of Service Attack Methods for IoT System

Author:Cui, YM;Liu, QL;Zheng, K;Huang, X

Source:2018 NINTH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY IN MEDICINE AND EDUCATION (ITME 2018),2018,Vol.

Abstract:Recently, the online cheating and attacking posed a threat to net safety. As an important component of the development of the information era, the Internet of Things (IoT) would cause serious property losses once it is attacked. This experiment is to use 3 devices to simulate the principle of the Denial of Service (DoS) attack. The attack is launched by Kali Linux in different ways. Furthermore, this paper lists the changed variables of the experiment and shows how the influence can be caused.

5467.How B2B relationships influence new product development in entrepreneurial firms? The role of psychological tension

Author:Zheng,Leven J.;Zhang,Yameng;Zhan,Wu;Sharma,Piyush

Source:Journal of Business Research,2022,Vol.139

Abstract:Although tension commonly exists in business-to-business (B2B) relationships, past research pays little attention to the potential dark side effects of psychological tensions, especially those between entrepreneurial firms and their client firms, despite their significant impact on these firms’ performance. We address this important research gap by exploring the nature and impact of psychological tensions between entrepreneurial firms and their client firms during the conceptualization and commercialization stages of the new product development (NPD) process. We employ a qualitative approach to conduct semi-structured interviews with 19 entrepreneurial firms operating in the artificial intelligence field in China, and identify two types of psychological tensions at the conceptualization stage (fear of losing the B2B relationship and divergent expectations) and one type of psychological tension at the commercialization stage (attention embeddedness). We also find that fear of losing the B2B relationship and divergent expectations lead to technological decontextualization, while attention embeddedness yields singular learning.

5468.Development of Modulation p-Doped 1310 nm InAs/GaAs Quantum Dot Laser Materials and Ultrashort Cavity Fabry-Perot and Distributed-Feedback Laser Diodes

Author:Li, QZ;Wang, X;Zhang, ZY;Chen, HM;Huang, YQ;Hou, CC;Wang, J;Zhang, RY;Ning, JQ;Min, JH;Zheng, CC

Source:ACS PHOTONICS,2018,Vol.5

Abstract:Multiple-layer InAs/GaAs quantum dot (QD) laser structures were etched to remove the p-side A1GaAs cladding layers to investigate the temperature-dependent photoluminescence (PL) characteristics. Four QD samples, including undoped as grown QDs, p-doped as grown QDs, undoped annealed QDs, and p-doped annealed QDs, were prepared by molecular beam epitaxy (MBE) and a postgrowth annealing process for comparison. Among them, modulation p-doped QD samples exhibit much less temperature dependent characteristics of PL spectra and notable insensitivity to intermixing compared to undoped ones. This is attributed to the effects of modulation p-doping, which can inhibit holes' thermal broadening in their closely spaced energy levels and significantly suppress In/Ga interdiffusion between QDs and their surrounding matrix. These results provide greater freedom in the choice of MBE growth for high-quality active regions and claddings of QD laser diodes. The superior features of the modulation p-doped QD materials have been transferred naturally to the laser devices. The continuous-wave ground-state (GS) lasing has been realized in both p-doped QD Fabry-Perot (F-P) and laterally coupled distributed-feedback (LC-DFB) narrow ridge lasers with very short cavity length without facet coatings, in which a 1315 nm GS lasing has been found in a F-P laser with a 400 ism cavity length, while single longitudinal mode lasing with a very large tunable range of 140 nm and side mode suppression ratio of 51 dB is achieved in an LC-DFB laser. This work demonstrates great development potential of InAs/GaAs QD lasers for applications in high-speed fiber-optic communication.

