Energy forward price prediction with a hybrid adaptive model

This paper presents a forecasting technique for forward electricity/gas prices, one day ahead. This technique combines a Kalman filter (KF) and a generalised autoregressive conditional heteroschedasticity (GARCH) model (often used in financial forecasting). The GARCH model is used to compute next value of a time series. The KF updates parameters of the GARCH model when the new observation is available. This technique is applied to real data from the UK energy markets to evaluate its performance. The results show that the forecasting accuracy is improved significantly by using this hybrid model. The methodology can be also applied to forecasting market clearing prices and electricity/gas loads.

Improved yields of full-length functional human FGF1 can be achieved using the methylotrophic yeast Pichia pastoris

We have produced human fibroblast growth factor 1 (hFGF1) in the methylotrophic yeast Pichia pastoris in order to obtain the large amounts of active protein required for subsequent functional and structural characterization. Four constructs were made to examine both intracellular and secreted expression, with variations in the location of the His6 tag at either end of the peptide. hFGF1 could be produced from all four constructs in shake flasks, but production was optimized by growing only the highest-yielding of these strains, which produced hFGF1 intracellularly, under tightly controlled conditions in a 3 L fermentor. One hundred and eight milligrams of pure protein was achieved per liter culture (corresponding to 0.68 mg of protein per gram of wet cells), the function of which was verified using NIH 3T3 cell cultures. This is a 30-fold improvement over previously reported yields of full-length hFGF1. © 2006 Elsevier Inc. All rights reserved.

A hybrid genetic algorithm for the multi-depot vehicle routing problem

The distribution of finished products from depots to customers is a practical and challenging problem in logistics management. Better routing and scheduling decisions can result in higher level of customer satisfaction because more customers can be served in a shorter time. The distribution problem is generally formulated as the vehicle routing problem (VRP). Nevertheless, there is a rigid assumption that there is only one depot. In cases, for instance, where a logistics company has more than one depot, the VRP is not suitable. To resolve this limitation, this paper focuses on the VRP with multiple depots, or multi-depot VRP (MDVRP). The MDVRP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To deal with the problem efficiently, two hybrid genetic algorithms (HGAs) are developed in this paper. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method and the nearest neighbor heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different problem sizes. It is proved that the performance of HGA2 is superior to that of HGA1 in terms of the total delivery time.

Altering the ribosomal subunit ratio in yeast maximizes recombinant protein yield

Background The production of high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences that has yet to be addressed in a truly rational manner. Typically eukaryotic protein production experiments have relied on varying expression construct cassettes such as promoters and tags, or culture process parameters such as pH, temperature and aeration to enhance yields. These approaches require repeated rounds of trial-and-error optimization and cannot provide a mechanistic insight into the biology of recombinant protein production. We published an early transcriptome analysis that identified genes implicated in successful membrane protein production experiments in yeast. While there has been a subsequent explosion in such analyses in a range of production organisms, no one has yet exploited the genes identified. The aim of this study was to use the results of our previous comparative transcriptome analysis to engineer improved yeast strains and thereby gain an understanding of the mechanisms involved in high-yielding protein production hosts. Results We show that tuning BMS1 transcript levels in a doxycycline-dependent manner resulted in optimized yields of functional membrane and soluble protein targets. Online flow microcalorimetry demonstrated that there had been a substantial metabolic change to cells cultured under high-yielding conditions, and in particular that high yielding cells were more metabolically efficient. Polysome profiling showed that the key molecular event contributing to this metabolically efficient, high-yielding phenotype is a perturbation of the ratio of 60S to 40S ribosomal subunits from approximately 1:1 to 2:1, and correspondingly of 25S:18S ratios from 2:1 to 3:1. This result is consistent with the role of the gene product of BMS1 in ribosome biogenesis. Conclusion This work demonstrates the power of a rational approach to recombinant protein production by using the results of transcriptome analysis to engineer improved strains, thereby revealing the underlying biological events involved.

Modelling and control of a hybrid stepping motor

The integration of a microprocessor and a medium power stepper motor in one control system brings together two quite different disciplines. Various methods of interfacing are examined and the problems involved in both hardware and software manipulation are investigated. Microprocessor open-loop control of the stepper motor is considered. The possible advantages of microprocessor closed-loop control are examined and the development of a system is detailed. The system uses position feedback to initiate each motor step. Results of the dynamic response of the system are presented and its performance discussed. Applications of the static torque characteristic of the stepper motor are considered followed by a review of methods of predicting the characteristic. This shows that accurate results are possible only when the effects of magnetic saturation are avoided or when the machine is available for magnetic circuit tests to be carried out. A new method of predicting the static torque characteristic is explained in detail. The method described uses the machine geometry and the magnetic characteristics of the iron types used in the machine. From this information the permeance of each iron component of the machine is calculated and by using the equivalent magnetic circuit of the machine, the total torque produced is predicted. It is shown how this new method is implemented on a digital computer and how the model may be used to investigate further aspects of the stepper motor in addition to the static torque.

