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.     

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.     

Ceramics composites from iron ore tailings and blast furnace slag

The search for materials and methods capable of reducing human impacts on the environment is of utmost importance nowadays. This study's primary purpose was to analyze the technical feasibility of ceramic composites production utilizing Fundão Dam's Iron Ore Tailings (IOT), Blast Furnace Slag (BFS) from charcoal, and Foundry Sand (FS) as partial substitutes for the traditional raw materials – sand and clay – for application in building industry materials. The composites were molded in rectangular specimens and fired at temperatures of 900, 950, 1000, 1050, and 1200 °C. The developed materials were analyzed and characterized by X-Ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), Thermogravimetry (TGA), and Differential Thermal Analysis (DTA). The obtained materials had flexural strength modulus of up to 12.19 MPa, water absorption ranging from 2 to 22%, linear shrinkage ranging from 0.02 to 6.50%, and apparent density ranging from 2.03 to 1.63 g/cm³. The study of the internal structure formation process revealed the formation of amorphous structures in the composites. The results demonstrated that these waste materials may be jointly used in construction materials, contributing to the reduction of natural resource extraction, besides enabling their correct disposal, minimizing environmental impacts, and improving the life quality of the surrounding communities.     

射孔完井出砂预测新模型及其在射孔优化中的应用

分析了射孔完井的油层出砂机理，以线弹性理论为基础，考虑变温应力和流体渗流作用的拖曳力影响，建立了一种新的射孔完井出砂预测模型。应用该模型研究射孔方位、射孔参数对油井出砂的影响，结果表明，深穿透射孔弹比大孔半径射孔弹能更好地避免孔道出砂，采用定向射孔能有效地减少油井出砂问题。其结果对砂岩油藏射孔优化设计具有一定指导意义。     

川东气藏直井完井方法的产能预测研究

在分析研究目前国内外油气井完井产能计算经验公式的基础上，针对四川气田东部浅层气藏常用的几种完井方式，建立了该地区完井产能预测的数学模型。通过实例计算，表明了其数学模型的准确可行性，并为出砂井和非出砂井的完井方式提供了选择依据：对于出砂井，砾石裸眼充填完井方式是最理想的完井方式；对于非出砂井，实际裸眼完井的产能最大。得出的结论对该地区直井完井方式的选择，完井参数优化设计以及产能预测具有一定的指导作用。     

琼东南盆地深水区储层分布规律

琼东南盆地深水区经历了断陷、断拗和拗陷3大构造演化和沉积充填阶段,主要发育4种沉积体系,相应地形成了4类主要储层:1)陵三段扇三角洲或滨海相砂岩储层;2)三亚、梅山组滨浅海相砂岩储层;3)三亚—莺黄组低位体储层;4)梅山组台地边缘礁滩灰岩储层。平面上,储层发育具有明显的分带性,可划分为:北部浅水陆架滨岸砂岩、三角洲砂岩储层发育带;中央坳陷低位体储层发育带;南部永乐隆起区碳酸盐岩储层发育带。深水区主要位于后2个带,每个带储层发育的控制因素不同,可以进一步划分为多个储层发育区。每个储层发育区存在多套储盖组合,每套储盖组合在多个储层区中发育。其中台地灰岩储层可能成为南部隆起区具有重要意义的勘探层系。      

辽河防洪应急工程中的加筋粉细砂筑坝技术

加筋粉细砂筑坝是一门新兴技术,通过在辽河防洪应急工程右岸李家堡段应用表明,该项技术在技术上是可行的、在经济上是合理的。本文介绍了该技术在辽河防洪应急工程右岸李家堡段的应用。     

新型潜油电泵防砂防垢吸入口的研究应用

针对中原油田矿化度高、出砂量大的开采现状,设计了潜油电泵防砂防垢吸入口,作为电动潜油泵提液系统的辅助设备,对井液先通过滤网防砂管工艺装置进行砂粒过滤,同时通过高强磁防垢器进行磁化处理,使矿化物分子结构改变,结垢缓解。解决了多砂和矿物质结垢而造成的泵卡及泵结垢等技术难题,现场应用效果良好。     

彩横条纬编织物的生产

在普通圆纬机上编织彩横条织物时，彩横务循环单元受到一定限制。而在具有四色或六色调线装置的横务纹机上编织彩横条织物时，可扩大彩横条循环单元的横列数。文中举列说明了彩横条织物的设计与上机工艺的制定方法。     

高含沙水深井泵站的综合治理

对攀钢动力厂深井泵站自投产以来出现的主要问题及其解决方案，方法进行了分析和论述。