Selective Supramolecular Fullerene-Porphyrin Interactions and Switching in Surface-Confined C(60)-Ce(TPP)(2) Dyads

The control of organic molecules, supramolecular complexes and donor-acceptor systems at interfaces is a key issue in the development of novel hybrid architectures for regulation of charge-carrier transport pathways in nanoelectronics or organic photovoltaics. However, at present little is known regarding the intricate features of stacked molecular nanostructures stabilized by noncovalent interactions. Here we explore at the single molecule level the geometry and electronic properties of model donor-acceptor dyads stabilized by van der Waals interactions on a single crystal Ag(111) support. Our combined scanning tunneling microscopy/spectroscopy (STM/STS) and first-principles computational modeling study reveals site-selective positioning of C(60) molecules on Ce(TPP)(2) porphyrin double-decker arrays with the fullerene centered on the π-system of the top bowl-shaped tetrapyrrole macrocycle. Three specific orientations of the C(60) cage in the van der Waals complex are identified that can be reversibly switched by STM manipulation protocols. Each configuration presents a distinct conductivity, which accounts for a tristable molecular switch and the tunability of the intradyad coupling. In addition, STS data evidence electronic decoupling of the hovering C(60) units from the metal substrate, a prerequisite for photophysical applications.     

To Score or Not to Score? Tripling Insights for Participatory Design

For evaluating visual-analytics tools, many studies confine to scoring user insights into data. For participatory design of those tools, we propose a three-level methodology to make more out of users' insights. The Relational Insight Organizer (RIO) helps to understand how insights emerge and build on one each other.     

Efficient moving horizon state and parameter estimation for SMB processes

In this paper, a moving horizon state and parameter estimation scheme for chromatographic simulated moving bed SMB processes is proposed. The simultaneous state and parameter estimation is based on a high-order nonlinear SMB model which incorporates rigorous models of the chromatographic columns and the discrete shiftings of the inlet and outlet ports. The estimation is performed using sparse measurement information: the concentrations of the components are only measured at the two outlet ports (which are periodically switched from one column to the next) and at one fixed location between two columns. The goal is to reconstruct the full state of the system, i.e. the concentration profiles along all columns, and to identify critical model parameters reliably such that the estimated model can be used in the context of online optimizing control. The state estimation scheme is based upon a deterministic model within the prediction horizon, state noise is only present in the state and the parameters prior to and at the beginning of the horizon. By solving the optimization problem with a multiple-shooting method and applying a real-time iteration scheme, the computation times are such that the scheme can be applied online. Numerical simulations of a validated model for a separation problem with nonlinear isotherms of the Langmuir type demonstrate the efficiency of the algorithm.     

Effect of Lowering Asymmetric Dimethylarginine (ADMA) on Vascular Pathology in Atherosclerotic ApoE-Deficient Mice with Reduced Renal Mass

The purpose of the work was to study the impact of the endogenous nitric oxide synthase (NOS) inhibitor asymmetric dimethylarginine (ADMA) and its degrading enzyme, dimethylarginine dimethylaminohydrolase (DDAH1), on atherosclerosis in subtotally nephrectomized (SNX) ApoE-deficient mice. Male DDAH1 transgenic mice (TG, n = 39) and C57Bl/6J wild-type littermates (WT, n = 27) with or without the deletion of the ApoE gene underwent SNX at the age of eight weeks. Animals were sacrificed at 12 months of age, and blood chemistry, as well as the extent of atherosclerosis within the entire aorta were analyzed. Sham treated (no renal mass reduction) ApoE-competent DDAH1 transgenic and wild-type littermates (n = 11) served as a control group. Overexpression of DDAH1 was associated with significantly lower ADMA levels in all treatment groups. Surprisingly, SNX mice did not exhibit higher ADMA levels compared to sham treated control mice. Furthermore, the degree of atherosclerosis in ApoE-deficient mice with SNX was similar in mice with or without overexpression of DDAH1. Overexpression of the ADMA degrading enzyme, DDAH1, did not ameliorate atherosclerosis in ApoE-deficient SNX mice. Furthermore, SNX in mice had no impact on ADMA levels, suggesting a minor role of this molecule in chronic kidney disease (CKD) in this mouse model.     

Current Status of Long Non-Coding RNAs in Human Cancer with Specific Focus on Colorectal Cancer

The latest investigations of long non-coding RNAs (lncRNAs) have revealed their important role in human cancers. LncRNAs are larger than 200 nucleotides in length and fulfill their cellular purpose without being translated into proteins. Though the molecular functions of some lncRNAs have been elucidated, there is still a high number of lncRNAs with unknown or controversial functions. In this review, we provide an overview of different lncRNAs and their role in human cancers. In particular, we emphasize their importance in tumorigenesis of colorectal cancer, the third most common cancer worldwide.     

