Customer participation and service outcomes: Mediating role of task-related affective well-being

This paper contributes to transformative service research by drawing on self-determination, elicitation of emotions framework, and feelings-as-information theories to explore how customer participation, task-related affective well-being, customer knowledge, task complexity, and service outcomes relate with each other. Design/methodology/approach-A synthesis of relevant literature on customer participation and customer well-being reveals a conceptual model with eleven testable propositions. Findings-The conceptual model shows that task-related affective well-being mediates the link between customer participation and service outcomes. Moreover, customer knowledge and task complexity moderate these links. Research limitations/implications-An empirically testable conceptual model models the roles of task-related affective well-being, customer knowledge and task complexity in the process by which customer participation influences service outcomes. Practical implications-Service managers can use the model to design services based on the effects of different types of customer participation on task-related affective well-being. Originality/value-This paper is one of the first to study the mediating role of task-related affective well-being in the relationship between customer participation and service outcomes. It does so by revealing the differential impact various types of participation have on service outcomes and the moderating role of customer knowledge and task complexity

Physical-vapor-deposited metal oxide thin films for pH sensing applications: Last decade of research progress

In the last several decades, metal oxide thin films have attracted significant attention for the development of various existing and emerging technological applications, including pH sensors. The mandate for consistent and precise pH sensing techniques has been increasing across various fields, including environmental monitoring, biotechnology, food and agricultural industries, and medical diagnostics. Metal oxide thin films grown using physical vapor deposition (PVD) with precise control over film thickness, composition, and morphology are beneficial for pH sensing applications such as enhancing pH sensitivity and stability, quicker response, repeatability, and compatibility with miniaturization. Various PVD techniques, including sputtering, evaporation, and ion beam deposition, used to fabricate thin films for tailoring materials’ properties for the advanced design and development of high-performing pH sensors, have been explored worldwide by many research groups. In addition, various thin film materials have also been investigated, including metal oxides, nitrides, and nanostructured films, to make very robust pH sensing electrodes with higher pH sensing performance. The development of novel materials and structures has enabled higher sensitivity, improved selectivity, and enhanced durability in harsh pH environments. The last decade has witnessed significant advancements in PVD thin films for pH sensing applications. The combination of precise film deposition techniques, novel materials, and surface functionalization strategies has led to improved pH sensing performance, making PVD thin films a promising choice for future pH sensing technologies

Unusual Stokes V profiles during flaring activity of a delta sunspot

We analyze a set of full Stokes profile observations of the flaring active region NOAA 10808 recorded with the Vector-Spectromagnetograph (VSM) of the SOLIS facility. We aim to quantify transient and permanent changes in the magnetic field and velocity field. The results are put in context with MDI magnetograms and reconstructed RHESSI X-ray images. We find signs of restructuring of the photospheric magnetic field during the flare close to the polarity inversion line (PIL) at the flaring site. At two locations in the umbra we encounter strong fields (approx. 3 kG), as inferred from the Stokes I profiles which, however, exhibit a low polarization signal. During the flare we observe in addition asymmetric Stokes V profiles at one of these sites. The asymmetric Stokes V profiles appear co-spatial and co-temporal with a strong apparent polarity reversal observed in MDI-magnetograms and a chromospheric hard X-ray source. The two-component atmosphere fits of the asymmetric Stokes profiles result in line-of-sight velocity differences in the range of approx. 12km/s to 14 km/s between the two components in the photosphere. Another possibility is that local atmospheric heating is causing the observed asymmetric Stokes V profile shape. In either case our analysis shows that a very localized patch of approx. 5 arcsec in the photospheric umbra, co-spatial with a flare footpoint, exhibits a sub-resolution fine structure.Comment: 13 pages, 10 figures, 1 tabl

