Innovation and performance:benchmarking Australian firms

This article empirically analyses the link between innovation and performance using a sample of large Australian firms, with a specific aim of developing benchmarking tools. Innovation is measured by firms' investment in R&D and applications for patents, trademarks and designs. An innovation index is constructed to provide one method of benchmarking. The index incorporates a firm's innovative activities into a single figure after accounting for firm size. The index provides a ranking of the most innovative firms in Australia. A second method of benchmarking uses a stochastic production frontier. This type of analysis identifies the firms which are located closest to a ‘best practice innovation frontier’.

Novel strategies to improve recombinant membrane protein production in yeast

Approximately 60% of pharmaceuticals target membrane proteins; 30% of the human genome codes for membrane proteins yet they represent less than 1% of known unique crystal structures deposited in the Protein Data Bank (PDB), with 50% of structures derived from recombinant membrane proteins having been synthesized in yeasts. G protein-coupled receptors (GPCRs) are an important class of membrane proteins that are not naturally abundant in their native membranes. Unfortunately their recombinant synthesis often suffers from low yields; moreover, function may be lost during extraction and purification from cell membranes, impeding research aimed at structural and functional determination. We therefore devised two novel strategies to improve functional yields of recombinant membrane proteins in the yeast Saccharomyces cerevisiae. We used human adenosine A2A receptor (hA2AR) as a model GPRC since it is functionally and structurally well characterised.In the first strategy, we investigated whether it is possible to provide yeast cells with a selective advantage (SA) in producing the fusion protein hA2AR-Ura3p when grown in medium lacking uracil; Ura3p is a decarboxylase that catalyzes the sixth enzymatic step in the de novo biosynthesis of pyrimidines, generating uridine monophosphate. The first transformant (H1) selected using the SA strategy gave high total yields of hA2AR-Ura3p, but low functional yields as determined by radio-ligand binding, leading to the discovery that the majority of the hA2AR-Ura3p had been internalized to the vacuole. The yeast deletion strain spt3Δ is thought to have slower translation rates and improved folding capabilities compared to wild-type cells and was therefore utilised for the SA strategy to generate a second transformant, SU1, which gave higher functional yields than H1. Subsequently hA2AR-Ura3p from H1 was solubilised with n-dodecyl-β-D-maltoside and cholesteryl hemisuccinate, which yielded functional hA2AR-Ura3p at the highest yield of all approaches used. The second strategy involved using knowledge of translational processes to improve recombinant protein synthesis to increase functional yield. Modification of existing expression vectors with an internal ribosome entry site (IRES) inserted into the 5ˊ untranslated region (UTR) of the gene encoding hA2AR was employed to circumvent regulatory controls on recombinant synthesis in the yeast host cell. The mechanisms involved were investigated through the use of yeast deletion strains and drugs that cause translation inhibition, which is known to improve protein folding and yield. The data highlight the potential to use deletion strains to increase IRES-mediated expression of recombinant hA2AR. Overall, the data presented in this thesis provide mechanistic insights into two novel strategies that can increase functional membrane protein yields in the eukaryotic microbe, S. cerevisiae.

Fully probabilistic control for stochastic nonlinear control systems with input dependent noise

Robust controllers for nonlinear stochastic systems with functional uncertainties can be consistently designed using probabilistic control methods. In this paper a generalised probabilistic controller design for the minimisation of the Kullback-Leibler divergence between the actual joint probability density function (pdf) of the closed loop control system, and an ideal joint pdf is presented emphasising how the uncertainty can be systematically incorporated in the absence of reliable systems models. To achieve this objective all probabilistic models of the system are estimated from process data using mixture density networks (MDNs) where all the parameters of the estimated pdfs are taken to be state and control input dependent. Based on this dependency of the density parameters on the input values, explicit formulations to the construction of optimal generalised probabilistic controllers are obtained through the techniques of dynamic programming and adaptive critic methods. Using the proposed generalised probabilistic controller, the conditional joint pdfs can be made to follow the ideal ones. A simulation example is used to demonstrate the implementation of the algorithm and encouraging results are obtained.

