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Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without reference to underlying biological processes. Furthermore, the construction of these models is often monolithic: they do not allow one to readily modify the processes involved or include the new ones, or to combine models at different scales. We show how to construct a simple model of immune response to a respiratory virus and a model of transmission using an easily modifiable set of rules allowing further refining and merging the two models together. The immune response model reproduces the expected response curve of PCR testing for COVID-19 and implies a long-tailed distribution of infectiousness reflective of individual heterogeneity. This immune response model, when combined with a transmission model, reproduces the previously reported shift in the population distribution of viral loads along an epidemic trajectory. This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’.

Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without reference to underlying biological processes. Furthermore, the construction of these models is often monolithic: they do not allow one to readily modify the processes involved or include the new ones, or to combine models at different scales. We show how to construct a simple model of immune response to a respiratory virus and a model of transmission using an easily modifiable set of rules allowing further refining and merging the two models together. The immune response model reproduces the expected response curve of PCR testing for COVID-19 and implies a long-tailed distribution of infectiousness reflective of individual heterogeneity. This immune response model, when combined with a transmission model, reproduces the previously reported shift in the population distribution of viral loads along an epidemic trajectory. This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’.

Background: Cerebral cavernous malformations (CCMs) are low-flow vascular malformations made up of dilated vascular spaces without intervening parenchyma that can occur throughout the central nervous system. CCMs can occur sporadically or in familial forms. Presentation is diverse, ranging from asymptomatic discoveries to drug-resistant epilepsy and hemorrhages. Methods: We describe the surgical management of CCMs in pediatric patients at Bambino Gesù Children's Hospital in Rome over the last 10 years. The cases have been stratified based on the clinical presentation and the relevant literature is discussed accordingly. Results: We discuss the rationale and technique used in these cases based on their presentation, as well as the generally positive outcomes we achieved with early surgical management, use of intra-operative ultrasound (ioUS) and intraoperative neuromonitoring. Conclusions: Surgical management of pediatric CCMs is a safe and effective strategy, low rates of postoperative morbidity and partial resection were observed.

Rule-based models generalise reaction-based models with reagents that have internal state and may be bound together to form complexes, as in chemistry. An important class of system that would be intractable if expressed as reactions or ordinary differential equations can be efficiently simulated when expressed as rules. In this paper we demonstrate the utility of the rule-based approach for epidemiological modelling presenting a suite of seven models illustrating the spread of infectious disease under different scenarios: wearing masks, infection via fomites and prevention by hand-washing, the concept of vector-borne diseases, testing and contact tracing interventions, disease propagation within motif-structured populations with shared environments such as schools, and superspreading events. Rule-based models allow to combine transparent modelling approach with scalability and compositionality and therefore can facilitate the study of aspects of infectious disease propagation in a richer context than would otherwise be feasible.

Across various scenarios, individuals cooperate with others to contribute towards a shared goal and ensure self-preservation. In game theory, the act of cooperation is considered as an individual producing some form of benefit to be utilised by others, under the expectation others will return the favour. In several scenarios, individuals make use of their own information to aid with their decision about who to connect and cooperate with. However, the choice of cooperation can be taken advantage of by opportunistic defectors, which can lead to significant disruption. This paper investigates how the diversity of opinion can contribute to the structure and mechanics of a dynamical network model and to the resilience of cooperation, by utilising a computational model where individuals make use of both public and private information to implement their decision. Our results show that increasing diversity leads to more stable, less connected and less prosperous networks coupled to more frequent, but shallower information cascades. Our work generally shows that the outcome of the conflict between cooperators and cheaters strongly depends on the interplay between population structure, individual decision making and individual opinions.

Rule-based models generalise reaction-based models with reagents that have internal state and may be bound together to form complexes, as in chemistry. An important class of system that would be intractable if expressed as reactions or ordinary differential equations can be efficiently simulated when expressed as rules. In this paper we demonstrate the utility of the rule-based approach for epidemiological modelling presenting a suite of seven models illustrating the spread of infectious disease under different scenarios: wearing masks, infection via fomites and prevention by hand-washing, the concept of vector-borne diseases, testing and contact tracing interventions, disease propagation within motif-structured populations with shared environments such as schools, and superspreading events. Rule-based models allow to combine transparent modelling approach with scalability and compositionality and therefore can facilitate the study of aspects of infectious disease propagation in a richer context than would otherwise be feasible.

