Miracle-dz/UniFAR-FTUs huggingface dataset:
Protocole d’annotation multi-label pour une nouvelle approche à la génération de réponse socio-émotionnelle orientée-tâche

Depuis l’apparition des systèmes conversationnels, la modélisation des comportements humains constitue un axe de recherche majeur afin de renforcer l’expression des attributs émotionnels de ces systèmes. En nous intéressant aux agents conversationnels génératifs orientés-tâches, nous proposons une nouvelle approche pour rendre la réponse générée plus pertinente au contexte émotionnel de l’interlocuteur. Cette approche consiste à ajouter une étape supplémentaire de prédiction de labels pour conditionner la réponse générée et assurer sa pertinence au contexte socio-émotionnel de l’utilisateur. Nous proposons une formulation de cette nouvelle tâche de prédiction en nous appuyant sur un protocole d’annotation de données que nous avons conçu et implémenté. À travers cet article, nous apportons les contributions suivantes: la formulation de la tâche de prédiction de labels socio-émotionnels et la description du protocole d’annotation associé. Avec cette méthodologie, nous visons à développer des systèmes conversationnels socialement pertinents et indépendants.
Attention sur les spans pour l’analyse syntaxique en constituants

Nous présentons une extension aux analyseurs syntaxiques en constituants neuronaux modernes qui consiste à doter les constituants potentiels d’une représentation vectorielle affinée en fonction du contexte par plusieurs applications successives d’un module de type transformer efficace (pooling par attention puis transformation non-linéaire). Nous appliquons cette extension à l’analyseur CRF de Yu Zhang & Al.Expérimentalement, nous testons cette extension sur deux corpus (PTB et FTB) avec ou sans vecteurs de mots dynamiques: cette extension permet d’avoir un gain constant dans toutes les configurations.
Entity Enhanced Attention Graph-Based Passages Retrieval

Passage retrieval is crucial in specialized domains where documents are long and complex, such as patents, legal documents, scientific reports, etc. We explore in this paper the integration of Entities and passages in Heterogeneous Attention Graph Models dedicated to passage retrieval. We use the two passage retrieval architectures based on re-ranking proposed in [1]. We experiment our proposal on the TREC CAR Y3 Passage Retrieval Task. The results obtained show an improvement over state-of-the-art techniques and proves the effectiveness of the approach. Our experiments also show the importance of using adequate parameters for such approach.
Exploitation de plongements de graphes pour l’extraction de relations biomédicales

L’intégration de connaissances externes dans les modèles neuronaux est très étudiée pour améliorer les performances des modèles de langue pré-entraînés, notamment en domaine biomédical. Dans cet article, nous explorons la contribution de plongements de bases de connaissances à une tâche d’extraction de relations. Pour deux mentions d’entités candidates dans un texte, nous faisons l’hypothèse que la connaissance de relations entre elles, issue d’une base de connaissances (BC) externe, aide à prédire l’existence d’une relation dans le texte, y compris lorsque les relations de BC sont différentes de celles du texte. Notre approche consiste à calculer des plongements du graphe de BC et à estimer la possibilité pour chaque paire d’entité du texte qu’elle soit reliée par une relation de BC. Les expériences menées sur trois tâches d’extraction de relations en domaine biomédical montrent que notre méthode surpasse le modèle PubMedBERT de base et donne des performances comparables aux méthodes de l’état de l’art.
Questionner pour expliquer: construction de liens explicites entre documents par la génération automatique de questions

Cette article présente une méthode d’exploration de documents basée sur la création d’un ensemble synthétique de questions et de réponses portant sur le corpus, ensemble qui est ensuite utilisé pour établir des liens explicables entre les documents. Nous menons une évaluation quantitative et qualitative des questions automatiquement générées en termes de leur forme et de leur pertinence pour l’exploration de la collection. De plus, nous présentons une étude quantitative des liens obtenus grâce à notre méthode sur une collection de document provenant d’archives numérisés.
Qui de DrBERT, Wikipédia ou Flan-T5 s’y connaît le plus en questions médicales ?

