Superconductivity up to 30 K in the vicinity of quantum critical point in BaFe2_{2}(As1−x_{1-x}Px_{x})2_{2}

We report bulk superconductivity induced by an isovalent doping of phosphorus in BaFe$_{2}$(As$_{1-x}$P$_{x}$)$_{2}$. The P-for-As substitution results in shrinkage of lattice, especially for the FeAs block layers. The resistivity anomaly associated with the spin-density-wave (SDW) transition in the undoped compound is gradually suppressed by the P doping. Superconductivity with the maximum $T_c$ of 30 K emerges at $x$=0.32, coinciding with a magnetic quantum critical point (QCP) which is evidenced by the disappearance of SDW order and the linear temperature-dependent resistivity in the normal state. The $T_c$ values were found to decrease with further P doping, and no superconductivity was observed down to 2 K for $x\geq$ 0.77. The appearance of superconductivity in the vicinity of QCP hints to the superconductivity mechanism in iron-based arsenides.Comment: 9 pages, 4 figures; more data; to appear in Journal of Physics: Condensed Matte

Numerical and Small-scale Physical Modelling of Wave Transmission by Wooden Fences

Mangrove forests, that often act as natural coastal defences, enormously suffered due to ongoing climate change and human disturbances. Thus, it is necessary to have a countermeasure to mitigate the loss of mangroves. Wooden fences are becoming a viable nature-based solution to protect vulnerable replanted mangrove forests. However, the wooden fence's hydraulic characteristics are not yet fully understood due to the complication of branches arrangement. In the present study, a small-scale wave flume modelling of wave damping by a wooden fence was constructed using the inner branches as an inhomogeneous arrangement tested in earlier flow-resistance experiments. The physical model results indicate that the wooden fence is highly effective on wave transmission and that the effectiveness in wave reduction depends on the relative fence thickness, B/Hi. To understand the scale effect on wave transmission further, the numerical model SWASH was used with the laboratory wave data. By applying the prior experiments' drag coefficient on steady flow, the uncalibrated numerical model gave a good agreement with the wave model results, with a root-mean-square error for the total transmitted wave heights of 4.7%. After validation, potential scale effects for small scale tests were determined from scaling simulations at both full scales and the applied 1:5 model scale. These simulations were performed for a fence porosity of 0.81, and different fence thicknesses to understand scale effects between model- and full-scale. Both wave reflection and transmission at model-scale are about 5% higher than full-scale results due to the increased drag coefficient and viscous effects. The effects of fence thickness and porosity were the same in large and small scale, and much larger than the error due to scale effects. Hence testing fence efficiency at physical small scale is regarded as a useful tool, together with numerical modelling.Coastal EngineeringHydraulic Structures and Flood Ris

Coarse grained description of the protein folding

We consider two- and three-dimensional lattice models of proteins which were characterized previously. We coarse grain their folding dynamics by reducing it to transitions between effective states. We consider two methods of selection of the effective states. The first method is based on the steepest descent mapping of states to underlying local energy minima and the other involves an additional projection to maximally compact conformations. Both methods generate connectivity patterns that allow to distinguish between the good and bad folders. Connectivity graphs corresponding to the folding funnel have few loops and are thus tree-like. The Arrhenius law for the median folding time of a 16-monomer sequence is established and the corresponding barrier is related to easily identifiable kinetic trap states.Comment: REVTeX, 9 pages, 15 EPS figures, to appear in Phys. Rev.

Energy landscapes, supergraphs, and "folding funnels" in spin systems

Dynamical connectivity graphs, which describe dynamical transition rates between local energy minima of a system, can be displayed against the background of a disconnectivity graph which represents the energy landscape of the system. The resulting supergraph describes both dynamics and statics of the system in a unified coarse-grained sense. We give examples of the supergraphs for several two dimensional spin and protein-related systems. We demonstrate that disordered ferromagnets have supergraphs akin to those of model proteins whereas spin glasses behave like random sequences of aminoacids which fold badly.Comment: REVTeX, 9 pages, two-column, 13 EPS figures include

Effect of the N-based ligands in copper complexes for depolymerisation of lignin

Several organic soluble N-based ligands and their copper complexes were firstly investigated as catalysts to depolymerise organosolv lignin in the organic solvent, dimethylformamide (DMF) and an ionic liquid (1-ethyl-3-methylimidazolium xylenesulfonate, [emim][ABS]). The results of screening depolymerisation reactions in DMF and [emim][ABS] showed that all the copper–amine complexes catalysed lignin depolymerisation more efficiently in ionic liquids than in DMF. Among the seven types of ligands, copper complexes with two types of ligands (E)-N-(pyridin-2-ylmethylene)aniline and (E)-4-methoxy-N-(pyridin-2-ylmethylene)aniline depolymerised the lignin more efficiently than the others. These two copper complexes with the N-based ligand were further studied to determine the most efficient conditions for the depolymerisation of the lignin. The most effective depolymerisation by conditions involved treatment at 180 °C for 12 h in [emim][ABS]. Cyclic voltammetric studies were carried out to investigate the reversible potential associated with the copper centers of their complexes with these N-based ligands. The results suggest that two types of ligands have more positive reversible potentials than those of other copper complexes

One-stage deep instrumental variable method for causal inference from observational data

