Topic Modeling for Automatic Analysis of Natural Language: A Case Study in an Italian Customer Support Center

This paper focuses on the automatic analysis of conversation transcriptions in the call center of a customer care service. The goal is to recognize topics related to problems and complaints discussed in several dialogues between customers and agents. Our study aims to implement a framework able to automatically cluster conversation transcriptions into cohesive and well-separated groups based on the content of the data. The framework can alleviate the analyst selecting proper values for the analysis and the clustering processes. To pursue this goal, we consider a probabilistic model based on the latent Dirichlet allocation, which associates transcriptions with a mixture of topics in different proportions. A case study consisting of transcriptions in the Italian natural language, and collected in a customer support center of an energy supplier, is considered in the paper. Performance comparison of different inference techniques is discussed using the case study. The experimental results demonstrate the approach’s efficacy in clustering Italian conversation transcriptions. It also results in a practical tool to simplify the analytic process and off-load the parameter tuning from the end-user. According to recent works in the literature, this paper may be valuable for introducing latent Dirichlet allocation approaches in topic modeling for the Italian natural language

A Comparison of Different Topic Modeling Methods through a Real Case Study of Italian Customer Care

The paper deals with the analysis of conversation transcriptions between customers and agents in a call center of a customer care service. The objective is to support the analysis of text transcription of human-to-human conversations, to obtain reports on customer problems and complaints, and on the way an agent has solved them. The aim is to provide customer care service with a high level of efficiency and user satisfaction. To this aim, topic modeling is considered since it facilitates insightful analysis from large documents and datasets, such as a summarization of the main topics and topic characteristics. This paper presents a performance comparison of four topic modeling algorithms: (i) Latent Dirichlet Allocation (LDA); (ii) Non-negative Matrix Factorization (NMF); (iii) Neural-ProdLDA (Neural LDA) and Contextualized Topic Models (CTM). The comparison study is based on a database containing real conversation transcriptions in Italian Natural Language. Experimental results and different topic evaluation metrics are analyzed in this paper to determine the most suitable model for the case study. The gained knowledge can be exploited by practitioners to identify the optimal strategy and to perform and evaluate topic modeling on Italian natural language transcriptions of human-to-human conversations. This work can be an asset for grounding applications of topic modeling and can be inspiring for similar case studies in the domain of customer care quality

The explicative power of the vector potential for superconductivity: a path for high school

In the classroom practice the notion of the magnetic vector potential is never introduced, both because it is not contained in secondary school textbooks and because teachers usually associate this concept with complex topics they dealt with in their university courses. In our experience instead, we have found that the introduction of the vector potential can be of great help in students’ understanding of electromagnetism and modern physics topics. In this paper we will show how the use of the vector potential allows a phenomenological and consistent explanation of superconductivity at a level suitable for high school students. We will deal with the two main aspects of superconductivity: the resistivity of the superconductor that drops to zero at the critical temperature and the expulsion of the magnetic field from the bulk of a superconductor (Meissner effect). By the use of the vector potential, students can build a phenomenological interpretation of superconductivity, always remaining in the frame of electromagnetism and thus avoiding the use of too complicated mathematical tools that the explanation of the microscopic mechanism would require

Incompressible analytical models for spinning-down pulsars

We study a class of Newtonian models for the deformations of non-magnetized neutron stars duringtheir spin-down. The models have all an analytical solution, and thus allow to understand easily thedependence of the strain on the star\u2019s main physical quantities, such as radius, mass and crust thickness.In the first \u201chistorical\u201d model the star is assumed to be comprised of a fluid core and an elastic crustwith the same density. We compare the response of stars with different masses and equations of stateto a decreasing centrifugal force, finding smaller deformations for heavier stars: the strain angle ispeaked at the equator and turns out to be a decreasing function of the mass.We introduce a second,more refined, model in which the core and the crust have different densities and the gravitationalpotential of the deformed body is self-consistently accounted for. Also in this case the strain angle isa decreasing function of the stellar mass, but its maximum value is at the poles and is always largerthan the corresponding one in the one-density model by a factor of two. Finally, within the presentanalytic approach, it is possible to estimate easily the impact of the Cowling approximation: neglectingthe perturbations of the gravitational potential, the strain angle is 40% of the one obtained with thecomplete model

Nefrolitiasi da iperparatiroidismo primitivo: uso del Cinacalcet in pazienti non trattabili con terapia chirurgica

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Modelling and collaboration as cognitive tools in physics education

The Green Paper on teacher education in Europe (Buchberger, 2002) highlights the crucial role of designing learning situations in which students can find opportunities to develop structures of meaning, knowledge and activities for a didactical reconstruction of the disciplinary contents, integrated with pedagogical competencies, methodologies and teaching practices.The epistemic role of models in physics (Hestenes, 1996) suggests that models can be included in teaching/learning methodologies and cannot be omitted in a cultural base in the education of teachers of all levels. Being models cognitive tools and not simple representations of phenomena, they cannot be transferred either as ready-to-use examples or taught as rules to apply; to favour interpretation teachers have to offer situated experiences of model building starting from experimental activities.A previous research showed that some elementary recurring basic model structures represent “syntactic elements” of a language oriented to modelling. For instance in the evolution toward equilibrium of different systems is possible to identify the flow of an extensive quantity which is conservative and whose flux intensity depends on the difference of the levels of a corresponding intensive quantity experiencing a resistance.The key role of the group investigation in a cooperative learning environment is implemented in a proposal of a research-based learning pathway based on modelling starting from experiments in a community of perspective primary teachers. The research aims to investigate how the modelling activity takes place during the individual and group exploration of experimental activities and how the collaborative work affects the ability to design models to interpret the observed phenomena. Moreover we analyze the role of single elementary model structure when building complex models with a qualitative modelling software such as VnR.A training pathway was designed, with specific activities and monitoring tools, and tested with a group of perspective primary school teachers of University of Udine (23 students) and University of Modena and Reggio Emilia (73 students).The training pathway was organized in two main activities organized in 4 phases according with tutorial for inquiry learning. Each thematic activity started with the design of an experiment for the exploration of a phenomenon followed by building and testing a model of the observed phenomena, first individually then in small groups. The first activity consisted in the study of phenomena evolving towards equilibrium; the second was in the form of a thought experiment concerning dynamical equilibrium. A final plenary discussion, chaired by the conductor, aimed at analysing to what extent the various model structures are consistent with the observed phenomena as well as to reflection on models comparison (similarities and differences).The software VnR was chosen due o its specifications of icon-based design and representation of simple relations between variables without the use of formulas. VnR is assumed to be an effective tool to let the participants to learn how to think in terms of variables and relations, to identify elementary structures as components of more complex models, to recognize similarities between different phenomena and to develop a dynamical approach to phenomena as processes evolving over time.The data collected during the activities, comprising specific tutorials, based on inquiry learning for all the activities, and models produced by the participants, both alone and in groups, were analysed according to the research questions

