Quantum computing with spin qubits in semiconductor structures

We survey recent work on designing and evaluating quantum computing implementations based on nuclear or bound-electron spins in semiconductor heterostructures at low temperatures and in high magnetic fields. General overview is followed by a summary of results of our theoretical calculations of decoherence time scales and spin-spin interactions. The latter were carried out for systems for which the two-dimensional electron gas provides the dominant carrier for spin dynamics via exchange of spin-excitons in the integer quantum Hall regime.     

Using artificial neural networks to detect unknown computer worms

Detecting computer worms is a highly challenging task. We present a new approach that uses artificial neural networks (ANN) to detect the presence of computer worms based on measurements of computer behavior. We compare ANN to three other classification methods and show the advantages of ANN for detection of known worms. We then proceed to evaluate ANN’s ability to detect the presence of an unknown worm. As the measurement of a large number of system features may require significant computational resources, we evaluate three feature selection techniques. We show that, using only five features, one can detect an unknown worm with an average accuracy of 90%. We use a causal index analysis of our trained ANN to identify rules that explain the relationships between the selected features and the identity of each worm. Finally, we discuss the possible application of our approach to host-based intrusion detection systems.     

Online variance minimization

We consider the following type of online variance minimization problem: In every trial t our algorithms get a covariance matrix C ^t and try to select a parameter vector w ^t−1 such that the total variance over a sequence of trials ?_t=1^T (w^t-1)^T C^tw^t-1\sum_{t=1}^{T} (\boldsymbol {w}^{t-1})^{\top} \boldsymbol {C}^{t}\boldsymbol {w}^{t-1} is not much larger than the total variance of the best parameter vector u chosen in hindsight. Two parameter spaces in ℝ ⁿ are considered—the probability simplex and the unit sphere. The first space is associated with the problem of minimizing risk in stock portfolios and the second space leads to an online calculation of the eigenvector with minimum eigenvalue of the total covariance matrix ?_t=1^T C^t\sum_{t=1}^{T} \boldsymbol {C}^{t}. For the first parameter space we apply the Exponentiated Gradient algorithm which is motivated with a relative entropy regularization. In the second case, the algorithm has to maintain uncertainty information over all unit directions u. For this purpose, directions are represented as dyads uu ^⊤ and the uncertainty over all directions as a mixture of dyads which is a density matrix. The motivating divergence for density matrices is the quantum version of the relative entropy and the resulting algorithm is a special case of the Matrix Exponentiated Gradient algorithm. In each of the two cases we prove bounds on the additional total variance incurred by the online algorithm over the best offline parameter.     

Balanced timed regular expressions

Several classes of regular expressions for timed languages accepted by timed automata have been suggested in the literature. In this article we introduce balanced timed regular expressions with colored parentheses which are equivalent to timed automata, and, differently from existing definitions, do not refer to clock values, and do not use additional operations such as intersection and renaming.     

On modeling the deformations and tool-workpiece interactions during machining metal matrix composites

Significance of application of metal matrix composites (MMCs) in various industries has already been demonstrated. In order to address the challenges faced during machining MMCs, development of novel modeling techniques for understanding the mechanics of the process is crucial. This paper presents a new approach towards finite element modeling of MMC machining process to facilitate the analysis of plastic deformations. Transient Lagrangian modeling is used with adaptive remeshing control in order to reduce the effects of mesh distortions on accurate estimation of plastic deformation during machining. The thorough understanding of MMC plastic deformations, which is achieved using the developed model, is an asset in analysis of MMC behavior during the process.     

Molecularly imprinted poly(acrylonitrile‐co‐acrylic acid) matrix with sclareol

There are presented results regarding a new set of molecularly imprinted polymers (MIPs) based on acrylonitrile:acrylic acid (AN:AA) copolymer matrix. As template, it was used sclareol, an important anticancer bioactive compound, never used before for molecular imprinting. An emerging and insufficient studied MIP preparation method, namely the phase inversion, was used to prepare 0.8 mm spherical sclareol MIPs (S‐MIPs). Three AN:AA copolymers, having the initial monomer ratios 90:10, 80:20, and 70:30, were synthesized by radical copolymerization in emulsion, without emulsifier. After that, each copolymer was dissolved in the presence of the template (sclareol) in dimethylformamide. The imprinting and the morphology of these new materials were analyzed by rheology, elemental analysis, infrared spectroscopy, size exclusion chromatography, thermogravimetric analysis, differential scanning calorimetry, batch rebinding tests, and Scatchard analysis. The conclusion was that the AN:AA‐80:20 matrix proved to be the optimized solution between high rigidity (given by the AN segments) and high affinity for the template (given by AA segments), the average imprinting factor for this system being 2.67. POLYM. ENG. SCI., 54:1484–1494, 2014. © 2013 Society of Plastics Engineers     

Bioavailability of nutraceuticals: Role of the food matrix,processing conditions,the gastrointestinal tract,and nanodelivery systems

Nowadays, many consumers prefer foods with a high content of nutraceuticals that contribute to the prevention or healing of chronic diseases. Therefore, in recent years, more and more researchers have studied the bioefficiency, safety, and toxicity of nutraceutical‐enriched foods. The key stage of nutraceutical bioefficiency is oral bioavailability, which involves the following processes: the release of nutraceuticals from food matrices or nanocarriers in gastrointestinal fluids, the solubilization of nutraceuticals and their interaction with other components of gastrointestinal fluids, the absorption of nutraceuticals by the epithelial layer, and the chemical and biochemical transformations into epithelial cells. These processes are endogenous factors that greatly influence the bioavailability of nutraceuticals. In addition to endogenous factors, the bioavailability of nutraceuticals is also affected by exogenous factors, such as: physicochemical properties of nutraceuticals, food matrix, food processing and storage, and so forth. Both the endogenous and exogenous factors are comprehensively analyzed in this review. Thus, the physicochemical and enzymatic processes involved in food digestion are described, highlighting the role of each stage of gastrointestinal tract (mouth, stomach, and intestine) in nutraceuticals bioaccessibility. The structure and functions of the mucus and epithelial layers, the mechanisms involved in the active and passive transport of nutraceuticals through the cell membrane, and phase I and phase II metabolism reactions are also discussed. Finally, this review focuses on several types of bioactive‐loaded nanocarriers such as lipid‐based, surfactant‐based, and biopolymeric nanocarriers that improve the bioavailability of nutraceuticals.     

Bistable hybrids in sol–gel technology for switching devices

Development of memories based on organic soft materials is a current industrial niche aimed at the upper contacts flash memories. The electrical bistability of such materials makes them ideal candidates for cost-effective, fast-programming switching devices. Hybrid thin films of SiO₂ with Rose Bengal (bis-triethylammonium) dopant are here reported for the first time, together with their characterisations. Technology-wise the main advantage of the films is the possibility to cast photolithographically, which is also cost-effective. The physical and chemical stability of the films yields reproducible devices, from both the microtechnological and electrical point of view.