London South Bank University
  • London, Greater London, United Kingdom
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Objective A systematic review of animal and human studies was conducted on genetically modified (GM) food consumption to assess its safety in terms of adverse effects/events to inform public concerns and future research. Methods Seven electronic databases were searched from January 1st 1983 till July 11th 2020 for in vivo, animal and human studies on the incidence of adverse effects/events of GM products consumption. Two authors independently identified eligible studies, assessed the study quality, and extracted data on the name of the periodical, author and affiliation, literature type, the theme of the study, publication year, funding, sample size, target population characteristics, type of the intervention/exposure, outcomes and outcome measures, and details of adverse effects/events. We used the Chi-square test to compare the adverse event reporting rates in articles funded by industry funding, government funding or unfunded articles. Results One crossover trial in humans and 203 animal studies from 179 articles met the inclusion criteria. The study quality was all assessed as being unclear or having a high risk of bias. Minor illnesses were reported in the human trial. Among the 204 studies, 59.46% of adverse events (22 of 37) were serious adverse events from 16 animal studies (7.84%). No significant differences were found in the adverse event reporting rates either between industry and government funding ( χ ² = 2.286, P = 0.131), industry and non-industry funding ( χ ² = 1.761, P = 0.185) or funded and non-funded articles ( χ ² = 0.491, P = 0.483). We finally identified 21 GM food-related adverse events involving 7 GM events (NK603 × MON810 maize, GTS 40-3-2 soybean, NK603 maize, MON863 maize, MON810 maize, MON863 × MON810 × NK603 maize and GM Shanyou 63 rice), which had all been on regulatory approval in some countries/regions. Conclusion Serious adverse events of GM consumption include mortality, tumour or cancer, significant low fertility, decreased learning and reaction abilities, and some organ abnormalities. Further clinical trials and long-term cohort studies in human populations, especially on GM food-related adverse events and the corresponding GM events, are still warranted. It suggests the necessity of labelling GM food so that consumers can make their own choice.
Keywords: Biosurfactant Microbial enhanced oil recovery Bacillus licheniformis Bacillus subtilis Core flooding micromodel Environmental risk assessment A B S T R A C T Biosurfactants have recently gained popularity because they have numerous benefits over chemical synthetic surfactants, including higher biodegradability, lower toxicity, higher foaming, environmental compatibility, and effective properties under harsh conditions. This study aimed to produce effective biosurfactants by selected bacterial strains isolated from Egyptian oil fields to improve oil recovery and investigate their environmental aspects for microbial enhanced oil recovery. The selected strains were incubated in a new proposed nutrient medium H to produce biosurfactants with optimum surface and emulsification activities. Stability studies were conducted to examine the tolerance of produced biosurfactants in harsh reservoir conditions. Core flooding tests were performed to investigate the potential of produced biosurfactants in enhancing oil recovery. The environmental risk assessment was conducted to investigate if there are any possible threats of the selected bacterial strains. Results showed that selected bacterial strains Bacillus licheniformis and Bacillus subtilis could produce effective biosurfactants that reached their maximum surface activity after 24 h of incubation by reducing the surface tension from 71.8 mN/m to 27.13 mN/m and 25.74 mN/m, and the interfacial tension against kerosene from 48.4 mN/m to 1.27 mN/m and 0.38 mN/m at critical micelle concentration of 0.06 g/l and 0.04 g/l, respectively. The produced biosurfactants by Bacillus licheniformis and Bacillus subtilis showed significant emul-sification activity against crude oil with emulsification indices of 50.2% and 63.7%, respectively. High stability was observed at high temperatures for a long-time period and more than 60% of their surface and emulsification activities were maintained over a wide range of pH and salinity. It was also found that 31.41-39.35% of additional oil could be recovered by the produced biosurfactants. Finally, Bacillus licheniformis and Bacillus subtilis are environmentally safe, have no potential for toxicity, and no risk could occur for MEOR.