Across various scenarios, individuals cooperate with others to contribute towards a shared goal and ensure self-preservation. In game theory, the act of cooperation is considered as an individual producing some form of benefit to be utilised by others, under the expectation others will return the favour. In several scenarios, individuals make use of their own information to aid with their decision about who to connect and cooperate with. However, the choice of cooperation can be taken advantage of by opportunistic defectors, which can lead to significant disruption. This paper investigates how the diversity of opinion can contribute to the structure and mechanics of a dynamical network model and to the resilience of cooperation, by utilising a computational model where individuals make use of both public and private information to implement their decision. Our results show that increasing diversity leads to more stable, less connected and less prosperous networks coupled to more frequent, but shallower information cascades. Our work generally shows that the outcome of the conflict between cooperators and cheaters strongly depends on the interplay between population structure, individual decision making and individual opinions.

Temporal bone fractures are a common lesion of the base of the skull. The diagnosis and management of temporal bone fractures require a multidisciplinary approach. Variable clinical presentations may arise from such fractures, ranging from an asymptomatic course to very serious consequences. The aim of this study was to report our experience with a series of patients with temporal bone fractures and to propose a diagnostic/therapeutic algorithm. This study enrolled 141 patients, 96 (68.1%) males and 45 (31.9%) females, ranging in age from 20 to 60 (average age: 39 +/- 4.1 years), with temporal bone fractures who were referred to Cardarelli Hospital between 2006 and 2018. The present paper presents a classification of temporal bone fractures and typical clinical sequelae and provides an illustration of their prognosis and treatment.

Cephalohematoma is a subperiosteal collection of blood above the skull. It is associated with operative and prolonged deliveries. In most cases the hematoma spontaneously resolves in a short span of time, usually within one month. In a few cases cephalohematoma can become ossified and require surgical treatment. Traditional belief that ossified cephalohematomas are an exclusively cosmetic issue has been called into question by recent description of EEG anomalies associated to a calcified cephalohematoma. We review relevant surgical literature, and we describe a novel variant of Wong's Radial Cap technique by foregoing healthy bone margin removal, removing the cephalohematoma lamellae in a stepwise fashion and using resorbable plaques for fixation. We furthermore review the rationale, timing and step-by-step execution of the procedure. An exemplary case description is discussed.

We present path entropy, an information-theoretic measure that captures the notion of patterning due to phase separation in organic tissues. Recent work has demonstrated, both in silico and in vitro, that phase separation in epithelia can arise simply from the forces at play between cells with differing mechanical properties. These qualitative results give rise to numerous questions about how the degree of patterning relates to model parameters or underlying biophysical properties. Answering these questions requires a consistent and meaningful way of quantifying degree of patterning that we observe. We define a resolution-independent measure that is better suited than image-processing techniques for comparing cellular structures. We show how this measure can be usefully applied in a selection of scenarios from biological experiment and computer simulation, and argue for the establishment of a tissue-graph library to assist with parameter estimation for synthetic morphology.

Microbial communities are increasingly utilized in biotechnology. Efficiency and productivity in many of these applications depends on the presence of cooperative interactions between members of the community. Two key processes underlying these interactions are the production of public goods and metabolic cross-feeding, which can be understood in the general framework of ecological and evolutionary (eco-evo) dynamics. In this review, we illustrate the relevance of cooperative interactions in microbial biotechnological processes, discuss their mechanistic origins and analyse their evolutionary resilience. Cooperative behaviours can be damaged by the emergence of ‘cheating’ cells that benefit from the cooperative interactions but do not contribute to them. Despite this, cooperative interactions can be stabilized by spatial segregation, by the presence of feedbacks between the evolutionary dynamics and the ecology of the community, by the role of regulatory systems coupled to the environmental conditions and by the action of horizontal gene transfer. Cooperative interactions enrich microbial communities with a higher degree of robustness against environmental stress and can facilitate the evolution of more complex traits. Therefore, the evolutionary resilience of microbial communities and their ability to constraint detrimental mutants should be considered to design robust biotechnological applications.

