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Runoff forecasting is crucial for planning and managing water resources. As hydrological data becomes more available, more data-driven models are being employed to enhance the effectiveness of runoff forecasting. To accurately and quantitatively assess the whole runoff forecast process, from model construction to application, a whole life cycle forecasting evaluation index system was established in this study to evaluate the data, factors, sample integrity, model construction, and forecast result. The analysis included quantitative evaluation criteria to comprehensively consider data quality, forecasting factor characterization, sample representativeness, model generalization, and result quality. An evaluation of forecast results from 7 river basins and their 85 hydrological stations in China showed that the proposed index system could accurately reflect the performance of the forecasting process. The overall performance of the forecasting model and process can be evaluated quantitatively based on the Euclidean distance, and the pathways to improve the forecasting effectiveness of the model can be identified based on the evaluation results. The validity of the proposed index is also experimentally demonstrated. The proposed index system can be applied to the evaluation of data-driven forecasting processes in various fields. [ABSTRACT FROM AUTHOR]

Background. Parkinson's disease (PD) is a neurodegenerative disease, a hallmark by the formation of misfolded and aggregated α-synuclein proteins. The expression of potential microRNA (miRNA) candidates isolated from serum and cerebrospinal fluid (CSF) exosomes of PD patients was assessed for their diagnostic value and their potential role as biomarkers for PD was explored. In this study, we characterize the expression level of miRNAs in the exosomes of blood sera and cerebrospinal fluid and explore their potential role as biomarkers for PD. Materials and Methods. A total of 209 patients having an onset of PD, along with 60 neurodegenerative (ND) disorders and 50 healthy controls were enrolled. Blood samples and CSF samples were collected and exosomes were isolated. The isolated exosomes were characterized using CD63 detection and exosomal RNA was extracted. Serum miRNA profiling was carried out by synthesizing cDNA from the purified RNA and miRNA transcripts were determined by qRT-PCR using SYBR Green PremixScript. microRNA profiling strategy was employed for extracting the exosomal miRNAs from the exosomes. Results. Five common miRNAs viz. miR-151a-5p, miR-24, mir-485-5p, mir-331-5p, and mir-214 were found to be upregulated with statistical significance in both the serum exosome and CSF exosomes. The investigation revealed that serum and CSF exosomal miRNA molecules are definitive biomarkers for PD with proper specificity and sensitivity. Conclusions. The significant level of miR-151a-5p, miR-24, mir-485-5p, mir-331-5p, and mir-214 was observed in the serum and CSF which may be established as a biomarker for the diagnosis of PD. [ABSTRACT FROM AUTHOR]