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Integrating blockchain with digital product passports for managing reverse supply chain
No full textThe reverse supply chain (RSC), vital for circular economies, faces considerable challenges, including transparency deficits, trust issues, and inefficient information sharing. Blockchain can enhance transparency and traceability in circular economy practices, but it has limitations in providing detailed, product-specific lifecycle data. In contrast, the digital product passport (DPP) is designed to provide this detailed information, offering comprehensive, high-quality data across a product’s entire lifecycle. By integrating DPP, the inherent data limitations of blockchain can be overcame, making it a more useful tool in promoting sustainable practices. The aim of this research is to explore integrating blockchain technology and the DPP to manage RSC for circular economy practices. To achieve this, a novel conceptual framework is presented that merge blockchain with DPP, potentially enhancing information efficiency throughout the entire lifecycle of end-of-life products and reducing uncertainties in RSC processes.12th CIRP Global Web Conference (CIRPe 2024)Procedia CIR
Exploration of ammonia stripping coupled adsorption-membrane filtration process for treating kitchen waste biogas slurry
Get PDFThe potential contamination of biogas slurry generated from the anaerobic digestion of kitchen waste (KW) poses a considerable challenge to its safe and effective utilization as a fertilizer. To tackle this problem, a novel route termed “AS-BC” was developed, integrating ammonia stripping (AS), biochar adsorption, and ceramic membrane filtration (CMF) for comprehensive pollutant mitigation. A stepwise optimization was carried out, comparing biochar adsorption investigation, the AS process, and the combined AS + CMF process. Results indicated that the AS process possessed the maximum total ammonia nitrogen (TAN) removal of 86.21% at an airflow rate of 40 L/min. The combined AS and CMF process with 0.1 μm membrane had best performance for total phosphorus (TP) with removal efficiencies of 80.45%–87.98%. Under the optimal biochar addition condition of 5 g/L with a particle size of 0.25–0.85 μm, the adsorption pretreatment effectively removed 0.41 g/g of soluble chemical oxygen demand (SCOD), prevented nutrient loss, and substantially enhanced pollutant removal efficiency in the subsequent CMF process. Compared to other routes, the route AS-BC achieved higher total nitrogen (TN), TAN, TP, and SCOD removal efficiency of 91.42%, 91.49%, 89.54%, and 76.34% from the raw biogas slurry, respectively. Moreover, the route AS-BC demonstrated its cost-effectiveness in producing nutrient-rich concentrated slurry suitable for use as fertilizer. The route AS-BC was proved to comprehensively remove various indicators from the KW biogas slurry while generating economically reuse by-products during the membrane filtration process. This study offers valuable insights into the trade-offs between AS performance enhancement and pollutant mitigation, pinpointing essential routes for future research and practical improvements.Ministry of Agriculture and Rural AffairsThe present work was funded by Jinhua City Science and Technology Bureau (2022-3-066) and Key Laboratory for Crop and Animal Integrated Farming, Ministry of Agriculture and Rural Affairs (202306).Environmental Researc
Suspended sediment transport in rivers: new indicators of transport dynamics for analysis of catchment and climate controls
No full textHolman, Ian P. - Associate SupervisorSuspended sediment is found naturally in rivers but can cause environmental and
engineering problems, especially if the quantity or quality has been altered. Many
factors affect suspended sediment concentration (SSC), such as land cover, land
use, vegetation growth, and weather, making it difficult to predict changes in SSC
at a location over short time periods (e.g., days to months). The aim of this
research was to improve the scientific understanding of intra-annual variations in
SSC through the statistical analysis of SSC timeseries data from rivers across a
variety of catchment and climate characteristics. The specific objectives were to:
(i) characterise the continental scale spatio-temporal variations in SSC dynamics
using new transport indicators, (ii) determine the contribution of climate to these
variations, and (iii) identify SS transport dynamic responses to climate oscillations
as a means to separate out the effects of shifts in seasonal weather from
catchment influences. The study used daily SSC (mg/l) and site attribute data
from the US Geological Survey (USGS), which included 1,666 gauging stations
of SSC across the continent, Hawaii and Puerto Rico. First, new indicators of
SSC dynamics were developed and applied to the data, based on magnitude,
frequency and timing (MFT). Through statistical analysis e.g., principal
component analysis (PCA) and K-means clustering, new insights in spatial
variability of temporal dynamics in SSC were identified e.g., high extreme events
in desert and mountainous areas, the longest duration of events in upper Midwest
and distinctly different timing of events in Puerto Rico. Next, further statistical
analyses (regression and geographically weighted regression) were conducted
on a reduced number of sites (n=120) to determine the relative importance of