Optimization of Discrete-Time, Stochastic Systems

* This research was supported by a grant from the Greek Ministry of Industry and Technology.

Editorial overview:new protein production tools for structural biology

Full text: The idea of producing proteins from recombinant DNA hatched almost half a century ago. In his PhD thesis, Peter Lobban foresaw the prospect of inserting foreign DNA (from any source, including mammalian cells) into the genome of a λ phage in order to detect and recover protein products from Escherichia coli [ 1 and 2]. Only a few years later, in 1977, Herbert Boyer and his colleagues succeeded in the first ever expression of a peptide-coding gene in E. coli — they produced recombinant somatostatin [ 3] followed shortly after by human insulin. The field has advanced enormously since those early days and today recombinant proteins have become indispensable in advancing research and development in all fields of the life sciences. Structural biology, in particular, has benefitted tremendously from recombinant protein biotechnology, and an overwhelming proportion of the entries in the Protein Data Bank (PDB) are based on heterologously expressed proteins. Nonetheless, synthesizing, purifying and stabilizing recombinant proteins can still be thoroughly challenging. For example, the soluble proteome is organized to a large part into multicomponent complexes (in humans often comprising ten or more subunits), posing critical challenges for recombinant production. A third of all proteins in cells are located in the membrane, and pose special challenges that require a more bespoke approach. Recent advances may now mean that even these most recalcitrant of proteins could become tenable structural biology targets on a more routine basis. In this special issue, we examine progress in key areas that suggests this is indeed the case. Our first contribution examines the importance of understanding quality control in the host cell during recombinant protein production, and pays particular attention to the synthesis of recombinant membrane proteins. A major challenge faced by any host cell factory is the balance it must strike between its own requirements for growth and the fact that its cellular machinery has essentially been hijacked by an expression construct. In this context, Bill and von der Haar examine emerging insights into the role of the dependent pathways of translation and protein folding in defining high-yielding recombinant membrane protein production experiments for the common prokaryotic and eukaryotic expression hosts. Rather than acting as isolated entities, many membrane proteins form complexes to carry out their functions. To understand their biological mechanisms, it is essential to study the molecular structure of the intact membrane protein assemblies. Recombinant production of membrane protein complexes is still a formidable, at times insurmountable, challenge. In these cases, extraction from natural sources is the only option to prepare samples for structural and functional studies. Zorman and co-workers, in our second contribution, provide an overview of recent advances in the production of multi-subunit membrane protein complexes and highlight recent achievements in membrane protein structural research brought about by state-of-the-art near-atomic resolution cryo-electron microscopy techniques. E. coli has been the dominant host cell for recombinant protein production. Nonetheless, eukaryotic expression systems, including yeasts, insect cells and mammalian cells, are increasingly gaining prominence in the field. The yeast species Pichia pastoris, is a well-established recombinant expression system for a number of applications, including the production of a range of different membrane proteins. Byrne reviews high-resolution structures that have been determined using this methylotroph as an expression host. Although it is not yet clear why P. pastoris is suited to producing such a wide range of membrane proteins, its ease of use and the availability of diverse tools that can be readily implemented in standard bioscience laboratories mean that it is likely to become an increasingly popular option in structural biology pipelines. The contribution by Columbus concludes the membrane protein section of this volume. In her overview of post-expression strategies, Columbus surveys the four most common biochemical approaches for the structural investigation of membrane proteins. Limited proteolysis has successfully aided structure determination of membrane proteins in many cases. Deglycosylation of membrane proteins following production and purification analysis has also facilitated membrane protein structure analysis. Moreover, chemical modifications, such as lysine methylation and cysteine alkylation, have proven their worth to facilitate crystallization of membrane proteins, as well as NMR investigations of membrane protein conformational sampling. Together these approaches have greatly