Leveraging Large Language Models for Automated Dialogue Analysis

Developing high-performing dialogue systems benefits from the automatic identification of undesirable behaviors in system responses. However, detecting such behaviors remains challenging, as it draws on a breadth of general knowledge and understanding of conversational practices. Although recent research has focused on building specialized classifiers for detecting specific dialogue behaviors, the behavior coverage is still incomplete and there is a lack of testing on real-world human-bot interactions. This paper investigates the ability of a state-of-the-art large language model (LLM), ChatGPT-3.5, to perform dialogue behavior detection for nine categories in real human-bot dialogues. We aim to assess whether ChatGPT can match specialized models and approximate human performance, thereby reducing the cost of behavior detection tasks. Our findings reveal that neither specialized models nor ChatGPT have yet achieved satisfactory results for this task, falling short of human performance. Nevertheless, ChatGPT shows promising potential and often outperforms specialized detection models. We conclude with an in-depth examination of the prevalent shortcomings of ChatGPT, offering guidance for future research to enhance LLM capabilities.Comment: Accepted to SIGDIAL 202

Essential role for non-canonical poly(A) polymerase GLD4 in cytoplasmic polyadenylation and carbohydrate metabolism

Regulation of gene expression at the level of cytoplasmic polyadenylation is important for many biological phenomena including cell cycle progression, mitochondrial respiration, and learning and memory. GLD4 is one of the non-canonical poly(A) polymerases that regulates cytoplasmic polyadenylation-induced translation, but its target mRNAs and role in cellular physiology is not well known. To assess the full panoply of mRNAs whose polyadenylation is controlled by GLD4, we performed an unbiased whole genome-wide screen using poy(U) chromatography and thermal elution. We identified hundreds of mRNAs regulated by GLD4, several of which are involved in carbohydrate metabolism including GLUT1, a major glucose transporter. Depletion of GLD4 not only reduced GLUT1 poly(A) tail length, but also GLUT1 protein. GLD4-mediated translational control of GLUT1 mRNA is dependent of an RNA binding protein, CPEB1, and its binding elements in the 3 UTR. Through regulating GLUT1 level, GLD4 affects glucose uptake into cells and lactate levels. Moreover, GLD4 depletion impairs glucose deprivation-induced GLUT1 up-regulation. In addition, we found that GLD4 affects glucose-dependent cellular phenotypes such as migration and invasion in glioblastoma cells. Our observations delineate a novel post-transcriptional regulatory network involving carbohydrate metabolism and glucose homeostasis mediated by GLD4

Soft Computing Models for the Development of Commercial Conversational Agents

Proceedings of: 6th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2011). Salamanca, April 6-8, 2011In this paper we present a proposal for the development of conversational agents that, on the one hand, takes into account the benefits of using standards like VoiceXML, whilst on the other, includes a module with a soft computing model that avoids the effort of manually defining the dialog strategy. This module is trained using a labeled dialog corpus, and selects the next system response considering a classification process based on neural networks that takes into account the dialog history. Thus, system developers only need to define a set of VoiceXML files, each including a system prompt and the associated grammar to recognize the users responses to the prompt. We have applied this technique to develop a conversational agent in VoiceXML that provides railway information in Spanish.Funded by projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02- 02/TEC, CAM CONTEXTS (S2009/TIC-1485), and DPS2008-07029-C02-02.Publicad

Arabidopsis ABCG34 contributes to defense against necrotrophic pathogens by mediating the secretion of camalexin

