{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T16:55:53Z","timestamp":1772297753791,"version":"3.50.1"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2016,1,22]],"date-time":"2016-01-22T00:00:00Z","timestamp":1453420800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"NSF in China","award":["61363066"],"award-info":[{"award-number":["61363066"]}]},{"name":"NSF in China","award":["11171252"],"award-info":[{"award-number":["11171252"]}]},{"name":"NSF in China","award":["11431002"],"award-info":[{"award-number":["11431002"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Optim Theory Appl"],"published-print":{"date-parts":[[2016,9]]},"DOI":"10.1007\/s10957-016-0869-2","type":"journal-article","created":{"date-parts":[[2016,1,22]],"date-time":"2016-01-22T14:34:41Z","timestamp":1453473281000},"page":"1009-1025","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["The Non-convex Sparse Problem with Nonnegative Constraint for Signal Reconstruction"],"prefix":"10.1007","volume":"170","author":[{"given":"Yong","family":"Wang","sequence":"first","affiliation":[]},{"given":"Guanglu","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Wanquan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Louis","family":"Caccetta","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,1,22]]},"reference":[{"key":"869_CR1","doi-asserted-by":"crossref","first-page":"1480","DOI":"10.1137\/120869778","volume":"23","author":"A Beck","year":"2013","unstructured":"Beck, A., Eldar, Y.C.: Sparsity constrained nonlinear optimization: optimality conditions and algorithms. SIAM J. Optim. 23, 1480\u20131509 (2013)","journal-title":"SIAM J. Optim."},{"key":"869_CR2","doi-asserted-by":"crossref","first-page":"2448","DOI":"10.1137\/100808071","volume":"23","author":"Z Lu","year":"2013","unstructured":"Lu, Z., Zhang, Y.: Sparse approximation via penalty decomposition methods. SIAM J. Optim. 23, 2448\u20132478 (2013)","journal-title":"SIAM J. Optim."},{"key":"869_CR3","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1007\/s00041-008-9035-z","volume":"14","author":"T Blumensath","year":"2008","unstructured":"Blumensath, T., Davies, M.E.: Iterative thresholding for sparse approximations. J. Fourier Anal. Appl. 14, 629\u2013654 (2008)","journal-title":"J. Fourier Anal. Appl."},{"key":"869_CR4","doi-asserted-by":"crossref","first-page":"5695","DOI":"10.1109\/TSP.2007.900760","volume":"55","author":"M Elad","year":"2007","unstructured":"Elad, M.: Optimized projections for compressed sensing. IEEE Trans. Signal Process. 55, 5695\u20135702 (2007)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR5","doi-asserted-by":"crossref","first-page":"2194","DOI":"10.1109\/TSP.2009.2040018","volume":"58","author":"M Hyder","year":"2010","unstructured":"Hyder, M., Mahata, K.: An improved smoothed $$l^0$$ l 0 approximation algorithm for sparse representation. IEEE Trans. Signal Process. 58, 2194\u20132205 (2010)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR6","doi-asserted-by":"crossref","first-page":"4973","DOI":"10.1109\/TSP.2012.2203124","volume":"60","author":"J Wang","year":"2012","unstructured":"Wang, J., Shim, B.: On the recovery limit of sparse signals using orthogonal matching pursuit. IEEE Trans. Signal Process. 60, 4973\u20134976 (2012)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR7","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1109\/TSP.2008.2007606","volume":"57","author":"H Mohimani","year":"2009","unstructured":"Mohimani, H., Babaie-Zadeh, M., Jutten, C.: A fast approach for overcomplete sparse decomposition based on smoothed $$l^0$$ l 0 norm. IEEE Trans. Signal Process. 57, 289\u2013301 (2009)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR8","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1137\/S0097539792240406","volume":"24","author":"BK Natraajan","year":"1995","unstructured":"Natraajan, B.K.: Sparse approximation to linear systems. SIAM J. Comput. 