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Early Childhood Exposure to Endocrine Disrupting and Neurotoxic Chemicals: Associations with Internalizing and Externalizing Difficulties from Childhood to Adolescence in the Rhea Cohort, Crete, Greece
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Data supporting these findings are available upon request from the corresponding author K.K.Many common chemicals are known or suspected to harm brain development, and children are particularly vulnerable, yet research on their long-term effects on mental health is limited. This study investigated the associations of early childhood exposure to endocrine disrupting and neurotoxic chemicals with the development of internalizing, externalizing, and attention-deficit/hyperactivity disorder (ADHD) symptoms from early childhood through adolescence in 387 children from the Rhea cohort in Crete, Greece. At age 4, serum concentrations of 3 organochlorine pesticides and 14 polychlorinated biphenyls, and urinary concentrations of 7 phthalate metabolites and 6 dialkyl phosphate metabolites were measured. Children’s symptoms were assessed via maternal reports at ages 4, 6, 11 and 15 years. Using generalized estimating equation models, the study found that early exposure to hexachlorobenzene (HCB) and dichlorodiphenyldichloroethylene (DDE) was associated with increased externalizing symptoms across ages in girls [beta (95% CI): 0.20 (0.04, 0.37) and 0.11 (0.01, 0.21), respectively]. Among girls, low molecular weight (LMW) phthalates were also linked to elevated internalizing and externalizing symptoms, as well as ADHD-related difficulties [beta (95% CI): 0.15 (0.04, 0.26), 0.13 (0.01, 0.25), and 0.13 (0.02, 0.24), respectively]. Additionally, exposure to organophosphate pesticides was associated with increased externalizing and ADHD symptoms [beta (95% CI): 0.13 (0.04, 0.22) and 0.12 (0.04, 0.20), respectively]. The findings suggest that early childhood exposure to environmental chemicals may have long-term effects on emotional and behavioral development, with pronounced effects observed only in girls.The Rhea project was financially supported by European projects (EU FP6-2003-Food-3-NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7-HEALTH-2009-single stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO, EUFP7-HEALTH-2012 Proposal No 308333 HELIX, FP7 European Union project, No. 264357 MeDALL), the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011–2014; Rhea Plus: Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health: 2012-15), the Hellenic Ministry of Health and the General Secretariat for Research and Innovation. The research project entitled “Developmental Trajectories of Internalizing and Externalizing Symptoms from Early Childhood to Adolescence: The Role of Psychosocial and Environmental Factors—IntExt Trajectories” was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “2nd Call for H.F.R.I. Research Projects to support Faculty Members & Researchers” (Project Number: 4397)
The KGB's Perception of DIA at the End of the Cold War
No full textThe KGB trained its officers to view the US Defense Intelligence Agency as a formidable enemy. This article explores an article published in the KGB's internal journal, Сборник КГБ (KGB Digest) in 1989. It describes the KGB's perceptions of DIA and recommends efforts that the KGB should take against it.https://www.afio.com/available-excerpts-from-the-intelligencer.htm
Lean manufacturing principles as a driver for digital transformation: Adoption insights and performance outcomes in Turkish SMEs
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonManufacturing companies have started to embrace Digital Transformation (DT) technologies to stay competitive and enhance their operational performance. However, the real industry implementation of DT technologies has proven challenging, particularly for small and medium-sized enterprises (SMEs) that face unique obstacles, especially within developing countries like Turkey. To improve the success rate, recent studies have been investigating the role of Lean Manufacturing (LM) principles to aid the adoption of DT technologies. Despite this interest, research on how LM principles can support DT adoption remains limited, particularly for SMEs. While larger corporations with greater resources are more frequently studied, SMEs often fall behind in DT adoption. Addressing this gap, this study examines how LM principles can aid Turkish manufacturing SMEs in adopting DT technologies, with the goal of improving their operational performance.
The theoretical lens of this research is institutional theory supported with contingency theory, to provide a more comprehensive understanding of DT technology adoption within SMEs in a developing country. While institutional theory offers valuable insights as one of the primary theoretical lenses of DT, existing research indicates that it often overlooks the specific challenges SMEs encounter in dynamic and diverse environments like manufacturing. To address this limitation, contingency theory is incorporated into the framework. As a result, the theoretical model is based on institutional theory, reinforced by contingency theory, to examine the impact of LM principles on the adoption of DT technologies in Turkish SMEs, with the goal of enhancing operational performance. Developing and validating this theoretical framework not only deepens the understanding of DT adoption in SMEs but also expands the institutional theory by establishing a robust model tailored to a more complex environment with specific needs and challenges of SMEs in developing countries.
