Long term monitoring of CO2 levels and ventilation rates in a naturally ventilated residential apartment

Indoor CO2 levels became particularly topical during the recent COVID-19 pandemic. In this study a long-term investigation of indoor CO2 levels in a 1970s built residential apartment in single occupancy is presented. Three NDIR CO2 sensors were used to measure CO2 levels over a one-year period. Mean CO2 levels over this period were 1278 ± 504 ppm, with elevated CO2 levels of greater than 2000 ppm not uncommon. Subsequent investigations used the single zone mass balance model and the decay of CO2 in the absence of occupants to estimate the ventilation rates in various configurations. A mean natural ventilation rate of 0.16 ACH was estimated with all windows closed. Opening fan light windows resulted in a mean ventilation rate of 2.86 ACH whereas opening all windows increased the mean ventilation rate to 19.1 ACH. Evidence was observed of the effect of both wind speed and indoor-outdoor temperature difference on the ventilation rates. It was concluded that with all windows closed the natural infiltration rate was insufficient to maintain optimal indoor air quality even in single occupancy. Opening the fan light windows was sufficient to achieve satisfactory indoor air quality but insufficient for the effective inhibition of airborne disease transmission

Showing mutual support through digital empathy badges

Charity badges and empathy (awareness) ribbons are common tokens of support for charities and other worthy causes. In this paper we revisit the concept of smart badges with the aim of developing digital equivalents of the charity badge/empathy ribbon. We describe the design of prototype low–cost digital empathy badges based around infra-red transceiver technology, that light up and play a ringtone in the presence of other badges and we present the findings of a small pilot study involving a dozen badge wearers

Designing for empathy in a church community

Whilst empathy is considered an essential component of our humanity, it is arguably absent as a design consideration when creating modern communications, where the focus is often one of speed and efficiency. However, as with all design attempts to promote a particular emotion, the inherent subjectivity means that it is best explored through practice based approaches. As such, this paper presents a research through design approach to designing for empathy, as a means of identifying some of the design sensibilities required to address such a challenge. We consider how design interventions to two currently personal rituals for reflecting upon prayers and worries within a church community in London may be extended and augmented in order to allow those prayers and worries to be shared more widely within the church community. It is expected that these interventions will promote conversation and support within the community, thus generating empathy between community members. From these designs we expect to be able to draw more general understandings about designing systems for empathy

Supporting empathy through embodiment in the design of interactive systems

Whilst empathy is considered an essential component of what it means to be human, it is arguably absent as a design objective when creating modern communication systems. This paper presents an approach to designing for, as opposed to with, empathy using the example of two design interventions to create embodied rituals reflecting prayers and worries of individuals within a church community. The aim of these interventions is to facilitate conversation and support within the community, thus generating empathy between community members, and inciting prosocial behaviour through embodied cognition

Using Bespoke LoRaWAN Heat Sensors to Explore Microclimate Effects within the London Urban Heat Islands– A Pilot Study in East London

The phenomenon of high temperature in the city relative to the suburbs is known as the urban heat island effect (UHI). This research explores the new possibilities offered by designing a lightweight, battery-powered sensor system communicating through Long Range Wide Area Networks (LoRa WAN) for studying the UHI. By coupling the sensor records to Geographic Information Systems (GIS) data, we explore the potential for informing UHI to policy makers to tailor adaptative and mitigative strategies to local environments. This paper presents evidence for applying LoRaWAN sensors to measure spatial variation of local climate, based on a sensor deployment in East London

An internet of old things as an augmented memory system

The interdisciplinary Tales of Things and electronic Memory (TOTeM) project investigates new contexts for augmenting things with stories in the emerging culture of the Internet of Things (IoT). Tales of Things is a tagging system which, based on two-dimensional barcodes (also called Quick Response or QR codes) and Radio Frequency Identification (RFID) technology, enables the capturing and sharing of object stories and the physical linking to objects via read and writable tags. Within the context of our study, it has functioned as a technology probe which we employed with the aim to stimulate discussion and identify desire lines that point to novel design opportunities for the engagement with personal and social memories linked to everyday objects. In this paper, we discuss results from fieldwork with different community groups in the course of which seemingly any object could form the basis of a meaningful story and act as entry point into rich inherent 'networks of meaning'. Such networks of meaning are often solely accessible for the owner of an object and are at risk of getting lost as time goes by. We discuss the different discourses that are inherent in these object stories and provide avenues for making these memories and meaning networks accessible and shareable. This paper critically reflects on Tales of Things as an example of an augmented memory system and discusses possible wider implications for the design of related systems. © 2011 Springer-Verlag London Limited

The effect of artificial selection on phenotypic plasticity in maize

Remarkable productivity has been achieved in crop species through artificial selection and adaptation to modern agronomic practices. Whether intensive selection has changed the ability of improved cultivars to maintain high productivity across variable environments is unknown. Understanding the genetic control of phenotypic plasticity and genotype by environment (G × E) interaction will enhance crop performance predictions across diverse environments. Here we use data generated from the Genomes to Fields (G2F) Maize G × E project to assess the effect of selection on G × E variation and characterize polymorphisms associated with plasticity. Genomic regions putatively selected during modern temperate maize breeding explain less variability for yield G × E than unselected regions, indicating that improvement by breeding may have reduced G × E of modern temperate cultivars. Trends in genomic position of variants associated with stability reveal fewer genic associations and enrichment of variants 0–5000 base pairs upstream of genes, hypothetically due to control of plasticity by short-range regulatory elements

Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets

Objectives: Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids. G2F’s genotype by environment project has released 2014 and 2015 datasets to the public, with 2016 and 2017 collected and soon to be made available. Data description: Datasets include DNA sequences; traditional phenotype descriptions, as well as detailed ear, cob, and kernel phenotypes quantified by image analysis; weather station measurements; and soil characterizations by site. Data are released as comma separated value spreadsheets accompanied by extensive README text descriptions. For genotypic and phenotypic data, both raw data and a version with outliers removed are reported. For weather data, two versions are reported: a full dataset calibrated against nearby National Weather Service sites and a second calibrated set with outliers and apparent artifacts removed