© 2019 IEEE. Causal inference from observational data aims to estimate causal effects when controlled experimentation is not feasible, but it faces challenges when unobserved confounders exist. The instrumental variable method resolves this problem by introducing a variable that is correlated with the treatment and affects the outcome only through the treatment. However, existing instrumental variable methods require two stages to separately estimate the conditional treatment distribution and the outcome generating function, which is not sufficiently effective. This paper presents a one-stage approach to jointly estimate the treatment distribution and the outcome generating function through a cleverly designed deep neural network structure. This study is the first to merge the two stages to leverage the outcome to the treatment distribution estimation. Further, the new deep neural network architecture is designed with two strategies (i.e., shared and separate) of learning a confounder representation account for different observational data. Such network architecture can unveil complex relationships between confounders, treatments, and outcomes. Experimental results show that our proposed method outperforms the state-of-the-art methods. It has a wide range of applications, from medical treatment design to policy making, population regulation and beyond

Evaluation of methods for oligonucleotide array data via quantitative real-time PCR

BACKGROUND: There are currently many different methods for processing and summarizing probe-level data from Affymetrix oligonucleotide arrays. It is of great interest to validate these methods and identify those that are most effective. There is no single best way to do this validation, and a variety of approaches is needed. Moreover, gene expression data are collected to answer a variety of scientific questions, and the same method may not be best for all questions. Only a handful of validation studies have been done so far, most of which rely on spike-in datasets and focus on the question of detecting differential expression. Here we seek methods that excel at estimating relative expression. We evaluate methods by identifying those that give the strongest linear association between expression measurements by array and the "gold-standard" assay. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) is generally considered the "gold-standard" assay for measuring gene expression by biologists and is often used to confirm findings from microarray data. Here we use qRT-PCR measurements to validate methods for the components of processing oligo array data: background adjustment, normalization, mismatch adjustment, and probeset summary. An advantage of our approach over spike-in studies is that methods are validated on a real dataset that was collected to address a scientific question. RESULTS: We initially identify three of six popular methods that consistently produced the best agreement between oligo array and RT-PCR data for medium- and high-intensity genes. The three methods are generally known as MAS5, gcRMA, and the dChip mismatch mode. For medium- and high-intensity genes, we identified use of data from mismatch probes (as in MAS5 and dChip mismatch) and a sequence-based method of background adjustment (as in gcRMA) as the most important factors in methods' performances. However, we found poor reliability for methods using mismatch probes for low-intensity genes, which is in agreement with previous studies. CONCLUSION: We advocate use of sequence-based background adjustment in lieu of mismatch adjustment to achieve the best results across the intensity spectrum. No method of normalization or probeset summary showed any consistent advantages

Molecular weight dependent structure and charge transport in MAPLE‐deposited poly(3‐hexylthiophene) thin films

In this work, poly(3‐hexylthiophene) (P3HT) films prepared using the matrix‐assisted pulsed laser evaporation (MAPLE) technique are shown to possess morphological structures that are dependent on molecular weight (MW). Specifically, the structures of low MW samples of MAPLE‐deposited film are composed of crystallites/aggregates embedded within highly disordered environments, whereas those of high MW samples are composed of aggregated domains connected by long polymer chains. Additionally, the crystallite size along the side‐chain (100) direction decreases, whereas the conjugation length increases with increasing molecular weight. This is qualitatively similar to the structure of spin‐cast films, though the MAPLE‐deposited films are more disordered. In‐plane carrier mobilities in the MAPLE‐deposited samples increase with MW, consistent with the notion that longer chains bridge adjacent aggregated domains thereby facilitating more effective charge transport. The carrier mobilities in the MAPLE‐deposited simples are consistently lower than those in the solvent‐cast samples for all molecular weights, consistent with the shorter conjugation length in samples prepared by this deposition technique. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2018, 56, 652–662The structure of MAPLE‐deposited P3HT thin films is shown to possess molecular weight (MW) dependence behavior. The MAPLE films deposited from low MW materials consist of crystallite domains embedded within a highly amorphous environment, whereas those deposited from high MW materials are composed of long polymer chains bridging the aggregate domains. The in‐plane mobility is shown to increase with MW, highlighting the importance of domain connectivity in facilitating charge transport in conjugated polymers.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142537/1/polb24588-sup-0001-suppinfo1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142537/2/polb24588_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142537/3/polb24588.pd

Structurally-informed Mutagenesis of a Stereochemically Promiscuous Aldolase Produces Mutants that Catalyse the Diastereoselective Syntheses of all Four Stereoisomers of 3-Deoxy-Hexulosonic acid

[Image: see text] A 2-keto-3-deoxygluconate aldolase from the hyperthermophile Sulfolobus solfataricus catalyzes the nonstereoselective aldol reaction of pyruvate and d-glyceraldehyde to produce 2-keto-3-deoxygluconate (d-KDGlc) and 2-keto-3-deoxy-d-galactonate (d-KDGal). Previous investigations into curing the stereochemical promiscuity of this hyperstable aldolase used high-resolution structures of the aldolase bound to d-KDGlc or d-KDGal to identify critical amino acids involved in substrate binding for mutation. This structure-guided approach enabled mutant variants to be created that could stereoselectively catalyze the aldol reaction of pyruvate and natural d-glyceraldehyde to selectively afford d-KDGlc or d-KDGal. Here we describe the creation of two further mutants of this Sulfolobus aldolase that can be used to catalyze aldol reactions between pyruvate and non-natural l-glyceraldehyde to enable the diastereoselective synthesis of l-KDGlc and l-KDGal. High-resolution crystal structures of all four variant aldolases have been determined (both unliganded and liganded), including Variant 1 with d-KDGlc, Variant 2 with pyruvate, Variant 3 with l-KDGlc, and Variant 4 with l-KDGal. These structures have enabled us to rationalize the observed changes in diastereoselectivities in these variant-catalyzed aldol reactions at a molecular level. Interestingly, the active site of Variant 4 was found to be sufficiently flexible to enable catalytically important amino acids to be replaced while still retaining sufficient enzymic activity to enable production of l-KDGal