24, 227\u2013234 (1995)","journal-title":"SIAM J. Comput."},{"key":"869_CR9","doi-asserted-by":"crossref","unstructured":"Hyder, M., Mahata, K.: An approximate $$l_0$$ l 0 norm minimization algorithm for compressed sensing. In: IEEE International Conference on Acoustics, Speech and Signal Precessing (ICASSP), pp. 3365\u20133368 (2009)","DOI":"10.1109\/ICASSP.2009.4960346"},{"key":"869_CR10","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1090\/S0894-0347-08-00610-3","volume":"22","author":"A Cohen","year":"2009","unstructured":"Cohen, A., Dahmen, W., DeVore, R.: Compressed sensing and best $$k$$ k -term approximation. J. Am. Math. Soc. 22, 211\u2013231 (2009)","journal-title":"J. Am. Math. Soc."},{"key":"869_CR11","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","volume":"52","author":"DL Donoho","year":"2006","unstructured":"Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory 52, 1289\u20131306 (2006)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"869_CR12","doi-asserted-by":"crossref","first-page":"4203","DOI":"10.1109\/TIT.2005.858979","volume":"51","author":"EJ Cand\u00e8s","year":"2005","unstructured":"Cand\u00e8s, E.J., Tao, T.: Decoding by linear programming. IEEE Trans. Inf. Theory 51, 4203\u20134215 (2005)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"869_CR13","doi-asserted-by":"crossref","first-page":"1207","DOI":"10.1002\/cpa.20124","volume":"59","author":"EJ Cand\u00e8s","year":"2006","unstructured":"Cand\u00e8s, E.J., Romberg, J., Tao, T.: Stable signal recovery from incomplete and inaccurate measurements. Commun. Pure Appl. Math. 59, 1207\u20131223 (2006)","journal-title":"Commun. Pure Appl. Math."},{"key":"869_CR14","doi-asserted-by":"crossref","first-page":"717","DOI":"10.1007\/s10208-009-9045-5","volume":"9","author":"EJ Cand\u00e8s","year":"2009","unstructured":"Cand\u00e8s, E.J., Recht, B.: Exact matrix completion via convex optimization. Found. Comput. Math. 9, 717\u2013772 (2009)","journal-title":"Found. Comput. Math."},{"key":"869_CR15","doi-asserted-by":"crossref","first-page":"2053","DOI":"10.1109\/TIT.2010.2044061","volume":"56","author":"EJ Cand\u00e8s","year":"2010","unstructured":"Cand\u00e8s, E.J., Tao, T.: The power of convex relaxation: near-optimal matrix completion. IEEE Trans. Inf. Theory 56, 2053\u20132080 (2010)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"869_CR16","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1109\/TPAMI.2008.79","volume":"31","author":"J Wright","year":"2009","unstructured":"Wright, J., Yang, A., Ganesh, A., Sastry, S., Ma, Y.: Robust face recognition via sparse representation. IEEE Trans. Pattern Recogn. Anal. Mach. Intell. 31, 210\u2013227 (2009)","journal-title":"IEEE Trans. Pattern Recogn. Anal. Mach. Intell."},{"key":"869_CR17","unstructured":"Koh, K., Kim, S.-J., Boyd, S.: The code package $$l_1\\_l_s$$ l 1 _ l s : http:\/\/stanford.edu\/~boyd\/l1_ls\/"},{"key":"869_CR18","unstructured":"Cand\u00e8s, E.J., Romberg, J.: The code package $$l_1$$ l 1 -magic: http:\/\/statweb.stanford.edu\/~candes\/l1magic\/"},{"key":"869_CR19","first-page":"585","volume":"1","author":"MAT Figueiredo","year":"2007","unstructured":"Figueiredo, M.A.T., Nowak, R.D., Wright, S.J.: Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems. IEEE J. Select. Top. Signal Process. 1, 585\u2013597 (2007)","journal-title":"IEEE J. Select. Top. Signal Process."},{"key":"869_CR20","unstructured":"Hale, E.T., Yin, W., Zhang, Y.: A fixed-point continuation method for $$l_1$$ l 1 -regularized minimization with applications to compressed sensing. CAAM Technical Report TR07-07, Rice University, Houston, TX, (2007)"},{"key":"869_CR21","doi-asserted-by":"crossref","first-page":"1895","DOI":"10.1109\/TSP.2010.2103066","volume":"59","author":"YJ Wang","year":"2011","unstructured":"Wang, Y.J., Zhou, G.L., Caccetta, L., Liu, W.Q.: An alternating direction algorithm for $$l_1$$ l 1 problems in compressive sensing. IEEE Trans. Signal Process. 