Ce papier décrit la participation de l’équipe LIUM-IRISA à la campagne d’évaluation DEFT 2023.Notre équipe a participé à la tâche principale. Cette année, celle-ci consiste à la mise en placed’approches afin de répondre automatiquement à des questions à choix multiples. Nous avons mis enplace plusieurs systèmes, un premier avec une base de connaissances, un second système utilisant unmodèle génératif, un système à base de similarité et un dernier système combinant un ensemble dedescripteurs.
Mechanische Kreislaufunterstützung im Schock

Zusammenfassung Mechanische Kreislaufunterstützungssysteme (engl. Mechanical Circulatory Support, MCS) haben in den letzten Jahren eine zunehmende Bedeutung in der akutmedizinischen Therapie des kritisch kranken Patienten im Schock erlangt. Aktuell stehen in Europa verschiede Systeme zur Verfügung, die sich in Wirkweise und Einsatzgebiet signifikant unterscheiden. Neben den MCS-Charakteristika und der Zentrumsexpertise sind aber auch Patientencharakteristika für die Auswahl des richtigen MCS zu beachten. Unterschiedliche Schockformen fordern eine differenzierte Therapie, je nach Ätiologie des Schocks und seiner hämodynamischen Akzentuierung (so braucht z. B. ein infarktbedingter kardiogener Schock mit führendem Linksherzversagen eine andere Therapie als ein infarktbedingter kardiogener Schock mit führendem Rechtsherzversagen). Die Auswahl des jeweiligen Herzunterstützungssystems richtet sich nach der Pathophysiologie der zugrunde liegenden Erkrankung. Bisweilen sind Kombinationen von mehreren Unterstützungssystemen erforderlich. Dieser Übersichtsartikel diskutiert die verschiedenen Systeme (extrakorporale Membranoxygenierung, intraaortale Ballonpumpe, Mikroaxillarpumpe/perkutanes linksventrikuläres Unterstützungssystem, perkutanes rechtsventrikuläres Unterstützungssystem) und deren Einsatzmöglichkeit im Kontext der verschiedenen Schockformen.
Reperfusion and cytoprotective agents are a mutually beneficial pair in ischaemic stroke therapy: an overview of pathophysiology, pharmacological targets and candidate drugs focusing on excitotoxicity and free radical

Stroke is the second-leading cause of death and the leading cause of disability in much of the world. In particular, China faces the greatest challenge from stroke, since the population is aged quickly. In decades of clinical trials, no neuroprotectant has had reproducible efficacy on primary clinical end points, because reperfusion is probably a necessity for neuroprotection to be clinically beneficial. Fortunately, the success of thrombolysis and endovascular thrombectomy has taken us into a reperfusion era of acute ischaemic stroke (AIS) therapy. Brain cytoprotective agents can prevent detrimental effects of ischaemia, and therefore ‘freeze’ ischaemic penumbra before reperfusion, extend the time window for reperfusion therapy. Because reperfusion often leads to reperfusion injury, including haemorrhagic transformation, brain oedema, infarct progression and neurological worsening, cytoprotective agents will enhance the efficacy and safety of reperfusion therapy by preventing or reducing reperfusion injuries. Therefore, reperfusion and cytoprotective agents are a mutually beneficial pair in AIS therapy. In this review, we outline critical pathophysiological events causing cell death within the penumbra after ischaemia or ischaemia/reperfusion in the acute phase of AIS, focusing on excitotoxicity and free radicals. We discuss key pharmacological targets for cytoprotective therapy and evaluate the recent advances of cytoprotective agents going through clinical trials, highlighting multitarget cytoprotective agents that intervene at multiple levels of the ischaemic and reperfusion cascade.
Effects of consecutive workdays and days off on low back pain, fatigue and stress: prospective cohort study among warehouse and construction workers

