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Automatic Phenotyping of Microscopic Skin Images
Get PDFThe Mouse Genetics Project (MGP) is a large-scale mutant mice production and phenotyping initiative that builds on the success of the Human Genome Project (HGP) to discover the functionality of all genes and their role in human diseases. The MGP aims to produce over 20,000 mutant lines of mouse model to investigate and quantify the impact of gene knockouts on the various organs. Due to the great deal of overlap between human and mouse genomes, most the acquired knowledge can be translated into diagnostics, biomarker identifications and eventually treatment for complex genetic-based diseases.
The skin is by far the largest organ in the mammalian body, and a complex structure of multiple layers consisting of different distinguishable cells and objects. Dermatology specialists have long associated many diseases with changes in different skin layers such as changes to the number of nuclei in the dermis and epidermis layers, the orientation of hair follicles, curvature of the outer border of the epidermis, and many more.
The manual quantification and analysis of such features/objects for a high throughput phenotype research project such as the MGP is an error-prone, time consuming and very costly in terms of resources and staff training. Recent rapid advances in biomedical image processing/analysis as well as the emergence of a variety of machine learning tools provide an exciting motivation to developing effective and efficient automatic solutions. Automation is as challenging as the manual methods but the challenges are of different nature. Therefore, this thesis is devoted to investigate, develop and test a number of automatic algorithms to quantify the above mentioned features/objects in mouse skin layers and experimentally identify the genetic causes of changes to these parameters in relation to skin diseases.
Our investigations and solutions had to deal with a number of technical challenges such as staining errors that lead colour overlapping between neighbouring layers/components, damages to the outer layers during preparation of images, the difficulty of establishing the ground truth for the large volume of image dataset, significant overlapping of nuclei objects, misalignments of tissues with the large volume of dataset. The main contributions of the thesis include:
1. Proposing an adaptive system that combines colour deconvolution and fuzzy c-mean methods to segment the three main skin layers in H&E images, namely the epidermis, dermis and fat cell layers, after establishing the limitation of existing solutions to overcome the challenges highlighted above.
2. Developing automatic methods for segmenting and counting nuclei in the epidermis and dermis layer in mice skin and demonstrating the ability of the proposal in identifying overlapping nuclei and separating them. Furthermore, we automatically identify a list of candidate genes responsible for abnormal changes to the number of nuclei.
3. Introducing a simple method to align the epidermis outer border in all images and designing an easy geometric-based formula to quantify the orientation of hair follicles with respect to the aligned epidermis as an indicator of skin abnormality. This led to identifying a list of candidate genes responsible for abnormal changes to the orientation of hair follicles.
4. Defining a simple mathematical model of the vaguely defined epidermis curvature as an indicator of skin abnormality and proposing a reliable scheme to quantify it.
5. Providing empirical evidences of the success for each of the above schemes by comparing the automatically determined quantification outputs with the ground truth determined by domain expert biology researchers.
6. Demonstrating the high potential of non-invasive, unsupervised machine learning techniques in the successful isolation of potentially interesting (knockout genes) relevant to genetic causes of skin abnormalities. This would facilitate high-throughput analysis in cutaneous research, with potential applications for screening drugs
Protectionism and Liberalisation in the Nigerian Insurance Sector: A Critical Examination of the role of Multinational Insurance Programmes in Dealing with Protectionist Trade Barriers
Get PDFThis thesis critically examines protectionism in the Nigerian Insurance Sector and discusses it in the context of both the liberalisation efforts of the World Trade Organization (WTO) and the anti-protectionist measures that are inherent in a multinational insurance programme. Chapter one introduces the work and provides insights into the background, aims and objectives of the research. The Chapter also identifies the key research questions to be answered by the work and further discusses the key concepts relevant to multinational insurance programmes.
Chapter two critically analyses the global anti-protectionist legal framework for the insurance sector enshrined in the WTO General Agreement for Trade in Services (GATS). It proceeds to analyse the Nigerian insurance regulations and closely examines the extent to which they comply with or diverge from Nigeria’s GATS obligations. This Chapter briefly discusses the insurance legal framework in the United Kingdom and comparatively identifies approaches that can be adopted and lessons Nigeria should learn from the UK. Despite the identified positives from the UK regulatory framework, Chapter two points out that the GATS liberalisation efforts have been highly inadequate and ineffective in resolving the insurance sector protectionism that characterises many jurisdictions including Nigeria. It therefore identifies multinational insurance programmes as a private sector driven solution to this problem and noted that the WTO approach and any other inter-governmental approach may not yield an immediate solution to this problem.
