Showing papers by "King's College, Aberdeen published in 2021"

The role of big data analytics in manufacturing agility and performance: moderation- mediation analysis of organizational creativity and of the involvement of customers as data analysts

Abstract: The involvement of customers as data analysts enables firms to gain valuable insights and create value from big data. We provide a theoretical explanation, drawn from the resource-based view, for the influence of the involvement of customers as data analysts and of the development of big data analytics capabilities in business to business contexts as routes to manufacturing agility and performance. Our study empirically tested a framework in which organizational creativity and the involvement of customers as data analysts may differentially influence the relationship between big data analytics capabilities and manufacturing agility. We further tested whether the relative impact of manufacturing agility depends on organizational creativity and the involvement of customers as data analysts. To test our proposed framework, we took a partial least square structural modeling approach using data collected through a survey involving 179 engineering manufacturers operating across different industrial sectors in Pakistan. We provide evidence for organizational creativity and customer involvement presenting a promising opportunity for manufacturers to gain better insights from resources, and for the deployment of big data analytics capabilities leading to better manufacturing agility and performance.

A role for virtual outcrop models in blended learning – improved 3D thinking and positive perceptions of learning

Abstract: . Virtual outcrop models are increasingly used in geoscience education to supplement field-based learning but their efficacy for teaching key 3D spatial thinking skills has been little tested. With the rapid increase in online digital learning resources and blended learning, most recently because of the global COVID-19 pandemic, understanding the role of virtual field environments in supporting and developing skills conventionally taught through field-based teaching has never been more critical. Here we show the efficacy of virtual outcrop models in improving 3D spatial thinking and provide evidence for positive perceptions amongst participants using virtual outcrops in teaching and learning. Our results show that, in a simple, multiple-choice scenario, participants were more likely to choose the 3D block diagram that best represents the structure when using a virtual outcrop (59 %) compared to more traditional representations, such as a geological map (50 %) or field photograph (40 %). We add depth to these results by capturing the perceptions of a cohort of students, within our full participant set, on the use of virtual outcrops for teaching and learning, after accessing a virtual field site and outcrops which they had previously visited during a day's field teaching. We also asked all participants if and how virtual outcrops could be used effectively for teaching and training, recording 87 % of positive responses. However, only 2 % of participants felt that virtual outcrops could potentially replace in-field teaching. We note that these positive findings signal significant potential for the effective use of virtual outcrops in a blended learning environment and for breaking barriers to increase the equality, diversity and inclusivity of geoscience field skills and teaching.

The performance impact of gender diversity in the top management team and board of directors: A multiteam systems approach

Abstract: Given the mixed evidence that having both women and men in the top management team (TMT) or in the board of directors (BOD) has a significant influence on organizational innovation, we resolve this issue by conceptualizing TMT-BOD gender diversity as part of a multiteam system, that has joint effects which impact organizational innovation. Evidence from the study of both Chinese firms and United Kingdom firms confirm our conceptualization by showing an interaction effect between TMT gender diversity and BOD gender diversity such that innovation is greatest when both are high. The positive TMT-BOD gender diversity interaction effect on innovation improves subsequent firm performance, particularly in dynamic environments. The findings refine current thinking by going beyond research that tests intra-team TMT or BOD diversity independently and instead considers inter-team diversity across both leadership teams within the strategic leadership upper echelons. In sum, findings show that high levels of TMT and BOD gender diversity result in more organizational innovation, which ultimately improves firm performance. We offer implications for women’s inclusion in leadership as well as for research on the upper echelons.

Anticipated effects of abiotic environmental change on intraspecific social interactions.

