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Continuous, self-driven liquid fertilizer extraction from human urine using microbial fuel cells for circular economy: Catholyte characterization
No full textThis work presents the development of urine filtration microbial fuel cells, converting urine into a purified catholyte in which key macronutrients such as nitrogen, phosphorus, and potassium (NPK) are recovered, and chemical oxygen demand (COD) is removed, with energy being continuously produced in the electrofiltration process. In this study, electrofiltrating-MFC (EF-MFC) bioreactors using ceramic-based membranes were assembled to oxidize urine and generate an electric current, which facilitated the movement of cationic species and water toward the cathode. As a result, a flux of purified cathodic filtrate was achieved at a 9.5 higher rate than the control, while the organic content was removed. The reactor design enabled continuous electropumping of the newly formed catholyte throughout the experiment. In addition, NPK were also recovered in the cathodic filtrate, thus demonstrating the electrofiltration capacity of the ceramic bioreactors. This work exploited pH and ion splitting mechanisms that were directly related to the electric field generated by the EF-MFC system and to study electro-osmotic drag as a continuous electropumping mechanism responsible for sustained extraction of water/nutrients from urine. Furthermore, the free chlorine detected in the catholyte produced may contribute to the quality and disinfection (safety) of the purified biofertilizer. The proposed technology allows for the additional oxidation of the organic fraction in urine on the cathode side of the half-cell while retaining a high proportion of all other key macronutrients for potential reuse as a liquid fertilizer as a byproduct of stable electrical current production in the process
Professional enablers: Inside the line between advice and offence
No full textThis guide explores how professional enablers become embedded in financial crime, often gradually and unintentionally, and what can be done to disrupt that trajectory. The learnings are taken from Tenet Law’s ‘At the Coalface’ webinar series, featuring guest Jonathan Gilbert, a former practising solicitor who was struck off for his facilitating role in a multimillion pound mortgage and bank fraud.Jonathan shared a personal and honest account of how advisory roles can slide into enabling fraud, the ethical compromises that normalise risk, and the personal and professional consequences that follow. He reflected on the investigation and imprisonment, and how those experiences now inform his work as an international educator and consultant in financial crime prevention.The key learnings address prevention, governance, and accountability through the realities of pressure, culture, and decision making, with the aim of helping firms recognise risk earlier and respond more effectively when it arises
Choice of lipid supplementation for in vitro erythroid cell culture impacts reticulocyte yield and characteristics
Get PDFLipids, particularly cholesterol, are critical components of red blood cell (RBC) membranes, influencing protein function, cell stability, and deformability. Reticulocytes (young RBC) derived from in vitro erythroid cultures have been reported to possess less cholesterol than their native counterparts, compromising their functional integrity and lifespan. However, variability in starting materials and culture protocols between studies has hindered definitive conclusions regarding the nature and consequences of this lipid deficiency. Here, we evaluated the influence of lipid sources on reticulocyte quality using a well-established CD34⁺ erythroid culture system. We compared the use of human AB serum and Octaplas (solvent/detergent (S/D)-extracted pooled plasma) as lipid sources. Our results reveal that S/D-extracted plasma leads to cholesterol-deficient reticulocytes with impaired characteristics, including reduced filtration yield, heightened osmotic fragility, and altered PIEZO1 activity. In contrast, AB serum supported the generation of functionally stable reticulocytes, with cholesterol supplementation required to rescue the majority of defects observed with culturing erythroid cells with plasma alone. Importantly, this study provides the first integrated lipidomic, metabolomic, and proteomic characterisation of in vitro-derived reticulocytes cultured under distinct lipid conditions. These multi-omic datasets offer new insights into the consequences of reduced lipid availability during erythroid culture and offer new insights into how culture media affects the development and functionality of lab grown blood
Interrogating marine plastics pollution regulations: The intended roles of the Global Plastics Treaty
No full textMarine plastic pollution is a growing global issue that severely affects our ecosystems, biodiversity, and human well-being. Both national and international organisations have established frameworks and regulations to address the increase of plastic pollution in marine environments, covering everything from rules on the disposal of hazardous materials and chemicals used in plastic manufacturing to initiatives that promote recycling. Despite these efforts, there remains a need for a more effective legal instrument to govern marine plastic pollution. Current conventions lack a comprehensive life-cycle approach or strong enforcement mechanisms. A Global Plastics Treaty could offer a potential solution and fill the gaps present in existing regulations. This article critically examines the current landscape of marine plastics regulation while analysing the intended contributions and challenges that a global plastics law might face in regulating marine plastic pollution
