基于实测数据的沉降预测方法综述

介绍了静态和动态两种基于实测数据的沉降外推预测方法,阐述了各种方法的适用范围和优缺点,指出基于实测数据的沉降预测法是针对建筑实测所得的离散沉降值,用数学模型预测地基的最终沉降量,具有较好的适用性。     

Genetic Variation of the Endangered Gentiana lutea L. var. aurantiaca (Gentianaceae) in Populations from the Northwest Iberian Peninsula

Gentiana lutea L. (G. lutea L.) is an endangered plant, patchily distributed along the mountains of Central and Southern Europe. In this study, inter-simple sequence repeat (ISSR) markers were used to investigate the genetic variation in this species within and among populations of G. lutea L. var. aurantiaca of the Cantabrian Mountains (Northwest Iberian Peninsula). Samples of G. lutea L. collected at different locations of the Pyrenees and samples of G. lutea L. subsp. vardjanii of the Dolomites Alps were also analyzed for comparison. Using nine ISSR primers, 106 bands were generated, and 89.6% of those were polymorphic. The populations from the Northwest Iberian Peninsula were clustered in three different groups, with a significant correlation between genetic and geographic distances. Gentiana lutea L. var. aurantiaca showed 19.8% private loci and demonstrated a remarkable level of genetic variation, both among populations and within populations; those populations with the highest level of isolation show the lowest genetic variation within populations. The low number of individuals, as well as the observed genetic structure of the analyzed populations makes it necessary to protect them to ensure their survival before they are too small to persist naturally.     

公路噪声源强预测模型研究进展

随着公路建设和城镇化的不断发展，车辆行驶过程中产生的环境噪声对沿线居民、学校的影响也日益明显。针对目前我国的标准规范中未明确给出公路噪声源强预测模型的问题，对国外公路环境噪声源强模型进行系统的分析和总结，并对我国公路噪声源强预测模型的研究提出建议。     

Relaxation Dynamics and Strain Persistency of Azobenzene‐Functionalized Polymers and Actuators

The accumulation of photoinduced deformation in azobenzene functionalized polymers has received a significant amount of attention in recent years. Critically, the induced photomechanical deformation in these systems experiences varying degrees of relaxation. Control over the persistence of photomechanical strains is vital to the broader utility of these materials in shape programmable systems including soft robotics and engineered origami. Furthermore, investigations of relaxation in light responsive polymer systems triggered by UV light are more prominent than those triggered by blue‐green light. In this study, the impact of chain mobility and initially induced photostrain on the relaxation dynamics of azobenzene‐functionalized polyimides after irradiation with blue light is examined. A modeling effort coupling chromophore population dynamics to material strain is carried out to further explore the relationship between material structure, relaxation dynamics, and macroscopic deformation. The implications for controlling strain persistence are highlighted by simulating one example of a photoprimed bistable actuator.     

企业需求预测准确性存在的问题及其应对策略(一)

鉴于需求预测在企业经营活动中具有重要地位,且会受到受各种因素影响,本文在对企业实际需求预测的方法、过程、系统、管理等问题进行梳理和分析的基础上,指出了通过优化需求预测方法、完善需求预测系统、改进需求预测管理,可有效控制需求预测和未来市场情况的偏差,从而持续提高需求预测的准确性,促进企业生产、销售的良性运行。     

Non-saturation Throughput of S-ALOHA Using the Time-Scale Decomposition Technique

S-ALOHA （Slotted ALOHA） random access protocol is a widely used protocol mainly for the transmission of short packets in wireless networks. Most papers consider either an infinite population model where the impact of the backoff protocol cannot be adequately evaluated or a finite population model where the number of nodes is fixed. In this letter, a combination of both models is proposed using the time-scale decomposition technique. This methodology allows to study the system under more realistic conditions where the dynamics of users enter and leaving the system are reflected on the performance of the system as well as the impact of the backoff protocol. Also, it allows studying the system in non-saturation conditions. The proposed methodology divides the analysis in two parts： packet-level and connection-level. This analysis renders suitable results when the time scale of the packet level and connection level statistics is different. On the other hand, when these scales are similar, the proposed methodology is no longer suited.     

