Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and Food

Copyright © 2021 van Erp, Reynolds, Maynard, Starke, Ibáñez Martín, Andres, Leite, Alvarez de Toledo, Schmidt Rivera, Trattner, Brewer, Adriano Martins, Kluczkovski, Frankowska, Bridle, Levy, Rauber, Tereza da Silva and Bosma. In this paper, we discuss the use of natural language processing and artificial intelligence to analyze nutritional and sustainability aspects of recipes and food. We present the state-of-the-art and some use cases, followed by a discussion of challenges. Our perspective on addressing these is that while they typically have a technical nature, they nevertheless require an interdisciplinary approach combining natural language processing and artificial intelligence with expert domain knowledge to create practical tools and comprehensive analysis for the food domain.Research Councils UK, the University of Manchester, the University of Sheffield, the STFC Food Network+ and the HEFCE Catalyst-funded N8 AgriFood Resilience Programme with matched funding from the N8 group of Universities; AHRC funded AHRC US-UK Food Digital Scholarship Network (Grant Reference: AH/S012591/1), STFC GCRF funded project “Trends in greenhouse gas emissions from Brazilian foods using GGDOT” (ST/S003320/1), the STFC funded project “Piloting Zooniverse for food, health and sustainability citizen science” (ST/T001410/1), and the STFC Food Network+ Awarded Scoping Project “Piloting Zooniverse to help us understand citizen food perceptions”; ESRC via the University of Sheffield Social Sciences Partnerships, Impact and Knowledge Exchange fund for “Recipe environmental impact calculator”; and through Research England via the University of Sheffield QR Strategic Priorities Fund projects “Cooking as part of a Sustainable Food System – creating an wider evidence base for policy makers”, and “Food based citizen science in the UK as a policy tool”; N8 AgriFood-funded project “Greenhouse Gas and Dietary choices Open-source Toolkit (GGDOT) hacknights.’; Brunel University internal Research England GCRF QR Fund; The University of Manchester GCRF QR Visiting Researcher Fellowship; National Institute of Informatics, Japan

Formation and emission of reactive chlorine in indoor air

Chlorine atoms are powerful atmospheric oxidants known to degrade air quality. Despite much focus, a direct measurement technique does not exist. Instead, chlorine atom precursors are used as proxies to study chlorine atom chemistry. Reactions of precursors resulting in chlorine atoms studied in outdoor environments are also possible indoors. Daily household activities, especially those involving chlorinated cleaning products, are suspected to contribute to indoor chlorine atom chemistry. Indoor air studies are hindered by sampling techniques, as few appropriate instruments exist. A common atmospheric measurement technique was evaluated while monitoring gas and particulate phase species emitted during indoor bleach use. This instrument collects a non-selective gaseous and a particulate chloride sample. Recent advances in indoor instrumentation allow for selective measurement of chlorine atom precursor, hydrogen chloride (HCl), using a cavity-ring down spectroscopy instrument. Present ubiquitously outdoors, atmospheric HCl is a result of direct emission and secondary production. Previous measurements of HCl indoors are rare and have been limited to non-residential buildings using integrated sampling. This sampling strategy does not provide the source of HCl emissions. In order to better understand sources of HCl indoors, real-time gas-phase mixing ratios of HCl during typical household activities were monitored such as floor exposure to bleach, detergent use in household dishwashers, and cooking events. Based on calculated rates of chlorine atom precursors, both photolysis and direct emission could be contributing to elevated HCl levels indoors. This work presents insights regarding HCl production and the influence of household activities on indoor air quality

Analyse, modélisation et implémentation de stratégies d’assistance : déploiement d’orthèses cognitives pour les activités instrumentales de la vie quotidienne des traumatisés crâniens