Abstract: Social interactions are ubiquitous across the animal kingdom. A variety of ecological and evolutionary processes are dependent on social interactions, such as movement, disease spread, information transmission, and density-dependent reproduction and survival. Social interactions, like any behaviour, are context dependent, varying with environmental conditions. Currently, environments are changing rapidly across multiple dimensions, becoming warmer and more variable, while habitats are increasingly fragmented and contaminated with pollutants. Social interactions are expected to change in response to these stressors and to continue to change into the future. However, a comprehensive understanding of the form and magnitude of the effects of these environmental changes on social interactions is currently lacking. Focusing on four major forms of rapid environmental change currently occurring, we review how these changing environmental gradients are expected to have immediate effects on social interactions such as communication, agonistic behaviours, and group formation, which will thereby induce changes in social organisation including mating systems, dominance hierarchies, and collective behaviour. Our review covers intraspecific variation in social interactions across environments, including studies in both the wild and in laboratory settings, and across a range of taxa. The expected responses of social behaviour to environmental change are diverse, but we identify several general themes. First, very dry, variable, fragmented, or polluted environments are likely to destabilise existing social systems. This occurs as these conditions limit the energy available for complex social interactions and affect dissimilar phenotypes differently. Second, a given environmental change can lead to opposite responses in social behaviour, and the direction of the response often hinges on the natural history of the organism in question. Third, our review highlights the fact that changes in environmental factors are not occurring in isolation: multiple factors are changing simultaneously, which may have antagonistic or synergistic effects, and more work should be done to understand these combined effects. We close by identifying methodological and analytical techniques that might help to study the response of social interactions to changing environments, highlight consistent patterns among taxa, and predict subsequent evolutionary change. We expect that the changes in social interactions that we document here will have consequences for individuals, groups, and for the ecology and evolution of populations, and therefore warrant a central place in the study of animal populations, particularly in an era of rapid environmental change.

The IDEAL household energy dataset, electricity, gas, contextual sensor data and survey data for 255 UK homes

Abstract: The IDEAL household energy dataset described here comprises electricity, gas and contextual data from 255 UK homes over a 23-month period ending in June 2018, with a mean participation duration of 286 days. Sensors gathered 1-second electricity data, pulse-level gas data, 12-second temperature, humidity and light data for each room, and 12-second temperature data from boiler pipes for central heating and hot water. 39 homes also included plug-level monitoring of selected electrical appliances, real-power measurement of mains electricity and key sub-circuits, and more detailed temperature monitoring of gas- and heat-using equipment, including radiators and taps. Survey data included occupant demographics, values, attitudes and self-reported energy awareness, household income, energy tariffs, and building, room and appliance characteristics. Linked secondary data comprises weather and level of urbanisation. The data is provided in comma-separated format with a custom-built API to facilitate usage, and has been cleaned and documented. The data has a wide range of applications, including investigating energy demand patterns and drivers, modelling building performance, and undertaking Non-Intrusive Load Monitoring research.

The challenges and possibilities of earthquake predictions using non-seismic precursors

Abstract: The catastrophic magnitude of life and monetary losses associated with earthquakes deserve serious attention and mitigation measures. However, in addition to the pre-earthquake and post-earthquake alleviation actions, the scientific community indeed needs to reconsider the possibilities of earthquake predictions using non-seismic precursors. A significant number of studies in the recent decades have reported several possible earthquake precursors such as anomalies in electric field, magnetic field, gas/aerosol emissions, ionospheric signals, ground water level, land surface temperature, surface deformations, animal behaviour, thermal infrared signals, atmospheric gravity waves, and lightning. Such substantial number of scientific articles and reported anomalous signals cannot be overlooked without a thoughtful appraisal. Here, we provide an opinion on the way forward for earthquake prediction in terms of challenges and possibilities while using non-seismic precursors. A general point of concern is the widely varying arrival times and the amplitudes of the anomalies, putting a question mark on their universal applicability as earthquake markers. However, a unifying concept which does not only define the physical basis of either all or most of these anomalies but which also streamlines their characterisation procedure must be the focus of future earthquake precursory research. Advancements in developing the adaptable instrumentation for in-situ observations of the claimed non-seismic precursors must be the next step and the satellite observations should not be taken as a replacement for field-based research. We support the need to standardise the precursor detection techniques and to employ a global-scale monitoring system for making any possible earthquake predictions reliable.

Bringing Onco-Innovation to Europe's Healthcare Systems: The Potential of Biomarker Testing, Real World Evidence, Tumour Agnostic Therapies to Empower Personalised Medicine.

