Evolution of adaptation’s evil Doppelgänger

It is widely assumed that language in some form or other originated by piggybacking on pre-existing learning mechanism not dedicated to language. Using evolutionary connectionist simulations, we explore the implications of such assumptions by determining the effect of constraints derived from an earlier evolved mechanism for sequential learning on the interaction between biological and linguistic adaptation across generations of language learners. Artificial neural networks were initially allowed to evolve “biologically” to improve their sequential learning abilities, after which language was introduced into the population. We compared the relative contribution of biological and linguistic adaptation by allowing both networks and language to change over time. The simulation results support two main conclusions: First, over generations, a consistent head-ordering emerged due to linguistic adaptation. This is consistent with previous studies suggesting that some apparently arbitrary aspects of linguistic structure may arise from cognitive constraints on sequential learning. Second, when networks were selected to maintain a good level of performance on the sequential learning task, language learnability is significantly improved by linguistic adaptation but not by biological adaptation. Indeed, the pressure toward maintaining a high level of sequential learning performance prevented biological assimilation of linguistic-specific knowledge from occurring.

A Hybrid Modelling Framework for Ecosystem-Based Climate Change Adaptation Using System Dynamics and Bayesian Networks

Recent attempts to create synthetic Escherichia coli methylotrophs identified that de novo biosynthesis of amino acids, in the presence of methanol, presents significant challenges in achieving autonomous methylotrophic growth. Previously engineered methanol-dependent strains required co-utilization of stoichiometric amounts of co-substrates and methanol. As such, these strains could not be evolved to grow on methanol alone. In this work, we have explored an alternative approach to enable biosynthesis of all amino acids from methanol-derived carbon in minimal media without stoichiometric coupling. First, we identified that biosynthesis of threonine was limiting the growth of our methylotrophic E. coli. To address this, we performed adaptive laboratory evolution to generate a strain that grew efficiently in minimal medium with methanol and threonine. Methanol assimilation and growth of the evolved strain were analyzed, and, interestingly, we found that the evolved strain synthesized all amino acids, including threonine, from methanol-derived carbon. The evolved strain was then further engineered through overexpression of an optimized threonine biosynthetic pathway. We show that the resulting methylotrophic E. coli strain has a methanol-dependent growth phenotype with homoserine as co-substrate. In contrast to previous methanol-dependent strains, co-utilization of homoserine is not stoichiometrically linked to methanol assimilation. As such, future engineering of this strain and successive adaptive evolution could enable autonomous growth on methanol as the sole carbon source. KEY POINTS: • Adaptive evolution of E. coli enables biosynthesis of all amino acids from methanol. • Overexpression of threonine biosynthesis pathway improves methanol assimilation. • Methanol-dependent growth is seen in minimal media with homoserine as co-substrate.

Insect immune proteins evolve more rapidly than nonimmune proteins. Based largely on genetic studies inDrosophilaspecies, this elevated rate appears to be due to adaptive evolution in only a small subset of immune proteins. The genetic signature of adaptive evolution is apparently a response by the host to interference or evasion of the immune system by pathogens, which are usually unknown. In contrast, many insect immune proteins appear to be constrained not to change because they interact with conserved molecular targets in a pathogen's cell wall or plasma membrane. Adaptive immune protein evolution may be attributable to a sustained arms race between host and pathogen or to rapid environmental change that exposes insects to new pathogen suites. Evidence of a correlation between the strength of selection and functional divergence in antimicrobial peptides provides confirmation that the inferred genetic signatures of adaptive evolution reflect a response to pathogen selective pressure.Key Concepts:A small set of immune proteins inDrosophilaevolve much more rapidly than other proteins.Insect antiviral proteins of the RNA interference system are among the top 3% of rapidly evolving proteins inDrosophila.There is surprisingly little evidence of adaptive evolution inDrosophilaantimicrobial peptides.Many receptors and effectors of the insect immune system appear to be evolutionary constrained due to their interaction with conserved target molecules.Pathogens target certain vulnerable immune proteins for suppression and positive selection in these proteins appears to reflect a counter response to this suppression.The selective pressure imposed by pathogens appears to be greater for social than nonsocial insects.Rapid changes in the types of pathogen that hosts encounter as well as long‐term co‐evolutionary arms races may drive adaptive immune protein evolution.Positive selection appears to drive the functional divergence of antimicrobial peptides in termites and other animals.

