Primary lung carcinoma

The following observations are based on an investigation of 212 cases of intrathoracic neoplasms that have occurred during the past 31 years at the Royal Infirmary of Edinburgh. The study was pursued mainly from the pathological stand point of view. In all, 38 cases were examined fairly completely macroscopically and microscopically and to this group of cases the term "group A" has been given., 57 cases were examined microscopically only and these plus the 38 cases mentioned above form "group A.B" which consists of 95 cases. In the remaining 117 cases v ith the exception of one or two, a pathological report but no sections, existed. These 117 cases form "group C".1. In Edinburgh Royal Infirmary, intrathoracic neoplasm (for meaning of term see page 6) forms about 1.3 per cent of all cases at autopsy and 8.3 per cent of all malignant diseases discovered at post-mortem.2. An analysis of post-mortem records at Edinburgh Royal Infirmary has shown that there has been no in:crease during 31 years in the incidence of intrathoracic neoplasm compared with total post-mortems, total tumours in all sites, total admissions or total deaths and that the rise noted in the last year or two is unlikely to be of any significance unless it continued and was sustained for several more years.3. Primary lung carcinoma occurs more frequently in Edinburgh in men than in women in the proportion of 5 :1.4. There appears to be no relation between occupation and the disease in Edinburgh; and no relation between occupation and lung carcinoma, is known except in so fer as the Schneeberg and Joadhimstal mines are concerned.5. Macroscopically the various types of primary bronchial carcinoma are very much alike and there is no relation between the type of growth and the amount of mediastinal infiltration.6. The formation of mucin does not necessarily prove that the carcinoma takes origin from the bronchial mucus glands.7. The pathology of the "cat-cell" bronchial carcinoma is more or less fully described and a curious calcification of the smaller vessels in these tumours has been noted.8. Arguments advanced in favour of the existence of alveolar carcinoma (2 cases described).9. Sarcoma of the lung may occur (2 cases described)

Information-theoretic Reasoning in Distributed and Autonomous Systems

The increasing prevalence of distributed and autonomous systems is transforming decision making in industries as diverse as agriculture, environmental monitoring, and healthcare. Despite significant efforts, challenges remain in robustly planning under uncertainty. In this thesis, we present a number of information-theoretic decision rules for improving the analysis and control of complex adaptive systems. We begin with the problem of quantifying the data storage (memory) and transfer (communication) within information processing systems. We develop an information-theoretic framework to study nonlinear interactions within cooperative and adversarial scenarios, solely from observations of each agent's dynamics. This framework is applied to simulations of robotic soccer games, where the measures reveal insights into team performance, including correlations of the information dynamics to the scoreline. We then study the communication between processes with latent nonlinear dynamics that are observed only through a filter. By using methods from differential topology, we show that the information-theoretic measures commonly used to infer communication in observed systems can also be used in certain partially observed systems. For robotic environmental monitoring, the quality of data depends on the placement of sensors. These locations can be improved by either better estimating the quality of future viewpoints or by a team of robots operating concurrently. By robustly handling the uncertainty of sensor model measurements, we are able to present the first end-to-end robotic system for autonomously tracking small dynamic animals, with a performance comparable to human trackers. We then solve the issue of coordinating multi-robot systems through distributed optimisation techniques. These allow us to develop non-myopic robot trajectories for these tasks and, importantly, show that these algorithms provide guarantees for convergence rates to the optimal payoff sequence