5469.An experimental study on geospatial indexing for sensor service discovery

Author:Wang, W;De, S;Cassar, G;Moessner, K

Source:EXPERT SYSTEMS WITH APPLICATIONS,2015,Vol.42

Abstract:The Internet of Things enables human beings to better interact with and understand their surrounding environments by extending computational capabilities to the physical world. A critical driving force behind this is the rapid development and wide deployment of wireless sensor networks, which continuously produce a large amount of real-world data for many application domains. Similar to many other large-scale distributed technologies, interoperability and scalability are the prominent and persistent challenges. The proposal of sensor-as-a-service aims to address these challenges; however, to our knowledge, there are no concrete implementations of techniques to support the idea, in particular, large-scale, distributed sensor service discovery. Based on the distinctive characteristics of the sensor services, we develop a scalable discovery architecture using geospatial indexing techniques and semantic service technologies. We perform extensive experimental studies to verify the performance of the proposed method and its applicability to large-scale, distributed sensor service discovery. (C) 2014 Elsevier Ltd. All rights reserved.

5470.Robust LMI-LQR Control for Dual-Active-Bridge DC-DC Converters With High Parameter Uncertainties

Author:Xia, PZ;Shi, HC;Wen, HQ;Bu, QL;Hu, YH;Yong, Y

Source:IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION,2020,Vol.6

Abstract:This article presents an improved linear-quadratic regulator (LQR) control based on linear matrix inequalities (LMIs) to optimize the key parameters for the closed-loop control of dual-active-bridge (DAB) converters with high system uncertainty. First, the polytopic model of an uncertain DAB converter is introduced according to the simplified DAB equivalent circuit. LMIs are then used in the improved LQR control to derive the optimized control parameters under the given constraints. An improved LMI-LQR hybrid closed-loop control is adopted with the output current introduced in the control loop to enhance the dynamic performance. The performance of the proposed LMI-LQR is compared with the conventional LQR in terms of transient responses under various load and line disturbances. Both the simulation and experimental results are provided to validate the advantages of the proposed control.

5471.Quantifying construction waste reduction through the application of prefabrication: a case study in Anhui, China

Author:Hao, JL;Chen, ZK;Zhang, ZH;Loehlein, G

Source:ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,2021,Vol.28

Abstract:Due to the rapid pace of urbanization in China, there has been a significant increase in construction work, which has resulted in the generation of more waste. Reducing the waste at source is the most efficient way to reduce its negative impacts, and prefabrication is a construction method that does exactly that. Since prefabricated construction generates less waste compared to conventional cast-in-situ construction, it is being promoted by the Chinese government. This study investigates the benefits of prefabrication and quantifies the percentage of construction waste reduction through its application in China. It does so by using a 26-storey concrete-brick residential building as a case study, and by conducting uncertainty analysis with Oracle Crystal Ball simulation software to assess the reduction of waste when using prefabricated components in place of cast-in-situ elements. Simulation results demonstrated that the waste generation rate for in-situ timber formwork and masonry work was 10.52 and 4.77 kg/m(2) respectively, and that the use of prefabricated components reduced those figures by 36.04%% and 25.53%% respectively. This study quantifies the benefits of prefabrication as a method for reducing the generation of construction waste in China. Not only would extensive use of prefabrication decrease the cost related to construction waste management in China, but it could also mitigate the environmental and social impacts of construction waste globally.

