Molecular recognition by wall-assembling-type nanocavity in aqueous media

Steroid cyclophanes, each having a macrocyclic ring attached to four bile acid moieties via chiral lysine connectors, were synthesized, and the binding of the 2-naphthylphenylketone (guest) to the steroid cyclophanes in water was investigated. The circular dichroism spectra of the steroid cyclophane with cholic acid and L-lysine were significantly affected by the binding of the guest, and the induced circular dichroism based on the absorption of the achiral guest was also observed. The binding of the guest to the steroid cyclophane with cholic acids and D-lysines induced changes in the circular dichroism spectra with the opposite sign of the molecular ellipticities. An induced circular dichroism spectral change was not observed upon binding of the guest to the analogous host without OH sites. These results strongly suggest that the guest is conformationally fixed through hydrogen bonding between the carbonyl group of the guest and the steroidal hydroxyl group of the host. The assembly of only four steroid residues on the macrocyclic ring probably provided a hydrophobic nanocavity for hydrogen bonding.     

A positive selection for plasmid loss in Saccharomyces cerevisiae using galactose-inducible growth inhibitory sequences

Counter-selections for the loss of introduced plasmid sequences are useful for gene manipulations in yeast. We have used GAL10 promoter-mediated overexpression of GIN sequences, which inhibit the growth of cells, to develop a novel counter-selection system. Yeast cells carrying a GIN sequence grow normally on glucose medium but are unable to grow on galactose medium, whereas derivatives that have lost the GIN sequence are able to grow in the presence of galactose. We constructed autonomously replicating, integrating, and disruption plasmids carrying GIN sequences and tested their use to select for loss of the plasmid. The results showed that the GIN sequences provide a selection for efficient loss of plasmids or integrated constructs from yeast during growth on galactose medium, indicating that this system can be used for plasmid shuffling, gene replacements and marker gene recycling. This counter-selection system has wide application, because any Gal+ strain and a wide variety of marker genes can be used. In addition, counter-selection systems using growth-inhibitory sequences should be applicable to other yeasts and possibly to other organisms.     

Symmetric lithium-ion cell based on lithium vanadium fluorophosphate with ionic liquid electrolyte

Lithium vanadium fluorophosphate, LiVPO₄F, was utilized as both cathode and anode for fabrication of a symmetric lithium-ion LiVPO₄F//LiVPO₄F cell. The electrochemical evolution of the LiVPO₄F//LiVPO₄F cell with the commonly used organic electrolyte LiPF₆/EC-DMC has shown that this cell works as a secondary battery, but exhibits poor durability at room temperature and absolutely does not work at increased operating temperatures. To improve the performance and safety of this symmetric battery, we substituted a non-flammable ionic liquid (IL) LiBF₄/EMIBF₄ electrolyte for the organic electrolyte. The symmetric battery using the IL electrolyte was examined galvanostatically at different rates and operating temperatures within the voltage range of 0.01–2.8 V. It was demonstrated that the IL-based symmetric cell worked as a secondary battery with a Coulombic efficiency of 77% at 0.1 mA cm⁻² and 25 °C. It was also found that the use of the IL electrolyte instead of the organic one resulted in the general reduction of the first discharge capacity by about 20–25% but provided much more stable behavior and a longer cycle life. Moreover, an increase of the discharge capacity of the IL-based symmetric battery up to 120 mA h g⁻¹ was observed when the operating temperature was increased up to 80 °C at 0.1 mA cm⁻². The obtained electrochemical behavior of both symmetric batteries was confirmed by complex-impedance measurements at different temperatures and cycling states. The thermal stability of LiVPO₄F with both the IL and organic electrolytes was also examined.     

Mechanical behavior of a single polymer chain in a non-solvent

Mechanical properties of a single polystyrene chain in mixtures of dioxane and methanol were measured with AFM. The effect of the solubility of the surrounding liquid on mechanical behavior of a polymer chain was examined. In good and Θ solvents, the force-extension curves exhibit a freely jointed chain (FJC)-like trend with good reproducibility. In a non-solvent, the profile of force-extension curve was dependent on the extension speed: an FJC-like nature emerged at the lower speed of 200 nm/s while saw-toothed curves were obtained at the higher speed of 2000 nm/s. The shape of saw-toothed curves varied from measurement to measurement. A force relaxation was also observed in the non-solvent under a fixed extension distance after 2000 nm/s extension. The mechanical behavior in non-solvents suggests that inhomogeneous deformation of a PS chain occurs due to reduction of the chain mobility.     

