Structural Aspects and Prediction of Calmodulin-Binding Proteins

Calmodulin (CaM) is an important intracellular protein that binds Ca²⁺ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca²⁺ concentration through interactions with CaM.     

森林抚育对森林生态系统的影响

伴随着我国社会经济的稳固发展,人们的生活质量逐渐有了明显改善,而在生态问题趋于严重使人们的环境保护意识显著提高的过程中,森林抚育对于森林生态系统的作用和价值愈发凸显。对此,文章针对森林抚育,从提高森林利用率、维持森林动植物生态平衡、增加可利用水资源等多个方面就其对森林生态系统的影响进行了分析,旨在给予相关森林保护工作者可行的帮助,并以此促进我国森林开发工作的可持续发展。     

Accurate ensemble pruning with PL-bagging

Ensemble pruning deals with the selection of base learners prior to combination in order to improve prediction accuracy and efficiency. In the ensemble literature, it has been pointed out that in order for an ensemble classifier to achieve higher prediction accuracy, it is critical for the ensemble classifier to consist of accurate classifiers which at the same time diverse as much as possible. In this paper, a novel ensemble pruning method, called PL-bagging, is proposed. In order to attain the balance between diversity and accuracy of base learners, PL-bagging employs positive Lasso to assign weights to base learners in the combination step. Simulation studies and theoretical investigation showed that PL-bagging filters out redundant base learners while it assigns higher weights to more accurate base learners. Such improved weighting scheme of PL-bagging further results in higher classification accuracy and the improvement becomes even more significant as the ensemble size increases. The performance of PL-bagging was compared with state-of-the-art ensemble pruning methods for aggregation of bootstrapped base learners using 22 real and 4 synthetic datasets. The results indicate that PL-bagging significantly outperforms state-of-the-art ensemble pruning methods such as Boosting-based pruning and Trimmed bagging.     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

一种新颖的基于非压缩数字视频的水印盲检测算法

数字水印是一种嵌入到多媒体数据中用来进行版权标识的工具。在众多的宿主媒体中，数字视频因具有隐藏容量大、透明性好、鲁棒性强等诸多优点而受到日益广泛的关注。但是很多文献中提到的视频水印都是从数据流中提取单帧图像进行处理，这类算法与静态图像的水印方法如出一辙，没有充分利用视频文件的各种特性。而且对帧平均、视频压缩等常见的运动图像攻击方法十分敏感。针对这些问题，本文以非压缩视频文件为实验对象，结合人类视觉模型和彩色图像场景分割的方法，提出并实现了一种基于视频时间轴的数字水印盲检测算法。实验结果表明算法有效实用。     

山西省森林植被对径流泥沙影响的研究

森林对径流量的影响是森林水文学研究的重要课题。该文通过大量实测水文资料 ,定量分析了部分流域森林对径流、泥沙、降水量等的影响。同时 ,森林对径流的影响 ,因气候、下垫面条件、植被类型和雨强等不同而存在差异     

Modeling alternative zoning strategies in forest management

To satisfy public demands for environmental values, forest companies are facing the prospect of a reduction in wood supply and increases in costs. Some Canadian provincial governments have proposed intensifying silviculture in special zones dedicated to timber production as the means for pushing out the forest possibility frontiers. In this paper, we compare the traditional two‐zone land allocation framework which includes ecological reserves and integrated forest management zones with the triad — a three‐zone scheme which adds a zone dedicated to intensive timber production. We compare the solutions of the mixed‐integer linear programs formulated under both land‐allocation frameworks. We explore through sensitivity analysis the conditions under which the triad regime can offset the impact on timber production from increased environmental demands. We show that under the realistic conditions characteristic to Coastal British Columbia, higher environmental demands may be satisfied under the triad regime without increasing the financial burdens on the industry or reducing its wood supply. This occurs, however, only if regulatory constraints in timber production zone are flexible.     

In flight MTF monitoring and compensation for CCD camera on CBERS-02

All image systems cause a blurring of the scene radiance field during image acquisi- tion. Accurate characterization of this blurring is referred to as the modulation transfer function (MTF)[1]. The MTF is a fundamental imaging system design specification and system quality metric often used in remote sensing. It results from the cumulative effects of the instrumental optics (diffraction, aberrations, focusing error), integration on a pho- tosensitive surface, charge diffusion along the arra…     

Harvesting small trees and forest residues

Eight countries collaborated and shared technical information on the harvesting of small trees and forest residues in a three year program. Proceedings and reports from workshops and reviews are summarized in a review of activities and harvesting systems of the participating countries. Four databases were developed for harvesting and transportation of these materials.     

Sediment chemistry and nutrient influx in a hydrologically restored bottomland hardwood forest in Midwestern USA

Exchanges of total N and C between a river and its floodplain forest have been enhanced by sedimentation processes during flood pulses at a 5‐ha bottomland hardwood forest located at the Olentangy River Wetland Research Park in central Ohio. In the spring of 2000, the forest was hydrologically restored by notching an artificial levee that had separated the Olentangy River and its floodplain forest for 100 years. One‐hundred flat sediment traps (30 cm × 30 cm) were used to collect sediment samples during spring/summer flooding events from 2003 to 2005. Results showed that sediment deposition is determined by the landscape variability during flooding events, Net sediment deposit in the wettest area averaged 134 ± 12 g‐dry wt m^?2 in 2003, 127 ± 17 g‐dry wt m^?2 in 2004 and 149 ± 23 g‐dry wt m^?2 in 2005. Total N and C sedimentation ranged from 0.49 to 0.92 g‐N m^?2 and 5.2 to 19.9 g‐C m^?2. Fe dominates the sediment chemistry and results show the elemental abundance in the order of Al > Fe > Ca > K > Mg > S > P > Na > Mn > Zn > B > Cu > Mo. A hydrologic pulsing index (HPI) could be used as an indicator for mass changes of energies with hydrologic pulsing events. Restoration of seasonally flooded bottomland forests could stimulate potentially large nutrient and Fe releases, which would eventually lead to an enhanced forest productivity and biodiversity. Copyright © 2007 John Wiley & Sons, Ltd.