Characterizing the hierarchical structures of bioactive sol-gel silicate glass and hybrid scaffolds for bone regeneration

Bone is the second most widely transplanted tissue after blood. Synthetic alternatives are needed that can reduce the need for transplants and regenerate bone by acting as active temporary templates for bone growth. Bioactive glasses are one of the most promising bone replacement/regeneration materials because they bond to existing bone, are degradable and stimulate new bone growth by the action of their dissolution products on cells. Sol-gel-derived bioactive glasses can be foamed to produce interconnected macropores suitable for tissue ingrowth, particularly cell migration and vascularization and cell penetration. The scaffolds fulfil many of the criteria of an ideal synthetic bone graft, but are not suitable for all bone defect sites because they are brittle. One strategy for improving toughness of the scaffolds without losing their other beneficial properties is to synthesize inorganic/organic hybrids. These hybrids have polymers introduced into the sol-gel process so that the organic and inorganic components interact at the molecular level, providing control over mechanical properties and degradation rates. However, a full understanding of how each feature or property of the glass and hybrid scaffolds affects cellular response is needed to optimize the materials and ensure long-term success and clinical products. This review focuses on the techniques that have been developed for characterizing the hierarchical structures of sol-gel glasses and hybrids, from atomicscale amorphous networks, through the covalent bonding between components in hybrids and nanoporosity, to quantifying open macroporous networks of the scaffolds. Methods for non-destructive in situ monitoring of degradation and bioactivity mechanisms of the materials are also included. © 2012 The Royal Society.

Analysis of the pore of the unusual major intrinsic protein channel, yeast Fps1p

Fps1p is a glycerol efflux channel from Saccharomyces cerevisiae. In this atypical major intrinsic protein neither of the signature NPA motifs of the family, which are part of the pore, is preserved. To understand the functional consequences of this feature, we analyzed the pseudo-NPA motifs of Fps1p by site-directed mutagenesis and assayed the resultant mutant proteins in vivo. In addition, we took advantage of the fact that the closest bacterial homolog of Fps1p, Escherichia coli GlpF, can be functionally expressed in yeast, thus enabling the analysis in yeast cells of mutations that make this typical major intrinsic protein more similar to Fps1p. We observed that mutations made in Fps1p to "restore" the signature NPA motifs did not substantially affect channel function. In contrast, when GlpF was mutated to resemble Fps1p, all mutants had reduced activity compared with wild type. We rationalized these data by constructing models of one GlpF mutant and of the transmembrane core of Fps1p. Our model predicts that the pore of Fps1p is more flexible than that of GlpF. We discuss the fact that this may accommodate the divergent NPA motifs of Fps1p and that the different pore structures of Fps1p and GlpF may reflect the physiological roles of the two glycerol facilitators.

The idea of the hybrid texts and translation:contact as conflict

Intercultural communication in the global environment frequently involves recourse to translation. This generates new phenomena which, in turn, raise new questions for translation theory and practice. This issue is concerned with the concept of the hybrid text as one of these phenomena. In this introductory chapter, a hybrid text is defined as: „a text that results from a translation process. It shows features that somehow seem ‘out of place'/‘strange'/‘unusual' for the receiving culture, i.e. the target culture”. It is important, however, to differentiate between the true hybrid, which is the result of positive authorial and/or translatorial decisions, and the inadequate text which exhibits features of translationese, resulting from a lack of competence. Textual, contextual and social features of hybrid texts are postulated (see discussion paper). These are the object of critical reflection in sub-sequent chapters, in relation to different genres. The potential of the hybrid text for translation research is explored.

Bridging large and small scales of water models using hybrid Molecular Dynamics/Fluctuating Hydrodynamics framework

This thesis presents a two-dimensional water model investigation and development of a multiscale method for the modelling of large systems, such as virus in water or peptide immersed in the solvent. We have implemented a two-dimensional ‘Mercedes Benz’ (MB) or BN2D water model using Molecular Dynamics. We have studied its dynamical and structural properties dependence on the model’s parameters. For the first time we derived formulas to calculate thermodynamic properties of the MB model in the microcanonical (NVE) ensemble. We also derived equations of motion in the isothermal–isobaric (NPT) ensemble. We have analysed the rotational degree of freedom of the model in both ensembles. We have developed and implemented a self-consistent multiscale method, which is able to communicate micro- and macro- scales. This multiscale method assumes, that matter consists of the two phases. One phase is related to micro- and the other to macroscale. We simulate the macro scale using Landau Lifshitz-Fluctuating Hydrodynamics, while we describe the microscale using Molecular Dynamics. We have demonstrated that the communication between the disparate scales is possible without introduction of fictitious interface or approximations which reduce the accuracy of the information exchange between the scales. We have investigated control parameters, which were introduced to control the contribution of each phases to the matter behaviour. We have shown, that microscales inherit dynamical properties of the macroscales and vice versa, depending on the concentration of each phase. We have shown, that Radial Distribution Function is not altered and velocity autocorrelation functions are gradually transformed, from Molecular Dynamics to Fluctuating Hydrodynamics description, when phase balance is changed. In this work we test our multiscale method for the liquid argon, BN2D and SPC/E water models. For the SPC/E water model we investigate microscale fluctuations which are computed using advanced mapping technique of the small scales to the large scales, which was developed by Voulgarakisand et. al.

