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This paper develops a model in which a sender strategically communicates with a group of receivers whose payoffs depend on the sender's information. It is shown that aggregate payoff externalities create an endogenous conflict of interests between the sender and the receivers, rendering full information revelation, in general infeasible. We demonstrate that an exogenous bias in the sender's preferences can improve public information provision and raise welfare. Two applications of the setup are discussed. [ABSTRACT FROM AUTHOR]

How diverse animal communication signals have arisen is a question that has fascinated many. Xenopus frogs have been a model system used for three decades to reveal insights into the neuroendocrine mechanisms and evolution of vocal diversity. Due to the ease of studying central nervous system control of the laryngeal muscles in vitro, Xenopus has helped us understand how variation in vocal communication signals between sexes and between species is produced at the molecular, cellular, and systems levels. Yet, it is becoming easier to make similar advances in non-model organisms. In this paper, we summarize our research on a group of frog species that have evolved a novel hind limb signal known as 'foot flagging.' We have previously shown that foot flagging is androgen dependent and that the evolution of foot flagging in multiple unrelated species is accompanied by the evolution of higher androgen hormone sensitivity in the leg muscles. Here, we present new preliminary data that compare patterns of androgen receptor expression and neuronal cell density in the lumbar spinal cord – the neuromotor system that controls the hind limb – between foot-flagging and non-foot-flagging frog species. We then relate our work to prior findings in Xenopus , highlighting which patterns of hormone sensitivity and neuroanatomical structure are shared between the neuromotor systems underlying Xenopus vocalizations and foot-flagging frogs' limb movement and which appear to be species-specific. Overall, we aim to illustrate the power of drawing inspiration from experiments in model organisms, in which the mechanistic details have been worked out, and then applying these ideas to a non-model species to reveal new details, further complexities, and fresh hypotheses. [Display omitted] • Communication signal diversification is associated with evolution of androgen-mediated traits • Comparing Xenopus and foot-flagging frogs reveals distinct neuroendocrine patterns associated with signal evolution • Comparative data on androgen receptor distribution and cell density in foot-flagging frog spinal cord is presented • Lumbar spinal circuitry may differ in foot-flagging frogs compared to other species [ABSTRACT FROM AUTHOR]

Sustainability reports may play an important role as a supporting tool in the transition of organisations towards more circular economy models, since their content can help to measure, monitor and communicate the organisations' transition and to establish goals in the short/medium term. The aim of this study is to determine whether it is possible to calculate indicators capable of measuring the transition of organisations towards circularity from the information that they are currently communicating in their Corporate Sustainability Reports (CSRs), and what information would need to be incorporated in these reports to successfully carry out this procedure. To this end, by applying a three-step methodology, 34 indicators grouped into 10 categories were proposed to measure the level of circularity of organisations. This was completed with a detailed proposal of units/metrics to measure the indicators, based on those that organisations commonly use in their CSRs. For this purpose, information from 8 international programmes/frameworks that measure circularity at the territorial level was combined with circularity information that organisations are currently communicating in their CSRs. Finally, the proposed set of indicators and metrics were applied to a Spanish organisation dedicated to the forestry and paper sector with a CSR based on GRI-Standards. The results demonstrated that 25 of the 34 proposed indicators (74%) can be measured directly using the information included in the CSRs. • Which indicators measure the advance of organisations towards circularity? • Which information organisations communicate in their Sustainability Reports (CSR)? • Can be circular indicators calculated using data from CSR? • Case study: 74% of the circular indicators can be calculated using data from CSR. [ABSTRACT FROM AUTHOR]

Advances in knowledge about breast cancer risk factors have led to the development of more comprehensive risk models. These integrate information on a variety of risk factors such as lifestyle, genetics, family history, and breast density. These risk models have the potential to deliver more personalised breast cancer prevention. This is through improving accuracy of risk estimates, enabling more effective targeting of preventive options and creating novel prevention pathways through enabling risk estimation in a wider variety of populations than currently possible. The systematic use of risk tools as part of population screening programmes is one such example. A clear understanding of how such tools can contribute to the goal of personalised prevention can aid in understanding and addressing barriers to implementation. In this paper we describe how emerging models, and their associated tools can contribute to the goal of personalised healthcare for breast cancer through health promotion, early disease detection (screening) and improved management of women at higher risk of disease. We outline how addressing specific challenges on the level of communication, evidence, evaluation, regulation, and acceptance, can facilitate implementation and uptake. [ABSTRACT FROM AUTHOR]

This paper introduces an innovative functional magnetic resonance imaging (fMRI) protocol to study real verbal interactions while limiting the impact of speech-related movement artefacts. This protocol is based on a sparse sampling acquisition technique and allowed participants to complete a referential communication task with a real interaction partner. During verbal interactions, speakers adjust their verbal productions depending on their interlocutors' knowledge of the referents being mentioned. These adjustments have been linked to theory of mind (ToM), the ability to infer other's mental states. We thus sought to determine if the brain regions supporting ToM would also be activated during a referential communication task in which participants have to present movie characters that vary in their likelihood of being known by their interlocutor. This pilot study establishes that the sparse sampling strategy is a viable option to study the neural correlates of referential communication while minimizing movement artefacts. In addition, the brain regions supporting ToM were recruited during the task, though specifically for the conditions where participants could adjust their verbal productions to the interlocutor's likely knowledge of the referent. This study therefore demonstrates the feasibility and relevance of a sparse-sampling approach to study verbal interactions with fMRI, including referential communication. [ABSTRACT FROM AUTHOR]

Animated GIF has become a key communication tool in contemporary social platforms thanks to highly compatible with affective performance, and it is gradually adopted in commercial applications. Therefore, the copyright protection of the animated GIF requires more attention. Digital watermarking is an effective method to embed invisible data into a digital medium that can identify the creator or authorized users. However, few works have been devoted to robust watermarking for the animated GIF. One of the main challenges is that the animated image also contains time frame dimension information compare with still images. This paper proposes a robust blind watermarking framework based 3D convolutional neural networks for the animated GIF image, which achieves watermark image embedding and extraction for the animated GIF. Also, noise simulation is developed in frame-level to ensure robustness for the attack of the temporal dimension in this framework. Furthermore, the invisibility of the watermarked animated image is optimized by adversarial learning. Experimental results provide the effectiveness of the proposed framework and show advantages over existing works. • A novel robust watermarking method for the animated GIF image is proposed. • Employ 3D convolutional neural networks to learn the feature of the animated GIF image at the frame-level. • Design various noise attacks to gain robustness of the animated GIF image watermarking. [ABSTRACT FROM AUTHOR]