Multi-scale analysis of the energy performance of supermarkets

The retail sector accounts for more than 3% of the total electricity consumption in the UK and approximately 1% of total UK CO2 emissions. The overarching aim of this project was to understand the energy consumption of the Tesco estate (the market leader), identify best practice, and find ways to identify opportunities for energy reduction. The literature review of this work covered the topic of energy consumption in the retail sector, and reviewed benchmarks for this type of buildings from the UK, Europe and the US. Related data analysis techniques used in the industry or presented in the literature were also reviewed. This revealed that there are many different analysis and forecasting techniques available, and that they fall into two different categories: techniques that require past energy consumption data in order to calculate the future consumption, such as statistical regression, and techniques that are able to estimate the energy consumption of buildings, based on the specific building’s characteristics, such as thermal simulation models. These are usually used for new buildings, but they could also be used in benchmarking exercises, in order to achieve best practice guides. Gaps in the industry knowledge were identified, and it was suggested that better analytical tools would enable the industry to create more accurate energy budgets for the year ahead leading to better operating margins. Benchmarks for the organisation’s buildings were calculated. Retail buildings in the Tesco estate were found to have electrical intensity values between 230 kWh/m2 and 2000 kWh/m2 per year. Still the average electrical intensity of these buildings in 2010-11 was found to be less than the calculated UK average of the 2006-07 period. The effect of weather on gas and electricity consumption was investigated, and was found to be significant (p<0.001). There was an effect related to the day-of-the-week, but this was found to be more related to the sales volume on those days. Sales volume was a proxy that was used to represent the number of customers walking through the stores. The built date of the building was also considered to be an interesting factor, as the building regulations changed significantly throughout the years and the sponsor did not usually carry out any fabric work when refurbishing the stores. User behaviour was also identified as an important factor that needed to be investigated further, relating to both how the staff perceives and manages the energy consumption in their work environment, as well as how the customers use the refrigeration equipment. Following a statistical analysis, significant factors were determined and used to create multiple linear regression models for electricity and gas demands in hypermarkets. Significant factors included the sales floor area of the store, the stock composition, and a factor representing the thermo-physical characteristics of the envelope. Two of the key findings are the statistical significance of operational usage factors, represented by volume of sales, on annual electricity demand and the absence of any statistically significant operational or weather related factors on annual gas demand. The results suggest that by knowing as little as four characteristics of a food retail store (size of sales area, sales volume, product mix, year of construction) one can confidently calculate its annual electricity demands (R2=0.75, p<0.001). Similarly by knowing the size of the sales area, product mix, ceiling height and number of floors, one can calculate the annual gas demands (R2=0.5, p<0.001). Using the models created, along with the actual energy consumption of stores, stores that are not as energy efficient as expected can be isolated and investigated further in order to understand the reason for poor energy performance. Refrigeration data from 10 stores were investigated, including data such as the electricity consumption of the pack, outside air temperature, discharge and suction pressure, as well as percentage of refrigerant gas in the receiver. Data mining methods (regression and Fourier transforms) were employed to remove known operational patterns (e.g. defrost cycles) and seasonal variations. Events that have had an effect on the electricity consumption of the system were highlighted and faults that had been identified by the existing methodology were filtered out. The resulting dataset was then analysed further to understand the events that increase the electricity demand of the systems in order to create an automatic identification method. The cases analysed demonstrated that the method presented could form part of a more advanced automatic fault detection solution; potential faults were difficult to identify in the original electricity dataset. However, treating the data with the method designed as part of this work has made it simpler to identify potential faults, and isolate probable causes. It was also shown that by monitoring the suction pressure of the packs, alongside the compressor run-times, one could identify further opportunities for electricity consumption reduction

An empirical study of electricity and gas demand drivers in large food retail buildings of a national organisation