This study investigates the surface modification of waste polyvinyl chloride (PVC) particles with encapsulated silane coupling agents (SCA) to improve the performance of PVC concrete and mortar. Concrete and mortar were prepared by replacing fine aggregates with equal volumes of PVC particles before and after modification, with volume replacement ratios of 5%, 10%, 15%, 20% and 25%. Experiments were performed to investigate the density, compressive strength and flexural strength of different contents of PVC concrete and mortar. Scanning Electron Microscope (SEM) was used to examine the surface morphology of PVC particles and the interface between the PVC particles and the cementitious material in the mortar. The results showed that the density of concrete and mortar gradually decreased with increasing PVC content; the 28d compressive strength of concrete and mortar increased by 10%-20% after modification with SCA; the 28d flexural strength of concrete and mortar increased by 5%-9%. The SEM results revealed that SCA on the surface of PVC particles improved the mechanical properties of the mortar by better combining the particles with the cementitious material.
Boiling is an essential process for many industrial applications, such as refrigeration, distillation, and chemical processes. The effectiveness of the heat transfer processes determines the efficiencies of these applications. This study presents the experimental data analysis for pool boiling performance of 0.10, 0.15, and 0.20 wt.% of multiwall carbon nanotubes/water nanofluid on smooth and straight, square, and circular grooved surfaces. According to the experimental results, the configuration S4 with a 30 mm deep circular groove inclined at a 45° angle and 33% higher than the base fluid on the smooth surface had the greatest enhancement in boiling heat transfer coefficient. The result indicated that the inclination of the circular groove had the potential to enhance significantly the pool boiling heat transfer process. Furthermore, this study demonstrated that analyzing the effectiveness of nanofluids in a variety of concentrations and geometrical configurations of heat transfer surfaces is still essential and desirable. MWCNT/water nanofluid pool boiling on smooth and new type of grooved surfaces experimentally studied. Based on experimental results highest boiling performance belong to 3mm deep circular groove inclined 45°angle. Boiling heat transfer coefficient is 33% higher for 0.2wt% of MWCNT/water nanofluid.
Previous work identified the operation of an attentional bias (AB) towards healthy food related stimuli among those with increasing tendencies towards orthorexia nervosa (ON) using a modified Stroop task. The current work aimed to replicate and extend our understanding of this effect by incorporating alternative measures of AB (i.e., the dot probe task) and ON (i.e., the Teruel Orthorexia Scale [ToS]) in a sample of self-defined vegans/vegetarians. The theoretical assertion of the ToS is the conceptual broadening of orthorexia with differentiable dimensions - one characterised as a “healthy” preoccupation with healthy food/eating patterns (HeOr) and the other by a more underlying pathology (OrNe). This study also aimed to examine the pattern of responding across these two dimensions according to factors known to predict ON. Eighty-six participants (mean age = 33.0 years; 20 males, 66 females) completed measures of obsessive compulsivity, perfectionism, state/trait anxiety and ToS as well as a dot probe designed to measure AB for healthy and unhealthy-related food stimuli, threat ratings of each of words utilised and perceived identity centrality as a vegan/vegetarianism. Results showed a dissociation of predicted determinants for “healthy” ON (HeOr) and pathological ON (OrNe). HeOr was predicted by increasing identity centrality whereas OrNe was predicted by increased OCD and perfectionism, and increased interference for healthy-related food words (in particular slowed disengagement) and not unhealthy related food words. Threat-related ratings of unhealthy food words was shown to be common across both dimensions. This pattern highlights cognitive and individual differences-based correlates of pathological and non-pathological ON.
An increasing number of studies have reported producing composite structures by combining thermoelectric and functional materials. However, combining energy filtering and ferroelectric polarization to enhance the dimensionless figure of merit thermoelectric ZT remains elusive. Here we report a composite that contains nanostructured BaTiO3 embedded in a Bi0.5Sb1.5Te3 matrix. We show that ferroelectric BaTiO3 particles are evenly composited with Bi0.5Sb1.5Te3 grains reducing the concentration of free charge carriers with increasing BaTiO3 content. Additionally, as a result of the energy-filtering effect and ferroelectric polarization, the Seebeck coefficient was improved by ∼10% with a ∼10% improvement in power factors. The BaTiO3 phase can effectively scatters phonons reducing lattice thermal conductivity κl (0.5 W m-1 K-1) and increasing ZT to 1.31 at 363 K in Bi0.5Sb1.5Te3 composites with 2 vol % BaTiO3 content giving an improvement of ∼25% over pure Bi0.5Sb1.5Te3. Our work indicates that the introduction of ferroelectric nanoparticles is an effective method for optimizing the ZT of Bi0.5Sb1.5Te3-based thermoelectric materials.
