1,721,103 research outputs found
Cory, Maynard S.
No full textCentro Asturiano membership record of Maynard S. Cory; Socio Number: 98320.https://digitalcommons.usf.edu/asturiano_membership/1838/thumbnail.jp
Research data supporting "Nanoscale molecular quantification of stem cell-hydrogel interactions"
No full textRaw data supporting: Maynard S. et al., 2020, ACS Nano, DOI: 10.1021/acsnano.0c07428
Preliminary report on some Minnesota lakes and their productiveness of fish food
Full text linkThis archival publication may not reflect current scientific knowledge or recommendations.Johnson, Maynard S.. (1933). Preliminary report on some Minnesota lakes and their productiveness of fish food. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/204020
Common Injurious Mammals of Minnesota
Full text linkThis archival publication may not reflect current scientific knowledge or recommendations. Current information available from University of Minnesota Agricultural Experiment Station: http://www.maes.umn.edu/Johnson, Maynard S.. (1930). Common Injurious Mammals of Minnesota. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/163688
Gauging HWRC performance from vehicle weigh-ticket data
No full textThis paper describes a modelling approach designed to investigate the variability in nett amenity bin weights produced by nine household waste recycling centres (HWRCs) in West Sussex, UK over a 12-month period. Compaction technique, vehicle type, site design and month were identified as key factors explaining 76% of the variability in the data. For each significant factor, a weighting coefficient was calculated to generate a predicted nett weight for every bin transaction. Analysis of predicted and observed mean bin weights suggested that three sites had similar characteristics but returned significantly different mean nett bin weights. Subsequent waste and site audits determined the possible sources of the remaining variability. Significant differences were identified in the proportions of bagged waste and dry recyclables deposited in the amenity waste stream at the sites, with significantly less observed at one site. Operational and managerial techniques (e.g. material separation, compaction frequency and site management ethos) were also identified as factors impacting on mean bin weights and general site performance. The model can be used to identify sites producing significantly different bin weights, enabling detailed ‘back-end’ waste analyses to be efficiently targeted and best practice in HWRC operation identifie
Analysis of mean bin weight data to monitor best practice at HWRCs
No full textThis paper describes a modelling approach used to investigate the significance of key factors (vehicle type, compaction type, site design, temporal effects) in influencing the variability in observed nett amenity bin weights produced by Household Waste Recycling Centres (HWRC). Understanding such variability is a prerequisite to achieving best operational practices, to minimise the number of vehicle movements between each HWRC and disposal sites, and achieve consequential environmental and traffic benefits. The method described can help to quickly identify sites that are producing significantly lighter bins, enabling detailed back-end analyses to be efficiently targeted and best practice in HWRC operation identified. Tested on weigh ticket data obtained from nine HWRCs across West Sussex, the model suggested that compaction technique, vehicle type, month and site design explained 76% of the variability in the observed nett amenity weights. For each factor, a weighting coefficient was calculated to generate a predicted nett weight for each bin transaction and Bognor Regis, Crawley and East Grinstead were identified as having similar characteristics but returning significantly different mean nett bin weights. Waste and site audits were then conducted at the three sites to try and determine the possible sources of the remaining variability. Significant differences were identified in the proportions of contained waste (bagged), wood, and dry recyclables entering the amenity waste stream with significantly less contained waste and dry recyclables observed in the amenity waste bins at Bognor Regis
The potential for local bring-sites to reduce householder recycling mileage
No full textUsing a significant database of origin postcodes, a study was designed to estimate the current annual mileage associated with visitor trips to household waste recycling centers (HWRCs)—known as manned recycling drop-off centers in the United States—and to identify how this mileage could be reduced if a series of "bring sites" (unmanned recycling drop-off centers) in the community were enhanced to take green garden waste. The total annual distance driven by approximately 4,677,000 visitors to the 26 HWRCs in Hampshire, United Kingdom, is estimated to be 40 million kilometers (assuming that 60% of visitors made dedicated trips), costing approximately £14 million (£1 = $1.896 in April 2005 U.S. dollars) in private transport and emitting approximately 1,873 tonnes of CO2 (as carbon) into the atmosphere. Providing a network of 104 bring sites capable of accepting green waste, in addition to the existing facilities provided by the 26 HWRCs, could save approximately 8.5 million kilometers (21%) of vehicle travel per annum (£3 million in visitor transport costs and approximately 369 tonnes of CO2 as carbon). Such a scheme would require a fleet of approximately 78 refuse collection vehicles at an annual cost to the scheme provider of slightly more than £1.5 million. If HWRCs become a major channel for the return and reprocessing of waste electrical and electronic equipment and some newly classified hazardous waste items, space at existing sites could become an issue. More local consolidation of certain waste categories (e.g., green waste) would enable HWRCs to focus their activities better
Multivariate analysis of the composition of materials collected in a survival bag co-mingled kerbside scheme: patterns and effectiveness of use
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