AbstractFood retail buildings account for a measurable proportion of a country's energy consumption and resultant carbon emissions so energy-operating costs are key business considerations. Increased understanding of end-use energy demands in this sector can enable development of effective benchmarking systems to underpin energy management tools. This could aid identification and evaluation of interventions to reduce operational energy demand. Whilst there are a number of theoretical and semi-empirical benchmarking and thermal modelling tools that can be used for food retail building stocks, these do not readily account for the variance of technical and non-technical factors that can influence end-use demands.This paper discusses the various drivers of energy end-uses of typical UK food retail stores. It reports on an empirical study of one organisation's hypermarket stock to evaluate the influence of various factors on annual store electricity and gas demands. Multiple regression models are discussed in the context of the development and application of a methodology for estimating annual energy end-use demand in food retail buildings. The established models account for 75% of the variation in electricity demand, 50% of the variation in gas demand in stores without CHP and 77% of the variation in gas demand in stores with CHP

Mannan detecting C-type lectin receptor probes recognise immune epitopes with diverse chemical, spatial and phylogenetic heterogeneity in fungal cell walls

Funding Information: This work was supported by the Wellcome Trust Investigator, Collaborative, Equipment, Strategic and Biomedical Resource awards (086827, 075470, 097377, 101873, 200208, 093378 and 099197), the Applied Molecular Biosciences Unit-UCIBIO (FCT/MCTES UID/Multi/04378/2019), Wellcome Trust Biomedical Resource grant (108430/Z/15/Z), March of Dimes (Arlington, Virginia, U.S.A.) Prematurity Research Center grant (22-FY18-821) and by the MRC Centre for Medical Mycology (N006364/1). The University of Aberdeen funded a studentship to IV as part of NARG?s Wellcome Senior Investigator Award. https://wellcome.ac.uk/ - Wellcome. https://mrc.ukri.org/ - MRC. https:// www.requimte.pt/ucibio/ - the Applied Molecular Biosciences Unit-UCIBIO. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © 2020 Vendele et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Peer reviewedPublisher PD

Women Scientists Who Made Nuclear Astrophysics

Female role models reduce the impact on women of stereotype threat, i.e., of being at risk of conforming to a negative stereotype about one's social, gender, or racial group [1,2]. This can lead women scientists to underperform or to leave their scientific career because of negative stereotypes such as, not being as talented or as interested in science as men. Sadly, history rarely provides role models for women scientists; instead, it often renders these women invisible [3]. In response to this situation, we present a selection of twelve outstanding women who helped to develop nuclear astrophysics

Community-curated and standardised metadata of published ancient metagenomic samples with AncientMetagenomeDir

Ancient DNA and RNA are valuable data sources for a wide range of disciplines. Within the field of ancient metagenomics, the number of published genetic datasets has risen dramatically in recent years, and tracking this data for reuse is particularly important for large-scale ecological and evolutionary studies of individual taxa and communities of both microbes and eukaryotes. AncientMetagenomeDir (archived at https://doi.org/10.5281/zenodo.3980833) is a collection of annotated metagenomic sample lists derived from published studies that provide basic, standardised metadata and accession numbers to allow rapid data retrieval from online repositories. These tables are community-curated and span multiple sub-disciplines to ensure adequate breadth and consensus in metadata definitions, as well as longevity of the database. Internal guidelines and automated checks facilitate compatibility with established sequence-read archives and term-ontologies, and ensure consistency and interoperability for future meta-analyses. This collection will also assist in standardising metadata reporting for future ancient metagenomic studies

Nature-based solutions efficiency evaluation against natural hazards: modelling methods, advantages and limitations