Individual cells process environmental information relevant to their functions using biochemical processes and signalling networks that implement a flow of information from the extracellular environment, across the cell membrane to the cytoplasm in which the actual cellular computation takes place (in the form of gene expression). In many cases, the environmental information to be processed are either molecules produced by other cells or shared extracellular molecules - in this case the processing of the environmental information is a distributed, highly parallel computing process, in which cells must synchronize, coordinate and cooperate. While the ability of cells to cooperate can increase their overall computational power, it also raises an evolutionary stability issue - population of cooperating cells are at risk of cheating cells invasions, cells that do not cooperate but exploit the benefits of the population. The bridge between membrane computing (as a mathematical formalization of cellular computing) and evolutionary dynamics (as mathematical formalization of Natural selection) could lead to interesting insights on the evolutionary stability of cellular computing.

Bacterial populations whose growth depends on the cooperative production of public goods are usually threatened by the rise of cheaters that do not contribute but just consume the common resource. Minimizing cheater invasions appears then as a necessary mechanism to maintain these populations. However, that invasions result instead in the persistence of cooperation is a prospect that has yet remained largely unexplored. Here, we show that the demographic collapse induced by cheaters in the population can actually contribute to the rescue of cooperation, in a clear illustration of how ecology and evolution can influence each other. The effect is made possible by the interplay between spatial constraints and the essentiality of the shared resource. We validate this result by carefully combining theory and experiments, with the engineering of a synthetic bacterial community in which the public compound allows survival to a lethal stress. The characterization of the experimental system identifies additional factors that can matter, like the impact of the lag phase on the tolerance to stress, or the appearance of spontaneous mutants. Our work explains the unanticipated dynamics that eco-evolutionary feedbacks can generate in microbial communities, feedbacks that reveal fundamental for the adaptive change of ecosystems at all scales.

Microbial communities are increasingly utilized in biotechnology. Efficiency and productivity in many of these applications depends on the presence of cooperative interactions between members of the community. Two key processes underlying these interactions are the production of public goods and metabolic cross-feeding, which can be understood in the general framework of ecological and evolutionary (eco-evo) dynamics. In this review, we illustrate the relevance of cooperative interactions in microbial biotechnological processes, discuss their mechanistic origins and analyse their evolutionary resilience. Cooperative behaviours can be damaged by the emergence of ‘cheating’ cells that benefit from the cooperative interactions but do not contribute to them. Despite this, cooperative interactions can be stabilized by spatial segregation, by the presence of feedbacks between the evolutionary dynamics and the ecology of the community, by the role of regulatory systems coupled to the environmental conditions and by the action of horizontal gene transfer. Cooperative interactions enrich microbial communities with a higher degree of robustness against environmental stress and can facilitate the evolution of more complex traits. Therefore, the evolutionary resilience of microbial communities and their ability to constraint detrimental mutants should be considered to design robust biotechnological applications.

Bacterial populations whose growth depends on the cooperative production of public goods are usually threatened by the rise of cheaters that do not contribute but just consume the common resource. Minimizing cheater invasions appears then as a necessary mechanism to maintain these populations. However, that invasions result instead in the persistence of cooperation is a prospect that has yet remained largely unexplored. Here, we show that the demographic collapse induced by cheaters in the population can actually contribute to the rescue of cooperation, in a clear illustration of how ecology and evolution can influence each other. The effect is made possible by the interplay between spatial constraints and the essentiality of the shared resource. We validate this result by carefully combining theory and experiments, with the engineering of a synthetic bacterial community in which the public compound allows survival to a lethal stress. The characterization of the experimental system identifies additional factors that can matter, like the impact of the lag phase on the tolerance to stress, or the appearance of spontaneous mutants. Our work explains the unanticipated dynamics that eco-evolutionary feedbacks can generate in microbial communities, feedbacks that reveal fundamental for the adaptive change of ecosystems at all scales.

Individual cells process environmental information relevant to their functions using biochemical processes and signalling networks that implement a flow of information from the extracellular environment, across the cell membrane to the cytoplasm in which the actual cellular computation takes place (in the form of gene expression). In many cases, the environmental information to be processed are either molecules produced by other cells or shared extracellular molecules - in this case the processing of the environmental information is a distributed, highly parallel computing process, in which cells must synchronize, coordinate and cooperate. While the ability of cells to cooperate can increase their overall computational power, it also raises an evolutionary stability issue - population of cooperating cells are at risk of cheating cells invasions, cells that do not cooperate but exploit the benefits of the population. The bridge between membrane computing (as a mathematical formalization of cellular computing) and evolutionary dynamics (as mathematical formalization of Natural selection) could lead to interesting insights on the evolutionary stability of cellular computing.