facilitated the structure determination of more than 40 membrane proteins to date. It may be an advantage to produce a target protein in mammalian cells, especially if authentic post-translational modifications such as glycosylation are required for proper activity. Chinese Hamster Ovary (CHO) cells and Human Embryonic Kidney (HEK) 293 cell lines have emerged as excellent hosts for heterologous production. The generation of stable cell-lines is often an aspiration for synthesizing proteins expressed in mammalian cells, in particular if high volumetric yields are to be achieved. In his report, Buessow surveys recent structures of proteins produced using stable mammalian cells and summarizes both well-established and novel approaches to facilitate stable cell-line generation for structural biology applications. The ambition of many biologists is to observe a protein's structure in the native environment of the cell itself. Until recently, this seemed to be more of a dream than a reality. Advances in nuclear magnetic resonance (NMR) spectroscopy techniques, however, have now made possible the observation of mechanistic events at the molecular level of protein structure. Smith and colleagues, in an exciting contribution, review emerging ‘in-cell NMR’ techniques that demonstrate the potential to monitor biological activities by NMR in real time in native physiological environments. A current drawback of NMR as a structure determination tool derives from size limitations of the molecule under investigation and the structures of large proteins and their complexes are therefore typically intractable by NMR. A solution to this challenge is the use of selective isotope labeling of the target protein, which results in a marked reduction of the complexity of NMR spectra and allows dynamic processes even in very large proteins and even ribosomes to be investigated. Kerfah and co-workers introduce methyl-specific isotopic labeling as a molecular tool-box, and review its applications to the solution NMR analysis of large proteins. Tyagi and Lemke next examine single-molecule FRET and crosslinking following the co-translational incorporation of non-canonical amino acids (ncAAs); the goal here is to move beyond static snap-shots of proteins and their complexes and to observe them as dynamic entities. The encoding of ncAAs through codon-suppression technology allows biomolecules to be investigated with diverse structural biology methods. In their article, Tyagi and Lemke discuss these approaches and speculate on the design of improved host organisms for ‘integrative structural biology research’. Our volume concludes with two contributions that resolve particular bottlenecks in the protein structure determination pipeline. The contribution by Crepin and co-workers introduces the concept of polyproteins in contemporary structural biology. Polyproteins are widespread in nature. They represent long polypeptide chains in which individual smaller proteins with different biological function are covalently linked together. Highly specific proteases then tailor the polyprotein into its constituent proteins. Many viruses use polyproteins as a means of organizing their proteome. The concept of polyproteins has now been exploited successfully to produce hitherto inaccessible recombinant protein complexes. For instance, by means of a self-processing synthetic polyprotein, the influenza polymerase, a high-value drug target that had remained elusive for decades, has been produced, and its high-resolution structure determined. In the contribution by Desmyter and co-workers, a further, often imposing, bottleneck in high-resolution protein structure determination is addressed: The requirement to form stable three-dimensional crystal lattices that diffract incident X-ray radiation to high resolution. Nanobodies have proven to be uniquely useful as crystallization chaperones, to coax challenging targets into suitable crystal lattices. Desmyter and co-workers review the generation of nanobodies by immunization, and highlight the application of this powerful technology to the crystallography of important protein specimens including G protein-coupled receptors (GPCRs). Recombinant protein production has come a long way since Peter Lobban's hypothesis in the late 1960s, with recombinant proteins now a dominant force in structural biology. The contributions in this volume showcase an impressive array of inventive approaches that are being developed and implemented, ever increasing the scope of recombinant technology to facilitate the determination of elusive protein structures. Powerful new methods from synthetic biology are further accelerating progress. Structure determination is now reaching into the living cell with the ultimate goal of observing functional molecular architectures in action in their native physiological environment. We anticipate that even the most challenging protein assemblies will be tackled by recombinant technology in the near future.

