The role of the scale and the frequency bandwidth of steering wheel vibration on road surface recognition

Automobile drivers are regularly exposed to vibrational stimuli in their vehicle. Of the automobile subsystems, the steering wheel is one of the most important due to its role in controlling the vehicle. In particular, the steering wheel plays an important role in transmitting information about the road and about the vehicle to the driver. This paper investigates the effect of steering system feedback gain and steering system feedback bandwidth on the human interpretation of the driving information transmitted by the steering wheel. Human recognition of road surface type was found to be highly dependent on the feedback gain and the feedback bandwidth of the steering wheel vibration. The results provide some basic guidelines for designing the control logic of steer by wire systems

Protein surface recognition with targeted fluorescent molecular probes

Protein surface recognition by fluorescent molecular sensors poses an immense challenge in supramolecular recognition chemistry owing to the immense difficulty of selectively targeting these large, relatively flat and non-contiguous domains. The fact that protein surfaces can exhibit different charges, topologies, and posttranslational modifications that can be found in other proteins in the mixture is an additional factor that complicates targeting and therefore, sensing specific protein surface modifications. A recent report, however, shows that the difficulty of sensing changes that occur on the surface of specific proteins could be circumvented by attaching a relatively non-specific synthetic receptor to a specific protein binder. The latter brings the receptor near the target protein and enhances its affinity toward its surface. Modifying the synthetic receptor with an environmentally sensitive fluorescent reporter along with suitable recognition elements enables such systems to target specific regions on protein surfaces and consequently, track modifications that result from conformational changes or binding interactions

Stereocontrolled protein surface recognition using chiral oligoamide proteomimetic foldamers

The development of foldamers capable of selective molecular recognition of solvent exposed protein surfaces represents an outstanding challenge in supramolecular chemical biology. Here we introduce an oligoamide foldamer with well-defined conformation that bears all the hallmarks of an information rich oligomer. Specifically, the foldamer recognizes its target protein hDM2 leading to inhibition of its protein–protein interaction with p53 in a manner that depends upon the composition, spatial projection and stereochemistry of functional groups appended to the scaffold. Most significantly, selective inhibition of p53/hDM2 can be achieved against four other targets and the selectivity for p53/hDM2 inhibition versus Mcl-1/NOXA-B inhibition is critically dependent upon the stereochemistry of the helix mimetic

Molecular investigation of polypyrrole and surface recognition by affinity peptides

textSuccessful tissue engineering strategies in the nervous system must be carefully crafted to interact favorably with the complex biochemical signals of the native environment. To date, all chronic implants incorporating electrical conductivity degrade in performance over time as the foreign body reaction and subsequent fibrous encapsulation isolate them from the host tissue. Our goal is to develop a peptide-based interfacial biomaterial that will non-covalently coat the surface of the conducting polymer polypyrrole, allowing the implant to interact with the nervous system through both electrical and chemical cues. Starting with a candidate peptide sequence discovered through phage display, we used computational simulations of the peptide on polypyrrole to describe the bound peptide structure, explore the mechanism of binding, and suggest new, better binding peptide sequences. After experimentally characterizing the polymer, we created a molecular mechanics model of polypyrrole using quantum mechanics calculations and compared its in silico properties to experimental observables such as density and chain packing. Using replica exchange molecular dynamics, we then modeled the behavior of affinity binding peptides on the surface of polypyrrole in explicit water and saline environments. Relative measurements of the contributions of each amino acid were made using distance measurements and computational alanine scanning.Biomedical Engineerin

