Dynamics and self-assembly of bio-functionalized gold nanoparticles in solution: Reactive molecular dynamics simulations

The self-assembling properties, stability, and dynamics of hybrid nanocarriers (gold nanoparticles (AuNPs) functionalized with cysteine-based peptides) in solution are studied through a series of classical molecular dynamics simulations based on a recently parametrized reactive force field. The results reveal, at the atomic level, all the details regarding the peptide adsorption mechanisms, nanoparticle stabilization, aggregation, and sintering. The data confirm and explain the experimental findings and disclose aspects that cannot be scrutinized by experiments. The biomolecules are both chemisorbed and physisorbed; self-interactions of the adsorbates and formation of stable networks of interconnected molecules on the AuNP surfaces limit substrate reconstructions, protect the AuNPs from the action of the solvent, and prevent direct interactions of the gold surfaces. The possibility of agglomeration of the functionalized nanoparticles, compared with the sintering of the bare supports in a water solution, is demonstrated through relatively long simulations and fast steered dynamics. The analysis of the trajectories reveals that the AuNPs were well stabilized by the peptides. This prevented particle sintering and kept the particles far apart; however, part of their chains could form interconnections (crosslinks) between neighboring gold vehicles. The excellent agreement of these results with the literature confirm the reliability of the method and its potential application to the modeling of more complex materials relevant to the biomedical sector.

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Mixtures of (N2)1−x : (O2) x at High Pressures and Low Temperatures

We performed Raman measurements at 18 K and pressures up to 25 GPa in order to construct a tentative phase diagram of the (N ₂)_1–x :(O ₂)_x –system at low temperatures. We varied the composition of the mixed system over the whole concentration range. Here we focused on the systems with high nitrogen concentration and pressures above 2 GPa. It is known that at room temperature oxygen is highly solvable in the –phase of N ₂. The experimental results show that oxygen suppresses the disorder–order transition –N ₂.     

On resolution with short clauses

We investigate properties ofk-resolution, a restricted version of resolution in which one parent clause must have length at mostk. Starting from a unit-preference strategy, we compare minimal proof lengths of unit-resolution and unrestricted resolution. In particular, we show that the speed-up by using resolution is bound by if the shortest unit-resolution refutation needst steps. Next we present an algorithm which decides whether the empty clause can be deduced by 2-resolution from a formula and has time complexity O(length()⁴). Finally we describe effects onk-resolution if a formula is transformed intot-CNF and show that extended 3-resolution is complete and sound.     

Fast approximation algorithms to minimize a special weighted flow-time criterion on a single machine with a non-availability interval and release dates

This paper is the first attempt to successfully design efficient approximation algorithms for the single-machine weighted flow-time minimization problem when jobs have different release dates and weights equal to their processing times under the assumption that one job is fixed (i.e., the machine is unavailable during a fixed interval corresponding to the fixed job). Our work is motivated by an interesting algorithmic application to the generation of valid inequalities in a branch-and-cut method. Our analysis shows that the trivial FIFO sequence can lead to an arbitrary large worst-case performance bound. Hence, we modify this sequence so that a new 2-approximation solution can be obtained for every instance and we prove the tightness of this bound. Then, we propose a fully polynomial-time approximation algorithm with efficient running time for the considered problem. Especially, the complexity of our algorithm is strongly polynomial.     

Iterant recombination with one-norm minimization for multilevel Markov chain algorithms via the ellipsoid method

Recently, it was shown how the convergence of a class of multigrid methods for computing the stationary distribution of sparse, irreducible Markov chains can be accelerated by the addition of an outer iteration based on iterant recombination. The acceleration was performed by selecting a linear combination of previous fine-level iterates with probability constraints to minimize the two-norm of the residual using a quadratic programming method. In this paper we investigate the alternative of minimizing the one-norm of the residual. This gives rise to a nonlinear convex program which must be solved at each acceleration step. To solve this minimization problem we propose to use a deep-cuts ellipsoid method for nonlinear convex programs. The main purpose of this paper is to investigate whether an iterant recombination approach can be obtained in this way that is competitive in terms of execution time and robustness. We derive formulas for subgradients of the one-norm objective function and the constraint functions, and show how an initial ellipsoid can be constructed that is guaranteed to contain the exact solution and give conditions for its existence. We also investigate using the ellipsoid method to minimize the two-norm. Numerical tests show that the one-norm and two-norm acceleration procedures yield a similar reduction in the number of multigrid cycles. The tests also indicate that one-norm ellipsoid acceleration is competitive with two-norm quadratic programming acceleration in terms of running time with improved robustness.     