5472.Flexible Composite Solid Electrolyte with an Active Inorganic Filler

Author:Sun, YY;Wang, JL;Fu, DS;Zhang, FR;Wang, ZC;Chen, X;Xu, JJ;Hu, JC;Wu, XD

Source:ACS SUSTAINABLE CHEMISTRY & ENGINEERING,2021,Vol.9

Abstract:Solid polymer electrolytes (SPEs) attract great attention due to their wide electrochemical stability window, low cost, and excellent processability. However, some obstacles, including their low ionic conductivity, poor solid-solid contact between the SPE and lithium metal electrode, and uneven lithium deposition behavior, hinder their application in solid-state lithium batteries. Herein, a flexible composite solid electrolyte is facilely designed and successfully fabricated by introducing reactive petal-like MoS2 nanosheets to a poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP)/lithium bis(fluorosulfonyl)imide (LiFSI) polymer electrolyte. The addition of petal-like MoS2 nanosheets not only greatly improves the room-temperature ionic conductivity to 2.8 x 10 (-4) S cm(-1) but also decreases interfacial impedance and in situ suppresses lithium dendrite growth. In the resulting solid-state batteries, both rate capacity (137 mAh g(-1) at 0.54C) and cycling stability (Coulombic efficiency in each cycle close to 100%% during 200 cycles) are obtained by employing the electrolyte. In addition, the rational mechanism of MoS2 in improving ion conduction and suppressing lithium dendrite growth is suggested.

5473.A novel beta parameter based fuzzy-logic controller for photovoltaic MPPT application

Author:Li, XS;Wen, HQ;Hu, YH;Jiang, L

Source:RENEWABLE ENERGY,2019,Vol.130

Abstract:In this paper, a novel beta parameter three-input one-output fuzzy-logic based maximum power point tracking (MPPT) algorithm is presented for the photovoltaic (PV) system application. The conventional fuzzy-logic controllers (FLCs) exhibit obvious limitations such as their dependence on the user's knowledge about the system and complicated rules. Furthermore, they show inherent dilemma between the rules number of FLC and the universality for various operating conditions, which is revealed and explained with details in this paper. Thus, a novel FLC is proposed by introducing a third input: an intermediate variable beta. It can simplify the fuzzy rule membership functions and cover wider operating conditions. The dependence on the user's knowledge about the system is reduced. The converging speed for transients is improved and oscillations around the MPPs are completely eliminated compared with conventional MPPT methods. Typical operation conditions such as varying solar irradiation and load resistance are tested for fair comparison of various algorithms. An experimental prototype was designed and main experimental results were presented to verify the advantages of the proposed algorithm. (C) 2018 Elsevier Ltd. All rights reserved.

5474.Low temperature solution-processed IGZO thin-film transistors

Author:Xu, WY;Hu, LY;Zhao, C;Zhang, LJ;Zhu, DL;Cao, PJ;Liu, WJ;Han, S;Liu, XK;Jia, F;Zeng, YX;Lu, YM

Source:APPLIED SURFACE SCIENCE,2018,Vol.455

Abstract:We reported the low-temperature high performance IGZO TFTs by solution processing. The influence of IGZO composition over broad range on thin films and devices properties were investigated by a wide range of characterization techniques. The schematic of TFT solution-processed IGZO TFTs mobility with different compositions has been obtained. In order to achieve decent TFT performance, the In content should be much high for solution-processed IGZO TFTs. The optimal solution-processed IGZO TFTs. with In:Ga:Zn = 5:1:1 composition exhibited a large mobility of 9.1 cm (2)V(-)1s-(1),low subthreshold swing of 0.22 V/decade, and high on/off ratio of 10(6) at 300 degrees C processing temperature.

5475.Composite Solid Electrolyte for Solid-State Lithium Batteries Workable at Room Temperature

Author:Sun, YY;Jin, F;Li, J;Liu, BT;Chen, X;Dong, HC;Mao, YY;Gu, W;Xu, JJ;Shen, YB;Wu, XD;Chen, LW

Source:ACS APPLIED ENERGY MATERIALS,2020,Vol.3

Abstract:Solid polymer electrolytes play a vital role in improving the safety of lithium batteries. However, low ionic conductivity and poor mechanical property limit their further applications. Herein, we fabricated a composite solid electrolyte (CSE) based on a polymer (polyvinylidene fluoride-hexafluoro propylene, PVDF-HFP) and an inorganic filler of porous graphitic carbon nitride (PGCN) nanosheets with a high specific surface area. The porous structure facilitated good distribution of PGCN in the PVDF-HFP matrix and offered abundant PVDF-HFP/PGCN interfaces, which might be beneficial for the Li+ transport. The CSE showed high ionic conductivity (2.3 x 10(-4) S/cm at 30 degrees C), excellent cycling performance, and outstanding physical and chemical properties. Moreover, the correlation of the ionic conductivities of the CSEs and the specific surface of the PGCN fillers was discussed, and the results revealed that the ionic conductivity of the CSE was increased with the increase in the specific surface of PGCN, indirectly demonstrating that the transport of the Li+ was mainly conducted on the interfaces between the polymer and the inorganic fillers.

