High-performance nanocomposites based on polyetherketones

Polyetherketones, PEKs, are an important family of high-performance thermoplastic materials that display a unique combination of toughness, stiffness, thermooxidative stability, chemical and solvent resistance, flame retardancy, and retention of physical properties at high temperatures. A relevant step forward in the development of these materials has been the recent incorporation of nanofillers to extend their utility in advanced technological applications. This review provides an extensive overview of the research on PEK-based nanocomposites with a special emphasis on both carbon-based nanofillers, such as nanotubes or nanofibers, and inorganic nanoparticles. Nanocomposites can be fabricated by simple, low-cost conventional techniques such as extrusion and compression molding, generally combined with pre-processing stages involving mechanochemical treatments in organic solvents. Different strategies employed to efficiently incorporate carbon nanofillers into these matrices, including polymer functionalization, covalent grafting and nanofiller wrapping in compatibilizing systems are described. The analysis of the influence of the preparation and processing conditions as well as the nanofiller type, attributes and loading on the structure and properties of the resulting materials is also considered. Composites incorporating carbon nanofillers display remarkably improved thermal stability, electrical and thermal conductivity as well as mechanical property enhancements compared to the neat polymers. On the other hand, the incorporation of inorganic nanoparticles such as WS₂, SiO₂ or Al₂O₃ significantly enhances the tribological properties of the matrix, mainly the coefficient of friction and wear resistance. Finally, current and potential applications of these multifunctional nanocomposite materials in fields such as medicine, telecommunications, electronics, aerospace, automobile and chemical industries are described.     

A decomposition-based approach for the selection of standardized modular containers

The standardisation of packaging and containers for product handling has potential benefits from transportation, material handling and environmental perspectives. Likewise, standardised modular containers play an important role in the Physical Internet (PI). To support implementation of standard modular containers, we introduce a mathematical model to select a requisite number of modular containers to pack a set of products to maximise space utilisation. A decomposition-based solution methodology is developed and presented. Computational results from industry-based problem instances indicate that using standardised modular containers results in increased space utilisation at the unit load level. This finding substantiates the use of modular containers in moving toward the PI.     

Economic model predictive control of nonlinear time‐delay systems: Closed‐loop stability and delay compensation

Closed‐loop stability of nonlinear time‐delay systems under Lyapunov‐based economic model predictive control (LEMPC) is considered. LEMPC is initially formulated with an ordinary differential equation model and is designed on the basis of an explicit stabilizing control law. To address closed‐loop stability under LEMPC, first, we consider the stability properties of the sampled‐data system resulting from the nonlinear continuous‐time delay system with state and input delay under a sample‐and‐hold implementation of the explicit controller. The steady‐state of this sampled‐data closed‐loop system is shown to be practically stable. Second, conditions such that closed‐loop stability, in the sense of boundedness of the closed‐loop state, under LEMPC are derived. A chemical process example is used to demonstrate that indeed closed‐loop stability is maintained under LEMPC for sufficiently small time‐delays. To cope with performance degradation owing to the effect of input delay, a predictor feedback LEMPC methodology is also proposed. The predictor feedback LEMPC design employs a predictor to compute a prediction of the state after the input delay period and an LEMPC scheme that is formulated with a differential difference equation (DDE) model, which describes the time‐delay system, initialized with the predicted state. The predictor feedback LEMPC is also applied to the chemical process example and yields improved closed‐loop stability and economic performance properties. © 2015 American Institute of Chemical Engineers AIChE J, 61: 4152–4165, 2015     

LEARNING TO FORGET: Architectural Recreation,Spatial Visualization and Imaging the Unseen

Children learn through play, through re-creating situations and events. While playing, children forget themselves, time is suspended, and mind, body and emotions work together simultaneously in the child's re-creations. This is a four-dimensional type of space, similar to the intuitive inner space that opens up during the spatial visualization of architectural recreation. The following discusses an architectural pedagogy that teaches students how to forget: how to leave behind the inherent symbolic and logic structures of the rational mind that would have them name things, so that they may develop the abilities of the metaphoric mind to visualize spatially and image the unseen.     

Association of the serotonin transporter gene promoter region (5-HTTLPR) polymorphism with biased attention for emotional stimuli.

A deletion polymorphism in the serotonin transporter-linked polymorphic region (5-HTTLPR) has been associated with vulnerability to affective disorders, yet the mechanism by which this gene confers vulnerability remains unclear. Two studies examined associations between the 5-HTTLPR polymorphism and attentional bias for emotional stimuli among nondepressed adults. Biased attention, attention engagement, and difficulty with attention disengagement were assessed with a spatial cuing task using emotional stimuli. Results from Study 1 (N = 38) indicated that short 5-HTTLPR allele carriers experienced greater difficulty disengaging their attention from sad and happy stimuli compared with long allele homozygotes. Study 2 participants (N = 144) were genotyped for the 5-HTTLPR polymorphism, including single nucleotide polymorphism rs25531 in the long allele of the 5-HTTLPR. Consistent with Study 1, individuals homozygous for the low-expressing 5-HTTLPR alleles (i.e., S and LG) experienced greater difficulty disengaging attention from sad, happy, and fear stimuli than high-expressing 5-HTTLPR homozygotes. Because this association exists in healthy adults, it may represent a susceptibility factor for affective disorders that becomes problematic during stressful life experiences. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Aging and Thermal Stability of the Mixed Product of the Ether‐Soluble Fraction of Bio‐Oil and Bio‐Diesel

