Interaction of Boron Carbide with Nickel Oxide

Thermodynamic methods and x-ray analysis have been applied to the chemical interactions in 0.9625 B₄C + 0.05 NiO + 0.0375 C, B₄C + NiO, B₄C + 4 NiO + 3 C mixtures; stages occur in the processes there that correspond to various temperature ranges. It is found that NiB always contains small amounts of lower borides, whose quantity does not exceed 2 mass% when the synthesis conditions are optimal.     

Partition coefficients of environmentally important phenols in a supercritical carbon dioxide-water system from cocurrent extraction without analysis of the compressible phase

Partition coefficients of phenol, salicylic acid, and several environmentally important chloro- and nitrophenols in a supercritical CO2-water system were measured using direct cocurrent extraction of aqueous solutions of the individual solutes with CO2. Partitioning data on the nitrophenols and salicylic acid were obtained for the first time. To bypass the troublesome and error-prone analysis of the CO2-rich phase, the present method employed only the solute concentrations in the aqueous phase before and after extraction to determine the partition coefficient. Unlike most previous engineering studies of phenol partitioning in a CO2-water system, the concentrations of phenolic solutes approached infinite dilution in both phases. This makes the results relevant to analytical-scale SFE of environmental water samples with CO2. Because of effective infinite dilution of the solutes, the partition coefficients provide a direct measure of relative CO2-philicity/hydrophilicity of the individual phenols. Compared to the octanol-water partition coefficients of substituted phenols, the CO2-water partition coefficients are more sensitive to substitution in the position neighboring the hydroxyl group.     

Experimental activation energies for evolution of oxygen and chlorine on oxide electrodes

The chlorine and oxygen overpotential in dependence on the current density i (A cm^?2) and on the temperature in the range of 15–75°C was measured at γ-MnO₂ and β-PbO₂ electrodes in concentrated water solutions of sodium chloride and perchlorate. From the measured values the experimental activation energy in dependence on overpotential was calculated and, for the temperature of 25°C, the constants of Tafel's equation (a,b) (α, i_o respectively) were evaluated.     

Nonlinear elasticity imaging: theory and phantom study

In tissue the Young's modulus cannot be assumed constant over a wide deformation range. For example, direct mechanical measurements on human prostate show up to a threefold increase in Young's modulus over a 10% deformation. In conventional elasticity imaging, these effects produce strain-dependent elastic contrast. Ignoring these effects generally leads to suboptimal contrast (stiffer tissues at lower strain are contrasted against softer tissues at higher strain), but measuring the nonlinear behavior results in enhanced tissue differentiation. To demonstrate the methods extracting nonlinear elastic properties, both simulations and measurements were performed on an agar-gelatin phantom. Multiple frames of phase-sensitive ultrasound data are acquired as the phantom is deformed by 12%. All interframe displacement data are brought back to the geometry of the first frame to form a three-dimensional (3-D) data set (depth, lateral, and preload dimensions). Data are fit to a 3-D second order polynomial model for each pixel that adjusts for deformation irregularities. For the phantom geometry and elastic properties considered in this paper, reconstructed frame-to-frame strain images using this model result in improved contrast to noise ratios (CNR) at all preload levels, without any sacrifice in spatial resolution. From the same model, strain hardening at all preload levels can be extracted. This is an independent contrast mechanism. Its maximum CNR occurs at 5.13% preload, and it is a 54% improvement over the best case (preload 10.6%) CNR for frame-to-frame strain reconstruction. Actual phantom measurements confirm the essential features of the simulation. Results show that modeling of the nonlinear elastic behavior has the potential to both increase detectability in elasticity imaging and provide a new independent mechanism for tissue differentiation.     

Structure-based design of inhibitors of NS3 serine protease of hepatitis C virus

We have designed small focused combinatorial library of hexapeptide inhibitors of NS3 serine protease of the hepatitis C virus (HCV) by structure-based molecular design complemented by combinatorial optimisation of the individual residues. Rational residue substitutions were guided by the structure and properties of the binding pockets of the enzyme's active site. The inhibitors were derived from peptides known to inhibit the NS3 serine protease by using unusual amino acids and alpha-ketocysteine or difluoroaminobutyric acid, which are known to bind to the S1 pocket of the catalytic site. Inhibition constants (Ki) of the designed library of inhibitors were predicted from a QSAR model that correlated experimental Ki of known peptidic inhibitors of NS3 with the enthalpies of enzyme-inhibitor interaction computed via molecular mechanics and the solvent effect contribution to the binding affinity derived from the continuum model of solvation. The library of the optimised inhibitors contains promising drug candidates-water-soluble anionic hexapeptides with predicted Ki* in the picomolar range.     

