AGB Stars and Their Circumstellar Envelopes: An Operative Approach to Computing Their Atmospheres

The study of AGB stars necessarily covers a wide range of topics, from the primary astronomical observations to their interpretation in terms of fundamental physics. All that requires proper ad hoc methodologies, among which numerical modeling of the outer layers of AGB stars plays a paramount role. In this paper, we present an iterative sequential procedure, operative and physically sound, tailored to compute extended stellar atmospheres. It will constitute the backbone of the in fieri TEIDE package to be implemented into our VULCAN code. Such an improvement will allow us to compute more realistic models of the extended atmospheres of AGB stars taking into account important physical aspects that are neglected in the actual version of VULCAN.

Lenience breeds strictness: The generosity-erosion effect in hiring decisions

In recruitment processes, candidates are often judged one after another. This sequential procedure affects the outcome of the process. Here, we introduce the generosity-erosion effect, which states that evaluators might be harsher in their assessment of candidates after grading previous candidates generously. Generosity is defined as giving a candidate the lowest possible grade required to progress in the hiring process. Analyzing a high-stake hiring process, we find that for each candidate graded generously, the probability for subsequent candidates to pass decreased by 7.7% (experiment 1; N = 11,281). Testing the boundary conditions of the generosity-effect, we explore a hiring process that, in contrast to the previous process, was very selective, because candidates were more likely to fail than to pass. In this scenario, no evidence is found for the generosity-erosion effect (experiment 2; N = 3171). Practical implications and mechanisms underlying the generosity-erosion effect are further discussed.

Sequential Procedure for Improving the Efficiency of CI Engine by Using Artificial Neural Networks

The authors have requested that this preprint be withdrawn due to a need to make corrections.

Improving judgment accuracy by sequential adjustment

Judging an object’s value based on relevant cues can be challenging. We propose a simple method to improve judgment accuracy: Instead of estimating a value after seeing all available cues simultaneously, individuals view cues sequentially, one after another, making and adjusting their estimate at each step. The sequential procedure may alleviate computational difficulties in cue integration, leading to higher judgment accuracy. We tested this hypothesis in two real-world tasks in which participants judged either the price of diamonds or the fuel economy of cars. Two studies with professional jewelers and car salespeople show that most participants indeed judged more accurately with a sequential than with a simultaneous procedure. Another two studies with college students further support this finding and show additionally that the sequential procedure could raise the judgment accuracy of inexperienced students to the same level as that of professionals judging with the simultaneous procedure.