To accomplish the research objectives, this study adopted a quantitative research approach. A questionnaire survey was administered, with responses collected from 208 participants representing Turkish SMEs. Following data collection, quantitative analysis was conducted using Structural Equation Modelling (SEM) with IBM SPSS and AMOS software. The SEM analysis results indicate that LM principles positively influence the adoption of DT technologies within Turkish SMEs, providing insights into the specific LM principles that drive this impact. Additionally, the analysis revealed that institutional pressures, specifically mimetic, coercive, and normative pressures arising from competitors, government regulations, and industry further supported DT adoption in Turkey. The findings also provide evidence that DT technologies contribute to improved operational performance within Turkish SMEs.
This research offers empirical evidence that LM principles support DT technology adoption in Turkish SMEs, providing valuable insights into how LM principles can contribute to DT adoption processes. From a theoretical perspective, the study extends the institutional theory framework by adapting it to more complex environments through the integration of contingency theory. Additionally, the findings provide practical guidance for managers on aligning their strategies to facilitate DT adoption and inform policymakers on the effects of creating supportive policies that enhance DT adoption among SMEs
Sustainability Reporting and External Assurance: Evidence From UK Listed Firms
Get PDFThis paper develops and tests a model explaining why some companies obtain external assurance for their sustainability reports while others do not. Our model integrates rational choice and stakeholder theories, providing novel insights into the sustainability assurance literature. Data were collected via an online questionnaire from 105 UK listed companies, and partial least squares structural equation modelling (PLS‐SEM) was employed to test the proposed model. We found that decision makers' perceived benefits of external assurance exert a direct positive effect, while perceived costs have a direct negative effect. Indirectly, external assurer independence and market competition positively influence the decision through perceived benefits, whereas adherence to sustainability reporting guidelines has an indirect negative effect. Additionally, institutional investors exert a direct positive impact on the decision to obtain assurance. Interestingly, when institutional investors demand external assurance, the influence of decision makers' perceptions of benefits and costs appears to diminish. These findings advance understanding of the interplay between rational choice and stakeholder theories in shaping decisions to obtain sustainability assurance. The study also carries practical implications for academics, business decision makers, external sustainability assurance providers and policymakers involved in the governance and oversight of sustainability reporting.The authors received no specific funding for this work
Recovered cellulosic fibres as a novel carrier for self-healing cementitious materials
No full textThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonCementitious materials are the most widely used construction material due to their ability to be used in a wide range of applications. However, cementitious materials place environmental stresses by OPC alone, accounting for 7% of global man-made CO2 emissions. Concrete is susceptible to microcracking, which puts a significant financial burden on the industry to repair. The use of self-healing technology has been an effective method in managing microcracking autonomously. This thesis aims to develop a sustainable selfhealing technology utilising recovered cellulose waste material from wastewater treatment as a novel carrier material for the application of self-healing cementitious materials. The approach used in this thesis involves a comprehensive experimental regime in which L. Pakistanensis was selected from a number of soil isolated microorganisms to be the most suitable for self-healing cementitious applications. The media was optimised for this particular bacterium to improve ureolytic activity to maximise CaCO3 production. The bacterial spores were then immobilised and coated to compare leakage, protective capabilities, and survival after immobilisation. Finally, the immobilised recovered cellulosic fibres were then used as additives in mortar to promote self-healing, in which the mechanical properties were measured, along with self-healing capabilities, monitoring the crack width and regained strength of the self-healing material. Finally, the healed products were then characterised using SEM, EDS, FTIR, and XRD to identify the material being produced. This study demonstrates the healing capabilities of a novel wild strain of bacterium, in which the optimised nutrients were able to show CaCO3 production of 0.43 g/100 mL after 72 hours. It was also able to demonstrate that upon investigating the microstructure of the immobilised bacteria and nutrients using oven drying, CaCO3 was produced, which was absent in the freeze-dried specimens. Furthermore, by utilising RCF as a carrier, it was able to heal a crack width of 0.60 mm within 28 days. Additionally, exposure to various healing conditions presented novel brown coloured healing products when exposed to 5% CO2. This study also uncovered the challenges associated with the requirement of liquid water for healing to occur, in which healing was observed with the use of RCF. Signs of healing were observed within 28 days in relative