Given a passage classify if the passage has a definite objective/aim/goal or not. Output '1' if the passage has a defininte objective/aim/goal and output '0' if the passage does not have a definite objective/aim/goal.

Example Input: Biomarkers predictive of recovery from acute kidney injury (AKI) after liver transplantation (LT) could enhance decision algorithms regarding the need for liver-kidney transplantation or renal sparing regimens. Multianalyte plasma/urine kidney injury protein panels were performed immediately before and 1 month post-LT in an initial test group divided by reversible pre-LT AKI (rAKI = post-LT renal recovery) versus no AKI (nAKI). This was followed by a larger validation set that included an additional group: irreversible pre-LT AKI (iAKI = no post-LT renal recovery). In the test group (n = 16), six pre-LT plasma (not urine) kidney injury proteins (osteopontin [OPN], neutrophil gelatinase-associated lipocalin, cystatin C, trefoil factor 3, tissue inhibitor of metalloproteinase [TIMP]-1, and -2-microglobulin) were higher in rAKI versus nAKI (P < 0.05) and returned to normal values with renal recovery post-LT. In the validation set (n = 46), a number of proteins were significantly higher in both rAKI and iAKI versus nAKI. However, only pre-LT plasma OPN (P = 0.009) and TIMP-1 (P = 0.019) levels were significantly higher in rAKI versus iAKI. Logistic regression modeling was used to correlate the probability of post-LT rAKI, factoring in both pre-LT protein markers and clinical variables. A combined model including elevated OPN and TIMP-1 levels, age <57, and absence of diabetes had the highest area under the curve of 0.82, compared to protein-only and clinical variable-only models.
Example Output: 0

Example Input: The ability of Yersinia pestis to form a biofilm is an important characteristic in flea transmission of this pathogen. Y. pestis laterally acquired two plasmids (pPCP1and pMT1) and the ability to form biofilms when it evolved from Yersinia pseudotuberculosis. Small regulatory RNAs (sRNAs) are thought to play a crucial role in the processes of biofilm formation and pathogenesis.', 'A pPCP1-derived sRNA HmsA (also known as sR084) was found to contribute to the enhanced biofilm formation phenotype of Y. pestis. The concentration of c-di-GMP was significantly reduced upon deletion of the hmsA gene in Y. pestis. The abundance of mRNA transcripts determining exopolysaccharide production, crucial for biofilm formation, was measured by primer extension, RT-PCR and lacZ transcriptional fusion assays in the wild-type and hmsA mutant strains. HmsA positively regulated biofilm synthesis-associated genes (hmsHFRS, hmsT and hmsCDE), but had no regulatory effect on the biofilm degradation-associated gene hmsP. Interestingly, the recently identified biofilm activator sRNA, HmsB, was rapidly degraded in the hmsA deletion mutant. Two genes (rovM and rovA) functioning as biofilm regulators were also found to be regulated by HmsA, whose regulatory effects were consistent with the HmsA-mediated biofilm phenotype.
Example Output: 0

Example Input: Both diet quality (DQ) and physical activity (PA) have been shown to play a role in the prevention of functional capacity (FC) decline. Because older adults (OA) with T2D are at a higher risk of FC decline compared to their non-diabetic counterparts, our aim was to determine if DQ alone, or combined with PA is associated with FC decline in OA with T2D over a 3-year follow-up in a secondary analysis of the NuAge cohort.', "In 159 OA with T2D (mean age=75 years), FC change was calculated as the difference in FC scores at T1 and T4 measured by the SMAF (Systeme de Mesure de l'Autonomie Fonctionnelle). Baseline DQ was calculated from three non-consecutive 24-h dietary recalls collected at T1 using the validated Canadian Healthy Eating Index (C-HEI). PA change was calculated from Physical Activity Scale for the Elderly (PASE) as T4-T1. Associations were evaluated between FC decline and four combinations of variables: C-HEI score < or 70 with PASE change < or > median and analyzed by GLM while controlling for covariates.", 'Neither DQ alone nor DQ combined with PA change were associated with FC decline over follow-up.
Example Output:
0