5476.An Improved Simultaneous Fault Diagnosis Method based on Cohesion Evaluation and BP-MLL for Rotating Machinery

Author:Zhang, YX;Han, Y;Yang, R;Su, DK;Wang, YQ;Di, Y;Lu, QD;Huang, MJ

Source:2020 IEEE 29TH INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE),2020,Vol.2020-June

Abstract:With the requirements for safety and stability of rotating machinery, its fault diagnosis is significantly important. To diagnose simultaneous faults of gearbox and bearing in rotating machinery under different working conditions, an improved algorithm based on cohesion-based feature selection and improved back-propagation multi-label learning (BP-MLL) is proposed in this paper. Cohesion evaluation technique is applied to construct a low-dimensional feature vector by selecting high sensitivity parameters in a high-dimensional vector from time and frequency domain. Improved BP-MLL neural network algorithm considers correlation between labels and adopts ReLU as activation function. To show the effectiveness of the proposed method, hardware experiments are conducted on wind turbine drivetrain diagnostics simulator (WTDDS) for simultaneous fault diagnosis. The experiment reveals that the proposed method can achieve better results than conventional methods under six performance evaluation metrics.

5477.Vehicle Type Classification and Attribute Prediction Using Multi-task RCNN

Author:Huo, ZQ;Xia, YZ;Zhang, BL

Source:2016 9TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2016),2016,Vol.

Abstract:Vehicle classification is an important subject of study due to its significance in a number of areas including law enforcement, traffic surveillance, autonomous navigation, and transportation management. While numerous approaches have been proposed, few studies have been published with regard to the multi-view classification of vehicles captured in real surveillance. In this paper, we consider the multi-view classification of vehicles as an attribute prediction problem with views (rear, front, and side) as attributes. The corresponding multi-task learning is implemented in the Region-based Convolutional Neural Network (RCNN) framework, which classifies vehicle categories (car, truck, bus, and van) and predicts the attributes simultaneously. Experiments on a field-captured vehicle dataset provide satisfactory results, with approximate 83%% accuracy for vehicle type classification and over 90%% accuracy for attribute prediction.

5478.A Deep Residual Shrinkage Neural Network-based Deep Reinforcement Learning Strategy in Financial Portfolio Management

Author:Sun, RY;Jiang, ZY;Su, JL

Source:2021 IEEE 6TH INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS (ICBDA 2021),2021,Vol.

Abstract:Reinforcement Learning algorithms are widely applied in many fields, such as price index prediction, image recognition, and natural language processing. This paper introduces a novel algorithm based on the classical Deep Reinforcement Learning algorithm and Deep Residual Shrinkage Neural Network for portfolio management. In this algorithm, the Ensemble of Identical Independent Evaluators framework put forward by Jiang et al. is adopted in the policy function. Following this, we adopt the Deep Residual Shrinkage Neural Network to function as the identical independent evaluator to optimize the algorithm. We use the cryptocurrency market in this research to assess the efficacy of our strategy with eight traditional portfolio management strategies as well as Jiang et al.'s reinforcement learning strategy. In our experiments, the Accumulated Yield is used to reflect the profit of the algorithm. Despite having a high commission rate of 0.25%% in back-tests, results show that our algorithm can achieve 44.5%% 105.4%% and 148.8%% returns in three different 50-days back-tests, which is five times more than the profit of other non-reinforcement learning strategies and Jiang et al.'s strategy. Furthermore, the Sharpe ratio demonstrates that the extra reward per unit risk of the our strategy is still better than other traditional portfolio management strategies and Jiang et al.'s strategy by at least 50%% in different time horizons.

