Summary fading knowledge of results (Kr): Test for the dynamic acquisition protocols

The primary purpose of this study was to examine the effects of dynamic acquisition protocols by comparing dynamic and static KR schedules in a single experiment. Five groups of participants (n = 13 per group) completed 90 acquisition trials of a force production task. The analysis of delayed no-KR retention test revealed that the participants in the summary fading KR group performed better than the three static KR groups, indicating that the dynamic acquisition protocols produces more efficient learning than static acquisition protocols. This finding is interpreted as support for Adams\u27 theory (1971) that the most appropriate acquisition protocol would be one that dynamically manipulates KR from higher frequency at beginning to lower frequency toward the end of the practice. However, the failure in finding the learning effect of reduced KR in this experiment is inconsistent with the conclusion of the previous studies (Guadagnoli et al., 1996, Winstein & Schmidt, 1990). The reasons for this discrepancy are discussed and the future directions are provided

Estrada index of hypergraphs via eigenvalues of tensors

A uniform hypergraph $\mathcal{H}$ is corresponding to an adjacency tensor $\mathcal{A}_\mathcal{H}$. We define an Estrada index of $\mathcal{H}$ by using all the eigenvalues $\lambda_1,\dots,\lambda_k$ of $\mathcal{A}_\mathcal{H}$ as $\sum_{i=1}^k e^{\lambda_i}$. The bounds for the Estrada indices of uniform hypergraphs are given. And we characterize the Estrada indices of $m$-uniform hypergraphs whose spectra of the adjacency tensors are $m$-symmetric. Specially, we characterize the Estrada indices of uniform hyperstars

NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm

BACKGROUND: Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design. RESULTS: In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed) and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM), also have been employed and compared with NBA-Palm. CONCLUSION: Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from:

Heat Transfer Correlations for Supercritical Water in Vertically Upward Tubes

Supercritical pressure water (SCW) has been widely used in many engineering fields and industries, such as fossil fuel-fired power plants, newly developed Gen-IV nuclear power plants and so forth. Heat transfer characteristics of SCW are of great importance for both design and safe operation of the related systems. Many heat transfer correlations have been developed in the history for predicting the heat transfer characteristics of SCW. However, the prediction accuracy of the existing correlations is less than satisfactory, especially in the cases with deteriorated heat transfer (DHT) because of the severe and quick variation in thermal physical properties of SCW in the vicinity of the fluids’ pseudo critical point. It is very necessary to develop new correlations for the heat transfer of SCW to meet the engineering requirements for satisfactory prediction of the heat transfer behavior of SCW. In this chapter, experimental data on heat transfer of SCW are extensively collected from published literatures, and the performance of the existing heat transfer correlations for SCW are reviewed and quantitatively evaluated against the collected experimental data, and then a new heat transfer correlation for SCW with high prediction accuracy is proposed

Anatomical physiological and biochemical processes involved in grapevine rootstock drought tolerance

In order to explore the drought resistance mechanism of grape rootstocks, two grape rootstock species, '1103P' (a drought-tolerant rootstock) and '101-14M' (drought-sensitive), were treated with moderate water deficit (field capacity of 45-50 %). Throughout the experimental period, the leaves of '1103P' showed a higher stomatal conductance (gs), relative water content and photosynthetic rate (Pn) than '101-14M', indicating '1103P' was more resistant to tolerant than '101-14M'. We propose that '1103P' could prevent water loss from leaves under drought conditions based on the discoveries that '1103P' had higher leaf phytohormone abscisic acid (ABA) content and leaf cuticular wax content, and smaller stomata aperture than those of '101-14M'. Additionally, the activities of H2O2-scavenging enzymes in leaves of '1103P' were higher than those of '101-14M' under drought conditions, indicating the lipid peroxidation induced by H2O2 of '1103P' was less serious than that of '101-14M'. Therefore, better water-saving and higher reactive oxygen species (ROS) scavenging abilities contributed together to stronger drought resistance of '1103P' than '101-14M'