Miracle-dz/UniFAR-FTUs huggingface dataset:
Microwave wireless power transmission techniques with microstrip antennas in human tissue for biomedical applications

The main aim of this thesis is the investigation and optimisation of microstrip antennas and microwave techniques for wireless power transmission in human tissue at 2.45 GHz (i.e., in the Industrial, Scientific, and Medical band). For this purpose, microstrip antennas of different geometries and sizes and a microwave two-antenna setup that includes an implantable encased antenna and an external antenna, are designed and investigated computationally and experimentally. An implantable antenna module was designed by enclosing a microstrip rectangular patch antenna inside a protective dielectric housing. The simulation results showed that, by optimising the dimensions and the dielectric properties of the protective housing, the influence of the surrounding material on the performance of the implanted antenna can be reduced and the efficiency of wireless power transmission can be increased. The performance of wireless power transmission in different materials including tissue mimicking gel and fresh minced meat was experimentally investigated using a measurement system with the two-antenna setup. A parametric study was performed using the measured and simulated transmission coefficients to determine the unknown electrical properties of the materials. The measurement and simulation results are in good agreement. An implantable miniature encased microstrip ring disk antenna was designed and optimised for wireless power transmission in human tissue, and a computational model of a measurement system was proposed and used to characterise microwave two-antenna setup techniques. It was found that, by matching the resonant frequencies, aligning the directions of propagation of the electromagnetic waves and electric field polarisation vectors of the external and implanted antennas, maximum wireless power transmission in human tissue can be achieved even if the external and implanted antennas have different geometries and sizes. It was also found that reflections of the electromagnetic waves at the air-tissue interface can be reduced and the efficiency of microwave wireless power transmission techniques can be significantly enhanced by adding a matching dielectric layer between the external antenna and human tissue. A novel implantable open cylindrical-rectangular microstrip patch antenna was pro-
Radar Cross Section Prediction Using Iterative Physical Optics With Physical Theory of Diffraction

A new approach is presented to predict radar cross section (RCS) of electrically large conducting geometries using iterative physical optics (IPO) in conjunction with physical theory of diffraction (PTD). IPO is based on iterative refinement of physical optics (PO) currents to include multiple reflections. However, IPO does not yield sufficient accuracy in diffraction dominant regions since it does not properly include effects of edge diffractions. Hence, the proposed approach includes diffraction effects using PTD, which introduces edge currents. Diffracted fields due to these edge currents are radiated on triangular facets to modify the PO currents before IPO iterations. Scattered fields are computed from converged IPO surface currents and PTD edge currents. A new set of PTD edge currents excited by the fields due to the IPO currents are also found and the fields radiated by these PTD edge currents are added to the scattered fields. Therefore, interactions between the surface and edge currents are included. Computations are accelerated by parallel processing using message passing interface (MPI). Monostatic and bistatic RCS are predicted using the proposed approach for tail-wing and trihedral corner reflector geometries. The IPO-PTD results are compared with method of moments (MoM) and multilevel fast multipole method results obtained using field calculations involving bodies of arbitrary shape (FEKO) commercial electromagnetic simulation software for validation.
Movements and Culture: Expanding the Terrain of Environmental Politics

Research on environmental politics typically focuses on the state as the unit of analysis. This special issue considers the larger terrain within which contention surrounding the environment occurs by focusing on two key drivers of environmental politics: (1) environmental movements and (2) the cultural dynamics of environmental issues. The articles engage with underexplored research questions, adopt novel methodologies, examine unique data sources, and contribute to existing theory about political contests over the natural environment.
Interdisciplinary study into the effect of a marine renewable energy testing facility on the underwater sound in Falmouth Bay

Wave energy has the potential to contribute considerably to the UK’s energy mix. The marine environment is already subjected to many anthropogenic pressures. There is a need to develop the industry as sustainably as possible. A key concern is the potential for underwater noise to affect marine life. A wave energy converter (WEC; BOLT Lifesaver, Fred Olsen Ltd.) was deployed at the Falmouth Bay marine renewable energy test site (FaBTest). The underwater sound levels were recorded at this site for a two week baseline period, a five-day installation period and intermittent operational and non-operational activity from March 2012 November 2013. The recordings were also analysed for the Marine Strategy Framework Directive (MSFD) indicator third octave bands of 63-Hz and 125-Hz for shipping noise. The median and modal sound levels in Falmouth Bay were found to be loudest in the frequency range 100 Hz 1 kHz and affected by local shipping activity. During installation activity, the sound levels were louder at all frequencies recorded as compared to similar periods with no installation activity, with a mean difference of 6.9 dB Hz-1 in the range 10 Hz to 48 kHz. Long term marine renewable energy construction projects may affect the MSFD indicator bands. There was little overall difference in the average sound levels for the operational and non-operational periods as the median PSD levels were louder by an average of 0.04 dB Hz-1 during the operational activity as compared to the non-operational activity. The results of this study indicate that the effect of a single WEC device on the overall sound levels in Falmouth Bay is relatively low considering the substantial presence of shipping in the area. However, in the immediate vicinity of the device (<200 m), the sound produced was found to be of significance to marine animals. It therefore requires considering in future deployments, particularly at a site with little anthropogenic activity.
Crime Prediction Using Big Data Analysis