Recombinant protein subunit vaccine synthesis in microbes:a role for yeast?

Objectives Recombinant protein subunit vaccines are formulated using protein antigens that have been synthesized in heterologous host cells. Several host cells are available for this purpose, ranging from Escherichia coli to mammalian cell lines. This article highlights the benefits of using yeast as the recombinant host. Key findings The yeast species, Saccharomyces cerevisiae and Pichia pastoris, have been used to optimize the functional yields of potential antigens for the development of subunit vaccines against a wide range of diseases caused by bacteria and viruses. Saccharomyces cerevisiae has also been used in the manufacture of 11 approved vaccines against hepatitis B virus and one against human papillomavirus; in both cases, the recombinant protein forms highly immunogenic virus-like particles. Summary Advances in our understanding of how a yeast cell responds to the metabolic load of producing recombinant proteins will allow us to identify host strains that have improved yield properties and enable the synthesis of more challenging antigens that cannot be produced in other systems. Yeasts therefore have the potential to become important host organisms for the production of recombinant antigens that can be used in the manufacture of subunit vaccines or in new vaccine development.

A multi-modular second life hybrid battery energy storage system for utility grid applications

The modern grid system or the smart grid is likely to be populated with multiple distributed energy sources, e.g. wind power, PV power, Plug-in Electric Vehicle (PEV). It will also include a variety of linear and nonlinear loads. The intermittent nature of renewable energies like PV, wind turbine and increased penetration of Electric Vehicle (EV) makes the stable operation of utility grid system challenging. In order to ensure a stable operation of the utility grid system and to support smart grid functionalities such as, fault ride-through, frequency response, reactive power support, and mitigation of power quality issues, an energy storage system (ESS) could play an important role. A fast acting bidirectional energy storage system which can rapidly provide and absorb power and/or VARs for a sufficient time is a potentially valuable tool to support this functionality. Battery energy storage systems (BESS) are one of a range suitable energy storage system because it can provide and absorb power for sufficient time as well as able to respond reasonably fast. Conventional BESS already exist on the grid system are made up primarily of new batteries. The cost of these batteries can be high which makes most BESS an expensive solution. In order to assist moving towards a low carbon economy and to reduce battery cost this work aims to research the opportunities for the re-use of batteries after their primary use in low and ultra-low carbon vehicles (EV/HEV) on the electricity grid system. This research aims to develop a new generation of second life battery energy storage systems (SLBESS) which could interface to the low/medium voltage network to provide necessary grid support in a reliable and in cost-effective manner. The reliability/performance of these batteries is not clear, but is almost certainly worse than a new battery. Manufacturers indicate that a mixture of gradual degradation and sudden failure are both possible and failure mechanisms are likely to be related to how hard the batteries were driven inside the vehicle. There are several figures from a number of sources including the DECC (Department of Energy and Climate Control) and Arup and Cenex reports indicate anything from 70,000 to 2.6 million electric and hybrid vehicles on the road by 2020. Once the vehicle battery has degraded to around 70-80% of its capacity it is considered to be at the end of its first life application. This leaves capacity available for a second life at a much cheaper cost than a new BESS Assuming a battery capability of around 5-18kWhr (MHEV 5kWh - BEV 18kWh battery) and approximate 10 year life span, this equates to a projection of battery storage capability available for second life of >1GWhrs by 2025. Moreover, each vehicle manufacturer has different specifications for battery chemistry, number and arrangement of battery cells, capacity, voltage, size etc. To enable research and investment in this area and to maximize the remaining life of these batteries, one of the design challenges is to combine these hybrid batteries into a grid-tie converter where their different performance characteristics, and parameter variation can be catered for and a hot swapping mechanism is available so that as a battery ends it second life, it can be replaced without affecting the overall system operation. This integration of either single types of batteries with vastly different performance capability or a hybrid battery system to a grid-tie 3 energy storage system is different to currently existing work on battery energy storage systems (BESS) which deals with a single type of battery with common characteristics. This thesis addresses and solves the power electronic design challenges in integrating second life hybrid batteries into a grid-tie energy storage unit for the first time. This study details a suitable multi-modular power electronic converter and its various switching strategies which can integrate widely different batteries to a grid-tie inverter irrespective of their characteristics, voltage levels and reliability. The proposed converter provides a high efficiency, enhanced control flexibility and has the capability to operate in different operational modes from the input to output. Designing an appropriate control system for this kind of hybrid battery storage system is also important because of the variation of battery types, differences in characteristics and different levels of degradations. This thesis proposes a generalised distributed power sharing strategy based on weighting function aims to optimally use a set of hybrid batteries according to their relative characteristics while providing the necessary grid support by distributing the power between the batteries. The strategy is adaptive in nature and varies as the individual battery characteristics change in real time as a result of degradation for example. A suitable bidirectional distributed control strategy or a module independent control technique has been developed corresponding to each mode of operation of the proposed modular converter. Stability is an important consideration in control of all power converters and as such this thesis investigates the control stability of the multi-modular converter in detailed. Many controllers use PI/PID based techniques with fixed control parameters. However, this is not found to be suitable from a stability point-of-view. Issues of control stability using this controller type under one of the operating modes has led to the development of an alternative adaptive and nonlinear Lyapunov based control for the modular power converter. Finally, a detailed simulation and experimental validation of the proposed power converter operation, power sharing strategy, proposed control structures and control stability issue have been undertaken using a grid connected laboratory based multi-modular hybrid battery energy storage system prototype. The experimental validation has demonstrated the feasibility of this new energy storage system operation for use in future grid applications.