5479.Is constant returns-to-scale a restrictive assumption for sector-level empirical macroeconomics? The case of Europe

Author:Walheer, B

Source:APPLIED ECONOMICS LETTERS,2019,Vol.26

Abstract:Assuming constant returns-to-scale is commonly agreed for empirical macroeconomic studies when countries are of interest. Recently, an increasing number of works have started to look at sectors building on the same assumption. In this letter, we question the reliability of this assumption for 10 European sectors for the period 1995-2014, for different production factor combinations. We make use of a simple sample-based nonparametric test that does not require any assumptions for any aspect of the production process. Our results suggest that, in general, this assumption is rather acceptable and that the specification with only capital and labour is the best in this case.

5480.TRY plant trait database - enhanced coverage and open access

Author:Kattge, J;Bonisch, G;Diaz, S;Lavorel, S;Prentice, IC;Leadley, P;Tautenhahn, S;Werner, GDA;Aakala, T;Abedi, M;Acosta, ATR;Adamidis, GC;Adamson, K;Aiba, M;Albert, CH;Alcantara, JM;Alcazar, CC;Aleixo, I;Ali, H;Amiaud, B;Ammer, C;Amoroso, MM;Anand, M;Anderson, C;Anten, N;Antos, J;Apgaua, DMG;Ashman, TL;Asmara, DH;Asner, GP;Aspinwall, M;Atkin, O;Aubin, I;Baastrup-Spohr, L;Bahalkeh, K;Bahn, M;Baker, T;Baker, WJ;Bakker, JP;Baldocchi, D;Baltzer, J;Banerjee, A;Baranger, A;Barlow, J;Barneche, DR;Baruch, Z;Bastianelli, D;Battles, J;Bauerle, W;Bauters, M;Bazzato, E;Beckmann, M;Beeckman, H;Beierkuhnlein, C;Bekker, R;Belfry, G;Belluau, M;Beloiu, M;Benavides, R;Benomar, L;Berdugo-Lattke, ML;Berenguer, E;Bergamin, R;Bergmann, J;Carlucci, MB;Berner, L;Bernhardt-Romermann, M;Bigler, C;Bjorkman, AD;Blackman, C;Blanco, C;Blonder, B;Blumenthal, D;Bocanegra-Gonzalez, KT;Boeckx, P;Bohlman, S;Bohning-Gaese, K;Boisvert-Marsh, L;Bond, W;Bond-Lamberty, B;Boom, A;Boonman, CCF;Bordin, K;Boughton, EH;Boukili, V;Bowman, DMJS;Bravo, S;Brendel, MR;Broadley, MR;Brown, KA;Bruelheide, H;Brumnich, F;Bruun, HH;Bruy, D;Buchanan, SW;Bucher, SF;Buchmann, N;Buitenwerf, R;Bunker, DE;Burger, J;Burrascano, S;Burslem, DFRP;Butterfield, BJ;Byun, C;Marques, M;Scalon, MC;Caccianiga, M;Cadotte, M;Cailleret, M;Camac, J;Camarero, JJ;Campany, C;Campetella, G;Campos, JA;Cano-Arboleda, L;Canullo, R;Carbognani, M;Carvalho, F;Casanoves, F;Castagneyrol, B;Catford, JA;Cavender-Bares, J;Cerabolini, BEL;Cervellini, M;Chacon-Madrigal, E;Chapin, K;Chapin, FS;Chelli, S;Chen, SC;Chen, AP;Cherubini, P;Chianucci, F;Choat, B;Chung, KS;Chytry, M;Ciccarelli, D;Coll, L;Collins, CG;Conti, L;Coomes, D;Cornelissen, JHC;Cornwell, WK;Corona, P;Coyea, M;Craine, J;Craven, D;Cromsigt, JPGM;Csecserits, A;Cufar, K;Cuntz, M;da