13,574 research outputs found

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice

    Pollution-induced community tolerance in freshwater biofilms – from molecular mechanisms to loss of community functions

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    Exposure to herbicides poses a threat to aquatic biofilms by affecting their community structure, physiology and function. These changes render biofilms to become more tolerant, but on the downside community tolerance has ecologic costs. A concept that addresses induced community tolerance to a pollutant (PICT) was introduced by Blanck and Wängberg (1988). The basic principle of the concept is that microbial communities undergo pollution-induced succession when exposed to a pollutant over a long period of time, which changes communities structurally and functionally and enhancing tolerance to the pollutant exposure. However, the mechanisms of tolerance and the ecologic consequences were hardly studied up to date. This thesis addresses the structural and functional changes in biofilm communities and applies modern molecular methods to unravel molecular tolerance mechanisms. Two different freshwater biofilm communities were cultivated for a period of five weeks, with one of the communities being contaminated with 4 μg L-1 diuron. Subsequently, the communities were characterized for structural and functional differences, especially focusing on their crucial role of photosynthesis. The community structure of the autotrophs was assessed using HPLC-based pigment analysis and their functional alterations were investigated using Imaging-PAM fluorometry to study photosynthesis and community oxygen profiling to determine net primary production. Then, the molecular fingerprints of the communities were measured with meta-transcriptomics (RNA-Seq) and GC-based community metabolomics approaches and analyzed with respect to changes in their molecular functions. The communities were acute exposed to diuron for one hour in a dose-response design, to reveal a potential PICT and uncover related adaptation to diuron exposure. The combination of apical and molecular methods in a dose-response design enabled the linkage of functional effects of diuron exposure and underlying molecular mechanisms based on a sensitivity analysis. Chronic exposure to diuron impaired freshwater biofilms in their biomass accrual. The contaminated communities particularly lost autotrophic biomass, reflected by the decrease in specific chlorophyll a content. This loss was associated with a change in the molecular fingerprint of the communities, which substantiates structural and physiological changes. The decline in autotrophic biomass could be due to a primary loss of sensitive autotrophic organisms caused by the selection of better adapted species in the course of chronic exposure. Related to this hypothesis, an increase in diuron tolerance has been detected in the contaminated communities and molecular mechanisms facilitating tolerance have been found. It was shown that genes of the photosystem, reductive-pentose phosphate cycle and arginine metabolism were differentially expressed among the communities and that an increased amount of potential antioxidant degradation products was found in the contaminated communities. This led to the hypothesis that contaminated communities may have adapted to oxidative stress, making them less sensitive to diuron exposure. Moreover, the photosynthetic light harvesting complex was altered and the photoprotective xanthophyll cycle was increased in the contaminated communities. Despite these adaptation strategies, the loss of autotrophic biomass has been shown to impair primary production. This impairment persisted even under repeated short-term exposure, so that the tolerance mechanisms cannot safeguard primary production as a key function in aquatic systems.:1. The effect of chemicals on organisms and their functions .............................. 1 1.1 Welcome to the anthropocene .......................................................................... 1 1.2 From cellular stress responses to ecosystem resilience ................................... 3 1.2.1 The individual pursuit for homeostasis ....................................................... 3 1.2.2 Stability from diversity ................................................................................. 5 1.3 Community ecotoxicology - a step forward in monitoring the effects of chemical pollution? ................................................................................................................. 6 1.4 Functional ecotoxicological assessment of microbial communities ................... 9 1.5 Molecular tools – the key to a mechanistic understanding of stressor effects from a functional perspective in microbial communities? ...................................... 12 2. Aims and Hypothesis ......................................................................................... 14 2.1 Research question .......................................................................................... 14 2.2 Hypothesis and outline .................................................................................... 15 2.3 Experimental approach & concept .................................................................. 16 2.3.1 Aquatic freshwater biofilms as model community ..................................... 16 2.3.2 Diuron as model herbicide ........................................................................ 17 2.3.3 Experimental design ................................................................................. 18 3. Structural and physiological changes in microbial communities after chronic exposure - PICT and altered functional capacity ................................................. 21 3.1 Introduction ..................................................................................................... 21 3.2 Methods .......................................................................................................... 