Hyperglycemia selectively increases the expression of cycloxygenase-2 in human aortic endothelial cells

The conversion of arachidonic acid to vasoactive prostanoids including prostacyclin, prostaglandins and tromboxanes is mediated by cycloxygenase (COX). Two isoforms of enzyme have been shown: a constitutive (COX-1) and an inducible form (COX-2). Products of the arachidonic acid metabolism may be involved in the impairment of endothelium-dependent vasodilatation observed both in experimental models and in patients with diabetes mellitus. To determine the effect of hyperglycemia on COX-1 and COX-2 expression, human aortic endothelial cells (HAEC) were exposed to normal (5.5mM) and high (22.2mM) concentrations of glucose for 5 days. Cells were also treated with mannitol (22.2 mM) to rule out an effect due to osmolality changes. COX-1 and COX-2 mRNA and protein expressions were analyzed by Southern and Western blotting, respectively. Treatment with high glucose was associated with a two-fold increase of both COX-2 mRNA (P<0.05) and protein levels (P<0.05), whereas no changes were observed for COX-1. Moreover high concentration of mannitol did not exert any significant effect. The present study demonstrates that both isoforms of COX are normally expressed in HAEC, but only COX-2 was stimulated after exposure to high glucose. The results of the present study may provide molecular basis to understand hyperglycemia-induced endothelial dysfunctio

Magnetic vector potential in secondary school: a teachers&#8217; path

The magnetic vector potential is traditionally presented only at university level and is widely considered as a pure mathematical tool to calculate the magnetic and the electric fields, i.e., a device without any (or at least with very poor) physical meaning. Even if, also in recent literature, many papers can be found which, on the contrary, clarify the physical meaning of the vector potential, to the best of our knowledge a clear and complete educational path on it is still missing. Our experience and some pilot experimentations with secondary school students and teachers, however, have driven us to seriously consider the opportunity to introduce the magnetic vector potential also at secondary school as a way both to better understand some fundamental aspects of classical electromagnetism and to open a door for a simple and a direct way of introducing important aspects of modern physics (i.e. the notion of the photon and the London equation of superconductivity). In this paper we\u2019ll discuss the motivations that led us to develop an educational path for the introduction of magnetic vector potential in upper secondary school, some considerations in order to clarify general aspects of its physical meaning with examples, and the framework of our course on magnetic vector potential for preservice teachers training at the Milano TFA (Formative Active Training) course

Experimental and theoretical study on bond behavior of GFRP bars in steel fiber reinforced self compacting concrete

To estimate the cracking and the deformational behavior of steel fiber reinforced selfcompacting concrete (SFRSCC) beams reinforced with glass fiber reinforced polymer (GFRP) bars, it is fundamental to understand the interfacial bond behavior of embedded bars. Hence, the evaluation of the bond behavior between GFRP and (SFRSCC) was investigated in this study. A closed-form formulation was derived, adopting a new local bond stress-slip relationship. Furthermore, an experimental program composed of pullout bending tests was carried out in order to assess the influence of the following parameters on the bond behavior: bar diameter, bar surface treatment, embedment length and SFRSCC cover thickness. Finally, a numerical simulation was performed with a FEM-based computer program in order to simulate the bond behavior between GFRP bar and SFRSCC by means of a non-linear bond-slip relationship assigned to the interface finite element. The predictive performance of the theoretical models was appraised by comparing experimental and numerical results

Differential effects on membrane permeability and viability of human keratinocyte cells undergoing very low intensity megasonic fields

Among different therapeutic applications of Ultrasound (US), transient membrane sonoporation (SP) - a temporary, non-lethal porosity, mechanically induced in cell membranes through US exposure - represents a compelling opportunity towards an efficient and safe drug delivery. Nevertheless, progresses in this field have been limited by an insufficient understanding of the potential cytotoxic effects of US related to the failure of the cellular repair and to the possible activation of inflammatory pathway. In this framework we studied the in vitro effects of very low-intensity US on a human keratinocyte cell line, which represents an ideal model system of skin protective barrier cells which are the first to be involved during medical US treatments. Bioeffects linked to US application at 1 MHz varying the exposure parameters were investigated by fluorescence microscopy and fluorescence activated cell sorting. Our results indicate that keratinocytes undergoing low US doses can uptake drug model molecules with size and efficiency which depend on exposure parameters. According to sub-cavitation SP models, we have identified the range of doses triggering transient membrane SP, actually with negligible biological damage. By increasing US doses we observed a reduced cells viability and an inflammatory gene overexpression enlightening novel healthy relevant strategies