Improved magnetic particle tracking technique in dense gas fluidized beds

Noninvasive monitoring of multiphase flow is rapidly gaining increased interest. More specifically noninvasive particle tracking techniques have received a lot of attention in recent years to study dense granular flow. However, these techniques are usually quite expensive and require strict safety measures. An improved magnetic particle tracking (MPT) technique for dense granular flow will be presented in this article. The improvements of the analysis technique for MPT will be demonstrated and rigorously tested with a three‐dimensional system and two‐dimensional sensor system. The strengths and limitations of the MPT technique will also be reported. Finally, the results of the MPT are compared with data obtained from a combined particle image velocimetry and digital image analysis technique. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3133–3142, 2014     

Synthesis,structural and optical properties of ZnS,CdS and HgS nanoparticles from dithiocarbamato single molecule precursors

Dithiocarbamate complexes of Zn(II), Cd(II) and Hg(II) were synthesize and characterized by elemental analysis, thermogravimetric analysis, UV–Vis, FTIR, ¹H- and ¹³C-NMR spectroscopy. The complexes were thermolyzed at 180°C to prepare HDA-capped ZnS, CdS and HgS nanoparticles. The optical properties of the nanoparticles showed absorptions that are blue shifted with respect to the bulk and narrow emissions. The ZnS nanoparticles are in the cubic phase with average crystallite sizes of 3–5 nm. The CdS nanoparticles consist of a mixture of cubic and hexagonal phases with particle sizes of 8–22 nm, while the HgS nanoparticles are in the cubic phase with average crystallite sizes of 7–14 nm.     

Polydisperse granular flows in a bladed mixer: Experiments and simulations of cohesionless spheres

The flow and segregation of polydisperse, spherical particle mixtures in a bladed mixer was investigated using experimental and computational techniques. Discrete element simulations were able to reproduce the qualitative segregation profiles and surface velocities observed experimentally. For a binary system with a 2:1 size ratio, segregation by size occurs due to a sieving mechanism. Segregation in the binary system is fast, with a fully segregated system observed after just 5 revolutions. However, the numerical simulations showed that the extent of segregation in the bladed mixer can be reduced by introducing intermediate particle sizes in between the smallest and the largest particles. Addition of intermediate particle sizes increases convective and diffusive particle motion promoting a mixing mechanism that reduces segregation via the sieving mechanism. Void fraction within the bladed mixer increases as the degree of polydispersity is increased allowing the particles to move more freely throughout the particle bed. Higher void fractions also increase the ability of large particles to penetrate deeper into the particle bed. Normal and shear stresses are also affected by particle size distributions, with lower average values obtained for the system with the largest number of particle species. Differences in the amount of stress generated by each particle species were observed. However, the difference in stresses is reduced as the number of particle species in the system is increased.     

Sampling methods for shortest vectors,closest vectors and successive minima

We study four problems from the geometry of numbers, the shortest vector problem  (Svp)$\left(\text{<small-caps>Svp</small-caps>}\right)$, the closest vector problem  (Cvp)$\left(\text{<small-caps>Cvp</small-caps>}\right)$, the successive minima problem  (Smp)$\left(\text{<small-caps>Smp</small-caps>}\right)$, and the shortest independent vectors problem   (Sivp$\text{<small-caps>Sivp</small-caps>}$). Extending and generalizing results of Ajtai, Kumar, and Sivakumar we present probabilistic single exponential time algorithms for all four problems for all _?p${?}_p$ norms. The results on Smp$\text{<small-caps>Smp</small-caps>}$ and Sivp$\text{<small-caps>Sivp</small-caps>}$ are new for all norms. The results on Svp$\text{<small-caps>Svp</small-caps>}$ and Cvp$\text{<small-caps>Cvp</small-caps>}$ generalize previous results of Ajtai et al. for the Euclidean _?2${?}_2$ norm to arbitrary _?p${?}_p$ norms. We achieve our results by introducing a new lattice problem, the generalized shortest vector problem   (GSvp$\text{<small-caps>GSvp</small-caps>}$). ¹ We describe a single exponential time algorithm for GSvp$\text{<small-caps>GSvp</small-caps>}$. We also describe polynomial time reductions from Svp,Cvp,Smp$\text{<small-caps>Svp</small-caps>},\text{<small-caps>Cvp</small-caps>},\text{<small-caps>Smp</small-caps>}$, and Sivp$\text{<small-caps>Sivp</small-caps>}$ to GSvp$\text{<small-caps>GSvp</small-caps>}$, establishing single exponential time algorithms for the four classical lattice problems. This approach leads to a unified algorithmic treatment of the lattice problems Svp,Cvp,Smp$\text{<small-caps>Svp</small-caps>},\text{<small-caps>Cvp</small-caps>},\text{<small-caps>Smp</small-caps>}$, and Sivp$\text{<small-caps>Sivp</small-caps>}$.     

Fair webs

Fair webs are energy-minimizing curve networks. Obtained via an extension of cubic splines or splines in tension to networks of curves, they are efficiently computable and possess a variety of interesting applications. We present properties of fair webs and their discrete counterparts, i.e., fair polygon networks. Applications of fair curve and polygon networks include fair surface design and approximation under constraints such as obstacle avoidance or guaranteed error bounds, aesthetic remeshing, parameterization and texture mapping, and surface restoration in geometric models.