The storage and thermal stability of blends of the ether‐soluble fraction of bio‐oil (ES) and bio‐diesel are reported. Fuel properties such as viscosity, water content, acid number and average molecular weight of the ES/bio‐diesel blends were measured before and after aging. Compared to the aging properties of bio‐oil alone, very small changes in water content and viscosity were shown for the blends aged at 80 °C for 180 h. Chemical changes were characterized using gel permeation chromatography, showing a slight increase in the molecular weight over time. Further confirmation of the changes was provided through Fourier transform infrared spectrometry, thermal decomposition analysis using a thermogravimetric analyzer, proton assignment using proton nuclear magnetic resonance, and carbon assignment using carbon nuclear magnetic resonance. Overall, the study indicates that ES/bio‐diesel blends are stable as fuel under the conditions tested in this paper.     

Motivating interdependent teams: Individual rewards, shared rewards, or something in between?

The primary purpose in this study was to extend theory and research regarding the motivational process in teams by examining the effects of hybrid rewards on team performance. Further, to better understand the underlying team level mechanisms, the authors examined whether the hypothesized benefits of hybrid over shared and individual rewards were due to increased information allocation and reduced social loafing. Results from 90 teams working on a command-and-control simulation supported the hypotheses. Hybrid rewards led to higher levels of team performance than did individual and shared rewards; these effects were due to improvements in information allocation and reductions in social loafing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Parent–offspring conflict theory: An evolutionary framework for understanding conflict within human families.

Decades of research demonstrate that conflict shapes and permeates a broad range of family processes. In the current article, we argue that greater insight, integration of knowledge, and empirical achievement in the study of family conflict can be realized by utilizing a powerful theory from evolutionary biology that is barely known within psychology: parent–offspring conflict theory (POCT). In the current article, we articulate POCT for psychological scientists, extend its scope by connecting it to the broader framework of life history theory, and draw out its implications for understanding conflict within human families. We specifically apply POCT to 2 instances of early mother–offspring interaction (prenatal conflict and weaning conflict); discuss the effects of genetic relatedness on behavioral conflict between parents, children, and their siblings; review the emerging literature on parent–offspring conflict over the choice of mates and spouses; and examine parent–offspring conflict from the perspective of imprinted genes. This review demonstrates the utility of POCT, not only for explaining what is known about conflict within families but also for generating novel hypotheses, suggesting new lines of research, and moving us toward the “big picture” by integrating across biological and psychological domains of knowledge. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Decoupled Roles for the Atypical,Bifurcated Binding Pocket of the ybfF Hydrolase

Serine hydrolases have diverse intracellular substrates, biological functions, and structural plasticity, and are thus important for biocatalyst design. Amongst serine hydrolases, the recently described ybfF enzyme family are promising novel biocatalysts with an unusual bifurcated substrate‐binding cleft and the ability to recognize commercially relevant substrates. We characterized in detail the substrate selectivity of a novel ybfF enzyme from Vibrio cholerae (Vc‐ybfF) by using a 21‐member library of fluorogenic ester substrates. We assigned the roles of the two substrate‐binding clefts in controlling the substrate selectivity and folded stability of Vc‐ybfF by comprehensive substitution analysis. The overall substrate preference of Vc‐ybfF was for short polar chains, but it retained significant activity with a range of cyclic and extended esters. This broad substrate specificity combined with the substitutional analysis demonstrates that the larger binding cleft controls the substrate specificity of Vc‐ybfF. Key selectivity residues (Tyr116, Arg120, Tyr209) are also located at the larger binding pocket and control the substrate specificity profile. In the structure of ybfF the narrower binding cleft contains water molecules prepositioned for hydrolysis, but based on substitution this cleft showed only minimal contribution to catalysis. Instead, the residues surrounding the narrow binding cleft and at the entrance to the binding pocket contributed significantly to the folded stability of Vc‐ybfF. The relative contributions of each cleft of the binding pocket to the catalytic activity and folded stability of Vc‐ybfF provide a valuable map for designing future biocatalysts based on the ybfF scaffold.     

The use of visual search for knowledge gathering in image decision support

This paper presents a new method of knowledge gathering for decision support in image understanding based on information extracted from the dynamics of saccadic eye movements. The framework involves the construction of a generic image feature extraction library, from which the feature extractors that are most relevant to the visual assessment by domain experts are determined automatically through factor analysis. The dynamics of the visual search are analyzed by using the Markov model for providing training information to novices on how and where to look for image features. The validity of the framework has been evaluated in a clinical scenario whereby the pulmonary vascular distribution on Computed Tomography images was assessed by experienced radiologists as a potential indicator of heart failure. The performance of the system has been demonstrated by training four novices to follow the visual assessment behavior of two experienced observers. In all cases, the accuracy of the students improved from near random decision making (33%) to accuracies ranging from 50% to 68%.