A combined model reduction algorithm for controlled biochemical systems

Background: Systems Biology continues to produce increasingly large models of complex biochemical reaction networks. In applications requiring, for example, parameter estimation, the use of agent-based modelling approaches, or real-time simulation, this growing model complexity can present a significant hurdle. Often, however, not all portions of a model are of equal interest in a given setting. In such situations methods of model reduction offer one possible approach for addressing the issue of complexity by seeking to eliminate those portions of a pathway that can be shown to have the least effect upon the properties of interest. Methods: In this paper a model reduction algorithm bringing together the complementary aspects of proper lumping and empirical balanced truncation is presented. Additional contributions include the development of a criterion for the selection of state-variable elimination via conservation analysis and use of an ‘averaged’ lumping inverse. This combined algorithm is highly automatable and of particular applicability in the context of ‘controlled’ biochemical networks. Results: The algorithm is demonstrated here via application to two examples; an 11 dimensional model of bacterial chemotaxis in Escherichia coli and a 99 dimensional model of extracellular regulatory kinase activation (ERK) mediated via the epidermal growth factor (EGF) and nerve growth factor (NGF) receptor pathways. In the case of the chemotaxis model the algorithm was able to reduce the model to 2 state-variables producing a maximal relative error between the dynamics of the original and reduced models of only 2.8% whilst yielding a 26 fold speed up in simulation time. For the ERK activation model the algorithm was able to reduce the system to 7 state-variables, incurring a maximal relative error of 4.8%, and producing an approximately 10 fold speed up in the rate of simulation. Indices of controllability and observability are additionally developed and demonstrated throughout the paper. These provide insight into the relative importance of individual reactants in mediating a biochemical system’s input-output response even for highly complex networks. Conclusions: Through application, this paper demonstrates that combined model reduction methods can produce a significant simplification of complex Systems Biology models whilst retaining a high degree of predictive accuracy. In particular, it is shown that by combining the methods of proper lumping and empirical balanced truncation it is often possible to produce more accurate reductions than can be obtained by the use of either method in isolation

A Dual Receptor Crosstalk Model of G-Protein-Coupled Signal Transduction

Macrophage cells that are stimulated by two different ligands that bind to G-protein-coupled receptors (GPCRs) usually respond as if the stimulus effects are additive, but for a minority of ligand combinations the response is synergistic. The G-protein-coupled receptor system integrates signaling cues from the environment to actuate cell morphology, gene expression, ion homeostasis, and other physiological states. We analyze the effects of the two signaling molecules complement factors 5a (C5a) and uridine diphosphate (UDP) on the intracellular second messenger calcium to elucidate the principles that govern the processing of multiple signals by GPCRs. We have developed a formal hypothesis, in the form of a kinetic model, for the mechanism of action of this GPCR signal transduction system using data obtained from RAW264.7 macrophage cells. Bayesian statistical methods are employed to represent uncertainty in both data and model parameters and formally tie the model to experimental data. When the model is also used as a tool in the design of experiments, it predicts a synergistic region in the calcium peak height dose response that results when cells are simultaneously stimulated by C5a and UDP. An analysis of the model reveals a potential mechanism for crosstalk between the Gαi-coupled C5a receptor and the Gαq-coupled UDP receptor signaling systems that results in synergistic calcium release

Dark Matter Search Results from the PICO-60C(3)F(8) Bubble Chamber

[EN] New results are reported from the operation of the PICO-60 dark matter detector, a bubble chamber filled with 52 kg of C3F8 located in the SNOLAB underground laboratory. As in previous PICO bubble chambers, PICO-60 C3F8 exhibits excellent electron recoil and alpha decay rejection, and the observed multiple-scattering neutron rate indicates a single-scatter neutron background of less than one event per month. A blind analysis of an efficiency-corrected 1167-kg day exposure at a 3.3-keV thermodynamic threshold reveals no single-scattering nuclear recoil candidates, consistent with the predicted background. These results set the most stringent direct-detection constraint to date on the weakly interacting massive particle (WIMP)-proton spin-dependent cross section at 3.4 x 10(-41) cm(2) for a 30-GeVc(-2) WIMP, more than 1 order of magnitude improvement from previous PICO results.The PICO Collaboration wishes to thank SNOLAB and its staff for support through underground space, logistical, and technical services. SNOLAB operations are supported by the Canada Foundation for Innovation and the Province of Ontario Ministry of Research and Innovation, with underground access provided by Vale at the Creighton mine site. We are grateful to Kristian Hahn and Stanislava Sevova of Northwestern University and Bjorn Penning of the University of Bristol for their assistance and useful discussion. We wish to acknowledge the support of the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canada Foundation for Innovation (CFI) for funding. We acknowledge the support from National Science Foundation (NSF) (Grants No. 0919526, No. 1506337, No. 1242637, and No. 1205987). We acknowledge that this work is supported by the U.S. Department of Energy (DOE) Office of Science, Office of High Energy Physics (under Award No. DE-SC-0012161), by a DOE Office of Science Graduate Student Research (SCGSR) award, by Direccion General Asuntos del Personal Academico, Universidad Nacional Autonoma de Mexico (DGAPA-UNAM) through the grant Programa de Apoyo a Proyectos de Investigacion e Innovacion Tecnologica (PAPIIT) No. IA100316 and by Consejo Nacional de Ciencia y Tecnologia (CONACyT) (Mexico) through Grant No. 252167, by the Department of Atomic Energy (DAE), the Government of India, under the Center of AstroParticle Physics II project (CAPP-II) at Saha Institute of Nuclear Physics (SINP), by the Czech Ministry of Education, Youth and Sports (Grant No. LM2015072), and by the Spanish Ministerio de Economia y Competitividad, Consolider MultiDark (Grant No. CSD2009-00064). This work is partially supported by the Kavli Institute for Cosmological Physics at the University of Chicago through NSF Grant No. 1125897, and an endowment from the Kavli Foundation and its founder Fred Kavli. We also wish to acknowledge the support from Fermi National Accelerator Laboratory under Contract No. De-AC02-07CH11359, and Pacific Northwest National Laboratory, which is operated by Battelle for the U.S. Department of Energy under Contract No. DE-AC05-76RL01830. We also thank Compute Canada and the Center for Advanced Computing, ACENET, Calcul Quebec, Compute Ontario, and WestGrid for the computational support.Amole, C.; Ardid Ramírez, M.; Arnquist, I.; Asner, DM.; Baxter, D.; Behnke, E.; Bhattacharjee, P.... (2017). Dark Matter Search Results from the PICO-60C(3)F(8) Bubble Chamber. Physical Review Letters. 118(25). https://doi.org/10.1103/PhysRevLett.118.251301S11825Olive, K. A. (2014). Review of Particle Physics. 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Methods of model reduction for large-scale biological systems: a survey of current methods and trends

