Creating lift versus building the base:current trends in marketing dynamics

Markets are dynamic by nature, and marketing efforts can be directed to stimulate, reduce, or to utilize these dynamics. The field of marketing dynamics aims at modeling the effects of marketing actions and policies on short-term performance (“lift”) and on long-term performance (“base”). One of the core questions within this field is: “How do marketing efforts affect outcome metrics such as revenues, profits, or shareholder value over time?” Developments in statistical modeling and new data sources allow marketing scientists to provide increasingly comprehensive answers to this question. We present an outlook on developments in modeling marketing dynamics and specify research directions.

Modeling of spectral and statistical properties of a random distributed feedback fiber laser

For the first time we report full numerical NLSE-based modeling of generation properties of random distributed feedback fiber laser based on Rayleigh scattering. The model which takes into account the random backscattering via its average strength only describes well power and spectral properties of random DFB fiber lasers. The influence of dispersion and nonlinearity on spectral and statistical properties is investigated. The evidence of non-gaussian intensity statistics is found. © 2013 Optical Society of America.

Characterization of the structure of RAMP1 by mutagenesis and molecular modeling

Receptor activity modifying proteins (RAMPs) are a family of single-pass transmembrane proteins that dimerize with G-protein-coupled receptors. They may alter the ligand recognition properties of the receptors (particularly for the calcitonin receptor-like receptor, CLR). Very little structural information is available about RAMPs. Here, an ab initio model has been generated for the extracellular domain of RAMP1. The disulfide bond arrangement (Cys 27-Cys82, Cys40-Cys72, and Cys 57-Cys104) was determined by site-directed mutagenesis. The secondary structure (a-helices from residues 29-51, 60-80, and 87-100) was established from a consensus of predictive routines. Using these constraints, an assemblage of 25,000 structures was constructed and these were ranked using an all-atom statistical potential. The best 1000 conformations were energy minimized. The lowest scoring model was refined by molecular dynamics simulation. To validate our strategy, the same methods were applied to three proteins of known structure; PDB:1HP8, PDB:1V54 chain H (residues 21-85), and PDB:1T0P. When compared to the crystal structures, the models had root mean-square deviations of 3.8 Å, 4.1 Å, and 4.0 Å, respectively. The model of RAMP1 suggested that Phe93, Tyr 100, and Phe101 form a binding interface for CLR, whereas Trp74 and Phe92 may interact with ligands that bind to the CLR/RAMP1 heterodimer. © 2006 by the Biophysical Society.

Multilevel analyses in marketing research:differentiating analytical outcomes

Marketing scholars are increasingly recognizing the importance of investigating phenomena at multiple levels. However, the analyses methods that are currently dominant within marketing may not be appropriate to dealing with multilevel or nested data structures. We identify the state of contemporary multilevel marketing research, finding that typical empirical approaches within marketing research may be less effective at explicitly taking account of multilevel data structures than those in other organizational disciplines. A Monte Carlo simulation, based on results from a previously published marketing study, demonstrates that different approaches to analysis of the same data can result in very different results (both in terms of power and effect size). The implication is that marketing scholars should be cautious when analyzing multilevel or other grouped data, and we provide a discussion and introduction to the use of hierarchical linear modeling for this purpose.

Network optimisation - A statistical physics perspective

Inference and optimisation of real-value edge variables in sparse graphs are studied using the tree based Bethe approximation optimisation algorithms. Equilibrium states of general energy functions involving a large set of real edge-variables that interact at the network nodes are obtained for networks in various cases. These include different cost functions, connectivity values, constraints on the edge bandwidth and the case of multiclass optimisation.

Control of second-life hybrid battery energy storage system based on modular boost-multilevel buck converter

To fully utilize second-life batteries on the grid system, a hybrid battery scheme needs to be considered for several reasons: the uncertainty over using a single source supply chain for second-life batteries, the differences in evolving battery chemistry and battery configuration by different suppliers to strive for greater power levels, and the uncertainty of degradation within a second-life battery. Therefore, these hybrid battery systems could have widely different module voltage, capacity, and initial state of charge and state of health. In order to suitably integrate and control these widely different batteries, a suitable multimodular converter topology and an associated control structure are required. This paper addresses these issues proposing a modular boost-multilevel buck converter based topology to integrate these hybrid second-life batteries to a grid-tie inverter. Thereafter, a suitable module-based distributed control architecture is introduced to independently utilize each converter module according to its characteristics. The proposed converter and control architecture are found to be flexible enough to integrate widely different batteries to an inverter dc link. Modeling, analysis, and experimental validation are performed on a single-phase modular hybrid battery energy storage system prototype to understand the operation of the control strategy with different hybrid battery configurations.

