Molecular prototypes for spin-based CNOT and SWAP quantum gates

We show that a chemically engineered structural asymmetry in [Tb2] molecular clusters renders the two weakly coupled Tb3+ spin qubits magnetically inequivalent. The magnetic energy level spectrum of these molecules meets then all conditions needed to realize a universal CNOT quantum gate. A proposal to realize a SWAP gate within the same molecule is also discussed. Electronic paramagnetic resonance experiments confirm that CNOT and SWAP transitions are not forbidden.

A need for determination of arsenic species at low levels in cereal-based food and infant cereals. Validation of a method by LC-ICPMS.

The present study arose from the need to determine inorganic arsenic (iAs) at low levels in cereal-based food. Validated methods with a low limit of detection (LOD) are required to analyse these kinds of food. An analytical method for the determination of iAs, methylarsonic acid (MA) and dimethylarsinic acid (DMA) in cereal-based food and infant cereals is reported. The method was optimised and validated to achieve low LODs. Ion chromatography-inductively coupled plasma mass spectrometry (LC-ICPMS) was used for arsenic speciation. The main quality parameters were established. To expand the applicability of the method, different cereal products were analysed: bread, biscuits, breakfast cereals, wheat flour, corn snacks, pasta and infant cereals. The total and inorganic arsenic content of 29 cereal-based food samples ranged between 3.7-35.6 and 3.1-26.0 microg As kg-1, respectively. The present method could be considered a valuable tool for assessing inorganic arsenic contents in cereal-based foods.

Individual-based modelling and simulation: towards a better understanding of growth dynamics from small inocula

Postprint (published version)

Energy-based modelling and simulation of the interconnection of a back-to-back converter and a doubly-fed induction machine

This paper describes the port interconnection of two subsystems: a power electronics subsystem (a back-to-back AC/CA converter (B2B), coupled to a phase of the power grid), and an electromechanical subsystem (a doubly-fed induction machine (DFIM). The B2B is a variable structure system (VSS), due to presence of control-actuated switches: however, from a modelling simulation, as well as a control-design, point of view, it is sensible to consider modulated transformers (MTF in the bond graph language) instead of the pairs of complementary switches. The port-Hamiltonian models of both subsystems are presented and, using a power-preserving interconnection, the Hamiltonian description of the whole system is obtained; detailed bond graphs of all subsystems and the complete system are also provided. Using passivity-based controllers computed in the Hamiltonian formalism for both subsystems, the whole model is simulated; simulations are run to rest the correctness and efficiency of the Hamiltonian network modelling approach used in this work.

A need for determination of arsenic species at low levels in cereal-based food and infant cereals. Validation of a method by LC-ICPMS.

The present study arose from the need to determine inorganic arsenic (iAs) at low levels in cereal-based food. Validated methods with a low limit of detection (LOD) are required to analyse these kinds of food. An analytical method for the determination of iAs, methylarsonic acid (MA) and dimethylarsinic acid (DMA) in cereal-based food and infant cereals is reported. The method was optimised and validated to achieve low LODs. Ion chromatography-inductively coupled plasma mass spectrometry (LC-ICPMS) was used for arsenic speciation. The main quality parameters were established. To expand the applicability of the method, different cereal products were analysed: bread, biscuits, breakfast cereals, wheat flour, corn snacks, pasta and infant cereals. The total and inorganic arsenic content of 29 cereal-based food samples ranged between 3.7-35.6 and 3.1-26.0 microg As kg-1, respectively. The present method could be considered a valuable tool for assessing inorganic arsenic contents in cereal-based foods.

Flocking behaviour: Agent-based simulation and hierarchical leadership.

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Likelihood-based approaches to modeling demand for medical care

We review recent likelihood-based approaches to modeling demand for medical care. A semi-nonparametric model along the lines of Cameron and Johansson's Poisson polynomial model, but using a negative binomial baseline model, is introduced. We apply these models, as well a semiparametric Poisson, hurdle semiparametric Poisson, and finite mixtures of negative binomial models to six measures of health care usage taken from the Medical Expenditure Panel survey. We conclude that most of the models lead to statistically similar results, both in terms of information criteria and conditional and unconditional prediction. This suggests that applied researchers may not need to be overly concerned with the choice of which of these models they use to analyze data on health care demand.

Lysine-based surfactants in nanovesicle formulations: the role of cationic charge position and hydrophobicity in in vitro cytotoxicity and intracellular delivery

Understanding nanomaterial interactions within cells is of increasing importance for assessing their toxicity and cellular transport. Here, we developed nanovesicles containing bioactive cationic lysine-based amphiphiles, and assessed whether these cationic compounds increase the likelihood of intracellular delivery and modulate toxicity. We found different cytotoxic responses among the formulations, depending on surfactant, cell line and endpoint assayed. The induction of mitochondrial dysfunction, oxidative stress and apoptosis were the general mechanisms underlying cytotoxicity. Fluorescence microscopy analysis demonstrated that nanovesicles were internalized by HeLa cells, and evidenced that their ability to release endocytosed materials into cell cytoplasm depends on the structural parameters of amphiphiles. The cationic charge position and hydrophobicity of surfactants determine the nanovesicle interactions within the cell and, thus, the resulting toxicity and intracellular behavior after cell uptake of the nanomaterial. The insights into some toxicity mechanisms of these new nanomaterials contribute to reducing the uncertainty surrounding their potential health hazards.

Fourier-based registration for robust forward-looking sonar mosaicing in low-visibility underwater environments

Vehicle operations in underwater environments are often compromised by poor visibility conditions. For instance, the perception range of optical devices is heavily constrained in turbid waters, thus complicating navigation and mapping tasks in environments such as harbors, bays, or rivers. A new generation of high-definition forward-looking sonars providing acoustic imagery at high frame rates has recently emerged as a promising alternative for working under these challenging conditions. However, the characteristics of the sonar data introduce difficulties in image registration, a key step in mosaicing and motion estimation applications. In this work, we propose the use of a Fourier-based registration technique capable of handling the low resolution, noise, and artifacts associated with sonar image formation. When compared to a state-of-the art region-based technique, our approach shows superior performance in the alignment of both consecutive and nonconsecutive views as well as higher robustness in featureless environments. The method is used to compute pose constraints between sonar frames that, integrated inside a global alignment framework, enable the rendering of consistent acoustic mosaics with high detail and increased resolution. An extensive experimental section is reported showing results in relevant field applications, such as ship hull inspection and harbor mapping