Elastic properties and secondary structure formation of single-stranded DNA at monovalent and divalent salt conditions

Single-stranded DNA (ssDNA) plays a major role in several biological processes. It is therefore of fundamental interest to understand how the elastic response and the formation of secondary structures are modulated by the interplay between base pairing and electrostatic interactions. Here we measure force-extension curves (FECs) of ssDNA molecules in optical tweezers set up over two orders of magnitude of monovalent and divalent salt conditions, and obtain its elastic parameters by fitting the FECs to semiflexible models of polymers. For both monovalent and divalent salts, we find that the electrostatic contribution to the persistence length is proportional to the Debye screening length, varying as the inverse of the square root of cation concentration. The intrinsic persistence length is equal to 0.7 nm for both types of salts, and the effectivity of divalent cations in screening electrostatic interactions appears to be 100-fold as compared with monovalent salt, in line with what has been recently reported for single-stranded RNA. Finally, we propose an analysis of the FECs using a model that accounts for the effective thickness of the filament at low salt condition and a simple phenomenological description that quantifies the formation of non-specific secondary structure at low forces.

Assessment of the levels of degradation in fat co- and by-products for feed uses and their relationships with some lipid composition parameters

This paper discusses the levels of degradation of some co- and byproducts of the food chain intended for feed uses. As the first part of a research project, 'Feeding Fats Safety', financed by the sixth Framework Programme-EC, a total of 123 samples were collected from 10 European countries, corresponding to fat co- and byproducts such as animal fats, fish oils, acid oils from refining, recycled cooking oils, and other. Several composition and degradation parameters (moisture, acid value, diacylglycerols and monoacylglycerols, peroxides, secondary oxidation products, polymers of triacylglycerols, fatty acid composition, tocopherols, and tocotrienols) were evaluated. These findings led to the conclusion that some fat by- and coproducts, such as fish oils, lecithins, and acid oils, show poor, nonstandardized quality and that production processes need to be greatly improved. Conclusions are also put forward about the applicability and utility of each analytical parameter for characterization and quality control.

Influence of process parameters on part quality and mechanical properties for DMLS and SLM with iron-based materials

Rapid manufacturing is an advanced manufacturing technology based on layer-by-layer manufacturing to produce a part. This paper presents experimental work carried out to investigate the effects of scan speed, layer thickness, and building direction on the following part features: dimensional error, surface roughness, and mechanical properties for DMLS with DS H20 powder and SLM with CL 20 powder (1.4404/AISI 316L). Findings were evaluated using ANOVA analysis. According to the experimental results, build direction has a significant effect on part quality, in terms of dimensional error and surface roughness. For the SLM process, the build direction has no influence on mechanical properties. Results of this research support industry estimating part quality and mechanical properties before the production of parts with additive manufacturing, using iron-based powders

Analytical Dirac-Hartree-Fock-Slater screening function for atoms (Z=1-92)

An analytical approximation, depending on five parameters, for the atomic screening function is proposed. The corresponding electrostatic potential takes a simple analytical form (superposition of three Yukawa potentials) well suited to most practical applications. Parameters in the screening function, determined by an analytical fitting procedure to Dirac-Hartree-Fock-Slater (DHFS) self-consistent data, are given for Z=1¿92. The reliability of this analytical approach is demonstrated by showing that (a) Born cross sections for elastic scattering of fast charged particles by the present analytical field and by the DHFS field practically coincide and (b) one-electron binding energies computed from the independent-particle model with our analytical field (corrected for exchange and electrostatic self-interaction) agree closely with the DHFS energy eigenvalues.

Monte Carlo simulation of x-ray spectra generated by kilo-electron-volt electrons

We present a general algorithm for the simulation of x-ray spectra emitted from targets of arbitrary composition bombarded with kilovolt electron beams. Electron and photon transport is simulated by means of the general-purpose Monte Carlo code PENELOPE, using the standard, detailed simulation scheme. Bremsstrahlung emission is described by using a recently proposed algorithm, in which the energy of emitted photons is sampled from numerical cross-section tables, while the angular distribution of the photons is represented by an analytical expression with parameters determined by fitting benchmark shape functions obtained from partial-wave calculations. Ionization of K and L shells by electron impact is accounted for by means of ionization cross sections calculated from the distorted-wave Born approximation. The relaxation of the excited atoms following the ionization of an inner shell, which proceeds through emission of characteristic x rays and Auger electrons, is simulated until all vacancies have migrated to M and outer shells. For comparison, measurements of x-ray emission spectra generated by 20 keV electrons impinging normally on multiple bulk targets of pure elements, which span the periodic system, have been performed using an electron microprobe. Simulation results are shown to be in close agreement with these measurements.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications