The visibility of the world and the invisibility of the soul. Phenomenological structure of the human perception

The essay intends to demonstrate the need to postulate an (invisible) spiritual reality in the human being as a condition of possibility of the world’s visibility. For that purpose, it employs the phenomenological method. It describes the structure of human sensitive perception. This description firstly presents the world’s structure (first distance). Secondly, it manifests the importance of the body as a border element between the soul and the world and as an organ by means of which the soul structures the world. It is the second distance the distance between the body and the world. But, thirdly, the description states that, no matter how intimately the soul interpenetrates the body and requires it to know the world, the soul is not the body. It is the third distance or the primordial distance between the soul and everything else (including the body itself).

Ecohumanists. Protection of physical ecology demands respect human ecology

What is the human being? Which is its origin and its end? What is the influence of the nature in the man and what is his impact on nature? Forthe animalists, men are like other animals; freedom and rationality are not signs of superiority, nor having rights over the animals. For the ecohumanists, human beings are part of nature, but is qualitatively different and superior to animals; and is the creator of the civilization. We analyze these two ecological looks. A special point is the contribution ofecohumanists -from the first half of the Renaissance, who dealt in extenso the dignity and freedom of the human being-, of Michelangelo and finally, of Mozart, through his four insurmountable operas, which display the difficulty of physical ecology to engender so much beauty, so much wealth, so much love for the creatures and so much variety.

Transcallosal connectivity of the human cortical motor network

The organizational and architectural configuration of white matter pathways connecting brain regions has ramifications for all facets of the human condition, including manifestations of incipient neurodegeneration. Although diffusion tensor imaging (DTI) has been used extensively to visualize white matter connectivity, due to the widespread presence of crossing fibres, the lateral projections of the corpus callosum are not normally detected using this methodology. Detailed knowledge of the transcallosal connectivity of the human cortical motor network has therefore remained elusive. We employed constrained spherical deconvolution (CSD) tractography - an approach that is much less susceptible to the influence of crossing fibres, in order to derive complete in-vivo characterizations of white matter pathways connecting specific motor cortical regions to their counterparts and other loci in the opposite hemisphere. The revealed patterns of connectivity closely resemble those derived from anatomical tracing in primates. It was established that dorsal premotor cortex (PMd) and supplementary motor area (SMA) have extensive interhemispheric connectivity - exhibiting both dense homologous projections, and widespread structural relations with every other region in the contralateral motor network. Through this in-vivo portrayal, the importance of non-primary motor regions for interhemispheric communication is emphasized. Additionally, distinct connectivity profiles were detected for the anterior and posterior subdivisions of primary motor cortex. The present findings provide a comprehensive representation of transcallosal white matter projections in humans, and have the potential to inform the development of models and hypotheses relating structural and functional brain connectivity.

Tyrosine kinase inhibitor insensitivity of non-cycling CD34+ human acute myeloid leukaemia cells with FMS-like tyrosine kinase 3 mutations.

The efficacy of tyrosine kinase (TK) inhibitors on non-cycling acute myeloid leukaemia (AML) cells, previously shown to have potent tumourigenic potential, is unknown. This pilot study describes the first attempt to characterize non-cycling cells from a small series of human FMS-like tyrosine kinase 3 (FLT3) mutation positive samples. CD34+ AML cells from patients with FLT3 mutation positive AML were cultured on murine stroma. In expansion cultures, non-cycling cells were found to retain CD34+ expression in contrast to dividing cells. Leukaemic gene rearrangements could be detected in non-cycling cells, indicating their leukaemic origin. Significantly, the FLT3-internal tandem duplication (ITD) mutation was found in the non-cycling fraction of four out of five cases. Exposure to the FLT3-directed inhibitor TKI258 clearly inhibited the growth of AML CD34+ cells in short-term cultures and colony-forming unit assays. Crucially, non-cycling cells were not eradicated, with the exception of one case, which exhibited exquisite sensitivity to the compound. Moreover, in longer-term cultures, TKI258-treated non-cycling cells showed no growth impairment compared to treatment-naive non-cycling cells. These findings suggest that non-cycling cells in AML may constitute a disease reservoir that is resistant to TK inhibition. Further studies with a larger sample size and other inhibitors are warranted.