Silva, AC;Dahlin, KM;Dainese, M;Dalke, I;Dalle Fratte, M;Anh, TDL;Danihelka, J;Dannoura, M;Dawson, S;de Beer, AJ;De Frutos, A;De Long, JR;Dechant, B;Delagrange, S;Delpierre, N;Derroire, G;Dias, AS;Diaz-Toribio, MH;Dimitrakopoulos, PG;Dobrowolski, M;Doktor, D;Drevojan, P;Dong, N;Dransfield, J;Dressler, S;Duarte, L;Ducouret, E;Dullinger, S;Durka, W;Duursma, R;Dymova, O;E-Vojtko, A;Eckstein, RL;Ejtehadi, H;Elser, J;Emilio, T;Engemann, K;Erfanian, MB;Erfmeier, A;Esquivel-Muelbert, A;Esser, G;Estiarte, M;Domingues, TF;Fagan, WF;Fagundez, J;Falster, DS;Fan, Y;Fang, JY;Farris, E;Fazlioglu, F;Feng, YH;Fernandez-Mendez, F;Ferrara, C;Ferreira, J;Fidelis, A;Finegan, B;Firn, J;Flowers, TJ;Flynn, DFB;Fontana, V;Forey, E;Forgiarini, C;Francois, L;Frangipani, M;Frank, D;Frenette-Dussault, C;Freschet, GT;Fry, EL;Fyllas, NM;Mazzochini, GG;Gachet, S;Gallagher, R;Ganade, G;Ganga, F;Garcia-Palacios, P;Gargaglione, V;Garnier, E;Garrido, JL;de Gasper, AL;Gea-Izquierdo, G;Gibson, D;Gillison, AN;Giroldo, A;Glasenhardt, MC;Gleason, S;Gliesch, M;Goldberg, E;Goldel, B;Gonzalez-Akre, E;Gonzalez-Andujar, JL;Gonzalez-Melo, A;Gonzalez-Robles, A;Graae, BJ;Granda, E;Graves, S;Green, WA;Gregor, T;Gross, N;Guerin, GR;Gunther, A;Gutierrez, AG;Haddock, L;Haines, A;Hall, J;Hambuckers, A;Han, WX;Harrison, SP;Hattingh, W;Hawes, JE;He, TH;He, PC;Heberling, JM;Helm, A;Hempel, S;Hentschel, J;Herault, B;Heres, AM;Herz, K;Heuertz, M;Hickler, T;Hietz, P;Higuchi, P;Hipp, AL;Hirons, A;Hock, M;Hogan, JA;Holl, K;Honnay, O;Hornstein, D;Hou, EQ;Hough-Snee, N;Hovstad, KA;Ichie, T;Igic, B;Illa, E;Isaac, M;Ishihara, M;Ivanov, L;Ivanova, L;Iversen, CM;Izquierdo, J;Jackson, RB;Jackson, B;Jactel, H;Jagodzinski, AM;Jandt, U;Jansen, S;Jenkins, T;Jentsch, A;Jespersen, JRP;Jiang, GF;Johansen, JL;Johnson, D;Jokela, EJ;Joly, CA;Jordan, GJ;Joseph, GS;Junaedi, D;Junker, RR;Justes, E;Kabzems, R;Kane, J;Kaplan, Z;Kattenborn, T;Kavelenova, L;Kearsley, E;Kempel, A;Kenzo, T;Kerkhoff, A;Khalil, MI;Kinlock, NL;Kissling, WD;Kitajima, K;Kitzberger, T;Kjoller, R;Klein, T;Kleyer, M;Klimesova, J;Klipel, J;Kloeppel, B;Klotz, S;Knops, JMH;Kohyama, T;Koike, F;Kollmann, J;Komac, B;Komatsu, K;Konig, C;Kraft, NJB;Kramer, K;Kreft, H;Kuhn, I;Kumarathunge, D;Kuppler, J;Kurokawa, H;Kurosawa, Y;Kuyah, S;Laclau, JP;Lafleur, B;Lallai, E;Lamb, E;Lamprecht, A;Larkin, DJ;Laughlin, D;Le