Accurate and real-time product demand forecasting is the need of the hour in the world of supply chain management. Predicting future product demand from historical sales data is a highly non-linear problem, subject to various external and environmental factors. In this work, we propose an optimised forecasting model-an extreme learning machine (ELM) model coupled with the Harris Hawks optimisation (HHO) algorithm to forecast product demand in an e-commerce company. ELM is preferred over traditional neural networks mainly due to its fast computational speed, which allows efficient demand forecasting in real-time. Our ELM-HHO model performed significantly better than ARIMA models that are commonly used in industries to forecast product demand. The performance of the proposed ELM-HHO model was also compared with traditional ELM, ELM auto-tuned using Bayesian Optimisation (ELM-BO), Gated Recurrent Unit (GRU) based recurrent neural network and Long Short Term Memory (LSTM) recurrent neural network models. Different performance metrics, i.e., Root Mean Squared Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Percentage Error (MPE) were used for the comparison of the selected models. Horizon forecasting at 3 days and 7 days ahead was also performed using the proposed approach. The results revealed that the proposed approach is superior to traditional product demand forecasting models in terms of prediction accuracy and it can be applied in real-time to predict future product demand based on the previous week's sales data. In particular, considering RMSE of forecasting, the proposed ELM-HHO model performed 62.73% better than the statistical ARIMA(7,1,0) model, 40.73% better than the neural network based GRU model, 34.05% better than the neural network based LSTM model, 27.16% better than the traditional non-optimised ELM model with 100 hidden nodes and 11.63% better than the ELM-BO model in forecasting product demand for future 3 months. The novelty of the proposed approach lies in the way the fast computational speed of ELMs has been combined with the accuracy gained by tuning hyperparameters using HHO. An increased number of hyperparameters has been optimised in our methodology compared to available models. The majority of approaches to improve the accuracy of ELM so far have only focused on tuning the weights and the biases of the hidden layer. In our hybrid model, we tune the number of hidden nodes, the number of input time lags and even the type of activation function used in the hidden layer in addition to tuning the weights and the biases. This has resulted in a significant increase in accuracy over previous methods. Our work presents an original way of performing product demand forecasting in real-time in industry with highly accurate results which are much better than pre-existing demand forecasting models.
The statistical design of experiments methodology (DoE) has been a valuable tool since its conception for the understanding of the relationship between factors and responses. Although it has been employed successfully in different research fields and industries for years, its application to the evaluation of lithium-ion batteries (LIBs) is just getting recognition. LIBs are one of the most promising technologies for a complete transition to sustainable energies, are the main technology behind electric vehicles and are fundamental for the continual development of portable electronic devices. This paper presents a critical literature review of the available DoE works applied to the manufacturing and characterisation of LIBs. An overview of DoE and the most important available designs are first presented, followed by a general introduction of the statistical analysis required for the interpretation of the results including regression models. Several aspects of the LIBs such as ageing, capacity, electrode formulation, active material synthesis, thermal design, charging and parameterisation are discussed based on the main objective of the respective DoE studies found in the literature. A case study is presented to visualise the practical application of DoE to the LIBs field. Perspectives and future outlook are given to highlight opportunities and potential areas of research in the application of traditional and modern designs to the LIB’s field. This critical review contributes to a better understanding of the DoE methodology with a focus on LIBs or LIBs related aspects which will lead to faster developments in the field.