Objectives Limited knowledge exists about day-to-day changes in physical and mental symptoms in warehouse and construction workers. This study investigated the associations between consecutive workdays and days off with low back pain (LBP) intensity, bodily fatigue and mental stress. Methods Participants (n=224) received daily questions for 21 days about LBP, fatigue, stress (outcome, 0–10 scales), and workdays and days off (exposure). We tested associations between 1–3 workdays (n=148) and 1–2 days off (n=158) with LBP intensity, bodily fatigue and mental stress after work and the following morning using linear mixed models with repeated measures controlling for relevant confounders. Results Consecutive workdays led to progressively increased LBP intensity, with three workdays increasing LBP intensity by 1.76 (95% CI 1.48 to 2.03) points. Bodily fatigue and mental stress increased after one workday (2.06 (95% CI 1.80 to 2.32) and 0.97 (95% CI 0.77 to 1.17) points, respectively) and remained stable for three workdays. After 1 day off, bodily fatigue and mental stress decreased −1.82 (95% CI −2.03 to −1.61) and −0.88 (95% CI −1.05 to −0.71) points, respectively, without decreasing further. In contrast, LBP intensity decreased progressively −1.09 (95% CI −1.27 to −0.91) and −1.45 (95% CI −1.67 to −1.24) points after 1 and 2 days off, respectively. Conclusions Workdays and days off affected the outcome variables differently. LBP intensity progressively increased with consecutive workdays, while workers needed 2 days off to recover. This study provides valuable knowledge about how to organise the workweek to prevent LBP, fatigue and stress, potentially reducing labour market withdrawal.
Lessons in Prevention and Cure: A User Study of Recovery from Flubot Smartphone Malware

The smishing-based malware Flubot was taken down in mid-2022, yet there is little understanding of how it directly impacted smartphone users. We engage with customers of a partner Internet Service Provider (ISP), who have suffered a Flubot infection on their smartphones. We surveyed 87 ISP customers who had been notified of a Flubot infection, in the months around and preceding the take-down of Flubot. We found that slightly over half of respondents were unaware of the malware infection before being notified, though many others had suspicions. We also observe that just over half of respondents experienced non-technical harms from the malware, with many experiencing harms before notification and several experiencing unwanted or aggressive activity from users of other infected devices. Many respondents reported not having removed the malware, while some discarded the infected device or stopped using online services in their efforts to be more secure afterwards. We offer recommendations, including that clearer guidance be sought to help users identify a malware infection (and not a focus only on prevention), and support provided for recovery from personal harms caused by mobile malware, as the impacts are not only technical.
Performance Analysis of Asymmetric High Gain Multi-Input Converter Under Widely Fluctuating Inputs

In this paper, the performance of a novel asymmetric high gain multi-input converter (AHG-MIC) which is supplied from three voltage sources is presented. The proposed AHG-MIC is synthesized by combining three individual high gain DC-DC converters (HGC) which are excited from different sources with different power ratings. The output of each HGCs is connected in parallel through ORing diodes to mitigate the circulating current and deliver the required output to the load. AHG-MIC is tested by supplying various input voltage levels to infer the voltage gain and power handling capabilities under different load conditions. The performance of the proposed AHG-MIC is analyzed using PSIM software. The performance is thoroughly studied under various combinations of input voltage levels like (i) nullifying one source and maintaining the other two sources at their nominal values, (ii) nullifying one source, making the other source to half of its nominal value while maintaining the 3rd source at its nominal value and (iii) nullifying two sources while maintaining the third source at its nominal value. Further, the output power levels are also lowered to check the overall working capabilities of the proposed AHG-MIC. The overall performance of the AHG-MIC is finally summarized for easier implementation.
Photo Steward: A Deliberative Collective Intelligence Workflow for Validating Historical Archives

