A class of solvable coupled nonlinear oscillators with amplitude independent frequencies

Existence of amplitude independent frequencies of oscillation is an unusual property for a nonlinear oscillator. We find that a class of N coupled nonlinear Liénard type oscillators exhibit this interesting property. We show that a specific subset can be explicitly solved from which we demonstrate the existence of periodic and quasiperiodic solutions. Another set of N coupled nonlinear oscillators, possessing the amplitude independent nature of frequencies, is almost integrable in the sense that the system can be reduced to a single nonautonomous first order scalar differential equation which can be easily integrated numerically.     

An object-parameter approach to predicting unknown data in incomplete fuzzy soft sets

Incomplete data in soft sets lead to uncertainty and inaccuracy in representing and handling information. This paper introduces notions of complete distance between two objects and relative dominance degree between two parameters. Based on both the notions, an object-parameter method is proposed to predict unknown data in incomplete fuzzy soft sets. The proposal makes full use of known data, including the information from the relationship between known values of all objects on a certain parameter and the information from the relationship between known values of an object on all parameters. The effectiveness of the proposal is verified by many examples under the compared investigation of classical predicted methods.     

On circular–linear one-factorizations of the complete graph

In Korchmáros et al. (2018)one-factorizations of the complete graph $K_n$ are constructed for $n=q+1$ with any odd prime power $q$ such that either $q\equiv 1(mod4)$ or $q=2^h?1$. The arithmetic restriction $n=q+1$ is due to the fact that the vertices of $K_n$ in the construction are the points of a conic $\Omega$ in the finite plane of order $q$. Here we work on the Euclidean plane and describe an analogous construction where the role of $\Omega$ is taken by a regular $n$-gon. This allows us to remove the above constraints and construct one-factorizations of $K_n$ for every even $n\ge 6$.     

中国进口食品安全风险评估的统计学方法

近年来,随着对外贸易的快速发展和人民生活水平的不断提高,我国已经成为食品进口大国。运用科学的方法优化检验资源配置,强化对进口食品安全的风险管理,是一个关系到人民福社的重大问题。国际上通行的做法是对不同种类的食品和检测项目的潜在风险进行评估,并根据评估结果制定有针对性的监督抽检计划,使得更多的检验资源可以投入到对高风险产品和项目的监管中去。我国在这方面的管理实践才刚刚起步,急需建立一套符合我国食品进口自身特点和管理需求的风险评价模型和相应的估计方法。本文借鉴了其它国家的相关做法,并结合我国进口食品的管理需求和历史检测数据的特点,制定了一套完整的风险评价和估计方法。     

Complete Moment Convergence for the Dependent Linear Processes with Random Coefficients

In this paper, we investigate the complete moment convergence for dependent linear processes with random coefficients to form     

管式炉中半导体激光器巴条Au80Sn20焊料封装研究

为了提高半导体激光器的封装质量和效率,引入管式炉利用夹具进行批量封装。由于封装质量的好坏直接影响半导体激光器的输出特性和使用寿命,利用MOCVD生长808 nm芯片,重点分析了管式炉温度和封装时间对半导体激光器巴条双面金锡封装质量的影响。利用X射线检测、结电压、光电特性参数和smile效应测试手段,确定了管式炉封装半导体激光器巴条的最优封装条件,为以后的产业化提供了指导意义。     

右半结肠癌完全结肠系膜切除术清扫肠系膜根部淋巴结效果观察

目的 探讨右半结肠癌行完全结肠系膜切除术（CME）清扫肠系膜根部淋巴结的临床疗效。方法 以2010年12月 至2012 年12 月行CME 的57 例右半结肠癌患者作为观察组,同期接受传统结肠癌根治术的99 例右半结肠癌患者作为对照组,对两组患者的淋巴结清扫数量、平均出血量、手术时间、住院时间、术后排气、排便时间、手术并发症、2年局部复发率及生存率等情况进行比较,初步评价CME 清扫肠系膜根部淋巴结的临床效果。结果 CME 组与对照组总淋巴结清扫数量分别为（22.6±2.8）、（14.6±2.7）枚,CME 组淋巴结清扫数量明显多于对照组（P＜0.05）;CME 组平均出血量为（167.4±20.8）ml,对照组为（205.4±19.3）ml,CME 组出血量少于对照组（P＜0.05）;两组的手术时间、住院时间、术后排气、排便时间比较差异均无统计学意义（均P＞0.05）;CME 组手术并发症发生率与对照组比较差异无统计学意义（P ＞0.05）;Ⅲ期患者CME 组2 年局部复发率38.2％、生存率88.2％,对照组分别为64.8％和68.5％,两组差异有统计学意义（均P＜0.05）。结论 右半结肠癌患者采用CME 清扫肠系膜根部 淋巴结是安全和有效的。     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.