Nursing student attrition is a significant concern in many countries, including the UK. Higher education institutions (HEIs) are seeking creative ways of improving retention and it is crucial to understand which support strategies encourage students to persist with their studies. This article describes a systematic review of the literature exploring nursing students' experiences and perceptions of support strategies used by HEIs to reduce attrition and improve retention. Having a sense of belonging, a connection with the university, self-confidence, self-efficacy and motivation appeared to make students more likely to stay on their course. Several support strategies appeared to enhance retention, including an automated text messaging system, an Academic, Personal and Professional Learning (APPL) support mechanism, a pastoral care support adviser service and an extracurricular student support group. Developing a holistic and multifaceted approach to retention involves working collaboratively with students to enhance the understanding of their needs.
We introduce a dynamical system to model the complex interaction between COVID-19 and economic activity. The model introduces some novelties not accounted by SIR-like models. The equilibrium of the system is an unstable focus, with fluctuations having increasing size and periodicity. Numerical simulations of the model produce waves which reproduce the pandemic dynamics. In observing the stylized facts linking economics and pandemic and stating related reasonable assumptions, we obtain a Lotka–Volterra co-dynamics. This outcome is confirmed by extensive simulations. The outcomes obtained qualitatively replicate some important stylized facts deepening the knowledge about the role of some parameters in their origin and eventually in their shaping.
This paper faces a central theme in applied statistics and information science, which is the assessment of the stochastic structure of rank-size laws in text analysis. We consider the words in a corpus by ranking them on the basis of their frequencies in descending order. The starting point is that the ranked data generated in linguistic contexts can be viewed as the realisations of a discrete states Markov chain, whose stationary distribution behaves according to a discretisation of the best fitted rank-size law. The employed methodological toolkit is Markov Chain Monte Carlo, specifically referring to the Metropolis-Hastings algorithm. The theoretical framework is applied to the rank-size analysis of the hapax legomena occurring in the speeches of the US Presidents. We offer a large number of statistical tests leading to the consistency of our methodological proposal. To pursue our scopes, we also offer arguments supporting that hapaxes are rare (“extreme”) events resulting from memory-less-like processes. Moreover, we show that the considered sample has the stochastic structure of a Markov chain of order one. Importantly, we discuss the versatility of the method, which is considered suitable for deducing similar outcomes for other applied science contexts.
Background Hospital remains the most common place of death in the UK, but there are ongoing concerns about the quality of end-of-life care provision in this setting. Evaluation of interventions in the last days of life or after a bereavement is methodologically and ethically challenging. Aim The aim was to describe interventions at the very end of life and in the immediate bereavement period in acute hospitals, with a particular focus on how these are evaluated. Method A scoping review was conducted. Studies were restricted to peer-reviewed original research or literature reviews, published between 2011 and 2021, and written in the English language. Databases searched were CINAHL, Medline and Psychinfo. Results From the search findings, 42 studies were reviewed, including quantitative (n=7), qualitative (n=14), mixed method (n=4) and literature reviews (n=17). Much of the current research about hospital-based bereavement care is derived from the intensive and critical care settings. Three themes were identified: (1) person-centred/family-centred care (memorialisation), (2) institutional approaches (quality of the environment, leadership, system-wide approaches and culture), (3) infrastructure and support systems (transdisciplinary working and staff support). There were limited studies on interventions to support staff. Conclusion Currently, there are few comprehensive tools for evaluating complex service interventions in a way that provides meaningful transferable data. Quantitative studies do not capture the complexity inherent in this form of care. Further qualitative studies would offer important insights into the interventions.
Chronic heart failure is a progressive and life-limiting syndrome that is caused by a failure of the heart to pump blood around the body effectively. It frequently leads to a range of distressing symptoms, such as breathlessness, fatigue and fluid retention. Chronic heart failure can be caused by a variety of cardiac diseases, but is commonly linked to coronary heart disease and hypertension. In response to these, the body initiates a series of compensatory mechanisms, which ultimately become maladaptive, and the manipulation of these mechanisms is the cornerstone of pharmacological management of the condition. This article explains the compensatory mechanisms that occur in chronic heart failure and outlines the medicines commonly used in its management.