The role of adaptation in the divergence of lineages has long been a central question in evolutionary biology, and as multilocus sequence data sets have become available for a wide range of taxa, empirical estimates of levels of adaptive molecular evolution are increasingly common. Estimates vary widely among taxa, with high levels of adaptive evolution in Drosophila, bacteria, and viruses but very little evidence of widespread adaptive evolution in hominids. Although estimates in plants are more limited, some recent work has suggested that rates of adaptive evolution in a range of plant taxa are surprisingly low and that there is little association between adaptive evolution and effective population size in contrast to patterns seen in other taxa. Here, we analyze data from 35 loci for six sunflower species that vary dramatically in effective population size. We find that rates of adaptive evolution are positively correlated with effective population size in these species, with a significant fraction of amino acid substitutions driven by positive selection in the species with the largest effective population sizes but little or no evidence of adaptive evolution in species with smaller effective population sizes. Although other factors likely contribute as well, in sunflowers effective population size appears to be an important determinant of rates of adaptive evolution.

Outdoor microalgal cultivation for the production of valuable biofuels and bioproducts typically requires high insolation and strains with high thermal (>37°C) tolerance. While some strains are naturally thermotolerant, other strains of interest require improved performance at elevated temperatures to enhance industrial viability. In this study, adaptive laboratory evolution (ALE) was performed for over 300 days using consecutive 0.5°C temperature increases in a constant temperature incubator to attain greater thermal tolerance in the industrially relevant diatom Nitzschia inconspicua str. Hildebrandi. The adapted strain was able to grow at a constant temperature of 37.5°C; whereas this constant temperature was lethal to the parental control, which had an upper-temperature boundary of 35.5°C before adaptive evolution. Several high-temperature clonal isolates were obtained from the evolved population following ALE, and increased temperature tolerance was observed in the clonal, parent, and non-clonal adapted cultures. This ALE method demonstrates the development of enhanced industrial algal strains without the production of genetically modified organisms (GMOs).

Agriculture is one sector of the economy which is highly vulnerable to climate change because of the natural relationship between environment, particularly temperature and water availability, and agricultural productivity. Changing climate is increasingly affecting high-value perennial plantation crops such as tea, rubber, coconut, palm oil, and coffee which generate significant export revenues and provide a major source of employment for rural populations in developing countries. Many studies in the literature have focused on climate change impacts on major annual crops; however, to date, there have been very few assessments of the economic impacts of climate change on perennial plantation agriculture. This thesis therefore seeks to estimate the impacts of climate change on two important aspects of plantation agriculture - crop production and labour demand - for the case of the tea plantation sector in Sri Lanka, as an example of a high-value perennial plantation crop in a developing country. The thesis also aims to identify enablers and barriers of adaptation to climate change for this sector of Sri Lanka’s economy. The impacts of climate change on production in Sri Lanka’s tea plantations are studied at estate-level (the primary decision making production unit) across all of the country’s tea growing regions using monthly resolution primary data for the period 2000-2014. The study employs a novel two-stage panel data approach to analyse weather and climate change effects on tea production and then to estimate production impacts for the short-, medium- and long-term future under three different global emissions scenarios. These analyses indicate that a hotter and wetter climate will have a detrimental effect on production. In high, medium and low emissions futures, the predictions show a negative proportional impact on production from increased rainfall and increased average temperature. On average across the data sample, a 12% decline in annual tea production is predicted under a high emissions scenario by 2050. The impacts of climate change on labour demand in tea plantations in Sri Lanka are investigated by implementing a panel structural model of profit maximisation based on a normalised quadratic functional form. The analysis uses historical primary data on estate profits, input prices and output prices, together with monsoonal rainfall, temperature and wet days for years between 2002-2014 to quantify climate impacts on estates’ demand for labour. Anticipated changes in rainfall are predicted to reduce annual labour demand by 2.6% across the tea plantation sector. This could have considerable social and welfare implications, particularly for the Indian Tamil women who comprise the majority of the sector’s workforce. Plantation agriculture is likely to be highly vulnerable to climate change because of its reliance on rain-fed production, long economic life span and the inability to easily switch crops due to high upfront capital costs. These distinct differences between annual and perennial agriculture, and the important role which plantation cropping plays in developing world agriculture, suggest that it is important to identify factors which affect choice of climate adaptation options in perennial crop production. Comprehensive knowledge of available adaptation options is of utmost importance if Sri Lanka’s tea estate managers are to counteract production losses from climate change and maintain their competitiveness in the international market. This is also vital for efficient and effective channeling of society’s resources to address the consequences of climate change. Employing data derived from face-to-face interviews with 50 tea estate managers in Sri Lanka, this study examines factors affecting choice of preferred adaptation options, barriers to adaptation and associated policy implications for tea production in Sri Lanka, as an example of a perennial tree crop system in a developing country. Tea estate managers are already adapting to a changing climate; however, particular adaptation methods are only adopted in some situations and locations. Multinomial logit analysis of data from estate manager interviews indicates that availability of information on climate change, company size, tea growing elevation, and observed increases in temperature and rainfall are key factors influencing the choice of preferred adaptation option. Analysis also finds that barriers such as a lack capital, inadequate access to near-term and medium-term climate knowledge, and poor governmental and institutional support may prevent estate managers from experimenting with new adaptation options. Policies should, therefore, be aimed at promoting new adaptation options through information exchange between stakeholders and integrating climate change adaptation with Sri Lanka’s national sustainable developmental goals. The primary message of the adaptation analysis in this study is that governmental and institutional support and involvement are critical requirements for facilitating effective adaptation. Findings from the thesis will help inform decision makers of the likely impacts of climate change on plantation cropping systems, and provide insights into barriers to adaptation and potential policy responses to improve the effectiveness of adaptation.

