Hydrophobic effects on protein/nucleic acid interaction: enhancement of substrate binding by mutating tyrosine 45 to tryptophan in ribonuclease Tl

Hydrophobic effects on binding of ribonuclease Tl to guaninebases of several ribonucleotides have been proved by mutatinga hydrophobic residue at the recognition site and by measuringthe effect on binding. Mutation of a hydrophobic surface residueto a more hydrophobic residue (Tyr45 – Trp) enhances thebinding to ribonucleotides, including mononucleotide inhibitorand product, and a synthetic substrate-analog trinudeotide aswell as the binding to dinucleotide substrates and RNA. Enhancementson binding to non-substrate ribonucleotides by the mutationhave been observed with free energy changes ranging from –2.2 to – 3 .9 kJ/mol. These changes are in good agreementwith that of substrate binding, –2.3 kJ/mol, which iscalculated from Michaelis constants obtained from kinetic studies.It is shown, by comparing the observed and calculated changesin binding free energy with differences in the observed transferfree energy changes of the amino acid side chains from organicsolvents to water, that the enhancement observed on guaninebinding comes from the difference in the hydrophobic effectsof the side chains of tyrosine and tryptophan. Furthermore,a linear relationship between nucleolytic activities and hydrophobicityof the residues (Ala, Phe, Tyr, Trp) at position 45 is observed.The mutation could not change substantially the base specificityof RNase Tl, which exhibits a prime requirement for guaninebases of substrates.     

Autoxidation of ethyl eicosapentaenoate and docosahexaenoate

The extent of oxidation of ethyl esters of eicosapentaenoic (EPA) and docosahexaenoic acids (DHA) was compared quantitatively with that of ethyl linoleate (Lo) and ethyl linolenate (Ln) by oxygen uptake and formation of conjugated diene, hydroperoxide and secondary oxidation products. EPA and DHA esters were oxidized rapidly even at 5 C in the dark after an induction period of 3–4 days, while the induction periods of Ln and Lo esters were 20 days and more than 60 days, respectively. Oxygen uptake of EPA and DHA esters after the induction period was 5.2 and 8.5 times faster than that of ethyl Ln, respectively. Hydroperoxides of EPA and DHA esters are much less stable than those of ethyl Lo. The peroxide value is not necessarily a good indication of oxidation in these polyenoic acids because a considerable amount of secondary products is formed at the early stage of oxidation. Polymers were found to be major secondary products in these polyenoic esters.     

The oxidative coupling of methane on alkali- and alkaline earth-phosphate catalysts

The oxidative coupling of methane has been tested over alkali- and alkaline earth-phosphate catalysts at 700 and 775 °C with and without the introduction of a small quantity of tetrachloromethane (TCM) to the feedstream. In general, the conversion of methane was enhanced by the addition of TCM but the effect on selectivity was dependent on the catalyst being examined. The selectivity to C₂ and higher hydrocarbons and that to oxidation products have been shown to have a dependence on the cation radius/charge ratio.     

Formation and transformation of cubic 3PbO·2Ta2O5 solid solution

The formation of lead tantalates in the PbO-rich region is studied using the powders prepared by the simultaneous hydrolysis of lead and tantalum alkoxides. Cubic 3PbO · 2Ta₂O₅ solid solutions crystallize at low temperatures from amorphous materials between 60 and 75 mol% PbO. The lattice parameter,a, increases linearly from 1.0545 to 1.0705 nm with increasing PbO. At higher temperatures the solid solutions above 66.67 mol% PbO are transformed into those of rhombohedral 2PbO · Ta₂O₅. Rhombohedral 5PbO · 2Ta₂O₅ is formed at 850 to 900 °C by transformation of 2PbO·Ta₂O₅ solid solution corresponding to 71.43 mol% PbO. The existence of previously reported 3PbO·Ta₂O₅ is not confirmed.     