Plant pathogens cause huge yield losses. Plant defense often depends on toxic secondary metabolites that inhibit pathogen growth. Because most secondary metabolites are also toxic to the plant, specific transporters are needed to deliver them to the pathogens. To identify the transporters that function in plant defense, we screened Arabidopsis thaliana mutants of full-size ABCG transporters for hypersensitivity to sclareol, an antifungal compound. We found that atabcg34 mutants were hypersensitive to sclareol and to the necrotrophic fungi Alternaria brassicicola and Botrytis cinerea. AtABCG34 expression was induced by A. brassicicola inoculation as well as by methyl-jasmonate, a defense-related phytohormone, and AtABCG34 was polarly localized at the external face of the plasma membrane of epidermal cells of leaves and roots. atabcg34 mutants secreted less camalexin, a major phytoalexin in A. thaliana, whereas plants overexpressing AtABCG34 secreted more camalexin to the leaf surface and were more resistant to the pathogen. When treated with exogenous camalexin, atabcg34 mutants exhibited hypersensitivity, whereas BY2 cells expressing AtABCG34 exhibited improved resistance. Analyses of natural Arabidopsis accessions revealed that AtABCG34 contributes to the disease resistance in naturally occurring genetic variants, albeit to a small extent. Together, our data suggest that AtABCG34 mediates camalexin secretion to the leaf surface and thereby prevents A. brassicicola infection.117Ysciescopu

Evaluating implicit feedback models using searcher simulations

In this article we describe an evaluation of relevance feedback (RF) algorithms using searcher simulations. Since these algorithms select additional terms for query modification based on inferences made from searcher interaction, not on relevance information searchers explicitly provide (as in traditional RF), we refer to them as implicit feedback models. We introduce six different models that base their decisions on the interactions of searchers and use different approaches to rank query modification terms. The aim of this article is to determine which of these models should be used to assist searchers in the systems we develop. To evaluate these models we used searcher simulations that afforded us more control over the experimental conditions than experiments with human subjects and allowed complex interaction to be modeled without the need for costly human experimentation. The simulation-based evaluation methodology measures how well the models learn the distribution of terms across relevant documents (i.e., learn what information is relevant) and how well they improve search effectiveness (i.e., create effective search queries). Our findings show that an implicit feedback model based on Jeffrey's rule of conditioning outperformed other models under investigation

Antifungal Prophylaxis and Risk for Invasive Mold Infections in Children with Hematologic Malignancies