Monolithiation of 5,5′‐Dibromo‐2,2′‐bithiophene Using Flow Microreactors: Mechanistic Implications and Synthetic Applications

The lithiation of 5,5′‐dibromo‐2,2′‐bithiophene with one equivalent of an alkyllithium such as n‐BuLi or s‐BuLi was studied by varying the residence time in flow microreactors. With a short residence time, the product 2,2′‐bithiophene (3) derived from dilithiation was obtained preferentially and a significant amount of the starting material 5,5′‐dibromo‐2,2′‐bithiophene remained unchanged. An increase in the residence time caused a higher yield of the product 5‐bromo‐2,2′‐bithiophene derived from monolithiation with expense in the yields of 2,2′‐bithiophene and 5,5′‐dibromo‐2,2′‐bithiophene. The lithiation using MeLi gave the product 5‐bromo‐2,2′‐bithiophene preferentially even with a very short residence time.     

Synthesis of optimal controllers for piecewise affine systems with sampled-data switching

This paper discusses the optimal control problem of the continuous-time piecewise affine (PWA) systems with sampled-data switching, where the switching action is executed based upon a condition on the state at each sampling time. First, an algebraic characterization for the problem to be feasible is derived. Next, an optimal continuous-time controller is derived for a general class of PWA systems with sampled-data switching, for which the optimal control problem is feasible but whose subsystems in some modes may be uncontrollable in the usual sense. Finally, as an application of the proposed approach, the high-speed and energy-saving control problem of the CPU processing is formulated, and the validity of the proposed methods is shown by numerical simulations.     

Well-posedness analysis of switch-driven piecewise affine systems

The well-posedness problem (existence and uniqueness of solutions) of a class of multi-modal piecewise affine systems is addressed, where binary-switches individually act under autonomous switching. First, a new transition rule on the discrete state, called the switch-based transition rule, is introduced and some relations with the mode-based transition rule are discussed. Next, a sufficient condition for such a multi-modal system to be well-posed for all external inputs is derived in terms of well-posedness of its subsystems of lower complexity "bimodal systems". Finally, an easily checkable condition for the bimodal system to be well-posed for all external inputs is given, which consequently allows us to algebraically determine well-posedness of the multi-modal systems in question.     

On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms

Outlier detection is a fundamental issue in data mining, specifically in fraud detection, network intrusion detection, network monitoring, etc. SmartSifter is an outlier detection engine addressing this problem from the viewpoint of statistical learning theory. This paper provides a theoretical basis for SmartSifter and empirically demonstrates its effectiveness. SmartSifter detects outliers in an on-line process through the on-line unsupervised learning of a probabilistic model (using a finite mixture model) of the information source. Each time a datum is input SmartSifter employs an on-line discounting learning algorithm to learn the probabilistic model. A score is given to the datum based on the learned model with a high score indicating a high possibility of being a statistical outlier. The novel features of SmartSifter are: (1) it is adaptive to non-stationary sources of data; (2) a score has a clear statistical/information-theoretic meaning; (3) it is computationally inexpensive; and (4) it can handle both categorical and continuous variables. An experimental application to network intrusion detection shows that SmartSifter was able to identify data with high scores that corresponded to attacks, with low computational costs. Further experimental application has identified a number of meaningful rare cases in actual health insurance pathology data from Australia's Health Insurance Commission.     

Efficient distribution-free population learning of simple concepts

We consider a variant of the ‘population learning model’ proposed by Kearns and Seung [8], in which the learner is required to be ‘distribution-free’ as well as computationally efficient. A population learner receives as input hypotheses from a large population of agents and produces as output its final hypothesis. Each agent is assumed to independently obtain labeled sample for the target concept and output a hypothesis. A polynomial time population learner is said to PAC-learn a concept class, if its hypothesis is probably approximately correct whenever the population size exceeds a certain bound which is polynomial, even if the sample size for each agent is fixed at some constant. We exhibit some general population learning strategies, and some simple concept classes that can be learned by them. These strategies include the ‘supremum hypothesis finder’, the ‘minimum superset finder’ (a special case of the ‘supremum hypothesis finder’), and various voting schemes. When coupled with appropriate agent algorithms, these strategies can learn a variety of simple concept classes, such as the ‘high–low game’, conjunctions, axis-parallel rectangles and others. We give upper bounds on the required population size for each of these cases, and show that these systems can be used to obtain a speed up from the ordinary PAC-learning model [11], with appropriate choices of sample and population sizes. With the population learner restricted to be a voting scheme, what we have is effectively a model of ‘population prediction’, in which the learner is to predict the value of the target concept at an arbitrarily drawn point, as a threshold function of the predictions made by its agents on the same point. We show that the population learning model is strictly more powerful than the population prediction model. Finally, we consider a variant of this model with classification noise, and exhibit a population learner for the class of conjunctions in this model. This revised version was published online in June 2006 with corrections to the Cover Date.