Digital Figurations : The Human Figure as Cinematic Concept

Mainstream cinema is to an ever-increasing degree deploying digital imaging technologies to work with the human form; expanding on it, morphing its features, or providing new ways of presenting it. This has prompted theories of simulation and virtualisation to explore the cultural and aesthetic implications, anxieties, and possibilities of a loss of the ‘real’ – in turn often defined in terms of the photographic trace. This thesis wants to provide another perspective. Following instead some recent imperatives in art-theory, this study looks to introduce and expand on the notion of the human figure, as pertaining to processes of figuration rather than (only) representation. The notion of the figure and figuration have an extended history in the fields of hermeneutics, aesthetics, and philosophy, through which they have come to stand for particular theories and methodologies with regards to images and their communication of meaning. This objective of this study is to appropriate these for film-theory, culminating in two case-studies to demonstrate how formal parameters present and organise ideas of the body and the human. The aim is to develop a material approach to contemporary digital practices, where bodies have not ceased to matter but are framed in new ways by new technologies.

Communication and behavior in high reliability organizations: An Analysis of Communication in Civil Aviation

Communication can be seen as one of the most important features to manage conflicts and the stress of the work teams that operate in environments with strong pressure, complex operations and continuous risk, which are aspects that characterize a high reliability organization. This article aims to highlight the importance of communication in high-reliability organizations, having as object of study the accidents and incidents in civil aviation area. It refers to a qualitative research, outlined by documental analysis based on investigations conducted by the Federal Aviation Administration and the Center of Investigation and Prevention of Aeronautical Accidents. The results point out that human errors account for 60 to 80 percent of accidents and incidents. Most of these occurrences are attributed to miscommunication between the professionals involved with the air and ground operation, such as pilots, crewmembers and maintenance staff, and flight controllers. Inappropriate tone of voice usage, difficulties to understand different accents between the issuer and the receiver or even difficulty to perceive red flags between the lines of verbal and non-verbal communication, are elements that contribute to the fata of understanding between people involved in the operation. As a research limitation this present research pointed out a lack of a special category of "interpersonal communications failures" in the official agency reports. So, the researchers must take the conceptual definition of "social ability", communication implied, to classify behaviors and communication matters accordingly. Other research finding indicates that communication is superficially approached in the contents of air operations courses what could mitigate the lack of communications skills as a social ability. Part of the research findings refers to the contents of communication skills development into the program to train professional involved in air flight and ground operations. So, it is expected that this present article gives an appropriate highlight towards the improvement of flight operations training programs. Developing communication skills among work teams in high reliability organizations can contribute to mitigate stress, accidents and incidents in Civil Aviation Field. The original contribution of this article is the proposal of the main contents that should be developed in a Communication Skills Training Program, specially addressed to Civil Aviation operations.

Disentangling trade-offs and synergies around ecosystem services with the influence network framework: illustration from a consultative process over the French Alps

An important aspect of sustainability is to maintain biodiversity and ecosystem functioning while improving human well-being. For this, the ecosystem service (ES) approach has the potential to bridge the still existing gap between ecological management and social development, especially by focusing on trade-offs and synergies between ES and between their beneficiaries. Several frameworks have been proposed to account for trade-offs and synergies between ES, and between ES and other components of social-ecological systems. However, to date, insufficient explicit attention has been paid to the three facets encompassed in the ES concept, namely potential supply, demand, and use, leading to incomplete descriptions of ES interactions. We expand on previous frameworks by proposing a new influence network framework (INF) based on an explicit consideration of influence relationships between these three ES facets, biodiversity, and external driving variables. We tested its ability to provide a comprehensive view of complex social-ecological interactions around ES through a consultative process focused on environmental management in the French Alps. We synthetized the interactions mentioned during this consultative process and grouped variables according to their overall propensity to influence or be influenced by the system. The resulting directed sequence of influences distinguished between: (1) mostly influential variables (dynamic social variables and ecological state variables), (2) target variables (provisioning and cultural services), and (3) mostly impacted variables (regulating services and biodiversity parameters). We discussed possible reasons for the discrepancies between actual and perceived influences and proposed options to overcome them. We demonstrated that the INF holds the potential to deliver collective assessments of ES relations by: (1) including ecological as well as social aspects, (2) providing opportunities for colearning processes between stakeholder groups, and (3) supporting communication about complex social-ecological systems and consequences for environmental management.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.