Grape must as a bioelectrochemical processor
Get PDFWe explore spontaneous voltage oscillations in grape must (mustalevria) fermentation systems. This study uses multichannel differential electrode arrays. Seven platinum−iridium (Pt/Ir) electrode pairs tracked bioelectrochemical changes for 200,000 s. They showed complex patterns over time and space. Frequencies varied from 0.00044 to 0.00215 Hz. Power spectral density analysis showed brown noise traits. The spectral slopes ranged from −2.01 to −3.28. This indicates strong temporal integration and memory effects during fermentation. Environmental correlation analysis showed temperature as the primary modulator (r = 0.245−0.558), while humidity exhibited negative correlations (−0.052 to −0.245). Binary state analysis showed that the system uses natural Boolean logic. XOR gates had the highest entropy at 0.93 bits. This suggests that there is significant temporal asynchrony across different spatial areas. Principal component analysis found activation patterns without a single strong mode. It needed 3−4 components to capture 77.6% of the system's variance. The fermentation medium showed uneven metabolic activity across different areas. Also, the electrode locations were statistically independent, with mutual information below 0.206 bits. These findings show that traditional food fermentation systems work like self-organizing bioelectrochemical processors. They can also perform distributed computation through local metabolic interactions. Brown noise scaling and memory effects can impact fermentation monitoring and control. This means short-term measurements may not accurately predict long-term behavior. This work shows that grape must fermentation can be a model system. It helps us study new computational properties in biological electrochemical systems
Residual strength and load redistribution in multi-bolted single lap joints with simulated environmentally assisted cracks
Get PDFEnvironmentally assisted cracking (EAC) in bolted joints poses a serious threat to the structural integrity of aerospace components. Despite widespread industry awareness, the mechanical consequences of spanwise EAC on load sharing in multi-bolt configurations remain insufficiently characterised. This study presents the first systematic experimental investigation into the residual strength and internal load redistribution of three-bolt single-lap shear joints containing predefined, EAC-like cracks. To isolate geometric effects from material-specific corrosion behaviour, 1050 aluminium was employed as a model material, and artificial cracks ranging from 15 to 30 mm were introduced at the central fastener hole. Quasi-static tensile testing, supported by strain-gauge instrumentation, a validated three-dimensional finite element model, and a simplified analytical model, was used to evaluate joint performance. All cracked specimens retained peak load capacities comparable to uncracked controls, indicating significant structural redundancy. However, this apparent resilience masked a critical shift in internal force flow: the fastener adjacent to the crack experienced up to 60 % load reduction, with adjacent bolts compensating for the loss. Importantly, all joints failed by abrupt net-section fracture at the outermost bolt, with no evidence of progressive bearing failure. These results challenge conventional assumptions of damage tolerance by revealing that preserved load capacity can coexist with unpredictable and brittle failure modes. The findings provide experimentally validated benchmarks for stiffness degradation and load sharing in damaged joints, offering guidance for the design, analysis, and maintenance of EAC-prone aerospace structures
Localisation of defects on carbon fibre surfaces using deep learning
Get PDFThis study explores the application of deep learning for localization and classification of common defects in carbon fibre materials. A Sony IMX250MZR polarisation camera was employed to leverage the polarising properties of CFRP surfaces. However, analysis revealed that the additional polarisation data provided minimal advantages. Instead, promising results were obtained using a standard monochrome output from the sensor. Defects were classified into two categories: "carbon fibre defects" and "foreign bodies". A dataset comprising of 2400+ annotated instances for each type was analysed using two state-of-the-art deep learning models: YOLOv11-seg,for instance segmentation, and SegFormer for pixel-wise classification. Images were captured under three different illumination conditions including specialized dome lighting and strip lights in ambient environments. Each lighting configuration yielded promising results, with dome lighting demonstrating superior performance. YOLOv11 achieved an average precision score of 0.817 under dome lighting, compared to 0.672 in the least favourable lighting scenario. SegFormer slightly outperformed YOLOv11 in segmentation accuracy, achieving a mean Intersection over Union (mIoU) of 0.742 compared to 0.678 for YOLOv11. The consistently high detection rates demonstrate the potential of both models for reliable identification of critical and minor defects, making them well-suited for industrial quality assurance
