An Artificial Neural Network Classifier Design Based-on Variable Kernel and Non-Parametric Density Estimation

This paper proposes a probabilistic variant of the SOM-kMER (Self Organising Map-kernel-based Maximum Entropy learning Rule) model for data classification. The classifier, known as pSOM-kMER (probabilistic SOM-kMER), is able to operate in a probabilistic environment and to implement the principles of statistical decision theory in undertaking classification problems. A distinctive feature of pSOM-kMER is its ability in revealing the underlying structure of data. In addition, the Receptive Field (RF) regions generated can be used for variable kernel and non-parametric density estimation. Empirical evaluation using benchmark datasets shows that pSOM-kMER is able to achieve good performance as compared with those from a number of machine learning systems. The applicability of the proposed model as a useful data classifier is also demonstrated with a real-world medical data classification problem.     

Studying the protein-protein interactions in the postsynaptic density by means of immunoabsorption and chemical crosslinking

Postsynaptic densities (PSDs), isolated from porcine cerebral cortices, are large disk-shaped aggregates consisting of hundreds of different proteins. To study the protein-protein interactions in such complex supramolecules, we developed a procedure to break up the PSD's overall structure, while preserving some interactions between individual proteins. Using the resulting PSD sample and an indirect immunoabsorption procedure, PSD-95 was isolated along with the α- and β-subunits of calcium calmodulin-dependent protein kinase II (CaMKIIα and CaMKIIβ), α-tubulin, β-tubulin, and Chapsyn110. Similarly, CaMKIIα was isolated along with CaMKIIβ, α-tubulin, β-tubulin, and small amounts of PSD-95. The proteins isolated from PSDs treated with a cleavable bifunctional crosslinking reagent were further subjected to diagonal gel electrophoresis analysis, and the results indicated that CaMKIIα resides next to α-tubulin in the PSD. Overall, the results obtained here suggest that within the PSD, large aggregates of CaMKIIα, CaMKIIβ, α-tubulin, and β-tubulin may occur that indirectly associate with PSD-95 and Chapsyn110. Such a protein organization would allow interactions with F-actin in the cytoplasm and with proteins, such as N-methyl-D-aspartate receptors, which reside on the postsynaptic membrane. Furthermore, it would facilitate binding to proteins such as the various microtubule-associated proteins that reside in the core region of the PSD.     

单苯环氯取代指数法预测二噁类化合物PCDDs的正辛醇/水分配系数

采用单苯环氯取代指数作为氯代二苯并二口恶口英类化合物 (PCDDs)的分子结构描述符 ,通过正向逐步线性回归方法建立了PCDDs的logKow与分子结构描述符之间的定量关系模型。与文献报道的MOD模型相比 ,该模型不仅具有显著的相关性 (n =43,Radj=0 898,SE =0 195 ,在α =0 0 5时 ,F =2 0 45 5 ,p =0 0 0 0 0 ) ,而且对于分子结构具有更好的区分能力。利用建立的模型 ,对没有logKow文献值的其他 33种PCDDs化合物给出了预测值     

Pseudoelastic behavior in Y1−xPrxBa2Cu3Oy compounds

Tensile tests show that ferroelastic loops always occur at 100–150 K, 200–250 K and room temperature in the Y_1–xPr_xBa₂Cu₃O_y samples withx=0 and 0.1 for whichT _c is 92 K and 82.5 K respectively, and the shape memory effect is always observed in the compact sample near 130 K, just similar to that of thermal elastic martensitic alloys. The loss fraction (W/W) which is proportional to the area of ferroelastic loop as a function of temperature shows that there always exist static hysteresis (W/W) peaks at 130 K and 110 K which are attributed to the phaselike transition (PLT) characterized by the jump of lattice parameters. No ferroelastic loops and shape memory effect are observed in the range of 100 K to 150 K for the lowerT _c samples withx=0.3, 0.4 and 0.6.     