De nos jours, les traumatismes cranio-cérébraux (TCC) sévères sont considérés comme un problème de santé publique au plan mondial. En effet, un TCC sévère engendre des répercussions importantes dans la vie des personnes l’ayant subi. Ces répercussions sont liées aux dysfonctionnements cognitifs, émotionnels et comportementaux. Ces troubles occasionnent une baisse, souvent très importante, de leur indépendance dans la réalisation des Activités Instrumentales de la Vie Quotidienne (AIVQ), telles que préparer un repas, gérer ses finances, utiliser son téléphone, conduire une automobile, faire des achats, etc. Très souvent, les personnes ayant subi un TCC sévère doivent retourner vivre au sein de leur domicile malgré les grandes difficultés liées à leur état. Les TCC sévères ressentiront très souvent le besoin d’assistance pour la réalisation des AIVQ. Cette thèse s’inscrit dans le cadre d’un grand projet de recherche financé par les Instituts de recherche en santé du Canada et le Conseil de Recherches en Sciences Naturelles et en Génie du Canada (CRSNG). En particulier, le Projet de Recherche Concertée sur la Santé (PRCS). L’objectif de cette thèse, au sein de ce projet, consiste à concevoir, représenter, formaliser et implémenter une structure d’assistance cognitive contextuelle et adaptative selon le profil des personnes atteintes de TCC sévère pour la réalisation des AIVQ. Cette assistance favorisera leur indépendance dans la réalisation des AIVQ au sein de leur domicile. La conception de cette assistance cognitive numérique implique un travail interdisciplinaire entre l’ergothérapie et l’informatique, afin de passer de la pratique d’assistance fournie par des cliniciens à la formulation formelle et à l’implémentation. Cette conception s’appuie sur une démarche de conception participative qui sollicite principalement les résidents d’un milieu d’hébergement alternatif domotisé.Abstract: Severe Traumatic Brain Injury (TBI) is considered a public health problem. Indeed, severe TBI causes significant cognitive, emotional and behavioral repercussions that impact the lives of these individuals, particularly their ndependence in Instrumental Activities of Daily Living (IADLs). Individuals who have experienced severe TBI frequently return to live in their homes despite the severe difficulties associated with their condition, though the need for assistance to perform IADLs frequently persists. The objective of this thesis is to design, represent, formalize and implement a context-aware and adaptive structure of cognitive assistance. This assistance is created according to the general needs of individuals with severe TBI for IADL performance. The proposed assistance will promote their independence to perform IADL in a home environment. The design of this cognitive assistance technology involves an interdisciplinary collaboration between occupational therapy and computer science, to evolve from the assistance provided by the clinicians to a formal computer science formulation and implementation. This design is based on a participative design approach that mainly involves TBI residents of a smart alternative housing unit. A prototype of a cognitive orthotic for meal preparation (COOK) was created and deployed within an alternative housing unit. Implementation of this cognitive orthotic lifted the prohibition on use of a stove for meal preparation that had previously been placed on their residents. By allowing these residents to cook independently, COOK has contributed to helping them become more independent in cooking and more confident in their ability to do so

Study and characterization of microstructural and physio-chemical properties of potato products for 3D food printing

