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Fashion sustainability advocacy and mindful consumption in the digital age: an analysis of Instagram influencers in the UK and Europe
No full textInternational audienceSocial media has become a prominent communication channel for fashion brands, playing a key role in influencing today’s consumer behaviour. One platform that has gained significant popularity in the past decade is Instagram, with its visually oriented focus. This platform has created dynamic new ways for brands, consumers, and content creators to interact. As Instagram continues to grow, it has increasingly been used for sustainability discourse, a contemporary theme in the fashion industry due to the environmental and social impacts.Previous research on Instagram's sustainability discourse has primarily focused on the perspectives of consumers and brands (Palakshappa et al., 2024; Marcella, 2023), particularly brand communications (Pookulangara et al., 2024; Milanesi et al., 2022) and consumer engagement strategies (Shahrin et al., 2022; Danielle et al., 2021). There has been limited exploration of how influencers independently communicate and advocate for sustainable fashion (Vladimirova et al., 2023; Jacobson & Harrison, 2022) and their influence on encouraging consumers to practice mindful consumption. Mindful consumption is defined as being conscious of both internal factors (thoughts and emotions) and external influences (product details and advertising) when considering the effects of consumption on oneself, society, and the environment (Garg et al., 2024).This study aims to investigate the role of Instagram content creators in shaping the sustainable fashion discourse and their influence in motivating consumers toward mindful consumption.Cognitive dissonance theory and parasocial interactions will be used as theoretical lens for this research (Cairns et al., 2022; Festinger, 1957) based on the idea that influencers can help reduce followers' cognitive dissonance regarding sustainable fashion by leveraging parasocial relationships. The influencer is considered as a friend by his/her follower despite having little or no relationship with them, where trust and admiration make their advocacy more persuasive. By sharing personal transformation stories telling how they transitioned to sustainable fashion or why they advocate for it, normalising small sustainable choices, and framing ethical fashion as aspirational and identity-enhancing, they help followers align their self-concept with mindful consumption, making sustainability feel desirable rather than restrictive (Cairns et al., 2022; Festinger, 1957).This study will employ a netnography approach (Vanini, 2019) to analyse Instagram content related to sustainable fashion communication, focusing specifically on fashion influencers based in the UK and Europe. Netnography is inspired by ethnography but applied to a digital context. It was developed by Kozinets to study digital communities. It facilitates the comprehension of behaviours and relations of participants in digital spaces (Vanini, 2019). Regardless of the absence of physical presence, members of online communities engage with each other’s emotions and expressions, reflecting fundamental aspects of human nature. These communities, which operate through social media facilitate interactions, allowing members to connect and communicate effectively in a digital space.Netnography is also used to understand the impact of influencers on their followers in the context of social media. Indeed, netnography has been applied in influencer marketing to investigate parasocial relationships between influencers and viewers, particularly in the context of travel live streaming (Deng, Benckendorff, & Wang, 2022). Therefore, netnography is well-suited for our research on how influencers advocating for sustainable consumption influence their followers. The selection of influencers will focus on those who actively advocate for sustainable fashion and have developed narrative strategies to encourage their followers to adopt more mindful consumption. We will analyse their narrative strategies in their posts and their interactions with their community. In total, we plan to collect data from 40 influencers (20 from the UK and 20 from France). Additionally, we will gather comments on their posts made by their followers. We plan to use a BERT deep-learning model to identify the narratives of the influencers and examine how they interact with their community to encourage mindful fashion consumption.This research will contribute to both academia and industry in two main ways. First, it will address the gap identified in the literature regarding the role of content creators in advocating sustainability and promoting mindful consumption. Second, the research will provide actionable insights for content creators on how to effectively communicate sustainability through Instagram to encourage mindful consumption
The Relationship Between France and Japan in Studying the Interpretation of Acousmatic Music