Post-quantum blockchain for internet of things domain

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIn the evolving realm of quantum computing, emerging advancements reveal substantial challenges and threats to existing cryptographic infrastructures, particularly impacting blockchain technologies. These are pivotal for securing the Internet of Things (IoT) ecosystems. The traditional blockchain structures, integral to myriad IoT applications, are susceptible to potential quantum computations, emphasizing an urgent need for innovations in post-quantum blockchain solutions to reinforce security in the expansive domain of IoT. This PhD thesis delves into the crucial exploration and meticulous examination of the development and implementation of post-quantum blockchain within the IoT landscape, focusing on the incorporation of advanced post-quantum cryptographic algorithms in Hyperledger Fabric, a forefront blockchain platform renowned for its versatility and robustness. The primary aim is to discern viable post-quantum cryptographic solutions capable of fortifying blockchain systems against impending quantum threats enhancing security and reliability in IoT applications. The research comprehensively evaluates various post-quantum public-key generation and digital signature algorithms, performing detailed analyses of their computational time and memory usage to identify optimal candidates. Furthermore, the thesis proposes an innovative lattice-based digital signature scheme Fast-Fourier Lattice-based Compact Signature over NTRU (Falcon), which leverages the Monte Carlo Markov Chain (MCMC) algorithm as a trapdoor sampler to augment its security attributes. The research introduces a post-quantum version of the Hyperledger Fabric blockchain that integrates post-quantum signatures. The system utilizes the Open Quantum Safe (OQS) library, rigorously tested against NIST round 3 candidates for optimal performance. The study highlights the capability to manage IoT data securely on the post-quantum Hyperledger Fabric blockchain through the Message Queue Telemetry Transport (MQTT) protocol. Such a configuration ensures safe data transfer from IoT sensors directly to the blockchain nodes, securing the processing and recording of sensor data within the node ledger. The research addresses the multifaceted challenges of quantum computing advancements and significantly contributes to establishing secure, efficient, and resilient post-quantum blockchain infrastructures tailored explicitly for the IoT domain. These findings are instrumental in elevating the security paradigms of IoT systems against quantum vulnerabilities and catalysing innovations in post-quantum cryptography and blockchain technologies. Furthermore, this thesis introduces strategies for the optimization of performance and scalability of post-quantum blockchain solutions and explores alternative, energy-efficient consensus mechanisms such as the Raft and Stellar Consensus Protocol (SCP), providing sustainable alternatives to the conventional Proof-of-Work (PoW) approach. A critical insight emphasized throughout this thesis is the imperative of synergistic collaboration among academia, industry, and regulatory bodies. This collaboration is pivotal to expedite the adoption and standardization of post-quantum blockchain solutions, fostering the development of interoperable and standardized technologies enriched with robust security and privacy frameworks for end users. In conclusion, this thesis furnishes profound insights and substantial contributions to implementing post-quantum blockchain in the IoT domain. It delineates original contributions to the knowledge and practices in the field, offering practical solutions and advancing the state-of-the-art in post-quantum cryptography and blockchain research, thereby paving the way for a secure and resilient future for interconnected IoT systems

Influencers, are they responsible for Bitcoin's volatility? Transfer entropy and Granger causality in prol of an answer

Bitcoin, like any other cryptocurrency, is subject to fluctuations in price. The volatility of this market can be a reflection of several reasons, such as public opinion, social networks and news. Social networks, in particular Twitter, are increasingly used as an important source of value extraction because through this network, it is possible to find out about news in real-time, follow the repercussions, know what experts in the financial world are commenting or thinking and even decide based on influencer's opinion whether to invest or not. This study investigates the influence that a specific group of people exert on Bitcoin volatility. A selection of influencers from the “crypto world” was made, and through the Twitter API, it was possible to select the tweets of the object of study. To choose the classification model for sentiment analysis, two techniques were compared, one being very popular with a focus on the domain of social networks and the other recently created and focused on finance. From the selected technique, only positive and negative sentiments were considered, and then the daily series of the Sentiment Score was calculated. Next, the causal relationship between Bitcoin and sentiment was investigated using Granger causality and Transfer Entropy tests. Transfer Entropy showed encouraging results, suggesting that there is a transfer of information from Sentiment to Returns and that it is possible for an influencer to contribute to Bitcoin’s volatilityO Bitcoin, assim como qualquer outra criptomoeda, está sujeito a flutuações no preço. A volatilidade desse mercado pode ser reflexo de vários motivos, tais como, opinião pública, redes sociais e notícias. As redes sociais, em particular o Twitter, cada vez mais é utilizado como uma fonte importante de extração de valor, isto porque através desta rede é possível saber das novidades em tempo real, acompanhar as repercussões, saber o que entendedores do mundo financeiro estão a comentar e decidir até mesmo com base na opinião de um influenciador se irá investir ou não. Este estudo investiga a influência que determinadas pessoas exercem sobre a volatilidade do Bitcoin. Foi feita uma seleção de influenciadores do “mundo crypto” e através da API do Twitter foi possível selecionar os tweets de objeto de estudo. Para a escolha do modelo de classificação para análise de sentimento foram comparadas duas técnicas, sendo uma muito popular com foco no domínio de redes sociais e a outra recém-criada e focada em finanças. A partir da técnica selecionada, apenas os sentimentos positivos e negativos foram considerados e então calculada a série diária do Sentiment Score. A seguir foi investigada a relação causal entre o Bitcoin e o sentiment utilizando os testes de causalidade de Granger e Entropia de Transferência. A Entropia de Transferência mostrou resultados animadores que sugerem existir transferência de informação de Sentiment para Returns e que, portanto, é possível que um influencer contribua para a volatilidade do Bitcoin