Introduction: Invasive mold infections (IMI) are a leading cause of mortality in immunocompromised hosts. Children diagnosed with hematologic malignancies experience profound, prolonged neutropenia following intensive chemotherapy, and are at increased risk for infection-related outcomes. Depending on the anticipated therapeutic intensity, antimicrobial prophylaxis may be employed to mitigate risk for infection. We conducted a retrospective review of children diagnosed with acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), or lymphoma between 2006-2015 and determined the incidence of IMI to be 4.8% (47/976), with an exceptionally high incidence observed in patients with AML (8.1%). This observation prompted a change in clinical practice that broadened prophylaxis for high risk patients to include coverage of molds, and resulted in development of a risk-stratified algorithm for antifungal prophylaxis in children with hematologic malignancies. The objective of this study was to evaluate the change in IMI incidence post-implementation of this algorithm, and to identify host factors contributing to risk for IMI in children with hematologic malignancies. Objective: The objective was to compare the incidence of IMI pre/post implementation of antifungal prophylaxis decision tree. Also, it was planned to evaluate the impact of race/ethnicity on the development of IMI in children with hematologic malignancies. Methods: We conducted a retrospective review of children ≤ 21 years old and diagnosed with ALL, AML, or lymphoma between 2016-2019, and were treated for IMI between 2016 and June 2020. To identify potential cases, we employed a strategy identical to the one used in the 2006-2015 review, specifically, a search of the electronic medical record utilizing ICD9 codes broadly inclusive of relevant cancer and fungal diagnoses. Each potentially eligible case was then reviewed for the following inclusion/exclusion criteria (also identical to the prior review): diagnosis and treatment of ALL, AML, or lymphoma at Texas Children’s Hospital, diagnosis of IMI that met criteria for ‘proven’ or ‘probable’ per the European Organization for Research and Treatment of Cancer/Mycoses Study Group and occurring prior to stem cell transplant, and no underlying immunodeficiency or history of solid organ transplant. Host and disease-related factors, as well as IMI incidence, were compared for 2006-2015 vs. 2016-2020 using a Chi-square, Fisher, or Student t-test as appropriate, and host factors predictive of IMI were assessed by multivariable linear regression. Results: The overall incidence of proven/probable IMI in children diagnosed with hematological malignancies between 2006-2019 was 4.2% (61/1456). The incidence of IMI decreased from 4.8% to 2.9% between 2006-2015 and 2016-2020. For specific diagnoses, the rate of IMI decreased from 5.0% to 3.6% (ALL, 35/705 vs. 10/276), from 1.9% to 1.4% (lymphoma, 47/976 vs. 14/480), and from 8.1% to 3.2% (AML, 9/111 vs. 2/62). No significant differences in host factor or disease-related characteristics were noted when comparing IMI cases in 2006-2015 vs. 2016-2020, nor were there differences in the proportion of patients in relapse at the time of IMI or taking antifungal prophylaxis. Substantial differences in representative mold species were noted between the two-time periods, e.g. Aspergillus spp. accounted for 19/47 IMI from 2006-2015, but accounted for none of the IMIs diagnosed 2016-2020. In 2016-2020, 5/14 IMI were due to Trichosporon spp., with 4/14 Rhizopus spp., 2/14 Fusarium spp., 1/14 Curvularia spp., 1/14 Histoplasma spp., and 1 that met criteria for probable IMI. In multivariable analyses (Table 1), Hispanics were more likely to develop an IMI than non-Hispanics (p=0.04, OR 1.94, CI 1.03-3.66), and those with lymphoma were less likely to develop an IMI than those with ALL (p=0.03, OR 0.33, CI 0.12-0.87). Patients diagnosed between 2016- 2019 were substantially less likely to develop IMI than those diagnosed 2006-2015 (p=0.003, OR 0.33, CI 0.16-0.69). Discussion and Conclusion: In this single institution study, risk for IMI in children with hematologic malignancies declined significantly after implementation of an antifungal prophylaxis algorithm that broadened coverage for high risk populations. Hispanics were at higher risk for IMI than non-Hispanics, suggesting a need to investigate relevant factors contributing to this disparity. This project can be used to further investigate the factors that contributed to invasive mold infections using a larger study populations. We can then continue to explore the potential contributing factors to the racial and ethnic disparities by including potential contributing factors such as socioeconomic factors and genetic risk

Bioavailable insulin-like growth factor-I as mediator of racial disparity in obesity-relevant breast and colorectal cancer risk among postmenopausal women

Bioavailable insulin-like growth factor (IGF)-I interacts with obesity and exogenous estrogen in a racial disparity in obesity-related cancer risk, yet their interconnected pathways are not fully characterized. We investigated whether circulating bioavailable IGF-I acted as a mediator of the racial disparity in obesity-related cancers such as breast and colorectal (CR) cancers and how obesity and estrogen use regulate this relationship

Effect of the GaAsP shell on optical properties of self-catalyzed GaAs nanowires grown on silicon

We realize growth of self-catalyzed core-shell GaAs/GaAsP nanowires (NWs) on Si substrates using molecular-beam epitaxy. Transmission electron microscopy (TEM) of single GaAs/GaAsP NWs confirms their high crystal quality and shows domination of the zinc-blende phase. This is further confirmed in optics of single NWs, studied using cw and time-resolved photoluminescence (PL). A detailed comparison with uncapped GaAs NWs emphasizes the effect of the GaAsP capping in suppressing the non-radiative surface states: significant PL enhancement in the core-shell structures exceeding 2000 times at 10K is observed; in uncapped NWs PL is quenched at 60K whereas single core-shell GaAs/GaAsP NWs exhibit bright emission even at room temperature. From analysis of the PL temperature dependence in both types of NW we are able to determine the main carrier escape mechanisms leading to the PL quench