Monte Carlo Procedure for Protein Design

A new method for sequence optimization in protein models is presented. The approach, which has inherited its basic philosophy from recent work by Deutsch and Kurosky [Phys. Rev. Lett. 76, 323 (1996)] by maximizing conditional probabilities rather than minimizing energy functions, is based upon a novel and very efficient multisequence Monte Carlo scheme. By construction, the method ensures that the designed sequences represent good folders thermodynamically. A bootstrap procedure for the sequence space search is devised making very large chains feasible. The algorithm is successfully explored on the two-dimensional HP model with chain lengths N=16, 18 and 32.Comment: 7 pages LaTeX, 4 Postscript figures; minor change

Geometric representations for minimalist grammars

We reformulate minimalist grammars as partial functions on term algebras for strings and trees. Using filler/role bindings and tensor product representations, we construct homomorphisms for these data structures into geometric vector spaces. We prove that the structure-building functions as well as simple processors for minimalist languages can be realized by piecewise linear operators in representation space. We also propose harmony, i.e. the distance of an intermediate processing step from the final well-formed state in representation space, as a measure of processing complexity. Finally, we illustrate our findings by means of two particular arithmetic and fractal representations.Comment: 43 pages, 4 figure

On the representation error in data assimilation

Representation, representativity, representativeness error, forward interpolation error, forward model error, observation operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This paper is an attempt to consolidate the terminology that has been used in the earth sciences literature and was suggested at a European Space Agency workshop held in Reading in April 2014. We review the state-of-the-art, and through examples, motivate the terminology. In addition to a theoretical framework, examples from application areas of satellite data assimilation, ocean reanalysis and atmospheric chemistry data assimilation are provided. Diagnosing representation error statistics as well as their use in state-of-the-art data assimilation systems is discussed within a consistent framework

PAN@FIRE: Overview of the cross-language !ndian Text re-use detection competition