Probabilistic DHP adaptive critic for nonlinear stochastic control systems

Following the recently developed algorithms for fully probabilistic control design for general dynamic stochastic systems (Herzallah & Káarnáy, 2011; Kárný, 1996), this paper presents the solution to the probabilistic dual heuristic programming (DHP) adaptive critic method (Herzallah & Káarnáy, 2011) and randomized control algorithm for stochastic nonlinear dynamical systems. The purpose of the randomized control input design is to make the joint probability density function of the closed loop system as close as possible to a predetermined ideal joint probability density function. This paper completes the previous work (Herzallah & Kárnáy, 2011; Kárný, 1996) by formulating and solving the fully probabilistic control design problem on the more general case of nonlinear stochastic discrete time systems. A simulated example is used to demonstrate the use of the algorithm and encouraging results have been obtained.

Stochastic control strategies and adaptive critic methods

Adaptive critic methods have common roots as generalizations of dynamic programming for neural reinforcement learning approaches. Since they approximate the dynamic programming solutions, they are potentially suitable for learning in noisy, nonlinear and nonstationary environments. In this study, a novel probabilistic dual heuristic programming (DHP) based adaptive critic controller is proposed. Distinct to current approaches, the proposed probabilistic (DHP) adaptive critic method takes uncertainties of forward model and inverse controller into consideration. Therefore, it is suitable for deterministic and stochastic control problems characterized by functional uncertainty. Theoretical development of the proposed method is validated by analytically evaluating the correct value of the cost function which satisfies the Bellman equation in a linear quadratic control problem. The target value of the critic network is then calculated and shown to be equal to the analytically derived correct value.

Efficient Control in Multistage Stochastic Optimization Problem

AMS subject classification: 90C31, 90A09, 49K15, 49L20.

A Stochastic Approach for Investigation Ultrafast Phenomena in Semiconductors

2002 Mathematics Subject Classification: 65C05

A Stochastic Control Approach to a Parabolic Equation, Reciprocal Processes

2000 Mathematics Subject Classi cation: 49L60, 60J60, 93E20.

Stability of the Inventory-Backorder Process in the (R; S) Inventory/Production Model

2000 Mathematics Subject Classification: 60G52, 90B30.

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations.

Stochastic calculations for fibre Raman amplifiers with randomly varying birefringence

For the first time for the model of real-world forward-pumped fibre Raman amplifier with the randomly varying birefringence, the stochastic calculations have been done numerically based on the Kloeden-Platen-Schurz algorithm. The results obtained for the averaged gain and gain fluctuations as a function of polarization mode dispersion (PMD) parameter agree quantitatively with the results of previously developed analytical model. Simultaneously, the direct numerical simulations demonstrate an increased stochastisation (maximum in averaged gain variation) within the region of the polarization mode dispersion parameter of 0.1÷0.3 ps/km1/2. The results give an insight into margins of applicability of a generic multi-scale technique widely used to derive coupled Manakov equations and allow generalizing analytic model with accounting for pump depletion, group-delay dispersion and Kerr-nonlinearity that is of great interest for development of the high-transmission-rates optical networks.

A cell-permeable tool for analysing APP intracellular domain function and manipulation of PIKfyve activity

The mechanisms for regulating PIKfyve complex activity are currently emerging. The PIKfyve complex, consisting of the phosphoinositide kinase PIKfyve (also known as FAB1), VAC14 and FIG4, is required for the production of phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2). PIKfyve function is required for homeostasis of the endo/lysosomal system and is crucially implicated in neuronal function and integrity, as loss of function mutations in the PIKfyve complex lead to neurodegeneration in mouse models and human patients. Our recent work has shown that the intracellular domain of the Amyloid Precursor Protein (APP), a molecule central to the aetiology of Alzheimer's disease binds to VAC14 and enhances PIKfyve function. Here we utilise this recent advance to create an easy-to-use tool for increasing PIKfyve activity in cells. We fused APP's intracellular domain (AICD) to the HIV TAT domain, a cell permeable peptide allowing proteins to penetrate cells. The resultant TAT-AICD fusion protein is cell permeable and triggers an increase of PI(3,5)P2. Using the PI(3,5)P2 specific GFP-ML1Nx2 probe we show that cell-permeable AICD alters PI(3,5)P2 dynamics. TAT-AICD also provides partial protection from pharmacological inhibition of PIKfyve. All three lines of evidence show that the APP intracellular domain activates the PIKfyve complex in cells, a finding that is important for our understanding of the mechanism of neurodegeneration in Alzheimer's disease.