Historical photographs of people generate significant cultural and economic value, but correctly identifying the subjects of photos can be a difficult task, requiring careful attention to detail while synthesizing large amounts of data from diverse sources. When photos are misidentified, the negative consequences can include financial losses and inaccuracies in the historical record, and even the spread of mis- and disinformation. To address this challenge, we introduce Photo Steward, an information stewardship architecture that leverages a deliberative workflow for validating historical photo IDs. We explored Photo Steward in the context of Civil War Photo Sleuth (CWPS), a popular online community dedicated to identifying photos from the American Civil War era (1861–65) using facial recognition and crowdsourcing. While the platform has been successful in identifying hundreds of unknown photographs, there have been concerns about unverified identifications and misidentifications. Our exploratory evaluation of Photo Steward on CWPS showed that its validation workflow encouraged users to deliberate while making photo ID decisions. Further, its stewardship visualizations helped users to assess photo ID information accurately, while fostering diverse forms of stigmergic collaboration.
Post-Spotlight Posts: The Impact of Sudden Social Media Attention on Account Behavior

Within social media communities, sudden attention is a frequent phenomenon where a particular user receives a rapid onset of heightened engagement. Using a statistical analysis, we examine the impacts that this outsized attention has on the subsequent behavior of accounts who received sudden social media attention for Twitter posts in the early stages of the Covid-19 pandemic. We find that accounts that received sudden social media attention were more likely to post after receiving sudden social media attention, though this effect was not persistent and did not boost original content production. We also find that these accounts were significantly more likely to alter their self-presentation through updating their “bio” after receiving suddenly increased attention.
Research on the Auxiliary Function and Mechanism of Social Media for Postgraduate Curriculum Learning ——Qualitative Analysis Based on Grounded Theory

With the wide application of video social media such as Tiktok and Station B, significant changes have occurred in how graduate students learn. Social media, with its rich curriculum supply and social attributes, makes it possible to solve the problems of high speed, severe high difficulty, firm theory, and poor learning effect of postgraduate curriculum learning. This research adopts the grounded theory method and uses NVivo12 qualitative analysis tools to assist in three-level coding to explore social media's supporting role and mechanism for postgraduate curriculum learning. The research found that social media curriculum learning has the advantages of individuality, diversity, freedom, convenience, and enjoyment, creating a new learning space for learners; Establishing a mechanism model of "motivation - media - effectiveness," which provides emotional support, knowledge deepening and intention strengthening; At the same time, however, the course supply of social media also has some problems such as fragmentation of content and information cocoon room, which have some adverse effects. Therefore, in postgraduate course learning, it is necessary to reasonably use social media and other emerging platforms for assisted learning to achieve better learning results.
Purposeful AI

The potential of AI to improve people’s lives is unlimited. However, designing AI-infused systems to realize this potential for all is challenging, and it is particularly challenging within under-served minority communities. Revisiting algorithms and data sources to eliminate biases in AI is an important step toward expanding its benefits. However, this leads to the realization that some applications, although unbiased, may simply not be what marginalized communities need. Marginalized communities live in a unique socioeconomic and cultural context and have difficulties taking advantage of traditional AI-powered systems due to language, digital literacy, or other barriers. Additionally, the systems that currently exist usually fail to address the unique challenges in these communities. Therefore, designers and researchers in AI must understand that a fundamental dimension of fairness and ethics is to empower and lift the lives of under-served populations through purposeful human-AI research. This research not only recognizes the unique intersectionality and needs present in each community, but also treats them as the primary audience by overcoming traditional barriers between researchers and underserved communities. This SIG proposal aims to initiate a multidisciplinary discussion around the design of AI systems that are purposefully targeted to marginalized populations. Within this discussion, our objective is to better understand how to conduct research to support and serve these communities – particularly if we are not members of such communities; and challenge the effectiveness of techniques like user-centered design in the context of AI-infused systems when the designer is not a member of the user community. In addition, we will delve into ways of translating research into practical applications to create a positive impact within these communities and narrow the disparities that exist in the optimal utilization of AI to improve lives for different communities.
Vision: Supporting Citizens in Adopting Privacy Enhancing Technologies

