Design and application of nanoscale actuators using block-copolymers

Block copolymers are versatile designer macromolecules where a “bottom-up” approach can be used to create tailored materials with unique properties. These simple building blocks allow us to create actuators that convert energy from a variety of sources (such as chemical, electrical and heat) into mechanical energy. In this review we will discuss the advantages and potential pitfalls of using block copolymers to create actuators, putting emphasis on the ways in which these materials can be synthesised and processed. Particular attention will be given to the theoretical background of microphase separation and how the phase diagram can be used during the design process of actuators. Different types of actuation will be discussed throughout.

An action research study with low proficiency learners in Japan to promote the learning of vocabulary through collocations.

This action research (AR) study explores an alternative approach to vocabulary instruction for low-proficiency university students: a change from targeting individual words from the general service list (West, 1953) to targeting frequent verb + noun collocations. A review of the literature indicated a focus on collocations instead of individual words could potentially address the students’ productive challenges with targeted vocabulary. Over the course of four reflective cycles, this thesis addresses three main aspects of collocation instruction. First, it examines if the students believe studying collocations is more useful than studying individual lexical items. Second, the thesis investigates whether a focus on collocations will lead to improvements in spoken fluency. This is tested through a comparison of a pre-intervention spoken assessment task with the findings from the same task completed 15 weeks later, after the intervention. Third, the thesis explores different procedures for the instructing of collocations under the classroom constraints of a university teaching context. In the first of the four reflective cycles, data is collected which indicates that the students believe a focus on collocations is superior to only teaching individual lexical items, that in the students’ opinion their productive abilities with the targeted structures has improved, and that delexicalized verb collocations are problematic for low-proficiency students. Reflective cycle two produces evidence indicating that productive tasks are superior to receptive tasks for fluency development. In reflective cycle three, productively challenging classroom tasks are investigated further and the findings indicate that tasks with higher productive demands result in greater improvements in spoken fluency. The fourth reflective cycle uses a different type of collocation list: frequent adjective + noun collocations. Despite this change, the findings remain consistent in that certain types of collocations are problematic for low-proficiency language learners and that the evidence shows productive tasks are necessary to improve the students’ spoken ability.

Urinary proteomic biomarkers in coronary artery disease

Urinary proteomics is emerging as a powerful non-invasive tool for diagnosis and monitoring of variety of human diseases. We tested whether signatures of urinary polypeptides can contribute to the existing biomarkers for coronary artery disease (CAD). We examined a total of 359 urine samples from 88 patients with severe CAD and 282 controls. Spot urine was analyzed using capillary electrophoresis on-line coupled to ESI-TOF-MS enabling characterization of more than 1000 polypeptides per sample. In a first step a "training set" for biomarker definition was created. Multiple biomarker patterns clearly distinguished healthy controls from CAD patients, and we extracted 15 peptides that define a characteristic CAD signature panel. In a second step, the ability of the CAD-specific panel to predict the presence of CAD was evaluated in a blinded study using a "test set." The signature panel showed sensitivity of 98% (95% confidence interval, 88.7-99.6) and 83% specificity (95% confidence interval, 51.6-97.4). Furthermore the peptide pattern significantly changed toward the healthy signature correlating with the level of physical activity after therapeutic intervention. Our results show that urinary proteomics can identify CAD patients with high confidence and might also play a role in monitoring the effects of therapeutic interventions. The workflow is amenable to clinical routine testing suggesting that non-invasive proteomics analysis can become a valuable addition to other biomarkers used in cardiovascular risk assessment.

The two limits debates: "Limits to Growth" and climate change

In this article we compare the current debate about global warming with the earlier discourse of Limits to Growth (LtG) of the 1970's. We are especially interested in the similarities of and differences between the two cases and therefore compare the policy challenges and lessons to be drawn. While the two debates differ on important issues, they share a technocratic orientation to public policy, and susceptibility to similar pitfalls. In both debates alarming scenarios about future catastrophes play an important role. We suggest that climate change policy discourse needs to focus more closely on the social, economic, and political dimensions of climate change, as opposed to its excessive emphasis on emission reduction targets. We also argue that an excessive faith in the market mechanisms to supply global warming mitigation technologies is problematic. In this respect, we provide a reality check regarding the political implications of emission targets and timetables and suggest how policy issues can be moved forward.

Quantifying hydrogel response using laser light scattering

The pH and counter-ion response of a microphase separated poly(methyl methacrylate)-block-poly(2-(diethylamino)ethyl methacrylate)-block-poly(methyl methacrylate) hydrogel has been investigated using laser light scattering on an imprinted micron scale topography. A quartz diffraction grating was used to create a micron-sized periodic structure on the surface of a thin film of the polymer and the resulting diffraction pattern used to calculate the swelling ratio of the polymer film in situ. A potentiometric titration and a sequence of counter ion species, taken from the Hofmeister series, have been used to compare the results obtained using this novel technique against small angle X-ray scattering (nanoscopic) and gravimetric studies of bulk gel pieces (macroscopic). For the first time, the technique has been proven to be an inexpensive and effective analytical tool for measuring hydrogel response on the microscopic scale.