23 3.2.1 Biofilm cultivation ...................................................................................... 23 3.2.2 Dry weight and autotrophic index ............................................................. 23 3.2.4 Pigment analysis of periphyton ................................................................. 23 3.2.4.1 In-vivo pigment analysis for community characterization ....................... 24 3.2.4.2 In-vivo pigment analysis based on Imaging-PAM fluorometry ............... 24 3.2.4.3 In-vivo pigment fluorescence for tolerance detection ............................. 26 3.2.4.4 Ex-vivo pigment analysis by high-pressure liquid-chromatography ....... 27 3.2.5 Community oxygen metabolism measurements ....................................... 28 3.3 Results and discussion ................................................................................... 29 3.3.1 Comparison of the structural community parameters ............................... 29 3.3.2 Photosynthetic activity and primary production of the communities after selection phase ................................................................................................. 33 3.3.3 Acquisition of photosynthetic tolerance .................................................... 34 3.3.4 Primary production at exposure conditions ............................................... 36 3.3.5 Tolerance detection in primary production ................................................ 37 3.4 Summary and Conclusion ........................................................................... 40 4. Community gene expression analysis by meta-transcriptomics ................... 41 4.1 Introduction to meta-transcriptomics ............................................................... 41 4.2. Methods ......................................................................................................... 43 4.2.1 Sampling and RNA extraction................................................................... 43 4.2.2 RNA sequencing analysis ......................................................................... 44 4.2.3 Data assembly and processing................................................................. 45 4.2.4 Prioritization of contigs and annotation ..................................................... 47 4.2.5 Sensitivity analysis of biological processes .............................................. 48 4.3 Results and discussion ................................................................................... 48 4.3.1 Characterization of the meta-transcriptomic fingerprints .......................... 49 4.3.2 Insights into community stress response mechanisms using trend analysis (DRomic’s) ......................................................................................................... 51 4.3.3 Response pattern in the isoform PS genes .............................................. 63 4.5 Summary and conclusion ................................................................................ 65 5. Community metabolome analysis ..................................................................... 66 5.1 Introduction to community metabolomics ........................................................ 66 5.2 Methods .......................................................................................................... 68 5.2.1 Sampling, metabolite extraction and derivatisation................................... 68 5.2.2 GC-TOF-MS analysis ............................................................................... 69 5.2.3 Data processing and statistical analysis ................................................... 69 5.3 Results and discussion ................................................................................... 70 5.3.1 Characterization of the metabolic fingerprints .......................................... 70 5.3.2 Difference in the metabolic fingerprints .................................................... 71 5.3.3 Differential metabolic responses of the communities to short-term exposure of diuron ............................................................................................................ 73 5.4 Summary and conclusion ................................................................................ 78 6. Synthesis ............................................................................................................. 79 6.1 Approaches and challenges for linking molecular data to functional measurements ...................................................................................................... 79 6.2 Methods .......................................................................................................... 83 6.2.1 Summary on the data ............................................................................... 83 6.2.2 Aggregation of molecular data to index values (TELI and MELI) .............. 83 6.2.3 Functional annotation of contigs and metabolites using KEGG ................ 83 6.3 Results and discussion ................................................................................... 85 6.3.1 Results of aggregation techniques ........................................................... 85 6.3.2 Sensitivity analysis of the different molecular approaches and endpoints 86 6.3.3 Mechanistic view of the molecular stress responses based on KEGG functions ............................................................................................................ 89 6.4 Consolidation of the results – holistic interpretation and discussion ............... 93 6.4.1 Adaptation to chronic diuron exposure - from molecular changes to community effects.............................................................................................. 93 6.4.2 Assessment of the ecological costs of Pollution-induced community tolerance based on primary production ............................................................. 94 6.5 Outlook ............................................................................................................ 9

