Simultaneous enhancement of the efficiency and stability of organic solar cells using PEDOT:PSS grafted with a PEGME buffer layer

We report a simple processing method to simultaneously improve the efficiency and stability of organic solar cells (OSCs). Poly(4-styrene sulfonate)-doped poly(3,4-ethylenedioxy-thiophene (PEDOT:PSS), widely used as hole transport layer (HTL) in OSCs, tends to accelerate the degradation of devices because of its hygroscopic and acidic properties. In this regard, we have modified PEDOT:PSS to reduce its hygroscopic and acidic properties through a condensation reaction between PEDOT:PSS and poly(ethylene glycol) methyl ether (PEGME) in order to improve the efficiency and stability of OSCs. As a result, the power conversion efficiency (PCE) increased by 21%, from 2.57% up to 3.11%. A better energy level alignment by the reduced work function of the modified PEDOT:PSS with a highest occupied molecular orbital (HOMO) level of poly(3-hexylthiophene-2,5-diyl) (P3HT) is considered the origin of the improved the efficiency. The half-life of OSCs with PEDOT:PSS modified with PEGME buffer layer also increased up to 3.5 times compared to that of devices with pristine PEDOT:PSS buffer layer.     

Friction compensation controller for load varying machine tool feed drive

The load applied to a machine tool feed drive changes during the machining process as material is removed. This load change alters the Coulomb friction of the feed drive. Because Coulomb friction accounts for a large part of the total friction the friction compensation control accuracy of the feed drives is limited if this nonlinear change in the applied load is not considered. This paper presents a new friction compensation method that estimates the machine tool load in real time and considers its effect on friction characteristics. A friction observer based on a Kalman filter with load estimation is proposed for friction compensation control considering the applied load change. A specially designed feed drive testbed that enables the applied load to be modified easily was constructed for experimental verification. Control performance and friction estimation accuracy are demonstrated experimentally using the testbed.     

基于分形插值的改进趋势面拟合法在地面沉降中的应用

针对区域地面沉降监测点数量有限、分布不均的情况,一般采用空间插值的手段建立表面拟合模型来解决。基于分形插值,采用随机选择迭代函数的思想对传统的趋势面拟合法作出改进,改进后拟合优度系数提高0.03,达到0.995,且改进前后的拟合结果符合显著性检验的要求。实验结果表明:改进前后趋势面拟合法拟合结果满足地面沉降监测的精度要求,改进后方法的拟合优度更高,对现实地面沉降量变化的描绘更加真实,可为沉降灾害评价工作提供更准确的依据。     

A new metaheuristic for optimization: Optics inspired optimization (OIO)

Due to the law of reflection, a concave reflecting surface/mirror causes the incident light rays to converge and a convex surface/mirror causes the light rays to reflect away so that they all appear to be diverging. These converging and diverging behaviors cause that the curved mirrors show different image types depending on the distance between the object and the mirror. We model such optical phenomena metaphorically into the searching process of numerical optimization by a new algorithm called optics inspired optimization (OIO). OIO treats the surface of the numerical function to be optimized as a reflecting surface in which each peak is assumed to reflect as a convex mirror and each valley to reflect as a concave one. Each individual is assumed to be an artificial object (or light point) that its artificially glittered ray is reflected back by the function surface, given that the surface is convex or concave, and the artificial image is formed (a candidate solution is generated within the search domain) based on the mirror equations adopted from physics of optics. Besides OIO, we introduce different variants of it, called ROIO (Rotation based OIO), and COIO (Convex combination based OIO) algorithms and conduct an extensive computational effort to find out the merit of the new algorithms. Our comparisons on benchmark test functions and a real world engineering design application (i.e., optimization of a centrifuge pump) demonstrate that the new algorithms are efficient and compete better than or similar to most of state of the art optimization algorithms with the advantage of accepting few input parameters.     

Automated network management and configuration using Probabilistic Trans-Algorithmic Search

Online configuration of large-scale systems such as networks requires parameter optimization within a limited amount of time, especially when configuration is needed as a response to recover from a failure in the system. To quickly configure such systems in an online manner, we propose a Probabilistic Trans-Algorithmic Search (PTAS) framework which leverages multiple optimization search algorithms in an iterative manner. PTAS applies a search algorithm to determine how to best distribute available experiment budget among multiple optimization search algorithms. It allocates an experiment budget to each available search algorithm and observes its performance on the system-at-hand. PTAS then probabilistically reallocates the experiment budget for the next round proportional to each algorithm’s performance relative to the rest of the algorithms. This “roulette wheel” approach probabilistically favors the more successful algorithm in the next round. Following each round, the PTAS framework “transfers” the best result(s) among the individual algorithms, making our framework a trans-algorithmic one. PTAS thus aims to systematize how to “search for the best search” and hybridize a set of search algorithms to attain a better search. We use three individual search algorithms, i.e., Recursive Random Search (RRS) (Ye and Kalyanaraman, 2004), Simulated Annealing (SA) (Laarhoven and Aarts, 1987), and Genetic Algorithm (GA) (Goldberg, 1989), and compare PTAS against the performance of RRS, GA, and SA. We show the performance of PTAS on well-known benchmark objective functions including scenarios where the objective function changes in the middle of the optimization process. To illustrate applicability of our framework to automated network management, we apply PTAS on the problem of optimizing link weights of an intra-domain routing protocol on three different topologies obtained from the Rocketfuel dataset. We also apply PTAS on the problem of optimizing aggregate throughput of a wireless ad hoc network by tuning datarates of traffic sources. Our experiments show that PTAS successfully picks the best performing algorithm, RRS or GA, and allocates the time wisely. Further, our results show that PTAS’ performance is not transient and steadily improves as more time is available for search.     

