A Model of Social Explanations for a Conversational Movie Recommendation System

A critical aspect of any recommendation process is explaining the reasoning behind each recommendation. These explanations can not only improve users' experiences, but also change their perception of the recommendation quality. This work describes our human-centered design for our conversational movie recommendation agent, which explains its decisions as humans would. After exploring and analyzing a corpus of dyadic interactions, we developed a computational model of explanations. We then incorporated this model in the architecture of a conversational agent and evaluated the resulting system via a user experiment. Our results show that social explanations can improve the perceived quality of both the system and the interaction, regardless of the intrinsic quality of the recommendations

The Howl - Spring 2019

The Howl is a magazine that is planned, researched, written, photographed and designed by Otterbein University’s ESL and international students. The magazine serves to give them a safe space in which to use their voice to share their cultures, experiences and lives. If you are interested in submitting to the Howl, please e-mail your writing or photography to [email protected]. Enjoy Otterbein ESL’s contribution to the Otterbein community’s literary scene.https://digitalcommons.otterbein.edu/the_howl/1006/thumbnail.jp

Cost-effectiveness analysis of left atrial appendage occlusion compared with pharmacological strategies for stroke prevention in atrial fibrillation

Background Transcatheter left atrial appendage occlusion (LAAO) is a promising therapy for stroke prophylaxis in non-valvular atrial fibrillation (NVAF) but its cost-effectiveness remains understudied. This study evaluated the cost- effectiveness of LAAO for stroke prophylaxis in NVAF. Methods A Markov decision analytic model was used to compare the cost-effectiveness of LAAO with 7 pharmacological strategies: aspirin alone, clopidogrel plus aspirin, warfarin, dabigatran 110 mg, dabigatran 150 mg, apixaban, and rivaroxaban. Outcome measures included quality-adjusted life years (QALYs), lifetime costs and incremental cost-effectiveness ratios (ICERs). Base-case data were derived from ACTIVE, RE-LY, ARISTOTLE, ROCKET-AF, PROTECT-AF and PREVAIL trials. One- way sensitivity analysis varied by CHADS2 score, HAS-BLED score, time horizons, and LAAO costs; and probabilistic sensitivity analysis using 10,000 Monte Carlo simulations was conducted to assess parameter uncertainty. Results LAAO was considered cost-effective compared with aspirin, clopidogrel plus aspirin, and warfarin, with ICER of US$5,115,$2,447, and $6,298 per QALY gained, respectively. LAAO was dominant (i.e. less costly but more effective) compared to other strategies. Sensitivity analysis demonstrated favorable ICERs of LAAO against other strategies in varied CHADS2 score, HAS-BLED score, time horizons (5 to 15 years) and LAAO costs. LAAO was cost-effective in 86.24$50,000/QALY. Conclusions Transcatheter LAAO is cost-effective for prevention of stroke in NVAF compared with 7 pharmacological strategies. Condensed abstract The transcatheter left atrial appendage occlusion (LAAO) is considered cost-effective against the standard 7 oral pharmacological strategies including acetylsalicylic acid (ASA) alone, clopidogrel plus ASA, warfarin, dabigatran 110 mg, dabigatran 150 mg, apixaban, and rivaroxaban for stroke prophylaxis in non-valvular atrial fibrillation management

Bacteroides Microbial Source Tracking Markers Perform Poorly in Predicting Enterobacteriaceae and Enteric Pathogen Contamination of Cow Milk Products and Milk-Containing Infant Food

Consumption of microbiologically contaminated food is one of the leading causes of diarrheal diseases. Understanding the source of enteric pathogens in food is important to guide effective interventions. Enterobacteriaceae bacterial assays typically used to assess food safety do not shed light on the source. Source-specific Bacteroides microbial source tracking (MST) markers have been proposed as alternative indicators for water fecal contamination assessment but have not been evaluated as an alternative fecal indicator in animal-derived foods. This study tested various milk products collected from vendors in urban Kenyan communities and infant foods made with the milk (n = 394 pairs) using conventional culture methods and TaqMan qPCR for enteric pathogens and human and bovine-sourced MST markers. Detection profiles of various enteric pathogens and Bacteroides MST markers in milk products differed from that of milk-containing infant foods. MST markers were more frequently detected in infant food prepared by caregivers, indicating recent contamination events were more likely to occur during food preparation at home. However, Bacteroides MST markers had lower sensitivity in detecting enteric pathogens in food than traditional Enterobacteriaceae indicators. Bacteroides MST markers tested in this study were not associated with the detection of culturable Salmonella enterica and Shigella sonnei in milk products or milk-containing infant food. The findings show that while Bacteroides MST markers could provide valuable information about how foods become contaminated, they may not be suitable for predicting the origin of the enteric pathogen contamination sources

Milk Product Safety and Household Food Hygiene Influence Bacterial Contamination of Infant Food in Peri-Urban Kenya.