59, 1895\u20131901 (2011)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000016","volume":"3","author":"S Boyd","year":"2010","unstructured":"Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J.: Distributed optimization and statistical learning via the alternating direction method of multipliers. Found. Trends Mach. Learn. 3, 1\u2013122 (2010)","journal-title":"Found. Trends Mach. Learn."},{"key":"869_CR23","doi-asserted-by":"crossref","unstructured":"Saab, R., Chartrand, R., Yilmaz, O.: Stable sparse approximations via nonconvex optimization. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 3885\u20133888 (2008)","DOI":"10.1109\/ICASSP.2008.4518502"},{"key":"869_CR24","doi-asserted-by":"crossref","unstructured":"Chartrand, R.: Nonconvex compressed sensing and error correction. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 889\u2013892 (2007)","DOI":"10.1109\/ICASSP.2007.366823"},{"key":"869_CR25","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1214\/08-EJS348","volume":"3","author":"Y She","year":"2009","unstructured":"She, Y.: Thresholding-based iterative selection procedures for model selection and shrinkage. Electron. J. Stat. 3, 384\u2013415 (2009)","journal-title":"Electron. J. Stat."},{"key":"869_CR26","doi-asserted-by":"crossref","first-page":"2976","DOI":"10.1016\/j.csda.2011.11.013","volume":"9","author":"Y She","year":"2012","unstructured":"She, Y.: An iterative algorithm for fitting nonconvex penalized generalized linear models with grouped predictors. Comput. Statist. Data Anal. 9, 2976\u20132990 (2012)","journal-title":"Comput. Statist. Data Anal."},{"key":"869_CR27","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/j.neucom.2013.03.017","volume":"119","author":"Q Lyu","year":"2013","unstructured":"Lyu, Q., Lin, Z., She, Y., Zhang, C.: A comparison of typical $$l_p$$ l p minimization algorithms. Neurocomputing 119, 413\u2013424 (2013)","journal-title":"Neurocomputing"},{"key":"869_CR28","doi-asserted-by":"crossref","unstructured":"Foucart, S., Lai, M.: Sparsest solutions of underdetermined linear systems via $$l_q$$ l q minimization for $$0 < {q} < 1$$ 0 < q < 1 . Appl. Comput. Harmon. Anal. 26, 395\u2013407 (2009)","DOI":"10.1016\/j.acha.2008.09.001"},{"key":"869_CR29","doi-asserted-by":"crossref","first-page":"4686","DOI":"10.1109\/TSP.2009.2026004","volume":"57","author":"G Gasso","year":"2009","unstructured":"Gasso, G., Rakotomamonjy, A., Canu, S.: Recovering sparse signals with a certain family of nonconvex penalties and DC programming. IEEE Trans. Signal Process. 57, 4686\u20134698 (2009)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR30","doi-asserted-by":"crossref","unstructured":"Ochs, P., Dosovitskiy, A., Brox, T., Pock, T.: An iterated $$l_1$$ l 1 algorithm for non-smooth non-convex optimization in computer vision. In: Computer Vision and Pattern Recognition (CVPR), IEEE Conference, pp. 1759\u20131766 (2013)","DOI":"10.1109\/CVPR.2013.230"},{"key":"869_CR31","unstructured":"Chen, X., Zhou, W.: Convergence of reweighted $$l_1$$ l 1 minimization algorithms and unique solution of truncated $$l_p$$ l p minimization. Technical report, Hong Kong Polytechnic University (2010)"},{"key":"869_CR32","doi-asserted-by":"crossref","unstructured":"Chartrand, R., Yin, W.: Iteratively reweighted algorithms for compressive sensing. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 3869\u20133872 (2008)","DOI":"10.1109\/ICASSP.2008.4518498"},{"key":"869_CR33","doi-asserted-by":"crossref","unstructured":"Lai, M., Wang, J.: An unconstrained $$l_q$$ l q minimization with $$0 < {q} < 1$$ 0 < q < 1 for sparse solution of under-determined linear systems. SIAM J. Optim. 21, 82\u2013101 (2011)","DOI":"10.1137\/090775397"},{"key":"869_CR34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1088\/0266-5611\/24\/3\/035020","volume":"24","author":"R Chartrand","year":"2008","unstructured":"Chartrand, R., Staneva, V.: Restricted isometry properties and nonconvex compressive sensing. Inverse Probl. 