胸腺五肽辅助治疗肺癌对免疫功能影响及其疗效的系统评价

为了系统地评价胸腺五肽作为辅助药物治疗各种肺癌的疗效及其对机体免疫功能的影响，利用电子检索收集有关胸腺五肽联合放疗或化疗方案治疗肺癌的临床随机对照试验文献，对符合纳入标准的文献，采用RevMan5.3 软件进行系统评价。最终共纳入文献 9 篇，总样本量 784 例。Meta 分析结果表明，胸腺五肽作为辅助药物治疗各种肺癌提高总有效率的差异无统计学意义[OR ＝ 1.44, 95%CI(0.99, 2.10), P ＝0.06 ＞ 0.05]。在对免疫功能的影响方面，胸腺五肽的使用显著增高外周血中的 CD3+ 细胞水平[OR ＝ 5.88, 95% CI(2.34, 9.42), P ＝0.001]，CD4+ 细胞水平也显著上升[OR ＝8.32, 95%CI(5.22, 11.42), P ＜ 0.00001] , CD4＋ /CD8＋比值也有明显的提高[OR ＝ 0.38, 95% CI(0.18, 0.59), P＝0.0002]，但 CD8+ 细胞水平的差异无统计学意义[OR ＝－3.12, 95% CI ( －9.02, 2.79), P ＞0.05]。总的来说，本研究在一定程度上反映了在辅助治疗肺癌方面，胸腺五肽能显著提高外周血中的 CD3+ 细胞水平、CD4+ 细胞水平、CD4+/CD8+ 比值。而对于治疗的有效率、CD8+ 细胞水平，差异无统计学意义。     

灵芝菌丝体多糖的分离纯化及其单糖组成分析与分子量测定

前期杂交优化后赤芝菌种经液体深层发酵后,提取灵芝菌丝体多糖,并过DEAE-Sepharose Fast Flow柱分离纯化,利用高效体积排阻色谱(HPSEC)检测多糖级分的纯度,采用完全酸水解PMP柱前衍生化RP—HPLC测定多糖级分的单糖组成,多角度光散射仪联用装置(SEC—MALLS)测定其绝对重均分子量(Mw),并且根据分子旋转半径与分子摩尔数的关系曲线斜率初步推断其空间构象。结果显示:分离纯化得到3个多糖级分GLMP1、GLMP2和GLMP3,HPSEC检测其峰面积百分比分别为93.58%,97.64%,99.19%,单糖组成分析结果表明GLMP1、GLMP2和GLMP3均含有甘露糖、鼠李糖、半乳糖醛酸、葡萄糖、半乳糖、木糖、阿拉伯糖和岩藻糖,但单糖摩尔比各异。SEC—MALLS测试GLMP1、GLMP2和GLMP3的Mw分别为4.526×105,4.603×104,3.760×103 g/mol,3个多糖级分构象可能均为高度紧缩且具有分支结构的聚合物。     

iM-SIMPLE: iMproved stable increased-throughput multi-hop link efficient routing protocol for Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are envisaged to play crucial role in psychological, medical and non-medical applications. This paper presents iM-SIMPLE; a reliable, and power efficient routing protocol with high throughput for WBAN. We deploy sensor nodes on human body to measure the physiological parameters such as blood pressure, temperature, glucose, lactic acid, EMG, acceleration, pressure, and position. Data from sensors is forwarded to intermediate node, from where it is transmitted to sink. An end user can access the required information available at sink via internet. To minimize energy consumption of the network, we utilize multi-hop mode of communication. A cost function is introduced to select the forwarder; node with high residual energy and least distance to sink has minimum cost function value and is selected. Residual energy parameter balances the energy consumption among the sensor nodes, and least distance improves packet delivery to sink because of reduced less path loss. We formulate the minimum energy consumption and high throughput problems as an Integer Linear Program. In order to support mobility, we also consider two body postures. Simulation results confirm the performance advantage of iM-SIMPLE compared to contemporary schemes in terms of maximizing stability period and throughput of the network.     

Systematic convergence of nonlinear stochastic estimators on the Special Orthogonal Group SO(3)

This paper introduces two novel nonlinear stochastic attitude estimators developed on the Special Orthogonal Group with the tracking error of the normalized Euclidean distance meeting predefined transient and steady‐state characteristics. The tracking error is confined to initially start within a predetermined large set such that the transient performance is guaranteed to obey dynamically reducing boundaries and decrease smoothly and asymptotically to the origin in probability from almost any initial condition. The proposed estimators produce accurate attitude estimates with remarkable convergence properties using measurements obtained from low‐cost inertial measurement units. The estimators proposed in continuous form are complemented by their discrete versions for the implementation purposes. The simulation results illustrate the effectiveness and robustness of the proposed estimators against uncertain measurements and large initialization error, whether in continuous or discrete form.     

Experimental and modeling approaches of MR behaviors under large step strains

Rheological properties of MR fluids under large step strain shear are presented in this paper. The experiments were carried out using a rheometer with parallel-plate geometry. Under the large step strain shear, MR fluids behave as nonlinear viscoelastic properties, where the stress relaxation modulus, G(t, γ), shows a decreasing trend with step strain. The experimental results indicate that G(t, γ) obeys time-strain separability. Thus, a mathematical form based on finite exponential serials is proposed to predict MR behavior. In this model, G(t, γ) is represented as the product of a linear stress relaxation, G(t), and the damping function, h(γ), i.e. G(t, γ)=G(t) h(γ). G(t) is simply represented as a three-parameter exponential serial and h(γ) has a sigmoidal form with two parameters. The parameters are identified by adopting an efficient optimization method proposed by Stango et al. The comparison between the experimental results and the model-predicted values indicates that this mathematical model can accurately predict MR behavior.