humidity conditions (60% and 95%). Finally, coating immobilised RCF with sodium silicate (30%) was able to demonstrate a regained strength of 47.26% within 28 days. This study shows the valorisation of a waste material which provides excellent self-healing capabilities due to its unique internal structure system, moisture absorption capabilities, and crack width controlling ability. It can therefore be selected as a suitable additive to cementitious material to promote effective healing. Although current challenges limit specific applications of self-healing technology. However, this novel carrier provides an alternative sustainable carrier option, which improves the application options of self-healing technology. There are limited studies in the literature using L. Pakistanensis and RCF for selfhealing applications, along with showing the ability of this novel self-healing agent to work without the presence of liquid water. These findings in this thesis contribute to a circular economy approach in the use of recovered material at the end of their service life and widen the application for self-healing, not limited to the presence of liquid water
Acceptability and feasibility of a sensor-instrumented ‘SmartSocks’ wearable prototype to detect agitation in people with dementia
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Code used in the data preparation and analysis is available at https://github.com/creesebyron/SmartSocks. Consent was not obtained for open posting of data. Data are embargoed on Brunel University of London’s research data repository, Figshare (10.17633/rd.brunel.30127036) and accessible via request. Access will be granted once users have consented to the data sharing agreement.Letter to Editor.The project is funded by Innovate UK (Biomedical Catalyst 2022 Round 2: Industry-led R&D), project number 10055596. This study was supported by the National Institute for Health and Care Research (NIHR) Exeter Biomedical Research Centre
Global sensitivity analysis of blue hydrogen production: a comparative study using machine learning
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The data generated in this work is made available at Brunel Figshare database at https://doi.org/10.17633/rd.brunel.29478566.v1.Supplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S0360319925051560?via%3Dihub#appsec1 .Data-driven modelling utilising machine learning (ML) techniques offers a powerful alternative to first-principles simulations of chemical processes. In this work, artificial neural networks and random forests were developed as surrogate models, trained on data from a first-principles model of sorption-enhanced steam methane reforming with chemical-looping combustion. These ML-based surrogates were integrated with global sensitivity analysis (GSA) approaches to identify key process drivers and evaluate the comparative performance of different GSA methods in chemical process modelling. The surrogate models achieved an approximately 99 % reduction in computational time compared to first-principles simulations, while maintaining predictive accuracy. Sensitivity analysis demonstrated that the CaO/natural gas (CaO/NG) ratio is a dominant parameter, strongly influencing carbon capture efficiency and hydrogen production performance (cold-gas efficiency and H2 purity). In-situ CO2 removal from the reformer was shown to shift equilibrium towards higher hydrogen yields while simultaneously enabling CO2 capture. Ratios of CaO/NG ≥ 1.00 ensured high capture efficiency, while improvements in cold-gas efficiency were observed from ratios ≥0.5. Among GSA methods, the Sobol approach delivered high computational efficiency (0.5 s) with first- and second-order sensitivities, whereas Shapley additive explanations provided greater interpretability but at significantly higher computational cost (384 s).The research presented in this work has received financial support from the UK Engineering and Physical Sciences Research Council (EPSRC) through the EPSRC Doctoral Training Partnerships (DTP) award, EP/T518116/1 (project reference: 2688399)
International expert consensus on surgery for type 2 diabetes mellitus
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No datasets were generated or analysed during the current study.Introduction:
Metabolic and bariatric surgery (MBS) has been an established treatment option for patients with Type 2 diabetes mellitus (T2DM), but there is a relative paucity of evidence-based guidelines on preoperative, operative, and postoperative considerations concerning metabolic surgery for T2DM patients. To address this gap, we initiated a Delphi consensus process with a diverse group of international multidisciplinary experts.
Method:
We embarked on a Delphi consensus-building exercise to propose an evidence-based expert consensus covering various aspects of MBS in patients with T2DM. We defined the scope of the exercise and proposed statements and surveyed the literature through electronic databases. The literature summary and voting process were conducted by 52 experts, who evaluated 44 statements. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria.
Results:
Consensus, defined as > 80% agreement, was reached for 43 out of 44 statements. The experts reached an agreement on the nature, terminology, and mechanisms of action of MBS. The currently available scores for predicting remission of T2DM after surgery are not robust enough for routine clinical use, and there is a need for further research to enable more personalized treatment. Additionally, they agreed that metabolic surgery for T2DM is cost-effective, and MBS procedures for treating T2DM vary in their safety and efficacy.