Road Surface Recognition at mm-Wavelengths Using a Polarimetric Radar

We demonstrate detection of ice formations on a road surface using a polarimetric radar operating at 87.5-92.5 GHz. The radar measures the scattering parameters of the surface at horizontal and vertical polarizations and their cross-polarization components. We demonstrate detection of ice for radar beam directed at up to 45⁰ angle of incidence with respect to the surface which allows for road surface characterization in front of a vehicle. The method used is based on a statistical approach where the 2-port scattering parameters are measured multiple times and used to calculate an average scatter coherence matrix representing the surface. The coherence matrix is then decomposed to eigenvalues/vectors, which are used to estimate polarimetric attributes such as target entropy(degree of randomness) and polarimetric pedestal (degree of depolarization). Through measurements of dry, ice-covered and wet road surfaces, we show that both entropy and depolarization are increased with respect to dry surface when a thin ice layer is formed, while their value decrease for the case of wet surface. It is also shown that these polarimetric attributes are not sensitive to surface roughness in dry conditions, minimizing the probability of false alarm due to road surface wear

Fusion of geometric and texture features for finger knuckle surface recognition

AbstractHand-based biometrics plays a significant role in establishing security for real-time environments involving human interaction and is found to be more successful in terms of high speed and accuracy. This paper investigates on an integrated approach for personal authentication using Finger Back Knuckle Surface (FBKS) based on two methodologies viz., Angular Geometric Analysis based Feature Extraction Method (AGFEM) and Contourlet Transform based Feature Extraction Method (CTFEM). Based on these methods, this personal authentication system simultaneously extracts shape oriented feature information and textural pattern information of FBKS for authenticating an individual. Furthermore, the proposed geometric and textural analysis methods extract feature information from both proximal phalanx and distal phalanx knuckle regions (FBKS), while the existing works of the literature concentrate only on the features of proximal phalanx knuckle region. The finger joint region found nearer to the tip of the finger is called distal phalanx region of FBKS, which is a unique feature and has greater potentiality toward identification. Extensive experiments conducted using newly created database with 5400 FBKS images and the obtained results infer that the integration of shape oriented features with texture feature information yields excellent accuracy rate of 99.12% with lowest equal error rate of 1.04%

Neural networks based recognition of 3D freeform surface from 2D sketch

In this paper, the Back Propagation (BP) network and Radial Basis Function (RBF) neural network are employed to recognize and reconstruct 3D freeform surface from 2D freehand sketch. Some tests and comparison experiments have been made to evaluate the performance for the reconstruction of freeform surfaces of both networks using simulation data. The experimental results show that both BP and RBF based freeform surface reconstruction methods are feasible; and the RBF network performed better. The RBF average point error between the reconstructed 3D surface data and the desired 3D surface data is less than 0.05 over all our 75 test sample data

Genome-scale identification of cellular pathways required for cell surface recognition.

Interactions mediated by cell surface receptors initiate important instructive signaling cues but can be difficult to detect in biochemical assays because they are often highly transient and membrane-embedded receptors are difficult to solubilize in their native conformation. Here, we address these biochemical challenges by using a genome-scale, cell-based genetic screening approach using CRISPR gene knockout technology to identify cellular pathways required for specific cell surface recognition events. By using high-affinity monoclonal antibodies and low-affinity ligands, we determined the necessary screening parameters, including the importance of establishing binding contributions from the glycocalyx, that permitted the unequivocal identification of genes encoding directly interacting membrane-embedded receptors with high statistical confidence. Importantly, we show that this genome-wide screening approach additionally identified receptor-specific pathways that are required for functional display of receptors on the cell surface that included chaperones, enzymes that add post-translational modifications, trafficking proteins, and transcription factors. Finally, we demonstrate the utility of the approach by identifying IGF2R (insulin like growth factor 2 receptor) as a binding partner for the R2 subunit of GABAB receptors. We show that this interaction is direct and is critically dependent on mannose-6-phosphate, providing a mechanism for the internalization and regulation of GABAB receptor signaling. We conclude that this single approach can reveal both the molecular nature and the genetic pathways required for functional cell surface display of receptors recognized by antibodies, secreted proteins, and membrane-embedded ligands without the need to make any prior assumptions regarding their biochemical properties. © 2018 Sharma et al.; Published by Cold Spring Harbor Laboratory Press