different catchment and climate factors. The MFT indicators of SS enabled
identification of short term dynamics and new understandings of varying influence
of land use and land cover. The key results were identified that agricultural covers
were positively related with low frequency SSC events. Urban and forest covers
brought higher frequency events, except in the driest region. Annual average
precipitation had a negative relationship with SSC magnitude. Finally, the
influence of climate oscillations e.g., El Niño–Southern Oscillation (ENSO), North
Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO) on SSC transport
dynamic indicators was evaluated for four catchments using continuous and
cross wavelet analyses. Periodicities in SSC indicators were identified that match
climate oscillations, suggesting that small shifts in seasonal weather (e.g., wetter
winters) can cause significant changes in SS transport dynamics in rivers. Future
works remain to be using latest SS data in the future or application of latest
technology e.g., turbidity as well as optimization of input parameters in modelling
by generation of MFT time series. This research provides new understandings of
SS transport dynamics in rivers and the relative importance of catchment and
climatic factors, which will inform practitioners of SS modelling for better
predictability in a changing climate.PhD in Wate
Two-photon dual-comb LiDAR for non-cooperative targets
Get PDFPresentationEngineering and Physical Sciences Research Council (EPSRC)AWERenishaw plcDefence and Security Doctoral Symposia 2024 (DSDS24
A systematic analysis and exposition of the Russian military term 'Maskirovka' [маскировка]
Get PDFThis paper describes the progress to date of a part-time PhD on the topic of ‘Maskirovka’, in the context of the Russian (and Soviet) military. A mixed methods approach, utilising analytical techniques from language-based disciplines, such as applied linguistics, lexicography and translation studies, has been conducting a systematic exposition of the topic. The study has employed qualitative text-analysis, intertextual analysis and multimodal analysis on a repository of N=161 original source texts between 1914 – 2024, and N=39 Russian military dictionaries and lexica between 1795 - 2024. Some initial insights and findings are describedDefence and Security Doctoral Symposia 2024 (DSDS24
Where are we with gender parity in academia and professional societies? A multinational look at women in soil science
Get PDFIssues of diversity, equity and inclusion (DEI), including gender equity, have gained increasing recognition at the beginning of the 21st century. As an academic discipline, soil science has been late in addressing gender equity, but several peer‐reviewed studies have been published in the last 5 years. This study investigated gender equity in the soil science university faculty/academic staff (f/as) and soil professional societies in Canada, Egypt, Mexico, Nigeria, the United Kingdom and the United States of America (USA) using data publicly available on the Internet and anonymized data from soil science professional societies. We found that women still lagged behind men among our soil science f/as by considerable margins (69.2% men vs. 30.8% women for pooled data for all six countries in this study), and that the percentage of women in soil science f/as positions are similar to those for f/as women in many other scientific fields. There are differences in gender equity by soil science subdiscipline that vary by country. In countries where data are available to make comparisons, over the last 6–8 years, the gender gap has closed to some degree, both overall and for sub‐disciplines. Women also often hold leadership positions in numbers that are lower than their representation among the f/as and membership in professional societies. In addition, women are recognised with awards such as society fellowship in numbers lower than their overall representation would suggest. This study concludes that progress has been made on several fronts in the last 6–8 years, but there is still much work to be done to achieve gender equity in soil science academia and professional societies. It is recommended that soil science societies collect, analyse and compare data on gender in the discipline so that progress can be evidenced, tracked and encouraged.European Journal of Soil Scienc
Developing prompts to facilitate generative pre-trained transformer classifying decision-errors in flight operations
Get PDFThe emergence of artificial intelligence (AI) with advanced natural language processing offers promising approaches for enhancing the capacity of textual classification. The aviation industry is increasingly interested in adopting AI to improve efficiency, safety, and cost efficiency. This study explores the potential and challenges of using AI to analyse decision errors in flight operations based on the HFACS framework. In pre-training, the model is trained based on a large amount of data to predict the next word in a sequence which allows the model to learn relationships between the words and their meaning in the accident investigation reports. Initial discoveries demonstrated that the AI model could supply a consistent HFACS framework and populate these dimensions with moderate accuracy. Future research is focused on the development of this HFACS-GPT model through fi-ne-tuning and deep learning, facilitating more reliable and consistent conversations.2024 Human Systems Integration International Conference HSI 202
