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Perceived Market Leadership and Customer Engagement for IT Companies in the Enterprise Software Market:Evaluating the Role of Social Media Marketing
Full text linkPurpose: This study evaluates the effectiveness of social media marketing (SMM) activities for IT companies (ITCs) in the enterprise software market. Specifically, it examines the impact of SMM activities on perceived market leadership and customer engagement while considering the moderating role of product category knowledge. Design/methodology/approach: A quantitative research design was employed, utilizing data collected from 322 users of customer relationship management (CRM) software who follow these companies on social media. Structural equation modeling (SEM) was used to test the proposed hypotheses and evaluate the relationships between SMM activities, perceived market leadership, and customer engagement. Findings: The results indicate that informativeness and customization in SMM activities significantly enhance perceived market leadership and customer engagement. Conversely, interaction and entertainment dimensions have limited impact. Perceived market leadership mediates the relationship between SMM activities and customer engagement. Moreover, product category knowledge strengthens the influence of informativeness on customer engagement. Originality/value: This study addresses a critical gap in the literature by exploring the role of SMM activities in B2B contexts, specifically in the enterprise software market, where research is limited. It provides actionable insights for ITCs, emphasizing the strategic importance of informative and tailored SMM approaches in establishing market leadership and fostering customer engagement.</p
AMCFF-RL:An Adaptive Multi-Modal CAN Bus Fuzzing Framework Leveraging Deep Reinforcement Learning
No full textThe increasing complexity and connectivity of modern vehicles have made automotive networks, particularly the Controller Area Network (CAN) bus, vulnerable to cyberattacks. Fuzzing is a critical technique for proactively finding security weaknesses, but traditional methods are inefficient and struggle to scale with the complexity of modern vehicles. This paper introduces AMCFF-RL, anadaptive framework that uses Deep Reinforcement Learning (DRL) with multi-modal feature extraction to systematically analyse for vulnerabilities. Rather than relying on unguided or purely random fuzzing, AMCFF-RL integrates multi-modal feature extraction with DRL and advanced visualization, allowingit to learn and adapt its strategy based on real-time feedback from the network and thereby improve the efficiency and effectiveness of the fuzzing process. Comprehensive visualization tools serve a dual purpose: they offer human-interpretable insights while also generating rich feature representations that support the anomaly detection pipeline and the DRL agent
Prevalence of exercise-induced bronchoconstriction in elite Chinese summer sport athletes
No full textABSTRACTBackground: Exercise-induced bronchoconstriction (EIB) is a prevalent respiratory condition among summer sport elite athletes, yet epidemiological data from Asian populations remain scarce. The objective of this study was to investigate the prevalence, sport-specific patterns, and physiological characteristics of EIB in Chinese summer sport elite athletes.Methods: A cross-sectional study of 500 summer sport elite athletes across 17 sports was conducted. Participants underwent standardized exercise challenge testing, spirometry, and serum biomarker assessments (eosinophils, interleukin-5 (IL-5), interleukin-8 (IL-8), Clara Cell protein 16 (CC16), immunoglobulin E (IgE), and uric acid (UA)).Results: EIB prevalence was 27.6% (138/500), with significant variation across sports: highest in swimming (51.52%) and lowest in wrestling (6.45%). Female athletes were more prevalent than males (31.1% vs. 23.7%, p = 0.030). Outdoor sports demonstrated higher rates than indoor disciplines (37.4% vs. 19.3%, p = 0.002). EIB-positive athletes showed pronounced post-exercise declines in forced expiratory volume in 1 s (FEV1) at 5 min (p < 0.001) and elevated inflammatory biomarkers: eosinophils (p < 0.001), neutrophils (p = 0.019), IL-5 (p < 0.001), IL-8 (p < 0.001), CC16 (p < 0.001), IgE (p < 0.001), and UA (p < 0.001) vs. EIB-negative counterparts. Conclusion: This is the first large-scale study of Chinese athletes to reveal EIB prevalence exceeding global averages. Distinct risk profiles emerge, associated with gender, athletic level, sport type, and environmental factors. The findings outline the need for targeted screening programs and biomarker-guided management to mitigate respiratory health risks in athletic populations.<br/
Hidden hardship:everyday experiences, coping strategies, and barriers to wellbeing in rural Britain
Full text linkPoverty in the UK is more often associated in public discourse, the media, and in policy with urban than rural areas. With the exception of notable pieces in rural geographies, research across the social sciences has also focussed more on urban than rural poverty. This is mistaken: rural poverty is a significant problem too. This paper focusses on rural hardship in the Cotswolds in the UK which is an area associated with affluence, super-rich celebrities, and royalty. Through participatory research, this paper seeks to understand how people in the North Cotswolds experience hardship, their coping strategies, and the barriers to improved wellbeing. It argues that the North Cotswolds is an area of hidden hardship which means that the rural idyll needs challenging further in public and policy discourse, which research such as this can play a role in. In doing so, this paper’s primary contribution is to have developed the conceptual language of hardship. This is significant for three main reasons. First, the paper argues that the language of hardship is more accessible methodologically, and secondly, that hardship can be a more encapsulating, holistic and multidimensional term than poverty. Thirdly, by using the theoretical lens of the philosopher Spinoza and his concepts of affect, affective capacity and conatus, the paper develops an original way of understanding hardship that results in the paper putting forward a definition of hardship as being about both struggle and resilience on an ongoing daily basis rather than about an emergency one-off situation
SEM images data set development of ML models to predict hydrogen embrittlement in welded 316 L/304 L stainless steels