BackgroundThe migration of Homo sapiens out of Africa and into northern latitudes required significant genetic and behavioral adaptations for survival in new and challenging environments. Among the most critical challenges was the extreme variation in daylight exposure, which influenced circadian rhythms, metabolism, and sleep-wake cycles. Circadian entrainment, the process by which organisms synchronize their internal biological clocks with external environmental cues, plays a crucial role in regulating sleep, feeding, and overall energy balance. Disruptions in circadian regulation are associated with various metabolic and neurodevelopmental disorders, yet the evolutionary mechanisms underlying circadian adaptations in early humans remain underexplored.Aims & ObjectivesWe explore the evolutionary history of the 15q11-q13 imprinted gene cluster, known for its involvement in Prader-Willi Syndrome (PWS), a neurodevelopmental disorder characterized by hyperphagia, obesity, and disrupted sleep-wake rhythms. In this study we aimed to identify genetic variants associated with circadian entrainment in early European populations, determine whether these genetic modifications represent convergent evolutionary adaptations, and examine the functional role of NPAP1 in lipid metabolism and sleep-wake regulation, with potential implications for PWS.MethodWe conducted a comprehensive paleogenomic analysis of ancient DNA from early northern European populations, utilizing whole-genome sequencing data to compare their genetic profiles with those of modern populations. Additionally, we performed a comparative analysis of the 15q11-q13 imprinted region, with a specific focus on NPAP1, to determine its role in lipid metabolism and circadian regulation.ResultsOur analysis revealed independent genetic changes in circadian entrainment pathways among early northern European settlers, suggesting a case of convergent evolution in response to extreme light cycles. These genetic adaptations were found in key regulators of circadian rhythms, which are involved in the synchronization of biological clocks.Furthermore, the paleogenetic analysis of the 15q11-q13 imprinted region revealed signatures of positive selection, with notable changes in NPAP1. Functional studies suggest that NPAP1 plays a novel role in lipid metabolism and circadian regulation, linking genetic adaptations in early humans to modern neurodevelopmental and metabolic disorders.Discussion & ConclusionsThe findings suggest that genetic adaptations in circadian entrainment pathways played a critical role in facilitating human survival in northern latitudes. These adaptations likely mitigated the physiological stress of seasonal variations in light exposure and food availability. The identification of positive selection within the 15q11-q13 locus, provides new insights into the evolutionary origins of metabolic and sleep-wake dysregulation observed in PWS.Overall, this study highlights the complex interplay between evolutionary genetics, circadian regulation, and neurodevelopmental disorders.

