A QUANTITATIVE ASSESSMENT OF E-GROCERS

Agribusiness,

Comprehensive study of ULF upstream waves observed in the topside ionosphere by CHAMP and on the ground

Based on magnetic field measurements from the satellite CHAMP, a detailed picture could be obtained of the upstream wave (UW) distribution in the topside ionosphere. The low, near-polar orbit of CHAMP, covering all local times, allows the global distribution of this type of pulsation to be revealed. The observations from space are compared to recordings of the ground-based MM100 meridional array covering the latitude range 66° to 42° in magnetic coordinates. UWs show up very clearly in the compressional component of the satellite magnetic field data, whereas on the ground, their signature is found in the H component, but it is mixed with oscillations from field line resonant pulsations. Here we first introduce a procedure for an automated detection of UW signatures, both in ground and space data. Then a statistical analysis is presented of UW pulsations recorded during a 132-day period, centred on the autumn 2001 equinox. Observations in the top-side ionosphere reveal a clear latitudinal distribution of the amplitudes. Largest signals are observed at the equator. Minima show up at about 40° latitude. The coherence between ground and satellite wave signatures is high over wide latitude and longitude ranges. We make suggestions about the entry mechanism of UWs from the foreshock region into the magnetosphere. The clear UW signature in satellite recordings between −60° and 60° latitude allows for detailed investigations of the dependence on solar wind conditions. We test the control of solar wind speed, interplanetary magnetic field strength and cone angle on UWs. For the first time, it is possible to derive details of the Doppler-shift effect by modifying the UW frequency from direct observations. The results reconcile foreshock wave generation predictions with near-Earth observations

TRACKING THE EVOLUTION OF E-GROCERS: A QUANTITATIVE ASSESSMENT

Forecasts of the proportion of food retailing likely to be conducted over the Internet remain small, perhaps only contributing 2 percent of sales. One reason for this low market share is the challenge E-Grocers face in developing strategies which respond to four key areas of interest to consumers: signals of firm quality; signals of product quality; the range of products offered; and service, or customer-relationship management (CRM). Careful attention to these consumer concerns is important in all retail relationships–-online or offline. This paper compares indicators of these factors across U.S. E-Grocers. A quantitative four-period ranking of online food-retailing strategies is presented for the nascent industry. Data from the third and fourth quarters of 2001, the fourth quarter of 2002, and the first quarter of 2004 provide the basis of this discussion. After initial setbacks, data show traditional ("“bricks”") grocery retailers successfully developing online strategies. Firms not primarily focused on groceries exited the E-Grocery sector, while the development of specialty food suppliers blurred the concept of online food retailing. Gaps in current strategies are indicated using content analyses of E-Grocery web sites.Agribusiness,

A Comparison of Machine Learning Algorithms for the Surveillance of Autism Spectrum Disorder

The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speeding up this process, but they lag behind human classification accuracy by about 5%. We explore whether more recently available document classification algorithms can close this gap. We applied 8 supervised learning algorithms to predict whether children meet the case definition for ASD based solely on the words in their evaluations. We compared the algorithms' performance across 10 random train-test splits of the data, using classification accuracy, F1 score, and number of positive calls to evaluate their potential use for surveillance. Across the 10 train-test cycles, the random forest and support vector machine with Naive Bayes features (NB-SVM) each achieved slightly more than 87% mean accuracy. The NB-SVM produced significantly more false negatives than false positives (P = 0.027), but the random forest did not, making its prevalence estimates very close to the true prevalence in the data. The best-performing neural network performed similarly to the random forest on both measures. The random forest performed as well as more recently available models like the NB-SVM and the neural network, and it also produced good prevalence estimates. NB-SVM may not be a good candidate for use in a fully-automated surveillance workflow due to increased false negatives. More sophisticated algorithms, like hierarchical convolutional neural networks, may not be feasible to train due to characteristics of the data. Current algorithms might perform better if the data are abstracted and processed differently and if they take into account information about the children in addition to their evaluations