Cell-cell communication in three dimensional microenvironments

Cellular behavior is dependent on a variety of extracellular cues required for normal tissue function, wound healing, and activation of the immune system. Removed from their in vivo microenvironment and cultured in vitro, cells lose many environmental cues and that may result in abberant behavior, making it difficult to study cellular processes. In order to mimic native tissue environments, optical tweezer and microfluidic technologies were used to place cells within defined areas of the culture environment. To provide three dimensional supports found in natural tissues, hydrogel scaffolds of poly (ethylene glycol) diacrylate and the basement membrane matrix Matrigel were used. Optical tweezer technology allowed precision placement and formation of homotypic and heterotypic arrays of human U937, HEK 293, and porcine mesenchymal stem cells. Alternatively, two microfluidic devices were designed to pattern Matrigel scaffolds. The first microfluidic device utilized laminar flow to spatially pattern multiple cell types within the device. Gradients of soluble molecules were then be formed and manipulated across the Matrigel scaffolds. Patterning Matrigel using laminar flow techniques require microfluidic expertise and do not produce consistent patterning conditions, limiting their use difficult in most cell culture laboratories. Thus, a buried Matrigel polydimethylsiloxane (PDMS) device was developed for spatial patterning of biological scaffolds. Matrigel is injected into micron sized channels of PDMS fabricated by soft lithography and allowed to thermally cure. Following curing, a second PDMS device was placed on top of the buried Matrigel channels to support media flow. In order to validate these systems, a cell-cell communication model system was developed utilizing LPS and TNFα signaling with fluorescent reporter systems to monitor communication in real time. We demonstrated the utility of microfluidic devices to support the cell-cell communication model system by co culturing three cell types within Matrigel scaffolds and monitoring signaling activity via fluorescent reporters.

Gestural communication of music structure during solo classical piano performance

The production and perception of music is a multimodal activity involving auditory, visual and conceptual processing, integrating these with prior knowledge and environmental experience. Musicians utilise expressive physical nuances to highlight salient features of the score. The question arises within the literature as to whether performers’ non-technical, non-sound-producing movements may be communicatively meaningful and convey important structural information to audience members and co-performers. In the light of previous performance research (Vines et al., 2006, Wanderley, 2002, Davidson, 1993), and considering findings within co-speech gestural research and auditory and audio-visual neuroscience, this thesis examines the nature of those movements not directly necessary for the production of sound, and their particular influence on audience perception. Within the current research 3D performance analysis is conducted using the Vicon 12- camera system and Nexus data-processing software. Performance gestures are identified as repeated patterns of motion relating to music structure, which not only express phrasing and structural hierarchy but are consistently and accurately interpreted as such by a perceiving audience. Gestural characteristics are analysed across performers and performance style using two Chopin preludes selected for their diverse yet comparable structures (Opus 28:7 and 6). Effects on perceptual judgements of presentation modes (visual-only, auditory-only, audiovisual, full- and point-light) and viewing conditions are explored. This thesis argues that while performance style is highly idiosyncratic, piano performers reliably generate structural gestures through repeated patterns of upper-body movement. The shapes and locations of phrasing motions are identified particular to the sample of performers investigated. Findings demonstrate that despite the personalised nature of the gestures, performers use increased velocity of movements to emphasise musical structure and that observers accurately and consistently locate phrasing junctures where these patterns and variation in motion magnitude, shape and velocity occur. By viewing performance motions in polar (spherical) rather than cartesian coordinate space it is possible to get mathematically closer to the movement generated by each of the nine performers, revealing distinct patterns of motion relating to phrasing structures, regardless of intended performance style. These patterns are highly individualised both to each performer and performed piece. Instantaneous velocity analysis indicates a right-directed bias of performance motion variation at salient structural features within individual performances. Perceptual analyses demonstrate that audience members are able to accurately and effectively detect phrasing structure from performance motion alone. This ability persists even for degraded point-light performances, where all extraneous environmental information has been removed. The relative contributions of audio, visual and audiovisual judgements demonstrate that the visual component of a performance does positively impact on the over- all accuracy of phrasing judgements, indicating that receivers are most effective in their recognition of structural segmentations when they can both see and hear a performance. Observers appear to make use of a rapid online judgement heuristics, adjusting response processes quickly to adapt and perform accurately across multiple modes of presentation and performance style. In line with existent theories within the literature, it is proposed that this processing ability may be related to cognitive and perceptual interpretation of syntax within gestural communication during social interaction and speech. Findings of this research may have future impact on performance pedagogy, computational analysis and performance research, as well as potentially influencing future investigations of the cognitive aspects of musical and gestural understanding.

