Self-Monitoring and Advertising: Evaluations of Image- versus Quality-Oriented Advertisements for Public/Private and Public Luxury/Necessity Products

High self-monitors tend to prefer image-oriented advertisements, whereas low self-monitors favor quality-oriented advertisements. Past research has found that image congruence had a stronger affect on product evaluations of high self-monitors relative to low self-monitors for public products, while this effect did not emerge for private products. Study 1 extended these findings by examining the effect of self-monitoring and public/private products on evaluations of image- versus quality-oriented advertisements. The participants were shown two sunglasses (public product) advertisements and two toilet paper (private product) advertisements; for each product, one advertisement was image-oriented and was quality-focused. The participants completed two questionnaires—one for each product type—and the self-monitoring scale. Study 2 employed a similar method but extended the self-monitoring propensity to different public products: Ice cream (luxury product) and a winter coat (necessity product). Past findings suggest that high self-monitors are influenced more when considering luxury, rather than necessity, products. Although not significant, analyses of Study 1 showed that high self-monitors preferred the image-oriented sunglasses advertisement, while low self-monitors preferred the quality-focused sunglasses advertisement. Both high and low self-monitors preferred the quality-oriented toilet paper advertisement. Although also not significant, the results of Study 2 illustrated that high self-monitors preferred the image-focused advertisement for both the luxury and necessity advertisements more than low self-monitors. The results of both studies confirm that high self-monitors prefer image-oriented advertisements for public products more than low self-monitors. Possible limitations and future research directions are discussed

Circadian methane oxidation in the root zone of rice plants

In the root zone of rice plants aerobic methanotrophic bacteria catalyze the oxidation of CH4 to CO2, thereby reducing CH4 emissions from paddy soils to the atmosphere. However, methods for in situ quantification of microbial processes in paddy soils are scarce. Here we adapted the push-pull tracer-test (PPT) method to quantify CH4 oxidation in the root zone of potted rice plants. During a PPT, a test solution containing CH4±O2 as reactant(s), Cl− and Ar as nonreactive tracers, and BES as an inhibitor of CH4 production was injected into the root zone at different times throughout the circadian cycle (daytime, early nighttime, late nighttime). After a 2-h incubation phase, the test solution/pore-water mixture was extracted from the same location and rates of CH4 oxidation were calculated from the ratio of measured reactant and nonreactive tracer concentrations. In separate rice pots, O2 concentrations in the vicinity of rice roots were measured throughout the circadian cycle using a fiber-optic sensor. Results indicated highly variable CH4 oxidation rates following a circadian pattern. Mean rates at daytime and early nighttime varied from 62 up to 451μmoll−1h−1, whereas at late nighttime CH4 oxidation rates were low, ranging from 13 to 37μmol l−1h−1. Similarly, daytime O2 concentration in the vicinity of rice roots increased to up to 250% air saturation, while nighttime O2 concentration dropped to below detection (<0.15% air saturation). Our results suggest a functional link between root-zone CH4 oxidation and photosynthetic O2 suppl

A portable MBE system for in situ X-Ray investigations at synchrotron beamlines

A portable synchrotron MBE system is designed and applied for in situ investigations. The growth chamber is equipped with all the standard MBE components such as effusion cells with shutters, main shutter, cooling shroud, manipulator, RHEED setup and pressure gauges. The characteristic feature of the system is the beryllium windows which are used for in situ x-ray measurements. An UHV sample transfer case allows in-vacuo transfer of samples prepared elsewhere. We describe the system design and demonstrate it's performance by investigating the annealing process of buried InGaAs self organized quantum dots

Fertilization effects on soil P, K, Ca and Mg contents in a mixed tree cropping system in Central Amazonia.

The main objective was to study the fertilizer effects on P, K, Ca e Mg contents in mixed tree cropping system with Brazil nut (Bertholletia excelsa), cupuaçu (Theobroma grandiflorum), peach palm (Bactris gasipaes), annatto (Bixa orellana) and pueraria (Pueraria phaseoloides)

Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization

Distributed learning paradigms, such as federated or decentralized learning, allow a collection of agents to solve global learning and optimization problems through limited local interactions. Most such strategies rely on a mixture of local adaptation and aggregation steps, either among peers or at a central fusion center. Classically, aggregation in distributed learning is based on averaging, which is statistically efficient, but susceptible to attacks by even a small number of malicious agents. This observation has motivated a number of recent works, which develop robust aggregation schemes by employing robust variations of the mean. We present a new attack based on sensitivity curve maximization (SCM), and demonstrate that it is able to disrupt existing robust aggregation schemes by injecting small, but effective perturbations

Robust and Efficient Aggregation for Distributed Learning

Distributed learning paradigms, such as federated and decentralized learning, allow for the coordination of models across a collection of agents, and without the need to exchange raw data. Instead, agents compute model updates locally based on their available data, and subsequently share the update model with a parameter server or their peers. This is followed by an aggregation step, which traditionally takes the form of a (weighted) average. Distributed learning schemes based on averaging are known to be susceptible to outliers. A single malicious agent is able to drive an averaging-based distributed learning algorithm to an arbitrarily poor model. This has motivated the development of robust aggregation schemes, which are based on variations of the median and trimmed mean. While such procedures ensure robustness to outliers and malicious behavior, they come at the cost of significantly reduced sample efficiency. This means that current robust aggregation schemes require significantly higher agent participation rates to achieve a given level of performance than their mean-based counterparts in non-contaminated settings. In this work we remedy this drawback by developing statistically efficient and robust aggregation schemes for distributed learning

Soil quality parameters of a xanthic ferralsol in the Amazon basin.

A Fertbio 2002 reuniu a XXV Reunião Brasileira de Fertilidade do Solo e Nutrição de Plantas, a IX Reunião Brasileira sobre Micorrizas, o VII Simpósio Brasileiro de Microbiologia do Solo e a Reunião Brasileira de Biologia do Solo, sob o tema: "Agricultura: bases ecológicas para o desenvolvimento social e econômico sustentado