Abstrak- Pada tahun 2007 masyarakat Desa Nglepen Yogyakarta di relokasi ke kawasan permukiman bantuan yang dibangun oleh lembaga Dome For The World Foundation. Relokasi ini dilakukan karena rumah masyarakat Desa Nglepen hancur setelah insiden gempa pada tahun 2006. Kondisi hunian bantuan yang memiliki karakteristik fisik sangat berbeda dengan rumah pada umumnya memicu masyarakat Desa Nglepen untuk melakukan adaptasi. Penelitian ini membahas mengenai klasifikasi berdasarkan latar belakang pemicu adaptasi terhadap klasifikasi adaptasi berdasarkan ruang, dan bentuk masyarakat Desa Nglepen. Penelitian ini dilakukan untuk mengetahui bagaimana karakteristik hasil produk adaptasi yang dihasilkan berdasarkan latar belakang pendorong adaptasi dalam upaya mengakomodasi aktivitas sehari-hari.Penelitian menggunakan metode deskriptif dengan pendekatan kualitatif dengan cara mendeskripsikan kondisi eksisting rumah dome beserta dengan latar belakang perubahannya. Sampel penelitian pada klasifikasi adaptasi ini ditentukan pada masyarakat Desa Nglepen yang ingin menetap dengan huniannya. Pengumpulan data dilakukan melalui proses observasi dan wawancara terhadap penghuni rumah dome dan studi literatur. Analisis dilakukan berdasarkan teori strategi adaptasi dan faktor yang mempengaruhi perilaku adaptasi untuk mencari klasifikasi adaptasi berdasarkan latar belakang faktor yang mempengaruhi.Hasil dari klasifikasi berdasarkan latar belakang dan klasifikasi berdasarkan ruang, dan bentuk adalah karakteristik dari setiap adaptasi berdasarkan latar belakang pemicu adaptasi. Karakteristik adaptasi meliputi sifat ruang antara tertutup atau terbuka, kemudian penambahan massa yang mempengaruhi bentuk meliputi penambahan kearah depan, belakang, dan terpisah, pada rumah dome.

Coastal communities are becoming increasingly aware of the risks to local infrastructure from more frequent and severe flooding, more extreme storm surges, and sea-level rise. As local governments are responsible for the lion’s share of land use decision-making and infrastructure development in coastal communities in the United States, local governments in the coastal zone will play a key role in adapting to the changing climate. Local decision-makers are facing hard questions about whether to build new infrastructure, adapt existing infrastructure to new standards, continue maintaining existing infrastructure as is, or abandon infrastructure altogether. Monroe County, Florida, for example, has begun to factor sea-level rise considerations into decisions related to road improvement projects, creating specific design standards addressing elevation and working to weigh the benefits and costs of different adaptation options such as elevating roads. Local governments are making these decisions in the context of increasingly unreliable and aging road systems, all while meeting current stormwater criteria which may require drainage improvements. Local decision-makers also are recognizing that crucial infrastructure decisions that directly affect their adaptation success are sometimes out of their control. In the case of the City of Tybee Island, Georgia, for example, tidal flooding restricts access to U.S. Highway 80 on an ever-increasing basis—yet the highway, the only road leading to the island, is not under the city’s jurisdiction but that of the Georgia Department of Transportation. To further complicate matters for local governments, both taking action and failing to act could result in either tort or “takings” liability in cases where a poorly maintained road results in harm to life or loss of property value from diminished access. Using the duty of state and local governments to maintain roads as a focus, this Article explores the complexity of adaptation at the local level as the impacts of climate change become more pronounced. Specifically, this Article presents an analysis of coastal communities in four South Atlantic states—Florida, Georgia, South Carolina, and North Carolina—that are currently facing questions about how to protect property and infrastructure as sea levels rise and flooding increases. This Article distills the findings of an interdisciplinary research project funded by the National Oceanic and Atmospheric Administration (“NOAA”), Florida Sea Grant, Georgia Sea Grant, South Carolina Sea Grant Consortium, and North Carolina Sea Grant. It also consists of a regional analysis comparing how tort and local government law can both further and hinder climate change resilience planning and climate adaptation efforts across these four states. Given that the federal government has offered little in terms of legislation, policy, or funding to direct or support climate adaptation activities, local efforts—and the litigation that inevitably results—are on the forefront of establishing the framework for defining adaptation policy more broadly and influencing the contours of tort and land use law. This Article, therefore, fills an important research gap in existing climate change literature, as it discusses how increased flooding at the local level is putting pressure on traditional conceptions of government duties, immunities, and authorities. This Article also uses roads as a case study to explore how sea-level rise is altering planning, maintenance, and funding for public infrastructure. This discussion focuses on local duties and responsibilities to build, rebuild, modify, or maintain existing roads for two primary reasons: (1) it is a widely shared function among jurisdictions and is the most obvious and visible type of infrastructure to the public, and (2) roads and highways, which are crucial to trade, defense, and nation-building, have long been under the purview of government regulation and funding in the United States. Recently, roads have also become a focal point in local government efforts to address rising sea levels and increased flooding. While sea-level rise may seem like a distant threat, many of its effects are being felt now, as low-lying coastal areas such as Norfolk, Virginia; Brunswick, Georgia; and Monroe County, Florida are experiencing increased nuisance or “sunny day” flooding occurring during seasonal or average high tides. Such flooding typically affects roads, temporarily closing them and increasing maintenance and repair costs. Residents who rely on these roads, often find themselves cut off from their homes, businesses, workplaces, schools, and local hospitals. In this way, sea-level rise and the flooding associated with it have become increasingly familiar and imminent, making roads the “climate change canary in the coal mine” for local governments. Part I of this Article briefly discusses recent sea-level rise issues and coastal science most relevant to the South Atlantic states—North Carolina, South Carolina, Georgia, and Florida. Part II analyzes and compares each state’s road ownership and maintenance duties, first by addressing the threshold question of ownership and jurisdiction, and then by explaining the multi-step analysis that governments must take to evaluate their duties to maintain roads in order to avoid liability. Part II also outlines the wide differences among the four states in our study area and observes a common thread, namely, that in almost each instance, local governments are faced with conflicting pressures that are likely to reward inaction over action and favor short-term political compromises over strategic investments in adaptation. This Part then details how counties and municipalities can discontinue their duties to maintain roads through the process of abandonment and how abandonment can lead to takings liability. Part III offers three proposals for encouraging coordinated adaptation action and protecting local governments that take action to address climate impacts: (1) redefining the scope of the duties that define reasonable conduct for governments in making decisions about public infrastructure in an era of rising sea levels; (2) defining the scope of sovereign immunity protections in a way that encourages innovative and creative decision-making in an era of climate uncertainty; and (3) calling for consistent adaptation duties and authorities at the state level as a crucial first step in mending the regulatory patchwork that currently exists at the state, county, and city levels in our four-state study area. Part IV concludes with a summary of observations and recommended next steps.