Nature-based solutions (NBS) for hydro-meteorological risks (HMRs) reduction and management are becoming increasingly popular, but challenges such as the lack of well-recognised standard methodologies to evaluate their performance and upscale their implementation remain. We systematically evaluate the current state-of-the art on the models and tools that are utilised for the optimum allocation, design and efficiency evaluation of NBS for five HMRs (flooding, droughts, heatwaves, landslides, and storm surges and coastal erosion). We found that methods to assess the complex issue of NBS efficiency and cost-benefits analysis are still in the development stage and they have only been implemented through the methodologies developed for other purposes such as fluid dynamics models in micro and catchment scale contexts. Of the reviewed numerical models and tools MIKE-SHE, SWMM (for floods), ParFlow-TREES, ACRU, SIMGRO (for droughts), WRF, ENVI-met (for heatwaves), FUNWAVE-TVD, BROOK90 (for landslides), TELEMAC and ADCIRC (for storm surges) are more flexible to evaluate the performance and effectiveness of specific NBS such as wetlands, ponds, trees, parks, grass, green roof/walls, tree roots, vegetations, coral reefs, mangroves, sea grasses, oyster reefs, sea salt marshes, sandy beaches and dunes. We conclude that the models and tools that are capable of assessing the multiple benefits, particularly the performance and cost-effectiveness of NBS for HMR reduction and management are not readily available. Thus, our synthesis of modelling methods can facilitate their selection that can maximise opportunities and refute the current political hesitation of NBS deployment compared with grey solutions for HMR management but also for the provision of a wide range of social and economic co-benefits. However, there is still a need for bespoke modelling tools that can holistically assess the various components of NBS from an HMR reduction and management perspective. Such tools can facilitate impact assessment modelling under different NBS scenarios to build a solid evidence base for upscaling and replicating the implementation of NBS

Patterns and universals of mate poaching across 53 nations : the effects of sex, culture, and personality on romantically attracting another person’s partner

As part of the International Sexuality Description Project, 16,954 participants from 53 nations were administered an anonymous survey about experiences with romantic attraction. Mate poaching--romantically attracting someone who is already in a relationship--was most common in Southern Europe, South America, Western Europe, and Eastern Europe and was relatively infrequent in Africa, South/Southeast Asia, and East Asia. Evolutionary and social-role hypotheses received empirical support. Men were more likely than women to report having made and succumbed to short-term poaching across all regions, but differences between men and women were often smaller in more gender-egalitarian regions. People who try to steal another's mate possess similar personality traits across all regions, as do those who frequently receive and succumb to the poaching attempts by others. The authors conclude that human mate-poaching experiences are universally linked to sex, culture, and the robust influence of personal dispositions.peer-reviewe

Are men universally more dismissing than women? Gender differences in romantic attachment across 62 cultural regions

The authors thank Susan Sprecher (USA), Del Paulhus (Canada), Glenn D. Wilson (England), Qazi Rahman (England), Alois Angleitner (Germany), Angelika Hofhansl (Austria), Tamio Imagawa (Japan), Minoru Wada (Japan), Junichi Taniguchi (Japan), and Yuji Kanemasa (Japan) for helping with data collection and contributing significantly to the samples used in this study.Gender differences in the dismissing form of adult romantic attachment were investigated as part of the International Sexuality Description Project—a survey study of 17,804 people from 62 cultural regions. Contrary to research findings previously reported in Western cultures, we found that men were not significantly more dismissing than women across all cultural regions. Gender differences in dismissing romantic attachment were evident in most cultures, but were typically only small to moderate in magnitude. Looking across cultures, the degree of gender differentiation in dismissing romantic attachment was predictably associated with sociocultural indicators. Generally, these associations supported evolutionary theories of romantic attachment, with smaller gender differences evident in cultures with high–stress and high–fertility reproductive environments. Social role theories of human sexuality received less support in that more progressive sex–role ideologies and national gender equity indexes were not cross–culturally linked as expected to smaller gender differences in dismissing romantic attachment.peer-reviewe

Ten millennia of hepatitis B virus evolution

Hepatitis B virus (HBV) has been infecting humans for millennia and remains a global health problem, but its past diversity and dispersal routes are largely unknown. We generated HBV genomic data from 137 Eurasians and Native Americans dated between ~10,500 and ~400 years ago. We date the most recent common ancestor of all HBV lineages to between ~20,000 and 12,000 years ago, with the virus present in European and South American hunter-gatherers during the early Holocene. After the European Neolithic transition, Mesolithic HBV strains were replaced by a lineage likely disseminated by early farmers that prevailed throughout western Eurasia for ~4000 years, declining around the end of the 2nd millennium BCE. The only remnant of this prehistoric HBV diversity is the rare genotype G, which appears to have reemerged during the HIV pandemic