We have witnessed an alarming growth in collecting citizens’ information by businesses and organizations. The more citizens’ information they collect, the greater their ability to utilize this knowledge for their own interests, often at the expense of society members. Despite the efforts made by privacy ecosystem members (such as researchers and regulatory entities) to protect citizens’ privacy against data collectors, the low adoption of Privacy Enhancing Technologies (PETs) by citizens remains concerning. To address these concerns, this vision paper proposes a user-centred approach to develop a tool that assists citizens in adopting PETs effectively. To this end, we plan to (1) understand the factors contributing to low PETs adoption via methods such as focus groups and in-depth interviews, (2) design an interactive tool to support citizens in adopting PETs in a user-friendly manner, and (3) evaluate the tool’s effectiveness through usability testing. The outcome will serve as an interactive tool which first receives the privacy concerns and needs of each user and then provides personalised PET recommendations accordingly.
The Impact of Budget Retrenchment on Income Distribution in Indonesia (including Statistical Annex): A Social Accounting Matrix Application

This document sets out a new method for assessing the implications of public expenditure cuts for income distribution. The instrument is a social accounting matrix providing the appropriate conceptual framework for estimating all the direct and indirect effects of changes in any given category of public expenditure (e.g. agricultural investment or education spending). By using this matrix it is possible to calculate the upstream effects of an adjustment measure on income distribution. It shows, for instance, that a decline in agricultural investment reduces employment and wages in the building sector. Similarly, a fall in education spending depresses the incomes of the skilled dependent labour force. The downstream effects have also been estimated: in the case of education this means cutbacks in free services to families and so a fall in their incomes. This method has been applied to Indonesia in 1984-88 by comparing the observed effects of lower public spending due to structural . L'impact d'une reduction des depenses budgetaires sur la distribution des revenus en Indonesie : Utilisation d'une matrice de comptabilite sociales Ce document presente une nouvelle methode pour evaluer l'incidence des reductions de depenses publiques sur la distribution des revenus. L'instrument choisi est une matrice de compatibilite sociale qui fournit le cadre conceptuel approprie pour estimer l'ensemble des effets directs et indirects de la variation d'une categorie de depenses publiques (par exemple les investissements dans l'agriculture ou les depenses d'education). Grâce a cette matrice, on peut calculer les effets en amont d'une mesure d'ajustement sur la distribution des revenus; on observe ainsi que la baisse des investissements dans l'agriculture entraine une reduction de l'emploi et des salaires dans le secteur du bâtiment, de meme que la baisse des depenses d'education conduit a celle des revenus des salaries qualifies. D'autre part, on estime les effets en aval : pour l'education cela se traduit par une diminution des services fournis gratuitement aux familles et donc une diminution de leur .
Nudging for Online Misinformation: a Design Inquiry

The use of technology to combat online misinformation is becoming a prominent topic of research and practice, yet most of the existing solutions do not consider the impact of cognitive biases in misinformation-related decision-making. Addressing this gap, the present paper explores the potential of nudging to inform the design of technological interventions that combat misinformation. We report on a design workshop with 29 participants, who were asked to conceive technology-mediated nudges for misinformation with the use of the "Nudge Deck", a design-support tool that presents 23 interaction design mechanisms for nudging.
Patient factors influencing dermal filler complications: prevention, assessment, and treatment

: While rare, complications do occur with the esthetic use of dermal fillers. Careful attention to patient factors and technique can do much to avoid these complications, and a well-informed practitioner can mitigate problems when they do occur. Since cosmetic surgery is usually an elective process, requested by the patient, clinical trials are complex to organize and run. For this reason, an international group of practicing physicians in the field of esthetics came together to share knowledge and to try and produce some informed guidance for their colleagues, considering the literature and also pooling their own extensive clinical experience. This manuscript aims to summarize the crucial aspects of patient selection, including absolute contraindications as well as situations that warrant caution, and also covers important considerations for the pre- and posttreatment periods as well as during the procedure itself. Guidance is given on both immediate and long-term management of adverse reactions. The majority of complications are related to accepting patients inappropriate for treatment or issues of steril-ity, placement, volume, and injection technique. It is clear that esthetic practitioners need an in-depth knowledge of all aspects of treatment with dermal fillers to achieve optimal outcomes for their patients.