The representativeness of the Annual Survey of Hours and Earnings and its implications for UK wage policy
No full textThe Annual Survey of Hours and Earnings (ASHE) is based on an annual one per cent sample of employee jobs and provides many of the UK’s official earnings statistics. These statistics are produced using official weights designed to make the achieved sample in each year representative of the population of employee jobs in Britain by gender, age, occupation, and region. However, we show that jobs in small, young, private-sector organisations remain significantly under-represented after applying these weights. To address this issue, we develop new weights and demonstrate their importance through policy-relevant examples. Our new estimates suggest that the bite of the National Living Wage is greater than previously reported, and the gender pay gap is wider. We conclude that a new official review of the methodology for ASHE is merited, to improve the accuracy and reliability of data informing earnings analysis and research in the UK
A temporally dynamic feature-extraction framework for phishing detection with LIME and SHAP explanations
Get PDFPhishing remains one of the most pervasive social engineering threats, exploiting human vulnerabilities and continuously evolving to bypass static detection mechanisms. Existing machine learning models achieve high accuracy but often act as opaque systems that lack robustness to evolving tactics and explainability, limiting trust and real-world deployment. In this research, we propose a dynamic Explainable AI (XAI) approach for phishing detection that integrates temporally aware feature extraction with dual interpretability through LIME and SHAP applied to the resulting window-level features. The novelty of this research lies in a temporally dynamic feature framework that simulates a plausible email reading progression using a heuristic temporal model and employs a sliding window aggregation method to capture behavioural and temporal patterns within email content. Using an aggregated dataset of 82,500 phishing and legitimate emails, dynamic features were extracted and used to train four classifiers: Random Forest, XGBoost, Multi-Layer Perceptron, and Logistic Regression. Ensemble models demonstrated strong performance with XGBoost achieving 94% accuracy and Random Forest 93%. This research addresses an important gap by combining dynamically constructed temporal features with transparent explanations, achieving high detection performance while preserving interpretability. These findings demonstrate that dynamic temporal modelling with explainable learning can enhance the trustworthiness and practicality of phishing detection systems, highlighting that temporally structured features and explainable learning can enhance the trustworthiness and practical deployability of phishing detection systems without incurring excessive computational overhead
LivDem-Families: Adapting the LivDem group intervention to support families to talk together about dementia
Get PDFIntroduction. LivDem is a psychoeducational group intervention designed to help people living with dementia talk more openly about their condition and adjust emotionally. While the original model focuses solely on individuals with dementia, limited involvement of family members can act as a barrier to wider relational support. Given the importance of maintaining strong relationships in dementia care, this study explores the adaptation of LivDem for couples and families.Method. The adaptation process involved four phases: (1) a survey of trained LivDem facilitators; (2) a stakeholder consultation with 26 participants including people with dementia, family members, facilitators, and professionals; (3) development of a manualised five-session intervention for families and couples, informed by public involvement; and (4) a pilot implementation with seven families. Sessions were delivered either by a clinical psychologist or by assistant psychologists under supervision. Quantitative and qualitative data were collected to assess feasibility, acceptability, and impact.Results. Initial findings from the pilot phase are promising. The seven families rated the intervention highly for acceptability (mean score: 19.3/20), appropriateness (19.3), and feasibility (19.2). Qualitative feedback indicated improved communication, emotional adjustment, and relational resilience. However, the intensity of the sessions led to disclosures of self-harm or harm to others in three families who were assessed or took part, suggesting a need for robust risk assessment and clinical oversight.Conclusion. The LivDem-families intervention shows strong potential for supporting relational adjustment to dementia. However, its emotional intensity necessitates careful screening and delivery by trained facilitators within appropriate clinical settings. A non-randomised feasibility study across two NHS sites is planned to further evaluate its integration into dementia care pathways