Daily deal shoppers: What drives social couponing?

This paper contributes to the service marketing literature with a focus on deal-of-the-day (DoD) website shopping. The work explores drivers of adoption of DoD shopping among young consumers. We show that value conscious consumers are less oriented towards DoD while deal-prone consumers are more likely to purchase DoD. In contrast to previous research, which found that price savings are the main reason for coupon use, our study finds that Enjoyment plays a major role in young consumers\u2019 DoD shopping behaviour. DoD platforms could leverage Enjoyment to create a compelling value proposition for both consumer and merchant attraction and retention

Novel chiral bis-phosphoramides as organocatalysts for tetrachlorosilane-mediated reactions

The formation of novel chiral bidentate phosphoroamides structures able to promote Lewis base-catalyzed Lewis acid-mediated reactions was investigated. Two different classes of phosphoroamides were synthetized: the first class presents a phthalic acid/primary diamine moiety, designed with the aim to perform a self-assembly recognition process through hydrogen bonds; the second one is characterized by the presence of two phosphoroamides as side arms connected to a central pyridine unit, able to chelate SiCl4in a 2:1 adduct. These species were tested as organocatalysts in the stereoselective allylation of benzaldehyde and a few other aromatic aldehydes with allyl tributyltin in the presence of SiCl4with good results. NMR studies confirm that only pyridine-based phosphoroamides effectively coordinate tetrachlorosilane and may lead to the generation of a self-assembled entity that would act as a promoter of the reaction. Although further work is necessary to clarify and confirm the formation of the hypothesized adduct, the study lays the foundation for the design and the synthesis of chiral supramolecular organocatalysts

Boron accumulation and tolerance in sweet basil (Ocimum basilicum L.) with green or purple leaves

Background and aims There is a wide variability in plant tolerance to boron (B) toxicity, which is often associated with the ability to limit B accumulation. This study was conducted on two cultivars of sweet basil (Ocimum basilicum L.) with different B tolerance: ‘Tigullio’, less tolerant and with green leaves; ‘Red Rubin’, more tolerant and with purple leaves. The main goal was to verify whether the greater B tolerance of ‘Red Rubin’ is attributable to an exclusion mechanism. Methods In three greenhouse experiments, plants were grown hydroponically with solution B concentration ranging from 0.25 (control) to 25 mg L−1. Results Tissue B concentration increased with increasing B supply. Boron concentrations in root and leaf tissues were comparable in ‘Tigullio’ and ‘Red Rubin’ or even higher in the purple cultivar. Boron supply did not affect the leaf concentration of total phenolic compounds and other nutrients. Leaf concentrations of total phenols and rosmarinic acid were remarkably higher in ‘Red Rubin’ than in ‘Tigullio’. Conclusions The greater B tolerance of ‘Red Rubin’ was associated with the ability to withstand higher concentrations of this element in plant tissues rather than to reduced B accumulation in the shoot. The high phenolic content was thought to contribute to the B tolerance of ‘Red Rubin’

The role of topography, soil, and remotely sensed vegetation condition towards predicting crop yield

Foreknowledge of the spatiotemporal drivers of crop yield would provide a valuable source of information to optimize on-farm inputs and maximize profitability. In recent years, an abundance of spatial data providing information on soils, topography, and vegetation condition have become available from both proximal and remote sensing platforms. Given the wide range of data costs (between USD $0−50/ha), it is important to understand where often limited financial resources should be directed to optimize field production. Two key questions arise. First, will these data actually aid in better fine-resolution yield prediction to help optimize crop management and farm economics? Second, what level of priority should stakeholders commit to in order to obtain these data? Before fully addressing these questions a remaining challenge is the complex nature of spatiotemporal yield variation. Here, a methodological framework is presented to separate the spatial and temporal components of crop yield variation at the subfield level. The framework can also be used to quantify the benefits of different data types on the predicted crop yield as well to better understand the connection of that data to underlying mechanisms controlling yield. Here, fine-resolution (10 m) datasets were assembled for eight 64 ha field sites, spanning a range of climatic, topographic, and soil conditions across Nebraska. Using Empirical Orthogonal Function (EOF) analysis, we found the first axis of variation contained 60–85 % of the explained variance from any particular field, thus greatly reducing the dimensionality of the problem. Using Multiple Linear Regression (MLR) and Random Forest (RF) approaches, we quantified that location within the field had the largest relative importance for modeling crop yield patterns. Secondary factors included a combination of vegetation condition, soil water content, and topography. With respect to predicting spatiotemporal crop yield patterns, we found the RF approach (prediction RMSE of 0.2−0.4 Mg/ha for maize) was superior to MLR (0.3−0.8 Mg/ha). While not directly comparable to MLR and RF the EOF approach had relatively low error (0.5–1.7 Mg/ha) and is intriguing as it requires few calibration parameters (2–6 used here) and utilizes the climate-based aridity index, allowing for pragmatic long-term predictions of subfield crop yield

