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Jerzy Wiśniewski

References Churgin, J. (1985). How to Count the Uncountable. Warsaw: Common Knowledge. Encyclopedia (2004). Kraków: Polish Scientific Publishers PWN, Vol. 10. Stevens, S.S. (1946). On the Theory of Measurement Scales. Science , Vol. 103, No. 2684. Wiśniewski, J.W. (1986). Econometric Study of Qualitative Phenomena. Methodological Study , Toruń: Scientific Publishers, Nicolaus Copernicus University. Wiśniewski, J.W. (2009

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Teodoro Lara, Nelson Merentes, Edgar Rosales and Ambrosio Tineo

References [1] Bohner M., Peterson A., Dynamic equations on time scales. An introduction with applications, Birkhäuser, Boston, 2001. [2] Dinu C., Convex functions on time scales, An. Univ. Craiova Ser. Mat. Inform. 35 (2008), 87-96. [3] Dinu C., Hermite-Hadamard inequality on time scales, J. Inequal. Appl. 2008 (2008), Art. ID 287947, 24 pp. [4] Hilger S., Analysis on measure chains-a unified approach to continuous and discrete calculus, Results Math. 18 (1990), 18-56. [5

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Adrian Duşa and Valeriu Frunzaru

. Bucureşti: Editura Economică. Cook, C., Heath, F., Thomson, R.L. and B. Thomson (2001) Score Reliability in Web- or Internet-Based Surveys: Unnumbered Graphic Rating Scales Versus Likert-Type Scales. Educational and Psychological Measurement , 61(4):697-706. Dawes, J. (2008) Do Data Characteristics Change According to the Number of Scales Points Used? An Experiment using a 5-point, 7-point and 10-point scales. International Journal of Market Research , 50(1):66-77. Finn, R.H. (1972) Effects of some variations in rating scale characteristics on the

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Qianhong Zhang, Yuanfu Shao and Jingzhong Liu

.1007/s11071-010-9664-z 4. Bohner, M.; Fan, M.; Zhang, J. - Existence of periodic solutions in predatorprey and competition dynamic systems, Nonlinear Anal. Real World Appl., 7 (2006), 1193-1204. 10.1016/j.nonrwa.2005.11.002 5. Bohner, M.; Peterson, A. - Advances in Dynamic Equations on Time Scales, Birkh¨auser, Boston, 2003. 6. Bohner, M.; Peterson, A. - Dynamic Equations on Time Scales. An Introduction with Applications, Birkh¨auser Boston, Inc., Boston, MA, 2001. 7. Cao, J.; Wang, J. - Global asymptotic

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Iwona Markowicz

References Parasuraman, A., Berry, L. L. & Zeithaml, V. A. (1988). Communication and Control Processes in the Delivery of Service Quality. Journal of Marketing , 52. Parasuraman, A., Berry, L. L. & Zeithaml, V. A. (1988). SERVQUAL: A Multiple-Item Scale for Measuring Customer Perceptions of Service Quality. Journal of Retailing , 64. Sagan, A. (2004). Jeden obraz ukazuje więcej niż 10 liczb, czyli jak budować mapy zadowolenia klienta z wykorzystaniem programu STATISTICA

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Taher S. Hassan and Said R. Grace

References [1] BOHNER, M.: Some oscillation criteria for first order delay dynamic equations, Far East J. Appl. Math. 18 (2005), 289-304. [2] BOHNER, M.-PETERSON, A.: Dynamic Equations on Time Scales: An Introduction with Applications. Birkh¨auser, Boston, 2001. [3] DURINA, J.-BACULIKOVA, B.: Property (A) of third-order advanced differential equations, Math. Slovaca 64 (2014), 339-346. [4] GRACE, S. R.-AGARWAL, R. P.-AKTAS, M. F.: On the oscillation of third order functional differential

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Katarzyna Paduszyńska, Krzysztof Kaczka, Agnieszka Dworzyńska, Karol Sieniawski and Lech Pomorski


The aim of the study was to assess the usefulness of prognostic scales: ASA (American Society of Anesthesiologist), MPI (Meinheim Peritonitis Index), MOFS (the Multiple Organ Failure Score) and SPI (the Simple Prognostic Index) in the prognosis of the course of disease in patients operated on for peritonitis.

Material and methods. The study was conducted in the Clinical Department of General and Oncological Surgery of the Medical University in Łódź between January 2009 to December 2010. During this period 263 patients were operated on for peritonitis. Before surgery all patients were classifed into particular groups according to the above mentioned prognostic scales according to their criteria.

Results. There were 29 (11%) deaths. ASA ≥4 (p<0.0001), MPI >30 (p<0.0001) MOFS ≥2 (p<0.0001), SPI II, III, IV (p<0.0001) were important risk factors of death.

Conclusions. 1. ASA, MPI, MOFS and SPI scales are of high signifcance in predicting the outcome in patients operated on for peritonitis. 2. The ASA scale in spite and due to its simplicity is adequate enough to be used in everyday practice in patients operated on for peritonitis. 3. The MPI scale is most suitable in the scientifc aims and in comparing the outcomes of patients operated on for peritonitis.

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Maria P. Shindova and Ani B. Belcheva

;58(1):31-7. 9. Hosey MT, Blinkhorn AS. An evaluation of four methods of assessing the behaviour of anxious child dental patients. Int J Paediatr Dent 1995;5(2):87-95. 10. Parkin SF. Assessment of the clinical validity of a simple scale for rating children’s dental anxiety. J Dent Child 1989;56(1):40-3. 11. Baum A, Singer JE, Singer JL. Issues in child health and adolescent health: handbook of psychology and health. 2 ed. Psychology Press; 2013;149-52. 12. Aartman I, Everdingen T, Hoogstraten J, et al. Appraisal of behavioral measurement techniques for

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Cristian Dinu, Mihai Stancu and Daniela Dănciulescu

References [1] R. P. Agarwal, M. Bohner, Basic calculus on time scales and some of its applications, Results Math. 35 (1999), 3-22. [2] M. Bohner and A. Peterson, Dynamic Equations on Time Scales, An introduction with Applications, Birkhäuser, Boston, 2001. [3] C. Dinu, A weighted Hermite-Hadamard inequality for Steffensen- Popoviciu and Hermite-Hadamard weights on time scales, Analele Ştiinţifice ale Universităţii \Ovidius", Constanţa, Ser. Mat., 17 (2009). [4] C. Dinu, \Hermite

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Bartłomiej Jefmański

References Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika , 43, 561–573. DOI: 10.1007/BF02293814. Bojadziev, M. & Bojadziev, G. (1995). Fuzzy Sets, Fuzzy Logic, Applications . Singapore: World Scientific Publishing. Carrasco, R.A., Munoz-Leiva, F., Sánchez-Fernández, J. & Liébana-Cabanillas, F.J. (2012). A model for the integration of e-financial services questionnaires with SERVQUAL scales under fuzzy linguistic modeling. Expert Systems with Applications , 39, 1535–1547. DOI: 10.1016/j.eswa.2012