Abstract: Rapid and continuing advances in biomarker testing are not being matched by uptake in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. The potential that genomics has brought to biomarker testing in diagnosis, prediction and research is being realised, pre‐eminently in many cancers, but also in an ever‐wider range of conditions— notably BRCA1/2 testing in ovarian, breast, pancreatic and prostate cancers. Nevertheless, the implementation of genetic testing in clinical routine setting is still challenging. Development is impeded by country‐related heterogeneity, data deficiencies, and lack of policy alignment on standards, approval—and the role of real‐world evidence in the process—and reimbursement. The acute nature of the problem is compellingly illustrated by the particular challenges facing the development and use of tumour agnostic therapies, where the gaps in preparedness for taking advantage of this innovative approach to cancer therapy are sharply exposed. Europe should already have in place a guarantee of universal access to a minimum suite of biomarker tests and should be planning for an optimum testing scenario with a wider range of biomarker tests integrated into a more sophisticated health system articulated around personalised medicine. Improving healthcare and winning advantages for Europe’s industrial competitiveness and innovation require an appropriate policy framework—starting with an update to outdated recommendations. We show herein the main issues and proposals that emerged during the previous advisory boards organised by the European Alliance for Personalized Medicine which mainly focus on possible scenarios of harmonisation of both oncogenetic testing and management of cancer patients.

A comprehensive survey on cultural algorithms

Abstract: Cultural Algorithms (CAs) are evolutionary algorithms (EAs) inspired by the conceptual models of the human cultural evolution process. In contrast to the conventional EAs, which work only based on the population space, CAs employ an additional space, called belief space, to collect the information about the behaviour of individuals in the search space. Since the emergence of CAs, they have been successfully extended to solve a wide variety of problems in different branches of science and technology. In this paper, a comprehensive survey on the recent advances in CAs is presented. Literature survey reveals some interesting challenges and future research directions.

The impact of public acceptance on cost efficiency and environmental sustainability in decentralized energy systems

Abstract: Funding Information: The authors would like to thank H.G. Schwarz-von Raumer as well as the German Federal Agency for Nature Conservation for providing the scenicness data. Large parts of the methodology of this study were developed during the first author's three-and-a-half year PhD study period. The first author would therefore like to thank the three funding bodies during this period: the German Federal Ministry of Education and Research (BMBF) within the Kopernikus Project ENSURE “New ENergy grid StructURes for the German Energiewende” (funding reference: FKZ 03SFK1N0 ), the PhD College “Energy and Resource Efficiency” ( ENRES ) from the Federal State of Baden-Wuerttemberg, as well as the German Federal Ministry for Economic Affairs and Energy (BMWi) within the TrafoKommune project (funding reference: 03EN3008F ).

Surface mass balance analysis at Naradu Glacier, Western Himalaya, India

Abstract: In the present study, we analyze a field-based seven-year data series of surface mass-balance measurements collected during 2011/12 to 2017/18 on Naradu Glacier, western Himalaya, India. The average annual specific mass balance for the said period is - 0.85 m w.e. with the maximum ablation of - 1.15 m w.e. The analysis shows that the topographic features, south and southeast aspects and slopes between 7 to 24 degrees are the reasons behind the maximum ablation from a particular zone. The causes of surface mass balance variability have been analyzed through multiple linear regression analyses (MLRA) by taking temperature and precipitation as predictors. The MLRA demonstrates that 71% of the observed surface mass balance variance can be explained by temperature and precipitation. It clearly illustrates the importance of summer temperature, which alone explains 64% variance of surface mass balance. The seasonal analysis shows that most of the surface mass balance variability is described by summer temperature and winter precipitation as two predictor variables. Among monthly combinations, surface mass balance variance is best characterized by June temperature and September precipitation.

On the Validity of Neural Mass Models.

Abstract: Modeling the dynamics of neural masses is a common approach in the study of neural populations. Various models have been proven useful to describe a plenitude of empirical observations including self-sustained local oscillations and patterns of distant synchronization. We discuss the extent to which mass models really resemble the mean dynamics of a neural population. In particular, we question the validity of neural mass models if the population under study comprises a mixture of excitatory and inhibitory neurons that are densely (inter-)connected. Starting from a network of noisy leaky integrate-and-fire neurons, we formulated two different population dynamics that both fall into the category of seminal Freeman neural mass models. The derivations contained several mean-field assumptions and time scale separation(s) between membrane and synapse dynamics. Our comparison of these neural mass models with the averaged dynamics of the population reveals bounds in the fraction of excitatory/inhibitory neuron as well as overall network degree for a mass model to provide adequate estimates. For substantial parameter ranges, our models fail to mimic the neural network's dynamics proper, be that in de-synchronized or in (high-frequency) synchronized states. Only around the onset of low-frequency synchronization our models provide proper estimates of the mean potential dynamics. While this shows their potential for, e.g., studying resting state dynamics obtained by encephalography with focus on the transition region, we must accept that predicting the more general dynamic outcome of a neural network via its mass dynamics requires great care.

