The Effects of Emotion Strategies on E-negotiation Behavior and Outcome

Emotional strategies have been well discussed in the face-to-face negotiation, but few studies have explored its application in the electronic negotiation system (ENS). The popularity of enegotiation has made this issue critical not only to commercial negotiators or businesses, but to the researchers who studied negotiations and developers of ENS. Aiming to reveal the relationships between the emotional negotiation strategy, negotiation behavior and results on the ENS, a model was developed and tested in this study. Four emotional strategies were investigated in this study: Positive Emotion Strategy, Negative Emotion Strategy, Positive/Negative Emotion Strategy, and Negative/ Positive Emotion Strategy so as to disclose (1) which strategy will reach the greater joint outcome and achieve a win-win solution; (2) which strategy will lead to an broken up result. An ENS system was also developed explicitly for this study in order to conduct the experiment and questionnaire survey. Findings are expected to shorten the negotiation time and cost via facilitating the trust between negotiators by using an effective emotional strategy

Fall risk assessment of bridge construction using Bayesian network transferring from fault tree analysis

Falling is the most common one during bridge construction. Current safety management on site mainly relies on checklist assessment. Yet the assessment result is often influenced by the ability and experience of the evaluator, thus is not impossible to achieve consistent and systematic assessment objective. Moreover, most critical factors that can prevent occurrence of accidents cannot be found from existing safety management and assessment method. This paper built a Bayesian Network (BN) model by converting Fault Tree to assess the fall risk of bridge construction projects. We analyse falling factors and their relationships in Bayesian Network, and collect prior probability event and calculate the probability for the entire model. Using the model to analyse and validate with the current bridge projects under construc­tion, the results from Bayesian Network is consistent with that from conventional labour safety performance assessment. Therefore, the ability to manage site safety of the model is proven to be useful

Fabrication of Nanostructured PLGA Scaffolds Using Anodic Aluminum Oxide Templates

PLGA (poly(lactic-co-glycolic acid)) is one of the most used biodegradable and biocompatible materials. Nanostructured PLGA even has great application potentials in tissue engineering. In this research, a fabrication technique for nanostructured PLGA membrane was investigated and developed. In this novel fabrication approach, an anodic aluminum oxide (AAO) film was use as the template ; the PLGA solution was then cast on it ; the vacuum air-extraction process was applied to transfer the nano porous pattern from the AAO membrane to the PLGA membrane and form nanostures on it. The cell culture experiments of the bovine endothelial cells demonstrated that the nanostructured PLGA membrane can double the cell growing rate. Compared to the conventional chemical-etching process, the physical fabrication method proposed in this research not only is simpler but also does not alter the characteristics of the PLGA. The nanostructure of the PLGA membrane can be well controlled by the AAO temperate.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

Responses of corn physiology and yield to six agricultural practices over three years in middle Tennessee

Different agricultural practices may have substantial impacts on crop physiology and yield. However, it is still not entirely clear how multiple agricultural practices such as tillage, biochar and different nutrient applications could influence corn physiology and yield. We conducted a three-year field experiment to study the responses of corn physiology, yield and soil respiration to six different agricultural practices. The six treatments included conventional tillage (CT) or no tillage (NT), in combination with nitrogen type (URAN or chicken litter) and application method, biochar, or denitrification inhibitor. A randomized complete block design was applied with six replications. Leaf photosynthetic rate, transpiration, plant height, leaf area index (LAI), biomass and yield were measured. Results showed that different agricultural practices had significant effects on plant leaf photosynthesis, transpiration, soil respiration, height and yield, but not on LAI and biomass. The average corn yield in the NT-URAN was 10.03 ton/ha, 28.9% more than in the CT-URAN. Compared to the NT-URAN, the NT-biochar had lower soil respiration and similar yield. All variables measured showed remarkable variations among the three years. Our results indicated that no tillage treatment substantially increased corn yield, probably due to the preservation of soil moisture during drought periods

Artificial Intelligence and Visual Analytics: A Deep-Learning Approach to Analyze Hotel Reviews & Responses

With a growing number of online reviews, consumers often rely on these reviews to make purchase decisions. However, little is known about managerial responses to online hotel reviews. This paper reports on a framework to integrate visual analytics and machine learning techniques to investigate whether hotel managers respond to positive and negative reviews differently and how to use a deep-learning approach to prioritize responses. In this study, forty 4- and 5-star hotels in London with 91,051 reviews and 70,397 responses were collected and analyzed. Visual analyses and machine learning were conducted. The results indicate most hotels (72.5%) showing no preference to respond to positive and negative reviews. Our proposed deep-learning approach outperformed existing algorithms to prioritize responses