Complex models of biochemical reaction systems have become increasingly common in the systems biology literature. The complexity of such models can present a number of obstacles for their practical use, often making problems difficult to intuit or computationally intractable. Methods of model reduction can be employed to alleviate the issue of complexity by seeking to eliminate those portions of a reaction network that have little or no effect upon the outcomes of interest, hence yielding simplified systems that retain an accurate predictive capacity. This review paper seeks to provide a brief overview of a range of such methods and their application in the context of biochemical reaction network models. To achieve this, we provide a brief mathematical account of the main methods including timescale exploitation approaches, reduction via sensitivity analysis, optimisation methods, lumping, and singular value decomposition-based approaches. Methods are reviewed in the context of large-scale systems biology type models, and future areas of research are briefly discussed

Genome-wide association study reveals novel genetic loci:a new polygenic risk score for mitral valve prolapse

AIMS: Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder. METHODS AND RESULTS: We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors. CONCLUSION: We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-beta signalling molecules and spectrin beta. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention. KEY QUESTION: Expand our understanding of the genetic basis for mitral valve prolapse (MVP). Uncover relevant pathways and target genes for MVP pathophysiology. Leverage genetic data for MVP risk prediction. KEY FINDING: Sixteen genetic loci were significantly associated with MVP, including 13 novel loci. Interesting target genes at these loci included LTBP2, TGFB2, ALKP3, BAG3, RBM20, and SPTBN1. A risk score including clinical factors and a polygenic risk score, performed best at predicting MVP, with an area under the receiver operating characteristics curve of 0.677. TAKE-HOME MESSAGE: Mitral valve prolapse has a polygenic basis: many genetic variants cumulatively influence pre-disposition for disease. Disease risk may be modulated via changes to transforming growth factor-beta signalling, the cytoskeleton, as well as cardiomyopathy pathways. Polygenic risk scores could enhance the MVP risk prediction

Interstitial fluid: the overlooked component of the tumor microenvironment?

Background: The interstitium, situated between the blood and lymph vessels and the cells, consists of a solid or matrix phase and a fluid phase, together constituting the tissue microenvironment. Here we focus on the interstitial fluid phase of tumors, i.e., the fluid bathing the tumor and stromal cells. Novel knowledge on this compartment may provide important insight into how tumors develop and how they respond to therapy. Results: We discuss available techniques for interstitial fluid isolation and implications of recent findings with respect to transcapillary fluid balance and uptake of macromolecular therapeutic agents. By the development of new methods it is emerging that local gradients exist in signaling substances from neoplastic tissue to plasma. Such gradients may provide new insight into the biology of tumors and mechanistic aspects linked to therapy. The emergence of sensitive proteomic technologies has made the interstitial fluid compartment in general and that of tumors in particular a highly valuable source for tissue-specific proteins that may serve as biomarker candidates. Potential biomarkers will appear locally at high concentrations in the tissue of interest and will eventually appear in the plasma, where they are diluted. Conclusions: Access to fluid that reliably reflects the local microenvironment enables us to identify substances that can be used in early detection and monitoring of disease