The sustainability of biological, social, economic and ecological communities is often determined by the outcome of social conflicts between cooperative and selfish individuals (cheaters). Cheaters avoid the cost of contributing to the community and can occasionally spread in the population leading to the complete collapse of cooperation. Although such collapse often unfolds unexpectedly, it is unclear whether one can detect the risk of cheater’s invasions and loss of cooperation in an evolving community. Here, we combine dynamical networks and evolutionary game theory to study the abrupt loss of cooperation with tools for studying critical transitions. We estimate the risk of cooperation collapse following the introduction of a single cheater under gradually changing conditions. We observe an increase in the average time it takes for cheaters to be eliminated from the community as the risk of collapse increases. We argue that such slow system response resembles slowing down in recovery rates prior to a critical transition. In addition, we show how changes in community structure reflect the risk of cooperation collapse. We find that these changes strongly depend on the mechanism that governs how cheaters evolve in the community. Our results highlight novel directions for detecting abrupt transitions in evolving networks.

The sustainability of biological, social, economic and ecological communities is often determined by the outcome of social conflicts between cooperative and selfish individuals (cheaters). Cheaters avoid the cost of contributing to the community and can occasionally spread in the population leading to the complete collapse of cooperation. Although such collapse often unfolds unexpectedly, it is unclear whether one can detect the risk of cheater’s invasions and loss of cooperation in an evolving community. Here, we combine dynamical networks and evolutionary game theory to study the abrupt loss of cooperation with tools for studying critical transitions. We estimate the risk of cooperation collapse following the introduction of a single cheater under gradually changing conditions. We observe an increase in the average time it takes for cheaters to be eliminated from the community as the risk of collapse increases. We argue that such slow system response resembles slowing down in recovery rates prior to a critical transition. In addition, we show how changes in community structure reflect the risk of cooperation collapse. We find that these changes strongly depend on the mechanism that governs how cheaters evolve in the community. Our results highlight novel directions for detecting abrupt transitions in evolving networks.

Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. Results: We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general.

Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling framework to represent the complexity of biological systems. Annotation approaches have been widely used for reaction-based formalisms such as SBML. However, rule-based languages still lack a rich annotation framework to add semantic information, such as machine-readable descriptions, to the components of a model. Results: We present an annotation framework and guidelines for annotating rule-based models, encoded in the commonly used Kappa and BioNetGen languages. We adapt widely adopted annotation approaches to rule-based models. We initially propose a syntax to store machine-readable annotations and describe a mapping between rule-based modelling entities, such as agents and rules, and their annotations. We then describe an ontology to both annotate these models and capture the information contained therein, and demonstrate annotating these models using examples. Finally, we present a proof of concept tool for extracting annotations from a model that can be queried and analyzed in a uniform way. The uniform representation of the annotations can be used to facilitate the creation, analysis, reuse and visualization of rule-based models. Although examples are given, using specific implementations the proposed techniques can be applied to rule-based models in general.

In the commons, communities whose growth depends on public good, individuals often rely on surprisingly simple strategies, or heuristics, to decide whether to contribute to the shared resource (at risk of exploitation by free-riders). Although this appears a limitation, we show here how four heuristics lead to sustainable growth when coupled to specific ecological constraints. The two simplest ones—contribute permanently or switch stochastically between contributing or not—are first shown to bring sustainability when the public good efficiently promotes growth. If efficiency declines and the commons is structured in small groups, the most effective strategy resides in contributing only when a majority of individuals are also contributors. In contrast, when group size becomes large, the most effective behaviour follows a minimal-effort rule: contribute only when it is strictly necessary. Both plastic strategies are observed in natural scenarios across scales that present them as relevant social motifs for the sustainable management of public goods.

In the commons, communities whose growth depends on public good, individuals often rely on surprisingly simple strategies, or heuristics, to decide whether to contribute to the shared resource (at risk of exploitation by free-riders). Although this appears a limitation, we show here how four heuristics lead to sustainable growth when coupled to specific ecological constraints. The two simplest ones—contribute permanently or switch stochastically between contributing or not—are first shown to bring sustainability when the public good efficiently promotes growth. If efficiency declines and the commons is structured in small groups, the most effective strategy resides in contributing only when a majority of individuals are also contributors. In contrast, when group size becomes large, the most effective behaviour follows a minimal-effort rule: contribute only when it is strictly necessary. Both plastic strategies are observed in natural scenarios across scales that present them as relevant social motifs for the sustainable management of public goods.