Bagousse-Pinguet, Y;le Maire, G;le Roux, PC;le Roux, E;Lee, T;Lens, F;Lewis, SL;Lhotsky, B;Li, YZ;Li, XE;Lichstein, JW;Liebergesell, M;Lim, JY;Lin, YS;Linares, JC;Liu, CJ;Liu, DJ;Liu, U;Livingstone, S;Llusia, J;Lohbeck, M;Lopez-Garcia, A;Lopez-Gonzalez, G;Lososova, Z;Louault, F;Lukacs, BA;Lukes, P;Luo, YJ;Lussu, M;Ma, SY;Pereira, CMR;Mack, M;Maire, V;Makela, A;Makinen, H;Malhado, ACM;Mallik, A;Manning, P;Manzoni, S;Marchetti, Z;Marchino, L;Marcilio-Silva, V;Marcon, E;Marignani, M;Markesteijn, L;Martin, A;Martinez-Garza, C;Martinez-Vilalta, J;Maskova, T;Mason, K;Mason, N;Massad, TJ;Masse, J;Mayrose, I;McCarthy, J;McCormack, ML;McCulloh, K;McFadden, IR;McGill, BJ;McPartland, MY;Medeiros, JS;Medlyn, B;Meerts, P;Mehrabi, Z;Meir, P;Melo, FPL;Mencuccini, M;Meredieu, C;Messier, J;Meszaros, I;Metsaranta, J;Michaletz, ST;Michelaki, C;Migalina, S;Milla, R;Miller, JED;Minden, V;Ming, R;Mokany, K;Moles, AT;Molnar, VA;Molofsky, J;Molz, M;Montgomery, RA;Monty, A;Moravcova, L;Moreno-Martinez, A;Moretti, M;Mori, AS;Mori, S;Morris, D;Morrison, J;Mucina, L;Mueller, S;Muir, CD;Muller, SC;Munoz, F;Myers-Smith, IH;Myster, RW;Nagano, M;Naidu, S;Narayanan, A;Natesan, B;Negoita, L;Nelson, AS;Neuschulz, EL;Ni, J;Niedrist, G;Nieto, J;Niinemets, U;Nolan, R;Nottebrock, H;Nouvellon, Y;Novakovskiy, A;Nystuen, KO;O'Grady, A;O'Hara, K;O'Reilly-Nugent, A;Oakley, S;Oberhuber, W;Ohtsuka, T;Oliveira, R;Ollerer, K;Olson, ME;Onipchenko, V;Onoda, Y;Onstein, RE;Ordonez, JC;Osada, N;Ostonen, I;Ottaviani, G;Otto, S;Overbeck, GE;Ozinga, WA;Pahl, AT;Paine, CET;Pakeman, RJ;Papageorgiou, AC;Parfionova, E;Partel, M;Patacca, M;Paula, S;Paule, J;Pauli, H;Pausas, JG;Peco, B;Penuelas, J;Perea, A;Peri, PL;Petisco-Souza, AC;Petraglia, A;Petritan, AM;Phillips, OL;Pierce, S;Pillar, VD;Pisek, J;Pomogaybin, A;Poorter, H;Portsmuth, A;Poschlod, P;Potvin, C;Pounds, D;Powell, AS;Power, SA;Prinzing, A;Puglielli, G;Pysek, P;Raevel, V;Rammig, A;Ransijn, J;Ray, CA;Reich, PB;Reichstein, M;Reid, DEB;Rejou-Mechain, M;de