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.     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

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.     

基于随机光栅的可调谐随机光纤激光器

提出一种基于随机光栅与高反射布拉格光栅(FBG)相结合的可调谐随机光纤激光器。利用980nm泵浦光源泵浦一段7m长的掺铒光纤(EDF)进行增益放大,由随机光栅提供随机反馈。随机光栅长7cm,具有约10000个折射率修改点,这些点由飞秒激光逐点写入,并沿光纤方向随机分布,两点相邻间隔小于10μm。同时,利用中心波长为1548nm的高反射FBG来组成半开放腔结构,实现了随机激光的输出。实验测得的泵浦阈值功率仅为18mW,斜率效率高达13.2%,并通过改变FBG的中心波长,实现了输出激光波长的可调谐,调谐范围为4.45nm(1548.04~1552.49nm)。得益于半开放式激光腔的设计和EDF的高增益,整个系统具有阈值低、效率高、结构简单等优点。     

Apparent power-law distributions in animal movements can arise from intraspecific interactions

Lévy flights have gained prominence for analysis of animal movement. In a Lévy flight, step-lengths are drawn from a heavy-tailed distribution such as a power law (PL), and a large number of empirical demonstrations have been published. Others, however, have suggested that animal movement is ill fit by PL distributions or contend a state-switching process better explains apparent Lévy flight movement patterns. We used a mix of direct behavioural observations and GPS tracking to understand step-length patterns in females of two related butterflies. We initially found movement in one species (Euphydryas editha taylori) was best fit by a bounded PL, evidence of a Lévy flight, while the other (Euphydryas phaeton) was best fit by an exponential distribution. Subsequent analyses introduced additional candidate models and used behavioural observations to sort steps based on intraspecific interactions (interactions were rare in E. phaeton but common in E. e. taylori). These analyses showed a mixed-exponential is favoured over the bounded PL for E. e. taylori and that when step-lengths were sorted into states based on the influence of harassing conspecific males, both states were best fit by simple exponential distributions. The direct behavioural observations allowed us to infer the underlying behavioural mechanism is a state-switching process driven by intraspecific interactions rather than a Lévy flight.     

Compiler compatible 5.66 Mb/mm2 8T 1R1W register file in 14 nm FinFET technology

1-read/1-write (1R1W) register file (RF) is a popular memory configuration in modern feature rich SoCs requiring significant amount of embedded memory. A memory compiler is constructed using the 8T RF bitcell spanning a range of instances from 32 b to 72 Kb. An 8T low-leakage bitcell of 0.106 μm² is used in a 14 nm FinFET technology with a 70 nm contacted gate pitch for high-density (HD) two-port (TP) RF memory compiler which achieves 5.66 Mb/mm² array density for a 72 Kb array which is the highest reported density in 14 nm FinFET technology. The density improvement is achieved by using techniques such as leaf-cell optimization (eliminating transistors), better architectural planning, top level connectivity through leaf-cell abutment and minimizing the number of unique leaf-cells. These techniques are fully compatible with memory compiler usage over the required span. Leakage power is minimized by using power-switches without degrading the density mentioned above. Self-induced supply voltage collapse technique is applied for write and a four stack static keeper is used for read Vmin improvement. Fabricated test chips using 14 nm process have demonstrated 2.33 GHz performance at 1.1 V/25 °C operation. Overall V_min of 550 mV is achieved with this design at 25 °C. The inbuilt power-switch improves leakage power by 12x in simulation. Approximately 8% die area of a leading 14 nm SoC in commercialization is occupied by these compiled RF instances.     

基于正演模拟的地震反射特征主要影响因素分析

随着储层地球物理学的发展，利用地震信息直接预测储层砂岩厚度的横向变化，愈来愈迫切要求对地震数据进行高保真处理。利用波动方程理论法对楔形体砂岩模型进行正演模拟，探讨了随机噪声、地层吸收对地震记录、地震属性以及砂岩预测结果的影响。分析认为，当Q小于100时，地层对地震反射能量吸收严重，需要在处理中加强能量补偿。当S／N小于5时，储层砂岩厚度与地震反射特征、地震属性的相关性变差，噪声对预测结果产生干扰，影响储层预测精度。     

一种高精度的非平稳随机信号实时建模算法研究

针对传统的非平稳随机信号时变参数筹分模型算法的不足,论文把非平稳随机信号时变参数差分模型与一种带自适应遗忘因子的RLS算法结合起来,形成一种有效的非平稳随机信号实时建模算法,仿真分析表明该算法不仅能获得快的收敛速度而且能获得高的建模精度。     

随机减量技术中周期激励的影响及消除方法

本文针对机械系统中通常存在确定性周期激励的事实 ,论证了周期干扰成分的存在对提取的随机减量特征信号的影响 ,基于数字滤波技术提出了一种从周期干扰环境中提取随机减量特征信号的简便方法。在回转机械稳定性监测中的应用实例表明本文提出的方法是有效的。