Rapid crack growth in a thermoelastic solid under mixed-mode thermomechanical loading

A two-dimensional steady-sate analysis of semi-infinite brittlecrack growth at a constant subcritical rate in an unboundedfully-coupled thermoelastic solid under mixed-mode thermomechanicalloading is made. The loading consists of normal and shear tractionsand heat fluxes applied as point sources (line loads in theout-of-plane direction). A related problem is solved exactly in an integral transformspace, and robust asymptotic forms used to reduce the originalproblem to a set of integral equations. The equations are partiallycoupled and exhibit operators of both Cauchy and Abel types,yet can be solved analytically. The temperature change field at a distance from the moving crackedge is then constructed, and its dominant term is found tobe controlled by the imposed heat fluxes. The role of this termis, indeed, enhanced if the heat fluxes serve to render thecrack as a net heat source/sink for the solid, as opposed tobeing a transmitter of heat across its plane. More generally,the influence of the thermoelastic coupling on this field, aswell as other functions, is found to increase with crack speed.     

Synthetic magnetic opals

We present studies of novel nanocomposites of BiNi impregnated into the structure of opals as well as inverse opals. Atomic force microscopy and high resolution elemental analyses show a highly ordered structure and uniform distribution of the BiNi filler in the matrix. These BiNi-based nanocomposites are found to exhibit distinct ferromagnetic-like ordering with transition temperature of about 675 K. As far as we know there exists no report in literature on any BiNi compound which is magnetic.     

Thermomechanical enhancement of DPP-4T through purposeful π-conjugation disruption

The design of polymer-based organic semiconductors that offer mechanical deformability while maintaining efficient semiconducting characteristics remains a significant challenge. Recent synthetic efforts have incorporated small alkyl segments directly into otherwise π-conjugated polymer backbones to enhance processability, mechanical deformability, and other properties. The resulting polymers can be used as stand-alone materials or as matrix polymers in complementary semiconducting polymer blends offering reasonable charge-carrier transport properties, thermal healing, and deformability. Here, a family of diketopyrrolopyrrole-tetrathiophene variants is explored via large-scale atomistic molecular dynamics simulations to examine the effect of alkyl segments incorporated into the polymer backbone on the polymer structure, dynamics, and thermal properties. Longer alkyl segments lead to polymer chains that are more flexible, compact, and mobile, with lower glass transition temperatures for the condensed phase.     

Molecular recognition of insulin by a synthetic receptor

The discovery of molecules that bind tightly and selectively to desired proteins continues to drive innovation at the interface of chemistry and biology. This paper describes the binding of human insulin by the synthetic receptor cucurbit[7]uril (Q7) in vitro. Isothermal titration calorimetry and fluorescence spectroscopy experiments show that Q7 binds to insulin with an equilibrium association constant of 1.5 × 10(6) M(-1) and with 50-100-fold selectivity versus proteins that are much larger but lack an N-terminal aromatic residue, and with >1000-fold selectivity versus an insulin variant lacking the N-terminal phenylalanine (Phe) residue. The crystal structure of the Q7·insulin complex shows that binding occurs at the N-terminal Phe residue and that the N-terminus unfolds to enable binding. These findings suggest that site-selective recognition is based on the properties inherent to a protein terminus, including the unique chemical epitope presented by the terminal residue and the greater freedom of the terminus to unfold, like the end of a ball of string, to accommodate binding. Insulin recognition was predicted accurately from studies on short peptides and exemplifies an approach to protein recognition by targeting the terminus.     

Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory

Background  

Although a large body of knowledge about both brain structure and function has been gathered over the last decades, we still have a poor understanding of their exact relationship. Graph theory provides a method to study the relation between network structure and function, and its application to neuroscientific data is an emerging research field. We investigated topological changes in large-scale functional brain networks in patients with Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) by means of graph theoretical analysis of resting-state EEG recordings. EEGs of 20 patients with mild to moderate AD, 15 FTLD patients, and 23 non-demented individuals were recorded in an eyes-closed resting-state. The synchronization likelihood (SL), a measure of functional connectivity, was calculated for each sensor pair in 0.5–4 Hz, 4–8 Hz, 8–10 Hz, 10–13 Hz, 13–30 Hz and 30–45 Hz frequency bands. The resulting connectivity matrices were converted to unweighted graphs, whose structure was characterized with several measures: mean clustering coefficient (local connectivity), characteristic path length (global connectivity) and degree correlation (network 'assortativity'). All results were normalized for network size and compared with random control networks.