Personalized graphical user interfaces have the potential to reduce visual complexity and improve efficiency by modifying the interface to better suit an individual user’s needs. Working in a personalized interface can make users faster, more accurate and more satisfied; in practice, however, personalization also comes with costs, such as a reliance on user effort to control the personalization, or the introduction of spatial instability when interface items are reorganized automatically. We conducted a series of studies to examine both the costs and benefits of personalization, and to identify techniques and contexts that would be the most likely to provide an overall benefit. We first interviewed long-term users of a software application that provides adaptable (usercontrolled) personalization. A design trade-off that emerged is that while personalization can increase the accessibility of features useful to a user’s current task, it may in turn negatively impact the user’s awareness of the full set of available features. To assess this potential trade-off, we introduced awareness as an evaluation metric to be used alongside more standard performance measures and we ran a series of three studies to understand how awareness relates to core task performance. These studies used two different measures to assess awareness, showing that personalization can impact both the recognition rate of unused features in the interface and user performance on new tasks requiring those features. We investigated both adaptive (system-controlled) and adaptable personalization techniques to help us understand the generalizability of the awareness concept. In addition to introducing and incorporating awareness into our evaluations, we studied how specific contextual and design characteristics impact the user’s experience with adaptive interfaces. In one study, we evaluated the impact of screen size on performance and user satisfaction with adaptive split menus. Results showed that the performance and satisfaction benefits of spatially reorganizing items in the interface are more likely to outweigh the costs when screen size is small. We also introduced a new adaptive personalization technique that maintains spatial stability, called ephemeral adaptation, and evaluated it through two studies. Ephemeral adaptation improves performance over both another closely related adaptive technique and a traditional interface.

Rate adaptation is critical to the system performance of Wireless Local Area Networks (WLANs). Existing rate adaptation schemes mostly make use of packet statistics or the signal strengths of received packets to adapt transmission rates, regardless of the packet priorities. In this paper, we first find out that it is beneficial for rate adaptation schemes to consider packet priorities when adapting transmission rates. We then propose a novel priority-based rate adaptation scheme for vehicular networks named SRAG (Stackelberg Rate Adaptation Game) which jointly considers channel conditions and packet priorities using game theory. In SRAG, rate adaptation is modeled as a game which consists of different priorities of users and each user tries to select an optimal transmission rate that maximizes its utility regardless of others' utilities. SRAG adopts a Stackelberg game model to regulate behaviors of self-interested users and gives priority to high priority users in order to achieve better overall performance. Extensive ns-2 simulations demonstrate that SRAG can provide much better performance for high priority users than existing rate adaptation schemes, while maintaining good performance for low priority users.