Crime is one of the most dangerous phenomena around the world. It is impossible to find a country or society free of crime, where criminals use all modern techniques and advanced technological methods in committing crimes, for example, cybercrime. In recent years, the generation of raw big crime data has been increased, therefore big data analysis become mandatory. Deep Learning is employed by using (LSTM) which is one of the Recurrent Neural Network (RNN) types. 'Criminal data in Chicago' is used as a dataset. An intelligent model is proposed for type, time, and place crime prediction to address the problem of high crime rates and reaching to help (police agencies - law enforcement institutions) to predict crime, reduce the spread of crime, as well as to make the best usage of security sources of (police elements - resources).
Exploring Personalizing Content Density Preference from User Behavior

In an increasingly populated area of mobile applications craving a user’s attention it is of increasing importance to engage the user through a personalized user experience. This includes delivering content which the user is likely to enjoy as well as showcasing that content in a way such that the user is likely to interact with it.This thesis details the exploration of personalizing the content density of articles in the popular mobile application Flipboard. We use past user behavior to power classification of content density preference using random forests. Our results indicate that a personalized presentation of content does increase the overall engagement of Flipboard’s users however the error rate is current too high for the classifier to be usefu.l
A Novel Method for Developing Post-quantum Digital Signature Algorithms on Non-commutative Associative Algebras

Introduction: Development of practical post-quantum signature algorithms is a current challenge in the area of cryptography. Recently, several candidates on post-quantum signature schemes, in which the exponentiation operations in a hidden commutative group contained in a non-commutative algebra is used, were proposed. Search for new mechanisms of using a hidden group, while developing signature schemes resistant to quantum attacks, is of significant practical interest. Purpose: Development of a new method for designing post-quantum signature algorithms on finite non-commutative associative algebras. Results: A novel method for developing digital signature algorithms on non-commutative algebras. A new four-dimensional finite non-commutative associative algebra set over the ground field GF(p) have been proposed as algebraic support of the signature algorithms. To provide a higher performance of the algorithm, in the introduced algebra the vector multiplication is defined by a sparse basis vector multiplication table. Study of the algebra structure has shown that it can be represented as a set of commutative subalgebras of three different types, which intersect exactly in the set of scalar vectors. Using the proposed method and introduced algebra, a new post-quantum signature scheme has been designed. The introduced method is characterized in using one of the elements of the signature (e, S) in form of the four-dimensional vector S that is computed as a masked product of two exponentiated elements G and H of a hidden commutative group: S = B-1GnHmC-1, where non-permutable vectors B and C are masking multipliers; the natural numbers n and m are calculated depending on the signed document M and public key. The pair composes a minimum generator systems of the hidden group. The signature verification equation has the form R = (Y1SZ1)e(Y2SZ2)e2, where pairwise non-permutable vectors Y1, Z1, Y2, and Z2 are element of the public key and natural number e that is computed depending on the value M and the vector R. Practical relevance: Due to sufficiently small size of public key and signature and high, the developed digital signature scheme represents interest as a practical post-quantum signature algorithm. The introduced method is very attractive to develop a post-quantum digital signature standard.
Shallow Deep Learning using Space-filling Curves for Malware Classification

