Technology transfer to China:a study of strategy in 20 EU industrial companies

Foreign direct investment has been important in China's economic development since the early 1980s. In recent years, the volume of inward FDI into China, according to some estimates, has been second only to that into the USA. The Chinese government has emphasised the need for FDI to be coupled with the transfer of more advanced technologies to China. For foreign companies, technology transfer raises the risk of losing their technology based competitive advantage to potential competitor firms. This risk may be exacerbated by insufficient legal protection of intellectual property rights in China. After briefly reviewing the development of Chinese official policy on technology transfer, this paper considers the strategy adopted by EU companies regarding the transfer of technology; in particular in advanced technology sectors. The research on which the paper is based included an analysis of information gathered from 20 leading EU companies with investments in China and operating in high-technology sectors. Information was gathered from senior company managers based in both China and Europe during the second half of 1998. The main findings include a measure of reluctance on the part of EU companies to transfer their core technologies to China and to base R&D capability there. At the same time, the companies appear aware that this policy may be unsustainable in the longer-term in the face of Chinese official policy and a desire to expand their operations in China. While they attempt to protect their existing technological knowledge, most of them accept that there will be technology "leakage" and therefore the most effective strategy is to maintain their technological lead through R&D.

Highly sensitive bend sensor based on Bragg grating in eccentric core polymer fiber

We report on an optical bend sensor based on a Bragg grating inscribed in an eccentric core polymer optical fiber. The device exhibits the strong fiber orientation dependence, the wide bend curvature range of ± 22.7 m-1 and high bend sensitivity of 63 pm/m-1.

State intervention in technology in the post war years: case studies in technology policy

This thesis is concerned with the means by which the state in Britain has attempted to influence the technological development of private industry in the period 1945-1979. Particular emphasis is laid on assessing the abilities of technology policy measures to promote innovation. With that objective, the innovation literature is selectively reviewed to draw up an analytical framework to evaluate the innovation content of policy (Chapter 2). Technology policy is taken to consist of the specific measures utilised by government and its agents that affect the technological behaviour of firms. The broad sweep of policy during the period under consideration is described in Chapter 3 which concentrates on elucidating its institutional structure and the activities of the bodies involved. The empirical core of the thesis consists of three parallel case studies of policy toward the computer, machine tool and textile machinery industries (Chapters 4-6). The studies provide detailed historical accounts of the development and composition of policy, relating it to its specific institutional and industrial contexts. Each reveals a different pattern and level of state intervention. The thesis concludes with a comparative review of the findings of the case studies within a discussion centred on the arguments presented in Chapter 2. Topics arising include the state's differential support for the range of activities involved in innovation, the location of state-funded R&D, the encouragement of supplier-user contact, and the difficulties raised in adoption and diffusion.

The combination of smart hydrogels and fibre optic sensor technology for analyte detection

The subject of investigation of the present research is the use of smart hydrogels with fibre optic sensor technology. The aim was to develop a costeffective sensor platform for the detection of water in hydrocarbon media, and of dissolved inorganic analytes, namely potassium, calcium and aluminium. The fibre optic sensors in this work depend upon the use of hydrogels to either entrap chemotropic agents or to respond to external environmental changes, by changing their inherent properties, such as refractive index (RI). A review of current fibre optic technology for sensing outlined that the main principles utilised are either the measurement of signal loss or a change in wavelength of the light transmitted through the system. The signal loss principle relies on changing the conditions required for total internal reflection to occur. Hydrogels are cross-linked polymer networks that swell but do not dissolve in aqueous environments. Smart hydrogels are synthetic materials that exhibit additional properties to those inherent in their structure. In order to control the non-inherent properties, the hydrogels were fabricated with the addition of chemotropic agents. For the detection of water, hydrogels of low refractive index were synthesized using fluorinated monomers. Sulfonated monomers were used for their extreme hydrophilicity as a means of water sensing through an RI change. To enhance the sensing capability of the hydrogel, chemotropic agents, such as pH indicators and cobalt salts, were used. The system comprises of the smart hydrogel coated onto an exposed section of the fibre optic core, connected to the interrogation system measuring the difference in the signal. Information obtained was analysed using a purpose designed software. The developed sensor platform showed that an increase in the target species caused an increase in the signal lost from the sensor system, allowing for a detection of the target species. The system has potential applications in areas such as clinical point of care, water detection in fuels and the detection of dissolved ions in the water industry.

