Multiple Noises in Diffusion Model for Semi-Supervised Multi-Domain Translation

Domain-to-domain translation involves generating a target domain sample given a condition in the source domain. Most existing methods focus on fixed input and output domains, i.e. they only work for specific configurations (i.e. for two domains, either $D_1\rightarrow{}D_2$ or $D_2\rightarrow{}D_1$). This paper proposes Multi-Domain Diffusion (MDD), a conditional diffusion framework for multi-domain translation in a semi-supervised context. Unlike previous methods, MDD does not require defining input and output domains, allowing translation between any partition of domains within a set (such as $(D_1, D_2)\rightarrow{}D_3$, $D_2\rightarrow{}(D_1, D_3)$, $D_3\rightarrow{}D_1$, etc. for 3 domains), without the need to train separate models for each domain configuration. The key idea behind MDD is to leverage the noise formulation of diffusion models by incorporating one noise level per domain, which allows missing domains to be modeled with noise in a natural way. This transforms the training task from a simple reconstruction task to a domain translation task, where the model relies on less noisy domains to reconstruct more noisy domains. We present results on a multi-domain (with more than two domains) synthetic image translation dataset with challenging semantic domain inversion

European Union Structural and Investment Funds and Celtic Language: An analysis of the 2007-2020 funding period in relation to Breton, Irish, Scottish Gaelic and Welsh

The European Structural and Investment Funds are distributed to the regional level within the EU, targeting primarily regions which are ‘less developed’ in terms of GDP as a percentage of EU average. At the same time, many of the national and linguistic minorities within the EU lie in geographically and economically peripheral areas, such as the traditional areas where Celtic languages are spoken. This working paper uses a qualitative method to examine projects in the regions in which four Celtic languages are or have been traditionally spoken, covering Breton, Irish, Scottish Gaelic and Welsh. Whilst the four languages and their heartland communities varying greatly in terms of numerical size and also economic marginalisation, all have received structural funds which can be linked directly to projects using the language or indirectly through projects in areas where there are a large percentage of speakers of the language. The findings show that the direct links are more prominent in the Scottish Highlands and Islands and West Wales, than the Irish Gaeltacht or Brittany. This is of course concerning in light of the UK’s recent departure from the EU and thus ending of applicability for ESIF

E4F1-mediated control of pyruvate dehydrogenase activity is essential for skin homeostasis.

The multifunctional protein E4 transcription factor 1 (E4F1) is an essential regulator of epidermal stem cell (ESC) maintenance. Here, we found that E4F1 transcriptionally regulates a metabolic program involved in pyruvate metabolism that is required to maintain skin homeostasis. E4F1 deficiency in basal keratinocytes resulted in deregulated expression of dihydrolipoamide acetyltransferase (Dlat), a gene encoding the E2 subunit of the mitochondrial pyruvate dehydrogenase (PDH) complex. Accordingly, E4f1 knock-out (KO) keratinocytes exhibited impaired PDH activity and a redirection of the glycolytic flux toward lactate production. The metabolic reprogramming of E4f1 KO keratinocytes associated with remodeling of their microenvironment and alterations of the basement membrane, led to ESC mislocalization and exhaustion of the ESC pool. ShRNA-mediated depletion of Dlat in primary keratinocytes recapitulated defects observed upon E4f1 inactivation, including increased lactate secretion, enhanced activity of extracellular matrix remodeling enzymes, and impaired clonogenic potential. Altogether, our data reveal a central role for Dlat in the metabolic program regulated by E4F1 in basal keratinocytes and illustrate the importance of PDH activity in skin homeostasis

Neurobiological degeneracy and affordance perception support functional intra-individual variability of inter-limb coordination during ice climbing

This study investigated the functional intra-individual movement variability of ice climbers differing in skill level to understand how icefall properties were used by participants as affordances to adapt inter-limb coordination patterns during performance. Seven expert climbers and seven beginners were observed as they climbed a 30 m icefall. Movement and positioning of the left and right hand ice tools, crampons and the climber's pelvis over the first 20 m of the climb were recorded and digitized using video footage from a camera (25 Hz) located perpendicular to the plane of the icefall. Inter-limb coordination, frequency and types of action and vertical axis pelvis displacement exhibited by each climber were analysed for the first five minutes of ascent. Participant perception of climbing affordances was assessed through: (i) calculating the ratio between exploratory movements and performed actions, and (ii), identifying, by self-confrontation interviews, the perceptual variables of environmental properties, which were significant to climbers for their actions. Data revealed that experts used a wider range of upper and lower limb coordination patterns, resulting in the emergence of different types of action and fewer exploratory movements, suggesting that effective holes in the icefall provided affordances to regulate performance. In contrast, beginners displayed lower levels of functional intra-individual variability of motor organization, due to repetitive swinging of ice tools and kicking of crampons to achieve and maintain a deep anchorage, suggesting lack of perceptual attunement and calibration to environmental properties to support climbing performanc

