Rectifying properties of a boron/nitrogen-doped C131-based molecular junction: A first-principles study

Using first-principles density functional theory and non-equilibrium Green′s function formalism for quantum transport calculation, we have investigated the electronic transport properties of the boron/nitrogen-doped C₁₃₁-based molecular junction. Our results show that an obvious rectifying behavior is observed. Moreover, the rectifying performance can be tuned by adjusting the doping sites. The mechanism for the rectifying phenomenon is suggested. The present findings could be helpful for the application of the C₁₃₁ molecule in the field of single molecular devices or nanometer electronics.     

Measurement and characterization of the human spinal cord SEEP response using event-related spinal fMRI

Although event-related fMRI is able to reliably detect brief changes in brain activity and is now widely used throughout systems and cognitive neuroscience, there have been no previous reports of event-related spinal cord fMRI. This is likely attributable to the various technical challenges associated with spinal fMRI (e.g., imaging a suitable length of the cord, reducing image artifacts from the vertebrae and intervertebral discs, and dealing with physiological noise from spinal cord motion). However, with many of these issues now resolved, the largest remaining impediment for event-related spinal fMRI is a deprived understanding of the spinal cord fMRI signal time course. Therefore, in this study, we used a proton density-weighted HASTE sequence, with functional contrast based on signal enhancement by extravascular water protons (SEEP), and a motion-compensating GLM analysis to (i) characterize the SEEP response function in the human cervical spinal cord and (ii) demonstrate the feasibility of event-related spinal fMRI. This was achieved by applying very brief (1 s) epochs of 22°C thermal stimulation to the palm of the hand and measuring the impulse response function. Our results suggest that the spinal cord SEEP response (time to peak ≈8 s; FWHM ≈4 s; and probably lacking pre- and poststimulus undershoots) is slower than previous estimates of SEEP or BOLD responses in the brain, but faster than previously reported spinal cord BOLD responses. Finally, by detecting and mapping consistent signal-intensity changes within and across subjects, and validating these regions with a block-designed experiment, this study represents the first successful demonstration of event-related spinal fMRI.     

针对散射激光的全向激光告警系统激光威胁源定位技术研究

针对目前散射激光告警中只能定位到散射激光光斑,而不能追溯到敌方来袭激光源的现状,构建了战场环境下包括敌方威胁激光源、照射于某平台上的散射激光光斑以及全向激光告警系统在内的空间三维几何模型,推导了平台上散射激光光斑轮廓解析表达式,以及轮廓上任意一点相对鱼眼镜头的物方半视场角表达式。将成像于探测器上的光斑进行鱼眼成像畸变校正并取光斑边缘点,计算得到三维几何模型诸参数。再将模型参数与传感器阵列信息相结合,可最终获取敌方威胁激光源相对系统的方位和距离信息。最后对以上方法进行了实验验证并对产生误差的原因进行了分析。     

不同线宽结构杂散光Kirk模型分析

采用Kirk测量法的杂散光模型研究了杂散光在不同线宽结构上杂散光的光强变化,通过图像对比度分析了杂散光对不同线宽结构的影响。基于Matlab软件仿真分析表明:线宽一定时,线条越稀疏,图像对比度越低,杂散光对成像图形分辨力的影响越大;线条线间比一定时,线宽尺寸越小,图像对比度越低,杂散光对成像图形分辨力的影响也越大。所以杂散光对线宽较小并且线条稀疏空间结构所成的图形造成的影响较大。光刻; Kirk测量法; 杂散光; 点扩散函数; 图像对比度     

N‐dimensional switch function for energy conservation in multiprocess reaction dynamics

The MReaDy program was designed for studying Multiprocess Reactive Dynamic systems, that is, complex chemical systems involving different and concurrent reactions. It builds a global potential energy surface integrating a variety of potential energy surfaces, each one of them representing an elementary reaction expected to play a role in the chemical process. For each elementary reaction, energy continuity problems may happen in the transition between potential energy surfaces due to differences in the functional form for each of the fragments, especially if built by different authors. A N‐dimensional switch function is introduced in MReaDy in order to overcome such a problem. As an example, results of a collision trajectory calculation for H₂ + OH → H₃O are presented, showing smooth transition in the potential energy, leading to conservation in the total energy. Calculations for a hydrogen combustion system from 1000 K up to 4000 K shows a variation of 0.012% when compared to the total energy of the system. © 2016 Wiley Periodicals, Inc.     