    Model Diagnostics meets Forecast Evaluation: Goodness-of-Fit, Calibration, and Related Topics

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    Principled forecast evaluation and model diagnostics are vital in fitting probabilistic models and forecasting outcomes of interest. A common principle is that fitted or predicted distributions ought to be calibrated, ideally in the sense that the outcome is indistinguishable from a random draw from the posited distribution. Much of this thesis is centered on calibration properties of various types of forecasts. In the first part of the thesis, a simple algorithm for exact multinomial goodness-of-fit tests is proposed. The algorithm computes exact pp-values based on various test statistics, such as the log-likelihood ratio and Pearson\u27s chi-square. A thorough analysis shows improvement on extant methods. However, the runtime of the algorithm grows exponentially in the number of categories and hence its use is limited. In the second part, a framework rooted in probability theory is developed, which gives rise to hierarchies of calibration, and applies to both predictive distributions and stand-alone point forecasts. Based on a general notion of conditional T-calibration, the thesis introduces population versions of T-reliability diagrams and revisits a score decomposition into measures of miscalibration, discrimination, and uncertainty. Stable and efficient estimators of T-reliability diagrams and score components arise via nonparametric isotonic regression and the pool-adjacent-violators algorithm. For in-sample model diagnostics, a universal coefficient of determination is introduced that nests and reinterprets the classical R2R^2 in least squares regression. In the third part, probabilistic top lists are proposed as a novel type of prediction in classification, which bridges the gap between single-class predictions and predictive distributions. The probabilistic top list functional is elicited by strictly consistent evaluation metrics, based on symmetric proper scoring rules, which admit comparison of various types of predictions

    A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms

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    Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data. A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability. To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity. A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case. The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change. The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence

    Strategies for Early Learners

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    Welcome to learning about how to effectively plan curriculum for young children. This textbook will address: • Developing curriculum through the planning cycle • Theories that inform what we know about how children learn and the best ways for teachers to support learning • The three components of developmentally appropriate practice • Importance and value of play and intentional teaching • Different models of curriculum • Process of lesson planning (documenting planned experiences for children) • Physical, temporal, and social environments that set the stage for children’s learning • Appropriate guidance techniques to support children’s behaviors as the self-regulation abilities mature. • Planning for preschool-aged children in specific domains including o Physical development o Language and literacy o Math o Science o Creative (the visual and performing arts) o Diversity (social science and history) o Health and safety • Making children’s learning visible through documentation and assessmenthttps://scholar.utc.edu/open-textbooks/1001/thumbnail.jp

    Omics measures of ageing and disease susceptibility

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    While genomics has been a major field of study for decades due to relatively inexpensive genotyping arrays, the recent advancement of technology has also allowed the measure and study of various “omics”. There are now numerous methods and platforms available that allow high throughput and high dimensional quantification of many types of biological molecules. Traditional genomics and transcriptomics are now joined by proteomics, metabolomics, glycomics, lipidomics and epigenomics. I was lucky to have access to a unique resource in the Orkney Complex Disease Study (ORCADES), a cohort of individuals from the Orkney Islands that are extremely deeply annotated. Approximately 1000 individuals in ORCADES have genomics, proteomics, lipidomics, glycomics, metabolomics, epigenomics, clinical risk factors and disease phenotypes, as well as body composition measurements from whole body scans. In addition to these cross-sectional omics and health related measures, these individuals also have linked electronic health records (EHR) available, allowing the assessment of the effect of these omics measures on incident disease over a ~10-year follow up period. In this thesis I use this phenotype rich resource to investigate the relationship between multiple types of omics measures and both ageing and health outcomes. First, I used the ORCADES data to construct measures of biological age (BA). The idea that there is an underlying rate at which the body deteriorates with age that varies between individuals of the same chronological age, this biological age, would be more indicative of health status, functional capacity and risk of age-related diseases than chronological age. Previous models estimating BA (ageing clocks) have predominantly been built using a single type of omics assay and comparison between different omics ageing clocks has been limited. I performed the most exhaustive comparison of different omics ageing clocks yet, with eleven clocks spanning nine different omics assays. I show that different omics clocks overlap in the information they provide about age, that some omics clocks track more generalised ageing while others track specific disease risk factors and that omics ageing clocks are prognostic of incident disease over and above chronological age. Second, I assessed whether individually or in multivariable models, omics measures are associated with health-related risk factors or prognostic of incident disease over 10 years post-assessment. I show that 2,686 single omics biomarkers are associated with 10 risk factors and 44 subsequent incident diseases. I also show that models built using multiple biomarkers from whole body scans, metabolomics, proteomics and clinical risk factors are prognostic of subsequent diabetes mellitus and that clinical risk factors are prognostic of incident hypertensive disorders, obesity, ischaemic heart disease and Framingham risk score. Third, I investigated the genetic architecture of a subset of the proteomics measures available in ORCADES, specifically 184 cardiovascular-related proteins. Combining genome-wide association (GWAS) summary statistics from ORCADES and 17 other cohorts from the SCALLOP Consortium, giving a maximum sample size of 26,494 individuals, I performed 184 genome-wide association meta-analyses (GWAMAs) on the levels of these proteins circulating in plasma. I discovered 592 independent significant loci associated with the levels of at least one protein. I found that between 8-37% of these significant loci colocalise with known expression quantitative trait loci (eQTL). I also find evidence of causal associations between 11 plasma protein levels and disease susceptibility using Mendelian randomisation, highlighting potential candidate drug targets