Peptide length significantly influences in vitro affinity for MHC class II molecules

Class II Major Histocompatibility Complex (MHC) molecules have an open-ended binding groove which can accommodate peptides of varying lengths. Several studies have demonstrated that peptide flanking residues (PFRs) which lie outside the core binding groove can influence peptide binding and T cell recognition. By using data from the AntiJen database we were able to characterise systematically the influence of PFRs on peptide affinity for MHC class II molecules.

Integration of a 3D hydrogel matrix within a hollow core photonic crystal fibre for DNA probe immobilization

In this paper, we demonstrate the integration of a 3D hydrogel matrix within a hollow core photonic crystal fibre (HC-PCF). In addition, we also show the fluorescence of Cy5-labelled DNA molecules immobilized within the hydrogel formed in two different types of HC-PCF. The 3D hydrogel matrix is designed to bind with the amino groups of biomolecules using an appropriate cross-linker, providing higher sensitivity and selectivity than the standard 2D coverage, enabling a greater number of probe molecules to be available per unit area. The HC-PCFs, on the other hand, can be designed to maximize the capture of fluorescence to improve sensitivity and provide longer interaction lengths. This could enable the development of fibre-based point-of-care and remote systems, where the enhanced sensitivity would relax the constraints placed on sources and detectors. In this paper, we will discuss the formation of such polyethylene glycol diacrylate (PEGDA) hydrogels within a HC-PCF, including their optical properties such as light propagation and auto-fluorescence.

ProxiMAX Randomisation:a new technology for non-degenerate saturation mutagenesis of contiguous codons

ProxiMAX randomisation achieves saturation mutagenesis of contiguous codons without degeneracy or bias. Offering an alternative to trinucleotide phosphoramidite chemistry, it uses nothing more sophisticated than unmodified oligonucleotides and standard molecular biology reagents and as such, requires no specialised chemistry, reagents nor equipment. When particular residues are known to affect protein activity/specificity, their combinatorial replacement with all 20 amino acids, or a subset thereof, can provide a rapid route to generating proteins with desirable characteristics. Conventionally, saturation mutagenesis replaced key codons with degenerate ones. Although simple to perform, that procedure resulted in unnecessarily large libraries, termination codons and inherent uneven amino acid representation. ProxiMAX randomisation is an enzyme-based technique that can encode unbiased representation of all or selected amino acids or else can provide required codons in pre-defined ratios. Each saturated position can be defined independently of the others. ProxiMAX randomisation is achieved via saturation cycling: an iterative process comprising blunt end ligation, amplification and digestion with a Type IIS restriction enzyme. We demonstrate both unbiased saturation of a short 6-mer peptide and saturation of a hypervariable region of a scfv antibody fragment, where 11 contiguous codons are saturated with selected codons, in pre-defined ratios. As such, ProxiMAX randomisation is particularly relevant to antibody engineering. The development of ProxiMAX randomisation from concept to reality is described.

Evaluation of integration technology approaches in the healthcare supply chain

Healthcare organisations are increasingly being challenged to look at their operations and find opportunities to improve the quality, efficiency and effectiveness of their supply chain services. In light of this situation, there is an apparent need for healthcare organisations to invest in integration technologies and to achieve the integration of supply chain processes, in order to break up the historical structure characterised by numerous interfaces and the segregation of responsibilities. The aim of this paper is to take an independent look at the healthcare supply chain and identify at different levels the core entities, processes, information flows, and system integration challenges which impede supply chain quality improvements to be realised. Moreover, this paper proposes, from an information systems perspective, a framework for the evaluation of different integration technology approaches, which can be used as a potential guideline tool for assessing integration technology alternatives, in order to add value to a healthcare-supply-chain management system. Copyright © 2007 Inderscience Enterprises Ltd.