Effects of hypoxic culture conditions on umbilical cord-derived human mesenchymal stem cells

Following cultivation of distinct mesenchymal stem cell (MSC) populations derived from human umbilical cord under hypoxic conditions (between 1.5% to 5% oxygen (O-2)) revealed a 2- to 3-fold reduced oxygen consumption rate as compared to the same cultures at normoxic oxygen levels (21% O-2). A simultaneous measurement of dissolved oxygen within the culture media from 4 different MSC donors ranged from 15 mu mol/L at 1.5% O-2 to 196 mu mol/L at normoxic 21% O-2. The proliferative capacity of the different hypoxic MSC populations was elevated as compared to the normoxic culture. This effect was paralleled by a significantly reduced cell damage or cell death under hypoxic conditions as evaluated by the cellular release of LDH whereby the measurement of caspase 3/7 activity revealed little if any differences in apoptotic cell death between the various cultures. The MSC culture under hypoxic conditions was associated with the induction of hypoxia-inducing factor-alpha (HIF-1 alpha) and an elevated expression of energy metabolism-associated genes including GLUT-1, LDH and PDK1. Concomitantly, a significantly enhanced glucose consumption and a corresponding lactate production could be observed in the hypoxic MSC cultures suggesting an altered metabolism of these human stem cells within the hypoxic environment.

A biochemical analysis into the co-translational folding of a G protein-coupled receptor; GPR35

The folding and targeting of membrane proteins poses a major challenge to the cell, as they must remain insertion competent while their highly hydrophobic transmembrane (TM) domains are transferred from the ribosome, through the aqueous cytosol and into the lipid bilayer. The biogenesis of a mature membrane protein takes place through the insertion and integration into the lipid bilayer. A number of TM proteins have been shown to gain some degree of secondary structure within the ribosome tunnel and to retain this conformation throughout maturation. Although studies into the folding and targeting of a number of membrane proteins have been carried out to date, there is little information on one of the largest class of eukaryotic membrane proteins; the G-protein-coupled receptors (GPCRs). This project studies the early folding events of the human ortholog of GPR35. To analyse the structure of the 1st TM domain, intermediates were generated and assessed by the biochemical method of pegylation (PEG-MAL). A structurally-similar microbial opsin (Bacterioopsin) was also used to investigate the differences in the early protein folding within eukaryotic and prokaryotic translation systems. Results showed that neither the 1st TM domain of GPR35 nor Bacterioopsin were capable of compacting in the ribosome tunnel before their N-terminus reached the ribosome exit point. The results for this assay remained consistent whether the proteins were translated in a eukaryotic or prokaryotic translation system. To examine the communication mechanism between the ribosome, the nascent chain and the protein targeting pathway, crosslinking experiments were carried out using the homobifunctional lysine cross-linker BS3. Specifically, the data generated here show that the nascent chain of GPR35 reaches the ribosomal protein uL23 in an extended conformation and interacts with the SRP protein as it exits the ribosome tunnel. This confirms the role of SRP in the co-translational targeting of GPR35. Using these methods insights into the early folding of GPCRs has been obtained. Further experiments using site-directed mutagenesis to reduce hydrophobicity in the 1st TM domain of GPR35, highlighted the mechanisms by which GPCRs are targeted to the endoplasmic reticulum. Confirming that hydrophobicity within the signal anchor sequence is essential of SRP-dependent targeting. Following the successful interaction of the nascent GPR35 and SRP, GPR35 is successfully targeted to ER membranes, shown here as dog pancreas microsomes (DPMs). Glycosylation of the GPR35 N-terminus was used to determine nascent chain structure as it is inserted into the ER membrane. These glycosylation experiments confirm that TM1 has obtained its compacted state whilst residing in the translocon. Finally, a site-specific cross-linking approach using the homobifunctional cysteine cross-linker, BMH, was used to study the lateral integration of GPR35 into the ER. Cross-linking of GPR35 TM1 and TM2 could be detected adjacent to a protein of ~45kDa, believed to be Sec61α. The loss of this adduct, as the nascent chain extends, showed the lateral movement of GPR35 TM1 from the translocon was dependent on the subsequent synthesis of TM2.

