A Cinderella Story: How Past Identity Salience Boosts Demand for Repurposed Products

Like Cinderella, many repurposed products involve a biographical transformation, from a tattered past identity (e.g., an old airbag) to a product with a valuable but different new identity (e.g., a backpack made from an airbag). In this article, the authors argue that marketers should help customers infer such product stories by highlighting the products' tattered past identities. Three field experiments and four controlled experiments show that making a product's past identity salient boosts demand across a variety of repurposed products. This is because past identity salience induces narrative thoughts about these products' biographies, which in turn allows customers to feel special. Results also suggest that this strategy of past identity salience needs to be particularly well-crafted for products with easily discernible past identities. These findings highlight a promising new facet of storytelling (i.e., stories that customers self-infer in response to minimal marketer input); create new opportunities for promoting products with a prior life; and deliver detailed guidance for the largely unexplored, growing market for upcycled and recycled products

Vibrational Satellites of C2_2S, C3_3S, and C4_4S: Microwave Spectral Taxonomy as a Stepping Stone to the Millimeter-Wave Band

We present a microwave spectral taxonomy study of several hydrocarbon/CS$_2$ discharge mixtures in which more than 60 distinct chemical species, their more abundant isotopic species, and/or their vibrationally excited states were detected using chirped-pulse and cavity Fourier-transform microwave spectroscopies. Taken together, in excess of 85 unique variants were detected, including several new isotopic species and more than 25 new vibrationally excited states of C$_2$S, C$_3$S, and C$_4$S, which have been assigned on the basis of published vibration-rotation interaction constants for C$_3$S, or newly calculated ones for C$_2$S and C$_4$S. On the basis of these precise, low-frequency measurements, several vibrationally exited states of C$_2$S and C$_3$S were subsequently identified in archival millimeter-wave data in the 253--280 GHz frequency range, ultimately providing highly accurate catalogs for astronomical searches. As part of this work, formation pathways of the two smaller carbon-sulfur chains were investigated using $^{13}$C isotopic spectroscopy, as was their vibrational excitation. The present study illustrates the utility of microwave spectral taxonomy as a tool for complex mixture analysis, and as a powerful and convenient `stepping stone' to higher frequency measurements in the millimeter and submillimeter bands.Comment: Accepted in PCC

gem-Dibromocyclopropanes and enzymatically derived cis-1,2-dihydrocatechols as building blocks in alkaloid synthesis

The application of the title building blocks, the 6,6-dibromobicyclo[3.1.0]hexanes and the cis-1,2-dihydrocatechols, to the total synthesis of crinine and lycorinine alkaloids is described.We thank the Australian Research Council and the Institute of Advanced Studies for generous financial support

Design and application of a flow cell for carbon-film based electrochemical enzyme biosensors

A flow cell has been designed for use with an electrochemical enzyme biosensor, based on low-cost carbon-film electrodes. Three types of mediators were used: cobalt and copper hexacyanoferrates and poly(neutral red) (PNR), covered with glucose oxidase (GOx) immobilised by cross-linking with glutaraldehyde in the presence of bovine serum albumin or inside a oxysilane sol-gel network. Mixtures of sol-gel precursors were made from 3-aminopropyl-triethoxysilane (APTOS) together with methyltrimethoxysilane (MTMOS), methyltriethoxysilane (MTEOS), tetraethyloxysilane (TEOS) or 3-glycidoxypropyl-trimethoxysilane (GOPMOS), and the best chosen for encapsulation. Optimisation in batch mode, using amperometric detection at fixed potential, showed the PNR-GOx modified carbon-film electrodes to be best for flow analysis for both glutaraldehyde and sol-gel enzyme immobilisation. Both types of enzyme electrode were tested under flow conditions and the reproducibility and stability of the biosensors were evaluated. The biosensors were used for fermentation monitoring of glucose in grape must and interference studies were also performed.http://www.sciencedirect.com/science/article/B6THP-4M0BH9Y-2/1/306f5db86217ea276bf808fb05c0288

Research Notes : Inheritance of fatty acid composition in soybean seed oil

While it has been demonstrated that the fatty acid composition of soybean oil can be changed by recurrent selection (Wilson et al., 1981), there is little information about the genetic control of oil biosynthesis in soybean seeds. In some species, such as rape (Downey and Harvey, 1963), safflower (Yermanos et al., 1967), and flax (Yermanos and Knowles, 1962), the male parent has a significant effect on the fatty acid composition of oil from F1 hybrid seeds. In corn (Jellum, 1966) and soybeans (Brim et al., 1968), the male parent has almost no effect on oil composition of F1 hybrid seeds

Learning Set Representations for LWIR In-Scene Atmospheric Compensation

Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed in point cloud classification. When applied to collected hyperspectral image data, this method shows comparable performance to Fast Line-of-Sight Atmospheric Analysis of Hypercubes-Infrared (FLAASH-IR), using an auto- mated pixel selection approach. Additionally, inference time is significantly reduced compared to FLAASH-IR with predictions made on average in 0.24 s on a 128 pixel by 5000 pixel data cube using a mobile graphics card. This computational speed-up on a low-power platform results in an autonomous atmospheric compensation method effective for real-time, onboard use, while only requiring a diversity of materials in the scene