Control of cascaded DC-DC converter based hybrid battery energy storage systems - Part II:Lyapunov approach

A cascaded DC-DC boost converter is one of the ways to integrate hybrid battery types within a grid-tie inverter. Due to the presence of different battery parameters within the system such as, state-of-charge and/or capacity, a module based distributed power sharing strategy may be used. To implement this sharing strategy, the desired control reference for each module voltage/current control loop needs to be dynamically varied according to these battery parameters. This can cause stability problem within the cascaded converters due to relative battery parameter variations when using the conventional PI control approach. This paper proposes a new control method based on Lyapunov Functions to eliminate this issue. The proposed solution provides a global asymptotic stability at a module level avoiding any instability issue due to parameter variations. A detailed analysis and design of the nonlinear control structure are presented under the distributed sharing control. At last thorough experimental investigations are shown to prove the effectiveness of the proposed control under grid-tie conditions.

HYBRID TCP/UDP video transport for H.264/AVC content delivery in burst loss networks

In this paper we propose a hybrid TCP/UDP transport, specifically for H.264/AVC encoded video, as a compromise between the delay-prone TCP and the loss-prone UDP. When implementing the hybrid approach, we argue that the playback at the receiver often need not be 100% perfect, provided that a certain level of quality is assured. Reliable TCP is used to transmit and guarantee delivery of the most important packets. This allows use of additional features in the H.264/AVC standard which simultaneously provide an enhanced playback quality, in addition to a reduction in throughput. These benefits are demonstrated through experimental results using a test-bed to emulate the hybrid proposal. We compare the proposed system with other protection methods, such as FEC, and in one case show that for the same bandwidth overhead, FEC is unable to match the performance of the hybrid system in terms of playback quality. Furthermore, we measure the delay associated with our approach, and examine its potential for use as an alternative to the conventional methods of transporting video by either TCP or UDP alone. © 2011 IEEE.

Membrane protein production in the Yeast, S. cerevisiae

The first crystal structures of recombinant mammalian membrane proteins were solved in 2005 using protein that had been produced in yeast cells. One of these, the rabbit Ca2+-ATPase SERCA1a, was synthesized in Saccharomyces cerevisiae. All host systems have their specific advantages and disadvantages, but yeast has remained a consistently popular choice in the eukaryotic membrane protein field because it is quick, easy and cheap to culture, whilst being able to post-translationally process eukaryotic membrane proteins. Very recent structures of recombinant membrane proteins produced in S. cerevisiae include those of the Arabidopsis thaliana NRT1.1 nitrate transporter and the fungal plant pathogen lipid scramblase, TMEM16. This chapter provides an overview of the methodological approaches underpinning these successes.

Collaborative filtering and deep learning based hybrid recommendation for cold start problem

Recommender systems (RS) are used by many social networking applications and online e-commercial services. Collaborative filtering (CF) is one of the most popular approaches used for RS. However traditional CF approach suffers from sparsity and cold start problems. In this paper, we propose a hybrid recommendation model to address the cold start problem, which explores the item content features learned from a deep learning neural network and applies them to the timeSVD++ CF model. Extensive experiments are run on a large Netflix rating dataset for movies. Experiment results show that the proposed hybrid recommendation model provides a good prediction for cold start items, and performs better than four existing recommendation models for rating of non-cold start items.