Negotiation, Email, and Internet Reverse Auctions: How Sourcing Mechanisms Deployed by Buyers Affect Suppliers’ Trust

The Internet has made a wealth of new tools available to the industrial buyer. However, researchers have suggested that computer mediated interaction with suppliers may not be conducive to strong supplier relationships in general and to trust in particular. This paper compares two computer-mediated sourcing tools (email negotiation and Internet reverse auctions) with face-to-face negotiation. Information richness theory suggests that the different media will produce different impacts relating to sellers’ trust in buyers. Data are generated with a simulation experiment using 117 subjects. We found that information richness affects seller-buyer trust: Sellers who used face-to-face negotiation, the richest medium in the study, always reported higher trust in their buyer counterparts than did sellers using Internet reverse auctions. There were also some trust advantages of face-to-face negotiation over email and limited advantages of email over reverse auctions. We also found that procurement complexity influences the relationship between information richness and trust. As hypothesized, when face-to-face negotiation is used, procurement complexity has no effect on seller trust. When reverse auctions are utilized, the greater the complexity of the purchase, the less the seller trust. However, when email is used, greater procurement complexity is associated with greater seller trust, and there are no differences in trust between the email and face-to-face channels. Finally, we found that sellers’ trust in buyers is positively associated with sellers’ desire for future dealings with the buyer

Occupation times of intervals until first passage times for spectrally negative Lévy processes

In this paper, we identify Laplace transforms of occupation times of intervals until first passage times for spectrally negative Lévy processes. New analytical identities for scale functions are derived and therefore the results are explicitly stated in terms of the scale functions of the process. Applications to option pricing and insurance risk models are also presented

Graph Classification Gaussian Processes via Spectral Features

Graph classification aims to categorise graphs based on their structure and node attributes. In this work, we propose to tackle this task using tools from graph signal processing by deriving spectral features, which we then use to design two variants of Gaussian process models for graph classification. The first variant uses spectral features based on the distribution of energy of a node feature signal over the spectrum of the graph. We show that even such a simple approach, having no learned parameters, can yield competitive performance compared to strong neural network and graph kernel baselines. A second, more sophisticated variant is designed to capture multi-scale and localised patterns in the graph by learning spectral graph wavelet filters, obtaining improved performance on synthetic and real-world data sets. Finally, we show that both models produce well calibrated uncertainty estimates, enabling reliable decision making based on the model predictions

Differential Kinetics of Aspergillus nidulans and Aspergillus fumigatus Phagocytosis

Acknowledgements: The authors would like to acknowledge Fraser P. Coxon and Ian Ganley for providing LC3-GFP-mCherry BMDMs. M.S.G. was supported by an FEMS research grant and F.L.v.d.V. was supported by ZonMW under the name EURO-CMC frame of E-Rare-2, the ERA-Net for Research on Rare Diseases.Peer reviewedPublisher PD

Diurnal Variation of Tropical Ice Cloud Microphysics: Evidence from Global Precipitation Measurement Microwave Imager Polarimetric Measurements

The diurnal variation of tropical ice clouds has been well observed and examined in terms of the occurring frequency and total mass but rarely from the viewpoint of ice microphysical parameters. It accounts for a large portion of uncertainties in evaluating ice cloud's role on global radiation and hydrological budgets. Owing to the advantage of precession orbit design and paired polarized observations at a high-frequency microwave band that is particularly sensitive to ice particle microphysical properties, three years of polarimetric difference (PD) measurements using the 166 GHz channel of Global Precipitation Measurement Microwave Imager (GPM-GMI) are compiled to reveal a strong diurnal cycle over tropical land (30degS-30deg N) with peak amplitude varying up to 38%. Since the PD signal is dominantly determined by ice crystal size, shape, and orientation, the diurnal cycle observed by GMI can be used to infer changes in ice crystal properties. Moreover, PD change is found to lead the diurnal changes of ice cloud occurring frequency and total ice mass by about 2 hours, which strongly implies that understanding ice microphysics is critical to predict, infer, and model ice cloud evolution and precipitation processes

Transductive Kernels for Gaussian Processes on Graphs

Kernels on graphs have had limited options for node-level problems. To address this, we present a novel, generalized kernel for graphs with node feature data for semi-supervised learning. The kernel is derived from a regularization framework by treating the graph and feature data as two Hilbert spaces. We also show how numerous kernel-based models on graphs are instances of our design. A kernel defined this way has transductive properties, and this leads to improved ability to learn on fewer training points, as well as better handling of highly non-Euclidean data. We demonstrate these advantages using synthetic data where the distribution of the whole graph can inform the pattern of the labels. Finally, by utilizing a flexible polynomial of the graph Laplacian within the kernel, the model also performed effectively in semi-supervised classification on graphs of various levels of homophily

Fermi Surface and Band Renormalization in (Sr,K)Fe2_2As2_2 Superconductor from Angle-Resolved Photoemission Spectroscopy

High resolution angle-resolved photoemission measurements have been carried out on (Sr,K)Fe$_2$As$_2$ superconductor (Tc=21 K). Three hole-like Fermi surface sheets are clearly resolved for the first time around the Gamma point. The overall electronic structure shows significant difference from the band structure calculations. Qualitative agreement between the measured and calculated band structure is realized by assuming a chemical potential shift of -0.2 eV. The obvious band renormalization suggests the importance of electron correlation in understanding the electronic structure of the Fe-based compounds.Comment: 4 pages, 4 figure

The Intratubular and Intracrine Renin-Angiotensin System in the Proximal Tubules of the Kidney and Its Roles in Angiotensin II-Induced Hypertension

The kidney plays a fundamental role in the physiological regulation of basal blood pressure and the development of hypertension. Although the mechanisms underlying hypertension are very complex, the renin-angiotensin system (RAS) in the kidney, especially intratubular and intracellular RAS, undoubtedly plays a critical role in maintaining basal blood pressure homeostasis and the development of angiotensin II (ANG II)-dependent hypertension. In the proximal tubules, ANG II activates two G protein-coupled receptors, AT1 and AT2, to exert powerful effects to regulate proximal tubular sodium and fluid reabsorption by activating cell surface as well as intracellular AT1 receptors. Increased production and actions of ANG II in the proximal tubules may cause salt and fluid retention, impair the pressure-natriuresis response, and consequently increase blood pressure in hypertension. The objectives of this chapter are to critically review and discuss our current understanding of intratubular and intracellular RAS in the kidney, and their contributions to basal blood pressure homeostasis and the development of ANG II-dependent hypertension. The new knowledge will likely help uncover novel renal mechanisms of hypertension, and develop kidney- or proximal tubule-specific strategies or drugs to prevent and treat hypertension in humans

Discretization of the velocity space in solution of the Boltzmann equation

We point out an equivalence between the discrete velocity method of solving the Boltzmann equation, of which the lattice Boltzmann equation method is a special example, and the approximations to the Boltzmann equation by a Hermite polynomial expansion. Discretizing the Boltzmann equation with a BGK collision term at the velocities that correspond to the nodes of a Hermite quadrature is shown to be equivalent to truncating the Hermite expansion of the distribution function to the corresponding order. The truncated part of the distribution has no contribution to the moments of low orders and is negligible at small Mach numbers. Higher order approximations to the Boltzmann equation can be achieved by using more velocities in the quadrature