Customer’s Acceptance of Humanoid Robots in Services: The Moderating Role of Risk Aversion

The emerging introduction of humanoid robots in service encounters is becoming a reality in the present and the short-term. Owing to this unstoppable advance, there is a need to better understand customers’ perceptions and reactions toward humanoid agents in service encounters. To shed some light on this underexplored phenomenon, this research investigates how the interaction between robot and customer’s features may contribute to a successful introduction of this disruptive innovation. Results of an empirical study with a sample of 168 US customers reveal that customer’s perceptions of robot’s human-likeness increase the intentions to use humanoid service robots. Interestingly, customers’ risk aversion moderates this relationship. Specifically, the study found that highly risk-averse customers tend to avoid using humanoids when they are perceived as highly mechanical-like. The discussion highlights the main contributions of the research, which combine previous knowledge on human–robot interaction and risk aversion from a marketing approach. Managerial implications derived from the research findings and the avenues opened for further research are described at the end

Concentration-Dependent, Size-Independent Toxicity of Citrate Capped AuNPs in Drosophila melanogaster

The expected potential benefits promised by nanotechnology in various fields have led to a rapid increase of the presence of engineered nanomaterials in a high number of commercial goods. This is generating increasing questions about possible risks for human health and environment, due to the lack of an in-depth assessment of the physical/chemical factors responsible for their toxic effects. In this work, we evaluated the toxicity of monodisperse citrate-capped gold nanoparticles (AuNPs) of different sizes (5, 15, 40, and 80 nm) in the model organism Drosophila melanogaster, upon ingestion. To properly evaluate and distinguish the possible dose- and/or size-dependent toxicity of the AuNPs, we performed a thorough assessment of their biological effects, using two different dose-metrics. In the first approach, we kept constant the total surface area of the differently sized AuNPs (Total Exposed Surface area approach, TES), while, in the second approach, we used the same number concentration of the four different sizes of AuNPs (Total Number of Nanoparticles approach, TNN). We observed a significant AuNPs-induced toxicity in vivo, namely a strong reduction of Drosophila lifespan and fertility performance, presence of DNA fragmentation, as well as a significant modification in the expression levels of genes involved in stress responses, DNA damage recognition and apoptosis pathway. Interestingly, we found that, within the investigated experimental conditions, the toxic effects in the exposed organisms were directly related to the concentration of the AuNPs administered, irrespective of their size

Avaliação da lordose lombar e sua relação com a dor lombopélvica em gestantes

O objetivo deste trabalho foi avaliar a magnitude da lordose lombar, sua influência na dor lombopélvica e a qualidade de vida em gestantes. Para tal, foi realizado um estudo com 20 mulheres não gestantes (C) e 13 gestantes ao longo dos trimestres gestacionais (G1, G2 e G3). Todas as mulheres foram submetidas à avaliação inicial para registro dos dados pessoais, hábitos de vida, antecedentes pessoais, uso de medicamentos, história ginecológica e obstétrica. Posteriormente, as voluntárias do grupo controle foram avaliadas uma vez e as gestantes foram avaliadas em três momentos distintos, no 10, 20 e 30 trimestres gestacionais. A avaliação do grau de lordose lombar foi realizada por meio de técnica fotogramétrica; a avaliação de locais de dor, o tipo de dor e sua intensidade foram feitas por meio do Questionário McGill de dor; e a avaliação da qualidade de vida foi feita pelo Questionário WHOQOL-bref. Neste trabalho, não foi possível observar padrão de alteração da curvatura lombar no decorrer da gestação. Também não foi observada relação entre a curvatura lombar e a dor lombopélvica relacionada à gestação.The purpose of this study was to evaluate the magnitude of lumbar lordosis, its influence on lumbopelvic pain and quality of life in pregnant women. To this end, a study was done with 20 non-pregnant women (C) and 13 pregnant women during the trimesters of pregnancy (G1, G2 and G3). All women underwent initial assessment for registration of personal data, lifestyle, personal history, medications, gynecological and obstetric history. Later, the volunteers in the control group were evaluated once and pregnant women were evaluated at three different times, the first, second and third trimesters of pregnancy. The evaluation of the degree of lumbar lordosis was performed by a photogrammetric technique. The assessment of points/places of pain, the kind of pain and its intensity were made by McGill Pain Questionnaire, and the quality of life assessment was made by WHOQOL-bref. In this study, it was not possible to observe a pattern of change in lumbar curvature during pregnancy. There was also no relationship between lumbar curvature and lumbopelvic pain related to pregnancy

Fuzzy Postprocessing to Advance the Quality of Continental Seasonal Hydrological Forecasts for River Basin Management

[EN] Streamflow forecasting services driven by seasonal meteorological forecasts from dynamic prediction systems deliver valuable information for decision-making in the water sector. Moving beyond the traditional river basin boundaries, large-scale hydrological models enable a coordinated, efficient, and harmonized anticipation and management of water-related risks (droughts, floods). However, the use of forecasts from such models at the river basin scale remains a challenge, depending on how the model reproduces the hydrological features of each particular river basin. Consequently, postprocessing of forecasts is a crucial step to ensure usefulness at the river basin scale. In this paper we present a methodology to postprocess seasonal streamflow forecasts from large-scale hydrological models and advance their quality for local applications. It consists of fuzzy logic systems that bias-adjust seasonal forecasts from a large-scale hydrological model by comparing its modeled streamflows with local observations. The methodology is demonstrated using forecasts from the pan-European hydrological model E-HYPE at the Jucar River basin (Spain). Fuzzy postprocessed forecasts are compared to postprocessed forecasts derived from a quantile mapping approach as a benchmark. Fuzzy postprocessing was able to provide skillful streamflow forecasts for the Jucar River basin, keeping most of the skill of raw E-HYPE forecasts and also outperforming quantile-mapping-based forecasts. The proposed methodology offers an efficient one-to-one mapping between large-scale modeled streamflows and basin-scale observations preserving its temporal dependence structure and can adapt its input set to increase the skill of postprocessed forecasts.This study was partially funded by the EU Horizon 2020 programme under the IMPREX research and innovation project (grant agreement no. 641.811), by the European Research Area for Climate Services programme (ER4CS) under the INNOVA project (Grant Agreement 690462), by the ADAPTAMED project (RTI2018-101483-B-I00) from the Ministerio de Ciencia, Innovacion Universidades (MICINN) of Spain, and by the postdoctoral program of Universitat Politecnica de Valencia (PAID 10-18). Funding was also received from the EU Horizon 2020 project S2S4E (Sub -seasonal to Seasonal forecasting for the Energy sector) under Grant Agreement 776787. 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