Toward the prediction of class I and II mouse major histocompatibility complex-peptide-binding affinity:in silico bioinformatic step-by-step guide using quantitative structure-activity relationships

Quantitative structure-activity relationship (QSAR) analysis is a cornerstone of modern informatics. Predictive computational models of peptide-major histocompatibility complex (MHC)-binding affinity based on QSAR technology have now become important components of modern computational immunovaccinology. Historically, such approaches have been built around semiqualitative, classification methods, but these are now giving way to quantitative regression methods. We review three methods--a 2D-QSAR additive-partial least squares (PLS) and a 3D-QSAR comparative molecular similarity index analysis (CoMSIA) method--which can identify the sequence dependence of peptide-binding specificity for various class I MHC alleles from the reported binding affinities (IC50) of peptide sets. The third method is an iterative self-consistent (ISC) PLS-based additive method, which is a recently developed extension to the additive method for the affinity prediction of class II peptides. The QSAR methods presented here have established themselves as immunoinformatic techniques complementary to existing methodology, useful in the quantitative prediction of binding affinity: current methods for the in silico identification of T-cell epitopes (which form the basis of many vaccines, diagnostics, and reagents) rely on the accurate computational prediction of peptide-MHC affinity. We have reviewed various human and mouse class I and class II allele models. Studied alleles comprise HLA-A*0101, HLA-A*0201, HLA-A*0202, HLA-A*0203, HLA-A*0206, HLA-A*0301, HLA-A*1101, HLA-A*3101, HLA-A*6801, HLA-A*6802, HLA-B*3501, H2-K(k), H2-K(b), H2-D(b) HLA-DRB1*0101, HLA-DRB1*0401, HLA-DRB1*0701, I-A(b), I-A(d), I-A(k), I-A(S), I-E(d), and I-E(k). In this chapter we show a step-by-step guide into predicting the reliability and the resulting models to represent an advance on existing methods. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made are freely available online at the URL http://www.jenner.ac.uk/MHCPred.

Microarray-formatted clinical biomarker assay development using peptide aptamers to anterior gradient-2

Anterior gradient-2 protein was identified using proteomic technologies as a p53 inhibitor which is overexpressed in human cancers, and this protein presents a novel pro-oncogenic target with which to develop diagnostic assays for biomarker detection in clinical tissue. Combinatorial phage-peptide libraries were used to select 12 amino acid polypeptide aptamers toward anterior gradient-2 to determine whether methods can be developed to affinity purify the protein from clinical biopsies. Selecting phage aptamers through four rounds of screening on recombinant human anterior gradient-2 protein identified two classes of peptide ligand that bind to distinct epitopes on anterior gradient-2 protein in an immunoblot. Synthetic biotinylated peptide aptamers bound in an ELISA format to anterior gradient-2, and substitution mutagenesis further minimized one polypeptide aptamer to a hexapeptide core. Aptamers containing this latter consensus sequence could be used to affinity purify to homogeneity human anterior gradient-2 protein from a single clinical biopsy. The spotting of a panel of peptide aptamers onto a protein microarray matrix could be used to quantify anterior gradient-2 protein from crude clinical biopsy lysates, providing a format for quantitative screening. These data highlight the utility of peptide combinatorial libraries to acquire rapidly a high-affinity ligand that can selectively bind a target protein from a clinical biopsy and provide a technological approach for clinical biomarker assay development in an aptamer microarray format.

The spectral sensitivity of long period gratings fabricated in elliptical core D-shaped optical fiber

Long period gratings (LPGs) were written into a D-shaped optical fibre, which has an elliptical core with a W-shaped refractive index profile. The LPG's attenuation bands were found to be sensitive to the polarisation of the interrogating light with a spectral separation of about 15nm between the two orthogonal polarisation states. In addition, two spectrally overlapping attenuation bands corresponding to orthogonal polarisation states were observed; modelling successfully reproduced this spectral feature. The spectral sensitivity of both orthogonal states was experimentally measured with respect to temperature, surrounding refractive index, and directional bending. These LPG devices produced blue and red wavelength shifts of the stop-bands due to bending in different directions. The measured spectral sensitivities to curvatures, d?/dR , ranged from -3.56nm m to +6.51nm m. The results obtained with these LPGs suggest that this type of fibre may be useful as a shape/bend sensor. It was also demonstrated that the neighbouring bands could be used to discriminate between temperature and bending and that overlapping orthogonal polarisation attenuation bands can be used to minimise error associated with polarisation.

