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Adoption of artificial intelligence and cutting-edge technologies for production system sustainability: A moderator-mediation analysis
Get PDFYesCutting-edge technologies like big data analytics (BDA), artificial intelligence (AI), quantum computing, blockchain, and digital twins have a profound impact on the sustainability of the production system. In addition, it is argued that turbulence in technology could negatively impact the adoption of these technologies and adversely impact the sustainability of the production system of the firm. The present study has demonstrated that the role of technological turbulence as a moderator could impact the relationships between the sustainability the of production system with its predictors. The study further analyses the mediating role of operational sustainability which could impact the firm performance. A theoretical model has been developed that is underpinned by dynamic capability view (DCV) theory and firm absorptive capacity theory. This model was verified by PLS-SEM with 412 responses from various manufacturing firms in India. There exists a positive and significant influence of AI and other cutting-edge technologies for keeping the production system sustainable
Microwave sensor for liquid mixture identification based on composite right left hand-zero-order resonator for sensitivity improvement
Get PDFYesThis work aims to present an improved version of the liquid mixture identification sensor, the proposed sensor is tested experimentaly on mixture of water ethanol, the identification of liquid is based on the measurement of frequency displacement, and comparison with reference values of water ethanol. This device is based on metamaterial structure which is a CRLH (composite right left hand) resonator with ZOR (Zero Order Resonator). The CRLH in addition to its property of miniaturization effect, when combined with ZOR, the resonant frequency of various volume fraction are extended, which make the sensitivity higher. The high sensitivity of the sensor is obtained by an optimum choice of the CRLH components. The geometrical size of the sensor is 20 mm by 11 mm. It was printed on a RT/Duroid 5880 substrate with a very short testing surface area of 4 mm by 8 mm, the liquid is placed on the top side of the sensor, exactly on the CRLH structure. Three prototypes of sensors operating from 1 GHz to 3 GHz are proposed, designed and simulated using the commercial software HFSS (high-frequency structural simulator). The main advantages of this work is first miaturization effect, second high sensitivity and finaly a wide range of liquid can be tested with this sensor. To prove the working principle, ethanol with different volume fractions was adopted as a liquid under test, the obtained results present very good agreement with the literature and suggested that it is a miniaturised and high sensitive candidate (better than 1.38%) for liquid mixture identification
Environmental conditions and bodily decomposition: Implications for long term management of war fatalities and the identification of the dead during the ongoing Ukrainian conflict
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The Impact of the Pandemic on Mental Health in Ethnically Diverse Mothers: Findings from the Born in Bradford, Tower Hamlets and Newham COVID-19 Research Programmes
Get PDFYesRestrictions implemented by the UK Government during the COVID-19 pandemic have served to worsen mental health outcomes, particularly amongst younger adults, women, those living with chronic health conditions, and parents of young children. Studies looking at the impact for ethnic minorities have reported inconsistent findings. This paper describes the mental health experiences of mothers from a large and highly ethnically diverse population during the pandemic, using secondary analysis of existing data from three COVID-19 research studies completed in Bradford and London (Tower Hamlets and Newham). A total of 2807 mothers participated in this study with 44% White British, 23% Asian/Asian British Pakistani, 8% Other White and 7% Asian/Asian British Bangladeshi s. We found that 28% of mothers experienced clinically important depressive symptoms and 21% anxiety symptoms during the pandemic. In unadjusted analyses, mothers from White Other, and Asian/Asian British Bangladeshi s had higher odds of experiencing symptoms, whilst mothers from Asian/Asian British Indian s were the least likely to experience symptoms. Once loneliness, social support and financial insecurity were controlled for, there were no statistically significant differences in depression and anxiety by ethnicity. Mental health problems experienced during the pandemic may have longer term consequences for public health. Policy and decision makers must have an understanding of the high risk of financial insecurity, loneliness and a lack of social support on mother’s mental health, and also recognise that some ethnic groups are far more likely to experience these issues and are, therefore, more vulnerable to poor mental health as a consequence.This study was funded by The Health Foundation COVID-19 Award (2301201), with further contributions from a Wellcome Trust infrastructure grant (WT101597MA); a joint grant from the UK Medical Research Council (MRC) and UK Economic and Social Science Research Council (ESRC) (MR/N024391/1); the National Institute for Health Research under its Applied Research Collaboration Yorkshire and Humber (NIHR200166); ActEarly UK Prevention Research Partnership Consortium (MR/S037527/1); Better Start Bradford through The National Lottery Community Fund; and the British Heart Foundation (CS/16/4/32482). The research conducted in London was funded by UKRI-ESRC ES/V004891/1 (Tower Hamlets), and by London Borough of Newham Public Health. Heys was supported by the NIHR Great Ormond Street Hospital Biomedical Research Centre
