Modeling Human Interaction to Design a Human-Computer Dialog System

This article presents the Cogni-CISMeF project, which aims at improving the health information search engine CISMeF, by including a conversational agent that interacts with the user in natural language. To study the cognitive processes involved during information search, a bottom-up methodology was adopted. An experiment has been set up to obtain human dialogs related to such searches. The analysis of these dialogs underlines the establishment of a common ground and accommodation effects to the user. A model of artificial agent is proposed, that guides the user by proposing examples, assistance and choices

Structural modifications and thermal transitions of standard maize starch after DIC hydrothermal treatment

International audienceStandard maize starch was hydrothermally treated by Instantaneous Controlled Pressure Drop (DIC) process at three pressure levels (1, 2 and 3 bar) corresponding to the temperatures of 100, 122 and 135 C (at 13–27% moisture), respectively. The structural effects of various hydrothermal conditions were examined with differential scanning calorimetry (DSC) and wide-angle X-ray diffraction. In order to understand the changes that occur during DIC treatment, melting endotherms of native maize starch at various moisture contents were determined. The gelatinization temperatures of DIC treated standard maize starch increased with DIC treatment. The transition temperatures (To, Tp) are closely related to the combined effect of pressure and processing time. At approximately 10 min of processing time, To and Tp were 65.7 and 72.3, 68.8 and 73.6 C, 74.8 and 79.8 C for pressure levels of 1, 2 and 3 bar, respectively (against 63.1 and 69.6 C for native starch). DIC treatment narrowed the gelatinization temperature range and decreased gelatinization enthalpy (DH), as the severity of processing conditions increased. DH decreased from 11.4 J g1 (native) to 11.0 (1 bar), 9.0 (2 bar) and 1.7 J g1 (3 bar) for treated maize starch during approximately 10 min. Relative crystallinity of hydrothermally treated starch decreased with increasing DIC conditions. The A-type crystalline pattern was progressively lost (at pressure level P2 bar) and substituted by the Vh-type X-ray diffraction pattern, corresponding to the formation of amylose–lipid complexes. For severe DIC conditions (pressure level of 3 bar), the substitution was completed. Microscopic observations revealed progressive loss of the birefringence of DIC treated starch granules except at low pressure (1 bar), while the integrity of starch granules was preserved for all the conditions. These modifications that reveal important changes in the crystalline organization of the starch granules are related to their functional properties

Antitumour effects of single or combined monoclonal antibodies directed against membrane antigens expressed by human B cells leukaemia

Background: The increasing availability of different monoclonal antibodies (mAbs) opens the way to more specific biologic therapy of cancer patients. However, despite the significant success of therapy in breast and ovarian carcinomas with anti-HER2 mAbs as well as in non-Hodkin B cell lymphomas with anti-CD20 mAbs, certain B cell malignancies such as B chronic lymphocytic leukaemia (B-CLL) respond poorly to anti-CD20 mAb, due to the low surface expression of this molecule. Thus, new mAbs adapted to each types of tumour will help to develop personalised mAb treatment. To this aim, we analyse the biological and therapeutic properties of three mAbs directed against the CD5, CD71 or HLA-DR molecules highly expressed on B-CLL cells. Results: The three mAbs, after purification and radiolabelling demonstrated high and specific binding capacity to various human leukaemia target cells. Further in vitro analysis showed that mAb anti-CD5 induced neither growth inhibition nor apoptosis, mAb anti-CD71 induced proliferation inhibition with no early sign of cell death and mAb anti-HLA-DR induced specific cell aggregation, but without evidence of apoptosis. All three mAbs induced various degrees of ADCC by NK cells, as well as phagocytosis by macrophages. Only the anti-HLA-DR mAb induced complement mediated lysis. Coincubation of different pairs of mAbs did not significantly modify the in vitro results. In contrast with these discrete and heterogeneous in vitro effects, in vivo the three mAbs demonstrated marked anti-tumour efficacy and prolongation of mice survival in two models of SCID mice, grafted either intraperitoneally or intravenously with the CD5 transfected JOK1-5.3 cells. This cell line was derived from a human hairy cell leukaemia, a type of malignancy known to have very similar biological properties as the B-CLL, whose cells constitutively express CD5. Interestingly, the combined injection of anti-CD5 with anti-HLA-DR or with anti-CD71 led to longer mouse survival, as compared to single mAb injection, up to complete inhibition of tumour growth in 100% mice treated with both anti-HLA-DR and anti-CD5. Conclusions: Altogether these data suggest that the combined use of two mAbs, such as anti-HLA-DR and anti-CD5, may significantly enhance their therapeutic potential

