predictive methods
Recently Published Documents

ABSTRACT Single-nucleotide polymorphism (SNPs) may cause the diverse functional impact on RNA or protein changing genotype and phenotype, which may lead to common or complex diseases like cancers. Accurate prediction of the functional impact of SNPs is crucial to discover the ‘influential’ (deleterious, pathogenic, disease-causing, and predisposing) variants from massive background polymorphisms in the human genome. Increasing computational methods have been developed to predict the functional impact of variants. However, predictive performances of these computational methods on massive genomic variants are still unclear. In this regard, we systematically evaluated 14 important computational methods including specific methods for one type of variant and general methods for multiple types of variants from several aspects; none of these methods achieved excellent (AUC ≥ 0.9) performance in both data sets. CADD and REVEL achieved excellent performance on multiple types of variants and missense variants, respectively. This comparison aims to assist researchers and clinicians to select appropriate methods or develop better predictive methods.

The article analyzes the literature data on the etiopathogenetic aspects of polyhydramnios, taking into account the leading risk factors for development. Despite the knowledge of the etiological aspects, the development of diagnostic tactics and predictive methods, the frequency of polyhydramnios does not tend to decrease, but remains at the level of 3-12% of the total number of births. Being a leading medical and social problem, which leads to high childhood morbidity, disability, as well as death, negatively affecting the quality of life not only of a single family, but also on the gene pool of the nation.

In this paper, we addressed the flow patterns over a light boxplane scale model to explain the previously discovered disagreement between its predicted and experimental aerodynamic characteristics. By tuft flow and CFD visualization, we explored the causes yielding a large zero lift pitching moment coefficient, lateral divergence, difference in fore and aft elevator lift, and poor high lift performance of the aircraft. The investigation revealed that the discrepancy in the pitching moment coefficient and lateral stability derivatives can be attributed to insufficient accuracy of the used predictive methods. The difference in fore and aft elevator lift and poor high lift performance of the aircraft may occur due to the low local Reynolds number, which causes the early flow separation over the elevators and flaperons when deflected downward at angles exceeding 10°. Additionally, some airframe changes are suggested to alleviate the lateral divergence of the model.

This paper presents an extended comparison study between 16 different linear and non-linear regression methods to predict the sugar, pH, and anthocyanin contents of grapes through hyperspectral imaging (HIS). Despite the numerous studies on this subject that can be found in the literature, they often rely on the application of one or a very limited set of predictive methods. The literature on multivariate regression methods is quite extensive, so the analytical domain explored is too narrow to guarantee that the best solution has been found. Therefore, we developed an integrated linear and non-linear predictive analytics comparison framework (L&NL-PAC), fully integrated with five preprocessing techniques and five different classes of regression methods, for an effective and robust comparison of all alternatives through a robust Monte Carlo double cross-validation stratified data splitting scheme. L&NLPAC allowed for the identification of the most promising preprocessing approaches, best regression methods, and wavelengths most contributing to explaining the variability of each enological parameter for the target dataset, providing important insights for the development of precision viticulture technology, based on the HSI of grape. Overall, the results suggest that the combination of the Savitzky−Golay first derivative and ridge regression can be a good choice for the prediction of the three enological parameters.

A tricky aspect in the use of all multivariate analysis methods is the choice of the number of Latent Variables to use in the model, whether in the case of exploratory methods such as Principal Components Analysis (PCA) or predictive methods such as Principal Components Regression (PCR), Partial Least Squares regression (PLS). For exploratory methods, we want to know which Latent Variables deserve to be selected for interpretation and which contain only noise. For predictive methods, we want to ensure that we include all the variability of interest for the prediction, without introducing variability that would lead to a reduction in the quality of the predictions for samples other than those used to create the multivariate model.

Abstract The Document on Rain (Yushu 雨書) is a short manuscript that forms part of the Beijing University collection of Han slips. This text, divided into two sections, has thus far garnered little scholarly attention. However, it presents to us an unusual example of a daybook (rishu 日書)-type manuscript, one which is primarily concerned with the weather. The Document on Rain, while sharing many characteristics of excavated daybooks, is unusual in its treatment of humans. Rather than providing advice on whether or not one should undertake activity on a certain day or engaging in the discourse about whether or not humans can manipulate the weather, the Document on Rain represents an understanding of the weather as a phenomenon that cannot be manipulated by humans, but one which can, perhaps, be understood. The Document on Rain integrates practices of prognostication based on calendrical and sexagenary cycles with theories about rain and its relationship to the symbolic characteristics of the twenty-eight lodges (ershiba xiu 二十八宿). This article analyses some of the predictive methods in the text and situates it within a longer tradition of meteoromantic practices.