Cyberbullying detection in Urdu language using machine learning
Get PDFYesCyberbullying has become a significant problem with the surge in the use of social media. The most basic way to prevent cyberbullying on these social media platforms is to identify and remove offensive comments. However, it is hard for humans to read and remove all the comments manually. Current research work focuses on using machine learning to detect and eliminate cyberbullying. Although most of the work has been conducted on English texts to detect cyberbullying, limited to no work can be found in Urdu. This paper aims to detect cyberbullying from the users' comments posted in Urdu on Twitter using machine learning and Natural Language Processing (NLP) techniques. To the best of our knowledge, cyberbullying detection on Urdu text comments has not been performed due to the lack of a publicly available standard Urdu dataset. In this paper, we created a dataset of offensive user-generated Urdu comments from Twitter. The comments in the dataset are classified into five categories. n-gram techniques are used to extract features at character and word levels. Various supervised machine-learning techniques are applied to the dataset to detect cyberbullying. Evaluation metrics such as precision, recall, accuracy and F1 scores are used to analyse the performance of machine learning techniques.Cyberbullying has become a significant problem with the surge in the use of social media. The most basic way to prevent cyberbullying on these social media platforms is to identify and remove offensive comments. However, it is hard for humans to read and remove all the comments manually. Current research work focuses on using machine learning to detect and eliminate cyberbullying. Although most of the work has been conducted on English texts to detect cyberbullying, limited to no work can be found in Urdu. This paper aims to detect cyberbullying from the users' comments posted in Urdu on Twitter using machine learning and Natural Language Processing (NLP) techniques. To the best of our knowledge, cyberbullying detection on Urdu text comments has not been performed due to the lack of a publicly available standard Urdu dataset. In this paper, we created a dataset of offensive user-generated Urdu comments from Twitter. The comments in the dataset are classified into five categories. n-gram techniques are used to extract features at character and word levels. Various supervised machine-learning techniques are applied to the dataset to detect cyberbullying. Evaluation metrics such as precision, recall, accuracy and F1 scores are used to analyse the performance of machine learning techniques
RNA-sequencing muscle plasticity to resistance exercise training and disuse in youth and older age
Get PDFYesMaintenance of skeletal muscle mass and function is critical to health and wellbeing throughout the lifespan. However, disuse through reduced physical activity (e.g., sedentarism), immobilisation, bed rest or microgravity has significant adverse effects on skeletal muscle health. Conversely, resistance exercise training (RET) induces positive muscle mass and strength adaptations. Several studies have employed microarray technology to understand the transcriptional basis of muscle atrophy and hypertrophy after disuse and RET, respectively, to devise fully effective therapeutic interventions. More recently, rapidly falling costs have seen RNA-sequencing (RNA-seq) increasingly applied in exploring muscle adaptations to RET and disuse. The aim of this review is to summarise the transcriptional responses to RET or disuse measured via RNA-seq in young and older adults. We also highlight analytical considerations to maximise the utility of RNA-seq in the context of skeletal muscle research. The limited number of muscle transcriptional signatures obtained thus far with RNA-seq are generally consistent with those obtained with microarrays. However, RNA-seq may provide additional molecular insight, particularly when combined with data-driven approaches such as correlation network analyses. In this context, it is essential to consider the most appropriate study design parameters as well as bioinformatic and statistical approaches. This will facilitate the use of RNA-seq to better understand the transcriptional regulators of skeletal muscle plasticity in response to increased or decreased use