24, 1\u201314 (2008)","journal-title":"Inverse Probl."},{"key":"869_CR35","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1109\/TCSII.2013.2296133","volume":"61","author":"JK Pant","year":"2014","unstructured":"Pant, J.K., Lu, W.S., Antoniou, A.: New improved algorithms for compressive sensing based on $$l_p$$ l p norm. IEEE Trans. Circuits Syst. II: Express Briefs 61, 198\u2013202 (2014)","journal-title":"IEEE Trans. Circuits Syst. II: Express Briefs"},{"key":"869_CR36","unstructured":"Krishnan, D., Fergus, R.: Fast image deconvolution using\u00a0hyper-Laplacian priors. In: Advances in Neural Information Processing Systems,\u00a0pp. 1033\u20131041 (2009)"},{"key":"869_CR37","doi-asserted-by":"crossref","first-page":"1013","DOI":"10.1109\/TNNLS.2012.2197412","volume":"23","author":"Z Xu","year":"2012","unstructured":"Xu, Z., Chang, X., Xu, F., Zhang, H.: $$L_{1\/2}$$ L 1 \/ 2 regularization: a thresholding representation theory and a fast solver. IEEE Trans. Neural Netw. Learn. Syst. 23, 1013\u20131027 (2012)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"869_CR38","doi-asserted-by":"crossref","first-page":"2317","DOI":"10.1109\/TSP.2014.2309076","volume":"62","author":"J Zeng","year":"2014","unstructured":"Zeng, J., Lin, S., Wang, Y., Xu, Z.: $$L_{1\/2}$$ L 1 \/ 2 regularization: convergence of iterative half thresholding algorithm. IEEE Trans. Signal Process. 62, 2317\u20132328 (2014)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR39","doi-asserted-by":"crossref","first-page":"4709","DOI":"10.1109\/TIP.2012.2214051","volume":"21","author":"X Chen","year":"2012","unstructured":"Chen, X., Ng, Michael K., Zhang, C.: Non-Lipschitz-regularization and box constrained model for image restoration. IEEE Trans. Image Process. 21, 4709\u20134721 (2012)","journal-title":"IEEE Trans. Image Process."},{"key":"869_CR40","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1109\/TSP.2009.2036064","volume":"58","author":"I Bayram","year":"2010","unstructured":"Bayram, I., Selesnick, I.W.: A subband adaptive iterative shrinkage\/thresholding algorithm. IEEE Trans. Signal Process. 58, 1131\u20131143 (2010)","journal-title":"IEEE Trans. Signal Process."},{"key":"869_CR41","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1137\/080716542","volume":"2","author":"A Beck","year":"2009","unstructured":"Beck, A., Teboulle, M.: A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci. 2, 183\u2013202 (2009)","journal-title":"SIAM J. Imaging Sci."},{"key":"869_CR42","doi-asserted-by":"crossref","unstructured":"Zuo, W., Meng, D., Zhang, L., Feng, X., Zhang, D.: A generalized iterated shrinkage algorithm for non-convex sparse coding. In: IEEE International Conference on Computer Vision (ICCV) (2013)","DOI":"10.1109\/ICCV.2013.34"},{"key":"869_CR43","unstructured":"Pan, L., Xiu, N., Zhou, S.: Gradient Support Projection Algorithm for Affine Feasibility Problem with Sparsity and Nonnegativity. arXiv preprint (2014) arXiv:1406.7178"},{"key":"869_CR44","doi-asserted-by":"crossref","first-page":"4813","DOI":"10.1109\/TIT.2008.929920","volume":"54","author":"AM Bruckstein","year":"2008","unstructured":"Bruckstein, A.M., Elad, M., Zibulevsky, M.: On the uniqueness of non-negative sparse solutions to underdetermined systems of equations. IEEE Trans. Inf. Theory 54, 4813\u20134820 (2008)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"869_CR45","doi-asserted-by":"publisher","unstructured":"Zhang, B., Mu, Z., Zeng, H., Luo, S.: Robust ear recognition via nonnegative sparse representation of Gabor orientation information. Sci. World J. 2014, 131605 (2014). doi: 10.1155\/2014\/131605","DOI":"10.1155\/2014\/131605"},{"key":"869_CR46","doi-asserted-by":"crossref","first-page":"9446","DOI":"10.1073\/pnas.0502269102","volume":"102","author":"DL