Poly(oxyphosphazenes): A unifying look at structure and morphology

Variations in thermotropic behavior have been investigated for many crystalline polyphosphazenes. Experimental results obtained from DSC, solid-state MAS NMR, dilatometry, mechanical property (creep and dynamic) measurements, birefringence, X-ray (wide and small-angle), and electron diffraction have been made as a function of temperature in an attempt to elucidate the structure-morphology behavior in these polymers. Initially all polyphosphazenes described in this study crystallize from dilute or moderately concentrated solutions in the monoclinic form with relatively low crystallinity (50%). When heated, these specimens expand atT(1) and adopt a chain-extended 2D mesophase morphology in order to relieve congestion. Above this first-orderT(1) temperature a chain-extended –P=N– chain backbone morphology transforms into an isotropic phase at the melting temperatureT _m. When cooled, samples transform into the mesostate. However, crystallization from the mesophase belowT(1) takes place into a 3D orthorhombic state. These two modes of ordering/disordering are in accordance with (i) a hexatic chain packing [betweenT(1) andT _m] with variously mobile side groups that also exhibits smectic features when mesogenic side groups are present and (ii) a 3D orthorhombic structure of high crystallinity belowT(1). The initial monoclinic phase is accessible only via a solution crystallization route. Solid-state MAS NMR, crystallization kinetic measurements, and optical microscopy studies obtained from oriented and unoriented polymers have been especially germane in providing a unifying picture for mesophase formation and ordering in polyoxyphosphazenes. X-ray and electron diffraction evidence is complicated by critical overlapping peaks that are found under these same conditions. They demonstrate that (a) positional disorder exists along the chain direction and (b) the side chain above, as well as below, theT(1) transition is governed by the mobility, size, and type of side group in circumstances where phase transformations occur.     

Steric stabilization of Stöber silica dispersions using organosilanes

Organosilanes of the general formula R _x Si(OR)_4–x (where R is an alkyl group and R = CH₃ or CH₂CH₃) were used to sterically stabilize hexane dispersions of submicrometre silica spheres. The dispersions were characterized according to sediment volume results. For 0.5m silica particles, the sediment density increased by more than a factor of three up to 50 to 55% of theoretical in the presence of organosilanes with 12 or more carbons in the R group. Solid-state¹³C nuclear magnetic resonance was used to characterize the powder-dispersant interaction; this technique can distinguish between carbons in the R group of the organosilane and residual organic groups in the silica. Scanning electron micrographs of filter compacts were used to further characterize the dispersions and indicated the presence of primary particles as well as small agglomerates.     

Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters

RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as biomarkers. This study used machine learning to reduce gene/non-coding RNA features. Dorsolateral prefrontal cortex (dlpfc) RNA-seq data from 254 individuals was obtained from the CommonMind consortium. The average predictive accuracy for SCZ patients was 67% based on coding genes, and 96% based on long non-coding RNAs (lncRNAs). Machine learning is a powerful algorithm to reduce functional biomarkers in SCZ patients. The lncRNAs capture the characteristics of SCZ tissue more accurately than mRNA as the former regulate every level of gene expression, not limited to mRNA levels.     

Investigation of the Anti-Methicillin-Resistant Staphylococcus aureus Activity of (+)-Tanikolide- and (+)-Malyngolide-Based Analogues Prepared by Asymmetric Synthesis

Herein, we report antibacterial and antifungal evaluation of a series of previously prepared (+)-tanikolide analogues. One analogue, (4S,6S)-4-methyltanikolide, displayed promising anti-methicillin-resistant Staphylococcus aureus activity with a MIC of 12.5 µg/mL. Based on the antimicrobial properties of the structurally related (−)-malyngolide, two further analogues (4S,6S)-4-methylmalyngolide and (4R,6S)-4-methylmalyngolide bearing a shortened n-nonyl alkyl side chain were prepared in the present study using a ZrCl₄-catalysed deprotection/cyclisation as the key step in their asymmetric synthesis. When these were tested for activity against anti-methicillin-resistant Staphylococcus aureus, the MIC increased to 50 µg/mL.     

Recent Advances in Boron Nitride Based Hybrid Polymer Nanocomposites

Boron nitride (BN) is an eminent inorganic compound having many interesting characteristics such as improved oxidation resistance, mechanical strength, good thermal conductivity (TC), higher bandgap, high chemical stability, thermal stability, high hydrophobicity, and electrical insulation. The use of BN as a filler in polymers is a well-established strategy to tailor the properties of polymer composites. Recent studies depict an interesting urge to reap the synergistic effect of various nanofillers with BN in the form of hybrids. Hence the consolidation of the works on BN based hybrid fillers would definitely attract researchers so that these new filler systems could be transformed into useful polymer nanocomposites in future. This review article focuses on the synthesis and characterization of various boron nitride based hybrids in detail. Moreover, the review also throws light on different BN hybrid reinforced polymer nanocomposites (PNCs) and their thermal, electrical, electronic as well as biomedical applications in a detailed manner. Thus the review anticipates serving as a tool toward understanding the recent trends in the field of boron nitride hybrid based ternary polymer composites.     