No full textInternational audienceThe article discusses a partnership between France and Japan on the subject of interpreting acousmatic music. The project began in France, in collaboration with the Motus musical company, CNRS, and the Paris-Saclay University. It aims to capture, analyze, and preserve interpretation by loudspeaker orchestra, known as ‘acousmoniums’. A device has been developed to record audio, MIDI and video performances. The MotusLab-Tool software was specially designed for analyzing and teaching interpretation using adapted visualizations. Since 2018, collaborations with the ACSM116 Festival have made it possible to create recordings using Japa-nese acousmoniums. These collaborations have also enhanced the quality of recording equipment, as well as initiated artistic style comparisons. In this way, several pieces were performed in France and Japan by various artists, with different acousmoniums
Electron Transfer Dissociation and Synchrotron UV Photodissociation of Trapped Sodiated Ions Produced From Polyacrylates by Electrospray Ionization
No full textInternational audienceRationale. Poly (acrylates)s can be distinguished from one another by the nature of their side chains. From model poly (acrylates)s, the purpose of this work was to evaluate the contribution of alternative activation techniques to the collisional activation, based on ion–ion and ion–photon interactions.Methods. Sodiated poly (acrylate)s produced by electrospray were isolated in an ion trap and then submitted to interactions with fluoranthene anions (by electron transfer dissociation) or with UV photons (from a synchrotron UV source, 16 eV) to induce gas‐phase decomposition. The resulting fragmentation pathways were investigated and compared with collision‐induced dissociation (CID). Ion mobility spectrometry was coupled to UV photoactivation for some isobaric species.Results. Electron capture from fluoranthene anions or electron loss under synchrotron UV irradiation induced dissociation that differs from CID. A coupling of ion mobility with UV photoactivation allowed the fragmentation of two isobaric species separately.Conclusions. The decomposition products (ETD, UV‐PD) stand out from those coming from classical low‐energy CID by inducing specific side‐chain fragmentations. These particular fragmentations make them easy to identify
Analysis of multiple contact types within the framework of semi-finite element method
No full textInternational audienceDynamic contact problems are common in engineering systems. Current dynamic contact simulations are prone to energy non-conservation and over-reliance on nodes accuracy. To address the above difficulties, a numerical algorithm based on the bipotential theory for solving the dynamic contact problems of multibody systems is proposed. Within the framework of semi-finite element method, the Uzawa iteration is embedded in Newton iteration to solve the nonlinear equation. By constructing the adaptive virtual points on the contact surface, the bipotential theory is introduced to compute the local dynamic contact force. In this work, both the interactive contact interface and the coupling contact interface are considered, and the numerical examples are extended from two-dimension line-to-line contact to three-dimension surface-to-surface contact. In addition, the influence of coupling components on the deformation and motion of each subsystem is also revealed. The numerical results show that the proposed algorithm is effective and stable, satisfies the law of energy conservation strictly and reduces the over-dependence on the nodes accuracy. This work can provide a reference for further research on balancing computation efficiency and accuracy
Immersion dans l’univers audiovisuel de Prometheus et Alien : Covenant (Ridley Scott, 2012, 2017) : pour une présence et une hapticité sonores
No full textInternational audienc
Straight from the Horse’s Mouth: Timing and Zoogeography of Domesticated Horse Arrivals in Mongolia and China
No full textInternational audienceThe timing, geographical pathways, and earliest uses for horses (Equus caballus) in East Asia have long been a scientific puzzle vigorously debated by scholars with different backgrounds across diverse disciplinary fields. Over the past two decades, a wide range of high-resolution evidence has been presented documenting the multi-regional dispersion of domesticated horses, but questions still abound, especially in the eastern regions of Eurasia. This study provides a rigorous critique of this body of evidence and advances hypotheses as to when and where domesticated horses first arrived in Mongolia and China. We present the earliest ancient DNA evidence for the DOM2 genetic lineage of modern domesticated horses in Mongolia and evaluate a comprehensive dataset of radiocarbon dates for East Asian domesticated horses using a Bayesian statistical approach that is powerful but seldom utilized by archaeologists. Our genetic and chronological evidence demonstrates that horses far to the east in Mongolia, interred in monumental prone burial contexts, were domesticated and contemporaneous with the earliest horses documented in western regions of Mongolia and Xinjiang. These results both complicate and clarify major questions related to the occurrence of domesticated horses within the greater region and help to explain the development of horse culture(s) and knowledge on the eastern steppe and at the Late Shang capital of Yinxu
Synthesis of polysaccharide-based block copolymers obtained by click chemistry from opened β-cyclodextrin and growth polymerization