Donoho","year":"2005","unstructured":"Donoho, D.L., Tanner, J.: Sparse nonnegative solution of underdetermined linear equations by linear programming. Proc. Natl. Acad. Sci. 102, 9446\u20139451 (2005)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"869_CR47","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.neucom.2012.06.042","volume":"105","author":"F Zou","year":"2013","unstructured":"Zou, F., Feng, H., Ling, H., Liu, C., Yan, L., Li, P., Li, D.: Nonnegative sparse coding induced hashing for image copy detection. Neurocomputing 105, 81\u201389 (2013)","journal-title":"Neurocomputing"},{"key":"869_CR48","first-page":"775","volume":"2012","author":"L Qin","year":"2012","unstructured":"Qin, L., Xiu, N., Kong, L., Li, Y.: Linear program relaxation of sparse nonnegative recovery in compressive sensing microarrays. Comput. Math. Methods Med. 2012, 775\u2013795 (2012)","journal-title":"Comput. Math. Methods Med."},{"key":"869_CR49","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1109\/TNNLS.2012.2226471","volume":"24","author":"R He","year":"2013","unstructured":"He, R., Zheng, W.S., Hu, B.G., Kong, X.W.: Two-stage nonnegative sparse representation for large-scale face recognition. IEEE Trans. Neural Netw. Learn. Syst. 24, 35\u201346 (2013)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"869_CR50","doi-asserted-by":"crossref","unstructured":"Ji, Y., Lin, T., Zha, H.: Mahalanobis distance based non-negative sparse representation for face recognition. In: IEEE International Conference on Machine Learning and Applications, 2009 (ICMLA \u201909), pp. 41\u201346 (2009)","DOI":"10.1109\/ICMLA.2009.50"},{"key":"869_CR51","doi-asserted-by":"crossref","unstructured":"Luo, Z., Qin, L., Kong, L., Xiu, N.: The nonnegative zero-norm minimization under generalized z-matrix measurement. J. Optim. Theory Appl. 160, 854\u2013864 (2014)","DOI":"10.1007\/s10957-013-0325-5"},{"key":"869_CR52","doi-asserted-by":"crossref","unstructured":"Chen, Y., Zhang, H., Zuo, Y., Wang, D.: An improved regularized latent semantic indexing with $$L_{1\/2}$$ L 1 \/ 2 regularization and non-negative constraints. 16th International Conference on Computational Science and Engineering, IEEE (2013)","DOI":"10.1109\/CSE.2013.156"},{"key":"869_CR53","unstructured":"Sun, W., Yuan, Y.-X.: Optimization theory and methods: nonlinear programming. In: Springer Optimization and Its Applications, vol. 1, Springer, New York (2006)"},{"key":"869_CR54","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1007\/BF01589116","volume":"45","author":"DC Liu","year":"1989","unstructured":"Liu, D.C., Nocedal, J.: On the limited memory method for large scale optimization. Math. Program. B 45, 503\u2013528 (1989)","journal-title":"Math. Program. B"},{"key":"869_CR55","doi-asserted-by":"crossref","first-page":"1190","DOI":"10.1137\/0916069","volume":"16","author":"RH Byrd","year":"1995","unstructured":"Byrd, R.H., Lu, P., Nocedal, J.: A limited memory algorithm for bound constrained optimization. SIAM J. Sci. Stat. Comput. 16, 1190\u20131208 (1995)","journal-title":"SIAM J. Sci. Stat. Comput."}],"container-title":["Journal of Optimization Theory and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10957-016-0869-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10957-016-0869-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10957-016-0869-2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,3]],"date-time":"2019-09-03T19:01:45Z","timestamp":1567537305000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10957-016-0869-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,1,22]]},"references-count":55,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2016,9]]}},"alternative-id":["869"],"URL":"https:\/\/doi.org\/10.1007\/s10957-016-0869-2","relation":{},"ISSN":["0022-3239","1573-2878"],"issn-type":[{"value":"0022-3239","type":"print"},{"value":"1573-2878","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,1,22]]}}}