Festina lente: learning and inertia among Italian automobile producers, 1896-1981

Based on the premise that learning and inertia develop and operatein organizations simultaneously, this paper examines under whatconditions adaptation or selection will take place. We haveanalyzed the process of technological scope expansion amongItalian automobile firms, and found that firms prone to expandingtheir technological competencies tend to be either specificallyorganized to benefit from variation-based learning or do soin response to pressures from competitive intensity in theirenvironment. But these effects hinge on the structure of themarket that evolves as the industry consolidates. We also examinethe failure rates of Italian auto firms and find that implementinga core change generates negative repercussions for survivalbut this effect can be countered by properties of the organizationaldesign that facilitate variation-based learning. Our resultssuggest that organization theory will benefit if ecologicaland learning theories are further integrated in future research.     

Biclustering in data mining

Biclustering consists in simultaneous partitioning of the set of samples and the set of their attributes (features) into subsets (classes). Samples and features classified together are supposed to have a high relevance to each other. In this paper we review the most widely used and successful biclustering techniques and their related applications. This survey is written from a theoretical viewpoint emphasizing mathematical concepts that can be met in existing biclustering techniques.     

Acoustically Enhanced Water Mist Suppression of Heptane Fueled Flames

Recent research has shown that acoustics can be used to suppress flames from a liquid fuel source. The results of these experiments indicated that acoustics alone are insufficient to control flames beyond the incipient stage. Recent research has also shown that variations in the delivery of water mist to a fire can enhance the mist’s efficiency. Therefore, the addition of acoustics to water mist may be an effective means of enhancing an established fire protection technology. For the first time, acoustics and water mist have been combined and studied as a flame suppression strategy. A series of experiments were conducted that explored the potential for coupling acoustics with water mist as means of flame suppression. Heptane fueled flames were created from two different sized ceramic fiber wicks: 30 mm?×?50 mm with 5 mL of fuel, and 60 mm?×?100 mm with 20 mL of fuel. The flames were then exposed to water mist delivered at a constant rate, which was found to be incapable of suppressing the flames. Next, low frequency sound waves at 62 Hz and 80 Hz were used to suppress flames from both wicks, with each frequency being generated by a different resonator. Finally, acoustics from both resonators were combined with water mist, and used to suppress flames from both wicks. The results showed that a combination of acoustic waves and water mist suppressed the flames more effectively than each individual technique on its own. This finding opens the possibility of developing more efficient ways to use water mist technology.     

Fabrication of buried microfluidic channels with observation windows using femtosecond laser photoablation and parylene-C coating

We developed an advanced method for fabricating microfluidic structures comprising channels and inputs/outputs buried within a silicon wafer based on single level lithography. We etched trenches into a silicon substrate, covered these trenches with parylene-C, and selectively opened their bottoms using femtosecond laser photoablation, forming channels and inputs/outputs by isotropic etching of silicon by xenon difluoride vapors. We subsequently sealed the channels with a second parylene-C layer. Unlike in previously published works, this entire process is conducted at ambient temperature to allow for integration with complementary metal oxide semiconductor devices for smart readout electronics. We also demonstrated a method of chip cryo-cleaving with parylene presence that allows for monitoring of the process development. We also created an observation window for in situ visualization inside the opaque silicon substrate by forming a hole in the parylene layer at the silicon backside and with local silicon removal by xenon difluoride vapor etching. We verified the microfluidic chip performance by forming a segmented flow of a fluorescein solution in an oil stream. This proposed technique provides opportunities for forming simple microfluidic systems with buried channels at ambient temperature.     

Robust self-assembly of graphs

Self-assembly is a process in which small building blocks interact autonomously to form larger structures. A recently studied model of self-assembly is the Accretive Graph Assembly Model whereby an edge-weighted graph is assembled one vertex at a time starting from a designated seed vertex. The weight of an edge specifies the magnitude of attraction (positive weight) or repulsion (negative weight) between adjacent vertices. It is feasible to add a vertex to the assembly if the total attraction minus repulsion of the already built neighbors exceeds a certain threshold, called the assembly temperature. This model naturally generalizes the extensively studied Tile Assembly Model. A natural question in graph self-assembly is to determine whether or not there exists a sequence of feasible vertex additions to realize the entire graph. However, even when it is feasible to realize the assembly, not much can be inferred about its likelihood of realization in practice due to the uncontrolled nature of the self-assembly process. Motivated by this, we introduce the robust self-assembly problem where the goal is to determine if every possible sequence of feasible vertex additions leads to the completion of the assembly. We show that the robust self-assembly problem is co-NP-complete even on planar graphs with two distinct edge weights. We then examine the tractability of the robust self-assembly problem on a natural subclass of planar graphs, namely grid graphs. We identify structural conditions that determine whether or not a grid graph can be robustly self-assembled, and give poly-time algorithms to determine this for several interesting cases of the problem. Finally, we also show that the problem of counting the number of feasible orderings that lead to the completion of an assembly is #P-complete.