This paper discusses research frontiers of membrane computing by presenting current open problems and research topics, together with the relevant background and motivation

In the commons, communities whose growth depends on public good, individuals often rely on surprisingly simple strategies, or heuristics, to decide whether to contribute to the shared resource (at risk of exploitation by free-riders). Although this appears a limitation, we show here how four heuristics lead to sustainable growth when coupled to specific ecological constraints. The two simplest ones - contribute permanently or switch stochastically between contributing or not - are first shown to bring sustainability when the public good efficiently promotes growth. If efficiency declines and the commons is structured in small groups, the most effective strategy resides in contributing only when a majority of individuals are also contributors. In contrast, when group size becomes large, the most effective behaviour follows a minimal-effort rule: contribute only when it is strictly necessary. Both plastic strategies are observed in natural scenarios across scales that present them as relevant social motifs for the sustainable management of public goods. © 2013 The Authors.

An extremely rare case of papillary carcinoma is described arising in a submental-intralingual thyroglossal duct cyst. A 27-year-old male presented with a painless swelling in the submental region extending to the tongue which had gradually been increasing in size over the last three months. Upon examination of the neck, a tender right paramedian mass was found in the submental region just above the hyoid bone, it was mobile upon swallowing without clinical evidence of cervical nodes. The Sistrunk surgical technique, extended to the submental and intra lingual region was used to radically remove the mass. The occurrence of carcinoma of the thyroglossal duct cyst, even though rare and unexpected, should always be considered an option, and histologically ruled out mainly on account of the atypical localization, such as the submental-intralingual reported herein. The two different surgical approaches reported in the literature, one more conservative and the other more aggressive, apparently alternatives, are, instead, complementary and adequate when strict diagnostic criteria and adequate follow-up, are observed.

RAS signaling plays a key role in controlling appropriate cell responses to extracellular stimuli and participates in early and late developmental processes. Although enhanced flow through this pathway has been established as a major contributor to oncogenesis, recent discoveries have revealed that aberrant RAS activation causes a group of clinically related developmental disorders characterized by facial dysmorphism, a wide spectrum of cardiac disease, reduced growth, variable cognitive deficits, ectodermal and musculoskeletal anomalies, and increased risk for certain malignancies. Here, we report that heterozygous germline mutations in CBL, a tumor-suppressor gene that is mutated in myeloid malignancies and encodes a multivalent adaptor protein with E3 ubiquitin ligase activity, can underlie a phenotype with clinical features fitting or partially overlapping Noonan syndrome (NS), the most common condition of this disease family. Independent CBL mutations were identified in two sporadic cases and two families from among 365 unrelated subjects who had NS or suggestive features and were negative for mutations in previously identified disease genes. Phenotypic heterogeneity and variable expressivity were documented. Mutations were missense changes altering evolutionarily conserved residues located in the RING finger domain or the linker connecting this domain to the N-terminal tyrosine kinase binding domain, a known mutational hot spot in myeloid malignancies. Mutations were shown to affect CBL-mediated receptor ubiquitylation and dysregulate signal flow through RAS. These findings document that germline mutations in CBL alter development to cause a clinically variable condition that resembles NS and that possibly predisposes to malignancies.