Impact of high-performance work systems on individual- and branch-level performance:test of a multilevel model of intermediate linkages

We proposed and tested a multilevel model, underpinned by empowerment theory, that examines the processes linking high-performance work systems (HPWS) and performance outcomes at the individual and organizational levels of analyses. Data were obtained from 37 branches of 2 banking institutions in Ghana. Results of hierarchical regression analysis revealed that branch-level HPWS relates to empowerment climate. Additionally, results of hierarchical linear modeling that examined the hypothesized cross-level relationships revealed 3 salient findings. First, experienced HPWS and empowerment climate partially mediate the influence of branch-level HPWS on psychological empowerment. Second, psychological empowerment partially mediates the influence of empowerment climate and experienced HPWS on service performance. Third, service orientation moderates the psychological empowerment-service performance relationship such that the relationship is stronger for those high rather than low in service orientation. Last, ordinary least squares regression results revealed that branch-level HPWS influences branch-level market performance through cross-level and individual-level influences on service performance that emerges at the branch level as aggregated service performance. © 2011 American Psychological Association.

High-throughput manufacturing of size-tuned liposomes by a new microfluidics method using enhanced statistical tools for characterization

Microfluidics has recently emerged as a new method of manufacturing liposomes, which allows for reproducible mixing in miliseconds on the nanoliter scale. Here we investigate microfluidics-based manufacturing of liposomes. The aim of these studies was to assess the parameters in a microfluidic process by varying the total flow rate (TFR) and the flow rate ratio (FRR) of the solvent and aqueous phases. Design of experiment and multivariate data analysis were used for increased process understanding and development of predictive and correlative models. High FRR lead to the bottom-up synthesis of liposomes, with a strong correlation with vesicle size, demonstrating the ability to in-process control liposomes size; the resulting liposome size correlated with the FRR in the microfluidics process, with liposomes of 50 nm being reproducibly manufactured. Furthermore, we demonstrate the potential of a high throughput manufacturing of liposomes using microfluidics with a four-fold increase in the volumetric flow rate, maintaining liposome characteristics. The efficacy of these liposomes was demonstrated in transfection studies and was modelled using predictive modeling. Mathematical modelling identified FRR as the key variable in the microfluidic process, with the highest impact on liposome size, polydispersity and transfection efficiency. This study demonstrates microfluidics as a robust and high-throughput method for the scalable and highly reproducible manufacture of size-controlled liposomes. Furthermore, the application of statistically based process control increases understanding and allows for the generation of a design-space for controlled particle characteristics.

Design of multilevel amplitude regenerative system

We propose a scheme for multilevel (nine or more) amplitude regeneration based on a nonlinear optical loop mirror (NOLM) and demonstrate through numerical modeling its efficiency and cascadability on circular 16-, 64-, and 256- symbol constellations. We show that the amplitude noise is efficiently suppressed. The design is flexible and enables variation of the number of levels and their positioning. The scheme is compatible with phase regenerators. Also, compared to the traditional single-NOLM configuration scheme, new features, such as reduced and sign-varied power-dependent phase shift, are available. The model is simple to implement, as it requires only two couplers in addition to the traditional NOLM, and offers a vast range of optimization parameters. © 2014 Optical Society of America.

Leveraging employee creativity through high performance work systems:a multilevel perspective

Research has looked at single rather than a configuration of human resource management (HRM) practices to influence creativity so it is not yet clear how these practices synergistically facilitate creativity and organisational performance. I address this significant but unanswered question in a three-part study. In Study 1, I develop a high performance work system (HPWS) for creativity scale. I use Study 2 sample to test the validity of the new scale. In Study 3, I test a multilevel model of the intervening processes through which branch HPWS for creativity influences creativity and branch performance. Specifically, at the branch level, I draw on social context theory and hypothesise that branch HPWS for creativity relates to climate for creativity which, in turn, leads to creativity, and ultimately, to profit. Furthermore, I hypothesise environmental dynamism as a boundary condition of the creativity-profit relationship. At the individual level, I hypothesise a cross-level effect of branch HPWS for creativity on employee-perceived HPWS. I draw on self-determination theory and argue that perceived HPWS for creativity relate to need satisfaction and the psychological pathways of intrinsic motivation and creative process engagement to predict creativity. I also hypothesise climate for creativity as a cross-level moderator of the intrinsic motivation-creativity and creative process engagement-creativity relationships. Results of hierarchical linear modeling (HLM) indicate that ten out of the fifteen hypotheses were supported. The findings of this study respond to calls for HPWS to be designed around a strategic focus by developing and providing initial validity evidence of an HPWS for creativity scale. The results reveal the underlying mechanisms through which HPWS for creativity simultaneously influences individual and branch creativity leading to profit. Lastly, results indicate environmental dynamism to be an important boundary condition of the creativity-profit relationship and climate for creativity as a cross-level moderator of the creative process engagement-creativity.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. 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 freely available online (http://www.jenner.ac.uk/MHCPred).