How Force Might Activate Talin's Vinculin Binding Sites: SMD Reveals a Structural Mechanism

Upon cell adhesion, talin physically couples the cytoskeleton via integrins to the extracellular matrix, and subsequent vinculin recruitment is enhanced by locally applied tensile force. Since the vinculin binding (VB) sites are buried in the talin rod under equilibrium conditions, the structural mechanism of how vinculin binding to talin is force-activated remains unknown. Taken together with experimental data, a biphasic vinculin binding model, as derived from steered molecular dynamics, provides high resolution structural insights how tensile mechanical force applied to the talin rod fragment (residues 486–889 constituting helices H1–H12) might activate the VB sites. Fragmentation of the rod into three helix subbundles is prerequisite to the sequential exposure of VB helices to water. Finally, unfolding of a VB helix into a completely stretched polypeptide might inhibit further binding of vinculin. The first events in fracturing the H1–H12 rods of talin1 and talin2 in subbundles are similar. The proposed force-activated α-helix swapping mechanism by which vinculin binding sites in talin rods are exposed works distinctly different from that of other force-activated bonds, including catch bonds

Optimization of 4D Process Planning using Genetic Algorithms

The presented work focuses on the presentation of a discrete event simulator which can be used for automated sequencing and optimization of building processes. The sequencing is based on the commonly used component–activity–resource relations taking structural and process constraints into account. For the optimization a genetic algorithm approach was developed, implemented and successfully applied to several real life steel constructions. In this contribution we discuss the application of the discrete event simulator including its optimization capabilities on a 4D process model of a steel structure of an automobile recycling facility

A Learning Rate Method for Full-Batch Gradient Descent

In this paper, we present a learning rate method for gradient descent using only first order information. This method requires no manual tuning of the learning rate. We applied this method on a linear neural network built from scratch, along with the full-batch gradient descent, where we calculated the gradients for the whole dataset to perform one parameter update. We tested the method on a moderate sized dataset of housing information and compared the result with that of the Adam optimizer used with a sequential neural network model from Keras. The comparison shows that our method finds the minimum in a much fewer number of epochs than does Adam

The role of retrospectively perceived parenting style and adult attachment behaviour in music performance anxiety

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Sensors on Textile Fibres Based on Ag/a-C:H:O Nanocomposite Coatings

In this contribution we present a study of the vacuum deposition process of metal/plasma polymer nanocomposite thin films monitored using plasma diagnostics (optical emission spectroscopy). We investigate the electrical properties of the nanocomposite structures suitable for their application as humidity sensors. Furthermore, the film microstructure is characterized by transmission electron microscopy and electron diffraction analysis. The amount of silver in the nanocomposite is evaluated using inductively coupled plasma optical emission spectrometry and the morphology of the structured system of metal electrodes and nanocomposite films on monofilament textile fibres is visualized using scanning electron microscopy. Ageing of nanocomposite coatings and the influence of an aqueous environment on their internal structure and properties are discussed

An Efficient, Movable Single-Particle Detector for Use in Cryogenic Ultra-High Vacuum Environments

A compact, highly efficient single-particle counting detector for ions of keV/u kinetic energy, movable by a long-stroke mechanical translation stage, has been developed at the Max-Planck-Institut f\"ur Kernphysik (Max Planck Institute for Nuclear Physics, MPIK). Both, detector and translation mechanics, can operate at ambient temperatures down to $\sim$ 10 K and consist fully of ultra-high vacuum (UHV) compatible, high-temperature bakeable and non-magnetic materials. The set-up is designed to meet the technical demands of MPIK's Cryogenic Storage Ring (CSR). We present a series of functional tests that demonstrate full suitability for this application and characterise the set-up with regard to its particle detection efficiency.Comment: 12 pages, 9 figures, version accepted for publication in Review of Scientific Instrument

Tanulási ráta módszer full-batch gradiens tanulásra

Cikkünkben egy olyan tanulásiráta-módszert mutatunk be gradienstanulásra, amely kizárólag elsőrendű információkat használ fel. Ezen módszer esetében nem szükséges a tanulási ráta manuális beállítása. Az algoritmust alkalmaztuk egy nulláról felépített lineáris neurális hálóra full-batch gradiens-módszer esetén, mikor a gradienst a teljes adathalmazra kiszámoljuk egy paraméter-aktualizálási lépésben. A módszert egy közepes méretű, szállásinformációkkal kapcsolatos adathalmazon teszteltük, a kapott eredményeket pedig összevetettük a Keras-beli Adam algoritmus által szolgáltatottakkal egy szekvenciális neurális háló esetén. Az eredmények azt mutatják, hogy az Adam algoritmushoz képest a mi módszerünk sokkal kevesebb epoch alatt megtalálja a minimumot