Effect of the Hofmeister anions upon the swelling of a self-assembled pH-responsive hydrogel

We report the effect of a range of monovalent sodium salts on the molecular equilibrium swelling of a simple synthetic microphase separated poly(methyl methacrylate)-block-poly(2-(diethylamino)ethyl methacrylate)-block-poly(methyl methacrylate) (PMMA88-b-PDEA223-b-PMMA88) pH-responsive hydrogel. Sodium acetate, sodium chloride, sodium bromide, sodium iodide, sodium nitrate and sodium thiocyanate were selected for study at controlled ionic strength and pH; all salts are taken from the Hofmeister series (HS). The influence of the anions on the expansion of the hydrogel was found to follow the reverse order of the classical HS. The expansion ratio of the gel measured in solutions containing the simple sodium halide salts (NaCl, NaBr, and NaI) was found to be strongly related to parameters which describe the interaction of the ion with water; surface charge density, viscosity coefficient, and entropy of hydration. A global study which also included nonspherical ions (NaAce, NaNO3 and NaSCN) showed the strongest correlation with the viscosity coefficient. Our results are interpreted in terms of the Collins model,(1) where larger ions have more mobile water in the first hydration cage immediately surrounding the gel, therefore making them more adhesive to the surface of the stationary phase of the gel and ultimately reducing the level of expansion.

Functional characterization of two human receptor activity-modifying protein 3 variants

Adrenomedullin (AM) and amylin are involved in angiogenesis/lymphangiogenesis and glucose homeostasis/food intake, respectively. They activate receptor activity-modifying protein (RAMP)/G protein-coupled receptor (GPCR) complexes. RAMP3 with the calcitonin receptor-like receptor (CLR) forms the AM(2) receptor, whereas when paired with the calcitonin receptor AMY(3) receptors are formed. RAMP3 interacts with other GPCRs although the consequences of these interactions are poorly understood. Therefore, variations in the RAMP3 sequence, such as single nucleotide polymorphisms or mutations could be relevant to human health. Variants of RAMP3 have been identified. In particular, analysis of AK222469 (Homo sapiens mRNA for receptor (calcitonin) activity-modifying protein 3 precursor variant) revealed several nucleotide differences, three of which encoded amino acid changes (Cys40Trp, Phe100Ser, Leu147Pro). Trp56Arg RAMP3 is a polymorphic variant of human RAMP3 at a conserved amino acid position. To determine their function we used wild-type (WT) human RAMP3 as a template for introducing amino acid mutations. Mutant or WT RAMP3 function was determined in Cos-7 cells with CLR or the calcitonin receptor (CT((a))). Cys40Trp/Phe100Ser/Leu147Pro RAMP3 was functionally compromised, with reduced AM and amylin potency at the respective AM(2) and AMY(3(a)) receptor complexes. Cys40Trp and Phe100Ser mutations contributed to this phenotype, unlike Leu147Pro. Reduced cell-surface expression of mutant receptor complexes probably explains the functional data. In contrast, Trp56Arg RAMP3 was WT in phenotype. This study provides insight into the role of these residues in RAMP3. The existence of AK222469 in the human population has implications for the function of RAMP3/GPCR complexes, particularly AM and amylin receptors.

Microspheres as a vehicle for biomolecule delivery to neural stem cells

Neural stem cells (NSC) are a valuable model system for understanding the intrinsic and extrinsic controls for self-renewal and differentiation choice. They also offer a platform for drug screening and neurotoxicity studies, and hold promise for cell replacement therapies for the treatment of neurodegenerative diseases. Fully exploiting the potential of this experimental tool often requires the manipulation of intrinsic cues of interest using transfection methods, to which NSC are relatively resistant. In this paper, we show that mouse and human NSC readily take up polystyrene-based microspheres which can be loaded with a range of chemical or biological cargoes. This uptake can take place in the undifferentiated stage without affecting NSC proliferation and their capacity to give rise to neurons and glia. We demonstrate that ß-galactosidase-loaded microspheres could be efficiently introduced into NSC with no apparent toxic effect, thus providing proof-of-concept for the use of microspheres as an alternative biomolecule delivery system.