A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

The work leading to this paper was funded through the European Union’s FP7 programme under Grant Agreement No. 282656 (REFORM). The framework methodology was developed within the context of Deliverable D2.1 of the REFORM programme, and all partners who contributed to the development of the four parts of this deliverable are included in the author list of this paper. More details on the REFORM framework can be obtained from part 1 of Deliverable D2.1 (Gurnell et al. 2014), which is downloadable from http://​www.​reformrivers.​eu/​results/​deliverables

Testing ab initio nuclear structure in neutron-rich nuclei: Lifetime measurements of second 2+ state in 16C and 20O

To test the predictive power of ab initio nuclear structure theory, the lifetime of the second 2+ state in neutron-rich 20O,τ(2+2)=150+80−30fs, and an estimate for the lifetime of the second 2+ state in 16C have been obtained for the first time. The results were achieved via a novel Monte Carlo technique that allowed us to measure nuclear state lifetimes in the tens-to-hundreds of femtoseconds range by analyzing the Doppler-shifted γ-transition line shapes of products of low-energy transfer and deep-inelastic processes in the reaction 18O(7.0MeV/u)+181Ta. The requested sensitivity could only be reached owing to the excellent performances of the Advanced γ-Tracking Array AGATA, coupled to the PARIS scintillator array and to the VAMOS++ magnetic spectrometer. The experimental lifetimes agree with predictions of ab initio calculations using two- and three-nucleon interactions, obtained with the valence-space in-medium similarity renormalization group for 20O and with the no-core shell model for 16C. The present measurement shows the power of electromagnetic observables, determined with high-precision γ spectroscopy, to assess the quality of first-principles nuclear structure calculations, complementing common benchmarks based on nuclear energies. The proposed experimental approach will be essential for short lifetime measurements in unexplored regions of the nuclear chart, including r-process nuclei, when intense beams, produced by Isotope Separation On-Line (ISOL) techniques, become available

Unmanned Aerial Vehicle-Based Phenotyping Using Morphometric and Spectral Analysis Can Quantify Responses of Wild Tomato Plants to Salinity Stress

With salt stress presenting a major threat to global food production, attention has turned to the identification and breeding of crop cultivars with improved salt tolerance. For instance, some accessions of wild species with higher salt tolerance than commercial varieties are being investigated for their potential to expand food production into marginal areas or to use brackish waters for irrigation. However, assessment of individual plant responses to salt stress in field trials is time-consuming, limiting, for example, longitudinal assessment of large numbers of plants. Developments in Unmanned Aerial Vehicle (UAV) sensing technologies provide a means for extensive, repeated and consistent phenotyping and have significant advantages over standard approaches. In this study, 199 accessions of the wild tomato species, Solanum pimpinellifolium, were evaluated through a field assessment of 600 control and 600 salt-treated plants. UAV imagery was used to: (1) delineate tomato plants from a time-series of eight RGB and two multi-spectral datasets, using an automated object-based image analysis approach; (2) assess four traits, i.e., plant area, growth rates, condition and Plant Projective Cover (PPC) over the growing season; and (3) use the mapped traits to identify the best-performing accessions in terms of yield and salt tolerance. For the first five campaigns, >99% of all tomato plants were automatically detected. The omission rate increased to 2–5% for the last three campaigns because of the presence of dead and senescent plants. Salt-treated plants exhibited a significantly smaller plant area (average control and salt-treated plant areas of 0.55 and 0.29 m2, respectively), maximum growth rate (daily maximum growth rate of control and salt-treated plant of 0.034 and 0.013 m2, respectively) and PPC (5–16% difference) relative to control plants. Using mapped plant condition, area, growth rate and PPC, we show that it was possible to identify eight out of the top 10 highest yielding accessions and that only five accessions produced high yield under both treatments. Apart from showcasing multi-temporal UAV-based phenotyping capabilities for the assessment of plant performance, this research has implications for agronomic studies of plant salt tolerance and for optimizing agricultural production under saline conditions