MammoWave is a microwave imaging device for breast lesion detection, employing two antennas which rotate azimuthally (horizontally) around the breast. The antennas operate in the 1-9 GHz band and are set in free space, i.e., pivotally, no matching liquid is required. Microwave images, subsequently obtained through the application of Huygens Principle, are intensity maps, representing the homogeneity of the dielectric properties of the breast tissues under test. In this paper, MammoWave is used to realise tissues dielectric differences and localise lesions by segmenting microwave images adaptively employing pulse coupled neural network (PCNN). Subsequently, a non-parametric thresholding technique is modelled to differentiate between breasts having no radiological finding (NF) or benign (BF) and breasts with malignant finding (MF). Resultant findings verify that automated breast lesion localization with microwave imaging matches the gold standard achieving 81.82% sensitivity in MF detection. The proposed method is tested on microwave images acquired from a feasibility study performed in Foligno Hospital, Italy. This study is based on 61 breasts from 35 patients; performance may vary with larger number of datasets and will be subsequently investigated.
The various rhetorics of ‘agile’, ‘agility’, and ‘agile working’ (AW) set an agenda for new ways of working and have recently gained traction in popular management discourse, particularly in the wake of the COVID-19 pandemic. Yet conceptually, these rhetorical varieties of ‘agile’ are underdeveloped in the academic literature. In this article we examine the stream of AW as being a particularly influential rhetoric. AW is critically evaluated by first identifying separate streams and rhetorics of ‘agile’ in the literature, and AW is then situated within this typology. To understand the particular version of reality being mainstreamed by the AW rhetoric, we then examine AWs conceptualisation as ‘a new way of working’, as promoted by dominant actors within the UK work context. We then consider existing studies of worker experiences under different employment arrangements that can be subsumed under the heading of ‘AW practices’. Our analysis highlights voids between what may be considered as mainstream HR practice when applied to standard employees compared to a spectrum of ‘non-standard’ workers. The implications for the role of HR in the implementation of AW and in managing the worker experience are discussed and future avenues for this under-researched area are offered.
Lumbar support exoskeletons with active and passive actuators are currently the cutting-edge technology for preventing back injuries in workers while lifting heavy objects. However, many challenges still exist in both types of exoskeletons, including rigid actuators, risks of human–robot interaction, high battery consumption, bulky design, and limited assistance. In this paper, the design of a compact, lightweight energy storage device combined with a rotary series elastic actuator (ES-RSEA) is proposed for use in a lumbar support exoskeleton to increase the level of assistance and exploit the human bioenergy during the two stages of the lifting task. The energy storage device takes the responsibility to store and release passive mechanical energy while RSEA provides excellent compliance and prevents injury from the human body’s undesired movement. The experimental tests on the spiral spring show excellent linear characteristics (above 99%) with an actual spring stiffness of 9.96 Nm/rad. The results demonstrate that ES-RSEA can provide maximum torque assistance in the ascent phase with 66.6 Nm while generating nearly 21 Nm of spring torque during descent without turning on the DC motor. Ultimately, the proposed design can maximize the energy storage of human energy, exploit the biomechanics of lifting tasks, and reduce the burden on human effort to perform lifting tasks.
Narratives around alcohol are important in determining how people decide who or what qualifies as problematic alcohol use. Narratives draw on common representations that are subject to influences including historical and normative influences. We argue that there are two dominant narratives that relate to how alcohol use disorder (AUD) is identified and addressed. The first is the historically embedded narrative of alcoholism as disease, and the second is the more recent narrative of positive or new sobriety. We present an argument that these two dominant narratives alone do not capture the wide and heterogeneous experience of alcohol harms, and as such a more diverse range of relatable narratives are required to reach and resonate with the broader community of people with AUDs. In particular , we reflect on the fact that these dominant narratives are both abstinence focused and therefore exclude many drinkers who are not willing and may not need, to consider lifelong sobriety to reduce their risk or experience of harms. We ask that alcohol policy professionals, researchers and lived experience advocates consider these issues and support diversifying the range of lived experiences, to support goals including public health outcomes, stigma reduction and alternative routes to recovery. ARTICLE HISTORY
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Nikolaos Amanatidis
  • Department of Education
Michael Berthaume
  • Division of Mechanical Engineering and Design
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