PRODUCTION AND CHARACTERIZATION OF NOVEL AIR FILTRATION MEDIA

HEPA and ULPA filtration systems have proven to be an advantageous instrument in removing common contaminants from the air. However, an increased pressure drop due to the build-up of particulates on the filters results in its inevitable decrease in performance. Improving current filtration systems would include increasing collection efficiency all the while either maintaining or reducing the differential pressure drop in order to extend the life of the filter. One method of improving collection efficiency would be viable by increasing the amount of surface area within the filter media by glass fibers because of their inherent quality of being smaller in diameter offering more surface area than melt spun fibers. This research examined alternate methods of producing fibers comparable or smaller in size than glass fibers. As well, a unique geometry fiber know as a Capillary Channel Polymer (CCPTM) was examined for its contribution towards filtration since it offers at least twice the surface area as a round fiber of equal denier. Nonwoven filter media were manufactured with CCPTM fibers and tested for collection efficiency and pressure drop. Although SEM images showed salt particles collecting within the grooves of the shaped fibers, they did not exhibit HEPA quality efficiencies. The pressure drop of these filters was low as compared to currently used M98 HEPA filters. This was potentially due to the CCPTM fibers being unable to pack as closely together as round glass fibers allowing for high air permeability which may have contributed to the lower collection efficiency and pressure drop. Modified melt blown round fibers were also examined since their fiber diameters measured within nano range and offered benefits in terms of ease of manufacturing. The nonwovens demonstrated HEPA quality collection efficiency but at a higher pressure drop than M98 media. The melt blown nonwovens, in addition to being thicker than the M98 media, lacked structural integrity which would allow them to be used alone as a filter. The effect of slip flow on fibers measuring less than 0.50 µm in diameter was analyzed for M98 and meltblown media. The meltblown sample which contained a higher amount of fibers within the slip flow regime and contained no scrim demonstrated HEPA quality collection efficiency when compared to the M98 media with comparable basis weight. Dissolvable bi-component fibers were also examined for their potential to produce nano-size sea fibers separated by a wet-laid process. Bi-component fibers can be manufactured via traditional melt-spun lines and offer not only nano-size islands in round but also unique geometry cross-sections such as CCPTM. Difficulties in effectively dissolving off the polymer sea leaving behind individual islands prevented an in-depth examination of their contribution towards filtration. Composite media composed of CCPTM and meltblown layers proved unsuccessful in terms of collection efficiency as well as thickness but demonstrated low pressure drop. Further investigation into layering techniques and adding additional meltblowns may prove fruitful for filtration media

Civil society governance decisions: certification organization response to artisanal and small-scale gold mining

Why do global governance organizations enter some economic sectors but not others? A simple model of material incentives suggests that similar organizations should make similar choices. Yet in the empirical realm of jewelry industry governance, similar organizations diverge in their response to artisanal and small-scale gold mining: certification organizations Fairtrade International and the Alliance for Responsible Mining have entered the sector, while the Rainforest Alliance has stayed out. To explain this puzzle and its implications for human development, the project proceeds in two steps. First, it enriches the simple model by taking a discursive institutional approach that traces the process by which norm entrepreneurs, organizational cultures, and network effects shape the sector entry decisions of organizations. Drawing on interview, document, and hyperlink data, the project argues that the interaction of norm entrepreneurs and organizational culture, more than network effects, explains sector entry decisions in the gold governance case. Second, the project uses the details of the certification standards to conduct a decision analysis that estimates their impact on human development. The analysis finds that certification organizations are likely to increase a miner’s income by 41%-79% over the status quo, which may lift some, though not all, miners out of poverty. It further finds that degree of environmental protection as well as which organization is best at providing it depends on the gold price and the governance context. At prices below $26,666, the Alliance is best and competition creates better or equal outcomes than monopolies. At prices above$26,666, however, Fairtrade is best, and competition creates perverse incentives for pollution reduction. This surprising finding suggests that in the realm of global governance, there can be too much of a good thing. The project argues that governance without governments can foster human development, but that better outcomes are possible in the gold mining case. It concludes by recommending that certification organizations do three things to maximize their positive impacts: 1) prevent de-certification, 2) cooperate rather than compete, and 3) aim to be irrelevant, because mining should be a transitory, not permanent, developing country livelihood