Application for Customisable Interaction with Physical Objects : A Tool for Speech and Language Therapists

Physical objects with digital properties are being used more and more by the public. One such term for these artefacts include "the Internet of Things''. Most of these objects are often impossible to further modify or customise, and thus serve just the single purpose intended by their creators. This thesis explores the possibility of customising physical objects in order to provide an affordable and flexible way of interacting with them. A prototype, involving a mobile phone application (Android) and wireless sensor technology (NFC tags), was developed for the medical domain of speech and language therapy. The system, developed in close association with two therapists, allows the customisation of current speech and language exercise and associated material. It is designed to also assist with logging the patient interactions during the conduction of such exercises. The proposed solution has been tested and validated by medical experts, and its user interface evaluated by non-patient users

Vision et apprentissage statistique pour la reconnaissance d'items comportementaux

Ce travail consiste en la détection d'items comportementaux permettant la prévention de l'hypovigilance du conducteur au volant. Nous disposons de vidéos prises depuis l'habitacle d'une voiture, chaque image de ces vidéos a été caractérisée par six items comportementaux; notre travail vise à retrouver ces items comportementaux, image par image. L'étude a été décomposée en deux phases : 1) Le suivi du visage et des gestes faciaux sur les vidéos. Nous avons appliqué une méthode de suivi d'objets déformables en vision 3D auquel nous avons inclus un modèle d'apparence basé sur un modèle de mélange. 2) La détection d'items comportementaux à partir des données extraites de ce suivi. Nous avons proposé l'utilisation d'un nouveau critère sensible aux coûts de mauvaise classification afin de résoudre le problème des déséquilibres lié aux items comportementaux. Ce critère est appliqué à la détection des items comportementaux à travers l'utilisation de MLPs et de IOHMMs.This work consists in the detection of behavioral items in order to prevent driver drowsiness. Videos were shot from within a car, and each picture of the video was characterized by six behavioral items. Our work consists in the retrieval of these items, picture by picture. The study was decomposed into two phases: 1) A Head and facial action tracking. A framework to 3D head pose and facial action tracking with an adaptive appearance model based on a mixture model is proposed to deal with face occlusion ; 2) A recognition of the behavioral items based on data retrieved from the tracking. We propose a new criterion leading to an adaptation of maximum likelihood estimation. The model outputs proper conditional probabilities into a user-defined interval. This criterion is applied to MLPs and IOHMMs for the recognition of the behavioral items.COMPIEGNE-BU (601592101) / SudocSudocFranceF

Exploring Photogrammetry : Implementation of a Hybrid Workshop

A photogrammetry workshop was organised under the HumInfra initiative, jointly between Linnaeus University and Umeå University (HumLab). The workshop aimed to provide participants with a comprehensive understanding of photogrammetry techniques within a limited timeframe. With ten participants, the workshop took place simultaneously in Växjö and Umeå, enabling a comparative analysis of the workshop’s effectiveness in different settings. The attendees, from the field of Humanities and Media Technology, were introduced to the fundamental concepts of photogrammetry, including image capturing and 3D model creation. This theoretical part was conducted using Zoom and co-delivered by the two organisers. The practical aspect of the workshop was done offline on each side and involved hands-on experience with industry-standard photogrammetry software, facilitated by experienced professionals. The last stage of the workshop included a discussion about the experience between the two groups of people. The findings revealed that participants successfully acquired the necessary skills to create 3D models in just 45 minutes, indicating the workshop’s efficiency in delivering practical knowledge within a limited time frame. Participant feedback highlighted the workshop’s effectiveness in providing a solid introduction to the world of photogrammetry and emphasised the importance of such initiatives in promoting technological literacy among individuals. This form of teaching redefined the usual hybrid format and was perceived as more rewarding by participants. The workshop’s integration into the HumInfra initiative allowed collaboration between physically distant universities. This event emphasises the significance of such workshops in preparing individuals for the evolving demands of the digital landscape and could be applied to other subjects using hands-on activities. It suggests the potential for further research into the comparative effectiveness of workshops in different settings

Valuation of climbing activities using Multi-Scale Jensen-Shannon Neighbour Embedding

International audienceThis paper presents a study carried out in a controlled environment that aims at understanding behavioural patterns in climbing activities. Multi-Scale Jensen-Shannon Neighbour Embedding [8], a recent advance in non linear dimension reduction, has been applied to recordings of movement sensors in order to help the visualization of coordination modes. Initial clustering results show a correlation with jerk, an indicator of fluency in climbing activities, but provides more details on behavioural patterns