Dios, VR;Ribeiro, S;Richardson, S;Riibak, K;Rillig, MC;Riviera, F;Robert, EMR;Roberts, S;Robroek, B;Roddy, A;Rodrigues, AV;Rogers, A;Rollinson, E;Rolo, V;Romermann, C;Ronzhina, D;Roscher, C;Rosell, JA;Rosenfield, MF;Rossi, C;Roy, DB;Royer-Tardif, S;Ruger, N;Ruiz-Peinado, R;Rumpf, SB;Rusch, GM;Ryo, M;Sack, L;Saldana, A;Salgado-Negret, B;Salguero-Gomez, R;Santa-Regina, I;Santacruz-Garcia, AC;Santos, J;Sardans, J;Schamp, B;Scherer-Lorenzen, M;Schleuning, M;Schmid, B;Schmidt, M;Schmitt, S;Schneider, JV;Schowanek, SD;Schrader, J;Schrodt, F;Schuldt, B;Schurr, F;Garvizu, GS;Semchenko, M;Seymour, C;Sfair, JC;Sharpe, JM;Sheppard, CS;Sheremetiev, S;Shiodera, S;Shipley, B;Shovon, TA;Siebenkas, A;Sierra, C;Silva, V;Silva, M;Sitzia, T;Sjoman, H;Slot, M;Smith, NG;Sodhi, D;Soltis, P;Soltis, D;Somers, B;Sonnier, G;Sorensen, MV;Sosinski, EE;Soudzilovskaia, NA;Souza, AF;Spasojevic, M;Sperandii, MG;Stan, AB;Stegen, J;Steinbauer, K;Stephan, JG;Sterck, F;Stojanovic, DB;Strydom, T;Suarez, ML;Svenning, JC;Svitkova, I;Svitok, M;Svoboda, M;Swaine, E;Swenson, N;Tabarelli, M;Takagi, K;Tappeiner, U;Tarifa, R;Tauugourdeau, S;Tavsanoglu, C;te Beest, M;Tedersoo, L;Thiffault, N;Thom, D;Thomas, E;Thompson, K;Thornton, PE;Thuiller, W;Tichy, L;Tissue, D;Tjoelker, MG;Tng, DYP;Tobias, J;Torok, P;Tarin, T;Torres-Ruiz, JM;Tothmeresz, B;Treurnicht, M;Trivellone, V;Trolliet, F;Trotsiuk, V;Tsakalos, JL;Tsiripidis, I;Tysklind, N;Umehara, T;Usoltsev, V;Vadeboncoeur, M;Vaezi, J;Valladares, F;Vamosi, J;van Bodegom, PM;van Breugel, M;Van Cleemput, E;van de Weg, M;van der Merwe, S;van der Plas, F;van der Sande, MT;van Kleunen, M;Van Meerbeek, K;Vanderwel, M;Vanselow, KA;Varhammar, A;Varone, L;Valderrama, MY;Vassilev, K;Vellend, M;Veneklaas, EJ;Verbeeck, H;Verheyen, K;Vibrans, A;Vieira, I;Villacis, J;Violle, C;Vivek, P;Wagner, K;Waldram, M;Waldron, A;Walker, AP;Waller, M;Walther, G;Wang, H;Wang, F;Wang, WQ;Watkins, H;Watkins, J;Weber, U;Weedon, JT;Wei, LP;Weigelt, P;Weiher, E;Wells, AW;Wellstein, C;Wenk, E;Westoby, M;Westwood, A;White, PJ;Whitten, M;Williams, M;Winkler, DE;Winter, K;Womack, C;Wright, IJ;Wright, SJ;Wright, J;Pinho, BX;Ximenes, F;Yamada, T;Yamaji, K;Yanai, R;Yankov, N;Yguel, B;Zanini, KJ;Zanne, AE;Zeleny, D;Zhao, YP;Zheng, JM;Zheng, J;Zieminska, K;Zirbel, CR;Zizka, G;Zo-Bi, IC;Zotz, G;Wirth, C

Source:GLOBAL CHANGE BIOLOGY,2020,Vol.26

Abstract: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.
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