Responding to recent concerns about the reliability of the published literature in psychology and other disciplines, we formed the X-Phi Replicability Project (XRP) to estimate the reproducibility of experimental philosophy (osf.io/dvkpr). Drawing on a representative sample of 40 x-phi studies published between 2003 and 2015, we enlisted 20 research teams across 8 countries to conduct a high-quality replication of each study in order to compare the results to the original published findings. We found that x-phi studiesas represented in our samplesuccessfully replicated about 70% of the time. We discuss possible reasons for this relatively high replication rate in the field of experimental philosophy and offer suggestions for best research practices going forward.

The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception, learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment, life, and mind, its epistemic status is unclear. Also unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences. Keywords Adaptation • Free energy • Life • Mechanism • Organicism 1 Introduction According to the free-energy principle (FEP), all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to explain how sensory cortex infers the causes of its inputs and learns causal regularities, FEP has been used to elucidate the function of action, perception, and attention, and to account for organisms' evolution and development (

According to a growing trend in theoretical neuroscience, the human perceptual system is akin to a Bayesian machine. The aim of this article is to clearly articulate the claims that perception can be considered Bayesian inference and that the brain can be considered a Bayesian machine, some of the epistemological challenges to these claims; and some of the implications of these claims. We address two questions: (i) How are Bayesian models used in theoretical neuroscience? (ii) From the use of Bayesian models in theoretical neuroscience, have we learned or can we hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine? From actual practice in theoretical neuroscience, we argue for three claims. First, currently Bayesian models do not provide mechanistic explanations; instead they are useful devices for predicting and systematizing observational statements about people's performances in a variety of perceptual tasks. That is, currently we should have an instrumentalist attitude towards Bayesian models in neuroscience. Second, the inference typically drawn from Bayesian behavioural performance in a variety of perceptual tasks to underlying Bayesian mechanisms should be understood within the three-level framework laid out by David Marr ([1982]). Third, we can hope to learn that perception is Bayesian inference or that the brain is a Bayesian machine to the extent that Bayesian models will prove successful in yielding secure and informative predictions of both subjects' perceptual performance and features of the underlying neural mechanisms.

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Textile Reinforced Concrete (TRC) is an advanced cement-based material in which fabrics used as reinforcement can bring significant loads in tension, allowing architects and engineers to use thin cross-sections. Previous research projects, developed during the last 10 years mainly in Germany, Israel and the USA, have shown the capabilities of such a material. In this paper an extensive experimental investigation of TRC is presented: tensile tests were carried out to obtain a complete mechanical characterization of the composite material under standard conditions, considering the influence of different variables such as reinforcement ratio, fabric geometry, curing conditions, displacement rate and specimen size