BACKGROUND: Milk is a common infant food in peri-urban Kenya that can transmit diarrhea-causing enteric pathogens. Little is known about how contamination of milk at point of purchase and household handling of milk-based infant foods contribute to infant exposure to enteric pathogens. OBJECTIVE: To compare the prevalence and concentrations of bacterial indicator organisms and enteric pathogens in unpackaged, fresh pasteurized, and ultra-high temperature (UHT) treated milk at purchase and assess the influence of the type of milk used to prepare infant food on contamination of this food. METHODS: Paired samples of purchased milk and infant food prepared with this milk were obtained from 188 households in low-income neighborhoods in Kisumu, Kenya. Samples were cultured on selective media to isolate Salmonella enterica, Shigella spp., Klebsiella aerogenes, Proteus spp., and Escherichia coli, with pathogens validated by PCR. Probability of detection of these bacteria was compared by milk product treatment and packaging method, and between milk at point of purchase vs. food at point of infant consumption. RESULTS: Unpackaged milk was most contaminated at point of purchase, but bacterial contamination was also present in pasteurized and UHT milk at purchase. Presence of bacteria in UHT and fresh pasteurized milk at purchase predicted presence of the same bacteria type in infant food. Prevalence of bacterial contamination and concentration level for bacterial indicators generally increased between point of purchase and consumption in UHT and fresh pasteurized milk-based food but decreased in unpackaged milk-based food. Prevalence of the four fecal bacteria were similar in infant foods prepared with each type of milk. CONCLUSION: Both pre-market contamination and post-purchase handling influence the likelihood of infants ingesting foods contaminated by diarrheal pathogens

Non-perturbative Euler-Heisenberg Lagrangian and Paraelectricity in Magnetized Massless QED

In this paper we calculate the non-perturbative Euler-Heisenberg Lagrangian for massless QED in a strong magnetic field $H$, where the breaking of the chiral symmetry is dynamically catalyzed by the external magnetic field via the formation of an electro-positron condensate. This chiral condensate leads to the generation of dynamical parameters that have to be found as solutions of non-perturbative Schwinger-Dyson equations. Since the electron-positron pairing mechanism leading to the breaking of the chiral symmetry is mainly dominated by the contributions from the infrared region of momenta much smaller than $\sqrt{eH}$, the magnetic field introduces a dynamical ultraviolet cutoff in the theory that also enters in the non-perturbative Euler-Heisenberg action. Using this action, we show that the system exhibits a significant paraelectricity in the direction parallel to the magnetic field. The nonperturbative nature of this effect is reflected in the non-analytic dependence of the obtained electric susceptibility on the fine-structure constant. The strong paraelectricity in the field direction is linked to the orientation of the electric dipole moments of the pairs that form the chiral condensate. The large electric susceptibility can be used to detect the realization of the magnetic catalysis of chiral symmetry breaking in physical systems.Comment: 18 pages, to be published in NP

Magnetoelectric Effect in Strongly Magnetized Color Superconductivity

The effect of a strong magnetic field on the electric polarization of a three-flavor color superconducting medium is investigated. We found that the electric susceptibility of this strongly magnetized medium is highly anisotropic. In the direction transverse to the applied magnetic field the susceptibility reduces to that of the vacuum, while in the longitudinal direction it depends on the magnetic field and decreases with it. The nature of this behavior is associated with the field's dependence of the Cooper pairs' coherence length, which plays the role of the electric dipole length. The field's dependence of the electric polarization is interpreted as the realization of the magnetoelectric effect in cold-dense quark matter.Comment: 10 pages, 1 figur

GEMv2 : Multilingual NLG benchmarking in a single line of code

Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using leaderboards, but the evaluation choices become sub-optimal as better alternatives arise. This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims. To make following best model evaluation practices easier, we introduce GEMv2. The new version of the Generation, Evaluation, and Metrics Benchmark introduces a modular infrastructure for dataset, model, and metric developers to benefit from each others work. GEMv2 supports 40 documented datasets in 51 languages. Models for all datasets can be evaluated online and our interactive data card creation and rendering tools make it easier to add new datasets to the living benchmark.Peer reviewe

GEMv2 : Multilingual NLG benchmarking in a single line of code

Evaluation in machine learning is usually informed by past choices, for example which datasets or metrics to use. This standardization enables the comparison on equal footing using leaderboards, but the evaluation choices become sub-optimal as better alternatives arise. This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims. To make following best model evaluation practices easier, we introduce GEMv2. The new version of the Generation, Evaluation, and Metrics Benchmark introduces a modular infrastructure for dataset, model, and metric developers to benefit from each others work. GEMv2 supports 40 documented datasets in 51 languages. Models for all datasets can be evaluated online and our interactive data card creation and rendering tools make it easier to add new datasets to the living benchmark.Peer reviewe