Identification of Folding Intermediates of Streblin,The Most Stable Serine Protease: Biophysical Analysis

Streblin, a serine proteinase from plant Streblus asper, has been used to investigate the conformational changes induced by pH, temperature, and chaotropes. The near/far UV circular dichroism activities under fluorescence emission spectroscopy and 8-aniline-1-naphthalene sulfonate (ANS) binding have been carried out to understand the unfolding of the protein in the presence of denaturants. Spectroscopic studies reveal that streblin belongs to the α+β class of proteins and exhibits stability towards chemical denaturants, guanidine hydrochloride (GuHCl). The pH-induced transition of this protein is noncooperative for transition phases between pH 0.5 and 2.5 (midpoint, 1.5) and pH 2.5 and 10.0 (midpoint, 6.5). At pH 1.0 or lower, the protein unfolds to form acid-unfolded state, and for pH 7.5 and above, protein turns into an alkaline denatured state characterized by the absence of ANS binding. At pH 2.0 (1 M GuHCl), streblin exists in a partially unfolded state with characteristics of a molten globule state. The protein is found to exhibit strong and predominant ANS binding. In total, six different intermediate states has been identified to show protein folding pathways.     

A Maximal Correlation Framework for Fair Machine Learning

As machine learning algorithms grow in popularity and diversify to many industries, ethical and legal concerns regarding their fairness have become increasingly relevant. We explore the problem of algorithmic fairness, taking an information–theoretic view. The maximal correlation framework is introduced for expressing fairness constraints and is shown to be capable of being used to derive regularizers that enforce independence and separation-based fairness criteria, which admit optimization algorithms for both discrete and continuous variables that are more computationally efficient than existing algorithms. We show that these algorithms provide smooth performance–fairness tradeoff curves and perform competitively with state-of-the-art methods on both discrete datasets (COMPAS, Adult) and continuous datasets (Communities and Crimes).     

Ohmic and step noise from a single trapping center hybridized with a Fermi sea

We show that single electron tunneling devices such as the Cooper-pair box or double quantum dot can be sensitive to the zero-point fluctuation of a single trapping center hybridized with a Fermi sea. If the trap energy level is close to the Fermi sea and has linewidth gamma > k(B)T, its noise spectrum has an Ohmic Johnson-Nyquist form, whereas for gamma < k(B)T the noise has a Lorentzian form expected from the semiclassical limit. Trap levels above the Fermi level are shown to lead to steps in the noise spectrum that can be used to probe their energetics, allowing the identification of individual trapping centers coupled to the device.     

A comparative study of the non-isothermal degradation of natural rubber from Mangabeira (Hancornia speciosa Gomes) and Seringueira (Hevea brasiliensis)

Due to the increasing search for alternative sources of natural rubber (NR) whose properties are similar to Hevea brasiliesis, several sources have been studied in the past few years. Among them, Mangabeira (Hancornia speciosa Gomes), which is native to Amazon rainforest and other regions of Brazil, has a potential as another viable rubber source. As a continuation of a series of comparative studies between Hancornia and Hevea (clone RRIM 600) these two species by our research team, their thermal behavior was analyzed by thermogravimetry (TG) using Flynn–Wall–Ozawa’s approach in order to obtain kinetic parameters (reaction order, pre-exponential factor and activation energy) of the decomposition process. Results indicated that the thermal behavior of NR from Hancornia was comparable to Hevea with some differences observed as follows: reaction order for Hancornia was higher than for Hevea at the beginning of degradation and very close for temperatures over 350 °C; activation energy and pre-exponential factor had the same trend, i.e., increased with increasing degree of conversion remaining almost constant between 20 and 70% and then increasing for higher degrees, although Hevea was slightly more thermally stable than Hancornia. These major influences in the degradation process in the early stage are attributed to differences in non-rubber constituents present in these two species.     

Numerical analysis and computational testing of a high accuracy Leray‐deconvolution model of turbulence

We study a computationally attractive algorithm (based on an extrapolated Crank‐Nicolson method) for a recently proposed family of high accuracy turbulence models, the Leray‐deconvolution family. First we prove convergence of the algorithm to the solution of the Navier‐Stokes equations and delineate its (optimal) accuracy. Numerical experiments are presented which confirm the convergence theory. Our 3d experiments also give a careful comparison of various related approaches. They show the combination of the Leray‐deconvolution regularization with the extrapolated Crank‐Nicolson method can be more accurate at higher Reynolds number that the classical extrapolated trapezoidal method of Baker (Report, Harvard University, 1976). We also show the higher order Leray‐deconvolution models (e.g. N = 1,2,3) have greater accuracy than the N = 0 case of the Leray‐α model. Numerical experiments for the 2d step problem are also successfully investigated. Around the critical Reynolds number, the low order models inhibit vortex shedding behind the step. The higher order models, correctly, do not. To estimate the complexity of using Leray‐deconvolution models for turbulent flow simulations we estimate the models' microscale.© 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2008     

The role of rebound spikes in the maintenance of self-sustained neural spiking activity

Nonlinear Dynamics - In general, the mechanisms that maintain the activity of neural systems after a triggering stimulus has been removed are not well understood. Different mechanisms involving at...     

Optical Dispersion Characteristics of Planar Microlenses

It is essential to know the wavelength dispersion of a planar microlens in order to suitably design optical systems which use such a component. For this purpose, the measurement of focal length over a wide range of the spectrum has been performed. It was clarified that the focal length varies by about 20% from blue (ƛ=0.442 μm) to near-infra red (ƛ=1.55μm) region. The maximum index difference between the lens center and substrate, an important parameter for the characterization of planar microlenses, has been estimated as a function of wavelength using the ray equation. The effect of angled incidence has been discussed.     

A Microoptic Network Unit Using Planar Microlens Array

We propose a new concept for an optical network unit using planar microlens array for fiber to the home networks. It is expected from this modeling that an optical coupling loss of 2.5 dB, a polarization dependent loss of 0.5 dB and an extinction ratio larger than 50 dB can be achieved. The structure design and its fabrication method are discussed.