Isolation kernel: the X factor in efficient and effective large scale online kernel learning

Large scale online kernel learning aims to build an efficient and scalable kernel-based predictive model incrementally from a sequence of potentially infinite data points. Current state-of-the-art large scale online kernel learning focuses on improving efficiency. Two key approaches to gain efficiency through approximation are (1) limiting the number of support vectors, and (2) using an approximate feature map. They often employ a kernel with a feature map with intractable dimensionality. While these approaches can deal with large scale datasets efficiently, this outcome is achieved by compromising predictive accuracy because of the approximation. We offer an alternative approach that puts the kernel used at the heart of the approach. It focuses on creating a sparse and finite-dimensional feature map of a kernel called Isolation Kernel. Using this new approach, to achieve the above aim of large scale online kernel learning becomes extremely simple—simply use Isolation Kernel instead of a kernel having a feature map with intractable dimensionality. We show that, using Isolation Kernel, large scale online kernel learning can be achieved efficiently without sacrificing accuracy.

     

Predicting viewer-perceived activity/dominance in soccer games with stick-breaking HMM using data from a fixed set of cameras

We attempted to predict activity/dominance for soccer games, where activity is defined as the degree of activity of the game as perceived by the viewer, whereas dominance is the degree at which the viewer perceives a particular team to dominate over the other team. Such activity/dominance information would help a layman viewer understand the game. It would also enable construction of an automatic digest creation system that extracts scenes having high activity/dominance. There are two facets of this study: 1. The main part of the underlying prediction model consists of a Stick-Breaking Hidden Markov Model, where the data automatically estimates the number of states of the Markov process behind the data. 2. The data used in this paper is vector time-series data consisting of player, referee, and ball positions, together with team information, acquired by a set of fixed cameras. The problem was approached with a Bayesian framework where learning and prediction were implemented by three different methods: Markov Chain Monte Carlo, Expectation Maximization, and Variational Bayes. The proposed method was tested using a dataset consisting of 10 professional soccer games and was compared against standard regression methods.     

Critical mass in the emergence of collective intelligence: a parallelized simulation of swarms in noisy environments

We extend an abstract agent-based swarming model based on the evolution of neural network controllers, to explore further the emergence of swarming. Our model is grounded in the ecological situation, in which agents can access some information from the environment about the resource location, but through a noisy channel. Swarming critically improves the efficiency of group foraging, by allowing agents to reach resource areas much more easily by correcting individual mistakes in group dynamics. As high levels of noise may make the emergence of collective behavior depend on a critical mass of agents, it is crucial to reach sufficient computing power to allow for the evolution of the whole set of dynamics in simulation. Since simulating neural controllers and information exchanges between agents are computationally intensive, to scale up simulations to model critical masses of individuals, the implementation requires careful optimization. We apply techniques from astrophysics known as treecodes to compute the signal propagation, and efficiently parallelize for multi-core architectures. Our results open up future research on signal-based emergent collective behavior as a valid collective strategy for uninformed search over a domain space.     

Gender Differences in Mouse and Cursor Movements

Computer cursor and mouse activities such as moving, pointing, selecting, and dragging are essential parts of everyday interactions. Yet it is unknown how men and women differ in the way they move computer cursors. This study examines gender differences in movements of computer cursors. In one experiment, the authors measured trajectories of computer cursors every 20 ms in a simple choice-reaching task and tested the extent to which movement features related to controlling and targeting diverge between male and female participants. Results showed significant gender differences in cursor motions. Female participants deviated from the straight path toward the target location to a larger degree than did male participants, and female participants showed more backward motions (deviating backward from the target location) than did male participants. Implications for sources of these gender differences, user interface and input device design, and musculoskeletal disorders in women are also discussed.     

An Example-based Procedural System for Element Arrangement

We present a method for synthesizing two dimensional (2D) element arrangements from an example. The main idea is to combine texture synthesis techniques based‐on a local neighborhood comparison and procedural modeling systems based‐on local growth. Given a user‐specified reference pattern, our system analyzes neigh‐borhood information of each element by constructing connectivity. Our synthesis process starts with a single seed and progressively places elements one by one by searching a reference element which has local features that are the most similar to the target place of the synthesized pattern. To support creative design activities, we introduce three types of interaction for controlling global features of the resulting pattern, namely a spray tool, a flow field tool, and a boundary tool. We also introduce a global optimization process that helps to avoid local error concentrations. We illustrate the feasibility of our method by creating several types of 2D patterns.