Adaptation is a wise choice for industrial ecosystem to face up the inevitable environment changes.It also provides a new paradigm for the study of interaction mechanisms and processes of coupled industrial ecosystem.There are a lot of mining cities in Northeast China,which approach their middle-age or old-age of resources exploitation.Faced with their disappearing superior status in resources problems,the subject on how to adjust the industrial ecosystem to the possible changes in the future,has become urgent in revitalizing the old industrial base of Northeast China.Based on a detailed discussion about the conception of industrial ecosystem adaptation of mining cities,the essay establishes an industrial adaptability assessment index system and model of mining cities from the aspects of adaptation factors of vulnerability,sensitivity,stability and resilience.According to the model,the industrial ecosystem adaptability,including regional differentiation,types and influencing factors of mining cities is evaluated.From a view of different resource types,the average score of industrial ecosystem adaptation shows a trend of metallurgical citiesmulti-resources citiescoal citiespetroleum cities.From a view of regional differences,it shows a trend of LiaoningJilinHeilongjiang;from a view of development stages,it has a trend of old-agedmiddle-agedjuvenile-aged;from a view of mining city size,it shows a trend of mega-citiesbig citiesmedium-sized cities.Then a cluster analysis method is applied to categorize the industrial ecosystems into four types: high adaptability and harmonious development between industry and ecology,high adaptable capacity and environmental development first,low adaptability and harmonious development between industry and ecology,low adaptable capacity and environmental development first.

Variation in streptomycin sensitivity and dark sensitivity of 36 rice genotypes of 3 different maturity groups was studied. Streptomycin sensitivity and dark sensitivity of rice genotypes were expressed in terms of bleaching index (BI) and senescence index (SI) respectively. Genotypes of each maturity group showed wide variation in their BI / SI value. The objective of this investigation was to find relationship of BI / SI parameter with yield, adaptability and stability in yield performance of rice genotypes. Yield performance of rice genotypes were evaluated over 12 environments. Adaptability and stability analysis were done following linear regression model of Eberhart and Russell and AMMI Stability Value (ASV) of purchase. BI parameter showed positive correlation with yielding ability and deviation from regression and negative correlation with adaptability parameter (b) for all the 3 maturity groups. But SI parameter showed negative correlation with yielding ability and positive correlation with adaptability parameter (b) for all the 3 maturity groups. This experimental study revealed that sensitivity of rice genotypes to SM in terms of BI could be used to predict yielding ability of genotypes and dark sensitivity (SI) could be used to indicate adaptability to rich environments or poor environments. This novel approach may help the breeder in indirect selection of high yielding genotypes and genotypes well adapted to rich or poor environments at an early seedling stage before going for multilocation trials. Key words: Streptomycin, dark treatment, Oryza sativa, adaptability.

Instructional designers are under increasing pressure to enhance the pedagogical quality and technical richness of their learning content offerings, while the task of authoring for such complex educational frameworks is expensive and time consuming. Personalisation and reusability of learning contents are two main factors which can be used to enhance the pedagogical impact of e-learning experiences while also optimising resources, such as the overall cost and time of designing materials for different e-learning systems. However, personalisation services require continuous fine tuning for the different features that should be used, and e-learning systems need sufficient flexibility to offer these continuously required changes. The semantic modelling of adaptable learning components can highly influence the personalisation of the learning experience and enables the reusability, adaptability and maintainability of these components. Through the discrete modelling of these components, the flexibility and extensibility of e-learning systems will be improved as learning contents can be separated from the adaptation logic which results in the learning content being no longer specific to any given adaptation rule, or instructional plan. This thesis proposes an innovative semantic rule-based approach to dynamically generate personalised learning content utilising reusable pieces of learning content. It describes an ontology-based engine that composes, at runtime, adapted learning experiences according to learner’s interaction with the system and learner’s characteristics. Additionally, enriching ontologies with semantic rules increases the reasoning power and helps to represent adaptation decisions. This novel approach aims to improve flexibility, extensibility and reusability of systems, while offering a pedagogically effective and satisfactory learning experience for learners. This thesis offers the theoretical models, design and implementation of an adaptive e-learning system in accordance with this approach. It also describes the evaluation of developed personalised adaptive e-learning system (Rule-PAdel) from pedagogical and technical perspectives.