Munkaszervezés a lean termelésben – mit magyaráznak a termelésmenedzsment koncepciók = Work organization in lean production – what production concepts explain

A tanulmány a lean termelés munkaszervezését három termelésmenedzsment koncepció segítségével vizsgálja. Az egyes koncepciók a szervezet eltérő metszeteit érintik: (1) a termék-folyamat mátrix (Hayes és Wheelwright, 1979) a termék és a folyamat jellemzőit helyezi középpontba. A lean hatására a szervezet a mátrixban a nagyobb választék és a folyamat alapú működés (nagyobb függőség) irányába mozdul el. Az elmozdulást üzemi szinten a magas elkötelezettségű munkavégzési rendszer gyakorlatainak bevezetése kíséri, mivel azok támogatják a rugalmas működést, a gyors kommunikációt és problémamegoldást. Az elmozdulás „minősége” és így a munkaszervezési gyakorlatok használata (mélyég, száma, munkavállalók bevonása) nagyban függ a termelési stratégiától és a lean érettségtől. (2) A termelési stratégia szakaszai (Wheelwright és Hayes, 1985) a termelés üzleti stratégiában játszott szerepét elemzik. A lean termelés összeegyeztethető a termelési stratégia harmadik szakaszának „command és control” szemléletmódjával. Az ilyen lean termelők költégfókuszúak, a hagyományos munkaerőképben gondolkodnak és körükben kevésbé jellemző az új emberi erőforrás gyakorlatok használata. A lean termelés adaptálása ösztönözheti a vállalatokat a termelési stratégia negyedik szintje felé. A negyedik szint a bevonásra, problémamegoldásra és tanulásra épít, amely megfelel a lean „emberek tisztelete” pillérének. (3) A lean érettségi modell (Hines és társai, 2004) a lean szervezeten belüli elmélyülését és terjedését mutatja be. A lean utazás során a vállalatok az eszköz alapú megközelítéstől a komplex értékrendszerben gondolkodó lean szervezet felé haladnak. A technikai tudásanyag egyre szélesebb körűvé válik, ami rávilágít a tudásátadás (személyek közöttire, de akár struktúrákba, folyamatokba építése is) képességének jelentőségére. Az emberi erőforrás gyakorlatok folyamatosan jelennek meg. De csak a legfejlettebb szakasz, a lean tanuló szervezet megjelenése teszi valóban szükségessé a munkavállalói kép újragondolását is. = This paper examines work organization in lean production with the help of three production concepts. These concepts embrace different dimensions of the organization: (1) the product-process matrix (Hayes and Wheelwright, 1979) is about product and process characteristics. Due to the lean the organization shifts within the matrix – towards higher variability and flow (higher level of interdependencies). On the shop floor the shift is accompanied by the introduction of high commitment work system’s practices, since those support flexible operations, fast communication and problem-solving. The „quality” of the shift and hence the application of these work practices (number of practices, their embeddeness, employee involvement) highly depends on manufacturing strategy and lean maturity. (2) The concept of stages of manufacturing strategy (Wheelwright and Hayes, 1985) analyzes the role of the manufacturing function in the business strategy. Lean production is compatible with the „command and control” approach of the third stage of manufacturing strategy. These lean producers are cost-driven, they have the traditional approach of employees and apply new work organization practices to a less extent. However, the implementation of lean production may drive these companies to the fourth stage. The fourth stage of manufacturing strategy is based on employee involvement, problem-solving and learning. This stage is in full accordance with the „respect for people” pillar of lean production. (3) Lean maturity (Hines et al., 2004) shows the path how lean management deepens and expands within an organization. During the lean journey, companies progress from the tool-based approach to the complex lean value system. The technical knowledge of lean becomes more and more comprehensive and it points out the crucial importance of knowledge conversion capabilities (intrapersonal or even how to build knowledge into structures, processes). Work organization practices constantly appear with the progress, but the review of the traditional approach of employees is only essential at the most advanced stage, when an organization becomes lean learning organization.