Stability,elastic and electronic properties of the Rh–Zr compounds from first-principles calculations

A systematic investigation on structural, elastic and electronic properties of Rh–Zr intermetallic compounds is conducted using first-principles electronic structure total energy calculations. The equilibrium lattice parameters, enthalpies of formation (E_for), cohesive energies (E_coh) and elastic constants are presented. Of the eleven considered candidate structures, Rh₄Zr₃ is most stable with the lowest E_for. The two orthogonal-type, relative to the CsCl-type, are the competing ground-state structures of RhZr. The result is in agreement with the experimental reports in the literature. The analysis of E_for and mechanical stability excludes the presence of Rh₂Zr and RhZr₄ at low temperature mentioned by .Curtarolo et al. [Calphad 29, 163 (2005)]. It is found that the bulk modulus B increases monotonously with Rh concentration, whereas all other quantities (shear modulus G, Young's modulus E, Poisson's ratio σ and ductility measured by B/G) show nonmonotonic variation. RhZr₂ exhibits the smallest shear/Young's modulus, the largest Poisson's ratio and ductility. Our results also indicate that all the Rh–Zr compounds considered are ductile. Furthermore, the detailed electronic structure analysis is implemented to understand the essence of stability.     

Molecular Cloning,Structural Analysis and Tissue Expression of Protein Phosphatase 3 Catalytic Subunit Alpha Isoform (PPP3CA) Gene in Tianfu Goat Muscle

Calcineurin, a Ca²⁺/calmodulin-dependent protein phosphatase, plays a critical role in controlling skeletal muscle fiber type. However, little information is available concerning the expression of calcineurin in goat. Therefore, protein phosphatase 3 catalytic subunit alpha isoform (PPP3CA) gene, also called calcineurin Aα, was cloned and its expression characterized in Tianfu goat muscle. Real time quantitative polymerase chain reaction (RT-qPCR) analyses revealed that Tianfu goat PPP3CA was detected in cardiac muscle, biceps femoris muscle, abdominal muscle, longissimus dors muscle, and soleus muscle. High expression levels were found in biceps femoris muscle, longissimus muscle and abdominal muscle (p < 0.01), and low expression levels were seen in cardiac muscle and soleus muscle (p > 0.05). In addition, the spatial-temporal mRNA expression levels showed different variation trends in different muscles with the age of the goats. Western blotting further revealed that PPP3CA protein was expressed in the above-mentioned tissues, with the highest level in biceps femoris muscle, and the lowest level in soleus muscle. In this study, we isolated the full-length coding sequence of Tianfu goat PPP3CA gene, analyzed its structure, and investigated its expression in different muscle tissues from different age stages. These results provide a foundation for understanding the function of the PPP3CA gene in goats.     

Churn prediction using comprehensible support vector machine: An analytical CRM application

Support vector machine (SVM) is currently state-of-the-art for classification tasks due to its ability to model nonlinearities. However, the main drawback of SVM is that it generates “black box” model, i.e. it does not reveal the knowledge learnt during training in human comprehensible form. The process of converting such opaque models into a transparent model is often regarded as rule extraction. In this paper we proposed a hybrid approach for extracting rules from SVM for customer relationship management (CRM) purposes. The proposed hybrid approach consists of three phases. (i) During first phase; SVM-RFE (SVM-recursive feature elimination) is employed to reduce the feature set. (ii) Dataset with reduced features is then used in the second phase to obtain SVM model and support vectors are extracted. (iii) Rules are then generated using Naive Bayes Tree (NBTree) in the final phase. The dataset analyzed in this research study is about Churn prediction in bank credit card customer (Business Intelligence Cup 2004) and it is highly unbalanced with 93.24% loyal and 6.76% churned customers. Further we employed various standard balancing approaches to balance the data and extracted rules. It is observed from the empirical results that the proposed hybrid outperformed all other techniques tested. As the reduced feature dataset is used, it is also observed that the proposed approach extracts smaller length rules, thereby improving the comprehensibility of the system. The generated rules act as an early warning expert system to the bank management.     

Numerical simulation of particulate processes for control and estimation by spectral methods

Results of application of pseudospectral methods, also known as spectral collocation methods, to practical particulate processes including growth, nucleation, aggregation, and breakage are presented. For growth‐dominated processes, a considerable reduction in model dimension can be achieved; for pure aggregation and breakage they form a viable option. To handle problems that include aggregation, breakage, and growth phenomena simultaneously, we introduce a hybrid algorithm combining the advantages of spectral methods and cell average or fixed pivot methods for aggregation and breakage. Results are shown for analytical examples as well as real processes taken from the fields of granulation and crystallization. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2309–2319, 2012