Conclusion:
This Delphi expert consensus statement guides clinicians on various aspects of metabolic surgery for T2DM and also grades the quality of the available evidence for each of the proposed statements.None
Developing diagnostic methods for fatigue damage assessment
Get PDFThis thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonMost of the metal’s failure happens because of the fatigue which is associated with metals that is subjected to cyclic loading over time. Fatigue damage detection is one of important technological issues in both academic and industrial fields. Early fatigue damage detection promotes circular economy and sustainability by prolonging the lifespan and durability of metals. In most metals, in low and high cycle fatigue, the stages of fatigue are pre-crack nucleation, crack nucleation, micro and macro crack growth, and final failure. Several techniques have been proposed and developed for detecting fatigue damage in metals. However, comparatively less attention has been given to early fatigue damage detection, specifically targeting the pre-crack nucleation stage. The pre-crack nucleation stage begins with an increase in dislocation density, followed by the formation of dislocation entanglements and ultimately, the development of slip bands. Subsequently, these slip bands induce intrusion and extrusion, serving as nucleation sites for cracks. The identification of these defects plays an important role as it can facilitate the use of appropriate treatment to either eliminate or mitigate the defects, consequently leading to increase in metals lifespan. The use of non-destructive testing (NDT) methods is particularly crucial in this context, given their wide applicability within industrial environments. Thus, in this thesis appropriate NDT methods for early damage detection fatigue in 316L stainless steel had been used. NDT methods enable the detection of fatigue damage without destruction of specimen.
Techniques such as electrical resistivity measurement and nonlinear ultrasonic testing are employed to detect these defects. The electrical resistance method operates on the principles of Ohm's law, whereby a current is applied to the metal and the resulting voltage drop is measured to determine its electrical resistance. The resistivity is then calculated based on the sample’s geometry. Structural defects including dislocations, entanglements, slip bands, and cracks contribute to scattering and elevation in electrical resistivity. However, to make this method works effectively, a responsive technique with the capability of nΩ resolution is needed. The used method in this study is a combination of delta mode and four-probe technique that effectively eliminates thermoelectric voltages resulting from temperature variations in the circuit and minimizes the impact of lead resistance. Another approach that is used in this study is nonlinear ultrasonic. In this technique, a wave is propagated through the metal specimen, and upon interaction with defects, higher frequency waves are generated. By detecting and analysing these signals, the presence of defects can be identified. This unique capability enables the detection of early fatigue defects such as dislocations and slip bands evolution, providing improved sensitivity and precision in defect identification. Findings indicate that both electrical resistivity measurement and nonlinear ultrasonic testing proficiently detect early-stage fatigue defects in 316L stainless steel. These methods reveal significant changes in two distinct regions prior to 10% of the component's fatigue life. Following the identification of two distinct regions of significant signal variation prior to 10% of the fatigue life, advanced microscopy techniques were employed to investigate the underlying mechanisms responsible for these observations. Optical microscopy and Scanning Transmission Electron Microscopy with High-Angle Annular Dark Field (STEM-HAADF) imaging were utilized to observe the microstructural evolution in 316L stainless steel. These methods confirmed that the detected signals are correlated with early microstructural changes, specifically the increase in dislocation density, the formation of dislocation tangles, and the onset of cellular structure formation.UKRI/EPSRC grant EP/V011804/1 and Brunel University Londo
Relationships between surprise, liking, and error perception in musical listening
Get PDFA large part of musical enjoyment stems from the interplay between predictability and surprise that evolves throughout a melody, and yet more extreme violation of musical predictions results in perception of an error. The aim of the present research was to investigate the relationship between liking and predictability in music and establish whether a relationship exists between the degree of unpredictability of a pitch and perception of an error. Moreover, we investigated whether certain individual differences between participants, or the musical style of the stimuli, affect these relationships between predictability and liking, surprise, or error perception. In the series of three experiments, participants were evaluated for musical background, personality traits, and creativity. They were then presented with classical or jazz melodies comprising varying degrees of predictability and reported liking, surprise, and error perception after each melody. We manipulated the predictability of musical notes using a computational model as a way of introducing gradated unpredictability. The results showed that participants had a strong preference for the most predictable melodies. Very unpredictable melodies, as identified by the model, were more often perceived as containing errors, but error perception was more forgiving in jazz compared to classical melodies. There was no evidence that individual differences such as creativity and openness to experience had any association with liking, surprise, or error perception. These results suggest predictability is a strong factor in both liking and error perception in musical listening. (PsycInfo Database Record (c) 2025 APA, all rights reserved
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