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40087-2_6The development of models for automatic detection of text re-use and plagiarism across languages has received increasing attention in recent years. However, the lack of an evaluation framework composed of annotated datasets has caused these efforts to be isolated. In this paper we present the CL!TR 2011 corpus, the first manually created corpus for the analysis of cross-language text re-use between English and Hindi. The corpus was used during the Cross-Language !ndian Text Re-Use Detection Competition. Here we overview the approaches applied the contestants and evaluate their quality when detecting a re-used text together with its source.This research work is partially funded by the WIQ-EI (IRSES grant n. 269180)and ACCURAT (grant n. 248347) projects, and the Seventh Framework Programme (FP7/2007-2013) under grant agreement n. 246016 from the European Union. The first author was partially funded by the CONACyT-Mexico 192021 grant and currently works under the ERCIM “Alain Bensoussan” Fellowship Programme. The research of the second author is in the framework of the VLC/Campus Microcluster on Multimodal Interaction in Intelligent Systems and partially funded by the MICINN research project TEXT-ENTERPRISE 2.0 TIN2009-13391-C04-03 (plan I+D+i). The research from AU-KBC Centre is supported by the Cross Lingual Information Access (CLIA) Phase II Project.Barrón Cedeño, LA.; Rosso ., P.; Sobha, LD.; Clough ., P.; Stevenson ., M. (2013). PAN@FIRE: Overview of the cross-language !ndian Text re-use detection competition. En Multilingual Information Access in South Asian Languages. Springer Verlag (Germany). 7536:59-70. https://doi.org/10.1007/978-3-642-40087-2_6S59707536Addanki, K., Wu, D.: An Evaluation of MT Alignment Baseline Approaches upon Cross-Lingual Plagiarism Detection. In: FIRE [12]Aggarwal, N., Asooja, K., Buitelaar, P.: Cross Lingual Text Reuse Detection Using Machine Translation & Similarity Measures. In: FIRE [12]Alegria, I., Forcada, M., Sarasola, K. (eds.): Proceedings of the SEPLN 2009 Workshop on Information Retrieval and Information Extraction for Less Resourced Languages. University of the Basque Country, Donostia, Donostia (2009)Barrón-Cedeño, A., Rosso, P., Pinto, D., Juan, A.: On Cross-Lingual Plagiarism Analysis Using a Statistical Model. In: Stein, B., Stamatatos, E., Koppel, M. (eds.) ECAI 2008 Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN 2008), vol. 377, pp. 9–13. CEUR-WS.org, Patras (2008), http://ceur-ws.org/Vol-377Bendersky, M., Croft, W.: Finding Text Reuse on the Web. In: Baeza-Yates, R., Boldi, P., Ribeiro-Neto, B., Cambazoglu, B. (eds.) Proceedings of the Second ACM International Conference on Web Search and Web Data Mining, pp. 262–271. ACM, Barcelona (2009)Ceska, Z., Toman, M., Jezek, K.: Multilingual Plagiarism Detection. In: Proceedings of the 13th International Conference on Artificial Intelligence (ICAI 2008), pp. 83–92. Springer, Varna (2008)Clough, P.: Plagiarism in Natural and Programming Languages: an Overview of Current Tools and Technologies. Research Memoranda: CS-00-05, Department of Computer Science. University of Sheffield, UK (2000)Clough, P.: Old and new challenges in automatic plagiarism detection. National UK Plagiarism Advisory Service (2003), http://ir.shef.ac.uk/cloughie/papers/pasplagiarism.pdfClough, P., Gaizauskas, R.: Corpora and Text Re-Use. In: Lüdeling, A., Kytö, M., McEnery, T. (eds.) Handbook of Corpus Linguistics. Handbooks of Linguistics and Communication Science, pp. 1249–1271. Mouton de Gruyter (2009)Clough, P., Stevenson, M.: Developing a Corpus of Plagiarised Examples. Language Resources and Evaluation 45(1), 5–24 (2011)Comas, R., Sureda, J.: Academic Cyberplagiarism: Tracing the Causes to Reach Solutions. In: Comas, R., Sureda, J. (eds.) Academic Cyberplagiarism [online dossier], Digithum. Iss, vol. 10, pp. 1–6. UOC (2008), http://bit.ly/cyberplagiarism_csMajumder, P., Mitra, M., Bhattacharyya, P., Subramaniam, L., Contractor, D., Rosso, P. (eds.): FIRE 2010 and 2011. LNCS, vol. 7536. Springer, Heidelberg (2013)Gale, W., Church, K.: A Program for Aligning Sentences in Bilingual Corpora. Computational Linguistics 19, 75–102 (1993)Ghosh, A., Bhaskar, P., Pal, S., Bandyopadhyay, S.: Rule Based Plagiarism Detection using Information Retrieval. In: Petras, et al. [24]Gupta, P., Singhal, K.: Mapping Hindi-English Text Re-use Document Pairs. In: FIRE [12]Head, A.: How today’s college students use Wikipedia for course-related research. First Monday 15(3) (March 2010), http://www.uic.edu/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2830/2476IEEE: A Plagiarism FAQ (2008), http://bit.ly/ieee_plagiarism (published: 2008; accessed March 3, 2010)Kulathuramaiyer, N., Maurer, H.: Coping With the Copy-Paste-Syndrome. In: Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2007 (E-Learn 2007), pp. 1072–1079. AACE, Quebec City (2007)Lee, C., Wu, C., Yang, H.: A Platform Framework for Cross-lingual Text Relatedness Evaluation and Plagiarism Detection. In: Proceedings of the 3rd International Conference on Innovative Computing Information (ICICIC 2008). IEEE Computer Society (2008)Martínez, I.: Wikipedia Usage by Mexican Students. The Constant Usage of Copy and Paste. In: Wikimania 2009, Buenos Aires, Argentina (2009), http://wikimania2009.wikimedia.orgMaurer, H., Kappe, F., Zaka, B.: Plagiarism - a survey. Journal of Universal Computer Science 12(8), 1050–1084 (2006)Palkovskii, Y., Belov, A.: Exploring Cross Lingual Plagiarism Detection in Hindi-English with n-gram Fingerprinting and VSM based Similarity Detection. In: FIRE [12]Palkovskii, Y., Belov, A., Muzika, I.: Using WordNet-based Semantic Similarity Measurement in External Plagiarism Detection - Notebook for PAN at CLEF 2011. In: Petras, et al. [24]Petras, V., Forner, P., Clough, P. (eds.): Notebook Papers of CLEF 2011 LABs and Workshops, Amsterdam, The Netherlands (September 2011)Potthast, M., Stein, B., Eiselt, A., Barrón-Cedeño, A., Rosso, P.: Overview of the 1st international competition on plagiarism detection. In: Stein, B., Rosso, P., Stamatatos, E., Koppel, M., Agirre, E. (eds.) SEPLN 2009 Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN 2009), vol. 502, pp. 1–9. CEUR-WS.org, San Sebastian (2009), http://ceur-ws.org/Vol-502Potthast, M., Barrón-Cedeño, A., Stein, B., Rosso, P.: Cross-Language Plagiarism Detection. Language Resources and Evaluation (LRE), Special Issue on Plagiarism and Authorship Analysis 45(1), 1–18 (2011)Potthast, M., Eiselt, A., Barrón-Cedeño, A., Stein, B., Rosso, P.: Overview of the 3rd International Competition on Plagiarism Detection. In: Petras, et al. [24]Potthast, M., Stein, B., Barrón-Cedeño, A., Rosso, P.: An Evaluation Framework for Plagiarism Detection. In: Huang, C.R., Jurafsky, D. (eds.) Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), pp. 997–1005. COLING 2010 Organizing Committee, Beijing (2010)Potthast, M., Barrón-Cedeño, A., Eiselt, A., Stein, B., Rosso, P.: Overview of the 2nd International Competition on Plagiarism Detection. In: Braschler, M., Harman, D. (eds.) Notebook Papers of CLEF 2010 LABs and Workshops, Padua, Italy (September 2010)Rambhoopal, K., Varma, V.: Cross-Lingual Text Reuse Detection Based On Keyphrase Extraction and Similarity Measures. In: FIRE [12]Weber, S.: Das Google-Copy-Paste-Syndrom. Wie Netzplagiate Ausbildung und Wissen gefahrden. Telepolis (2007