Using support vector machine to predict beta- and gamma-turns in proteins

By using the composite vector with increment of diversity, position conservation scoring function, and predictive secondary structures to express the information of sequence, a support vector machine (SVM) algorithm for predicting beta- and gamma-turns in the proteins is proposed. The 426 and 320 nonhomologous protein chains described by Guruprasad and Rajkumar (Guruprasad and Rajkumar J. Biosci 2000, 25,143) are used for training and testing the predictive model of the beta- and gamma-turns, respectively. The overall prediction accuracy and the Matthews correlation coefficient in 7-fold cross-validation are 79.8% and 0.47, respectively, for the beta-turns. The overall prediction accuracy in 5-fold cross-validation is 61.0% for the gamma-turns. These results are significantly higher than the other algorithms in the prediction of beta- and gamma-turns using the same datasets. In addition, the 547 and 823 nonhomologous protein chains described by Fuchs and Alix (Fuchs and Alix Proteins: Struct Funct Bioinform 2005, 59, 828) are used for training and testing the predictive model of the beta- and gamma-turns, and better results are obtained. This algorithm may be helpful to improve the performance of protein turns' prediction. To ensure the ability of the SVM method to correctly classify beta-turn and non-beta-turn (gamma-turn and non-gamma-turn), the receiver operating characteristic threshold independent measure curves are provided.     

How deeply are core electrons perturbed when valence electrons are spin polarized? The case study of transition metal compounds

The ferromagnetic and antiferromagnetic wave functions of the KMnF₃ perovskite have been evaluated quantum-mechanically by using an all electron approach and, for comparison, pseudopotentials on the transition metal and the fluorine ions. It is shown that the different number of α and β electrons in the d shell of Mn perturbs the inner shells, with shifts between the α and β eigenvalues that can be as large as 6 eV for the 3s level, and is far from negligible also for the 2s and 2p states. The valence electrons of F are polarized by the majority spin electrons of Mn, and in turn, spin polarize their 1s electrons. When a pseudopotential is used, such a spin polarization of the core functions of Mn and F can obviously not take place. The importance of such a spin polarization can be appreciated by comparing (i) the spin density at the Mn and F nuclear position, and then the Fermi contact constant, a crucial quantity for the hyperfine coupling, and (ii) the ferromagnetic–antiferromagnetic energy difference, when obtained with an all electron or a pseudopotential scheme, and exploring how the latter varies with pressure. This difference is as large as 50% of the all electron datum, and is mainly due to the rigid treatment of the F ion core. The effect of five different functionals on the core spin polarization is documented.     

Development and Optimization of Ciprofloxacin HCl-Loaded Chitosan Nanoparticles Using Box–Behnken Experimental Design

Various chitosan (CS)-based nanoparticles (CS-NPs) of ciprofloxacin hydrochloride (CHCl) have been investigated for therapeutic delivery and to enhance antimicrobial efficacy. However, the Box–Behnken design (BBD)-supported statistical optimization of NPs of CHCl has not been performed in the literature. As a result, the goal of this study was to look into the key interactions and quadratic impacts of formulation variables on the performance of CHCl-CS-NPs in a systematic way. To optimize CHCl-loaded CS-NPs generated by the ionic gelation process, the response surface methodology (RSM) was used. The BBD was used with three factors on three levels and three replicas at the central point. Tripolyphosphate, CS concentrations, and ultrasonication energy were chosen as independent variables after preliminary screening. Particle size (PS), polydispersity index (PDI), zeta potential (ZP), encapsulation efficiency (EE), and in vitro release were the dependent factors (responses). Prepared NPs were found in the PS range of 198–304 nm with a ZP of 27–42 mV. EE and drug release were in the range of 23–45% and 36–61%, respectively. All of the responses were optimized at the same time using a desirability function based on Design Expert^® modeling and a desirability factor of 95%. The minimum inhibitory concentration (MIC) of the improved formula against two bacterial strains, Pseudomonas aeruginosa and Staphylococcus aureus, was determined. The MIC of the optimized NPs was found to be decreased 4-fold compared with pure CHCl. The predicted and observed values for the optimized formulation were nearly identical. The BBD aided in a better understanding of the intrinsic relationship between formulation variables and responses, as well as the optimization of CHCl-loaded CS-NPs in a time- and labor-efficient manner.     

Parameters estimation and VLE calculation in asymmetric binary mixtures containing carbon dioxide + n-alkanols

In the present work, the estimation of the parameters for asymmetric binary mixtures of carbon dioxide + n-alkanols has been developed. The binary interaction parameter k₁₂ of the second virial coefficient and non-random two liquid model parameters τ₁₂ and τ₂₁ were obtained using Peng–Robinson equation of state coupled with the Wong–Sandler mixing rules. In all cases, Levenberg–Marquardt minimization algorithm was used for the parameters optimization employing an objective function based on the calculation of the distribution coefficients for each component. Vapor–liquid equilibrium for binary asymmetric mixtures (CO₂ + n-alkanol, from methanol to 1-decanol) was calculated using the obtained values of the mentioned parameters. The agreement between calculated and experimental values was satisfactory.