New horizons in mouse immunoinformatics:reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity

Quantitative structure–activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide–protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2–Db, H2–Kb and H2–Kk. As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online (http://www.jenner.ac.uk/MHCPred).

Technology enhanced learning in Higher Education

Technology-Enhanced Learning in Higher Education is an anthology produced by the international association, Learning in Higher Education (LiHE). LiHE, whose scope includes the activities of colleges, universities and other institutions of higher education, has been one of the leading organisations supporting a shift in the education process from a transmission-based philosophy to a student-centred, learning-based approach. Traditionally education has been envisaged as a process in which the teacher disseminates knowledge and information to the student, and directs them to perform – instructing, cajoling, encouraging them as appropriate – despite different students’ abilities. Yet higher education is currently experiencing rapid transformation, with the introduction of a broad range of technologies which have the potential to enhance student learning. This anthology draws upon the experiences of those practitioners who have been pioneering new applications of technology in higher education, highlighting not only the technologies themselves but also the impact which they have had on student learning. The anthology illustrates how new technologies – which are increasingly well-known and accepted by today’s ‘digital natives’ undertaking higher education – can be adopted and incorporated. One key conclusion is that learning remains a social process even in technology-enhanced learning contexts. So the technology-based proxies we construct need to retain and reflect the agency of the teacher. Technology-Enhanced Learning in Higher Education showcases some of the latest pedagogical technologies and their most creative, state-of-the-art applications to learning in higher education from around the world. Each of the chapters explores technology-enhanced learning in higher education in terms of either policy or practice. They contain detailed descriptions of approaches taken in very different curriculum areas, and demonstrate clearly that technology may and can enhance learning only if it is designed with the learning process of students at its core. So the use of technology in education is more linked to pedagogy than it is to bits and bytes.

Peptide binding to HLA-DP proteins at pH 5.0 and pH 7.0:a quantitative molecular docking study

Background: HLA-DPs are class II MHC proteins mediating immune responses to many diseases. Peptides bind MHC class II proteins in the acidic environment within endosomes. Acidic pH markedly elevates association rate constants but dissociation rates are almost unchanged in the pH range 5.0 - 7.0. This pH-driven effect can be explained by the protonation/deprotonation states of Histidine, whose imidazole has a pKa of 6.0. At pH 5.0, imidazole ring is protonated, making Histidine positively charged and very hydrophilic, while at pH 7.0 imidazole is unprotonated, making Histidine less hydrophilic. We develop here a method to predict peptide binding to the four most frequent HLA-DP proteins: DP1, DP41, DP42 and DP5, using a molecular docking protocol. Dockings to virtual combinatorial peptide libraries were performed at pH 5.0 and pH 7.0. Results: The X-ray structure of the peptide - HLA-DP2 protein complex was used as a starting template to model by homology the structure of the four DP proteins. The resulting models were used to produce virtual combinatorial peptide libraries constructed using the single amino acid substitution (SAAS) principle. Peptides were docked into the DP binding site using AutoDock at pH 5.0 and pH 7.0. The resulting scores were normalized and used to generate Docking Score-based Quantitative Matrices (DS-QMs). The predictive ability of these QMs was tested using an external test set of 484 known DP binders. They were also compared to existing servers for DP binding prediction. The models derived at pH 5.0 predict better than those derived at pH 7.0 and showed significantly improved predictions for three of the four DP proteins, when compared to the existing servers. They are able to recognize 50% of the known binders in the top 5% of predicted peptides. Conclusions: The higher predictive ability of DS-QMs derived at pH 5.0 may be rationalised by the additional hydrogen bond formed between the backbone carbonyl oxygen belonging to the peptide position before p1 (p-1) and the protonated ε-nitrogen of His 79β. Additionally, protonated His residues are well accepted at most of the peptide binding core positions which is in a good agreement with the overall negatively charged peptide binding site of most MHC proteins. © 2012 Patronov et al.; licensee BioMed Central Ltd.