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.     

In Silico Analysis of the Molecular-Level Impact of SMPD1 Variants on Niemann-Pick Disease Severity

Sphingomyelin phosphodiesterase (SMPD1) is a key enzyme in the sphingolipid metabolism. Genetic SMPD1 variants have been related to the Niemann-Pick lysosomal storage disorder, which has different degrees of phenotypic severity ranging from severe symptomatology involving the central nervous system (type A) to milder ones (type B). They have also been linked to neurodegenerative disorders such as Parkinson and Alzheimer. In this paper, we leveraged structural, evolutionary and stability information on SMPD1 to predict and analyze the impact of variants at the molecular level. We developed the SMPD1-ZooM algorithm, which is able to predict with good accuracy whether variants cause Niemann-Pick disease and its phenotypic severity; the predictor is freely available for download. We performed a large-scale analysis of all possible SMPD1 variants, which led us to identify protein regions that are either robust or fragile with respect to amino acid variations, and show the importance of aromatic-involving interactions in SMPD1 function and stability. Our study also revealed a good correlation between SMPD1-ZooM scores and in vitro loss of SMPD1 activity. The understanding of the molecular effects of SMPD1 variants is of crucial importance to improve genetic screening of SMPD1-related disorders and to develop personalized treatments that restore SMPD1 functionality.     

川中地区侏罗系沙溪庙组致密气处理和解释关键技术与应用

四川盆地蕴含丰富的致密砂岩气资源，近期利用高精度三维资料开展侏罗系沙溪庙组河道砂体勘探取得突出成效。沙溪庙组河道砂体具有横向变化快、储层非均质性强的特点，因此提高河道砂体的边界识别及其含气性预测精度是致密气地震勘探的关键。通过开展AVO特征低频保护的“六分法”（分类、分频、分时、分域、分步和分区）高保真叠前去噪、近地表Q补偿和OVT域叠前时间偏移等技术攻关，形成了一套针对川中地区侏罗系沙溪庙组致密气藏的“双高”（高保真、高分辨率）地震处理技术，并创新应用“双亮点”属性及多波、多分量砂体含气性地震预测等解释技术，提高了含气砂体预测精度。该技术系列在川中沙溪庙组致密气预测应用成果显著，地震数据频带得到了拓宽，低频信息更加丰富，资料信噪比明显提升，河道边界及其含气性预测的精度大幅提高，钻井成功率超过83%，应用成果有力地支撑了该地区沙溪庙组致密气的增储上产。     

FE-SEA方法在平台支持船噪声预报中的应用

平台支持船由于作业需要通常配备有动力定位系统,其在侧推工况下舱室噪声超标较为严重。针对这个问题采用计算流体力学(CFD)方法,得到侧推螺旋桨作用在导管上的脉动压力,并将时域计算结果转换成噪声计算的激励条件。采用有限元(FE)与统计能量分析(SEA)混合方法建立船体中频段FE-SEA耦合模型并建立船体高频段SEA模型,对某65 m AHTS船侧推工况下全频段(63 Hz~8000 Hz)舱室噪声进行预报,分析该船噪声分布规律及主要影响因素。并建立起全船的SEA模型,在中频段对比SEA与FE-SEA两种方法得到的舱室声压级频谱曲线,验证了使用混合模型的必要性。     

Fire safe,sustainable loose furnishing

The aim of this exploratory study has been to investigate the fire properties and environmental aspects of different upholstery material combinations, mainly for domestic applications. An analysis of the sustainability and circularity of selected textiles, along with lifecycle assessment, is used to qualitatively evaluate materials from an environmental perspective. The cone calorimeter was the primary tool used to screen 20 different material combinations from a fire performance perspective. It was found that textile covers of conventional fibres such as wool, cotton and polyester, can be improved by blending them with fire resistant speciality fibres. A new three‐dimensional web structure has been examined as an alternative padding material, showing preliminary promising fire properties with regard to ignition time, heat release rates and smoke production.     

防气窜固井技术研究

从气窜机理、气窜预测方法、提高水泥浆防气窜性能、防气窜固井工艺技术四个方面进行研究,为固井防气窜提供理论依据,进而提升防气窜固井技术。     

Boosting discharge capability of α-Ni(OH)2 by cobalt doping based on robust spherical structure

α-Ni(OH)₂ is a promising candidate of the currently commercialized β-Ni(OH)₂ due to its higher theoretical discharge capacity in alkaline solution; however, its instability and poor conductivity plague the practical application. Herein, we propose α-Ni(OH)₂ with Co doping and spherical structure to strengthen the stability and enhance the conductivity and use it as the cathode for nickel-metal hydride batteries. Studies show that proper Co doping promotes the electrochemical reaction between the active materials and the electrolyte due to the spherical α-Ni(OH)₂ with enlarged interlayer distance and abundant hole channels, as well as high conductivity of Co, therefore, the obtained spherical α-Ni(OH)₂ with 7 mol% Co doping delivers significantly improved discharge capability, which is 384.6 mAh g^?1 at 70 mA g^?1 (0.2 C), increased by 54.3 mAh g^?1 compared with pure α-Ni(OH)₂, and at a high current of 5 C, it still gives 269.4 mAh g^?1, in contrast 218.5 mA g^?1 for the pure α-Ni(OH)₂. Besides, the cycling stability of the α-Ni(OH)₂ with 7 mol% Co doping maintains 340 cycles at a capacity retention of 80% (1C), which is extended 110 cycles in contrast to the pure α-Ni(OH)₂. These results provide the underpinning platform of α-Ni(OH)₂ for battery applications with high discharge ability and cycle life.     

从蚕的生命到艺术：中国古代生命观的哲学表达

中国考古出土的蚕业实物及蚕的艺术形象比较丰富,蚕的艺术形象如蚕纹、陶蚕蛹、牙雕蚕、玉石蚕、铜蚕、金蚕等,可统称为"蚕的模拟形态"。对蚕的模拟形态的功用,已有的诸多解释都有待完善。研究表明,蚕的模拟形态或艺术形象表达的功用或为饰品,或为装饰图案,或有待进一步考究。但无论哪种功用,用"蚕"这一形象都蕴含了特有的用意。通过对中国古代生命观的考察,文章认为蚕的艺术形象折射出相应的中国古代哲学生命观,即中国古人追求的死而复生、生生不息、羽化成仙、长乐无极等观念。     

Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.