Effects of deletion of the Streptococcus pneumoniae lipoprotein diacylglyceryl transferase gene lgt on ABC transporter function and on growth in vivo

Lipoproteins are an important class of surface associated proteins that have diverse roles and frequently are involved in the virulence of bacterial pathogens. As prolipoproteins are attached to the cell membrane by a single enzyme, prolipoprotein diacylglyceryl transferase (Lgt), deletion of the corresponding gene potentially allows the characterisation of the overall importance of lipoproteins for specific bacterial functions. We have used a Δlgt mutant strain of Streptococcus pneumoniae to investigate the effects of loss of lipoprotein attachment on cation acquisition, growth in media containing specific carbon sources, and virulence in different infection models. Immunoblots of triton X-114 extracts, flow cytometry and immuno-fluorescence microscopy confirmed the Δlgt mutant had markedly reduced lipoprotein expression on the cell surface. The Δlgt mutant had reduced growth in cation depleted medium, increased sensitivity to oxidative stress, reduced zinc uptake, and reduced intracellular levels of several cations. Doubling time of the Δlgt mutant was also increased slightly when grown in medium with glucose, raffinose and maltotriose as sole carbon sources. These multiple defects in cation and sugar ABC transporter function for the Δlgt mutant were associated with only slightly delayed growth in complete medium. However the Δlgt mutant had significantly reduced growth in blood or bronchoalveolar lavage fluid and a marked impairment in virulence in mouse models of nasopharyngeal colonisation, sepsis and pneumonia. These data suggest that for S. pneumoniae loss of surface localisation of lipoproteins has widespread effects on ABC transporter functions that collectively prevent the Δlgt mutant from establishing invasive infection

Harnessing Evolution of Multi-Turn Conversations for Effective Answer Retrieval

With the improvements in speech recognition and voice generation technologies over the last years, a lot of companies have sought to develop conversation understanding systems that run on mobile phones or smart home devices through natural language interfaces. Conversational assistants, such as Google Assistant and Microsoft Cortana, can help users to complete various types of tasks. This requires an accurate understanding of the user's information need as the conversation evolves into multiple turns. Finding relevant context in a conversation's history is challenging because of the complexity of natural language and the evolution of a user's information need. In this work, we present an extensive analysis of language, relevance, dependency of user utterances in a multi-turn information-seeking conversation. To this aim, we have annotated relevant utterances in the conversations released by the TREC CaST 2019 track. The annotation labels determine which of the previous utterances in a conversation can be used to improve the current one. Furthermore, we propose a neural utterance relevance model based on BERT fine-tuning, outperforming competitive baselines. We study and compare the performance of multiple retrieval models, utilizing different strategies to incorporate the user's context. The experimental results on both classification and retrieval tasks show that our proposed approach can effectively identify and incorporate the conversation context. We show that processing the current utterance using the predicted relevant utterance leads to a 38% relative improvement in terms of nDCG@20. Finally, to foster research in this area, we have released the dataset of the annotations.Comment: To appear in ACM CHIIR 2020, Vancouver, BC, Canad

An interdisciplinary clinical practice model for the management of low-back pain in primary care: the CLIP project

<p>Abstract</p> <p>Background</p> <p>Low-back pain is responsible for significant disability and costs in industrialized countries. Only a minority of subjects suffering from low-back pain will develop persistent disability. However, this minority is responsible for the majority of costs and has the poorest health outcomes. The objective of the Clinic on Low-back pain in Interdisciplinary Practice (CLIP) project was to develop a primary care interdisciplinary practice model for the clinical management of low-back pain and the prevention of persistent disability.</p> <p>Methods</p> <p>Using previously published guidelines, systematic reviews and meta-analyses, a clinical management model for low-back pain was developed by the project team. A structured process facilitating discussions on this model among researchers, stakeholders and clinicians was created. The model was revised following these exchanges, without deviating from the evidence.</p> <p>Results</p> <p>A model consisting of nine elements on clinical management of low-back pain and prevention of persistent disability was developed. The model's two core elements for the prevention of persistent disability are the following: 1) the evaluation of the prognosis at the fourth week of disability, and of key modifiable barriers to return to usual activities if the prognosis is unfavourable; 2) the evaluation of the patient's perceived disability every four weeks, with the evaluation and management of barriers to return to usual activities if perceived disability has not sufficiently improved.</p> <p>Conclusion</p> <p>A primary care interdisciplinary model aimed at improving quality and continuity of care for patients with low-back pain was developed. The effectiveness, efficiency and applicability of the CLIP model in preventing persistent disability in patients suffering from low-back pain should be assessed.</p