Chapter three essentially assesses the internal and external workings and operation of Multinational Insurance Programmes. The Chapter introduces and extensively discusses the Multinational Insurance Programme as a special type of insurance and argues that it was invented as a result of globalisation and it exists in two major forms – admitted and non-admitted cover. It then critically analyses the solutions and drawbacks inherent in both an admitted and non-admitted insurance cover. Finally, the chapter discusses the various forms of non-admitted cover including the design and structure of a controlled master policy.
Chapter four acknowledges the fact that the adoption of Multinational Insurance Programme helps to address the problem of protectionism, but it raises an additional issue of the legality of its adoption in the context of Nigerian law and under the laws of other non-admitted jurisdictions. The chapter therefore addresses this issue and discusses instances where severe regulatory sanctions had been imposed for usage of this form of insurance. The chapter further discusses the response by experts to this legality challenge through the invention of circumventing tools or permissive options like cut-through clauses, financial interest clauses, fronting arrangements, among others.
Chapter five recognises that apart from regulatory protectionism, state actors adopt fiscal measures in the form of taxation to protect a particular sector. The chapter proceeds with a critical analysis of the role of taxation as a protectionist tool in Nigeria and points out the widespread discrimination and unfair tax laws and policies that have stalled the growth of the insurance sector and affect both admitted and non-admitted insurers alike. The chapter queries the rationale for such laws and policies, especially in view of the fact that it discourages growth and investment in the insurance sector. The chapter contains solutions for each problem identified and recommends quick fix option for the implementation of some of these solutions.
Chapter six of this thesis, summarises the work and concludes by making strong recommendations that can turn the fortunes of the Nigerian insurance sector through the adoption of more liberal laws and policies
Charlie's Law: Clarifying the Legal Standard to be Used in Medical Decision Making for Children
No full textThe case of Charlie Gard highlights an area of law which is in critical need of reform and clarification: which legal standard should be applied in medical decision-making situations for children, when there is an effort to override the wishes of the parents. Charlie’s Law would make clear the threshold is that of “significant harm” and not of “best interests,” ensuring more protection for parental wishes and reducing needless interference, amounting to an exercise of arbitrary paternalism, from medical treaters and courts. This chapter explores the significance and benefits of clearly establishing the “significant harm” threshold
Geographical Indications of traditional handicrafts: a cultural element in a predominantly economic activity
Get PDFThe effect of globalization has seen a cross-cultural exchange on cultural forms and cultural diversity. This demands to seek the most effective, comprehensive, and appropriate mechanisms to safeguard and protect traditional knowledge. Established international treaties and regional/national conventions appear to cover the international trade of products but to what degree they discriminate among products is to be tested. In order to do so international and regional legislations as well as bilateral agreements between the European Union and Latin American countries will be considered. Additionally, when handicraft is at issue the debate over the relationship between cultural heritage and intellectual property is relevant. This paper argues the topic of Geographical Indications as a tool to protect but also to safeguard and preserve traditional handicraft. By examining local frameworks and the importance of international harmony, the study will show that the protection of geographical indications goes beyond economic goals
Political Stability, Austerity Measures, External Imbalance and Debt Impact on the Egyptian Economy
No full textEconomic difficulties manifested by the low GDP per Capita, high unemployment, high rates of inflation, limited sources of foreign currency, mounting internal and external debts, and high subsidies, had been facing Egypt for a long time. Despite the higher growth rates in Egypt in the first decade of the millennium, the persisting economic difficulties and political instability problems led to 2011 uprise.
Against expectations, the political instability, security issues and unrest, which followed the uprise, and the world economic difficulties led to further deepening of the economic problems of Egypt due to the reduction in the limited sources of foreign currency and fragile economic structure.
Egypt dependence on income from remittances, the Suez Canal and tourism as the main sources of foreign currency are inadequate. Egypt should diversify its economic activities by further engagements in the services sector, direct more effort to technological advances and increase the added-value to its products by empowering the large youth and educated population
Literature Review of Renewable Energy Policies and Impacts
Get PDFBy 2017, 128 countries have adopted renewable energy support policies, compared to just 48 countries in 2005.