    Examining the Impact of Personal Social Media Use at Work on Workplace Outcomes

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    A noticable shift is underway in today’s multi-generational workforce. As younger employees propel digital workforce transformation and embrace technology adoption in the workplace, organisations need to show they are forward-thinking in their digital transformation strategies, and the emergent integration of social media in organisations is reshaping internal communication strategies, in a bid to improve corporate reputations and foster employee engagement. However, the impact of personal social media use on psychological and behavioural workplace outcomes is still debatebale with contrasting results in the literature identifying both positive and negative effects on workplace outcomes among organisational employees. This study seeks to examine this debate through the lens of social capital theory and study personal social media use at work using distinct variables of social use, cognitive use, and hedonic use. A quantitative analysis of data from 419 organisational employees in Jordan using SEM-PLS reveals that personal social media use at work is a double-edged sword as its impact differs by usage types. First, the social use of personal social media at work reduces job burnout, turnover intention, presenteeism, and absenteeism; it also increases job involvement and organisational citizen behaviour. Second, the cognitive use of personal social media at work increases job involvement, organisational citizen behaviour, employee adaptability, and decreases presenteeism and absenteeism; it also increases job burnout and turnover intention. Finally, the hedonic use of personal social media at work carries only negative effects by increasing job burnout and turnover intention. This study contributes to managerial understanding by showing the impact of different types of personal social media usage and recommends that organisations not limit employee access to personal social media within work time, but rather focus on raising awareness of the negative effects of excessive usage on employee well-being and encourage low to moderate use of personal social media at work and other personal and work-related online interaction associated with positive workplace outcomes. It also clarifies the need for further research in regions such as the Middle East with distinct cultural and socio-economic contexts

    Unraveling the effect of sex on human genetic architecture

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    Sex is arguably the most important differentiating characteristic in most mammalian species, separating populations into different groups, with varying behaviors, morphologies, and physiologies based on their complement of sex chromosomes, amongst other factors. In humans, despite males and females sharing nearly identical genomes, there are differences between the sexes in complex traits and in the risk of a wide array of diseases. Sex provides the genome with a distinct hormonal milieu, differential gene expression, and environmental pressures arising from gender societal roles. This thus poses the possibility of observing gene by sex (GxS) interactions between the sexes that may contribute to some of the phenotypic differences observed. In recent years, there has been growing evidence of GxS, with common genetic variation presenting different effects on males and females. These studies have however been limited in regards to the number of traits studied and/or statistical power. Understanding sex differences in genetic architecture is of great importance as this could lead to improved understanding of potential differences in underlying biological pathways and disease etiology between the sexes and in turn help inform personalised treatments and precision medicine. In this thesis we provide insights into both the scope and mechanism of GxS across the genome of circa 450,000 individuals of European ancestry and 530 complex traits in the UK Biobank. We found small yet widespread differences in genetic architecture across traits through the calculation of sex-specific heritability, genetic correlations, and sex-stratified genome-wide association studies (GWAS). We further investigated whether sex-agnostic (non-stratified) efforts could potentially be missing information of interest, including sex-specific trait-relevant loci and increased phenotype prediction accuracies. Finally, we studied the potential functional role of sex differences in genetic architecture through sex biased expression quantitative trait loci (eQTL) and gene-level analyses. Overall, this study marks a broad examination of the genetics of sex differences. Our findings parallel previous reports, suggesting the presence of sexual genetic heterogeneity across complex traits of generally modest magnitude. Furthermore, our results suggest the need to consider sex-stratified analyses in future studies in order to shed light into possible sex-specific molecular mechanisms
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