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J. Pivko, P. Makovický, A. Makarevich, A. Sirotkin, P. Makovický and E. Kubovičová

: Bromsulphatalein clearance and total billirubin level in cow deprived of food and water. Zbl. Vet. Med. A, 22, 605-610. 8. Edmonson, A. J., Lean, I. J., Weaver, L. D., Farver, T., Webster, G. 1989: A body condition scoring chart for Holstein dairy cows. J. Dairy Sci., 72, 68-78. 9. Enwonwu, C. O., Stambaugh, R., Sreebny, L., 1971: Synthesis and degradation of liver ribosomal RNA in fed and fasted rats. J. Nutr., 101, 337-346. 10. Fon Tacer, K., Rozman, D., 2011: Nonalcoholic fatty liver disease: focus on lipoprotein and lipid

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Syed Mudassir Laeeq, Abbas Ali Tasneem, Farina M. Hanif, Nasir Hassan Luck, Rajesh Mandhwani and Rajesh Wadhva

dysfunction and increased risk of vascular malformation. [ 2 ] Since GI diseases are common in ESRD patients, multiple studies have been conducted to study the endoscopic findings in this population. Most common reason for endoscopic evaluation has been UGIB. [ 2 , 4 ] Several scoring systems have also been developed to classify patients with UGIB according to their outcome. One such scoring system is the Glasgow Blatchford bleeding Score (GBS), a well-established tool to stratify patients in dire need of intervention from UGIB on the basis of their history, physical

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Jawaid Iqbal, Muhammad Ali Khalid, Farina M. Hanif, Rajesh Mandhwani, Syed Mudassir Laeeq, Zain Majid and Nasir Hassan Luck

Stage Liver Disease (MELD) is a validated chronic liver disease (CLD) severity scoring system that includes serum bilirubin, serum creatinine, and the international normalized ratio (INR). An increasing MELD score is associated with progression of hepatic dysfunction, severity and three-month mortality risk.[ 5 ] MELD is also used to prioritize patients on liver transplant waiting list. It is considered better than the Child-Turcotte-Pugh (CTP) score, in part, because of the inclusion of creatinine, which reflects the prognostic impact of renal function.[ 6

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Qiaozhi Wang, Hao Xue, Fengjun Li, Dongwon Lee and Bo Luo

. Liu and E. Terzi. A framework for computing the privacy scores of users in online social networks. ACM Transactions on Knowledge Discovery from Data , 5(1), 2010. [46] W. Liu and D. Ruths. What’s in a name? using first names as features for gender inference in twitter. In AAAI spring symposium: Analyzing microtext , volume 13, page 01, 2013. [47] B. Luo and D. Lee. On protecting private information in social networks: a proposal. In IEEE ICME Workshop of M3SN . IEEE, 2009. [48] A. Machanavajjhala, D. Kifer, J. Gehrke, and M. Venkitasubramaniam

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Milorad M. Stojadinovic, Damjan N. Pantic and Miroslav M. Stojadinovic

(9):1228-42. PubMed PMID: 16096414. 8. Brawley OW (2012). Trends in prostate cancer in the United States. J Natl Cancer Inst Monogr. 2012(45):152-6. doi: 10.1093/jncimonographs/lgs035. 9. Pepe P, Pennisi M (2015). Gleason score stratification according to age at diagnosis in 1028 men. Contemp Oncol (Pozn). 19(6):471-3. doi: 10.5114/ wo.2015.56654. 10. Muralidhar V, Ziehr DR, Mahal BA, Chen YW, Nezolosky MD, Viswanathan VB, et al. (2015). Association Between Older Age and Increasing Gleason Score. Clin Genitourin Cancer. 13

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Bangon Pinkaew, Paraya Assanasen and Chaweewan Bunnag

blindfolded with a hygienic face mask to prevent visual detection of the substances. Participants were allowed to sniff each bottle only once to save time. Three bottles were then presented to each nostril in a fixed randomized order with a total of 16 trials. If participants answered correctly, bottles containing odorous or odorless substances in triplicate for each trial were used and one score was given. Smell discrimination scores of each nostril ranged from 0 to 16. Smell identification test The smell identification or odorant naming test (SIT) was conducted

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Milka Elena Escalera Chávez and Cristóbal Hernández

References Altman, E. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. The Journal of Finance, 23: 589-609. DOI: 10.1111/j.1540-6261.1968.tb00843.x. Altman, E. (2013). Predicting financial distress of companies: Revisiting the Z score and zeta models.in Edward Elgar Publishing (eds) Handbook of Research Methods and Applications in Empirical Finance, 428-455.DOI:10.4337/9780857936097.00027 Argenti, J. (1976). Corporate planning and Corporate Collapse. Long Range Planning

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José M. Pratas, Anna Volossovitch and Ana I. Carita

Introduction In soccer, it has been demonstrated that performance of teams can be influenced by the scoreline ( Lago-Peñas, 2012 ; Gómez et al., 2013). Soccer players perform significantly less high-intensity activity when winning than when losing or when the score is tied ( Lago et al., 2010 ). It was also shown that teams had longer periods of possession in matches when they were losing than when they were winning (Lago-Peñas and Dellal, 2010; Lago-Peñas and Gomez-Lopez, 2014), teams played more in the attack and defensive zones when the score was level

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Marco Di Zio and Ugo Guarnera

., and Scholtus, S. (2011). Handbook of Statistical Data Editing and Imputation. New York: John Wiley and Sons. Ghosh-Dastidar, B. and Schafer, J.L. (2006). Outlier Detection and Editing Procedures for Continuous Multivariate Data. Journal of Official Statistics, 22, 487-506. Granquist, L. (1997). The New View on Editing. International Statistical Review, 65, 381-387. Hedlin, D. (2003). Score Functions to Reduce Business Survey Editing at the U.K. Office for National Statistics. Journal of Official Statistics, 19, 177

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Enrico Fiore, Laura Perillo, Giorgio Marchesini, Giuseppe Piccione, Elisabetta Giudice, Alessandro Zumbo, Leonardo Armato, Giorgia Fabbri and Matteo Gianesella

References Bicalho R.C., Oikonomou G. (2013). Control and prevention of lameness associated with claw lesions in dairy cows. Livest. Sci., 156: 96–105. Bicalho R.C., Cheong S.H., Cramer G., Guard C.L. (2007). Association between a visual and an automated locomotion score in lactating Holstein cows. J. Dairy Sci., 90: 3294–3300. Brzozowska A., Łukaszewicz M., Sender G., Kolasińska D., Oprządek J. (2014). Locomotor activity of dairy cows in relation to season and lactation. Appl. Anim. Behav. Sci., 156: 6–11. Chesterton R.N., Lawrence K