Type-2 TOPSIS:a group decision problem when ideal values are not extreme endpoints

In the traditional TOPSIS, the ideal solutions are assumed to be located at the endpoints of the data interval. However, not all performance attributes possess ideal values at the endpoints. We termed performance attributes that have ideal values at extreme points as Type-1 attributes. Type-2 attributes however possess ideal values somewhere within the data interval instead of being at the extreme end points. This provides a preference ranking problem when all attributes are computed and assumed to be of the Type-1 nature. To overcome this issue, we propose a new Fuzzy DEA method for computing the ideal values and distance function of Type-2 attributes in a TOPSIS methodology. Our method allows Type-1 and Type-2 attributes to be included in an evaluation system without compromising the ranking quality. The efficacy of the proposed model is illustrated with a vendor evaluation case for a high-tech investment decision making exercise. A comparison analysis with the traditional TOPSIS is also presented. © 2012 Springer Science+Business Media B.V.

A bi-objective weighted model for improving the discrimination power in MCDEA

Lack of discrimination power and poor weight dispersion remain major issues in Data Envelopment Analysis (DEA). Since the initial multiple criteria DEA (MCDEA) model developed in the late 1990s, only goal programming approaches; that is, the GPDEA-CCR and GPDEA-BCC were introduced for solving the said problems in a multi-objective framework. We found GPDEA models to be invalid and demonstrate that our proposed bi-objective multiple criteria DEA (BiO-MCDEA) outperforms the GPDEA models in the aspects of discrimination power and weight dispersion, as well as requiring less computational codes. An application of energy dependency among 25 European Union member countries is further used to describe the efficacy of our approach. © 2013 Elsevier B.V. All rights reserved.

Intellectual property enforcement in smaller UK firms:a report for the Strategic Advisory Board for Intellectual Property Policy (SABIP)

This report details research into the enforcement of intellectual property (IP). It considers the attitudes and practices of small and medium-sized enterprises (SMEs) and micro firms as well as the cost implications of the present IP enforcement system in the UK. According to an earlier report for SABIP, by Weatherall et al. 2009, in the Gowers Review of Intellectual Property questions of enforcement were largely addressed through assertion, rather than empirical research. This report aims to provide such research. Our study included both an online survey and a phone survey. These concentrated on SMEs and micro firms rather than being a comparative study with large firms. Further work obtained information on Patents and Registered Design cases listed for hearings in the Patents Court from 2003 to 2009. The analysis of this data provides some evidence that complements the results of the survey.

Using genetic algorithms for improved discrete sequence prediction

A statistics-based method using genetic algorithms for predicting discrete sequences is presented. The prediction of the next value is based upon a fixed number of previous values and the statistics offered by the training data. According to the statistics, in similar past cases different values occurred next. If these values are considered with the appropriate weights, the forecast is successful. Weights are generated by genetic algorithms.

A fuzzy expected value approach under generalized data envelopment analysis

Fuzzy data envelopment analysis (DEA) models emerge as another class of DEA models to account for imprecise inputs and outputs for decision making units (DMUs). Although several approaches for solving fuzzy DEA models have been developed, there are some drawbacks, ranging from the inability to provide satisfactory discrimination power to simplistic numerical examples that handles only triangular fuzzy numbers or symmetrical fuzzy numbers. To address these drawbacks, this paper proposes using the concept of expected value in generalized DEA (GDEA) model. This allows the unification of three models - fuzzy expected CCR, fuzzy expected BCC, and fuzzy expected FDH models - and the ability of these models to handle both symmetrical and asymmetrical fuzzy numbers. We also explored the role of fuzzy GDEA model as a ranking method and compared it to existing super-efficiency evaluation models. Our proposed model is always feasible, while infeasibility problems remain in certain cases under existing super-efficiency models. In order to illustrate the performance of the proposed method, it is first tested using two established numerical examples and compared with the results obtained from alternative methods. A third example on energy dependency among 23 European Union (EU) member countries is further used to validate and describe the efficacy of our approach under asymmetric fuzzy numbers.

Carbon efficiency evaluation:an analytical framework using fuzzy DEA

Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency of alternatives based on their inputs and outputs. The alternatives can be in the form of countries who attempt to enhance their productivity and environmental efficiencies concurrently. However, when desirable outputs such as productivity increases, undesirable outputs increase as well (e.g. carbon emissions), thus making the performance evaluation questionable. In addition, traditional environmental efficiency has been typically measured by crisp input and output (desirable and undesirable). However, the input and output data, such as CO2 emissions, in real-world evaluation problems are often imprecise or ambiguous. This paper proposes a DEA-based framework where the input and output data are characterized by symmetrical and asymmetrical fuzzy numbers. The proposed method allows the environmental evaluation to be assessed at different levels of certainty. The validity of the proposed model has been tested and its usefulness is illustrated using two numerical examples. An application of energy efficiency among 23 European Union (EU) member countries is further presented to show the applicability and efficacy of the proposed approach under asymmetric fuzzy numbers.