Full text linkThis study focuses on the machine learning (ML)-based identification of defects caused by hydrogen embrittlement (H2E) in the welded zones of 316 L/304 L stainless steels. It involves developing a robust SEM image dataset to train ML models for accurate defect identification. Initially, Gas Metal Arc Welding (GMAW) samples were manufactured with weld gap variations of 0.8 mm, 1.2 mm, and 1.5 mm. The welding parameters used were: (i) welding speeds of 15 mm/sec and 10 mm/sec, (ii) wire feed rate of 5.5 m/min, and (iii) voltage of 15.5 V. The samples were then exposed to a hydrogen gas environment at a pressure of 80 bar for 150 h. When analyzed using scanning electron microscopy (SEM) & electron backscatter diffraction (EBSD), H2E was observed on the surfaces of the welded zones (WZ) and heat-affected zones (HAZ). These defects, validated through literature, were segregated / sectioned as defect-based feature images and stored as a dataset. A preliminary analysis of the images validated after with 16 DOE's using AlexNet, a convolutional neural network (CNN)-based ML model, showed significant identification of these defects with 90 % accuracy. The trained models helped identify areas and understand previously unidentified defects. Through a focused discussion on defect detection, supported by validation using classification (CNN Accuracy, Precision, Recall, and F1-Score) and regression metrics (R2 and Success Rate), the article demonstrates the potential of ML-based approaches in advancing welding diagnostics.</p
Reconstructing prehistoric land cover and landuse in complex 'blue-green' landscapes
No full textEnvironmental context is vital when analysing archaeological sites and interpreting past human activity. Pollen, being widely dispersed and readily preserved in wetland sediments, is frequently used to investigate past land cover, especially in wetland-rich ‘blue-green’ lowland landscapes (landscapes formed in locations where hydrology is an important determinant of natural vegetation, geomorphology and land use, such as river valleys and estuaries; landscapes which are transitional between aquatic-dominated and terrestrial-dominated). Recent developments in quantitative landcover reconstruction from pollen diagrams, such as the Multiple Scenario Approach (MSA), improve interpretations by taking into account variations in pollen production, dispersal, and sedimentary basin properties. We apply the MSA to derive quantitative, spatially-informed land cover reconstructions for four prehistoric periods in a major UK blue-green lowland landscape, the Humberhead Levels. Reconstructed quantified land cover broadly confirms inferences from previous studies, showing the spread of wet woodland and development of raised mires in the middle Holocene, whilst highlighting the spatial complexity of this dynamic blue-green landscape. The reconstruction process highlights gaps in available data and shows, for example, that the complex interplay of freshwater and marine systems in the later Holocene is only partially understood; thus reconstructions can inform the development of future research agendas in this and other blue-green landscapes. The spatially referenced MSA outputs offer a powerful means of enhancing the integration of pollen analysis with other disciplines, including archaeology, and for developing clear hypotheses for future research
Associations of long-term cumulative C-reactive protein and glycoprotein acetyls concentrations in childhood, adolescence and adulthood with adulthood retinal microvascular structure
Full text linkBACKGROUNG AND AIMS: Inflammation is associated with cardiovascular disease development and microvascular dysfunction. The aim of the present study is to test the hypothesis that long-term exposure to chronic inflammation in childhood and adulthood is associated with adverse retinal microvascular structure in young and mid-adulthood.METHODS: We analyzed data derived from the Special Turku Coronary Risk Factor Intervention Project (STRIP) and longitudinal Cardiovascular Risk in Young Finns Study (YFS). In STRIP, fundus photos were taken in young adulthood (aged 26 years), and in YFS in mid-adulthood (aged 34-49 years). Retinal microvascular measures were derived in both cohorts (arteriolar and venular diameters and tortuosity; additionally, fractal dimensions in STRIP). Cumulative exposure as the area under the curve for high-sensitivity C-reactive protein (hsCRP) and glycoprotein acetyls (GlycA), and other conventional cardiovascular risk factors was determined over a 15- and 17-year period in STRIP, and a 10-year period in YFS. Overall, retinal microvascular and cumulative hsCRP and/or GlycA were available for 344 STRIP and 1211 YFS participants, thus forming the cohort of the present study.RESULTS: In both cohorts, cumulative hsCRP was associated with wider venules when adjusted for sex (and age in YFS), and further for related cardiovascular risk factors. In young adulthood (STRIP), higher exposure to cumulative hsCRP was associated with decreased venular tortuosity, whereas in mid-adulthood (YFS), the association was inverse. Cumulative hsCRP was not associated with arteriolar measures whereas cumulative GlycA showed no significant association with any retinal microvascular measures.CONCLUSIONS: Long-term cumulative hsCRP exposure was associated with wider venules in young and mid-adulthood, whereas the associations with venular tortuosity were inconsistent. Wider retinal venules might act as a marker for cumulative inflammatory burden.</p
Addressing ‘value’ concerns with advocacy research:Dance education in the UK
No full textThis chapter offers a critical examination of the concept of ‘value’ in relation to dance education in the United Kingdom during a period characterised by heightened uncertainty. Against the backdrop of governmental budgetary cuts, the seismic impact of the COVID-19 pandemic, and the complex repercussions of Brexit, this writing explores evolving perceptions of dance education, linked to held values and necessitated advocacy. Drawing upon the personal experiences and reflections of a researcher who transitioned from dance teacher to academic investigator, this chapter engages in an exploration of debates that have developed within this shifting terrain. It draws upon unpublished writing by the author (2010; 2016) and updates it by drawing upon more recent academic discourse and the implications of global and national activity for dance research scholars. By navigating debates concerning the concept of value(s) and of advocacy in dance research, the chapter aims to assess the vulnerabilities of dance education research in the UK but also its capacity for resilience and innovation in the face of uncertainty. Ultimately, this chapter invites readers to contemplate the purpose and perceived value of dance education and research, in a context and time defined by flux and ambiguity