The incidents of malware attacks are continually increasing at a rapid rate, thanks to the lucrative potential in schemes such as ransomware, credential stealing Trojans and cryptominers. Their explosive growth is compounded by the ease with which variants can be created from original strains. As a result, anti-virus organisations are struggling to keep up, with some reporting upwards of 14 million samples processed per month. These sheer volumes have caused a shift towards machine learning and artificial intelligence in an effort to alleviate the manual burden of analysis and classification. This research presents a novel framework for the classification of malware into distinct family classes through computer vision and deep learning. In the proposed framework, malware binaries are represented in an abstract form as images mapped through mathematical constructs known as space-filling curves. Convolutional neural networks were constructed and applied to the malware images to build predictive models for classification. The models were optimised using an auto-tuning function for the hyper parameters, which included Bayesian Optimisation, Random search and HyperBand, providing an exhaustive search on the hyper parameters. On a training dataset of 13k malware samples from 23 distinct families, the models yielded an average score of 95% for precision, recall and f1-score. The final deep learning model was validated for robustness against a dataset of more recent variants, comprising 12,816 samples from 16 malware families, returning classification scores of 95%, 86% and 90% for precision, recall and f1-score. The final model was demonstrated to outperform a similar benchmark model considerably. The results show the potential of the deep learning framework as a viable solution to the classification of malware, without the need for manually intensive feature generation or invasive processing techniques.
Two-Sex Demography, Sexual Niche Differentiation, and the Geographic Range Limits of Texas Bluegrass (Poa arachnifera)

Understanding the mechanisms that generate biogeographic range limits is a long-standing goal of ecology. It is widely hypothesized that distributional limits reflect the environmental niche, but this hypothesis is complicated by the potential for intraspecific niche heterogeneity. In dioecious species, sexual niche differentiation may cause divergence between the sexes in their limits of environmental suitability. We studied range boundary formation in Texas bluegrass (Poa arachnifera), a perennial dioecious plant, testing the alternative hypotheses that range limits reflect the niche limits of females only versus the combined contributions of females and males, including their interdependence via mating. Common garden experiments across a longitudinal aridity gradient revealed female-biased flowering approaching eastern range limits, suggesting that mate limitation may constrain the species’ distribution. However, a demographic model showed that declines in λ approaching range limits were driven almost entirely by female vital rates. The dominant role of females was attributable to seed viability being robust to sex ratio variation and to low sensitivity of λ to reproductive transitions. We suggest that female-dominant range limits may be common to long-lived species with polygamous mating systems and that female responses to environmental drivers may often be sufficient for predicting range shifts in response to environmental change.
Matching the Training Program to the Call Centre Model for Best Practice

Call centre managers adopt different business strategies which may determine the choice of model of service delivery. For example, the three models identified by Batt and Moynihan (2002) - routine mass production, professional service, mass customisation - are differentiated by factors such as job design and training and market segmentation, which reflect the business strategy adopted. A call centre can also move across the models as business strategy changes. These moves impact upon the training required for Customer Service Representatives (CSRs) because the model of service delivery changes to reflect the change in the business strategy. To achieve best practice for call centre training, training programs need to be modified for each model. The thirteen developed and recommended steps for best practice training for the professional service model can be adapted to meet the requirements of the other two models. This is shown by a discussion of a case study of an insurance and membership organisation.
Development and Application of a Decision Support System for Municipal Water Infrastructure Planning: Challenges and Successes

Many water utilities across the country continue to face the challenge of intelligent planning for cost effective, efficient operation, larger demands, stricter government regulations, and potentially shrinking water supplies. Continued evolution in computer hardware and software products has provided the planners and the decision-makers the benefit of utilizing faster and more user-friendly computer models to facilitate and support long-term planning decisions. However, investment in any number of off-the shelf and proprietary models still requires a significant amount of time and financial resources. The risk for utilities is great because even after these resources have been invested, questions are often raised about how the results will be used, who will operate the model, and how long will be the model's useful life. These issues, among others, faced the City of Portland, Oregon Bureau of Water Works during the development of a long-term Infrastructure Master Plan (IMP). Forecasted peak season water demand may increase as much as 24% by 2050 due to population growth alone. Additional water will be required to promote healthy fish habitat for endangered and threatened species. Global warming may also result in higher demands as well as impact streamflow timing and volume. Coupled with these factors is an existing water supply infrastructure that may not be capable of meeting current service area demands beyond 2010. The need to plan for these future contingencies prompted Portland to develop the IMP. The IMP identified over 40 planning scenarios that included service area expansions, three levels of conservation, varying groundwater blending ratios, and a suite of infrastructure improvements. Those improvements included groundwater expansion, dam raises, water treatment plant construction, and a third dam construction. The computational requirements needed to evaluate multiple scenarios in Portland's complex system were beyond any tools available in the organization at the time. Therefore, the need for a sophisticated water infrastructure planning tool became apparent. The purpose of this paper is to discuss the development and application of the Supply and Transmission Model (STM). Successes and challenges will be presented from the perspective of Portland's planners and decision-makers.
Multifunctional conformal grayscale electromagnetic metamaterials