Demand-Orientated Power Production from Biogas: Modeling and Simulations under Swedish Conditions

The total share of intermittent renewable electricity is increasing, intensifying the need for power balancing in future electricity systems. Demand-orientated combined heat and power (CHP) production from biogas has potential for this purpose. An agricultural biogas plant, using cattle manure and sugar beet for biogas and CHP production, was analyzed here. The model Dynamic Biogas plant Model (DyBiM) was developed and connected to the Anaerobic Digestion Model No. 1 (ADM1). Flexible scenarios were simulated and compared against a reference scenario with continuous production, to evaluate the technical requirements and economic implications of demand-orientated production. The study was set in Swedish conditions regarding electricity and heat price, and the flexibility approaches assessed were increased CHP and gas storage capacity and feeding management. The results showed that larger gas storage capacity was needed for demand-orientated CHP production but that feeding management reduced the storage requirement because of fast biogas production response to feeding. Income from electricity increased by 10%, applying simple electricity production strategies to a doubled CHP capacity. However, as a result of the currently low Swedish diurnal electricity price variation and lack of subsidies for demand-orientated electricity production, the increase in income was too low to cover the investment costs. Nevertheless, DyBiM proved to be a useful modeling tool for assessing the economic outcome of different flexibility scenarios for demand-orientated CHP production

Natriuretic peptide activation of extracellular regulated kinase 1/2 (ERK1/2) pathway by particulate guanylyl cyclases in GH3 somatolactotropes.

The natriuretic peptides, Atrial-, B-type and C-type natriuretric peptides (ANP, BNP, CNP), are regulators of many endocrine tissues and exert their effects predominantly through the activation of their specific guanylyl cyclase receptors (GC-A and GC-B) to generate cGMP. Whereas cGMP-independent signalling has been reported in response to natriuretic peptides, this is mediated via either the clearance receptor (Npr-C) or a renal-specific NPR-Bi isoform, which both lack intrinsic guanylyl cyclase activity. Here, we report evidence of GC-B-dependent cGMP-independent signalling in pituitary GH3 cells. Stimulation of GH3 cells with CNP resulted in a rapid and sustained enhancement of ERK1/2 phosphorylation (P-ERK1/2), an effect that was not mimicked by dibutryl-cGMP. Furthermore, CNP-stimulated P-ERK1/2 occurred at concentrations below that required for cGMP accumulation. The effect of CNP on P-ERK1/2 was sensitive to pharmacological blockade of MEK (U0126) and Src kinases (PP2). Silencing of the GC-B1 and GC-B2 splice variants of the GC-B receptor by using targeted short interfering RNAs completely blocked the CNP effects on P-ERK1/2. CNP failed to alter GH3 cell proliferation or cell cycle distribution but caused a concentration-dependent increase in the activity of the human glycoprotein α-subunit promoter (αGSU) in a MEK-dependent manner. Finally, CNP also activated the p38 and JNK MAPK pathways in GH3 cells. These findings reveal an additional mechanism of GC-B signalling and suggest additional biological roles for CNP in its target tissues

Bevacizumab for the Treatment of Recurrent Glioblastoma

Despite advances in upfront therapy, the prognosis in the great majority of patients with glioblastoma (GBM) is poor as almost all recur and result in disease-related death. Glioblastoma are highly vascularized cancers with elevated expression levels of vascular endothelial growth factor (VEGF), the dominant mediator of angiogenesis. A compelling biologic rationale, a need for improved therapy, and positive results from studies of bevacizumab in other cancers led to the evaluation of bevacizumab in the treatment of recurrent GBM. Bevacizumab, a humanized monoclonal antibody that targets VEGF, has been shown to improve patient outcomes in combination with chemotherapy (most commonly irinotecan) in recurrent GBM, and on the basis of positive results in two prospective phase 2 studies, bevacizumab was granted accelerated approval by the US Food and Drug Administration (FDA) as a single agent in recurrent GBM. Bevacizumab therapy is associated with manageable, class-specific toxicity as severe treatment-related adverse events are observed in only a minority of patients. With the goal of addressing questions and controversies regarding the optimal use of bevacizumab, the objective of this review is to provide a summary of the clinical efficacy and safety data of bevacizumab in patients with recurrent GBM, the practical issues surrounding the administration of bevacizumab, and ongoing investigations of bevacizumab in managing GBM