These policies played a crucial role in helping countries to shift from conventional energy to renewable energy
by overcoming the barriers facing the development of renewable energy. This paper reviews the studies, which
outlined the policies used by different governments to support the development of renewable energy, which
includes: Tax incentives, Loans, Feed-in tariff, and Renewable portfolio standard. The literature review covers
different studies that examined the impacts of renewable energy on economic growth, job creation, welfare, CO2
emissions, electricity prices, and fuel imports. Researches have used different methodological approaches,
different periods, and different countries to examine the impacts of renewable energy. The studies found that
the policies used were essential to shift to renewable energy substantially reduced carbon emission, and the
majority concluded that renewable energy has a positive correlation with economic growth, job creation and
welfare
Catalyst for Empowering Women and Boosting Gender Equality in South Mediterranean Countries: The case of Egypt
Get PDFThis policy brief proposes and recommends further policies to urgently, strengthen the current quest for empowering women and for reducing inequality in the Mediterranean countries and specifically in Egypt. It seeks to provide a policy-mix for additional policies that also contribute in achieving sustainable development
Big Data for the Greater Good: An Introduction
Get PDFBig Data, perceived as one of the breakthrough technological developments of our times, has the potential to revolutionize essentially any area of knowledge and impact on any aspect of our life. Using advanced analytics techniques such as text analytics, machine learning, predictive analytics, data mining, statistics, and natural language processing, analysts, researchers, and business users can analyze previously inaccessible or unusable data to gain new insights resulting in better and faster decisions, and producing both economic and social value; it can have an impact on employment growth, productivity, the development of new products and services, traffic management, spread of viral outbreaks, and so on. But great opportunities also bring great challenges, such as the loss of individual privacy. In this chapter, we aim to provide an introduction into what Big Data is and an overview of the social value that can be extracted from it; to this aim, we explore some of the key literature on the subject. We also call attention to the potential ‘dark’ side of Big Data, but argue that more studies are needed to fully understand the downside of it. We conclude this chapter with some final reflections
The curse of dimensionality of decision-making units: A simple approach to increase the discriminatory power of data envelopment analysis
Get PDFData envelopment analysis (DEA) is a technique for identifying the best practices of a given set of decision-making units (DMUs) whose performance is categorized by multiple performance metrics that are classified as inputs and outputs. Although DEA is regarded as non-parametric, the sample size can be an issue of great importance in determining the efficiency scores for the evaluated units, empirically, when the use of too many inputs and outputs may result in a significant number of DMUs being rated as efficient. In the DEA literature, empirical rules have been established to avoid too many DMUs being rated as efficient. These empirical thresholds relate the number of variables with the number of observations. When the number of DMUs is below the empirical threshold levels, the discriminatory power among the DMUs may weaken, which leads to the data set not being suitable to apply traditional DEA models. In the literature, the lack of discrimination is often referred to as the “curse of dimensionality”. To overcome this drawback, we provide a simple approach to increase the discriminatory power between efficient and inefficient DMUs using the well-known pure DEA model, which considers either inputs only or outputs only. Three real cases, namely printed circuit boards, Greek banks, and quality of life in Fortune’s best cities, have been discussed to illustrate the proposed approach
Ligity: A Non-Superpositional, Knowledge-Based Approach to Virtual Screening
Get PDFWe present Ligity, a hybrid ligand-structurebased, non-superpositional method for virtual screening of large databases of small molecules. Ligity uses the relative spatial distribution of pharmacophoric interaction points (PIPs) derived from the conformations of small molecules. These are compared
with the PIPs derived from key interaction features found in protein−ligand complexes and are used to prioritize likely binders. We investigated the effect of generating PIPs using the single lowest energy conformer versus an ensemble of conformers for each screened ligand, using different bin sizes for the distance between two features, utilizing triangular sets of pharmacophoric features (3-PIPs) versus chiral tetrahedral sets (4-PIPs), fusing data for targets with multiple protein−ligand complex structures, and applying different similarity measures. Ligity was benchmarked using the Directory of Useful Decoys-Enhanced (DUD-E). Optimal results were obtained using the tetrahedral PIPs derived from an ensemble of bound ligand conformers and a bin size of 1.5 Å, which are used as the default settings for Ligity. The high-throughput screening mode of Ligity, using only the lowest-energy conformer of each ligand, was used for benchmarking against the whole of the DUD-E, and a more resource-intensive, “information-rich” mode of Ligity, using a conformational ensemble of each ligand, were used for a representative subset of 10 targets. Against the full DUD-E database, mean area under the receiver operating characteristic curve (AUC) values ranged from 0.44 to 0.99, while for the representative subset they ranged from 0.61 to 0.86. Data fusion further improved Ligity’s performance, with mean AUC values ranging from 0.64 to 0.95. Ligity is very efficient compared to a protein−ligand docking method such as AutoDock Vina: if the time taken for the precalculation of Ligity descriptors is included in the comparison, then Ligity is about 20 times faster than docking. A direct comparison of the virtual screening steps shows Ligity to be over 5000 times faster. Ligity highly ranks the lowest-energy conformers of DUD-E actives, in a statistically significant manner, behavior that is not observed for DUD-E decoys. Thus, our results suggest that active compounds tend to bind in relatively low-energy conformations compared to decoys. This may be because actives - and thus their lowest-energy conformations - have been optimized for conformational complementarity with their cognate binding sites