User quality of experience of mulsemedia applications

User Quality of Experience (QoE) is of fundamental importance in multimedia applications and has been extensively studied for decades. However, user QoE in the context of the emerging multiple-sensorial media (mulsemedia) services, which involve different media components than the traditional multimedia applications, have not been comprehensively studied. This article presents the results of subjective tests which have investigated user perception of mulsemedia content. In particular, the impact of intensity of certain mulsemedia components including haptic and airflow on user-perceived experience are studied. Results demonstrate that by making use of mulsemedia the overall user enjoyment levels increased by up to 77%

From a systems view to spotting a hidden island : A narrative review implicating insula function in alcoholism

Excessive use of alcohol promotes the development of alcohol addiction, but the understanding of how alcohol induced brain alterations lead to addiction remains limited. To further this understanding, we adopted an unbiased discovery strategy based on the principles of systems medicine. We used functional magnetic resonance imaging data from patients and animal models of alcohol addiction-like behaviors, and developed mathematical models of the 'relapse-prone' network states to identify brain sites and functional networks that can be selectively targeted by therapeutic interventions. Our systems level, non-local, and largely unbiased analyses converged on a few well-defined brain regions, with the insula emerging as one of the most consistent findings across studies. In proof-of-concept experiments we were able to demonstrate that it is possible to guide network dynamics towards increased resilience in animals but an initial translation into a clinical trial targeting the insula failed. Here, in a narrative review, we summarize the key experiments, methodological developments and knowledge gained from this complete round of a discovery cycle moving from identification of 'relapse-prone' network states in humans and animals to target validation and intervention trial. Future concerted efforts are necessary to gain a deeper understanding of insula function a in a state-dependent, circuit-specific and cell population perspective, and to develop the means for insula-directed interventions, before therapeutic targeting of this structure may become possible.Peer reviewe

Near-equatorial Pi2 and Pc3 waves observed by CHAMP and on SAMBA/MAGDAS stations

We have examined simultaneous ULF activity in the Pi2 and Pc3 bands at the near-equatorial magnetic stations in South America from SAMBA and MAGDAS arrays and low-orbiting CHAMP satellite during its passage over this meridional network. At the nighttime, both Pi2 and Pc3 waves in the upper ionosphere and on the ground are nearly of the same magnitude and in-phase. At the same time, the daytime Pc3 pulsations on the ground and in space are nearly out-of-phase. Comparison of observational results with the theoretical notions on the MHD wave interaction with the system ionosphere–atmosphere–ground suggests that nighttime low-latitude Pi2 and Pc3 wave signatures are produced by magnetospheric fast compressional mode. The daytime near-equatorial Pc3 waves still resist a quantative interpretation. These waves may be produced by a combination of two mechanisms: compressional mode leakage through the ionosphere, and by oscillatory ionospheric current spreading towards equatorial latitudes

Doxycycline Alters the Porcine Renal Proteome and Degradome during Hypothermic Machine Perfusion

Ischemia-reperfusion injury (IRI) is a hallmark for tissue injury in donation after circulatory death (DCD) kidneys. The implementation of hypothermic machine perfusion (HMP) provides a platform for improved preservation of DCD kidneys. Doxycycline administration has shown protective effects during IRI. Therefore, we explored the impact of doxycycline on proteolytic degradation mechanisms and the urinary proteome of perfused kidney grafts. Porcine kidneys underwent 30 min of warm ischemia, 24 h of oxygenated HMP (control/doxycycline) and 240 min of ex vivo reperfusion. A proteomic analysis revealed distinctive clustering profiles between urine samples collected at T15 min and T240 min. High-efficiency undecanal-based N-termini (HUNTER) kidney tissue degradomics revealed significantly more proteolytic activity in the control group at T-10. At T240, significantly more proteolytic activity was observed in the doxycycline group, indicating that doxycycline alters protein degradation during HMP. In conclusion, doxycycline administration during HMP led to significant proteomic and proteolytic differences and protective effects by attenuating urinary NGAL levels. Ultimately, we unraveled metabolic, and complement and coagulation pathways that undergo alterations during machine perfusion and that could be targeted to attenuate IRI induced injury