An expert survey to assess the current status and future challenges of energy system analysis

Abstract: Decision support systems like computer-aided energy system analysis (ESA) are considered one of the main pillars for developing sustainable and reliable energy transformation strategies. Although today's diverse tools can already support decision-makers in a variety of research questions, further developments are still necessary. Intending to identify opportunities and challenges in the field, we classify modelling topics into modelling capabilities (32), methodologies (15), implementation issues (15) and management issues (7) from an extensive literature review. Based on a quantitative expert survey of energy system modellers (N = 61) mainly working with simulation and optimisation models, the Status of Development and the Complexity of Realisation of those modelling topics are assessed. While the rated items are considered to be more complex than actually represented, no significant outliers are determinable, showing that there is no consensus about particular aspects of ESA that are lacking development. Nevertheless, a classification of the items in terms of a specially defined modelling strategy matrix identifies capabilities like land-use planning patterns, equity and distributional effects and endogenous technological learning as “low hanging fruits” for enhancement, as well as a large number of complex topics that are already well implemented. The remaining “tough nuts” regarding modelling capabilities include non-energy sector and social behaviour interaction effects. In general, the optimisation and simulation models differ in their respective strengths, justifying the existence of both. While methods were generally rated as quite well developed, combinatorial optimisation approaches, as well as machine learning, are identified as important research methods to be developed further for ESA.

Global and high-level effects in crowding cannot be predicted by either high-dimensional pooling or target cueing.

Abstract: In visual crowding, the perception of a target deteriorates in the presence of nearby flankers. Traditionally, target-flanker interactions have been considered as local, mostly deleterious, low-level, and feature specific, occurring when information is pooled along the visual processing hierarchy. Recently, a vast literature of high-level effects in crowding (grouping effects and face-holistic crowding in particular) led to a different understanding of crowding, as a global, complex, and multilevel phenomenon that cannot be captured or explained by simple pooling models. It was recently argued that these high-level effects may still be captured by more sophisticated pooling models, such as the Texture Tiling model (TTM). Unlike simple pooling models, the high-dimensional pooling stage of the TTM preserves rich information about a crowded stimulus and, in principle, this information may be sufficient to drive high-level and global aspects of crowding. In addition, it was proposed that grouping effects in crowding may be explained by post-perceptual target cueing. Here, we extensively tested the predictions of the TTM on the results of six different studies that highlighted high-level effects in crowding. Our results show that the TTM cannot explain any of these high-level effects, and that the behavior of the model is equivalent to a simple pooling model. In addition, we show that grouping effects in crowding cannot be predicted by post-perceptual factors, such as target cueing. Taken together, these results reinforce once more the idea that complex target-flanker interactions determine crowding and that crowding occurs at multiple levels of the visual hierarchy.

Identification of ROBO2 as a Potential Locus Associated with Inhaled Corticosteroid Response in Childhood Asthma.

Abstract: Inhaled corticosteroids (ICS) are the most common asthma controller medication. An important contribution of genetic factors in ICS response has been evidenced. Here, we aimed to identify novel genetic markers involved in ICS response in asthma. A genome-wide association study (GWAS) of the change in lung function after 6 weeks of ICS treatment was performed in 166 asthma patients from the SLOVENIA study. Patients with an improvement in lung function ≥8% were considered as ICS responders. Suggestively associated variants (p-value ≤ 5 × 10-6) were evaluated in an independent study (n = 175). Validation of the association with asthma exacerbations despite ICS use was attempted in European (n = 2681) and admixed (n = 1347) populations. Variants previously associated with ICS response were also assessed for replication. As a result, the SNP rs1166980 from the ROBO2 gene was suggestively associated with the change in lung function (OR for G allele: 7.01, 95% CI: 3.29-14.93, p = 4.61 × 10-7), although this was not validated in CAMP. ROBO2 showed gene-level evidence of replication with asthma exacerbations despite ICS use in Europeans (minimum p-value = 1.44 × 10-5), but not in admixed individuals. The association of PDE10A-T with ICS response described by a previous study was validated. This study suggests that ROBO2 could be a potential novel locus for ICS response in Europeans.