No full textInternational audienceThe synthesis of well-defined oligosaccharides via cyclodextrin (CD) ring opening is an efficient method for obtaining tailored monomers, which are then suitable for further polymerization. Starting from benzoylated β-CD, which contains seven glucose units, pure difunctionalized benzoylated heptaoses were synthesized. This approach produced heptaoligosaccharides with either azide (A) or propargyl (B) as reactive groups at the reducing and non-reducing ends with a yield between 81 and 96 %, and corresponding to α,ω-diazidoheptaose, α,ω-dipropargylheptaose, and ω-azido-α-propargylheptaose for the AA, BB, and AB monomers, respectively. A highly efficient deprotection process provided access to difunctionalized linear and polar heptasaccharides with high purity (87–99 %). The newly synthesized oligosaccharidic blocks were then polymerized via copper-catalyzed 1,3-dipolar cycloaddition leading to seven original and distinct polymers. These include unprotected (AA-BB or AB-AB) or benzoylated (AB-AB) homo- and hetero-copolymers, as well as hydrophobic blocks randomly distributed with hydrophilic ones (AB-AB) or alternating unprotected-benzoylated blocks (AA-BB). Two additional polymers were obtained by quaternization of triazole rings. Characterization by SEC, TGA, XRD, NMR, and MALDI-TOF MS revealed that a mixture of polymers containing 1–34 blocks could be obtained, with a degree of polymerization ranging from 126 to 238 sugar units and moderate to excellent yields (30–85 %)
Understanding the worst-kept secret of high-frequency trading
No full textInternational audienceVolume imbalance in a limit order book is often considered as a reliable indicator for predicting future price moves. In this work, we seek to analyse the nuances of the relationship between prices and volume imbalance. To this end, we study a market-making problem which allows us to view the imbalance as an optimal response to price moves. In our model, there is an underlying efficient price driving the mid-price, which follows the model with uncertainty zones. A single market maker knows the underlying efficient price and consequently the probability of a mid-price jump in the future. She controls the volumes she quotes at the best bid and ask prices. Solving her optimization problem allows us to understand endogenously the price-imbalance connection and to confirm in particular that it is optimal to quote a predictive imbalance. Our model can also be used by a platform to select a suitable tick size, which is known to be a crucial topic in financial regulation. The value function of the market maker's control problem can be viewed as a family of functions, indexed by the level of the market maker's inventory, solving a coupled system of PDEs. We show existence and uniqueness of classical solutions to this coupled system of equations. In the case of a continuous inventory, we also prove uniqueness of the market maker's optimal control policy
Learning conditional distributions on continuous spaces
No full textInternational audienceWe investigate sample-based learning of conditional distributions on multi-dimensional unit boxes, allowing for different dimensions of the feature and target spaces. Our approach involves clustering data near varying query points in the feature space to create empirical measures in the target space. We employ two distinct clustering schemes: one based on a fixed-radius ball and the other on nearest neighbors. We establish upper bounds for the convergence rates of both methods and, from these bounds, deduce optimal configurations for the radius and the number of neighbors. We propose to incorporate the nearest neighbors method into neural network training, as our empirical analysis indicates it has better performance in practice. For efficiency, our training process utilizes approximate nearest neighbors search with random binary space partitioning. Additionally, we employ the Sinkhorn algorithm and a sparsity-enforced transport plan. Our empirical findings demonstrate that, with a suitably designed structure, the neural network has the ability to adapt to a suitable level of Lipschitz continuity locally. For reproducibility, our code is available at \url{https://github.com/zcheng-a/LCD_kNN}
The Silene latifolia genome and its giant Y chromosome
No full textData and materials availability: Sequencing data (long reads, short reads, and Omni-C datasets), genome assembly, and annotation are available under the project PRJNA1132743 on the National Center for Biotechnology Information (NCBI). All analyses and pipelines to generate figures are available on GitHub (https://github.com/Silene-genome/genome-paper) and Zenodo: https://doi.org/10.5281/zenodo.14434538.International audienceIn many species with sex chromosomes, the Y is a tiny chromosome. However, the dioecious plant has a giant ~550-megabase Y chromosome, which has remained unsequenced so far. We used a long- and short-read hybrid approach to obtain a high-quality male genome. Comparative analysis of the sex chromosomes with their homologs in outgroups showed that the Y is highly rearranged and degenerated. Recombination suppression between X and Y extended in several steps and triggered a massive accumulation of repeats on the Y as well as in the nonrecombining pericentromeric region of the X, leading to giant sex chromosomes. Using sex phenotype mutants, we identified candidate sex-determining genes on the Y in locations consistent with their favoring recombination suppression events 11 and 5 million years ago