A critical review of the decarbonisation potential in the U.K. cement industry
Get PDFAs urbanisation and infrastructure development continue to drive rising cement demand, the imperative to significantly reduce emissions from this emissions-intensive sector has become increasingly urgent, especially in the context of global climate goals such as achieving net zero emissions by 2050. This review examines the status, challenges and prospects of low-carbon cement technologies and mitigation strategies through the lens of the U.K. cement industry. A mixed-methods approach was employed, combining structured literature searches across academic databases with analyses of industry reports, market data and technological roadmaps to ensure a comprehensive evaluation. Following an outline of cement production, resource flows and the sector’s landscape in the U.K., the review delves into an array of decarbonisation pathways. This includes deploying the best available technologies (BATs), fuel switching, carbon capture utilisation and storage (CCUS), clinker substitution and low-carbon cement formulations. A critical assessment is provided on the technological readiness, costs, resource availability considerations and scalability aspects governing the widespread implementation prospects of these approaches within the U.K. cement industry. Furthermore, this study proposes a roadmap that considers priority avenues and policy needs essential for facilitating the transition towards sustainable cement production aligned with the U.K.’s net zero obligations by 2050. This evaluation contributes significantly to the ongoing decarbonisation discourse by holistically mapping technological solutions and strategic imperatives tailored to the unique challenges and opportunities presented by the U.K. cement sector.This research was funded by Transforming Foundation Industries Research and Innovation Hub (TransFIRe), grant number EP/V054627/1.Material
CFAR detection in heterogeneous K- distributed sea-clutter background
Get PDFDetection of targets at sea is challenging due to unwanted echo returns from the sea surface, i.e. sea clutter returns. To account for the undesired effects of sea clutter at the receiver, and to control the probability of detection and false alarm, the K-distribution has often been used to provide a promising statistical fit to real clutter data. However, controlling the performance of the receiver becomes very challenging in heterogeneous clutter, that is when there is a sudden transition from one clutter region to another with a change in shape and/or scale distribution parameters. A possible solution to this challenge is to use some prior information on the sea clutter characteristics to generate clutter maps that inform adaptive detection
solutions. This prior information can be obtained by the radar in real time (or close to real time) using oceanographic models, statistical clustering or potentially Artificial Intelligence.This research presents our first step in this direction by investigating detection in heterogeneous fully correlated K-distributed sea clutter. A transition line between homogeneous clutter regions is estimated using the statistical parameters of a K-distribution, to avoid polluting the training windows of a Constant False Alarm Rate (CFAR) detector with non-representative data. The transition cells assist to resolve the heterogeneous clutter into
small homogeneous clutter regions and for every homogeneous region a CFAR detector is designed according to the K-distribution shape parameter. Results are obtained and presented for simulated data as well as for real sea clutter data provided by Hensoldt UK.Hensoldt UKDefence and Security Doctoral Symposia 2024 (DSDS24
The soil microbial methylome: a tool to explore the role of epigenetic memory in driving soil abiotic legacy effects
Get PDFEpigenetics is a phenomenon whereby a stable hereditable change in gene expression can occur without changing the DNA sequence. DNA methylation (the addition of a methyl group to specific nucleotides in specific DNA motifs) is the most studied epigenetic mechanism and is widely observed in both eukaryotic and prokaryotic cells. We hypothesise that the soil methylome may play an important role in the manifestation of soil abiotic legacy effects, whereby temporary exposure of soil microbial communities to particular environmental conditions influences future soil microbial function. These abiotic legacy effects are important because they underpin the delivery of key ecosystem services in response to global environmental change. Third generation long-read sequencing technologies, such as Pacific Bioscience Single-Molecule Real-Time sequencing (SMRT-seq) and Oxford Nanopore sequencing provide an opportunity to study methylome heterogeneity in complex microbial communities. The simultaneous measurement of epigenetic, transcriptional, and microbial community composition changes may lead to the development of biomarkers of historic environmental stress and a greater understanding of the role of the soil methylome in the resilience of soil microbial communities to future environmental perturbations. It is therefore timely to add the meta-epigenetic layer to the multi-omics analysis of the soil microbiome to advance our understanding of soil abiotic legacy effects.Soil Biology and Biochemistr