The flow of lubricant as a mist in the piston assembly and crankcase of a fired gasoline engine
Get PDFYesThe tribological performance of the piston assembly of an automotive engine is highly influenced by the complex flow mechanisms that supply lubricant to the upper piston rings. As well as affecting friction and wear, the oil consumption and emissions of the engine are strongly influenced by these mechanisms. There is a significant body of work that seeks to model these flows effectively. However, these models are not able to fully describe the flow of lubricant through the piston assembly. Some experimental studies indicate that droplets of lubricant carried in the gas flows through the piston assembly may account for some of this. This work describes an investigation into the nature of lubricant misting in a fired gasoline engine. Previous work in a laboratory simulator showed that the tendency of a lubricant to form mist is dependent on the viscosity of the lubricant and the type and concentration of viscosity modifier. The higher surface area-to-volume ratio of the lubricant if more droplets are formed or if the droplets are smaller is hypothesised to increase the degradation rate of the lubricant. The key work in the investigation was to measure the size distribution of the droplets in the crankcase of a fired gasoline engine. Droplets were extracted from the crankcase and passed through a laser diffraction particle sizer. Three characteristic droplet size ranges were observed: Spray sized (250–1000 μm); Major mist (30–250 μm); and Minor mist (0.1–30 μm). Higher base oil viscosity tended to reduce the proportion of mist-sized droplets. The viscoelasticity contributed by a polymeric viscosity modifier reduced the proportion of mist droplets, especially at high load
Building social capital in cruise travel via social network sites
Get PDFYesThe purpose of this study is to investigate what type of Facebook posts
help cruise lines build bridging and bonding social capital. The study
applies the Chi-Square Automatic Interaction Detection (CHAID) method
to identify which types of posts establish bridging and bonding social
capital. The analysis is conducted on an international cruise line’s official
Facebook posts posted between 1 January 2018 and 1 January 2020
before the Covid-19 pandemic. The results highlight that media type,
embedding passenger motivation, and a ship image help establish both
bridging and bonding social capital, while content type helps establish
bridging social capital. The paper is original because it helps
understand how cruise lines can improve bonding and bridging social
capital via social media. The paper also enhances understanding of
social capital theory in the travel industry by investigating the
relationship between Facebook post types and social capital in cruise
shipping
An isotope signature for diffuse idiopathic skeletal hyperostosis?
Get PDFYesObjectives: Diffuse idiopathic skeletal hyperostosis (DISH) has recurrently been associated with a rich diet (high in protein and higher trophic level foods); however, very few studies have investigated this link using carbon and nitrogen (δ13C and δ15N) stable isotope analysis. This paper explores the relationship between DISH and diet in two Roman urban communities by analyzing individuals with and without DISH.
Materials and methods: δ13C and δ15N analysis carried out on collagen from 33 rib samples (No DISH: 27; early DISH: 4; DISH: 2) selected from individuals buried at the Romano-British site of Baldock (UK), 41 rib samples (No DISH: 38; early DISH: 3) from individuals from the Catalan Roman site of Santa Caterina (Barcelona, Spain). Additionally, six faunal samples from Baldock and seven from Santa Caterina were analyzed.
Results: Standardized human isotope data from Santa Caterina show high δ15N probably associated to a diet combining terrestrial resources and freshwater fish. In contrast, isotope results from Baldock suggest a terrestrial-based diet. Individuals with DISH do not show isotopic ratios indicative of rich diet and there is no correlation between stage of DISH development and δ13C and δ15N.
Conclusion: The results of this study suggest that individuals with DISH followed a similar or isotopically similar diet as those individuals without DISH in Baldock and in Santa Caterina and therefore, while DISH may have been influenced by individual's dietary habits, this is not reflected in their isotopic signature.Institute of Life Sciences Research Studentship, University of Bradford, Bradford, U
A computational framework for measuring the facial emotional expressions
No full textNoThe purpose of this chapter is to discuss and present a computational framework for detecting and analysing facial expressions efficiently. The approach here is to identify the face and estimate regions of facial features of interest using the optical flow algorithm. Once the regions and their dynamics are computed a rule based system can be utilised for classification. Using this framework, we show how it is possible to accurately identify and classify facial expressions to match with FACS coding and to infer the underlying basic emotions in real time