Optimisation Method for Training Deep Neural Networks in Classification of Non- functional Requirements

Non-functional requirements (NFRs) are regarded critical to a software system's success. The majority of NFR detection and classification solutions have relied on supervised machine learning models. It is hindered by the lack of labelled data for training and necessitate a significant amount of time spent on feature engineering. In this work we explore emerging deep learning techniques to reduce the burden of feature engineering. The goal of this study is to develop an autonomous system that can classify NFRs into multiple classes based on a labelled corpus. In the first section of the thesis, we standardise the NFRs ontology and annotations to produce a corpus based on five attributes: usability, reliability, efficiency, maintainability, and portability. In the second section, the design and implementation of four neural networks, including the artificial neural network, convolutional neural network, long short-term memory, and gated recurrent unit are examined to classify NFRs. These models, necessitate a large corpus. To overcome this limitation, we proposed a new paradigm for data augmentation. This method uses a sort and concatenates strategy to combine two phrases from the same class, resulting in a two-fold increase in data size while keeping the domain vocabulary intact. We compared our method to a baseline (no augmentation) and an existing approach Easy data augmentation (EDA) with pre-trained word embeddings. All training has been performed under two modifications to the data; augmentation on the entire data before train/validation split vs augmentation on train set only. Our findings show that as compared to EDA and baseline, NFRs classification model improved greatly, and CNN outperformed when trained using our suggested technique in the first setting. However, we saw a slight boost in the second experimental setup with just train set augmentation. As a result, we can determine that augmentation of the validation is required in order to achieve acceptable results with our proposed approach. We hope that our ideas will inspire new data augmentation techniques, whether they are generic or task specific. Furthermore, it would also be useful to implement this strategy in other languages

Designing Incentives Enabled Decentralized User Data Sharing Framework

Data sharing practices are much needed to strike a balance between user privacy, user experience, and profit. Different parties collect user data, for example, companies offering apps, social networking sites, and others, whose primary motive is an enhanced business model while giving optimal services to the end-users. However, the collection of user data is associated with serious privacy and security issues. The sharing platform also needs an effective incentive mechanism to realize transparent access to the user data while distributing fair incentives. The emerging literature on the topic includes decentralized data sharing approaches. However, there has been no universal method to track who shared what, to whom, when, for what purpose and under what condition in a verifiable manner until recently, when the distributed ledger technologies emerged to become the most effective means for designing a decentralized peer-to-peer network. This Ph.D. research includes an engineering approach for specifying the operations for designing incentives and user-controlled data-sharing platforms. The thesis presents a series of empirical studies and proposes novel blockchains- and smart contracts-based DUDS (Decentralized User Data Sharing) framework conceptualizing user-controlled data sharing practices. The DUDS framework supports immutability, authenticity, enhanced security, trusted records and is a promising means to share user data in various domains, including among researchers, customer data in e-commerce, tourism applications, etc. The DUDS framework is evaluated via performance analyses and user studies. The extended Technology Acceptance Model and a Trust-Privacy-Security Model are used to evaluate the usability of the DUDS framework. The evaluation allows uncovering the role of different factors affecting user intention to adopt data-sharing platforms. The results of the evaluation point to guidelines and methods for embedding privacy, user transparency, control, and incentives from the start in the design of a data-sharing framework to provide a platform that users can trust to protect their data while allowing them to control it and share it in the ways they want

Gendering the Field

The chapters in this book offer concrete examples from all over the world to show how community livelihoods in mineral-rich tracts can be more sustainable by fully integrating gender concerns into all aspects of the relationship between mining practices and mine affected communities. By looking at the mining industry and the mine-affected communities through a gender lens, the authors indicate a variety of practical strategies to mitigate the impacts of mining on women’s livelihoods without undermining women’s voice and status within the mine-affected communities. The term ‘field’ in the title of this volume is not restricted to the open-cut pits of large scale mining operations which are male-dominated workplaces, or with mining as a masculine, capital-intensive industry, but also connotes the wider range of mineral extractive practices which are carried out informally by women and men of artisanal communities at much smaller geographical scales throughout the mineral-rich tracts of poorer countries