Ultraviolet properties of maximal supergravity

We argue that recent results in string perturbation theory indicate that the four-graviton amplitude of four-dimensional N=8 supergravity might be ultraviolet finite up to eight loops. We similarly argue that the h-loop M-graviton amplitude might be finite for h<7+M/2.     

ITON Schottky contacts for GaN based UV photodetectors

Lateral Schottky ultraviolet detectors were fabricated in GaN using indium-tin-oxynitride (ITON) as a contact metal. The GaN semiconductor material was grown on 2 in. sapphire substrate by metal-organic chemical vapor deposition (MOCVD). The Schottky contact has been realized using ITON that has been deposited using sputter techniques. I-V characteristics have been measured with and without UV illumination. The device shows photo-to-dark current ratios of 10³ at −1 V bias. The spectral responsivity of the UV detectors has been determined. The high spectral responsivity of more than 30 A/W at 240 nm is explained by a high internal gain caused by generation-recombination centers at the ITON/GaN interface. Persistent photocurrent effect has been observed in UV light (on-off) switching operation, time constant and electron capture coefficient of the transition has been determined.     

Closed‐form approximations for spread options in Lévy markets

We provide new closed‐form approximations for the pricing of spread options in three specific instances of exponential Lévy markets, ie, when log‐returns are modeled as Brownian motions (Black‐Scholes model), variance gamma processes (VG model), or normal inverse Gaussian processes (NIG model). For the specific case of exchange options (spread options with zero strike), we generalize the well‐known Margrabe formula (1978) that is valid in a Black‐Scholes model to the VG model under a homogeneity assumption.     

Biocompatible Lipid‐Coated Persistent Luminescent Nanoparticles for In Vivo Imaging of Dendritic Cell Migration

Dendritic cell (DC)‐based vaccines for immunotherapy have already achieved promising results in the last decade. To further improve current treatment protocols and enhance the therapeutic outcome, noninvasive in vivo tracking of DCs remains of crucial importance. Persistent luminescent nanoparticles (PLNPs) are inorganic materials which show an afterglow for hours after the optical excitation has ceased. If the afterglow is in the near‐infrared, the emission of injected particles can be tracked in vivo. However, stability and toxicity issues limit the use of bare PLNPs for biological applications. Therefore, appropriate surface functionalization is needed to improve their biocompatibility. In this study, it is demonstrated that near‐infrared light emitting LiGa₅O₈:Cr³⁺ nanoparticles can be functionalized with a biocompatible lipid coating which provides them with outstanding stability in biological media. In vitro experiments show efficient uptake, absence of cytotoxicity even at very high particle concentrations, and no adverse effects on the maturation potential of DCs. DCs labeled with lipid‐coated LiGa₅O₈:Cr³⁺ nanoparticles injected in mice can be imaged over days, confirming efficient in vivo migration to the popliteal lymph node. Together the results show that lipid coated LiGa₅O₈:Cr³⁺ nanoparticles possess excellent possibilities for further use in research and development of DC based vaccines.     

Quantitative analysis of the stabilization by substrate of Staphylococcus aureus PC1 beta-lactamase

BACKGROUND: The stabilization of enzymes in the presence of substrates has been recognized for a long time. Quantitative information regarding this phenomenon is, however, rather scarce since the enzyme destroys the potential stabilizing agent during the course of the experiments. In this work, enzyme unfolding was followed by monitoring the progressive decrease of the rate of substrate utilization by the Staphylococcus aureus PC1 beta-lactamase, at temperatures above the melting point of the enzyme. RESULTS: Enzyme inactivation was directly followed by spectrophotometric measurements. In the presence of substrate concentrations above the K(m) values, significant stabilization was observed with all tested compounds. A combination of unfolding kinetic measurements and enzymatic studies, both under steady-state and non-steady-state regimes, allowed most of the parameters characteristic of the two concurrent phenomena (i.e. substrate hydrolysis and enzyme denaturation) to be evaluated. In addition, molecular modelling studies show a good correlation between the extent of stabilization, and the magnitude of the energies of interaction with the enzyme. CONCLUSIONS: Our analysis indicates that the enzyme is substantially stabilized towards heat-induced denaturation, independently of the relative proportions of non-covalent Henri-Michaelis complex (ES) and acyl-enzyme adduct (ES*). Thus, for those substrates with which the two catalytic intermediates are expected to be significantly populated, both species (ES and ES*) appear to be similarly stabilized. This analysis contributes a new quantitative approach to the problem.     

Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains

Operational forecasting in supply chain management supports a variety of short-term planning decisions, such as production scheduling and inventory management. In this respect, improving short-term forecast accuracy is a way to build a more agile supply chain for manufacturing companies. Demand forecasting often relies on well-established univariate forecasting methods to extrapolate historical demand. Collaboration across the supply chain, including information sharing, is suggested in the literature to improve upon the forecast accuracy of such traditional methods. In this paper, we review empirical studies considering the use of downstream information in demand forecasting and investigate different modeling approaches and forecasting methods to incorporate such data. Where empirical findings on information sharing mainly focus on point-of-sale data in two-level supply chains, this research empirically investigates the added value of using sell-through data originating from intermediaries, next to historical demand figures, in a multi-echelon supply chain. In a case study concerning a US drug manufacturer, we evaluate different methods to incorporate this data and consider both time series methods and machine learning techniques to produce multi-step ahead weekly forecasts. The results show that the manufacturer can effectively improve its short-term forecast accuracy by integrating sell-through data into the forecasting process and provide useful insights as to the different modeling approaches used. The conclusion holds for all forecast horizons considered, though it is most pronounced for one-step ahead forecasts. Therefore, our research provides a clear incentive for manufacturers to assess the forecast accuracy that can be achieved by using sell-through data.     

Antidesigns and regularity of partial spreads in dual polar graphs

We give several examples of designs and antidesigns in classical finite polar spaces. These types of subsets of maximal totally isotropic subspaces generalize the dualization of the concepts of m ‐ovoids and tight sets of points in generalized quadrangles. We also consider regularity of partial spreads and spreads. The techniques that we apply were developed by Delsarte. In some polar spaces of small rank, some of these subsets turn out to be completely regular codes. © 2010 Wiley Periodicals, Inc. J Combin Designs 19: 202‐216, 2011