The correlation between laryngo-pharyngeal reflux and dysphonia has been evaluated in patients without significant laryngoscopic findings and without vocal misuse. Studies were performed, using a validated questionnaire on typical reflux symptoms as well as instrumental means, e.g. videolaryngoscopy, multi-electrode 24-hr oesophageal pH monitoring, vocal acoustic analysis, gastro-oesophagoscopy, on 62 patients (51 male, 11 female) with dysphonia for > or = 3 months, selected from 350) consecutive patients presenting with voice disorders. Standard criteria were: absence of laryngeal neoformation (benign or malignant) and correct use of voice. Anti-reflux treatment was prescribed in all selected patients. A group of 62 selected patients without laryngo-pharyngeal disease were studied as controls. Mean values of the harmonic to noise ratio and maximum phonation time were pathological in all patients with dysphonia and significantly correlated (p = 0) with the entity of the larynx alteration. The 24-hour pH monitoring revealed gastro-oesophageal reflux in all cases with a clear prevalence of episodes in the upright, compared to supine, position. From a multiple regression analysis of pH-metric values, considered important in predicting maximum phonation time and harmonic to noise ratio alteration. the significant predictors (p < 0.01) were those parameters indicating the existence of a laryngo-pharyngeal reflux disease: in an upright position, the prevalence of the number of refluxes and of time of pH < 4. In conclusion, the association between electro-acoustic reliefs and laryngoscopic data, as well as an alteration in maximum phonation time and harmonic to noise ratio in patients with pH-metric indicative parameters of laryngo-pharyngeal reflux disease led to the hypothesis of a possible correlation between entity and duration of the reflux and dysfunction of the arytenoid muscles, upon which chronic vocal fatigue, with consequent laryngeal compensatory stres

This report introduces main results and recommendations of the research project “Wind Energy Production in COld climates” WECO (JOR3-CT95-0014), which was partially supported by the European Commission DG XII Non Nuclear Energy Programme aiming at the investigation of wind turbines under cold climate operation. It is shown experimentally and by numerical simulations that icing of rotor blades or other components lead to decreased production due to ice accretion or safety demands. The icing effect is directly related to the climate of the site of the wind turbine, and varies strongly from region to region in Europe. Extreme low air temperature again arises new demands for design parameters. Icing of anemometers and other wind gauges typically lead to wrong estimation of wind power potential and operational problems of wind turbines. The icing map over Europe, based on meteorological observations from 120 synoptic stations, show that icing and cold weather conditions occur in large regions in Europe, not only in the Nordic countries but also especially at mountainous regions in Northern Europe, Germany, UK, Alps, Spain and central Italy. On the other hand new megawatt turbines are high enough to encounter in-cloud icing even in lowlands. Following the method used to construct the European wind atlas, icing data is presented to show how it affects on-site wind power production. Experimental data, wind tunnel simulations and numerical analyses were used to describe the ice formation on wind turbine blades, to produce the C l, Cd values, to calculate the power curves for iced wind turbines, and to study the loads. Ice on blades usually decreases the power production. At harsh sites the annual power loss may be up to 20-50 %. The project also produced a preliminary method to combine the European Wind Atlas method, iced power curves and statistics of in-cloud icing to estimate annual or monthly losses due to icing at desired site. For environmental safety i

This study assessed soil size fractions from bulk soil to the nanoparticulate (less than 0.2 micron) fraction and the associated gold contents. It has demonstrated the method to quantify gold in these very small size fractions and shown there are differences in the micro and nanoparticulate fractions compared to the bulk or medium fractions that are routinely analysed in mineral exploration. The study is limited by the fact that the samples are not oriented with respect to known gold mineralisation and by the small number of samples and the small weight of nanoparticulate sample size material recovered. The small volumes of material analysed result in increased errors, but has effectively demonstrated that the size fractions can be separated, analysed and provide different information. The results are plotted spatially as an example for exploration feasibility, but do not assess which fraction provides the best exploration sample medium. Future research requires a more rigorous assessment of the method to exactly quantify the nanoparticulate size fraction separated, along with more focused orientation surveys to determine if significant benefit exists for analysing the micro and nanoparticulate fractions of soils for gold exploration; a process that is not currently conducted by industry., This study assessed soil size fractions from bulk soil to the nanoparticulate (less than 0.2 micron) fraction and the associated gold contents. It has demonstrated the method to quantify gold in these very small size fractions and shown there are differences in the micro and nanoparticulate fractions compared to the bulk or medium fractions that are routinely analysed in mineral exploration. The study is limited by the fact that the samples are not oriented with respect to known gold mineralisation and by the small number of samples and the small weight of nanoparticulate sample size material recovered. The small volumes of material analysed result in increased errors, but has effectively demonstrated that the size fractions can be separated, analysed and provide different information. The results are plotted spatially as an example for exploration feasibility, but do not assess which fraction provides the best exploration sample medium. Future research requires a more rigorous assessment of the method to exactly quantify the nanoparticulate size fraction separated, along with more focused orientation surveys to determine if significant benefit exists for analysing the micro and nanoparticulate fractions of soils for gold exploration; a process that is not currently conducted by industry.