Cotutela Universitat Politècnica de Catalunya i Lebanese UniversityPremi extraordinari doctorat UPC curs 2017-2018. Àmbit de Ciències3D food printing is a precise digitalized process that is based on monitoring the characteristics of the printed substrate in accordance with the process parameters. In this thesis mashed potatoes were first mixed with different food additives (agar, alginate, lecithin and glycerol) at different concentrations (0.5, 1 and 1.5%) in order to compare how each additive would affect the yield stress, viscosity, thixotropy, mechanical properties as well as the internal microstructure of potato puree. It was observed that agar and alginate enhanced the rheological and mechanical properties of puree by forming a stronger internetwork structure thus providing better printing with many build up shapes and that are stable post deposition. On the other hand, lecithin and glycerol decreases the rheological and mechanical properties of puree and thus although the extrusion was smooth, end printed products were unstable and collapsed instantly. Additionally, to inspect the reason behind obtaining those rheological and mechanical values a further investigation at the molecular level (applying FTIR and XRD) was done. It was revealed that additives such as glycerol and lecithin can penetrate the starch granules and induce a more intense effect on the structure as their respective concentrations increase by either suppressing (ex, glycerol) or enhancing (ex lecithin) the starch structure. In contrast, long polymeric molecules such as agar and alginate interact partially via the surface of the starch granules modifying partially the conformation of starch structure, which confirms the previous deductions from the rheological properties part. Furthermore, FTIR spectra showed that the skeleton formed by the amylose/amylopectin is somehow hidden in the dehydrated potato flakes, but was covered almost completely upon the addition of water such as to complement that of an original raw potato FTIR spectra, proving that water molecules have a central role in the maintenance of the starch structure conformation. To verify this hypothesis, task 4 was developed in order to make sure after what time of water reduction is the starch conformation altered (using this time potato tubers) and to identify whether the starch structure is modified more by the effect of the water removal or the heat treatment (microwaved and boiling). Findings showed that microwaved (MP) and boiled (BP) potato were more susceptible for water evaporation by freeze drying expressed via the following microstructural changes only after 6 hours of lyophilization; 1- obtaining an IR spectrum with much lower intensities (dried spectrum) compared to the initial spectrum, 2- undergoing a major transformation from gelatinized swollen starch to some recoiling towards a dried starch granule (SEM figures), 3- exhibiting an increase in the intensity of their respective XRD patterns. Moreover, RP took around 24 hours to reach a dried stage that was characterized by some ruptured granules embedded within leached starch matrix, an FTIR spectra that resembles in intensity that of BP and MP, possessing two peaks at 485 cm-1 and 620 cm-1 and that were assigned as a distinctive for a dried potato starch spectrum. Concluding that water removal sublimes the effect of the heat processing treatment, being the major contributor in the modifications of the starch structure. MP and BP were then used as basic samples for 3D printing trials while adding to each different food substrates at 1% concentration with respect to the weight (butter, olive oil, alginate and agar) except for carrots which were added at a ratio of 1/3 of the respective potato weight. All MP samples showed higher rheological and mechanical properties that lead to more stable printed products. Best printability was accounted with butter insertion which elevated the yield stress and thixotropy, thus increasing structural integrity and maintaining higher retaining shape property while preserving smooth extrusion and creamy surface structure.La impresión 3D de alimentos es un proceso digitalizado preciso que se basa en el monitoreo de las características del sustrato impreso de acuerdo con los parámetros del proceso. En esta tesis, se ha utilizado como substrato el puré de patatas mezclado con diferentes aditivos alimentarios (agar, alginato, lecitina y glicerol) a diferentes concentraciones (0,5, 1 y 1,5%) para poder comparar el efecto de cada aditivo sobre las propiedades reologicas (límite elástico, viscosidad, tixotropía), mecánicas y la microestructura interna del puré de patata. Los resultados han permitido observar que el agar y el alginato mejoraron las propiedades reológicas y mecánicas del puré al formar una estructura de interconexión más fuerte, proporcionando una mejor impresión con diversidad de formas y estables después de la deposición. Por otro lado, el uso de lecitina y glicerol disminuyeron las propiedades reológicas y mecánicas del puré y, por lo tanto, aunque la extrusión fue posible, los productos finales impresos fueron inestables y se colapsaron al instante. Adicionalmente, para validar la obtención de esos valores reológicos y mecánicos, se realizó una investigación adicional a nivel molecular aplicando FTIR y XRD. Los resultados indicaron que los aditivos glicerol y lecitina pueden penetrar en los gránulos de almidón e inducir un efecto más intenso sobre la estructura a medida que aumentan la concentración, suprimiendo (glicerol) o potenciando (lecitina) la estructura del almidón. Por el contrario, moléculas poliméricas largas como agar y alginato interactúan parcialmente a través de la superficie de los gránulos de almidón modificando parcialmente la conformación de su estructura, lo que confirmó los resultados previos de las propiedades reológicas. Además, los espectros FTIR mostraron que el esqueleto formado por la amilosa / amilopectina que esta " oculto" en las escamas de patata deshidratada, con la adición de agua vuelve a tener prácticamente el espectro original de FTIR de la patata cruda, lo que demuestra que las moléculas de agua tienen un papel central en el mantenimiento de la conformación de la estructura del almidón. Para verificar la hipótesis, de que " la reducción del agua puede alterar la conformación y estructura del almidón del tubérculo de patata" se procedió a comprobar el efecto de la eliminación de agua (liofilización) o el efecto del tratamiento térmico (cocción en microondas o hervido). Los resultados mostraron que la evaporación del agua por liofilización presentaba cambios micro-estructurales superiores a las cocinadas en microondas (MP) o hervida (BP) ya que con solo 6 horas de liofilización se obtuvo; un espectro FTIR con intensidades mucho más bajas (espectro seco) en comparación con el espectro inicial; se observó mediante SEM una transformación importante del almidón hinchado (gelatinizado) hacia un gránulo de almidón seco y se incrementó la intensidad de sus respectivos patrones de X-RD. Además, en la patata cruda (RP) se tardó alrededor de 24 horas en alcanzar la deshidratación, que se caracterizó por algunos gránulos rotos incrustados dentro de la matriz del almidón lixiviado, un espectro FTIR que se asemeja en intensidad al de BP y MP, (picos a 485 cm-1 y 620 cm-1) que fueron asignados como un distintivo para un espectro de almidón de patata deshidratada. Concluyendo que la eliminación del agua por sublimación produce efectos micro-estructurales superiores al del procesamiento térmico, siendo el agua el principal contribuyente de las modificaciones de la estructura del almidón. Para finalizar, se usaron estos dos tratamientos: cocción al microondas (MP) y hervido (BP) para las pruebas de impresión 3D. Los resultados obtenidos indicaron que todas las muestras MP mostraron mejores propiedades reológicas y mecánicas lo que nos permitió obtener productos impresos más establesAward-winningPostprint (published version

Memory-based preferential choice in large option spaces

Whether adding songs to a playlist or groceries to a shopping basket, everyday decisions often require us to choose between an innumerable set of options. Laboratory studies of preferential choice have made considerable progress in describing how people navigate fixed sets of options. Yet, questions remain about how well this generalises to more complex, everyday choices. In this thesis, I ask how people navigate large option spaces, focusing particularly on how long-term memory supports decisions. In the first project, I explore how large option spaces are structured in the mind. A topic model trained on the purchasing patterns of consumers uncovered an intuitive set of themes that centred primarily around goals (e.g., tomatoes go well in a salad), suggesting that representations are geared to support action. In the second project, I explore how such representations are queried during memory-based decisions, where options must be retrieved from memory. Using a large dataset of over 100,000 online grocery shops, results revealed that consumers query multiple systems of associative memory when determining what choose next. Attending to certain knowledge sources, as estimated by a cognitive model, predicted important retrieval errors, such as the propensity to forget or add unwanted products. In the final project, I ask how preferences could be learned and represented in large option spaces, where most options are untried. A cognitive model of sequential decision making is proposed, which learns preferences over choice attributes, allowing for the generalisation of preferences to unseen options, by virtue of their similarity to previous choices. This model explains reduced exploration patterns behaviour observed in the supermarket and preferential choices in more controlled laboratory settings. Overall, this suggests that consumers depend on associative systems in long-term memory when navigating large spaces of options, enabling inferences about the conceptual properties and subjective value of novel options