Validation of a Novel Sensing Approach for Continuous Pavement Monitoring Using Full-Scale APT Testing

The objective of this paper is to present a novel approach for the continuous monitoring of pavement condition through the use of combined piezoelectric sensing and novel condition-based interpretation methods. The performance of the developed approach is validated for the detection of bottom-up fatigue cracking through full-scale accelerated pavement testing (APT). The innovative piezoelectric sensors are installed at the bottom of a thin 102 mm (4 in.) asphalt layer. The structure is then loaded until failure (up to 1 million loading cycles in this study). The condition-based approach, used in this work, does not rely on stain measurements and allows users to bypass the need for any structural or finite-element models. Instead, the data compression approach relies on variations in strain energy harvested by smart sensors to track changes in material and structural conditions. Falling weight deflectometer (FWD) measurements and visual inspections were used to validate the observations from the sensing system. The results in this paper present a first large-scale validation in pavement structures for a piezopowered sensing system combined with a new response-only based approach for data reduction and interpretation. The proposed data analysis method has demonstrated a very early detection capability compared to classical inspection methods, which unveils a huge potential for improved pavement monitoring

Influence of the structural modulations and the Chain-ladder interaction in the Sr_14−xCa_xCu_24O_41Sr\_{14-x}Ca\_{x}Cu\_{24}O\_{41} compounds

We studied the effects of the incommensurate structural modulations on the ladder subsystem of the $Sr\_{14-x}Ca\_{x}Cu\_{24}O\_{41}$ family of compounds using ab-initio explicitly-correlated calculations. From these calculations we derived $t-J$ model as a function of the fourth crystallographic coordinate $\tau$ describing the incommensurate modulations. It was found that in the highly calcium-doped system, the on-site orbital energies are strongly modulated along the ladder legs. On the contrary the two sites of the ladder rungs are iso-energetic and the holes are thus expected to be delocalized on the rungs. Chain-ladder interactions were also evaluated and found to be very negligible. The ladder superconductivity model for these systems is discussed in the light of the present results.Comment: 8 octobre 200

Metal ion-dependent, reversible, protein filament formation by designed beta-roll polypeptides

<p>Abstract</p> <p>Background</p> <p>A right-handed, calcium-dependent β-roll structure found in secreted proteases and repeat-in-toxin proteins was used as a template for the design of minimal, soluble, monomeric polypeptides that would fold in the presence of Ca²⁺. Two polypeptides were synthesised to contain two and four metal-binding sites, respectively, and exploit stacked tryptophan pairs to stabilise the fold and report on the conformational state of the polypeptide.</p> <p>Results</p> <p>Initial analysis of the two polypeptides in the presence of calcium suggested the polypeptides were disordered. The addition of lanthanum to these peptides caused aggregation. Upon further study by right angle light scattering and electron microscopy, the aggregates were identified as ordered protein filaments that required lanthanum to polymerize. These filaments could be disassembled by the addition of a chelating agent. A simple head-to-tail model is proposed for filament formation that explains the metal ion-dependency. The model is supported by the capping of one of the polypeptides with biotin, which disrupts filament formation and provides the ability to control the average length of the filaments.</p> <p>Conclusion</p> <p>Metal ion-dependent, reversible protein filament formation is demonstrated for two designed polypeptides. The polypeptides form filaments that are approximately 3 nm in diameter and several hundred nm in length. They are not amyloid-like in nature as demonstrated by their behaviour in the presence of congo red and thioflavin T. A capping strategy allows for the control of filament length and for potential applications including the "decoration" of a protein filament with various functional moieties.</p

An effective all-atom potential for proteins

We describe and test an implicit solvent all-atom potential for simulations of protein folding and aggregation. The potential is developed through studies of structural and thermodynamic properties of 17 peptides with diverse secondary structure. Results obtained using the final form of the potential are presented for all these peptides. The same model, with unchanged parameters, is furthermore applied to a heterodimeric coiled-coil system, a mixed alpha/beta protein and a three-helix-bundle protein, with very good results. The computational efficiency of the potential makes it possible to investigate the free-energy landscape of these 49--67-residue systems with high statistical accuracy, using only modest computational resources by today's standards

Interatomic potentials and solvation parameters from protein engineering data for buried residues

Van der Waals (vdW) interaction energies between different atom types, energies of hydrogen bonds (H‐bonds), and atomic solvation parameters (ASPs) have been derived from the published thermodynamic stabilities of 106 mutants with available crystal structures by use of an originally designed model for the calculation of free‐energy differences. The set of mutants included substitutions of uncharged, inflexible, water‐inaccessible residues in α‐helices and β‐sheets of T4, human, and hen lysozymes and HI ribonuclease. The determined energies of vdW interactions and H‐bonds were smaller than in molecular mechanics and followed the “like dissolves like” rule, as expected in condensed media but not in vacuum. The depths of modified Lennard‐Jones potentials were −0.34, −0.12, and −0.06 kcal/mole for similar atom types (polar–polar, aromatic–aromatic, and aliphatic–aliphatic interactions, respectively) and −0.10, −0.08, −0.06, −0.02, and nearly 0 kcal/mole for different types (sulfur–polar, sulfur–aromatic, sulfur–aliphatic, aliphatic–aromatic, and carbon–polar, respectively), whereas the depths of H‐bond potentials were −1.5 to −1.8 kcal/mole. The obtained solvation parameters, that is, transfer energies from water to the protein interior, were 19, 7, −1, −21, and −66 cal/moleÅ 2 for aliphatic carbon, aromatic carbon, sulfur, nitrogen, and oxygen, respectively, which is close to the cyclohexane scale for aliphatic and aromatic groups but intermediate between octanol and cyclohexane for others. An analysis of additional replacements at the water–protein interface indicates that vdW interactions between protein atoms are reduced when they occur across water.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106915/1/111984_ftp.pd

Deciphering the Preference and Predicting the Viability of Circular Permutations in Proteins

Circular permutation (CP) refers to situations in which the termini of a protein are relocated to other positions in the structure. CP occurs naturally and has been artificially created to study protein function, stability and folding. Recently CP is increasingly applied to engineer enzyme structure and function, and to create bifunctional fusion proteins unachievable by tandem fusion. CP is a complicated and expensive technique. An intrinsic difficulty in its application lies in the fact that not every position in a protein is amenable for creating a viable permutant. To examine the preferences of CP and develop CP viability prediction methods, we carried out comprehensive analyses of the sequence, structural, and dynamical properties of known CP sites using a variety of statistics and simulation methods, such as the bootstrap aggregating, permutation test and molecular dynamics simulations. CP particularly favors Gly, Pro, Asp and Asn. Positions preferred by CP lie within coils, loops, turns, and at residues that are exposed to solvent, weakly hydrogen-bonded, environmentally unpacked, or flexible. Disfavored positions include Cys, bulky hydrophobic residues, and residues located within helices or near the protein's core. These results fostered the development of an effective viable CP site prediction system, which combined four machine learning methods, e.g., artificial neural networks, the support vector machine, a random forest, and a hierarchical feature integration procedure developed in this work. As assessed by using the hydrofolate reductase dataset as the independent evaluation dataset, this prediction system achieved an AUC of 0.9. Large-scale predictions have been performed for nine thousand representative protein structures; several new potential applications of CP were thus identified. Many unreported preferences of CP are revealed in this study. The developed system is the best CP viability prediction method currently available. This work will facilitate the application of CP in research and biotechnology