Modélisation du dialogue homme-machine pour la recherche d'informations : approche questions-réponses

This thesis describes the design of a computer-human dialog system for information search. This system is able to interact with the user in natural language using cooperative strategies. To study the dialog processes involved during information search, a bottom-up approach was adopted. Experiments have been set up to obtain human dialogs related to such searches in the context of the health information system CISMeF. It turns out that the structure arising from the analysis of the dialogs matches a semantic approach called “issue-based dialog”. Starting from the model GoDIS, our artificial agent model adds several enhancements that allow to propose examples, assistance and choices. The model is implemented and some elements of evaluation are discussed.Cette thèse décrit la conception d’un système de dialogue Homme- Machine pour la recherche d’informations capable d’interagir avec l’utilisateur en langue naturelle en utilisant des stratégies coopératives. Pour étudier les processus dialogiques impliqués dans la recherche d’informations, une méthodologie ascendante a été adoptée. Une série d’expérimentations a permis le recueil de corpus de dialogues humains présentant de telles recherches dans le cadre du système de documentation médicale CISMeF. L’analyse des dialogues recueillis a montré que leur structure correspond bien aux structures sémantiques de l’approche « questionsréponses ». Fondé sur un modèle existant nommé GoDIS, notre système y intègre de nombreux ajouts permettant d’améliorer la cohérence du dialogue et de proposer des exemples, des choix, des assistances. Une implémentation de ce modèle est réalisée et des pistes d’évaluation sont proposées

Dialogue system modeling for information retrieval with an issue-based approach

Cette thèse décrit la conception d’un système de dialogue Homme- Machine pour la recherche d’informations capable d’interagir avec l’utilisateur en langue naturelle en utilisant des stratégies coopératives. Pour étudier les processus dialogiques impliqués dans la recherche d’informations, une méthodologie ascendante a été adoptée. Une série d’expérimentations a permis le recueil de corpus de dialogues humains présentant de telles recherches dans le cadre du système de documentation médicale CISMeF. L’analyse des dialogues recueillis a montré que leur structure correspond bien aux structures sémantiques de l’approche « questionsréponses ». Fondé sur un modèle existant nommé GoDIS, notre système y intègre de nombreux ajouts permettant d’améliorer la cohérence du dialogue et de proposer des exemples, des choix, des assistances. Une implémentation de ce modèle est réalisée et des pistes d’évaluation sont proposées.This thesis describes the design of a computer-human dialog system for information search. This system is able to interact with the user in natural language using cooperative strategies. To study the dialog processes involved during information search, a bottom-up approach was adopted. Experiments have been set up to obtain human dialogs related to such searches in the context of the health information system CISMeF. It turns out that the structure arising from the analysis of the dialogs matches a semantic approach called “issue-based dialog”. Starting from the model GoDIS, our artificial agent model adds several enhancements that allow to propose examples, assistance and choices. The model is implemented and some elements of evaluation are discussed

Modélisation du dialogue homme-machine pour la recherche d'informations (approche questions-réponses)

Cette thèse décrit la conception d un système de dialogue Homme- Machine pour la recherche d informations capable d interagir avec l utilisateur en langue naturelle en utilisant des stratégies coopératives. Pour étudier les processus dialogiques impliqués dans la recherche d informations, une méthodologie ascendante a été adoptée. Une série d expérimentations a permis le recueil de corpus de dialogues humains présentant de telles recherches dans le cadre du système de documentation médicale CISMeF. L analyse des dialogues recueillis a montré que leur structure correspond bien aux structures sémantiques de l approche questionsréponses . Fondé sur un modèle existant nommé GoDIS, notre système y intègre de nombreux ajouts permettant d améliorer la cohérence du dialogue et de proposer des exemples, des choix, des assistances. Une implémentation de ce modèle est réalisée et des pistes d évaluation sont proposées.This thesis describes the design of a computer-human dialog system for information search. This system is able to interact with the user in natural language using cooperative strategies. To study the dialog processes involved during information search, a bottom-up approach was adopted. Experiments have been set up to obtain human dialogs related to such searches in the context of the health information system CISMeF. It turns out that the structure arising from the analysis of the dialogs matches a semantic approach called issue-based dialog . Starting from the model GoDIS, our artificial agent model adds several enhancements that allow to propose examples, assistance and choices. The model is implemented and some elements of evaluation are discussed.ROUEN-INSA Madrillet (765752301) / SudocSudocFranceF