'Explicit Learning: an Effort towards Human Scheduling Algorithms'

Abstract Scheduling problems are generally NP-hard combinatorial problems, and a lot of research has been done to solve these problems heuristically. However, most of the previous approaches are problem-specific and research into the development of a general scheduling algorithm is still in its infancy. Mimicking the natural evolutionary process of the survival of the fittest, Genetic Algorithms (GAs) have attracted much attention in solving difficult scheduling problems in recent years. Some obstacles exist when using GAs: there is no canonical mechanism to deal with constraints, which are commonly met in most real-world scheduling problems, and small changes to a solution are difficult. To overcome both difficulties, indirect approaches have been presented (in [1] and [2]) for nurse scheduling and driver scheduling, where GAs are used by mapping the solution space, and separate decoding routines then build solutions to the original problem. In our previous indirect GAs, learning is implicit and is restricted to the efficient adjustment of weights for a set of rules that are used to construct schedules. The major limitation of those approaches is that they learn in a non-human way: like most existing construction algorithms, once the best weight combination is found, the rules used in the construction process are fixed at each iteration. However, normally a long sequence of moves is needed to construct a schedule and using fixed rules at each move is thus unreasonable and not coherent with human learning processes. When a human scheduler is working, he normally builds a schedule step by step following a set of rules. After much practice, the scheduler gradually masters the knowledge of which solution parts go well with others. He can identify good parts and is aware of the solution quality even if the scheduling process is not completed yet, thus having the ability to finish a schedule by using flexible, rather than fixed, rules. In this research we intend to design more human-like scheduling algorithms, by using ideas derived from Bayesian Optimization Algorithms (BOA) and Learning Classifier Systems (LCS) to implement explicit learning from past solutions. BOA can be applied to learn to identify good partial solutions and to complete them by building a Bayesian network of the joint distribution of solutions [3]. A Bayesian network is a directed acyclic graph with each node corresponding to one variable, and each variable corresponding to individual rule by which a schedule will be constructed step by step. The conditional probabilities are computed according to an initial set of promising solutions. Subsequently, each new instance for each node is generated by using the corresponding conditional probabilities, until values for all nodes have been generated. Another set of rule strings will be generated in this way, some of which will replace previous strings based on fitness selection. If stopping conditions are not met, the Bayesian network is updated again using the current set of good rule strings. The algorithm thereby tries to explicitly identify and mix promising building blocks. It should be noted that for most scheduling problems the structure of the network model is known and all the variables are fully observed. In this case, the goal of learning is to find the rule values that maximize the likelihood of the training data. Thus learning can amount to 'counting' in the case of multinomial distributions. In the LCS approach, each rule has its strength showing its current usefulness in the system, and this strength is constantly assessed [4]. To implement sophisticated learning based on previous solutions, an improved LCS-based algorithm is designed, which consists of the following three steps. The initialization step is to assign each rule at each stage a constant initial strength. Then rules are selected by using the Roulette Wheel strategy. The next step is to reinforce the strengths of the rules used in the previous solution, keeping the strength of unused rules unchanged. The selection step is to select fitter rules for the next generation. It is envisaged that the LCS part of the algorithm will be used as a hill climber to the BOA algorithm. This is exciting and ambitious research, which might provide the stepping-stone for a new class of scheduling algorithms. Data sets from nurse scheduling and mall problems will be used as test-beds. It is envisaged that once the concept has been proven successful, it will be implemented into general scheduling algorithms. It is also hoped that this research will give some preliminary answers about how to include human-like learning into scheduling algorithms and may therefore be of interest to researchers and practitioners in areas of scheduling and evolutionary computation. References 1. Aickelin, U. and Dowsland, K. (2003) 'Indirect Genetic Algorithm for a Nurse Scheduling Problem', Computer & Operational Research (in print). 2. Li, J. and Kwan, R.S.K. (2003), 'Fuzzy Genetic Algorithm for Driver Scheduling', European Journal of Operational Research 147(2): 334-344. 3. Pelikan, M., Goldberg, D. and Cantu-Paz, E. (1999) 'BOA: The Bayesian Optimization Algorithm', IlliGAL Report No 99003, University of Illinois. 4. Wilson, S. (1994) 'ZCS: A Zeroth-level Classifier System', Evolutionary Computation 2(1), pp 1-18.

Compounds, creativity and complexity in climate change communication: the case of ‘carbon indulgences’

This article deals with climate change from a linguistic perspective. Climate change is an extremely complex issue that has exercised the minds of experts and policy makers with renewed urgency in recent years. It has prompted an explosion of writing in the media, on the internet and in the domain of popular science and literature, as well as a proliferation of new compounds around the word ‘carbon’ as a hub, such as ‘carbon indulgence’, a new compound that will be studied in this article. Through a linguistic analysis of lexical and discourse formations around such ‘carbon compounds’ we aim to contribute to a broader understanding of the meaning of climate change. Lexical carbon compounds are used here as indicators for observing how human symbolic cultures change and adapt in response to environmental threats and how symbolic innovation and transmission occurs.