Spatially Varying Mixtures Incorporating Line Processes for Image Segmentation

Spatially varying mixture models are characterized by the dependence of their mixing proportions on location (contextual mixing proportions) and they have been widely used in image segmentation. In this work, Gauss-Markov random field (MRF) priors are employed along with spatially varying mixture models to ensure the preservation of region boundaries in image segmentation. To preserve region boundaries, two distinct models for a line process involved in the MRF prior are proposed. The first model considers edge preservation by imposing a Bernoulli prior on the normally distributed local differences of the contextual mixing proportions. It is a discrete line process model whose parameters are computed by variational inference. The second model imposes Gamma prior on the Student’s-t distributed local differences of the contextual mixing proportions. It is a continuous line process whose parameters are also automatically estimated by the Expectation-Maximization (EM) algorithm. The proposed models are numerically evaluated and two important issues in image segmentation by mixture models are also investigated and discussed: the constraints to be imposed on the contextual mixing proportions to be probability vectors and the MRF optimization strategy in the frameworks of the standard and variational EM algorithm.     

Understanding cost drivers of software evolution: a quantitative and qualitative investigation of change effort in two evolving software systems

Making changes to software systems can prove costly and it remains a challenge to understand the factors that affect the costs of software evolution. This study sought to identify such factors by investigating the effort expended by developers to perform 336 change tasks in two different software organizations. We quantitatively analyzed data from version control systems and change trackers to identify factors that correlated with change effort. In-depth interviews with the developers about a subset of the change tasks further refined the analysis. Two central quantitative results found that dispersion of changed code and volatility of the requirements for the change task correlated with change effort. The analysis of the qualitative interviews pointed to two important, underlying cost drivers: Difficulties in comprehending dispersed code and difficulties in anticipating side effects of changes. This study demonstrates a novel method for combining qualitative and quantitative analysis to assess cost drivers of software evolution. Given our findings, we propose improvements to practices and development tools to manage and reduce the costs.     

Protected subspaces in quantum information

In certain situations the state of a quantum system, after transmission through a quantum channel, can be perfectly restored. This can be done by “coding” the state space of the system before transmission into a “protected” part of a larger state space, and by applying a proper “decoding” map afterwards. By a version of the Heisenberg Principle, which we prove, such a protected space must be “dark” in the sense that no information leaks out during the transmission. We explain the role of the Knill–Laflamme condition in relation to protection and darkness, and we analyze several degrees of protection, whether related to error correction, or to state restauration after a measurement. Recent results on higher rank numerical ranges of operators are used to construct examples. In particular, dark spaces are constructed for any map of rank 2, for a biased permutations channel and for certain separable maps acting on multipartite systems. Furthermore, error correction subspaces are provided for a class of tri-unitary noise models.     

Nano-structured solid oxide fuel cell design with superior power output at high and intermediate operation temperatures

A solid oxide fuel cell (SOFC) with a thin-film yttria-stabilized zirconia (YSZ) electrolyte was developed and tested. This novel SOFC shows a similar multilayer set-up as other current anode-supported SOFCs and is composed of a Ni/8YSZ anode, a gas-tight 8YSZ electrolyte layer, a dense Sr-diffusion barrier layer and a LSCF cathode. To increase the power density and lower the SOFC operating temperature, the thickness of the electrolyte layer was reduced from around 10 μm in current cells to 1 μm, using a nanoparticle deposition method. By using the novel 1 μm electrolyte layer, the current density of our SOFC progressed to 2.7, 2.1 and 1.6 A/cm² at operation temperatures of 800, 700 and 650°C, respectively, and out-performs all similar cells reported to date in the literature. An important consideration is also that cost-effective dip-coating and spin-coating methods are applied for the fabrication of the thin-film electrolyte. Processing of 1 μm layers on the very porous anode substrate material was initially experienced as very difficult and therefore 8YSZ nanoparticle coatings were developed and optimized on porous 8YSZ model substrates and transferred afterwards to regular anode substrates. In this paper, the preparation of the novel SOFC is shown and its morphology is illustrated with high resolution SEM pictures. Further, the performance in a standard SOFC test is demonstrated.