Study of partial discharge characteristics at repetitive square voltages based on UHF method

Due to overvoltage produced by inverter output,inverter-fed motor insulation systems often experience fast electrical aging process,especially when partial discharge(PD) is incepted.Before putting into use,the PD detection should be performed on inverter-fed motors at repetitive square voltages to avoid the PD caused insulation deterioration when the motors are collected to inverters having specific characteristics.However,unlike PD tests at AC/DC voltages proposed in IEC 60270,the PD detection at repetitive square voltages is much more complex because of serious interference generated by impulse generator.To solve the problem,ultra-high frequency(UHF) method seems recommendable for its preferable signal-to-noise ratio(SNR).The chief aim of this study is to investigate PD pulse and statistical characteristics of turn-to-turn insulation for inverter-fed traction motors.A square-shaped Archimedes antenna,specially designed for the PD detection at repetitive square voltages of fast rise times,was used to perform PD tests on turn-to-turn insulation models.Time and frequency analysis results indicate that energy component of generator disturbance and PD pulses are mainly distributed in the 0-0.5 GHz and 0.6-1.5 GHz range,respectively.Based on the results,suitable filter was designed for power disturbance suppression.Additionally,resorting to the sensor unit(i.e.antenna and filter) and the PD test system,the PD statistical features at square voltages of different frequencies were obtained.Experimental results show that higher frequency will give rise,statistically,to PD of lower magnitudes distributing at smaller phases.A reasonable interpretation of this phenomenon was presented.Lastly,according to the PD statistical features,some suggestions for the PD detection system design,generator parameter optimization and the PD pulse extracting were given.The results of this work would be beneficial to the increase of the sensitivity when performing the PD detection on insulation systems for inverter-fed motors at repetitive square voltages and thus,improving the reliability of inverter-fed motors.     

有限差分法和隐式龙格库塔法求解Burgers方程

提出一个新的方法求解一维Burgers方程,组合使用有限差分法和隐式龙格库塔法求解Burgers方程。首先使用二阶有限差分法进行空间离散,得到一个常微分方程组,然后使用高阶A稳定的隐式龙格库塔法求解常微分方程组,最后比较数值解和精确解,数值结果证实该方法有很高的精度和稳定性。     

Performance of Sewage Sludge Treatment and Electricity Generation by Different Configuration Microbial Fuel Cells

This paper compared the degradation efficiency of sludge organic matters and electric-production by two typical microbial fuel cells——dual-chamber microbial fuel cell(DMFC)and single chamber air cathode microbial fuel cell(SAMFC),and the variations of sludge protein,polysaccharide and ammonia nitrogen within the systems were also investigated.The results showed that the concentration of sludge soluble chemical oxygen demand,protein and carbohydrate of DMFC are higher than these of SAMFC during the systems operation,while DMFC can achieve a better ammonia nitrogen removal than SAMFC.Under the same operation condition,the stable voltage output of DMFC and SAMFC is 0.61 V and 0.37 V;the maximum power density of DMFC and SAMFC is 2.79 W/m3and 1.25 W/m3;TCOD removal efficiency of DMFC and SAMFC is 34.14%and 28.63%for 12 d,respectively.Meanwhile,DMFC has a higher coulomb efficiency than SAMFC,but both are less than5%.The results showed that DMFC present a better performance on sludge degradation and electric-production.     

Accurate mirror-based camera pose estimation with explicit geometric meanings

An accurate closed form solution is proposed to estimate camera pose by several mirrored reference object images acquired via a planar mirror under different unknown poses. Compared with state-of-the-art methods, our method is more accurate when there are more than three images and has explicit geometric meanings. This method also properly handles cases in which some of the mirror poses are parallel. The central idea is to minimize an error metric based on all reflections of rotation, which enables the camera rotation to be estimated directly by SVD of sum of mirrored camera rotations. After that, the camera translation is computed by solving a large system of linear equations to minimize object space collinearity error. Both synthesized data and real data experiments show the advantages of our approach.