We present conformal grayscale metamaterials that encodes multifunctional electromagnetic responses for a broad angle and broad bandwidth in an arbitrary form factor. Pushing the limit in the material degrees of freedom, the metamaterial assumes a high contrast, grayscale dielectric constants varying at the subwavelength scale. Conformal form factor is realized by discretizing the device into irregular voxels. Extremely high performing devices are inverse designed via gradient-based optimization and fabricated via additive manufacturing. We demonstrate a suite of multifunctional wave manipulations at RF frequency, including dispersion engineering, beam forming and steering in an airfoil-shaped structure, and conformal carpet cloak.
Continuing Bonds after Loss by Suicide: A Systematic Review

The concept of continuing bonds as an alternative to detachment from the deceased person has gained traction in grief literature over the years. Those bereaved by suicide are likely to experience various grief reactions and may be at-risk for adverse grief and mental health outcomes. However, it remains unclear how those bereaved by suicide experience continuing bonds. To address this gap, we conducted a systematic review according to PRISMA guidelines. Searches of peer-reviewed literature in Medline, PsycINFO, Embase, Emcare, EBM Reviews, and Scopus identified 15 studies (2 quantitative and 13 qualitative) reporting on 12 samples, published between 2010 and 2021. The study quality of the quantitative studies was poor, but it was fair amongst the qualitative studies. People bereaved by suicide experienced continuing bonds across a variety of domains and reported mostly positive experiences. Factors that tended to have an impact on the expression of continuing bonds included time since bereavement, relationship to the deceased, social expectations, sex of the bereaved, and the ability of the bereaved to make meaning of the death. The review concludes that most participants reported positive experiences with continuing bonds. However, discrepancies between males and females and between those bereaved by suicide and those bereaved by other causes warrants further investigation. In addition, longitudinal community-based research involving representative samples is needed to understand the evolution and experience of continuing bonds over time in those bereaved by suicide and to inform future efforts in supporting them.
Does location matter? Unpacking the dynamic relationship between the spatial context and embeddedness in women’s entrepreneurship

ABSTRACT Responding to calls for research that stresses the importance of embeddedness in entrepreneurship research, this paper examines the relationship between the spatial context and the social embeddedness in shaping and influencing women’s entrepreneurial behaviour. A particular focus is placed on gender norms, through exploring how embeddedness is gendered and that the gender norms of the context in which women entrepreneurs are and were located can constrain and/or enable their entrepreneurial actions. Furthermore, knowledge about different spatial contexts means that women can orient themselves to different gender norms and entrepreneurial behaviours. This study draws on 27 in-depth, semi-structured interviews with Saudi women entrepreneurs operating businesses within or beyond conservative, patriarchal contexts which feature different gender norms (enforced or relaxed). The findings show that when remaining within or moving between contexts, individuals have the potential to embed themselves to very different extents – through processes of over-embedding, reduce-embedding and re-mbedding – reflecting the options available for entrepreneurial action-taking and access to resources.
International Taxation and the Global Structure of Capitalism: The Influence of the OECD in the Design of the International Tax System

This article offers a Marxian interpretation of international taxation in the context of a global structure of capitalism that has evolved toward a core/periphery division, driven by the process of accumulation of capital and a moving away from the rate of profit’s tendency to fall. Taxation played an active role in this, deploying its functions of money regulator and enabling the realization of surplus value and the accumulation of capital. International taxation projects such functions onto the global capitalist system, aligning tax revenue with the holding of money. The analysis of taxation tendencies focuses on OECD proposals and OECD countries. Although improbable given the functions of taxation within capitalism, I propose certain tax reforms as an alternative to the current structure and tendencies of taxation. JEL Classification: F01, H29
Affectionate touch in satisfying and dissatisfying romantic relationships

Past research has shown consistent benefits associated with and resulting from affectionate touch, though past research is based almost exclusively on highly satisfied and otherwise non-representative samples. The current research used two nationally representative samples to test correlates (Study 1) and anticipated consequences (Study 2) of affectionate touch in romantic relationships. In Study 1, greater kissing frequency was associated with greater individual well-being, and these links were especially pronounced in the most satisfying relationships. In Study 2, participants who were randomly assigned to imagine receiving affectionate touch from their spouse anticipated greater individual well-being (less stress and greater life satisfaction) and relational benefits (greater perceived partner affection, state security, cognitive interdependence, and relationship quality). These benefits were stronger among people with moderate or high relationship satisfaction but observed even for the subset of individuals (approximately one-third of the sample) who rated their relationships as “distressed. ” Theoretical and practical implications are discussed.