Structure development in biaxially stretched polystyrene film: Part II. Theoretical analysis of orientation development

The present paper describes an analysis of the orientation developed in biaxially stretched polystyrene films in terms of the kinematics of the process and a viscoelastic constitutive equation. It was possible to achieve reasonable agreement of predicted and experimental birefringences through use of a convected Maxwell model and the Rheo-Optical Law.     

Objective classification of vehicle seat discomfort

The objective of this study was to identify how physiological measures relate to self-reported vehicle seating discomfort. Twelve subjects of varied anthropometric characteristics were enrolled in the study. Subjects sat in two seats over a 2-h period and were evaluated via three physiological measures (near-infrared spectroscopy, electromyography and pressure mapping) yielding six testing sessions. Subjective discomfort surveys were recorded before and after each session for nine regions of the body. Conditional classification discomfort models were developed through dichotomised physiological responses and anthropometry to predict subjective discomfort in specific body locations. Models revealed that subjects taller than 171 cm with reduced blood oxygenation in the biceps femoris or constant, low-level muscle activity in the trapezius tended to report discomfort in the lower extremities or neck, respectively. Subjects weighing less than 58 kg with reduced blood oxygenation in the biceps femoris or unevenly distributed pressure patterns tended to report discomfort in the buttocks. The sensitivities and specificities of cross-validated models ranged between 0.69 and 1.00.     

Predicting and interpreting identification errors in military vehicle training using multidimensional scaling

We compared methods for predicting and understanding the source of confusion errors during military vehicle identification training. Participants completed training to identify main battle tanks. They also completed card-sorting and similarity-rating tasks to express their mental representation of resemblance across the set of training items. We expected participants to selectively attend to a subset of vehicle features during these tasks, and we hypothesised that we could predict identification confusion errors based on the outcomes of the card-sort and similarity-rating tasks. Based on card-sorting results, we were able to predict about 45% of observed identification confusions. Based on multidimensional scaling of the similarity-rating data, we could predict more than 80% of identification confusions. These methods also enabled us to infer the dimensions receiving significant attention from each participant. This understanding of mental representation may be crucial in creating personalised training that directs attention to features that are critical for accurate identification.

Practitioner Summary: Participants completed military vehicle identification training and testing, along with card-sorting and similarity-rating tasks. The data enabled us to predict up to 84% of identification confusion errors and to understand the mental representation underlying these errors. These methods have potential to improve training and reduce identification errors leading to fratricide.     

FA composition and regiospecific analysis of Acer saccharum (sugar maple tree) and Acer saccharinum (silver maple tree) seed oils

GC analysis was performed to determine regiospecific distribution and FA composition in seed oils of the Aceraceae species, Acer saccharum and A. saccharinum. The oil content in the seeds was low at 5.0% in A. saccharum and 5.8% in A. saccharinum, and the main FA were linoleic (30.8 and 29.4%), oleic (21.3 and 27.6%), palmitic (10.1 and 10.5%), and cis-vaccenic (9.4 and 7.9%) acids, respectively. In addition, both oils contained long-chain monoenes of the n−9 and n−7 groups, including 11-eicosenoic, 13-docosenoic, 15-tetracosenoic, 13-eicosenoic, and 15-docosenoic acids, whereas γ-linolenic acid accounted for 0.8% of total FA in A. saccharum, and 0.5% in A. saccharinum. Regiospecific analysis, performed using the methodology of dibutyroyl derivatives of MAG, indicated that linoleic, oleic, and linolenic acids were mainly esterified at the internal position of TAG in both seed oils, whereas long-chain monoenes of the n−7 group were almost exclusively esterified on the external positions.     

Learning perceptually grounded word meanings from unaligned parallel data

In order for robots to effectively understand natural language commands, they must be able to acquire meaning representations that can be mapped to perceptual features in the external world. Previous approaches to learning these grounded meaning representations require detailed annotations at training time. In this paper, we present an approach to grounded language acquisition which is capable of jointly learning a policy for following natural language commands such as “Pick up the tire pallet,” as well as a mapping between specific phrases in the language and aspects of the external world; for example the mapping between the words “the tire pallet” and a specific object in the environment. Our approach assumes a parametric form for the policy that the robot uses to choose actions in response to a natural language command that factors based on the structure of the language. We use a gradient method to optimize model parameters. Our evaluation demonstrates the effectiveness of the model on a corpus of commands given to a robotic forklift by untrained users.